LASER APPLICATIONS AND OTHER TOPICS IN QUANTUM ELECTRONICS: Application of the stochastic parallel gradient descent algorithm for numerical simulation and analysis of the coherent summation of radiation from fibre amplifiers

NASA Astrophysics Data System (ADS)

Zhou, Pu; Wang, Xiaolin; Li, Xiao; Chen, Zilum; Xu, Xiaojun; Liu, Zejin

2009-10-01

Coherent summation of fibre laser beams, which can be scaled to a relatively large number of elements, is simulated by using the stochastic parallel gradient descent (SPGD) algorithm. The applicability of this algorithm for coherent summation is analysed and its optimisaton parameters and bandwidth limitations are studied.

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

PubMed

Liu, Mingxue; Dong, Faqin; Zhang, Wei; Nie, Xiaoqin; Sun, Shiyong; Wei, Hongfu; Luo, Lang; Xiang, Sha; Zhang, Gege

2016-08-15

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 SrSO4 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. Copyright © 2016 Elsevier B.V. All rights reserved.

Gradient descent algorithm applied to wavefront retrieval from through-focus images by an extreme ultraviolet microscope with partially coherent source

DOE PAGES

Yamazoe, Kenji; Mochi, Iacopo; Goldberg, Kenneth A.

2014-12-01

The wavefront retrieval by gradient descent algorithm that is typically applied to coherent or incoherent imaging is extended to retrieve a wavefront from a series of through-focus images by partially coherent illumination. For accurate retrieval, we modeled partial coherence as well as object transmittance into the gradient descent algorithm. However, this modeling increases the computation time due to the complexity of partially coherent imaging simulation that is repeatedly used in the optimization loop. To accelerate the computation, we incorporate not only the Fourier transform but also an eigenfunction decomposition of the image. As a demonstration, the extended algorithm is appliedmore » to retrieve a field-dependent wavefront of a microscope operated at extreme ultraviolet wavelength (13.4 nm). The retrieved wavefront qualitatively matches the expected characteristics of the lens design.« less

Gradient descent algorithm applied to wavefront retrieval from through-focus images by an extreme ultraviolet microscope with partially coherent source

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

Yamazoe, Kenji; Mochi, Iacopo; Goldberg, Kenneth A.

The wavefront retrieval by gradient descent algorithm that is typically applied to coherent or incoherent imaging is extended to retrieve a wavefront from a series of through-focus images by partially coherent illumination. For accurate retrieval, we modeled partial coherence as well as object transmittance into the gradient descent algorithm. However, this modeling increases the computation time due to the complexity of partially coherent imaging simulation that is repeatedly used in the optimization loop. To accelerate the computation, we incorporate not only the Fourier transform but also an eigenfunction decomposition of the image. As a demonstration, the extended algorithm is appliedmore » to retrieve a field-dependent wavefront of a microscope operated at extreme ultraviolet wavelength (13.4 nm). The retrieved wavefront qualitatively matches the expected characteristics of the lens design.« less

Noise-shaping gradient descent-based online adaptation algorithms for digital calibration of analog circuits.

PubMed

Chakrabartty, Shantanu; Shaga, Ravi K; Aono, Kenji

2013-04-01

Analog circuits that are calibrated using digital-to-analog converters (DACs) use a digital signal processor-based algorithm for real-time adaptation and programming of system parameters. In this paper, we first show that this conventional framework for adaptation yields suboptimal calibration properties because of artifacts introduced by quantization noise. We then propose a novel online stochastic optimization algorithm called noise-shaping or ΣΔ gradient descent, which can shape the quantization noise out of the frequency regions spanning the parameter adaptation trajectories. As a result, the proposed algorithms demonstrate superior parameter search properties compared to floating-point gradient methods and better convergence properties than conventional quantized gradient-methods. In the second part of this paper, we apply the ΣΔ gradient descent algorithm to two examples of real-time digital calibration: 1) balancing and tracking of bias currents, and 2) frequency calibration of a band-pass Gm-C biquad filter biased in weak inversion. For each of these examples, the circuits have been prototyped in a 0.5-μm complementary metal-oxide-semiconductor process, and we demonstrate that the proposed algorithm is able to find the optimal solution even in the presence of spurious local minima, which are introduced by the nonlinear and non-monotonic response of calibration DACs.

Analysis of Online Composite Mirror Descent Algorithm.

PubMed

Lei, Yunwen; Zhou, Ding-Xuan

2017-03-01

We study the convergence of the online composite mirror descent algorithm, which involves a mirror map to reflect the geometry of the data and a convex objective function consisting of a loss and a regularizer possibly inducing sparsity. Our error analysis provides convergence rates in terms of properties of the strongly convex differentiable mirror map and the objective function. For a class of objective functions with Hölder continuous gradients, the convergence rates of the excess (regularized) risk under polynomially decaying step sizes have the order [Formula: see text] after [Formula: see text] iterates. Our results improve the existing error analysis for the online composite mirror descent algorithm by avoiding averaging and removing boundedness assumptions, and they sharpen the existing convergence rates of the last iterate for online gradient descent without any boundedness assumptions. Our methodology mainly depends on a novel error decomposition in terms of an excess Bregman distance, refined analysis of self-bounding properties of the objective function, and the resulting one-step progress bounds.

Gradient descent for robust kernel-based regression

NASA Astrophysics Data System (ADS)

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.

Medical image registration by combining global and local information: a chain-type diffeomorphic demons algorithm.

PubMed

Liu, Xiaozheng; Yuan, Zhenming; Zhu, Junming; Xu, Dongrong

2013-12-07

The demons algorithm is a popular algorithm for non-rigid image registration because of its computational efficiency and simple implementation. The deformation forces of the classic demons algorithm were derived from image gradients by considering the deformation to decrease the intensity dissimilarity between images. However, the methods using the difference of image intensity for medical image registration are easily affected by image artifacts, such as image noise, non-uniform imaging and partial volume effects. The gradient magnitude image is constructed from the local information of an image, so the difference in a gradient magnitude image can be regarded as more reliable and robust for these artifacts. Then, registering medical images by considering the differences in both image intensity and gradient magnitude is a straightforward selection. In this paper, based on a diffeomorphic demons algorithm, we propose a chain-type diffeomorphic demons algorithm by combining the differences in both image intensity and gradient magnitude for medical image registration. Previous work had shown that the classic demons algorithm can be considered as an approximation of a second order gradient descent on the sum of the squared intensity differences. By optimizing the new dissimilarity criteria, we also present a set of new demons forces which were derived from the gradients of the image and gradient magnitude image. We show that, in controlled experiments, this advantage is confirmed, and yields a fast convergence.

A pipeline leakage locating method based on the gradient descent algorithm

NASA Astrophysics Data System (ADS)

Li, Yulong; Yang, Fan; Ni, Na

2018-04-01

A pipeline leakage locating method based on the gradient descent algorithm is proposed in this paper. The method has low computing complexity, which is suitable for practical application. We have built experimental environment in real underground pipeline network. A lot of real data has been gathered in the past three months. Every leak point has been certificated by excavation. Results show that positioning error is within 0.4 meter. Rate of false alarm and missing alarm are both under 20%. The calculating time is not above 5 seconds.

Fast and Accurate Poisson Denoising With Trainable Nonlinear Diffusion.

PubMed

Feng, Wensen; Qiao, Peng; Chen, Yunjin; Wensen Feng; Peng Qiao; Yunjin Chen; Feng, Wensen; Chen, Yunjin; Qiao, Peng

2018-06-01

The degradation of the acquired signal by Poisson noise is a common problem for various imaging applications, such as medical imaging, night vision, and microscopy. Up to now, many state-of-the-art Poisson denoising techniques mainly concentrate on achieving utmost performance, with little consideration for the computation efficiency. Therefore, in this paper we aim to propose an efficient Poisson denoising model with both high computational efficiency and recovery quality. To this end, we exploit the newly developed trainable nonlinear reaction diffusion (TNRD) model which has proven an extremely fast image restoration approach with performance surpassing recent state-of-the-arts. However, the straightforward direct gradient descent employed in the original TNRD-based denoising task is not applicable in this paper. To solve this problem, we resort to the proximal gradient descent method. We retrain the model parameters, including the linear filters and influence functions by taking into account the Poisson noise statistics, and end up with a well-trained nonlinear diffusion model specialized for Poisson denoising. The trained model provides strongly competitive results against state-of-the-art approaches, meanwhile bearing the properties of simple structure and high efficiency. Furthermore, our proposed model comes along with an additional advantage, that the diffusion process is well-suited for parallel computation on graphics processing units (GPUs). For images of size , our GPU implementation takes less than 0.1 s to produce state-of-the-art Poisson denoising performance.

Adjoint shape optimization for fluid-structure interaction of ducted flows

NASA Astrophysics Data System (ADS)

Heners, J. P.; Radtke, L.; Hinze, M.; Düster, A.

2018-03-01

Based on the coupled problem of time-dependent fluid-structure interaction, equations for an appropriate adjoint problem are derived by the consequent use of the formal Lagrange calculus. Solutions of both primal and adjoint equations are computed in a partitioned fashion and enable the formulation of a surface sensitivity. This sensitivity is used in the context of a steepest descent algorithm for the computation of the required gradient of an appropriate cost functional. The efficiency of the developed optimization approach is demonstrated by minimization of the pressure drop in a simple two-dimensional channel flow and in a three-dimensional ducted flow surrounded by a thin-walled structure.

14 CFR 23.69 - Enroute climb/descent.

Code of Federal Regulations, 2013 CFR

2013-01-01

... inoperative and its propeller in the minimum drag position; (2) The remaining engine(s) at not more than... climb/descent. (a) All engines operating. The steady gradient and rate of climb must be determined at... applicant with— (1) Not more than maximum continuous power on each engine; (2) The landing gear retracted...

14 CFR 23.69 - Enroute climb/descent.

Code of Federal Regulations, 2014 CFR

2014-01-01

... inoperative and its propeller in the minimum drag position; (2) The remaining engine(s) at not more than... climb/descent. (a) All engines operating. The steady gradient and rate of climb must be determined at... applicant with— (1) Not more than maximum continuous power on each engine; (2) The landing gear retracted...

14 CFR 23.69 - Enroute climb/descent.

Code of Federal Regulations, 2012 CFR

2012-01-01

... inoperative and its propeller in the minimum drag position; (2) The remaining engine(s) at not more than... climb/descent. (a) All engines operating. The steady gradient and rate of climb must be determined at... applicant with— (1) Not more than maximum continuous power on each engine; (2) The landing gear retracted...

14 CFR 23.69 - Enroute climb/descent.

Code of Federal Regulations, 2011 CFR

2011-01-01

... inoperative and its propeller in the minimum drag position; (2) The remaining engine(s) at not more than... climb/descent. (a) All engines operating. The steady gradient and rate of climb must be determined at... applicant with— (1) Not more than maximum continuous power on each engine; (2) The landing gear retracted...

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

Antoine, Xavier; Levitt, Antoine; Tang, Qinglin

2017-08-01

We propose a preconditioned nonlinear conjugate gradient method coupled with a spectral spatial discretization scheme for computing the ground states (GS) of rotating Bose-Einstein condensates (BEC), modeled by the Gross-Pitaevskii Equation (GPE). We first start by reviewing the classical gradient flow (also known as imaginary time (IMT)) method which considers the problem from the PDE standpoint, leading to numerically solve a dissipative equation. Based on this IMT equation, we analyze the forward Euler (FE), Crank-Nicolson (CN) and the classical backward Euler (BE) schemes for linear problems and recognize classical power iterations, allowing us to derive convergence rates. By considering the alternative point of view of minimization problems, we propose the preconditioned steepest descent (PSD) and conjugate gradient (PCG) methods for the GS computation of the GPE. We investigate the choice of the preconditioner, which plays a key role in the acceleration of the convergence process. The performance of the new algorithms is tested in 1D, 2D and 3D. We conclude that the PCG method outperforms all the previous methods, most particularly for 2D and 3D fast rotating BECs, while being simple to implement.

14 CFR 23.75 - Landing distance.

Code of Federal Regulations, 2010 CFR

2010-01-01

... to the 50 foot height and— (1) The steady approach must be at a gradient of descent not greater than... tests that a maximum steady approach gradient steeper than 5.2 percent, down to the 50-foot height, is safe. The gradient must be established as an operating limitation and the information necessary to...

Particle swarm optimization-based automatic parameter selection for deep neural networks and its applications in large-scale and high-dimensional data

PubMed Central

2017-01-01

In this paper, we propose a new automatic hyperparameter selection approach for determining the optimal network configuration (network structure and hyperparameters) for deep neural networks using particle swarm optimization (PSO) in combination with a steepest gradient descent algorithm. In the proposed approach, network configurations were coded as a set of real-number m-dimensional vectors as the individuals of the PSO algorithm in the search procedure. During the search procedure, the PSO algorithm is employed to search for optimal network configurations via the particles moving in a finite search space, and the steepest gradient descent algorithm is used to train the DNN classifier with a few training epochs (to find a local optimal solution) during the population evaluation of PSO. After the optimization scheme, the steepest gradient descent algorithm is performed with more epochs and the final solutions (pbest and gbest) of the PSO algorithm to train a final ensemble model and individual DNN classifiers, respectively. The local search ability of the steepest gradient descent algorithm and the global search capabilities of the PSO algorithm are exploited to determine an optimal solution that is close to the global optimum. We constructed several experiments on hand-written characters and biological activity prediction datasets to show that the DNN classifiers trained by the network configurations expressed by the final solutions of the PSO algorithm, employed to construct an ensemble model and individual classifier, outperform the random approach in terms of the generalization performance. Therefore, the proposed approach can be regarded an alternative tool for automatic network structure and parameter selection for deep neural networks. PMID:29236718

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Method of Real-Time Principal-Component Analysis

NASA Technical Reports Server (NTRS)

Duong, Tuan; Duong, Vu

2005-01-01

Dominant-element-based gradient descent and dynamic initial learning rate (DOGEDYN) is a method of sequential principal-component analysis (PCA) that is well suited for such applications as data compression and extraction of features from sets of data. In comparison with a prior method of gradient-descent-based sequential PCA, this method offers a greater rate of learning convergence. Like the prior method, DOGEDYN can be implemented in software. However, the main advantage of DOGEDYN over the prior method lies in the facts that it requires less computation and can be implemented in simpler hardware. It should be possible to implement DOGEDYN in compact, low-power, very-large-scale integrated (VLSI) circuitry that could process data in real time.

Separating figure from ground with a parallel network.

PubMed

Kienker, P K; Sejnowski, T J; Hinton, G E; Schumacher, L E

1986-01-01

The differentiation of figure from ground plays an important role in the perceptual organization of visual stimuli. The rapidity with which we can discriminate the inside from the outside of a figure suggests that at least this step in the process may be performed in visual cortex by a large number of neurons in several different areas working together in parallel. We have attempted to simulate this collective computation by designing a network of simple processing units that receives two types of information: bottom-up input from the image containing the outlines of a figure, which may be incomplete, and a top-down attentional input that biases one part of the image to be the inside of the figure. No presegmentation of the image was assumed. Two methods for performing the computation were explored: gradient descent, which seeks locally optimal states, and simulated annealing, which attempts to find globally optimal states by introducing noise into the computation. For complete outlines, gradient descent was faster, but the range of input parameters leading to successful performance was very narrow. In contrast, simulated annealing was more robust: it worked over a wider range of attention parameters and a wider range of outlines, including incomplete ones. Our network model is too simplified to serve as a model of human performance, but it does demonstrate that one global property of outlines can be computed through local interactions in a parallel network. Some features of the model, such as the role of noise in escaping from nonglobal optima, may generalize to more realistic models.

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

NASA Astrophysics Data System (ADS)

Jia, Ningning; Y Lam, Edmund

2010-04-01

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 k1 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.

Computational trigonometry

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

Gustafson, K.

1994-12-31

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

On the boundary conditions on a shock wave for hypersonic flow around a descent vehicle

NASA Astrophysics Data System (ADS)

Golomazov, M. M.; Ivankov, A. A.

2013-12-01

Stationary hypersonic flow around a descent vehicle is examined by considering equilibrium and nonequilibrium reactions. We study how physical-chemical processes and shock wave conditions for gas species influence the shock-layer structure. It is shown that conservation conditions of species on the shock wave cause high-temperature and concentration gradients in the shock layer when we calculate spacecraft deceleration trajectory in the atmosphere at 75 km altitude.

Simplicial Descent Categories

NASA Astrophysics Data System (ADS)

Rodriguez Gonzalez, Beatriz

2008-04-01

Much of the homotopical and homological structure of the categories of chain complexes and topological spaces can be deduced from the existence and properties of the 'simple' functors Tot : {double chain complexes} -> {chain complexes} and geometric realization : {sSets} -> {Top}, or similarly, Tot : {simplicial chain complexes} -> {chain complexes} and | | : {sTop} -> {Top}. The purpose of this thesis is to abstract this situation, and to this end we introduce the notion of '(co)simplicial descent category'. It is inspired by Guillen-Navarros's '(cubical) descent categories'. The key ingredients in a (co)simplicial descent category D are a class E of morphisms in D, called equivalences, and a 'simple' functor s : {(co)simplicial objects in D} -> D. They must satisfy axioms like 'Eilenberg-Zilber', 'exactness' and 'acyclicity'. This notion covers a wide class of examples, as chain complexes, sSets, topological spaces, filtered cochain complexes (where E = filtered quasi-isomorphisms or E = E_2-isomorphisms), commutative differential graded algebras (with s = Navarro's Thom-Whitney simple), DG-modules over a DG-category and mixed Hodge complexes, where s = Deligne's simple. From the simplicial descent structure we obtain homotopical structure on D, as cone and cylinder objects. We use them to i) explicitly describe the morphisms of HoD=D[E^{-1}] similarly to the case of calculus of fractions; ii) endow HoD with a non-additive pre-triangulated structure, that becomes triangulated in the stable additive case. These results use the properties of a 'total functor', which associates to any biaugmented bisimplicial object a simplicial object. It is the simplicial analogue of the total chain complex of a double complex, and it is left adjoint to Illusie's 'decalage' functor.

An Adaptive Orientation Estimation Method for Magnetic and Inertial Sensors in the Presence of Magnetic Disturbances

PubMed Central

Fan, Bingfei; Li, Qingguo; Wang, Chao; Liu, Tao

2017-01-01

Magnetic and inertial sensors have been widely used to estimate the orientation of human segments due to their low cost, compact size and light weight. However, the accuracy of the estimated orientation is easily affected by external factors, especially when the sensor is used in an environment with magnetic disturbances. In this paper, we propose an adaptive method to improve the accuracy of orientation estimations in the presence of magnetic disturbances. The method is based on existing gradient descent algorithms, and it is performed prior to sensor fusion algorithms. The proposed method includes stationary state detection and magnetic disturbance severity determination. The stationary state detection makes this method immune to magnetic disturbances in stationary state, while the magnetic disturbance severity determination helps to determine the credibility of magnetometer data under dynamic conditions, so as to mitigate the negative effect of the magnetic disturbances. The proposed method was validated through experiments performed on a customized three-axis instrumented gimbal with known orientations. The error of the proposed method and the original gradient descent algorithms were calculated and compared. Experimental results demonstrate that in stationary state, the proposed method is completely immune to magnetic disturbances, and in dynamic conditions, the error caused by magnetic disturbance is reduced by 51.2% compared with original MIMU gradient descent algorithm. PMID:28534858

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

Yang, Y. M., E-mail: ymingy@gmail.com; Bednarz, B.; Svatos, M.

Purpose: The future of radiation therapy will require advanced inverse planning solutions to support single-arc, multiple-arc, and “4π” delivery modes, which present unique challenges in finding an optimal treatment plan over a vast search space, while still preserving dosimetric accuracy. The successful clinical implementation of such methods would benefit from Monte Carlo (MC) based dose calculation methods, which can offer improvements in dosimetric accuracy when compared to deterministic methods. The standard method for MC based treatment planning optimization leverages the accuracy of the MC dose calculation and efficiency of well-developed optimization methods, by precalculating the fluence to dose relationship withinmore » a patient with MC methods and subsequently optimizing the fluence weights. However, the sequential nature of this implementation is computationally time consuming and memory intensive. Methods to reduce the overhead of the MC precalculation have been explored in the past, demonstrating promising reductions of computational time overhead, but with limited impact on the memory overhead due to the sequential nature of the dose calculation and fluence optimization. The authors propose an entirely new form of “concurrent” Monte Carlo treat plan optimization: a platform which optimizes the fluence during the dose calculation, reduces wasted computation time being spent on beamlets that weakly contribute to the final dose distribution, and requires only a low memory footprint to function. In this initial investigation, the authors explore the key theoretical and practical considerations of optimizing fluence in such a manner. Methods: The authors present a novel derivation and implementation of a gradient descent algorithm that allows for optimization during MC particle transport, based on highly stochastic information generated through particle transport of very few histories. A gradient rescaling and renormalization algorithm, and the concept of momentum from stochastic gradient descent were used to address obstacles unique to performing gradient descent fluence optimization during MC particle transport. The authors have applied their method to two simple geometrical phantoms, and one clinical patient geometry to examine the capability of this platform to generate conformal plans as well as assess its computational scaling and efficiency, respectively. Results: The authors obtain a reduction of at least 50% in total histories transported in their investigation compared to a theoretical unweighted beamlet calculation and subsequent fluence optimization method, and observe a roughly fixed optimization time overhead consisting of ∼10% of the total computation time in all cases. Finally, the authors demonstrate a negligible increase in memory overhead of ∼7–8 MB to allow for optimization of a clinical patient geometry surrounded by 36 beams using their platform. Conclusions: This study demonstrates a fluence optimization approach, which could significantly improve the development of next generation radiation therapy solutions while incurring minimal additional computational overhead.« less

Concurrent Monte Carlo transport and fluence optimization with fluence adjusting scalable transport Monte Carlo

PubMed Central

Svatos, M.; Zankowski, C.; Bednarz, B.

2016-01-01

Purpose: The future of radiation therapy will require advanced inverse planning solutions to support single-arc, multiple-arc, and “4π” delivery modes, which present unique challenges in finding an optimal treatment plan over a vast search space, while still preserving dosimetric accuracy. The successful clinical implementation of such methods would benefit from Monte Carlo (MC) based dose calculation methods, which can offer improvements in dosimetric accuracy when compared to deterministic methods. The standard method for MC based treatment planning optimization leverages the accuracy of the MC dose calculation and efficiency of well-developed optimization methods, by precalculating the fluence to dose relationship within a patient with MC methods and subsequently optimizing the fluence weights. However, the sequential nature of this implementation is computationally time consuming and memory intensive. Methods to reduce the overhead of the MC precalculation have been explored in the past, demonstrating promising reductions of computational time overhead, but with limited impact on the memory overhead due to the sequential nature of the dose calculation and fluence optimization. The authors propose an entirely new form of “concurrent” Monte Carlo treat plan optimization: a platform which optimizes the fluence during the dose calculation, reduces wasted computation time being spent on beamlets that weakly contribute to the final dose distribution, and requires only a low memory footprint to function. In this initial investigation, the authors explore the key theoretical and practical considerations of optimizing fluence in such a manner. Methods: The authors present a novel derivation and implementation of a gradient descent algorithm that allows for optimization during MC particle transport, based on highly stochastic information generated through particle transport of very few histories. A gradient rescaling and renormalization algorithm, and the concept of momentum from stochastic gradient descent were used to address obstacles unique to performing gradient descent fluence optimization during MC particle transport. The authors have applied their method to two simple geometrical phantoms, and one clinical patient geometry to examine the capability of this platform to generate conformal plans as well as assess its computational scaling and efficiency, respectively. Results: The authors obtain a reduction of at least 50% in total histories transported in their investigation compared to a theoretical unweighted beamlet calculation and subsequent fluence optimization method, and observe a roughly fixed optimization time overhead consisting of ∼10% of the total computation time in all cases. Finally, the authors demonstrate a negligible increase in memory overhead of ∼7–8 MB to allow for optimization of a clinical patient geometry surrounded by 36 beams using their platform. Conclusions: This study demonstrates a fluence optimization approach, which could significantly improve the development of next generation radiation therapy solutions while incurring minimal additional computational overhead. PMID:27277051

14 CFR 23.75 - Landing distance.

Code of Federal Regulations, 2012 CFR

2012-01-01

... to the 50 foot height and— (1) The steady approach must be at a gradient of descent not greater than 5.2 percent (3 degrees) down to the 50-foot height. (2) In addition, an applicant may demonstrate by tests that a maximum steady approach gradient steeper than 5.2 percent, down to the 50-foot height, is...

14 CFR 23.75 - Landing distance.

Code of Federal Regulations, 2014 CFR

2014-01-01

... to the 50 foot height and— (1) The steady approach must be at a gradient of descent not greater than 5.2 percent (3 degrees) down to the 50-foot height. (2) In addition, an applicant may demonstrate by tests that a maximum steady approach gradient steeper than 5.2 percent, down to the 50-foot height, is...

14 CFR 23.75 - Landing distance.

Code of Federal Regulations, 2013 CFR

2013-01-01

... to the 50 foot height and— (1) The steady approach must be at a gradient of descent not greater than 5.2 percent (3 degrees) down to the 50-foot height. (2) In addition, an applicant may demonstrate by tests that a maximum steady approach gradient steeper than 5.2 percent, down to the 50-foot height, is...

Coordinated Beamforming for MISO Interference Channel: Complexity Analysis and Efficient Algorithms

DTIC Science & Technology

2010-01-01

Algorithm The cyclic coordinate descent algorithm is also known as the nonlinear Gauss - Seidel iteration [32]. There are several studies of this type of...vkρ(vi−1). It can be shown that the above BB gradient projection direction is always a descent direction. The R-linear convergence of the BB method has...KKT solution ) of the inexact pricing algorithm for MISO interference channel. The latter is interesting since the convergence of the original pricing

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

Khadijah, Wan; Rivaie, Mohd; Mamat, Mustafa

2017-08-01

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

Natural learning in NLDA networks.

PubMed

González, Ana; Dorronsoro, José R

2007-07-01

Non Linear Discriminant Analysis (NLDA) networks combine a standard Multilayer Perceptron (MLP) transfer function with the minimization of a Fisher analysis criterion. In this work we will define natural-like gradients for NLDA network training. Instead of a more principled approach, that would require the definition of an appropriate Riemannian structure on the NLDA weight space, we will follow a simpler procedure, based on the observation that the gradient of the NLDA criterion function J can be written as the expectation nablaJ(W)=E[Z(X,W)] of a certain random vector Z and defining then I=E[Z(X,W)Z(X,W)(t)] as the Fisher information matrix in this case. This definition of I formally coincides with that of the information matrix for the MLP or other square error functions; the NLDA J criterion, however, does not have this structure. Although very simple, the proposed approach shows much faster convergence than that of standard gradient descent, even when its costlier complexity is taken into account. While the faster convergence of natural MLP batch training can be also explained in terms of its relationship with the Gauss-Newton minimization method, this is not the case for NLDA training, as we will see analytically and numerically that the hessian and information matrices are different.

Optimized computational imaging methods for small-target sensing in lens-free holographic microscopy

NASA Astrophysics Data System (ADS)

Xiong, Zhen; Engle, Isaiah; Garan, Jacob; Melzer, Jeffrey E.; McLeod, Euan

2018-02-01

Lens-free holographic microscopy is a promising diagnostic approach because it is cost-effective, compact, and suitable for point-of-care applications, while providing high resolution together with an ultra-large field-of-view. It has been applied to biomedical sensing, where larger targets like eukaryotic cells, bacteria, or viruses can be directly imaged without labels, and smaller targets like proteins or DNA strands can be detected via scattering labels like micro- or nano-spheres. Automated image processing routines can count objects and infer target concentrations. In these sensing applications, sensitivity and specificity are critically affected by image resolution and signal-to-noise ratio (SNR). Pixel super-resolution approaches have been shown to boost resolution and SNR by synthesizing a high-resolution image from multiple, partially redundant, low-resolution images. However, there are several computational methods that can be used to synthesize the high-resolution image, and previously, it has been unclear which methods work best for the particular case of small-particle sensing. Here, we quantify the SNR achieved in small-particle sensing using regularized gradient-descent optimization method, where the regularization is based on cardinal-neighbor differences, Bayer-pattern noise reduction, or sparsity in the image. In particular, we find that gradient-descent with sparsity-based regularization works best for small-particle sensing. These computational approaches were evaluated on images acquired using a lens-free microscope that we assembled from an off-the-shelf LED array and color image sensor. Compared to other lens-free imaging systems, our hardware integration, calibration, and sample preparation are particularly simple. We believe our results will help to enable the best performance in lens-free holographic sensing.

Energy minimization in medical image analysis: Methodologies and applications.

PubMed

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.

Online learning in optical tomography: a stochastic approach

NASA Astrophysics Data System (ADS)

Chen, Ke; Li, Qin; Liu, Jian-Guo

2018-07-01

We study the inverse problem of radiative transfer equation (RTE) using stochastic gradient descent method (SGD) in this paper. Mathematically, optical tomography amounts to recovering the optical parameters in RTE using the incoming–outgoing pair of light intensity. We formulate it as a PDE-constraint optimization problem, where the mismatch of computed and measured outgoing data is minimized with same initial data and RTE constraint. The memory and computation cost it requires, however, is typically prohibitive, especially in high dimensional space. Smart iterative solvers that only use partial information in each step is called for thereafter. Stochastic gradient descent method is an online learning algorithm that randomly selects data for minimizing the mismatch. It requires minimum memory and computation, and advances fast, therefore perfectly serves the purpose. In this paper we formulate the problem, in both nonlinear and its linearized setting, apply SGD algorithm and analyze the convergence performance.

Accelerating IMRT optimization by voxel sampling

NASA Astrophysics Data System (ADS)

Martin, Benjamin C.; Bortfeld, Thomas R.; Castañon, David A.

2007-12-01

This paper presents a new method for accelerating intensity-modulated radiation therapy (IMRT) optimization using voxel sampling. Rather than calculating the dose to the entire patient at each step in the optimization, the dose is only calculated for some randomly selected voxels. Those voxels are then used to calculate estimates of the objective and gradient which are used in a randomized version of a steepest descent algorithm. By selecting different voxels on each step, we are able to find an optimal solution to the full problem. We also present an algorithm to automatically choose the best sampling rate for each structure within the patient during the optimization. Seeking further improvements, we experimented with several other gradient-based optimization algorithms and found that the delta-bar-delta algorithm performs well despite the randomness. Overall, we were able to achieve approximately an order of magnitude speedup on our test case as compared to steepest descent.

An Approach to Stable Gradient-Descent Adaptation of Higher Order Neural Units.

PubMed

Bukovsky, Ivo; Homma, Noriyasu

2017-09-01

Stability evaluation of a weight-update system of higher order neural units (HONUs) with polynomial aggregation of neural inputs (also known as classes of polynomial neural networks) for adaptation of both feedforward and recurrent HONUs by a gradient descent method is introduced. An essential core of the approach is based on the spectral radius of a weight-update system, and it allows stability monitoring and its maintenance at every adaptation step individually. Assuring the stability of the weight-update system (at every single adaptation step) naturally results in the adaptation stability of the whole neural architecture that adapts to the target data. As an aside, the used approach highlights the fact that the weight optimization of HONU is a linear problem, so the proposed approach can be generally extended to any neural architecture that is linear in its adaptable parameters.

Reduced-gravity Testing of The Huygens Probe Ssp Tiltmeter and Hasi Accelerometer Sensors and Their Role In Reconstruction of The Probe Descent Dynamics

NASA Astrophysics Data System (ADS)

Ghafoor, N.; Zarnecki, J.

When the ESA Huygens Probe arrives at Titan in 2005, measurements taken during and after the descent through the atmosphere are likely to revolutionise our under- standing of SaturnSs most enigmatic moon. The accurate atmospheric profiling of Titan from these measurements will require knowledge of the probe descent trajectory and in some cases attitude history, whilst certain atmospheric information (e.g. wind speeds) may be inferred directly from the probe dynamics during descent. Two of the instruments identified as contributing valuable information for the reconstruction of the probeSs parachute descent dynamics are the Surface Science Package Tilt sensor (SSP-TIL) and the Huygens Atmospheric Structure Instrument servo accelerometer (HASI-ACC). This presentation provides an overview of these sensors and their static calibration before describing an investigation into their real-life dynamic performance under simulated Titan-gravity conditions via a low-cost parabolic flight opportunity. The combined use of SSP-TIL and HASI-ACC in characterising the aircraft dynam- ics is also demonstrated and some important challenges are highlighted. Results from some simple spin tests are also presented. Finally, having validated the performance of the sensors under simulated Titan conditions, estimates are made as to the output of SSP-TIL and HASI-ACC under a variety of probe dynamics, ranging from verti- cal descent with spin to a simple 3 degree-of-freedom parachute descent model with horizontal gusting. It is shown how careful consideration must be given to the instru- mentsS principles of operation in each case, and also the impact of the sampling rates and resolutions as selected for the Huygens mission. The presentation concludes with a discussion of ongoing work on more advanced descent modelling and surface dy- namics modelling, and also of a proposal for the testing of the sensors on a sea-surface.

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

NASA Technical Reports Server (NTRS)

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.

Implementation of a Balance Operator in NCOM

DTIC Science & Technology

2016-04-07

the background temperature Tb and salinity Sb fields do), f is the Coriolis parameter, k is the vertical unit vector, ∇ is the horizontal gradient, p... effectively used as a natural metric in the space of cost function gradients. The associated geometry inhibits descent in the unbalanced directions...28) where f is the local Coriolis parameter, ∆yv is the local grid spacing in the y direction at a v point, and the overbars indicates horizontal

A feasible DY conjugate gradient method for linear equality constraints

NASA Astrophysics Data System (ADS)

LI, Can

2017-09-01

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

Approximate solution of the p-median minimization problem

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

A modified form of conjugate gradient method for unconstrained optimization problems

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Implementation of a Balance Operator in NCOM

DTIC Science & Technology

2016-04-07

the background temperature Tb and salinity Sb fields do), f is the Coriolis parameter, k is the vertical unit vector, ∇ is the horizontal gradient, p... effectively used as a natural metric in the space of cost function gradients. The associated geometry inhibits descent in the unbalanced directions and...28) where f is the local Coriolis parameter, ∆yv is the local grid spacing in the y direction at a v point, and the overbars indicates horizontal

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Groundwater Productivity and Quality of The Quartzite Ridge of RÓdA~o and Their Vicinities (center of Portugal)

NASA Astrophysics Data System (ADS)

Duque, J.; Chambel, A.

When the ESA Huygens Probe arrives at Titan in 2005, measurements taken during and after the descent through the atmosphere are likely to revolutionise our under- standing of SaturnSs most enigmatic moon. The accurate atmospheric profiling of Titan from these measurements will require knowledge of the probe descent trajectory and in some cases attitude history, whilst certain atmospheric information (e.g. wind speeds) may be inferred directly from the probe dynamics during descent. Two of the instruments identified as contributing valuable information for the reconstruction of the probeSs parachute descent dynamics are the Surface Science Package Tilt sensor (SSP-TIL) and the Huygens Atmospheric Structure Instrument servo accelerometer (HASI-ACC). This presentation provides an overview of these sensors and their static calibration before describing an investigation into their real-life dynamic performance under simulated Titan-gravity conditions via a low-cost parabolic flight opportunity. The combined use of SSP-TIL and HASI-ACC in characterising the aircraft dynam- ics is also demonstrated and some important challenges are highlighted. Results from some simple spin tests are also presented. Finally, having validated the performance of the sensors under simulated Titan conditions, estimates are made as to the output of SSP-TIL and HASI-ACC under a variety of probe dynamics, ranging from verti- cal descent with spin to a simple 3 degree-of-freedom parachute descent model with horizontal gusting. It is shown how careful consideration must be given to the instru- mentsS principles of operation in each case, and also the impact of the sampling rates and resolutions as selected for the Huygens mission. The presentation concludes with a discussion of ongoing work on more advanced descent modelling and surface dy- namics modelling, and also of a proposal for the testing of the sensors on a sea-surface.

ATMOS/ATLAS-3 Observations of Long-Lived Tracers and Descent in the Antarctic Vortex in November 1994

NASA Technical Reports Server (NTRS)

Abrams, M. C.; Manney, G. L.; Gunson, M. R.; Abbas, M. M.; Chang, A. Y.; Goldman, A.; Irion, F. W.; Michelsen, H. A.; Newchurch, M. J.; Rinsland, C. P.;

14 CFR 23.253 - High speed characteristics.

Code of Federal Regulations, 2013 CFR

2013-01-01

... and characteristics include gust upsets, inadvertent control movements, low stick force gradients in relation to control friction, passenger movement, leveling off from climb, and descent from Mach to... normal attitude and its speed reduced to VMO/MMO, without— (1) Exceptional piloting strength or skill; (2...

14 CFR 23.253 - High speed characteristics.

Code of Federal Regulations, 2014 CFR

2014-01-01

... and characteristics include gust upsets, inadvertent control movements, low stick force gradients in relation to control friction, passenger movement, leveling off from climb, and descent from Mach to... normal attitude and its speed reduced to VMO/MMO, without— (1) Exceptional piloting strength or skill; (2...

Using a Gradient Vector to Find Multiple Periodic Oscillations in Suspension Bridge Models

ERIC Educational Resources Information Center

Humphreys, L. D.; McKenna, P. J.

2005-01-01

This paper describes how the method of steepest descent can be used to find periodic solutions of differential equations. Applications to two suspension bridge models are discussed, and the method is used to find non-obvious large-amplitude solutions.

Nonuniformity correction for an infrared focal plane array based on diamond search block matching.

PubMed

Sheng-Hui, Rong; Hui-Xin, Zhou; Han-Lin, Qin; Rui, Lai; Kun, Qian

2016-05-01

In scene-based nonuniformity correction algorithms, artificial ghosting and image blurring degrade the correction quality severely. In this paper, an improved algorithm based on the diamond search block matching algorithm and the adaptive learning rate is proposed. First, accurate transform pairs between two adjacent frames are estimated by the diamond search block matching algorithm. Then, based on the error between the corresponding transform pairs, the gradient descent algorithm is applied to update correction parameters. During the process of gradient descent, the local standard deviation and a threshold are utilized to control the learning rate to avoid the accumulation of matching error. Finally, the nonuniformity correction would be realized by a linear model with updated correction parameters. The performance of the proposed algorithm is thoroughly studied with four real infrared image sequences. Experimental results indicate that the proposed algorithm can reduce the nonuniformity with less ghosting artifacts in moving areas and can also overcome the problem of image blurring in static areas.

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

NASA Astrophysics Data System (ADS)

Dong, Bing; Ren, De-Qing; Zhang, Xi

2011-08-01

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.

3D-Web-GIS RFID location sensing system for construction objects.

PubMed

Ko, Chien-Ho

2013-01-01

Construction site managers could benefit from being able to visualize on-site construction objects. Radio frequency identification (RFID) technology has been shown to improve the efficiency of construction object management. The objective of this study is to develop a 3D-Web-GIS RFID location sensing system for construction objects. An RFID 3D location sensing algorithm combining Simulated Annealing (SA) and a gradient descent method is proposed to determine target object location. In the algorithm, SA is used to stabilize the search process and the gradient descent method is used to reduce errors. The locations of the analyzed objects are visualized using the 3D-Web-GIS system. A real construction site is used to validate the applicability of the proposed method, with results indicating that the proposed approach can provide faster, more accurate, and more stable 3D positioning results than other location sensing algorithms. The proposed system allows construction managers to better understand worksite status, thus enhancing managerial efficiency.

Optimization of OT-MACH Filter Generation for Target Recognition

NASA Technical Reports Server (NTRS)

Johnson, Oliver C.; Edens, Weston; Lu, Thomas T.; Chao, Tien-Hsin

2009-01-01

An automatic Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter generator for use in a gray-scale optical correlator (GOC) has been developed for improved target detection at JPL. While the OT-MACH filter has been shown to be an optimal filter for target detection, actually solving for the optimum is too computationally intensive for multiple targets. Instead, an adaptive step gradient descent method was tested to iteratively optimize the three OT-MACH parameters, alpha, beta, and gamma. The feedback for the gradient descent method was a composite of the performance measures, correlation peak height and peak to side lobe ratio. The automated method generated and tested multiple filters in order to approach the optimal filter quicker and more reliably than the current manual method. Initial usage and testing has shown preliminary success at finding an approximation of the optimal filter, in terms of alpha, beta, gamma values. This corresponded to a substantial improvement in detection performance where the true positive rate increased for the same average false positives per image.

3D-Web-GIS RFID Location Sensing System for Construction Objects

PubMed Central

2013-01-01

Construction site managers could benefit from being able to visualize on-site construction objects. Radio frequency identification (RFID) technology has been shown to improve the efficiency of construction object management. The objective of this study is to develop a 3D-Web-GIS RFID location sensing system for construction objects. An RFID 3D location sensing algorithm combining Simulated Annealing (SA) and a gradient descent method is proposed to determine target object location. In the algorithm, SA is used to stabilize the search process and the gradient descent method is used to reduce errors. The locations of the analyzed objects are visualized using the 3D-Web-GIS system. A real construction site is used to validate the applicability of the proposed method, with results indicating that the proposed approach can provide faster, more accurate, and more stable 3D positioning results than other location sensing algorithms. The proposed system allows construction managers to better understand worksite status, thus enhancing managerial efficiency. PMID:23864821

Cosmic Microwave Background Mapmaking with a Messenger Field

NASA Astrophysics Data System (ADS)

Huffenberger, Kevin M.; Næss, Sigurd K.

2018-01-01

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

A new smoothing modified three-term conjugate gradient method for [Formula: see text]-norm minimization problem.

PubMed

Du, Shouqiang; Chen, Miao

2018-01-01

We consider a kind of nonsmooth optimization problems with [Formula: see text]-norm minimization, which has many applications in compressed sensing, signal reconstruction, and the related engineering problems. Using smoothing approximate techniques, this kind of nonsmooth optimization problem can be transformed into a general unconstrained optimization problem, which can be solved by the proposed smoothing modified three-term conjugate gradient method. The smoothing modified three-term conjugate gradient method is based on Polak-Ribière-Polyak conjugate gradient method. For the Polak-Ribière-Polyak conjugate gradient method has good numerical properties, the proposed method possesses the sufficient descent property without any line searches, and it is also proved to be globally convergent. Finally, the numerical experiments show the efficiency of the proposed method.

A General Method for Solving Systems of Non-Linear Equations

NASA Technical Reports Server (NTRS)

Nachtsheim, Philip R.; Deiss, Ron (Technical Monitor)

1995-01-01

The method of steepest descent is modified so that accelerated convergence is achieved near a root. It is assumed that the function of interest can be approximated near a root by a quadratic form. An eigenvector of the quadratic form is found by evaluating the function and its gradient at an arbitrary point and another suitably selected point. The terminal point of the eigenvector is chosen to lie on the line segment joining the two points. The terminal point found lies on an axis of the quadratic form. The selection of a suitable step size at this point leads directly to the root in the direction of steepest descent in a single step. Newton's root finding method not infrequently diverges if the starting point is far from the root. However, the current method in these regions merely reverts to the method of steepest descent with an adaptive step size. The current method's performance should match that of the Levenberg-Marquardt root finding method since they both share the ability to converge from a starting point far from the root and both exhibit quadratic convergence near a root. The Levenberg-Marquardt method requires storage for coefficients of linear equations. The current method which does not require the solution of linear equations requires more time for additional function and gradient evaluations. The classic trade off of time for space separates the two methods.

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

PubMed

Bhaya, Amit; Kaszkurewicz, Eugenius

2004-01-01

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

Statistical Physics for Adaptive Distributed Control

NASA Technical Reports Server (NTRS)

Wolpert, David H.

2005-01-01

A viewgraph presentation on statistical physics for distributed adaptive control is shown. The topics include: 1) The Golden Rule; 2) Advantages; 3) Roadmap; 4) What is Distributed Control? 5) Review of Information Theory; 6) Iterative Distributed Control; 7) Minimizing L(q) Via Gradient Descent; and 8) Adaptive Distributed Control.

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

PubMed

Chowdhary, J; Keyes, T

2002-02-01

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

Algorithms for Mathematical Programming with Emphasis on Bi-level Models

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

Goldfarb, Donald; Iyengar, Garud

2014-05-22

The research supported by this grant was focused primarily on first-order methods for solving large scale and structured convex optimization problems and convex relaxations of nonconvex problems. These include optimal gradient methods, operator and variable splitting methods, alternating direction augmented Lagrangian methods, and block coordinate descent methods.

An Impacting Descent Probe for Europa and the Other Galilean Moons of Jupiter

NASA Astrophysics Data System (ADS)

Wurz, P.; Lasi, D.; Thomas, N.; Piazza, D.; Galli, A.; Jutzi, M.; Barabash, S.; Wieser, M.; Magnes, W.; Lammer, H.; Auster, U.; Gurvits, L. I.; Hajdas, W.

2017-08-01

We present a study of an impacting descent probe that increases the science return of spacecraft orbiting or passing an atmosphere-less planetary bodies of the solar system, such as the Galilean moons of Jupiter. The descent probe is a carry-on small spacecraft (<100 kg), to be deployed by the mother spacecraft, that brings itself onto a collisional trajectory with the targeted planetary body in a simple manner. A possible science payload includes instruments for surface imaging, characterisation of the neutral exosphere, and magnetic field and plasma measurement near the target body down to very low-altitudes ( 1 km), during the probe's fast ( km/s) descent to the surface until impact. The science goals and the concept of operation are discussed with particular reference to Europa, including options for flying through water plumes and after-impact retrieval of very-low altitude science data. All in all, it is demonstrated how the descent probe has the potential to provide a high science return to a mission at a low extra level of complexity, engineering effort, and risk. This study builds upon earlier studies for a Callisto Descent Probe for the former Europa-Jupiter System Mission of ESA and NASA, and extends them with a detailed assessment of a descent probe designed to be an additional science payload for the NASA Europa Mission.

Oscillatory neural network for pattern recognition: trajectory based classification and supervised learning.

PubMed

Miller, Vonda H; Jansen, Ben H

2008-12-01

Computer algorithms that match human performance in recognizing written text or spoken conversation remain elusive. The reasons why the human brain far exceeds any existing recognition scheme to date in the ability to generalize and to extract invariant characteristics relevant to category matching are not clear. However, it has been postulated that the dynamic distribution of brain activity (spatiotemporal activation patterns) is the mechanism by which stimuli are encoded and matched to categories. This research focuses on supervised learning using a trajectory based distance metric for category discrimination in an oscillatory neural network model. Classification is accomplished using a trajectory based distance metric. Since the distance metric is differentiable, a supervised learning algorithm based on gradient descent is demonstrated. Classification of spatiotemporal frequency transitions and their relation to a priori assessed categories is shown along with the improved classification results after supervised training. The results indicate that this spatiotemporal representation of stimuli and the associated distance metric is useful for simple pattern recognition tasks and that supervised learning improves classification results.

Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures.

PubMed

Arana-Daniel, Nancy; Gallegos, Alberto A; López-Franco, Carlos; Alanís, Alma Y; Morales, Jacob; López-Franco, Adriana

2016-01-01

With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classification, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classification problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.

A gradient system solution to Potts mean field equations and its electronic implementation.

PubMed

Urahama, K; Ueno, S

1993-03-01

A gradient system solution method is presented for solving Potts mean field equations for combinatorial optimization problems subject to winner-take-all constraints. In the proposed solution method the optimum solution is searched by using gradient descent differential equations whose trajectory is confined within the feasible solution space of optimization problems. This gradient system is proven theoretically to always produce a legal local optimum solution of combinatorial optimization problems. An elementary analog electronic circuit implementing the presented method is designed on the basis of current-mode subthreshold MOS technologies. The core constituent of the circuit is the winner-take-all circuit developed by Lazzaro et al. Correct functioning of the presented circuit is exemplified with simulations of the circuits implementing the scheme for solving the shortest path problems.

Hybrid DFP-CG method for solving unconstrained optimization problems

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Neural networks applications to control and computations

NASA Technical Reports Server (NTRS)

Luxemburg, Leon A.

1994-01-01

Several interrelated problems in the area of neural network computations are described. First an interpolation problem is considered, then a control problem is reduced to a problem of interpolation by a neural network via Lyapunov function approach, and finally a new, faster method of learning as compared with the gradient descent method, was introduced.

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

PubMed

Wu, Yanlin

2017-01-01

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

North Pacific Cloud Feedbacks Inferred from Synoptic-Scale Dynamic and Thermodynamic Relationships

NASA Technical Reports Server (NTRS)

Norris, Joel R.; Iacobellis, Sam F.

2005-01-01

This study analyzed daily satellite cloud observations and reanalysis dynamical parameters to determine how mid-tropospheric vertical velocity and advection over the sea surface temperature gradient control midlatitude North Pacific cloud properties. Optically thick clouds with high tops are generated by synoptic ascent, but two different cloud regimes occur under synoptic descent. When vertical motion is downward during summer, extensive stratocumulus cloudiness is associated with near surface northerly wind, while frequent cloudless pixels occur with southerly wind. Examinations of ship-reported cloud types indicates that midlatitude stratocumulus breaks up as the the boundary level decouples when it is advected equatorward over warmer water. Cumulus is prevalent under conditions of synoptic descent and cold advection during winter. Poleward advection of subtropical air over colder water causes stratification of the near-surface layer that inhibits upward mixing of moisture and suppresses cloudiness until a fog eventually forms. Averaging of cloud and radiation data into intervals of 500-hPa vertical velocity and advection over the SST gradient enables the cloud response to changes in temperature and the stratification of the lower troposphere to be investigated independent of the dynamics.

Understanding and Optimizing Asynchronous Low-Precision Stochastic Gradient Descent

PubMed Central

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

Limited-memory fast gradient descent method for graph regularized nonnegative matrix factorization.

PubMed

Guan, Naiyang; Wei, Lei; Luo, Zhigang; Tao, Dacheng

2013-01-01

Graph regularized nonnegative matrix factorization (GNMF) decomposes a nonnegative data matrix X[Symbol:see text]R(m x n) to the product of two lower-rank nonnegative factor matrices, i.e.,W[Symbol:see text]R(m x r) and H[Symbol:see text]R(r x n) (r < min {m,n}) and aims to preserve the local geometric structure of the dataset by minimizing squared Euclidean distance or Kullback-Leibler (KL) divergence between X and WH. The multiplicative update rule (MUR) is usually applied to optimize GNMF, but it suffers from the drawback of slow-convergence because it intrinsically advances one step along the rescaled negative gradient direction with a non-optimal step size. Recently, a multiple step-sizes fast gradient descent (MFGD) method has been proposed for optimizing NMF which accelerates MUR by searching the optimal step-size along the rescaled negative gradient direction with Newton's method. However, the computational cost of MFGD is high because 1) the high-dimensional Hessian matrix is dense and costs too much memory; and 2) the Hessian inverse operator and its multiplication with gradient cost too much time. To overcome these deficiencies of MFGD, we propose an efficient limited-memory FGD (L-FGD) method for optimizing GNMF. In particular, we apply the limited-memory BFGS (L-BFGS) method to directly approximate the multiplication of the inverse Hessian and the gradient for searching the optimal step size in MFGD. The preliminary results on real-world datasets show that L-FGD is more efficient than both MFGD and MUR. To evaluate the effectiveness of L-FGD, we validate its clustering performance for optimizing KL-divergence based GNMF on two popular face image datasets including ORL and PIE and two text corpora including Reuters and TDT2. The experimental results confirm the effectiveness of L-FGD by comparing it with the representative GNMF solvers.

Research on particle swarm optimization algorithm based on optimal movement probability

NASA Astrophysics Data System (ADS)

Ma, Jianhong; Zhang, Han; He, Baofeng

2017-01-01

The particle swarm optimization algorithm to improve the control precision, and has great application value training neural network and fuzzy system control fields etc.The traditional particle swarm algorithm is used for the training of feed forward neural networks,the search efficiency is low, and easy to fall into local convergence.An improved particle swarm optimization algorithm is proposed based on error back propagation gradient descent. Particle swarm optimization for Solving Least Squares Problems to meme group, the particles in the fitness ranking, optimization problem of the overall consideration, the error back propagation gradient descent training BP neural network, particle to update the velocity and position according to their individual optimal and global optimization, make the particles more to the social optimal learning and less to its optimal learning, it can avoid the particles fall into local optimum, by using gradient information can accelerate the PSO local search ability, improve the multi beam particle swarm depth zero less trajectory information search efficiency, the realization of improved particle swarm optimization algorithm. Simulation results show that the algorithm in the initial stage of rapid convergence to the global optimal solution can be near to the global optimal solution and keep close to the trend, the algorithm has faster convergence speed and search performance in the same running time, it can improve the convergence speed of the algorithm, especially the later search efficiency.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Pixel-based OPC optimization based on conjugate gradients.

PubMed

Ma, Xu; Arce, Gonzalo R

2011-01-31

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

The Descending Helium Balloon

ERIC Educational Resources Information Center

Helseth, Lars Egil

2014-01-01

I describe a simple and fascinating experiment wherein helium leaks out of a rubber balloon, thereby causing it to descend. An estimate of the volumetric leakage rate is made by measuring its rate of descent.

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

PubMed

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

2014-01-27

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

Recursive inverse kinematics for robot arms via Kalman filtering and Bryson-Frazier smoothing

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Scheid, R. E., Jr.

1987-01-01

This paper applies linear filtering and smoothing theory to solve recursively the inverse kinematics problem for serial multilink manipulators. This problem is to find a set of joint angles that achieve a prescribed tip position and/or orientation. A widely applicable numerical search solution is presented. The approach finds the minimum of a generalized distance between the desired and the actual manipulator tip position and/or orientation. Both a first-order steepest-descent gradient search and a second-order Newton-Raphson search are developed. The optimal relaxation factor required for the steepest descent method is computed recursively using an outward/inward procedure similar to those used typically for recursive inverse dynamics calculations. The second-order search requires evaluation of a gradient and an approximate Hessian. A Gauss-Markov approach is used to approximate the Hessian matrix in terms of products of first-order derivatives. This matrix is inverted recursively using a two-stage process of inward Kalman filtering followed by outward smoothing. This two-stage process is analogous to that recently developed by the author to solve by means of spatial filtering and smoothing the forward dynamics problem for serial manipulators.

Fault-tolerant nonlinear adaptive flight control using sliding mode online learning.

PubMed

Krüger, Thomas; Schnetter, Philipp; Placzek, Robin; Vörsmann, Peter

2012-08-01

An expanded nonlinear model inversion flight control strategy using sliding mode online learning for neural networks is presented. The proposed control strategy is implemented for a small unmanned aircraft system (UAS). This class of aircraft is very susceptible towards nonlinearities like atmospheric turbulence, model uncertainties and of course system failures. Therefore, these systems mark a sensible testbed to evaluate fault-tolerant, adaptive flight control strategies. Within this work the concept of feedback linearization is combined with feed forward neural networks to compensate for inversion errors and other nonlinear effects. Backpropagation-based adaption laws of the network weights are used for online training. Within these adaption laws the standard gradient descent backpropagation algorithm is augmented with the concept of sliding mode control (SMC). Implemented as a learning algorithm, this nonlinear control strategy treats the neural network as a controlled system and allows a stable, dynamic calculation of the learning rates. While considering the system's stability, this robust online learning method therefore offers a higher speed of convergence, especially in the presence of external disturbances. The SMC-based flight controller is tested and compared with the standard gradient descent backpropagation algorithm in the presence of system failures. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

PubMed

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.

Product Distribution Theory for Control of Multi-Agent Systems

NASA Technical Reports Server (NTRS)

Lee, Chia Fan; Wolpert, David H.

2004-01-01

Product Distribution (PD) theory is a new framework for controlling Multi-Agent Systems (MAS's). First we review one motivation of PD theory, as the information-theoretic extension of conventional full-rationality game theory to the case of bounded rational agents. In this extension the equilibrium of the game is the optimizer of a Lagrangian of the (probability distribution of) the joint stare of the agents. Accordingly we can consider a team game in which the shared utility is a performance measure of the behavior of the MAS. For such a scenario the game is at equilibrium - the Lagrangian is optimized - when the joint distribution of the agents optimizes the system's expected performance. One common way to find that equilibrium is to have each agent run a reinforcement learning algorithm. Here we investigate the alternative of exploiting PD theory to run gradient descent on the Lagrangian. We present computer experiments validating some of the predictions of PD theory for how best to do that gradient descent. We also demonstrate how PD theory can improve performance even when we are not allowed to rerun the MAS from different initial conditions, a requirement implicit in some previous work.

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

PubMed

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.

Coordinated control system modelling of ultra-supercritical unit based on a new T-S fuzzy structure.

PubMed

Hou, Guolian; Du, Huan; Yang, Yu; Huang, Congzhi; Zhang, Jianhua

2018-03-01

The thermal power plant, especially the ultra-supercritical unit is featured with severe nonlinearity, strong multivariable coupling. In order to deal with these difficulties, it is of great importance to build an accurate and simple model of the coordinated control system (CCS) in the ultra-supercritical unit. In this paper, an improved T-S fuzzy model identification approach is proposed. First of all, the k-means++ algorithm is employed to identify the premise parameters so as to guarantee the number of fuzzy rules. Then, the local linearized models are determined by using the incremental historical data around the cluster centers, which are obtained via the stochastic gradient descent algorithm with momentum and variable learning rate. Finally, with the proposed method, the CCS model of a 1000 MW USC unit in Tai Zhou power plant is developed. The effectiveness of the proposed approach is validated by the given extensive simulation results, and it can be further employed to design the overall advanced controllers for the CCS in an USC unit. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Online Sequential Projection Vector Machine with Adaptive Data Mean Update

PubMed Central

Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei

2016-01-01

We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM. PMID:27143958

Improved artificial bee colony algorithm for wavefront sensor-less system in free space optical communication

NASA Astrophysics Data System (ADS)

Niu, Chaojun; Han, Xiang'e.

2015-10-01

Adaptive optics (AO) technology is an effective way to alleviate the effect of turbulence on free space optical communication (FSO). A new adaptive compensation method can be used without a wave-front sensor. Artificial bee colony algorithm (ABC) is a population-based heuristic evolutionary algorithm inspired by the intelligent foraging behaviour of the honeybee swarm with the advantage of simple, good convergence rate, robust and less parameter setting. In this paper, we simulate the application of the improved ABC to correct the distorted wavefront and proved its effectiveness. Then we simulate the application of ABC algorithm, differential evolution (DE) algorithm and stochastic parallel gradient descent (SPGD) algorithm to the FSO system and analyze the wavefront correction capabilities by comparison of the coupling efficiency, the error rate and the intensity fluctuation in different turbulence before and after the correction. The results show that the ABC algorithm has much faster correction speed than DE algorithm and better correct ability for strong turbulence than SPGD algorithm. Intensity fluctuation can be effectively reduced in strong turbulence, but not so effective in week turbulence.

Online Sequential Projection Vector Machine with Adaptive Data Mean Update.

PubMed

Chen, Lin; Jia, Ji-Ting; Zhang, Qiong; Deng, Wan-Yu; Wei, Wei

2016-01-01

We propose a simple online learning algorithm especial for high-dimensional data. The algorithm is referred to as online sequential projection vector machine (OSPVM) which derives from projection vector machine and can learn from data in one-by-one or chunk-by-chunk mode. In OSPVM, data centering, dimension reduction, and neural network training are integrated seamlessly. In particular, the model parameters including (1) the projection vectors for dimension reduction, (2) the input weights, biases, and output weights, and (3) the number of hidden nodes can be updated simultaneously. Moreover, only one parameter, the number of hidden nodes, needs to be determined manually, and this makes it easy for use in real applications. Performance comparison was made on various high-dimensional classification problems for OSPVM against other fast online algorithms including budgeted stochastic gradient descent (BSGD) approach, adaptive multihyperplane machine (AMM), primal estimated subgradient solver (Pegasos), online sequential extreme learning machine (OSELM), and SVD + OSELM (feature selection based on SVD is performed before OSELM). The results obtained demonstrated the superior generalization performance and efficiency of the OSPVM.

A Fast Deep Learning System Using GPU

DTIC Science & Technology

2014-06-01

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

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

Oliver, R.; Soler, R.; Terradas, J.

Observations of active regions and limb prominences often show cold, dense blobs descending with an acceleration smaller than that of free fall. The dynamics of these condensations falling in the solar corona is investigated in this paper using a simple fully ionized plasma model. We find that the presence of a heavy condensation gives rise to a dynamical rearrangement of the coronal pressure that results in the formation of a large pressure gradient that opposes gravity. Eventually this pressure gradient becomes so large that the blob acceleration vanishes or even points upward. Then, the blob descent is characterized by anmore » initial acceleration phase followed by an essentially constant velocity phase. These two stages can be identified in published time-distance diagrams of coronal rain events. Both the duration of the first stage and the velocity attained by the blob increase for larger values of the ratio of blob to coronal density, for larger blob mass, and for smaller coronal temperature. Dense blobs are characterized by a detectable density growth (up to 60% in our calculations) and by a steepening of the density in their lower part, that could lead to the formation of a shock. They also emit sound waves that could be detected as small intensity changes with periods of the order of 100 s and lasting between a few and about 10 periods. Finally, the curvature of falling paths with large radii is only relevant when a very dense blob falls along inclined magnetic field lines.« less

Nonlinear Performance Seeking Control using Fuzzy Model Reference Learning Control and the Method of Steepest Descent

NASA Technical Reports Server (NTRS)

Kopasakis, George

1997-01-01

Performance Seeking Control (PSC) attempts to find and control the process at the operating condition that will generate maximum performance. In this paper a nonlinear multivariable PSC methodology will be developed, utilizing the Fuzzy Model Reference Learning Control (FMRLC) and the method of Steepest Descent or Gradient (SDG). This PSC control methodology employs the SDG method to find the operating condition that will generate maximum performance. This operating condition is in turn passed to the FMRLC controller as a set point for the control of the process. The conventional SDG algorithm is modified in this paper in order for convergence to occur monotonically. For the FMRLC control, the conventional fuzzy model reference learning control methodology is utilized, with guidelines generated here for effective tuning of the FMRLC controller.

Analysis of a New Variational Model to Restore Point-Like and Curve-Like Singularities in Imaging

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

Aubert, Gilles, E-mail: gaubert@unice.fr; Blanc-Feraud, Laure, E-mail: Laure.Blanc-Feraud@inria.fr; Graziani, Daniele, E-mail: Daniele.Graziani@inria.fr

2013-02-15

The paper is concerned with the analysis of a new variational model to restore point-like and curve-like singularities in biological images. To this aim we investigate the variational properties of a suitable energy which governs these pathologies. Finally in order to realize numerical experiments we minimize, in the discrete setting, a regularized version of this functional by fast descent gradient scheme.

On Nonconvex Decentralized Gradient Descent

DTIC Science & Technology

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

Understanding the Convolutional Neural Networks with Gradient Descent and Backpropagation

NASA Astrophysics Data System (ADS)

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.

Adaptive ISAR Imaging of Maneuvering Targets Based on a Modified Fourier Transform.

PubMed

Wang, Binbin; Xu, Shiyou; Wu, Wenzhen; Hu, Pengjiang; Chen, Zengping

2018-04-27

Focusing on the inverse synthetic aperture radar (ISAR) imaging of maneuvering targets, this paper presents a new imaging method which works well when the target's maneuvering is not too severe. After translational motion compensation, we describe the equivalent rotation of maneuvering targets by two variables-the relative chirp rate of the linear frequency modulated (LFM) signal and the Doppler focus shift. The first variable indicates the target's motion status, and the second one represents the possible residual error of the translational motion compensation. With them, a modified Fourier transform matrix is constructed and then used for cross-range compression. Consequently, the imaging of maneuvering is converted into a two-dimensional parameter optimization problem in which a stable and clear ISAR image is guaranteed. A gradient descent optimization scheme is employed to obtain the accurate relative chirp rate and Doppler focus shift. Moreover, we designed an efficient and robust initialization process for the gradient descent method, thus, the well-focused ISAR images of maneuvering targets can be achieved adaptively. Human intervention is not needed, and it is quite convenient for practical ISAR imaging systems. Compared to precedent imaging methods, the new method achieves better imaging quality under reasonable computational cost. Simulation results are provided to validate the effectiveness and advantages of the proposed method.

Applying Gradient Descent in Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

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.

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

PubMed

Xu, Xiao; Kong, Fan-Yu

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

Aini, Nurul; Rivaie, Mohd; Mamat, Mustafa

2016-11-01

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

Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models.

PubMed

Yuan, Gonglin; Duan, Xiabin; Liu, Wenjie; Wang, Xiaoliang; Cui, Zengru; Sheng, Zhou

2015-01-01

Two new PRP conjugate Algorithms are proposed in this paper based on two modified PRP conjugate gradient methods: the first algorithm is proposed for solving unconstrained optimization problems, and the second algorithm is proposed for solving nonlinear equations. The first method contains two aspects of information: function value and gradient value. The two methods both possess some good properties, as follows: 1) βk ≥ 0 2) the search direction has the trust region property without the use of any line search method 3) the search direction has sufficient descent property without the use of any line search method. Under some suitable conditions, we establish the global convergence of the two algorithms. We conduct numerical experiments to evaluate our algorithms. The numerical results indicate that the first algorithm is effective and competitive for solving unconstrained optimization problems and that the second algorithm is effective for solving large-scale nonlinear equations.

Two New PRP Conjugate Gradient Algorithms for Minimization Optimization Models

PubMed Central

Yuan, Gonglin; Duan, Xiabin; Liu, Wenjie; Wang, Xiaoliang; Cui, Zengru; Sheng, Zhou

2015-01-01

Two new PRP conjugate Algorithms are proposed in this paper based on two modified PRP conjugate gradient methods: the first algorithm is proposed for solving unconstrained optimization problems, and the second algorithm is proposed for solving nonlinear equations. The first method contains two aspects of information: function value and gradient value. The two methods both possess some good properties, as follows: 1)β k ≥ 0 2) the search direction has the trust region property without the use of any line search method 3) the search direction has sufficient descent property without the use of any line search method. Under some suitable conditions, we establish the global convergence of the two algorithms. We conduct numerical experiments to evaluate our algorithms. The numerical results indicate that the first algorithm is effective and competitive for solving unconstrained optimization problems and that the second algorithm is effective for solving large-scale nonlinear equations. PMID:26502409

A mesh gradient technique for numerical optimization

NASA Technical Reports Server (NTRS)

Willis, E. A., Jr.

1973-01-01

A class of successive-improvement optimization methods in which directions of descent are defined in the state space along each trial trajectory are considered. The given problem is first decomposed into two discrete levels by imposing mesh points. Level 1 consists of running optimal subarcs between each successive pair of mesh points. For normal systems, these optimal two-point boundary value problems can be solved by following a routine prescription if the mesh spacing is sufficiently close. A spacing criterion is given. Under appropriate conditions, the criterion value depends only on the coordinates of the mesh points, and its gradient with respect to those coordinates may be defined by interpreting the adjoint variables as partial derivatives of the criterion value function. In level 2, the gradient data is used to generate improvement steps or search directions in the state space which satisfy the boundary values and constraints of the given problem.

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

NASA Astrophysics Data System (ADS)

Kisi, Ozgur; Shiri, Jalal

2012-06-01

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

Learning Structured Classifiers with Dual Coordinate Ascent

DTIC Science & Technology

2010-06-01

stochastic gradient descent (SGD) [LeCun et al., 1998], and the margin infused relaxed algorithm (MIRA) [ Crammer et al., 2006]. This paper presents a...evaluate these methods on the Prague Dependency Treebank us- ing online large-margin learning tech- niques ( Crammer et al., 2003; McDonald et al., 2005...between two kinds of factors: hard constraint factors, which are used to rule out forbidden par- tial assignments by mapping them to zero potential values

Dynamic metrology and data processing for precision freeform optics fabrication and testing

NASA Astrophysics Data System (ADS)

Aftab, Maham; Trumper, Isaac; Huang, Lei; Choi, Heejoo; Zhao, Wenchuan; Graves, Logan; Oh, Chang Jin; Kim, Dae Wook

2017-06-01

Dynamic metrology holds the key to overcoming several challenging limitations of conventional optical metrology, especially with regards to precision freeform optical elements. We present two dynamic metrology systems: 1) adaptive interferometric null testing; and 2) instantaneous phase shifting deflectometry, along with an overview of a gradient data processing and surface reconstruction technique. The adaptive null testing method, utilizing a deformable mirror, adopts a stochastic parallel gradient descent search algorithm in order to dynamically create a null testing condition for unknown freeform optics. The single-shot deflectometry system implemented on an iPhone uses a multiplexed display pattern to enable dynamic measurements of time-varying optical components or optics in vibration. Experimental data, measurement accuracy / precision, and data processing algorithms are discussed.

Learning algorithms for human-machine interfaces.

PubMed

Danziger, Zachary; Fishbach, Alon; Mussa-Ivaldi, Ferdinando A

2009-05-01

The goal of this study is to create and examine machine learning algorithms that adapt in a controlled and cadenced way to foster a harmonious learning environment between the user and the controlled device. To evaluate these algorithms, we have developed a simple experimental framework. Subjects wear an instrumented data glove that records finger motions. The high-dimensional glove signals remotely control the joint angles of a simulated planar two-link arm on a computer screen, which is used to acquire targets. A machine learning algorithm was applied to adaptively change the transformation between finger motion and the simulated robot arm. This algorithm was either LMS gradient descent or the Moore-Penrose (MP) pseudoinverse transformation. Both algorithms modified the glove-to-joint angle map so as to reduce the endpoint errors measured in past performance. The MP group performed worse than the control group (subjects not exposed to any machine learning), while the LMS group outperformed the control subjects. However, the LMS subjects failed to achieve better generalization than the control subjects, and after extensive training converged to the same level of performance as the control subjects. These results highlight the limitations of coadaptive learning using only endpoint error reduction.

On the fusion of tuning parameters of fuzzy rules and neural network

NASA Astrophysics Data System (ADS)

Mamuda, Mamman; Sathasivam, Saratha

2017-08-01

Learning fuzzy rule-based system with neural network can lead to a precise valuable empathy of several problems. Fuzzy logic offers a simple way to reach at a definite conclusion based upon its vague, ambiguous, imprecise, noisy or missing input information. Conventional learning algorithm for tuning parameters of fuzzy rules using training input-output data usually end in a weak firing state, this certainly powers the fuzzy rule and makes it insecure for a multiple-input fuzzy system. In this paper, we introduce a new learning algorithm for tuning the parameters of the fuzzy rules alongside with radial basis function neural network (RBFNN) in training input-output data based on the gradient descent method. By the new learning algorithm, the problem of weak firing using the conventional method was addressed. We illustrated the efficiency of our new learning algorithm by means of numerical examples. MATLAB R2014(a) software was used in simulating our result The result shows that the new learning method has the best advantage of training the fuzzy rules without tempering with the fuzzy rule table which allowed a membership function of the rule to be used more than one time in the fuzzy rule base.

Learning Algorithms for Human–Machine Interfaces

PubMed Central

Fishbach, Alon; Mussa-Ivaldi, Ferdinando A.

2012-01-01

The goal of this study is to create and examine machine learning algorithms that adapt in a controlled and cadenced way to foster a harmonious learning environment between the user and the controlled device. To evaluate these algorithms, we have developed a simple experimental framework. Subjects wear an instrumented data glove that records finger motions. The high-dimensional glove signals remotely control the joint angles of a simulated planar two-link arm on a computer screen, which is used to acquire targets. A machine learning algorithm was applied to adaptively change the transformation between finger motion and the simulated robot arm. This algorithm was either LMS gradient descent or the Moore–Penrose (MP) pseudoinverse transformation. Both algorithms modified the glove-to-joint angle map so as to reduce the endpoint errors measured in past performance. The MP group performed worse than the control group (subjects not exposed to any machine learning), while the LMS group outperformed the control subjects. However, the LMS subjects failed to achieve better generalization than the control subjects, and after extensive training converged to the same level of performance as the control subjects. These results highlight the limitations of coadaptive learning using only endpoint error reduction. PMID:19203886

A Relation Between the Eikonal Equation Associated to a Potential Energy Surface and a Hyperbolic Wave Equation.

PubMed

Bofill, Josep Maria; Quapp, Wolfgang; Caballero, Marc

2012-12-11

The potential energy surface (PES) of a molecule can be decomposed into equipotential hypersurfaces. We show in this article that the hypersurfaces are the wave fronts of a certain hyperbolic partial differential equation, a wave equation. It is connected with the gradient lines, or the steepest descent, or the steepest ascent lines of the PES. The energy seen as a reaction coordinate plays the central role in this treatment.

Regularized Dual Averaging Image Reconstruction for Full-Wave Ultrasound Computed Tomography.

PubMed

Matthews, Thomas P; Wang, Kun; Li, Cuiping; Duric, Neb; Anastasio, Mark A

2017-05-01

Ultrasound computed tomography (USCT) holds great promise for breast cancer screening. Waveform inversion-based image reconstruction methods account for higher order diffraction effects and can produce high-resolution USCT images, but are computationally demanding. Recently, a source encoding technique has been combined with stochastic gradient descent (SGD) to greatly reduce image reconstruction times. However, this method bundles the stochastic data fidelity term with the deterministic regularization term. This limitation can be overcome by replacing SGD with a structured optimization method, such as the regularized dual averaging method, that exploits knowledge of the composition of the cost function. In this paper, the dual averaging method is combined with source encoding techniques to improve the effectiveness of regularization while maintaining the reduced reconstruction times afforded by source encoding. It is demonstrated that each iteration can be decomposed into a gradient descent step based on the data fidelity term and a proximal update step corresponding to the regularization term. Furthermore, the regularization term is never explicitly differentiated, allowing nonsmooth regularization penalties to be naturally incorporated. The wave equation is solved by the use of a time-domain method. The effectiveness of this approach is demonstrated through computer simulation and experimental studies. The results suggest that the dual averaging method can produce images with less noise and comparable resolution to those obtained by the use of SGD.

A different approach to estimate nonlinear regression model using numerical methods

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Reconstructing the Surface Permittivity Distribution from Data Measured by the CONSERT Instrument aboard Rosetta: Method and Simulations

NASA Astrophysics Data System (ADS)

Plettemeier, D.; Statz, C.; Hegler, S.; Herique, A.; Kofman, W. W.

2014-12-01

One of the main scientific objectives of the Comet Nucleus Sounding Experiment by Radiowave Transmission (CONSERT) aboard Rosetta is to perform a dielectric characterization of comet 67P/Chuyurmov-Gerasimenko's nucleus by means of a bi-static sounding between the lander Philae launched onto the comet's surface and the orbiter Rosetta. For the sounding, the lander part of CONSERT will receive and process the radio signal emitted by the orbiter part of the instrument and transmit a signal to the orbiter to be received by CONSERT. CONSERT will also be operated as bi-static RADAR during the descent of the lander Philae onto the comet's surface. From data measured during the descent, we aim at reconstructing a surface permittivity map of the comet at the landing site and along the path below the descent trajectory. This surface permittivity map will give information on the bulk material right below and around the landing site and the surface roughness in areas covered by the instrument along the descent. The proposed method to estimate the surface permittivity distribution is based on a least-squares based inversion approach in frequency domain. The direct problem of simulating the wave-propagation between lander and orbiter at line-of-sight and the signal reflected on the comet's surface is modelled using a dielectric physical optics approximation. Restrictions on the measurement positions by the descent orbitography and limitations on the instrument dynamic range will be dealt with by application of a regularization technique where the surface permittivity distribution and the gradient with regard to the permittivity is projected in a domain defined by a viable model of the spatial material and roughness distribution. The least-squares optimization step of the reconstruction is performed in such domain on a reduced set of parameters yielding stable results. The viability of the proposed method is demonstrated by reconstruction results based on simulated data.

The Double Star Orbit Initial Value Problem

NASA Astrophysics Data System (ADS)

Hensley, Hagan

2018-04-01

Many precise algorithms exist to find a best-fit orbital solution for a double star system given a good enough initial value. Desmos is an online graphing calculator tool with extensive capabilities to support animations and defining functions. It can provide a useful visual means of analyzing double star data to arrive at a best guess approximation of the orbital solution. This is a necessary requirement before using a gradient-descent algorithm to find the best-fit orbital solution for a binary system.

Learning in Modular Systems

DTIC Science & Technology

2010-05-07

important for deep modular systems is that taking a series of small update steps and stopping before convergence, so called early stopping, is a form of regu...larization around the initial parameters of the system . For example, the stochastic gradient descent 5 1 u + 1 v = 1 6‖x2‖q = ‖x‖22q 22 Chapter 2...Aside from the overall speed of the classifier, no quantitative performance analysis was given, and the role played by the features in the larger system

Dynamic load balancing algorithm for molecular dynamics based on Voronoi cells domain decompositions

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

Fattebert, J.-L.; Richards, D.F.; Glosli, J.N.

2012-12-01

We present a new algorithm for automatic parallel load balancing in classical molecular dynamics. It assumes a spatial domain decomposition of particles into Voronoi cells. It is a gradient method which attempts to minimize a cost function by displacing Voronoi sites associated with each processor/sub-domain along steepest descent directions. Excellent load balance has been obtained for quasi-2D and 3D practical applications, with up to 440·10 6 particles on 65,536 MPI tasks.

Differential Frequency Hopping (DFH) Modulation for Underwater Acoustic Communications and Networking

DTIC Science & Technology

2009-10-09

trains the coefficients c of a finite impulse response (FIR) filter by gradient descent. The coefficients at iteration k + 1 are computed with the update... absorption . Figure 9 shows the reflection loss as a function of grazing angle for this bottom model. Note that below 30◦ this bottom model predicts...less than 1 dB loss per ray bounce. 11 Figure 9: Jackson bottom reflection loss for sand at 15 kHz Absorption Loss The absorption loss in the medium was

Hills and Valleys: Understanding the Under-Eye

PubMed Central

Naik, Milind N

2016-01-01

Soft tissue deflation and descent have long been implicated in the pathogenesis of facial aging. In the periorbital area, the upper orbital region is thought to change by descent of the eyebrow, as well as deflation of brow fat. While the understanding of the aging changes in the upper eyelid region are relatively simple, the lower eyelid poses a myriad of aging changes, each demanding a specific management plan. These can be best described in terms of elevations, or ‘Hills’ and hollows, or ‘Valleys’. This article simplifies the understanding of the lower eyelid in the light of anatomical knowledge, and available literature. It forms a basis of easy diagnosis and treatment of the soft tissue changes in the lower eyelid and malar region. PMID:27398004

2014 Summer Series - Ethiraj Venkatapathy - Mary Poppins Approach to Human Mars Mission Entry, Descent and Landing

NASA Image and Video Library

2014-06-17

NASA is investing in a number of technologies to extend Entry, Descent and Landing (EDL) capabilities to enable Human Missions to Mars. These technologies will also enable robotic Science missions. Human missions will require landing payloads of 10?s of metric tons, not possible with today's technology. Decelerating from entry speeds around 15,000 miles per hour to landing in a matter of minutes will require very large drag or deceleration. The one way to achieve required deceleration is to deploy a large surface that can be stowed during launch and deployed prior to entry. This talk will highlight a simple concept similar to an umbrella. Though the concept is simple, the size required for human Mars missions and the heating encountered during entry are significant challenges. The mechanically deployable system can also enable robotic science missions to Venus and is also equally applicable for bringing back cube-satellites and other small payloads. The scalable concept called Adaptive Deployable Entry and Placement Technology (ADEPT) is under development and is the focus of this talk.

Acceleration of Convergence to Equilibrium in Markov Chains by Breaking Detailed Balance

NASA Astrophysics Data System (ADS)

Kaiser, Marcus; Jack, Robert L.; Zimmer, Johannes

2017-07-01

We analyse and interpret the effects of breaking detailed balance on the convergence to equilibrium of conservative interacting particle systems and their hydrodynamic scaling limits. For finite systems of interacting particles, we review existing results showing that irreversible processes converge faster to their steady state than reversible ones. We show how this behaviour appears in the hydrodynamic limit of such processes, as described by macroscopic fluctuation theory, and we provide a quantitative expression for the acceleration of convergence in this setting. We give a geometrical interpretation of this acceleration, in terms of currents that are antisymmetric under time-reversal and orthogonal to the free energy gradient, which act to drive the system away from states where (reversible) gradient-descent dynamics result in slow convergence to equilibrium.

A dynamical regularization algorithm for solving inverse source problems of elliptic partial differential equations

NASA Astrophysics Data System (ADS)

Zhang, Ye; Gong, Rongfang; Cheng, Xiaoliang; Gulliksson, Mårten

2018-06-01

This study considers the inverse source problem for elliptic partial differential equations with both Dirichlet and Neumann boundary data. The unknown source term is to be determined by additional boundary conditions. Unlike the existing methods found in the literature, which usually employ the first-order in time gradient-like system (such as the steepest descent methods) for numerically solving the regularized optimization problem with a fixed regularization parameter, we propose a novel method with a second-order in time dissipative gradient-like system and a dynamical selected regularization parameter. A damped symplectic scheme is proposed for the numerical solution. Theoretical analysis is given for both the continuous model and the numerical algorithm. Several numerical examples are provided to show the robustness of the proposed algorithm.

A flight management algorithm and guidance for fuel-conservative descents in a time-based metered air traffic environment: Development and flight test results

NASA Technical Reports Server (NTRS)

Knox, C. E.

1984-01-01

A simple airborne flight management descent algorithm designed to define a flight profile subject to the constraints of using idle thrust, a clean airplane configuration (landing gear up, flaps zero, and speed brakes retracted), and fixed-time end conditions was developed and flight tested in the NASA TSRV B-737 research airplane. The research test flights, conducted in the Denver ARTCC automated time-based metering LFM/PD ATC environment, demonstrated that time guidance and control in the cockpit was acceptable to the pilots and ATC controllers and resulted in arrival of the airplane over the metering fix with standard deviations in airspeed error of 6.5 knots, in altitude error of 23.7 m (77.8 ft), and in arrival time accuracy of 12 sec. These accuracies indicated a good representation of airplane performance and wind modeling. Fuel savings will be obtained on a fleet-wide basis through a reduction of the time error dispersions at the metering fix and on a single-airplane basis by presenting the pilot with guidance for a fuel-efficient descent.

Algorithm for Training a Recurrent Multilayer Perceptron

NASA Technical Reports Server (NTRS)

Parlos, Alexander G.; Rais, Omar T.; Menon, Sunil K.; Atiya, Amir F.

2004-01-01

An improved algorithm has been devised for training a recurrent multilayer perceptron (RMLP) for optimal performance in predicting the behavior of a complex, dynamic, and noisy system multiple time steps into the future. [An RMLP is a computational neural network with self-feedback and cross-talk (both delayed by one time step) among neurons in hidden layers]. Like other neural-network-training algorithms, this algorithm adjusts network biases and synaptic-connection weights according to a gradient-descent rule. The distinguishing feature of this algorithm is a combination of global feedback (the use of predictions as well as the current output value in computing the gradient at each time step) and recursiveness. The recursive aspect of the algorithm lies in the inclusion of the gradient of predictions at each time step with respect to the predictions at the preceding time step; this recursion enables the RMLP to learn the dynamics. It has been conjectured that carrying the recursion to even earlier time steps would enable the RMLP to represent a noisier, more complex system.

Fourier ptychographic reconstruction using Poisson maximum likelihood and truncated Wirtinger gradient.

PubMed

Bian, Liheng; Suo, Jinli; Chung, Jaebum; Ou, Xiaoze; Yang, Changhuei; Chen, Feng; Dai, Qionghai

2016-06-10

Fourier ptychographic microscopy (FPM) is a novel computational coherent imaging technique for high space-bandwidth product imaging. Mathematically, Fourier ptychographic (FP) reconstruction can be implemented as a phase retrieval optimization process, in which we only obtain low resolution intensity images corresponding to the sub-bands of the sample's high resolution (HR) spatial spectrum, and aim to retrieve the complex HR spectrum. In real setups, the measurements always suffer from various degenerations such as Gaussian noise, Poisson noise, speckle noise and pupil location error, which would largely degrade the reconstruction. To efficiently address these degenerations, we propose a novel FP reconstruction method under a gradient descent optimization framework in this paper. The technique utilizes Poisson maximum likelihood for better signal modeling, and truncated Wirtinger gradient for effective error removal. Results on both simulated data and real data captured using our laser-illuminated FPM setup show that the proposed method outperforms other state-of-the-art algorithms. Also, we have released our source code for non-commercial use.

Binding in pair potentials of liquid simple metals from nonlocality in electronic kinetic energy

NASA Technical Reports Server (NTRS)

Perrot, F.; March, N. H.

1990-01-01

The paper presents an explicit expression for the pair potential in liquid simple metals from low-order density-gradient theory when the superposition of single-center displaced charges is employed. Numerical results are presented for the gradient expansion pair interaction in liquid Na and Be. The low-order density-gradient equation for the pair potential is presented.

Application of Artificial Neural Networks in the Design and Optimization of a Nanoparticulate Fingolimod Delivery System Based on Biodegradable Poly(3-Hydroxybutyrate-Co-3-Hydroxyvalerate).

PubMed

Shahsavari, Shadab; Rezaie Shirmard, Leila; Amini, Mohsen; Abedin Dokoosh, Farid

2017-01-01

Formulation of a nanoparticulate Fingolimod delivery system based on biodegradable poly(3-hydroxybutyrate-co-3-hydroxyvalerate) was optimized according to artificial neural networks (ANNs). Concentration of poly(3-hydroxybutyrate-co-3-hydroxyvalerate), PVA and amount of Fingolimod is considered as the input value, and the particle size, polydispersity index, loading capacity, and entrapment efficacy as output data in experimental design study. In vitro release study was carried out for best formulation according to statistical analysis. ANNs are employed to generate the best model to determine the relationships between various values. In order to specify the model with the best accuracy and proficiency for the in vitro release, a multilayer percepteron with different training algorithm has been examined. Three training model formulations including Levenberg-Marquardt (LM), gradient descent, and Bayesian regularization were employed for training the ANN models. It is demonstrated that the predictive ability of each training algorithm is in the order of LM > gradient descent > Bayesian regularization. Also, optimum formulation was achieved by LM training function with 15 hidden layers and 20 neurons. The transfer function of the hidden layer for this formulation and the output layer were tansig and purlin, respectively. Also, the optimization process was developed by minimizing the error among the predicted and observed values of training algorithm (about 0.0341). Copyright © 2016 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

Piecewise convexity of artificial neural networks.

PubMed

Rister, Blaine; Rubin, Daniel L

2017-10-01

Although artificial neural networks have shown great promise in applications including computer vision and speech recognition, there remains considerable practical and theoretical difficulty in optimizing their parameters. The seemingly unreasonable success of gradient descent methods in minimizing these non-convex functions remains poorly understood. In this work we offer some theoretical guarantees for networks with piecewise affine activation functions, which have in recent years become the norm. We prove three main results. First, that the network is piecewise convex as a function of the input data. Second, that the network, considered as a function of the parameters in a single layer, all others held constant, is again piecewise convex. Third, that the network as a function of all its parameters is piecewise multi-convex, a generalization of biconvexity. From here we characterize the local minima and stationary points of the training objective, showing that they minimize the objective on certain subsets of the parameter space. We then analyze the performance of two optimization algorithms on multi-convex problems: gradient descent, and a method which repeatedly solves a number of convex sub-problems. We prove necessary convergence conditions for the first algorithm and both necessary and sufficient conditions for the second, after introducing regularization to the objective. Finally, we remark on the remaining difficulty of the global optimization problem. Under the squared error objective, we show that by varying the training data, a single rectifier neuron admits local minima arbitrarily far apart, both in objective value and parameter space. Copyright © 2017 Elsevier Ltd. All rights reserved.

Manifold regularized discriminative nonnegative matrix factorization with fast gradient descent.

PubMed

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.

Sparse Representation with Spatio-Temporal Online Dictionary Learning for Efficient Video Coding.

PubMed

Dai, Wenrui; Shen, Yangmei; Tang, Xin; Zou, Junni; Xiong, Hongkai; Chen, Chang Wen

2016-07-27

Classical dictionary learning methods for video coding suer from high computational complexity and interfered coding eciency by disregarding its underlying distribution. This paper proposes a spatio-temporal online dictionary learning (STOL) algorithm to speed up the convergence rate of dictionary learning with a guarantee of approximation error. The proposed algorithm incorporates stochastic gradient descents to form a dictionary of pairs of 3-D low-frequency and highfrequency spatio-temporal volumes. In each iteration of the learning process, it randomly selects one sample volume and updates the atoms of dictionary by minimizing the expected cost, rather than optimizes empirical cost over the complete training data like batch learning methods, e.g. K-SVD. Since the selected volumes are supposed to be i.i.d. samples from the underlying distribution, decomposition coecients attained from the trained dictionary are desirable for sparse representation. Theoretically, it is proved that the proposed STOL could achieve better approximation for sparse representation than K-SVD and maintain both structured sparsity and hierarchical sparsity. It is shown to outperform batch gradient descent methods (K-SVD) in the sense of convergence speed and computational complexity, and its upper bound for prediction error is asymptotically equal to the training error. With lower computational complexity, extensive experiments validate that the STOL based coding scheme achieves performance improvements than H.264/AVC or HEVC as well as existing super-resolution based methods in ratedistortion performance and visual quality.

Crosswind Shear Gradient Affect on Wake Vortices

NASA Technical Reports Server (NTRS)

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.

The formation of stable pH gradients with weak monovalent buffers for isoelectric focusing in free solution

NASA Technical Reports Server (NTRS)

Mosher, Richard A.; Thormann, Wolfgang; Graham, Aly; Bier, Milan

1985-01-01

Two methods which utilize simple buffers for the generation of stable pH gradients (useful for preparative isoelectric focusing) are compared and contrasted. The first employs preformed gradients comprised of two simple buffers in density-stabilized free solution. The second method utilizes neutral membranes to isolate electrolyte reservoirs of constant composition from the separation column. It is shown by computer simulation that steady-state gradients can be formed at any pH range with any number of components in such a system.

Efficient two-dimensional compressive sensing in MIMO radar

NASA Astrophysics Data System (ADS)

Shahbazi, Nafiseh; Abbasfar, Aliazam; Jabbarian-Jahromi, Mohammad

2017-12-01

Compressive sensing (CS) has been a way to lower sampling rate leading to data reduction for processing in multiple-input multiple-output (MIMO) radar systems. In this paper, we further reduce the computational complexity of a pulse-Doppler collocated MIMO radar by introducing a two-dimensional (2D) compressive sensing. To do so, we first introduce a new 2D formulation for the compressed received signals and then we propose a new measurement matrix design for our 2D compressive sensing model that is based on minimizing the coherence of sensing matrix using gradient descent algorithm. The simulation results show that our proposed 2D measurement matrix design using gradient decent algorithm (2D-MMDGD) has much lower computational complexity compared to one-dimensional (1D) methods while having better performance in comparison with conventional methods such as Gaussian random measurement matrix.

Statistical Mechanics of Node-perturbation Learning with Noisy Baseline

NASA Astrophysics Data System (ADS)

Hara, Kazuyuki; Katahira, Kentaro; Okada, Masato

2017-02-01

Node-perturbation learning is a type of statistical gradient descent algorithm that can be applied to problems where the objective function is not explicitly formulated, including reinforcement learning. It estimates the gradient of an objective function by using the change in the object function in response to the perturbation. The value of the objective function for an unperturbed output is called a baseline. Cho et al. proposed node-perturbation learning with a noisy baseline. In this paper, we report on building the statistical mechanics of Cho's model and on deriving coupled differential equations of order parameters that depict learning dynamics. We also show how to derive the generalization error by solving the differential equations of order parameters. On the basis of the results, we show that Cho's results are also apply in general cases and show some general performances of Cho's model.

Development and implementation of (Q)SAR modeling within the CHARMMing web-user interface.

PubMed

Weidlich, Iwona E; Pevzner, Yuri; Miller, Benjamin T; Filippov, Igor V; Woodcock, H Lee; Brooks, Bernard R

2015-01-05

Recent availability of large publicly accessible databases of chemical compounds and their biological activities (PubChem, ChEMBL) has inspired us to develop a web-based tool for structure activity relationship and quantitative structure activity relationship modeling to add to the services provided by CHARMMing (www.charmming.org). This new module implements some of the most recent advances in modern machine learning algorithms-Random Forest, Support Vector Machine, Stochastic Gradient Descent, Gradient Tree Boosting, so forth. A user can import training data from Pubchem Bioassay data collections directly from our interface or upload his or her own SD files which contain structures and activity information to create new models (either categorical or numerical). A user can then track the model generation process and run models on new data to predict activity. © 2014 Wiley Periodicals, Inc.

Design for a Simple and Inexpensive Cylinder-within-a-Cylinder Gradient Maker for the Undergraduate Biochemistry Laboratory

ERIC Educational Resources Information Center

Sims, Paul A.; O'Mealey, Gary B.; Khan, Nabeel A.; Larabee, Chelsea M.

2011-01-01

A design for a simple and inexpensive gradient maker is described. The gradient maker is assembled by (i) cutting the tops off two plastic bottles of differing diameters to produce two cylinders with intact bottoms; (ii) drilling a small hole toward the bottom of the smaller diameter cylinder and plugging the hole with a size 00 cork stopper; and…

Shape optimisation of an underwater Bernoulli gripper

NASA Astrophysics Data System (ADS)

Flint, Tim; Sellier, Mathieu

2015-11-01

In this work, we are interested in maximising the suction produced by an underwater Bernoulli gripper. Bernoulli grippers work by exploiting low pressure regions caused by the acceleration of a working fluid through a narrow channel, between the gripper and a surface, to provide a suction force. This mechanism allows for non-contact adhesion to various surfaces and may be used to hold a robot to the hull of a ship while it inspects welds for example. A Bernoulli type pressure analysis was used to model the system with a Darcy friction factor approximation to include the effects of frictional losses. The analysis involved a constrained optimisation in order to avoid cavitation within the mechanism which would result in decreased performance and damage to surfaces. A sensitivity based method and gradient descent approach was used to find the optimum shape of a discretised surface. The model's accuracy has been quantified against finite volume computational fluid dynamics simulation (ANSYS CFX) using the k- ω SST turbulence model. Preliminary results indicate significant improvement in suction force when compared to a simple geometry by retaining a pressure just above that at which cavitation would occur over as much surface area as possible. Doctoral candidate in the Mechanical Engineering Department of the University of Canterbury, New Zealand.

Adaptive Importance Sampling for Control and Inference

NASA Astrophysics Data System (ADS)

Kappen, H. J.; Ruiz, H. C.

2016-03-01

Path integral (PI) control problems are a restricted class of non-linear control problems that can be solved formally as a Feynman-Kac PI and can be estimated using Monte Carlo sampling. In this contribution we review PI control theory in the finite horizon case. We subsequently focus on the problem how to compute and represent control solutions. We review the most commonly used methods in robotics and control. Within the PI theory, the question of how to compute becomes the question of importance sampling. Efficient importance samplers are state feedback controllers and the use of these requires an efficient representation. Learning and representing effective state-feedback controllers for non-linear stochastic control problems is a very challenging, and largely unsolved, problem. We show how to learn and represent such controllers using ideas from the cross entropy method. We derive a gradient descent method that allows to learn feed-back controllers using an arbitrary parametrisation. We refer to this method as the path integral cross entropy method or PICE. We illustrate this method for some simple examples. The PI control methods can be used to estimate the posterior distribution in latent state models. In neuroscience these problems arise when estimating connectivity from neural recording data using EM. We demonstrate the PI control method as an accurate alternative to particle filtering.

Adaptive conversion of a high-order mode beam into a near-diffraction-limited beam.

PubMed

Zhao, Haichuan; Wang, Xiaolin; Ma, Haotong; Zhou, Pu; Ma, Yanxing; Xu, Xiaojun; Zhao, Yijun

2011-08-01

We present a new method for efficiently transforming a high-order mode beam into a nearly Gaussian beam with much higher beam quality. The method is based on modulation of phases of different lobes by stochastic parallel gradient descent algorithm and coherent addition after phase flattening. We demonstrate the method by transforming an LP11 mode into a nearly Gaussian beam. The experimental results reveal that the power in the diffraction-limited bucket in the far field is increased by more than a factor of 1.5.

Controlled weather balloon ascents and descents for atmospheric research and climate monitoring

PubMed Central

Kräuchi, Andreas; Philipona, Rolf; Romanens, Gonzague; Hurst, Dale F.; Hall, Emrys G.; Jordan, Allen F.

2017-01-01

In situ upper-air measurements are often made with instruments attached to weather balloons launched at the surface and lifted into the stratosphere. Present-day balloon-borne sensors allow near-continuous measurements from the Earth’s surface to about 35 km (3–5 hPa), where the balloons burst and their instrument payloads descend with parachutes. It has been demonstrated that ascending weather balloons can perturb the air measured by very sensitive humidity and temperature sensors trailing behind them, particularly in the upper troposphere and lower stratosphere (UTLS). The use of controlled balloon descent for such measurements has therefore been investigated and is described here. We distinguish between the single balloon technique that uses a simple automatic valve system to release helium from the balloon at a preset ambient pressure, and the double balloon technique that uses a carrier balloon to lift the payload and a parachute balloon to control the descent of instruments after the carrier balloon is released at preset altitude. The automatic valve technique has been used for several decades for water vapor soundings with frost point hygrometers, whereas the double balloon technique has recently been re-established and deployed to measure radiation and temperature profiles through the atmosphere. Double balloon soundings also strongly reduce pendulum motion of the payload, stabilizing radiation instruments during ascent. We present the flight characteristics of these two ballooning techniques and compare the quality of temperature and humidity measurements made during ascent and descent. PMID:29263765

Methods to estimate effective population size using pedigree data: Examples in dog, sheep, cattle and horse

PubMed Central

2013-01-01

Background Effective population sizes of 140 populations (including 60 dog breeds, 40 sheep breeds, 20 cattle breeds and 20 horse breeds) were computed using pedigree information and six different computation methods. Simple demographical information (number of breeding males and females), variance of progeny size, or evolution of identity by descent probabilities based on coancestry or inbreeding were used as well as identity by descent rate between two successive generations or individual identity by descent rate. Results Depending on breed and method, effective population sizes ranged from 15 to 133 056, computation method and interaction between computation method and species showing a significant effect on effective population size (P < 0.0001). On average, methods based on number of breeding males and females and variance of progeny size produced larger values (4425 and 356, respectively), than those based on identity by descent probabilities (average values between 93 and 203). Since breeding practices and genetic substructure within dog breeds increased inbreeding, methods taking into account the evolution of inbreeding produced lower effective population sizes than those taking into account evolution of coancestry. The correlation level between the simplest method (number of breeding males and females, requiring no genealogical information) and the most sophisticated one ranged from 0.44 to 0.60 according to species. Conclusions When choosing a method to compute effective population size, particular attention should be paid to the species and the specific genetic structure of the population studied. PMID:23281913

Controlled weather balloon ascents and descents for atmospheric research and climate monitoring.

PubMed

Kräuchi, Andreas; Philipona, Rolf; Romanens, Gonzague; Hurst, Dale F; Hall, Emrys G; Jordan, Allen F

2016-01-01

In situ upper-air measurements are often made with instruments attached to weather balloons launched at the surface and lifted into the stratosphere. Present-day balloon-borne sensors allow near-continuous measurements from the Earth's surface to about 35 km (3-5 hPa), where the balloons burst and their instrument payloads descend with parachutes. It has been demonstrated that ascending weather balloons can perturb the air measured by very sensitive humidity and temperature sensors trailing behind them, particularly in the upper troposphere and lower stratosphere (UTLS). The use of controlled balloon descent for such measurements has therefore been investigated and is described here. We distinguish between the single balloon technique that uses a simple automatic valve system to release helium from the balloon at a preset ambient pressure, and the double balloon technique that uses a carrier balloon to lift the payload and a parachute balloon to control the descent of instruments after the carrier balloon is released at preset altitude. The automatic valve technique has been used for several decades for water vapor soundings with frost point hygrometers, whereas the double balloon technique has recently been re-established and deployed to measure radiation and temperature profiles through the atmosphere. Double balloon soundings also strongly reduce pendulum motion of the payload, stabilizing radiation instruments during ascent. We present the flight characteristics of these two ballooning techniques and compare the quality of temperature and humidity measurements made during ascent and descent.

The African Diaspora: Using the Multivalent Theory to Understand Slave Autobiographies

ERIC Educational Resources Information Center

Morehouse, Maggi M.

2007-01-01

In simple terms, diaspora can be defined as the identity community that is formed when people move. Although the term African Diaspora seems relatively new, a number of 20th century scholars have utilized a diasporic framework to explain the commonalities among people of African descent around the world. The earliest scholars did not use the term;…

Analyzing the Rate at Which Languages Lose the Influence of a Common Ancestor

ERIC Educational Resources Information Center

Rafferty, Anna N.; Griffiths, Thomas L.; Klein, Dan

2014-01-01

Analyzing the rate at which languages change can clarify whether similarities across languages are solely the result of cognitive biases or might be partially due to descent from a common ancestor. To demonstrate this approach, we use a simple model of language evolution to mathematically determine how long it should take for the distribution over…

Expressions of the fundamental equation of gradient elution and a numerical solution of these equations under any gradient profile.

PubMed

Nikitas, P; Pappa-Louisi, A

2005-09-01

The original work carried out by Freiling and Drake in gradient liquid chromatography is rewritten in the current language of reversed-phase liquid chromatography. This allows for the rigorous derivation of the fundamental equation for gradient elution and the development of two alternative expressions of this equation, one of which is free from the constraint that the holdup time must be constant. In addition, the above derivation results in a very simple numerical solution of the various equations of gradient elution under any gradient profile. The theory was tested using eight catechol-related solutes in mobile phases modified with methanol, acetonitrile, or 2-propanol. It was found to be a satisfactory prediction of solute gradient retention behavior even if we used a simple linear description for the isocratic elution of these solutes.

Intelligence system based classification approach for medical disease diagnosis

NASA Astrophysics Data System (ADS)

Sagir, Abdu Masanawa; Sathasivam, Saratha

2017-08-01

The prediction of breast cancer in women who have no signs or symptoms of the disease as well as survivability after undergone certain surgery has been a challenging problem for medical researchers. The decision about presence or absence of diseases depends on the physician's intuition, experience and skill for comparing current indicators with previous one than on knowledge rich data hidden in a database. This measure is a very crucial and challenging task. The goal is to predict patient condition by using an adaptive neuro fuzzy inference system (ANFIS) pre-processed by grid partitioning. To achieve an accurate diagnosis at this complex stage of symptom analysis, the physician may need efficient diagnosis system. A framework describes methodology for designing and evaluation of classification performances of two discrete ANFIS systems of hybrid learning algorithms least square estimates with Modified Levenberg-Marquardt and Gradient descent algorithms that can be used by physicians to accelerate diagnosis process. The proposed method's performance was evaluated based on training and test datasets with mammographic mass and Haberman's survival Datasets obtained from benchmarked datasets of University of California at Irvine's (UCI) machine learning repository. The robustness of the performance measuring total accuracy, sensitivity and specificity is examined. In comparison, the proposed method achieves superior performance when compared to conventional ANFIS based gradient descent algorithm and some related existing methods. The software used for the implementation is MATLAB R2014a (version 8.3) and executed in PC Intel Pentium IV E7400 processor with 2.80 GHz speed and 2.0 GB of RAM.

Split Bregman multicoil accelerated reconstruction technique: A new framework for rapid reconstruction of cardiac perfusion MRI

PubMed Central

Kamesh Iyer, Srikant; Tasdizen, Tolga; Likhite, Devavrat; DiBella, Edward

2016-01-01

Purpose: Rapid reconstruction of undersampled multicoil MRI data with iterative constrained reconstruction method is a challenge. The authors sought to develop a new substitution based variable splitting algorithm for faster reconstruction of multicoil cardiac perfusion MRI data. Methods: The new method, split Bregman multicoil accelerated reconstruction technique (SMART), uses a combination of split Bregman based variable splitting and iterative reweighting techniques to achieve fast convergence. Total variation constraints are used along the spatial and temporal dimensions. The method is tested on nine ECG-gated dog perfusion datasets, acquired with a 30-ray golden ratio radial sampling pattern and ten ungated human perfusion datasets, acquired with a 24-ray golden ratio radial sampling pattern. Image quality and reconstruction speed are evaluated and compared to a gradient descent (GD) implementation and to multicoil k-t SLR, a reconstruction technique that uses a combination of sparsity and low rank constraints. Results: Comparisons based on blur metric and visual inspection showed that SMART images had lower blur and better texture as compared to the GD implementation. On average, the GD based images had an ∼18% higher blur metric as compared to SMART images. Reconstruction of dynamic contrast enhanced (DCE) cardiac perfusion images using the SMART method was ∼6 times faster than standard gradient descent methods. k-t SLR and SMART produced images with comparable image quality, though SMART was ∼6.8 times faster than k-t SLR. Conclusions: The SMART method is a promising approach to reconstruct good quality multicoil images from undersampled DCE cardiac perfusion data rapidly. PMID:27036592

Development of gradient descent adaptive algorithms to remove common mode artifact for improvement of cardiovascular signal quality.

PubMed

Ciaccio, Edward J; Micheli-Tzanakou, Evangelia

2007-07-01

Common-mode noise degrades cardiovascular signal quality and diminishes measurement accuracy. Filtering to remove noise components in the frequency domain often distorts the signal. Two adaptive noise canceling (ANC) algorithms were tested to adjust weighted reference signals for optimal subtraction from a primary signal. Update of weight w was based upon the gradient term of the steepest descent equation: [see text], where the error epsilon is the difference between primary and weighted reference signals. nabla was estimated from Deltaepsilon(2) and Deltaw without using a variable Deltaw in the denominator which can cause instability. The Parallel Comparison (PC) algorithm computed Deltaepsilon(2) using fixed finite differences +/- Deltaw in parallel during each discrete time k. The ALOPEX algorithm computed Deltaepsilon(2)x Deltaw from time k to k + 1 to estimate nabla, with a random number added to account for Deltaepsilon(2) . Deltaw--> 0 near the optimal weighting. Using simulated data, both algorithms stably converged to the optimal weighting within 50-2000 discrete sample points k even with a SNR = 1:8 and weights which were initialized far from the optimal. Using a sharply pulsatile cardiac electrogram signal with added noise so that the SNR = 1:5, both algorithms exhibited stable convergence within 100 ms (100 sample points). Fourier spectral analysis revealed minimal distortion when comparing the signal without added noise to the ANC restored signal. ANC algorithms based upon difference calculations can rapidly and stably converge to the optimal weighting in simulated and real cardiovascular data. Signal quality is restored with minimal distortion, increasing the accuracy of biophysical measurement.

Evaluating the accuracy performance of Lucas-Kanade algorithm in the circumstance of PIV application

NASA Astrophysics Data System (ADS)

Pan, Chong; Xue, Dong; Xu, Yang; Wang, JinJun; Wei, RunJie

2015-10-01

Lucas-Kanade (LK) algorithm, usually used in optical flow filed, has recently received increasing attention from PIV community due to its advanced calculation efficiency by GPU acceleration. Although applications of this algorithm are continuously emerging, a systematic performance evaluation is still lacking. This forms the primary aim of the present work. Three warping schemes in the family of LK algorithm: forward/inverse/symmetric warping, are evaluated in a prototype flow of a hierarchy of multiple two-dimensional vortices. Second-order Newton descent is also considered here. The accuracy & efficiency of all these LK variants are investigated under a large domain of various influential parameters. It is found that the constant displacement constraint, which is a necessary building block for GPU acceleration, is the most critical issue in affecting LK algorithm's accuracy, which can be somehow ameliorated by using second-order Newton descent. Moreover, symmetric warping outbids the other two warping schemes in accuracy level, robustness to noise, convergence speed and tolerance to displacement gradient, and might be the first choice when applying LK algorithm to PIV measurement.

Geodesic regression on orientation distribution functions with its application to an aging study.

PubMed

Du, Jia; Goh, Alvina; Kushnarev, Sergey; Qiu, Anqi

2014-02-15

In this paper, we treat orientation distribution functions (ODFs) derived from high angular resolution diffusion imaging (HARDI) as elements of a Riemannian manifold and present a method for geodesic regression on this manifold. In order to find the optimal regression model, we pose this as a least-squares problem involving the sum-of-squared geodesic distances between observed ODFs and their model fitted data. We derive the appropriate gradient terms and employ gradient descent to find the minimizer of this least-squares optimization problem. In addition, we show how to perform statistical testing for determining the significance of the relationship between the manifold-valued regressors and the real-valued regressands. Experiments on both synthetic and real human data are presented. In particular, we examine aging effects on HARDI via geodesic regression of ODFs in normal adults aged 22 years old and above. © 2013 Elsevier Inc. All rights reserved.

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

PubMed Central

Gregor, Jens; Fessler, Jeffrey A.

2015-01-01

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

Simple Microfluidic Device For Studying Chemotaxis In Response To Dual Gradients

PubMed Central

Moussavi-Haramic, S. F.; Pezzi, H. M.; Huttenlocher, A.; Beebe, D. J.

2016-01-01

Chemotaxis is a fundamental biological process where complex chemotactic gradients are integrated and prioritized to guide cell migration toward specific locations. To understand the mechanisms of gradient dependent cell migration, it is important to develop in vitro models that recapitulate key attributes of the chemotactic cues present in vivo. Current in vitro tools for studying cell migration are not amenable to easily study the response of neutrophils to dual gradients. Many of these systems require external pumps and complex setups to establish and maintain the gradients. Here we report a simple yet innovative microfluidic device for studying cell migration in the presence of dual chemotactic gradients through a 3-dimensional substrate. The device is tested and validated by studying the migration of the neutrophil-like cell line PLB-985 to gradients of fMLP. Furthermore, the device is expanded and used with heparinised whole blood, whereupon neutrophils were observed to migrate from whole blood towards gradients of fMLP eliminating the need for any neutrophil purification or capture steps. PMID:25893484

Stream-profile analysis and stream-gradient index

USGS Publications Warehouse

Hack, John T.

1973-01-01

The generally regular three-dimensional geometry of drainage networks is the basis for a simple method of terrain analysis providing clues to bedrock conditions and other factors that determine topographic forms. On a reach of any stream, a gradient-index value can be obtained which allows meaningful comparisons of channel slope on streams of different sizes. The index is believed to reflect stream power or competence and is simply the product of the channel slope at a point and channel length measured along the longest stream above the pointwhere the calculation is made. In an adjusted topography, changes in gradient-index values along a stream generally correspond to differences in bedrock or introduced load. In any landscape the gradient index of a stream is related to total relief and stream regimen. Thus, climate, tectonic events, and geomorphic history must be considered in using the gradient index. Gradient-index values can be obtained quickly by simple measurements on topographic maps, or they can be obtained by more sophisticated photogrammetric measurements that involve simple computer calculations from x, y, z coordinates.

New recursive-least-squares algorithms for nonlinear active control of sound and vibration using neural networks.

PubMed

Bouchard, M

2001-01-01

In recent years, a few articles describing the use of neural networks for nonlinear active control of sound and vibration were published. Using a control structure with two multilayer feedforward neural networks (one as a nonlinear controller and one as a nonlinear plant model), steepest descent algorithms based on two distinct gradient approaches were introduced for the training of the controller network. The two gradient approaches were sometimes called the filtered-x approach and the adjoint approach. Some recursive-least-squares algorithms were also introduced, using the adjoint approach. In this paper, an heuristic procedure is introduced for the development of recursive-least-squares algorithms based on the filtered-x and the adjoint gradient approaches. This leads to the development of new recursive-least-squares algorithms for the training of the controller neural network in the two networks structure. These new algorithms produce a better convergence performance than previously published algorithms. Differences in the performance of algorithms using the filtered-x and the adjoint gradient approaches are discussed in the paper. The computational load of the algorithms discussed in the paper is evaluated for multichannel systems of nonlinear active control. Simulation results are presented to compare the convergence performance of the algorithms, showing the convergence gain provided by the new algorithms.

Kurtosis Approach for Nonlinear Blind Source Separation

NASA Technical Reports Server (NTRS)

Duong, Vu A.; Stubbemd, Allen R.

2005-01-01

In this paper, we introduce a new algorithm for blind source signal separation for post-nonlinear mixtures. The mixtures are assumed to be linearly mixed from unknown sources first and then distorted by memoryless nonlinear functions. The nonlinear functions are assumed to be smooth and can be approximated by polynomials. Both the coefficients of the unknown mixing matrix and the coefficients of the approximated polynomials are estimated by the gradient descent method conditional on the higher order statistical requirements. The results of simulation experiments presented in this paper demonstrate the validity and usefulness of our approach for nonlinear blind source signal separation.

On Vehicle Placement to Intercept Moving Targets (Preprint)

DTIC Science & Technology

2010-03-09

which is feasible only if X1 −X2 = 0 and Y1 − Y2 = 0. We now present the main result for this section. Theorem 3.4 (Minimizing expected cost) From an...Vandenberghe (2004)) leads the vehicle to the unique global minimizer of Cexp. Let V ⊂ [0,W ], and choose φ(x) such that φ(x) = 0,∀x ∈ [0,W ] \\ V. Then, Theorem ...R>0, and following gradient descent with V as the region of integration, the vehicle remains inside [0,W ] × R>0 at all subsequent times. 3 Theorem

Product Distribution Theory and Semi-Coordinate Transformations

NASA Technical Reports Server (NTRS)

Airiau, Stephane; Wolpert, David H.

2004-01-01

Product Distribution (PD) theory is a new framework for doing distributed adaptive control of a multiagent system (MAS). We introduce the technique of "coordinate transformations" in PD theory gradient descent. These transformations selectively couple a few agents with each other into "meta-agents". Intuitively, this can be viewed as a generalization of forming binding contracts between those agents. Doing this sacrifices a bit of the distributed nature of the MAS, in that there must now be communication from multiple agents in determining what joint-move is finally implemented However, as we demonstrate in computer experiments, these transformations improve the performance of the MAS.

Deep kernel learning method for SAR image target recognition

NASA Astrophysics Data System (ADS)

Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao

2017-10-01

With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.

Derivative Free Gradient Projection Algorithms for Rotation

ERIC Educational Resources Information Center

Jennrich, Robert I.

2004-01-01

A simple modification substantially simplifies the use of the gradient projection (GP) rotation algorithms of Jennrich (2001, 2002). These algorithms require subroutines to compute the value and gradient of any specific rotation criterion of interest. The gradient can be difficult to derive and program. It is shown that using numerical gradients…

Gradient flows without blow-up for Lefschetz thimbles

DOE PAGES

Tanizaki, Yuya; Nishimura, Hiromichi; Verbaarschot, Jacobus J. M.

2017-10-16

We propose new gradient flows that define Lefschetz thimbles and do not blow up in a finite flow time. Here, we study analytic properties of these gradient flows, and confirm them by numerical tests in simple examples.

Optimization for high-dose-rate brachytherapy of cervical cancer with adaptive simulated annealing and gradient descent.

PubMed

Yao, Rui; Templeton, Alistair K; Liao, Yixiang; Turian, Julius V; Kiel, Krystyna D; Chu, James C H

2014-01-01

To validate an in-house optimization program that uses adaptive simulated annealing (ASA) and gradient descent (GD) algorithms and investigate features of physical dose and generalized equivalent uniform dose (gEUD)-based objective functions in high-dose-rate (HDR) brachytherapy for cervical cancer. Eight Syed/Neblett template-based cervical cancer HDR interstitial brachytherapy cases were used for this study. Brachytherapy treatment plans were first generated using inverse planning simulated annealing (IPSA). Using the same dwell positions designated in IPSA, plans were then optimized with both physical dose and gEUD-based objective functions, using both ASA and GD algorithms. Comparisons were made between plans both qualitatively and based on dose-volume parameters, evaluating each optimization method and objective function. A hybrid objective function was also designed and implemented in the in-house program. The ASA plans are higher on bladder V75% and D2cc (p=0.034) and lower on rectum V75% and D2cc (p=0.034) than the IPSA plans. The ASA and GD plans are not significantly different. The gEUD-based plans have higher homogeneity index (p=0.034), lower overdose index (p=0.005), and lower rectum gEUD and normal tissue complication probability (p=0.005) than the physical dose-based plans. The hybrid function can produce a plan with dosimetric parameters between the physical dose-based and gEUD-based plans. The optimized plans with the same objective value and dose-volume histogram could have different dose distributions. Our optimization program based on ASA and GD algorithms is flexible on objective functions, optimization parameters, and can generate optimized plans comparable with IPSA. Copyright © 2014 American Brachytherapy Society. Published by Elsevier Inc. All rights reserved.

A ℓ2, 1 norm regularized multi-kernel learning for false positive reduction in Lung nodule CAD.

PubMed

Cao, Peng; Liu, Xiaoli; Zhang, Jian; Li, Wei; Zhao, Dazhe; Huang, Min; Zaiane, Osmar

2017-03-01

The aim of this paper is to describe a novel algorithm for False Positive Reduction in lung nodule Computer Aided Detection(CAD). In this paper, we describes a new CT lung CAD method which aims to detect solid nodules. Specially, we proposed a multi-kernel classifier with a ℓ 2, 1 norm regularizer for heterogeneous feature fusion and selection from the feature subset level, and designed two efficient strategies to optimize the parameters of kernel weights in non-smooth ℓ 2, 1 regularized multiple kernel learning algorithm. The first optimization algorithm adapts a proximal gradient method for solving the ℓ 2, 1 norm of kernel weights, and use an accelerated method based on FISTA; the second one employs an iterative scheme based on an approximate gradient descent method. The results demonstrates that the FISTA-style accelerated proximal descent method is efficient for the ℓ 2, 1 norm formulation of multiple kernel learning with the theoretical guarantee of the convergence rate. Moreover, the experimental results demonstrate the effectiveness of the proposed methods in terms of Geometric mean (G-mean) and Area under the ROC curve (AUC), and significantly outperforms the competing methods. The proposed approach exhibits some remarkable advantages both in heterogeneous feature subsets fusion and classification phases. Compared with the fusion strategies of feature-level and decision level, the proposed ℓ 2, 1 norm multi-kernel learning algorithm is able to accurately fuse the complementary and heterogeneous feature sets, and automatically prune the irrelevant and redundant feature subsets to form a more discriminative feature set, leading a promising classification performance. Moreover, the proposed algorithm consistently outperforms the comparable classification approaches in the literature. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The Amount and Preferred Orientation of Simple-shear in a Deformation Tensor: Implications for Detecting Shear Zones and Faults with GPS

NASA Astrophysics Data System (ADS)

Johnson, A. M.; Griffiths, J. H.

2007-05-01

At the 2005 Fall Meeting of the American Geophysical Union, Griffiths and Johnson [2005] introduced a method of extracting from the deformation-gradient (and velocity-gradient) tensor the amount and preferred orientation of simple-shear associated with 2-D shear zones and faults. Noting the 2-D is important because the shear zones and faults in Griffiths and Johnson [2005] were assumed non-dilatant and infinitely long, ignoring the scissors- like action along strike associated with shear zones and faults of finite length. Because shear zones and faults can dilate (and contract) normal to their walls and can have a scissors-like action associated with twisting about an axis normal to their walls, the more general method of detecting simple-shear is introduced and called MODES "method of detecting simple-shear." MODES can thus extract from the deformation-gradient (and velocity- gradient) tensor the amount and preferred orientation of simple-shear associated with 3-D shear zones and faults near or far from the Earth's surface, providing improvements and extensions to existing analytical methods used in active tectonics studies, especially strain analysis and dislocation theory. The derivation of MODES is based on one definition and two assumptions: by definition, simple-shear deformation becomes localized in some way; by assumption, the twirl within the deformation-gradient (or the spin within the velocity-gradient) is due to a combination of simple-shear and twist, and coupled with the simple- shear and twist is a dilatation of the walls of shear zones and faults. The preferred orientation is thus the orientation of the plane containing the simple-shear and satisfying the mechanical and kinematical boundary conditions. Results from a MODES analysis are illustrated by means of a three-dimensional diagram, the cricket- ball, which is reminiscent of the seismologist's "beach ball." In this poster, we present the underlying theory of MODES and illustrate how it works by analyzing the three- dimensional displacements measured with the Global Positioning System across the 1999 Chi-Chi earthquake ground rupture in Taiwan. In contrast to the deformation zone in the upper several meters of the ground below the surface detected by Yu et al. [2001], MODES determines the orientation and direction of shift of a shear zone representing the earthquake fault within the upper several hundred or thousand meters of ground below the surface. Thus, one value of the MODES analysis in this case is to provide boundary conditions for dislocation solutions for the subsurface shape of the main rupture during the earthquake.

Pixel-By Estimation of Scene Motion in Video

NASA Astrophysics Data System (ADS)

Tashlinskii, A. G.; Smirnov, P. V.; Tsaryov, M. G.

2017-05-01

The paper considers the effectiveness of motion estimation in video using pixel-by-pixel recurrent algorithms. The algorithms use stochastic gradient decent to find inter-frame shifts of all pixels of a frame. These vectors form shift vectors' field. As estimated parameters of the vectors the paper studies their projections and polar parameters. It considers two methods for estimating shift vectors' field. The first method uses stochastic gradient descent algorithm to sequentially process all nodes of the image row-by-row. It processes each row bidirectionally i.e. from the left to the right and from the right to the left. Subsequent joint processing of the results allows compensating inertia of the recursive estimation. The second method uses correlation between rows to increase processing efficiency. It processes rows one after the other with the change in direction after each row and uses obtained values to form resulting estimate. The paper studies two criteria of its formation: gradient estimation minimum and correlation coefficient maximum. The paper gives examples of experimental results of pixel-by-pixel estimation for a video with a moving object and estimation of a moving object trajectory using shift vectors' field.

Mirror gait retraining for the treatment of patellofemoral pain in female runners

PubMed Central

Willy, Richard W.; Scholz, John P.; Davis, Irene S.

2012-01-01

Background Abnormal hip mechanics are often implicated in female runners with patellofemoral pain. We sought to evaluate a simple gait retraining technique, using a full-length mirror, in female runners with patellofemoral pain and abnormal hip mechanics. Transfer of the new motor skill to the untrained tasks of single leg squat and step descent was also evaluated. Methods Ten female runners with patellofemoral pain completed 8 sessions of mirror and verbal feedback on their lower extremity alignment during treadmill running. During the last 4 sessions, mirror and verbal feedback were progressively removed. Hip mechanics were assessed during running gait, a single leg squat and a step descent, both pre- and post-retraining. Subjects returned to their normal running routines and analyses were repeated at 1-month and 3-month post-retraining. Data were analyzed via repeated measures analysis of variance. Findings Subjects reduced peaks of hip adduction, contralateral pelvic drop, and hip abduction moment during running (P<0.05, effect size=0.69–2.91). Skill transfer to single leg squatting and step descent was noted (P<0.05, effect size=0.91–1.35). At 1 and 3 months post retraining, most mechanics were maintained in the absence of continued feedback. Subjects reported improvements in pain and function (P<0.05, effect size=3.81–7.61) and maintained through 3 months post retraining. Interpretation Mirror gait retraining was effective in improving mechanics and measures of pain and function. Skill transfer to the untrained tasks of squatting and step descent indicated that a higher level of motor learning had occurred. Extended follow-up is needed to determine the long term efficacy of this treatment. PMID:22917625

An Experiment Using Sucrose Density Gradients in the Undergraduate Biochemistry Laboratory.

ERIC Educational Resources Information Center

Turchi, Sandra L.; Weiss, Monica

1988-01-01

Describes an experiment to be performed in an undergraduate biochemistry laboratory that is based on a gradient centrifugation system employing a simple bench top centrifuge, a freezer, and frozen surcose gradient solution to separate macromolecules and subcellular components. (CW)

High-resolution Anorectal Manometry for Identifying Defecatory Disorders and Rectal Structural Abnormalities in Women.

PubMed

Prichard, David O; Lee, Taehee; Parthasarathy, Gopanandan; Fletcher, Joel G; Zinsmeister, Alan R; Bharucha, Adil E

2017-03-01

Contrary to conventional wisdom, the rectoanal gradient during evacuation is negative in many healthy people, undermining the utility of anorectal high-resolution manometry (HRM) for diagnosing defecatory disorders. We aimed to compare HRM and magnetic resonance imaging (MRI) for assessing rectal evacuation and structural abnormalities. We performed a retrospective analysis of 118 patients (all female; 51 with constipation, 48 with fecal incontinence, and 19 with rectal prolapse; age, 53 ± 1 years) assessed by HRM, the rectal balloon expulsion test (BET), and MRI at Mayo Clinic, Rochester, Minnesota, from February 2011 through March 2013. Thirty healthy asymptomatic women (age, 37 ± 2 years) served as controls. We used principal components analysis of HRM variables to identify rectoanal pressure patterns associated with rectal prolapse and phenotypes of patients with prolapse. Compared with patients with normal findings from the rectal BET, patients with an abnormal BET had lower median rectal pressure (36 vs 22 mm Hg, P = .002), a more negative median rectoanal gradient (-6 vs -29 mm Hg, P = .006) during evacuation, and a lower proportion of evacuation on the basis of MRI analysis (median of 40% vs 80%, P < .0001). A score derived from rectal pressure and anorectal descent during evacuation and a patulous anal canal was associated (P = .005) with large rectoceles (3 cm or larger). A principal component (PC) logistic model discriminated between patients with and without prolapse with 96% accuracy. Among patients with prolapse, there were 2 phenotypes, which were characterized by high (PC1) or low (PC2) anal pressures at rest and squeeze along with higher rectal and anal pressures (PC1) or a higher rectoanal gradient during evacuation (PC2). In a retrospective analysis of patients assessed by HRM, measurements of rectal evacuation by anorectal HRM, BET, and MRI were correlated. HRM alone and together with anorectal descent during evacuation may identify rectal prolapse and large rectoceles, respectively, and also identify unique phenotypes of rectal prolapse. Copyright © 2017 AGA Institute. Published by Elsevier Inc. All rights reserved.

Direct Temperature Measurements during Netlander Descent on Mars

NASA Astrophysics Data System (ADS)

Colombatti, G.; Angrilli, F.; Ferri, F.; Francesconi, A.; Fulchignoni, M.; Lion Stoppato, P. F.; Saggi, B.

1999-09-01

A new design for a platinum thermoresistance temperature sensor has been developed and tested in Earth's atmosphere and stratosphere. It will be one of the sensors equipping the scientific package ATMIS (Atmospheric and Meteorology Instrument System), which will be devoted to the measurement of the meteorological parameters during both the entry/descent phase and the surface phase, aboard the Netlanders. In particular vertical profiles of temperature, density and pressure will allow the resolution of vertical gradients to investigate the atmospheric structure and dynamics. In view of the future missions to Mars, Netlander represents a unique chance to increase significantly the climate record both in time and in space, doubling the current knowledge of the atmospheric parameters. Furthermore is the only opportunity to conduct direct measurement of temperature and pressure (outside the boundary layer of the airbags used for the landing). The temperature sensor proposed is a platinum thermoresistance, enhancement of HASI TEM (Cassini/Huygens Mission); a substantial improvement of the performances, i.e. a faster dynamic response, has been obtained. Two different prototypes of new design sensor have been built, laboratory test are proceeding and the second one has been already flown aboard a stratospheric balloon.

A novel technique for real-time estimation of edge pedestal density gradients via reflectometer time delay data

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

Zeng, L., E-mail: zeng@fusion.gat.com; Doyle, E. J.; Rhodes, T. L.

2016-11-15

A new model-based technique for fast estimation of the pedestal electron density gradient has been developed. The technique uses ordinary mode polarization profile reflectometer time delay data and does not require direct profile inversion. Because of its simple data processing, the technique can be readily implemented via a Field-Programmable Gate Array, so as to provide a real-time density gradient estimate, suitable for use in plasma control systems such as envisioned for ITER, and possibly for DIII-D and Experimental Advanced Superconducting Tokamak. The method is based on a simple edge plasma model with a linear pedestal density gradient and low scrape-off-layermore » density. By measuring reflectometer time delays for three adjacent frequencies, the pedestal density gradient can be estimated analytically via the new approach. Using existing DIII-D profile reflectometer data, the estimated density gradients obtained from the new technique are found to be in good agreement with the actual density gradients for a number of dynamic DIII-D plasma conditions.« less

Northern Hemisphere Nitrous Oxide Morphology during the 1989 AASE and the 1991-1992 AASE 2 Campaigns

NASA Technical Reports Server (NTRS)

Podolske, James R.; Loewenstein, Max; Weaver, Alex; Strahan, Susan; Chan, K. Roland

1993-01-01

Nitrous oxide vertical profiles and latitudinal distributions for the 1989 AASE and 1992 AASE II northern polar winters are developed from the ATLAS N2O dataset, using both potential temperature and pressure as vertical coordinates. Morphologies show strong descent occurring poleward of the polar jet. The AASE II morphology shows a mid latitude 'surf zone,' characterized by strong horizontal mixing, and a horizontal gradient south of 30 deg N due to the sub-tropical jet. These features are similar to those produced by two-dimensional photochemical models which include coupling between transport, radiation, and chemistry.

Northern hemisphere nitrous oxide morphology during the 1989 AASE and the 1991-1992 AASE 2 campaigns

NASA Technical Reports Server (NTRS)

Podolske, James R.; Loewenstein, Max; Weaver, Alex; Strahan, Susan E.; Chan, K. Roland

1993-01-01

Nitrous oxide vertical profiles and latitudinal distributions for the 1989 Airborne Antarctic Ozone Experiment (AASE) and 1992 AASE 2 northern polar winters are developed from the ATLAS N2O dataset, using both potential temperature and pressure as vertical coordinates. Morphologies show strong descent occuring poleward of the polar jet. The AASE 2 morphology shows a mid latitude 'surf zone', characterized by strong horizontal mixing, and a horizontal gradient south of 30 deg N due to the sub-tropical jet. These features are similar to those produced by two-dimensional photochemical models which include coupling between transport, radiation, and chemistry.

Output Feedback Stabilization for a Class of Multi-Variable Bilinear Stochastic Systems with Stochastic Coupling Attenuation

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

Zhang, Qichun; Zhou, Jinglin; Wang, Hong

In this paper, stochastic coupling attenuation is investigated for a class of multi-variable bilinear stochastic systems and a novel output feedback m-block backstepping controller with linear estimator is designed, where gradient descent optimization is used to tune the design parameters of the controller. It has been shown that the trajectories of the closed-loop stochastic systems are bounded in probability sense and the stochastic coupling of the system outputs can be effectively attenuated by the proposed control algorithm. Moreover, the stability of the stochastic systems is analyzed and the effectiveness of the proposed method has been demonstrated using a simulated example.

A Gradient Taguchi Method for Engineering Optimization

NASA Astrophysics Data System (ADS)

Hwang, Shun-Fa; Wu, Jen-Chih; He, Rong-Song

2017-10-01

To balance the robustness and the convergence speed of optimization, a novel hybrid algorithm consisting of Taguchi method and the steepest descent method is proposed in this work. Taguchi method using orthogonal arrays could quickly find the optimum combination of the levels of various factors, even when the number of level and/or factor is quite large. This algorithm is applied to the inverse determination of elastic constants of three composite plates by combining numerical method and vibration testing. For these problems, the proposed algorithm could find better elastic constants in less computation cost. Therefore, the proposed algorithm has nice robustness and fast convergence speed as compared to some hybrid genetic algorithms.

Kurtosis Approach Nonlinear Blind Source Separation

NASA Technical Reports Server (NTRS)

Duong, Vu A.; Stubbemd, Allen R.

2005-01-01

In this paper, we introduce a new algorithm for blind source signal separation for post-nonlinear mixtures. The mixtures are assumed to be linearly mixed from unknown sources first and then distorted by memoryless nonlinear functions. The nonlinear functions are assumed to be smooth and can be approximated by polynomials. Both the coefficients of the unknown mixing matrix and the coefficients of the approximated polynomials are estimated by the gradient descent method conditional on the higher order statistical requirements. The results of simulation experiments presented in this paper demonstrate the validity and usefulness of our approach for nonlinear blind source signal separation Keywords: Independent Component Analysis, Kurtosis, Higher order statistics.

Atmospheric tides on Venus. III - The planetary boundary layer

NASA Technical Reports Server (NTRS)

Dobrovolskis, A. R.

1983-01-01

Diurnal solar heating of Venus' surface produces variable temperatures, winds, and pressure gradients within a shallow layer at the bottom of the atmosphere. The corresponding asymmetric mass distribution experiences a tidal torque tending to maintain Venus' slow retrograde rotation. It is shown that including viscosity in the boundary layer does not materially affect the balance of torques. On the other hand, friction between the air and ground can reduce the predicted wind speeds from about 5 to about 1 m/sec in the lower atmosphere, more consistent with the observations from Venus landers and descent probes. Implications for aeolian activity on Venus' surface and for future missions are discussed.

Enhancement of the beam quality of non-uniform output slab laser amplifier with a 39-actuator rectangular piezoelectric deformable mirror.

PubMed

Yang, Ping; Ning, Yu; Lei, Xiang; Xu, Bing; Li, Xinyang; Dong, Lizhi; Yan, Hu; Liu, Wenjing; Jiang, Wenhan; Liu, Lei; Wang, Chao; Liang, Xingbo; Tang, Xiaojun

2010-03-29

We present a slab laser amplifier beam cleanup experimental system based on a 39-actuator rectangular piezoelectric deformable mirror. Rather than use a wave-front sensor to measure distortions in the wave-front and then apply a conjugation wave-front for compensating them, the system uses a Stochastic Parallel Gradient Descent algorithm to maximize the power contained within a far-field designated bucket. Experimental results demonstrate that at the output power of 335W, more than 30% energy concentrates in the 1x diffraction-limited area while the beam quality is enhanced greatly.

An image morphing technique based on optimal mass preserving mapping.

PubMed

Zhu, Lei; Yang, Yan; Haker, Steven; Tannenbaum, Allen

2007-06-01

Image morphing, or image interpolation in the time domain, deals with the metamorphosis of one image into another. In this paper, a new class of image morphing algorithms is proposed based on the theory of optimal mass transport. The L(2) mass moving energy functional is modified by adding an intensity penalizing term, in order to reduce the undesired double exposure effect. It is an intensity-based approach and, thus, is parameter free. The optimal warping function is computed using an iterative gradient descent approach. This proposed morphing method is also extended to doubly connected domains using a harmonic parameterization technique, along with finite-element methods.

An Image Morphing Technique Based on Optimal Mass Preserving Mapping

PubMed Central

Zhu, Lei; Yang, Yan; Haker, Steven; Tannenbaum, Allen

2013-01-01

Image morphing, or image interpolation in the time domain, deals with the metamorphosis of one image into another. In this paper, a new class of image morphing algorithms is proposed based on the theory of optimal mass transport. The L2 mass moving energy functional is modified by adding an intensity penalizing term, in order to reduce the undesired double exposure effect. It is an intensity-based approach and, thus, is parameter free. The optimal warping function is computed using an iterative gradient descent approach. This proposed morphing method is also extended to doubly connected domains using a harmonic parameterization technique, along with finite-element methods. PMID:17547128

Quantum generalisation of feedforward neural networks

NASA Astrophysics Data System (ADS)

Wan, Kwok Ho; Dahlsten, Oscar; Kristjánsson, Hlér; Gardner, Robert; Kim, M. S.

2017-09-01

We propose a quantum generalisation of a classical neural network. The classical neurons are firstly rendered reversible by adding ancillary bits. Then they are generalised to being quantum reversible, i.e., unitary (the classical networks we generalise are called feedforward, and have step-function activation functions). The quantum network can be trained efficiently using gradient descent on a cost function to perform quantum generalisations of classical tasks. We demonstrate numerically that it can: (i) compress quantum states onto a minimal number of qubits, creating a quantum autoencoder, and (ii) discover quantum communication protocols such as teleportation. Our general recipe is theoretical and implementation-independent. The quantum neuron module can naturally be implemented photonically.

Genetic algorithm and graph theory based matrix factorization method for online friend recommendation.

PubMed

Li, Qu; Yao, Min; Yang, Jianhua; Xu, Ning

2014-01-01

Online friend recommendation is a fast developing topic in web mining. In this paper, we used SVD matrix factorization to model user and item feature vector and used stochastic gradient descent to amend parameter and improve accuracy. To tackle cold start problem and data sparsity, we used KNN model to influence user feature vector. At the same time, we used graph theory to partition communities with fairly low time and space complexity. What is more, matrix factorization can combine online and offline recommendation. Experiments showed that the hybrid recommendation algorithm is able to recommend online friends with good accuracy.

Railway obstacle detection algorithm using neural network

NASA Astrophysics Data System (ADS)

Yu, Mingyang; Yang, Peng; Wei, Sen

2018-05-01

Aiming at the difficulty of detection of obstacle in outdoor railway scene, a data-oriented method based on neural network to obtain image objects is proposed. First, we mark objects of images(such as people, trains, animals) acquired on the Internet. and then use the residual learning units to build Fast R-CNN framework. Then, the neural network is trained to get the target image characteristics by using stochastic gradient descent algorithm. Finally, a well-trained model is used to identify an outdoor railway image. if it includes trains and other objects, it will issue an alert. Experiments show that the correct rate of warning reached 94.85%.

A hybrid Gerchberg-Saxton-like algorithm for DOE and CGH calculation

NASA Astrophysics Data System (ADS)

Wang, Haichao; Yue, Weirui; Song, Qiang; Liu, Jingdan; Situ, Guohai

2017-02-01

The Gerchberg-Saxton (GS) algorithm is widely used in various disciplines of modern sciences and technologies where phase retrieval is required. However, this legendary algorithm most likely stagnates after a few iterations. Many efforts have been taken to improve this situation. Here we propose to introduce the strategy of gradient descent and weighting technique to the GS algorithm, and demonstrate it using two examples: design of a diffractive optical element (DOE) to achieve off-axis illumination in lithographic tools, and design of a computer generated hologram (CGH) for holographic display. Both numerical simulation and optical experiments are carried out for demonstration.

Convergence of fractional adaptive systems using gradient approach.

PubMed

Gallegos, Javier A; Duarte-Mermoud, Manuel A

2017-07-01

Conditions for boundedness and convergence of the output error and the parameter error for various Caputo's fractional order adaptive schemes based on the steepest descent method are derived in this paper. To this aim, the concept of sufficiently exciting signals is introduced, characterized and related to the concept of persistently exciting signals used in the integer order case. An application is designed in adaptive indirect control of integer order systems using fractional equations to adjust parameters. This application is illustrated for a pole placement adaptive problem. Advantages of using fractional adjustment in control adaptive schemes are experimentally obtained. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

NASA Technical Reports Server (NTRS)

Arian, Eyal; Taasan, Shlomo

1994-01-01

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

Measurement of lung expansion with computed tomography and comparison with quantitative histology.

PubMed

Coxson, H O; Mayo, J R; Behzad, H; Moore, B J; Verburgt, L M; Staples, C A; Paré, P D; Hogg, J C

1995-11-01

The total and regional lung volumes were estimated from computed tomography (CT), and the pleural pressure gradient was determined by using the milliliters of gas per gram of tissue estimated from the X-ray attenuation values and the pressure-volume curve of the lung. The data show that CT accurately estimated the volume of the resected lobe but overestimated its weight by 24 +/- 19%. The volume of gas per gram of tissue was less in the gravity-dependent regions due to a pleural pressure gradient of 0.24 +/- 0.08 cmH2O/cm of descent in the thorax. The proportion of tissue to air obtained with CT was similar to that obtained by quantitative histology. We conclude that the CT scan can be used to estimate total and regional lung volumes and that measurements of the proportions of tissue and air within the thorax by CT can be used in conjunction with quantitative histology to evaluate lung structure.

Predictability of Top of Descent Location for Operational Idle-Thrust Descents

NASA Technical Reports Server (NTRS)

Stell, Laurel L.

2010-01-01

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 uncertainty models, commercial flights executed idle-thrust descents at a specified descent speed, and the recorded data included the specified descent speed profile, aircraft weight, and the winds entered into the FMS as well as the radar data. The FMS computed the intended descent path assuming idle thrust after top of descent (TOD), and the controllers and pilots then endeavored to allow the FMS to fly the descent to the meter fix with minimal human intervention. The horizontal flight path, cruise and meter fix altitudes, and actual TOD location were extracted from the radar data. Using approximately 70 descents each in Boeing 757 and Airbus 319/320 aircraft, multiple regression estimated TOD location as a linear function of the available predictive factors. The cruise and meter fix altitudes, descent speed, and wind clearly improve goodness of fit. The aircraft weight improves fit for the Airbus descents but not for the B757. Except for a few statistical outliers, the residuals have absolute value less than 5 nmi. Thus, these predictive factors adequately explain the TOD location, which indicates the data do not include excessive noise.

An approach to multiobjective optimization of rotational therapy. II. Pareto optimal surfaces and linear combinations of modulated blocked arcs for a prostate geometry.

PubMed

Pardo-Montero, Juan; Fenwick, John D

2010-06-01

The purpose of this work is twofold: To further develop an approach to multiobjective optimization of rotational therapy treatments recently introduced by the authors [J. Pardo-Montero and J. D. Fenwick, "An approach to multiobjective optimization of rotational therapy," Med. Phys. 36, 3292-3303 (2009)], especially regarding its application to realistic geometries, and to study the quality (Pareto optimality) of plans obtained using such an approach by comparing them with Pareto optimal plans obtained through inverse planning. In the previous work of the authors, a methodology is proposed for constructing a large number of plans, with different compromises between the objectives involved, from a small number of geometrically based arcs, each arc prioritizing different objectives. Here, this method has been further developed and studied. Two different techniques for constructing these arcs are investigated, one based on image-reconstruction algorithms and the other based on more common gradient-descent algorithms. The difficulty of dealing with organs abutting the target, briefly reported in previous work of the authors, has been investigated using partial OAR unblocking. Optimality of the solutions has been investigated by comparison with a Pareto front obtained from inverse planning. A relative Euclidean distance has been used to measure the distance of these plans to the Pareto front, and dose volume histogram comparisons have been used to gauge the clinical impact of these distances. A prostate geometry has been used for the study. For geometries where a blocked OAR abuts the target, moderate OAR unblocking can substantially improve target dose distribution and minimize hot spots while not overly compromising dose sparing of the organ. Image-reconstruction type and gradient-descent blocked-arc computations generate similar results. The Pareto front for the prostate geometry, reconstructed using a large number of inverse plans, presents a hockey-stick shape comprising two regions: One where the dose to the target is close to prescription and trade-offs can be made between doses to the organs at risk and (small) changes in target dose, and one where very substantial rectal sparing is achieved at the cost of large target underdosage. Plans computed following the approach using a conformal arc and four blocked arcs generally lie close to the Pareto front, although distances of some plans from high gradient regions of the Pareto front can be greater. Only around 12% of plans lie a relative Euclidean distance of 0.15 or greater from the Pareto front. Using the alternative distance measure of Craft ["Calculating and controlling the error of discrete representations of Pareto surfaces in convex multi-criteria optimization," Phys. Medica (to be published)], around 2/5 of plans lie more than 0.05 from the front. Computation of blocked arcs is quite fast, the algorithms requiring 35%-80% of the running time per iteration needed for conventional inverse plan computation. The geometry-based arc approach to multicriteria optimization of rotational therapy allows solutions to be obtained that lie close to the Pareto front. Both the image-reconstruction type and gradient-descent algorithms produce similar modulated arcs, the latter one perhaps being preferred because it is more easily implementable in standard treatment planning systems. Moderate unblocking provides a good way of dealing with OARs which abut the PTV. Optimization of geometry-based arcs is faster than usual inverse optimization of treatment plans, making this approach more rapid than an inverse-based Pareto front reconstruction.

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

Tanizaki, Yuya; Nishimura, Hiromichi; Verbaarschot, Jacobus J. M.

We propose new gradient flows that define Lefschetz thimbles and do not blow up in a finite flow time. Here, we study analytic properties of these gradient flows, and confirm them by numerical tests in simple examples.

Operational implications of some NACA/NASA rotary wing induced velocity studies

NASA Technical Reports Server (NTRS)

Heyson, H. H.

1980-01-01

Wind tunnel measurements show that the wake of a rotor, except at near-hovering speeds, is not like that of a propeller. The wake is more like that of a wing except that, because of the slow speeds, the wake velocities may be much greater. The helicopter can produce a wake hazard to following light aircraft that is disproportionately great compared to an equivalent fixed-wing aircraft. This hazard should be recognized by both pilots and airport controllers when operating in congested areas. Even simple momentum theory shows that, in autorotation and partial-power descent, the required power is a complex function of both airspeed and descent angle. The nonlinear characteristic, together with an almost total lack of usable instrumentation at low airspeeds, has led to numerous power-settling accidents. The same theory shows that there is a minimum forward speed at which a rotor can autorotate. Neglect of, or inadequate appraisal of this minimum speed has also led to numerous accidents. Ground effect and the problems it creates is discussed.

Parachute Models Used in the Mars Science Laboratory Entry, Descent, and Landing Simulation

NASA Technical Reports Server (NTRS)

Cruz, Juan R.; Way, David W.; Shidner, Jeremy D.; Davis, Jody L.; Powell, Richard W.; Kipp, Devin M.; Adams, Douglas S.; Witkowski, Al; Kandis, Mike

2013-01-01

An end-to-end simulation of the Mars Science Laboratory (MSL) entry, descent, and landing (EDL) sequence was created at the NASA Langley Research Center using the Program to Optimize Simulated Trajectories II (POST2). This simulation is capable of providing numerous MSL system and flight software responses, including Monte Carlo-derived statistics of these responses. The MSL POST2 simulation includes models of EDL system elements, including those related to the parachute system. Among these there are models for the parachute geometry, mass properties, deployment, inflation, opening force, area oscillations, aerodynamic coefficients, apparent mass, interaction with the main landing engines, and off-loading. These models were kept as simple as possible, considering the overall objectives of the simulation. The main purpose of this paper is to describe these parachute system models to the extent necessary to understand how they work and some of their limitations. A list of lessons learned during the development of the models and simulation is provided. Future improvements to the parachute system models are proposed.

METALLICITY GRADIENTS THROUGH DISK INSTABILITY: A SIMPLE MODEL FOR THE MILKY WAY'S BOXY BULGE

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

Martinez-Valpuesta, Inma; Gerhard, Ortwin, E-mail: imv@mpe.mpg.de, E-mail: gerhard@mpe.mpg.de

2013-03-20

Observations show a clear vertical metallicity gradient in the Galactic bulge, which is often taken as a signature of dissipative processes in the formation of a classical bulge. Various evidence shows, however, that the Milky Way is a barred galaxy with a boxy bulge representing the inner three-dimensional part of the bar. Here we show with a secular evolution N-body model that a boxy bulge formed through bar and buckling instabilities can show vertical metallicity gradients similar to the observed gradient if the initial axisymmetric disk had a comparable radial metallicity gradient. In this framework, the range of metallicities inmore » bulge fields constrains the chemical structure of the Galactic disk at early times before bar formation. Our secular evolution model was previously shown to reproduce inner Galaxy star counts and we show here that it also has cylindrical rotation. We use it to predict a full mean metallicity map across the Galactic bulge from a simple metallicity model for the initial disk. This map shows a general outward gradient on the sky as well as longitudinal perspective asymmetries. We also briefly comment on interpreting metallicity gradient observations in external boxy bulges.« less

Influence of smooth temperature variation on hotspot ignition

NASA Astrophysics Data System (ADS)

Reinbacher, Fynn; Regele, Jonathan David

2018-01-01

Autoignition in thermally stratified reactive mixtures originates in localised hotspots. The ignition behaviour is often characterised using linear temperature gradients and more recently constant temperature plateaus combined with temperature gradients. Acoustic timescale characterisation of plateau regions has been successfully used to characterise the type of mechanical disturbance that will be created from a plateau core ignition. This work combines linear temperature gradients with superelliptic cores in order to more accurately account for a local temperature maximum of finite size and the smooth temperature variation contained inside realistic hotspot centres. A one-step Arrhenius reaction is used to model a H2-air reactive mixture. Using the superelliptic approach a range of behaviours for temperature distributions are investigated by varying the temperature profile between the gradient only and plateau and gradient bounding cases. Each superelliptic case is compared to a respective plateau and gradient case where simple acoustic timescale characterisation may be performed. It is shown that hot spots equivalent with excitation-to-acoustic timescale ratios sufficiently greater than unity exhibit behaviour very similar to a simple plateau-gradient model. However, for larger hot spots with timescale ratios sufficiently less than unity the reaction behaviour is highly dependent on the smooth temperature profile contained within the core region.

Optimum Strategies for Selecting Descent Flight-Path Angles

NASA Technical Reports Server (NTRS)

Wu, Minghong G. (Inventor); Green, Steven M. (Inventor)

2016-01-01

An information processing system and method for adaptively selecting an aircraft descent flight path for an aircraft, are provided. The system receives flight adaptation parameters, including aircraft flight descent time period, aircraft flight descent airspace region, and aircraft flight descent flyability constraints. The system queries a plurality of flight data sources and retrieves flight information including any of winds and temperatures aloft data, airspace/navigation constraints, airspace traffic demand, and airspace arrival delay model. The system calculates a set of candidate descent profiles, each defined by at least one of a flight path angle and a descent rate, and each including an aggregated total fuel consumption value for the aircraft following a calculated trajectory, and a flyability constraints metric for the calculated trajectory. The system selects a best candidate descent profile having the least fuel consumption value while the fly ability constraints metric remains within aircraft flight descent flyability constraints.

Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines

PubMed Central

Neftci, Emre O.; Augustine, Charles; Paul, Somnath; Detorakis, Georgios

2017-01-01

An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP) rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F) neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning. PMID:28680387

Event-Driven Random Back-Propagation: Enabling Neuromorphic Deep Learning Machines.

PubMed

Neftci, Emre O; Augustine, Charles; Paul, Somnath; Detorakis, Georgios

2017-01-01

An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Gradient Back Propagation (BP) rule, often relies on the immediate availability of network-wide information stored with high-precision memory during learning, and precise operations that are difficult to realize in neuromorphic hardware. Remarkably, recent work showed that exact backpropagated gradients are not essential for learning deep representations. Building on these results, we demonstrate an event-driven random BP (eRBP) rule that uses an error-modulated synaptic plasticity for learning deep representations. Using a two-compartment Leaky Integrate & Fire (I&F) neuron, the rule requires only one addition and two comparisons for each synaptic weight, making it very suitable for implementation in digital or mixed-signal neuromorphic hardware. Our results show that using eRBP, deep representations are rapidly learned, achieving classification accuracies on permutation invariant datasets comparable to those obtained in artificial neural network simulations on GPUs, while being robust to neural and synaptic state quantizations during learning.

Towards pattern generation and chaotic series prediction with photonic reservoir computers

NASA Astrophysics Data System (ADS)

Antonik, Piotr; Hermans, Michiel; Duport, François; Haelterman, Marc; Massar, Serge

2016-03-01

Reservoir Computing is a bio-inspired computing paradigm for processing time dependent signals that is particularly well suited for analog implementations. Our team has demonstrated several photonic reservoir computers with performance comparable to digital algorithms on a series of benchmark tasks such as channel equalisation and speech recognition. Recently, we showed that our opto-electronic reservoir computer could be trained online with a simple gradient descent algorithm programmed on an FPGA chip. This setup makes it in principle possible to feed the output signal back into the reservoir, and thus highly enrich the dynamics of the system. This will allow to tackle complex prediction tasks in hardware, such as pattern generation and chaotic and financial series prediction, which have so far only been studied in digital implementations. Here we report simulation results of our opto-electronic setup with an FPGA chip and output feedback applied to pattern generation and Mackey-Glass chaotic series prediction. The simulations take into account the major aspects of our experimental setup. We find that pattern generation can be easily implemented on the current setup with very good results. The Mackey-Glass series prediction task is more complex and requires a large reservoir and more elaborate training algorithm. With these adjustments promising result are obtained, and we now know what improvements are needed to match previously reported numerical results. These simulation results will serve as basis of comparison for experiments we will carry out in the coming months.

Region Segmentation in the Frequency Domain Applied to Upper Airway Real-Time Magnetic Resonance Images

PubMed Central

Narayanan, Shrikanth

2009-01-01

We describe a method for unsupervised region segmentation of an image using its spatial frequency domain representation. The algorithm was designed to process large sequences of real-time magnetic resonance (MR) images containing the 2-D midsagittal view of a human vocal tract airway. The segmentation algorithm uses an anatomically informed object model, whose fit to the observed image data is hierarchically optimized using a gradient descent procedure. The goal of the algorithm is to automatically extract the time-varying vocal tract outline and the position of the articulators to facilitate the study of the shaping of the vocal tract during speech production. PMID:19244005

Simultaneous digital super-resolution and nonuniformity correction for infrared imaging systems.

PubMed

Meza, Pablo; Machuca, Guillermo; Torres, Sergio; Martin, Cesar San; Vera, Esteban

2015-07-20

In this article, we present a novel algorithm to achieve simultaneous digital super-resolution and nonuniformity correction from a sequence of infrared images. We propose to use spatial regularization terms that exploit nonlocal means and the absence of spatial correlation between the scene and the nonuniformity noise sources. We derive an iterative optimization algorithm based on a gradient descent minimization strategy. Results from infrared image sequences corrupted with simulated and real fixed-pattern noise show a competitive performance compared with state-of-the-art methods. A qualitative analysis on the experimental results obtained with images from a variety of infrared cameras indicates that the proposed method provides super-resolution images with significantly less fixed-pattern noise.

A new version of Stochastic-parallel-gradient-descent algorithm (SPGD) for phase correction of a distorted orbital angular momentum (OAM) beam

NASA Astrophysics Data System (ADS)

Jiao Ling, LIn; Xiaoli, Yin; Huan, Chang; Xiaozhou, Cui; Yi-Lin, Guo; Huan-Yu, Liao; Chun-YU, Gao; Guohua, Wu; Guang-Yao, Liu; Jin-KUn, Jiang; Qing-Hua, Tian

2018-02-01

Atmospheric turbulence limits the performance of orbital angular momentum-based free-space optical communication (FSO-OAM) system. In order to compensate phase distortion induced by atmospheric turbulence, wavefront sensorless adaptive optics (WSAO) has been proposed and studied in recent years. In this paper a new version of SPGD called MZ-SPGD, which combines the Z-SPGD based on the deformable mirror influence function and the M-SPGD based on the Zernike polynomials, is proposed. Numerical simulations show that the hybrid method decreases convergence times markedly but can achieve the same compensated effect compared to Z-SPGD and M-SPGD.

CP decomposition approach to blind separation for DS-CDMA system using a new performance index

NASA Astrophysics Data System (ADS)

Rouijel, Awatif; Minaoui, Khalid; Comon, Pierre; Aboutajdine, Driss

2014-12-01

In this paper, we present a canonical polyadic (CP) tensor decomposition isolating the scaling matrix. This has two major implications: (i) the problem conditioning shows up explicitly and could be controlled through a constraint on the so-called coherences and (ii) a performance criterion concerning the factor matrices can be exactly calculated and is more realistic than performance metrics used in the literature. Two new algorithms optimizing the CP decomposition based on gradient descent are proposed. This decomposition is illustrated by an application to direct-sequence code division multiplexing access (DS-CDMA) systems; computer simulations are provided and demonstrate the good behavior of these algorithms, compared to others in the literature.

A rapid and robust gradient measurement technique using dynamic single-point imaging.

PubMed

Jang, Hyungseok; McMillan, Alan B

2017-09-01

We propose a new gradient measurement technique based on dynamic single-point imaging (SPI), which allows simple, rapid, and robust measurement of k-space trajectory. To enable gradient measurement, we utilize the variable field-of-view (FOV) property of dynamic SPI, which is dependent on gradient shape. First, one-dimensional (1D) dynamic SPI data are acquired from a targeted gradient axis, and then relative FOV scaling factors between 1D images or k-spaces at varying encoding times are found. These relative scaling factors are the relative k-space position that can be used for image reconstruction. The gradient measurement technique also can be used to estimate the gradient impulse response function for reproducible gradient estimation as a linear time invariant system. The proposed measurement technique was used to improve reconstructed image quality in 3D ultrashort echo, 2D spiral, and multi-echo bipolar gradient-echo imaging. In multi-echo bipolar gradient-echo imaging, measurement of the k-space trajectory allowed the use of a ramp-sampled trajectory for improved acquisition speed (approximately 30%) and more accurate quantitative fat and water separation in a phantom. The proposed dynamic SPI-based method allows fast k-space trajectory measurement with a simple implementation and no additional hardware for improved image quality. Magn Reson Med 78:950-962, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Biocompatible patterning of proteins on wettability gradient surface by thermo-transfer printing.

PubMed

Kim, Sungho; Ryu, Yong-Sang; Suh, Jeng-Hun; Keum, Chang-Min; Sohn, Youngjoo; Lee, Sin-Doo

2014-08-01

We develop a simple and biocompatible method of patterning proteins on a wettability gradient surface by thermo-transfer printing. The wettability gradient is produced on a poly(dimethylsiloxane) (PDMS)-modified glass substrate through the temperature gradient during thermo-transfer printing. The water contact angle on the PDMS-modified surface is found to gradually increase along the direction of the temperature gradient from a low to a high temperature region. Based on the wettability gradient, the gradual change in the adsorption and immobilization of proteins (cholera toxin B subunit) is achieved in a microfluidic cell with the PDMS-modified surface.

A Comparative Study of Probability Collectives Based Multi-agent Systems and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Huang, Chien-Feng; Wolpert, David H.; Bieniawski, Stefan; Strauss, Charles E. M.

2005-01-01

We compare Genetic Algorithms (GA's) with Probability Collectives (PC), a new framework for distributed optimization and control. In contrast to GA's, PC-based methods do not update populations of solutions. Instead they update an explicitly parameterized probability distribution p over the space of solutions. That updating of p arises as the optimization of a functional of p. The functional is chosen so that any p that optimizes it should be p peaked about good solutions. The PC approach works in both continuous and discrete problems. It does not suffer from the resolution limitation of the finite bit length encoding of parameters into GA alleles. It also has deep connections with both game theory and statistical physics. We review the PC approach using its motivation as the information theoretic formulation of bounded rationality for multi-agent systems. It is then compared with GA's on a diverse set of problems. To handle high dimensional surfaces, in the PC method investigated here p is restricted to a product distribution. Each distribution in that product is controlled by a separate agent. The test functions were selected for their difficulty using either traditional gradient descent or genetic algorithms. On those functions the PC-based approach significantly outperforms traditional GA's in both rate of descent, trapping in false minima, and long term optimization.

Atrioventricular nonuniformity of pericardial constraint.

PubMed

Hamilton, Douglas R; Sas, Rozsa; Tyberg, John V

2004-10-01

Physiologists and clinicians commonly refer to "pressure" as a measure of the constraining effects of the pericardium; however, "pericardial pressure" is really a local measurement of epicardial radial stress. During diastole, from the bottom of the y descent to the beginning of the a wave, pericardial pressure over the right atrium (P(pRA)) is approximately equal to that over the right ventricle (P(pRV)). However, in systole, during the interval between the bottom of the x descent and the peak of the v wave, these two pericardial pressures appear to be completely decoupled in that P(pRV) decreases, whereas P(pRA) remains constant or increases. This decoupling indicates considerable mechanical independence between the RA and RV during systole. That is, RV systolic emptying lowers P(pRV), but P(pRA) continues to increase, suggesting that the relation of the pericardium to the RA must allow effective constraint, even though the pericardium over the RV is simultaneously slack. In conclusion, we measured the pericardial pressure responsible for the previously reported nonuniformity of pericardial strain. P(pRA) and P(pRV) are closely coupled during diastole, but during systole they become decoupled. Systolic nonuniformity of pericardial constraint may augment the atrioventricular valve-opening pressure gradient in early diastole and, so, affect ventricular filling.

A comparison of discrete versus continuous adjoint states to invert groundwater flow in heterogeneous dual porosity systems

NASA Astrophysics Data System (ADS)

Delay, Frederick; Badri, Hamid; Fahs, Marwan; Ackerer, Philippe

2017-12-01

Dual porosity models become increasingly used for simulating groundwater flow at the large scale in fractured porous media. In this context, model inversions with the aim of retrieving the system heterogeneity are frequently faced with huge parameterizations for which descent methods of inversion with the assistance of adjoint state calculations are well suited. We compare the performance of discrete and continuous forms of adjoint states associated with the flow equations in a dual porosity system. The discrete form inherits from previous works by some of the authors, as the continuous form is completely new and here fully differentiated for handling all types of model parameters. Adjoint states assist descent methods by calculating the gradient components of the objective function, these being a key to good convergence of inverse solutions. Our comparison on the basis of synthetic exercises show that both discrete and continuous adjoint states can provide very similar solutions close to reference. For highly heterogeneous systems, the calculation grid of the continuous form cannot be too coarse, otherwise the method may show lack of convergence. This notwithstanding, the continuous adjoint state is the most versatile form as its non-intrusive character allows for plugging an inversion toolbox quasi-independent from the code employed for solving the forward problem.

Flight Management System Execution of Idle-Thrust Descents in Operations

NASA Technical Reports Server (NTRS)

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.

Mathematical model for steady state, simple ampholyte isoelectric focusing: Development, computer simulation and implementation

NASA Technical Reports Server (NTRS)

Palusinski, O. A.; Allgyer, T. T.

1979-01-01

The elimination of Ampholine from the system by establishing the pH gradient with simple ampholytes is proposed. A mathematical model was exercised at the level of the two-component system by using values for mobilities, diffusion coefficients, and dissociation constants representative of glutamic acid and histidine. The constants assumed in the calculations are reported. The predictions of the model and computer simulation of isoelectric focusing experiments are in direct importance to obtain Ampholine-free, stable pH gradients.

Training Excitatory-Inhibitory Recurrent Neural Networks for Cognitive Tasks: A Simple and Flexible Framework

PubMed Central

Wang, Xiao-Jing

2016-01-01

The ability to simultaneously record from large numbers of neurons in behaving animals has ushered in a new era for the study of the neural circuit mechanisms underlying cognitive functions. One promising approach to uncovering the dynamical and computational principles governing population responses is to analyze model recurrent neural networks (RNNs) that have been optimized to perform the same tasks as behaving animals. Because the optimization of network parameters specifies the desired output but not the manner in which to achieve this output, “trained” networks serve as a source of mechanistic hypotheses and a testing ground for data analyses that link neural computation to behavior. Complete access to the activity and connectivity of the circuit, and the ability to manipulate them arbitrarily, make trained networks a convenient proxy for biological circuits and a valuable platform for theoretical investigation. However, existing RNNs lack basic biological features such as the distinction between excitatory and inhibitory units (Dale’s principle), which are essential if RNNs are to provide insights into the operation of biological circuits. Moreover, trained networks can achieve the same behavioral performance but differ substantially in their structure and dynamics, highlighting the need for a simple and flexible framework for the exploratory training of RNNs. Here, we describe a framework for gradient descent-based training of excitatory-inhibitory RNNs that can incorporate a variety of biological knowledge. We provide an implementation based on the machine learning library Theano, whose automatic differentiation capabilities facilitate modifications and extensions. We validate this framework by applying it to well-known experimental paradigms such as perceptual decision-making, context-dependent integration, multisensory integration, parametric working memory, and motor sequence generation. Our results demonstrate the wide range of neural activity patterns and behavior that can be modeled, and suggest a unified setting in which diverse cognitive computations and mechanisms can be studied. PMID:26928718

Integral design method for simple and small Mars lander system using membrane aeroshell

NASA Astrophysics Data System (ADS)

Sakagami, Ryo; Takahashi, Ryohei; Wachi, Akifumi; Koshiro, Yuki; Maezawa, Hiroyuki; Kasai, Yasko; Nakasuka, Shinichi

2018-03-01

To execute Mars surface exploration missions, spacecraft need to overcome the difficulties of the Mars entry, descent, and landing (EDL) sequences. Previous landing missions overcame these challenges with complicated systems that could only be executed by organizations with mature technology and abundant financial resources. In this paper, we propose a novel integral design methodology for a small, simple Mars lander that is achievable even by organizations with limited technology and resources such as universities or emerging countries. We aim to design a lander (including its interplanetary cruise stage) whose size and mass are under 1 m3 and 150 kg, respectively. We adopted only two components for Mars EDL process: a "membrane aeroshell" for the Mars atmospheric entry and descent sequence and one additional mechanism for the landing sequence. The landing mechanism was selected from the following three candidates: (1) solid thrusters, (2) aluminum foam, and (3) a vented airbag. We present a reasonable design process, visualize dependencies among parameters, summarize sizing methods for each component, and propose the way to integrate these components into one system. To demonstrate the effectiveness, we applied this methodology to the actual Mars EDL mission led by the National Institute of Information and Communications Technology (NICT) and the University of Tokyo. As a result, an 80 kg class Mars lander with a 1.75 m radius membrane aeroshell and a vented airbag was designed, and the maximum landing shock that the lander will receive was 115 G.

Influence of smooth temperature variation on hotspot ignition

DOE PAGES

Reinbacher, Fynn; Regele, Jonathan David

2017-10-06

Autoignition in thermally stratified reactive mixtures originates in localised hotspots. The ignition behaviour is often characterised using linear temperature gradients and more recently constant temperature plateaus combined with temperature gradients. Acoustic timescale characterisation of plateau regions has been successfully used to characterise the type of mechanical disturbance that will be created from a plateau core ignition. This work combines linear temperature gradients with superelliptic cores in order to more accurately account for a local temperature maximum of finite size and the smooth temperature variation contained inside realistic hotspot centres. A one-step Arrhenius reaction is used to model a H 2–airmore » reactive mixture. Using the superelliptic approach a range of behaviours for temperature distributions are investigated by varying the temperature profile between the gradient only and plateau and gradient bounding cases. Each superelliptic case is compared to a respective plateau and gradient case where simple acoustic timescale characterisation may be performed. It is shown that hot spots equivalent with excitation-to-acoustic timescale ratios sufficiently greater than unity exhibit behaviour very similar to a simple plateau-gradient model. Furthermore, for larger hot spots with timescale ratios sufficiently less than unity the reaction behaviour is highly dependent on the smooth temperature profile contained within the core region.« less

Influence of smooth temperature variation on hotspot ignition

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

Reinbacher, Fynn; Regele, Jonathan David

Autoignition in thermally stratified reactive mixtures originates in localised hotspots. The ignition behaviour is often characterised using linear temperature gradients and more recently constant temperature plateaus combined with temperature gradients. Acoustic timescale characterisation of plateau regions has been successfully used to characterise the type of mechanical disturbance that will be created from a plateau core ignition. This work combines linear temperature gradients with superelliptic cores in order to more accurately account for a local temperature maximum of finite size and the smooth temperature variation contained inside realistic hotspot centres. A one-step Arrhenius reaction is used to model a H 2–airmore » reactive mixture. Using the superelliptic approach a range of behaviours for temperature distributions are investigated by varying the temperature profile between the gradient only and plateau and gradient bounding cases. Each superelliptic case is compared to a respective plateau and gradient case where simple acoustic timescale characterisation may be performed. It is shown that hot spots equivalent with excitation-to-acoustic timescale ratios sufficiently greater than unity exhibit behaviour very similar to a simple plateau-gradient model. Furthermore, for larger hot spots with timescale ratios sufficiently less than unity the reaction behaviour is highly dependent on the smooth temperature profile contained within the core region.« less

Surface Tension Gradients Induced by Temperature: The Thermal Marangoni Effect

ERIC Educational Resources Information Center

Gugliotti, Marcos; Baptisto, Mauricio S.; Politi, Mario J.

2004-01-01

Surface tensions gradients were generated in a thin liquid film because of the local increase in temperature, for demonstration purposes. This is performed using a simple experiment and allows different alternatives for heat generation to be used.

Microecology: Using Fast-Growing Filamentous Fungi to Study the Effects of Environmental Gradients on the Growth Patterns of Hyphae

ERIC Educational Resources Information Center

Delpech, Roger

2004-01-01

This paper describes some simple and rapid techniques for examining the growth responses of fungal hyphae cultivated on environmental gradients. The creation of such gradients using agar-based growth media in petri dishes is explained, along with recommendations for quantitative macroscopic and microscopic measurements. The intention is to provide…

Deep neural mapping support vector machines.

PubMed

Li, Yujian; Zhang, Ting

2017-09-01

The choice of kernel has an important effect on the performance of a support vector machine (SVM). The effect could be reduced by NEUROSVM, an architecture using multilayer perceptron for feature extraction and SVM for classification. In binary classification, a general linear kernel NEUROSVM can be theoretically simplified as an input layer, many hidden layers, and an SVM output layer. As a feature extractor, the sub-network composed of the input and hidden layers is first trained together with a virtual ordinary output layer by backpropagation, then with the output of its last hidden layer taken as input of the SVM classifier for further training separately. By taking the sub-network as a kernel mapping from the original input space into a feature space, we present a novel model, called deep neural mapping support vector machine (DNMSVM), from the viewpoint of deep learning. This model is also a new and general kernel learning method, where the kernel mapping is indeed an explicit function expressed as a sub-network, different from an implicit function induced by a kernel function traditionally. Moreover, we exploit a two-stage procedure of contrastive divergence learning and gradient descent for DNMSVM to jointly training an adaptive kernel mapping instead of a kernel function, without requirement of kernel tricks. As a whole of the sub-network and the SVM classifier, the joint training of DNMSVM is done by using gradient descent to optimize the objective function with the sub-network layer-wise pre-trained via contrastive divergence learning of restricted Boltzmann machines. Compared to the separate training of NEUROSVM, the joint training is a new algorithm for DNMSVM to have advantages over NEUROSVM. Experimental results show that DNMSVM can outperform NEUROSVM and RBFSVM (i.e., SVM with the kernel of radial basis function), demonstrating its effectiveness. Copyright © 2017 Elsevier Ltd. All rights reserved.

Application of artificial neural network to predict clay sensitivity in a high landslide prone area using CPTu data- A case study in Southwest of Sweden

NASA Astrophysics Data System (ADS)

Shahri, Abbas; Mousavinaseri, Mahsasadat; Naderi, Shima; Espersson, Maria

2015-04-01

Application of Artificial Neural Networks (ANNs) in many areas of engineering, in particular to geotechnical engineering problems such as site characterization has demonstrated some degree of success. The present paper aims to evaluate the feasibility of several various types of ANN models to predict the clay sensitivity of soft clays form piezocone penetration test data (CPTu). To get the aim, a research database of CPTu data of 70 test points around the Göta River near the Lilli Edet in the southwest of Sweden which is a high prone land slide area were collected and considered as input for ANNs. For training algorithms the quick propagation, conjugate gradient descent, quasi-Newton, limited memory quasi-Newton and Levenberg-Marquardt were developed tested and trained using the CPTu data to provide a comparison between the results of field investigation and ANN models to estimate the clay sensitivity. The reason of using the clay sensitivity parameter in this study is due to its relation to landslides in Sweden.A special high sensitive clay namely quick clay is considered as the main responsible for experienced landslides in Sweden which has high sensitivity and prone to slide. The training and testing program was started with 3-2-1 ANN architecture structure. By testing and trying several various architecture structures and changing the hidden layer in order to have a higher output resolution the 3-4-4-3-1 architecture structure for ANN in this study was confirmed. The tested algorithm showed that increasing the hidden layers up to 4 layers in ANN can improve the results and the 3-4-4-3-1 architecture structure ANNs for prediction of clay sensitivity represent reliable and reasonable response. The obtained results showed that the conjugate gradient descent algorithm with R2=0.897 has the best performance among the tested algorithms. Keywords: clay sensitivity, landslide, Artificial Neural Network

Efficacy of Metarhizium anisopliae isolate MAX-2 from Shangri-la, China under desiccation stress

PubMed Central

2014-01-01

Background Metarhizium anisopliae, a soil-borne entomopathogen found worldwide, is an interesting fungus for biological control. However, its efficacy in the fields is significantly affected by environmental conditions, particularly moisture. To overcome the weakness of Metarhizium and determine its isolates with antistress capacity, the efficacies of four M. anisopliae isolates, which were collected from arid regions of Yunnan Province in China during the dry season, were determined at different moisture levels, and the efficacy of the isolate MAX-2 from Shangri-la under desiccation stress was evaluated at low moisture level. Results M. anisopliae isolates MAX-2, MAC-6, MAL-1, and MAQ-28 showed gradient descent efficacies against sterile Tenebrio molitor larvae, and gradient descent capacities against desiccation with the decrease in moisture levels. The efficacy of MAX-2 showed no significant differences at 35% moisture level than those of the other isolates. However, significant differences were found at 8% to 30% moisture levels. The efficacies of all isolates decreased with the decrease in moisture levels. MAX-2 was relatively less affected by desiccation stress. Its efficacy was almost unaffected by the decrease at moisture levels > 25%, but slowly decreased at moisture levels < 25%. By contrast, the efficacies of other isolates rapidly decreased with the decrease in moisture levels. MAX-2 caused different infection characteristics on T. molitor larvae under desiccation stress and in wet microhabitat. Local black patches were found on the cuticles of the insects, and the cadavers dried without fungal growth under desiccation stress. However, dark black internodes and fungal growth were found after death of the insects in the wet microhabitat. Conclusions MAX-2 showed significantly higher efficacy and superior antistress capacity than the other isolates under desiccation stress. The infection of sterile T. molitor larvae at low moisture level constituted a valid laboratory bioassay system in evaluating M. anisopliae efficacy under desiccation stress. PMID:24383424

Efficacy of Metarhizium anisopliae isolate MAX-2 from Shangri-la, China under desiccation stress.

PubMed

Chen, Zi-Hong; Xu, Ling; Yang, Feng-lian; Ji, Guang-Hai; Yang, Jing; Wang, Jian-Yun

2014-01-03

Metarhizium anisopliae, a soil-borne entomopathogen found worldwide, is an interesting fungus for biological control. However, its efficacy in the fields is significantly affected by environmental conditions, particularly moisture. To overcome the weakness of Metarhizium and determine its isolates with antistress capacity, the efficacies of four M. anisopliae isolates, which were collected from arid regions of Yunnan Province in China during the dry season, were determined at different moisture levels, and the efficacy of the isolate MAX-2 from Shangri-la under desiccation stress was evaluated at low moisture level. M. anisopliae isolates MAX-2, MAC-6, MAL-1, and MAQ-28 showed gradient descent efficacies against sterile Tenebrio molitor larvae, and gradient descent capacities against desiccation with the decrease in moisture levels. The efficacy of MAX-2 showed no significant differences at 35% moisture level than those of the other isolates. However, significant differences were found at 8% to 30% moisture levels. The efficacies of all isolates decreased with the decrease in moisture levels. MAX-2 was relatively less affected by desiccation stress. Its efficacy was almost unaffected by the decrease at moisture levels > 25%, but slowly decreased at moisture levels < 25%. By contrast, the efficacies of other isolates rapidly decreased with the decrease in moisture levels. MAX-2 caused different infection characteristics on T. molitor larvae under desiccation stress and in wet microhabitat. Local black patches were found on the cuticles of the insects, and the cadavers dried without fungal growth under desiccation stress. However, dark black internodes and fungal growth were found after death of the insects in the wet microhabitat. MAX-2 showed significantly higher efficacy and superior antistress capacity than the other isolates under desiccation stress. The infection of sterile T. molitor larvae at low moisture level constituted a valid laboratory bioassay system in evaluating M. anisopliae efficacy under desiccation stress.

Cell orientation gradients on an inverse opal substrate.

PubMed

Lu, Jie; Zou, Xin; Zhao, Ze; Mu, Zhongde; Zhao, Yuanjin; Gu, Zhongze

2015-05-20

The generation of cell gradients is critical for understanding many biological systems and realizing the unique functionality of many implanted biomaterials. However, most previous work can only control the gradient of cell density and this has no effect on the gradient of cell orientation, which has an important role in regulating the functions of many connecting tissues. Here, we report on a simple stretched inverse opal substrate for establishing desired cell orientation gradients. It was demonstrated that tendon fibroblasts on the stretched inverse opal gradient showed a corresponding alignment along with the elongation gradient of the substrate. This "random-to-aligned" cell gradient reproduces the insertion part of many connecting tissues, and thus, will have important applications in tissue engineering.

Smoothing of cost function leads to faster convergence of neural network learning

NASA Astrophysics Data System (ADS)

Xu, Li-Qun; Hall, Trevor J.

1994-03-01

One of the major problems in supervised learning of neural networks is the inevitable local minima inherent in the cost function f(W,D). This often makes classic gradient-descent-based learning algorithms that calculate the weight updates for each iteration according to (Delta) W(t) equals -(eta) (DOT)$DELwf(W,D) powerless. In this paper we describe a new strategy to solve this problem, which, adaptively, changes the learning rate and manipulates the gradient estimator simultaneously. The idea is to implicitly convert the local- minima-laden cost function f((DOT)) into a sequence of its smoothed versions {f(beta t)}Ttequals1, which, subject to the parameter (beta) t, bears less details at time t equals 1 and gradually more later on, the learning is actually performed on this sequence of functionals. The corresponding smoothed global minima obtained in this way, {Wt}Ttequals1, thus progressively approximate W-the desired global minimum. Experimental results on a nonconvex function minimization problem and a typical neural network learning task are given, analyses and discussions of some important issues are provided.

A hybrid neural network model for noisy data regression.

PubMed

Lee, Eric W M; Lim, Chee Peng; Yuen, Richard K K; Lo, S M

2004-04-01

A hybrid neural network model, based on the fusion of fuzzy adaptive resonance theory (FA ART) and the general regression neural network (GRNN), is proposed in this paper. Both FA and the GRNN are incremental learning systems and are very fast in network training. The proposed hybrid model, denoted as GRNNFA, is able to retain these advantages and, at the same time, to reduce the computational requirements in calculating and storing information of the kernels. A clustering version of the GRNN is designed with data compression by FA for noise removal. An adaptive gradient-based kernel width optimization algorithm has also been devised. Convergence of the gradient descent algorithm can be accelerated by the geometric incremental growth of the updating factor. A series of experiments with four benchmark datasets have been conducted to assess and compare effectiveness of GRNNFA with other approaches. The GRNNFA model is also employed in a novel application task for predicting the evacuation time of patrons at typical karaoke centers in Hong Kong in the event of fire. The results positively demonstrate the applicability of GRNNFA in noisy data regression problems.

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

PubMed

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.

Adaptation to Space: An Introduction

NASA Technical Reports Server (NTRS)

Hargens, Alan R.

1995-01-01

The cardiovascular and musculoskeletal systems are normally exposed to gradients of blood pressure and weight on Earth. These gradients increase blood pressure and tissue weight in dependent tissues of the body. Exposure to actual and simulated microgravity causes blood and tissue fluid to shift from the legs to the head. Studies of humans in space have documented facial edema, space motion sickness, decreased plasma volume, muscle atrophy, and loss of bone strength. Return of astronauts to Earth is accompanied by orthostatic intolerance, decreased neuromuscular coordination, and reduced exercise capacity. These factors decrease performance during descent from orbit and increase risk during emergency egress from the spacecraft. Models of simulated microgravity include 6 deg head-down tilt, immersion, and prolonged horizontal bedrest. Head-down tilt is the most accepted model and studies using this model of up to one year have been performed in Russia. Animal models which offer clear insights into the role of gravity on vertebrates include the developing giraffe and snakes from various habitats. Finally, possible countermeasures to speed readaptation of astronauts to gravity after prolonged space flight will be discussed.

One Giant Leap for Categorizers: One Small Step for Categorization Theory

PubMed Central

Smith, J. David; Ell, Shawn W.

2015-01-01

We explore humans’ rule-based category learning using analytic approaches that highlight their psychological transitions during learning. These approaches confirm that humans show qualitatively sudden psychological transitions during rule learning. These transitions contribute to the theoretical literature contrasting single vs. multiple category-learning systems, because they seem to reveal a distinctive learning process of explicit rule discovery. A complete psychology of categorization must describe this learning process, too. Yet extensive formal-modeling analyses confirm that a wide range of current (gradient-descent) models cannot reproduce these transitions, including influential rule-based models (e.g., COVIS) and exemplar models (e.g., ALCOVE). It is an important theoretical conclusion that existing models cannot explain humans’ rule-based category learning. The problem these models have is the incremental algorithm by which learning is simulated. Humans descend no gradient in rule-based tasks. Very different formal-modeling systems will be required to explain humans’ psychology in these tasks. An important next step will be to build a new generation of models that can do so. PMID:26332587

Implementing a Bayes Filter in a Neural Circuit: The Case of Unknown Stimulus Dynamics.

PubMed

Sokoloski, Sacha

2017-09-01

In order to interact intelligently with objects in the world, animals must first transform neural population responses into estimates of the dynamic, unknown stimuli that caused them. The Bayesian solution to this problem is known as a Bayes filter, which applies Bayes' rule to combine population responses with the predictions of an internal model. The internal model of the Bayes filter is based on the true stimulus dynamics, and in this note, we present a method for training a theoretical neural circuit to approximately implement a Bayes filter when the stimulus dynamics are unknown. To do this we use the inferential properties of linear probabilistic population codes to compute Bayes' rule and train a neural network to compute approximate predictions by the method of maximum likelihood. In particular, we perform stochastic gradient descent on the negative log-likelihood of the neural network parameters with a novel approximation of the gradient. We demonstrate our methods on a finite-state, a linear, and a nonlinear filtering problem and show how the hidden layer of the neural network develops tuning curves consistent with findings in experimental neuroscience.

Field evaluation of flight deck procedures for flying CTAS descents

DOT National Transportation Integrated Search

1997-01-01

Flight deck descent procedures were developed for a field evaluation of the CTAS Descent Advisor conducted in the fall of 1995. During this study, CTAS descent clearances were issued to 185 commercial flights at Denver International Airport. Data col...

An improved silver staining procedure for schizodeme analysis in polyacrylamide gradient gels.

PubMed

Gonçalves, A M; Nehme, N S; Morel, C M

1990-01-01

A simple protocol is described for the silver staining of polyacrylamide gradient gels used for the separation of restriction fragments of kinetoplast DNA [schizodeme analysis of trypanosomatids (Morel et al., 1980)]. The method overcomes the problems of non-uniform staining and strong background color which are frequently encountered when conventional protocols for silver staining of linear gels are applied to gradient gels. The method described has proven to be of general applicability for DNA, RNA and protein separations in gradient gels.

Toward the Darwinian transition: Switching between distributed and speciated states in a simple model of early life.

PubMed

Arnoldt, Hinrich; Strogatz, Steven H; Timme, Marc

2015-01-01

It has been hypothesized that in the era just before the last universal common ancestor emerged, life on earth was fundamentally collective. Ancient life forms shared their genetic material freely through massive horizontal gene transfer (HGT). At a certain point, however, life made a transition to the modern era of individuality and vertical descent. Here we present a minimal model for stochastic processes potentially contributing to this hypothesized "Darwinian transition." The model suggests that HGT-dominated dynamics may have been intermittently interrupted by selection-driven processes during which genotypes became fitter and decreased their inclination toward HGT. Stochastic switching in the population dynamics with three-point (hypernetwork) interactions may have destabilized the HGT-dominated collective state and essentially contributed to the emergence of vertical descent and the first well-defined species in early evolution. A systematic nonlinear analysis of the stochastic model dynamics covering key features of evolutionary processes (such as selection, mutation, drift and HGT) supports this view. Our findings thus suggest a viable direction out of early collective evolution, potentially enabling the start of individuality and vertical Darwinian evolution.

Inertial measurements of free-living activities: assessing mobility to predict falls.

PubMed

Wang, Kejia; Lovell, Nigel H; Del Rosario, Michael B; Liu, Ying; Wang, Jingjing; Narayanan, Michael R; Brodie, Matthew A D; Delbaere, Kim; Menant, Jasmine; Lord, Stephen R; Redmond, Stephen J

2014-01-01

An exploratory analysis was conducted into how simple features, from acceleration at the lower back and ankle during simulated free-living walking, stair ascent and descent, correlate with age, the overall fall risk from a clinically validated Physiological Profile Assessment (PPA), and its sub-components. Inertial data were captured from 92 older adults aged 78-95 (42 female, mean age 84.1, standard deviation 3.9 years). The dominant frequency, peak width from Welch's power spectral density estimate, and signal variance along each axis, from each sensor location and for each activity were calculated. Several correlations were found between these features and the physiological risk factors. The strongest correlations were from the dominant frequency at the ankle along the mediolateral direction during stair ascent (Spearman's correlation coefficient p = - 0.45) with anterioposterior sway, and signal variance of the anterioposterior acceleration at the lower back during stair descent (p = - 0.45) with age. These findings should aid future attempts to classify activities and predict falls in older adults, based on true free-living data from a range of activities.

How to define pathologic pelvic floor descent in MR defecography during defecation?

PubMed

Schawkat, Khoschy; Heinrich, Henriette; Parker, Helen L; Barth, Borna K; Mathew, Rishi P; Weishaupt, Dominik; Fox, Mark; Reiner, Caecilia S

2018-06-01

To assess the extents of pelvic floor descent both during the maximal straining phase and the defecation phase in healthy volunteers and in patients with pelvic floor disorders, studied with MR defecography (MRD), and to define specific threshold values for pelvic floor descent during the defecation phase. Twenty-two patients (mean age 51 ± 19.4) with obstructed defecation and 20 healthy volunteers (mean age 33.4 ± 11.5) underwent 3.0T MRD in supine position using midsagittal T2-weighted images. Two radiologists performed measurements in reference to PCL-lines in straining and during defecation. In order to identify cutoff values of pelvic floor measurements for diagnosis of pathologic pelvic floor descent [anterior, middle, and posterior compartments (AC, MC, PC)], receiver-operating characteristic (ROC) curves were plotted. Pelvic floor descent of all three compartments was significantly larger during defecation than at straining in patients and healthy volunteers (p < 0.002). When grading pelvic floor descent in the straining phase, only two healthy volunteers showed moderate PC descent (10%), which is considered pathologic. However, when applying the grading system during defecation, PC descent was overestimated with 50% of the healthy volunteers (10 of 20) showing moderate PC descent. The AUC for PC measurements during defecation was 0.77 (p = 0.003) and suggests a cutoff value of 45 mm below the PCL to identify patients with pathologic PC descent. With the adapted cutoff, only 15% of healthy volunteers show pathologic PC descent during defecation. MRD measurements during straining and defecation can be used to differentiate patients with pelvic floor dysfunction from healthy volunteers. However, different cutoff values should be used during straining and during defecation to define normal or pathologic PC descent.

Evaluation of pelvic descent disorders by dynamic contrast roentgenography.

PubMed

Takano, M; Hamada, A

2000-10-01

For precise diagnosis and rational treatment of the increasing number of patients with descent of intrapelvic organ(s) and anatomic plane(s), dynamic contrast roentgenography of multiple intrapelvic organs and planes is described. Sixty-six patients, consisting of 11 males, with a mean age (+/- standard deviation) of 65.6+/-14.2 years and with chief complaints of intrapelvic organ and perineal descent or defecation problems, were examined in this study. Dynamic contrast roentgenography was obtained by opacifying the ileum, urinary bladder, vagina, rectum, and the perineum. Films were taken at both squeeze and strain phases. On the films the lowest points of each organ and plane were plotted, and the distances from the standard line drawn at the upper surface of the sacrum were measured. The values were corrected to percentages according to the height of the sacrococcygeal bone of each patient. From these corrected values, organ or plane descents at strain and squeeze were diagnosed and graphically demonstrated as a descentgram in each patient. Among 17 cases with subjective symptoms of bladder descent, 9 cases (52.9 percent) showed roentgenographic descent. By the same token, among the cases with subjective feeling of descent of the vagina, uterus, peritoneum, perineum, rectum, and anus, roentgenographic descent was confirmed in 15 of 20 (75 percent), 7 of 9 (77.8 percent), 6 of 16 (37.5 percent), 33 of 33 (100 percent), 25 of 37 (67.6 percent), and 22 of 36 (61.6 percent), respectively. The descentgrams were divided into three patterns: anorectal descent type, female genital descent type, and total organ descent type. Dynamic contrast roentgenography and successive descentgraphy of multiple intrapelvic organs and planes are useful for objective diagnosis and rational treatment of patients with descent disorders of the intrapelvic organ(s) and plane(s).

Panel flutter optimization by gradient projection

NASA Technical Reports Server (NTRS)

Pierson, B. L.

1975-01-01

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

Divergence and Necessary Conditions for Extremums

NASA Technical Reports Server (NTRS)

Quirein, J. A.

1973-01-01

The problem is considered of finding a dimension reducing transformation matrix B that maximizes the divergence in the reduced dimension for multi-class cases. A comparitively simple expression for the gradient of the average divergence with respect to B is developed. The developed expression for the gradient contains no eigenvectors or eigenvalues; also, all matrix inversions necessary to evaluate the gradient are available from computing the average divergence.

Wake Vortex Prediction Models for Decay and Transport Within Stratified Environments

NASA Astrophysics Data System (ADS)

Switzer, George F.; Proctor, Fred H.

2002-01-01

This paper proposes two simple models to predict vortex transport and decay. The models are determined empirically from results of three-dimensional large eddy simulations, and are applicable to wake vortices out of ground effect and not subjected to environmental winds. The results, from the large eddy simulations assume a range of ambient turbulence and stratification levels. The models and the results from the large eddy simulations support the hypothesis that the decay of the vortex hazard is decoupled from its change in descent rate.

Analysis of various descent trajectories for a hypersonic-cruise, cold-wall research airplane

NASA Technical Reports Server (NTRS)

Lawing, P. L.

1975-01-01

The probable descent operating conditions for a hypersonic air-breathing research airplane were examined. Descents selected were cruise angle of attack, high dynamic pressure, high lift coefficient, turns, and descents with drag brakes. The descents were parametrically exercised and compared from the standpoint of cold-wall (367 K) aircraft heat load. The descent parameters compared were total heat load, peak heating rate, time to landing, time to end of heat pulse, and range. Trends in total heat load as a function of cruise Mach number, cruise dynamic pressure, angle-of-attack limitation, pull-up g-load, heading angle, and drag-brake size are presented.

A piloted simulator evaluation of a ground-based 4-D descent advisor algorithm

NASA Technical Reports Server (NTRS)

Davis, Thomas J.; Green, Steven M.; Erzberger, Heinz

1990-01-01

A ground-based, four dimensional (4D) descent-advisor algorithm is under development at NASA-Ames. The algorithm combines detailed aerodynamic, propulsive, and atmospheric models with an efficient numerical integration scheme to generate 4D descent advisories. The ability is investigated of the 4D descent advisor algorithm to provide adequate control of arrival time for aircraft not equipped with on-board 4D guidance systems. A piloted simulation was conducted to determine the precision with which the descent advisor could predict the 4D trajectories of typical straight-in descents flown by airline pilots under different wind conditions. The effects of errors in the estimation of wind and initial aircraft weight were also studied. A description of the descent advisor as well as the result of the simulation studies are presented.

STS-1 operational flight profile. Volume 5: Descent, cycle 3. Appendix C: Monte Carlo dispersion analysis

NASA Technical Reports Server (NTRS)

1980-01-01

The results of three nonlinear the Monte Carlo dispersion analyses for the Space Transportation System 1 Flight (STS-1) Orbiter Descent Operational Flight Profile, Cycle 3 are presented. Fifty randomly selected simulation for the end of mission (EOM) descent, the abort once around (AOA) descent targeted line are steep target line, and the AOA descent targeted to the shallow target line are analyzed. These analyses compare the flight environment with system and operational constraints on the flight environment and in some cases use simplified system models as an aid in assessing the STS-1 descent flight profile. In addition, descent flight envelops are provided as a data base for use by system specialists to determine the flight readiness for STS-1. The results of these dispersion analyses supersede results of the dispersion analysis previously documented.

Power plant fault detection using artificial neural network

NASA Astrophysics Data System (ADS)

Thanakodi, Suresh; Nazar, Nazatul Shiema Moh; Joini, Nur Fazriana; Hidzir, Hidzrin Dayana Mohd; Awira, Mohammad Zulfikar Khairul

2018-02-01

The fault that commonly occurs in power plants is due to various factors that affect the system outage. There are many types of faults in power plants such as single line to ground fault, double line to ground fault, and line to line fault. The primary aim of this paper is to diagnose the fault in 14 buses power plants by using an Artificial Neural Network (ANN). The Multilayered Perceptron Network (MLP) that detection trained utilized the offline training methods such as Gradient Descent Backpropagation (GDBP), Levenberg-Marquardt (LM), and Bayesian Regularization (BR). The best method is used to build the Graphical User Interface (GUI). The modelling of 14 buses power plant, network training, and GUI used the MATLAB software.

Incoherent beam combining based on the momentum SPGD algorithm

NASA Astrophysics Data System (ADS)

Yang, Guoqing; Liu, Lisheng; Jiang, Zhenhua; Guo, Jin; Wang, Tingfeng

2018-05-01

Incoherent beam combining (ICBC) technology is one of the most promising ways to achieve high-energy, near-diffraction laser output. In this paper, the momentum method is proposed as a modification of the stochastic parallel gradient descent (SPGD) algorithm. The momentum method can improve the speed of convergence of the combining system efficiently. The analytical method is employed to interpret the principle of the momentum method. Furthermore, the proposed algorithm is testified through simulations as well as experiments. The results of the simulations and the experiments show that the proposed algorithm not only accelerates the speed of the iteration, but also keeps the stability of the combining process. Therefore the feasibility of the proposed algorithm in the beam combining system is testified.

Frequency-domain ultrasound waveform tomography breast attenuation imaging

NASA Astrophysics Data System (ADS)

Sandhu, Gursharan Yash Singh; Li, Cuiping; Roy, Olivier; West, Erik; Montgomery, Katelyn; Boone, Michael; Duric, Neb

2016-04-01

Ultrasound waveform tomography techniques have shown promising results for the visualization and characterization of breast disease. By using frequency-domain waveform tomography techniques and a gradient descent algorithm, we have previously reconstructed the sound speed distributions of breasts of varying densities with different types of breast disease including benign and malignant lesions. By allowing the sound speed to have an imaginary component, we can model the intrinsic attenuation of a medium. We can similarly recover the imaginary component of the velocity and thus the attenuation. In this paper, we will briefly review ultrasound waveform tomography techniques, discuss attenuation and its relations to the imaginary component of the sound speed, and provide both numerical and ex vivo examples of waveform tomography attenuation reconstructions.

Deep turbulence effects mitigation with coherent combining of 21 laser beams over 7 km.

PubMed

Weyrauch, Thomas; Vorontsov, Mikhail; Mangano, Joseph; Ovchinnikov, Vladimir; Bricker, David; Polnau, Ernst; Rostov, Andrey

2016-02-15

We demonstrate coherent beam combining and adaptive mitigation of atmospheric turbulence effects over 7 km under strong scintillation conditions using a coherent fiber array laser transmitter operating in a target-in-the-loop setting. The transmitter system is composed of a densely packed array of 21 fiber collimators with integrated capabilities for piston, tip, and tilt control of the outgoing beams wavefront phases. A small cat's-eye retro reflector was used for evaluation of beam combining and turbulence compensation performance at the target plane, and to provide the feedback signal for control of piston and tip/tilt phases of the transmitted beams using the stochastic parallel gradient descent maximization of the power-in-the-bucket metric.

WS-BP: An efficient wolf search based back-propagation algorithm

NASA Astrophysics Data System (ADS)

Nawi, Nazri Mohd; Rehman, M. Z.; Khan, Abdullah

2015-05-01

Wolf Search (WS) is a heuristic based optimization algorithm. Inspired by the preying and survival capabilities of the wolves, this algorithm is highly capable to search large spaces in the candidate solutions. This paper investigates the use of WS algorithm in combination with back-propagation neural network (BPNN) algorithm to overcome the local minima problem and to improve convergence in gradient descent. The performance of the proposed Wolf Search based Back-Propagation (WS-BP) algorithm is compared with Artificial Bee Colony Back-Propagation (ABC-BP), Bat Based Back-Propagation (Bat-BP), and conventional BPNN algorithms. Specifically, OR and XOR datasets are used for training the network. The simulation results show that the WS-BP algorithm effectively avoids the local minima and converge to global minima.

Aeroassisted orbital maneuvering using Lyapunov optimal feedback control

NASA Technical Reports Server (NTRS)

Grantham, Walter J.; Lee, Byoung-Soo

1987-01-01

A Liapunov optimal feedback controller incorporating a preferred direction of motion at each state of the system which is opposite to the gradient of a specified descent function is developed for aeroassisted orbital transfer from high-earth orbit to LEO. The performances of the Liapunov controller and a calculus-of-variations open-loop minimum-fuel controller, both of which are based on the 1962 U.S. Standard Atmosphere, are simulated using both the 1962 U.S. Standard Atmosphere and an atmosphere corresponding to the STS-6 Space Shuttle flight. In the STS-6 atmosphere, the calculus-of-variations open-loop controller fails to exit the atmosphere, while the Liapunov controller achieves the optimal minimum-fuel conditions, despite the + or - 40 percent fluctuations in the STS-6 atmosphere.

An experimental trip to the Calculus of Variations

NASA Astrophysics Data System (ADS)

Arroyo, Josu

2008-04-01

This paper presents a collection of experiments in the Calculus of Variations. The implementation of the Gradient Descent algorithm built on cubic-splines acting as "numerically friendly" elementary functions, give us ways to solve variational problems by constructing the solution. It wins a pragmatic point of view: one gets solutions sometimes as fast as possible, sometimes as close as possible to the true solutions. The balance speed/precision is not always easy to achieve. Starting from the most well-known, classic or historical formulation of a variational problem, section 2 describes briefly the bridge between theoretical and computational formulations. The next sections show the results of several kind of experiments; from the most basics, as those about geodesics, to the most complex, as those about vesicles.

Soft learning vector quantization and clustering algorithms based on ordered weighted aggregation operators.

PubMed

Karayiannis, N B

2000-01-01

This paper presents the development and investigates the properties of ordered weighted learning vector quantization (LVQ) and clustering algorithms. These algorithms are developed by using gradient descent to minimize reformulation functions based on aggregation operators. An axiomatic approach provides conditions for selecting aggregation operators that lead to admissible reformulation functions. Minimization of admissible reformulation functions based on ordered weighted aggregation operators produces a family of soft LVQ and clustering algorithms, which includes fuzzy LVQ and clustering algorithms as special cases. The proposed LVQ and clustering algorithms are used to perform segmentation of magnetic resonance (MR) images of the brain. The diagnostic value of the segmented MR images provides the basis for evaluating a variety of ordered weighted LVQ and clustering algorithms.

Quantitative characterization of turbidity by radiative transfer based reflectance imaging

PubMed Central

Tian, Peng; Chen, Cheng; Jin, Jiahong; Hong, Heng; Lu, Jun Q.; Hu, Xin-Hua

2018-01-01

A new and noncontact approach of multispectral reflectance imaging has been developed to inversely determine the absorption coefficient of μa, the scattering coefficient of μs and the anisotropy factor g of a turbid target from one measured reflectance image. The incident beam was profiled with a diffuse reflectance standard for deriving both measured and calculated reflectance images. A GPU implemented Monte Carlo code was developed to determine the parameters with a conjugate gradient descent algorithm and the existence of unique solutions was shown. We noninvasively determined embedded region thickness in heterogeneous targets and estimated in vivo optical parameters of nevi from 4 patients between 500 and 950nm for melanoma diagnosis to demonstrate the potentials of quantitative reflectance imaging. PMID:29760971

High angular resolution diffusion imaging with stimulated echoes: compensation and correction in experiment design and analysis.

PubMed

Lundell, Henrik; Alexander, Daniel C; Dyrby, Tim B

2014-08-01

Stimulated echo acquisition mode (STEAM) diffusion MRI can be advantageous over pulsed-gradient spin-echo (PGSE) for diffusion times that are long compared with T2 . It therefore has potential for biomedical diffusion imaging applications at 7T and above where T2 is short. However, gradient pulses other than the diffusion gradients in the STEAM sequence contribute much greater diffusion weighting than in PGSE and lead to a disrupted experimental design. Here, we introduce a simple compensation to the STEAM acquisition that avoids the orientational bias and disrupted experiment design that these gradient pulses can otherwise produce. The compensation is simple to implement by adjusting the gradient vectors in the diffusion pulses of the STEAM sequence, so that the net effective gradient vector including contributions from diffusion and other gradient pulses is as the experiment intends. High angular resolution diffusion imaging (HARDI) data were acquired with and without the proposed compensation. The data were processed to derive standard diffusion tensor imaging (DTI) maps, which highlight the need for the compensation. Ignoring the other gradient pulses, a bias in DTI parameters from STEAM acquisition is found, due both to confounds in the analysis and the experiment design. Retrospectively correcting the analysis with a calculation of the full B matrix can partly correct for these confounds, but an acquisition that is compensated as proposed is needed to remove the effect entirely. © 2014 The Authors. NMR in Biomedicine published by John Wiley & Sons, Ltd.

A Simple Temperature Gradient Apparatus To Determine Thermal Preference in "Daphnia."

ERIC Educational Resources Information Center

Fenske, Christiane; McCauley, Robert

2002-01-01

Explores the dominant factor controlling the distribution of Daphnia. Describes components of a temperature gradient apparatus that can be assembled from materials readily obtainable in the laboratory and hardware stores. Investigates whether the mean depth of Daphnia is determined by temperature. (KHR)

Analysis and calculation by integral methods of laminar compressible boundary-layer with heat transfer and with and without pressure gradient

NASA Technical Reports Server (NTRS)

Morduchow, Morris

1955-01-01

A survey of integral methods in laminar-boundary-layer analysis is first given. A simple and sufficiently accurate method for practical purposes of calculating the properties (including stability) of the laminar compressible boundary layer in an axial pressure gradient with heat transfer at the wall is presented. For flow over a flat plate, the method is applicable for an arbitrarily prescribed distribution of temperature along the surface and for any given constant Prandtl number close to unity. For flow in a pressure gradient, the method is based on a Prandtl number of unity and a uniform wall temperature. A simple and accurate method of determining the separation point in a compressible flow with an adverse pressure gradient over a surface at a given uniform wall temperature is developed. The analysis is based on an extension of the Karman-Pohlhausen method to the momentum and the thermal energy equations in conjunction with fourth- and especially higher degree velocity and stagnation-enthalpy profiles.

Description of the computations and pilot procedures for planning fuel-conservative descents with a small programmable calculator

NASA Technical Reports Server (NTRS)

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

1983-01-01

A simplified flight management descent algorithm was developed and programmed on a small programmable calculator. It 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 algorithm may also be used for planning fuel conservative descents when time is not a consideration. 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 temperature effects. The flight management descent algorithm and the vertical performance modeling required for the DC-10 airplane is described.

Efficient and precise calculation of the b-matrix elements in diffusion-weighted imaging pulse sequences.

PubMed

Zubkov, Mikhail; Stait-Gardner, Timothy; Price, William S

2014-06-01

Precise NMR diffusion measurements require detailed knowledge of the cumulative dephasing effect caused by the numerous gradient pulses present in most NMR pulse sequences. This effect, which ultimately manifests itself as the diffusion-related NMR signal attenuation, is usually described by the b-value or the b-matrix in the case of multidirectional diffusion weighting, the latter being common in diffusion-weighted NMR imaging. Neglecting some of the gradient pulses introduces an error in the calculated diffusion coefficient reaching in some cases 100% of the expected value. Therefore, ensuring the b-matrix calculation includes all the known gradient pulses leads to significant error reduction. Calculation of the b-matrix for simple gradient waveforms is rather straightforward, yet it grows cumbersome when complexly shaped and/or numerous gradient pulses are introduced. Making three broad assumptions about the gradient pulse arrangement in a sequence results in an efficient framework for calculation of b-matrices as well providing some insight into optimal gradient pulse placement. The framework allows accounting for the diffusion-sensitising effect of complexly shaped gradient waveforms with modest computational time and power. This is achieved by using the b-matrix elements of the simple unmodified pulse sequence and minimising the integration of the complexly shaped gradient waveform in the modified sequence. Such re-evaluation of the b-matrix elements retains all the analytical relevance of the straightforward approach, yet at least halves the amount of symbolic integration required. The application of the framework is demonstrated with the evaluation of the expression describing the diffusion-sensitizing effect, caused by different bipolar gradient pulse modules. Copyright © 2014 Elsevier Inc. All rights reserved.

Spectral edge: gradient-preserving spectral mapping for image fusion.

PubMed

Connah, David; Drew, Mark S; Finlayson, Graham D

2015-12-01

This paper describes a novel approach to image fusion for color display. Our goal is to generate an output image whose gradient matches that of the input as closely as possible. We achieve this using a constrained contrast mapping paradigm in the gradient domain, where the structure tensor of a high-dimensional gradient representation is mapped exactly to that of a low-dimensional gradient field which is then reintegrated to form an output. Constraints on output colors are provided by an initial RGB rendering. Initially, we motivate our solution with a simple "ansatz" (educated guess) for projecting higher-D contrast onto color gradients, which we expand to a more rigorous theorem to incorporate color constraints. The solution to these constrained optimizations is closed-form, allowing for simple and hence fast and efficient algorithms. The approach can map any N-D image data to any M-D output and can be used in a variety of applications using the same basic algorithm. In this paper, we focus on the problem of mapping N-D inputs to 3D color outputs. We present results in five applications: hyperspectral remote sensing, fusion of color and near-infrared or clear-filter images, multilighting imaging, dark flash, and color visualization of magnetic resonance imaging diffusion-tensor imaging.

The Yearly Variation in Fall-Winter Arctic Winter Vortex Descent

NASA Technical Reports Server (NTRS)

Schoeberl, Mark R.; Newman, Paul A.

1999-01-01

Using the change in HALOE methane profiles from early September to late March, we have estimated the minimum amount of diabatic descent within the polar which takes place during Arctic winter. The year to year variations are a result in the year to year variations in stratospheric wave activity which (1) modify the temperature of the vortex and thus the cooling rate; (2) reduce the apparent descent by mixing high amounts of methane into the vortex. The peak descent amounts from HALOE methane vary from l0km -14km near the arrival altitude of 25 km. Using a diabatic trajectory calculation, we compare forward and backward trajectories over the course of the winter using UKMO assimilated stratospheric data. The forward calculation agrees fairly well with the observed descent. The backward calculation appears to be unable to produce the observed amount of descent, but this is only an apparent effect due to the density decrease in parcels with altitude. Finally we show the results for unmixed descent experiments - where the parcels are fixed in latitude and longitude and allowed to descend based on the local cooling rate. Unmixed descent is found to always exceed mixed descent, because when normal parcel motion is included, the path average cooling is always less than the cooling at a fixed polar point.

Automatic toilet seat lowering apparatus

DOEpatents

Guerty, Harold G.

1994-09-06

A toilet seat lowering apparatus includes a housing defining an internal cavity for receiving water from the water supply line to the toilet holding tank. A descent delay assembly of the apparatus can include a stationary dam member and a rotating dam member for dividing the internal cavity into an inlet chamber and an outlet chamber and controlling the intake and evacuation of water in a delayed fashion. A descent initiator is activated when the internal cavity is filled with pressurized water and automatically begins the lowering of the toilet seat from its upright position, which lowering is also controlled by the descent delay assembly. In an alternative embodiment, the descent initiator and the descent delay assembly can be combined in a piston linked to the rotating dam member and provided with a water channel for creating a resisting pressure to the advancing piston and thereby slowing the associated descent of the toilet seat. A toilet seat lowering apparatus includes a housing defining an internal cavity for receiving water from the water supply line to the toilet holding tank. A descent delay assembly of the apparatus can include a stationary dam member and a rotating dam member for dividing the internal cavity into an inlet chamber and an outlet chamber and controlling the intake and evacuation of water in a delayed fashion. A descent initiator is activated when the internal cavity is filled with pressurized water and automatically begins the lowering of the toilet seat from its upright position, which lowering is also controlled by the descent delay assembly. In an alternative embodiment, the descent initiator and the descent delay assembly can be combined in a piston linked to the rotating dam member and provided with a water channel for creating a resisting pressure to the advancing piston and thereby slowing the associated descent of the toilet seat.

Occurrence of Sporadic -E layer during the Low Solar Activity over the Anomaly Crest Region Bhopal, India

NASA Astrophysics Data System (ADS)

Bhawre, Purushottam

2016-07-01

Ionospheric anomaly crest regions are most challenging for scientific community to understand its mechanism and investigation, for this purpose we are investigating some inospheric result for this region. The study is based on the ionogram data recorded by IPS-71 Digital Ionosonde installed over anomaly crust region Bhopal (Geo.Lat.23.2° N, Geo. Long77.4° E, Dip latitude18.4°) over a four year period from January 2007 to December 2010, covering the ending phase of 23rd Solar Cycle and starting phase of 24th solar cycle. This particular period is felt to be very suitable for examining the sunspot number and it encompasses periods of low solar activities. Quarterly ionograms are analyzed for 24 hours during these study years and have been carefully examined to note down the presence of sporadic- E. We also note down the space weather activities along with the study. The studies are divided in mainly four parts with space and geomagnetic activities during these periods. The occurrence probability of this layer is highest in summer solstice, moderate during equinox and low during winter solstice. Remarkable occurrence peaks appear from June to July in summer and from December to January in winter. The layer occurrence showed a double peak variation with distinct layer groups, in the morning (0200 LT) and the other during evening (1800 LT).The morning layer descent was associated with layer density increase indicating the strengthening of the layer while it decreased during the evening layer descent. The result indicates the presence of semi-diurnal tide over the location while the higher descent velocities could be due to the modulation of the ionization by gravity waves along with the tides. The irregularities associated with the gradient-drift instability disappear during the counter electrojet and the current flow is reversed in westward.

A new approach to blind deconvolution of astronomical images

NASA Astrophysics Data System (ADS)

Vorontsov, S. V.; Jefferies, S. M.

2017-05-01

We readdress the strategy of finding approximate regularized solutions to the blind deconvolution problem, when both the object and the point-spread function (PSF) have finite support. Our approach consists in addressing fixed points of an iteration in which both the object x and the PSF y are approximated in an alternating manner, discarding the previous approximation for x when updating x (similarly for y), and considering the resultant fixed points as candidates for a sensible solution. Alternating approximations are performed by truncated iterative least-squares descents. The number of descents in the object- and in the PSF-space play a role of two regularization parameters. Selection of appropriate fixed points (which may not be unique) is performed by relaxing the regularization gradually, using the previous fixed point as an initial guess for finding the next one, which brings an approximation of better spatial resolution. We report the results of artificial experiments with noise-free data, targeted at examining the potential capability of the technique to deconvolve images of high complexity. We also show the results obtained with two sets of satellite images acquired using ground-based telescopes with and without adaptive optics compensation. The new approach brings much better results when compared with an alternating minimization technique based on positivity-constrained conjugate gradients, where the iterations stagnate when addressing data of high complexity. In the alternating-approximation step, we examine the performance of three different non-blind iterative deconvolution algorithms. The best results are provided by the non-negativity-constrained successive over-relaxation technique (+SOR) supplemented with an adaptive scheduling of the relaxation parameter. Results of comparable quality are obtained with steepest descents modified by imposing the non-negativity constraint, at the expense of higher numerical costs. The Richardson-Lucy (or expectation-maximization) algorithm fails to locate stable fixed points in our experiments, due apparently to inappropriate regularization properties.

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

NASA Astrophysics Data System (ADS)

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 benchmark FWI approach involving the standard gradient.

Planning fuel-conservative descents with or without time constraints using a small programmable calculator: Algorithm development and flight test results

NASA Technical Reports Server (NTRS)

Knox, C. E.

1983-01-01

A simplified flight-management descent algorithm, programmed on a small programmable calculator, was developed and flight tested. It 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 algorithm may also be used for planning fuel-conservative descents when time is not a consideration. 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 temperature effects. The flight-management descent algorithm is described. The results of flight tests flown with a T-39A (Sabreliner) airplane are presented.

Description of the computations and pilot procedures for planning fuel-conservative descents with a small programmable calculator

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

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

A simplified flight management descent algorithm was developed and programmed on a small programmable calculator. It 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 algorithm may also be used for planning fuel conservative descents when time is not a consideration. 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 temperature effects. The flight management descent algorithm and the vertical performance modelingmore » required for the DC-10 airplane is described.« less

Linear Subspace Ranking Hashing for Cross-Modal Retrieval.

PubMed

Li, Kai; Qi, Guo-Jun; Ye, Jun; Hua, Kien A

2017-09-01

Hashing has attracted a great deal of research in recent years due to its effectiveness for the retrieval and indexing of large-scale high-dimensional multimedia data. In this paper, we propose a novel ranking-based hashing framework that maps data from different modalities into a common Hamming space where the cross-modal similarity can be measured using Hamming distance. Unlike existing cross-modal hashing algorithms where the learned hash functions are binary space partitioning functions, such as the sign and threshold function, the proposed hashing scheme takes advantage of a new class of hash functions closely related to rank correlation measures which are known to be scale-invariant, numerically stable, and highly nonlinear. Specifically, we jointly learn two groups of linear subspaces, one for each modality, so that features' ranking orders in different linear subspaces maximally preserve the cross-modal similarities. We show that the ranking-based hash function has a natural probabilistic approximation which transforms the original highly discontinuous optimization problem into one that can be efficiently solved using simple gradient descent algorithms. The proposed hashing framework is also flexible in the sense that the optimization procedures are not tied up to any specific form of loss function, which is typical for existing cross-modal hashing methods, but rather we can flexibly accommodate different loss functions with minimal changes to the learning steps. We demonstrate through extensive experiments on four widely-used real-world multimodal datasets that the proposed cross-modal hashing method can achieve competitive performance against several state-of-the-arts with only moderate training and testing time.

New learning based super-resolution: use of DWT and IGMRF prior.

PubMed

Gajjar, Prakash P; Joshi, Manjunath V

2010-05-01

In this paper, we propose a new learning-based approach for super-resolving an image captured at low spatial resolution. Given the low spatial resolution test image and a database consisting of low and high spatial resolution images, we obtain super-resolution for the test image. We first obtain an initial high-resolution (HR) estimate by learning the high-frequency details from the available database. A new discrete wavelet transform (DWT) based approach is proposed for learning that uses a set of low-resolution (LR) images and their corresponding HR versions. Since the super-resolution is an ill-posed problem, we obtain the final solution using a regularization framework. The LR image is modeled as the aliased and noisy version of the corresponding HR image, and the aliasing matrix entries are estimated using the test image and the initial HR estimate. The prior model for the super-resolved image is chosen as an Inhomogeneous Gaussian Markov random field (IGMRF) and the model parameters are estimated using the same initial HR estimate. A maximum a posteriori (MAP) estimation is used to arrive at the cost function which is minimized using a simple gradient descent approach. We demonstrate the effectiveness of the proposed approach by conducting the experiments on gray scale as well as on color images. The method is compared with the standard interpolation technique and also with existing learning-based approaches. The proposed approach can be used in applications such as wildlife sensor networks, remote surveillance where the memory, the transmission bandwidth, and the camera cost are the main constraints.

Quantitative Analysis of Cancer Cell Migration in Gradients Of EGF, HGF, and SDF-alpha Using a Microfluidic Chemotaxis Device

DTIC Science & Technology

2005-01-01

Quantitative Analysis of Cancer Cell Migration in Gradients of EGF, HGF, and SDF-alpha Using a Microfluidic Chemotaxis Device The University of California...allowing for parallel analysis . Additionally, simple methods of localizing gels into microdevices are demonstrated. The device was characterized by...To overcome some of these drawbacks, several approaches have utilized free diffusion to produce gradients in static environ - ments.5-9 However

Simple computer method provides contours for radiological images

NASA Technical Reports Server (NTRS)

Newell, J. D.; Keller, R. A.; Baily, N. A.

1975-01-01

Computer is provided with information concerning boundaries in total image. Gradient of each point in digitized image is calculated with aid of threshold technique; then there is invoked set of algorithms designed to reduce number of gradient elements and to retain only major ones for definition of contour.

Strength gradient enhances fatigue resistance of steels

NASA Astrophysics Data System (ADS)

Ma, Zhiwei; Liu, Jiabin; Wang, Gang; Wang, Hongtao; Wei, Yujie; Gao, Huajian

2016-02-01

Steels are heavily used in infrastructure and the transportation industry, and enhancing their fatigue resistance is a major challenge in materials engineering. In this study, by introducing a gradient microstructure into 304 austenitic steel, which is one of the most widely used types of stainless steel, we show that a strength gradient substantially enhances the fatigue life of the material. Pre-notched samples with negative strength gradients in front of the notch’s tip endure many more fatigue cycles than do samples with positive strength gradients during the crack initiation stage, and samples with either type of gradient perform better than do gradient-free samples with the same average yield strength. However, as a crack grows, samples with positive strength gradients exhibit better resistance to fatigue crack propagation than do samples with negative gradients or no gradient. This study demonstrates a simple and promising strategy for using gradient structures to enhance the fatigue resistance of materials and complements related studies of strength and ductility.

Strength gradient enhances fatigue resistance of steels

PubMed Central

Ma, Zhiwei; Liu, Jiabin; Wang, Gang; Wang, Hongtao; Wei, Yujie; Gao, Huajian

2016-01-01

Steels are heavily used in infrastructure and the transportation industry, and enhancing their fatigue resistance is a major challenge in materials engineering. In this study, by introducing a gradient microstructure into 304 austenitic steel, which is one of the most widely used types of stainless steel, we show that a strength gradient substantially enhances the fatigue life of the material. Pre-notched samples with negative strength gradients in front of the notch’s tip endure many more fatigue cycles than do samples with positive strength gradients during the crack initiation stage, and samples with either type of gradient perform better than do gradient-free samples with the same average yield strength. However, as a crack grows, samples with positive strength gradients exhibit better resistance to fatigue crack propagation than do samples with negative gradients or no gradient. This study demonstrates a simple and promising strategy for using gradient structures to enhance the fatigue resistance of materials and complements related studies of strength and ductility. PMID:26907708

Validation of Genome-Wide Prostate Cancer Associations in Men of African Descent

PubMed Central

Chang, Bao-Li; Spangler, Elaine; Gallagher, Stephen; Haiman, Christopher A.; Henderson, Brian; Isaacs, William; Benford, Marnita L.; Kidd, LaCreis R.; Cooney, Kathleen; Strom, Sara; Ann Ingles, Sue; Stern, Mariana C.; Corral, Roman; Joshi, Amit D.; Xu, Jianfeng; Giri, Veda N.; Rybicki, Benjamin; Neslund-Dudas, Christine; Kibel, Adam S.; Thompson, Ian M.; Leach, Robin J.; Ostrander, Elaine A.; Stanford, Janet L.; Witte, John; Casey, Graham; Eeles, Rosalind; Hsing, Ann W.; Chanock, Stephen; Hu, Jennifer J.; John, Esther M.; Park, Jong; Stefflova, Klara; Zeigler-Johnson, Charnita; Rebbeck, Timothy R.

2010-01-01

Background Genome-wide association studies (GWAS) have identified numerous prostate cancer susceptibility alleles, but these loci have been identified primarily in men of European descent. There is limited information about the role of these loci in men of African descent. Methods We identified 7,788 prostate cancer cases and controls with genotype data for 47 GWAS-identified loci. Results We identified significant associations for SNP rs10486567 at JAZF1, rs10993994 at MSMB, rs12418451 and rs7931342 at 11q13, and rs5945572 and rs5945619 at NUDT10/11. These associations were in the same direction and of similar magnitude as those reported in men of European descent. Significance was attained at all report prostate cancer susceptibility regions at chromosome 8q24, including associations reaching genome-wide significance in region 2. Conclusion We have validated in men of African descent the associations at some, but not all, prostate cancer susceptibility loci originally identified in European descent populations. This may be due to heterogeneity in genetic etiology or in the pattern of genetic variation across populations. Impact The genetic etiology of prostate cancer in men of African descent differs from that of men of European descent. PMID:21071540

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

PubMed

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.

Floristic composition and across-track reflectance gradient in Landsat images over Amazonian forests

NASA Astrophysics Data System (ADS)

Muro, Javier; doninck, Jasper Van; Tuomisto, Hanna; Higgins, Mark A.; Moulatlet, Gabriel M.; Ruokolainen, Kalle

2016-09-01

Remotely sensed image interpretation or classification of tropical forests can be severely hampered by the effects of the bidirectional reflection distribution function (BRDF). Even for narrow swath sensors like Landsat TM/ETM+, the influence of reflectance anisotropy can be sufficiently strong to introduce a cross-track reflectance gradient. If the BRDF could be assumed to be linear for the limited swath of Landsat, it would be possible to remove this gradient during image preprocessing using a simple empirical method. However, the existence of natural gradients in reflectance caused by spatial variation in floristic composition of the forest can restrict the applicability of such simple corrections. Here we use floristic information over Peruvian and Brazilian Amazonia acquired through field surveys, complemented with information from geological maps, to investigate the interaction of real floristic gradients and the effect of reflectance anisotropy on the observed reflectances in Landsat data. In addition, we test the assumption of linearity of the BRDF for a limited swath width, and whether different primary non-inundated forest types are characterized by different magnitudes of the directional reflectance gradient. Our results show that a linear function is adequate to empirically correct for view angle effects, and that the magnitude of the across-track reflectance gradient is independent of floristic composition in the non-inundated forests we studied. This makes a routine correction of view angle effects possible. However, floristic variation complicates the issue, because different forest types have different mean reflectances. This must be taken into account when deriving the correction function in order to avoid eliminating natural gradients.

Recursive least-squares learning algorithms for neural networks

NASA Astrophysics Data System (ADS)

Lewis, Paul S.; Hwang, Jenq N.

1990-11-01

This paper presents the development of a pair of recursive least squares (ItLS) algorithms for online training of multilayer perceptrons which are a class of feedforward artificial neural networks. These algorithms incorporate second order information about the training error surface in order to achieve faster learning rates than are possible using first order gradient descent algorithms such as the generalized delta rule. A least squares formulation is derived from a linearization of the training error function. Individual training pattern errors are linearized about the network parameters that were in effect when the pattern was presented. This permits the recursive solution of the least squares approximation either via conventional RLS recursions or by recursive QR decomposition-based techniques. The computational complexity of the update is 0(N2) where N is the number of network parameters. This is due to the estimation of the N x N inverse Hessian matrix. Less computationally intensive approximations of the ilLS algorithms can be easily derived by using only block diagonal elements of this matrix thereby partitioning the learning into independent sets. A simulation example is presented in which a neural network is trained to approximate a two dimensional Gaussian bump. In this example RLS training required an order of magnitude fewer iterations on average (527) than did training with the generalized delta rule (6 1 BACKGROUND Artificial neural networks (ANNs) offer an interesting and potentially useful paradigm for signal processing and pattern recognition. The majority of ANN applications employ the feed-forward multilayer perceptron (MLP) network architecture in which network parameters are " trained" by a supervised learning algorithm employing the generalized delta rule (GDIt) [1 2]. The GDR algorithm approximates a fixed step steepest descent algorithm using derivatives computed by error backpropagatiori. The GDII algorithm is sometimes referred to as the backpropagation algorithm. However in this paper we will use the term backpropagation to refer only to the process of computing error derivatives. While multilayer perceptrons provide a very powerful nonlinear modeling capability GDR training can be very slow and inefficient. In linear adaptive filtering the analog of the GDR algorithm is the leastmean- squares (LMS) algorithm. Steepest descent-based algorithms such as GDR or LMS are first order because they use only first derivative or gradient information about the training error to be minimized. To speed up the training process second order algorithms may be employed that take advantage of second derivative or Hessian matrix information. Second order information can be incorporated into MLP training in different ways. In many applications especially in the area of pattern recognition the training set is finite. In these cases block learning can be applied using standard nonlinear optimization techniques [3 4 5].

Analysis of bacterial migration. 2: Studies with multiple attractant gradients

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

Strauss, I.; Frymier, P.D.; Hahn, C.M.

1995-02-01

Many motile bacteria exhibit chemotaxis, the ability to bias their random motion toward or away from increasing concentrations of chemical substances which benefit or inhibit their survival, respectively. Since bacteria encounter numerous chemical concentration gradients simultaneously in natural surroundings, it is necessary to know quantitatively how a bacterial population responds in the presence of more than one chemical stimulus to develop predictive mathematical models describing bacterial migration in natural systems. This work evaluates three hypothetical models describing the integration of chemical signals from multiple stimuli: high sensitivity, maximum signal, and simple additivity. An expression for the tumbling probability for individualmore » stimuli is modified according to the proposed models and incorporated into the cell balance equation for a 1-D attractant gradient. Random motility and chemotactic sensitivity coefficients, required input parameters for the model, are measured for single stimulus responses. Theoretical predictions with the three signal integration models are compared to the net chemotactic response of Escherichia coli to co- and antidirectional gradients of D-fucose and [alpha]-methylaspartate in the stopped-flow diffusion chamber assay. Results eliminate the high-sensitivity model and favor the simple additivity over the maximum signal. None of the simple models, however, accurately predict the observed behavior, suggesting a more complex model with more steps in the signal processing mechanism is required to predict responses to multiple stimuli.« less

Planning fuel-conservative descents with or without time constraints using a small programmable calculator: algorithm development and flight test results

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

Knox, C.E.

A simplified flight-management descent algorithm, programmed on a small programmable calculator, was developed and flight tested. It 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 algorithm may also be used for planning fuel-conservative descents when time is not a consideration. 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 temperature effects. The flight-management descent algorithm is described. The results of flight testsmore » flown with a T-39A (Sabreliner) airplane are presented.« less

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

PubMed

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 control group without symptoms. Three-dimensional endovaginal ultrasonography is a reliable technique for assessment of perineal descent. Using this technique, excessive perineal descent can be defined as displacement of the anorectal junction >1 cm and/or its position below the symphysis pubis on Valsalva maneuver.

Entry trajectory and atmosphere reconstruction methodologies for the Mars Exploration Rover mission

NASA Astrophysics Data System (ADS)

Desai, Prasun N.; Blanchard, Robert C.; Powell, Richard W.

2004-02-01

The Mars Exploration Rover (MER) mission will land two landers on the surface of Mars, arriving in January 2004. Both landers will deliver the rovers to the surface by decelerating with the aid of an aeroshell, a supersonic parachute, retro-rockets, and air bags for safely landing on the surface. The reconstruction of the MER descent trajectory and atmosphere profile will be performed for all the phases from hypersonic flight through landing. A description of multiple methodologies for the flight reconstruction is presented from simple parameter identification methods through a statistical Kalman filter approach.

Study of Chemotaxis and Cell–Cell Interactions in Cancer with Microfluidic Devices

PubMed Central

Sai, Jiqing; Rogers, Matthew; Hockemeyer, Kathryn; Wikswo, John P.; Richmond, Ann

2017-01-01

Microfluidic devices have very broad applications in biological assays from simple chemotaxis assays to much more complicated 3D bioreactors. In this chapter, we describe the design and methods for performing chemotaxis assays using simple microfluidic chemotaxis chambers. With these devices, using real-time video microscopy we can examine the chemotactic responses of neutrophil-like cells under conditions of varying gradient steepness or flow rate and then utilize software programs to calculate the speed and angles of cell migration as gradient steepness and flow are varied. Considering the shearing force generated on the cells by the constant flow that is required to produce and maintain a stable gradient, the trajectories of the cell migration will reflect the net result of both shear force generated by flow and the chemotactic force resulting from the chemokine gradient. Moreover, the effects of mutations in chemokine receptors or the presence of inhibitors of intracellular signals required for gradient sensing can be evaluated in real time. We also describe a method to monitor intracellular signals required for cells to alter cell polarity in response to an abrupt switch in gradient direction. Lastly, we demonstrate an in vitro method for studying the interactions of human cancer cells with human endothelial cells, fibroblasts, and leukocytes, as well as environmental chemokines and cytokines, using 3D microbioreactors that mimic the in vivo microenvironment. PMID:26921940

The role of boundary layer momentum advection in the mean location of the ITCZ

NASA Astrophysics Data System (ADS)

Dixit, Vishal; Srinivasan, J.

2017-08-01

The inter-tropical convergence zones (ITCZ) form closer to the equator during equinoxes while they form well away from the equator during the boreal summer. A simple three-way balance between the pressure gradients, Coriolis force and effective Rayleigh friction has been classically used to diagnose the location of maximum boundary layer convergence in the near equatorial ITCZ. If such a balance can capture the dynamics of off-equatorial convergence was not known. We used idealized aqua planet simulations with fixed, zonally symmetric sea surface temperature boundary conditions to simulate the near equatorial and off-equatorial ITCZ. As opposed to the convergence of inter-hemispheric flows in the near equatorial convergence, the off-equatorial convergence forms due to the deceleration of cross-equatorial meridional flow. The detailed momentum budget of the off-equatorial convergence zone reveals that the simple balance is not sufficient to capture the relevant dynamics. The deceleration of the meridional flow is strongly modulated by the inertial effects due to the meridional advection of zonal momentum in addition to the terms in the simple balance. The simple balance predicts a spurious near equatorial convergence and a consistent off-equatorial convergence of the meridional flow. The spurious convergence disappears when inertial effects are included in the balance. As cross equatorial meridional flow decelerates to form convergence, the inertial effects cancel the pressure gradient effects near the equator while they add away from the equator. The contribution to the off-equatorial convergence induced by the pressure gradients is significantly larger than the contribution due to the inertial effects and hence pressure gradients appear to be the primary factor in anchoring the strength and location of the off-equatorial convergence.

Transmit Designs for the MIMO Broadcast Channel With Statistical CSI

NASA Astrophysics Data System (ADS)

Wu, Yongpeng; Jin, Shi; Gao, Xiqi; McKay, Matthew R.; Xiao, Chengshan

2014-09-01

We investigate the multiple-input multiple-output broadcast channel with statistical channel state information available at the transmitter. The so-called linear assignment operation is employed, and necessary conditions are derived for the optimal transmit design under general fading conditions. Based on this, we introduce an iterative algorithm to maximize the linear assignment weighted sum-rate by applying a gradient descent method. To reduce complexity, we derive an upper bound of the linear assignment achievable rate of each receiver, from which a simplified closed-form expression for a near-optimal linear assignment matrix is derived. This reveals an interesting construction analogous to that of dirty-paper coding. In light of this, a low complexity transmission scheme is provided. Numerical examples illustrate the significant performance of the proposed low complexity scheme.

Sparse decomposition of seismic data and migration using Gaussian beams with nonzero initial curvature

NASA Astrophysics Data System (ADS)

Liu, Peng; Wang, Yanfei

2018-04-01

We study problems associated with seismic data decomposition and migration imaging. We first represent the seismic data utilizing Gaussian beam basis functions, which have nonzero curvature, and then consider the sparse decomposition technique. The sparse decomposition problem is an l0-norm constrained minimization problem. In solving the l0-norm minimization, a polynomial Radon transform is performed to achieve sparsity, and a fast gradient descent method is used to calculate the waveform functions. The waveform functions can subsequently be used for sparse Gaussian beam migration. Compared with traditional sparse Gaussian beam methods, the seismic data can be properly reconstructed employing fewer Gaussian beams with nonzero initial curvature. The migration approach described in this paper is more efficient than the traditional sparse Gaussian beam migration.

Taming the Wild: A Unified Analysis of Hogwild!-Style Algorithms.

PubMed

De Sa, Christopher; Zhang, Ce; Olukotun, Kunle; Ré, Christopher

2015-12-01

Stochastic gradient descent (SGD) is a ubiquitous algorithm for a variety of machine learning problems. Researchers and industry have developed several techniques to optimize SGD's runtime performance, including asynchronous execution and reduced precision. Our main result is a martingale-based analysis that enables us to capture the rich noise models that may arise from such techniques. Specifically, we use our new analysis in three ways: (1) we derive convergence rates for the convex case (Hogwild!) with relaxed assumptions on the sparsity of the problem; (2) we analyze asynchronous SGD algorithms for non-convex matrix problems including matrix completion; and (3) we design and analyze an asynchronous SGD algorithm, called Buckwild!, that uses lower-precision arithmetic. We show experimentally that our algorithms run efficiently for a variety of problems on modern hardware.

Object recognition in images via a factor graph model

NASA Astrophysics Data System (ADS)

He, Yong; Wang, Long; Wu, Zhaolin; Zhang, Haisu

2018-04-01

Object recognition in images suffered from huge search space and uncertain object profile. Recently, the Bag-of- Words methods are utilized to solve these problems, especially the 2-dimension CRF(Conditional Random Field) model. In this paper we suggest the method based on a general and flexible fact graph model, which can catch the long-range correlation in Bag-of-Words by constructing a network learning framework contrasted from lattice in CRF. Furthermore, we explore a parameter learning algorithm based on the gradient descent and Loopy Sum-Product algorithms for the factor graph model. Experimental results on Graz 02 dataset show that, the recognition performance of our method in precision and recall is better than a state-of-art method and the original CRF model, demonstrating the effectiveness of the proposed method.

Optimal landing of a helicopter in autorotation

NASA Technical Reports Server (NTRS)

Lee, A. Y. N.

1985-01-01

Gliding descent in autorotation is a maneuver used by helicopter pilots in case of engine failure. The landing of a helicopter in autorotation is formulated as a nonlinear optimal control problem. The OH-58A helicopter was used. Helicopter vertical and horizontal velocities, vertical and horizontal displacement, and the rotor angle speed were modeled. An empirical approximation for the induced veloctiy in the vortex-ring state were provided. The cost function of the optimal control problem is a weighted sum of the squared horizontal and vertical components of the helicopter velocity at touchdown. Optimal trajectories are calculated for entry conditions well within the horizontal-vertical restriction curve, with the helicopter initially in hover or forwared flight. The resultant two-point boundary value problem with path equality constraints was successfully solved using the Sequential Gradient Restoration Technique.

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

NASA Technical Reports Server (NTRS)

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.

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

PubMed

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

2013-01-21

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

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

NASA Astrophysics Data System (ADS)

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

2013-01-01

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

GPU-based stochastic-gradient optimization for non-rigid medical image registration in time-critical applications

NASA Astrophysics Data System (ADS)

Bhosale, Parag; Staring, Marius; Al-Ars, Zaid; Berendsen, Floris F.

2018-03-01

Currently, non-rigid image registration algorithms are too computationally intensive to use in time-critical applications. Existing implementations that focus on speed typically address this by either parallelization on GPU-hardware, or by introducing methodically novel techniques into CPU-oriented algorithms. Stochastic gradient descent (SGD) optimization and variations thereof have proven to drastically reduce the computational burden for CPU-based image registration, but have not been successfully applied in GPU hardware due to its stochastic nature. This paper proposes 1) NiftyRegSGD, a SGD optimization for the GPU-based image registration tool NiftyReg, 2) random chunk sampler, a new random sampling strategy that better utilizes the memory bandwidth of GPU hardware. Experiments have been performed on 3D lung CT data of 19 patients, which compared NiftyRegSGD (with and without random chunk sampler) with CPU-based elastix Fast Adaptive SGD (FASGD) and NiftyReg. The registration runtime was 21.5s, 4.4s and 2.8s for elastix-FASGD, NiftyRegSGD without, and NiftyRegSGD with random chunk sampling, respectively, while similar accuracy was obtained. Our method is publicly available at https://github.com/SuperElastix/NiftyRegSGD.

Medial-based deformable models in nonconvex shape-spaces for medical image segmentation.

PubMed

McIntosh, Chris; Hamarneh, Ghassan

2012-01-01

We explore the application of genetic algorithms (GA) to deformable models through the proposition of a novel method for medical image segmentation that combines GA with nonconvex, localized, medial-based shape statistics. We replace the more typical gradient descent optimizer used in deformable models with GA, and the convex, implicit, global shape statistics with nonconvex, explicit, localized ones. Specifically, we propose GA to reduce typical deformable model weaknesses pertaining to model initialization, pose estimation and local minima, through the simultaneous evolution of a large number of models. Furthermore, we constrain the evolution, and thus reduce the size of the search-space, by using statistically-based deformable models whose deformations are intuitive (stretch, bulge, bend) and are driven in terms of localized principal modes of variation, instead of modes of variation across the entire shape that often fail to capture localized shape changes. Although GA are not guaranteed to achieve the global optima, our method compares favorably to the prevalent optimization techniques, convex/nonconvex gradient-based optimizers and to globally optimal graph-theoretic combinatorial optimization techniques, when applied to the task of corpus callosum segmentation in 50 mid-sagittal brain magnetic resonance images.

Image counter-forensics based on feature injection

NASA Astrophysics Data System (ADS)

Iuliani, M.; Rossetto, S.; Bianchi, T.; De Rosa, Alessia; Piva, A.; Barni, M.

2014-02-01

Starting from the concept that many image forensic tools are based on the detection of some features revealing a particular aspect of the history of an image, in this work we model the counter-forensic attack as the injection of a specific fake feature pointing to the same history of an authentic reference image. We propose a general attack strategy that does not rely on a specific detector structure. Given a source image x and a target image y, the adversary processes x in the pixel domain producing an attacked image ~x, perceptually similar to x, whose feature f(~x) is as close as possible to f(y) computed on y. Our proposed counter-forensic attack consists in the constrained minimization of the feature distance Φ(z) =│ f(z) - f(y)│ through iterative methods based on gradient descent. To solve the intrinsic limit due to the numerical estimation of the gradient on large images, we propose the application of a feature decomposition process, that allows the problem to be reduced into many subproblems on the blocks the image is partitioned into. The proposed strategy has been tested by attacking three different features and its performance has been compared to state-of-the-art counter-forensic methods.

Efficient Online Learning Algorithms Based on LSTM Neural Networks.

PubMed

Ergen, Tolga; Kozat, Suleyman Serdar

2017-09-13

We investigate online nonlinear regression and introduce novel regression structures based on the long short term memory (LSTM) networks. For the introduced structures, we also provide highly efficient and effective online training methods. To train these novel LSTM-based structures, we put the underlying architecture in a state space form and introduce highly efficient and effective particle filtering (PF)-based updates. We also provide stochastic gradient descent and extended Kalman filter-based updates. Our PF-based training method guarantees convergence to the optimal parameter estimation in the mean square error sense provided that we have a sufficient number of particles and satisfy certain technical conditions. More importantly, we achieve this performance with a computational complexity in the order of the first-order gradient-based methods by controlling the number of particles. Since our approach is generic, we also introduce a gated recurrent unit (GRU)-based approach by directly replacing the LSTM architecture with the GRU architecture, where we demonstrate the superiority of our LSTM-based approach in the sequential prediction task via different real life data sets. In addition, the experimental results illustrate significant performance improvements achieved by the introduced algorithms with respect to the conventional methods over several different benchmark real life data sets.

Why do disk galaxies present a common gas-phase metallicity gradient?

NASA Astrophysics Data System (ADS)

Chang, R.; Zhang, Shuhui; Shen, Shiyin; Yin, Jun; Hou, Jinliang

2017-03-01

CALIFA data show that isolated disk galaxies present a common gas-phase metallicity gradient, with a characteristic slope of -0.1dex/re between 0.3 and 2 disk effective radius re (Sanchez et al. 2014). Here we construct a simple model to investigate which processes regulate the formation and evolution.

HPLC of the Polypeptides in a Hydrolyzate of Egg-White Lysozyme. An Experiment for the Undergraduate Biochemistry Laboratory.

ERIC Educational Resources Information Center

Richardson, W. S., III; Burns, L.

1988-01-01

Describes a simple high-performance liquid chromatography experiment for undergraduate biochemistry laboratories. The experiment illustrates the separation of polypeptides by a step gradient elution using a single pump instrument with no gradient attachments. Discusses instrumentation, analysis, a sample preparation, and results. (CW)

A study of progress of labour using intrapartum translabial ultrasound, assessing head station, direction, and angle of descent.

PubMed

Tutschek, B; Braun, T; Chantraine, F; Henrich, W

2011-01-01

Intrapartum translabial ultrasound (ITU) has the potential to objectively and quantitatively assess the progress of labour. The relationships between the different ITU parameters and their development during normal term labour have not been studied. Observational study. University teaching hospital. Labouring women with normal term fetuses in cephalic presentation. Intrapartum translabial ultrasound measurements for 'head station', 'head direction', and 'angle of descent' (AoD) were taken in 50 labouring women, compared, studied for repeatability, and correlated with the progress of labour. Reproducibility and correlation of ITU parameters and their pattern of changes during labour. All three ITU parameters were clinically well reproducible. AoD and head station were interchangeable, and could be calculated from each other. Head station and head direction changed in a typical pattern along the birth canal. Time to delivery correlated with ITU head station. Intrapartum translabial ultrasound is a simple technique that improves the understanding of normal and abnormal labour, enables the objective measurement of birth progress and provides a more scientific basis for assessing labour. © 2010 The Authors Journal compilation © RCOG 2010 BJOG An International Journal of Obstetrics and Gynaecology.

Axial compartmentation of descending and ascending thin limbs of Henle's loops

PubMed Central

Westrick, Kristen Y.; Serack, Bradley; Dantzler, William H.

2013-01-01

In the inner medulla, radial organization of nephrons and blood vessels around collecting duct (CD) clusters leads to two lateral interstitial regions and preferential intersegmental fluid and solute flows. As the descending (DTLs) and ascending thin limbs (ATLs) pass through these regions, their transepithelial fluid and solute flows are influenced by variable transepithelial solute gradients and structure-to-structure interactions. The goal of this study was to quantify structure-to-structure interactions, so as to better understand compartmentation and flows of transepithelial water, NaCl, and urea and generation of the axial osmotic gradient. To accomplish this, we determined lateral distances of AQP1-positive and AQP1-negative DTLs and ATLs from their nearest CDs, so as to gauge interactions with intercluster and intracluster lateral regions and interactions with interstitial nodal spaces (INSs). DTLs express reduced AQP1 and low transepithelial water permeability along their deepest segments. Deep AQP1-null segments, prebend segments, and ATLs lie equally near to CDs. Prebend segments and ATLs abut CDs and INSs throughout much of their descent and ascent, respectively; however, the distal 30% of ATLs of the longest loops lie distant from CDs as they approach the outer medullary boundary and have minimal interaction with INSs. These relationships occur regardless of loop length. Finally, we show that ascending vasa recta separate intercluster AQP1-positive DTLs from descending vasa recta, thereby minimizing dilution of gradients that drive solute secretion. We hypothesize that DTLs and ATLs enter and exit CD clusters in an orchestrated fashion that is important for generation of the corticopapillary solute gradient by minimizing NaCl and urea loss. PMID:23195680

Axial compartmentation of descending and ascending thin limbs of Henle's loops.

PubMed

Westrick, Kristen Y; Serack, Bradley; Dantzler, William H; Pannabecker, Thomas L

2013-02-01

In the inner medulla, radial organization of nephrons and blood vessels around collecting duct (CD) clusters leads to two lateral interstitial regions and preferential intersegmental fluid and solute flows. As the descending (DTLs) and ascending thin limbs (ATLs) pass through these regions, their transepithelial fluid and solute flows are influenced by variable transepithelial solute gradients and structure-to-structure interactions. The goal of this study was to quantify structure-to-structure interactions, so as to better understand compartmentation and flows of transepithelial water, NaCl, and urea and generation of the axial osmotic gradient. To accomplish this, we determined lateral distances of AQP1-positive and AQP1-negative DTLs and ATLs from their nearest CDs, so as to gauge interactions with intercluster and intracluster lateral regions and interactions with interstitial nodal spaces (INSs). DTLs express reduced AQP1 and low transepithelial water permeability along their deepest segments. Deep AQP1-null segments, prebend segments, and ATLs lie equally near to CDs. Prebend segments and ATLs abut CDs and INSs throughout much of their descent and ascent, respectively; however, the distal 30% of ATLs of the longest loops lie distant from CDs as they approach the outer medullary boundary and have minimal interaction with INSs. These relationships occur regardless of loop length. Finally, we show that ascending vasa recta separate intercluster AQP1-positive DTLs from descending vasa recta, thereby minimizing dilution of gradients that drive solute secretion. We hypothesize that DTLs and ATLs enter and exit CD clusters in an orchestrated fashion that is important for generation of the corticopapillary solute gradient by minimizing NaCl and urea loss.

Effects of flutamide and finasteride on rat testicular descent.

PubMed

Spencer, J R; Torrado, T; Sanchez, R S; Vaughan, E D; Imperato-McGinley, J

1991-08-01

The endocrine control of descent of the testis in mammalian species is poorly understood. The androgen dependency of testicular descent was studied in the rat using an antiandrogen (flutamide) and an inhibitor of the enzyme 5 alpha-reductase (finasteride). Androgen receptor blockade inhibited testicular descent more effectively than inhibition of 5 alpha-reductase activity. Moreover, its inhibitory effect was limited to the outgrowth phase of the gubernaculum testis, particularly the earliest stages of outgrowth. Gubernacular size was also significantly reduced in fetuses exposed to flutamide during the outgrowth period. In contrast, androgen receptor blockade or 5 alpha-reductase inhibition applied after the initiation of gubernacular outgrowth or during the regression phase did not affect testicular descent. Successful inhibition of the development of epididymis and vas by prenatal flutamide did not correlate with ipsilateral testicular maldescent, suggesting that an intact epididymis is not required for descent of the testis. Plasma androgen assays confirmed significant inhibition of dihydrotestosterone formation in finasteride-treated rats. These data suggest that androgens, primarily testosterone, are required during the early phases of gubernacular outgrowth for subsequent successful completion of testicular descent.

Enhancement of orientation gradients during simple shear deformation by application of simple compression

NASA Astrophysics Data System (ADS)

Jahedi, Mohammad; Ardeljan, Milan; Beyerlein, Irene J.; Paydar, Mohammad Hossein; Knezevic, Marko

2015-06-01

We use a multi-scale, polycrystal plasticity micromechanics model to study the development of orientation gradients within crystals deforming by slip. At the largest scale, the model is a full-field crystal plasticity finite element model with explicit 3D grain structures created by DREAM.3D, and at the finest scale, at each integration point, slip is governed by a dislocation density based hardening law. For deformed polycrystals, the model predicts intra-granular misorientation distributions that follow well the scaling law seen experimentally by Hughes et al., Acta Mater. 45(1), 105-112 (1997), independent of strain level and deformation mode. We reveal that the application of a simple compression step prior to simple shearing significantly enhances the development of intra-granular misorientations compared to simple shearing alone for the same amount of total strain. We rationalize that the changes in crystallographic orientation and shape evolution when going from simple compression to simple shearing increase the local heterogeneity in slip, leading to the boost in intra-granular misorientation development. In addition, the analysis finds that simple compression introduces additional crystal orientations that are prone to developing intra-granular misorientations, which also help to increase intra-granular misorientations. Many metal working techniques for refining grain sizes involve a preliminary or concurrent application of compression with severe simple shearing. Our finding reveals that a pre-compression deformation step can, in fact, serve as another processing variable for improving the rate of grain refinement during the simple shearing of polycrystalline metals.

Blocking, descent and gravity waves: Observations and modelling of a MAP northerly föhn event

NASA Astrophysics Data System (ADS)

Jiang, Qingfang; Doyle, James D.; Smith, Ronald B.

2005-01-01

A northerly föhn event observed during the special observational period of the Mesoscale Alpine Programme is investigated based on observational analysis and numerical modelling. The focus of this study includes three dynamical processes associated with mountain perturbations and their interactions, namely, windward flow blocking, descent and warming on the lee side, and mountain waves. Observations indicate the presence of a deep weak-flow layer underneath a stable layer, associated with Alpine-scale blocking. Satellite imagery reveals a föhninduced cloud-free area to the south of the Alps, which is consistent with flow descent diagnosed from radiosondes and constant-volume balloons. Moderate-amplitude stationary waves were observed by research aircraft over the major Alpine peaks. Satellite images and balloon data indicate the presence of stationary trapped-wave patterns located to the north of the Alpine massif.Satisfactory agreement is found between observations and a real-data COAMPS simulation nested to 1 km resolution. COAMPS indicates the presence of trapped waves associated with a sharp decrease of Scorer parameter above a stable layer in the mid-troposphere. Underneath the stable layer, moist low-level flow is blocked to the north of the Alps. The warm air in the stable layer descends in the lee and recovers its altitude over a relatively short horizontal distance through a hydraulic jump.Blocking reduces the effective mountain and hence significantly reduces mountain drag. A simple empirical formula for estimation of the effective mountain height, he, is derived based on numerical simulations. The formula states he/hc = (h/hc), where h is the real mountain height and hc is the critical mountain height to have flow stagnation.

Sagittal MRI often overestimates the degree of cerebellar tonsillar ectopia: a potential for misdiagnosis of the Chiari I malformation.

PubMed

Tubbs, R Shane; Yan, Huang; Demerdash, Amin; Chern, Joshua J; Fries, Fabian N; Oskouian, Rod J; Oakes, W Jerry

2016-07-01

We hypothesized that by using coronal MRI, Chiari I malformation could be more precisely diagnosed, would provide simple anatomic landmarks, would provide information regarding asymmetry of hindbrain herniation, and would be a better method for analyzing the tonsillar herniation postoperatively when the opisthion has been removed. Fifty consecutive pediatric patients diagnosed with Chiari I malformation had comparison between the measurements of their caudally descended cerebellar tonsils on midsagittal and coronal MRI images. On MRI coronal imaging, tonsillar asymmetry was found in 48 patients. Maximal left tonsillar descent was 20.9 mm, and maximal right tonsillar descent was 17.4 mm. On MRI sagittal imaging, tonsillar descent ranged from 5 to 27.4 mm. Fifty-eight % of patients had syringomyelia. Five patients (10 %) on coronal MRI were found to have both cerebellar tonsils that were less than 3 mm below the foramen magnum. However, all of these patients had greater than 3 mm of tonsillar ectopia on sagittal imaging. Nineteen patients (38 %) on coronal MRI were found to have one of the cerebellar tonsils that were less than 3 mm below the foramen magnum. Similarly, each of these had greater than 3 mm of tonsillar ecotpia as measured on midsagittal MRI. Also, based on these findings, Chiari I malformation is almost always an asymmetrical tonsillar ectopia. Sagittal MRI overestimates the degree of tonsillar ectopia in patients with Chiari I malformation. Misdiagnosis may occur if sagittal imaging alone is used. The cerebellar tonsils are paramedian structures, and this should be kept in mind when interpreting midline sagittal MRI.

The evolving approach to the evaluation of low-gradient aortic stenosis.

PubMed

Cutting, William B; Bavry, Anthony A

2018-04-07

Severe aortic stenosis (AS) is typically identified by a low valve area (≤1.0 cm 2 ) and high mean gradient (≥40 mm Hg). A subset of patients are found to have a less than severe mean gradient (<40 mm Hg) despite a low valve area. These latter types can present as either low ejection fraction with low-gradient AS (stage D2) or normal ejection fraction with low-gradient AS (stage D3). Determining the true severity of disease within these categories has proved difficult. In this review we illustrate both traditional and novel techniques that can be used for further valvular assessment. We also propose a simple algorithm that can be used to evaluate low-gradient AS. Published by Elsevier Inc.

Testicular descent related to growth hormone treatment.

PubMed

Papadimitriou, Anastasios; Fountzoula, Ioanna; Grigoriadou, Despina; Christianakis, Stratos; Tzortzatou, Georgia

2003-01-01

An 8.7 year-old boy with cryptorchidism and growth hormone (GH) deficiency due to septooptic dysplasia presented testicular descent related to the commencement of hGH treatment. This case suggests a role for GH in testicular descent.

Aircraft Vortex Wake Descent and Decay under Real Atmospheric Effects

DOT National Transportation Integrated Search

1973-10-01

Aircraft vortex wake descent and decay in a real atmosphere is studied analytically. Factors relating to encounter hazard, wake generation, wake descent and stability, and atmospheric dynamics are considered. Operational equations for encounter hazar...

Computational and theoretical investigation of Mars's atmospheric impact on the descent module "Exomars-2018" under aerodynamic deceleration

NASA Astrophysics Data System (ADS)

Golomazov, M. M.; Ivankov, A. A.

2016-12-01

Methods for calculating the aerodynamic impact of the Martian atmosphere on the descent module "Exomars-2018" intended for solving the problem of heat protection of the descent module during aerodynamic deceleration are presented. The results of the investigation are also given. The flow field and radiative and convective heat exchange are calculated along the trajectory of the descent module until parachute system activation.

Apollo lunar descent guidance

NASA Technical Reports Server (NTRS)

Klumpp, A. R.

1974-01-01

Apollo lunar-descent guidance transfers the Lunar Module from a near-circular orbit to touchdown, traversing a 17 deg central angle and a 15 km altitude in 11 min. A group of interactive programs in an onboard computer guide the descent, controlling altitude and the descent propulsion system throttle. A ground-based program pre-computes guidance targets. The concepts involved in this guidance are described. Explicit and implicit guidance are discussed, guidance equations are derived, and the earlier Apollo explicit equation is shown to be an inferior special case of the later implicit equation. Interactive guidance, by which the two-man crew selects a landing site in favorable terrain and directs the trajectory there, is discussed. Interactive terminal-descent guidance enables the crew to control the essentially vertical descent rate in order to land in minimum time with safe contact speed. The altitude maneuver routine uses concepts that make gimbal lock inherently impossible.

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

NASA Technical Reports Server (NTRS)

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.

Comparison of Alcator C data with the Rebut-Lallia-Watkins critical gradient scaling

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

Hutchinson, I.H.

The critical temperature gradient model of Rebut, Lallia and Watkins is compared with data from Alcator C. The predicted central electron temperature is derived from the model, and a simple analytic formula is given. It is found to be in quite good agreement with the observed temperatures on Alcator C under ohmic heating conditions. However, the thermal diffusivity postulated in the model for gradients that exceed the critical is not consistent with the observed electron heating by Lower Hybrid waves.

The effect of density gradients on hydrometers

NASA Astrophysics Data System (ADS)

Heinonen, Martti; Sillanpää, Sampo

2003-05-01

Hydrometers are simple but effective instruments for measuring the density of liquids. In this work, we studied the effect of non-uniform density of liquid on a hydrometer reading. The effect induced by vertical temperature gradients was investigated theoretically and experimentally. A method for compensating for the effect mathematically was developed and tested with experimental data obtained with the MIKES hydrometer calibration system. In the tests, the method was found reliable. However, the reliability depends on the available information on the hydrometer dimensions and density gradients.

Shocks and metallicity gradients in normal star-forming galaxies

NASA Astrophysics Data System (ADS)

Ho, I.-Ting

Gas flow is one of the most fundamental processes driving galaxy evolution. This thesis explores gas flows in local galaxies by studying metallicity gradients and galactic-scale outflows in normal star-forming galaxies. This is made possible by new integral field spectroscopy data that provide simultaneously spatial and spectral information of galaxies. First, I measure metallicity gradients in isolated disk galaxies and show that their metallicity gradients are remarkably simple and universal. When the metallicity gradients are normalized to galaxy sizes, all the 49 galaxies studied have virtually the same metallicity gradient. I model the common metallicity gradient using a simple chemical evolution model to understand its origin. The common metallicity gradient is a direct result of the coevolution of gas and stellar disk while galactic disks build up their masses from inside-out. Tight constraints on the mass outflow rates and inflow rates can be placed by the chemical evolution model. Second, I investigate galactic winds in normal star-forming galaxies using data from an integral field spectroscopy survey. I demonstrate how to search for galactic winds by probing emission line ratios, shocks, and gas kinematics. Galactic winds are found to be common even in normal star-forming galaxies that were not expected to host winds. By comparing galaxies with and without hosting winds, I show that galaxies with high star formation rate surface densities and bursty star formation histories are more likely to drive large-scale galactic winds. Finally, lzifu, a toolkit for fitting multiple emission lines simultaneously in integral field spectroscopy data, is developed in this thesis. I describe in detail the structure of the toolkit and demonstrate the capabilities of lzifu.

Directed transport by surface chemical potential gradients for enhancing analyte collection in nanoscale sensors.

PubMed

Sitt, Amit; Hess, Henry

2015-05-13

Nanoscale detectors hold great promise for single molecule detection and the analysis of small volumes of dilute samples. However, the probability of an analyte reaching the nanosensor in a dilute solution is extremely low due to the sensor's small size. Here, we examine the use of a chemical potential gradient along a surface to accelerate analyte capture by nanoscale sensors. Utilizing a simple model for transport induced by surface binding energy gradients, we study the effect of the gradient on the efficiency of collecting nanoparticles and single and double stranded DNA. The results indicate that chemical potential gradients along a surface can lead to an acceleration of analyte capture by several orders of magnitude compared to direct collection from the solution. The improvement in collection is limited to a relatively narrow window of gradient slopes, and its extent strongly depends on the size of the gradient patch. Our model allows the optimization of gradient layouts and sheds light on the fundamental characteristics of chemical potential gradient induced transport.

B1 gradient coherence selection using a tapered stripline.

PubMed

van Meerten, S G J; Tijssen, K C H; van Bentum, P J M; Kentgens, A P M

2018-01-01

Pulsed-field gradients are common in modern liquid state NMR pulse sequences. They are often used instead of phase cycles for the selection of coherence pathways, thereby decreasing the time required for the NMR experiment. Soft off-resonance pulses with a B 1 gradient result in a spatial encoding similar to that created by pulsed-field (B 0 ) gradients. In this manuscript we show that pulse sequences with pulsed-field gradients can easily be converted to one which uses off-resonance B 1 field gradient (OFFBEAT) pulses. The advantage of B 1 gradient pulses for coherence selection is that the chemical shift evolution during the pulses is (partially) suppressed. Therefore no refocusing echos are required to correct for evolution during the gradient pulses. A tapered stripline is shown to be a convenient tool for creating a well-defined gradient in the B 1 field strength. B 1 gradient coherence selection using a tapered stripline is a simple and cheap alternative to B 0 pulsed-field gradients. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

On the modeling of breath-by-breath oxygen uptake kinetics at the onset of high-intensity exercises: simulated annealing vs. GRG2 method.

PubMed

Bernard, Olivier; Alata, Olivier; Francaux, Marc

2006-03-01

Modeling in the time domain, the non-steady-state O2 uptake on-kinetics of high-intensity exercises with empirical models is commonly performed with gradient-descent-based methods. However, these procedures may impair the confidence of the parameter estimation when the modeling functions are not continuously differentiable and when the estimation corresponds to an ill-posed problem. To cope with these problems, an implementation of simulated annealing (SA) methods was compared with the GRG2 algorithm (a gradient-descent method known for its robustness). Forty simulated Vo2 on-responses were generated to mimic the real time course for transitions from light- to high-intensity exercises, with a signal-to-noise ratio equal to 20 dB. They were modeled twice with a discontinuous double-exponential function using both estimation methods. GRG2 significantly biased two estimated kinetic parameters of the first exponential (the time delay td1 and the time constant tau1) and impaired the precision (i.e., standard deviation) of the baseline A0, td1, and tau1 compared with SA. SA significantly improved the precision of the three parameters of the second exponential (the asymptotic increment A2, the time delay td2, and the time constant tau2). Nevertheless, td2 was significantly biased by both procedures, and the large confidence intervals of the whole second component parameters limit their interpretation. To compare both algorithms on experimental data, 26 subjects each performed two transitions from 80 W to 80% maximal O2 uptake on a cycle ergometer and O2 uptake was measured breath by breath. More than 88% of the kinetic parameter estimations done with the SA algorithm produced the lowest residual sum of squares between the experimental data points and the model. Repeatability coefficients were better with GRG2 for A1 although better with SA for A2 and tau2. Our results demonstrate that the implementation of SA improves significantly the estimation of most of these kinetic parameters, but a large inaccuracy remains in estimating the parameter values of the second exponential.

Shape regularized active contour based on dynamic programming for anatomical structure segmentation

NASA Astrophysics Data System (ADS)

Yu, Tianli; Luo, Jiebo; Singhal, Amit; Ahuja, Narendra

2005-04-01

We present a method to incorporate nonlinear shape prior constraints into segmenting different anatomical structures in medical images. Kernel space density estimation (KSDE) is used to derive the nonlinear shape statistics and enable building a single model for a class of objects with nonlinearly varying shapes. The object contour is coerced by image-based energy into the correct shape sub-distribution (e.g., left or right lung), without the need for model selection. In contrast to an earlier algorithm that uses a local gradient-descent search (susceptible to local minima), we propose an algorithm that iterates between dynamic programming (DP) and shape regularization. DP is capable of finding an optimal contour in the search space that maximizes a cost function related to the difference between the interior and exterior of the object. To enforce the nonlinear shape prior, we propose two shape regularization methods, global and local regularization. Global regularization is applied after each DP search to move the entire shape vector in the shape space in a gradient descent fashion to the position of probable shapes learned from training. The regularized shape is used as the starting shape for the next iteration. Local regularization is accomplished through modifying the search space of the DP. The modified search space only allows a certain amount of deformation of the local shape from the starting shape. Both regularization methods ensure the consistency between the resulted shape with the training shapes, while still preserving DP"s ability to search over a large range and avoid local minima. Our algorithm was applied to two different segmentation tasks for radiographic images: lung field and clavicle segmentation. Both applications have shown that our method is effective and versatile in segmenting various anatomical structures under prior shape constraints; and it is robust to noise and local minima caused by clutter (e.g., blood vessels) and other similar structures (e.g., ribs). We believe that the proposed algorithm represents a major step in the paradigm shift to object segmentation under nonlinear shape constraints.

Convection driven generation of long-range material gradients

PubMed Central

Du, Yanan; Hancock, Matthew J.; He, Jiankang; Villa-Uribe, Jose; Wang, Ben; Cropek, Donald M.; Khademhosseini, Ali

2009-01-01

Natural materials exhibit anisotropy with variations in soluble factors, cell distribution, and matrix properties. The ability to recreate the heterogeneity of the natural materials is a major challenge for investigating cell-material interactions and for developing biomimetic materials. Here we present a generic fluidic approach using convection and alternating flow to rapidly generate multi-centimeter gradients of biomolecules, polymers, beads and cells and cross-gradients of two species in a microchannel. Accompanying theoretical estimates and simulations of gradient growth provide design criteria over a range of material properties. A poly(ethyleneglycol) hydrogel gradient, a porous collagen gradient and a composite material with a hyaluronic acid/gelatin cross-gradient were generated with continuous variations in material properties and in their ability to regulate cellular response. This simple yet generic fluidic platform should prove useful for creating anisotropic biomimetic materials and high-throughput platforms for investigating cell-microenvironment interaction. PMID:20035990

Evaluation of vertical profiles to design continuous descent approach procedure

NASA Astrophysics Data System (ADS)

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 uncertainties in external factors. Analysis from operational feasibility perspective suggests that two key features of the performance based Flight Management System (FMS) i.e. required time of arrival (RTA) and geometric descent path would help in reduction of unpredictability associated with arrival time and vertical profile of aircraft guided by the FMS coupled with auto-pilot (AP) and auto-throttle (AT). The statistical analysis of the vertical profiles of CDA also suggests that for procedure design window type, 'AT or above' and 'AT or below' altitude and FPA constraints are more realistic and useful compared to obsolete 'AT' type altitude constraint.

Tunable electronic lens using a gradient polymer network liquid crystal

NASA Astrophysics Data System (ADS)

Ren, Hongwen; Wu, Shin-Tson

2003-01-01

Tunable electronic lenses using gradient polymer network liquid crystal (PNLC) cells were demonstrated. By changing the photomask pattern, both positive and negative lenses were fabricated. The advantages of such a PNLC lens are low operation voltage, large aperture size, and simple electrode design. To overcome the polarization dependence, stacking two orthogonal homogeneous PNLC cells is considered.

A Descent Rate Control Approach to Developing an Autonomous Descent Vehicle

NASA Astrophysics Data System (ADS)

Fields, Travis D.

Circular parachutes have been used for aerial payload/personnel deliveries for over 100 years. In the past two decades, significant work has been done to improve the landing accuracies of cargo deliveries for humanitarian and military applications. This dissertation discusses the approach developed in which a circular parachute is used in conjunction with an electro-mechanical reefing system to manipulate the landing location. Rather than attempt to steer the autonomous descent vehicle directly, control of the landing location is accomplished by modifying the amount of time spent in a particular wind layer. Descent rate control is performed by reversibly reefing the parachute canopy. The first stage of the research investigated the use of a single actuation during descent (with periodic updates), in conjunction with a curvilinear target. Simulation results using real-world wind data are presented, illustrating the utility of the methodology developed. Additionally, hardware development and flight-testing of the single actuation autonomous descent vehicle are presented. The next phase of the research focuses on expanding the single actuation descent rate control methodology to incorporate a multi-actuation path-planning system. By modifying the parachute size throughout the descent, the controllability of the system greatly increases. The trajectory planning methodology developed provides a robust approach to accurately manipulate the landing location of the vehicle. The primary benefits of this system are the inherent robustness to release location errors and the ability to overcome vehicle uncertainties (mass, parachute size, etc.). A separate application of the path-planning methodology is also presented. An in-flight path-prediction system was developed for use in high-altitude ballooning by utilizing the path-planning methodology developed for descent vehicles. The developed onboard system improves landing location predictions in-flight using collected flight information during the ascent and descent. Simulation and real-world flight tests (using the developed low-cost hardware) demonstrate the significance of the improvements achievable when flying the developed system.

Predicting longshore gradients in longshore transport: the CERC formula compared to Delft3D

USGS Publications Warehouse

List, Jeffrey H.; Hanes, Daniel M.; Ruggiero, Peter

2007-01-01

The prediction of longshore transport gradients is critical for forecasting shoreline change. We employ simple test cases consisting of shoreface pits at varying distances from the shoreline to compare the longshore transport gradients predicted by the CERC formula against results derived from the process-based model Delft3D. Results show that while in some cases the two approaches give very similar results, in many cases the results diverge greatly. Although neither approach is validated with field data here, the Delft3D-based transport gradients provide much more consistent predictions of erosional and accretionary zones as the pit location varies across the shoreface.

An evaluation of descent strategies for TNAV-equipped aircraft in an advanced metering environment

NASA Technical Reports Server (NTRS)

Izumi, K. H.; Schwab, R. W.; Groce, J. L.; Coote, M. A.

1986-01-01

Investigated were the effects on system throughput and fleet fuel usage of arrival aircraft utilizing three 4D RNAV descent strategies (cost optimal, clean-idle Mach/CAS and constant descent angle Mach/CAS), both individually and in combination, in an advanced air traffic control metering environment. Results are presented for all mixtures of arrival traffic consisting of three Boeing commercial jet types and for all combinations of the three descent strategies for a typical en route metering airport arrival distribution.

An annealed chaotic maximum neural network for bipartite subgraph problem.

PubMed

Wang, Jiahai; Tang, Zheng; Wang, Ronglong

2004-04-01

In this paper, based on maximum neural network, we propose a new parallel algorithm that can help the maximum neural network escape from local minima by including a transient chaotic neurodynamics for bipartite subgraph problem. The goal of the bipartite subgraph problem, which is an NP- complete problem, is to remove the minimum number of edges in a given graph such that the remaining graph is a bipartite graph. Lee et al. presented a parallel algorithm using the maximum neural model (winner-take-all neuron model) for this NP- complete problem. The maximum neural model always guarantees a valid solution and greatly reduces the search space without a burden on the parameter-tuning. However, the model has a tendency to converge to a local minimum easily because it is based on the steepest descent method. By adding a negative self-feedback to the maximum neural network, we proposed a new parallel algorithm that introduces richer and more flexible chaotic dynamics and can prevent the network from getting stuck at local minima. After the chaotic dynamics vanishes, the proposed algorithm is then fundamentally reined by the gradient descent dynamics and usually converges to a stable equilibrium point. The proposed algorithm has the advantages of both the maximum neural network and the chaotic neurodynamics. A large number of instances have been simulated to verify the proposed algorithm. The simulation results show that our algorithm finds the optimum or near-optimum solution for the bipartite subgraph problem superior to that of the best existing parallel algorithms.

An alternative means of retaining ocular structure and improving immunoreactivity for light microscopy studies

PubMed Central

Sun, Ning; Shibata, Brad; Hess, John F.

2015-01-01

Purpose Several properties of ocular tissue make fixation for light microscopy problematic. Because the eye is spherical, immersion fixation necessarily results in a temporal gradient of fixation, with surfaces fixing more rapidly and thoroughly than interior structures. The problem is compounded by the fact that the layers of the eye wall are compositionally quite different, resulting in different degrees of fixation-induced shrinkage and distortion. Collectively, these result in non-uniform preservation, as well as buckling and/or retinal detachment. This gradient problem is most acute for the lens, where the density of proteins can delay fixation of the central lens for days, and where the fixation gradient parallels the age gradient of lens cells, which complicates data interpretation. Our goal was to identify a simple method for minimizing some of the problems arising from immersion fixation, which avoided covalent modification of antigens, retained high quality structure, and maintained tissue in a state that is amenable to common cytochemical techniques. Methods A simple and inexpensive derivative of the freeze-substitution approach was developed and compared to fixation by immersion in formalin. Preservation of structure, immunoreactivity, GFP and tdTomato fluorescence, lectin reactivity, outer segment auto fluorescence, Click-iT chemistry, compatibility with in situ hybdrdization, and the ability to rehydrate eyes after fixation by freeze substitution for subsequent cryo sectioning were assessed. Results An inexpensive and simple variant of the freeze substitution approach provides excellent structural preservation for light microscopy, and essentially eliminates ocular buckling, retinal detachment, and outer segment auto-fluorescence, without covalent modification of tissue antigens. The approach shows a notable improvement in preservation of immunoreactivity. TdTomato intrinsic fluorescence is also preserved, as is compatibility with in situ hybridization, lectin labeling, and the Click-iT chemistry approach to labeling the thymidine analog EdU. On the negative side, this approach dramatically reduced intrinsic GFP fluorescence. Conclusions A simple, cost-effective derivative of the freeze substitution process is described that is of particular value in the study of rodent or other small eyes, where fixation gradients, globe buckling, retinal detachment, differential shrinkage, autofluorescence, and tissue immunoreactivity have been problematic. PMID:25991907

THE AFRICAN DESCENT AND GLAUCOMA EVALUATION STUDY (ADAGES): PREDICTORS OF VISUAL FIELD DAMAGE IN GLAUCOMA SUSPECTS

PubMed Central

Khachatryan, Naira; Medeiros, Felipe A.; Sharpsten, Lucie; Bowd, Christopher; Sample, Pamela A.; Liebmann, Jeffrey M.; Girkin, Christopher A.; Weinreb, Robert N.; Miki, Atsuya; Hammel, Na’ama; Zangwill, Linda M.

2015-01-01

Purpose To evaluate racial differences in the development of visual field (VF) damage in glaucoma suspects. Design Prospective, observational cohort study. Methods Six hundred thirty six eyes from 357 glaucoma suspects with normal VF at baseline were included from the multicenter African Descent and Glaucoma Evaluation Study (ADAGES). Racial differences in the development of VF damage were examined using multivariable Cox Proportional Hazard models. Results Thirty one (25.4%) of 122 African descent participants and 47 (20.0%) of 235 European descent participants developed VF damage (p=0.078). In multivariable analysis, worse baseline VF mean deviation, higher mean arterial pressure during follow up, and a race *mean intraocular pressure (IOP) interaction term were significantly associated with the development of VF damage suggesting that racial differences in the risk of VF damage varied by IOP. At higher mean IOP levels, race was predictive of the development of VF damage even after adjusting for potentially confounding factors. At mean IOPs during follow-up of 22, 24 and 26 mmHg, multivariable hazard ratios (95%CI) for the development of VF damage in African descent compared to European descent subjects were 2.03 (1.15–3.57), 2.71 (1.39–5.29), and 3.61 (1.61–8.08), respectively. However, at lower mean IOP levels (below 22 mmHg) during follow-up, African descent was not predictive of the development of VF damage. Conclusion In this cohort of glaucoma suspects with similar access to treatment, multivariate analysis revealed that at higher mean IOP during follow-up, individuals of African descent were more likely to develop VF damage than individuals of European descent. PMID:25597839

[Ethnic differences in forensic psychiatry: an exploratory study at a Dutch forensic psychiatric centre].

PubMed

van der Stoep, T

Compared to the percentage of ethnic minorities in the general population, ethnic minorities are overrepresented in forensic psychiatry. If these minorities are to be treated successfully, we need to know more about this group. So far, however, little is known about the differences between mental disorders and types of offences associated with patients of non-Dutch descent and those associated with patients of Dutch descent.
AIM: To take the first steps to obtain the information we need in order to provide customised care for patients of non-Dutch descent.
METHOD: It proved possible to identify differences between patients of Dutch and non-Dutch descent with regard to treatment, diagnosis and offences committed within a group of patients who were admitted to the forensic psychiatric centre Oostvaarderskliniek during the period 2001 - 2014.
RESULTS: The treatment of patients of non-Dutch descent lasted longer than the treatment of patients of Dutch descent (8.5 year versus 6.6 year). Furthermore, patients from ethnic minority groups were diagnosed more often with schizophrenia (49.1% versus 21.4%), but less often with pervasive developmental disorders or sexual disorders. Patients of non-Dutch descent were more often convicted for sexual crimes where the victim was aged 16 years or older, whereas patients of Dutch descent were convicted of sexual crimes where the victim was under 16.
CONCLUSION: There are differences between patients of Dutch and non-Dutch descent with regard to treatment duration, diagnosis and offences they commit. Future research needs to investigate whether these results are representative for the entire field of forensic psychiatry and to discover the reasons for these differences.

A spatiotemporally controllable chemical gradient generator via acoustically oscillating sharp-edge structures.

PubMed

Huang, Po-Hsun; Chan, Chung Yu; Li, Peng; Nama, Nitesh; Xie, Yuliang; Wei, Cheng-Hsin; Chen, Yuchao; Ahmed, Daniel; Huang, Tony Jun

2015-11-07

The ability to generate stable, spatiotemporally controllable concentration gradients is critical for resolving the dynamics of cellular response to a chemical microenvironment. Here we demonstrate an acoustofluidic gradient generator based on acoustically oscillating sharp-edge structures, which facilitates in a step-wise fashion the rapid mixing of fluids to generate tunable, dynamic chemical gradients. By controlling the driving voltage of a piezoelectric transducer, we demonstrated that the chemical gradient profiles can be conveniently altered (spatially controllable). By adjusting the actuation time of the piezoelectric transducer, moreover, we generated pulsatile chemical gradients (temporally controllable). With these two characteristics combined, we have developed a spatiotemporally controllable gradient generator. The applicability and biocompatibility of our acoustofluidic gradient generator are validated by demonstrating the migration of human dermal microvascular endothelial cells (HMVEC-d) in response to a generated vascular endothelial growth factor (VEGF) gradient, and by preserving the viability of HMVEC-d cells after long-term exposure to an acoustic field. Our device features advantages such as simple fabrication and operation, compact and biocompatible device, and generation of spatiotemporally tunable gradients.

The impact of Asian descent on the incidence of acquired severe aplastic anaemia in children.

PubMed

McCahon, Emma; Tang, Keith; Rogers, Paul C J; McBride, Mary L; Schultz, Kirk R

2003-04-01

Previous studies have suggested an increased incidence of acquired severe aplastic anaemia in Asian populations. We evaluated the incidence of aplastic anaemia in people of Asian descent, using a well-defined paediatric (0-14 years) population in British Columbia, Canada to minimize environmental factors. The incidence in children of East/South-east Asian descent (6.9/million/year) and South Asian (East Indian) descent (7.3/million/year) was higher than for those of White/mixed ethnic descent (1.7/million/year). There appeared to be no contribution by environmental factors. This study shows that Asian children have an increased incidence of severe aplastic anaemia possibly as a result of a genetic predisposition.

Non-Gradient Blue Native Polyacrylamide Gel Electrophoresis.

PubMed

Luo, Xiaoting; Wu, Jinzi; Jin, Zhen; Yan, Liang-Jun

2017-02-02

Gradient blue native polyacrylamide gel electrophoresis (BN-PAGE) is a well established and widely used technique for activity analysis of high-molecular-weight proteins, protein complexes, and protein-protein interactions. Since its inception in the early 1990s, a variety of minor modifications have been made to this gradient gel analytical method. Here we provide a major modification of the method, which we call non-gradient BN-PAGE. The procedure, similar to that of non-gradient SDS-PAGE, is simple because there is no expensive gradient maker involved. The non-gradient BN-PAGE protocols presented herein provide guidelines on the analysis of mitochondrial protein complexes, in particular, dihydrolipoamide dehydrogenase (DLDH) and those in the electron transport chain. Protocols for the analysis of blood esterases or mitochondrial esterases are also presented. The non-gradient BN-PAGE method may be tailored for analysis of specific proteins according to their molecular weight regardless of whether the target proteins are hydrophobic or hydrophilic. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Intrascrotal CGRP 8-37 causes a delay in testicular descent in mice.

PubMed

Samarakkody, U K; Hutson, J M

1992-07-01

The genitofemoral nerve is a key factor in the inguinoscrotal descent of the testis. The effect of androgens may be mediated via the central nervous system, which in turn secretes the neurotransmitter calcitonin gene-related peptide (CGRP) at the genitofemoral nerve endings, to cause testicular descent. The effect of endogenous CGRP was examined by weekly injections of a vehicle with or without synthetic antagonist (CGRP 8-37) into the developing scrotum of neonatal mice. The descent of the testis was delayed in the experimental group compared with the control group. At 2 weeks of age 43% of controls had descended testes compared with 0% of experimental animals. At 3 weeks of age 17% of experimentals still had undescended testes, whereas all testes were descended in controls. At 4 weeks 3 testes remained undescended in the experimental group. It is concluded that the CGRP antagonist can retard testicular descent. This result is consistent with the hypothesis that CGRP is an important intermediary in testicular descent.

Human chorionic gonadotropin but not the calcitonin gene-related peptide induces postnatal testicular descent in mice.

PubMed

Houle, A M; Gagné, D

1995-01-01

The androgen-regulated paracrine factor, calcitonin gene-related peptide (CGRP), has been proposed as a possible mediator of testicular descent. This peptide has been found to increase rhythmic contractions of gubernaculae and is known to be released by the genitofemoral nerve. We have investigated the ability of CGRP to induce premature testicular descent. CGRP was administered alone, or in combination with human chorionic gonadotropin (hCG) to C57BL/6 male mice postnatally. The extent of testicular descent at 18 days postpartum was then ascertained. The potential relationship between testicular weight and descent was also examined. Our results show that testes of mice treated with either hCG alone, or in combination with 500 ng CGRP, were at a significantly lower position than those of controls by 16% and 17%, respectively. In contrast, mice treated with 500 ng of CGRP alone had testes at a higher position when compared to those of controls, by 19%. In mice treated with 50 ng of CGRP alone or in combination with hCG, testes were at a position similar to those in controls. Furthermore, testicular descent was analyzed in relation to testicular weight, and we found that significantly smaller testes per gram of body weight than those of controls were at a significantly lower position compared to those of controls. Our data demonstrate that CGRP had no effect on postnatal testicular descent and that there is no relationship between postnatal descent and testicular weight.

Machine Learning Interface for Medical Image Analysis.

PubMed

Zhang, Yi C; Kagen, Alexander C

2017-10-01

TensorFlow is a second-generation open-source machine learning software library with a built-in framework for implementing neural networks in wide variety of perceptual tasks. Although TensorFlow usage is well established with computer vision datasets, the TensorFlow interface with DICOM formats for medical imaging remains to be established. Our goal is to extend the TensorFlow API to accept raw DICOM images as input; 1513 DaTscan DICOM images were obtained from the Parkinson's Progression Markers Initiative (PPMI) database. DICOM pixel intensities were extracted and shaped into tensors, or n-dimensional arrays, to populate the training, validation, and test input datasets for machine learning. A simple neural network was constructed in TensorFlow to classify images into normal or Parkinson's disease groups. Training was executed over 1000 iterations for each cross-validation set. The gradient descent optimization and Adagrad optimization algorithms were used to minimize cross-entropy between the predicted and ground-truth labels. Cross-validation was performed ten times to produce a mean accuracy of 0.938 ± 0.047 (95 % CI 0.908-0.967). The mean sensitivity was 0.974 ± 0.043 (95 % CI 0.947-1.00) and mean specificity was 0.822 ± 0.207 (95 % CI 0.694-0.950). We extended the TensorFlow API to enable DICOM compatibility in the context of DaTscan image analysis. We implemented a neural network classifier that produces diagnostic accuracies on par with excellent results from previous machine learning models. These results indicate the potential role of TensorFlow as a useful adjunct diagnostic tool in the clinical setting.

Parameter estimation of history-dependent leaky integrate-and-fire neurons using maximum-likelihood methods

PubMed Central

Dong, Yi; Mihalas, Stefan; Russell, Alexander; Etienne-Cummings, Ralph; Niebur, Ernst

2012-01-01

When a neuronal spike train is observed, what can we say about the properties of the neuron that generated it? A natural way to answer this question is to make an assumption about the type of neuron, select an appropriate model for this type, and then to choose the model parameters as those that are most likely to generate the observed spike train. This is the maximum likelihood method. If the neuron obeys simple integrate and fire dynamics, Paninski, Pillow, and Simoncelli (2004) showed that its negative log-likelihood function is convex and that its unique global minimum can thus be found by gradient descent techniques. The global minimum property requires independence of spike time intervals. Lack of history dependence is, however, an important constraint that is not fulfilled in many biological neurons which are known to generate a rich repertoire of spiking behaviors that are incompatible with history independence. Therefore, we expanded the integrate and fire model by including one additional variable, a variable threshold (Mihalas & Niebur, 2009) allowing for history-dependent firing patterns. This neuronal model produces a large number of spiking behaviors while still being linear. Linearity is important as it maintains the distribution of the random variables and still allows for maximum likelihood methods to be used. In this study we show that, although convexity of the negative log-likelihood is not guaranteed for this model, the minimum of the negative log-likelihood function yields a good estimate for the model parameters, in particular if the noise level is treated as a free parameter. Furthermore, we show that a nonlinear function minimization method (r-algorithm with space dilation) frequently reaches the global minimum. PMID:21851282

Transformable descent vehicles

NASA Astrophysics Data System (ADS)

Pichkhadze, K. M.; Finchenko, V. S.; Aleksashkin, S. N.; Ostreshko, B. A.

2016-12-01

This article presents some types of planetary descent vehicles, the shape of which varies in different flight phases. The advantages of such vehicles over those with unchangeable form (from launch to landing) are discussed. It is shown that the use of transformable descent vehicles widens the scope of possible tasks to solve.

43 CFR 10.14 - Lineal descent and cultural affiliation.

Code of Federal Regulations, 2011 CFR

2011-10-01

... evidence sufficient to: (i) Establish the identity and cultural characteristics of the earlier group, (ii... 43 Public Lands: Interior 1 2011-10-01 2011-10-01 false Lineal descent and cultural affiliation... GRAVES PROTECTION AND REPATRIATION REGULATIONS General § 10.14 Lineal descent and cultural affiliation...

43 CFR 10.14 - Lineal descent and cultural affiliation.

Code of Federal Regulations, 2010 CFR

2010-10-01

... evidence sufficient to: (i) Establish the identity and cultural characteristics of the earlier group, (ii... 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...

Rocket measurements of electron density irregularities during MAC/SINE

NASA Technical Reports Server (NTRS)

Ulwick, J. C.

1989-01-01

Four Super Arcas rockets were launched at the Andoya Rocket Range, Norway, as part of the MAC/SINE campaign to measure electron density irregularities with high spatial resolution in the cold summer polar mesosphere. They were launched as part of two salvos: the turbulent/gravity wave salvo (3 rockets) and the EISCAT/SOUSY radar salvo (one rocket). In both salvos meteorological rockets, measuring temperature and winds, were also launched and the SOUSY radar, located near the launch site, measured mesospheric turbulence. Electron density irregularities and strong gradients were measured by the rocket probes in the region of most intense backscatter observed by the radar. The electron density profiles (8 to 4 on ascent and 4 on descent) show very different characteristics in the peak scattering region and show marked spatial and temporal variability. These data are intercompared and discussed.

Ellipsoidal fuzzy learning for smart car platoons

NASA Astrophysics Data System (ADS)

Dickerson, Julie A.; Kosko, Bart

1993-12-01

A neural-fuzzy system combined supervised and unsupervised learning to find and tune the fuzzy-rules. An additive fuzzy system approximates a function by covering its graph with fuzzy rules. A fuzzy rule patch can take the form of an ellipsoid in the input-output space. Unsupervised competitive learning found the statistics of data clusters. The covariance matrix of each synaptic quantization vector defined on ellipsoid centered at the centroid of the data cluster. Tightly clustered data gave smaller ellipsoids or more certain rules. Sparse data gave larger ellipsoids or less certain rules. Supervised learning tuned the ellipsoids to improve the approximation. The supervised neural system used gradient descent to find the ellipsoidal fuzzy patches. It locally minimized the mean-squared error of the fuzzy approximation. Hybrid ellipsoidal learning estimated the control surface for a smart car controller.

Adaptive filter design using recurrent cerebellar model articulation controller.

PubMed

Lin, Chih-Min; Chen, Li-Yang; Yeung, Daniel S

2010-07-01

A novel adaptive filter is proposed using a recurrent cerebellar-model-articulation-controller (CMAC). The proposed locally recurrent globally feedforward recurrent CMAC (RCMAC) has favorable properties of small size, good generalization, rapid learning, and dynamic response, thus it is more suitable for high-speed signal processing. To provide fast training, an efficient parameter learning algorithm based on the normalized gradient descent method is presented, in which the learning rates are on-line adapted. Then the Lyapunov function is utilized to derive the conditions of the adaptive learning rates, so the stability of the filtering error can be guaranteed. To demonstrate the performance of the proposed adaptive RCMAC filter, it is applied to a nonlinear channel equalization system and an adaptive noise cancelation system. The advantages of the proposed filter over other adaptive filters are verified through simulations.

Speckle-metric-optimization-based adaptive optics for laser beam projection and coherent beam combining.

PubMed

Vorontsov, Mikhail; Weyrauch, Thomas; Lachinova, Svetlana; Gatz, Micah; Carhart, Gary

2012-07-15

Maximization of a projected laser beam's power density at a remotely located extended object (speckle target) can be achieved by using an adaptive optics (AO) technique based on sensing and optimization of the target-return speckle field's statistical characteristics, referred to here as speckle metrics (SM). SM AO was demonstrated in a target-in-the-loop coherent beam combining experiment using a bistatic laser beam projection system composed of a coherent fiber-array transmitter and a power-in-the-bucket receiver. SM sensing utilized a 50 MHz rate dithering of the projected beam that provided a stair-mode approximation of the outgoing combined beam's wavefront tip and tilt with subaperture piston phases. Fiber-integrated phase shifters were used for both the dithering and SM optimization with stochastic parallel gradient descent control.

Algorithm based on the Thomson problem for determination of equilibrium structures of metal nanoclusters

NASA Astrophysics Data System (ADS)

Arias, E.; Florez, E.; Pérez-Torres, J. F.

2017-06-01

A new algorithm for the determination of equilibrium structures suitable for metal nanoclusters is proposed. The algorithm performs a stochastic search of the minima associated with the nuclear potential energy function restricted to a sphere (similar to the Thomson problem), in order to guess configurations of the nuclear positions. Subsequently, the guessed configurations are further optimized driven by the total energy function using the conventional gradient descent method. This methodology is equivalent to using the valence shell electron pair repulsion model in guessing initial configurations in the traditional molecular quantum chemistry. The framework is illustrated in several clusters of increasing complexity: Cu7, Cu9, and Cu11 as benchmark systems, and Cu38 and Ni9 as novel systems. New equilibrium structures for Cu9, Cu11, Cu38, and Ni9 are reported.

Hybrid preconditioning for iterative diagonalization of ill-conditioned generalized eigenvalue problems in electronic structure calculations

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

Cai, Yunfeng, E-mail: yfcai@math.pku.edu.cn; Department of Computer Science, University of California, Davis 95616; Bai, Zhaojun, E-mail: bai@cs.ucdavis.edu

2013-12-15

The iterative diagonalization of a sequence of large ill-conditioned generalized eigenvalue problems is a computational bottleneck in quantum mechanical methods employing a nonorthogonal basis for ab initio electronic structure calculations. We propose a hybrid preconditioning scheme to effectively combine global and locally accelerated preconditioners for rapid iterative diagonalization of such eigenvalue problems. In partition-of-unity finite-element (PUFE) pseudopotential density-functional calculations, employing a nonorthogonal basis, we show that the hybrid preconditioned block steepest descent method is a cost-effective eigensolver, outperforming current state-of-the-art global preconditioning schemes, and comparably efficient for the ill-conditioned generalized eigenvalue problems produced by PUFE as the locally optimal blockmore » preconditioned conjugate-gradient method for the well-conditioned standard eigenvalue problems produced by planewave methods.« less

A dual estimate method for aeromagnetic compensation

NASA Astrophysics Data System (ADS)

Ma, Ming; Zhou, Zhijian; Cheng, Defu

2017-11-01

Scalar aeromagnetic surveys have played a vital role in prospecting. However, before analysis of the surveys’ aeromagnetic data is possible, the aircraft’s magnetic interference should be removed. The extensively adopted linear model for aeromagnetic compensation is computationally efficient but faces an underfitting problem. On the other hand, the neural model proposed by Williams is more powerful at fitting but always suffers from an overfitting problem. This paper starts off with an analysis of these two models and then proposes a dual estimate method to combine them together to improve accuracy. This method is based on an unscented Kalman filter, but a gradient descent method is implemented over the iteration so that the parameters of the linear model are adjustable during flight. The noise caused by the neural model’s overfitting problem is suppressed by introducing an observation noise.

Algorithm based on the Thomson problem for determination of equilibrium structures of metal nanoclusters.

PubMed

Arias, E; Florez, E; Pérez-Torres, J F

2017-06-28

A new algorithm for the determination of equilibrium structures suitable for metal nanoclusters is proposed. The algorithm performs a stochastic search of the minima associated with the nuclear potential energy function restricted to a sphere (similar to the Thomson problem), in order to guess configurations of the nuclear positions. Subsequently, the guessed configurations are further optimized driven by the total energy function using the conventional gradient descent method. This methodology is equivalent to using the valence shell electron pair repulsion model in guessing initial configurations in the traditional molecular quantum chemistry. The framework is illustrated in several clusters of increasing complexity: Cu 7 , Cu 9 , and Cu 11 as benchmark systems, and Cu 38 and Ni 9 as novel systems. New equilibrium structures for Cu 9 , Cu 11 , Cu 38 , and Ni 9 are reported.

Radial basis function network learns ceramic processing and predicts related strength and density

NASA Technical Reports Server (NTRS)

Cios, Krzysztof J.; Baaklini, George Y.; Vary, Alex; Tjia, Robert E.

1993-01-01

Radial basis function (RBF) neural networks were trained using the data from 273 Si3N4 modulus of rupture (MOR) bars which were tested at room temperature and 135 MOR bars which were tested at 1370 C. Milling time, sintering time, and sintering gas pressure were the processing parameters used as the input features. Flexural strength and density were the outputs by which the RBF networks were assessed. The 'nodes-at-data-points' method was used to set the hidden layer centers and output layer training used the gradient descent method. The RBF network predicted strength with an average error of less than 12 percent and density with an average error of less than 2 percent. Further, the RBF network demonstrated a potential for optimizing and accelerating the development and processing of ceramic materials.

Derivation of the threshold condition for the ion temperature gradient mode with an inverted density profile from a simple physics picture

NASA Astrophysics Data System (ADS)

Jhang, Hogun

2018-05-01

We show that the threshold condition for the toroidal ion temperature gradient (ITG) mode with an inverted density profile can be derived from a simple physics argument. The key in this picture is that the density inversion reduces the ion compression due to the ITG mode and the electron drift motion mitigates the poloidal potential build-up. This condition reproduces the same result that has been reported from a linear gyrokinetic calculation [T. S. Hahm and W. M. Tang, Phys. Fluids B 1, 1185 (1989)]. The destabilizing role of trapped electrons in toroidal geometry is easily captured in this picture.

Aligned coaxial tungsten oxide-carbon nanotube sheet: a flexible and gradient electrochromic film.

PubMed

Yao, Zhaojun; Di, Jiangtao; Yong, Zhenzhong; Zhao, Zhigang; Li, Qingwen

2012-08-25

We develop a simple dry wrapping method to fabricate a tungsten oxide (WO(3))/carbon nanotube (CNT) cable, in which WO(3) layers act as an electrochromic component while aligned CNTs as the core provide mechanical support and an anisotropic, continuous electron transport pathway. Interestingly, the resultant cable material exhibits an obvious gradient electrochromic phenomenon.

Gradient Scouting in Reversed-Phase HPLC Revisited

ERIC Educational Resources Information Center

Alcazar, A.; Jurado, J. M.; Gonzalez, A. G.

2011-01-01

Gradient scouting is the best way to decide the most suitable elution mode in reversed-phase high-performance liquid chromatography (RP-HPLC). A simple rule for this decision involves the evaluation of the ratio [delta]t/t[subscript G] (where [delta]t is the difference in the retention time between the last and the first peak and t[subscript G] is…

Implementing quantum logic gates with gradient ascent pulse engineering: principles and practicalities.

PubMed

Rowland, Benjamin; Jones, Jonathan A

2012-10-13

We briefly describe the use of gradient ascent pulse engineering (GRAPE) pulses to implement quantum logic gates in nuclear magnetic resonance quantum computers, and discuss a range of simple extensions to the core technique. We then consider a range of difficulties that can arise in practical implementations of GRAPE sequences, reflecting non-idealities in the experimental systems used.

Mapping axonal density and average diameter using non-monotonic time-dependent gradient-echo MRI

NASA Astrophysics Data System (ADS)

Nunes, Daniel; Cruz, Tomás L.; Jespersen, Sune N.; Shemesh, Noam

2017-04-01

White Matter (WM) microstructures, such as axonal density and average diameter, are crucial to the normal function of the Central Nervous System (CNS) as they are closely related with axonal conduction velocities. Conversely, disruptions of these microstructural features may result in severe neurological deficits, suggesting that their noninvasive mapping could be an important step towards diagnosing and following pathophysiology. Whereas diffusion based MRI methods have been proposed to map these features, they typically entail the application of powerful gradients, which are rarely available in the clinic, or extremely long acquisition schemes to extract information from parameter-intensive models. In this study, we suggest that simple and time-efficient multi-gradient-echo (MGE) MRI can be used to extract the axon density from susceptibility-driven non-monotonic decay in the time-dependent signal. We show, both theoretically and with simulations, that a non-monotonic signal decay will occur for multi-compartmental microstructures - such as axons and extra-axonal spaces, which were here used as a simple model for the microstructure - and that, for axons parallel to the main magnetic field, the axonal density can be extracted. We then experimentally demonstrate in ex-vivo rat spinal cords that its different tracts - characterized by different microstructures - can be clearly contrasted using the MGE-derived maps. When the quantitative results are compared against ground-truth histology, they reflect the axonal fraction (though with a bias, as evident from Bland-Altman analysis). As well, the extra-axonal fraction can be estimated. The results suggest that our model is oversimplified, yet at the same time evidencing a potential and usefulness of the approach to map underlying microstructures using a simple and time-efficient MRI sequence. We further show that a simple general-linear-model can predict the average axonal diameters from the four model parameters, and map these average axonal diameters in the spinal cords. While clearly further modelling and theoretical developments are necessary, we conclude that salient WM microstructural features can be extracted from simple, SNR-efficient multi-gradient echo MRI, and that this paves the way towards easier estimation of WM microstructure in vivo.

Mapping axonal density and average diameter using non-monotonic time-dependent gradient-echo MRI.

PubMed

Nunes, Daniel; Cruz, Tomás L; Jespersen, Sune N; Shemesh, Noam

2017-04-01

White Matter (WM) microstructures, such as axonal density and average diameter, are crucial to the normal function of the Central Nervous System (CNS) as they are closely related with axonal conduction velocities. Conversely, disruptions of these microstructural features may result in severe neurological deficits, suggesting that their noninvasive mapping could be an important step towards diagnosing and following pathophysiology. Whereas diffusion based MRI methods have been proposed to map these features, they typically entail the application of powerful gradients, which are rarely available in the clinic, or extremely long acquisition schemes to extract information from parameter-intensive models. In this study, we suggest that simple and time-efficient multi-gradient-echo (MGE) MRI can be used to extract the axon density from susceptibility-driven non-monotonic decay in the time-dependent signal. We show, both theoretically and with simulations, that a non-monotonic signal decay will occur for multi-compartmental microstructures - such as axons and extra-axonal spaces, which were here used as a simple model for the microstructure - and that, for axons parallel to the main magnetic field, the axonal density can be extracted. We then experimentally demonstrate in ex-vivo rat spinal cords that its different tracts - characterized by different microstructures - can be clearly contrasted using the MGE-derived maps. When the quantitative results are compared against ground-truth histology, they reflect the axonal fraction (though with a bias, as evident from Bland-Altman analysis). As well, the extra-axonal fraction can be estimated. The results suggest that our model is oversimplified, yet at the same time evidencing a potential and usefulness of the approach to map underlying microstructures using a simple and time-efficient MRI sequence. We further show that a simple general-linear-model can predict the average axonal diameters from the four model parameters, and map these average axonal diameters in the spinal cords. While clearly further modelling and theoretical developments are necessary, we conclude that salient WM microstructural features can be extracted from simple, SNR-efficient multi-gradient echo MRI, and that this paves the way towards easier estimation of WM microstructure in vivo. Copyright © 2017 Elsevier Inc. All rights reserved.

Overview of the Phoenix Entry, Descent and Landing System

NASA Technical Reports Server (NTRS)

Grover, Rob

2005-01-01

A viewgraph presentation on the entry, descent and landing system of Phoenix is shown. The topics include: 1) Phoenix Mission Goals; 2) Payload; 3) Aeroshell/Entry Comparison; 4) Entry Trajectory Comparison; 5) Phoenix EDL Timeline; 6) Hypersonic Phase; 7) Parachute Phase; 8) Terminal Descent Phase; and 9) EDL Communications.

Ascent/Descent Software

NASA Technical Reports Server (NTRS)

Brown, Charles; Andrew, Robert; Roe, Scott; Frye, Ronald; Harvey, Michael; Vu, Tuan; Balachandran, Krishnaiyer; Bly, Ben

2012-01-01

The Ascent/Descent Software Suite has been used to support a variety of NASA Shuttle Program mission planning and analysis activities, such as range safety, on the Integrated Planning System (IPS) platform. The Ascent/Descent Software Suite, containing Ascent Flight Design (ASC)/Descent Flight Design (DESC) Configuration items (Cis), lifecycle documents, and data files used for shuttle ascent and entry modeling analysis and mission design, resides on IPS/Linux workstations. A list of tools in Navigation (NAV)/Prop Software Suite represents tool versions established during or after the IPS Equipment Rehost-3 project.

Descent Stage of Mars Science Laboratory During Assembly

NASA Technical Reports Server (NTRS)

2008-01-01

This image from early October 2008 shows personnel working on the descent stage of NASA's Mars Science Laboratory inside the Spacecraft Assembly Facility at NASA's Jet Propulsion Laboratory, Pasadena, Calif.

The descent stage will provide rocket-powered deceleration for a phase of the arrival at Mars after the phases using the heat shield and parachute. When it nears the surface, the descent stage will lower the rover on a bridle the rest of the way to the ground. The larger three of the orange spheres in the descent stage are fuel tanks. The smaller two are tanks for pressurant gas used for pushing the fuel to the rocket engines.

JPL, a division of the California Institute of Technology, manages the Mars Science Laboratory Project for the NASA Science Mission Directorate, Washington.

Dynamics of the Venera 13 and 14 descent modules in the parachute segment of descent

NASA Astrophysics Data System (ADS)

Vishniak, A. A.; Kariagin, V. P.; Kovtunenko, V. M.; Kotov, B. B.; Kuznetsov, V. V.; Lopatkin, A. I.; Perov, O. V.; Pichkhadze, K. M.; Rysev, O. V.

1983-05-01

The parachute system for the Venera 13 and 14 descent modules was designed to assure the prescribed duration of descent in the Venus cloud layer as well as the separation of heat-shield elements from the module. A mathematical model is developed which makes possible a numerical analysis of the dynamics of the module-parachute system with allowance for parachute inertia, atmospheric turbulence, the means by which the parachute is attachead to the module, and the elasticity and damping of the suspended system. A formula is derived for determining the period of oscillations of the module in the parachute segment of descent. A comparison of theoretical and experimental results shows that this formula can be used in the design calculations, especially at the early stage of module development.

Automation for Accommodating Fuel-Efficient Descents in Constrained Airspace

NASA Technical Reports Server (NTRS)

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.

User's manual for a fuel-conservative descent planning algorithm implemented on a small programmable calculator

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

Vicroy, D.D.

A simplified flight management descent algorithm was developed and programmed on a small programmable calculator. It 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 algorithm may also be used for planning fuel conservative descents when time is not a consideration. 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 temperature effects. An explanation and examples of how the algorithm is used,more » as well as a detailed flow chart and listing of the algorithm are contained.« less

Regularized lattice Boltzmann model for immiscible two-phase flows with power-law rheology

NASA Astrophysics Data System (ADS)

Ba, Yan; Wang, Ningning; Liu, Haihu; Li, Qiang; He, Guoqiang

2018-03-01

In this work, a regularized lattice Boltzmann color-gradient model is developed for the simulation of immiscible two-phase flows with power-law rheology. This model is as simple as the Bhatnagar-Gross-Krook (BGK) color-gradient model except that an additional regularization step is introduced prior to the collision step. In the regularization step, the pseudo-inverse method is adopted as an alternative solution for the nonequilibrium part of the total distribution function, and it can be easily extended to other discrete velocity models no matter whether a forcing term is considered or not. The obtained expressions for the nonequilibrium part are merely related to macroscopic variables and velocity gradients that can be evaluated locally. Several numerical examples, including the single-phase and two-phase layered power-law fluid flows between two parallel plates, and the droplet deformation and breakup in a simple shear flow, are conducted to test the capability and accuracy of the proposed color-gradient model. Results show that the present model is more stable and accurate than the BGK color-gradient model for power-law fluids with a wide range of power-law indices. Compared to its multiple-relaxation-time counterpart, the present model can increase the computing efficiency by around 15%, while keeping the same accuracy and stability. Also, the present model is found to be capable of reasonably predicting the critical capillary number of droplet breakup.

Constant pressure mode extended simple gradient liquid chromatography system for micro and nanocolumns.

PubMed

Šesták, Jozef; Kahle, Vladislav

2014-07-11

Performing gradient liquid chromatography at constant pressure instead of constant flow rate has serious potential for shortening the analysis time and increasing the productivity of HPLC instruments that use gradient methods. However, in the constant pressure mode the decreasing column permeability during a long period of time negatively affects the repeatability of retention time. Thus a volume-based approach, in which the detector signal is plotted as a function of retention volume, must be taken into consideration. Traditional HPLC equipment, however, requires quite complex hardware and software modifications in order to work at constant pressure and in the volume-based mode. In this short communication, a low cost and easily feasible pressure-controlled extension of the previously described simple gradient liquid chromatography platform is proposed. A test mixture of four nitro esters was separated by 10-60% (v/v) acetone/water gradient and a high repeatability of retention volumes at 20MPa (RSD less than 0.45%) was realized. Separations were also performed at different values of pressure (20, 25, and 31MPa), and only small variations of the retention volumes (up to 0.8%) were observed. In this particular case, the gain in the analysis speed of 7% compared to the constant flow mode was realized at a constant pressure. Copyright © 2014 Elsevier B.V. All rights reserved.

Temperature gradients in a portion of Michigan: a review of the usefulness of data from the AAPG geothermal survey of North America

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

Vaught, T.L.

1980-08-01

Temperature gradient data derived from drill holes in an east-west zone through the center of the southern peninsula of Michigan are analyzed. The purpose of this work is to investigate possible problems in utilizing the American Association of Petroleum Geologists data base. Michigan was chosen because a review of that State's geothermal potential shows inconsistencies between gradients from shallow wells and nearby deeper wells and because the geology of the State is relativey simple. The structure and stratigraphy are discussed because an understanding of Michigan basin geology makes it easier to predict the influence of lithology on the basin's geothermalmore » gradients. Explanations for elevated gradients are reviewed. (MHR)« less

Mapping longitudinal stream connectivity in the North St. Vrain Creek watershed of Colorado

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

Wohl, Ellen; Rathburn, Sara; Chignell, Stephen

We use reach-scale stream gradient as an indicator of longitudinal connectivity for water, sediment, and organic matter in a mountainous watershed in Colorado. Stream reaches with the highest gradient tend to have narrow valley bottoms with limited storage space and attenuation of downstream fluxes, whereas stream reaches with progressively lower gradients have progressively more storage and greater attenuation. We compared the distribution of stream gradient to stream-reach connectivity rankings that incorporated multiple potential control variables, including lithology, upland vegetation, hydroclimatology, road crossings, and flow diversions. We then assessed connectivity rankings using different weighting schemes against stream gradient and against field-basedmore » understanding of relative connectivity within the watershed. Here, we conclude that stream gradient, which is simple to map using publicly available data and digital elevation models, is the most robust indicator of relative longitudinal connectivity within the river network.« less

Dynamics of Scroll Wave in a Three-Dimensional System with Changing Gradient.

PubMed

Yuan, Xiao-Ping; Chen, Jiang-Xing; Zhao, Ye-Hua; Liu, Gui-Quan; Ying, He-Ping

2016-01-01

The dynamics of a scroll wave in an excitable medium with gradient excitability is studied in detail. Three parameter regimes can be distinguished by the degree of gradient. For a small gradient, the system reaches a simple rotating synchronization. In this regime, the rigid rotating velocity of spiral waves is maximal in the layers with the highest filament twist. As the excitability gradient increases, the scroll wave evolutes into a meandering synchronous state. This transition is accompanied by a variation in twisting rate. Filament twisting may prevent the breakup of spiral waves in the bottom layers with a low excitability with which a spiral breaks in a 2D medium. When the gradient is large enough, the twisted filament breaks up, which results in a semi-turbulent state where the lower part is turbulent while the upper part contains a scroll wave with a low twisting filament.

Fgf8 morphogen gradient forms by a source-sink mechanism with freely diffusing molecules.

PubMed

Yu, Shuizi Rachel; Burkhardt, Markus; Nowak, Matthias; Ries, Jonas; Petrásek, Zdenek; Scholpp, Steffen; Schwille, Petra; Brand, Michael

2009-09-24

It is widely accepted that tissue differentiation and morphogenesis in multicellular organisms are regulated by tightly controlled concentration gradients of morphogens. How exactly these gradients are formed, however, remains unclear. Here we show that Fgf8 morphogen gradients in living zebrafish embryos are established and maintained by two essential factors: fast, free diffusion of single molecules away from the source through extracellular space, and a sink function of the receiving cells, regulated by receptor-mediated endocytosis. Evidence is provided by directly examining single molecules of Fgf8 in living tissue by fluorescence correlation spectroscopy, quantifying their local mobility and concentration with high precision. By changing the degree of uptake of Fgf8 into its target cells, we are able to alter the shape of the Fgf8 gradient. Our results demonstrate that a freely diffusing morphogen can set up concentration gradients in a complex multicellular tissue by a simple source-sink mechanism.

Mapping longitudinal stream connectivity in the North St. Vrain Creek watershed of Colorado

DOE PAGES

Wohl, Ellen; Rathburn, Sara; Chignell, Stephen; ...

2016-05-06

We use reach-scale stream gradient as an indicator of longitudinal connectivity for water, sediment, and organic matter in a mountainous watershed in Colorado. Stream reaches with the highest gradient tend to have narrow valley bottoms with limited storage space and attenuation of downstream fluxes, whereas stream reaches with progressively lower gradients have progressively more storage and greater attenuation. We compared the distribution of stream gradient to stream-reach connectivity rankings that incorporated multiple potential control variables, including lithology, upland vegetation, hydroclimatology, road crossings, and flow diversions. We then assessed connectivity rankings using different weighting schemes against stream gradient and against field-basedmore » understanding of relative connectivity within the watershed. Here, we conclude that stream gradient, which is simple to map using publicly available data and digital elevation models, is the most robust indicator of relative longitudinal connectivity within the river network.« less

Tracer-Based Determination of Vortex Descent in the 1999-2000 Arctic Winter

NASA Technical Reports Server (NTRS)

Greenblatt, Jeffery B.; Jost, Hans-Juerg; Loewenstein, Max; Podolske, James R.; Hurst, Dale F.; Elkins, James W.; Schauffler, Sue M.; Atlas, Elliot L.; Herman, Robert L.; Webster, Christopher R.

2001-01-01

A detailed analysis of available in situ and remotely sensed N2O and CH4 data measured in the 1999-2000 winter Arctic vortex has been performed in order to quantify the temporal evolution of vortex descent. Differences in potential temperature (theta) among balloon and aircraft vertical profiles (an average of 19-23 K on a given N2O or CH4 isopleth) indicated significant vortex inhomogeneity in late fall as compared with late winter profiles. A composite fall vortex profile was constructed for November 26, 1999, whose error bars encompassed the observed variability. High-latitude, extravortex profiles measured in different years and seasons revealed substantial variability in N2O and CH4 on theta surfaces, but all were clearly distinguishable from the first vortex profiles measured in late fall 1999. From these extravortex-vortex differences, we inferred descent prior to November 26: 397+/-15 K (1sigma) at 30 ppbv N2O and 640 ppbv CH4, and 28+/-13 K above 200 ppbv N2O and 1280 ppbv CH4. Changes in theta were determined on five N2O and CH4 isopleths from November 26 through March 12, and descent rates were calculated on each N2O isopleth for several time intervals. The maximum descent rates were seen between November 26 and January 27: 0.82+/-0.20 K/day averaged over 50-250 ppbv N2O. By late winter (February 26-March 12), the average rate had decreased to 0.10+/-0.25 K/day. Descent rates also decreased with increasing N2O; the winter average (November 26-March 5) descent rate varied from 0.75+/-0.10 K/day at 50 ppbv to 0.40+/-0.11 K/day at 250 ppbv. Comparison of these results with observations and models of descent in prior years showed very good overall agreement. Two models of the 1999-2000 vortex descent, SLIMCAT and REPROBUS, despite theta offsets with respect to observed profiles of up to 20 K on most tracer isopleths, produced descent rates that agreed very favorably with the inferred rates from observation.

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

PubMed

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.

Human Scleral Structural Stiffness Increases More Rapidly With Age in Donors of African Descent Compared to Donors of European Descent

PubMed Central

Fazio, Massimo A.; Grytz, Rafael; Morris, Jeffrey S.; Bruno, Luigi; Girkin, Christopher A.; Downs, J. Crawford

2014-01-01

Purpose. We tested the hypothesis that the variation of peripapillary scleral structural stiffness with age is different in donors of European (ED) and African (AD) descent. Methods. Posterior scleral shells from normal eyes from donors of European (n = 20 pairs; previously reported) and African (n = 9 pairs) descent aged 0 and 90 years old were inflation tested within 48 hours post mortem. Scleral shells were pressurized from 5 to 45 mm Hg and the full-field, 3-dimensional (3D) deformation of the outer surface was recorded at submicrometric accuracy using speckle interferometry (ESPI). Mean maximum principal (tensile) strain of the peripapillary and midperipheral regions surrounding the optic nerve head (ONH) were fit using a functional mixed effects model that accounts for intradonor variability, same-race correlation, and spatial autocorrelation to estimate the effect of race on the age-related changes in mechanical scleral strain. Results. Mechanical tensile strain significantly decreased with age in the peripapillary sclera in the African and European descent groups (P < 0.001), but the age-related stiffening was significantly greater in the African descent group (P < 0.05). Maximum principal strain in the peripapillary sclera was significantly higher than in the midperipheral sclera for both ethnic groups. Conclusions. The sclera surrounding the ONH stiffens more rapidly with age in the African descent group compared to the European group. Stiffening of the peripapillary sclera with age may be related to the higher prevalence of glaucoma in the elderly and persons of African descent. PMID:25237162

Human scleral structural stiffness increases more rapidly with age in donors of African descent compared to donors of European descent.

PubMed

Fazio, Massimo A; Grytz, Rafael; Morris, Jeffrey S; Bruno, Luigi; Girkin, Christopher A; Downs, J Crawford

2014-09-18

We tested the hypothesis that the variation of peripapillary scleral structural stiffness with age is different in donors of European (ED) and African (AD) descent. Posterior scleral shells from normal eyes from donors of European (n = 20 pairs; previously reported) and African (n = 9 pairs) descent aged 0 and 90 years old were inflation tested within 48 hours post mortem. Scleral shells were pressurized from 5 to 45 mm Hg and the full-field, 3-dimensional (3D) deformation of the outer surface was recorded at submicrometric accuracy using speckle interferometry (ESPI). Mean maximum principal (tensile) strain of the peripapillary and midperipheral regions surrounding the optic nerve head (ONH) were fit using a functional mixed effects model that accounts for intradonor variability, same-race correlation, and spatial autocorrelation to estimate the effect of race on the age-related changes in mechanical scleral strain. Mechanical tensile strain significantly decreased with age in the peripapillary sclera in the African and European descent groups (P < 0.001), but the age-related stiffening was significantly greater in the African descent group (P < 0.05). Maximum principal strain in the peripapillary sclera was significantly higher than in the midperipheral sclera for both ethnic groups. The sclera surrounding the ONH stiffens more rapidly with age in the African descent group compared to the European group. Stiffening of the peripapillary sclera with age may be related to the higher prevalence of glaucoma in the elderly and persons of African descent. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

CVB: the Constrained Vapor Bubble Capillary Experiment on the International Space Station MARANGONI FLOW REGION

NASA Technical Reports Server (NTRS)

Wayner, Peter C., Jr.; Kundan, Akshay; Plawsky, Joel

2014-01-01

The Constrained Vapor Bubble (CVB) is a wickless, grooved heat pipe and we report on a full- scale fluids experiment flown on the International Space Station (ISS). The CVB system consists of a relatively simple setup a quartz cuvette with sharp corners partially filled with either pentane or an ideal mixture of pentane and isohexane as the working fluids. Along with temperature and pressure measurements, the two-dimensional thickness profile of the menisci formed at the corners of the quartz cuvette was determined using the Light Microscopy Module (LMM). Even with the large, millimeter dimensions of the CVB, interfacial forces dominate in these exceedingly small Bond Number systems. The experiments were carried out at various power inputs. Although conceptually simple, the transport processes were found to be very complex with many different regions. At the heated end of the CVB, due to a high temperature gradient, we observed Marangoni flow at some power inputs. This region from the heated end to the central drop region is defined as a Marangoni dominated region. We present a simple analysis based on interfacial phenomena using only measurements from the ISS experiments that lead to a predictive equation for the thickness of the film near the heated end of the CVB. The average pressure gradient for flow in the film is assumed due to the measured capillary pressure at the two ends of the liquid film and that the pressure stress gradient due to cohesion self adjusts to a constant value over a distance L. The boundary conditions are the no slip condition at the wall interface and an interfacial shear stress at the liquid- vapor interface due to the Marangoni stress, which is due to the high temperature gradient. Although the heated end is extremely complex, since it includes three- dimensional variations in radiation, conduction, evaporation, condensation, fluid flow and interfacial forces, we find that using the above simplifying assumptions, a simple successful model can be developed.

Latin American Immigrant Women and Intergenerational Sex Education

ERIC Educational Resources Information Center

Alcalde, Maria Cristina; Quelopana, Ana Maria

2013-01-01

People of Latin American descent make up the largest and fastest-growing minority group in the USA. Rates of pregnancy, childbirth, and sexually transmitted infections among people of Latin American descent are higher than among other ethnic groups. This paper builds on research that suggests that among families of Latin American descent, mothers…

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

PubMed

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.

Toward a Caribbean psychology: an African-centered approach.

PubMed

Sutherland, Marcia Elizabeth

2011-01-01

Although the Americas and Caribbean region are purported to comprise different ethnic groups, this article’s focus is on people of African descent, who represent the largest ethnic group in many countries. The emphasis on people of African descent is related to their family structure, ethnic identity, cultural, psychohistorical, and contemporary psychosocial realities. This article discusses the limitations of Western psychology for theory, research, and applied work on people of African descent in the Americas and Caribbean region. In view of the adaptations that some people of African descent have made to slavery, colonialism, and more contemporary forms of cultural intrusions, it is argued that when necessary, notwithstanding Western psychology’s limitations, Caribbean psychologists should reconstruct mainstream psychology to address the psychological needs of these Caribbean people. The relationship between theory and psychological interventions for the optimal development of people of African descent is emphasized throughout this article. In this regard, the African-centered and constructionist viewpoint is argued to be of utility in addressing the psychological growth and development of people of African descent living in the Americas and Caribbean region.

Effects of aircraft and flight parameters on energy-efficient profile descents in time-based metered traffic

NASA Technical Reports Server (NTRS)

Dejarnette, F. R.

1984-01-01

Concepts to save fuel while preserving airport capacity by combining time based metering with profile descent procedures were developed. A computer algorithm is developed to provide the flight crew with the information needed to fly from an entry fix to a metering fix and arrive there at a predetermined time, altitude, and airspeed. The flight from the metering fix to an aim point near the airport was calculated. The flight path is divided into several descent and deceleration segments. Descents are performed at constant Mach numbers or calibrated airspeed, whereas decelerations occur at constant altitude. The time and distance associated with each segment are calculated from point mass equations of motion for a clean configuration with idle thrust. Wind and nonstandard atmospheric properties have a large effect on the flight path. It is found that uncertainty in the descent Mach number has a large effect on the predicted flight time. Of the possible combinations of Mach number and calibrated airspeed for a descent, only small changes were observed in the fuel consumed.

Design optimization of single mixed refrigerant LNG process using a hybrid modified coordinate descent algorithm

NASA Astrophysics Data System (ADS)

Qyyum, Muhammad Abdul; Long, Nguyen Van Duc; Minh, Le Quang; Lee, Moonyong

2018-01-01

Design optimization of the single mixed refrigerant (SMR) natural gas liquefaction (LNG) process involves highly non-linear interactions between decision variables, constraints, and the objective function. These non-linear interactions lead to an irreversibility, which deteriorates the energy efficiency of the LNG process. In this study, a simple and highly efficient hybrid modified coordinate descent (HMCD) algorithm was proposed to cope with the optimization of the natural gas liquefaction process. The single mixed refrigerant process was modeled in Aspen Hysys® and then connected to a Microsoft Visual Studio environment. The proposed optimization algorithm provided an improved result compared to the other existing methodologies to find the optimal condition of the complex mixed refrigerant natural gas liquefaction process. By applying the proposed optimization algorithm, the SMR process can be designed with the 0.2555 kW specific compression power which is equivalent to 44.3% energy saving as compared to the base case. Furthermore, in terms of coefficient of performance (COP), it can be enhanced up to 34.7% as compared to the base case. The proposed optimization algorithm provides a deep understanding of the optimization of the liquefaction process in both technical and numerical perspectives. In addition, the HMCD algorithm can be employed to any mixed refrigerant based liquefaction process in the natural gas industry.

Ascent/descent ancillary data production user's guide

NASA Technical Reports Server (NTRS)

Brans, H. R.; Seacord, A. W., II; Ulmer, J. W.

1986-01-01

The Ascent/Descent Ancillary Data Product, also called the A/D BET because it contains a Best Estimate of the Trajectory (BET), is a collection of trajectory, attitude, and atmospheric related parameters computed for the ascent and descent phases of each Shuttle Mission. These computations are executed shortly after the event in a post-flight environment. A collection of several routines including some stand-alone routines constitute what is called the Ascent/Descent Ancillary Data Production Program. A User's Guide for that program is given. It is intended to provide the reader with all the information necessary to generate an Ascent or a Descent Ancillary Data Product. It includes descriptions of the input data and output data for each routine, and contains explicit instructions on how to run each routine. A description of the final output product is given.

Time-specific androgen blockade with flutamide inhibits testicular descent in the rat.

PubMed

Husmann, D A; McPhaul, M J

1991-09-01

Inhibition of androgen action by flutamide, a nonsteroidal antiandrogen, blocked testicular descent in 40% of the testes exposed to this agent continuously from gestational day 13 through postpartal day 28. By contrast, only 11% of the testes failed to descend when blocked by 5 alpha-reductase inhibitors during the same period. Flutamide administration over narrower time intervals (gestational day 13-15, 16-17, or 18-19) revealed maximal interference with testicular descent after androgen inhibition during gestational days 16-17. No significant differences in testicular or epididymal weights were evident between descended and undescended testes; furthermore, no correlation was detected between the presence of epididymal abnormalities and testicular descent. These findings indicate that androgen inhibition during a brief period of embryonic development can block testicular descent. The mechanism through which this inhibition occurs remains to be elucidated.

A conflict analysis of 4D descent strategies in a metered, multiple-arrival route environment

NASA Technical Reports Server (NTRS)

Izumi, K. H.; Harris, C. S.

1990-01-01

A conflict analysis was performed on multiple arrival traffic at a typical metered airport. The Flow Management Evaluation Model (FMEM) was used to simulate arrival operations using Denver Stapleton's arrival route structure. Sensitivities of conflict performance to three different 4-D descent strategies (clear-idle Mach/Constant AirSpeed (CAS), constant descent angle Mach/CAS and energy optimal) were examined for three traffic mixes represented by those found at Denver Stapleton, John F. Kennedy and typical en route metering (ERM) airports. The Monte Carlo technique was used to generate simulation entry point times. Analysis results indicate that the clean-idle descent strategy offers the best compromise in overall performance. Performance measures primarily include susceptibility to conflict and conflict severity. Fuel usage performance is extrapolated from previous descent strategy studies.

Analysis of Flight Management System Predictions of Idle-Thrust Descents

NASA Technical Reports Server (NTRS)

Stell, Laurel

2010-01-01

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 predictor and its uncertainty models, descents from cruise to the meter fix were executed using vertical navigation in a B737-700 simulator and a B777-200 simulator, both with commercial FMSs. For both aircraft types, the FMS computed the intended descent path for a specified speed profile assuming idle thrust after top of descent (TOD), and then it controlled the avionics without human intervention. The test matrix varied aircraft weight, descent speed, and wind conditions. The first analysis in this paper determined the effect of the test matrix parameters on the FMS computation of TOD location, and it compared the results to those for the current ground predictor in the Efficient Descent Advisor (EDA). The second analysis was similar but considered the time to fly a specified distance to the meter fix. The effects of the test matrix variables together with the accuracy requirements for the predictor will determine the allowable error for the predictor inputs. For the B737, the EDA prediction of meter fix crossing time agreed well with the FMS; but its prediction of TOD location probably was not sufficiently accurate to enable idle-thrust descents in congested airspace, even though the FMS and EDA gave similar shapes for TOD location as a function of the test matrix variables. For the B777, the FMS and EDA gave different shapes for the TOD location function, and the EDA prediction of the TOD location is not accurate enough to fully enable the concept. Furthermore, the differences between the FMS and EDA predictions of meter fix crossing time for the B777 indicated that at least one of them was not sufficiently accurate.

Body density affects stroke patterns in Baikal seals.

PubMed

Watanabe, Yuuki; Baranov, Eugene A; Sato, Katsufumi; Naito, Yasuhiko; Miyazaki, Nobuyuki

2006-09-01

Buoyancy is one of the primary external forces acting on air-breathing divers and it can affect their swimming energetics. Because the body composition of marine mammals (i.e. the relative amounts of lower-density lipid and higher-density lean tissue) varies individually and seasonally, their buoyancy also fluctuates widely, and individuals would be expected to adjust their stroke patterns during dives accordingly. To test this prediction, we attached acceleration data loggers to four free-ranging Baikal seals Phoca sibirica in Lake Baikal and monitored flipper stroking activity as well as swimming speed, depth and inclination of the body axis (pitch). In addition to the logger, one seal (Individual 4) was equipped with a lead weight that was jettisoned after a predetermined time period so that we had a set of observations on the same individual with different body densities. These four data sets revealed the general diving patterns of Baikal seals and also provided direct insights into the influence of buoyancy on these patterns. Seals repeatedly performed dives of a mean duration of 7.0 min (max. 15.4 min), interrupted by a mean surface duration of 1.2 min. Dive depths were 66 m on average, but varied substantially, with a maximum depth of 324 m. The seals showed different stroke patterns among individuals; some seals stroked at lower rates during descent than ascent, while the others had higher stroke rates during descent than ascent. When the lead weight was detached from Individual 4, the seal increased its stroke rate in descent by shifting swimming mode from prolonged glides to more stroke-and-glide swimming, and decreased its stroke rate in ascent by shifting from continuous stroking to stroke-and-glide swimming. We conclude that seals adopt different stroke patterns according to their individual buoyancies. We also demonstrate that the terminal speed reached by Individual 4 during prolonged glide in descent depended on its total buoyancy and pitch, with higher speeds reached in the weighted condition and at steeper pitch. A simple physical model allowed us to estimate the body density of the seal from the speed and pitch (1,027-1,046 kg m(-3), roughly corresponding to 32-41% lipid content, for the weighted condition; 1,014-1,022 kg m(-3), 43-47% lipid content, for the unweighted condition).

Rotary Wing Deceleration Use on Titan

NASA Technical Reports Server (NTRS)

Young, Larry A.; Steiner, Ted J.

2011-01-01

Rotary wing decelerator (RWD) systems were compared against other methods of atmospheric deceleration and were determined to show significant potential for application to a system requiring controlled descent, low-velocity landing, and atmospheric research capability on Titan. Design space exploration and down-selection results in a system with a single rotor utilizing cyclic pitch control. Models were developed for selection of a RWD descent system for use on Titan and to determine the relationships between the key design parameters of such a system and the time of descent. The possibility of extracting power from the system during descent was also investigated.

An optimization-based framework for anisotropic simplex mesh adaptation

NASA Astrophysics Data System (ADS)

Yano, Masayuki; Darmofal, David L.

2012-09-01

We present a general framework for anisotropic h-adaptation of simplex meshes. Given a discretization and any element-wise, localizable error estimate, our adaptive method iterates toward a mesh that minimizes error for a given degrees of freedom. Utilizing mesh-metric duality, we consider a continuous optimization problem of the Riemannian metric tensor field that provides an anisotropic description of element sizes. First, our method performs a series of local solves to survey the behavior of the local error function. This information is then synthesized using an affine-invariant tensor manipulation framework to reconstruct an approximate gradient of the error function with respect to the metric tensor field. Finally, we perform gradient descent in the metric space to drive the mesh toward optimality. The method is first demonstrated to produce optimal anisotropic meshes minimizing the L2 projection error for a pair of canonical problems containing a singularity and a singular perturbation. The effectiveness of the framework is then demonstrated in the context of output-based adaptation for the advection-diffusion equation using a high-order discontinuous Galerkin discretization and the dual-weighted residual (DWR) error estimate. The method presented provides a unified framework for optimizing both the element size and anisotropy distribution using an a posteriori error estimate and enables efficient adaptation of anisotropic simplex meshes for high-order discretizations.

Implementation of neural network for color properties of polycarbonates

NASA Astrophysics Data System (ADS)

Saeed, U.; Ahmad, S.; Alsadi, J.; Ross, D.; Rizvi, G.

2014-05-01

In present paper, the applicability of artificial neural networks (ANN) is investigated for color properties of plastics. The neural networks toolbox of Matlab 6.5 is used to develop and test the ANN model on a personal computer. An optimal design is completed for 10, 12, 14,16,18 & 20 hidden neurons on single hidden layer with five different algorithms: batch gradient descent (GD), batch variable learning rate (GDX), resilient back-propagation (RP), scaled conjugate gradient (SCG), levenberg-marquardt (LM) in the feed forward back-propagation neural network model. The training data for ANN is obtained from experimental measurements. There were twenty two inputs including resins, additives & pigments while three tristimulus color values L*, a* and b* were used as output layer. Statistical analysis in terms of Root-Mean-Squared (RMS), absolute fraction of variance (R squared), as well as mean square error is used to investigate the performance of ANN. LM algorithm with fourteen neurons on hidden layer in Feed Forward Back-Propagation of ANN model has shown best result in the present study. The degree of accuracy of the ANN model in reduction of errors is proven acceptable in all statistical analysis and shown in results. However, it was concluded that ANN provides a feasible method in error reduction in specific color tristimulus values.

The Dropout Learning Algorithm

PubMed Central

Baldi, Pierre; Sadowski, Peter

2014-01-01

Dropout is a recently introduced algorithm for training neural network by randomly dropping units during training to prevent their co-adaptation. A mathematical analysis of some of the static and dynamic properties of dropout is provided using Bernoulli gating variables, general enough to accommodate dropout on units or connections, and with variable rates. The framework allows a complete analysis of the ensemble averaging properties of dropout in linear networks, which is useful to understand the non-linear case. The ensemble averaging properties of dropout in non-linear logistic networks result from three fundamental equations: (1) the approximation of the expectations of logistic functions by normalized geometric means, for which bounds and estimates are derived; (2) the algebraic equality between normalized geometric means of logistic functions with the logistic of the means, which mathematically characterizes logistic functions; and (3) the linearity of the means with respect to sums, as well as products of independent variables. The results are also extended to other classes of transfer functions, including rectified linear functions. Approximation errors tend to cancel each other and do not accumulate. Dropout can also be connected to stochastic neurons and used to predict firing rates, and to backpropagation by viewing the backward propagation as ensemble averaging in a dropout linear network. Moreover, the convergence properties of dropout can be understood in terms of stochastic gradient descent. Finally, for the regularization properties of dropout, the expectation of the dropout gradient is the gradient of the corresponding approximation ensemble, regularized by an adaptive weight decay term with a propensity for self-consistent variance minimization and sparse representations. PMID:24771879

Hair Breakage in Patients of African Descent: Role of Dermoscopy

PubMed Central

Quaresma, Maria Victória; Martinez Velasco, María Abril; Tosti, Antonella

2015-01-01

Dermoscopy represents a useful technique for the diagnosis and follow-up of hair and scalp disorders. To date, little has been published regarding dermoscopy findings of hair disorders in patients of African descent. This article illustrates how dermoscopy allows fast diagnosis of hair breakage due to intrinsic factors and chemical damage in African descent patients. PMID:27170942

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

ERIC Educational Resources Information Center

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…

Assembly of multiple cell gradients directed by three-dimensional microfluidic channels.

PubMed

Li, Yiwei; Feng, Xiaojun; Wang, Yachao; Du, Wei; Chen, Peng; Liu, Chao; Liu, Bi-Feng

2015-08-07

Active control over the cell gradient is essential for understanding biological systems and the reconstitution of the functionality of many types of tissues, particularly for organ-on-a-chip. Here, we propose a three-dimensional (3D) microfluidic strategy for generating controllable cell gradients. In this approach, a homogeneous cell suspension is loaded into a 3D stair-shaped PDMS microchannel to generate a cell gradient within 10 min by sedimentation. We demonstrate that cell gradients of various profiles (exponential and piecewise linear) can be achieved by precisely controlling the height of each layer during the fabrication. With sequential seeding, we further demonstrate the generation of two overlapping cell gradients on the same glass substrate with pre-defined designs. The cell gradient-based QD cytotoxicity assay also demonstrated that cell behaviors and resistances were regulated by the changes in cell density. These results reveal that the proposed 3D microfluidic strategy provides a simple and versatile means for establishing controllable gradients in cell density, opening up a new avenue for reconstructing functional tissues.

Teaching Simulation and Computer-Aided Separation Optimization in Liquid Chromatography by Means of Illustrative Microsoft Excel Spreadsheets

ERIC Educational Resources Information Center

Fasoula, S.; Nikitas, P.; Pappa-Louisi, A.

2017-01-01

A series of Microsoft Excel spreadsheets were developed to simulate the process of separation optimization under isocratic and simple gradient conditions. The optimization procedure is performed in a stepwise fashion using simple macros for an automatic application of this approach. The proposed optimization approach involves modeling of the peak…

Device for Lowering Mars Science Laboratory Rover to the Surface

NASA Technical Reports Server (NTRS)

2008-01-01

This is hardware for controlling the final lowering of NASA's Mars Science Laboratory rover to the surface of Mars from the spacecraft's hovering, rocket-powered descent stage.

The photo shows the bridle device assembly, which is about two-thirds of a meter, or 2 feet, from end to end, and has two main parts. The cylinder on the left is the descent brake. On the right is the bridle assembly, including a spool of nylon and Vectran cords that will be attached to the rover.

When pyrotechnic bolts fire to sever the rigid connection between the rover and the descent stage, gravity will pull the tethered rover away from the descent stage. The bridle or tether, attached to three points on the rover, will unspool from the bridle assembly, beginning from the larger-diameter portion of the spool at far right. The rotation rate of the assembly, hence the descent rate of the rover, will be governed by the descent brake. Inside the housing of that brake are gear boxes and banks of mechanical resistors engineered to prevent the bridle from spooling out too quickly or too slowly. The length of the bridle will allow the rover to be lowered about 7.5 meters (25 feet) while still tethered to the descent stage.

The Starsys division of SpaceDev Inc., Poway, Calif., provided the descent brake. NASA's Jet Propulsion Laboratory, Pasadena, Calif., built the bridle assembly. Vectran is a product of Kuraray Co. Ltd., Tokyo. JPL, a division of the California Institute of Technology, manages the Mars Science Laboratory Project for the NASA Science Mission Directorate, Washington.

Antarctic Polar Descent and Planetary Wave Activity Observed in ISAMS CO from April to July 1992

NASA Technical Reports Server (NTRS)

Allen, D. R.; Stanford, J. L.; Nakamura, N.; Lopez-Valverde, M. A.; Lopez-Puertas, M.; Taylor, F. W.; Remedios, J. J.

2000-01-01

Antarctic polar descent and planetary wave activity in the upper stratosphere and lower mesosphere are observed in ISAMS CO data from April to July 1992. CO-derived mean April-to-May upper stratosphere descent rates of 15 K/day (0.25 km/day) at 60 S and 20 K/day (0.33 km/day) at 80 S are compared with descent rates from diabatic trajectory analyses. At 60 S there is excellent agreement, while at 80 S the trajectory-derived descent is significantly larger in early April. Zonal wavenumber 1 enhancement of CO is observed on 9 and 28 May, coincident with enhanced wave 1 in UKMO geopotential height. The 9 May event extends from 40 to 70 km and shows westward phase tilt with height, while the 28 May event extends from 40 to 50 km and shows virtually no phase tilt with height.

The Uncertain Significance of Low Vitamin D levels in African Descent Populations: A Review of the Bone and Cardiometabolic Literature

PubMed Central

O'Connor, Michelle Y; Thoreson, Caroline K; Ramsey, Natalie L M; Ricks, Madia; Sumner, Anne E

2014-01-01

Vitamin D levels in people of African descent are often described as inadequate or deficient. Whether low vitamin D levels in people of African descent lead to compromised bone or cardiometabolic health is unknown. Clarity on this issue is essential because if clinically significant vitamin D deficiency is present, vitamin D supplementation is necessary. However, if vitamin D is metabolically sufficient, vitamin D supplementation could be wasteful of scarce resources and even harmful. In this review vitamin D physiology is described with a focus on issues specific to populations of African descent such as the influence of melanin on endogenous vitamin D production and lactose intolerance on the willingness of people to ingest vitamin D fortified foods. Then data on the relationship of vitamin D to bone and cardiometabolic health in people of African descent are evaluated. PMID:24267433

Descent Assisted Split Habitat Lunar Lander Concept

NASA Technical Reports Server (NTRS)

Mazanek, Daniel D.; Goodliff, Kandyce; Cornelius, David M.

2008-01-01

The Descent Assisted Split Habitat (DASH) lunar lander concept utilizes a disposable braking stage for descent and a minimally sized pressurized volume for crew transport to and from the lunar surface. The lander can also be configured to perform autonomous cargo missions. Although a braking-stage approach represents a significantly different operational concept compared with a traditional two-stage lander, the DASH lander offers many important benefits. These benefits include improved crew egress/ingress and large-cargo unloading; excellent surface visibility during landing; elimination of the need for deep-throttling descent engines; potentially reduced plume-surface interactions and lower vertical touchdown velocity; and reduced lander gross mass through efficient mass staging and volume segmentation. This paper documents the conceptual study on various aspects of the design, including development of sortie and outpost lander configurations and a mission concept of operations; the initial descent trajectory design; the initial spacecraft sizing estimates and subsystem design; and the identification of technology needs

Descent graphs in pedigree analysis: applications to haplotyping, location scores, and marker-sharing statistics.

PubMed Central

Sobel, E.; Lange, K.

1996-01-01

The introduction of stochastic methods in pedigree analysis has enabled geneticists to tackle computations intractable by standard deterministic methods. Until now these stochastic techniques have worked by running a Markov chain on the set of genetic descent states of a pedigree. Each descent state specifies the paths of gene flow in the pedigree and the founder alleles dropped down each path. The current paper follows up on a suggestion by Elizabeth Thompson that genetic descent graphs offer a more appropriate space for executing a Markov chain. A descent graph specifies the paths of gene flow but not the particular founder alleles traveling down the paths. This paper explores algorithms for implementing Thompson's suggestion for codominant markers in the context of automatic haplotyping, estimating location scores, and computing gene-clustering statistics for robust linkage analysis. Realistic numerical examples demonstrate the feasibility of the algorithms. PMID:8651310

Gradient Pre-Emphasis to Counteract First-Order Concomitant Fields on Asymmetric MRI Gradient Systems

PubMed Central

Tao, Shengzhen; Weavers, Paul T.; Trzasko, Joshua D.; Shu, Yunhong; Huston, John; Lee, Seung-Kyun; Frigo, Louis M.; Bernstein, Matt A.

2016-01-01

PURPOSE To develop a gradient pre-emphasis scheme that prospectively counteracts the effects of the first-order concomitant fields for any arbitrary gradient waveform played on asymmetric gradient systems, and to demonstrate the effectiveness of this approach using a real-time implementation on a compact gradient system. METHODS After reviewing the first-order concomitant fields that are present on asymmetric gradients, a generalized gradient pre-emphasis model assuming arbitrary gradient waveforms is developed to counteract their effects. A numerically straightforward, simple to implement approximate solution to this pre-emphasis problem is derived, which is compatible with the current hardware infrastructure used on conventional MRI scanners for eddy current compensation. The proposed method was implemented on the gradient driver sub-system, and its real-time use was tested using a series of phantom and in vivo data acquired from 2D Cartesian phase-difference, echo-planar imaging (EPI) and spiral acquisitions. RESULTS The phantom and in vivo results demonstrate that unless accounted for, first-order concomitant fields introduce considerable phase estimation error into the measured data and result in images exhibiting spatially dependent blurring/distortion. The resulting artifacts are effectively prevented using the proposed gradient pre-emphasis. CONCLUSION An efficient and effective gradient pre-emphasis framework is developed to counteract the effects of first-order concomitant fields of asymmetric gradient systems. PMID:27373901

Spherical gradient-index lenses as perfect imaging and maximum power transfer devices.

PubMed

Gordon, J M

2000-08-01

Gradient-index lenses can be viewed from the perspectives of both imaging and nonimaging optics, that is, in terms of both image fidelity and achievable flux concentration. The simple class of gradient-index lenses with spherical symmetry, often referred to as modified Luneburg lenses, is revisited. An alternative derivation for established solutions is offered; the method of Fermat's strings and the principle of skewness conservation are invoked. Then these nominally perfect imaging devices are examined from the additional vantage point of power transfer, and the degree to which they realize the thermodynamic limit to flux concentration is determined. Finally, the spherical gradient-index lens of the fish eye is considered as a modified Luneburg lens optimized subject to material constraints.

The Role of Nonlinear Gradients in Parallel Imaging: A k-Space Based Analysis.

PubMed

Galiana, Gigi; Stockmann, Jason P; Tam, Leo; Peters, Dana; Tagare, Hemant; Constable, R Todd

2012-09-01

Sequences that encode the spatial information of an object using nonlinear gradient fields are a new frontier in MRI, with potential to provide lower peripheral nerve stimulation, windowed fields of view, tailored spatially-varying resolution, curved slices that mirror physiological geometry, and, most importantly, very fast parallel imaging with multichannel coils. The acceleration for multichannel images is generally explained by the fact that curvilinear gradient isocontours better complement the azimuthal spatial encoding provided by typical receiver arrays. However, the details of this complementarity have been more difficult to specify. We present a simple and intuitive framework for describing the mechanics of image formation with nonlinear gradients, and we use this framework to review some the main classes of nonlinear encoding schemes.

Descent Equations Starting from High Rank Chern-Simons

NASA Astrophysics Data System (ADS)

Kang, Bei; Pan, Yi; Wu, Ke; Yang, Jie; Yang, Zi-Feng

2018-04-01

In this paper a set of generalized descent equations are proposed. The solutions to those descent equations labeled by r for any r (r ≥ 2, r ɛ ℕ) are forms of degrees varying from 0 to (2r ‑ 1). And the case of r = 2 is mainly discussed. Supported by National Natural Science Foundation of China under Grant Nos. 11475116, 11401400

Mars Science Laboratory Entry, Descent and Landing System Overview

NASA Technical Reports Server (NTRS)

Steltzner, Adam D.; San Martin, A. Miguel; Rivellini, Tomasso P.; Chen, Allen

2013-01-01

The Mars Science Laboratory project recently places the Curiosity rove on the surface of Mars. With the success of the landing system, the performance envelope of entry, descent and landing capabilities has been extended over the previous state of the art. This paper will present an overview to the MSL entry, descent and landing system design and preliminary flight performance results.

Study of Some Planetary Atmospheres Features by Probe Entry and Descent Simulations

NASA Technical Reports Server (NTRS)

Gil, P. J. S.; Rosa, P. M. B.

2005-01-01

Characterization of planetary atmospheres is analyzed by its effects in the entry and descent trajectories of probes. Emphasis is on the most important variables that characterize atmospheres e.g. density profile with altitude. Probe trajectories are numerically determined with ENTRAP, a developing multi-purpose computational tool for entry and descent trajectory simulations capable of taking into account many features and perturbations. Real data from Mars Pathfinder mission is used. The goal is to be able to determine more accurately the atmosphere structure by observing real trajectories and what changes are to expect in probe descent trajectories if atmospheres have different properties than the ones assumed initially.

Rapid Generation of Optimal Asteroid Powered Descent Trajectories Via Convex Optimization

NASA Technical Reports Server (NTRS)

Pinson, Robin; Lu, Ping

2015-01-01

This paper investigates a convex optimization based method that can rapidly generate the fuel optimal asteroid powered descent trajectory. The ultimate goal is to autonomously design the optimal powered descent trajectory on-board the spacecraft immediately prior to the descent burn. Compared to a planetary powered landing problem, the major difficulty is the complex gravity field near the surface of an asteroid that cannot be approximated by a constant gravity field. This paper uses relaxation techniques and a successive solution process that seeks the solution to the original nonlinear, nonconvex problem through the solutions to a sequence of convex optimal control problems.

NASA aviation safety reporting system

NASA Technical Reports Server (NTRS)

1978-01-01

Reports describing various types of communication problems are presented along with summaries dealing with judgment and decision making. Concerns relating to the ground proximity warning system are summarized and several examples of true terrain proximity warnings are provided. An analytic study of reports relating to profile descents was performed. Problems were found to be associated with charting and graphic presentation of the descents, with lack of uniformity of the descent procedures among facilities using them, and with the flight crew workload engendered by profile descents, particularly when additional requirements are interposed by air traffic control during the execution of the profiles. A selection of alert bulletins and responses to them were reviewed.

Tracer-based Determination of Vortex Descent in the 1999/2000 Arctic Winter

NASA Technical Reports Server (NTRS)

Greenblatt, Jeffrey B.; Jost, Hans-Juerg; Loewenstein, Max; Podolske, James R.; Hurst, Dale F.; Elkins, James W.; Schauffler, Sue M.; Atlas, Elliot L.; Herman, Robert L.; Webster, Chrisotopher R.

2002-01-01

A detailed analysis of available in situ and remotely sensed N2O and CH4 data measured in the 1999/2000 winter Arctic vortex has been performed in order to quantify the temporal evolution of vortex descent. Differences in potential temperature (theta) among balloon and aircraft vertical profiles (an average of 19-23 K on a given N2O or CH4 isopleth) indicated significant vortex inhomogeneity in late fall as compared with late winter profiles. A composite fall vortex profile was constructed for 26 November 1999, whose error bars encompassed the observed variability. High-latitude extravortex profiles measured in different years and seasons revealed substantial variability in N2O and CH4 on theta surfaces, but all were clearly distinguishable from the first vortex profiles measured in late fall 1999. From these extravortex-vortex differences we inferred descent prior to 26 November: as much as 397 plus or minus 15 K (lsigma) at 30 ppbv N2O and 640 ppbv CH4, and falling to 28 plus or minus 13 K above 200 ppbv N2O and 1280 ppbv CH4. Changes in theta were determined on five N2O and CH4 isopleths from 26 November through 12 March, and descent rates were calculated on each N2O isopleth for several time intervals. The maximum descent rates were seen between 26 November and 27 January: 0.82 plus or minus 0.20 K/day averaged over 50- 250 ppbv N2O. By late winter (26 February to 12 March), the average rate had decreased to 0.10 plus or minus 0.25 K/day. Descent rates also decreased with increasing N2O; the winter average (26 November to 5 March) descent rate varied from 0.75 plus or minus 0.10 K/day at 50 ppbv to 0.40 plus or minus 0.11 K/day at 250 ppbv. Comparison of these results with observations and models of descent in prior years showed very good overall agreement. Two models of the 1999/2000 vortex descent, SLIMCAT and REPROBUS, despite theta offsets with respect to observed profiles of up to 20 K on most tracer isopleths, produced descent rates that agreed very favorably with the inferred rates from observation.

Variational stereo imaging of oceanic waves with statistical constraints.

PubMed

Gallego, Guillermo; Yezzi, Anthony; Fedele, Francesco; Benetazzo, Alvise

2013-11-01

An image processing observational technique for the stereoscopic reconstruction of the waveform of oceanic sea states is developed. The technique incorporates the enforcement of any given statistical wave law modeling the quasi-Gaussianity of oceanic waves observed in nature. The problem is posed in a variational optimization framework, where the desired waveform is obtained as the minimizer of a cost functional that combines image observations, smoothness priors and a weak statistical constraint. The minimizer is obtained by combining gradient descent and multigrid methods on the necessary optimality equations of the cost functional. Robust photometric error criteria and a spatial intensity compensation model are also developed to improve the performance of the presented image matching strategy. The weak statistical constraint is thoroughly evaluated in combination with other elements presented to reconstruct and enforce constraints on experimental stereo data, demonstrating the improvement in the estimation of the observed ocean surface.

Material parameter estimation with terahertz time-domain spectroscopy.

PubMed

Dorney, T D; Baraniuk, R G; Mittleman, D M

2001-07-01

Imaging systems based on terahertz (THz) time-domain spectroscopy offer a range of unique modalities owing to the broad bandwidth, subpicosecond duration, and phase-sensitive detection of the THz pulses. Furthermore, the possibility exists for combining spectroscopic characterization or identification with imaging because the radiation is broadband in nature. To achieve this, we require novel methods for real-time analysis of THz waveforms. This paper describes a robust algorithm for extracting material parameters from measured THz waveforms. Our algorithm simultaneously obtains both the thickness and the complex refractive index of an unknown sample under certain conditions. In contrast, most spectroscopic transmission measurements require knowledge of the sample's thickness for an accurate determination of its optical parameters. Our approach relies on a model-based estimation, a gradient descent search, and the total variation measure. We explore the limits of this technique and compare the results with literature data for optical parameters of several different materials.

Asynchronous Incremental Stochastic Dual Descent Algorithm for Network Resource Allocation

NASA Astrophysics Data System (ADS)

Bedi, Amrit Singh; Rajawat, Ketan

2018-05-01

Stochastic network optimization problems entail finding resource allocation policies that are optimum on an average but must be designed in an online fashion. Such problems are ubiquitous in communication networks, where resources such as energy and bandwidth are divided among nodes to satisfy certain long-term objectives. This paper proposes an asynchronous incremental dual decent resource allocation algorithm that utilizes delayed stochastic {gradients} for carrying out its updates. The proposed algorithm is well-suited to heterogeneous networks as it allows the computationally-challenged or energy-starved nodes to, at times, postpone the updates. The asymptotic analysis of the proposed algorithm is carried out, establishing dual convergence under both, constant and diminishing step sizes. It is also shown that with constant step size, the proposed resource allocation policy is asymptotically near-optimal. An application involving multi-cell coordinated beamforming is detailed, demonstrating the usefulness of the proposed algorithm.

Wavefront sensorless adaptive optics ophthalmoscopy in the human eye

PubMed Central

Hofer, Heidi; Sredar, Nripun; Queener, Hope; Li, Chaohong; Porter, Jason

2011-01-01

Wavefront sensor noise and fidelity place a fundamental limit on achievable image quality in current adaptive optics ophthalmoscopes. Additionally, the wavefront sensor ‘beacon’ can interfere with visual experiments. We demonstrate real-time (25 Hz), wavefront sensorless adaptive optics imaging in the living human eye with image quality rivaling that of wavefront sensor based control in the same system. A stochastic parallel gradient descent algorithm directly optimized the mean intensity in retinal image frames acquired with a confocal adaptive optics scanning laser ophthalmoscope (AOSLO). When imaging through natural, undilated pupils, both control methods resulted in comparable mean image intensities. However, when imaging through dilated pupils, image intensity was generally higher following wavefront sensor-based control. Despite the typically reduced intensity, image contrast was higher, on average, with sensorless control. Wavefront sensorless control is a viable option for imaging the living human eye and future refinements of this technique may result in even greater optical gains. PMID:21934779

High-resolution coded-aperture design for compressive X-ray tomography using low resolution detectors

NASA Astrophysics Data System (ADS)

Mojica, Edson; Pertuz, Said; Arguello, Henry

2017-12-01

One of the main challenges in Computed Tomography (CT) is obtaining accurate reconstructions of the imaged object while keeping a low radiation dose in the acquisition process. In order to solve this problem, several researchers have proposed the use of compressed sensing for reducing the amount of measurements required to perform CT. This paper tackles the problem of designing high-resolution coded apertures for compressed sensing computed tomography. In contrast to previous approaches, we aim at designing apertures to be used with low-resolution detectors in order to achieve super-resolution. The proposed method iteratively improves random coded apertures using a gradient descent algorithm subject to constraints in the coherence and homogeneity of the compressive sensing matrix induced by the coded aperture. Experiments with different test sets show consistent results for different transmittances, number of shots and super-resolution factors.

Monte Carlo-based Reconstruction in Water Cherenkov Detectors using Chroma

NASA Astrophysics Data System (ADS)

Seibert, Stanley; Latorre, Anthony

2012-03-01

We demonstrate the feasibility of event reconstruction---including position, direction, energy and particle identification---in water Cherenkov detectors with a purely Monte Carlo-based method. Using a fast optical Monte Carlo package we have written, called Chroma, in combination with several variance reduction techniques, we can estimate the value of a likelihood function for an arbitrary event hypothesis. The likelihood can then be maximized over the parameter space of interest using a form of gradient descent designed for stochastic functions. Although slower than more traditional reconstruction algorithms, this completely Monte Carlo-based technique is universal and can be applied to a detector of any size or shape, which is a major advantage during the design phase of an experiment. As a specific example, we focus on reconstruction results from a simulation of the 200 kiloton water Cherenkov far detector option for LBNE.

Adaptive beam shaping for improving the power coupling of a two-Cassegrain-telescope

NASA Astrophysics Data System (ADS)

Ma, Haotong; Hu, Haojun; Xie, Wenke; Zhao, Haichuan; Xu, Xiaojun; Chen, Jinbao

2013-08-01

We demonstrate the adaptive beam shaping for improving the power coupling of a two-Cassegrain-telescope based on the stochastic parallel gradient descent (SPGD) algorithm and dual phase only liquid crystal spatial light modulators (LC-SLMs). Adaptive pre-compensation the wavefront of projected laser beam at the transmitter telescope is chosen to improve the power coupling efficiency. One phase only LC-SLM adaptively optimizes phase distribution of the projected laser beam and the other generates turbulence phase screen. The intensity distributions of the dark hollow beam after passing through the turbulent atmosphere with and without adaptive beam shaping are analyzed in detail. The influence of propagation distance and aperture size of the Cassegrain-telescope on coupling efficiency are investigated theoretically and experimentally. These studies show that the power coupling can be significantly improved by adaptive beam shaping. The technique can be used in optical communication, deep space optical communication and relay mirror.

Learning and optimization with cascaded VLSI neural network building-block chips

NASA Technical Reports Server (NTRS)

Duong, T.; Eberhardt, S. P.; Tran, M.; Daud, T.; Thakoor, A. P.

1992-01-01

To demonstrate the versatility of the building-block approach, two neural network applications were implemented on cascaded analog VLSI chips. Weights were implemented using 7-b multiplying digital-to-analog converter (MDAC) synapse circuits, with 31 x 32 and 32 x 32 synapses per chip. A novel learning algorithm compatible with analog VLSI was applied to the two-input parity problem. The algorithm combines dynamically evolving architecture with limited gradient-descent backpropagation for efficient and versatile supervised learning. To implement the learning algorithm in hardware, synapse circuits were paralleled for additional quantization levels. The hardware-in-the-loop learning system allocated 2-5 hidden neurons for parity problems. Also, a 7 x 7 assignment problem was mapped onto a cascaded 64-neuron fully connected feedback network. In 100 randomly selected problems, the network found optimal or good solutions in most cases, with settling times in the range of 7-100 microseconds.

Off-Policy Integral Reinforcement Learning Method to Solve Nonlinear Continuous-Time Multiplayer Nonzero-Sum Games.

PubMed

Song, Ruizhuo; Lewis, Frank L; Wei, Qinglai

2017-03-01

This paper establishes an off-policy integral reinforcement learning (IRL) method to solve nonlinear continuous-time (CT) nonzero-sum (NZS) games with unknown system dynamics. The IRL algorithm is presented to obtain the iterative control and off-policy learning is used to allow the dynamics to be completely unknown. Off-policy IRL is designed to do policy evaluation and policy improvement in the policy iteration algorithm. Critic and action networks are used to obtain the performance index and control for each player. The gradient descent algorithm makes the update of critic and action weights simultaneously. The convergence analysis of the weights is given. The asymptotic stability of the closed-loop system and the existence of Nash equilibrium are proved. The simulation study demonstrates the effectiveness of the developed method for nonlinear CT NZS games with unknown system dynamics.

Active semi-supervised learning method with hybrid deep belief networks.

PubMed

Zhou, Shusen; Chen, Qingcai; Wang, Xiaolong

2014-01-01

In this paper, we develop a novel semi-supervised learning algorithm called active hybrid deep belief networks (AHD), to address the semi-supervised sentiment classification problem with deep learning. First, we construct the previous several hidden layers using restricted Boltzmann machines (RBM), which can reduce the dimension and abstract the information of the reviews quickly. Second, we construct the following hidden layers using convolutional restricted Boltzmann machines (CRBM), which can abstract the information of reviews effectively. Third, the constructed deep architecture is fine-tuned by gradient-descent based supervised learning with an exponential loss function. Finally, active learning method is combined based on the proposed deep architecture. We did several experiments on five sentiment classification datasets, and show that AHD is competitive with previous semi-supervised learning algorithm. Experiments are also conducted to verify the effectiveness of our proposed method with different number of labeled reviews and unlabeled reviews respectively.

Impact of a variational objective analysis scheme on a regional area numerical model: The Italian Air Force Weather Service experience

NASA Astrophysics Data System (ADS)

Bonavita, M.; Torrisi, L.

2005-03-01

A new data assimilation system has been designed and implemented at the National Center for Aeronautic Meteorology and Climatology of the Italian Air Force (CNMCA) in order to improve its operational numerical weather prediction capabilities and provide more accurate guidance to operational forecasters. The system, which is undergoing testing before operational use, is based on an “observation space” version of the 3D-VAR method for the objective analysis component, and on the High Resolution Regional Model (HRM) of the Deutscher Wetterdienst (DWD) for the prognostic component. Notable features of the system include a completely parallel (MPI+OMP) implementation of the solution of analysis equations by a preconditioned conjugate gradient descent method; correlation functions in spherical geometry with thermal wind constraint between mass and wind field; derivation of the objective analysis parameters from a statistical analysis of the innovation increments.

Multi-Sensor Registration of Earth Remotely Sensed Imagery

NASA Technical Reports Server (NTRS)

LeMoigne, Jacqueline; Cole-Rhodes, Arlene; Eastman, Roger; Johnson, Kisha; Morisette, Jeffrey; Netanyahu, Nathan S.; Stone, Harold S.; Zavorin, Ilya; Zukor, Dorothy (Technical Monitor)

2001-01-01

Assuming that approximate registration is given within a few pixels by a systematic correction system, we develop automatic image registration methods for multi-sensor data with the goal of achieving sub-pixel accuracy. Automatic image registration is usually defined by three steps; feature extraction, feature matching, and data resampling or fusion. Our previous work focused on image correlation methods based on the use of different features. In this paper, we study different feature matching techniques and present five algorithms where the features are either original gray levels or wavelet-like features, and the feature matching is based on gradient descent optimization, statistical robust matching, and mutual information. These algorithms are tested and compared on several multi-sensor datasets covering one of the EOS Core Sites, the Konza Prairie in Kansas, from four different sensors: IKONOS (4m), Landsat-7/ETM+ (30m), MODIS (500m), and SeaWIFS (1000m).

Efficient numerical calculation of MHD equilibria with magnetic islands, with particular application to saturated neoclassical tearing modes

NASA Astrophysics Data System (ADS)

Raburn, Daniel Louis

We have developed a preconditioned, globalized Jacobian-free Newton-Krylov (JFNK) solver for calculating equilibria with magnetic islands. The solver has been developed in conjunction with the Princeton Iterative Equilibrium Solver (PIES) and includes two notable enhancements over a traditional JFNK scheme: (1) globalization of the algorithm by a sophisticated backtracking scheme, which optimizes between the Newton and steepest-descent directions; and, (2) adaptive preconditioning, wherein information regarding the system Jacobian is reused between Newton iterations to form a preconditioner for our GMRES-like linear solver. We have developed a formulation for calculating saturated neoclassical tearing modes (NTMs) which accounts for the incomplete loss of a bootstrap current due to gradients of multiple physical quantities. We have applied the coupled PIES-JFNK solver to calculate saturated island widths on several shots from the Tokamak Fusion Test Reactor (TFTR) and have found reasonable agreement with experimental measurement.

Learning and tuning fuzzy logic controllers through reinforcements.

PubMed

Berenji, H R; Khedkar, P

1992-01-01

A method for learning and tuning a fuzzy logic controller based on reinforcements from a dynamic system is presented. It is shown that: the generalized approximate-reasoning-based intelligent control (GARIC) architecture learns and tunes a fuzzy logic controller even when only weak reinforcement, such as a binary failure signal, is available; introduces a new conjunction operator in computing the rule strengths of fuzzy control rules; introduces a new localized mean of maximum (LMOM) method in combining the conclusions of several firing control rules; and learns to produce real-valued control actions. Learning is achieved by integrating fuzzy inference into a feedforward network, which can then adaptively improve performance by using gradient descent methods. The GARIC architecture is applied to a cart-pole balancing system and demonstrates significant improvements in terms of the speed of learning and robustness to changes in the dynamic system's parameters over previous schemes for cart-pole balancing.

African and Non-African Admixture Components in African Americans and An African Caribbean Population

PubMed Central

Murray, Tanda; Beaty, Terri H.; Mathias, Rasika A.; Rafaels, Nicholas; Grant, Audrey Virginia; Faruque, Mezbah U.; Watson, Harold R.; Ruczinski, Ingo; Dunston, Georgia M.; Barnes, Kathleen C.

2013-01-01

Admixture is a potential source of confounding in genetic association studies, so it becomes important to detect and estimate admixture in a sample of unrelated individuals. Populations of African descent in the US and the Caribbean share similar historical backgrounds but the distributions of African admixture may differ. We selected 416 ancestry informative markers (AIMs) to estimate and compare admixture proportions using STRUCTURE in 906 unrelated African Americans (AAs) and 294 Barbadians (ACs) from a study of asthma. This analysis showed AAs on average were 72.5% African, 19.6% European and 8% Asian, while ACs were 77.4% African, 15.9% European, and 6.7% Asian which were significantly different. A principal components analysis based on these AIMs yielded one primary eigenvector that explained 54.04% of the variation and captured a gradient from West African to European admixture. This principal component was highly correlated with African vs. European ancestry as estimated by STRUCTURE (r2 = 0.992, r2 = 0.912, respectively). To investigate other African contributions to African American and Barbadian admixture, we performed PCA on ~14,000 (14k) genome-wide SNPs in AAs, ACs, Yorubans, Luhya and Maasai African groups, and estimated genetic distances (FST). We found AAs and ACs were closest genetically (FST = 0.008), and both were closer to the Yorubans than the other East African populations. In our sample of individuals of African descent, ~400 well-defined AIMs were just as good for detecting substructure as ~14,000 random SNPs drawn from a genome-wide panel of markers. PMID:20717976

Cancer patterns among children of Turkish descent in Germany: A study at the German Childhood Cancer Registry

PubMed Central

Spallek, Jacob; Spix, Claudia; Zeeb, Hajo; Kaatsch, Peter; Razum, Oliver

2008-01-01

Background Cancer risks of migrants might differ from risks of the indigenous population due to differences in socioeconomic status, life style, or genetic factors. The aim of this study was to investigate cancer patterns among children of Turkish descent in Germany. Methods We identified cases with Turkish names (as a proxy of Turkish descent) among the 37,259 cases of childhood cancer registered in the German Childhood Cancer Registry (GCCR) during 1980–2005. As it is not possible to obtain reference population data for children of Turkish descent, the distribution of cancer diagnoses was compared between cases of Turkish descent and all remaining (mainly German) cases in the registry, using proportional cancer incidence ratios (PCIRs). Results The overall distribution of cancer diagnoses was similar in the two groups. The PCIRs in three diagnosis groups were increased for cases of Turkish descent: acute non-lymphocytic leukaemia (PCIR 1.23; CI (95%) 1.02–1.47), Hodgkin's disease (1.34; 1.13–1.59) and Non-Hodgkin/Burkitt lymphoma (1.19; 1.02–1.39). Age, sex, and period of diagnosis showed no influence on the distribution of diagnoses. Conclusion No major differences were found in cancer patterns among cases of Turkish descent compared to all other cases in the GCCR. Slightly higher proportions of systemic malignant diseases indicate that analytical studies involving migrants may help investigating the causes of such cancers. PMID:18462495

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

NASA Technical Reports Server (NTRS)

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.

Guiding neuron development with planar surface gradients of substrate cues deposited using microfluidic devices.

PubMed

Millet, Larry J; Stewart, Matthew E; Nuzzo, Ralph G; Gillette, Martha U

2010-06-21

Wiring the nervous system relies on the interplay of intrinsic and extrinsic signaling molecules that control neurite extension, neuronal polarity, process maturation and experience-dependent refinement. Extrinsic signals establish and enrich neuron-neuron interactions during development. Understanding how such extrinsic cues direct neurons to establish neural connections in vitro will facilitate the development of organized neural networks for investigating the development and function of nervous system networks. Producing ordered networks of neurons with defined connectivity in vitro presents special technical challenges because the results must be compliant with the biological requirements of rewiring neural networks. Here we demonstrate the ability to form stable, instructive surface-bound gradients of laminin that guide postnatal hippocampal neuron development in vitro. Our work uses a three-channel, interconnected microfluidic device that permits the production of adlayers of planar substrates through the combination of laminar flow, diffusion and physisorption. Through simple flow modifications, a variety of patterns and gradients of laminin (LN) and fluorescein isothiocyanate-conjugated poly-l-lysine (FITC-PLL) were deposited to present neurons with an instructive substratum to guide neuronal development. We present three variations in substrate design that produce distinct growth regimens for postnatal neurons in dispersed cell cultures. In the first approach, diffusion-mediated gradients of LN were formed on cover slips to guide neurons toward increasing LN concentrations. In the second approach, a combined gradient of LN and FITC-PLL was produced using aspiration-driven laminar flow to restrict neuronal growth to a 15 microm wide growth zone at the center of the two superimposed gradients. The last approach demonstrates the capacity to combine binary lines of FITC-PLL in conjunction with surface gradients of LN and bovine serum albumin (BSA) to produce substrate adlayers that provide additional levels of control over growth. This work demonstrates the advantages of spatio-temporal fluid control for patterning surface-bound gradients using a simple microfluidics-based substrate deposition procedure. We anticipate that this microfluidics-based patterning approach will provide instructive patterns and surface-bound gradients to enable a new level of control in guiding neuron development and network formation.

Asymptotic boundary conditions for dissipative waves: General theory

NASA Technical Reports Server (NTRS)

Hagstrom, Thomas

1990-01-01

An outstanding issue in the computational analysis of time dependent problems is the imposition of appropriate radiation boundary conditions at artificial boundaries. Accurate conditions are developed which are based on the asymptotic analysis of wave propagation over long ranges. Employing the method of steepest descents, dominant wave groups are identified and simple approximations to the dispersion relation are considered in order to derive local boundary operators. The existence of a small number of dominant wave groups may be expected for systems with dissipation. Estimates of the error as a function of domain size are derived under general hypotheses, leading to convergence results. Some practical aspects of the numerical construction of the asymptotic boundary operators are also discussed.

Optimal Pitch Thrust-Vector Angle and Benefits for all Flight Regimes

NASA Technical Reports Server (NTRS)

Gilyard, Glenn B.; Bolonkin, Alexander

2000-01-01

The NASA Dryden Flight Research Center is exploring the optimum thrust-vector angle on aircraft. Simple aerodynamic performance models for various phases of aircraft flight are developed and optimization equations and algorithms are presented in this report. Results of optimal angles of thrust vectors and associated benefits for various flight regimes of aircraft (takeoff, climb, cruise, descent, final approach, and landing) are given. Results for a typical wide-body transport aircraft are also given. The benefits accruable for this class of aircraft are small, but the technique can be applied to other conventionally configured aircraft. The lower L/D aerodynamic characteristics of fighters generally would produce larger benefits than those produced for transport aircraft.

Efficient Approaches for Evaluating the Planar Microstrip Green's Function and its Applications to the Analysis of Microstrip Antennas.

NASA Astrophysics Data System (ADS)

Barkeshli, Sina

A relatively simple and efficient closed form asymptotic representation of the microstrip dyadic surface Green's function is developed. The large parameter in this asymptotic development is proportional to the lateral separation between the source and field points along the planar microstrip configuration. Surprisingly, this asymptotic solution remains accurate even for very small (almost two tenths of a wavelength) lateral separation of the source and field points. The present asymptotic Green's function will thus allow a very efficient calculation of the currents excited on microstrip antenna patches/feed lines and monolithic millimeter and microwave integrated circuit (MIMIC) elements based on a moment method (MM) solution of an integral equation for these currents. The kernal of the latter integral equation is the present asymptotic form of the microstrip Green's function. It is noted that the conventional Sommerfeld integral representation of the microstrip surface Green's function is very poorly convergent when used in this MM formulation. In addition, an efficient exact steepest descent path integral form employing a radially propagating representation of the microstrip dyadic Green's function is also derived which exhibits a relatively faster convergence when compared to the conventional Sommerfeld integral representation. The same steepest descent form could also be obtained by deforming the integration contour of the conventional Sommerfeld representation; however, the radially propagating integral representation exhibits better convergence properties for laterally separated source and field points even before the steepest descent path of integration is used. Numerical results based on the efficient closed form asymptotic solution for the microstrip surface Green's function developed in this work are presented for the mutual coupling between a pair of dipoles on a single layer grounded dielectric slab. The accuracy of the latter calculations is confirmed by comparison with results based on an exact integral representation for that Green's function.

A Simple Experiment for Visualizing Diffusion

ERIC Educational Resources Information Center

Helseth, L. E.

2011-01-01

We propose a simple and fascinating experiment for studying diffusion in gels using a pH-sensitive dye. By doping agar with methyl red, we obtain a gel which rapidly reacts to changes in pH by changing its absorption spectrum. The pH gradients can be followed using a digital camera, and we demonstrate here that the pH-sensitive colour changes can…

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

ERIC Educational Resources Information Center

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…

Use of Total Electron Content data to analyze ionosphere electron density gradients

NASA Astrophysics Data System (ADS)

Nava, B.; Radicella, S. M.; Leitinger, R.; Coisson, P.

In presence of electron density gradients the thin shell approximation for the ionosphere used together with a simple mapping function to convert slant Total Electron Content TEC to vertical TEC could lead to TEC conversion errors Therefore these mapping function errors can be used to identify the effects of the electron density gradients in the ionosphere In the present work high precision GPS derived slant TEC data have been used to investigate the effects of the electron density gradients in the middle and low latitude ionosphere under geomagnetic quiet and disturbed conditions In particular the data corresponding to the geographic area of the American sector for the days 5-7 April 2000 have been used to perform a complete analysis of mapping function errors based on the coinciding pierce point technique The results clearly illustrate the electron density gradient effects according to the locations considered and to the actual levels of disturbance of the ionosphere

Surface erosion caused on Mars from Viking descent engine plume

USGS Publications Warehouse

Hutton, R.E.; Moore, H.J.; Scott, R.F.; Shorthill, R.W.; Spitzer, C.R.

1980-01-01

During the Martian landings the descent engine plumes on Viking Lander 1 (VL-1) and Viking Lander 2 (VL-2) eroded the Martian surface materials. This had been anticipated and investigated both analytically and experimentally during the design phase of the Viking spacecraft. This paper presents data on erosion obtained during the tests of the Viking descent engine and the evidence for erosion by the descent engines of VL-1 and VL-2 on Mars. From these and other results, it is concluded that there are four distinct surface materials on Mars: (1) drift material, (2) crusty to cloddy material, (3) blocky material, and (4) rock. ?? 1980 D. Reidel Publishing Co.

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

NASA Technical Reports Server (NTRS)

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.

Tunable, Flexible, and Efficient Optimization of Control Pulses for Practical Qubits

NASA Astrophysics Data System (ADS)

Machnes, Shai; Assémat, Elie; Tannor, David; Wilhelm, Frank K.

2018-04-01

Quantum computation places very stringent demands on gate fidelities, and experimental implementations require both the controls and the resultant dynamics to conform to hardware-specific constraints. Superconducting qubits present the additional requirement that pulses must have simple parameterizations, so they can be further calibrated in the experiment, to compensate for uncertainties in system parameters. Other quantum technologies, such as sensing, require extremely high fidelities. We present a novel, conceptually simple and easy-to-implement gradient-based optimal control technique named gradient optimization of analytic controls (GOAT), which satisfies all the above requirements, unlike previous approaches. To demonstrate GOAT's capabilities, with emphasis on flexibility and ease of subsequent calibration, we optimize fast coherence-limited pulses for two leading superconducting qubits architectures—flux-tunable transmons and fixed-frequency transmons with tunable couplers.

Partial exposure of frog heart to high-potassium solution: an easily reproducible model mimicking ST segment changes.

PubMed

Kon, Nobuaki; Abe, Nozomu; Miyazaki, Masahiro; Mushiake, Hajime; Kazama, Itsuro

2018-04-18

By simply inducing burn injuries on the bullfrog heart, we previously reported a simple model of abnormal ST segment changes observed in human ischemic heart disease. In the present study, instead of inducing burn injuries, we partially exposed the surface of the frog heart to high-potassium (K + ) solution to create a concentration gradient of the extracellular K + within the myocardium. Dual recordings of ECG and the cardiac action potential demonstrated significant elevation of the ST segment and the resting membrane potential, indicating its usefulness as a simple model of heart injury. Additionally, from our results, Na + /K + -ATPase activity was thought to be primarily responsible for generating the K + concentration gradient and inducing the ST segment changes in ECG.

Highly efficient organic solar cells with improved vertical donor-acceptor compositional gradient via an inverted off-center spinning method

DOE PAGES

Huang, Jiang; Carpenter, Joshua H.; Li, Chang -Zhi; ...

2015-12-02

A novel, yet simple solution fabrication technique to address the trade-off between photocurrent and fill factor in thick bulk heterojunction organic solar cells is described. Lastly, the inverted off-center spinning technique promotes a vertical gradient of the donor–acceptor phase-separated morphology, enabling devices with near 100% internal quantum efficiency and a high power conversion efficiency of 10.95%.

Integrated Targeting and Guidance for Powered Planetary Descent

NASA Astrophysics Data System (ADS)

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.

Integrated Targeting and Guidance for Powered Planetary Descent

NASA Astrophysics Data System (ADS)

Azimov, Dilmurat M.; Bishop, Robert H.

2018-06-01

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.

A molecular signature of an arrest of descent in human parturition

PubMed Central

MITTAL, Pooja; ROMERO, Roberto; TARCA, Adi L.; DRAGHICI, Sorin; NHAN-CHANG, Chia-Ling; CHAIWORAPONGSA, Tinnakorn; HOTRA, John; GOMEZ, Ricardo; KUSANOVIC, Juan Pedro; LEE, Deug-Chan; KIM, Chong Jai; HASSAN, Sonia S.

2010-01-01

Objective This study was undertaken to identify the molecular basis of an arrest of descent. Study Design Human myometrium was obtained from women in term labor (TL; n=29) and arrest of descent (AODes, n=21). Gene expression was characterized using Illumina® HumanHT-12 microarrays. A moderated t-test and false discovery rate adjustment were applied for analysis. Confirmatory qRT-PCR and immunoblot was performed in an independent sample set. Results 400 genes were differentially expressed between women with an AODes compared to those with TL. Gene Ontology analysis indicated enrichment of biological processes and molecular functions related to inflammation and muscle function. Impacted pathways included inflammation and the actin cytoskeleton. Overexpression of HIF1A, IL-6, and PTGS2 in AODES was confirmed. Conclusion We have identified a stereotypic pattern of gene expression in the myometrium of women with an arrest of descent. This represents the first study examining the molecular basis of an arrest of descent using a genome-wide approach. PMID:21284969

Air-Traffic Controllers Evaluate The Descent Advisor

NASA Technical Reports Server (NTRS)

Tobias, Leonard; Volckers, Uwe; Erzberger, Heinz

1992-01-01

Report describes study of Descent Advisor algorithm: software automation aid intended to assist air-traffic controllers in spacing traffic and meeting specified times or arrival. Based partly on mathematical models of weather conditions and performances of aircraft, it generates suggested clearances, including top-of-descent points and speed-profile data to attain objectives. Study focused on operational characteristics with specific attention to how it can be used for prediction, spacing, and metering.

Design principles of descent vehicles with an inflatable braking device

NASA Astrophysics Data System (ADS)

Alexashkin, S. N.; Pichkhadze, K. M.; Finchenko, V. S.

2013-12-01

A new type of descent vehicle (DVs) is described: a descent vehicle with an inflatable braking device (IBD DV). IBD development issues, as well as materials needed for the design, manufacturing, and testing of an IBD and its thermal protection, are discussed. A list is given of Russian integrated test facilities intended for testing IBD DVs. Progress is described in the development of IBD DVs in Russia and abroad.

Synonymous ABCA3 Variants Do Not Increase Risk for Neonatal Respiratory Distress Syndrome

PubMed Central

Wambach, Jennifer A.; Wegner, Daniel J.; Heins, Hillary B.; Druley, Todd E.; Mitra, Robi D.; Hamvas, Aaron; Cole, F. Sessions

2014-01-01

Objective To determine whether synonymous variants in the adenosine triphosphate-binding cassette A3 transporter (ABCA3) gene increase the risk for neonatal respiratory distress syndrome (RDS) in term and late preterm infants of European and African descent. Study design Using next-generation pooled sequencing of race-stratified DNA samples from infants of European and African descent at $34 weeks gestation with and without RDS (n = 503), we scanned all exons of ABCA3, validated each synonymous variant with an independent genotyping platform, and evaluated race-stratified disease risk associated with common synonymous variants and collapsed frequencies of rare synonymous variants. Results The synonymous ABCA3 variant frequency spectrum differs between infants of European descent and those of African descent. Using in silico prediction programs and statistical strategies, we found no potentially disruptive synonymous ABCA3 variants or evidence of selection pressure. Individual common synonymous variants and collapsed frequencies of rare synonymous variants did not increase disease risk in term and late-preterm infants of European or African descent. Conclusion In contrast to rare, nonsynonymous ABCA3 mutations, synonymous ABCA3 variants do not increase the risk for neonatal RDS among term and late-preterm infants of European or African descent. PMID:24657120

A systematic review and meta-analysis of comparative studies assessing the efficacy of luteinizing hormone-releasing hormone therapy for children with cryptorchidism.

PubMed

Li, Tao; Gao, Liang; Chen, Peng; Bu, Siyuan; Cao, Dehong; Yang, Lu; Wei, Qiang

2016-05-01

To assess the efficacy of intranasal luteinizing hormone-releasing hormone (LHRH) therapy for cryptorchidism. Eligible studies were identified by two reviewers using PubMed, Embase, and Web of Science databases. Primary outcomes were complete testicular descent rate, complete testicular descent rate for nonpalpable testis, and pre-scrotal and inguinal testis. Secondary outcomes included testicular descent with different medicines strategy and a subgroup analysis. Pooled data including the 1255 undescended testes showed that complete testicular descent rate was 20.9 % in LHRH group versus 5.6 % in the placebo group, which was significantly different [relative risk (RR) 3.94, 95 % confidence interval (CI) 2.14-7.28, P < 0.0001]. There was also a significant difference in the incidence of pre-scrotal and inguinal position testis descent, with 22.8 % in the LHRH group versus 3.6 % in the placebo group (RR 5.79, 95 % CI 2.94-11.39, P < 0.00001). However, side effects were more frequent in the LHRH group (RR 2.61, 95 % CI 1.52-4.49, P = 0.0005). There were no significant differences for nonpalpable testes. LHRH had significant benefits on testicular descent, particularly for inguinal and pre-scrotal testes, which was also accompanied by temporary slight side effects.

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

PubMed Central

Rebbeck, Timothy R.; Devesa, Susan S.; Chang, Bao-Li; Bunker, Clareann H.; Cheng, Iona; Cooney, Kathleen; Eeles, Rosalind; Fernandez, Pedro; Giri, Veda N.; Gueye, Serigne M.; Haiman, Christopher A.; Henderson, Brian E.; Heyns, Chris F.; Hu, Jennifer J.; Ingles, Sue Ann; Isaacs, William; Jalloh, Mohamed; John, Esther M.; Kibel, Adam S.; Kidd, LaCreis R.; Layne, Penelope; Leach, Robin J.; Neslund-Dudas, Christine; Okobia, Michael N.; Ostrander, Elaine A.; Park, Jong Y.; Patrick, Alan L.; Phelan, Catherine M.; Ragin, Camille; Roberts, Robin A.; Rybicki, Benjamin A.; Stanford, Janet L.; Strom, Sara; Thompson, Ian M.; Witte, John; Xu, Jianfeng; Yeboah, Edward; Hsing, Ann W.; Zeigler-Johnson, Charnita M.

2013-01-01

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. PMID:23476788

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

PubMed

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.

Optimization with artificial neural network systems - A mapping principle and a comparison to gradient based methods

NASA Technical Reports Server (NTRS)

Leong, Harrison Monfook

1988-01-01

General formulae for mapping optimization problems into systems of ordinary differential equations associated with artificial neural networks are presented. A comparison is made to optimization using gradient-search methods. The performance measure is the settling time from an initial state to a target state. A simple analytical example illustrates a situation where dynamical systems representing artificial neural network methods would settle faster than those representing gradient-search. Settling time was investigated for a more complicated optimization problem using computer simulations. The problem was a simplified version of a problem in medical imaging: determining loci of cerebral activity from electromagnetic measurements at the scalp. The simulations showed that gradient based systems typically settled 50 to 100 times faster than systems based on current neural network optimization methods.

The influence of a high pressure gradient on unsteady velocity perturbations in the case of a turbulent supersonic flow

NASA Technical Reports Server (NTRS)

Dussauge, J. P.; Debieve, J. F.

1980-01-01

The amplification or reduction of unsteady velocity perturbations under the influence of strong flow acceleration or deceleration was studied. Supersonic flows with large velocity, pressure gradients, and the conditions in which the velocity fluctuations depend on the action of the average gradients of pressure and velocity rather than turbulence, are described. Results are analyzed statistically and interpreted as a return to laminar process. It is shown that this return to laminar implies negative values in the turbulence production terms for kinetic energy. A simple geometrical representation of the Reynolds stress production is given.

Pore and grain boundary migration under a temperature gradient: A phase-field model study

DOE PAGES

Biner, S. B.

2016-03-16

In this study, the collective migration behavior of pores and grain boundaries under a temperature gradient is studied for simple single crystal, bi-crystal and polycrystal configurations with a phase-field model formulism. For simulation of the microstructure of solids, composed of pores and grain boundaries, the results indicate that not only the volume fraction of pores, but also its spatial partitioning between the grain boundary junctions and the grain boundary segments appears to be important. In addition to various physical properties, the evolution kinetics, under given temperature gradients, will be strongly influenced with the initial morphology of a poly-crystalline microstructure.

Design of automation tools for management of descent traffic

NASA Technical Reports Server (NTRS)

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 evaluations at an en route center.

Mars Descent Imager (MARDI) on the Mars Polar Lander

USGS Publications Warehouse

Malin, M.C.; Caplinger, M.A.; Carr, M.H.; Squyres, S.; Thomas, P.; Veverka, J.

2001-01-01

The Mars Descent Imager, or MARDI, experiment on the Mars Polar Lander (MPL) consists of a camera characterized by small physical size and mass (???6 ?? 6 ?? 12 cm, including baffle; <500 gm), low power requirements (<2.5 W, including power supply losses), and high science performance (1000 x 1000 pixel, low noise). The intent of the investigation is to acquire nested images over a range of resolutions, from 8 m/pixel to better than 1 cm/pixel, during the roughly 2 min it takes the MPL to descend from 8 km to the surface under parachute and rocket-powered deceleration. Observational goals will include studies of (1) surface morphology (e.g., nature and distribution of landforms indicating past and present environmental processes); (2) local and regional geography (e.g., context for other lander instruments: precise location, detailed local relief); and (3) relationships to features seen in orbiter data. To accomplish these goals, MARDI will collect three types of images. Four small images (256 x 256 pixels) will be acquired on 0.5 s centers beginning 0.3 s before MPL's heatshield is jettisoned. Sixteen full-frame images (1024 X 1024, circularly edited) will be acquired on 5.3 s centers thereafter. Just after backshell jettison but prior to the start of powered descent, a "best final nonpowered descent image" will be acquired. Five seconds after the start of powered descent, the camera will begin acquiring images on 4 s centers. Storage for as many as ten 800 x 800 pixel images is available during terminal descent. A number of spacecraft factors are likely to impact the quality of MARDI images, including substantial motion blur resulting from large rates of attitude variation during parachute descent and substantial rocket-engine-induced vibration during powered descent. In addition, the mounting location of the camera places the exhaust plume of the hydrazine engines prominently in the field of view. Copyright 2001 by the American Geophysical Union.

A Dictionary Learning Approach with Overlap for the Low Dose Computed Tomography Reconstruction and Its Vectorial Application to Differential Phase Tomography

PubMed Central

Mirone, Alessandro; Brun, Emmanuel; Coan, Paola

2014-01-01

X-ray based Phase-Contrast Imaging (PCI) techniques have been demonstrated to enhance the visualization of soft tissues in comparison to conventional imaging methods. Nevertheless the delivered dose as reported in the literature of biomedical PCI applications often equals or exceeds the limits prescribed in clinical diagnostics. The optimization of new computed tomography strategies which include the development and implementation of advanced image reconstruction procedures is thus a key aspect. In this scenario, we implemented a dictionary learning method with a new form of convex functional. This functional contains in addition to the usual sparsity inducing and fidelity terms, a new term which forces similarity between overlapping patches in the superimposed regions. The functional depends on two free regularization parameters: a coefficient multiplying the sparsity-inducing norm of the patch basis functions coefficients, and a coefficient multiplying the norm of the differences between patches in the overlapping regions. The solution is found by applying the iterative proximal gradient descent method with FISTA acceleration. The gradient is computed by calculating projection of the solution and its error backprojection at each iterative step. We study the quality of the solution, as a function of the regularization parameters and noise, on synthetic data for which the solution is a-priori known. We apply the method on experimental data in the case of Differential Phase Tomography. For this case we use an original approach which consists in using vectorial patches, each patch having two components: one per each gradient component. The resulting algorithm, implemented in the European Synchrotron Radiation Facility tomography reconstruction code PyHST, has proven to be efficient and well-adapted to strongly reduce the required dose and the number of projections in medical tomography. PMID:25531987

A dictionary learning approach with overlap for the low dose computed tomography reconstruction and its vectorial application to differential phase tomography.

PubMed

Mirone, Alessandro; Brun, Emmanuel; Coan, Paola

2014-01-01

X-ray based Phase-Contrast Imaging (PCI) techniques have been demonstrated to enhance the visualization of soft tissues in comparison to conventional imaging methods. Nevertheless the delivered dose as reported in the literature of biomedical PCI applications often equals or exceeds the limits prescribed in clinical diagnostics. The optimization of new computed tomography strategies which include the development and implementation of advanced image reconstruction procedures is thus a key aspect. In this scenario, we implemented a dictionary learning method with a new form of convex functional. This functional contains in addition to the usual sparsity inducing and fidelity terms, a new term which forces similarity between overlapping patches in the superimposed regions. The functional depends on two free regularization parameters: a coefficient multiplying the sparsity-inducing L1 norm of the patch basis functions coefficients, and a coefficient multiplying the L2 norm of the differences between patches in the overlapping regions. The solution is found by applying the iterative proximal gradient descent method with FISTA acceleration. The gradient is computed by calculating projection of the solution and its error backprojection at each iterative step. We study the quality of the solution, as a function of the regularization parameters and noise, on synthetic data for which the solution is a-priori known. We apply the method on experimental data in the case of Differential Phase Tomography. For this case we use an original approach which consists in using vectorial patches, each patch having two components: one per each gradient component. The resulting algorithm, implemented in the European Synchrotron Radiation Facility tomography reconstruction code PyHST, has proven to be efficient and well-adapted to strongly reduce the required dose and the number of projections in medical tomography.

Mars Science Laboratory's Descent Stage

NASA Technical Reports Server (NTRS)

2008-01-01

This portion of NASA's Mars Science Laboratory, called the descent stage, does its main work during the final few minutes before touchdown on Mars.

The descent stage will provide rocket-powered deceleration for a phase of the arrival at Mars after the phases using the heat shield and parachute. When it nears the surface, the descent stage will lower the rover on a bridle the rest of the way to the ground.

The Mars Science Laboratory spacecraft is being assembled and tested for launch in 2011.

This image was taken at NASA's Jet Propulsion Laboratory, Pasadena, Calif., which manages the Mars Science Laboratory Mission for NASA's Science Mission Directorate, Washington. JPL is a division of the California Institute of Technology.

Advances in POST2 End-to-End Descent and Landing Simulation for the ALHAT Project

NASA Technical Reports Server (NTRS)

Davis, Jody L.; Striepe, Scott A.; Maddock, Robert W.; Hines, Glenn D.; Paschall, Stephen, II; Cohanim, Babak E.; Fill, Thomas; Johnson, Michael C.; Bishop, Robert H.; DeMars, Kyle J.;

Fast Optimization for Aircraft Descent and Approach Trajectory

NASA Technical Reports Server (NTRS)

Luchinsky, Dmitry G.; Schuet, Stefan; Brenton, J.; Timucin, Dogan; Smith, David; Kaneshige, John

2017-01-01

We address problem of on-line scheduling of the aircraft descent and approach trajectory. We formulate a general multiphase optimal control problem for optimization of the descent trajectory and review available methods of its solution. We develop a fast algorithm for solution of this problem using two key components: (i) fast inference of the dynamical and control variables of the descending trajectory from the low dimensional flight profile data and (ii) efficient local search for the resulting reduced dimensionality non-linear optimization problem. We compare the performance of the proposed algorithm with numerical solution obtained using optimal control toolbox General Pseudospectral Optimal Control Software. We present results of the solution of the scheduling problem for aircraft descent using novel fast algorithm and discuss its future applications.

A marker-based watershed method for X-ray image segmentation.

PubMed

Zhang, Xiaodong; Jia, Fucang; Luo, Suhuai; Liu, Guiying; Hu, Qingmao

2014-03-01

Digital X-ray images are the most frequent modality for both screening and diagnosis in hospitals. To facilitate subsequent analysis such as quantification and computer aided diagnosis (CAD), it is desirable to exclude image background. A marker-based watershed segmentation method was proposed to segment background of X-ray images. The method consisted of six modules: image preprocessing, gradient computation, marker extraction, watershed segmentation from markers, region merging and background extraction. One hundred clinical direct radiograph X-ray images were used to validate the method. Manual thresholding and multiscale gradient based watershed method were implemented for comparison. The proposed method yielded a dice coefficient of 0.964±0.069, which was better than that of the manual thresholding (0.937±0.119) and that of multiscale gradient based watershed method (0.942±0.098). Special means were adopted to decrease the computational cost, including getting rid of few pixels with highest grayscale via percentile, calculation of gradient magnitude through simple operations, decreasing the number of markers by appropriate thresholding, and merging regions based on simple grayscale statistics. As a result, the processing time was at most 6s even for a 3072×3072 image on a Pentium 4 PC with 2.4GHz CPU (4 cores) and 2G RAM, which was more than one time faster than that of the multiscale gradient based watershed method. The proposed method could be a potential tool for diagnosis and quantification of X-ray images. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

A low-cost, mechanically simple apparatus for measuring eddy current-induced magnetic fields in MRI.

PubMed

Gilbert, Kyle M; Martyn Klassen, L; Menon, Ravi S

2013-10-01

The fidelity of gradient waveforms in MRI pulse sequences is essential to the acquisition of images and spectra with minimal distortion artefacts. Gradient waveforms can become nonideal when eddy currents are created in nearby conducting structures; however, the resultant magnetic fields can be characterised and compensated for by measuring the spatial and temporal field response following a gradient impulse. This can be accomplished using a grid of radiofrequency (RF) coils. The RF coils must adhere to strict performance requirements: they must achieve a high sensitivity and signal-to-noise ratio (SNR), have minimal susceptibility field gradients between the sample and surrounding material interfaces and be highly decoupled from each other. In this study, an apparatus is presented that accomplishes these tasks with a low-cost, mechanically simple solution. The coil system consists of six transmit/receive RF coils immersed in a high-molarity saline solution. The sensitivity and SNR following an excitation pulse are sufficiently high to allow accurate phase measurements during free-induction decays; the intrinsic susceptibility matching of the materials, because of the unique design of the coil system, results in sufficiently narrow spectral line widths (mean of 19 Hz), and adjacent RF coils are highly decoupled (mean S12 of -47 dB). The temporal and spatial distributions of eddy currents following a gradient pulse are measured to validate the efficacy of the design, and the resultant amplitudes and time constants required for zeroth- and first-order compensation are provided. Copyright © 2013 John Wiley & Sons, Ltd.

Velocity Gradient Power Functional for Brownian Dynamics.

PubMed

de Las Heras, Daniel; Schmidt, Matthias

2018-01-12

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

Velocity Gradient Power Functional for Brownian Dynamics

NASA Astrophysics Data System (ADS)

de las Heras, Daniel; Schmidt, Matthias

2018-01-01

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

A hybrid microfluidic-vacuum device for direct interfacing with conventional cell culture methods

PubMed Central

Chung, Bong Geun; Park, Jeong Won; Hu, Jia Sheng; Huang, Carlos; Monuki, Edwin S; Jeon, Noo Li

2007-01-01

Background Microfluidics is an enabling technology with a number of advantages over traditional tissue culture methods when precise control of cellular microenvironment is required. However, there are a number of practical and technical limitations that impede wider implementation in routine biomedical research. Specialized equipment and protocols required for fabrication and setting up microfluidic experiments present hurdles for routine use by most biology laboratories. Results We have developed and validated a novel microfluidic device that can directly interface with conventional tissue culture methods to generate and maintain controlled soluble environments in a Petri dish. It incorporates separate sets of fluidic channels and vacuum networks on a single device that allows reversible application of microfluidic gradients onto wet cell culture surfaces. Stable, precise concentration gradients of soluble factors were generated using simple microfluidic channels that were attached to a perfusion system. We successfully demonstrated real-time optical live/dead cell imaging of neural stem cells exposed to a hydrogen peroxide gradient and chemotaxis of metastatic breast cancer cells in a growth factor gradient. Conclusion This paper describes the design and application of a versatile microfluidic device that can directly interface with conventional cell culture methods. This platform provides a simple yet versatile tool for incorporating the advantages of a microfluidic approach to biological assays without changing established tissue culture protocols. PMID:17883868

Iterative free-energy optimization for recurrent neural networks (INFERNO).

PubMed

Pitti, Alexandre; Gaussier, Philippe; Quoy, Mathias

2017-01-01

The intra-parietal lobe coupled with the Basal Ganglia forms a working memory that demonstrates strong planning capabilities for generating robust yet flexible neuronal sequences. Neurocomputational models however, often fails to control long range neural synchrony in recurrent spiking networks due to spontaneous activity. As a novel framework based on the free-energy principle, we propose to see the problem of spikes' synchrony as an optimization problem of the neurons sub-threshold activity for the generation of long neuronal chains. Using a stochastic gradient descent, a reinforcement signal (presumably dopaminergic) evaluates the quality of one input vector to move the recurrent neural network to a desired activity; depending on the error made, this input vector is strengthened to hill-climb the gradient or elicited to search for another solution. This vector can be learned then by one associative memory as a model of the basal-ganglia to control the recurrent neural network. Experiments on habit learning and on sequence retrieving demonstrate the capabilities of the dual system to generate very long and precise spatio-temporal sequences, above two hundred iterations. Its features are applied then to the sequential planning of arm movements. In line with neurobiological theories, we discuss its relevance for modeling the cortico-basal working memory to initiate flexible goal-directed neuronal chains of causation and its relation to novel architectures such as Deep Networks, Neural Turing Machines and the Free-Energy Principle.

Resolving the conundrum of inbreeding depression but no inbreeding avoidance: Estimating sex‐specific selection on inbreeding by song sparrows (Melospiza melodia)

PubMed Central

Reid, Jane M.; Arcese, Peter; Bocedi, Greta; Duthie, A. Bradley; Wolak, Matthew E.; Keller, Lukas F.

2015-01-01

Inbreeding avoidance among interacting females and males is not always observed despite inbreeding depression in offspring fitness, creating an apparent “inbreeding paradox.” This paradox could be resolved if selection against inbreeding was in fact weak, despite inbreeding depression. However, the net magnitude and direction of selection on the degree to which females and males inbreed by pairing with relatives has not been explicitly estimated. We used long‐term pedigree data to estimate phenotypic selection gradients on the degree of inbreeding that female and male song sparrows (Melospiza melodia) expressed by forming socially persistent breeding pairs with relatives. Fitness was measured as the total numbers of offspring and grand offspring contributed to the population, and as corresponding expected numbers of identical‐by‐descent allele copies, thereby accounting for variation in offspring survival, reproduction, and relatedness associated with variation in parental inbreeding. Estimated selection gradients on the degree to which individuals paired with relatives were weakly positive in females, but negative in males that formed at least one socially persistent pairing. However, males that paired had higher mean fitness than males that remained socially unpaired. These analyses suggest that net selection against inbreeding may be weak in both sexes despite strong inbreeding depression, thereby resolving the “inbreeding paradox.” PMID:26420476

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

PubMed

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.

So Happy Together

NASA Technical Reports Server (NTRS)

2008-01-01

These three images show the progression of 'stacking' the Mars Science Laboratory rover and its descent stage in one of the Jet Propulsion Laboratory's 'clean room.' In the first image, the car-size rover is in the middle of the picture with several team members surrounding it. The team members are all dressed in special head-to-toe white suits, called 'bunny suits.' One team member is holding on to a tether to guide the large insect-like descent stage down on top of the rover. The descent stage looms high in this image. The second image shows the descent stage a few feet above the rover with the team member continuing to guide the two pieces together. The final image shows the two pieces on top of each other.

Imagine taking a very long 10-month journey with someone you've just recently met! The assembly team successfully introduced the Mars Science Laboratory rover to one of its space travel partners. For the first time, it was coupled with its 'descent stage,' the part of the spacecraft that lowers the rover to the Martian surface.

Up until now, thousands of hands and minds have been making sure this pairing is a perfect fit ... on paper. The intricate parts of the rover and descent stage have all separately undergone some serious testing. Now that they're stacked together, their teams can see how they fit together in real life. With this match-making a success, the rover and descent stage will be joined with the protective case (the 'aeroshell') for more testing. But, these pieces aren't staying together forever! They'll be separated, checked, and assembled many more times before finally coming together just before launch.

Eye Movement Patterns of the Elderly during Stair Descent:Effect of Illumination

NASA Astrophysics Data System (ADS)

Kasahara, Satoko; Okabe, Sonoko; Nakazato, Naoko; Ohno, Yuko

The relationship between the eye movement pattern during stair descent and illumination was studied in 4 elderly people in comparison with that in 5 young people. The illumination condition was light (85.0±30.9 lx) or dark (0.7±0.3 lx), and data of eye movements were obtained using an eye mark recorder. A flight of 15 steps was used for the experiment, and data on 3 steps in the middle, on which the descent movements were stabilized, were analyzed. The elderly subjects pointed their eyes mostly directly in front in the facial direction regardless of the illumination condition, but the young subjects tended to look down under the light condition. The young subjects are considered to have confirmed the safety of the front by peripheral vision, checked the stepping surface by central vision, and still maintained the upright position without leaning forward during stair descent. The elderly subjects, in contrast, always looked at the visual target by central vision even under the light condition and leaned forward. The range of eye movements was larger vertically than horizontally in both groups, and a characteristic eye movement pattern of repeating a vertical shuttle movement synchronous with descent of each step was observed. Under the dark condition, the young subjects widened the range of vertical eye movements and reduced duration of fixation. The elderly subjects showed no change in the range of eye movements but increased duration of fixation during stair descent. These differences in the eye movements are considered to be compensatory reactions to narrowing of the vertical visual field, reduced dark adaptation, and reduced dynamic visual acuity due to aging. These characteristics of eye movements of the elderly lead to an anteriorly leaned posture and lack of attention to the front during stair descent.

Microfludic Device for Creating Ionic Strength Gradients over DNA Microarrays for Efficient DNA Melting Studies and Assay Development

PubMed Central

Petersen, Jesper; Poulsen, Lena; Birgens, Henrik; Dufva, Martin

2009-01-01

The development of DNA microarray assays is hampered by two important aspects: processing of the microarrays is done under a single stringency condition, and characteristics such as melting temperature are difficult to predict for immobilized probes. A technical solution to these limitations is to use a thermal gradient and information from melting curves, for instance to score genotypes. However, application of temperature gradients normally requires complicated equipment, and the size of the arrays that can be investigated is restricted due to heat dissipation. Here we present a simple microfluidic device that creates a gradient comprising zones of defined ionic strength over a glass slide, in which each zone corresponds to a subarray. Using this device, we demonstrated that ionic strength gradients function in a similar fashion as corresponding thermal gradients in assay development. More specifically, we noted that (i) the two stringency modulators generated melting curves that could be compared, (ii) both led to increased assay robustness, and (iii) both were associated with difficulties in genotyping the same mutation. These findings demonstrate that ionic strength stringency buffers can be used instead of thermal gradients. Given the flexibility of design of ionic gradients, these can be created over all types of arrays, and encompass an attractive alternative to temperature gradients, avoiding curtailment of the size or spacing of subarrays on slides associated with temperature gradients. PMID:19277213

Microfludic device for creating ionic strength gradients over DNA microarrays for efficient DNA melting studies and assay development.

PubMed

Petersen, Jesper; Poulsen, Lena; Birgens, Henrik; Dufva, Martin

2009-01-01

The development of DNA microarray assays is hampered by two important aspects: processing of the microarrays is done under a single stringency condition, and characteristics such as melting temperature are difficult to predict for immobilized probes. A technical solution to these limitations is to use a thermal gradient and information from melting curves, for instance to score genotypes. However, application of temperature gradients normally requires complicated equipment, and the size of the arrays that can be investigated is restricted due to heat dissipation. Here we present a simple microfluidic device that creates a gradient comprising zones of defined ionic strength over a glass slide, in which each zone corresponds to a subarray. Using this device, we demonstrated that ionic strength gradients function in a similar fashion as corresponding thermal gradients in assay development. More specifically, we noted that (i) the two stringency modulators generated melting curves that could be compared, (ii) both led to increased assay robustness, and (iii) both were associated with difficulties in genotyping the same mutation. These findings demonstrate that ionic strength stringency buffers can be used instead of thermal gradients. Given the flexibility of design of ionic gradients, these can be created over all types of arrays, and encompass an attractive alternative to temperature gradients, avoiding curtailment of the size or spacing of subarrays on slides associated with temperature gradients.

Designing Feature and Data Parallel Stochastic Coordinate Descent Method forMatrix and Tensor Factorization

DTIC Science & Technology

2016-05-11

AFRL-AFOSR-JP-TR-2016-0046 Designing Feature and Data Parallel Stochastic Coordinate Descent Method for Matrix and Tensor Factorization U Kang Korea...maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or   any other aspect...Designing Feature and Data Parallel Stochastic Coordinate Descent Method for Matrix and Tensor Factorization 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER FA2386

Using survival analysis to determine association between maternal pelvis height and antenatal fetal head descent in Ugandan mothers.

PubMed

Munabi, Ian Guyton; Luboga, Samuel Abilemech; Mirembe, Florence

2015-01-01

Fetal head descent is used to demonstrate the maternal pelvis capacity to accommodate the fetal head. This is especially important in low resource settings that have high rates of childbirth related maternal deaths and morbidity. This study looked at maternal height and an additional measure, maternal pelvis height, from automotive engineering. The objective of the study was to determine the associations between maternal: height and pelvis height with the rate of fetal head descent in expectant Ugandan mothers. This was a cross sectional study on 1265 singleton mothers attending antenatal clinics at five hospitals in various parts of Uganda. In addition to the routine antenatal examination, each mother had their pelvis height recorded following informed consent. Survival analysis was done using STATA 12. It was found that 27% of mothers had fetal head descent with an incident rate of 0.028 per week after the 25th week of pregnancy. Significant associations were observed between the rate of fetal head descent with: maternal height (Adj Haz ratio 0.93 P < 0.01) and maternal pelvis height (Adj Haz ratio 1.15 P < 0.01). The significant associations observed between maternal: height and pelvis height with rate of fetal head descent, demonstrate a need for further study of maternal pelvis height as an additional decision support tool for screening mothers in low resource settings.

Using survival analysis to determine association between maternal pelvis height and antenatal fetal head descent in Ugandan mothers

PubMed Central

Munabi, Ian Guyton; Luboga, Samuel Abilemech; Mirembe, Florence

2015-01-01

Introduction Fetal head descent is used to demonstrate the maternal pelvis capacity to accommodate the fetal head. This is especially important in low resource settings that have high rates of childbirth related maternal deaths and morbidity. This study looked at maternal height and an additional measure, maternal pelvis height, from automotive engineering. The objective of the study was to determine the associations between maternal: height and pelvis height with the rate of fetal head descent in expectant Ugandan mothers. Methods This was a cross sectional study on 1265 singleton mothers attending antenatal clinics at five hospitals in various parts of Uganda. In addition to the routine antenatal examination, each mother had their pelvis height recorded following informed consent. Survival analysis was done using STATA 12. Results It was found that 27% of mothers had fetal head descent with an incident rate of 0.028 per week after the 25th week of pregnancy. Significant associations were observed between the rate of fetal head descent with: maternal height (Adj Haz ratio 0.93 P < 0.01) and maternal pelvis height (Adj Haz ratio 1.15 P < 0.01). Conclusion The significant associations observed between maternal: height and pelvis height with rate of fetal head descent, demonstrate a need for further study of maternal pelvis height as an additional decision support tool for screening mothers in low resource settings. PMID:26918071

Phase-unwrapping algorithm by a rounding-least-squares approach

NASA Astrophysics Data System (ADS)

Juarez-Salazar, Rigoberto; Robledo-Sanchez, Carlos; Guerrero-Sanchez, Fermin

2014-02-01

A simple and efficient phase-unwrapping algorithm based on a rounding procedure and a global least-squares minimization is proposed. Instead of processing the gradient of the wrapped phase, this algorithm operates over the gradient of the phase jumps by a robust and noniterative scheme. Thus, the residue-spreading and over-smoothing effects are reduced. The algorithm's performance is compared with four well-known phase-unwrapping methods: minimum cost network flow (MCNF), fast Fourier transform (FFT), quality-guided, and branch-cut. A computer simulation and experimental results show that the proposed algorithm reaches a high-accuracy level than the MCNF method by a low-computing time similar to the FFT phase-unwrapping method. Moreover, since the proposed algorithm is simple, fast, and user-free, it could be used in metrological interferometric and fringe-projection automatic real-time applications.

[Prognostic value on recovery rates for the application of sperm preparation techniques and their evaluation in sperm function].

PubMed

Barroso, Gerardo; Chaya, Miguel; Bolaños, Rubén; Rosado, Yadira; García León, Fernando; Ibarrola, Eduardo

2005-05-01

To evaluate sperm recovery and total sperm motility in three different sperm preparation techniques (density gradient, simple washing and swim-up). A total of 290 subjects were randomly evaluated from November 2001 to March 2003. The density gradient method required Isolate (upper and lower layers). Centrifugation was performed at 400 g for 10 minutes and evaluation was done using the Makler counting chamber. The simple washing method included the use of HTF-M complemented with 7.5% of SSS, with centrifugation at 250 g, obtaining at the end 0.5 mL of the sperm sample. The swim-up method required HTF-M complemented with 7.5% of SSS, with an incubation period of 60 minutes at 37 degrees C. The demographic characteristics evaluated through their standard error, 95% ICC, and 50th percentile were similar. The application of multiple comparison tests and analysis of variance showed significant differences between the sperm preparations before and after capacitation. It was observed a superior recovery rate with the density gradient and swim-up methods; nevertheless, the samples used for the simple washing method showed a diminished sperm recovery from the original sample. Sperm preparation techniques have become very useful in male infertility treatments allowing higher sperm recovery and motility rates. The seminal parameters evaluated from the original sperm sample will determine the best sperm preparation technique in those patients who require it.

A signal-flow-graph approach to on-line gradient calculation.

PubMed

Campolucci, P; Uncini, A; Piazza, F

2000-08-01

A large class of nonlinear dynamic adaptive systems such as dynamic recurrent neural networks can be effectively represented by signal flow graphs (SFGs). By this method, complex systems are described as a general connection of many simple components, each of them implementing a simple one-input, one-output transformation, as in an electrical circuit. Even if graph representations are popular in the neural network community, they are often used for qualitative description rather than for rigorous representation and computational purposes. In this article, a method for both on-line and batch-backward gradient computation of a system output or cost function with respect to system parameters is derived by the SFG representation theory and its known properties. The system can be any causal, in general nonlinear and time-variant, dynamic system represented by an SFG, in particular any feedforward, time-delay, or recurrent neural network. In this work, we use discrete-time notation, but the same theory holds for the continuous-time case. The gradient is obtained in a straightforward way by the analysis of two SFGs, the original one and its adjoint (obtained from the first by simple transformations), without the complex chain rule expansions of derivatives usually employed. This method can be used for sensitivity analysis and for learning both off-line and on-line. On-line learning is particularly important since it is required by many real applications, such as digital signal processing, system identification and control, channel equalization, and predistortion.

Powered Flight Design and Reconstructed Performance Summary for the Mars Science Laboratory Mission

NASA Technical Reports Server (NTRS)

Sell, Steven; Chen, Allen; Davis, Jody; San Martin, Miguel; Serricchio, Frederick; Singh, Gurkirpal

2013-01-01

The Powered Flight segment of Mars Science Laboratory's (MSL) Entry, Descent, and Landing (EDL) system extends from backshell separation through landing. This segment is responsible for removing the final 0.1% of the kinetic energy dissipated during EDL and culminating with the successful touchdown of the rover on the surface of Mars. Many challenges exist in the Powered Flight segment: extraction of Powered Descent Vehicle from the backshell, performing a 300m divert maneuver to avoid the backshell and parachute, slowing the descent from 85 m/s to 0.75 m/s and successfully lowering the rover on a 7.5m bridle beneath the rocket-powered Descent Stage and gently placing it on the surface using the Sky Crane Maneuver. Finally, the nearly-spent Descent Stage must execute a Flyaway maneuver to ensure surface impact a safe distance from the Rover. This paper provides an overview of the powered flight design, key features, and event timeline. It also summarizes Curiosity's as flown performance on the night of August 5th as reconstructed by the flight team.

Forces in inhomogeneous open active-particle systems.

PubMed

Razin, Nitzan; Voituriez, Raphael; Elgeti, Jens; Gov, Nir S

2017-11-01

We study the force that noninteracting pointlike active particles apply to a symmetric inert object in the presence of a gradient of activity and particle sources and sinks. We consider two simple patterns of sources and sinks that are common in biological systems. We analytically solve a one-dimensional model designed to emulate higher-dimensional systems, and study a two-dimensional model by numerical simulations. We specify when the particle flux due to the creation and annihilation of particles can act to smooth the density profile that is induced by a gradient in the velocity of the active particles, and find the net resultant force due to both the gradient in activity and the particle flux. These results are compared qualitatively to observations of nuclear motion inside the oocyte, that is driven by a gradient in activity of actin-coated vesicles.

Hot Flashes

MedlinePlus

... report menopausal hot flashes than do women of European descent. Hot flashes are less common in women of Japanese and Chinese descent than in white European women. Complications Nighttime hot flashes (night sweats) can ...

Carrier Screening

MedlinePlus

... most common in people of Eastern or Central European Jewish, French Canadian, and Cajun descent. But anyone ... most commonly affects people of Eastern and Central European Jewish, Cajun, and French Canadian descent, but it ...

Monoamine Oxidase A Promoter Variable Number of Tandem Repeats (MAOA-uVNTR) in Alcoholics According to Lesch Typology

PubMed Central

Samochowiec, Agnieszka; Chęć, Magdalena; Kopaczewska, Edyta; Samochowiec, Jerzy; Lesch, Otto; Grochans, Elżbieta; Jasiewicz, Andrzej; Bienkowski, Przemyslaw; Łukasz, Kołodziej; Grzywacz, Anna

2015-01-01

Background: The aim of this study was to examine the association between the MAOA-uVNTR gene polymorphism in a homogeneous subgroups of patients with alcohol dependence categorized according to Lesch’s typology. Methods: DNA was provided from alcohol dependent (AD) patients (n = 370) and healthy control subjects (n = 168) all of Polish descent. The history of alcoholism was obtained using the Polish version of the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA). Samples were genotyped using PCR methods. Results: We found no association between alcohol dependence and MAOA gene polymorphism. Conclusions: Lesch typology is a clinical consequence of the disease and its phenotypic description is too complex for a simple genetic analysis. PMID:25809512

A simple mathematical model of gradual Darwinian evolution: emergence of a Gaussian trait distribution in adaptation along a fitness gradient.

PubMed

Biktashev, Vadim N

2014-04-01

We consider a simple mathematical model of gradual Darwinian evolution in continuous time and continuous trait space, due to intraspecific competition for common resource in an asexually reproducing population in constant environment, while far from evolutionary stable equilibrium. The model admits exact analytical solution. In particular, Gaussian distribution of the trait emerges from generic initial conditions.

Stem cell migration and mechanotransduction on linear stiffness gradient hydrogels

PubMed Central

Hadden, William J.; Young, Jennifer L.; Holle, Andrew W.; McFetridge, Meg L.; Kim, Du Yong; Wijesinghe, Philip; Taylor-Weiner, Hermes; Wen, Jessica H.; Lee, Andrew R.; Bieback, Karen; Vo, Ba-Ngu; Sampson, David D.; Kennedy, Brendan F.; Spatz, Joachim P.; Choi, Yu Suk

2017-01-01

The spatial presentation of mechanical information is a key parameter for cell behavior. We have developed a method of polymerization control in which the differential diffusion distance of unreacted cross-linker and monomer into a prepolymerized hydrogel sink results in a tunable stiffness gradient at the cell–matrix interface. This simple, low-cost, robust method was used to produce polyacrylamide hydrogels with stiffness gradients of 0.5, 1.7, 2.9, 4.5, 6.8, and 8.2 kPa/mm, spanning the in vivo physiological and pathological mechanical landscape. Importantly, three of these gradients were found to be nondurotactic for human adipose-derived stem cells (hASCs), allowing the presentation of a continuous range of stiffnesses in a single well without the confounding effect of differential cell migration. Using these nondurotactic gradient gels, stiffness-dependent hASC morphology, migration, and differentiation were studied. Finally, the mechanosensitive proteins YAP, Lamin A/C, Lamin B, MRTF-A, and MRTF-B were analyzed on these gradients, providing higher-resolution data on stiffness-dependent expression and localization. PMID:28507138

Analytic Formulation and Numerical Implementation of an Acoustic Pressure Gradient Prediction

NASA Technical Reports Server (NTRS)

Lee, Seongkyu; Brentner, Kenneth S.; Farassat, Fereidoun

2007-01-01

The scattering of rotor noise is an area that has received little attention over the years, yet the limited work that has been done has shown that both the directivity and intensity of the acoustic field may be significantly modified by the presence of scattering bodies. One of the inputs needed to compute the scattered acoustic field is the acoustic pressure gradient on a scattering surface. Two new analytical formulations of the acoustic pressure gradient have been developed and implemented in the PSU-WOPWOP rotor noise prediction code. These formulations are presented in this paper. The first formulation is derived by taking the gradient of Farassat's retarded-time Formulation 1A. Although this formulation is relatively simple, it requires numerical time differentiation of the acoustic integrals. In the second formulation, the time differentiation is taken inside the integrals analytically. The acoustic pressure gradient predicted by these new formulations is validated through comparison with the acoustic pressure gradient determined by a purely numerical approach for two model rotors. The agreement between analytic formulations and numerical method is excellent for both stationary and moving observers case.

European population substructure is associated with mucocutaneous manifestations and autoantibody production in systemic lupus erythematosus

PubMed Central

Chung, Sharon A.; Tian, Chao; Taylor, Kimberly E.; Lee, Annette T.; Ortmann, Ward A.; Hom, Geoffrey; Graham, Robert R.; Nititham, Joanne; Kelly, Jennifer A.; Morrisey, Jean; Wu, Hui; Yin, Hong; Alarcón-Riquelme, Marta E.; Tsao, Betty P.; Harley, John B.; Gaffney, Patrick M.; Moser, Kathy L.; Manzi, Susan; Petri, Michelle; Gregersen, Peter K.; Langefeld, Carl D.; Behrens, Timothy W.; Seldin, Michael F.; Criswell, Lindsey A.

2009-01-01

Objective To determine whether genetic substructure in European-derived populations is associated with specific manifestations of systemic lupus erythematosus (SLE), including mucocutaneous phenotypes, autoantibody production, and renal disease. Methods SLE patients of European descent (n=1754) from 8 case collections were genotyped for over 1,400 ancestry informative markers that define a north/south gradient of European substructure. Based on these genetic markers, we used the STRUCTURE program to characterize each SLE patient in terms of percent northern (vs. southern) European ancestry. Non-parametric methods, including tests of trend, were used to identify associations between northern European ancestry and specific SLE manifestations. Results In multivariate analyses, increasing levels of northern European ancestry were significantly associated with photosensitivity (ptrend=0.0021, OR for highest quartile of northern European ancestry compared to lowest quartile 1.64, 95% CI 1.13–2.35) and discoid rash (ptrend=0.014, ORhigh-low 1.93, 95% CI 0.98–3.83). In contrast, northern European ancestry was protective for anticardiolipin (ptrend=1.6 × 10−4, ORhigh-low 0.46, 95% CI 0.30–0.69) and anti-dsDNA (ptrend=0.017, ORhigh-low 0.67, 95% CI 0.46–0.96) autoantibody production. Conclusions This study demonstrates that specific SLE manifestations vary according to northern vs. southern European ancestry. Thus, genetic ancestry may contribute to the clinical heterogeneity and variation in disease outcomes among SLE patients of European descent. Moreover, these results suggest that genetic studies of SLE subphenotypes will need to carefully address issues of population substructure due to genetic ancestry. PMID:19644962

Ethnic differences in resting metabolic rate, respiratory quotient and body temperature: a comparison of Africans and European Australians.

PubMed

Adzika Nsatimba, P A; Pathak, K; Soares, M J

2016-08-01

A comparison of resting metabolic rate (RMR), respiratory quotient (RQ) and body temperature between adults of African and European descent. Twenty-nine sub-Saharan Africans (SSA; 13 men and 16 women) and thirty-two Australians of European descent (EUR; eight men and 24 women) had RMR and RQ measured by indirect calorimetry. Dual-energy X-ray absorptiometry was used to determine fat mass (FM), fat-free mass, bone mineral content (BMC), appendicular lean tissue mass and non-appendicular lean tissue mass. Total skeletal muscle mass (SMM) was predicted. Residual mass (RM) was the difference between body weight and the sum of FM, SMM and BMC. The short form of the International Physical Activity Questionnaire was used to determine habitual physical activity (PA). Tympanic in the ear temperature (IET) and forearm to fingertip temperature gradients (FFG) were monitored throughout the protocol. The unadjusted RMR of SSA was significantly lower compared to EUR. Adjusted for age, sex, season, PA, FM, BMC, SMM and RM, this difference in RMR was still evident (mean ± SE, SSA: 4880 ± 161 kJ/d vs. EUR: 5979 ± 111, P < 0.005). The same model of adjustment also uncovered a significantly lower adjusted IET (SSA: 35.26 °C ± 0.133 vs. EUR: 35.60 ± 0.091, P < 0.05), a higher adjusted RQ (SSA: 0.86 ± 0.014 vs. EUR: 0.83 ± 0.010, P < 0.05) but no difference in adjusted FFG. In this study, SSA had a lower RMR, higher RQ and lower IET relative to EUR Australians.

Construction of oxygen and chemical concentration gradients in a single microfluidic device for studying tumor cell-drug interactions in a dynamic hypoxia microenvironment.

PubMed

Wang, Lei; Liu, Wenming; Wang, Yaolei; Wang, Jian-chun; Tu, Qin; Liu, Rui; Wang, Jinyi

2013-02-21

Recent microfluidic advancements in oxygen gradients have greatly promoted controllable oxygen-sensitive cellular investigations at microscale resolution. However, multi-gradient integration in a single microfluidic device for tissue-mimicking cell investigation is not yet well established. In this study, we describe a method that can generate oxygen and chemical concentration gradients in a single microfluidic device via the formation of an oxygen gradient in a chamber and a chemical concentration gradient between adjacent chambers. The oxygen gradient dynamics were systematically investigated, and were quantitatively controlled using simple exchange between the aerial oxygen and the oxygen-free conditions in the gas-permeable polydimethylsiloxane channel. Meanwhile, the chemical gradient dynamics was generated using a special channel-branched device. For potential medical applications of the established oxygen and chemical concentration gradients, a tumor cell therapy assessment was performed using two antitumor drugs (tirapazamine and bleomycin) and two tumor cell lines (human lung adenocarcinoma A549 cells and human cervical carcinoma HeLa cells). The results of the proof-of-concept experiment indicate the dose-dependent antitumor effect of the drugs and hypoxia-induced cytotoxicity of tirapazamine. We demonstrate that the integration of oxygen and chemical concentration gradients in a single device can be applied to investigating oxygen- and chemical-sensitive cell events, which can also be valuable in the development of multi-gradient generating procedures and specific drug screening.

Apollo 15 mission report, supplement 4: Descent propulsion system final flight evaluation

NASA Technical Reports Server (NTRS)

Avvenire, A. T.; Wood, S. C.

1972-01-01

The results of a postflight analysis of the LM-10 Descent Propulsion System (DPS) during the Apollo 15 Mission are reported. The analysis determined the steady state performance of the DPS during the descent phase of the manned lunar landing. Flight measurement discrepancies are discussed. Simulated throttle performance results are cited along with overall performance results. Evaluations of the propellant quantity gaging system, propellant loading, pressurization system, and engine are reported. Graphic illustrations of the evaluations are included.

Apollo experience report: Descent propulsion system

NASA Technical Reports Server (NTRS)

Hammock, W. R., Jr.; Currie, E. C.; Fisher, A. E.

1973-01-01

The propulsion system for the descent stage of the lunar module was designed to provide thrust to transfer the fully loaded lunar module with two crewmen from the lunar parking orbit to the lunar surface. A history of the development of this system is presented. Development was accomplished primarily by ground testing of individual components and by testing the integrated system. Unique features of the descent propulsion system were the deep throttling capability and the use of a lightweight cryogenic helium pressurization system.

Cryptorchidism and delayed testicular descent in Florida black bears.

PubMed

Dunbar, M R; Cunningham, M W; Wooding, J B; Roth, R P

1996-10-01

Retained testes were found in 11 (16%) of 71 black bears (Ursus americanus) examined over a 3-year period in Florida (USA). Four of the 11 bears were older than one year and weighed more than 32 kg; therefore, they were considered to be cryptorchid. The remaining seven bears may have had delayed testicular descent due to their apparent normal immature development. This is the first known published report of the prevalence of cryptorchidism and apparently normal delayed testicular descent in a black bear population.

Mars Science Laboratory Entry, Descent and Landing System Development Challenges and Preliminary Flight Performance

NASA Technical Reports Server (NTRS)

Steltzner, Adam D.; San Martin, A. Miguel; Rivellini, Tommaso P.

2013-01-01

The Mars Science Laboratory project recently landed the Curiosity rover on the surface of Mars. With the success of the landing system, the performance envelope of entry, descent, and landing capabilities has been extended over the previous state of the art. This paper will present an overview of the MSL entry, descent, and landing system, a discussion of a subset of its development challenges, and include a discussion of preliminary results of the flight reconstruction effort.

Distribution of thermal neutrons in a temperature gradient

NASA Astrophysics Data System (ADS)

Molinari, V. G.; Pollachini, L.

A method to determine the spatial distribution of the thermal spectrum of neutrons in heterogeneous systems is presented. The method is based on diffusion concepts and has a simple mathematical structure which increases computing efficiency. The application of this theory to the neutron thermal diffusion induced by a temperature gradient, as found in nuclear reactors, is described. After introducing approximations, a nonlinear equation system representing the neutron temperature is given. Values of the equation parameters and its dependence on geometrical factors and media characteristics are discussed.

Pure phase encode magnetic field gradient monitor.

PubMed

Han, Hui; MacGregor, Rodney P; Balcom, Bruce J

2009-12-01

Numerous methods have been developed to measure MRI gradient waveforms and k-space trajectories. The most promising new strategy appears to be magnetic field monitoring with RF microprobes. Multiple RF microprobes may record the magnetic field evolution associated with a wide variety of imaging pulse sequences. The method involves exciting one or more test samples and measuring the time evolution of magnetization through the FIDs. Two critical problems remain. The gradient waveform duration is limited by the sample T(2)*, while the k-space maxima are limited by gradient dephasing. The method presented is based on pure phase encode FIDs and solves the above two problems in addition to permitting high strength gradient measurement. A small doped water phantom (1-3 mm droplet, T(1), T(2), T(2)* < 100 micros) within a microprobe is excited by a series of closely spaced broadband RF pulses each followed by FID single point acquisition. Two trial gradient waveforms have been chosen to illustrate the technique, neither of which could be measured by the conventional RF microprobe measurement. The first is an extended duration gradient waveform while the other illustrates the new method's ability to measure gradient waveforms with large net area and/or high amplitude. The new method is a point monitor with simple implementation and low cost hardware requirements.

Use of total electron content data to analyze ionosphere electron density gradients

NASA Astrophysics Data System (ADS)

Nava, B.; Radicella, S. M.; Leitinger, R.; Coïsson, P.

In the presence of electron density gradients the thin shell approximation for the ionosphere, used together with a simple mapping function to convert slant total electron content (TEC) to vertical TEC, could lead to TEC conversion errors. These "mapping function errors" can therefore be used to detect the electron density gradients in the ionosphere. In the present work GPS derived slant TEC data have been used to investigate the effects of the electron density gradients in the middle and low latitude ionosphere under geomagnetic quiet and disturbed conditions. In particular the data corresponding to the geographic area of the American Sector for the days 5-7 April 2000 have been used to perform a complete analysis of mapping function errors based on the "coinciding pierce point technique". The results clearly illustrate the electron density gradient effects according to the locations considered and to the actual levels of disturbance of the ionosphere. In addition, the possibility to assess an ionospheric shell height able to minimize the mapping function errors has been verified.

Mars Science Laboratory Descent Stage

NASA Image and Video Library

2011-11-10

The descent stage of NASA Mars Science Laboratory spacecraft is being lifted during assembly of the spacecraft in this photograph taken inside the Payload Hazardous Servicing Facility at NASA Kennedy Space Center, Fla.