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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Segmentation of human face using gradient-based approach

NASA Astrophysics Data System (ADS)

Baskan, Selin; Bulut, M. Mete; Atalay, Volkan

2001-04-01

This paper describes a method for automatic segmentation of facial features such as eyebrows, eyes, nose, mouth and ears in color images. This work is an initial step for wide range of applications based on feature-based approaches, such as face recognition, lip-reading, gender estimation, facial expression analysis, etc. Human face can be characterized by its skin color and nearly elliptical shape. For this purpose, face detection is performed using color and shape information. Uniform illumination is assumed. No restrictions on glasses, make-up, beard, etc. are imposed. Facial features are extracted using the vertically and horizontally oriented gradient projections. The gradient of a minimum with respect to its neighbor maxima gives the boundaries of a facial feature. Each facial feature has a different horizontal characteristic. These characteristics are derived by extensive experimentation with many face images. Using fuzzy set theory, the similarity between the candidate and the feature characteristic under consideration is calculated. Gradient-based method is accompanied by the anthropometrical information, for robustness. Ear detection is performed using contour-based shape descriptors. This method detects the facial features and circumscribes each facial feature with the smallest rectangle possible. AR database is used for testing. The developed method is also suitable for real-time systems.

Super-resolution fusion of complementary panoramic images based on cross-selection kernel regression interpolation.

PubMed

Chen, Lidong; Basu, Anup; Zhang, Maojun; Wang, Wei; Liu, Yu

2014-03-20

A complementary catadioptric imaging technique was proposed to solve the problem of low and nonuniform resolution in omnidirectional imaging. To enhance this research, our paper focuses on how to generate a high-resolution panoramic image from the captured omnidirectional image. To avoid the interference between the inner and outer images while fusing the two complementary views, a cross-selection kernel regression method is proposed. First, in view of the complementarity of sampling resolution in the tangential and radial directions between the inner and the outer images, respectively, the horizontal gradients in the expected panoramic image are estimated based on the scattered neighboring pixels mapped from the outer, while the vertical gradients are estimated using the inner image. Then, the size and shape of the regression kernel are adaptively steered based on the local gradients. Furthermore, the neighboring pixels in the next interpolation step of kernel regression are also selected based on the comparison between the horizontal and vertical gradients. In simulation and real-image experiments, the proposed method outperforms existing kernel regression methods and our previous wavelet-based fusion method in terms of both visual quality and objective evaluation.

Single fiber lignin distributions based on the density gradient column method

Treesearch

Brian Boyer; Alan W. Rudie

2007-01-01

The density gradient column method was used to determine the effects of uniform and non-uniform pulping processes on variation in individual fiber lignin concentrations of the resulting pulps. A density gradient column uses solvents of different densities and a mixing process to produce a column of liquid with a smooth transition from higher density at the bottom to...

Design and Performance of Property Gradient Ternary Nitride Coating Based on Process Control.

PubMed

Yan, Pei; Chen, Kaijie; Wang, Yubin; Zhou, Han; Peng, Zeyu; Jiao, Li; Wang, Xibin

2018-05-09

Surface coating is an effective approach to improve cutting tool performance, and multiple or gradient coating structures have become a common development strategy. However, composition mutations at the interfaces decrease the performance of multi-layered coatings. The key mitigation technique has been to reduce the interface effect at the boundaries. This study proposes a structure design method for property-component gradient coatings based on process control. The method produces coatings with high internal cohesion and high external hardness, which could reduce the composition and performance mutations at the interface. A ZrTiN property gradient ternary nitride coating was deposited on cemented carbide by multi-arc ion plating with separated Ti and Zr targets. The mechanical properties, friction behaviors, and cutting performances were systematically investigated, compared with a single-layer coating. The results indicated that the gradient coating had better friction and wear performance with lower wear rate and higher resistance to peeling off during sliding friction. The gradient coating had better wear and damage resistance in cutting processes, with lower machined surface roughness Ra. Gradient-structured coatings could effectively inhibit micro crack initiation and growth under alternating force and temperature load. This method could be extended to similar ternary nitride coatings.

Subsurface temperatures and geothermal gradients on the north slope of Alaska

USGS Publications Warehouse

Collett, T.S.; Bird, K.J.; Magoon, L.B.

1993-01-01

On the North Slope of Alaska, geothermal gradient data are available from high-resolution, equilibrated well-bore surveys and from estimates based on well-log identification of the base of ice-bearing permafrost. A total of 46 North Slope wells, considered to be in or near thermal equilibrium, have been surveyed with high-resolution temperatures devices and geothermal gradients can be interpreted directly from these recorded temperature profiles. To augment the limited North Slope temperature data base, a new method of evaluating local geothermal gradients has been developed. In this method, a series of well-log picks for the base of the ice-bearing permafrost from 102 wells have been used, along with regional temperature constants derived from the high-resolution stabilized well-bore temperature surveys, to project geothermal gradients. Geothermal gradients calculated from the high-resolution temperature surveys generally agree with those projected from known ice-bearing permafrost depths over most of the North Slope. Values in the ice-bearing permafrost range from ??? 1.5??C 100 m in the Prudhoe Bay area to ??? 4.5??C 100 m in the east-central portion of the National Petroleum Reserve in Alaska. Geothermal gradients below the ice-bearing permafrost sequence range from ??? 1.6??C 100 m to ??? 5.2??C 100 m. ?? 1993.

Improving the accuracy of the gradient method for determining soil carbon dioxide efflux

USDA-ARS?s Scientific Manuscript database

Continuous soil CO2 efflux (Fsoil) estimates can be obtained by the gradient method (GM), but the utility of the method is hindered by uncertainties in the application of published models for the diffusion coefficient (Ds). We compared two in-situ methods for determining Ds, one based calibrating th...

Method and means for a spatial and temporal probe for laser-generated plumes based on density gradients

DOEpatents

Yeung, E.S.; Chen, G.

1990-05-01

A method and means are disclosed for a spatial and temporal probe for laser generated plumes based on density gradients includes generation of a plume of vaporized material from a surface by an energy source. The probe laser beam is positioned so that the plume passes through the probe laser beam. Movement of the probe laser beam caused by refraction from the density gradient of the plume is monitored. Spatial and temporal information, correlated to one another, is then derived. 15 figs.

The equivalent magnetizing method applied to the design of gradient coils for MRI.

PubMed

Lopez, Hector Sanchez; Liu, Feng; Crozier, Stuart

2008-01-01

This paper presents a new method for the design of gradient coils for Magnetic Resonance Imaging systems. The method is based on the equivalence between a magnetized volume surrounded by a conducting surface and its equivalent representation in surface current/charge density. We demonstrate that the curl of the vertical magnetization induces a surface current density whose stream line defines the coil current pattern. This method can be applied for coils wounds on arbitrary surface shapes. A single layer unshielded transverse gradient coil is designed and compared, with the designs obtained using two conventional methods. Through the presented example we demonstrate that the generated unconventional current patterns obtained using the magnetizing current method produces a superior gradient coil performance than coils designed by applying conventional methods.

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.

Evaluation of an alternate method for sampling benthic macroinvertebrates in low-gradient streams sampled as part of the National Rivers and Streams Assessment.

PubMed

Flotemersch, Joseph E; North, Sheila; Blocksom, Karen A

2014-02-01

Benthic macroinvertebrates are sampled in streams and rivers as one of the assessment elements of the US Environmental Protection Agency's National Rivers and Streams Assessment. In a 2006 report, the recommendation was made that different yet comparable methods be evaluated for different types of streams (e.g., low gradient vs. high gradient). Consequently, a research element was added to the 2008-2009 National Rivers and Streams Assessment to conduct a side-by-side comparison of the standard macroinvertebrate sampling method with an alternate method specifically designed for low-gradient wadeable streams and rivers that focused more on stream edge habitat. Samples were collected using each method at 525 sites in five of nine aggregate ecoregions located in the conterminous USA. Methods were compared using the benthic macroinvertebrate multimetric index developed for the 2006 Wadeable Streams Assessment. Statistical analysis did not reveal any trends that would suggest the overall assessment of low-gradient streams on a regional or national scale would change if the alternate method was used rather than the standard sampling method, regardless of the gradient cutoff used to define low-gradient streams. Based on these results, the National Rivers and Streams Survey should continue to use the standard field method for sampling all streams.

Defect Detection of Steel Surfaces with Global Adaptive Percentile Thresholding of Gradient Image

NASA Astrophysics Data System (ADS)

Neogi, Nirbhar; Mohanta, Dusmanta K.; Dutta, Pranab K.

2017-12-01

Steel strips are used extensively for white goods, auto bodies and other purposes where surface defects are not acceptable. On-line surface inspection systems can effectively detect and classify defects and help in taking corrective actions. For detection of defects use of gradients is very popular in highlighting and subsequently segmenting areas of interest in a surface inspection system. Most of the time, segmentation by a fixed value threshold leads to unsatisfactory results. As defects can be both very small and large in size, segmentation of a gradient image based on percentile thresholding can lead to inadequate or excessive segmentation of defective regions. A global adaptive percentile thresholding of gradient image has been formulated for blister defect and water-deposit (a pseudo defect) in steel strips. The developed method adaptively changes the percentile value used for thresholding depending on the number of pixels above some specific values of gray level of the gradient image. The method is able to segment defective regions selectively preserving the characteristics of defects irrespective of the size of the defects. The developed method performs better than Otsu method of thresholding and an adaptive thresholding method based on local properties.

$L_{0}$ Gradient Projection.

PubMed

Ono, Shunsuke

2017-04-01

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

Gradient-based Electrical Properties Tomography (gEPT): a Robust Method for Mapping Electrical Properties of Biological Tissues In Vivo Using Magnetic Resonance Imaging

PubMed Central

Liu, Jiaen; Zhang, Xiaotong; Schmitter, Sebastian; Van de Moortele, Pierre-Francois; He, Bin

2014-01-01

Purpose To develop high-resolution electrical properties tomography (EPT) methods and investigate a gradient-based EPT (gEPT) approach which aims to reconstruct the electrical properties (EP), including conductivity and permittivity, of an imaged sample from experimentally measured B1 maps with improved boundary reconstruction and robustness against measurement noise. Theory and Methods Using a multi-channel transmit/receive stripline head coil, with acquired B1 maps for each coil element, by assuming negligible Bz component compared to transverse B1 components, a theory describing the relationship between B1 field, EP value and their spatial gradient has been proposed. The final EP images were obtained through spatial integration over the reconstructed EP gradient. Numerical simulation, physical phantom and in vivo human experiments at 7 T have been conducted to evaluate the performance of the proposed methods. Results Reconstruction results were compared with target EP values in both simulations and phantom experiments. Human experimental results were compared with EP values in literature. Satisfactory agreement was observed with improved boundary reconstruction. Importantly, the proposed gEPT method proved to be more robust against noise when compared to previously described non-gradient-based EPT approaches. Conclusion The proposed gEPT approach holds promises to improve EP mapping quality by recovering the boundary information and enhancing robustness against noise. PMID:25213371

Subpixel displacement measurement method based on the combination of particle swarm optimization and gradient algorithm

NASA Astrophysics Data System (ADS)

Guang, Chen; Qibo, Feng; Keqin, Ding; Zhan, Gao

2017-10-01

A subpixel displacement measurement method based on the combination of particle swarm optimization (PSO) and gradient algorithm (GA) was proposed for accuracy and speed optimization in GA, which is a subpixel displacement measurement method better applied in engineering practice. An initial integer-pixel value was obtained according to the global searching ability of PSO, and then gradient operators were adopted for a subpixel displacement search. A comparison was made between this method and GA by simulated speckle images and rigid-body displacement in metal specimens. The results showed that the computational accuracy of the combination of PSO and GA method reached 0.1 pixel in the simulated speckle images, or even 0.01 pixels in the metal specimen. Also, computational efficiency and the antinoise performance of the improved method were markedly enhanced.

Detection of ferromagnetic target based on mobile magnetic gradient tensor system

NASA Astrophysics Data System (ADS)

Gang, Y. I. N.; Yingtang, Zhang; Zhining, Li; Hongbo, Fan; Guoquan, Ren

2016-03-01

Attitude change of mobile magnetic gradient tensor system critically affects the precision of gradient measurements, thereby increasing ambiguity in target detection. This paper presents a rotational invariant-based method for locating and identifying ferromagnetic targets. Firstly, unit magnetic moment vector was derived based on the geometrical invariant, such that the intermediate eigenvector of the magnetic gradient tensor is perpendicular to the magnetic moment vector and the source-sensor displacement vector. Secondly, unit source-sensor displacement vector was derived based on the characteristic that the angle between magnetic moment vector and source-sensor displacement is a rotational invariant. By introducing a displacement vector between two measurement points, the magnetic moment vector and the source-sensor displacement vector were theoretically derived. To resolve the problem of measurement noises existing in the realistic detection applications, linear equations were formulated using invariants corresponding to several distinct measurement points and least square solution of magnetic moment vector and source-sensor displacement vector were obtained. Results of simulation and principal verification experiment showed the correctness of the analytical method, along with the practicability of the least square method.

Single image super-resolution using self-optimizing mask via fractional-order gradient interpolation and reconstruction.

PubMed

Yang, Qi; Zhang, Yanzhu; Zhao, Tiebiao; Chen, YangQuan

2017-04-04

Image super-resolution using self-optimizing mask via fractional-order gradient interpolation and reconstruction aims to recover detailed information from low-resolution images and reconstruct them into high-resolution images. Due to the limited amount of data and information retrieved from low-resolution images, it is difficult to restore clear, artifact-free images, while still preserving enough structure of the image such as the texture. This paper presents a new single image super-resolution method which is based on adaptive fractional-order gradient interpolation and reconstruction. The interpolated image gradient via optimal fractional-order gradient is first constructed according to the image similarity and afterwards the minimum energy function is employed to reconstruct the final high-resolution image. Fractional-order gradient based interpolation methods provide an additional degree of freedom which helps optimize the implementation quality due to the fact that an extra free parameter α-order is being used. The proposed method is able to produce a rich texture detail while still being able to maintain structural similarity even under large zoom conditions. Experimental results show that the proposed method performs better than current single image super-resolution techniques. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Development, validation, and comparison of ICA-based gradient artifact reduction algorithms for simultaneous EEG-spiral in/out and echo-planar fMRI recordings

PubMed Central

Ryali, S; Glover, GH; Chang, C; Menon, V

2009-01-01

EEG data acquired in an MRI scanner are heavily contaminated by gradient artifacts that can significantly compromise signal quality. We developed two new methods based on Independent Component Analysis (ICA) for reducing gradient artifacts from spiral in-out and echo-planar pulse sequences at 3T, and compared our algorithms with four other commonly used methods: average artifact subtraction (Allen et al. 2000), principal component analysis (Niazy et al. 2005), Taylor series (Wan et al. 2006) and a conventional temporal ICA algorithm. Models of gradient artifacts were derived from simulations as well as a water phantom and performance of each method was evaluated on datasets constructed using visual event-related potentials (ERPs) as well as resting EEG. Our new methods recovered ERPs and resting EEG below the beta band (< 12.5 Hz) with high signal-to-noise ratio (SNR > 4). Our algorithms outperformed all of these methods on resting EEG in the theta- and alpha-bands (SNR > 4); however, for all methods, signal recovery was modest (SNR ~ 1) in the beta-band and poor (SNR < 0.3) in the gamma-band and above. We found that the conventional ICA algorithm performed poorly with uniformly low SNR (< 0.1). Taken together, our new ICA-based methods offer a more robust technique for gradient artifact reduction when scanning at 3T using spiral in-out and echo-planar pulse sequences. We provide new insights into the strengths and weaknesses of each method using a unified subspace framework. PMID:19580873

Using phylogeny and functional traits for assessing community assembly along environmental gradients: A deterministic process driven by elevation.

PubMed

Xu, Jinshi; Chen, Yu; Zhang, Lixia; Chai, Yongfu; Wang, Mao; Guo, Yaoxin; Li, Ting; Yue, Ming

2017-07-01

Community assembly processes is the primary focus of community ecology. Using phylogenetic-based and functional trait-based methods jointly to explore these processes along environmental gradients are useful ways to explain the change of assembly mechanisms under changing world. Our study combined these methods to test assembly processes in wide range gradients of elevation and other habitat environmental factors. We collected our data at 40 plots in Taibai Mountain, China, with more than 2,300 m altitude difference in study area and then measured traits and environmental factors. Variance partitioning was used to distinguish the main environment factors leading to phylogeny and traits change among 40 plots. Principal component analysis (PCA) was applied to colligate other environment factors. Community assembly patterns along environmental gradients based on phylogenetic and functional methods were studied for exploring assembly mechanisms. Phylogenetic signal was calculated for each community along environmental gradients in order to detect the variation of trait performance on phylogeny. Elevation showed a better explanatory power than other environment factors for phylogenetic and most traits' variance. Phylogenetic and several functional structure clustered at high elevation while some conserved traits overdispersed. Convergent tendency which might be caused by filtering or competition along elevation was detected based on functional traits. Leaf dry matter content (LDMC) and leaf nitrogen content along PCA 1 axis showed conflicting patterns comparing to patterns showed on elevation. LDMC exhibited the strongest phylogenetic signal. Only the phylogenetic signal of maximum plant height showed explicable change along environmental gradients. Synthesis . Elevation is the best environment factors for predicting phylogeny and traits change. Plant's phylogenetic and some functional structures show environmental filtering in alpine region while it shows different assembly processes in middle- and low-altitude region by different trait/phylogeny. The results highlight deterministic processes dominate community assembly in large-scale environmental gradients. Performance of phylogeny and traits along gradients may be independent with each other. The novel method for calculating functional structure which we used in this study and the focus of phylogenetic signal change along gradients may provide more useful ways to detect community assembly mechanisms.

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

PubMed

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

2015-01-01

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

Testing the limits of gradient sensing

PubMed Central

Lakhani, Vinal

2017-01-01

The ability to detect a chemical gradient is fundamental to many cellular processes. In multicellular organisms gradient sensing plays an important role in many physiological processes such as wound healing and development. Unicellular organisms use gradient sensing to move (chemotaxis) or grow (chemotropism) towards a favorable environment. Some cells are capable of detecting extremely shallow gradients, even in the presence of significant molecular-level noise. For example, yeast have been reported to detect pheromone gradients as shallow as 0.1 nM/μm. Noise reduction mechanisms, such as time-averaging and the internalization of pheromone molecules, have been proposed to explain how yeast cells filter fluctuations and detect shallow gradients. Here, we use a Particle-Based Reaction-Diffusion model of ligand-receptor dynamics to test the effectiveness of these mechanisms and to determine the limits of gradient sensing. In particular, we develop novel simulation methods for establishing chemical gradients that not only allow us to study gradient sensing under steady-state conditions, but also take into account transient effects as the gradient forms. Based on reported measurements of reaction rates, our results indicate neither time-averaging nor receptor endocytosis significantly improves the cell’s accuracy in detecting gradients over time scales associated with the initiation of polarized growth. Additionally, our results demonstrate the physical barrier of the cell membrane sharpens chemical gradients across the cell. While our studies are motivated by the mating response of yeast, we believe our results and simulation methods will find applications in many different contexts. PMID:28207738

Surface Profile and Stress Field Evaluation using Digital Gradient Sensing Method

DOE PAGES

Miao, C.; Sundaram, B. M.; Huang, L.; ...

2016-08-09

Shape and surface topography evaluation from measured orthogonal slope/gradient data is of considerable engineering significance since many full-field optical sensors and interferometers readily output accurate data of that kind. This has applications ranging from metrology of optical and electronic elements (lenses, silicon wafers, thin film coatings), surface profile estimation, wave front and shape reconstruction, to name a few. In this context, a new methodology for surface profile and stress field determination based on a recently introduced non-contact, full-field optical method called digital gradient sensing (DGS) capable of measuring small angular deflections of light rays coupled with a robust finite-difference-based least-squaresmore » integration (HFLI) scheme in the Southwell configuration is advanced here. The method is demonstrated by evaluating (a) surface profiles of mechanically warped silicon wafers and (b) stress gradients near growing cracks in planar phase objects.« less

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].

SU-C-BRA-02: Gradient Based Method of Target Delineation On PET/MR Image of Head and Neck Cancer Patients

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

Dance, M; Chera, B; Falchook, A

2015-06-15

Purpose: Validate the consistency of a gradient-based segmentation tool to facilitate accurate delineation of PET/CT-based GTVs in head and neck cancers by comparing against hybrid PET/MR-derived GTV contours. Materials and Methods: A total of 18 head and neck target volumes (10 primary and 8 nodal) were retrospectively contoured using a gradient-based segmentation tool by two observers. Each observer independently contoured each target five times. Inter-observer variability was evaluated via absolute percent differences. Intra-observer variability was examined by percentage uncertainty. All target volumes were also contoured using the SUV percent threshold method. The thresholds were explored case by case so itsmore » derived volume matched with the gradient-based volume. Dice similarity coefficients (DSC) were calculated to determine overlap of PET/CT GTVs and PET/MR GTVs. Results: The Levene’s test showed there was no statistically significant difference of the variances between the observer’s gradient-derived contours. However, the absolute difference between the observer’s volumes was 10.83%, with a range from 0.39% up to 42.89%. PET-avid regions with qualitatively non-uniform shapes and intensity levels had a higher absolute percent difference near 25%, while regions with uniform shapes and intensity levels had an absolute percent difference of 2% between observers. The average percentage uncertainty between observers was 4.83% and 7%. As the volume of the gradient-derived contours increased, the SUV threshold percent needed to match the volume decreased. Dice coefficients showed good agreement of the PET/CT and PET/MR GTVs with an average DSC value across all volumes at 0.69. Conclusion: Gradient-based segmentation of PET volume showed good consistency in general but can vary considerably for non-uniform target shapes and intensity levels. PET/CT-derived GTV contours stemming from the gradient-based tool show good agreement with the anatomically and metabolically more accurate PET/MR-derived GTV contours, but tumor delineation accuracy can be further improved with the use PET/MR.« less

Determination of boundaries between ranges of high and low gradient of beam profile.

PubMed

Wendykier, Jacek; Bieniasiewicz, Marcin; Grządziel, Aleksandra; Jedynak, Tadeusz; Kośniewski, Wiktor; Reudelsdorf, Marta; Wendykier, Piotr

2016-01-01

This work addresses the problem of treatment planning system commissioning by introducing a new method of determination of boundaries between high and low gradient in beam profile. The commissioning of a treatment planning system is a very important task in the radiation therapy. One of the main goals of this task is to compare two field profiles: measured and calculated. Applying points of 80% and 120% of nominal field size can lead to the incorrect determination of boundaries, especially for small field sizes. The method that is based on the beam profile gradient allows for proper assignment of boundaries between high and low gradient regions even for small fields. TRS 430 recommendations for commissioning were used. The described method allows a separation between high and low gradient, because it directly uses the value of the gradient of a profile. For small fields, the boundaries determined by the new method allow a commissioning of a treatment planning system according to the TRS 430, while the point of 80% of nominal field size is already in the high gradient region. The method of determining the boundaries by using the beam profile gradient can be extremely helpful during the commissioning of the treatment planning system for Intensity Modulated Radiation Therapy or for other techniques which require very small field sizes.

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.

Gradient-based Optimization for Poroelastic and Viscoelastic MR Elastography

PubMed Central

Tan, Likun; McGarry, Matthew D.J.; Van Houten, Elijah E.W.; Ji, Ming; Solamen, Ligin; Weaver, John B.

2017-01-01

We describe an efficient gradient computation for solving inverse problems arising in magnetic resonance elastography (MRE). The algorithm can be considered as a generalized ‘adjoint method’ based on a Lagrangian formulation. One requirement for the classic adjoint method is assurance of the self-adjoint property of the stiffness matrix in the elasticity problem. In this paper, we show this property is no longer a necessary condition in our algorithm, but the computational performance can be as efficient as the classic method, which involves only two forward solutions and is independent of the number of parameters to be estimated. The algorithm is developed and implemented in material property reconstructions using poroelastic and viscoelastic modeling. Various gradient- and Hessian-based optimization techniques have been tested on simulation, phantom and in vivo brain data. The numerical results show the feasibility and the efficiency of the proposed scheme for gradient calculation. PMID:27608454

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

NASA Astrophysics Data System (ADS)

Lavery, N.; Taylor, C.

1999-07-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

A new leakage measurement method for damaged seal material

NASA Astrophysics Data System (ADS)

Wang, Shen; Yao, Xue Feng; Yang, Heng; Yuan, Li; Dong, Yi Feng

2018-07-01

In this paper, a new leakage measurement method based on the temperature field and temperature gradient field is proposed for detecting the leakage location and measuring the leakage rate in damaged seal material. First, a heat transfer leakage model is established, which can calculate the leakage rate based on the temperature gradient field near the damaged zone. Second, a finite element model of an infinite plate with a damaged zone is built to calculate the leakage rate, which fits the simulated leakage rate well. Finally, specimens in a tubular rubber seal with different damage shapes are used to conduct the leakage experiment, validating the correctness of this new measurement principle for the leakage rate and the leakage position. The results indicate the feasibility of the leakage measurement method for damaged seal material based on the temperature gradient field from infrared thermography.

Aeromagnetic gradient compensation method for helicopter based on ɛ-support vector regression algorithm

NASA Astrophysics Data System (ADS)

Wu, Peilin; Zhang, Qunying; Fei, Chunjiao; Fang, Guangyou

2017-04-01

Aeromagnetic gradients are typically measured by optically pumped magnetometers mounted on an aircraft. Any aircraft, particularly helicopters, produces significant levels of magnetic interference. Therefore, aeromagnetic compensation is essential, and least square (LS) is the conventional method used for reducing interference levels. However, the LSs approach to solving the aeromagnetic interference model has a few difficulties, one of which is in handling multicollinearity. Therefore, we propose an aeromagnetic gradient compensation method, specifically targeted for helicopter use but applicable on any airborne platform, which is based on the ɛ-support vector regression algorithm. The structural risk minimization criterion intrinsic to the method avoids multicollinearity altogether. Local aeromagnetic anomalies can be retained, and platform-generated fields are suppressed simultaneously by constructing an appropriate loss function and kernel function. The method was tested using an unmanned helicopter and obtained improvement ratios of 12.7 and 3.5 in the vertical and horizontal gradient data, respectively. Both of these values are probably better than those that would have been obtained from the conventional method applied to the same data, had it been possible to do so in a suitable comparative context. The validity of the proposed method is demonstrated by the experimental result.

What is the best way to contour lung tumors on PET scans? Multiobserver validation of a gradient-based method using a NSCLC digital PET phantom.

PubMed

Werner-Wasik, Maria; Nelson, Arden D; Choi, Walter; Arai, Yoshio; Faulhaber, Peter F; Kang, Patrick; Almeida, Fabio D; Xiao, Ying; Ohri, Nitin; Brockway, Kristin D; Piper, Jonathan W; Nelson, Aaron S

2012-03-01

To evaluate the accuracy and consistency of a gradient-based positron emission tomography (PET) segmentation method, GRADIENT, compared with manual (MANUAL) and constant threshold (THRESHOLD) methods. Contouring accuracy was evaluated with sphere phantoms and clinically realistic Monte Carlo PET phantoms of the thorax. The sphere phantoms were 10-37 mm in diameter and were acquired at five institutions emulating clinical conditions. One institution also acquired a sphere phantom with multiple source-to-background ratios of 2:1, 5:1, 10:1, 20:1, and 70:1. One observer segmented (contoured) each sphere with GRADIENT and THRESHOLD from 25% to 50% at 5% increments. Subsequently, seven physicians segmented 31 lesions (7-264 mL) from 25 digital thorax phantoms using GRADIENT, THRESHOLD, and MANUAL. For spheres <20 mm in diameter, GRADIENT was the most accurate with a mean absolute % error in diameter of 8.15% (10.2% SD) compared with 49.2% (51.1% SD) for 45% THRESHOLD (p < 0.005). For larger spheres, the methods were statistically equivalent. For varying source-to-background ratios, GRADIENT was the most accurate for spheres >20 mm (p < 0.065) and <20 mm (p < 0.015). For digital thorax phantoms, GRADIENT was the most accurate (p < 0.01), with a mean absolute % error in volume of 10.99% (11.9% SD), followed by 25% THRESHOLD at 17.5% (29.4% SD), and MANUAL at 19.5% (17.2% SD). GRADIENT had the least systematic bias, with a mean % error in volume of -0.05% (16.2% SD) compared with 25% THRESHOLD at -2.1% (34.2% SD) and MANUAL at -16.3% (20.2% SD; p value <0.01). Interobserver variability was reduced using GRADIENT compared with both 25% THRESHOLD and MANUAL (p value <0.01, Levene's test). GRADIENT was the most accurate and consistent technique for target volume contouring. GRADIENT was also the most robust for varying imaging conditions. GRADIENT has the potential to play an important role for tumor delineation in radiation therapy planning and response assessment. Copyright © 2012. Published by Elsevier Inc.

Gradients estimation from random points with volumetric tensor in turbulence

NASA Astrophysics Data System (ADS)

Watanabe, Tomoaki; Nagata, Koji

2017-12-01

We present an estimation method of fully-resolved/coarse-grained gradients from randomly distributed points in turbulence. The method is based on a linear approximation of spatial gradients expressed with the volumetric tensor, which is a 3 × 3 matrix determined by a geometric distribution of the points. The coarse grained gradient can be considered as a low pass filtered gradient, whose cutoff is estimated with the eigenvalues of the volumetric tensor. The present method, the volumetric tensor approximation, is tested for velocity and passive scalar gradients in incompressible planar jet and mixing layer. Comparison with a finite difference approximation on a Cartesian grid shows that the volumetric tensor approximation computes the coarse grained gradients fairly well at a moderate computational cost under various conditions of spatial distributions of points. We also show that imposing the solenoidal condition improves the accuracy of the present method for solenoidal vectors, such as a velocity vector in incompressible flows, especially when the number of the points is not large. The volumetric tensor approximation with 4 points poorly estimates the gradient because of anisotropic distribution of the points. Increasing the number of points from 4 significantly improves the accuracy. Although the coarse grained gradient changes with the cutoff length, the volumetric tensor approximation yields the coarse grained gradient whose magnitude is close to the one obtained by the finite difference. We also show that the velocity gradient estimated with the present method well captures the turbulence characteristics such as local flow topology, amplification of enstrophy and strain, and energy transfer across scales.

A blind deconvolution method based on L1/L2 regularization prior in the gradient space

NASA Astrophysics Data System (ADS)

Cai, Ying; Shi, Yu; Hua, Xia

2018-02-01

In the process of image restoration, the result of image restoration is very different from the real image because of the existence of noise, in order to solve the ill posed problem in image restoration, a blind deconvolution method based on L1/L2 regularization prior to gradient domain is proposed. The method presented in this paper first adds a function to the prior knowledge, which is the ratio of the L1 norm to the L2 norm, and takes the function as the penalty term in the high frequency domain of the image. Then, the function is iteratively updated, and the iterative shrinkage threshold algorithm is applied to solve the high frequency image. In this paper, it is considered that the information in the gradient domain is better for the estimation of blur kernel, so the blur kernel is estimated in the gradient domain. This problem can be quickly implemented in the frequency domain by fast Fast Fourier Transform. In addition, in order to improve the effectiveness of the algorithm, we have added a multi-scale iterative optimization method. This paper proposes the blind deconvolution method based on L1/L2 regularization priors in the gradient space can obtain the unique and stable solution in the process of image restoration, which not only keeps the edges and details of the image, but also ensures the accuracy of the results.

Edge gradients evaluation for 2D hybrid finite volume method model

USDA-ARS?s Scientific Manuscript database

In this study, a two-dimensional depth-integrated hydrodynamic model was developed using FVM on a hybrid unstructured collocated mesh system. To alleviate the negative effects of mesh irregularity and non-uniformity, a conservative evaluation method for edge gradients based on the second-order Tayl...

Inverse solutions for electrical impedance tomography based on conjugate gradients methods

NASA Astrophysics Data System (ADS)

Wang, M.

2002-01-01

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

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

PubMed Central

Feng, Shuo

2014-01-01

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

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

PubMed

Feng, Shuo; Ji, Jim

2014-04-01

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

Microsphere-based gradient implants for osteochondral regeneration: a long-term study in sheep

PubMed Central

Mohan, Neethu; Gupta, Vineet; Sridharan, Banu Priya; Mellott, Adam J; Easley, Jeremiah T; Palmer, Ross H; Galbraith, Richard A; Key, Vincent H; Berkland, Cory J; Detamore, Michael S

2015-01-01

Background: The microfracture technique for cartilage repair has limited ability to regenerate hyaline cartilage. Aim: The current study made a direct comparison between microfracture and an osteochondral approach with microsphere-based gradient plugs. Materials & methods: The PLGA-based scaffolds had opposing gradients of chondroitin sulfate and β-tricalcium phosphate. A 1-year repair study in sheep was conducted. Results: The repair tissues in the microfracture were mostly fibrous and had scattered fissures with degenerative changes. Cartilage regenerated with the gradient plugs had equal or superior mechanical properties; had lacunated cells and stable matrix as in hyaline cartilage. Conclusion: This first report of gradient scaffolds in a long-term, large animal, osteochondral defect demonstrated potential for equal or better cartilage repair than microfracture. PMID:26418471

Nested Conjugate Gradient Algorithm with Nested Preconditioning for Non-linear Image Restoration.

PubMed

Skariah, Deepak G; Arigovindan, Muthuvel

2017-06-19

We develop a novel optimization algorithm, which we call Nested Non-Linear Conjugate Gradient algorithm (NNCG), for image restoration based on quadratic data fitting and smooth non-quadratic regularization. The algorithm is constructed as a nesting of two conjugate gradient (CG) iterations. The outer iteration is constructed as a preconditioned non-linear CG algorithm; the preconditioning is performed by the inner CG iteration that is linear. The inner CG iteration, which performs preconditioning for outer CG iteration, itself is accelerated by an another FFT based non-iterative preconditioner. We prove that the method converges to a stationary point for both convex and non-convex regularization functionals. We demonstrate experimentally that proposed method outperforms the well-known majorization-minimization method used for convex regularization, and a non-convex inertial-proximal method for non-convex regularization functional.

Determination of reversed-phase high performance liquid chromatography based octanol-water partition coefficients for neutral and ionizable compounds: Methodology evaluation.

PubMed

Liang, Chao; Qiao, Jun-Qin; Lian, Hong-Zhen

2017-12-15

Reversed-phase liquid chromatography (RPLC) based octanol-water partition coefficient (logP) or distribution coefficient (logD) determination methods were revisited and assessed comprehensively. Classic isocratic and some gradient RPLC methods were conducted and evaluated for neutral, weak acid and basic compounds. Different lipophilicity indexes in logP or logD determination were discussed in detail, including the retention factor logk w corresponding to neat water as mobile phase extrapolated via linear solvent strength (LSS) model from isocratic runs and calculated with software from gradient runs, the chromatographic hydrophobicity index (CHI), apparent gradient capacity factor (k g ') and gradient retention time (t g ). Among the lipophilicity indexes discussed, logk w from whether isocratic or gradient elution methods best correlated with logP or logD. Therefore logk w is recommended as the preferred lipophilicity index for logP or logD determination. logk w easily calculated from methanol gradient runs might be the main candidate to replace logk w calculated from classic isocratic run as the ideal lipophilicity index. These revisited RPLC methods were not applicable for strongly ionized compounds that are hardly ion-suppressed. A previously reported imperfect ion-pair RPLC method was attempted and further explored for studying distribution coefficients (logD) of sulfonic acids that totally ionized in the mobile phase. Notably, experimental logD values of sulfonic acids were given for the first time. The IP-RPLC method provided a distinct way to explore logD values of ionized compounds. Copyright © 2017 Elsevier B.V. All rights reserved.

Monitoring gradient profile on-line in micro- and nano-high performance liquid chromatography using conductivity detection.

PubMed

Zhang, Min; Chen, Apeng; Lu, Joann J; Cao, Chengxi; Liu, Shaorong

2016-08-19

In micro- or nano-flow high performance liquid chromatography (HPLC), flow-splitters and gradient elutions are commonly used for reverse phase HPLC separations. When a flow splitter was used at a high split-ratio (e.g., 1000:1 or higher), the actual gradient may deviate away from the programmed gradient. Sometimes, mobile phase concentrations can deviate by as much as 5%. In this work, we noticed that the conductivity (σ) of a gradient decreased with the increasing organic-solvent fraction (φ). Based on the relationship between σ and φ, a method was developed for monitoring gradient profile on-line to record any deviations in these HPLC systems. The conductivity could be measured by a traditional conductivity detector or a capacitively coupled contactless conductivity detector (C(4)D). The method was applied for assessing the performance of an electroosmotic pump (EOP) based nano-HPLC. We also observed that σ value of the gradient changed with system pressure; a=0.0175ΔP (R(2)=0.964), where a is the percentage of the conductivity increase and ΔP is the system pressure in bar. This effect was also investigated. Copyright © 2016. Published by Elsevier B.V.

Orthonormal vector general polynomials derived from the Cartesian gradient of the orthonormal Zernike-based polynomials.

PubMed

Mafusire, Cosmas; Krüger, Tjaart P J

2018-06-01

The concept of orthonormal vector circle polynomials is revisited by deriving a set from the Cartesian gradient of Zernike polynomials in a unit circle using a matrix-based approach. The heart of this model is a closed-form matrix equation of the gradient of Zernike circle polynomials expressed as a linear combination of lower-order Zernike circle polynomials related through a gradient matrix. This is a sparse matrix whose elements are two-dimensional standard basis transverse Euclidean vectors. Using the outer product form of the Cholesky decomposition, the gradient matrix is used to calculate a new matrix, which we used to express the Cartesian gradient of the Zernike circle polynomials as a linear combination of orthonormal vector circle polynomials. Since this new matrix is singular, the orthonormal vector polynomials are recovered by reducing the matrix to its row echelon form using the Gauss-Jordan elimination method. We extend the model to derive orthonormal vector general polynomials, which are orthonormal in a general pupil by performing a similarity transformation on the gradient matrix to give its equivalent in the general pupil. The outer form of the Gram-Schmidt procedure and the Gauss-Jordan elimination method are then applied to the general pupil to generate the orthonormal vector general polynomials from the gradient of the orthonormal Zernike-based polynomials. The performance of the model is demonstrated with a simulated wavefront in a square pupil inscribed in a unit circle.

A general strategy for performing temperature-programming in high performance liquid chromatography--further improvements in the accuracy of retention time predictions of segmented temperature gradients.

PubMed

Wiese, Steffen; Teutenberg, Thorsten; Schmidt, Torsten C

2012-01-27

In the present work it is shown that the linear elution strength (LES) model which was adapted from temperature-programming gas chromatography (GC) can also be employed for systematic method development in high-temperature liquid chromatography (HT-HPLC). The ability to predict isothermal retention times based on temperature-gradient as well as isothermal input data was investigated. For a small temperature interval of ΔT=40°C, both approaches result in very similar predictions. Average relative errors of predicted retention times of 2.7% and 1.9% were observed for simulations based on isothermal and temperature-gradient measurements, respectively. Concurrently, it was investigated whether the accuracy of retention time predictions of segmented temperature gradients can be further improved by temperature dependent calculation of the parameter S(T) of the LES relationship. It was found that the accuracy of retention time predictions of multi-step temperature gradients can be improved to around 1.5%, if S(T) was also calculated temperature dependent. The adjusted experimental design making use of four temperature-gradient measurements was applied for systematic method development of selected food additives by high-temperature liquid chromatography. Method development was performed within a temperature interval from 40°C to 180°C using water as mobile phase. Two separation methods were established where selected food additives were baseline separated. In addition, a good agreement between simulation and experiment was observed, because an average relative error of predicted retention times of complex segmented temperature gradients less than 5% was observed. Finally, a schedule of recommendations to assist the practitioner during systematic method development in high-temperature liquid chromatography was established. Copyright © 2011 Elsevier B.V. All rights reserved.

Determination of wall shear stress from mean velocity and Reynolds shear stress profiles

NASA Astrophysics Data System (ADS)

Volino, Ralph J.; Schultz, Michael P.

2018-03-01

An analytical method is presented for determining the Reynolds shear stress profile in steady, two-dimensional wall-bounded flows using the mean streamwise velocity. The method is then utilized with experimental data to determine the local wall shear stress. The procedure is applicable to flows on smooth and rough surfaces with arbitrary pressure gradients. It is based on the streamwise component of the boundary layer momentum equation, which is transformed into inner coordinates. The method requires velocity profiles from at least two streamwise locations, but the formulation of the momentum equation reduces the dependence on streamwise gradients. The method is verified through application to laminar flow solutions and turbulent DNS results from both zero and nonzero pressure gradient boundary layers. With strong favorable pressure gradients, the method is shown to be accurate for finding the wall shear stress in cases where the Clauser fit technique loses accuracy. The method is then applied to experimental data from the literature from zero pressure gradient studies on smooth and rough walls, and favorable and adverse pressure gradient cases on smooth walls. Data from very near the wall are not required for determination of the wall shear stress. Wall friction velocities obtained using the present method agree with those determined in the original studies, typically to within 2%.

Refractive index gradient measurement across the thickness of a dielectric film by the prism coupling method

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

Sokolov, Viktor I; Panchenko, Vladislav Ya; Seminogov, V N

2012-08-31

A method is proposed for measuring the refractive index gradient n(z) in nonuniformly thick dielectric films. The method is based on the excitation of waveguide modes in a film using the prism coupling technique and on the calculation of n(z) and film thickness H{sub f} with the help of the angular positions of the TE or TM modes. The method can be used for an arbitrary shape of the index modulation over the film thickness in the limit of a small gradient [{Delta} n(z)/n(z) || 1]. (laser applications and other topics in quantum electronics)

A wet/wet differential pressure sensor for measuring vertical hydraulic gradient.

PubMed

Fritz, Brad G; Mackley, Rob D

2010-01-01

Vertical hydraulic gradient is commonly measured in rivers, lakes, and streams for studies of groundwater-surface water interaction. While a number of methods with subtle differences have been applied, these methods can generally be separated into two categories; measuring surface water elevation and pressure in the subsurface separately or making direct measurements of the head difference with a manometer. Making separate head measurements allows for the use of electronic pressure sensors, providing large datasets that are particularly useful when the vertical hydraulic gradient fluctuates over time. On the other hand, using a manometer-based method provides an easier and more rapid measurement with a simpler computation to calculate the vertical hydraulic gradient. In this study, we evaluated a wet/wet differential pressure sensor for use in measuring vertical hydraulic gradient. This approach combines the advantage of high-temporal frequency measurements obtained with instrumented piezometers with the simplicity and reduced potential for human-induced error obtained with a manometer board method. Our results showed that the wet/wet differential pressure sensor provided results comparable to more traditional methods, making it an acceptable method for future use.

Functional linear models to test for differences in prairie wetland hydraulic gradients

USGS Publications Warehouse

Greenwood, Mark C.; Sojda, Richard S.; Preston, Todd M.; Swayne, David A.; Yang, Wanhong; Voinov, A.A.; Rizzoli, A.; Filatova, T.

2010-01-01

Functional data analysis provides a framework for analyzing multiple time series measured frequently in time, treating each series as a continuous function of time. Functional linear models are used to test for effects on hydraulic gradient functional responses collected from three types of land use in Northeastern Montana at fourteen locations. Penalized regression-splines are used to estimate the underlying continuous functions based on the discretely recorded (over time) gradient measurements. Permutation methods are used to assess the statistical significance of effects. A method for accommodating missing observations in each time series is described. Hydraulic gradients may be an initial and fundamental ecosystem process that responds to climate change. We suggest other potential uses of these methods for detecting evidence of climate change.

2D joint inversion of CSAMT and magnetic data based on cross-gradient theory

NASA Astrophysics Data System (ADS)

Wang, Kun-Peng; Tan, Han-Dong; Wang, Tao

2017-06-01

A two-dimensional forward and backward algorithm for the controlled-source audio-frequency magnetotelluric (CSAMT) method is developed to invert data in the entire region (near, transition, and far) and deal with the effects of artificial sources. First, a regularization factor is introduced in the 2D magnetic inversion, and the magnetic susceptibility is updated in logarithmic form so that the inversion magnetic susceptibility is always positive. Second, the joint inversion of the CSAMT and magnetic methods is completed with the introduction of the cross gradient. By searching for the weight of the cross-gradient term in the objective function, the mutual influence between two different physical properties at different locations are avoided. Model tests show that the joint inversion based on cross-gradient theory offers better results than the single-method inversion. The 2D forward and inverse algorithm for CSAMT with source can effectively deal with artificial sources and ensures the reliability of the final joint inversion algorithm.

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

PubMed Central

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

2011-01-01

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

Systematic generation of buffer systems for pH gradient ion exchange chromatography and their application.

PubMed

Kröner, Frieder; Hubbuch, Jürgen

2013-04-12

pH gradient protein separations are widely used techniques in the field of protein analytics, of which isoelectric focusing is the most well known application. The chromatographic variant, based on the formation of pH gradients in ion exchange columns is only rarely applied due to the difficulties to form controllable, linear pH gradients over a broad pH range. This work describes a method for the systematic generation of buffer compositions with linear titration curves, resulting in well controllable pH gradients. To generate buffer compositions with linear titration curves an in silico method was successfully developed. With this tool, buffer compositions for pH gradient ion exchange chromatography with pH ranges spanning up to 7.5 pH units were established and successfully validated. Subsequently, the buffer systems were used to characterize the elution behavior of 22 different model proteins in cation and anion exchange pH gradient chromatography. The results of both chromatographic modes as well as isoelectric focusing were compared to describe differences in between the methods. Copyright © 2013 Elsevier B.V. All rights reserved.

Computational study of the effect of gradient magnetic field in navigation of spherical particles

NASA Astrophysics Data System (ADS)

Karvelas, E. G.; Lampropoulos, N. K.; Papadimitriou, D. I.; Karakasidis, T. E.; Sarris, I. E.

2017-11-01

The use of spherical magnetic nanoparticles that are coated with drugs and can be navigated in arteries to attack tumors is proposed as an alternative to chemotherapy. Navigation of particles is due to magnetic field gradients that may be produced in an MRI device. In the present work, a computational study for the evaluation of the magnitude of the gradient magnetic field for particles navigation in Y bifurcations is presented. For this purpose, the presented method solves for the fluid flow and includes all the important forces that act on the particles in their discrete motion. The method is based on an iteration algorithm that adjusts the gradient magnetic field to minimize the particles’ deviation from a desired trajectory. Using the above mentioned method, the appropriate range of the gradient magnetic field for optimum navigation of nanoparticles’s aggregation is found.

Canceling the Gravity Gradient Phase Shift in Atom Interferometry.

PubMed

D'Amico, G; Rosi, G; Zhan, S; Cacciapuoti, L; Fattori, M; Tino, G M

2017-12-22

Gravity gradients represent a major obstacle in high-precision measurements by atom interferometry. Controlling their effects to the required stability and accuracy imposes very stringent requirements on the relative positioning of freely falling atomic clouds, as in the case of precise tests of Einstein's equivalence principle. We demonstrate a new method to exactly compensate the effects introduced by gravity gradients in a Raman-pulse atom interferometer. By shifting the frequency of the Raman lasers during the central π pulse, it is possible to cancel the initial position- and velocity-dependent phase shift produced by gravity gradients. We apply this technique to simultaneous interferometers positioned along the vertical direction and demonstrate a new method for measuring local gravity gradients that does not require precise knowledge of the relative position between the atomic clouds. Based on this method, we also propose an improved scheme to determine the Newtonian gravitational constant G towards the 10 ppm relative uncertainty.

Canceling the Gravity Gradient Phase Shift in Atom Interferometry

NASA Astrophysics Data System (ADS)

D'Amico, G.; Rosi, G.; Zhan, S.; Cacciapuoti, L.; Fattori, M.; Tino, G. M.

2017-12-01

Gravity gradients represent a major obstacle in high-precision measurements by atom interferometry. Controlling their effects to the required stability and accuracy imposes very stringent requirements on the relative positioning of freely falling atomic clouds, as in the case of precise tests of Einstein's equivalence principle. We demonstrate a new method to exactly compensate the effects introduced by gravity gradients in a Raman-pulse atom interferometer. By shifting the frequency of the Raman lasers during the central π pulse, it is possible to cancel the initial position- and velocity-dependent phase shift produced by gravity gradients. We apply this technique to simultaneous interferometers positioned along the vertical direction and demonstrate a new method for measuring local gravity gradients that does not require precise knowledge of the relative position between the atomic clouds. Based on this method, we also propose an improved scheme to determine the Newtonian gravitational constant G towards the 10 ppm relative uncertainty.

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.

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.

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.

Optimization of Turbine Engine Cycle Analysis with Analytic Derivatives

NASA Technical Reports Server (NTRS)

Hearn, Tristan; Hendricks, Eric; Chin, Jeffrey; Gray, Justin; Moore, Kenneth T.

2016-01-01

A new engine cycle analysis tool, called Pycycle, was built using the OpenMDAO framework. Pycycle provides analytic derivatives allowing for an efficient use of gradient-based optimization methods on engine cycle models, without requiring the use of finite difference derivative approximation methods. To demonstrate this, a gradient-based design optimization was performed on a turbofan engine model. Results demonstrate very favorable performance compared to an optimization of an identical model using finite-difference approximated derivatives.

Ultrasound image edge detection based on a novel multiplicative gradient and Canny operator.

PubMed

Zheng, Yinfei; Zhou, Yali; Zhou, Hao; Gong, Xiaohong

2015-07-01

To achieve the fast and accurate segmentation of ultrasound image, a novel edge detection method for speckle noised ultrasound images was proposed, which was based on the traditional Canny and a novel multiplicative gradient operator. The proposed technique combines a new multiplicative gradient operator of non-Newtonian type with the traditional Canny operator to generate the initial edge map, which is subsequently optimized by the following edge tracing step. To verify the proposed method, we compared it with several other edge detection methods that had good robustness to noise, with experiments on the simulated and in vivo medical ultrasound image. Experimental results showed that the proposed algorithm has higher speed for real-time processing, and the edge detection accuracy could be 75% or more. Thus, the proposed method is very suitable for fast and accurate edge detection of medical ultrasound images. © The Author(s) 2014.

Optimization of Turbine Engine Cycle Analysis with Analytic Derivatives

NASA Technical Reports Server (NTRS)

Hearn, Tristan; Hendricks, Eric; Chin, Jeffrey; Gray, Justin; Moore, Kenneth T.

2016-01-01

A new engine cycle analysis tool, called Pycycle, was recently built using the OpenMDAO framework. This tool uses equilibrium chemistry based thermodynamics, and provides analytic derivatives. This allows for stable and efficient use of gradient-based optimization and sensitivity analysis methods on engine cycle models, without requiring the use of finite difference derivative approximation methods. To demonstrate this, a gradient-based design optimization was performed on a multi-point turbofan engine model. Results demonstrate very favorable performance compared to an optimization of an identical model using finite-difference approximated derivatives.

Stripe nonuniformity correction for infrared imaging system based on single image optimization

NASA Astrophysics Data System (ADS)

Hua, Weiping; Zhao, Jufeng; Cui, Guangmang; Gong, Xiaoli; Ge, Peng; Zhang, Jiang; Xu, Zhihai

2018-06-01

Infrared imaging is often disturbed by stripe nonuniformity noise. Scene-based correction method can effectively reduce the impact of stripe noise. In this paper, a stripe nonuniformity correction method based on differential constraint is proposed. Firstly, the gray distribution of stripe nonuniformity is analyzed and the penalty function is constructed by the difference of horizontal gradient and vertical gradient. With the weight function, the penalty function is optimized to obtain the corrected image. Comparing with other single-frame approaches, experiments show that the proposed method performs better in both subjective and objective analysis, and does less damage to edge and detail. Meanwhile, the proposed method runs faster. We have also discussed the differences between the proposed idea and multi-frame methods. Our method is finally well applied in hardware system.

Using gradient-based ray and candidate shadow maps for environmental illumination distribution estimation

NASA Astrophysics Data System (ADS)

Eem, Changkyoung; Kim, Iksu; Hong, Hyunki

2015-07-01

A method to estimate the environmental illumination distribution of a scene with gradient-based ray and candidate shadow maps is presented. In the shadow segmentation stage, we apply a Canny edge detector to the shadowed image by using a three-dimensional (3-D) augmented reality (AR) marker of a known size and shape. Then the hierarchical tree of the connected edge components representing the topological relation is constructed, and the connected components are merged, taking their hierarchical structures into consideration. A gradient-based ray that is perpendicular to the gradient of the edge pixel in the shadow image can be used to extract the shadow regions. In the light source detection stage, shadow regions with both a 3-D AR marker and the light sources are partitioned into candidate shadow maps. A simple logic operation between each candidate shadow map and the segmented shadow is used to efficiently compute the area ratio between them. The proposed method successively extracts the main light sources according to their relative contributions on the segmented shadows. The proposed method can reduce unwanted effects due to the sampling positions in the shadow region and the threshold values in the shadow edge detection.

Local CC2 response method based on the Laplace transform: analytic energy gradients for ground and excited states.

PubMed

Ledermüller, Katrin; Schütz, Martin

2014-04-28

A multistate local CC2 response method for the calculation of analytic energy gradients with respect to nuclear displacements is presented for ground and electronically excited states. The gradient enables the search for equilibrium geometries of extended molecular systems. Laplace transform is used to partition the eigenvalue problem in order to obtain an effective singles eigenvalue problem and adaptive, state-specific local approximations. This leads to an approximation in the energy Lagrangian, which however is shown (by comparison with the corresponding gradient method without Laplace transform) to be of no concern for geometry optimizations. The accuracy of the local approximation is tested and the efficiency of the new code is demonstrated by application calculations devoted to a photocatalytic decarboxylation process of present interest.

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.

Thermal structure of Sikhote Alin and adjacent areas based on spectral analysis of the anomalous magnetic field

NASA Astrophysics Data System (ADS)

Didenko, A. N.; Nosyrev, M. Yu.; Shevchenko, B. F.; Gilmanova, G. Z.

2017-11-01

The depth of the base of the magnetoactive layer and the geothermal gradient in the Sikhote Alin crust are estimated based on a method determining the Curie depth point of magnetoactive masses by using spectral analysis of the anomalous magnetic field. A detailed map of the geothermal gradient is constructed for the first time for the Sikhote Alin and adjacent areas of the Central Asian belt. Analysis of this map shows that the zones with a higher geothermal gradient geographically fit the areas with a higher level of seismicity.

Joint design of large-tip-angle parallel RF pulses and blipped gradient trajectories.

PubMed

Cao, Zhipeng; Donahue, Manus J; Ma, Jun; Grissom, William A

2016-03-01

To design multichannel large-tip-angle kT-points and spokes radiofrequency (RF) pulses and gradient waveforms for transmit field inhomogeneity compensation in high field magnetic resonance imaging. An algorithm to design RF subpulse weights and gradient blip areas is proposed to minimize a magnitude least-squares cost function that measures the difference between realized and desired state parameters in the spin domain, and penalizes integrated RF power. The minimization problem is solved iteratively with interleaved target phase updates, RF subpulse weights updates using the conjugate gradient method with optimal control-based derivatives, and gradient blip area updates using the conjugate gradient method. Two-channel parallel transmit simulations and experiments were conducted in phantoms and human subjects at 7 T to demonstrate the method and compare it to small-tip-angle-designed pulses and circularly polarized excitations. The proposed algorithm designed more homogeneous and accurate 180° inversion and refocusing pulses than other methods. It also designed large-tip-angle pulses on multiple frequency bands with independent and joint phase relaxation. Pulses designed by the method improved specificity and contrast-to-noise ratio in a finger-tapping spin echo blood oxygen level dependent functional magnetic resonance imaging study, compared with circularly polarized mode refocusing. A joint RF and gradient waveform design algorithm was proposed and validated to improve large-tip-angle inversion and refocusing at ultrahigh field. © 2015 Wiley Periodicals, Inc.

Brain vascular image enhancement based on gradient adjust with split Bregman

NASA Astrophysics Data System (ADS)

Liang, Xiao; Dong, Di; Hui, Hui; Zhang, Liwen; Fang, Mengjie; Tian, Jie

2016-04-01

Light Sheet Microscopy is a high-resolution fluorescence microscopic technique which enables to observe the mouse brain vascular network clearly with immunostaining. However, micro-vessels are stained with few fluorescence antibodies and their signals are much weaker than large vessels, which make micro-vessels unclear in LSM images. In this work, we developed a vascular image enhancement method to enhance micro-vessel details which should be useful for vessel statistics analysis. Since gradient describes the edge information of the vessel, the main idea of our method is to increase the gradient values of the enhanced image to improve the micro-vessels contrast. Our method contained two steps: 1) calculate the gradient image of LSM image, and then amplify high gradient values of the original image to enhance the vessel edge and suppress low gradient values to remove noises. Then we formulated a new L1-norm regularization optimization problem to find an image with the expected gradient while keeping the main structure information of the original image. 2) The split Bregman iteration method was used to deal with the L1-norm regularization problem and generate the final enhanced image. The main advantage of the split Bregman method is that it has both fast convergence and low memory cost. In order to verify the effectiveness of our method, we applied our method to a series of mouse brain vascular images acquired from a commercial LSM system in our lab. The experimental results showed that our method could greatly enhance micro-vessel edges which were unclear in the original images.

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

NASA Technical Reports Server (NTRS)

Pandya, Mohagna J.; Baysal, Oktay

1997-01-01

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

Coupling temporal and spatial gradient information in high-density unstructured Lagrangian measurements

NASA Astrophysics Data System (ADS)

Wong, Jaime G.; Rosi, Giuseppe A.; Rouhi, Amirreza; Rival, David E.

2017-10-01

Particle tracking velocimetry (PTV) produces high-quality temporal information that is often neglected when computing spatial gradients. A method is presented here to utilize this temporal information in order to improve the estimation of spatial gradients for spatially unstructured Lagrangian data sets. Starting with an initial guess, this method penalizes any gradient estimate where the substantial derivative of vorticity along a pathline is not equal to the local vortex stretching/tilting. Furthermore, given an initial guess, this method can proceed on an individual pathline without any further reference to neighbouring pathlines. The equivalence of the substantial derivative and vortex stretching/tilting is based on the vorticity transport equation, where viscous diffusion is neglected. By minimizing the residual of the vorticity-transport equation, the proposed method is first tested to reduce error and noise on a synthetic Taylor-Green vortex field dissipating in time. Furthermore, when the proposed method is applied to high-density experimental data collected with `Shake-the-Box' PTV, noise within the spatial gradients is significantly reduced. In the particular test case investigated here of an accelerating circular plate captured during a single run, the method acts to delineate the shear layer and vortex core, as well as resolve the Kelvin-Helmholtz instabilities, which were previously unidentifiable without the use of ensemble averaging. The proposed method shows promise for improving PTV measurements that require robust spatial gradients while retaining the unstructured Lagrangian perspective.

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

PubMed

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

2011-12-01

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

SU-F-J-95: Impact of Shape Complexity On the Accuracy of Gradient-Based PET Volume Delineation

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

Dance, M; Wu, G; Gao, Y

2016-06-15

Purpose: Explore correlation of tumor complexity shape with PET target volume accuracy when delineated with gradient-based segmentation tool. Methods: A total of 24 clinically realistic digital PET Monte Carlo (MC) phantoms of NSCLC were used in the study. The phantom simulated 29 thoracic lesions (lung primary and mediastinal lymph nodes) of varying size, shape, location, and {sup 18}F-FDG activity. A program was developed to calculate a curvature vector along the outline and the standard deviation of this vector was used as a metric to quantify a shape’s “complexity score”. This complexity score was calculated for standard geometric shapes and MC-generatedmore » target volumes in PET phantom images. All lesions were contoured using a commercially available gradient-based segmentation tool and the differences in volume from the MC-generated volumes were calculated as the measure of the accuracy of segmentation. Results: The average absolute percent difference in volumes between the MC-volumes and gradient-based volumes was 11% (0.4%–48.4%). The complexity score showed strong correlation with standard geometric shapes. However, no relationship was found between the complexity score and the accuracy of segmentation by gradient-based tool on MC simulated tumors (R{sup 2} = 0.156). When the lesions were grouped into primary lung lesions and mediastinal/mediastinal adjacent lesions, the average absolute percent difference in volumes were 6% and 29%, respectively. The former group is more isolated and the latter is more surround by tissues with relatively high SUV background. Conclusion: The complexity shape of NSCLC lesions has little effect on the accuracy of the gradient-based segmentation method and thus is not a good predictor of uncertainty in target volume delineation. Location of lesion within a relatively high SUV background may play a more significant role in the accuracy of gradient-based segmentation.« less

Positive Contrast Visualization of Nitinol Devices using Susceptibility Gradient Mapping

PubMed Central

Vonken, Evert-jan P.A.; Schär, Michael; Stuber, Matthias

2008-01-01

MRI visualization of devices is traditionally based on the signal loss due to T2* effects originating from the local susceptibility differences. To visualize nitinol devices with positive contrast a recently introduced post processing method is adapted to map the induced susceptibility gradients. This method operates on regular gradient echo MR images and maps the shift in k-space in a (small) neighborhood of every voxel by Fourier analysis followed by a center of mass calculation. The quantitative map of the local shifts generates the positive contrast image of the devices, while areas without susceptibility gradients render a background with noise only. The positive signal response of this method depends only on the choice of the voxel neighborhood size. The properties of the method are explained and the visualization of a nitinol wire and two stents are shown for illustration. PMID:18727096

Projection methods for line radiative transfer in spherical media.

NASA Astrophysics Data System (ADS)

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

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

Visualizing dispersive features in 2D image via minimum gradient method

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

He, Yu; Wang, Yan; Shen, Zhi -Xun

Here, we developed a minimum gradient based method to track ridge features in a 2D image plot, which is a typical data representation in many momentum resolved spectroscopy experiments. Through both analytic formulation and numerical simulation, we compare this new method with existing DC (distribution curve) based and higher order derivative based analyses. We find that the new method has good noise resilience and enhanced contrast especially for weak intensity features and meanwhile preserves the quantitative local maxima information from the raw image. An algorithm is proposed to extract 1D ridge dispersion from the 2D image plot, whose quantitative applicationmore » to angle-resolved photoemission spectroscopy measurements on high temperature superconductors is demonstrated.« less

Visualizing dispersive features in 2D image via minimum gradient method

DOE PAGES

He, Yu; Wang, Yan; Shen, Zhi -Xun

2017-07-24

Here, we developed a minimum gradient based method to track ridge features in a 2D image plot, which is a typical data representation in many momentum resolved spectroscopy experiments. Through both analytic formulation and numerical simulation, we compare this new method with existing DC (distribution curve) based and higher order derivative based analyses. We find that the new method has good noise resilience and enhanced contrast especially for weak intensity features and meanwhile preserves the quantitative local maxima information from the raw image. An algorithm is proposed to extract 1D ridge dispersion from the 2D image plot, whose quantitative applicationmore » to angle-resolved photoemission spectroscopy measurements on high temperature superconductors is demonstrated.« less

Deterministic convergence of chaos injection-based gradient method for training feedforward neural networks.

PubMed

Zhang, Huisheng; Zhang, Ying; Xu, Dongpo; Liu, Xiaodong

2015-06-01

It has been shown that, by adding a chaotic sequence to the weight update during the training of neural networks, the chaos injection-based gradient method (CIBGM) is superior to the standard backpropagation algorithm. This paper presents the theoretical convergence analysis of CIBGM for training feedforward neural networks. We consider both the case of batch learning as well as the case of online learning. Under mild conditions, we prove the weak convergence, i.e., the training error tends to a constant and the gradient of the error function tends to zero. Moreover, the strong convergence of CIBGM is also obtained with the help of an extra condition. The theoretical results are substantiated by a simulation example.

An automatic and accurate method of full heart segmentation from CT image based on linear gradient model

NASA Astrophysics Data System (ADS)

Yang, Zili

2017-07-01

Heart segmentation is an important auxiliary method in the diagnosis of many heart diseases, such as coronary heart disease and atrial fibrillation, and in the planning of tumor radiotherapy. Most of the existing methods for full heart segmentation treat the heart as a whole part and cannot accurately extract the bottom of the heart. In this paper, we propose a new method based on linear gradient model to segment the whole heart from the CT images automatically and accurately. Twelve cases were tested in order to test this method and accurate segmentation results were achieved and identified by clinical experts. The results can provide reliable clinical support.

2D-3D registration using gradient-based MI for image guided surgery systems

NASA Astrophysics Data System (ADS)

Yim, Yeny; Chen, Xuanyi; Wakid, Mike; Bielamowicz, Steve; Hahn, James

2011-03-01

Registration of preoperative CT data to intra-operative video images is necessary not only to compare the outcome of the vocal fold after surgery with the preplanned shape but also to provide the image guidance for fusion of all imaging modalities. We propose a 2D-3D registration method using gradient-based mutual information. The 3D CT scan is aligned to 2D endoscopic images by finding the corresponding viewpoint between the real camera for endoscopic images and the virtual camera for CT scans. Even though mutual information has been successfully used to register different imaging modalities, it is difficult to robustly register the CT rendered image to the endoscopic image due to varying light patterns and shape of the vocal fold. The proposed method calculates the mutual information in the gradient images as well as original images, assigning more weight to the high gradient regions. The proposed method can emphasize the effect of vocal fold and allow a robust matching regardless of the surface illumination. To find the viewpoint with maximum mutual information, a downhill simplex method is applied in a conditional multi-resolution scheme which leads to a less-sensitive result to local maxima. To validate the registration accuracy, we evaluated the sensitivity to initial viewpoint of preoperative CT. Experimental results showed that gradient-based mutual information provided robust matching not only for two identical images with different viewpoints but also for different images acquired before and after surgery. The results also showed that conditional multi-resolution scheme led to a more accurate registration than single-resolution.

A Method for Computing the Core Flow in Three-Dimensional Leading-Edge Vortices. Ph.D. Thesis - North Carolina State Univ.

NASA Technical Reports Server (NTRS)

Luckring, J. M.

1985-01-01

A theory is presented for calculating the flow in the core of a separation-induced leading-edge vortex. The method is based on matching inner and outer representations of the vortex. The inner model of the vortex is based on the quasicylindrical Navier-Stokes equations; the flow is assumed to be steady, axially symmetric, and incompressible and in addition, gradients in the radial direction are assumed to be much larger then gradients in the axial direction. The outer model is based on the three-dimensional free-vortex-sheet theory, a higher-order panel method which solves the Prandtl-Glauert equation including nonlinear boundary conditions pertinent to the concentrated vorticity representation of the leading edge vortex. The resultant flow is evaluated a posteriori for evidence of incipient vortex breakdown and the critical helix angle concept, in conjunction with an adverse longitudinal pressure gradient, is found to correlate well with the occurrence of vortex breakdown at the trailing edge of delta, arrow, and diamond wings.

Determination of elastic moduli from measured acoustic velocities.

PubMed

Brown, J Michael

2018-06-01

Methods are evaluated in solution of the inverse problem associated with determination of elastic moduli for crystals of arbitrary symmetry from elastic wave velocities measured in many crystallographic directions. A package of MATLAB functions provides a robust and flexible environment for analysis of ultrasonic, Brillouin, or Impulsive Stimulated Light Scattering datasets. Three inverse algorithms are considered: the gradient-based methods of Levenberg-Marquardt and Backus-Gilbert, and a non-gradient-based (Nelder-Mead) simplex approach. Several data types are considered: body wave velocities alone, surface wave velocities plus a side constraint on X-ray-diffraction-based axes compressibilities, or joint body and surface wave velocities. The numerical algorithms are validated through comparisons with prior published results and through analysis of synthetic datasets. Although all approaches succeed in finding low-misfit solutions, the Levenberg-Marquardt method consistently demonstrates effectiveness and computational efficiency. However, linearized gradient-based methods, when applied to a strongly non-linear problem, may not adequately converge to the global minimum. The simplex method, while slower, is less susceptible to being trapped in local misfit minima. A "multi-start" strategy (initiate searches from more than one initial guess) provides better assurance that global minima have been located. Numerical estimates of parameter uncertainties based on Monte Carlo simulations are compared to formal uncertainties based on covariance calculations. Copyright © 2018 Elsevier B.V. All rights reserved.

Uncertainty based pressure reconstruction from velocity measurement with generalized least squares

NASA Astrophysics Data System (ADS)

Zhang, Jiacheng; Scalo, Carlo; Vlachos, Pavlos

2017-11-01

A method using generalized least squares reconstruction of instantaneous pressure field from velocity measurement and velocity uncertainty is introduced and applied to both planar and volumetric flow data. Pressure gradients are computed on a staggered grid from flow acceleration. The variance-covariance matrix of the pressure gradients is evaluated from the velocity uncertainty by approximating the pressure gradient error to a linear combination of velocity errors. An overdetermined system of linear equations which relates the pressure and the computed pressure gradients is formulated and then solved using generalized least squares with the variance-covariance matrix of the pressure gradients. By comparing the reconstructed pressure field against other methods such as solving the pressure Poisson equation, the omni-directional integration, and the ordinary least squares reconstruction, generalized least squares method is found to be more robust to the noise in velocity measurement. The improvement on pressure result becomes more remarkable when the velocity measurement becomes less accurate and more heteroscedastic. The uncertainty of the reconstructed pressure field is also quantified and compared across the different methods.

Analytical energy gradient based on spin-free infinite-order Douglas-Kroll-Hess method with local unitary transformation

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

Nakajima, Yuya; Seino, Junji; Nakai, Hiromi, E-mail: nakai@waseda.jp

In this study, the analytical energy gradient for the spin-free infinite-order Douglas-Kroll-Hess (IODKH) method at the levels of the Hartree-Fock (HF), density functional theory (DFT), and second-order Møller-Plesset perturbation theory (MP2) is developed. Furthermore, adopting the local unitary transformation (LUT) scheme for the IODKH method improves the efficiency in computation of the analytical energy gradient. Numerical assessments of the present gradient method are performed at the HF, DFT, and MP2 levels for the IODKH with and without the LUT scheme. The accuracies are examined for diatomic molecules such as hydrogen halides, halogen dimers, coinage metal (Cu, Ag, and Au) halides,more » and coinage metal dimers, and 20 metal complexes, including the fourth–sixth row transition metals. In addition, the efficiencies are investigated for one-, two-, and three-dimensional silver clusters. The numerical results confirm the accuracy and efficiency of the present method.« less

Møller-Plesset perturbation theory gradient in the generalized hybrid orbital quantum mechanical and molecular mechanical method

NASA Astrophysics Data System (ADS)

Jung, Jaewoon; Sugita, Yuji; Ten-no, S.

2010-02-01

An analytic gradient expression is formulated and implemented for the second-order Møller-Plesset perturbation theory (MP2) based on the generalized hybrid orbital QM/MM method. The method enables us to obtain an accurate geometry at a reasonable computational cost. The performance of the method is assessed for various isomers of alanine dipepetide. We also compare the optimized structures of fumaramide-derived [2]rotaxane and cAMP-dependent protein kinase with experiment.

Minimum maximum temperature gradient coil design.

PubMed

While, Peter T; Poole, Michael S; Forbes, Larry K; Crozier, Stuart

2013-08-01

Ohmic heating is a serious problem in gradient coil operation. A method is presented for redesigning cylindrical gradient coils to operate at minimum peak temperature, while maintaining field homogeneity and coil performance. To generate these minimaxT coil windings, an existing analytic method for simulating the spatial temperature distribution of single layer gradient coils is combined with a minimax optimization routine based on sequential quadratic programming. Simulations are provided for symmetric and asymmetric gradient coils that show considerable improvements in reducing maximum temperature over existing methods. The winding patterns of the minimaxT coils were found to be heavily dependent on the assumed thermal material properties and generally display an interesting "fish-eye" spreading of windings in the dense regions of the coil. Small prototype coils were constructed and tested for experimental validation and these demonstrate that with a reasonable estimate of material properties, thermal performance can be improved considerably with negligible change to the field error or standard figures of merit. © 2012 Wiley Periodicals, Inc.

Stochastic Spectral Descent for Discrete Graphical Models

DOE PAGES

Carlson, David; Hsieh, Ya-Ping; Collins, Edo; ...

2015-12-14

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

Gradient-based multiconfiguration Shepard interpolation for generating potential energy surfaces for polyatomic reactions.

PubMed

Tishchenko, Oksana; Truhlar, Donald G

2010-02-28

This paper describes and illustrates a way to construct multidimensional representations of reactive potential energy surfaces (PESs) by a multiconfiguration Shepard interpolation (MCSI) method based only on gradient information, that is, without using any Hessian information from electronic structure calculations. MCSI, which is called multiconfiguration molecular mechanics (MCMM) in previous articles, is a semiautomated method designed for constructing full-dimensional PESs for subsequent dynamics calculations (classical trajectories, full quantum dynamics, or variational transition state theory with multidimensional tunneling). The MCSI method is based on Shepard interpolation of Taylor series expansions of the coupling term of a 2 x 2 electronically diabatic Hamiltonian matrix with the diagonal elements representing nonreactive analytical PESs for reactants and products. In contrast to the previously developed method, these expansions are truncated in the present version at the first order, and, therefore, no input of electronic structure Hessians is required. The accuracy of the interpolated energies is evaluated for two test reactions, namely, the reaction OH+H(2)-->H(2)O+H and the hydrogen atom abstraction from a model of alpha-tocopherol by methyl radical. The latter reaction involves 38 atoms and a 108-dimensional PES. The mean unsigned errors averaged over a wide range of representative nuclear configurations (corresponding to an energy range of 19.5 kcal/mol in the former case and 32 kcal/mol in the latter) are found to be within 1 kcal/mol for both reactions, based on 13 gradients in one case and 11 in the other. The gradient-based MCMM method can be applied for efficient representations of multidimensional PESs in cases where analytical electronic structure Hessians are too expensive or unavailable, and it provides new opportunities to employ high-level electronic structure calculations for dynamics at an affordable cost.

Oscillator strengths, first-order properties, and nuclear gradients for local ADC(2).

PubMed

Schütz, Martin

2015-06-07

We describe theory and implementation of oscillator strengths, orbital-relaxed first-order properties, and nuclear gradients for the local algebraic diagrammatic construction scheme through second order. The formalism is derived via time-dependent linear response theory based on a second-order unitary coupled cluster model. The implementation presented here is a modification of our previously developed algorithms for Laplace transform based local time-dependent coupled cluster linear response (CC2LR); the local approximations thus are state specific and adaptive. The symmetry of the Jacobian leads to considerable simplifications relative to the local CC2LR method; as a result, a gradient evaluation is about four times less expensive. Test calculations show that in geometry optimizations, usually very similar geometries are obtained as with the local CC2LR method (provided that a second-order method is applicable). As an exemplary application, we performed geometry optimizations on the low-lying singlet states of chlorophyllide a.

Spectral-Element Simulations of Wave Propagation in Porous Media: Finite-Frequency Sensitivity Kernels Based Upon Adjoint Methods

NASA Astrophysics Data System (ADS)

Morency, C.; Tromp, J.

2008-12-01

The mathematical formulation of wave propagation in porous media developed by Biot is based upon the principle of virtual work, ignoring processes at the microscopic level, and does not explicitly incorporate gradients in porosity. Based on recent studies focusing on averaging techniques, we derive the macroscopic porous medium equations from the microscale, with a particular emphasis on the effects of gradients in porosity. In doing so, we are able to naturally determine two key terms in the momentum equations and constitutive relationships, directly translating the coupling between the solid and fluid phases, namely a drag force and an interfacial strain tensor. In both terms, gradients in porosity arise. One remarkable result is that when we rewrite this set of equations in terms of the well known Biot variables us, w), terms involving gradients in porosity are naturally accommodated by gradients involving w, the fluid motion relative to the solid, and Biot's formulation is recovered, i.e., it remains valid in the presence of porosity gradients We have developed a numerical implementation of the Biot equations for two-dimensional problems based upon the spectral-element method (SEM) in the time domain. The SEM is a high-order variational method, which has the advantage of accommodating complex geometries like a finite-element method, while keeping the exponential convergence rate of (pseudo)spectral methods. As in the elastic and acoustic cases, poroelastic wave propagation based upon the SEM involves a diagonal mass matrix, which leads to explicit time integration schemes that are well-suited to simulations on parallel computers. Effects associated with physical dispersion & attenuation and frequency-dependent viscous resistance are addressed by using a memory variable approach. Various benchmarks involving poroelastic wave propagation in the high- and low-frequency regimes, and acoustic-poroelastic and poroelastic-poroelastic discontinuities have been successfully performed. We present finite-frequency sensitivity kernels for wave propagation in porous media based upon adjoint methods. We first show that the adjoint equations in porous media are similar to the regular Biot equations upon defining an appropriate adjoint source. Then we present finite-frequency kernels for seismic phases in porous media (e.g., fast P, slow P, and S). These kernels illustrate the sensitivity of seismic observables to structural parameters and form the basis of tomographic inversions. Finally, we show an application of this imaging technique related to the detection of buried landmines and unexploded ordnance (UXO) in porous environments.

Effect of exosome isolation methods on physicochemical properties of exosomes and clearance of exosomes from the blood circulation.

PubMed

Yamashita, Takuma; Takahashi, Yuki; Nishikawa, Makiya; Takakura, Yoshinobu

2016-01-01

Exosomes, which are expected to be delivery systems for biomolecules such as nucleic acids, are collected by several methods. However, the effect of exosome isolation methods on the characteristics of exosomes as drug carriers, such as recovery efficiency after sterile filtration and pharmacokinetics, has not been investigated despite the importance of these characteristics for the development of exosome-based delivery systems. In the present study, exosomes collected from murine melanoma B16-BL6 cells by several methods were compared with respect to dispersibility, recovery rate after filtering, and clearance from the blood circulation in mice. The exosomes were collected by three ultracentrifugation-based methods: simple ultracentrifugation/pelleting (pelleting method), ultracentrifugation with an iodixanol cushion (cushion method), and ultracentrifugation on an iodixanol density gradient (gradient method). The isolation methods had little effect on the particle number of exosomes. In contrast, transmission electron microscopy observation and size distribution measurement using tunable resistive pulse sensing indicated that the exosomes of the gradient method were more dispersed than the others. The exosomes were labeled with Gaussia luciferase and intravenously injected into mice. Clearance of injected exosomes from the blood circulation did not significantly change with isolation methods. When the exosomes were filtered using a 0.2-μm filter, the recovery rate was 82% for the exosomes of the gradient method, whereas it was less than 50% for the others. These results indicate that the exosome isolation method markedly affects the dispersibility and filtration efficiency of the exosomes. Copyright © 2015 Elsevier B.V. All rights reserved.

No-reference image quality assessment based on natural scene statistics and gradient magnitude similarity

NASA Astrophysics Data System (ADS)

Jia, Huizhen; Sun, Quansen; Ji, Zexuan; Wang, Tonghan; Chen, Qiang

2014-11-01

The goal of no-reference/blind image quality assessment (NR-IQA) is to devise a perceptual model that can accurately predict the quality of a distorted image as human opinions, in which feature extraction is an important issue. However, the features used in the state-of-the-art "general purpose" NR-IQA algorithms are usually natural scene statistics (NSS) based or are perceptually relevant; therefore, the performance of these models is limited. To further improve the performance of NR-IQA, we propose a general purpose NR-IQA algorithm which combines NSS-based features with perceptually relevant features. The new method extracts features in both the spatial and gradient domains. In the spatial domain, we extract the point-wise statistics for single pixel values which are characterized by a generalized Gaussian distribution model to form the underlying features. In the gradient domain, statistical features based on neighboring gradient magnitude similarity are extracted. Then a mapping is learned to predict quality scores using a support vector regression. The experimental results on the benchmark image databases demonstrate that the proposed algorithm correlates highly with human judgments of quality and leads to significant performance improvements over state-of-the-art methods.

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

PubMed

Fessler, J A; Booth, S D

1999-01-01

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

A Sea-Sky Line Detection Method for Unmanned Surface Vehicles Based on Gradient Saliency.

PubMed

Wang, Bo; Su, Yumin; Wan, Lei

2016-04-15

Special features in real marine environments such as cloud clutter, sea glint and weather conditions always result in various kinds of interference in optical images, which make it very difficult for unmanned surface vehicles (USVs) to detect the sea-sky line (SSL) accurately. To solve this problem a saliency-based SSL detection method is proposed. Through the computation of gradient saliency the line features of SSL are enhanced effectively, while other interference factors are relatively suppressed, and line support regions are obtained by a region growing method on gradient orientation. The SSL identification is achieved according to region contrast, line segment length and orientation features, and optimal state estimation of SSL detection is implemented by introducing a cubature Kalman filter (CKF). In the end, the proposed method is tested on a benchmark dataset from the "XL" USV in a real marine environment, and the experimental results demonstrate that the proposed method is significantly superior to other state-of-the-art methods in terms of accuracy rate and real-time performance, and its accuracy and stability are effectively improved by the CKF.

3D ductile crack propagation within a polycrystalline microstructure using XFEM

NASA Astrophysics Data System (ADS)

Beese, Steffen; Loehnert, Stefan; Wriggers, Peter

2018-02-01

In this contribution we present a gradient enhanced damage based method to simulate discrete crack propagation in 3D polycrystalline microstructures. Discrete cracks are represented using the eXtended finite element method. The crack propagation criterion and the crack propagation direction for each point along the crack front line is based on the gradient enhanced damage variable. This approach requires the solution of a coupled problem for the balance of momentum and the additional global equation for the gradient enhanced damage field. To capture the discontinuity of the displacements as well as the gradient enhanced damage along the discrete crack, both fields are enriched using the XFEM in combination with level sets. Knowing the crack front velocity, level set methods are used to compute the updated crack geometry after each crack propagation step. The applied material model is a crystal plasticity model often used for polycrystalline microstructures of metals in combination with the gradient enhanced damage model. Due to the inelastic material behaviour after each discrete crack propagation step a projection of the internal variables from the old to the new crack configuration is required. Since for arbitrary crack geometries ill-conditioning of the equation system may occur due to (near) linear dependencies between standard and enriched degrees of freedom, an XFEM stabilisation technique based on a singular value decomposition of the element stiffness matrix is proposed. The performance of the presented methodology to capture crack propagation in polycrystalline microstructures is demonstrated with a number of numerical examples.

Reconstruction of fluorescence molecular tomography with a cosinoidal level set method.

PubMed

Zhang, Xuanxuan; Cao, Xu; Zhu, Shouping

2017-06-27

Implicit shape-based reconstruction method in fluorescence molecular tomography (FMT) is capable of achieving higher image clarity than image-based reconstruction method. However, the implicit shape method suffers from a low convergence speed and performs unstably due to the utilization of gradient-based optimization methods. Moreover, the implicit shape method requires priori information about the number of targets. A shape-based reconstruction scheme of FMT with a cosinoidal level set method is proposed in this paper. The Heaviside function in the classical implicit shape method is replaced with a cosine function, and then the reconstruction can be accomplished with the Levenberg-Marquardt method rather than gradient-based methods. As a result, the priori information about the number of targets is not required anymore and the choice of step length is avoided. Numerical simulations and phantom experiments were carried out to validate the proposed method. Results of the proposed method show higher contrast to noise ratios and Pearson correlations than the implicit shape method and image-based reconstruction method. Moreover, the number of iterations required in the proposed method is much less than the implicit shape method. The proposed method performs more stably, provides a faster convergence speed than the implicit shape method, and achieves higher image clarity than the image-based reconstruction method.

Preliminary Structural Design Using Topology Optimization with a Comparison of Results from Gradient and Genetic Algorithm Methods

NASA Technical Reports Server (NTRS)

Burt, Adam O.; Tinker, Michael L.

2014-01-01

In this paper, genetic algorithm based and gradient-based topology optimization is presented in application to a real hardware design problem. Preliminary design of a planetary lander mockup structure is accomplished using these methods that prove to provide major weight savings by addressing the structural efficiency during the design cycle. This paper presents two alternative formulations of the topology optimization problem. The first is the widely-used gradient-based implementation using commercially available algorithms. The second is formulated using genetic algorithms and internally developed capabilities. These two approaches are applied to a practical design problem for hardware that has been built, tested and proven to be functional. Both formulations converged on similar solutions and therefore were proven to be equally valid implementations of the process. This paper discusses both of these formulations at a high level.

Optimization Based Efficiencies in First Order Reliability Analysis

NASA Technical Reports Server (NTRS)

Peck, Jeffrey A.; Mahadevan, Sankaran

2003-01-01

This paper develops a method for updating the gradient vector of the limit state function in reliability analysis using Broyden's rank one updating technique. In problems that use commercial code as a black box, the gradient calculations are usually done using a finite difference approach, which becomes very expensive for large system models. The proposed method replaces the finite difference gradient calculations in a standard first order reliability method (FORM) with Broyden's Quasi-Newton technique. The resulting algorithm of Broyden updates within a FORM framework (BFORM) is used to run several example problems, and the results compared to standard FORM results. It is found that BFORM typically requires fewer functional evaluations that FORM to converge to the same answer.

Exploration Opportunity Search of Near-earth Objects Based on Analytical Gradients

NASA Astrophysics Data System (ADS)

Ren, Yuan; Cui, Ping-Yuan; Luan, En-Jie

2008-07-01

The problem of search of opportunity for the exploration of near-earth minor objects is investigated. For rendezvous missions, the analytical gradients of the performance index with respect to the free parameters are derived using the variational calculus and the theory of state-transition matrix. After generating randomly some initial guesses in the search space, the performance index is optimized, guided by the analytical gradients, leading to the local minimum points representing the potential launch opportunities. This method not only keeps the global-search property of the traditional method, but also avoids the blindness in the latter, thereby increasing greatly the computing speed. Furthermore, with this method, the searching precision could be controlled effectively.

Search of exploration opportunity for near earth objects based on analytical gradients

NASA Astrophysics Data System (ADS)

Ren, Y.; Cui, P. Y.; Luan, E. J.

2008-01-01

The problem of searching for exploration opportunity of near Earth objects is investigated. For rendezvous missions, the analytical gradients of performance index with respect to free parameters are derived by combining the calculus of variation with the theory of state-transition matrix. Then, some initial guesses are generated random in the search space, and the performance index is optimized with the guidance of analytical gradients from these initial guesses. This method not only keeps the property of global search in traditional method, but also avoids the blindness in the traditional exploration opportunity search; hence, the computing speed could be increased greatly. Furthermore, by using this method, the search precision could be controlled effectively.

Evaluation of redundancy analysis to identify signatures of local adaptation.

PubMed

Capblancq, Thibaut; Luu, Keurcien; Blum, Michael G B; Bazin, Eric

2018-05-26

Ordination is a common tool in ecology that aims at representing complex biological information in a reduced space. In landscape genetics, ordination methods such as principal component analysis (PCA) have been used to detect adaptive variation based on genomic data. Taking advantage of environmental data in addition to genotype data, redundancy analysis (RDA) is another ordination approach that is useful to detect adaptive variation. This paper aims at proposing a test statistic based on RDA to search for loci under selection. We compare redundancy analysis to pcadapt, which is a nonconstrained ordination method, and to a latent factor mixed model (LFMM), which is a univariate genotype-environment association method. Individual-based simulations identify evolutionary scenarios where RDA genome scans have a greater statistical power than genome scans based on PCA. By constraining the analysis with environmental variables, RDA performs better than PCA in identifying adaptive variation when selection gradients are weakly correlated with population structure. Additionally, we show that if RDA and LFMM have a similar power to identify genetic markers associated with environmental variables, the RDA-based procedure has the advantage to identify the main selective gradients as a combination of environmental variables. To give a concrete illustration of RDA in population genomics, we apply this method to the detection of outliers and selective gradients on an SNP data set of Populus trichocarpa (Geraldes et al., 2013). The RDA-based approach identifies the main selective gradient contrasting southern and coastal populations to northern and continental populations in the northwestern American coast. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Error measure comparison of currently employed dose-modulation schemes for e-beam proximity effect control

NASA Astrophysics Data System (ADS)

Peckerar, Martin C.; Marrian, Christie R.

1995-05-01

Standard matrix inversion methods of e-beam proximity correction are compared with a variety of pseudoinverse approaches based on gradient descent. It is shown that the gradient descent methods can be modified using 'regularizers' (terms added to the cost function minimized during gradient descent). This modification solves the 'negative dose' problem in a mathematically sound way. Different techniques are contrasted using a weighted error measure approach. It is shown that the regularization approach leads to the highest quality images. In some cases, ignoring negative doses yields results which are worse than employing an uncorrected dose file.

Measurement and Analysis of the Temperature Gradient of Blackbody Cavities, for Use in Radiation Thermometry

NASA Astrophysics Data System (ADS)

De Lucas, Javier; Segovia, José Juan

2018-05-01

Blackbody cavities are the standard radiation sources widely used in the fields of radiometry and radiation thermometry. Its effective emissivity and uncertainty depend to a large extent on the temperature gradient. An experimental procedure based on the radiometric method for measuring the gradient is followed. Results are applied to particular blackbody configurations where gradients can be thermometrically estimated by contact thermometers and where the relationship between both basic methods can be established. The proposed procedure may be applied to commercial blackbodies if they are modified allowing secondary contact temperature measurement. In addition, the established systematic may be incorporated as part of the actions for quality assurance in routine calibrations of radiation thermometers, by using the secondary contact temperature measurement for detecting departures from the real radiometrically obtained gradient and the effect on the uncertainty. On the other hand, a theoretical model is proposed to evaluate the effect of temperature variations on effective emissivity and associated uncertainty. This model is based on a gradient sample chosen following plausible criteria. The model is consistent with the Monte Carlo method for calculating the uncertainty of effective emissivity and complements others published in the literature where uncertainty is calculated taking into account only geometrical variables and intrinsic emissivity. The mathematical model and experimental procedure are applied and validated using a commercial type three-zone furnace, with a blackbody cavity modified to enable a secondary contact temperature measurement, in the range between 400 °C and 1000 °C.

GBAS Ionospheric Anomaly Monitoring Based on a Two-Step Approach

PubMed Central

Zhao, Lin; Yang, Fuxin; Li, Liang; Ding, Jicheng; Zhao, Yuxin

2016-01-01

As one significant component of space environmental weather, the ionosphere has to be monitored using Global Positioning System (GPS) receivers for the Ground-Based Augmentation System (GBAS). This is because an ionospheric anomaly can pose a potential threat for GBAS to support safety-critical services. The traditional code-carrier divergence (CCD) methods, which have been widely used to detect the variants of the ionospheric gradient for GBAS, adopt a linear time-invariant low-pass filter to suppress the effect of high frequency noise on the detection of the ionospheric anomaly. However, there is a counterbalance between response time and estimation accuracy due to the fixed time constants. In order to release the limitation, a two-step approach (TSA) is proposed by integrating the cascaded linear time-invariant low-pass filters with the adaptive Kalman filter to detect the ionospheric gradient anomaly. The performance of the proposed method is tested by using simulated and real-world data, respectively. The simulation results show that the TSA can detect ionospheric gradient anomalies quickly, even when the noise is severer. Compared to the traditional CCD methods, the experiments from real-world GPS data indicate that the average estimation accuracy of the ionospheric gradient improves by more than 31.3%, and the average response time to the ionospheric gradient at a rate of 0.018 m/s improves by more than 59.3%, which demonstrates the ability of TSA to detect a small ionospheric gradient more rapidly. PMID:27240367

A Smoothed Eclipse Model for Solar Electric Propulsion Trajectory Optimization

NASA Technical Reports Server (NTRS)

Aziz, Jonathan D.; Scheeres, Daniel J.; Parker, Jeffrey S.; Englander, Jacob A.

2017-01-01

Solar electric propulsion (SEP) is the dominant design option for employing low-thrust propulsion on a space mission. Spacecraft solar arrays power the SEP system but are subject to blackout periods during solar eclipse conditions. Discontinuity in power available to the spacecraft must be accounted for in trajectory optimization, but gradient-based methods require a differentiable power model. This work presents a power model that smooths the eclipse transition from total eclipse to total sunlight with a logistic function. Example trajectories are computed with differential dynamic programming, a second-order gradient-based method.

Infrared and visible image fusion based on total variation and augmented Lagrangian.

PubMed

Guo, Hanqi; Ma, Yong; Mei, Xiaoguang; Ma, Jiayi

2017-11-01

This paper proposes a new algorithm for infrared and visible image fusion based on gradient transfer that achieves fusion by preserving the intensity of the infrared image and then transferring gradients in the corresponding visible one to the result. The gradient transfer suffers from the problems of low dynamic range and detail loss because it ignores the intensity from the visible image. The new algorithm solves these problems by providing additive intensity from the visible image to balance the intensity between the infrared image and the visible one. It formulates the fusion task as an l 1 -l 1 -TV minimization problem and then employs variable splitting and augmented Lagrangian to convert the unconstrained problem to a constrained one that can be solved in the framework of alternating the multiplier direction method. Experiments demonstrate that the new algorithm achieves better fusion results with a high computation efficiency in both qualitative and quantitative tests than gradient transfer and most state-of-the-art methods.

Iris Location Algorithm Based on the CANNY Operator and Gradient Hough Transform

NASA Astrophysics Data System (ADS)

Zhong, L. H.; Meng, K.; Wang, Y.; Dai, Z. Q.; Li, S.

2017-12-01

In the iris recognition system, the accuracy of the localization of the inner and outer edges of the iris directly affects the performance of the recognition system, so iris localization has important research meaning. Our iris data contain eyelid, eyelashes, light spot and other noise, even the gray transformation of the images is not obvious, so the general methods of iris location are unable to realize the iris location. The method of the iris location based on Canny operator and gradient Hough transform is proposed. Firstly, the images are pre-processed; then, calculating the gradient information of images, the inner and outer edges of iris are coarse positioned using Canny operator; finally, according to the gradient Hough transform to realize precise localization of the inner and outer edge of iris. The experimental results show that our algorithm can achieve the localization of the inner and outer edges of the iris well, and the algorithm has strong anti-interference ability, can greatly reduce the location time and has higher accuracy and stability.

Modeling of salt and pH gradient elution in ion-exchange chromatography.

PubMed

Schmidt, Michael; Hafner, Mathias; Frech, Christian

2014-01-01

The separation of proteins by internally and externally generated pH gradients in chromatofocusing on ion-exchange columns is a well-established analytical method with a large number of applications. In this work, a stoichiometric displacement model was used to describe the retention behavior of lysozyme on SP Sepharose FF and a monoclonal antibody on Fractogel SO3 (S) in linear salt and pH gradient elution. The pH dependence of the binding charge B in the linear gradient elution model is introduced using a protein net charge model, while the pH dependence of the equilibrium constant is based on a thermodynamic approach. The model parameter and pH dependences are calculated from linear salt gradient elutions at different pH values as well as from linear pH gradient elutions at different fixed salt concentrations. The application of the model for the well-characterized protein lysozyme resulted in almost identical model parameters based on either linear salt or pH gradient elution data. For the antibody, only the approach based on linear pH gradients is feasible because of the limited pH range useful for salt gradient elution. The application of the model for the separation of an acid variant of the antibody from the major monomeric form is discussed. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

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

2008-11-01

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

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

NASA Technical Reports Server (NTRS)

Freund, Roland

1989-01-01

We consider conjugate gradient type methods for the solution of large sparse linear system Ax equals b with complex symmetric coefficient matrices A equals A(T). Such linear systems arise in important applications, such as the numerical solution of the complex Helmholtz equation. Furthermore, most complex non-Hermitian linear systems which occur in practice are actually complex symmetric. We investigate conjugate gradient type iterations which are based on a variant of the nonsymmetric Lanczos algorithm for complex symmetric matrices. We propose a new approach with iterates defined by a quasi-minimal residual property. The resulting algorithm presents several advantages over the standard biconjugate gradient method. We also include some remarks on the obvious approach to general complex linear systems by solving equivalent real linear systems for the real and imaginary parts of x. Finally, numerical experiments for linear systems arising from the complex Helmholtz equation are reported.

A simple method for MR elastography: a gradient-echo type multi-echo sequence.

PubMed

Numano, Tomokazu; Mizuhara, Kazuyuki; Hata, Junichi; Washio, Toshikatsu; Homma, Kazuhiro

2015-01-01

To demonstrate the feasibility of a novel MR elastography (MRE) technique based on a conventional gradient-echo type multi-echo MR sequence which does not need additional bipolar magnetic field gradients (motion encoding gradient: MEG), yet is sensitive to vibration. In a gradient-echo type multi-echo MR sequence, several images are produced from each echo of the train with different echo times (TEs). If these echoes are synchronized with the vibration, each readout's gradient lobes achieve a MEG-like effect, and the later generated echo causes a greater MEG-like effect. The sequence was tested for the tissue-mimicking agarose gel phantoms and the psoas major muscles of healthy volunteers. It was confirmed that the readout gradient lobes caused an MEG-like effect and the later TE images had higher sensitivity to vibrations. The magnitude image of later generated echo suffered the T2 decay and the susceptibility artifacts, but the wave image and elastogram of later generated echo were unaffected by these effects. In in vivo experiments, this method was able to measure the mean shear modulus of the psoas major muscle. From the results of phantom experiments and volunteer studies, it was shown that this method has clinical application potential. Copyright © 2014 Elsevier Inc. All rights reserved.

Detection of blob objects in microscopic zebrafish images based on gradient vector diffusion.

PubMed

Li, Gang; Liu, Tianming; Nie, Jingxin; Guo, Lei; Malicki, Jarema; Mara, Andrew; Holley, Scott A; Xia, Weiming; Wong, Stephen T C

2007-10-01

The zebrafish has become an important vertebrate animal model for the study of developmental biology, functional genomics, and disease mechanisms. It is also being used for drug discovery. Computerized detection of blob objects has been one of the important tasks in quantitative phenotyping of zebrafish. We present a new automated method that is able to detect blob objects, such as nuclei or cells in microscopic zebrafish images. This method is composed of three key steps. The first step is to produce a diffused gradient vector field by a physical elastic deformable model. In the second step, the flux image is computed on the diffused gradient vector field. The third step performs thresholding and nonmaximum suppression based on the flux image. We report the validation and experimental results of this method using zebrafish image datasets from three independent research labs. Both sensitivity and specificity of this method are over 90%. This method is able to differentiate closely juxtaposed or connected blob objects, with high sensitivity and specificity in different situations. It is characterized by a good, consistent performance in blob object detection.

Simultaneous auto-calibration and gradient delays estimation (SAGE) in non-Cartesian parallel MRI using low-rank constraints.

PubMed

Jiang, Wenwen; Larson, Peder E Z; Lustig, Michael

2018-03-09

To correct gradient timing delays in non-Cartesian MRI while simultaneously recovering corruption-free auto-calibration data for parallel imaging, without additional calibration scans. The calibration matrix constructed from multi-channel k-space data should be inherently low-rank. This property is used to construct reconstruction kernels or sensitivity maps. Delays between the gradient hardware across different axes and RF receive chain, which are relatively benign in Cartesian MRI (excluding EPI), lead to trajectory deviations and hence data inconsistencies for non-Cartesian trajectories. These in turn lead to higher rank and corrupted calibration information which hampers the reconstruction. Here, a method named Simultaneous Auto-calibration and Gradient delays Estimation (SAGE) is proposed that estimates the actual k-space trajectory while simultaneously recovering the uncorrupted auto-calibration data. This is done by estimating the gradient delays that result in the lowest rank of the calibration matrix. The Gauss-Newton method is used to solve the non-linear problem. The method is validated in simulations using center-out radial, projection reconstruction and spiral trajectories. Feasibility is demonstrated on phantom and in vivo scans with center-out radial and projection reconstruction trajectories. SAGE is able to estimate gradient timing delays with high accuracy at a signal to noise ratio level as low as 5. The method is able to effectively remove artifacts resulting from gradient timing delays and restore image quality in center-out radial, projection reconstruction, and spiral trajectories. The low-rank based method introduced simultaneously estimates gradient timing delays and provides accurate auto-calibration data for improved image quality, without any additional calibration scans. © 2018 International Society for Magnetic Resonance in Medicine.

A fast referenceless PRFS-based MR thermometry by phase finite difference

NASA Astrophysics Data System (ADS)

Zou, Chao; Shen, Huan; He, Mengyue; Tie, Changjun; Chung, Yiu-Cho; Liu, Xin

2013-08-01

Proton resonance frequency shift-based MR thermometry is a promising temperature monitoring approach for thermotherapy but its accuracy is vulnerable to inter-scan motion. Model-based referenceless thermometry has been proposed to address this problem but phase unwrapping is usually needed before the model fitting process. In this paper, a referenceless MR thermometry method using phase finite difference that avoids the time consuming phase unwrapping procedure is proposed. Unlike the previously proposed phase gradient technique, the use of finite difference in the new method reduces the fitting error resulting from the ringing artifacts associated with phase discontinuity in the calculation of the phase gradient image. The new method takes into account the values at the perimeter of the region of interest because of their direct relevance to the extrapolated baseline phase of the region of interest (where temperature increase takes place). In simulation study, in vivo and ex vivo experiments, the new method has a root-mean-square temperature error of 0.35 °C, 1.02 °C and 1.73 °C compared to 0.83 °C, 2.81 °C, and 3.76 °C from the phase gradient method, respectively. The method also demonstrated a slightly higher, albeit small, temperature accuracy than the original referenceless MR thermometry method. The proposed method is computationally efficient (∼0.1 s per image), making it very suitable for the real time temperature monitoring.

Three-dimensional full waveform inversion of short-period teleseismic wavefields based upon the SEM-DSM hybrid method

NASA Astrophysics Data System (ADS)

Monteiller, Vadim; Chevrot, Sébastien; Komatitsch, Dimitri; Wang, Yi

2015-08-01

We present a method for high-resolution imaging of lithospheric structures based on full waveform inversion of teleseismic waveforms. We model the propagation of seismic waves using our recently developed direct solution method/spectral-element method hybrid technique, which allows us to simulate the propagation of short-period teleseismic waves through a regional 3-D model. We implement an iterative quasi-Newton method based upon the L-BFGS algorithm, where the gradient of the misfit function is computed using the adjoint-state method. Compared to gradient or conjugate-gradient methods, the L-BFGS algorithm has a much faster convergence rate. We illustrate the potential of this method on a synthetic test case that consists of a crustal model with a crustal discontinuity at 25 km depth and a sharp Moho jump. This model contains short- and long-wavelength heterogeneities along the lateral and vertical directions. The iterative inversion starts from a smooth 1-D model derived from the IASP91 reference Earth model. We invert both radial and vertical component waveforms, starting from long-period signals filtered at 10 s and gradually decreasing the cut-off period down to 1.25 s. This multiscale algorithm quickly converges towards a model that is very close to the true model, in contrast to inversions involving short-period waveforms only, which always get trapped into a local minimum of the cost function.

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

PubMed

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

2017-05-01

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

Perspectives in flow-based microfluidic gradient generators for characterizing bacterial chemotaxis

PubMed Central

Wolfram, Christopher J.; Rubloff, Gary W.; Luo, Xiaolong

2016-01-01

Chemotaxis is a phenomenon which enables cells to sense concentrations of certain chemical species in their microenvironment and move towards chemically favorable regions. Recent advances in microbiology have engineered the chemotactic properties of bacteria to perform novel functions, but traditional methods of characterizing chemotaxis do not fully capture the associated cell motion, making it difficult to infer mechanisms that link the motion to the microbiology which induces it. Microfluidics offers a potential solution in the form of gradient generators. Many of the gradient generators studied to date for this application are flow-based, where a chemical species diffuses across the laminar flow interface between two solutions moving through a microchannel. Despite significant research efforts, flow-based gradient generators have achieved mixed success at accurately capturing the highly subtle chemotactic responses exhibited by bacteria. Here we present an analysis encompassing previously published versions of flow-based gradient generators, the theories that govern their gradient-generating properties, and new, more practical considerations that result from experimental factors. We conclude that flow-based gradient generators present a challenge inherent to their design in that the residence time and gradient decay must be finely balanced, and that this significantly narrows the window for reliable observation and quantification of chemotactic motion. This challenge is compounded by the effects of shear on an ellipsoidal bacterium that causes it to preferentially align with the direction of flow and subsequently suppresses the cross-flow chemotactic response. These problems suggest that a static, non-flowing gradient generator may be a more suitable platform for chemotaxis studies in the long run, despite posing greater difficulties in design and fabrication. PMID:27917249

Perspectives in flow-based microfluidic gradient generators for characterizing bacterial chemotaxis.

PubMed

Wolfram, Christopher J; Rubloff, Gary W; Luo, Xiaolong

2016-11-01

Chemotaxis is a phenomenon which enables cells to sense concentrations of certain chemical species in their microenvironment and move towards chemically favorable regions. Recent advances in microbiology have engineered the chemotactic properties of bacteria to perform novel functions, but traditional methods of characterizing chemotaxis do not fully capture the associated cell motion, making it difficult to infer mechanisms that link the motion to the microbiology which induces it. Microfluidics offers a potential solution in the form of gradient generators. Many of the gradient generators studied to date for this application are flow-based, where a chemical species diffuses across the laminar flow interface between two solutions moving through a microchannel. Despite significant research efforts, flow-based gradient generators have achieved mixed success at accurately capturing the highly subtle chemotactic responses exhibited by bacteria. Here we present an analysis encompassing previously published versions of flow-based gradient generators, the theories that govern their gradient-generating properties, and new, more practical considerations that result from experimental factors. We conclude that flow-based gradient generators present a challenge inherent to their design in that the residence time and gradient decay must be finely balanced, and that this significantly narrows the window for reliable observation and quantification of chemotactic motion. This challenge is compounded by the effects of shear on an ellipsoidal bacterium that causes it to preferentially align with the direction of flow and subsequently suppresses the cross-flow chemotactic response. These problems suggest that a static, non-flowing gradient generator may be a more suitable platform for chemotaxis studies in the long run, despite posing greater difficulties in design and fabrication.

Disaggregation and separation dynamics of magnetic particles in a microfluidic flow under an alternating gradient magnetic field

NASA Astrophysics Data System (ADS)

Cao, Quanliang; Li, Zhenhao; Wang, Zhen; Qi, Fan; Han, Xiaotao

2018-05-01

How to prevent particle aggregation in the magnetic separation process is of great importance for high-purity separation, while it is a challenging issue in practice. In this work, we report a novel method to solve this problem for improving the selectivity of size-based separation by use of a gradient alternating magnetic field. The specially designed magnetic field is capable of dynamically adjusting the magnetic field direction without changing the direction of magnetic gradient force acting on the particles. Using direct numerical simulations, we show that particles within a certain center-to-center distance are inseparable under a gradient static magnetic field since they are easy aggregated and then start moving together. By contrast, it has been demonstrated that alternating repulsive and attractive interaction forces between particles can be generated to avoid the formation of aggregations when the alternating gradient magnetic field with a given alternating frequency is applied, enabling these particles to be continuously separated based on size-dependent properties. The proposed magnetic separation method and simulation results have the significance for fundamental understanding of particle dynamic behavior and improving the separation efficiency.

On the usefulness of gradient information in multi-objective deformable image registration using a B-spline-based dual-dynamic transformation model: comparison of three optimization algorithms

NASA Astrophysics Data System (ADS)

Pirpinia, Kleopatra; Bosman, Peter A. N.; Sonke, Jan-Jakob; van Herk, Marcel; Alderliesten, Tanja

2015-03-01

The use of gradient information is well-known to be highly useful in single-objective optimization-based image registration methods. However, its usefulness has not yet been investigated for deformable image registration from a multi-objective optimization perspective. To this end, within a previously introduced multi-objective optimization framework, we use a smooth B-spline-based dual-dynamic transformation model that allows us to derive gradient information analytically, while still being able to account for large deformations. Within the multi-objective framework, we previously employed a powerful evolutionary algorithm (EA) that computes and advances multiple outcomes at once, resulting in a set of solutions (a so-called Pareto front) that represents efficient trade-offs between the objectives. With the addition of the B-spline-based transformation model, we studied the usefulness of gradient information in multiobjective deformable image registration using three different optimization algorithms: the (gradient-less) EA, a gradientonly algorithm, and a hybridization of these two. We evaluated the algorithms to register highly deformed images: 2D MRI slices of the breast in prone and supine positions. Results demonstrate that gradient-based multi-objective optimization significantly speeds up optimization in the initial stages of optimization. However, allowing sufficient computational resources, better results could still be obtained with the EA. Ultimately, the hybrid EA found the best overall approximation of the optimal Pareto front, further indicating that adding gradient-based optimization for multiobjective optimization-based deformable image registration can indeed be beneficial

Spiral Gradient Coil Design for Use in Cylindrical MRI Systems.

PubMed

Wang, Yaohui; Xin, Xuegang; Liu, Feng; Crozier, Stuart

2018-04-01

In magnetic resonance imaging, the stream function based method is commonly used in the design of gradient coils. However, this method can be prone to errors associated with the discretization of continuous current density and wire connections. In this paper, we propose a novel gradient coil design scheme that works directly in the wire space, avoiding the system errors that may appear in the stream function approaches. Specifically, the gradient coil pattern is described with dedicated spiral functions adjusted to allow the coil to produce the required field gradients in the imaging area, minimal stray field, and other engineering terms. The performance of a designed spiral gradient coil was compared with its stream-function counterpart. The numerical evaluation shows that when compared with the conventional solution, the inductance and resistance was reduced by 20.9 and 10.5%, respectively. The overall coil performance (evaluated by the figure of merit (FoM)) was improved up to 26.5% for the x -gradient coil design; for the z-gradient coil design, the inductance and resistance were reduced by 15.1 and 6.7% respectively, and the FoM was increased by 17.7%. In addition, by directly controlling the wire distributions, the spiral gradient coil design was much sparser than conventional coils.

Parameter Optimization for Turbulent Reacting Flows Using Adjoints

NASA Astrophysics Data System (ADS)

Lapointe, Caelan; Hamlington, Peter E.

2017-11-01

The formulation of a new adjoint solver for topology optimization of turbulent reacting flows is presented. This solver provides novel configurations (e.g., geometries and operating conditions) based on desired system outcomes (i.e., objective functions) for complex reacting flow problems of practical interest. For many such problems, it would be desirable to know optimal values of design parameters (e.g., physical dimensions, fuel-oxidizer ratios, and inflow-outflow conditions) prior to real-world manufacture and testing, which can be expensive, time-consuming, and dangerous. However, computational optimization of these problems is made difficult by the complexity of most reacting flows, necessitating the use of gradient-based optimization techniques in order to explore a wide design space at manageable computational cost. The adjoint method is an attractive way to obtain the required gradients, because the cost of the method is determined by the dimension of the objective function rather than the size of the design space. Here, the formulation of a novel solver is outlined that enables gradient-based parameter optimization of turbulent reacting flows using the discrete adjoint method. Initial results and an outlook for future research directions are provided.

Detection, localization and classification of multiple dipole-like magnetic sources using magnetic gradient tensor data

NASA Astrophysics Data System (ADS)

Gang, Yin; Yingtang, Zhang; Hongbo, Fan; Zhining, Li; Guoquan, Ren

2016-05-01

We have developed a method for automatic detection, localization and classification (DLC) of multiple dipole sources using magnetic gradient tensor data. First, we define modified tilt angles to estimate the approximate horizontal locations of the multiple dipole-like magnetic sources simultaneously and detect the number of magnetic sources using a fixed threshold. Secondly, based on the isotropy of the normalized source strength (NSS) response of a dipole, we obtain accurate horizontal locations of the dipoles. Then the vertical locations are calculated using magnitude magnetic transforms of magnetic gradient tensor data. Finally, we invert for the magnetic moments of the sources using the measured magnetic gradient tensor data and forward model. Synthetic and field data sets demonstrate effectiveness and practicality of the proposed method.

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

Applications of thermal-gradients method for the optimization of α-amylase crystallization conditions based on dynamic and static light scattering data

NASA Astrophysics Data System (ADS)

Delboni, L. F.; Iulek, J.; Burger, R.; da Silva, A. C. R.; Moreno, A.

2002-02-01

The expression, purification, crystallization, and characterization by X-ray diffraction of α-amylase are described here. Dynamic and static light scattering methods with a temperature controller was used to optimize the crystallization conditions of α-amylase from Bacillus stearothermophilus an important enzyme in many fields of industrial activity. After applying thermal gradients for growing crystals, X-ray cryo-crystallographic methods were employed for the data collection. Crystals grown by these thermal-gradients diffracted up to a maximum resolution of 3.8 Å, which allowed the determination of the unit cell constants as follows: a=61.7 Å, b=86.7 Å, c=92.2 Å and space group C222 (or C222 1).

Lateral Temperature-Gradient Method for High-Throughput Characterization of Material Processing by Millisecond Laser Annealing.

PubMed

Bell, Robert T; Jacobs, Alan G; Sorg, Victoria C; Jung, Byungki; Hill, Megan O; Treml, Benjamin E; Thompson, Michael O

2016-09-12

A high-throughput method for characterizing the temperature dependence of material properties following microsecond to millisecond thermal annealing, exploiting the temperature gradients created by a lateral gradient laser spike anneal (lgLSA), is presented. Laser scans generate spatial thermal gradients of up to 5 °C/μm with peak temperatures ranging from ambient to in excess of 1400 °C, limited only by laser power and materials thermal limits. Discrete spatial property measurements across the temperature gradient are then equivalent to independent measurements after varying temperature anneals. Accurate temperature calibrations, essential to quantitative analysis, are critical and methods for both peak temperature and spatial/temporal temperature profile characterization are presented. These include absolute temperature calibrations based on melting and thermal decomposition, and time-resolved profiles measured using platinum thermistors. A variety of spatially resolved measurement probes, ranging from point-like continuous profiling to large area sampling, are discussed. Examples from annealing of III-V semiconductors, CdSe quantum dots, low-κ dielectrics, and block copolymers are included to demonstrate the flexibility, high throughput, and precision of this technique.

Determination of Acidity Constants by Gradient Flow-Injection Titration

ERIC Educational Resources Information Center

Conceicao, Antonio C. L.; Minas da Piedade, Manuel E.

2006-01-01

A three-hour laboratory experiment, designed for an advanced undergraduate course in instrumental analysis that illustrates the application of the gradient chamber flow-injection titration (GCFIT) method with spectrophotometric detection to determine acidity constants is presented. The procedure involves the use of an acid-base indicator to obtain…

Histogram of gradient and binarized statistical image features of wavelet subband-based palmprint features extraction

NASA Astrophysics Data System (ADS)

Attallah, Bilal; Serir, Amina; Chahir, Youssef; Boudjelal, Abdelwahhab

2017-11-01

Palmprint recognition systems are dependent on feature extraction. A method of feature extraction using higher discrimination information was developed to characterize palmprint images. In this method, two individual feature extraction techniques are applied to a discrete wavelet transform of a palmprint image, and their outputs are fused. The two techniques used in the fusion are the histogram of gradient and the binarized statistical image features. They are then evaluated using an extreme learning machine classifier before selecting a feature based on principal component analysis. Three palmprint databases, the Hong Kong Polytechnic University (PolyU) Multispectral Palmprint Database, Hong Kong PolyU Palmprint Database II, and the Delhi Touchless (IIDT) Palmprint Database, are used in this study. The study shows that our method effectively identifies and verifies palmprints and outperforms other methods based on feature extraction.

DISENTANGLING AGN AND STAR FORMATION ACTIVITY AT HIGH REDSHIFT USING HUBBLE SPACE TELESCOPE GRISM SPECTROSCOPY

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

Bridge, Joanna S.; Zeimann, Gregory R.; Trump, Jonathan R.

2016-08-01

Differentiating between active galactic nucleus (AGN) activity and star formation in z ∼ 2 galaxies is difficult because traditional methods, such as line-ratio diagnostics, change with redshift, while multi-wavelength methods (X-ray, radio, IR) are sensitive to only the brightest AGNs. We have developed a new method for spatially resolving emission lines using the Hubble Space Telescope /Wide Field Camera 3 G141 grism spectra and quantifying AGN activity through the spatial gradient of the [O iii]/H β line ratio. Through detailed simulations, we show that our novel line-ratio gradient approach identifies ∼40% more low-mass and obscured AGNs than obtained by classicalmore » methods. Based on our simulations, we developed a relationship that maps the stellar mass, star formation rate, and measured [O iii]/H β gradient to the AGN Eddington ratio. We apply our technique to previously studied stacked samples of galaxies at z ∼ 2 and find that our results are consistent with these studies. This gradient method will also be able to inform other areas of galaxy evolution science, such as inside-out quenching and metallicity gradients, and will be widely applicable to future spatially resolved James Webb Space Telescope data.« less

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.

Acoustic characteristics of the medium with gradient change of impedance

NASA Astrophysics Data System (ADS)

Hu, Bo; Yang, Desen; Sun, Yu; Shi, Jie; Shi, Shengguo; Zhang, Haoyang

2015-10-01

The medium with gradient change of acoustic impedance is a new acoustic structure which developed from multiple layer structures. In this paper, the inclusion is introduced and a new set of equations is developed. It can obtain better acoustic properties based on the medium with gradient change of acoustic impedance. Theoretical formulation has been systematically addressed which demonstrates how the idea of utilizing this method. The sound reflection and absorption coefficients were obtained. At last, the validity and the correctness of this method are assessed by simulations. The results show that appropriate design of parameters of the medium can improve underwater acoustic properties.

Iterative reconstruction methods in atmospheric tomography: FEWHA, Kaczmarz and Gradient-based algorithm

NASA Astrophysics Data System (ADS)

Ramlau, R.; Saxenhuber, D.; Yudytskiy, M.

2014-07-01

The problem of atmospheric tomography arises in ground-based telescope imaging with adaptive optics (AO), where one aims to compensate in real-time for the rapidly changing optical distortions in the atmosphere. Many of these systems depend on a sufficient reconstruction of the turbulence profiles in order to obtain a good correction. Due to steadily growing telescope sizes, there is a strong increase in the computational load for atmospheric reconstruction with current methods, first and foremost the MVM. In this paper we present and compare three novel iterative reconstruction methods. The first iterative approach is the Finite Element- Wavelet Hybrid Algorithm (FEWHA), which combines wavelet-based techniques and conjugate gradient schemes to efficiently and accurately tackle the problem of atmospheric reconstruction. The method is extremely fast, highly flexible and yields superior quality. Another novel iterative reconstruction algorithm is the three step approach which decouples the problem in the reconstruction of the incoming wavefronts, the reconstruction of the turbulent layers (atmospheric tomography) and the computation of the best mirror correction (fitting step). For the atmospheric tomography problem within the three step approach, the Kaczmarz algorithm and the Gradient-based method have been developed. We present a detailed comparison of our reconstructors both in terms of quality and speed performance in the context of a Multi-Object Adaptive Optics (MOAO) system for the E-ELT setting on OCTOPUS, the ESO end-to-end simulation tool.

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

PubMed

Huang, Yuanyuan; Liu, Changhe

2017-01-01

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

On the convergence of a linesearch based proximal-gradient method for nonconvex optimization

NASA Astrophysics Data System (ADS)

Bonettini, S.; Loris, I.; Porta, F.; Prato, M.; Rebegoldi, S.

2017-05-01

We consider a variable metric linesearch based proximal gradient method for the minimization of the sum of a smooth, possibly nonconvex function plus a convex, possibly nonsmooth term. We prove convergence of this iterative algorithm to a critical point if the objective function satisfies the Kurdyka-Łojasiewicz property at each point of its domain, under the assumption that a limit point exists. The proposed method is applied to a wide collection of image processing problems and our numerical tests show that our algorithm results to be flexible, robust and competitive when compared to recently proposed approaches able to address the optimization problems arising in the considered applications.

Method for extruding pitch based foam

DOEpatents

Klett, James W.

2002-01-01

A method and apparatus for extruding pitch based foam is disclosed. The method includes the steps of: forming a viscous pitch foam; passing the precursor through an extrusion tube; and subjecting the precursor in said extrusion tube to a temperature gradient which varies along the length of the extrusion tube to form an extruded carbon foam. The apparatus includes an extrusion tube having a passageway communicatively connected to a chamber in which a viscous pitch foam formed in the chamber paring through the extrusion tube, and a heating mechanism in thermal communication with the tube for heating the viscous pitch foam along the length of the tube in accordance with a predetermined temperature gradient.

Automated correction of improperly rotated diffusion gradient orientations in diffusion weighted MRI.

PubMed

Jeurissen, Ben; Leemans, Alexander; Sijbers, Jan

2014-10-01

Ensuring one is using the correct gradient orientations in a diffusion MRI study can be a challenging task. As different scanners, file formats and processing tools use different coordinate frame conventions, in practice, users can end up with improperly oriented gradient orientations. Using such wrongly oriented gradient orientations for subsequent diffusion parameter estimation will invalidate all rotationally variant parameters and fiber tractography results. While large misalignments can be detected by visual inspection, small rotations of the gradient table (e.g. due to angulation of the acquisition plane), are much more difficult to detect. In this work, we propose an automated method to align the coordinate frame of the gradient orientations with that of the corresponding diffusion weighted images, using a metric based on whole brain fiber tractography. By transforming the gradient table and measuring the average fiber trajectory length, we search for the transformation that results in the best global 'connectivity'. To ensure a fast calculation of the metric we included a range of algorithmic optimizations in our tractography routine. To make the optimization routine robust to spurious local maxima, we use a stochastic optimization routine that selects a random set of seed points on each evaluation. Using simulations, we show that our method can recover the correct gradient orientations with high accuracy and precision. In addition, we demonstrate that our technique can successfully recover rotated gradient tables on a wide range of clinically realistic data sets. As such, our method provides a practical and robust solution to an often overlooked pitfall in the processing of diffusion MRI. Copyright © 2014 Elsevier B.V. All rights reserved.

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

Gradient of the temperature function at the voxel (i, j, k) for heterogeneous bio-thermal model

NASA Astrophysics Data System (ADS)

Cen, Wei; Hoppe, Ralph; Sun, Aiwu; Gu, Ning; Lu, Rongbo

2018-06-01

Determination of the relationship between electromagnetic power absorption and temperature distributions inside highly heterogeneous biological samples based on numerical methods is essential in biomedical engineering (e.g. microwave thermal ablation in clinic). In this paper, the gradient expression is examined and analyzed in detail, as how the gradient operators can be discretized is the only real difficulty to the solution of bio-heat equation for highly inhomogeneous model utilizing implicit scheme.

Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map.

PubMed

Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen

2015-09-11

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate.

A new edge detection algorithm based on Canny idea

NASA Astrophysics Data System (ADS)

Feng, Yingke; Zhang, Jinmin; Wang, Siming

2017-10-01

The traditional Canny algorithm has poor self-adaptability threshold, and it is more sensitive to noise. In order to overcome these drawbacks, this paper proposed a new edge detection method based on Canny algorithm. Firstly, the media filtering and filtering based on the method of Euclidean distance are adopted to process it; secondly using the Frei-chen algorithm to calculate gradient amplitude; finally, using the Otsu algorithm to calculate partial gradient amplitude operation to get images of thresholds value, then find the average of all thresholds that had been calculated, half of the average is high threshold value, and the half of the high threshold value is low threshold value. Experiment results show that this new method can effectively suppress noise disturbance, keep the edge information, and also improve the edge detection accuracy.

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

PubMed

Dorri, Fatemeh; Azmi, Paeiz; Dorri, Faezeh

2012-02-01

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

A hybrid neural learning algorithm using evolutionary learning and derivative free local search method.

PubMed

Ghosh, Ranadhir; Yearwood, John; Ghosh, Moumita; Bagirov, Adil

2006-06-01

In this paper we investigate a hybrid model based on the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. Also we discuss different variants for hybrid models using the Discrete Gradient method and an evolutionary strategy for determining the weights in a feed forward artificial neural network. The Discrete Gradient method has the advantage of being able to jump over many local minima and find very deep local minima. However, earlier research has shown that a good starting point for the discrete gradient method can improve the quality of the solution point. Evolutionary algorithms are best suited for global optimisation problems. Nevertheless they are cursed with longer training times and often unsuitable for real world application. For optimisation problems such as weight optimisation for ANNs in real world applications the dimensions are large and time complexity is critical. Hence the idea of a hybrid model can be a suitable option. In this paper we propose different fusion strategies for hybrid models combining the evolutionary strategy with the discrete gradient method to obtain an optimal solution much quicker. Three different fusion strategies are discussed: a linear hybrid model, an iterative hybrid model and a restricted local search hybrid model. Comparative results on a range of standard datasets are provided for different fusion hybrid models.

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

PubMed Central

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

2008-01-01

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

Moving force identification based on modified preconditioned conjugate gradient method

NASA Astrophysics Data System (ADS)

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

2018-06-01

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

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.

Performance of local optimization in single-plane fluoroscopic analysis for total knee arthroplasty.

PubMed

Prins, A H; Kaptein, B L; Stoel, B C; Lahaye, D J P; Valstar, E R

2015-11-05

Fluoroscopy-derived joint kinematics plays an important role in the evaluation of knee prostheses. Fluoroscopic analysis requires estimation of the 3D prosthesis pose from its 2D silhouette in the fluoroscopic image, by optimizing a dissimilarity measure. Currently, extensive user-interaction is needed, which makes analysis labor-intensive and operator-dependent. The aim of this study was to review five optimization methods for 3D pose estimation and to assess their performance in finding the correct solution. Two derivative-free optimizers (DHSAnn and IIPM) and three gradient-based optimizers (LevMar, DoNLP2 and IpOpt) were evaluated. For the latter three optimizers two different implementations were evaluated: one with a numerically approximated gradient and one with an analytically derived gradient for computational efficiency. On phantom data, all methods were able to find the 3D pose within 1mm and 1° in more than 85% of cases. IpOpt had the highest success-rate: 97%. On clinical data, the success rates were higher than 85% for the in-plane positions, but not for the rotations. IpOpt was the most expensive method and the application of an analytically derived gradients accelerated the gradient-based methods by a factor 3-4 without any differences in success rate. In conclusion, 85% of the frames can be analyzed automatically in clinical data and only 15% of the frames require manual supervision. The optimal success-rate on phantom data (97% with IpOpt) on phantom data indicates that even less supervision may become feasible. Copyright © 2015 Elsevier Ltd. All rights reserved.

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

PubMed

Bernal, Javier; Torres-Jimenez, Jose

2015-01-01

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

Model of separation performance of bilinear gradients in scanning format counter-flow gradient electrofocusing techniques.

PubMed

Shameli, Seyed Mostafa; Glawdel, Tomasz; Ren, Carolyn L

2015-03-01

Counter-flow gradient electrofocusing allows the simultaneous concentration and separation of analytes by generating a gradient in the total velocity of each analyte that is the sum of its electrophoretic velocity and the bulk counter-flow velocity. In the scanning format, the bulk counter-flow velocity is varying with time so that a number of analytes with large differences in electrophoretic mobility can be sequentially focused and passed by a single detection point. Studies have shown that nonlinear (such as a bilinear) velocity gradients along the separation channel can improve both peak capacity and separation resolution simultaneously, which cannot be realized by using a single linear gradient. Developing an effective separation system based on the scanning counter-flow nonlinear gradient electrofocusing technique usually requires extensive experimental and numerical efforts, which can be reduced significantly with the help of analytical models for design optimization and guiding experimental studies. Therefore, this study focuses on developing an analytical model to evaluate the separation performance of scanning counter-flow bilinear gradient electrofocusing methods. In particular, this model allows a bilinear gradient and a scanning rate to be optimized for the desired separation performance. The results based on this model indicate that any bilinear gradient provides a higher separation resolution (up to 100%) compared to the linear case. This model is validated by numerical studies. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A novel retinal vessel extraction algorithm based on matched filtering and gradient vector flow

NASA Astrophysics Data System (ADS)

Yu, Lei; Xia, Mingliang; Xuan, Li

2013-10-01

The microvasculature network of retina plays an important role in the study and diagnosis of retinal diseases (age-related macular degeneration and diabetic retinopathy for example). Although it is possible to noninvasively acquire high-resolution retinal images with modern retinal imaging technologies, non-uniform illumination, the low contrast of thin vessels and the background noises all make it difficult for diagnosis. In this paper, we introduce a novel retinal vessel extraction algorithm based on gradient vector flow and matched filtering to segment retinal vessels with different likelihood. Firstly, we use isotropic Gaussian kernel and adaptive histogram equalization to smooth and enhance the retinal images respectively. Secondly, a multi-scale matched filtering method is adopted to extract the retinal vessels. Then, the gradient vector flow algorithm is introduced to locate the edge of the retinal vessels. Finally, we combine the results of matched filtering method and gradient vector flow algorithm to extract the vessels at different likelihood levels. The experiments demonstrate that our algorithm is efficient and the intensities of vessel images exactly represent the likelihood of the vessels.

High-Fidelity Geometric Modeling and Mesh Generation for Mechanics Characterization of Polycrystalline Materials

DTIC Science & Technology

2014-10-26

From the parameterization results, we extract adaptive and anisotropic T-meshes for the further T- spline surface construction. Finally, a gradient flow...field-based method [7, 12] to generate adaptive and anisotropic quadrilateral meshes, which can be used as the control mesh for high-order T- spline ...parameterization results, we extract adaptive and anisotropic T-meshes for the further T- spline surface construction. Finally, a gradient flow-based

Finite difference time domain (FDTD) method for modeling the effect of switched gradients on the human body in MRI.

PubMed

Zhao, Huawei; Crozier, Stuart; Liu, Feng

2002-12-01

Numerical modeling of the eddy currents induced in the human body by the pulsed field gradients in MRI presents a difficult computational problem. It requires an efficient and accurate computational method for high spatial resolution analyses with a relatively low input frequency. In this article, a new technique is described which allows the finite difference time domain (FDTD) method to be efficiently applied over a very large frequency range, including low frequencies. This is not the case in conventional FDTD-based methods. A method of implementing streamline gradients in FDTD is presented, as well as comparative analyses which show that the correct source injection in the FDTD simulation plays a crucial rule in obtaining accurate solutions. In particular, making use of the derivative of the input source waveform is shown to provide distinct benefits in accuracy over direct source injection. In the method, no alterations to the properties of either the source or the transmission media are required. The method is essentially frequency independent and the source injection method has been verified against examples with analytical solutions. Results are presented showing the spatial distribution of gradient-induced electric fields and eddy currents in a complete body model. Copyright 2002 Wiley-Liss, Inc.

Gradient Dynamics and Entropy Production Maximization

NASA Astrophysics Data System (ADS)

Janečka, Adam; Pavelka, Michal

2018-01-01

We compare two methods for modeling dissipative processes, namely gradient dynamics and entropy production maximization. Both methods require similar physical inputs-how energy (or entropy) is stored and how it is dissipated. Gradient dynamics describes irreversible evolution by means of dissipation potential and entropy, it automatically satisfies Onsager reciprocal relations as well as their nonlinear generalization (Maxwell-Onsager relations), and it has statistical interpretation. Entropy production maximization is based on knowledge of free energy (or another thermodynamic potential) and entropy production. It also leads to the linear Onsager reciprocal relations and it has proven successful in thermodynamics of complex materials. Both methods are thermodynamically sound as they ensure approach to equilibrium, and we compare them and discuss their advantages and shortcomings. In particular, conditions under which the two approaches coincide and are capable of providing the same constitutive relations are identified. Besides, a commonly used but not often mentioned step in the entropy production maximization is pinpointed and the condition of incompressibility is incorporated into gradient dynamics.

On the Convergence Analysis of the Optimized Gradient Method.

PubMed

Kim, Donghwan; Fessler, Jeffrey A

2017-01-01

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

On the Convergence Analysis of the Optimized Gradient Method

PubMed Central

Kim, Donghwan; Fessler, Jeffrey A.

2016-01-01

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

AUTOMATED CELL SEGMENTATION WITH 3D FLUORESCENCE MICROSCOPY IMAGES.

PubMed

Kong, Jun; Wang, Fusheng; Teodoro, George; Liang, Yanhui; Zhu, Yangyang; Tucker-Burden, Carol; Brat, Daniel J

2015-04-01

A large number of cell-oriented cancer investigations require an effective and reliable cell segmentation method on three dimensional (3D) fluorescence microscopic images for quantitative analysis of cell biological properties. In this paper, we present a fully automated cell segmentation method that can detect cells from 3D fluorescence microscopic images. Enlightened by fluorescence imaging techniques, we regulated the image gradient field by gradient vector flow (GVF) with interpolated and smoothed data volume, and grouped voxels based on gradient modes identified by tracking GVF field. Adaptive thresholding was then applied to voxels associated with the same gradient mode where voxel intensities were enhanced by a multiscale cell filter. We applied the method to a large volume of 3D fluorescence imaging data of human brain tumor cells with (1) small cell false detection and missing rates for individual cells; and (2) trivial over and under segmentation incidences for clustered cells. Additionally, the concordance of cell morphometry structure between automated and manual segmentation was encouraging. These results suggest a promising 3D cell segmentation method applicable to cancer studies.

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

Won, Yoo Jai; Ki, Hyungson

A novel picosecond-laser pulsed laser deposition method has been developed for fabricating functionally graded films with pre-designed gradient profiles. Theoretically, the developed method is capable of precisely fabricating films with any thicknesses and any gradient profiles by controlling the laser beam powers for the two different targets based on the film composition profiles. As an implementation example, we have successfully constructed functionally graded diamond-like carbon films with six different gradient profiles: linear, quadratic, cubic, square root, cubic root, and sinusoidal. Energy dispersive X-ray spectroscopy is employed for investigating the chemical composition along the thickness of the film, and the depositionmore » profile and thickness errors are found to be less than 3% and 1.04%, respectively. To the best of the authors' knowledge, this is the first method for fabricating films with designed gradient profiles and has huge potential in many areas of coatings and films, including multifunctional optical films. We believe that this method is not only limited to the example considered in this study, but also can be applied to all material combinations as long as they can be deposited using the pulsed laser deposition technique.« less

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Retention prediction and separation optimization under multilinear gradient elution in liquid chromatography with Microsoft Excel macros.

PubMed

Fasoula, S; Zisi, Ch; Gika, H; Pappa-Louisi, A; Nikitas, P

2015-05-22

A package of Excel VBA macros have been developed for modeling multilinear gradient retention data obtained in single or double gradient elution mode by changing organic modifier(s) content and/or eluent pH. For this purpose, ten chromatographic models were used and four methods were adopted for their application. The methods were based on (a) the analytical expression of the retention time, provided that this expression is available, (b) the retention times estimated using the Nikitas-Pappa approach, (c) the stepwise approximation, and (d) a simple numerical approximation involving the trapezoid rule for integration of the fundamental equation for gradient elution. For all these methods, Excel VBA macros have been written and implemented using two different platforms; the fitting and the optimization platform. The fitting platform calculates not only the adjustable parameters of the chromatographic models, but also the significance of these parameters and furthermore predicts the analyte elution times. The optimization platform determines the gradient conditions that lead to the optimum separation of a mixture of analytes by using the Solver evolutionary mode, provided that proper constraints are set in order to obtain the optimum gradient profile in the minimum gradient time. The performance of the two platforms was tested using experimental and artificial data. It was found that using the proposed spreadsheets, fitting, prediction, and optimization can be performed easily and effectively under all conditions. Overall, the best performance is exhibited by the analytical and Nikitas-Pappa's methods, although the former cannot be used under all circumstances. Copyright © 2015 Elsevier B.V. All rights reserved.

3D Printed Programmable Release Capsules.

PubMed

Gupta, Maneesh K; Meng, Fanben; Johnson, Blake N; Kong, Yong Lin; Tian, Limei; Yeh, Yao-Wen; Masters, Nina; Singamaneni, Srikanth; McAlpine, Michael C

2015-08-12

The development of methods for achieving precise spatiotemporal control over chemical and biomolecular gradients could enable significant advances in areas such as synthetic tissue engineering, biotic-abiotic interfaces, and bionanotechnology. Living organisms guide tissue development through highly orchestrated gradients of biomolecules that direct cell growth, migration, and differentiation. While numerous methods have been developed to manipulate and implement biomolecular gradients, integrating gradients into multiplexed, three-dimensional (3D) matrices remains a critical challenge. Here we present a method to 3D print stimuli-responsive core/shell capsules for programmable release of multiplexed gradients within hydrogel matrices. These capsules are composed of an aqueous core, which can be formulated to maintain the activity of payload biomolecules, and a poly(lactic-co-glycolic) acid (PLGA, an FDA approved polymer) shell. Importantly, the shell can be loaded with plasmonic gold nanorods (AuNRs), which permits selective rupturing of the capsule when irradiated with a laser wavelength specifically determined by the lengths of the nanorods. This precise control over space, time, and selectivity allows for the ability to pattern 2D and 3D multiplexed arrays of enzyme-loaded capsules along with tunable laser-triggered rupture and release of active enzymes into a hydrogel ambient. The advantages of this 3D printing-based method include (1) highly monodisperse capsules, (2) efficient encapsulation of biomolecular payloads, (3) precise spatial patterning of capsule arrays, (4) "on the fly" programmable reconfiguration of gradients, and (5) versatility for incorporation in hierarchical architectures. Indeed, 3D printing of programmable release capsules may represent a powerful new tool to enable spatiotemporal control over biomolecular gradients.

Magnetic field of longitudinal gradient bend

NASA Astrophysics Data System (ADS)

Aiba, Masamitsu; Böge, Michael; Ehrlichman, Michael; Streun, Andreas

2018-06-01

The longitudinal gradient bend is an effective method for reducing the natural emittance in light sources. It is, however, not a common element. We have analyzed its magnetic field and derived a set of formulae. Based on the derivation, we discuss how to model the longitudinal gradient bend in accelerator codes that are used for designing electron storage rings. Strengths of multipole components can also be evaluated from the formulae, and we investigate the impact of higher order multipole components in a very low emittance lattice.

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

PubMed

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

2008-11-21

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

Surface-from-gradients without discrete integrability enforcement: A Gaussian kernel approach.

PubMed

Ng, Heung-Sun; Wu, Tai-Pang; Tang, Chi-Keung

2010-11-01

Representative surface reconstruction algorithms taking a gradient field as input enforce the integrability constraint in a discrete manner. While enforcing integrability allows the subsequent integration to produce surface heights, existing algorithms have one or more of the following disadvantages: They can only handle dense per-pixel gradient fields, smooth out sharp features in a partially integrable field, or produce severe surface distortion in the results. In this paper, we present a method which does not enforce discrete integrability and reconstructs a 3D continuous surface from a gradient or a height field, or a combination of both, which can be dense or sparse. The key to our approach is the use of kernel basis functions, which transfer the continuous surface reconstruction problem into high-dimensional space, where a closed-form solution exists. By using the Gaussian kernel, we can derive a straightforward implementation which is able to produce results better than traditional techniques. In general, an important advantage of our kernel-based method is that the method does not suffer discretization and finite approximation, both of which lead to surface distortion, which is typical of Fourier or wavelet bases widely adopted by previous representative approaches. We perform comparisons with classical and recent methods on benchmark as well as challenging data sets to demonstrate that our method produces accurate surface reconstruction that preserves salient and sharp features. The source code and executable of the system are available for downloading.

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.

Integrated Design of Downwind Land-Based Wind Turbines using Analytic Gradients

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

Ning, Andrew; Petch, Derek

2016-12-01

Wind turbines are complex systems where component-level changes can have significant system-level effects. Effective wind turbine optimization generally requires an integrated analysis approach with a large number of design variables. Optimizing across large variable sets is orders of magnitude more efficient with gradient-based methods as compared with gradient-free method, particularly when using exact gradients. We have developed a wind turbine analysis set of over 100 components where 90% of the models provide numerically exact gradients through symbolic differentiation, automatic differentiation, and adjoint methods. This framework is applied to a specific design study focused on downwind land-based wind turbines. Downwind machinesmore » are of potential interest for large wind turbines where the blades are often constrained by the stiffness required to prevent a tower strike. The mass of these rotor blades may be reduced by utilizing a downwind configuration where the constraints on tower strike are less restrictive. The large turbines of this study range in power rating from 5-7MW and in diameter from 105m to 175m. The changes in blade mass and power production have important effects on the rest of the system, and thus the nacelle and tower systems are also optimized. For high-speed wind sites, downwind configurations do not appear advantageous. The decrease in blade mass (10%) is offset by increases in tower mass caused by the bending moment from the rotor-nacelle-assembly. For low-wind speed sites, the decrease in blade mass is more significant (25-30%) and shows potential for modest decreases in overall cost of energy (around 1-2%).« less

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.

ANOTHER LOOK AT THE FAST ITERATIVE SHRINKAGE/THRESHOLDING ALGORITHM (FISTA)*

PubMed Central

Kim, Donghwan; Fessler, Jeffrey A.

2017-01-01

This paper provides a new way of developing the “Fast Iterative Shrinkage/Thresholding Algorithm (FISTA)” [3] that is widely used for minimizing composite convex functions with a nonsmooth term such as the ℓ1 regularizer. In particular, this paper shows that FISTA corresponds to an optimized approach to accelerating the proximal gradient method with respect to a worst-case bound of the cost function. This paper then proposes a new algorithm that is derived by instead optimizing the step coefficients of the proximal gradient method with respect to a worst-case bound of the composite gradient mapping. The proof is based on the worst-case analysis called Performance Estimation Problem in [11]. PMID:29805242

A Modified Magnetic Gradient Contraction Based Method for Ferromagnetic Target Localization

PubMed Central

Wang, Chen; Zhang, Xiaojuan; Qu, Xiaodong; Pan, Xiao; Fang, Guangyou; Chen, Luzhao

2016-01-01

The Scalar Triangulation and Ranging (STAR) method, which is based upon the unique properties of magnetic gradient contraction, is a high real-time ferromagnetic target localization method. Only one measurement point is required in the STAR method and it is not sensitive to changes in sensing platform orientation. However, the localization accuracy of the method is limited by the asphericity errors and the inaccurate value of position leads to larger errors in the estimation of magnetic moment. To improve the localization accuracy, a modified STAR method is proposed. In the proposed method, the asphericity errors of the traditional STAR method are compensated with an iterative algorithm. The proposed method has a fast convergence rate which meets the requirement of high real-time localization. Simulations and field experiments have been done to evaluate the performance of the proposed method. The results indicate that target parameters estimated by the modified STAR method are more accurate than the traditional STAR method. PMID:27999322

Efficient gradient calibration based on diffusion MRI

PubMed Central

Teh, Irvin; Maguire, Mahon L.

2016-01-01

Purpose To propose a method for calibrating gradient systems and correcting gradient nonlinearities based on diffusion MRI measurements. Methods The gradient scaling in x, y, and z were first offset by up to 5% from precalibrated values to simulate a poorly calibrated system. Diffusion MRI data were acquired in a phantom filled with cyclooctane, and corrections for gradient scaling errors and nonlinearity were determined. The calibration was assessed with diffusion tensor imaging and independently validated with high resolution anatomical MRI of a second structured phantom. Results The errors in apparent diffusion coefficients along orthogonal axes ranged from −9.2% ± 0.4% to + 8.8% ± 0.7% before calibration and −0.5% ± 0.4% to + 0.8% ± 0.3% after calibration. Concurrently, fractional anisotropy decreased from 0.14 ± 0.03 to 0.03 ± 0.01. Errors in geometric measurements in x, y and z ranged from −5.5% to + 4.5% precalibration and were likewise reduced to −0.97% to + 0.23% postcalibration. Image distortions from gradient nonlinearity were markedly reduced. Conclusion Periodic gradient calibration is an integral part of quality assurance in MRI. The proposed approach is both accurate and efficient, can be setup with readily available materials, and improves accuracy in both anatomical and diffusion MRI to within ±1%. Magn Reson Med 77:170–179, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. PMID:26749277

The performance of monotonic and new non-monotonic gradient ascent reconstruction algorithms for high-resolution neuroreceptor PET imaging.

PubMed

Angelis, G I; Reader, A J; Kotasidis, F A; Lionheart, W R; Matthews, J C

2011-07-07

Iterative expectation maximization (EM) techniques have been extensively used to solve maximum likelihood (ML) problems in positron emission tomography (PET) image reconstruction. Although EM methods offer a robust approach to solving ML problems, they usually suffer from slow convergence rates. The ordered subsets EM (OSEM) algorithm provides significant improvements in the convergence rate, but it can cycle between estimates converging towards the ML solution of each subset. In contrast, gradient-based methods, such as the recently proposed non-monotonic maximum likelihood (NMML) and the more established preconditioned conjugate gradient (PCG), offer a globally convergent, yet equally fast, alternative to OSEM. Reported results showed that NMML provides faster convergence compared to OSEM; however, it has never been compared to other fast gradient-based methods, like PCG. Therefore, in this work we evaluate the performance of two gradient-based methods (NMML and PCG) and investigate their potential as an alternative to the fast and widely used OSEM. All algorithms were evaluated using 2D simulations, as well as a single [(11)C]DASB clinical brain dataset. Results on simulated 2D data show that both PCG and NMML achieve orders of magnitude faster convergence to the ML solution compared to MLEM and exhibit comparable performance to OSEM. Equally fast performance is observed between OSEM and PCG for clinical 3D data, but NMML seems to perform poorly. However, with the addition of a preconditioner term to the gradient direction, the convergence behaviour of NMML can be substantially improved. Although PCG is a fast convergent algorithm, the use of a (bent) line search increases the complexity of the implementation, as well as the computational time involved per iteration. Contrary to previous reports, NMML offers no clear advantage over OSEM or PCG, for noisy PET data. Therefore, we conclude that there is little evidence to replace OSEM as the algorithm of choice for many applications, especially given that in practice convergence is often not desired for algorithms seeking ML estimates.

Aircraft Detection in High-Resolution SAR Images Based on a Gradient Textural Saliency Map

PubMed Central

Tan, Yihua; Li, Qingyun; Li, Yansheng; Tian, Jinwen

2015-01-01

This paper proposes a new automatic and adaptive aircraft target detection algorithm in high-resolution synthetic aperture radar (SAR) images of airport. The proposed method is based on gradient textural saliency map under the contextual cues of apron area. Firstly, the candidate regions with the possible existence of airport are detected from the apron area. Secondly, directional local gradient distribution detector is used to obtain a gradient textural saliency map in the favor of the candidate regions. In addition, the final targets will be detected by segmenting the saliency map using CFAR-type algorithm. The real high-resolution airborne SAR image data is used to verify the proposed algorithm. The results demonstrate that this algorithm can detect aircraft targets quickly and accurately, and decrease the false alarm rate. PMID:26378543

Field-gradient partitioning for fracture and frictional contact in the material point method: Field-gradient partitioning for fracture and frictional contact in the material point method [Fracture and frictional contact in material point method using damage-field gradients for velocity-field partitioning

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

Homel, Michael A.; Herbold, Eric B.

Contact and fracture in the material point method require grid-scale enrichment or partitioning of material into distinct velocity fields to allow for displacement or velocity discontinuities at a material interface. We present a new method which a kernel-based damage field is constructed from the particle data. The gradient of this field is used to dynamically repartition the material into contact pairs at each node. Our approach avoids the need to construct and evolve explicit cracks or contact surfaces and is therefore well suited to problems involving complex 3-D fracture with crack branching and coalescence. A straightforward extension of this approachmore » permits frictional ‘self-contact’ between surfaces that are initially part of a single velocity field, enabling more accurate simulation of granular flow, porous compaction, fragmentation, and comminution of brittle materials. Finally, numerical simulations of self contact and dynamic crack propagation are presented to demonstrate the accuracy of the approach.« less

Field-gradient partitioning for fracture and frictional contact in the material point method: Field-gradient partitioning for fracture and frictional contact in the material point method [Fracture and frictional contact in material point method using damage-field gradients for velocity-field partitioning

DOE PAGES

Homel, Michael A.; Herbold, Eric B.

2016-08-15

Contact and fracture in the material point method require grid-scale enrichment or partitioning of material into distinct velocity fields to allow for displacement or velocity discontinuities at a material interface. We present a new method which a kernel-based damage field is constructed from the particle data. The gradient of this field is used to dynamically repartition the material into contact pairs at each node. Our approach avoids the need to construct and evolve explicit cracks or contact surfaces and is therefore well suited to problems involving complex 3-D fracture with crack branching and coalescence. A straightforward extension of this approachmore » permits frictional ‘self-contact’ between surfaces that are initially part of a single velocity field, enabling more accurate simulation of granular flow, porous compaction, fragmentation, and comminution of brittle materials. Finally, numerical simulations of self contact and dynamic crack propagation are presented to demonstrate the accuracy of the approach.« less

A TPMS-based method for modeling porous scaffolds for bionic bone tissue engineering.

PubMed

Shi, Jianping; Zhu, Liya; Li, Lan; Li, Zongan; Yang, Jiquan; Wang, Xingsong

2018-05-09

In the field of bone defect repair, gradient porous scaffolds have received increased attention because they provide a better environment for promoting tissue regeneration. In this study, we propose an effective method to generate bionic porous scaffolds based on the TPMS (triply periodic minimal surface) and SF (sigmoid function) methods. First, cortical bone morphological features (e.g., pore size and distribution) were determined for several regions of a rabbit femoral bone by analyzing CT-scans. A finite element method was used to evaluate the mechanical properties of the bone at these respective areas. These results were used to place different TPMS substructures into one scaffold domain with smooth transitions. The geometrical parameters of the scaffolds were optimized to match the elastic properties of a human bone. With this proposed method, a functional gradient porous scaffold could be designed and produced by an additive manufacturing method.

Efficient l1 -norm-based low-rank matrix approximations for large-scale problems using alternating rectified gradient method.

PubMed

Kim, Eunwoo; Lee, Minsik; Choi, Chong-Ho; Kwak, Nojun; Oh, Songhwai

2015-02-01

Low-rank matrix approximation plays an important role in the area of computer vision and image processing. Most of the conventional low-rank matrix approximation methods are based on the l2 -norm (Frobenius norm) with principal component analysis (PCA) being the most popular among them. However, this can give a poor approximation for data contaminated by outliers (including missing data), because the l2 -norm exaggerates the negative effect of outliers. Recently, to overcome this problem, various methods based on the l1 -norm, such as robust PCA methods, have been proposed for low-rank matrix approximation. Despite the robustness of the methods, they require heavy computational effort and substantial memory for high-dimensional data, which is impractical for real-world problems. In this paper, we propose two efficient low-rank factorization methods based on the l1 -norm that find proper projection and coefficient matrices using the alternating rectified gradient method. The proposed methods are applied to a number of low-rank matrix approximation problems to demonstrate their efficiency and robustness. The experimental results show that our proposals are efficient in both execution time and reconstruction performance unlike other state-of-the-art methods.

Effects of reconstructed magnetic field from sparse noisy boundary measurements on localization of active neural source.

PubMed

Shen, Hui-min; Lee, Kok-Meng; Hu, Liang; Foong, Shaohui; Fu, Xin

2016-01-01

Localization of active neural source (ANS) from measurements on head surface is vital in magnetoencephalography. As neuron-generated magnetic fields are extremely weak, significant uncertainties caused by stochastic measurement interference complicate its localization. This paper presents a novel computational method based on reconstructed magnetic field from sparse noisy measurements for enhanced ANS localization by suppressing effects of unrelated noise. In this approach, the magnetic flux density (MFD) in the nearby current-free space outside the head is reconstructed from measurements through formulating the infinite series solution of the Laplace's equation, where boundary condition (BC) integrals over the entire measurements provide "smooth" reconstructed MFD with the decrease in unrelated noise. Using a gradient-based method, reconstructed MFDs with good fidelity are selected for enhanced ANS localization. The reconstruction model, spatial interpolation of BC, parametric equivalent current dipole-based inverse estimation algorithm using reconstruction, and gradient-based selection are detailed and validated. The influences of various source depths and measurement signal-to-noise ratio levels on the estimated ANS location are analyzed numerically and compared with a traditional method (where measurements are directly used), and it was demonstrated that gradient-selected high-fidelity reconstructed data can effectively improve the accuracy of ANS localization.

Determination of the electric field gradient in RbCaF3 near the phase transition

NASA Astrophysics Data System (ADS)

Hepp, M. A.; Man, P. P.; Trokiner, A.; Zanni, H.; Fraissard, J.

1992-12-01

The fluoroperovskite, RbCaF 3 undergoes a phase transition at 195.5K from a cubic to a tetragonal phase. The order parameter for this transition is directly related to the electric field gradient which arises in the tetragonal phase. In this work, we have used three NMR methods to measure the electric field gradient at the 87Rb site in a single crystal of RbCaF 3, very near this transition. These experiments are based on recent theoretical developments which allow the measurement of quadrupole parameters even for nuclei in a weak electric field gradient.

A practical approach for predicting retention time shifts due to pressure and temperature gradients in ultra-high-pressure liquid chromatography.

PubMed

Åsberg, Dennis; Chutkowski, Marcin; Leśko, Marek; Samuelsson, Jörgen; Kaczmarski, Krzysztof; Fornstedt, Torgny

2017-01-06

Large pressure gradients are generated in ultra-high-pressure liquid chromatography (UHPLC) using sub-2μm particles causing significant temperature gradients over the column due to viscous heating. These pressure and temperature gradients affect retention and ultimately result in important selectivity shifts. In this study, we developed an approach for predicting the retention time shifts due to these gradients. The approach is presented as a step-by-step procedure and it is based on empirical linear relationships describing how retention varies as a function of temperature and pressure and how the average column temperature increases with the flow rate. It requires only four experiments on standard equipment, is based on straightforward calculations, and is therefore easy to use in method development. The approach was rigorously validated against experimental data obtained with a quality control method for the active pharmaceutical ingredient omeprazole. The accuracy of retention time predictions was very good with relative errors always less than 1% and in many cases around 0.5% (n=32). Selectivity shifts observed between omeprazole and the related impurities when changing the flow rate could also be accurately predicted resulting in good estimates of the resolution between critical peak pairs. The approximations which the presented approach are based on were all justified. The retention factor as a function of pressure and temperature was studied in an experimental design while the temperature distribution in the column was obtained by solving the fundamental heat and mass balance equations for the different experimental conditions. We strongly believe that this approach is sufficiently accurate and experimentally feasible for this separation to be a valuable tool when developing a UHPLC method. After further validation with other separation systems, it could become a useful approach in UHPLC method development, especially in the pharmaceutical industry where demands are high for robustness and regulatory oversight. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

A gradient-based approach for automated crest-line detection and analysis of sand dune patterns on planetary surfaces

NASA Astrophysics Data System (ADS)

Lancaster, N.; LeBlanc, D.; Bebis, G.; Nicolescu, M.

2015-12-01

Dune-field patterns are believed to behave as self-organizing systems, but what causes the patterns to form is still poorly understood. The most obvious (and in many cases the most significant) aspect of a dune system is the pattern of dune crest lines. Extracting meaningful features such as crest length, orientation, spacing, bifurcations, and merging of crests from image data can reveal important information about the specific dune-field morphological properties, development, and response to changes in boundary conditions, but manual methods are labor-intensive and time-consuming. We are developing the capability to recognize and characterize patterns of sand dunes on planetary surfaces. Our goal is to develop a robust methodology and the necessary algorithms for automated or semi-automated extraction of dune morphometric information from image data. Our main approach uses image processing methods to extract gradient information from satellite images of dune fields. Typically, the gradients have a dominant magnitude and orientation. In many cases, the images have two major dominant gradient orientations, for the sunny and shaded side of the dunes. A histogram of the gradient orientations is used to determine the dominant orientation. A threshold is applied to the image based on gradient orientations which agree with the dominant orientation. The contours of the binary image can then be used to determine the dune crest-lines, based on pixel intensity values. Once the crest-lines have been extracted, the morphological properties can be computed. We have tested our approach on a variety of images of linear and crescentic (transverse) dunes and compared dune detection algorithms with manually-digitized dune crest lines, achieving true positive values of 0.57-0.99; and false positives values of 0.30-0.67, indicating that out approach is generally robust.

Concentration gradient along scala tympani following the local application of gentamicin to the round window membrane

PubMed Central

Plontke, Stefan K.; Mynatt, Robert; Gill, Ruth M.; Borgmann, Stefan; Salt, Alec N.

2008-01-01

Objectives The distribution of gentamicin along the fluid spaces of the cochlea following local applications has never previously been demonstrated. Computer simulations have predicted that significant basal-apical concentration gradients might be expected and histological studies indicate that hair cell damage is greater at the base than at the apex following local gentamicin application. In the present study, gradients of gentamicin along the cochlea were measured. Methods A recently-developed method of sampling perilymph from the cochlear apex of guinea pigs was used, in which the samples represent fluid originating from different regions along scala tympani. Gentamicin concentration was determined in sequential apical samples which were taken following up to three hours of local application to the round window niche. Results Substantial gradients of gentamicin along the length of scala tympani were demonstrated and quantified, averaging more than 4000 times greater concentration at the base compared to the apex at the time of sampling. Peak concentrations and gradients for gentamicin varied considerably between animals, likely resulting from variations in round window membrane permeability and rates of perilymph flow. Conclusions The large gradients for gentamicin demonstrated here in guinea pigs account for how it is possible to suppress vestibular function in some patients with a local application of gentamicin without damaging auditory function. Variations in round window membrane permeability and in perilymph flow could account for why hearing losses are observed in some patients. PMID:17603318

Geometrically Flexible and Efficient Flow Analysis of High Speed Vehicles Via Domain Decomposition, Part 1: Unstructured-Grid Solver for High Speed Flows

NASA Technical Reports Server (NTRS)

White, Jeffery A.; Baurle, Robert A.; Passe, Bradley J.; Spiegel, Seth C.; Nishikawa, Hiroaki

2017-01-01

The ability to solve the equations governing the hypersonic turbulent flow of a real gas on unstructured grids using a spatially-elliptic, 2nd-order accurate, cell-centered, finite-volume method has been recently implemented in the VULCAN-CFD code. This paper describes the key numerical methods and techniques that were found to be required to robustly obtain accurate solutions to hypersonic flows on non-hex-dominant unstructured grids. The methods and techniques described include: an augmented stencil, weighted linear least squares, cell-average gradient method, a robust multidimensional cell-average gradient-limiter process that is consistent with the augmented stencil of the cell-average gradient method and a cell-face gradient method that contains a cell skewness sensitive damping term derived using hyperbolic diffusion based concepts. A data-parallel matrix-based symmetric Gauss-Seidel point-implicit scheme, used to solve the governing equations, is described and shown to be more robust and efficient than a matrix-free alternative. In addition, a y+ adaptive turbulent wall boundary condition methodology is presented. This boundary condition methodology is deigned to automatically switch between a solve-to-the-wall and a wall-matching-function boundary condition based on the local y+ of the 1st cell center off the wall. The aforementioned methods and techniques are then applied to a series of hypersonic and supersonic turbulent flat plate unit tests to examine the efficiency, robustness and convergence behavior of the implicit scheme and to determine the ability of the solve-to-the-wall and y+ adaptive turbulent wall boundary conditions to reproduce the turbulent law-of-the-wall. Finally, the thermally perfect, chemically frozen, Mach 7.8 turbulent flow of air through a scramjet flow-path is computed and compared with experimental data to demonstrate the robustness, accuracy and convergence behavior of the unstructured-grid solver for a realistic 3-D geometry on a non-hex-dominant grid.

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.

Prediction and validation of concentration gradient generation in a paper-based microfluidic channel

NASA Astrophysics Data System (ADS)

Jang, Ilhoon; Kim, Gang-June; Song, Simon

2016-11-01

A paper-based microfluidic channel has obtained attention as a diagnosis device that can implement various chemical or biological reactions. With benefits of thin, flexible, and strong features of paper devices, for example, it is often utilized for cell culture where controlling oxygen, nutrients, metabolism, and signaling molecules gradient affects the growth and movement of the cells. Among various features of paper-based microfluidic devices, we focus on establishment of concentration gradient in a paper channel. The flow is subject to dispersion and capillary effects because a paper is a porous media. In this presentation, we describe facile, fast and accurate method of generating a concentration gradient by using flow mixing of different concentrations. Both theoretical prediction and experimental validation are discussed along with inter-diffusion characteristics of porous flows. This work was supported by the National Research Foundation of Korea(NRF) Grant funded by the Korea government(MSIP) (No. 2016R1A2B3009541).

A STANDARDIZED ASSESSMENT METHOD (SAM) FOR RIVERINE MACROINVERTEBRATES

EPA Science Inventory

A macroinvertebrate sampling method for large rivers based on desirable characteristics of existing nonwadeable methods was developed and tested. Six sites each were sampled on the Great Miami and Kentucky Rivers, reflecting a human disturbance gradient. Samples were collected ...

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.

A general strategy for performing temperature-programming in high performance liquid chromatography--prediction of segmented temperature gradients.

PubMed

Wiese, Steffen; Teutenberg, Thorsten; Schmidt, Torsten C

2011-09-28

In the present work it is shown that the linear elution strength (LES) model which was adapted from temperature-programming gas chromatography (GC) can also be employed to predict retention times for segmented-temperature gradients based on temperature-gradient input data in liquid chromatography (LC) with high accuracy. The LES model assumes that retention times for isothermal separations can be predicted based on two temperature gradients and is employed to calculate the retention factor of an analyte when changing the start temperature of the temperature gradient. In this study it was investigated whether this approach can also be employed in LC. It was shown that this approximation cannot be transferred to temperature-programmed LC where a temperature range from 60°C up to 180°C is investigated. Major relative errors up to 169.6% were observed for isothermal retention factor predictions. In order to predict retention times for temperature gradients with different start temperatures in LC, another relationship is required to describe the influence of temperature on retention. Therefore, retention times for isothermal separations based on isothermal input runs were predicted using a plot of the natural logarithm of the retention factor vs. the inverse temperature and a plot of the natural logarithm of the retention factor vs. temperature. It could be shown that a plot of lnk vs. T yields more reliable isothermal/isocratic retention time predictions than a plot of lnk vs. 1/T which is usually employed. Hence, in order to predict retention times for temperature-gradients with different start temperatures in LC, two temperature gradient and two isothermal measurements have been employed. In this case, retention times can be predicted with a maximal relative error of 5.5% (average relative error: 2.9%). In comparison, if the start temperature of the simulated temperature gradient is equal to the start temperature of the input data, only two temperature-gradient measurements are required. Under these conditions, retention times can be predicted with a maximal relative error of 4.3% (average relative error: 2.2%). As an example, the systematic method development for an isothermal as well as a temperature gradient separation of selected sulfonamides by means of the adapted LES model is demonstrated using a pure water mobile phase. Both methods are compared and it is shown that the temperature-gradient separation provides some advantages over the isothermal separation in terms of limits of detection and analysis time. Copyright © 2011 Elsevier B.V. All rights reserved.

lop-DWI: A Novel Scheme for Pre-Processing of Diffusion-Weighted Images in the Gradient Direction Domain.

PubMed

Sepehrband, Farshid; Choupan, Jeiran; Caruyer, Emmanuel; Kurniawan, Nyoman D; Gal, Yaniv; Tieng, Quang M; McMahon, Katie L; Vegh, Viktor; Reutens, David C; Yang, Zhengyi

2014-01-01

We describe and evaluate a pre-processing method based on a periodic spiral sampling of diffusion-gradient directions for high angular resolution diffusion magnetic resonance imaging. Our pre-processing method incorporates prior knowledge about the acquired diffusion-weighted signal, facilitating noise reduction. Periodic spiral sampling of gradient direction encodings results in an acquired signal in each voxel that is pseudo-periodic with characteristics that allow separation of low-frequency signal from high frequency noise. Consequently, it enhances local reconstruction of the orientation distribution function used to define fiber tracks in the brain. Denoising with periodic spiral sampling was tested using synthetic data and in vivo human brain images. The level of improvement in signal-to-noise ratio and in the accuracy of local reconstruction of fiber tracks was significantly improved using our method.

Arbitrary magnetic field gradient waveform correction using an impulse response based pre-equalization technique.

PubMed

Goora, Frédéric G; Colpitts, Bruce G; Balcom, Bruce J

2014-01-01

The time-varying magnetic fields used in magnetic resonance applications result in the induction of eddy currents on conductive structures in the vicinity of both the sample under investigation and the gradient coils. These eddy currents typically result in undesired degradations of image quality for MRI applications. Their ubiquitous nature has resulted in the development of various approaches to characterize and minimize their impact on image quality. This paper outlines a method that utilizes the magnetic field gradient waveform monitor method to directly measure the temporal evolution of the magnetic field gradient from a step-like input function and extracts the system impulse response. With the basic assumption that the gradient system is sufficiently linear and time invariant to permit system theory analysis, the impulse response is used to determine a pre-equalized (optimized) input waveform that provides a desired gradient response at the output of the system. An algorithm has been developed that calculates a pre-equalized waveform that may be accurately reproduced by the amplifier (is physically realizable) and accounts for system limitations including system bandwidth, amplifier slew rate capabilities, and noise inherent in the initial measurement. Significant improvements in magnetic field gradient waveform fidelity after pre-equalization have been realized and are summarized. Copyright © 2013 Elsevier Inc. All rights reserved.

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

PubMed

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

2004-05-01

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

Toward development of mobile application for hand arthritis screening.

PubMed

Akhbardeh, Farhad; Vasefi, Fartash; Tavakolian, Kouhyar; Bradley, David; Fazel-Rezai, Reza

2015-01-01

Arthritis is one of the most common health problems affecting people throughout the world. The goal of the work presented in this paper is to provide individuals, who may be developing or have developed arthritis, with a mobile application to assess and monitor the progress of their disease using their smartphone. The image processing algorithm includes finger border detection algorithm to monitor joint thickness and angular deviation abnormalities, which are common symptoms of arthritis. In this work, we have analyzed and compared gradient, thresholding and Canny algorithms for border detection. The effect of image spatial resolution (down-sampling) is also investigated. The results calculated based on 36 joint measurements show that the mean errors for gradient, thresholding, and Canny methods are 0.20, 2.13, and 2.03 mm, respectively. In addition, the average error for different image resolutions is analyzed and the minimum required resolution is determined for each method. The results confirm that recent smartphone imaging capabilities can provide enough accuracy for hand border detection and finger joint analysis based on gradient method.

An adjoint method for gradient-based optimization of stellarator coil shapes

NASA Astrophysics Data System (ADS)

Paul, E. J.; Landreman, M.; Bader, A.; Dorland, W.

2018-07-01

We present a method for stellarator coil design via gradient-based optimization of the coil-winding surface. The REGCOIL (Landreman 2017 Nucl. Fusion 57 046003) approach is used to obtain the coil shapes on the winding surface using a continuous current potential. We apply the adjoint method to calculate derivatives of the objective function, allowing for efficient computation of analytic gradients while eliminating the numerical noise of approximate derivatives. We are able to improve engineering properties of the coils by targeting the root-mean-squared current density in the objective function. We obtain winding surfaces for W7-X and HSX which simultaneously decrease the normal magnetic field on the plasma surface and increase the surface-averaged distance between the coils and the plasma in comparison with the actual winding surfaces. The coils computed on the optimized surfaces feature a smaller toroidal extent and curvature and increased inter-coil spacing. A technique for computation of the local sensitivity of figures of merit to normal displacements of the winding surface is presented, with potential applications for understanding engineering tolerances.

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

PubMed Central

Bernal, Javier; Torres-Jimenez, Jose

2015-01-01

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

PET and MRI image fusion based on combination of 2-D Hilbert transform and IHS method.

PubMed

Haddadpour, Mozhdeh; Daneshvar, Sabalan; Seyedarabi, Hadi

2017-08-01

The process of medical image fusion is combining two or more medical images such as Magnetic Resonance Image (MRI) and Positron Emission Tomography (PET) and mapping them to a single image as fused image. So purpose of our study is assisting physicians to diagnose and treat the diseases in the least of the time. We used Magnetic Resonance Image (MRI) and Positron Emission Tomography (PET) as input images, so fused them based on combination of two dimensional Hilbert transform (2-D HT) and Intensity Hue Saturation (IHS) method. Evaluation metrics that we apply are Discrepancy (D k ) as an assessing spectral features and Average Gradient (AG k ) as an evaluating spatial features and also Overall Performance (O.P) to verify properly of the proposed method. In this paper we used three common evaluation metrics like Average Gradient (AG k ) and the lowest Discrepancy (D k ) and Overall Performance (O.P) to evaluate the performance of our method. Simulated and numerical results represent the desired performance of proposed method. Since that the main purpose of medical image fusion is preserving both spatial and spectral features of input images, so based on numerical results of evaluation metrics such as Average Gradient (AG k ), Discrepancy (D k ) and Overall Performance (O.P) and also desired simulated results, it can be concluded that our proposed method can preserve both spatial and spectral features of input images. Copyright © 2017 Chang Gung University. Published by Elsevier B.V. All rights reserved.

Direct magnetic field estimation based on echo planar raw data.

PubMed

Testud, Frederik; Splitthoff, Daniel Nicolas; Speck, Oliver; Hennig, Jürgen; Zaitsev, Maxim

2010-07-01

Gradient recalled echo echo planar imaging is widely used in functional magnetic resonance imaging. The fast data acquisition is, however, very sensitive to field inhomogeneities which manifest themselves as artifacts in the images. Typically used correction methods have the common deficit that the data for the correction are acquired only once at the beginning of the experiment, assuming the field inhomogeneity distribution B(0) does not change over the course of the experiment. In this paper, methods to extract the magnetic field distribution from the acquired k-space data or from the reconstructed phase image of a gradient echo planar sequence are compared and extended. A common derivation for the presented approaches provides a solid theoretical basis, enables a fair comparison and demonstrates the equivalence of the k-space and the image phase based approaches. The image phase analysis is extended here to calculate the local gradient in the readout direction and improvements are introduced to the echo shift analysis, referred to here as "k-space filtering analysis." The described methods are compared to experimentally acquired B(0) maps in phantoms and in vivo. The k-space filtering analysis presented in this work demonstrated to be the most sensitive method to detect field inhomogeneities.

Multiscale infrared and visible image fusion using gradient domain guided image filtering

NASA Astrophysics Data System (ADS)

Zhu, Jin; Jin, Weiqi; Li, Li; Han, Zhenghao; Wang, Xia

2018-03-01

For better surveillance with infrared and visible imaging, a novel hybrid multiscale decomposition fusion method using gradient domain guided image filtering (HMSD-GDGF) is proposed in this study. In this method, hybrid multiscale decomposition with guided image filtering and gradient domain guided image filtering of source images are first applied before the weight maps of each scale are obtained using a saliency detection technology and filtering means with three different fusion rules at different scales. The three types of fusion rules are for small-scale detail level, large-scale detail level, and base level. Finally, the target becomes more salient and can be more easily detected in the fusion result, with the detail information of the scene being fully displayed. After analyzing the experimental comparisons with state-of-the-art fusion methods, the HMSD-GDGF method has obvious advantages in fidelity of salient information (including structural similarity, brightness, and contrast), preservation of edge features, and human visual perception. Therefore, visual effects can be improved by using the proposed HMSD-GDGF method.

Energy harvesting from vibration of Timoshenko nanobeam under base excitation considering flexoelectric and elastic strain gradient effects

NASA Astrophysics Data System (ADS)

Managheb, S. A. M.; Ziaei-Rad, S.; Tikani, R.

2018-05-01

The coupling between polarization and strain gradients is called flexoelectricity. This phenomenon exists in all dielectrics with any symmetry. In this paper, energy harvesting from a Timoshenko beam is studied by considering the flexoelectric and strain gradient effects. General governing equations and related boundary conditions are derived using Hamilton's principle. The flexoelectric effects are defined by gradients of normal and shear strains which lead to a more general model. The developed model also covers the classical Timoshenko beam theory by ignoring the flexoelectric effect. Based on the developed model, flexoelectricity effect on dielectric beams and energy harvesting from cantilever beam under harmonic base excitation is investigated. A parametric study was conducted to evaluate the effects of flexoelectric coefficients, strain gradient constants, base acceleration and the attaching tip mass on the energy harvested from a cantilever Timoshenko beam. Results show that the flexoelectricity has a significant effect on the energy harvester performance, especially in submicron and nano scales. In addition, this effect makes the beam to behave softer than before and also it changes the harvester first resonance frequency. The present study provides guidance for flexoelectric nano-beam analysis and a method to evaluate the performance of energy harvester in nano-dielectric devices.

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Solving large mixed linear models using preconditioned conjugate gradient iteration.

PubMed

Strandén, I; Lidauer, M

1999-12-01

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

Advanced Magnetic Materials Methods and Numerical Models for Fluidization in Microgravity and Hypogravity

NASA Technical Reports Server (NTRS)

Atwater, James; Wheeler, Richard, Jr.; Akse, James; Jovanovic, Goran; Reed, Brian

2013-01-01

To support long-duration manned missions in space such as a permanent lunar base, Mars transit, or Mars Surface Mission, improved methods for the treatment of solid wastes, particularly methods that recover valuable resources, are needed. The ability to operate under microgravity and hypogravity conditions is essential to meet this objective. The utilization of magnetic forces to manipulate granular magnetic media has provided the means to treat solid wastes under variable gravity conditions by filtration using a consolidated magnetic media bed followed by thermal processing of the solid wastes in a fluidized bed reactor. Non-uniform magnetic fields will produce a magnetic field gradient in a bed of magnetically susceptible media toward the distributor plate of a fluidized bed reactor. A correctly oriented magnetic field gradient will generate a downward direct force on magnetic media that can substitute for gravitational force in microgravity, or which may augment low levels of gravity, such as on the Moon or Mars. This approach is termed Gradient Magnetically Assisted Fluidization (G-MAFB), in which the magnitude of the force on the fluidized media depends upon the intensity of the magnetic field (H), the intensity of the field gradient (dH/dz), and the magnetic susceptibility of the media. Fluidized beds based on the G-MAFB process can operate in any gravitational environment by tuning the magnetic field appropriately. Magnetic materials and methods have been developed that enable G-MAFB operation under variable gravity conditions.

Reentry-Vehicle Shape Optimization Using a Cartesian Adjoint Method and CAD Geometry

NASA Technical Reports Server (NTRS)

Nemec, Marian; Aftosmis, Michael J.

2006-01-01

A DJOINT solutions of the governing flow equations are becoming increasingly important for the development of efficient analysis and optimization algorithms. A well-known use of the adjoint method is gradient-based shape. Given an objective function that defines some measure of performance, such as the lift and drag functionals, its gradient is computed at a cost that is essentially independent of the number of design variables (e.g., geometric parameters that control the shape). Classic aerodynamic applications of gradient-based optimization include the design of cruise configurations for transonic and supersonic flow, as well as the design of high-lift systems. are perhaps the most promising approach for addressing the issues of flow solution automation for aerodynamic design problems. In these methods, the discretization of the wetted surface is decoupled from that of the volume mesh. This not only enables fast and robust mesh generation for geometry of arbitrary complexity, but also facilitates access to geometry modeling and manipulation using parametric computer-aided design (CAD). In previous work on Cartesian adjoint solvers, Melvin et al. developed an adjoint formulation for the TRANAIR code, which is based on the full-potential equation with viscous corrections. More recently, Dadone and Grossman presented an adjoint formulation for the two-dimensional Euler equations using a ghost-cell method to enforce the wall boundary conditions. In Refs. 18 and 19, we presented an accurate and efficient algorithm for the solution of the adjoint Euler equations discretized on Cartesian meshes with embedded, cut-cell boundaries. Novel aspects of the algorithm were the computation of surface shape sensitivities for triangulations based on parametric-CAD models and the linearization of the coupling between the surface triangulation and the cut-cells. The accuracy of the gradient computation was verified using several three-dimensional test cases, which included design variables such as the free stream parameters and the planform shape of an isolated wing. The objective of the present work is to extend our adjoint formulation to problems involving general shape changes. Factors under consideration include the computation of mesh sensitivities that provide a reliable approximation of the objective function gradient, as well as the computation of surface shape sensitivities based on a direct-CAD interface. We present detailed gradient verification studies and then focus on a shape optimization problem for an Apollo-like reentry vehicle. The goal of the optimization is to enhance the lift-to-drag ratio of the capsule by modifying the shape of its heat-shield in conjunction with a center-of-gravity (c.g.) offset. This multipoint and multi-objective optimization problem is used to demonstrate the overall effectiveness of the Cartesian adjoint method for addressing the issues of complex aerodynamic design.

An accelerated algorithm for discrete stochastic simulation of reaction-diffusion systems using gradient-based diffusion and tau-leaping.

PubMed

Koh, Wonryull; Blackwell, Kim T

2011-04-21

Stochastic simulation of reaction-diffusion systems enables the investigation of stochastic events arising from the small numbers and heterogeneous distribution of molecular species in biological cells. Stochastic variations in intracellular microdomains and in diffusional gradients play a significant part in the spatiotemporal activity and behavior of cells. Although an exact stochastic simulation that simulates every individual reaction and diffusion event gives a most accurate trajectory of the system's state over time, it can be too slow for many practical applications. We present an accelerated algorithm for discrete stochastic simulation of reaction-diffusion systems designed to improve the speed of simulation by reducing the number of time-steps required to complete a simulation run. This method is unique in that it employs two strategies that have not been incorporated in existing spatial stochastic simulation algorithms. First, diffusive transfers between neighboring subvolumes are based on concentration gradients. This treatment necessitates sampling of only the net or observed diffusion events from higher to lower concentration gradients rather than sampling all diffusion events regardless of local concentration gradients. Second, we extend the non-negative Poisson tau-leaping method that was originally developed for speeding up nonspatial or homogeneous stochastic simulation algorithms. This method calculates each leap time in a unified step for both reaction and diffusion processes while satisfying the leap condition that the propensities do not change appreciably during the leap and ensuring that leaping does not cause molecular populations to become negative. Numerical results are presented that illustrate the improvement in simulation speed achieved by incorporating these two new strategies.

The crack detection algorithm of pavement image based on edge information

NASA Astrophysics Data System (ADS)

Yang, Chunde; Geng, Mingyue

2018-05-01

As the images of pavement cracks are affected by a large amount of complicated noises, such as uneven illumination and water stains, the detected cracks are discontinuous and the main body information at the edge of the cracks is easily lost. In order to solve the problem, a crack detection algorithm in pavement image based on edge information is proposed. Firstly, the image is pre-processed by the nonlinear gray-scale transform function and reconstruction filter to enhance the linear characteristic of the crack. At the same time, an adaptive thresholding method is designed to coarsely extract the cracks edge according to the gray-scale gradient feature and obtain the crack gradient information map. Secondly, the candidate edge points are obtained according to the gradient information, and the edge is detected based on the single pixel percolation processing, which is improved by using the local difference between pixels in the fixed region. Finally, complete crack is obtained by filling the crack edge. Experimental results show that the proposed method can accurately detect pavement cracks and preserve edge information.

Statistical Mechanics of the Delayed Reward-Based Learning with Node Perturbation

NASA Astrophysics Data System (ADS)

Hiroshi Saito,; Kentaro Katahira,; Kazuo Okanoya,; Masato Okada,

2010-06-01

In reward-based learning, reward is typically given with some delay after a behavior that causes the reward. In machine learning literature, the framework of the eligibility trace has been used as one of the solutions to handle the delayed reward in reinforcement learning. In recent studies, the eligibility trace is implied to be important for difficult neuroscience problem known as the “distal reward problem”. Node perturbation is one of the stochastic gradient methods from among many kinds of reinforcement learning implementations, and it searches the approximate gradient by introducing perturbation to a network. Since the stochastic gradient method does not require a objective function differential, it is expected to be able to account for the learning mechanism of a complex system, like a brain. We study the node perturbation with the eligibility trace as a specific example of delayed reward-based learning, and analyzed it using a statistical mechanics approach. As a result, we show the optimal time constant of the eligibility trace respect to the reward delay and the existence of unlearnable parameter configurations.

3D printing for the design and fabrication of polymer-based gradient scaffolds.

PubMed

Bracaglia, Laura G; Smith, Brandon T; Watson, Emma; Arumugasaamy, Navein; Mikos, Antonios G; Fisher, John P

2017-07-01

To accurately mimic the native tissue environment, tissue engineered scaffolds often need to have a highly controlled and varied display of three-dimensional (3D) architecture and geometrical cues. Additive manufacturing in tissue engineering has made possible the development of complex scaffolds that mimic the native tissue architectures. As such, architectural details that were previously unattainable or irreproducible can now be incorporated in an ordered and organized approach, further advancing the structural and chemical cues delivered to cells interacting with the scaffold. This control over the environment has given engineers the ability to unlock cellular machinery that is highly dependent upon the intricate heterogeneous environment of native tissue. Recent research into the incorporation of physical and chemical gradients within scaffolds indicates that integrating these features improves the function of a tissue engineered construct. This review covers recent advances on techniques to incorporate gradients into polymer scaffolds through additive manufacturing and evaluate the success of these techniques. As covered here, to best replicate different tissue types, one must be cognizant of the vastly different types of manufacturing techniques available to create these gradient scaffolds. We review the various types of additive manufacturing techniques that can be leveraged to fabricate scaffolds with heterogeneous properties and discuss methods to successfully characterize them. Additive manufacturing techniques have given tissue engineers the ability to precisely recapitulate the native architecture present within tissue. In addition, these techniques can be leveraged to create scaffolds with both physical and chemical gradients. This work offers insight into several techniques that can be used to generate graded scaffolds, depending on the desired gradient. Furthermore, it outlines methods to determine if the designed gradient was achieved. This review will help to condense the abundance of information that has been published on the creation and characterization of gradient scaffolds and to provide a single review discussing both methods for manufacturing gradient scaffolds and evaluating the establishment of a gradient. Copyright © 2017. Published by Elsevier Ltd.

Topology optimization of finite strain viscoplastic systems under transient loads [Dynamic topology optimization based on finite strain visco-plasticity

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

Ivarsson, Niklas; Wallin, Mathias; Tortorelli, Daniel

In this paper, a transient finite strain viscoplastic model is implemented in a gradient-based topology optimization framework to design impact mitigating structures. The model's kinematics relies on the multiplicative split of the deformation gradient, and the constitutive response is based on isotropic hardening viscoplasticity. To solve the mechanical balance laws, the implicit Newmark-beta method is used together with a total Lagrangian finite element formulation. The optimization problem is regularized using a partial differential equation filter and solved using the method of moving asymptotes. Sensitivities required to solve the optimization problem are derived using the adjoint method. To demonstrate the capabilitymore » of the algorithm, several protective systems are designed, in which the absorbed viscoplastic energy is maximized. Finally, the numerical examples demonstrate that transient finite strain viscoplastic effects can successfully be combined with topology optimization.« less

Topology optimization of finite strain viscoplastic systems under transient loads [Dynamic topology optimization based on finite strain visco-plasticity

DOE PAGES

Ivarsson, Niklas; Wallin, Mathias; Tortorelli, Daniel

2018-02-08

In this paper, a transient finite strain viscoplastic model is implemented in a gradient-based topology optimization framework to design impact mitigating structures. The model's kinematics relies on the multiplicative split of the deformation gradient, and the constitutive response is based on isotropic hardening viscoplasticity. To solve the mechanical balance laws, the implicit Newmark-beta method is used together with a total Lagrangian finite element formulation. The optimization problem is regularized using a partial differential equation filter and solved using the method of moving asymptotes. Sensitivities required to solve the optimization problem are derived using the adjoint method. To demonstrate the capabilitymore » of the algorithm, several protective systems are designed, in which the absorbed viscoplastic energy is maximized. Finally, the numerical examples demonstrate that transient finite strain viscoplastic effects can successfully be combined with topology optimization.« less

Socioeconomic Position, Health, and Possible Explanations: A Tale of Two Cohorts

PubMed Central

Fuhrer, R.; Shipley, M. J.; Chastang, J. F.; Schmaus, A.; Niedhammer, I.; Stansfeld, S. A.; Goldberg, M.; Marmot, M. G.

2002-01-01

Objectives. We examined whether the social gradient for measures of morbidity is comparable in English and French public employees and investigated risk factors that may explain this gradient. Methods. This longitudinal study of 2 occupational cohorts—5825 London civil servants and 6818 French office-based employees—used 2 health outcomes: long spells of sickness absence during a 4-year follow-up and self-reported health. Results. Strong social gradients in health were observed in both cohorts. Health behaviors showed different relations with socioeconomic position in the 2 samples. Psychosocial work characteristics showed strong gradients in both cohorts. Cohort-specific significant risk factors explained between 12% and 56% of the gradient in sickness absence and self-reported health. Conclusions. Our cross-cultural comparison suggests that some common susceptibility may underlie the social gradient in health and disease, which explains why inequalities occur in cultures with different patterns of morbidity and mortality. PMID:12144986

A Novel Gradient Vector Flow Snake Model Based on Convex Function for Infrared Image Segmentation

PubMed Central

Zhang, Rui; Zhu, Shiping; Zhou, Qin

2016-01-01

Infrared image segmentation is a challenging topic because infrared images are characterized by high noise, low contrast, and weak edges. Active contour models, especially gradient vector flow, have several advantages in terms of infrared image segmentation. However, the GVF (Gradient Vector Flow) model also has some drawbacks including a dilemma between noise smoothing and weak edge protection, which decrease the effect of infrared image segmentation significantly. In order to solve this problem, we propose a novel generalized gradient vector flow snakes model combining GGVF (Generic Gradient Vector Flow) and NBGVF (Normally Biased Gradient Vector Flow) models. We also adopt a new type of coefficients setting in the form of convex function to improve the ability of protecting weak edges while smoothing noises. Experimental results and comparisons against other methods indicate that our proposed snakes model owns better ability in terms of infrared image segmentation than other snakes models. PMID:27775660

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

PubMed

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

2010-11-22

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

Feedback-Based Projected-Gradient Method for Real-Time Optimization of Aggregations of Energy Resources

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

Dall-Anese, Emiliano; Bernstein, Andrey; Simonetto, Andrea

This paper develops an online optimization method to maximize operational objectives of distribution-level distributed energy resources (DERs), while adjusting the aggregate power generated (or consumed) in response to services requested by grid operators. The design of the online algorithm is based on a projected-gradient method, suitably modified to accommodate appropriate measurements from the distribution network and the DERs. By virtue of this approach, the resultant algorithm can cope with inaccuracies in the representation of the AC power flows, it avoids pervasive metering to gather the state of noncontrollable resources, and it naturally lends itself to a distributed implementation. Optimality claimsmore » are established in terms of tracking of the solution of a well-posed time-varying convex optimization problem.« less

Feedback-Based Projected-Gradient Method For Real-Time Optimization of Aggregations of Energy Resources: Preprint

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

Dall-Anese, Emiliano; Bernstein, Andrey; Simonetto, Andrea

This paper develops an online optimization method to maximize the operational objectives of distribution-level distributed energy resources (DERs) while adjusting the aggregate power generated (or consumed) in response to services requested by grid operators. The design of the online algorithm is based on a projected-gradient method, suitably modified to accommodate appropriate measurements from the distribution network and the DERs. By virtue of this approach, the resultant algorithm can cope with inaccuracies in the representation of the AC power, it avoids pervasive metering to gather the state of noncontrollable resources, and it naturally lends itself to a distributed implementation. Optimality claimsmore » are established in terms of tracking of the solution of a well-posed time-varying optimization problem.« less

Modified conjugate gradient method for diagonalizing large matrices.

PubMed

Jie, Quanlin; Liu, Dunhuan

2003-11-01

We present an iterative method to diagonalize large matrices. The basic idea is the same as the conjugate gradient (CG) method, i.e, minimizing the Rayleigh quotient via its gradient and avoiding reintroducing errors to the directions of previous gradients. Each iteration step is to find lowest eigenvector of the matrix in a subspace spanned by the current trial vector and the corresponding gradient of the Rayleigh quotient, as well as some previous trial vectors. The gradient, together with the previous trial vectors, play a similar role as the conjugate gradient of the original CG algorithm. Our numeric tests indicate that this method converges significantly faster than the original CG method. And the computational cost of one iteration step is about the same as the original CG method. It is suitable for first principle calculations.

Finite Element Analysis of Surface Residual Stress in Functionally Gradient Cemented Carbide Tool

NASA Astrophysics Data System (ADS)

Su, Chuangnan; Liu, Deshun; Tang, Siwen; Li, Pengnan; Qiu, Xinyi

2018-03-01

A component distribution model is proposed for three-component functionally gradient cemented carbide (FGCC) based on electron probe microanalysis results obtained for gradient layer thickness, microstructure, and elemental distribution. The residual surface stress of FGCC-T5 tools occurring during the fabrication process is analyzed using an ANSYS-implemented finite element method (FEM) and X-ray diffraction. A comparison of the experimental and calculated values verifies the feasibility of using FEM to analyze the residual surface stress in FGCC-T5 tools. The effects of the distribution index, geometrical shape, substrate thickness, gradient layer thickness, and position of the cobalt-rich layer on residual surface stress are studied in detail.

Thermal Management Techniques for Oil-Free Turbomachinery Systems

NASA Technical Reports Server (NTRS)

Radil, Kevin; DellaCorte, Chris; Zeszotek, Michelle

2006-01-01

Tests were performed to evaluate three different methods of utilizing air to provide thermal management control for compliant journal foil air bearings. The effectiveness of the methods was based on bearing bulk temperature and axial thermal gradient reductions during air delivery. The first method utilized direct impingement of air on the inner surface of a hollow test journal during operation. The second, less indirect method achieved heat removal by blowing air inside the test journal to simulate air flowing axially through a hollow, rotating shaft. The third method emulated the most common approach to removing heat by forcing air axially through the bearing s support structure. Internal bearing temperatures were measured with three, type K thermocouples embedded in the bearing that measured general internal temperatures and axial thermal gradients. Testing was performed in a 1 atm, 260 C ambient environment with the bearing operating at 60 krpm and supporting a load of 222 N. Air volumetric flows of 0.06, 0.11, and 0.17 cubic meters per minute at approximately 150 to 200 C were used. The tests indicate that all three methods provide thermal management but at different levels of effectiveness. Axial cooling of the bearing support structure had a greater effect on bulk temperature for each air flow and demonstrated that the thermal gradients could be influenced by the directionality of the air flow. Direct air impingement on the journal's inside surface provided uniform reductions in both bulk temperature and thermal gradients. Similar to the direct method, indirect journal cooling had a uniform cooling effect on both bulk temperatures and thermal gradients but was the least effective of the three methods.

A high speed model-based approach for wavefront sensorless adaptive optics systems

NASA Astrophysics Data System (ADS)

Lianghua, Wen; Yang, Ping; Shuai, Wang; Wenjing, Liu; Shanqiu, Chen; Xu, Bing

2018-02-01

To improve temporal-frequency property of wavefront sensorless adaptive optics (AO) systems, a fast general model-based aberration correction algorithm is presented. The fast general model-based approach is based on the approximately linear relation between the mean square of the aberration gradients and the second moment of far-field intensity distribution. The presented model-based method is capable of completing a mode aberration effective correction just applying one disturbing onto the deformable mirror(one correction by one disturbing), which is reconstructed by the singular value decomposing the correlation matrix of the Zernike functions' gradients. Numerical simulations of AO corrections under the various random and dynamic aberrations are implemented. The simulation results indicate that the equivalent control bandwidth is 2-3 times than that of the previous method with one aberration correction after applying N times disturbing onto the deformable mirror (one correction by N disturbing).

Iterated unscented Kalman filter for phase unwrapping of interferometric fringes.

PubMed

Xie, Xianming

2016-08-22

A fresh phase unwrapping algorithm based on iterated unscented Kalman filter is proposed to estimate unambiguous unwrapped phase of interferometric fringes. This method is the result of combining an iterated unscented Kalman filter with a robust phase gradient estimator based on amended matrix pencil model, and an efficient quality-guided strategy based on heap sort. The iterated unscented Kalman filter that is one of the most robust methods under the Bayesian theorem frame in non-linear signal processing so far, is applied to perform simultaneously noise suppression and phase unwrapping of interferometric fringes for the first time, which can simplify the complexity and the difficulty of pre-filtering procedure followed by phase unwrapping procedure, and even can remove the pre-filtering procedure. The robust phase gradient estimator is used to efficiently and accurately obtain phase gradient information from interferometric fringes, which is needed for the iterated unscented Kalman filtering phase unwrapping model. The efficient quality-guided strategy is able to ensure that the proposed method fast unwraps wrapped pixels along the path from the high-quality area to the low-quality area of wrapped phase images, which can greatly improve the efficiency of phase unwrapping. Results obtained from synthetic data and real data show that the proposed method can obtain better solutions with an acceptable time consumption, with respect to some of the most used algorithms.

Control Theory based Shape Design for the Incompressible Navier-Stokes Equations

NASA Astrophysics Data System (ADS)

Cowles, G.; Martinelli, L.

2003-12-01

A design method for shape optimization in incompressible turbulent viscous flow has been developed and validated for inverse design. The gradient information is determined using a control theory based algorithm. With such an approach, the cost of computing the gradient is negligible. An additional adjoint system must be solved which requires the cost of a single steady state flow solution. Thus, this method has an enormous advantage over traditional finite-difference based algorithms. The method of artificial compressibility is utilized to solve both the flow and adjoint systems. An algebraic turbulence model is used to compute the eddy viscosity. The method is validated using several inverse wing design test cases. In each case, the program must modify the shape of the initial wing such that its pressure distribution matches that of the target wing. Results are shown for the inversion of both finite thickness wings as well as zero thickness wings which can be considered a model of yacht sails.

Spiral trajectory design: a flexible numerical algorithm and base analytical equations.

PubMed

Pipe, James G; Zwart, Nicholas R

2014-01-01

Spiral-based trajectories for magnetic resonance imaging can be advantageous, but are often cumbersome to design or create. This work presents a flexible numerical algorithm for designing trajectories based on explicit definition of radial undersampling, and also gives several analytical expressions for charactering the base (critically sampled) class of these trajectories. Expressions for the gradient waveform, based on slew and amplitude limits, are developed such that a desired pitch in the spiral k-space trajectory is followed. The source code for this algorithm, written in C, is publicly available. Analytical expressions approximating the spiral trajectory (ignoring the radial component) are given to characterize measurement time, gradient heating, maximum gradient amplitude, and off-resonance phase for slew-limited and gradient amplitude-limited cases. Several numerically calculated trajectories are illustrated, and base Archimedean spirals are compared with analytically obtained results. Several different waveforms illustrate that the desired slew and amplitude limits are reached, as are the desired undersampling patterns, using the numerical method. For base Archimedean spirals, the results of the numerical and analytical approaches are in good agreement. A versatile numerical algorithm was developed, and was written in publicly available code. Approximate analytical formulas are given that help characterize spiral trajectories. Copyright © 2013 Wiley Periodicals, Inc.

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

NASA Technical Reports Server (NTRS)

Freund, Roland

1988-01-01

Conjugate gradient type methods are considered for the solution of large linear systems Ax = b with complex coefficient matrices of the type A = T + i(sigma)I where T is Hermitian and sigma, a real scalar. Three different conjugate gradient type approaches with iterates defined by a minimal residual property, a Galerkin type condition, and an Euclidian error minimization, respectively, are investigated. In particular, numerically stable implementations based on the ideas behind Paige and Saunder's SYMMLQ and MINRES for real symmetric matrices are proposed. Error bounds for all three methods are derived. It is shown how the special shift structure of A can be preserved by using polynomial preconditioning. Results on the optimal choice of the polynomial preconditioner are given. Also, some numerical experiments for matrices arising from finite difference approximations to the complex Helmholtz equation are reported.

Risk assessment of metals in road-deposited sediment along an urban-rural gradient.

PubMed

Zhao, Hongtao; Li, Xuyong

2013-03-01

We applied the traditional risk assessment methods originally designed for soils and river sediments to evaluation of risk associated with metals in road-deposited sediment (RDS) along an urban-rural gradient that included central urban (UCA), urban village (UVA), central suburban county (CSA), rural town (RTA), and rural village (RVA) areas in the Beijing metropolitan region. A new indicator RI(RDS) was developed which integrated the RDS characteristics of mobility, grain size and amount with the potential ecological risk index. The risk associated with metals in RDS in urban areas was generally higher than that in rural areas based on the assessment using traditional methods, but the risk was higher in urban and rural village areas than the areas with higher administration units based on the indicator RI(RDS). These findings implied that RDS characteristics variation with the urban-rural gradient must be considered in metal risk assessment and RDS washoff pollution control. Copyright © 2012 Elsevier Ltd. All rights reserved.

Image denoising based on noise detection

NASA Astrophysics Data System (ADS)

Jiang, Yuanxiang; Yuan, Rui; Sun, Yuqiu; Tian, Jinwen

2018-03-01

Because of the noise points in the images, any operation of denoising would change the original information of non-noise pixel. A noise detection algorithm based on fractional calculus was proposed to denoise in this paper. Convolution of the image was made to gain direction gradient masks firstly. Then, the mean gray was calculated to obtain the gradient detection maps. Logical product was made to acquire noise position image next. Comparisons in the visual effect and evaluation parameters after processing, the results of experiment showed that the denoising algorithms based on noise were better than that of traditional methods in both subjective and objective aspects.

Underwater optical communications using orbital angular momentum-based spatial division multiplexing

NASA Astrophysics Data System (ADS)

Willner, Alan E.; Zhao, Zhe; Ren, Yongxiong; Li, Long; Xie, Guodong; Song, Haoqian; Liu, Cong; Zhang, Runzhou; Bao, Changjing; Pang, Kai

2018-02-01

In this paper, we review high-capacity underwater optical communications using orbital angular momentum (OAM)-based spatial division multiplexing. We discuss methods to generate and detect blue-green optical data-carrying OAM beams as well as various underwater effects, including attenuation, scattering, current, and thermal gradients on OAM beams. Attention is also given to the system performance of high-capacity underwater optical communication links using OAM-based space division multiplexing. The paper closes with a discussion of a digital signal processing (DSP) algorithm to mitigate the inter-mode crosstalk caused by thermal gradients.

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

NASA Technical Reports Server (NTRS)

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

1985-01-01

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

Conjugate gradient heat bath for ill-conditioned actions.

PubMed

Ceriotti, Michele; Bussi, Giovanni; Parrinello, Michele

2007-08-01

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

Differential heating: A versatile method for thermal conductivity measurements in high-energy-density matter

DOE PAGES

Ping, Y.; Fernandez-Panella, A.; Sio, H.; ...

2015-09-04

We propose a method for thermal conductivity measurements of high energy density matter based on differential heating. A temperature gradient is created either by surface heating of one material or at an interface between two materials by different energy deposition. The subsequent heat conduction across the temperature gradient is observed by various time-resolved probing techniques. Conceptual designs of such measurements using laser heating, proton heating, and x-ray heating are presented. As a result, the sensitivity of the measurements to thermal conductivity is confirmed by simulations.

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

NASA Technical Reports Server (NTRS)

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

1984-01-01

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

Texture feature extraction based on a uniformity estimation method for local brightness and structure in chest CT images.

PubMed

Peng, Shao-Hu; Kim, Deok-Hwan; Lee, Seok-Lyong; Lim, Myung-Kwan

2010-01-01

Texture feature is one of most important feature analysis methods in the computer-aided diagnosis (CAD) systems for disease diagnosis. In this paper, we propose a Uniformity Estimation Method (UEM) for local brightness and structure to detect the pathological change in the chest CT images. Based on the characteristics of the chest CT images, we extract texture features by proposing an extension of rotation invariant LBP (ELBP(riu4)) and the gradient orientation difference so as to represent a uniform pattern of the brightness and structure in the image. The utilization of the ELBP(riu4) and the gradient orientation difference allows us to extract rotation invariant texture features in multiple directions. Beyond this, we propose to employ the integral image technique to speed up the texture feature computation of the spatial gray level dependent method (SGLDM). Copyright © 2010 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Spatial wavefield gradient-based seismic wavefield separation

NASA Astrophysics Data System (ADS)

Van Renterghem, C.; Schmelzbach, C.; Sollberger, D.; Robertsson, J. OA

2018-03-01

Measurements of the horizontal and vertical components of particle motion combined with estimates of the spatial gradients of the seismic wavefield enable seismic data to be acquired and processed using single dedicated multicomponent stations (e.g. rotational sensors) and/or small receiver groups instead of large receiver arrays. Here, we present seismic wavefield decomposition techniques that use spatial wavefield gradient data to separate land and ocean bottom data into their upgoing/downgoing and P/S constituents. Our method is based on the elastodynamic representation theorem with the derived filters requiring local measurements of the wavefield and its spatial gradients only. We demonstrate with synthetic data and a land seismic field data example that combining translational measurements with spatial wavefield gradient estimates allows separating seismic data recorded either at the Earth's free-surface or at the sea bottom into upgoing/downgoing and P/S wavefield constituents for typical incidence angle ranges of body waves. A key finding is that the filter application only requires knowledge of the elastic properties exactly at the recording locations and is valid for a wide elastic property range.

Improving the time efficiency of the Fourier synthesis method for slice selection in magnetic resonance imaging.

PubMed

Tahayori, B; Khaneja, N; Johnston, L A; Farrell, P M; Mareels, I M Y

2016-01-01

The design of slice selective pulses for magnetic resonance imaging can be cast as an optimal control problem. The Fourier synthesis method is an existing approach to solve these optimal control problems. In this method the gradient field as well as the excitation field are switched rapidly and their amplitudes are calculated based on a Fourier series expansion. Here, we provide a novel insight into the Fourier synthesis method via representing the Bloch equation in spherical coordinates. Based on the spherical Bloch equation, we propose an alternative sequence of pulses that can be used for slice selection which is more time efficient compared to the original method. Simulation results demonstrate that while the performance of both methods is approximately the same, the required time for the proposed sequence of pulses is half of the original sequence of pulses. Furthermore, the slice selectivity of both sequences of pulses changes with radio frequency field inhomogeneities in a similar way. We also introduce a measure, referred to as gradient complexity, to compare the performance of both sequences of pulses. This measure indicates that for a desired level of uniformity in the excited slice, the gradient complexity for the proposed sequence of pulses is less than the original sequence. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

New methods for the assessment of accommodative convergence.

PubMed

Asakawa, Ken; Ishikawa, Hitoshi; Shoji, Nobuyuki

2009-01-01

The authors introduced a new objective method for measuring horizontal eye movements based on the first Purkinje image with the use of infrared charge-coupled device (CCD) cameras and compared stimulus accommodative convergence to accommodation (AC/A) ratios as determined by a standard gradient method. The study included 20 patients, 5 to 9 years old, who had intermittent exotropia (10 eyes) and accommodative esotropia (10 eyes). Measurement of horizontal eye movements in millimeters (mm), based on the first Purkinje image, was obtained with a TriIRIS C9000 instrument (Hamamatsu Photonics K.K., Hamamatsu, Japan). The stimulus AC/A ratio was determined with the far gradient method. The average values of horizontal eye movements (mm) and eye deviation (Delta) (a) before and (b) after an accommodative stimulus of 3.00 diopters (D) were calculated with the following formula: horizontal eye movements (mm/D) and stimulus AC/A ratio (Delta/D) = (b - a)/3. The average values of the horizontal eye movements and the stimulus AC/A ratio were 0.5 mm/D and 3.8 Delta/D, respectively. Correlation analysis showed a strong positive correlation between these two parameters (r = 0.92). Moreover, horizontal eye movements are directly proportional to the AC/A ratio measured with the gradient method. The methods used in this study allow objective recordings of accommodative convergence to be obtained in many clinical situations. Copyright 2009, SLACK Incorporated.

Imputed forest structure uncertainty varies across elevational and longitudinal gradients in the western Cascade mountains, Oregon, USA

Treesearch

David M. Bell; Matthew J. Gregory; Janet L. Ohmann

2015-01-01

Imputation provides a useful method for mapping forest attributes across broad geographic areas based on field plot measurements and Landsat multi-spectral data, but the resulting map products may be of limited use without corresponding analyses of uncertainties in predictions. In the case of k-nearest neighbor (kNN) imputation with k = 1, such as the Gradient Nearest...

Gradient-based reliability maps for ACM-based segmentation of hippocampus.

PubMed

Zarpalas, Dimitrios; Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos

2014-04-01

Automatic segmentation of deep brain structures, such as the hippocampus (HC), in MR images has attracted considerable scientific attention due to the widespread use of MRI and to the principal role of some structures in various mental disorders. In this literature, there exists a substantial amount of work relying on deformable models incorporating prior knowledge about structures' anatomy and shape information. However, shape priors capture global shape characteristics and thus fail to model boundaries of varying properties; HC boundaries present rich, poor, and missing gradient regions. On top of that, shape prior knowledge is blended with image information in the evolution process, through global weighting of the two terms, again neglecting the spatially varying boundary properties, causing segmentation faults. An innovative method is hereby presented that aims to achieve highly accurate HC segmentation in MR images, based on the modeling of boundary properties at each anatomical location and the inclusion of appropriate image information for each of those, within an active contour model framework. Hence, blending of image information and prior knowledge is based on a local weighting map, which mixes gradient information, regional and whole brain statistical information with a multi-atlas-based spatial distribution map of the structure's labels. Experimental results on three different datasets demonstrate the efficacy and accuracy of the proposed method.

Localized, gradient-reversed ultrafast z-spectroscopy in vivo at 7T.

PubMed

Wilson, Neil E; D'Aquilla, Kevin; Debrosse, Catherine; Hariharan, Hari; Reddy, Ravinder

2016-10-01

To collect ultrafast z-spectra in vivo in situations where voxel homogeneity cannot be assured. Saturating in the presence of a gradient encodes the frequency offset spatially across a voxel. This encoding can be resolved by applying a similar gradient during readout. Acquiring additional scans with the gradient polarity reversed effectively mirrors the spatial locations of the frequency offsets so that the same physical location of a positive offset in the original scan will contribute a negative offset in the gradient-reversed scan. Gradient-reversed ultrafast z-spectroscopy (GRUFZS) was implemented and tested in a modified, localized PRESS sequence at 7T. Lysine phantoms were scanned at various concentrations and compared with coventionally-acquired z-spectra. Scans were acquired in vivo in human brain from homogeneous and inhomogeneous voxels with the ultrafast direction cycled between read, phase, and slice. Results were compared to those from a similar conventional z-spectroscopy PRESS-based sequence. Asymmetry spectra from GRUFZS are more consistent and reliable than those without gradient reversal and are comparable to those from conventional z-spectroscopy. GRUFZS offers significant acceleration in data acquisition compared to traditional chemical exchange saturation transfer methods with high spectral resolution and showed higher relative SNR effficiency. GRUFZS offers a method of collecting ultrafast z-spectra in voxels with the inhomogeneity often found in vivo. Magn Reson Med 76:1039-1046, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

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

PubMed Central

Reilly, John; Glisic, Branko

2018-01-01

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

Steering of aggregating magnetic microparticles using propulsion gradients coils in an MRI Scanner.

PubMed

Mathieu, Jean-Baptiste; Martel, Sylvain

2010-05-01

Upgraded gradient coils can effectively enhance the MRI steering of magnetic microparticles in a branching channel. Applications of this method include MRI targeting of magnetic embolization agents for oncologic therapy. A magnetic suspension of Fe(3)O(4) magnetic particles was injected inside a y-shaped microfluidic channel. Magnetic gradients of 0, 50, 100, 200, and 400 mT/m were applied to the magnetic particles perpendicularly to the flow by a custom-built gradient coil inside a 1.5-T MRI scanner. Measurement of the steering ratio was performed both by video analyses and quantification of the mass of the particles collected at each outlet of the microfluidic channel, using atomic absorption spectroscopy. Magnetic particles steering ratios of 0.99 and 0.75 were reached with 400 mT/m gradient amplitude and measured by video analyses and atomic absorption spectroscopy, respectively. Experimental data shows that the steering ratio increases with higher magnetic gradients. Moreover, theory suggests that larger particles (or aggregates), higher magnetizations, and lower flows can also be used to improve the steering ratio. The technological limitation of the approach is that an MRI gradient amplitude increase to a few hundred milliteslas per meter is needed. A simple analytical method based on magnetophoretic velocity predictions and geometric considerations is proposed for steering ratio calculation. (c) 2010 Wiley-Liss, Inc.

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

PubMed

Reilly, John; Glisic, Branko

2018-03-01

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

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.

Detection of acoustic waves by NMR using a radiofrequency field gradient

NASA Astrophysics Data System (ADS)

Madelin, Guillaume; Baril, Nathalie; Lewa, Czeslaw J.; Franconi, Jean-Michel; Canioni, Paul; Thiaudiére, Eric; de Certaines, Jacques D.

2003-03-01

A B1 field gradient-based method previously described for the detection of mechanical vibrations has been applied to detect oscillatory motions in condensed matter originated from acoustic waves. A ladder-shaped coil generating a quasi-constant RF-field gradient was associated with a motion-encoding NMR sequence consisting in a repetitive binomial 1 3¯3 1¯ RF pulse train (stroboscopic acquisition). The NMR response of a gel phantom subject to acoustic wave excitation in the 20-200 Hz range was investigated. Results showed a linear relationship between the NMR signal and the wave amplitude and a spectroscopic selectivity of the NMR sequence with respect to the input acoustic frequency. Spin displacements as short as a few tens of nanometers were able to be detected with this method.

Detection of acoustic waves by NMR using a radiofrequency field gradient.

PubMed

Madelin, Guillaume; Baril, Nathalie; Lewa, Czeslaw J; Franconi, Jean Michel; Canioni, Paul; Thiaudiére, Eric; de Certaines, Jacques D

2003-03-01

A B(1) field gradient-based method previously described for the detection of mechanical vibrations has been applied to detect oscillatory motions in condensed matter originated from acoustic waves. A ladder-shaped coil generating a quasi-constant RF-field gradient was associated with a motion-encoding NMR sequence consisting in a repetitive binomial 13;31; RF pulse train (stroboscopic acquisition). The NMR response of a gel phantom subject to acoustic wave excitation in the 20-200 Hz range was investigated. Results showed a linear relationship between the NMR signal and the wave amplitude and a spectroscopic selectivity of the NMR sequence with respect to the input acoustic frequency. Spin displacements as short as a few tens of nanometers were able to be detected with this method.

Quantitative DIC microscopy using an off-axis self-interference approach.

PubMed

Fu, Dan; Oh, Seungeun; Choi, Wonshik; Yamauchi, Toyohiko; Dorn, August; Yaqoob, Zahid; Dasari, Ramachandra R; Feld, Michael S

2010-07-15

Traditional Normarski differential interference contrast (DIC) microscopy is a very powerful method for imaging nonstained biological samples. However, one of its major limitations is the nonquantitative nature of the imaging. To overcome this problem, we developed a quantitative DIC microscopy method based on off-axis sample self-interference. The digital holography algorithm is applied to obtain quantitative phase gradients in orthogonal directions, which leads to a quantitative phase image through a spiral integration of the phase gradients. This method is practically simple to implement on any standard microscope without stringent requirements on polarization optics. Optical sectioning can be obtained through enlarged illumination NA.

A benchmark study of electronic excitation energies, transition moments, and excited-state energy gradients on the nicotine molecule

NASA Astrophysics Data System (ADS)

Egidi, Franco; Segado, Mireia; Koch, Henrik; Cappelli, Chiara; Barone, Vincenzo

2014-12-01

In this work, we report a comparative study of computed excitation energies, oscillator strengths, and excited-state energy gradients of (S)-nicotine, chosen as a test case, using multireference methods, coupled cluster singles and doubles, and methods based on time-dependent density functional theory. This system was chosen because its apparent simplicity hides a complex electronic structure, as several different types of valence excitations are possible, including n-π*, π-π*, and charge-transfer states, and in order to simulate its spectrum it is necessary to describe all of them consistently well by the chosen method.

A benchmark study of electronic excitation energies, transition moments, and excited-state energy gradients on the nicotine molecule

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

Egidi, Franco, E-mail: franco.egidi@sns.it; Segado, Mireia; Barone, Vincenzo, E-mail: vincenzo.barone@sns.it

In this work, we report a comparative study of computed excitation energies, oscillator strengths, and excited-state energy gradients of (S)-nicotine, chosen as a test case, using multireference methods, coupled cluster singles and doubles, and methods based on time-dependent density functional theory. This system was chosen because its apparent simplicity hides a complex electronic structure, as several different types of valence excitations are possible, including n-π{sup *}, π-π{sup *}, and charge-transfer states, and in order to simulate its spectrum it is necessary to describe all of them consistently well by the chosen method.

Correction of geometric distortion in Propeller echo planar imaging using a modified reversed gradient approach

PubMed Central

Chang, Hing-Chiu; Chuang, Tzu-Chao; Wang, Fu-Nien; Huang, Teng-Yi; Chung, Hsiao-Wen

2013-01-01

Objective This study investigates the application of a modified reversed gradient algorithm to the Propeller-EPI imaging method (periodically rotated overlapping parallel lines with enhanced reconstruction based on echo-planar imaging readout) for corrections of geometric distortions due to the EPI readout. Materials and methods Propeller-EPI acquisition was executed with 360-degree rotational coverage of the k-space, from which the image pairs with opposite phase-encoding gradient polarities were extracted for reversed gradient geometric and intensity corrections. The spatial displacements obtained on a pixel-by-pixel basis were fitted using a two-dimensional polynomial followed by low-pass filtering to assure correction reliability in low-signal regions. Single-shot EPI images were obtained on a phantom, whereas high spatial resolution T2-weighted and diffusion tensor Propeller-EPI data were acquired in vivo from healthy subjects at 3.0 Tesla, to demonstrate the effectiveness of the proposed algorithm. Results Phantom images show success of the smoothed displacement map concept in providing improvements of the geometric corrections at low-signal regions. Human brain images demonstrate prominently superior reconstruction quality of Propeller-EPI images with modified reversed gradient corrections as compared with those obtained without corrections, as evidenced from verification against the distortion-free fast spin-echo images at the same level. Conclusions The modified reversed gradient method is an effective approach to obtain high-resolution Propeller-EPI images with substantially reduced artifacts. PMID:23630654

Methodology of automated ionosphere front velocity estimation for ground-based augmentation of GNSS

NASA Astrophysics Data System (ADS)

Bang, Eugene; Lee, Jiyun

2013-11-01

ionospheric anomalies occurring during severe ionospheric storms can pose integrity threats to Global Navigation Satellite System (GNSS) Ground-Based Augmentation Systems (GBAS). Ionospheric anomaly threat models for each region of operation need to be developed to analyze the potential impact of these anomalies on GBAS users and develop mitigation strategies. Along with the magnitude of ionospheric gradients, the speed of the ionosphere "fronts" in which these gradients are embedded is an important parameter for simulation-based GBAS integrity analysis. This paper presents a methodology for automated ionosphere front velocity estimation which will be used to analyze a vast amount of ionospheric data, build ionospheric anomaly threat models for different regions, and monitor ionospheric anomalies continuously going forward. This procedure automatically selects stations that show a similar trend of ionospheric delays, computes the orientation of detected fronts using a three-station-based trigonometric method, and estimates speeds for the front using a two-station-based method. It also includes fine-tuning methods to improve the estimation to be robust against faulty measurements and modeling errors. It demonstrates the performance of the algorithm by comparing the results of automated speed estimation to those manually computed previously. All speed estimates from the automated algorithm fall within error bars of ± 30% of the manually computed speeds. In addition, this algorithm is used to populate the current threat space with newly generated threat points. A larger number of velocity estimates helps us to better understand the behavior of ionospheric gradients under geomagnetic storm conditions.

[Accurate 3D free-form registration between fan-beam CT and cone-beam CT].

PubMed

Liang, Yueqiang; Xu, Hongbing; Li, Baosheng; Li, Hongsheng; Yang, Fujun

2012-06-01

Because the X-ray scatters, the CT numbers in cone-beam CT cannot exactly correspond to the electron densities. This, therefore, results in registration error when the intensity-based registration algorithm is used to register planning fan-beam CT and cone-beam CT. In order to reduce the registration error, we have developed an accurate gradient-based registration algorithm. The gradient-based deformable registration problem is described as a minimization of energy functional. Through the calculus of variations and Gauss-Seidel finite difference method, we derived the iterative formula of the deformable registration. The algorithm was implemented by GPU through OpenCL framework, with which the registration time was greatly reduced. Our experimental results showed that the proposed gradient-based registration algorithm could register more accurately the clinical cone-beam CT and fan-beam CT images compared with the intensity-based algorithm. The GPU-accelerated algorithm meets the real-time requirement in the online adaptive radiotherapy.

Vibration of initially stressed carbon nanotubes under magneto-thermal environment for nanoparticle delivery via higher-order nonlocal strain gradient theory

NASA Astrophysics Data System (ADS)

Farajpour, M. R.; Shahidi, A. R.; Tabataba'i-Nasab, F.; Farajpour, A.

2018-06-01

In this paper, the forced vibration of a single-walled carbon nanotube (SWCNT) under a moving nanoparticle is investigated based on the higher-order nonlocal strain gradient theory. The SWCNT is subjected to thermo-mechanical stresses and an external longitudinal magnetic field. The influences of higher-order stress gradients in conjunction with the strain gradient nonlocality are taken into account. Using Hamilton's principle and Maxwell's equations, the higher-order differential equations of motion are derived. An analytical solution is obtained for the dynamic deflection of SWCNTs using the Galerkin method. Furthermore, the governing differential equation is solved numerically using the precise integration method. The results of the two solution procedures are compared and an excellent agreement is found between them. Finally, the influences of various scale parameters, the velocity of the moving nanoparticle, the initial axial stress, the temperature change and longitudinal magnetic field on the dynamic response of SWCNTs are investigated.

New methods for interpretation of magnetic vector and gradient tensor data I: eigenvector analysis and the normalised source strength

NASA Astrophysics Data System (ADS)

Clark, David A.

2012-09-01

Acquisition of magnetic gradient tensor data is likely to become routine in the near future. New methods for inverting gradient tensor surveys to obtain source parameters have been developed for several elementary, but useful, models. These include point dipole (sphere), vertical line of dipoles (narrow vertical pipe), line of dipoles (horizontal cylinder), thin dipping sheet, and contact models. A key simplification is the use of eigenvalues and associated eigenvectors of the tensor. The normalised source strength (NSS), calculated from the eigenvalues, is a particularly useful rotational invariant that peaks directly over 3D compact sources, 2D compact sources, thin sheets and contacts, and is independent of magnetisation direction. In combination the NSS and its vector gradient determine source locations uniquely. NSS analysis can be extended to other useful models, such as vertical pipes, by calculating eigenvalues of the vertical derivative of the gradient tensor. Inversion based on the vector gradient of the NSS over the Tallawang magnetite deposit obtained good agreement between the inferred geometry of the tabular magnetite skarn body and drill hole intersections. Besides the geological applications, the algorithms for the dipole model are readily applicable to the detection, location and characterisation (DLC) of magnetic objects, such as naval mines, unexploded ordnance, shipwrecks, archaeological artefacts, and buried drums.

Point-spread function reconstruction in ground-based astronomy by l(1)-l(p) model.

PubMed

Chan, Raymond H; Yuan, Xiaoming; Zhang, Wenxing

2012-11-01

In ground-based astronomy, images of objects in outer space are acquired via ground-based telescopes. However, the imaging system is generally interfered by atmospheric turbulence, and hence images so acquired are blurred with unknown point-spread function (PSF). To restore the observed images, the wavefront of light at the telescope's aperture is utilized to derive the PSF. A model with the Tikhonov regularization has been proposed to find the high-resolution phase gradients by solving a least-squares system. Here we propose the l(1)-l(p) (p=1, 2) model for reconstructing the phase gradients. This model can provide sharper edges in the gradients while removing noise. The minimization models can easily be solved by the Douglas-Rachford alternating direction method of a multiplier, and the convergence rate is readily established. Numerical results are given to illustrate that the model can give better phase gradients and hence a more accurate PSF. As a result, the restored images are much more accurate when compared to the traditional Tikhonov regularization model.

Estimates of recharge to unconfined aquifers and leakage to confined aquifers in the seven-county metropolitan area of Minneapolis-St. Paul, Minnesota

USGS Publications Warehouse

Ruhl, James F.; Kanivetsky, Roman; Shmagin, Boris

2002-01-01

Recharge estimates, which generally varied within 10 in./yr for each of the methods, generally were largest based on the precipitation, ground-water level fluctuation, and age dating of shallow ground water methods, slightly smaller based on the streamflow-recession displacement method, and smallest based on the watershed characteristics method. Leakage, which was less than 1 in./yr, varied within 1 order of magnitude based on the ground-water level fluctuation method and as much as 4 orders of magnitude based on analyses of vertical-hydraulic gradients.

Multiple velocity encoding in the phase of an MRI signal

NASA Astrophysics Data System (ADS)

Benitez-Read, E. E.

2017-01-01

The measurement of fluid velocity by encoding it in the phase of a magnetic resonance imaging (MRI) signal could allow the discrimination of the stationary spins signals from those of moving spins. This results in a wide variety of applications i.e. in medicine, in order to obtain more than angiograms, blood velocity images of veins, arteries and other vessels without having static tissue perturbing the signal of fluid in motion. The work presented in this paper is a theoretical analysis of some novel methods for multiple fluid velocity encoding in the phase of an MRI signal. These methods are based on a tripolar gradient (TPG) and can be an alternative to the conventional methods based on a bipolar gradient (BPG) and could be more suitable for multiple velocity encoding in the phase of an MRI signal.

Topology optimization of finite strain viscoplastic systems under transient loads

DOE PAGES

Ivarsson, Niklas; Wallin, Mathias; Tortorelli, Daniel

2018-02-08

In this paper, a transient finite strain viscoplastic model is implemented in a gradient-based topology optimization framework to design impact mitigating structures. The model's kinematics relies on the multiplicative split of the deformation gradient, and the constitutive response is based on isotropic hardening viscoplasticity. To solve the mechanical balance laws, the implicit Newmark-beta method is used together with a total Lagrangian finite element formulation. The optimization problem is regularized using a partial differential equation filter and solved using the method of moving asymptotes. Sensitivities required to solve the optimization problem are derived using the adjoint method. To demonstrate the capabilitymore » of the algorithm, several protective systems are designed, in which the absorbed viscoplastic energy is maximized. Finally, the numerical examples demonstrate that transient finite strain viscoplastic effects can successfully be combined with topology optimization.« less

Development, evaluation and application of a modified micrometeorological gradient method for long-term estimation of gaseous dry deposition over forest canopies.

EPA Science Inventory

Small pollutant concentration gradients between levels above a plant canopy result in large uncertainties in estimated air–surface exchange fluxes when using existing micrometeorological gradient methods, including the aerodynamic gradient method (AGM) and the modified Bowen rati...

Edge remap for solids

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

Kamm, James R.; Love, Edward; Robinson, Allen C.

We review the edge element formulation for describing the kinematics of hyperelastic solids. This approach is used to frame the problem of remapping the inverse deformation gradient for Arbitrary Lagrangian-Eulerian (ALE) simulations of solid dynamics. For hyperelastic materials, the stress state is completely determined by the deformation gradient, so remapping this quantity effectively updates the stress state of the material. A method, inspired by the constrained transport remap in electromagnetics, is reviewed, according to which the zero-curl constraint on the inverse deformation gradient is implicitly satisfied. Open issues related to the accuracy of this approach are identified. An optimization-based approachmore » is implemented to enforce positivity of the determinant of the deformation gradient. The efficacy of this approach is illustrated with numerical examples.« less

A unified tensor level set for image segmentation.

PubMed

Wang, Bin; Gao, Xinbo; Tao, Dacheng; Li, Xuelong

2010-06-01

This paper presents a new region-based unified tensor level set model for image segmentation. This model introduces a three-order tensor to comprehensively depict features of pixels, e.g., gray value and the local geometrical features, such as orientation and gradient, and then, by defining a weighted distance, we generalized the representative region-based level set method from scalar to tensor. The proposed model has four main advantages compared with the traditional representative method as follows. First, involving the Gaussian filter bank, the model is robust against noise, particularly the salt- and pepper-type noise. Second, considering the local geometrical features, e.g., orientation and gradient, the model pays more attention to boundaries and makes the evolving curve stop more easily at the boundary location. Third, due to the unified tensor pixel representation representing the pixels, the model segments images more accurately and naturally. Fourth, based on a weighted distance definition, the model possesses the capacity to cope with data varying from scalar to vector, then to high-order tensor. We apply the proposed method to synthetic, medical, and natural images, and the result suggests that the proposed method is superior to the available representative region-based level set method.

MRI brain tumor segmentation based on improved fuzzy c-means method

NASA Astrophysics Data System (ADS)

Deng, Wankai; Xiao, Wei; Pan, Chao; Liu, Jianguo

2009-10-01

This paper focuses on the image segmentation, which is one of the key problems in medical image processing. A new medical image segmentation method is proposed based on fuzzy c- means algorithm and spatial information. Firstly, we classify the image into the region of interest and background using fuzzy c means algorithm. Then we use the information of the tissues' gradient and the intensity inhomogeneities of regions to improve the quality of segmentation. The sum of the mean variance in the region and the reciprocal of the mean gradient along the edge of the region are chosen as an objective function. The minimum of the sum is optimum result. The result shows that the clustering segmentation algorithm is effective.

A chemometric-assisted method for the simultaneous determination of malachite green and crystal violet in water based on absorbance-pH data generated by a homemade pH gradient apparatus.

PubMed

Yu, Shuling; Yuan, Xuejie; Yang, Jing; Yuan, Jintao; Shi, Jiahua; Wang, Yali; Chen, Yuewen; Gao, Shufang

2015-01-01

An attractive method of generating second-order data was developed by a dropping technique to generate pH gradient simultaneously coupled with diode-array spectrophotometer scanning. A homemade apparatus designed for the pH gradient. The method and the homemade apparatus were used to simultaneously determine malachite green (MG) and crystal violet (CV) in water samples. The absorbance-pH second-order data of MG or CV were obtained from the spectra of MG or CV in a series of pH values of HCl-KCl solution. The second-order data of mixtures containing MG and CV that coexisted with interferents were analyzed using multidimensional partial least-squares with residual bilinearization. The method and homemade apparatus were used to simultaneously determine MG and CV in fish farming water samples and in river ones with satisfactory results. The presented method and the homemade apparatus could serve as an alternative tool to handle some analysis problems. Copyright © 2015 Elsevier B.V. All rights reserved.

Patellar segmentation from 3D magnetic resonance images using guided recursive ray-tracing for edge pattern detection

NASA Astrophysics Data System (ADS)

Cheng, Ruida; Jackson, Jennifer N.; McCreedy, Evan S.; Gandler, William; Eijkenboom, J. J. F. A.; van Middelkoop, M.; McAuliffe, Matthew J.; Sheehan, Frances T.

2016-03-01

The paper presents an automatic segmentation methodology for the patellar bone, based on 3D gradient recalled echo and gradient recalled echo with fat suppression magnetic resonance images. Constricted search space outlines are incorporated into recursive ray-tracing to segment the outer cortical bone. A statistical analysis based on the dependence of information in adjacent slices is used to limit the search in each image to between an outer and inner search region. A section based recursive ray-tracing mechanism is used to skip inner noise regions and detect the edge boundary. The proposed method achieves higher segmentation accuracy (0.23mm) than the current state-of-the-art methods with the average dice similarity coefficient of 96.0% (SD 1.3%) agreement between the auto-segmentation and ground truth surfaces.

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

USGS Publications Warehouse

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

1984-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

Comparison of genetic algorithms with conjugate gradient methods

NASA Technical Reports Server (NTRS)

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

1972-01-01

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

Multidisciplinary design optimization using genetic algorithms

NASA Technical Reports Server (NTRS)

Unal, Resit

1994-01-01

Multidisciplinary design optimization (MDO) is an important step in the conceptual design and evaluation of launch vehicles since it can have a significant impact on performance and life cycle cost. The objective is to search the system design space to determine values of design variables that optimize the performance characteristic subject to system constraints. Gradient-based optimization routines have been used extensively for aerospace design optimization. However, one limitation of gradient based optimizers is their need for gradient information. Therefore, design problems which include discrete variables can not be studied. Such problems are common in launch vehicle design. For example, the number of engines and material choices must be integer values or assume only a few discrete values. In this study, genetic algorithms are investigated as an approach to MDO problems involving discrete variables and discontinuous domains. Optimization by genetic algorithms (GA) uses a search procedure which is fundamentally different from those gradient based methods. Genetic algorithms seek to find good solutions in an efficient and timely manner rather than finding the best solution. GA are designed to mimic evolutionary selection. A population of candidate designs is evaluated at each iteration, and each individual's probability of reproduction (existence in the next generation) depends on its fitness value (related to the value of the objective function). Progress toward the optimum is achieved by the crossover and mutation operations. GA is attractive since it uses only objective function values in the search process, so gradient calculations are avoided. Hence, GA are able to deal with discrete variables. Studies report success in the use of GA for aircraft design optimization studies, trajectory analysis, space structure design and control systems design. In these studies reliable convergence was achieved, but the number of function evaluations was large compared with efficient gradient methods. Applicaiton of GA is underway for a cost optimization study for a launch-vehicle fuel-tank and structural design of a wing. The strengths and limitations of GA for launch vehicle design optimization is studied.

The effect of swim-up and gradient sperm preparation techniques on deoxyribonucleic acid (DNA) fragmentation in subfertile patients.

PubMed

Oguz, Yuksel; Guler, Ismail; Erdem, Ahmet; Mutlu, Mehmet Firat; Gumuslu, Seyhan; Oktem, Mesut; Bozkurt, Nuray; Erdem, Mehmet

2018-03-23

To compare the effect of two different sperm preparation techniques, including swim-up and gradient methods on sperm deoxyribonucleic acid (DNA) fragmentation status of semen samples from unexplained and mild male factor subfertile patients undergoing intrauterine insemination (IUI). A prospective randomized study was conducted in 65 subfertile patients, including 34 unexplained and 31 male factor infertility to compare basal and post-procedure DNA fragmentation rates in swim-up and gradient techniques. Sperm DNA fragmentation rates were evaluated by a sperm chromatin dispersion (SCD) test in two portions of each sample of semen that was prepared with either swim-up or gradient techniques. Sperm motility and morphology were also assessed based on WHO 2010 criteria. Swim-up but not gradient method yielded a statistically significant reduction in the DNA fragmented sperm rate after preparation as compared to basal rates, in the semen samples of both unexplained (41.85 ± 22.04 vs. 28.58 ± 21.93, p < 0.001 for swim-up; and 41.85 ± 22.04 vs. 38.79 ± 22.30, p = 0.160 for gradient) and mild male factor (46.61 ± 19.38 vs. 30.32 ± 18.20, p < 0.001 for swim-up and 46.61 ± 19.38 vs. 44.03 ± 20.87, p = 0.470 for gradient) subgroups. Swim-up method significantly reduces sperm DNA fragmentation rates and may have some prognostic value on intrauterine insemination in patients with decreased sperm DNA integrity.

A Class of Prediction-Correction Methods for Time-Varying Convex Optimization

NASA Astrophysics Data System (ADS)

Simonetto, Andrea; Mokhtari, Aryan; Koppel, Alec; Leus, Geert; Ribeiro, Alejandro

2016-09-01

This paper considers unconstrained convex optimization problems with time-varying objective functions. We propose algorithms with a discrete time-sampling scheme to find and track the solution trajectory based on prediction and correction steps, while sampling the problem data at a constant rate of $1/h$, where $h$ is the length of the sampling interval. The prediction step is derived by analyzing the iso-residual dynamics of the optimality conditions. The correction step adjusts for the distance between the current prediction and the optimizer at each time step, and consists either of one or multiple gradient steps or Newton steps, which respectively correspond to the gradient trajectory tracking (GTT) or Newton trajectory tracking (NTT) algorithms. Under suitable conditions, we establish that the asymptotic error incurred by both proposed methods behaves as $O(h^2)$, and in some cases as $O(h^4)$, which outperforms the state-of-the-art error bound of $O(h)$ for correction-only methods in the gradient-correction step. Moreover, when the characteristics of the objective function variation are not available, we propose approximate gradient and Newton tracking algorithms (AGT and ANT, respectively) that still attain these asymptotical error bounds. Numerical simulations demonstrate the practical utility of the proposed methods and that they improve upon existing techniques by several orders of magnitude.

Precise locating approach of the beacon based on gray gradient segmentation interpolation in satellite optical communications.

PubMed

Wang, Qiang; Liu, Yuefei; Chen, Yiqiang; Ma, Jing; Tan, Liying; Yu, Siyuan

2017-03-01

Accurate location computation for a beacon is an important factor of the reliability of satellite optical communications. However, location precision is generally limited by the resolution of CCD. How to improve the location precision of a beacon is an important and urgent issue. In this paper, we present two precise centroid computation methods for locating a beacon in satellite optical communications. First, in terms of its characteristics, the beacon is divided into several parts according to the gray gradients. Afterward, different numbers of interpolation points and different interpolation methods are applied in the interpolation area; we calculate the centroid position after interpolation and choose the best strategy according to the algorithm. The method is called a "gradient segmentation interpolation approach," or simply, a GSI (gradient segmentation interpolation) algorithm. To take full advantage of the pixels of the beacon's central portion, we also present an improved segmentation square weighting (SSW) algorithm, whose effectiveness is verified by the simulation experiment. Finally, an experiment is established to verify GSI and SSW algorithms. The results indicate that GSI and SSW algorithms can improve locating accuracy over that calculated by a traditional gray centroid method. These approaches help to greatly improve the location precision for a beacon in satellite optical communications.

Full waveform inversion in the frequency domain using classified time-domain residual wavefields

NASA Astrophysics Data System (ADS)

Son, Woohyun; Koo, Nam-Hyung; Kim, Byoung-Yeop; Lee, Ho-Young; Joo, Yonghwan

2017-04-01

We perform the acoustic full waveform inversion in the frequency domain using residual wavefields that have been separated in the time domain. We sort the residual wavefields in the time domain according to the order of absolute amplitudes. Then, the residual wavefields are separated into several groups in the time domain. To analyze the characteristics of the residual wavefields, we compare the residual wavefields of conventional method with those of our residual separation method. From the residual analysis, the amplitude spectrum obtained from the trace before separation appears to have little energy at the lower frequency bands. However, the amplitude spectrum obtained from our strategy is regularized by the separation process, which means that the low-frequency components are emphasized. Therefore, our method helps to emphasize low-frequency components of residual wavefields. Then, we generate the frequency-domain residual wavefields by taking the Fourier transform of the separated time-domain residual wavefields. With these wavefields, we perform the gradient-based full waveform inversion in the frequency domain using back-propagation technique. Through a comparison of gradient directions, we confirm that our separation method can better describe the sub-salt image than the conventional approach. The proposed method is tested on the SEG/EAGE salt-dome model. The inversion results show that our algorithm is better than the conventional gradient based waveform inversion in the frequency domain, especially for deeper parts of the velocity model.

Multi-Scale Modification of Metallic Implants With Pore Gradients, Polyelectrolytes and Their Indirect Monitoring In vivo

PubMed Central

Vrana, Nihal E.; Dupret-Bories, Agnes; Chaubaroux, Christophe; Rieger, Elisabeth; Debry, Christian; Vautier, Dominique; Metz-Boutigue, Marie-Helene; Lavalle, Philippe

2013-01-01

Metallic implants, especially titanium implants, are widely used in clinical applications. Tissue in-growth and integration to these implants in the tissues are important parameters for successful clinical outcomes. In order to improve tissue integration, porous metallic implants have being developed. Open porosity of metallic foams is very advantageous, since the pore areas can be functionalized without compromising the mechanical properties of the whole structure. Here we describe such modifications using porous titanium implants based on titanium microbeads. By using inherent physical properties such as hydrophobicity of titanium, it is possible to obtain hydrophobic pore gradients within microbead based metallic implants and at the same time to have a basement membrane mimic based on hydrophilic, natural polymers. 3D pore gradients are formed by synthetic polymers such as Poly-L-lactic acid (PLLA) by freeze-extraction method. 2D nanofibrillar surfaces are formed by using collagen/alginate followed by a crosslinking step with a natural crosslinker (genipin). This nanofibrillar film was built up by layer by layer (LbL) deposition method of the two oppositely charged molecules, collagen and alginate. Finally, an implant where different areas can accommodate different cell types, as this is necessary for many multicellular tissues, can be obtained. By, this way cellular movement in different directions by different cell types can be controlled. Such a system is described for the specific case of trachea regeneration, but it can be modified for other target organs. Analysis of cell migration and the possible methods for creating different pore gradients are elaborated. The next step in the analysis of such implants is their characterization after implantation. However, histological analysis of metallic implants is a long and cumbersome process, thus for monitoring host reaction to metallic implants in vivo an alternative method based on monitoring CGA and different blood proteins is also described. These methods can be used for developing in vitro custom-made migration and colonization tests and also be used for analysis of functionalized metallic implants in vivo without histology. PMID:23851618

Multi-scale modification of metallic implants with pore gradients, polyelectrolytes and their indirect monitoring in vivo.

PubMed

Vrana, Nihal E; Dupret-Bories, Agnes; Chaubaroux, Christophe; Rieger, Elisabeth; Debry, Christian; Vautier, Dominique; Metz-Boutigue, Marie-Helene; Lavalle, Philippe

2013-07-01

Metallic implants, especially titanium implants, are widely used in clinical applications. Tissue in-growth and integration to these implants in the tissues are important parameters for successful clinical outcomes. In order to improve tissue integration, porous metallic implants have being developed. Open porosity of metallic foams is very advantageous, since the pore areas can be functionalized without compromising the mechanical properties of the whole structure. Here we describe such modifications using porous titanium implants based on titanium microbeads. By using inherent physical properties such as hydrophobicity of titanium, it is possible to obtain hydrophobic pore gradients within microbead based metallic implants and at the same time to have a basement membrane mimic based on hydrophilic, natural polymers. 3D pore gradients are formed by synthetic polymers such as Poly-L-lactic acid (PLLA) by freeze-extraction method. 2D nanofibrillar surfaces are formed by using collagen/alginate followed by a crosslinking step with a natural crosslinker (genipin). This nanofibrillar film was built up by layer by layer (LbL) deposition method of the two oppositely charged molecules, collagen and alginate. Finally, an implant where different areas can accommodate different cell types, as this is necessary for many multicellular tissues, can be obtained. By, this way cellular movement in different directions by different cell types can be controlled. Such a system is described for the specific case of trachea regeneration, but it can be modified for other target organs. Analysis of cell migration and the possible methods for creating different pore gradients are elaborated. The next step in the analysis of such implants is their characterization after implantation. However, histological analysis of metallic implants is a long and cumbersome process, thus for monitoring host reaction to metallic implants in vivo an alternative method based on monitoring CGA and different blood proteins is also described. These methods can be used for developing in vitro custom-made migration and colonization tests and also be used for analysis of functionalized metallic implants in vivo without histology.

A straightforward method for measuring the range of apparent density of microplastics.

PubMed

Li, Lingyun; Li, Mengmeng; Deng, Hua; Cai, Li; Cai, Huiwen; Yan, Beizhan; Hu, Jun; Shi, Huahong

2018-10-15

Density of microplastics has been regarded as the primary property that affect the distribution and bioavailability of microplastics in the water column. For measuring the density of microplastis, we developed a simple and rapid method based on density gradient solutions. In this study, we tested four solvents to make the density gradient solutions, i.e., ethanol (0.8 g/cm 3 ), ultrapure water (1.0 g/cm 3 ), saturated NaI (1.8 g/cm 3 ) and ZnCl 2 (1.8 g/cm 3 ). Density of microplastics was measured via observing the float or sink status in the density gradient solutions. We found that density gradient solutions made from ZnCl 2 had a larger uncertainty in measuring density than that from NaI, most likely due to a higher surface tension of ZnCl 2 solution. Solutions made from ethanol, ultrapure water, and NaI showed consistent density results with listed densities of commercial products, indicating that these density gradient solutions were suitable for measuring microplastics with a density range of 0.8-1.8 g/cm 3 . Copyright © 2018 Elsevier B.V. All rights reserved.

Shaping and timing gradient pulses to reduce MRI acoustic noise.

PubMed

Segbers, Marcel; Rizzo Sierra, Carlos V; Duifhuis, Hendrikus; Hoogduin, Johannes M

2010-08-01

A method to reduce the acoustic noise generated by gradient systems in MRI has been recently proposed; such a method is based on the linear response theory. Since the physical cause of MRI acoustic noise is the time derivative of the gradient current, a common trapezoid current shape produces an acoustic gradient coil response mainly during the rising and falling edge. In the falling edge, the coil acoustic response presents a 180 degrees phase difference compared to the rising edge. Therefore, by varying the width of the trapezoid and keeping the ramps constant, it is possible to suppress one selected frequency and its higher harmonics. This value is matched to one of the prominent resonance frequencies of the gradient coil system. The idea of cancelling a single frequency is extended to a second frequency, using two successive trapezoid-shaped pulses presented at a selected interval. Overall sound pressure level reduction of 6 and 10 dB is found for the two trapezoid shapes and a single pulse shape, respectively. The acoustically optimized pulse shape proposed is additionally tested in a simulated echo planar imaging readout train, obtaining a sound pressure level reduction of 12 dB for the best case.

Mechanism of competitive grain growth in a curvilinear channel of crystal-sorter during the orientational solidification of nickel-based heat-resistant alloy

NASA Astrophysics Data System (ADS)

Monastyrskiy, V. P.; Pozdnyakov, A. N.; Ershov, M. Yu.; Monastyrskiy, A. V.

2017-07-01

Using numerical simulation in the ProCAST program complex, the conditions of the solidification of heat-resistant nickel alloy in curvilinear channels of a ceramic mold have been investigated. It has been shown that, in practically important cases, the vector of the temperature gradient is oriented along the axis of the curvilinear channel. In a spiral crystal selector, a cyclic change in the preferred direction of growth occurs because of the cyclic change in the direction of the vector of the temperature gradient. The fact that the vector of the temperature gradient is almost always directed along the axis of the curvilinear channel makes it possible to govern the orientation of the vector of the temperature gradient in space and, therefore, to obtain a grain with the preferred crystallographic orientation. Based on the results of this investigation, a method of the grain selection with a desired azimuthal orientation is proposed.

Gradient optimization and nonlinear control

NASA Technical Reports Server (NTRS)

Hasdorff, L.

1976-01-01

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

Reduced-Reference Quality Assessment Based on the Entropy of DWT Coefficients of Locally Weighted Gradient Magnitudes.

PubMed

Golestaneh, S Alireza; Karam, Lina

2016-08-24

Perceptual image quality assessment (IQA) attempts to use computational models to estimate the image quality in accordance with subjective evaluations. Reduced-reference (RR) image quality assessment (IQA) methods make use of partial information or features extracted from the reference image for estimating the quality of distorted images. Finding a balance between the number of RR features and accuracy of the estimated image quality is essential and important in IQA. In this paper we propose a training-free low-cost RRIQA method that requires a very small number of RR features (6 RR features). The proposed RRIQA algorithm is based on the discrete wavelet transform (DWT) of locally weighted gradient magnitudes.We apply human visual system's contrast sensitivity and neighborhood gradient information to weight the gradient magnitudes in a locally adaptive manner. The RR features are computed by measuring the entropy of each DWT subband, for each scale, and pooling the subband entropies along all orientations, resulting in L RR features (one average entropy per scale) for an L-level DWT. Extensive experiments performed on seven large-scale benchmark databases demonstrate that the proposed RRIQA method delivers highly competitive performance as compared to the state-of-the-art RRIQA models as well as full reference ones for both natural and texture images. The MATLAB source code of REDLOG and the evaluation results are publicly available online at https://http://lab.engineering.asu.edu/ivulab/software/redlog/.

Separation of foreground and background from light field using gradient information.

PubMed

Lee, Jae Young; Park, Rae-Hong

2017-02-01

Studies of computer vision or machine vision applications using a light field camera have been increasing in recent years. However, the abilities that the light field camera has are not fully used in these applications. In this paper, we propose a method for direct separation of foreground and background that uses the gradient information and can be used in various applications such as pre-processing. From an optical phenomenon whereby the bundles of rays from the background are flipped, we derive that the disparity sign of the background in the captured three-dimensional scene has the opposite disparity sign of the foreground. Using the majority-weighted voting algorithm based on the gradient information with the Lambertian assumption and the gradient constraint, the foreground and background can be separated at each pixel. In regard to pre-processing, the proposed method can be used for various applications such as occlusion and saliency detection, disparity estimation, and so on. Experimental results with the EPFL light field dataset and Stanford Lytro light field dataset show that the proposed method achieves better performance in terms of the occlusion detection, and thus can be effectively used in pre-processing for saliency detection and disparity estimation.

Representing Matrix Cracks Through Decomposition of the Deformation Gradient Tensor in Continuum Damage Mechanics Methods

NASA Technical Reports Server (NTRS)

Leone, Frank A., Jr.

2015-01-01

A method is presented to represent the large-deformation kinematics of intraply matrix cracks and delaminations in continuum damage mechanics (CDM) constitutive material models. The method involves the additive decomposition of the deformation gradient tensor into 'crack' and 'bulk material' components. The response of the intact bulk material is represented by a reduced deformation gradient tensor, and the opening of an embedded cohesive interface is represented by a normalized cohesive displacement-jump vector. The rotation of the embedded interface is tracked as the material deforms and as the crack opens. The distribution of the total local deformation between the bulk material and the cohesive interface components is determined by minimizing the difference between the cohesive stress and the bulk material stress projected onto the cohesive interface. The improvements to the accuracy of CDM models that incorporate the presented method over existing approaches are demonstrated for a single element subjected to simple shear deformation and for a finite element model of a unidirectional open-hole tension specimen. The material model is implemented as a VUMAT user subroutine for the Abaqus/Explicit finite element software. The presented deformation gradient decomposition method reduces the artificial load transfer across matrix cracks subjected to large shearing deformations, and avoids the spurious secondary failure modes that often occur in analyses based on conventional progressive damage models.

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

NASA Astrophysics Data System (ADS)

Paletou, F.; Anterrieu, E.

2009-12-01

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

A Robust Gradient Based Method for Building Extraction from LiDAR and Photogrammetric Imagery.

PubMed

Siddiqui, Fasahat Ullah; Teng, Shyh Wei; Awrangjeb, Mohammad; Lu, Guojun

2016-07-19

Existing automatic building extraction methods are not effective in extracting buildings which are small in size and have transparent roofs. The application of large area threshold prohibits detection of small buildings and the use of ground points in generating the building mask prevents detection of transparent buildings. In addition, the existing methods use numerous parameters to extract buildings in complex environments, e.g., hilly area and high vegetation. However, the empirical tuning of large number of parameters reduces the robustness of building extraction methods. This paper proposes a novel Gradient-based Building Extraction (GBE) method to address these limitations. The proposed method transforms the Light Detection And Ranging (LiDAR) height information into intensity image without interpolation of point heights and then analyses the gradient information in the image. Generally, building roof planes have a constant height change along the slope of a roof plane whereas trees have a random height change. With such an analysis, buildings of a greater range of sizes with a transparent or opaque roof can be extracted. In addition, a local colour matching approach is introduced as a post-processing stage to eliminate trees. This stage of our proposed method does not require any manual setting and all parameters are set automatically from the data. The other post processing stages including variance, point density and shadow elimination are also applied to verify the extracted buildings, where comparatively fewer empirically set parameters are used. The performance of the proposed GBE method is evaluated on two benchmark data sets by using the object and pixel based metrics (completeness, correctness and quality). Our experimental results show the effectiveness of the proposed method in eliminating trees, extracting buildings of all sizes, and extracting buildings with and without transparent roof. When compared with current state-of-the-art building extraction methods, the proposed method outperforms the existing methods in various evaluation metrics.

A Robust Gradient Based Method for Building Extraction from LiDAR and Photogrammetric Imagery

PubMed Central

Siddiqui, Fasahat Ullah; Teng, Shyh Wei; Awrangjeb, Mohammad; Lu, Guojun

2016-01-01

Existing automatic building extraction methods are not effective in extracting buildings which are small in size and have transparent roofs. The application of large area threshold prohibits detection of small buildings and the use of ground points in generating the building mask prevents detection of transparent buildings. In addition, the existing methods use numerous parameters to extract buildings in complex environments, e.g., hilly area and high vegetation. However, the empirical tuning of large number of parameters reduces the robustness of building extraction methods. This paper proposes a novel Gradient-based Building Extraction (GBE) method to address these limitations. The proposed method transforms the Light Detection And Ranging (LiDAR) height information into intensity image without interpolation of point heights and then analyses the gradient information in the image. Generally, building roof planes have a constant height change along the slope of a roof plane whereas trees have a random height change. With such an analysis, buildings of a greater range of sizes with a transparent or opaque roof can be extracted. In addition, a local colour matching approach is introduced as a post-processing stage to eliminate trees. This stage of our proposed method does not require any manual setting and all parameters are set automatically from the data. The other post processing stages including variance, point density and shadow elimination are also applied to verify the extracted buildings, where comparatively fewer empirically set parameters are used. The performance of the proposed GBE method is evaluated on two benchmark data sets by using the object and pixel based metrics (completeness, correctness and quality). Our experimental results show the effectiveness of the proposed method in eliminating trees, extracting buildings of all sizes, and extracting buildings with and without transparent roof. When compared with current state-of-the-art building extraction methods, the proposed method outperforms the existing methods in various evaluation metrics. PMID:27447631

Hybrid High-Order methods for finite deformations of hyperelastic materials

NASA Astrophysics Data System (ADS)

Abbas, Mickaël; Ern, Alexandre; Pignet, Nicolas

2018-01-01

We devise and evaluate numerically Hybrid High-Order (HHO) methods for hyperelastic materials undergoing finite deformations. The HHO methods use as discrete unknowns piecewise polynomials of order k≥1 on the mesh skeleton, together with cell-based polynomials that can be eliminated locally by static condensation. The discrete problem is written as the minimization of a broken nonlinear elastic energy where a local reconstruction of the displacement gradient is used. Two HHO methods are considered: a stabilized method where the gradient is reconstructed as a tensor-valued polynomial of order k and a stabilization is added to the discrete energy functional, and an unstabilized method which reconstructs a stable higher-order gradient and circumvents the need for stabilization. Both methods satisfy the principle of virtual work locally with equilibrated tractions. We present a numerical study of the two HHO methods on test cases with known solution and on more challenging three-dimensional test cases including finite deformations with strong shear layers and cavitating voids. We assess the computational efficiency of both methods, and we compare our results to those obtained with an industrial software using conforming finite elements and to results from the literature. The two HHO methods exhibit robust behavior in the quasi-incompressible regime.

Adjoint Algorithm for CAD-Based Shape Optimization Using a Cartesian Method

NASA Technical Reports Server (NTRS)

Nemec, Marian; Aftosmis, Michael J.

2004-01-01

Adjoint solutions of the governing flow equations are becoming increasingly important for the development of efficient analysis and optimization algorithms. A well-known use of the adjoint method is gradient-based shape optimization. Given an objective function that defines some measure of performance, such as the lift and drag functionals, its gradient is computed at a cost that is essentially independent of the number of design variables (geometric parameters that control the shape). More recently, emerging adjoint applications focus on the analysis problem, where the adjoint solution is used to drive mesh adaptation, as well as to provide estimates of functional error bounds and corrections. The attractive feature of this approach is that the mesh-adaptation procedure targets a specific functional, thereby localizing the mesh refinement and reducing computational cost. Our focus is on the development of adjoint-based optimization techniques for a Cartesian method with embedded boundaries.12 In contrast t o implementations on structured and unstructured grids, Cartesian methods decouple the surface discretization from the volume mesh. This feature makes Cartesian methods well suited for the automated analysis of complex geometry problems, and consequently a promising approach to aerodynamic optimization. Melvin et developed an adjoint formulation for the TRANAIR code, which is based on the full-potential equation with viscous corrections. More recently, Dadone and Grossman presented an adjoint formulation for the Euler equations. In both approaches, a boundary condition is introduced to approximate the effects of the evolving surface shape that results in accurate gradient computation. Central to automated shape optimization algorithms is the issue of geometry modeling and control. The need to optimize complex, "real-life" geometry provides a strong incentive for the use of parametric-CAD systems within the optimization procedure. In previous work, we presented an effective optimization framework that incorporates a direct-CAD interface. In this work, we enhance the capabilities of this framework with efficient gradient computations using the discrete adjoint method. We present details of the adjoint numerical implementation, which reuses the domain decomposition, multigrid, and time-marching schemes of the flow solver. Furthermore, we explain and demonstrate the use of CAD in conjunction with the Cartesian adjoint approach. The final paper will contain a number of complex geometry, industrially relevant examples with many design variables to demonstrate the effectiveness of the adjoint method on Cartesian meshes.

Investigation of 3D histograms of oriented gradients for image-based registration of CT with interventional CBCT

NASA Astrophysics Data System (ADS)

Trimborn, Barbara; Wolf, Ivo; Abu-Sammour, Denis; Henzler, Thomas; Schad, Lothar R.; Zöllner, Frank G.

2017-03-01

Image registration of preprocedural contrast-enhanced CTs to intraprocedual cone-beam computed tomography (CBCT) can provide additional information for interventional liver oncology procedures such as transcatheter arterial chemoembolisation (TACE). In this paper, a novel similarity metric for gradient-based image registration is proposed. The metric relies on the patch-based computation of histograms of oriented gradients (HOG) building the basis for a feature descriptor. The metric was implemented in a framework for rigid 3D-3D-registration of pre-interventional CT with intra-interventional CBCT data obtained during the workflow of a TACE. To evaluate the performance of the new metric, the capture range was estimated based on the calculation of the mean target registration error and compared to the results obtained with a normalized cross correlation metric. The results show that 3D HOG feature descriptors are suitable as image-similarity metric and that the novel metric can compete with established methods in terms of registration accuracy

Conjugate gradient coupled with multigrid for an indefinite problem

NASA Technical Reports Server (NTRS)

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

1984-01-01

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

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

PubMed

Feng, Shuo; Ji, Jim

2013-01-01

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

Thermally tailored gradient topography surface on elastomeric thin films.

PubMed

Roy, Sudeshna; Bhandaru, Nandini; Das, Ritopa; Harikrishnan, G; Mukherjee, Rabibrata

2014-05-14

We report a simple method for creating a nanopatterned surface with continuous variation in feature height on an elastomeric thin film. The technique is based on imprinting the surface of a film of thermo-curable elastomer (Sylgard 184), which has continuous variation in cross-linking density introduced by means of differential heating. This results in variation of viscoelasticity across the length of the surface and the film exhibits differential partial relaxation after imprinting with a flexible stamp and subjecting it to an externally applied stress for a transient duration. An intrinsic perfect negative replica of the stamp pattern is initially created over the entire film surface as long as the external force remains active. After the external force is withdrawn, there is partial relaxation of the applied stresses, which is manifested as reduction in amplitude of the imprinted features. Due to the spatial viscoelasticity gradient, the extent of stress relaxation induced feature height reduction varies across the length of the film (L), resulting in a surface with a gradient topography with progressively varying feature heights (hF). The steepness of the gradient can be controlled by varying the temperature gradient as well as the duration of precuring of the film prior to imprinting. The method has also been utilized for fabricating wettability gradient surfaces using a high aspect ratio biomimetic stamp. The use of a flexible stamp allows the technique to be extended for creating a gradient topography on nonplanar surfaces as well. We also show that the gradient surfaces with regular structures can be used in combinatorial studies related to pattern directed dewetting.

An efficient formulation and implementation of the analytic energy gradient method to the single and double excitation coupled-cluster wave function - Application to Cl2O2

NASA Technical Reports Server (NTRS)

Rendell, Alistair P.; Lee, Timothy J.

1991-01-01

The analytic energy gradient for the single and double excitation coupled-cluster (CCSD) wave function has been reformulated and implemented in a new set of programs. The reformulated set of gradient equations have a smaller computational cost than any previously published. The iterative solution of the linear equations and the construction of the effective density matrices are fully vectorized, being based on matrix multiplications. The new method has been used to investigate the Cl2O2 molecule, which has recently been postulated as an important intermediate in the destruction of ozone in the stratosphere. In addition to reporting computational timings, the CCSD equilibrium geometries, harmonic vibrational frequencies, infrared intensities, and relative energetics of three isomers of Cl2O2 are presented.

Multifidelity Analysis and Optimization for Supersonic Design

NASA Technical Reports Server (NTRS)

Kroo, Ilan; Willcox, Karen; March, Andrew; Haas, Alex; Rajnarayan, Dev; Kays, Cory

2010-01-01

Supersonic aircraft design is a computationally expensive optimization problem and multifidelity approaches over a significant opportunity to reduce design time and computational cost. This report presents tools developed to improve supersonic aircraft design capabilities including: aerodynamic tools for supersonic aircraft configurations; a systematic way to manage model uncertainty; and multifidelity model management concepts that incorporate uncertainty. The aerodynamic analysis tools developed are appropriate for use in a multifidelity optimization framework, and include four analysis routines to estimate the lift and drag of a supersonic airfoil, a multifidelity supersonic drag code that estimates the drag of aircraft configurations with three different methods: an area rule method, a panel method, and an Euler solver. In addition, five multifidelity optimization methods are developed, which include local and global methods as well as gradient-based and gradient-free techniques.

Model-based morphological segmentation and labeling of coronary angiograms.

PubMed

Haris, K; Efstratiadis, S N; Maglaveras, N; Pappas, C; Gourassas, J; Louridas, G

1999-10-01

A method for extraction and labeling of the coronary arterial tree (CAT) using minimal user supervision in single-view angiograms is proposed. The CAT structural description (skeleton and borders) is produced, along with quantitative information for the artery dimensions and assignment of coded labels, based on a given coronary artery model represented by a graph. The stages of the method are: 1) CAT tracking and detection; 2) artery skeleton and border estimation; 3) feature graph creation; and iv) artery labeling by graph matching. The approximate CAT centerline and borders are extracted by recursive tracking based on circular template analysis. The accurate skeleton and borders of each CAT segment are computed, based on morphological homotopy modification and watershed transform. The approximate centerline and borders are used for constructing the artery segment enclosing area (ASEA), where the defined skeleton and border curves are considered as markers. Using the marked ASEA, an artery gradient image is constructed where all the ASEA pixels (except the skeleton ones) are assigned the gradient magnitude of the original image. The artery gradient image markers are imposed as its unique regional minima by the homotopy modification method, the watershed transform is used for extracting the artery segment borders, and the feature graph is updated. Finally, given the created feature graph and the known model graph, a graph matching algorithm assigns the appropriate labels to the extracted CAT using weighted maximal cliques on the association graph corresponding to the two given graphs. Experimental results using clinical digitized coronary angiograms are presented.

A microfluidic multi-injector for gradient generation.

PubMed

Chung, Bong Geun; Lin, Francis; Jeon, Noo Li

2006-06-01

This paper describes a microfluidic multi-injector (MMI) that can generate temporal and spatial concentration gradients of soluble molecules. Compared to conventional glass micropipette-based methods that generate a single gradient, the MMI exploits microfluidic integration and actuation of multiple pulsatile injectors to generate arbitrary overlapping gradients that have not previously been possible. The MMI device is fabricated in poly(dimethylsiloxane) (PDMS) using multi-layer soft lithography and consists of fluidic channels and control channels with pneumatically actuated on-chip barrier valves. Repetitive actuation of on-chip valves control pulsatile release of solution that establishes microscopic chemical gradients around the orifice. The volume of solution released per actuation cycle ranged from 30 picolitres to several hundred picolitres and increased linearly with the duration of valve opening. The shape of the measured gradient profile agreed closely with the simulated diffusion profile from a point source. Steady state gradient profiles could be attained within 10 minutes, or less with an optimized pulse sequence. Overlapping gradients from 2 injectors were generated and characterized to highlight the advantages of MMI over conventional micropipette assays. The MMI platform should be useful for a wide range of basic and applied studies on chemotaxis and axon guidance.

Slab Geometry and Segmentation on Seismogenic Subduction Zone; Insight from gravity gradients

NASA Astrophysics Data System (ADS)

Saraswati, A. T.; Mazzotti, S.; Cattin, R.; Cadio, C.

2017-12-01

Slab geometry is a key parameter to improve seismic hazard assessment in subduction zones. In many cases, information about structures beneath subduction are obtained from geophysical dedicated studies, including geodetic and seismic measurements. However, due to the lack of global information, both geometry and segmentation in seismogenic zone of many subductions remain badly-constrained. Here we propose an alternative approach based on satellite gravity observations. The GOCE (Gravity field and steady-state Ocean Circulation Explorer) mission enables to probe Earth deep mass structures from gravity gradients, which are more sensitive to spatial structure geometry and directional properties than classical gravitational data. Gravity gradients forward modeling of modeled slab is performed by using horizontal and vertical gravity gradient components to better determine slab geophysical model rather than vertical gradient only. Using polyhedron method, topography correction on gravity gradient signal is undertaken to enhance the anomaly signal of lithospheric structures. Afterward, we compare residual gravity gradients with the calculated signals associated with slab geometry. In this preliminary study, straightforward models are used to better understand the characteristic of gravity gradient signals due to deep mass sources. We pay a special attention to the delineation of slab borders and dip angle variations.

Analytic energy gradients for the coupled-cluster singles and doubles method with the density-fitting approximation

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

Bozkaya, Uğur, E-mail: ugur.bozkaya@hacettepe.edu.tr; Department of Chemistry, Atatürk University, Erzurum 25240; Sherrill, C. David

2016-05-07

An efficient implementation is presented for analytic gradients of the coupled-cluster singles and doubles (CCSD) method with the density-fitting approximation, denoted DF-CCSD. Frozen core terms are also included. When applied to a set of alkanes, the DF-CCSD analytic gradients are significantly accelerated compared to conventional CCSD for larger molecules. The efficiency of our DF-CCSD algorithm arises from the acceleration of several different terms, which are designated as the “gradient terms”: computation of particle density matrices (PDMs), generalized Fock-matrix (GFM), solution of the Z-vector equation, formation of the relaxed PDMs and GFM, back-transformation of PDMs and GFM to the atomic orbitalmore » (AO) basis, and evaluation of gradients in the AO basis. For the largest member of the alkane set (C{sub 10}H{sub 22}), the computational times for the gradient terms (with the cc-pVTZ basis set) are 2582.6 (CCSD) and 310.7 (DF-CCSD) min, respectively, a speed up of more than 8-folds. For gradient related terms, the DF approach avoids the usage of four-index electron repulsion integrals. Based on our previous study [U. Bozkaya, J. Chem. Phys. 141, 124108 (2014)], our formalism completely avoids construction or storage of the 4-index two-particle density matrix (TPDM), using instead 2- and 3-index TPDMs. The DF approach introduces negligible errors for equilibrium bond lengths and harmonic vibrational frequencies.« less

Solving traveling salesman problems with DNA molecules encoding numerical values.

PubMed

Lee, Ji Youn; Shin, Soo-Yong; Park, Tai Hyun; Zhang, Byoung-Tak

2004-12-01

We introduce a DNA encoding method to represent numerical values and a biased molecular algorithm based on the thermodynamic properties of DNA. DNA strands are designed to encode real values by variation of their melting temperatures. The thermodynamic properties of DNA are used for effective local search of optimal solutions using biochemical techniques, such as denaturation temperature gradient polymerase chain reaction and temperature gradient gel electrophoresis. The proposed method was successfully applied to the traveling salesman problem, an instance of optimization problems on weighted graphs. This work extends the capability of DNA computing to solving numerical optimization problems, which is contrasted with other DNA computing methods focusing on logical problem solving.

QMR: A Quasi-Minimal Residual method for non-Hermitian linear systems

NASA Technical Reports Server (NTRS)

Freund, Roland W.; Nachtigal, Noel M.

1990-01-01

The biconjugate gradient (BCG) method is the natural generalization of the classical conjugate gradient algorithm for Hermitian positive definite matrices to general non-Hermitian linear systems. Unfortunately, the original BCG algorithm is susceptible to possible breakdowns and numerical instabilities. A novel BCG like approach is presented called the quasi-minimal residual (QMR) method, which overcomes the problems of BCG. An implementation of QMR based on a look-ahead version of the nonsymmetric Lanczos algorithm is proposed. It is shown how BCG iterates can be recovered stably from the QMR process. Some further properties of the QMR approach are given and an error bound is presented. Finally, numerical experiments are reported.

Universal field matching in craniospinal irradiation by a background-dose gradient-optimized method.

PubMed

Traneus, Erik; Bizzocchi, Nicola; Fellin, Francesco; Rombi, Barbara; Farace, Paolo

2018-01-01

The gradient-optimized methods are overcoming the traditional feathering methods to plan field junctions in craniospinal irradiation. In this note, a new gradient-optimized technique, based on the use of a background dose, is described. Treatment planning was performed by RayStation (RaySearch Laboratories, Stockholm, Sweden) on the CT scans of a pediatric patient. Both proton (by pencil beam scanning) and photon (by volumetric modulated arc therapy) treatments were planned with three isocenters. An 'in silico' ideal background dose was created first to cover the upper-spinal target and to produce a perfect dose gradient along the upper and lower junction regions. Using it as background, the cranial and the lower-spinal beams were planned by inverse optimization to obtain dose coverage of their relevant targets and of the junction volumes. Finally, the upper-spinal beam was inversely planned after removal of the background dose and with the previously optimized beams switched on. In both proton and photon plans, the optimized cranial and the lower-spinal beams produced a perfect linear gradient in the junction regions, complementary to that produced by the optimized upper-spinal beam. The final dose distributions showed a homogeneous coverage of the targets. Our simple technique allowed to obtain high-quality gradients in the junction region. Such technique universally works for photons as well as protons and could be applicable to the TPSs that allow to manage a background dose. © 2017 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Magnetic separation of algae

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

Nath, Pulak; Twary, Scott N.

Described herein are methods and systems for harvesting, collecting, separating and/or dewatering algae using iron based salts combined with a magnetic field gradient to separate algae from an aqueous solution.

Phase gradient imaging for positive contrast generation to superparamagnetic iron oxide nanoparticle-labeled targets in magnetic resonance imaging.

PubMed

Zhu, Haitao; Demachi, Kazuyuki; Sekino, Masaki

2011-09-01

Positive contrast imaging methods produce enhanced signal at large magnetic field gradient in magnetic resonance imaging. Several postprocessing algorithms, such as susceptibility gradient mapping and phase gradient mapping methods, have been applied for positive contrast generation to detect the cells targeted by superparamagnetic iron oxide nanoparticles. In the phase gradient mapping methods, smoothness condition has to be satisfied to keep the phase gradient unwrapped. Moreover, there has been no discussion about the truncation artifact associated with the algorithm of differentiation that is performed in k-space by the multiplication with frequency value. In this work, phase gradient methods are discussed by considering the wrapping problem when the smoothness condition is not satisfied. A region-growing unwrapping algorithm is used in the phase gradient image to solve the problem. In order to reduce the truncation artifact, a cosine function is multiplied in the k-space to eliminate the abrupt change at the boundaries. Simulation, phantom and in vivo experimental results demonstrate that the modified phase gradient mapping methods may produce improved positive contrast effects by reducing truncation or wrapping artifacts. Copyright © 2011 Elsevier Inc. All rights reserved.

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory

PubMed Central

Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM. PMID:29391864

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory.

PubMed

Yang, Haimin; Pan, Zhisong; Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.

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

PubMed

Chang, Joshua; Paydarfar, David

2014-12-01

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

Compensated geothermal gradient: new map of old data

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

Ibrahim, M.W.

1986-05-01

Bottom-hole temperature measurement is one of the oldest forms of downhole information acquired by the oil industry. Old and new geothermal maps that are based on these measurements have invariably been drawn with an assumed constant or average ground surface temperature over the mapped areas. However, near ground-surface equilibrium temperature is a variable rather than a constant over any region; therefore, old and current geothermal gradient mapping methods give a false impression of the true thermal level of subsurface strata, and may lead to erroneous results of temperature-based calculations, such as the TTI. In this paper, a geothermal mapping methodmore » is presented in which extrapolated surface temperature is coupled with the corresponding geothermal gradient over the mapped area. The method was tested on areas in the Middle East and Africa. Results indicate that it is especially effective in delineating loci of vertical geothermal heat flux carried upwards by ascending subsurface fluids; such areas are preferential sites for hydrocarbon entrapment, especially in young sedimentary basins where migration is still in progress.« less

Blind retrospective motion correction of MR images.

PubMed

Loktyushin, Alexander; Nickisch, Hannes; Pohmann, Rolf; Schölkopf, Bernhard

2013-12-01

Subject motion can severely degrade MR images. A retrospective motion correction algorithm, Gradient-based motion correction, which significantly reduces ghosting and blurring artifacts due to subject motion was proposed. The technique uses the raw data of standard imaging sequences; no sequence modifications or additional equipment such as tracking devices are required. Rigid motion is assumed. The approach iteratively searches for the motion trajectory yielding the sharpest image as measured by the entropy of spatial gradients. The vast space of motion parameters is efficiently explored by gradient-based optimization with a convergence guarantee. The method has been evaluated on both synthetic and real data in two and three dimensions using standard imaging techniques. MR images are consistently improved over different kinds of motion trajectories. Using a graphics processing unit implementation, computation times are in the order of a few minutes for a full three-dimensional volume. The presented technique can be an alternative or a complement to prospective motion correction methods and is able to improve images with strong motion artifacts from standard imaging sequences without requiring additional data. Copyright © 2013 Wiley Periodicals, Inc., a Wiley company.

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.

Multiple-Point Temperature Gradient Algorithm for Ring Laser Gyroscope Bias Compensation

PubMed Central

Li, Geng; Zhang, Pengfei; Wei, Guo; Xie, Yuanping; Yu, Xudong; Long, Xingwu

2015-01-01

To further improve ring laser gyroscope (RLG) bias stability, a multiple-point temperature gradient algorithm is proposed for RLG bias compensation in this paper. Based on the multiple-point temperature measurement system, a complete thermo-image of the RLG block is developed. Combined with the multiple-point temperature gradients between different points of the RLG block, the particle swarm optimization algorithm is used to tune the support vector machine (SVM) parameters, and an optimized design for selecting the thermometer locations is also discussed. The experimental results validate the superiority of the introduced method and enhance the precision and generalizability in the RLG bias compensation model. PMID:26633401

Photometric correction for an optical CCD-based system based on the sparsity of an eight-neighborhood gray gradient.

PubMed

Zhang, Yuzhong; Zhang, Yan

2016-07-01

In an optical measurement and analysis system based on a CCD, due to the existence of optical vignetting and natural vignetting, photometric distortion, in which the intensity falls off away from the image center, affects the subsequent processing and measuring precision severely. To deal with this problem, an easy and straightforward method used for photometric distortion correction is presented in this paper. This method introduces a simple polynomial fitting model of the photometric distortion function and employs a particle swarm optimization algorithm to get these model parameters by means of a minimizing eight-neighborhood gray gradient. Compared with conventional calibration methods, this method can obtain the profile information of photometric distortion from only a single common image captured by the optical CCD-based system, with no need for a uniform luminance area source used as a standard reference source and relevant optical and geometric parameters in advance. To illustrate the applicability of this method, numerical simulations and photometric distortions with different lens parameters are evaluated using this method in this paper. Moreover, the application example of temperature field correction for casting billets also demonstrates the effectiveness of this method. The experimental results show that the proposed method is able to achieve the maximum absolute error for vignetting estimation of 0.0765 and the relative error for vignetting estimation from different background images of 3.86%.

Systematic interpolation method predicts protein chromatographic elution with salt gradients, pH gradients and combined salt/pH gradients.

PubMed

Creasy, Arch; Barker, Gregory; Carta, Giorgio

2017-03-01

A methodology is presented to predict protein elution behavior from an ion exchange column using both individual or combined pH and salt gradients based on high-throughput batch isotherm data. The buffer compositions are first optimized to generate linear pH gradients from pH 5.5 to 7 with defined concentrations of sodium chloride. Next, high-throughput batch isotherm data are collected for a monoclonal antibody on the cation exchange resin POROS XS over a range of protein concentrations, salt concentrations, and solution pH. Finally, a previously developed empirical interpolation (EI) method is extended to describe protein binding as a function of the protein and salt concentration and solution pH without using an explicit isotherm model. The interpolated isotherm data are then used with a lumped kinetic model to predict the protein elution behavior. Experimental results obtained for laboratory scale columns show excellent agreement with the predicted elution curves for both individual or combined pH and salt gradients at protein loads up to 45 mg/mL of column. Numerical studies show that the model predictions are robust as long as the isotherm data cover the range of mobile phase compositions where the protein actually elutes from the column. Copyright © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Correction of geometric distortion in Propeller echo planar imaging using a modified reversed gradient approach.

PubMed

Chang, Hing-Chiu; Chuang, Tzu-Chao; Lin, Yi-Ru; Wang, Fu-Nien; Huang, Teng-Yi; Chung, Hsiao-Wen

2013-04-01

This study investigates the application of a modified reversed gradient algorithm to the Propeller-EPI imaging method (periodically rotated overlapping parallel lines with enhanced reconstruction based on echo-planar imaging readout) for corrections of geometric distortions due to the EPI readout. Propeller-EPI acquisition was executed with 360-degree rotational coverage of the k-space, from which the image pairs with opposite phase-encoding gradient polarities were extracted for reversed gradient geometric and intensity corrections. The spatial displacements obtained on a pixel-by-pixel basis were fitted using a two-dimensional polynomial followed by low-pass filtering to assure correction reliability in low-signal regions. Single-shot EPI images were obtained on a phantom, whereas high spatial resolution T2-weighted and diffusion tensor Propeller-EPI data were acquired in vivo from healthy subjects at 3.0 Tesla, to demonstrate the effectiveness of the proposed algorithm. Phantom images show success of the smoothed displacement map concept in providing improvements of the geometric corrections at low-signal regions. Human brain images demonstrate prominently superior reconstruction quality of Propeller-EPI images with modified reversed gradient corrections as compared with those obtained without corrections, as evidenced from verification against the distortion-free fast spin-echo images at the same level. The modified reversed gradient method is an effective approach to obtain high-resolution Propeller-EPI images with substantially reduced artifacts.

A method for real-time implementation of HOG feature extraction

NASA Astrophysics Data System (ADS)

Luo, Hai-bo; Yu, Xin-rong; Liu, Hong-mei; Ding, Qing-hai

2011-08-01

Histogram of oriented gradient (HOG) is an efficient feature extraction scheme, and HOG descriptors are feature descriptors which is widely used in computer vision and image processing for the purpose of biometrics, target tracking, automatic target detection(ATD) and automatic target recognition(ATR) etc. However, computation of HOG feature extraction is unsuitable for hardware implementation since it includes complicated operations. In this paper, the optimal design method and theory frame for real-time HOG feature extraction based on FPGA were proposed. The main principle is as follows: firstly, the parallel gradient computing unit circuit based on parallel pipeline structure was designed. Secondly, the calculation of arctangent and square root operation was simplified. Finally, a histogram generator based on parallel pipeline structure was designed to calculate the histogram of each sub-region. Experimental results showed that the HOG extraction can be implemented in a pixel period by these computing units.

Strategies and Applications for Incorporating Physical and Chemical Signal Gradients in Tissue Engineering

PubMed Central

Singh, Milind; Berkland, Cory

2008-01-01

From embryonic development to wound repair, concentration gradients of bioactive signaling molecules guide tissue formation and regeneration. Moreover, gradients in cellular and extracellular architecture as well as in mechanical properties are readily apparent in native tissues. Perhaps tissue engineers can take a cue from nature in attempting to regenerate tissues by incorporating gradients into engineering design strategies. Indeed, gradient-based approaches are an emerging trend in tissue engineering, standing in contrast to traditional approaches of homogeneous delivery of cells and/or growth factors using isotropic scaffolds. Gradients in tissue engineering lie at the intersection of three major paradigms in the field—biomimetic, interfacial, and functional tissue engineering—by combining physical (via biomaterial design) and chemical (with growth/differentiation factors and cell adhesion molecules) signal delivery to achieve a continuous transition in both structure and function. This review consolidates several key methodologies to generate gradients, some of which have never been employed in a tissue engineering application, and discusses strategies for incorporating these methods into tissue engineering and implant design. A key finding of this review was that two-dimensional physicochemical gradient substrates, which serve as excellent high-throughput screening tools for optimizing desired biomaterial properties, can be enhanced in the future by transitioning from two dimensions to three dimensions, which would enable studies of cell–protein–biomaterial interactions in a more native tissue–like environment. In addition, biomimetic tissue regeneration via combined delivery of graded physical and chemical signals appears to be a promising strategy for the regeneration of heterogeneous tissues and tissue interfaces. In the future, in vivo applications will shed more light on the performance of gradient-based mechanical integrity and signal delivery strategies compared to traditional tissue engineering approaches. PMID:18803499

Strategies and applications for incorporating physical and chemical signal gradients in tissue engineering.

PubMed

Singh, Milind; Berkland, Cory; Detamore, Michael S

2008-12-01

From embryonic development to wound repair, concentration gradients of bioactive signaling molecules guide tissue formation and regeneration. Moreover, gradients in cellular and extracellular architecture as well as in mechanical properties are readily apparent in native tissues. Perhaps tissue engineers can take a cue from nature in attempting to regenerate tissues by incorporating gradients into engineering design strategies. Indeed, gradient-based approaches are an emerging trend in tissue engineering, standing in contrast to traditional approaches of homogeneous delivery of cells and/or growth factors using isotropic scaffolds. Gradients in tissue engineering lie at the intersection of three major paradigms in the field-biomimetic, interfacial, and functional tissue engineering-by combining physical (via biomaterial design) and chemical (with growth/differentiation factors and cell adhesion molecules) signal delivery to achieve a continuous transition in both structure and function. This review consolidates several key methodologies to generate gradients, some of which have never been employed in a tissue engineering application, and discusses strategies for incorporating these methods into tissue engineering and implant design. A key finding of this review was that two-dimensional physicochemical gradient substrates, which serve as excellent high-throughput screening tools for optimizing desired biomaterial properties, can be enhanced in the future by transitioning from two dimensions to three dimensions, which would enable studies of cell-protein-biomaterial interactions in a more native tissue-like environment. In addition, biomimetic tissue regeneration via combined delivery of graded physical and chemical signals appears to be a promising strategy for the regeneration of heterogeneous tissues and tissue interfaces. In the future, in vivo applications will shed more light on the performance of gradient-based mechanical integrity and signal delivery strategies compared to traditional tissue engineering approaches.

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

Li, Xiao-Dong; Park, Changbom; Forero-Romero, J. E.

We propose a method based on the redshift dependence of the Alcock-Paczynski (AP) test to measure the expansion history of the universe. It uses the isotropy of the galaxy density gradient field to constrain cosmological parameters. If the density parameter Ω {sub m} or the dark energy equation of state w are incorrectly chosen, the gradient field appears to be anisotropic with the degree of anisotropy varying with redshift. We use this effect to constrain the cosmological parameters governing the expansion history of the universe. Although redshift-space distortions (RSD) induced by galaxy peculiar velocities also produce anisotropies in the gradientmore » field, these effects are close to uniform in magnitude over a large range of redshift. This makes the redshift variation of the gradient field anisotropy relatively insensitive to the RSD. By testing the method on mock surveys drawn from the Horizon Run 3 cosmological N-body simulations, we demonstrate that the cosmological parameters can be estimated without bias. Our method is complementary to the baryon acoustic oscillation or topology methods as it depends on D{sub AH} , the product of the angular diameter distance and the Hubble parameter.« less

Nonlinear optimization with linear constraints using a projection method

NASA Technical Reports Server (NTRS)

Fox, T.

1982-01-01

Nonlinear optimization problems that are encountered in science and industry are examined. A method of projecting the gradient vector onto a set of linear contraints is developed, and a program that uses this method is presented. The algorithm that generates this projection matrix is based on the Gram-Schmidt method and overcomes some of the objections to the Rosen projection method.

A PDE Sensitivity Equation Method for Optimal Aerodynamic Design

NASA Technical Reports Server (NTRS)

Borggaard, Jeff; Burns, John

1996-01-01

The use of gradient based optimization algorithms in inverse design is well established as a practical approach to aerodynamic design. A typical procedure uses a simulation scheme to evaluate the objective function (from the approximate states) and its gradient, then passes this information to an optimization algorithm. Once the simulation scheme (CFD flow solver) has been selected and used to provide approximate function evaluations, there are several possible approaches to the problem of computing gradients. One popular method is to differentiate the simulation scheme and compute design sensitivities that are then used to obtain gradients. Although this black-box approach has many advantages in shape optimization problems, one must compute mesh sensitivities in order to compute the design sensitivity. In this paper, we present an alternative approach using the PDE sensitivity equation to develop algorithms for computing gradients. This approach has the advantage that mesh sensitivities need not be computed. Moreover, when it is possible to use the CFD scheme for both the forward problem and the sensitivity equation, then there are computational advantages. An apparent disadvantage of this approach is that it does not always produce consistent derivatives. However, for a proper combination of discretization schemes, one can show asymptotic consistency under mesh refinement, which is often sufficient to guarantee convergence of the optimal design algorithm. In particular, we show that when asymptotically consistent schemes are combined with a trust-region optimization algorithm, the resulting optimal design method converges. We denote this approach as the sensitivity equation method. The sensitivity equation method is presented, convergence results are given and the approach is illustrated on two optimal design problems involving shocks.

A NEW HPLC METHOD FOR SEPARATION OF PHYTOPLANKTON PIGMENTS IN NATURAL SAMPLES

EPA Science Inventory

A new high-performance liquid chromatographic (HPLC) method was developed to analyze, in a single run, most polar and non-polar chlorophylls and carotenoids from marine phytoplankton. The method is based on a reverse-phase amide C16 (RP-amide C16) column and an elution gradient o...

A validated stability-indicating UPLC method for desloratadine and its impurities in pharmaceutical dosage forms.

PubMed

Rao, Dantu Durga; Satyanarayana, N V; Malleswara Reddy, A; Sait, Shakil S; Chakole, Dinesh; Mukkanti, K

2010-02-05

A novel stability-indicating gradient reverse phase ultra-performance liquid chromatographic (RP-UPLC) method was developed for the determination of purity of desloratadine in presence of its impurities and forced degradation products. The method was developed using Waters Aquity BEH C18 column with mobile phase containing a gradient mixture of solvents A and B. The eluted compounds were monitored at 280nm. The run time was 8min within which desloratadine and its five impurities were well separated. Desloratadine was subjected to the stress conditions of oxidative, acid, base, hydrolytic, thermal and photolytic degradation. Desloratadine was found to degrade significantly in oxidative and thermal stress conditions and stable in acid, base, hydrolytic and photolytic degradation conditions. The degradation products were well resolved from main peak and its impurities, thus proved the stability-indicating power of the method. The developed method was validated as per ICH guidelines with respect to specificity, linearity, limit of detection, limit of quantification, accuracy, precision and robustness. This method was also suitable for the assay determination of desloratadine in pharmaceutical dosage forms.

Evaluation of extreme ionospheric total electron content gradient associated with plasma bubbles for GNSS Ground-Based Augmentation System

NASA Astrophysics Data System (ADS)

Saito, S.; Yoshihara, T.

2017-08-01

Associated with plasma bubbles, extreme spatial gradients in ionospheric total electron content (TEC) were observed on 8 April 2008 at Ishigaki (24.3°N, 124.2°E, +19.6° magnetic latitude), Japan. The largest gradient was 3.38 TECU km-1 (total electron content unit, 1 TECU = 1016 el m-2), which is equivalent to an ionospheric delay gradient of 540 mm km-1 at the GPS L1 frequency (1.57542 GHz). This value is confirmed by using multiple estimating methods. The observed value exceeds the maximum ionospheric gradient that has ever been observed (412 mm km-1 or 2.59 TECU km-1) to be associated with a severe magnetic storm. It also exceeds the assumed maximum value (500 mm km-1 or 3.08 TECU km-1) which was used to validate the draft international standard for Global Navigation Satellite System (GNSS) Ground-Based Augmentation Systems (GBAS) to support Category II/III approaches and landings. The steepest part of this extreme gradient had a scale size of 5.3 km, and the front-normal velocities were estimated to be 71 m s-1 with a wavefront-normal direction of east-northeastward. The total width of the transition region from outside to inside the plasma bubble was estimated to be 35.3 km. The gradient of relatively small spatial scale size may fall between an aircraft and a GBAS ground subsystem and may be undetectable by both aircraft and ground.

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

PubMed

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

2014-09-01

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

Large scale micro-photometry for high resolution pH-characterization during electro-osmotic pumping and modular micro-swimming

NASA Astrophysics Data System (ADS)

Niu, Ran; Khodorov, Stanislav; Weber, Julian; Reinmüller, Alexander; Palberg, Thomas

2017-11-01

Micro-fluidic pumps as well as artificial micro-swimmers are conveniently realized exploiting phoretic solvent flows based on local gradients of temperature, electrolyte concentration or pH. We here present a facile micro-photometric method for monitoring pH gradients and demonstrate its performance and scope on different experimental situations including an electro-osmotic pump and modular micro-swimmers assembled from ion exchange resin beads and polystyrene colloids. In combination with the present microscope and DSLR camera our method offers a 2 μm spatial resolution at video frame rate over a field of view of 3920 × 2602 μm2. Under optimal conditions we achieve a pH-resolution of 0.05 with about equal contributions from statistical and systematical uncertainties. Our quantitative micro-photometric characterization of pH gradients which develop in time and reach out several mm is anticipated to provide valuable input for reliable modeling and simulations of a large variety of complex flow situations involving pH-gradients including artificial micro-swimmers, microfluidic pumping or even electro-convection.

Mixed finite-element formulations in piezoelectricity and flexoelectricity

PubMed Central

2016-01-01

Flexoelectricity, the linear coupling of strain gradient and electric polarization, is inherently a size-dependent phenomenon. The energy storage function for a flexoelectric material depends not only on polarization and strain, but also strain-gradient. Thus, conventional finite-element methods formulated solely on displacement are inadequate to treat flexoelectric solids since gradients raise the order of the governing differential equations. Here, we introduce a computational framework based on a mixed formulation developed previously by one of the present authors and a colleague. This formulation uses displacement and displacement-gradient as separate variables which are constrained in a ‘weighted integral sense’ to enforce their known relation. We derive a variational formulation for boundary-value problems for piezo- and/or flexoelectric solids. We validate this computational framework against available exact solutions. Our new computational method is applied to more complex problems, including a plate with an elliptical hole, stationary cracks, as well as tension and shear of solids with a repeating unit cell. Our results address several issues of theoretical interest, generate predictions of experimental merit and reveal interesting flexoelectric phenomena with potential for application. PMID:27436967

Mixed finite-element formulations in piezoelectricity and flexoelectricity.

PubMed

Mao, Sheng; Purohit, Prashant K; Aravas, Nikolaos

2016-06-01

Flexoelectricity, the linear coupling of strain gradient and electric polarization, is inherently a size-dependent phenomenon. The energy storage function for a flexoelectric material depends not only on polarization and strain, but also strain-gradient. Thus, conventional finite-element methods formulated solely on displacement are inadequate to treat flexoelectric solids since gradients raise the order of the governing differential equations. Here, we introduce a computational framework based on a mixed formulation developed previously by one of the present authors and a colleague. This formulation uses displacement and displacement-gradient as separate variables which are constrained in a 'weighted integral sense' to enforce their known relation. We derive a variational formulation for boundary-value problems for piezo- and/or flexoelectric solids. We validate this computational framework against available exact solutions. Our new computational method is applied to more complex problems, including a plate with an elliptical hole, stationary cracks, as well as tension and shear of solids with a repeating unit cell. Our results address several issues of theoretical interest, generate predictions of experimental merit and reveal interesting flexoelectric phenomena with potential for application.

Micromorphic approach for gradient-extended thermo-elastic-plastic solids in the logarithmic strain space

NASA Astrophysics Data System (ADS)

Aldakheel, Fadi

2017-11-01

The coupled thermo-mechanical strain gradient plasticity theory that accounts for microstructure-based size effects is outlined within this work. It extends the recent work of Miehe et al. (Comput Methods Appl Mech Eng 268:704-734, 2014) to account for thermal effects at finite strains. From the computational viewpoint, the finite element design of the coupled problem is not straightforward and requires additional strategies due to the difficulties near the elastic-plastic boundaries. To simplify the finite element formulation, we extend it toward the micromorphic approach to gradient thermo-plasticity model in the logarithmic strain space. The key point is the introduction of dual local-global field variables via a penalty method, where only the global fields are restricted by boundary conditions. Hence, the problem of restricting the gradient variable to the plastic domain is relaxed, which makes the formulation very attractive for finite element implementation as discussed in Forest (J Eng Mech 135:117-131, 2009) and Miehe et al. (Philos Trans R Soc A Math Phys Eng Sci 374:20150170, 2016).

Gravity gradient preprocessing at the GOCE HPF

NASA Astrophysics Data System (ADS)

Bouman, J.; Rispens, S.; Gruber, T.; Schrama, E.; Visser, P.; Tscherning, C. C.; Veicherts, M.

2009-04-01

One of the products derived from the GOCE observations are the gravity gradients. These gravity gradients are provided in the Gradiometer Reference Frame (GRF) and are calibrated in-flight using satellite shaking and star sensor data. In order to use these gravity gradients for application in Earth sciences and gravity field analysis, additional pre-processing needs to be done, including corrections for temporal gravity field signals to isolate the static gravity field part, screening for outliers, calibration by comparison with existing external gravity field information and error assessment. The temporal gravity gradient corrections consist of tidal and non-tidal corrections. These are all generally below the gravity gradient error level, which is predicted to show a 1/f behaviour for low frequencies. In the outlier detection the 1/f error is compensated for by subtracting a local median from the data, while the data error is assessed using the median absolute deviation. The local median acts as a high-pass filter and it is robust as is the median absolute deviation. Three different methods have been implemented for the calibration of the gravity gradients. All three methods use a high-pass filter to compensate for the 1/f gravity gradient error. The baseline method uses state-of-the-art global gravity field models and the most accurate results are obtained if star sensor misalignments are estimated along with the calibration parameters. A second calibration method uses GOCE GPS data to estimate a low degree gravity field model as well as gravity gradient scale factors. Both methods allow to estimate gravity gradient scale factors down to the 10-3 level. The third calibration method uses high accurate terrestrial gravity data in selected regions to validate the gravity gradient scale factors, focussing on the measurement band. Gravity gradient scale factors may be estimated down to the 10-2 level with this method.

Preprocessing of gravity gradients at the GOCE high-level processing facility

NASA Astrophysics Data System (ADS)

Bouman, Johannes; Rispens, Sietse; Gruber, Thomas; Koop, Radboud; Schrama, Ernst; Visser, Pieter; Tscherning, Carl Christian; Veicherts, Martin

2009-07-01

One of the products derived from the gravity field and steady-state ocean circulation explorer (GOCE) observations are the gravity gradients. These gravity gradients are provided in the gradiometer reference frame (GRF) and are calibrated in-flight using satellite shaking and star sensor data. To use these gravity gradients for application in Earth scienes and gravity field analysis, additional preprocessing needs to be done, including corrections for temporal gravity field signals to isolate the static gravity field part, screening for outliers, calibration by comparison with existing external gravity field information and error assessment. The temporal gravity gradient corrections consist of tidal and nontidal corrections. These are all generally below the gravity gradient error level, which is predicted to show a 1/ f behaviour for low frequencies. In the outlier detection, the 1/ f error is compensated for by subtracting a local median from the data, while the data error is assessed using the median absolute deviation. The local median acts as a high-pass filter and it is robust as is the median absolute deviation. Three different methods have been implemented for the calibration of the gravity gradients. All three methods use a high-pass filter to compensate for the 1/ f gravity gradient error. The baseline method uses state-of-the-art global gravity field models and the most accurate results are obtained if star sensor misalignments are estimated along with the calibration parameters. A second calibration method uses GOCE GPS data to estimate a low-degree gravity field model as well as gravity gradient scale factors. Both methods allow to estimate gravity gradient scale factors down to the 10-3 level. The third calibration method uses high accurate terrestrial gravity data in selected regions to validate the gravity gradient scale factors, focussing on the measurement band. Gravity gradient scale factors may be estimated down to the 10-2 level with this method.

A New Artificial Neural Network Enhanced by the Shuffled Complex Evolution Optimization with Principal Component Analysis (SP-UCI) for Water Resources Management

NASA Astrophysics Data System (ADS)

Hayatbini, N.; Faridzad, M.; Yang, T.; Akbari Asanjan, A.; Gao, X.; Sorooshian, S.

2016-12-01

The Artificial Neural Networks (ANNs) are useful in many fields, including water resources engineering and management. However, due to the non-linear and chaotic characteristics associated with natural processes and human decision making, the use of ANNs in real-world applications is still limited, and its performance needs to be further improved for a broader practical use. The commonly used Back-Propagation (BP) scheme and gradient-based optimization in training the ANNs have already found to be problematic in some cases. The BP scheme and gradient-based optimization methods are associated with the risk of premature convergence, stuck in local optimums, and the searching is highly dependent on initial conditions. Therefore, as an alternative to BP and gradient-based searching scheme, we propose an effective and efficient global searching method, termed the Shuffled Complex Evolutionary Global optimization algorithm with Principal Component Analysis (SP-UCI), to train the ANN connectivity weights. Large number of real-world datasets are tested with the SP-UCI-based ANN, as well as various popular Evolutionary Algorithms (EAs)-enhanced ANNs, i.e., Particle Swarm Optimization (PSO)-, Genetic Algorithm (GA)-, Simulated Annealing (SA)-, and Differential Evolution (DE)-enhanced ANNs. Results show that SP-UCI-enhanced ANN is generally superior over other EA-enhanced ANNs with regard to the convergence and computational performance. In addition, we carried out a case study for hydropower scheduling in the Trinity Lake in the western U.S. In this case study, multiple climate indices are used as predictors for the SP-UCI-enhanced ANN. The reservoir inflows and hydropower releases are predicted up to sub-seasonal to seasonal scale. Results show that SP-UCI-enhanced ANN is able to achieve better statistics than other EAs-based ANN, which implies the usefulness and powerfulness of proposed SP-UCI-enhanced ANN for reservoir operation, water resources engineering and management. The SP-UCI-enhanced ANN is universally applicable to many other regression and prediction problems, and it has a good potential to be an alternative to the classical BP scheme and gradient-based optimization methods.

Rapid analysis of charge variants of monoclonal antibodies using non-linear salt gradient in cation-exchange high performance liquid chromatography.

PubMed

Joshi, Varsha; Kumar, Vijesh; Rathore, Anurag S

2015-08-07

A method is proposed for rapid development of a short, analytical cation exchange high performance liquid chromatography method for analysis of charge heterogeneity in monoclonal antibody products. The parameters investigated and optimized include pH, shape of elution gradient and length of the column. It is found that the most important parameter for development of a shorter method is the choice of the shape of elution gradient. In this paper, we propose a step by step approach to develop a non-linear sigmoidal shape gradient for analysis of charge heterogeneity for two different monoclonal antibody products. The use of this gradient not only decreases the run time of the method to 4min against the conventional method that takes more than 40min but also the resolution is retained. Superiority of the phosphate gradient over sodium chloride gradient for elution of mAbs is also observed. The method has been successfully evaluated for specificity, sensitivity, linearity, limit of detection, and limit of quantification. Application of this method as a potential at-line process analytical technology tool has been suggested. Copyright © 2015 Elsevier B.V. All rights reserved.

Automatic lesion boundary detection in dermoscopy images using gradient vector flow snakes

PubMed Central

Erkol, Bulent; Moss, Randy H.; Stanley, R. Joe; Stoecker, William V.; Hvatum, Erik

2011-01-01

Background Malignant melanoma has a good prognosis if treated early. Dermoscopy images of pigmented lesions are most commonly taken at × 10 magnification under lighting at a low angle of incidence while the skin is immersed in oil under a glass plate. Accurate skin lesion segmentation from the background skin is important because some of the features anticipated to be used for diagnosis deal with shape of the lesion and others deal with the color of the lesion compared with the color of the surrounding skin. Methods In this research, gradient vector flow (GVF) snakes are investigated to find the border of skin lesions in dermoscopy images. An automatic initialization method is introduced to make the skin lesion border determination process fully automated. Results Skin lesion segmentation results are presented for 70 benign and 30 melanoma skin lesion images for the GVF-based method and a color histogram analysis technique. The average errors obtained by the GVF-based method are lower for both the benign and melanoma image sets than for the color histogram analysis technique based on comparison with manually segmented lesions determined by a dermatologist. Conclusions The experimental results for the GVF-based method demonstrate promise as an automated technique for skin lesion segmentation in dermoscopy images. PMID:15691255

Discontinuous Skeletal Gradient Discretisation methods on polytopal meshes

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

Di Pietro, Daniele A.; Droniou, Jérôme; Manzini, Gianmarco

Here, in this work we develop arbitrary-order Discontinuous Skeletal Gradient Discretisations (DSGD) on general polytopal meshes. Discontinuous Skeletal refers to the fact that the globally coupled unknowns are broken polynomials on the mesh skeleton. The key ingredient is a high-order gradient reconstruction composed of two terms: (i) a consistent contribution obtained mimicking an integration by parts formula inside each element and (ii) a stabilising term for which sufficient design conditions are provided. An example of stabilisation that satisfies the design conditions is proposed based on a local lifting of high-order residuals on a Raviart–Thomas–Nédélec subspace. We prove that the novelmore » DSGDs satisfy coercivity, consistency, limit-conformity, and compactness requirements that ensure convergence for a variety of elliptic and parabolic problems. Lastly, links with Hybrid High-Order, non-conforming Mimetic Finite Difference and non-conforming Virtual Element methods are also studied. Numerical examples complete the exposition.« less

2D data-space cross-gradient joint inversion of MT, gravity and magnetic data

NASA Astrophysics Data System (ADS)

Pak, Yong-Chol; Li, Tonglin; Kim, Gang-Sop

2017-08-01

We have developed a data-space multiple cross-gradient joint inversion algorithm, and validated it through synthetic tests and applied it to magnetotelluric (MT), gravity and magnetic datasets acquired along a 95 km profile in Benxi-Ji'an area of northeastern China. To begin, we discuss a generalized cross-gradient joint inversion for multiple datasets and model parameters sets, and formulate it in data space. The Lagrange multiplier required for the structural coupling in the data-space method is determined using an iterative solver to avoid calculation of the inverse matrix in solving the large system of equations. Next, using model-space and data-space methods, we inverted the synthetic data and field data. Based on our result, the joint inversion in data-space not only delineates geological bodies more clearly than the separate inversion, but also yields nearly equal results with the one in model-space while consuming much less memory.

Discontinuous Skeletal Gradient Discretisation methods on polytopal meshes

DOE PAGES

Di Pietro, Daniele A.; Droniou, Jérôme; Manzini, Gianmarco

2017-11-21

Here, in this work we develop arbitrary-order Discontinuous Skeletal Gradient Discretisations (DSGD) on general polytopal meshes. Discontinuous Skeletal refers to the fact that the globally coupled unknowns are broken polynomials on the mesh skeleton. The key ingredient is a high-order gradient reconstruction composed of two terms: (i) a consistent contribution obtained mimicking an integration by parts formula inside each element and (ii) a stabilising term for which sufficient design conditions are provided. An example of stabilisation that satisfies the design conditions is proposed based on a local lifting of high-order residuals on a Raviart–Thomas–Nédélec subspace. We prove that the novelmore » DSGDs satisfy coercivity, consistency, limit-conformity, and compactness requirements that ensure convergence for a variety of elliptic and parabolic problems. Lastly, links with Hybrid High-Order, non-conforming Mimetic Finite Difference and non-conforming Virtual Element methods are also studied. Numerical examples complete the exposition.« less

A biconjugate gradient type algorithm on massively parallel architectures

NASA Technical Reports Server (NTRS)

Freund, Roland W.; Hochbruck, Marlis

1991-01-01

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

Hardware architecture design of a fast global motion estimation method

NASA Astrophysics Data System (ADS)

Liang, Chaobing; Sang, Hongshi; Shen, Xubang

2015-12-01

VLSI implementation of gradient-based global motion estimation (GME) faces two main challenges: irregular data access and high off-chip memory bandwidth requirement. We previously proposed a fast GME method that reduces computational complexity by choosing certain number of small patches containing corners and using them in a gradient-based framework. A hardware architecture is designed to implement this method and further reduce off-chip memory bandwidth requirement. On-chip memories are used to store coordinates of the corners and template patches, while the Gaussian pyramids of both the template and reference frame are stored in off-chip SDRAMs. By performing geometric transform only on the coordinates of the center pixel of a 3-by-3 patch in the template image, a 5-by-5 area containing the warped 3-by-3 patch in the reference image is extracted from the SDRAMs by burst read. Patched-based and burst mode data access helps to keep the off-chip memory bandwidth requirement at the minimum. Although patch size varies at different pyramid level, all patches are processed in term of 3x3 patches, so the utilization of the patch-processing circuit reaches 100%. FPGA implementation results show that the design utilizes 24,080 bits on-chip memory and for a sequence with resolution of 352x288 and frequency of 60Hz, the off-chip bandwidth requirement is only 3.96Mbyte/s, compared with 243.84Mbyte/s of the original gradient-based GME method. This design can be used in applications like video codec, video stabilization, and super-resolution, where real-time GME is a necessity and minimum memory bandwidth requirement is appreciated.

Isolation and purification of rabbit mesenchymal stem cells using an optimized protocol.

PubMed

Lin, Chunbo; Shen, Maorong; Chen, Weiping; Li, Xiaofeng; Luo, Daoming; Cai, Jinhong; Yang, Yuan

2015-11-01

Mesenchymal stem cells were first isolated and grown in vitro by Friedenstein over 40 yr ago; however, their isolation remains challenging as they lack unique markers for identification and are present in very small quantities in mesenchymal tissues and bone marrow. Using whole marrow samples, common methods for mesenchymal stem cell isolation are the adhesion method and density gradient fractionation. The whole marrow sample adhesion method still results in the nonspecific isolation of mononuclear cells, and activation and/or potential loss of target cells. Density gradient fractionation methods are complicated, and may result in contamination with toxic substances that affect cell viability. In the present study, we developed an optimized protocol for the isolation and purification of mesenchymal stem cells based on the principles of hypotonic lysis and natural sedimentation.

Fractionation of Saprolegnia diclina (Oomycetes) satelite DNAs by AgNO3/Cs2SO4 density gradient centrifugation.

PubMed

Neish, G A; Green, B R

1977-12-14

Saprolegnia diclina DNA has been fractionated using preparative AgNO3/Cs2SO4 and CsCl density gradients. In addition to the previously identified major satellite DNA, there are two minor DNA components banding at 1.682 and 1.701 g - cm(-3) in CsCl. Purified major satellite DNA bands at 1.707 g - cm(-3) giving a base composition of 48% G + C in good agreement with 47% G + C calculated from its Tm value. The nuclear DNA base composition is 58% G + C by both methods. The base composition of the major satellite DNA suggests that it may represent ribosomal DNA cistrons.

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

PubMed

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

2006-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-06-01

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

Nondestructive testing and characterization of residual stress field using an ultrasonic method

NASA Astrophysics Data System (ADS)

Song, Wentao; Xu, Chunguang; Pan, Qinxue; Song, Jianfeng

2016-03-01

To address the difficulty in testing and calibrating the stress gradient in the depth direction of mechanical components, a new technology of nondestructive testing and characterization of the residual stress gradient field by ultrasonic method is proposed based on acoustoelasticity theory. By carrying out theoretical analysis, the sensitivity coefficients of different types of ultrasonic are obtained by taking the low carbon steel(12%C) as a research object. By fixing the interval distance between sending and receiving transducers, the mathematical expressions of the change of stress and the variation of time are established. To design one sending-one receiving and oblique incidence ultrasonic detection probes, according to Snell law, the critically refracted longitudinal wave (LCR wave) is excited at a certain depth of the fixed distance of the tested components. Then, the relationship between the depth of LCR wave detection and the center frequency of the probe in Q235 steel is obtained through experimental study. To detect the stress gradient in the depth direction, a stress gradient LCR wave detection model is established, through which the stress gradient formula is derived by the relationship between center frequency and detecting depth. A C-shaped stress specimen of Q235 steel is designed to conduct stress loading tests, and the stress is measured with the five group probes at different center frequencies. The accuracy of ultrasonic testing is verified by X-ray stress analyzer. The stress value of each specific depth is calculated using the stress gradient formula. Accordingly, the ultrasonic characterization of residual stress field is realized. Characterization results show that the stress gradient distribution is consistent with the simulation in ANSYS. The new technology can be widely applied in the detection of the residual stress gradient field caused by mechanical processing, such as welding and shot peening.

Methods of harmonic synthesis for global geopotential models and their first-, second- and third-order gradients

NASA Astrophysics Data System (ADS)

Fantino, E.; Casotto, S.

2009-07-01

Four widely used algorithms for the computation of the Earth’s gravitational potential and its first-, second- and third-order gradients are examined: the traditional increasing degree recursion in associated Legendre functions and its variant based on the Clenshaw summation, plus the methods of Pines and Cunningham-Metris, which are free from the singularities that distinguish the first two methods at the geographic poles. All four methods are reorganized with the lumped coefficients approach, which in the cases of Pines and Cunningham-Metris requires a complete revision of the algorithms. The characteristics of the four methods are studied and described, and numerical tests are performed to assess and compare their precision, accuracy, and efficiency. In general the performance levels of all four codes exhibit large improvements over previously published versions. From the point of view of numerical precision, away from the geographic poles Clenshaw and Legendre offer an overall better quality. Furthermore, Pines and Cunningham-Metris are affected by an intrinsic loss of precision at the equator and suffer from additional deterioration when the gravity gradients components are rotated into the East-North-Up topocentric reference system.

Design optimization using adjoint of Long-time LES for the trailing edge of a transonic turbine vane

NASA Astrophysics Data System (ADS)

Talnikar, Chaitanya; Wang, Qiqi

2017-11-01

Adjoint-based design optimization methods have been applied to low-fidelity simulation methods like Reynolds Averaged Navier-Stokes (RANS) and are useful for designing fluid machinery components. But to reliably capture the complex flow phenomena involved in turbomachinery, high fidelity simulations like large eddy simulation (LES) are required. Unfortunately due to the chaotic dynamics of turbulence, the unsteady adjoint method for LES diverges and produces incorrect gradients. Using a viscosity stabilized unsteady adjoint method developed for LES, the gradient can be obtained with reasonable accuracy. In this paper, design of the trailing edge of a gas turbine inlet guide vane is performed with the objective to reduce stagnation pressure loss and heat transfer over the surface of the vane. Slight changes in the shape of trailing edge can significantly impact these quantities by altering the boundary layer development process and separation points. The trailing edge is parameterized using a linear combination of 5 convex designs. Bayesian optimization is used as a global optimizer with the objective function evaluated from the LES and gradients obtained using the viscosity adjoint method. Results from the optimization, performed on the supercomputer Mira, are presented.

An analytical model of SAGD process considering the effect of threshold pressure gradient

NASA Astrophysics Data System (ADS)

Morozov, P.; Abdullin, A.; Khairullin, M.

2018-05-01

An analytical model is proposed for the development of super-viscous oil deposits by the method of steam-assisted gravity drainage, taking into account the nonlinear filtration law with the limiting gradient. The influence of non-Newtonian properties of oil on the productivity of a horizontal well and the cumulative steam-oil ratio are studied. Verification of the proposed model based on the results of physical modeling of the SAGD process was carried out.

Analysis and correction of gradient nonlinearity bias in ADC measurements

PubMed Central

Malyarenko, Dariya I.; Ross, Brian D.; Chenevert, Thomas L.

2013-01-01

Purpose Gradient nonlinearity of MRI systems leads to spatially-dependent b-values and consequently high non-uniformity errors (10–20%) in ADC measurements over clinically relevant field-of-views. This work seeks practical correction procedure that effectively reduces observed ADC bias for media of arbitrary anisotropy in the fewest measurements. Methods All-inclusive bias analysis considers spatial and time-domain cross-terms for diffusion and imaging gradients. The proposed correction is based on rotation of the gradient nonlinearity tensor into the diffusion gradient frame where spatial bias of b-matrix can be approximated by its Euclidean norm. Correction efficiency of the proposed procedure is numerically evaluated for a range of model diffusion tensor anisotropies and orientations. Results Spatial dependence of nonlinearity correction terms accounts for the bulk (75–95%) of ADC bias for FA = 0.3–0.9. Residual ADC non-uniformity errors are amplified for anisotropic diffusion. This approximation obviates need for full diffusion tensor measurement and diagonalization to derive a corrected ADC. Practical scenarios are outlined for implementation of the correction on clinical MRI systems. Conclusions The proposed simplified correction algorithm appears sufficient to control ADC non-uniformity errors in clinical studies using three orthogonal diffusion measurements. The most efficient reduction of ADC bias for anisotropic medium is achieved with non-lab-based diffusion gradients. PMID:23794533

C library for topological study of the electronic charge density.

PubMed

Vega, David; Aray, Yosslen; Rodríguez, Jesús

2012-12-05

The topological study of the electronic charge density is useful to obtain information about the kinds of bonds (ionic or covalent) and the atom charges on a molecule or crystal. For this study, it is necessary to calculate, at every space point, the electronic density and its electronic density derivatives values up to second order. In this work, a grid-based method for these calculations is described. The library, implemented for three dimensions, is based on a multidimensional Lagrange interpolation in a regular grid; by differentiating the resulting polynomial, the gradient vector, the Hessian matrix and the Laplacian formulas were obtained for every space point. More complex functions such as the Newton-Raphson method (to find the critical points, where the gradient is null) and the Cash-Karp Runge-Kutta method (used to make the gradient paths) were programmed. As in some crystals, the unit cell has angles different from 90°, the described library includes linear transformations to correct the gradient and Hessian when the grid is distorted (inclined). Functions were also developed to handle grid containing files (grd from DMol® program, CUBE from Gaussian® program and CHGCAR from VASP® program). Each one of these files contains the data for a molecular or crystal electronic property (such as charge density, spin density, electrostatic potential, and others) in a three-dimensional (3D) grid. The library can be adapted to make the topological study in any regular 3D grid by modifying the code of these functions. Copyright © 2012 Wiley Periodicals, Inc.

Higher Nucleoporin-Importinβ Affinity at the Nuclear Basket Increases Nucleocytoplasmic Import

PubMed Central

Azimi, Mohammad; Mofrad, Mohammad R. K.

2013-01-01

Several in vitro studies have shown the presence of an affinity gradient in nuclear pore complex proteins for the import receptor Importinβ, at least partially contributing to nucleocytoplasmic transport, while others have historically argued against the presence of such a gradient. Nonetheless, the existence of an affinity gradient has remained an uncharacterized contributing factor. To shed light on the affinity gradient theory and better characterize how the existence of such an affinity gradient between the nuclear pore and the import receptor may influence the nucleocytoplasmic traffic, we have developed a general-purpose agent based modeling (ABM) framework that features a new method for relating rate constants to molecular binding and unbinding probabilities, and used our ABM approach to quantify the effects of a wide range of forward and reverse nucleoporin-Importinβ affinity gradients. Our results indicate that transport through the nuclear pore complex is maximized with an effective macroscopic affinity gradient of 2000 µM, 200 µM and 10 µM in the cytoplasmic, central channel and nuclear basket respectively. The transport rate at this gradient is approximately 10% higher than the transport rate for a comparable pore lacking any affinity gradient, which has a peak transport rate when all nucleoporins have an affinity of 200 µM for Importinβ. Furthermore, this optimal ratio of affinity gradients is representative of the ratio of affinities reported for the yeast nuclear pore complex – suggesting that the affinity gradient seen in vitro is highly optimized. PMID:24282617

Solving the scalability issue in quantum-based refinement: Q|R#1.

PubMed

Zheng, Min; Moriarty, Nigel W; Xu, Yanting; Reimers, Jeffrey R; Afonine, Pavel V; Waller, Mark P

2017-12-01

Accurately refining biomacromolecules using a quantum-chemical method is challenging because the cost of a quantum-chemical calculation scales approximately as n m , where n is the number of atoms and m (≥3) is based on the quantum method of choice. This fundamental problem means that quantum-chemical calculations become intractable when the size of the system requires more computational resources than are available. In the development of the software package called Q|R, this issue is referred to as Q|R#1. A divide-and-conquer approach has been developed that fragments the atomic model into small manageable pieces in order to solve Q|R#1. Firstly, the atomic model of a crystal structure is analyzed to detect noncovalent interactions between residues, and the results of the analysis are represented as an interaction graph. Secondly, a graph-clustering algorithm is used to partition the interaction graph into a set of clusters in such a way as to minimize disruption to the noncovalent interaction network. Thirdly, the environment surrounding each individual cluster is analyzed and any residue that is interacting with a particular cluster is assigned to the buffer region of that particular cluster. A fragment is defined as a cluster plus its buffer region. The gradients for all atoms from each of the fragments are computed, and only the gradients from each cluster are combined to create the total gradients. A quantum-based refinement is carried out using the total gradients as chemical restraints. In order to validate this interaction graph-based fragmentation approach in Q|R, the entire atomic model of an amyloid cross-β spine crystal structure (PDB entry 2oNA) was refined.

[Analysis and Control of in Vivo Kinetics of Exosomes for the Development of Exosome-based DDS].

PubMed

Takahashi, Yuki; Nishikawa, Makiya; Takakura, Yoshinobu

2016-01-01

  Exosomes are secretory membrane vesicles containing lipids, proteins, and nucleic acids. They act as intercellular transporters by delivering their components to exosome recipient cells. Based on their endogenous delivery system properties, exosomes are expected to become drug delivery systems (DDS) for various molecules such as nucleic acid-based drugs. Important factors such as drug loading to exosomes, production, and pharmacokinetics of exosomes need to be considered for the development of exosome-based DDS. Of these, the pharmacokinetics of exosomes have rarely been studied, probably because of the lack of quantitative evaluation methods of in vivo exosomal pharmacokinetics. We selected lactadherin as an exosome tropic protein and developed it as a fusion protein with Gaussia luciferase to label exosomes for in vivo imaging. In addition, a fusion protein of lactadherin and streptavidin was developed, and the tissue distribution of exosomes was quantitatively evaluated by radiolabeling the exosomes using (125)I-labeled biotin. Using labeled exosomes, we found that intravenously injected exosomes were rapidly cleared from the systemic circulation by macrophages. In addition, the exosomes were mainly distributed to the liver, lung, and spleen. We also examined the effect of exosome isolation methods on their physicochemical and pharmacokinetic properties. We found that exosomes collected by the ultracentrifugation-based density-gradient method were more dispersed than exosomes collected by other methods, including the ultracentrifugation-based pelleting method. The gradient method is more time-consuming than others; therefore the development of a more efficient method for exosome isolation will advance the development of exosome-based DDS.

PET/MR Synchronization by Detection of Switching Gradients

NASA Astrophysics Data System (ADS)

Weissler, Bjoern; Gebhardt, Pierre; Lerche, Christoph W.; Soultanidis, Georgios M.; Wehner, Jakob; Heberling, Dirk; Schulz, Volkmar

2015-06-01

The full potential of simultaneous Positron Emission Tomography (PET) and Magnetic Resonance Imaging (MRI) acquisition, such as dynamic studies or motion compensation, can only be explored if the data of both modalities is temporally synchronized. As such hybrid imaging systems are commonly realized as custom-made PET inserts for commercially available MRI scanner, a synchronization solution has to be implemented (depending on the vendor of the MRI system). In contrast, we demonstrate a simple method for temporal synchronization, which does not require a connection to the MRI. It uses the normally undesired effect of induced voltages on the PET electronics from switching MRI gradients. The electronic circuit needs very few components and the gradient pick-up coils are made from PCB traces and vias on the PET detector boards. Neither programming the MRI nor any physical connection to the MR scanner is needed, thus avoiding electromagnetic compatibility problems. This method works inherently with most MRI sequences and is a vendor- independent solution. A characterization of the sensors in an MRI scanner showed that the MRI gradients are detected with a precision of 120 μs (with the current implementation). Using different trigger thresholds, it is possible to trigger selectively on certain MRI sequences, depending on their gradient slew rate settings. Timings and pulse diagrams of MRI sequences can be recognized from the generated data. The method was successfully used for temporal alignment between PET and MRI in an MRI-based PET-motion-compensation application.

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

PubMed

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

1999-12-01

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

A practically unconditionally gradient stable scheme for the N-component Cahn-Hilliard system

NASA Astrophysics Data System (ADS)

Lee, Hyun Geun; Choi, Jeong-Whan; Kim, Junseok

2012-02-01

We present a practically unconditionally gradient stable conservative nonlinear numerical scheme for the N-component Cahn-Hilliard system modeling the phase separation of an N-component mixture. The scheme is based on a nonlinear splitting method and is solved by an efficient and accurate nonlinear multigrid method. The scheme allows us to convert the N-component Cahn-Hilliard system into a system of N-1 binary Cahn-Hilliard equations and significantly reduces the required computer memory and CPU time. We observe that our numerical solutions are consistent with the linear stability analysis results. We also demonstrate the efficiency of the proposed scheme with various numerical experiments.

Precision bounds for gradient magnetometry with atomic ensembles

NASA Astrophysics Data System (ADS)

Apellaniz, Iagoba; Urizar-Lanz, Iñigo; Zimborás, Zoltán; Hyllus, Philipp; Tóth, Géza

2018-05-01

We study gradient magnetometry with an ensemble of atoms with arbitrary spin. We calculate precision bounds for estimating the gradient of the magnetic field based on the quantum Fisher information. For quantum states that are invariant under homogeneous magnetic fields, we need to measure a single observable to estimate the gradient. On the other hand, for states that are sensitive to homogeneous fields, a simultaneous measurement is needed, as the homogeneous field must also be estimated. We prove that for the cases studied in this paper, such a measurement is feasible. We present a method to calculate precision bounds for gradient estimation with a chain of atoms or with two spatially separated atomic ensembles. We also consider a single atomic ensemble with an arbitrary density profile, where the atoms cannot be addressed individually, and which is a very relevant case for experiments. Our model can take into account even correlations between particle positions. While in most of the discussion we consider an ensemble of localized particles that are classical with respect to their spatial degree of freedom, we also discuss the case of gradient metrology with a single Bose-Einstein condensate.

On investigating wall shear stress in two-dimensional plane turbulent wall jets

NASA Astrophysics Data System (ADS)

Mehdi, Faraz; Johansson, Gunnar; White, Christopher; Naughton, Jonathan

2012-11-01

Mehdi & White [Exp Fluids 50:43-51(2011)] presented a full momentum integral based method for determining wall shear stress in zero pressure gradient turbulent boundary layers. They utilized the boundary conditions at the wall and at the outer edge of the boundary layer. A more generalized expression is presented here that uses just one boundary condition at the wall. The method is mathematically exact and has an advantage of having no explicit streamwise gradient terms. It is successfully applied to two different experimental plane turbulent wall jet datasets for which independent estimates of wall shear stress were known. Complications owing to experimental inaccuracies in determining wall shear stress from the proposed method are also discussed.

Gradient stationary phase optimized selectivity liquid chromatography with conventional columns.

PubMed

Chen, Kai; Lynen, Frédéric; Szucs, Roman; Hanna-Brown, Melissa; Sandra, Pat

2013-05-21

Stationary phase optimized selectivity liquid chromatography (SOSLC) is a promising technique to optimize the selectivity of a given separation. By combination of different stationary phases, SOSLC offers excellent possibilities for method development under both isocratic and gradient conditions. The so far available commercial SOSLC protocol utilizes dedicated column cartridges and corresponding cartridge holders to build up the combined column of different stationary phases. The present work is aimed at developing and extending the gradient SOSLC approach towards coupling conventional columns. Generic tubing was used to connect short commercially available LC columns. Fast and base-line separation of a mixture of 12 compounds containing phenones, benzoic acids and hydroxybenzoates under both isocratic and linear gradient conditions was selected to demonstrate the potential of SOSLC. The influence of the connecting tubing on the deviation of predictions is also discussed.

Dynamic response of porous functionally graded material nanobeams subjected to moving nanoparticle based on nonlocal strain gradient theory

NASA Astrophysics Data System (ADS)

Barati, Mohammad Reza

2017-11-01

Up to now, nonlocal strain gradient theory (NSGT) is broadly applied to examine free vibration, static bending and buckling of nanobeams. This theory captures nonlocal stress field effects together with the microstructure-dependent strain gradient effects. In this study, forced vibrations of NSGT nanobeams on elastic substrate subjected to moving loads are examined. The nanobeam is made of functionally graded material (FGM) with even and uneven porosity distributions inside the material structure. The graded material properties with porosities are described by a modified power-law model. Dynamic deflection of the nanobeam is obtained via Galerkin and inverse Laplace transform methods. The importance of nonlocal parameter, strain gradient parameter, moving load velocity, porosity volume fraction, type of porosity distribution and elastic foundation on forced vibration behavior of nanobeams are discussed.

Drawing for Traffic Marking Using Bidirectional Gradient-Based Detection with MMS LIDAR Intensity

NASA Astrophysics Data System (ADS)

Takahashi, G.; Takeda, H.; Nakamura, K.

2016-06-01

Recently, the development of autonomous cars is accelerating on the integration of highly advanced artificial intelligence, which increases demand for a digital map with high accuracy. In particular, traffic markings are required to be precisely digitized since automatic driving utilizes them for position detection. To draw traffic markings, we benefit from Mobile Mapping Systems (MMS) equipped with high-density Laser imaging Detection and Ranging (LiDAR) scanners, which produces large amount of data efficiently with XYZ coordination along with reflectance intensity. Digitizing this data, on the other hand, conventionally has been dependent on human operation, which thus suffers from human errors, subjectivity errors, and low reproductivity. We have tackled this problem by means of automatic extraction of traffic marking, which partially accomplished to draw several traffic markings (G. Takahashi et al., 2014). The key idea of the method was extracting lines using the Hough transform strategically focused on changes in local reflection intensity along scan lines. However, it failed to extract traffic markings properly in a densely marked area, especially when local changing points are close each other. In this paper, we propose a bidirectional gradient-based detection method where local changing points are labelled with plus or minus group. Given that each label corresponds to the boundary between traffic markings and background, we can identify traffic markings explicitly, meaning traffic lines are differentiated correctly by the proposed method. As such, our automated method, a highly accurate and non-human-operator-dependent method using bidirectional gradient-based algorithm, can successfully extract traffic lines composed of complex shapes such as a cross walk, resulting in minimizing cost and obtaining highly accurate results.

Ship detection based on rotation-invariant HOG descriptors for airborne infrared images

NASA Astrophysics Data System (ADS)

Xu, Guojing; Wang, Jinyan; Qi, Shengxiang

2018-03-01

Infrared thermal imagery is widely used in various kinds of aircraft because of its all-time application. Meanwhile, detecting ships from infrared images attract lots of research interests in recent years. In the case of downward-looking infrared imagery, in order to overcome the uncertainty of target imaging attitude due to the unknown position relationship between the aircraft and the target, we propose a new infrared ship detection method which integrates rotation invariant gradient direction histogram (Circle Histogram of Oriented Gradient, C-HOG) descriptors and the support vector machine (SVM) classifier. In details, the proposed method uses HOG descriptors to express the local feature of infrared images to adapt to changes in illumination and to overcome sea clutter effects. Different from traditional computation of HOG descriptor, we subdivide the image into annular spatial bins instead of rectangle sub-regions, and then Radial Gradient Transform (RGT) on the gradient is applied to achieve rotation invariant histogram information. Considering the engineering application of airborne and real-time requirements, we use SVM for training ship target and non-target background infrared sample images to discriminate real ships from false targets. Experimental results show that the proposed method has good performance in both the robustness and run-time for infrared ship target detection with different rotation angles.

Stable Computation of the Vertical Gradient of Potential Field Data Based on Incorporating the Smoothing Filters

NASA Astrophysics Data System (ADS)

Baniamerian, Jamaledin; Liu, Shuang; Abbas, Mahmoud Ahmed

2018-04-01

The vertical gradient is an essential tool in interpretation algorithms. It is also the primary enhancement technique to improve the resolution of measured gravity and magnetic field data, since it has higher sensitivity to changes in physical properties (density or susceptibility) of the subsurface structures than the measured field. If the field derivatives are not directly measured with the gradiometers, they can be calculated from the collected gravity or magnetic data using numerical methods such as those based on fast Fourier transform technique. The gradients behave similar to high-pass filters and enhance the short-wavelength anomalies which may be associated with either small-shallow sources or high-frequency noise content in data, and their numerical computation is susceptible to suffer from amplification of noise. This behaviour can adversely affect the stability of the derivatives in the presence of even a small level of the noise and consequently limit their application to interpretation methods. Adding a smoothing term to the conventional formulation of calculating the vertical gradient in Fourier domain can improve the stability of numerical differentiation of the field. In this paper, we propose a strategy in which the overall efficiency of the classical algorithm in Fourier domain is improved by incorporating two different smoothing filters. For smoothing term, a simple qualitative procedure based on the upward continuation of the field to a higher altitude is introduced to estimate the related parameters which are called regularization parameter and cut-off wavenumber in the corresponding filters. The efficiency of these new approaches is validated by computing the first- and second-order derivatives of noise-corrupted synthetic data sets and then comparing the results with the true ones. The filtered and unfiltered vertical gradients are incorporated into the extended Euler deconvolution to estimate the depth and structural index of a magnetic sphere, hence, quantitatively evaluating the methods. In the real case, the described algorithms are used to enhance a portion of aeromagnetic data acquired in Mackenzie Corridor, Northern Mainland, Canada.

Statistical Feature Extraction for Artifact Removal from Concurrent fMRI-EEG Recordings

PubMed Central

Liu, Zhongming; de Zwart, Jacco A.; van Gelderen, Peter; Kuo, Li-Wei; Duyn, Jeff H.

2011-01-01

We propose a set of algorithms for sequentially removing artifacts related to MRI gradient switching and cardiac pulsations from electroencephalography (EEG) data recorded during functional magnetic resonance imaging (fMRI). Special emphases are directed upon the use of statistical metrics and methods for the extraction and selection of features that characterize gradient and pulse artifacts. To remove gradient artifacts, we use a channel-wise filtering based on singular value decomposition (SVD). To remove pulse artifacts, we first decompose data into temporally independent components and then select a compact cluster of components that possess sustained high mutual information with the electrocardiogram (ECG). After the removal of these components, the time courses of remaining components are filtered by SVD to remove the temporal patterns phase-locked to the cardiac markers derived from the ECG. The filtered component time courses are then inversely transformed into multi-channel EEG time series free of pulse artifacts. Evaluation based on a large set of simultaneous EEG-fMRI data obtained during a variety of behavioral tasks, sensory stimulations and resting conditions showed excellent data quality and robust performance attainable by the proposed methods. These algorithms have been implemented as a Matlab-based toolbox made freely available for public access and research use. PMID:22036675

Statistical feature extraction for artifact removal from concurrent fMRI-EEG recordings.

PubMed

Liu, Zhongming; de Zwart, Jacco A; van Gelderen, Peter; Kuo, Li-Wei; Duyn, Jeff H

2012-02-01

We propose a set of algorithms for sequentially removing artifacts related to MRI gradient switching and cardiac pulsations from electroencephalography (EEG) data recorded during functional magnetic resonance imaging (fMRI). Special emphasis is directed upon the use of statistical metrics and methods for the extraction and selection of features that characterize gradient and pulse artifacts. To remove gradient artifacts, we use channel-wise filtering based on singular value decomposition (SVD). To remove pulse artifacts, we first decompose data into temporally independent components and then select a compact cluster of components that possess sustained high mutual information with the electrocardiogram (ECG). After the removal of these components, the time courses of remaining components are filtered by SVD to remove the temporal patterns phase-locked to the cardiac timing markers derived from the ECG. The filtered component time courses are then inversely transformed into multi-channel EEG time series free of pulse artifacts. Evaluation based on a large set of simultaneous EEG-fMRI data obtained during a variety of behavioral tasks, sensory stimulations and resting conditions showed excellent data quality and robust performance attainable with the proposed methods. These algorithms have been implemented as a Matlab-based toolbox made freely available for public access and research use. Published by Elsevier Inc.

Fundamental performance of transverse wind estimator from Shack-Hartmann wave-front sensor measurements.

PubMed

Li, Zhenghan; Li, Xinyang

2018-04-30

Real time transverse wind estimation contributes to predictive correction which is used to compensate for the time delay error in the control systems of adaptive optics (AO) system. Many methods that apply Shack-Hartmann wave-front sensor to wind profile measurement have been proposed. One of the obvious problems is the lack of a fundamental benchmark to compare the various methods. In this work, we present the fundamental performance limits for transverse wind estimator from Shack-Hartmann wave-front sensor measurements using Cramér-Rao lower bound (CRLB). The bound provides insight into the nature of the transverse wind estimation, thereby suggesting how to design and improve the estimator in the different application scenario. We analyze the theoretical bound and find that factors such as slope measurement noise, wind velocity and atmospheric coherence length r 0 have important influence on the performance. Then, we introduced the non-iterative gradient-based transverse wind estimator. The source of the deterministic bias of the gradient-based transverse wind estimators is analyzed for the first time. Finally, we derived biased CRLB for the gradient-based transverse wind estimators from Shack-Hartmann wave-front sensor measurements and the bound can predict the performance of estimator more accurately.

In situ measurements of tritium evapotranspiration (³H-ET) flux over grass and soil using the gradient and eddy covariance experimental methods and the FAO-56 model.

PubMed

Connan, O; Maro, D; Hébert, D; Solier, L; Caldeira Ideas, P; Laguionie, P; St-Amant, N

2015-10-01

The behaviour of tritium in the environment is linked to the water cycle. We compare three methods of calculating the tritium evapotranspiration flux from grassland cover. The gradient and eddy covariance methods, together with a method based on the theoretical Penmann-Monteith model were tested in a study carried out in 2013 in an environment characterised by high levels of tritium activity. The results show that each of the three methods gave similar results. The various constraints applying to each method are discussed. The results show a tritium evapotranspiration flux of around 15 mBq m(-2) s(-1) in this environment. These results will be used to improve the entry parameters for the general models of tritium transfers in the environment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dosimetric comparison of different treatment modalities for stereotactic radiotherapy.

PubMed

Hsu, Shih-Ming; Lai, Yuan-Chun; Jeng, Chien-Chung; Tseng, Chia-Ying

2017-09-16

The modalities for performing stereotactic radiotherapy (SRT) on the brain include the cone-based linear accelerator (linac), the flattening filter-free (FFF) volumetric modulated arc therapy (VMAT) linac, and tomotherapy. In this study, the cone-based linac, FFF-VMAT linac, and tomotherapy modalities were evaluated by measuring the differences in doses delivered during brain SRT and experimentally assessing the accuracy of the output radiation doses through clinical measurements. We employed a homemade acrylic dosimetry phantom representing the head, within which a thermoluminescent dosimeter (TLD) and radiochromic EBT3 film were installed. Using the conformity/gradient index (CGI) and Paddick methods, the quality of the doses delivered by the various SRT modalities was evaluated. The quality indicators included the uniformity, conformity, and gradient indices. TLDs and EBT3 films were used to experimentally assess the accuracy of the SRT dose output. The dose homogeneity indices of all the treatment modalities were lower than 1.25. The cone-based linac had the best conformity for all tumors, regardless of the tumor location and size, followed by the FFF-VMAT linac; tomography was the worst-performing treatment modality in this regard. The cone-based linac had the best gradient, regardless of the tumor location and size, whereas the FFF-VMAT linac had a better gradient than tomotherapy for a large tumor diameter (28 mm). The TLD and EBT3 measurements of the dose at the center of tumors indicated that the average difference between the measurements and the calculated dose was generally less than 4%. When the 3% 3-mm gamma passing rate metric was used, the average passing rates of all three treatment modalities exceeded 98%. Regarding the dose, the cone-based linac had the best conformity and steepest dose gradient for tumors of different sizes and distances from the brainstem. The results of this study suggest that SRT should be performed using the cone-based linac on tumors that require treatment plans with a steep dose gradient, even as the tumor is slightly irregular, we should also consider using a high dose gradient of the cone base to treat and protect the normal tissue. If normal tissues require special protection exist at positions that are superior or inferior to the tumor, we can consider using tomotherapy or Cone base with couch at 0° for treatment.

On event-based optical flow detection

PubMed Central

Brosch, Tobias; Tschechne, Stephan; Neumann, Heiko

2015-01-01

Event-based sensing, i.e., the asynchronous detection of luminance changes, promises low-energy, high dynamic range, and sparse sensing. This stands in contrast to whole image frame-wise acquisition by standard cameras. Here, we systematically investigate the implications of event-based sensing in the context of visual motion, or flow, estimation. Starting from a common theoretical foundation, we discuss different principal approaches for optical flow detection ranging from gradient-based methods over plane-fitting to filter based methods and identify strengths and weaknesses of each class. Gradient-based methods for local motion integration are shown to suffer from the sparse encoding in address-event representations (AER). Approaches exploiting the local plane like structure of the event cloud, on the other hand, are shown to be well suited. Within this class, filter based approaches are shown to define a proper detection scheme which can also deal with the problem of representing multiple motions at a single location (motion transparency). A novel biologically inspired efficient motion detector is proposed, analyzed and experimentally validated. Furthermore, a stage of surround normalization is incorporated. Together with the filtering this defines a canonical circuit for motion feature detection. The theoretical analysis shows that such an integrated circuit reduces motion ambiguity in addition to decorrelating the representation of motion related activations. PMID:25941470

Analytical Energy Gradients for Excited-State Coupled-Cluster Methods

NASA Astrophysics Data System (ADS)

Wladyslawski, Mark; Nooijen, Marcel

The equation-of-motion coupled-cluster (EOM-CC) and similarity transformed equation-of-motion coupled-cluster (STEOM-CC) methods have been firmly established as accurate and routinely applicable extensions of single-reference coupled-cluster theory to describe electronically excited states. An overview of these methods is provided, with emphasis on the many-body similarity transform concept that is the key to a rationalization of their accuracy. The main topic of the paper is the derivation of analytical energy gradients for such non-variational electronic structure approaches, with an ultimate focus on obtaining their detailed algebraic working equations. A general theoretical framework using Lagrange's method of undetermined multipliers is presented, and the method is applied to formulate the EOM-CC and STEOM-CC gradients in abstract operator terms, following the previous work in [P.G. Szalay, Int. J. Quantum Chem. 55 (1995) 151] and [S.R. Gwaltney, R.J. Bartlett, M. Nooijen, J. Chem. Phys. 111 (1999) 58]. Moreover, the systematics of the Lagrange multiplier approach is suitable for automation by computer, enabling the derivation of the detailed derivative equations through a standardized and direct procedure. To this end, we have developed the SMART (Symbolic Manipulation and Regrouping of Tensors) package of automated symbolic algebra routines, written in the Mathematica programming language. The SMART toolkit provides the means to expand, differentiate, and simplify equations by manipulation of the detailed algebraic tensor expressions directly. The Lagrangian multiplier formulation establishes a uniform strategy to perform the automated derivation in a standardized manner: A Lagrange multiplier functional is constructed from the explicit algebraic equations that define the energy in the electronic method; the energy functional is then made fully variational with respect to all of its parameters, and the symbolic differentiations directly yield the explicit equations for the wavefunction amplitudes, the Lagrange multipliers, and the analytical gradient via the perturbation-independent generalized Hellmann-Feynman effective density matrix. This systematic automated derivation procedure is applied to obtain the detailed gradient equations for the excitation energy (EE-), double ionization potential (DIP-), and double electron affinity (DEA-) similarity transformed equation-of-motion coupled-cluster singles-and-doubles (STEOM-CCSD) methods. In addition, the derivatives of the closed-shell-reference excitation energy (EE-), ionization potential (IP-), and electron affinity (EA-) equation-of-motion coupled-cluster singles-and-doubles (EOM-CCSD) methods are derived. Furthermore, the perturbative EOM-PT and STEOM-PT gradients are obtained. The algebraic derivative expressions for these dozen methods are all derived here uniformly through the automated Lagrange multiplier process and are expressed compactly in a chain-rule/intermediate-density formulation, which facilitates a unified modular implementation of analytic energy gradients for CCSD/PT-based electronic methods. The working equations for these analytical gradients are presented in full detail, and their factorization and implementation into an efficient computer code are discussed.

Full magnetic gradient tensor from triaxial aeromagnetic gradient measurements: Calculation and application

NASA Astrophysics Data System (ADS)

Luo, Yao; Wu, Mei-Ping; Wang, Ping; Duan, Shu-Ling; Liu, Hao-Jun; Wang, Jin-Long; An, Zhan-Feng

2015-09-01

The full magnetic gradient tensor (MGT) refers to the spatial change rate of the three field components of the geomagnetic field vector along three mutually orthogonal axes. The tensor is of use to geological mapping, resources exploration, magnetic navigation, and others. However, it is very difficult to measure the full magnetic tensor gradient using existing engineering technology. We present a method to use triaxial aeromagnetic gradient measurements for deriving the full MGT. The method uses the triaxial gradient data and makes full use of the variation of the magnetic anomaly modulus in three dimensions to obtain a self-consistent magnetic tensor gradient. Numerical simulations show that the full MGT data obtained with the proposed method are of high precision and satisfy the requirements of data processing. We selected triaxial aeromagnetic gradient data from the Hebei Province for calculating the full MGT. Data processing shows that using triaxial tensor gradient data allows to take advantage of the spatial rate of change of the total field in three dimensions and suppresses part of the independent noise in the aeromagnetic gradient. The calculated tensor components have improved resolution, and the transformed full tensor gradient satisfies the requirement of geological mapping and interpretation.

Gradient-based stochastic estimation of the density matrix

NASA Astrophysics Data System (ADS)

Wang, Zhentao; Chern, Gia-Wei; Batista, Cristian D.; Barros, Kipton

2018-03-01

Fast estimation of the single-particle density matrix is key to many applications in quantum chemistry and condensed matter physics. The best numerical methods leverage the fact that the density matrix elements f(H)ij decay rapidly with distance rij between orbitals. This decay is usually exponential. However, for the special case of metals at zero temperature, algebraic decay of the density matrix appears and poses a significant numerical challenge. We introduce a gradient-based probing method to estimate all local density matrix elements at a computational cost that scales linearly with system size. For zero-temperature metals, the stochastic error scales like S-(d+2)/2d, where d is the dimension and S is a prefactor to the computational cost. The convergence becomes exponential if the system is at finite temperature or is insulating.

Using two classification schemes to develop vegetation indices of biological integrity for wetlands in West Virginia, USA.

PubMed

Veselka, Walter; Rentch, James S; Grafton, William N; Kordek, Walter S; Anderson, James T

2010-11-01

Bioassessment methods for wetlands, and other bodies of water, have been developed worldwide to measure and quantify changes in "biological integrity." These assessments are based on a classification system, meant to ensure appropriate comparisons between wetland types. Using a local site-specific disturbance gradient, we built vegetation indices of biological integrity (Veg-IBIs) based on two commonly used wetland classification systems in the USA: One based on vegetative structure and the other based on a wetland's position in a landscape and sources of water. The resulting class-specific Veg-IBIs were comprised of 1-5 metrics that varied in their sensitivity to the disturbance gradient (R2=0.14-0.65). Moreover, the sensitivity to the disturbance gradient increased as metrics from each of the two classification schemes were combined (added). Using this information to monitor natural and created wetlands will help natural resource managers track changes in biological integrity of wetlands in response to anthropogenic disturbance and allows the use of vegetative communities to set ecological performance standards for mitigation banks.

Local stellar kinematics from RAVE data—VIII. Effects of the Galactic disc perturbations on stellar orbits of red clump stars

NASA Astrophysics Data System (ADS)

Önal Taş, Ö.; Bilir, S.; Plevne, O.

2018-02-01

We aim to probe the dynamic structure of the extended Solar neighborhood by calculating the radial metallicity gradients from orbit properties, which are obtained for axisymmetric and non-axisymmetric potential models, of red clump (RC) stars selected from the RAdial Velocity Experiment's Fourth Data Release. Distances are obtained by assuming a single absolute magnitude value in near-infrared, i.e. M_{Ks}=-1.54±0.04 mag, for each RC star. Stellar orbit parameters are calculated by using the potential functions: (i) for the MWPotential2014 potential, (ii) for the same potential with perturbation functions of the Galactic bar and transient spiral arms. The stellar age is calculated with a method based on Bayesian statistics. The radial metallicity gradients are evaluated based on the maximum vertical distance (z_{max}) from the Galactic plane and the planar eccentricity (ep) of RC stars for both of the potential models. The largest radial metallicity gradient in the 0< z_{max} ≤0.5 kpc distance interval is -0.065±0.005 dex kpc^{-1} for a subsample with ep≤0.1, while the lowest value is -0.014±0.006 dex kpc^{-1} for the subsample with ep≤0.5. We find that at z_{max}>1 kpc, the radial metallicity gradients have zero or positive values and they do not depend on ep subsamples. There is a large radial metallicity gradient for thin disc, but no radial gradient found for thick disc. Moreover, the largest radial metallicity gradients are obtained where the outer Lindblad resonance region is effective. We claim that this apparent change in radial metallicity gradients in the thin disc is a result of orbital perturbation originating from the existing resonance regions.

Magnetoelectrets prepared by using temperature gradient method

NASA Astrophysics Data System (ADS)

Ojha, Pragya; Qureshi, M. S.; Malik, M. M.

2015-05-01

A novel Temperature Gradient method for preparation of magnetoelectret is proposed. Non uniform magnetic field and temperature gradient are expected to be the main cause for the formation of magnetoelectrets (MEs). Being bad conductors of heat, during their formation, there is a possibility for the existence of a temperature gradient along the dielectric electrode interface. In this condition, the motion of, molecules and charge carriers are dependent on Temperature Gradient in a preferred direction. To increase this temperature gradient on both sides of the sample novel method for the preparation of MEs is developed for the first time. For this method the special sample holders are designed in our laboratory. MEs are prepared in such a way that one surface is cooled and the other is heated, during the process. With the help of XRD analysis using Type-E orientation pattern and surface charge studies on magnetoelectrets, the two main causes Non uniform magnetic field and temperature gradient for the formation of magnetoelectrets (MEs), are authenticated experimentally.

A Data Driven Model for Predicting RNA-Protein Interactions based on Gradient Boosting Machine.

PubMed

Jain, Dharm Skandh; Gupte, Sanket Rajan; Aduri, Raviprasad

2018-06-22

RNA protein interactions (RPI) play a pivotal role in the regulation of various biological processes. Experimental validation of RPI has been time-consuming, paving the way for computational prediction methods. The major limiting factor of these methods has been the accuracy and confidence of the predictions, and our in-house experiments show that they fail to accurately predict RPI involving short RNA sequences such as TERRA RNA. Here, we present a data-driven model for RPI prediction using a gradient boosting classifier. Amino acids and nucleotides are classified based on the high-resolution structural data of RNA protein complexes. The minimum structural unit consisting of five residues is used as the descriptor. Comparative analysis of existing methods shows the consistently higher performance of our method irrespective of the length of RNA present in the RPI. The method has been successfully applied to map RPI networks involving both long noncoding RNA as well as TERRA RNA. The method is also shown to successfully predict RNA and protein hubs present in RPI networks of four different organisms. The robustness of this method will provide a way for predicting RPI networks of yet unknown interactions for both long noncoding RNA and microRNA.

Fast gradient-based algorithm on extended landscapes for wave-front reconstruction of Earth observation satellite

NASA Astrophysics Data System (ADS)

Thiebaut, C.; Perraud, L.; Delvit, J. M.; Latry, C.

2016-07-01

We present an on-board satellite implementation of a gradient-based (optical flows) algorithm for the shifts estimation between images of a Shack-Hartmann wave-front sensor on extended landscapes. The proposed algorithm has low complexity in comparison with classical correlation methods which is a big advantage for being used on-board a satellite at high instrument data rate and in real-time. The electronic board used for this implementation is designed for space applications and is composed of radiation-hardened software and hardware. Processing times of both shift estimations and pre-processing steps are compatible of on-board real-time computation.

Anisotropic failure and size effects in periodic honeycomb materials: A gradient-elasticity approach

NASA Astrophysics Data System (ADS)

Réthoré, Julien; Dang, Thi Bach Tuyet; Kaltenbrunner, Christine

2017-02-01

This paper proposes a fracture mechanics model for the analysis of crack propagation in periodic honeycomb materials. The model is based on gradient-elasticity which enables us to account for the effect of the material structure at the macroscopic scale. For simulating the propagation of cracks along an arbitrary path, the numerical implementation is elaborated based on an extended finite element method with the required level of continuity. The two main features captured by the model are directionality and size effect. The numerical predictions are consistent with experimental results on honeycomb materials but also with results reported in the literature for microstructurally short cracks in metals.

Weighted graph based ordering techniques for preconditioned conjugate gradient methods

NASA Technical Reports Server (NTRS)

Clift, Simon S.; Tang, Wei-Pai

1994-01-01

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

Method and apparatus for an optical function generator for seamless tiled displays

NASA Technical Reports Server (NTRS)

Johnson, Michael (Inventor); Chen, Chung-Jen (Inventor)

2004-01-01

Producing seamless tiled images from multiple displays includes measuring a luminance profile of each of the displays, computing a desired luminance profile for each of the displays, and determining a spatial gradient profile of each of the displays based on the measured luminance profile and the computed desired luminance profile. The determined spatial gradient profile is applied to a spatial filter to be inserted into each of the displays to produce the seamless tiled display image.

An optimization approach for fitting canonical tensor decompositions.

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

Dunlavy, Daniel M.; Acar, Evrim; Kolda, Tamara Gibson

Tensor decompositions are higher-order analogues of matrix decompositions and have proven to be powerful tools for data analysis. In particular, we are interested in the canonical tensor decomposition, otherwise known as the CANDECOMP/PARAFAC decomposition (CPD), which expresses a tensor as the sum of component rank-one tensors and is used in a multitude of applications such as chemometrics, signal processing, neuroscience, and web analysis. The task of computing the CPD, however, can be difficult. The typical approach is based on alternating least squares (ALS) optimization, which can be remarkably fast but is not very accurate. Previously, nonlinear least squares (NLS) methodsmore » have also been recommended; existing NLS methods are accurate but slow. In this paper, we propose the use of gradient-based optimization methods. We discuss the mathematical calculation of the derivatives and further show that they can be computed efficiently, at the same cost as one iteration of ALS. Computational experiments demonstrate that the gradient-based optimization methods are much more accurate than ALS and orders of magnitude faster than NLS.« less

Efficient gradient calibration based on diffusion MRI.

PubMed

Teh, Irvin; Maguire, Mahon L; Schneider, Jürgen E

2017-01-01

To propose a method for calibrating gradient systems and correcting gradient nonlinearities based on diffusion MRI measurements. The gradient scaling in x, y, and z were first offset by up to 5% from precalibrated values to simulate a poorly calibrated system. Diffusion MRI data were acquired in a phantom filled with cyclooctane, and corrections for gradient scaling errors and nonlinearity were determined. The calibration was assessed with diffusion tensor imaging and independently validated with high resolution anatomical MRI of a second structured phantom. The errors in apparent diffusion coefficients along orthogonal axes ranged from -9.2% ± 0.4% to + 8.8% ± 0.7% before calibration and -0.5% ± 0.4% to + 0.8% ± 0.3% after calibration. Concurrently, fractional anisotropy decreased from 0.14 ± 0.03 to 0.03 ± 0.01. Errors in geometric measurements in x, y and z ranged from -5.5% to + 4.5% precalibration and were likewise reduced to -0.97% to + 0.23% postcalibration. Image distortions from gradient nonlinearity were markedly reduced. Periodic gradient calibration is an integral part of quality assurance in MRI. The proposed approach is both accurate and efficient, can be setup with readily available materials, and improves accuracy in both anatomical and diffusion MRI to within ±1%. Magn Reson Med 77:170-179, 2017. © 2016 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. © 2016 Wiley Periodicals, Inc.

Monitoring of the spatio-temporal change in the interplate coupling at northeastern Japan subduction zone based on the spatial gradients of surface velocity field

NASA Astrophysics Data System (ADS)

Iinuma, Takeshi

2018-04-01

A monitoring method to grasp the spatio-temporal change in the interplate coupling in a subduction zone based on the spatial gradients of surface displacement rate fields is proposed. I estimated the spatio-temporal change in the interplate coupling along the plate boundary in northeastern (NE) Japan by applying the proposed method to the surface displacement rates based on global positioning system observations. The gradient of the surface velocities is calculated in each swath configured along the direction normal to the Japan Trench for time windows such as 0.5, 1, 2, 3 and 5 yr being shifted by one week during the period of 1997-2016. The gradient of the horizontal velocities is negative and has a large magnitude when the interplate coupling at the shallow part (less than approximately 50 km in depth) beneath the profile is strong, and the sign of the gradient of the vertical velocity is sensitive to the existence of the coupling at the deep part (greater than approximately 50 km in depth). The trench-parallel variation of the spatial gradients of a displacement rate field clearly corresponds to the trench-parallel variation of the amplitude of the interplate coupling on the plate interface, as well as the rupture areas of previous interplate earthquakes. Temporal changes in the trench-parallel variation of the spatial gradient of the displacement rate correspond to the strengthening or weakening of the interplate coupling. We can monitor the temporal change in the interplate coupling state by calculating the spatial gradients of the surface displacement rate field to some extent without performing inversion analyses with applying certain constraint conditions that sometimes cause over- and/or underestimation at areas of limited spatial resolution far from the observation network. The results of the calculation confirm known interplate events in the NE Japan subduction zone, such as the post-seismic slip of the 2003 M8.0 Tokachi-oki and 2005 M7.2 Miyagi-oki earthquakes and the recovery of the interplate coupling around the rupture area of the 1994 M7.6 Sanriku-Haruka-oki earthquake. The results also indicate the semi-periodic occurrence of slow slip events and the expansion of the area of slow slip events before the 2011 Tohoku-oki earthquake (M9.0) approaching the hypocentre of the Tohoku-oki earthquake.

Transport characteristics of nanoparticle-based ferrofluids in a gel model of the brain

PubMed Central

Basak, Soubir; Brogan, David; Dietrich, Hans; Ritter, Rogers; Dacey, Ralph G; Biswas, Pratim

2009-01-01

A current advance in nanotechnology is the selective targeting of therapeutics by external magnetic field-guided delivery. This is an important area of research in medicine. The use of magnetic forces results in the formation of agglomerated structures in the field region. The transport characteristics of these agglomerated structures are explored. A nonintrusive method based on in situ light-scattering techniques is used to characterize the velocity of such particles in a magnetic field gradient. A transport model for the chain-like agglomerates is developed based on these experimental observations. The transport characteristics of magnetic nanoparticle drug carriers are then explored in gel-based simulated models of the brain. Results of such measurements demonstrate decreased diffusion of magnetic nanoparticles when placed in a high magnetic field gradient. PMID:19421367

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

NASA Technical Reports Server (NTRS)

Poole, E. L.

1986-01-01

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

An 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

Optimization-based image reconstruction in x-ray computed tomography by sparsity exploitation of local continuity and nonlocal spatial self-similarity

NASA Astrophysics Data System (ADS)

Han-Ming, Zhang; Lin-Yuan, Wang; Lei, Li; Bin, Yan; Ai-Long, Cai; Guo-En, Hu

2016-07-01

The additional sparse prior of images has been the subject of much research in problems of sparse-view computed tomography (CT) reconstruction. A method employing the image gradient sparsity is often used to reduce the sampling rate and is shown to remove the unwanted artifacts while preserve sharp edges, but may cause blocky or patchy artifacts. To eliminate this drawback, we propose a novel sparsity exploitation-based model for CT image reconstruction. In the presented model, the sparse representation and sparsity exploitation of both gradient and nonlocal gradient are investigated. The new model is shown to offer the potential for better results by introducing a similarity prior information of the image structure. Then, an effective alternating direction minimization algorithm is developed to optimize the objective function with a robust convergence result. Qualitative and quantitative evaluations have been carried out both on the simulation and real data in terms of accuracy and resolution properties. The results indicate that the proposed method can be applied for achieving better image-quality potential with the theoretically expected detailed feature preservation. Project supported by the National Natural Science Foundation of China (Grant No. 61372172).

Determining the number of chemical species in nuclear magnetic resonance data matrix by taking advantage of collinearity and noise.

PubMed

Wang, Wanping; Shao, Limin; Yuan, Bin; Zhang, Xu; Liu, Maili

2018-08-31

The number of chemical species is crucial in analyzing pulsed field gradient nuclear magnetic resonance spectral data. Any method to determine the number must handle the obstacles of collinearity and noise. Collinearity in pulsed field gradient NMR data poses a serious challenge to and fails many existing methods. A novel method is proposed by taking advantage of the two obstacles instead of eliminating them. In the proposed method, the determination is based on discriminating decay-profile-dominant eigenvectors from noise-dominant ones, and the discrimination is implemented with a novel low- and high-frequency energy ratio (LHFER). Its performance is validated with both simulated and experimental data. The method is mathematically rigorous, computationally efficient, and readily automated. It also has the potential to be applied to other types of data in which collinearity is fairly severe. Copyright © 2018 Elsevier B.V. All rights reserved.

Meropenem/colistin synergy testing for multidrug-resistant Acinetobacter baumannii strains by a two-dimensional gradient technique applicable in routine microbiology.

PubMed

van Belkum, Alex; Halimi, Diane; Bonetti, Eve-Julie; Renzi, Gesuele; Cherkaoui, Abdessalam; Sauvonnet, Véronique; Martelin, Roland; Durand, Géraldine; Chatellier, Sonia; Zambardi, Gilles; Engelhardt, Anette; Karlsson, Åsa; Schrenzel, Jacques

2015-01-01

Precise assessment of potential therapeutic synergy, antagonism or indifference between antimicrobial agents currently depends on time-consuming and hard-to-standardize in vitro chequerboard titration methods. We here present a method based on a novel two-dimensional antibiotic gradient technique named Xact™. We used a test comprising a combination of perpendicular gradients of meropenem and colistin in a single quadrant. We compared test outcomes with those obtained with classical chequerboard microbroth dilution testing in a study involving 27 unique strains of multidrug-resistant Acinetobacter baumannii from diverse origins. We were able to demonstrate 92% concordance between the new technology and classical chequerboard titration using the A. baumannii collection. Two strains could not be analysed by Xact™ due to their out-of-range MIC of meropenem (>128 mg/L). The new test was shown to be diagnostically useful, easy to implement and less labour intensive than the classical method. © The Author 2014. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Implementation of a dose gradient method into optimization of dose distribution in prostate cancer 3D-CRT plans

PubMed Central

Giżyńska, Marta K.; Kukołowicz, Paweł F.; Kordowski, Paweł

2014-01-01

Aim The aim of this work is to present a method of beam weight and wedge angle optimization for patients with prostate cancer. Background 3D-CRT is usually realized with forward planning based on a trial and error method. Several authors have published a few methods of beam weight optimization applicable to the 3D-CRT. Still, none on these methods is in common use. Materials and methods Optimization is based on the assumption that the best plan is achieved if dose gradient at ICRU point is equal to zero. Our optimization algorithm requires beam quality index, depth of maximum dose, profiles of wedged fields and maximum dose to femoral heads. The method was tested for 10 patients with prostate cancer, treated with the 3-field technique. Optimized plans were compared with plans prepared by 12 experienced planners. Dose standard deviation in target volume, and minimum and maximum doses were analyzed. Results The quality of plans obtained with the proposed optimization algorithms was comparable to that prepared by experienced planners. Mean difference in target dose standard deviation was 0.1% in favor of the plans prepared by planners for optimization of beam weights and wedge angles. Introducing a correction factor for patient body outline for dose gradient at ICRU point improved dose distribution homogeneity. On average, a 0.1% lower standard deviation was achieved with the optimization algorithm. No significant difference in mean dose–volume histogram for the rectum was observed. Conclusions Optimization shortens very much time planning. The average planning time was 5 min and less than a minute for forward and computer optimization, respectively. PMID:25337411

Comparison of Fracture Gradient Methods for the FutureGen 2.0 Carbon Storage Site, Ill., USA.

NASA Astrophysics Data System (ADS)

Appriou, D.; Spane, F.; Wurstner White, S.; Kelley, M. E.; Sullivan, E. C.; Bonneville, A.; Gilmore, T. J.

2014-12-01

As part of a first-of-its-kind carbon dioxide storage project, FutureGen Industrial Alliance is planning to inject 1.1 MMt/yr of supercritical CO2 over a 20-year period within a 1240 m deep saline aquifer (Mount Simon Sandstone) located in Morgan County, Illinois, USA. Numerous aspects of the design and operational activities of the CO2 storage site are dependent on the geomechanical properties of the targeted reservoir zone, as well as of the overlying confining zone and the underlying crystalline Precambrian basement. Detailed determination of the state-of-stress within the subsurface is of paramount importance in successfully designing well drilling/completion aspects, as well as assessing the risk of induced seismicity and the potential for creating and/or reopening pre-existing fractures; all of which help ensure the safe long-term storage of injected CO2. The quantitative determination of the subsurface fracture gradient is one of the key geomechanical parameters for the site injection design and operational limits (e.g., maximum safe injection pressure). A characterization well drilled in 2011 provides subsurface geomechanical characterization information for the FutureGen 2.0 site, and includes: 1) continuous elastic properties inferred from sonic/acoustic wireline logs 2) discrete depth geomechanical laboratory core measurements and 3) results obtained from hydraulic fracturing tests of selected borehole/depth-intervals. In this paper, the precise fracture gradients derived from borehole geomechanical test results are compared with semi-empirical, fracture gradient calculation/relationships based on elastic property wireline surveys and laboratory geomechanical core test results. Implications for using various fracture-gradients obtained from the different methods are assessed using PNNL's subsurface multiphase flow and transport simulator STOMP-CO2. The implications for operational activities at the site (based on using different fracture gradients) are also discussed.

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.

Generalized three-dimensional lattice Boltzmann color-gradient method for immiscible two-phase pore-scale imbibition and drainage in porous media

NASA Astrophysics Data System (ADS)

Leclaire, Sébastien; Parmigiani, Andrea; Malaspinas, Orestis; Chopard, Bastien; Latt, Jonas

2017-03-01

This article presents a three-dimensional numerical framework for the simulation of fluid-fluid immiscible compounds in complex geometries, based on the multiple-relaxation-time lattice Boltzmann method to model the fluid dynamics and the color-gradient approach to model multicomponent flow interaction. New lattice weights for the lattices D3Q15, D3Q19, and D3Q27 that improve the Galilean invariance of the color-gradient model as well as for modeling the interfacial tension are derived and provided in the Appendix. The presented method proposes in particular an approach to model the interaction between the fluid compound and the solid, and to maintain a precise contact angle between the two-component interface and the wall. Contrarily to previous approaches proposed in the literature, this method yields accurate solutions even in complex geometries and does not suffer from numerical artifacts like nonphysical mass transfer along the solid wall, which is crucial for modeling imbibition-type problems. The article also proposes an approach to model inflow and outflow boundaries with the color-gradient method by generalizing the regularized boundary conditions. The numerical framework is first validated for three-dimensional (3D) stationary state (Jurin's law) and time-dependent (Washburn's law and capillary waves) problems. Then, the usefulness of the method for practical problems of pore-scale flow imbibition and drainage in porous media is demonstrated. Through the simulation of nonwetting displacement in two-dimensional random porous media networks, we show that the model properly reproduces three main invasion regimes (stable displacement, capillary fingering, and viscous fingering) as well as the saturating zone transition between these regimes. Finally, the ability to simulate immiscible two-component flow imbibition and drainage is validated, with excellent results, by numerical simulations in a Berea sandstone, a frequently used benchmark case used in this field, using a complex geometry that originates from a 3D scan of a porous sandstone. The methods presented in this article were implemented in the open-source PALABOS library, a general C++ matrix-based library well adapted for massive fluid flow parallel computation.

Quantitative structure-retention relationship models for the prediction of the reversed-phase HPLC gradient retention based on the heuristic method and support vector machine.

PubMed

Du, Hongying; Wang, Jie; Yao, Xiaojun; Hu, Zhide

2009-01-01

The heuristic method (HM) and support vector machine (SVM) were used to construct quantitative structure-retention relationship models by a series of compounds to predict the gradient retention times of reversed-phase high-performance liquid chromatography (HPLC) in three different columns. The aims of this investigation were to predict the retention times of multifarious compounds, to find the main properties of the three columns, and to indicate the theory of separation procedures. In our method, we correlated the retention times of many diverse structural analytes in three columns (Symmetry C18, Chromolith, and SG-MIX) with their representative molecular descriptors, calculated from the molecular structures alone. HM was used to select the most important molecular descriptors and build linear regression models. Furthermore, non-linear regression models were built using the SVM method; the performance of the SVM models were better than that of the HM models, and the prediction results were in good agreement with the experimental values. This paper could give some insights into the factors that were likely to govern the gradient retention process of the three investigated HPLC columns, which could theoretically supervise the practical experiment.

A Requirements-Driven Optimization Method for Acoustic Liners Using Analytic Derivatives

NASA Technical Reports Server (NTRS)

Berton, Jeffrey J.; Lopes, Leonard V.

2017-01-01

More than ever, there is flexibility and freedom in acoustic liner design. Subject to practical considerations, liner design variables may be manipulated to achieve a target attenuation spectrum. But characteristics of the ideal attenuation spectrum can be difficult to know. Many multidisciplinary system effects govern how engine noise sources contribute to community noise. Given a hardwall fan noise source to be suppressed, and using an analytical certification noise model to compute a community noise measure of merit, the optimal attenuation spectrum can be derived using multidisciplinary systems analysis methods. In a previous paper on this subject, a method deriving the ideal target attenuation spectrum that minimizes noise perceived by observers on the ground was described. A simple code-wrapping approach was used to evaluate a community noise objective function for an external optimizer. Gradients were evaluated using a finite difference formula. The subject of this paper is an application of analytic derivatives that supply precise gradients to an optimization process. Analytic derivatives improve the efficiency and accuracy of gradient-based optimization methods and allow consideration of more design variables. In addition, the benefit of variable impedance liners is explored using a multi-objective optimization.

Automatic knee cartilage delineation using inheritable segmentation

NASA Astrophysics Data System (ADS)

Dries, Sebastian P. M.; Pekar, Vladimir; Bystrov, Daniel; Heese, Harald S.; Blaffert, Thomas; Bos, Clemens; van Muiswinkel, Arianne M. C.

2008-03-01

We present a fully automatic method for segmentation of knee joint cartilage from fat suppressed MRI. The method first applies 3-D model-based segmentation technology, which allows to reliably segment the femur, patella, and tibia by iterative adaptation of the model according to image gradients. Thin plate spline interpolation is used in the next step to position deformable cartilage models for each of the three bones with reference to the segmented bone models. After initialization, the cartilage models are fine adjusted by automatic iterative adaptation to image data based on gray value gradients. The method has been validated on a collection of 8 (3 left, 5 right) fat suppressed datasets and demonstrated the sensitivity of 83+/-6% compared to manual segmentation on a per voxel basis as primary endpoint. Gross cartilage volume measurement yielded an average error of 9+/-7% as secondary endpoint. For cartilage being a thin structure, already small deviations in distance result in large errors on a per voxel basis, rendering the primary endpoint a hard criterion.

A critical analysis of some popular methods for the discretisation of the gradient operator in finite volume methods

NASA Astrophysics Data System (ADS)

Syrakos, Alexandros; Varchanis, Stylianos; Dimakopoulos, Yannis; Goulas, Apostolos; Tsamopoulos, John

2017-12-01

Finite volume methods (FVMs) constitute a popular class of methods for the numerical simulation of fluid flows. Among the various components of these methods, the discretisation of the gradient operator has received less attention despite its fundamental importance with regards to the accuracy of the FVM. The most popular gradient schemes are the divergence theorem (DT) (or Green-Gauss) scheme and the least-squares (LS) scheme. Both are widely believed to be second-order accurate, but the present study shows that in fact the common variant of the DT gradient is second-order accurate only on structured meshes whereas it is zeroth-order accurate on general unstructured meshes, and the LS gradient is second-order and first-order accurate, respectively. This is explained through a theoretical analysis and is confirmed by numerical tests. The schemes are then used within a FVM to solve a simple diffusion equation on unstructured grids generated by several methods; the results reveal that the zeroth-order accuracy of the DT gradient is inherited by the FVM as a whole, and the discretisation error does not decrease with grid refinement. On the other hand, use of the LS gradient leads to second-order accurate results, as does the use of alternative, consistent, DT gradient schemes, including a new iterative scheme that makes the common DT gradient consistent at almost no extra cost. The numerical tests are performed using both an in-house code and the popular public domain partial differential equation solver OpenFOAM.

A modified micrometeorological gradient method for estimating O3 dry depositions over a forest canopy

NASA Astrophysics Data System (ADS)

Wu, Z. Y.; Zhang, L.; Wang, X. M.; Munger, J. W.

2015-07-01

Small pollutant concentration gradients between levels above a plant canopy result in large uncertainties in estimated air-surface exchange fluxes when using existing micrometeorological gradient methods, including the aerodynamic gradient method (AGM) and the modified Bowen ratio method (MBR). A modified micrometeorological gradient method (MGM) is proposed in this study for estimating O3 dry deposition fluxes over a forest canopy using concentration gradients between a level above and a level below the canopy top, taking advantage of relatively large gradients between these levels due to significant pollutant uptake in the top layers of the canopy. The new method is compared with the AGM and MBR methods and is also evaluated using eddy-covariance (EC) flux measurements collected at the Harvard Forest Environmental Measurement Site, Massachusetts, during 1993-2000. All three gradient methods (AGM, MBR, and MGM) produced similar diurnal cycles of O3 dry deposition velocity (Vd(O3)) to the EC measurements, with the MGM method being the closest in magnitude to the EC measurements. The multi-year average Vd(O3) differed significantly between these methods, with the AGM, MBR, and MGM method being 2.28, 1.45, and 1.18 times that of the EC, respectively. Sensitivity experiments identified several input parameters for the MGM method as first-order parameters that affect the estimated Vd(O3). A 10% uncertainty in the wind speed attenuation coefficient or canopy displacement height can cause about 10% uncertainty in the estimated Vd(O3). An unrealistic leaf area density vertical profile can cause an uncertainty of a factor of 2.0 in the estimated Vd(O3). Other input parameters or formulas for stability functions only caused an uncertainly of a few percent. The new method provides an alternative approach to monitoring/estimating long-term deposition fluxes of similar pollutants over tall canopies.

A matrix-form GSM-CFD solver for incompressible fluids and its application to hemodynamics

NASA Astrophysics Data System (ADS)

Yao, Jianyao; Liu, G. R.

2014-10-01

A GSM-CFD solver for incompressible flows is developed based on the gradient smoothing method (GSM). A matrix-form algorithm and corresponding data structure for GSM are devised to efficiently approximate the spatial gradients of field variables using the gradient smoothing operation. The calculated gradient values on various test fields show that the proposed GSM is capable of exactly reproducing linear field and of second order accuracy on all kinds of meshes. It is found that the GSM is much more robust to mesh deformation and therefore more suitable for problems with complicated geometries. Integrated with the artificial compressibility approach, the GSM is extended to solve the incompressible flows. As an example, the flow simulation of carotid bifurcation is carried out to show the effectiveness of the proposed GSM-CFD solver. The blood is modeled as incompressible Newtonian fluid and the vessel is treated as rigid wall in this paper.

Thermal Boundary Layer Effects on Line-of-Sight Tunable Diode Laser Absorption Spectroscopy (TDLAS) Gas Concentration Measurements.

PubMed

Qu, Zhechao; Werhahn, Olav; Ebert, Volker

2018-06-01

The effects of thermal boundary layers on tunable diode laser absorption spectroscopy (TDLAS) measurement results must be quantified when using the line-of-sight (LOS) TDLAS under conditions with spatial temperature gradient. In this paper, a new methodology based on spectral simulation is presented quantifying the LOS TDLAS measurement deviation under conditions with thermal boundary layers. The effects of different temperature gradients and thermal boundary layer thickness on spectral collisional widths and gas concentration measurements are quantified. A CO 2 TDLAS spectrometer, which has two gas cells to generate the spatial temperature gradients, was employed to validate the simulation results. The measured deviations and LOS averaged collisional widths are in very good agreement with the simulated results for conditions with different temperature gradients. We demonstrate quantification of thermal boundary layers' thickness with proposed method by exploitation of the LOS averaged the collisional width of the path-integrated spectrum.

Using dual classifications in the development of avian wetland indices of biological integrity for wetlands in West Virginia, USA.

PubMed

Veselka, Walter; Anderson, James T; Kordek, Walter S

2010-05-01

Considerable resources are being used to develop and implement bioassessment methods for wetlands to ensure that "biological integrity" is maintained under the United States Clean Water Act. Previous research has demonstrated that avian composition is susceptible to human impairments at multiple spatial scales. Using a site-specific disturbance gradient, we built avian wetland indices of biological integrity (AW-IBI) specific to two wetland classification schemes, one based on vegetative structure and the other based on the wetland's position in the landscape and sources of water. The resulting class-specific AW-IBI was comprised of one to four metrics that varied in their sensitivity to the disturbance gradient. Some of these metrics were specific to only one of the classification schemes, whereas others could discriminate varying levels of disturbance regardless of classification scheme. Overall, all of the derived biological indices specific to the vegetative structure-based classes of wetlands had a significant relation with the disturbance gradient; however, the biological index derived for floodplain wetlands exhibited a more consistent response to a local disturbance gradient. We suspect that the consistency of this response is due to the inherent nature of the connectivity of available habitat in floodplain wetlands.

Reliable clarity automatic-evaluation method for optical remote sensing images

NASA Astrophysics Data System (ADS)

Qin, Bangyong; Shang, Ren; Li, Shengyang; Hei, Baoqin; Liu, Zhiwen

2015-10-01

Image clarity, which reflects the sharpness degree at the edge of objects in images, is an important quality evaluate index for optical remote sensing images. Scholars at home and abroad have done a lot of work on estimation of image clarity. At present, common clarity-estimation methods for digital images mainly include frequency-domain function methods, statistical parametric methods, gradient function methods and edge acutance methods. Frequency-domain function method is an accurate clarity-measure approach. However, its calculation process is complicate and cannot be carried out automatically. Statistical parametric methods and gradient function methods are both sensitive to clarity of images, while their results are easy to be affected by the complex degree of images. Edge acutance method is an effective approach for clarity estimate, while it needs picking out the edges manually. Due to the limits in accuracy, consistent or automation, these existing methods are not applicable to quality evaluation of optical remote sensing images. In this article, a new clarity-evaluation method, which is based on the principle of edge acutance algorithm, is proposed. In the new method, edge detection algorithm and gradient search algorithm are adopted to automatically search the object edges in images. Moreover, The calculation algorithm for edge sharpness has been improved. The new method has been tested with several groups of optical remote sensing images. Compared with the existing automatic evaluation methods, the new method perform better both in accuracy and consistency. Thus, the new method is an effective clarity evaluation method for optical remote sensing images.

Estimating the number of people in crowded scenes

NASA Astrophysics Data System (ADS)

Kim, Minjin; Kim, Wonjun; Kim, Changick

2011-01-01

This paper presents a method to estimate the number of people in crowded scenes without using explicit object segmentation or tracking. The proposed method consists of three steps as follows: (1) extracting space-time interest points using eigenvalues of the local spatio-temporal gradient matrix, (2) generating crowd regions based on space-time interest points, and (3) estimating the crowd density based on the multiple regression. In experimental results, the efficiency and robustness of our proposed method are demonstrated by using PETS 2009 dataset.

A spectrophotometric screening method for avermectin oxidizing microorganisms.

PubMed

Wang, Yuan-Shan; Hu, Qi-Wei; Zheng, Xing-Chang; Zhang, Jian-Fen; Zheng, Yu-Guo

2017-04-01

A spectrophotometric screening method for avermectin oxidizing microbes by determination of 4″-oxo-avermectin was established based on the reaction between 4″-oxo-avermectin and 2,4-dinitrophenylhydrazine. Combined with a gradient HPLC assay, microorganisms capable of regioselectively oxidizing avermectin to 4″-oxo-avermectin were successfully obtained by this method. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Kolbasin, V. A.; Ivanov, A. I.; Pedash, V. Y.

The two pulse shape discrimination methods were implemented in real-time. The pulse gradient analysis method was implemented programmatically on PC. The method based on artificial neural network was programmatically implemented using CUDA platform. It is shown that both implementations can provide up to 10{sup 6} pulses per second processing performance. The results for pulse shape discrimination using polycrystalline stilbene and LiF detectors were shown. (authors)

A new sparse optimization scheme for simultaneous beam angle and fluence map optimization in radiotherapy planning

NASA Astrophysics Data System (ADS)

Liu, Hongcheng; Dong, Peng; Xing, Lei

2017-08-01

{{\\ell }2,1} -minimization-based sparse optimization was employed to solve the beam angle optimization (BAO) in intensity-modulated radiation therapy (IMRT) planning. The technique approximates the exact BAO formulation with efficiently computable convex surrogates, leading to plans that are inferior to those attainable with recently proposed gradient-based greedy schemes. In this paper, we alleviate/reduce the nontrivial inconsistencies between the {{\\ell }2,1} -based formulations and the exact BAO model by proposing a new sparse optimization framework based on the most recent developments in group variable selection. We propose the incorporation of the group-folded concave penalty (gFCP) as a substitution to the {{\\ell }2,1} -minimization framework. The new formulation is then solved by a variation of an existing gradient method. The performance of the proposed scheme is evaluated by both plan quality and the computational efficiency using three IMRT cases: a coplanar prostate case, a coplanar head-and-neck case, and a noncoplanar liver case. Involved in the evaluation are two alternative schemes: the {{\\ell }2,1} -minimization approach and the gradient norm method (GNM). The gFCP-based scheme outperforms both counterpart approaches. In particular, gFCP generates better plans than those obtained using the {{\\ell }2,1} -minimization for all three cases with a comparable computation time. As compared to the GNM, the gFCP improves both the plan quality and computational efficiency. The proposed gFCP-based scheme provides a promising framework for BAO and promises to improve both planning time and plan quality.

A new sparse optimization scheme for simultaneous beam angle and fluence map optimization in radiotherapy planning.

PubMed

Liu, Hongcheng; Dong, Peng; Xing, Lei

2017-07-20

[Formula: see text]-minimization-based sparse optimization was employed to solve the beam angle optimization (BAO) in intensity-modulated radiation therapy (IMRT) planning. The technique approximates the exact BAO formulation with efficiently computable convex surrogates, leading to plans that are inferior to those attainable with recently proposed gradient-based greedy schemes. In this paper, we alleviate/reduce the nontrivial inconsistencies between the [Formula: see text]-based formulations and the exact BAO model by proposing a new sparse optimization framework based on the most recent developments in group variable selection. We propose the incorporation of the group-folded concave penalty (gFCP) as a substitution to the [Formula: see text]-minimization framework. The new formulation is then solved by a variation of an existing gradient method. The performance of the proposed scheme is evaluated by both plan quality and the computational efficiency using three IMRT cases: a coplanar prostate case, a coplanar head-and-neck case, and a noncoplanar liver case. Involved in the evaluation are two alternative schemes: the [Formula: see text]-minimization approach and the gradient norm method (GNM). The gFCP-based scheme outperforms both counterpart approaches. In particular, gFCP generates better plans than those obtained using the [Formula: see text]-minimization for all three cases with a comparable computation time. As compared to the GNM, the gFCP improves both the plan quality and computational efficiency. The proposed gFCP-based scheme provides a promising framework for BAO and promises to improve both planning time and plan quality.

Concentration gradient along the scala tympani after local application of gentamicin to the round window membrane.

PubMed

Plontke, Stefan K; Mynatt, Robert; Gill, Ruth M; Borgmann, Stefan; Salt, Alec N

2007-07-01

The distribution of gentamicin along the fluid spaces of the cochlea after local applications has never previously been demonstrated. Computer simulations have predicted that significant basal-apical concentration gradients might be expected, and histologic studies indicate that hair cell damage is greater at the base than at the apex after local gentamicin application. In the present study, gradients of gentamicin along the cochlea were measured. A recently developed method of sampling perilymph from the cochlear apex of guinea pigs was used in which the samples represent fluid originating from different regions along the scala tympani. Gentamicin concentration was determined in sequential apical samples that were taken after up to 3 hours of local application to the round window niche. Substantial gradients of gentamicin along the length of the scala tympani were demonstrated and quantified, averaging more than 4,000 times greater concentration at the base compared with the apex at the time of sampling. Peak concentrations and gradients for gentamicin varied considerably between animals, likely resulting from variations in round window membrane permeability and rates of perilymph flow. The large gradients for gentamicin demonstrated here in guinea pigs account for how it is possible to suppress vestibular function in some patients with a local application of gentamicin without damaging auditory function. Variations in round window membrane permeability and in perilymph flow could account for why hearing losses are observed in some patients.

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

NASA Astrophysics Data System (ADS)

Tape, Carl; Liu, Qinya; Tromp, Jeroen

2007-03-01

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

Segmentation of touching mycobacterium tuberculosis from Ziehl-Neelsen stained sputum smear images

NASA Astrophysics Data System (ADS)

Xu, Chao; Zhou, Dongxiang; Liu, Yunhui

2015-12-01

Touching Mycobacterium tuberculosis objects in the Ziehl-Neelsen stained sputum smear images present different shapes and invisible boundaries in the adhesion areas, which increases the difficulty in objects recognition and counting. In this paper, we present a segmentation method of combining the hierarchy tree analysis with gradient vector flow snake to address this problem. The skeletons of the objects are used for structure analysis based on the hierarchy tree. The gradient vector flow snake is used to estimate the object edge. Experimental results show that the single objects composing the touching objects are successfully segmented by the proposed method. This work will improve the accuracy and practicability of the computer-aided diagnosis of tuberculosis.

High Performance Liquid Chromatographic Analysis of Phytoplankton Pigments Using a C16-Amide Column

EPA Science Inventory

A reverse-phase high performance liquid chromatographic (RP-HPLC) method was developed to analyze in a single run, most polar and non-polar chlorophylls and carotenoids from marine phytoplankton. The method is based on a RP-C16-Amide column and a ternary gradient system consistin...

Two-dimensional imaging of two types of radicals by the CW-EPR method

NASA Astrophysics Data System (ADS)

Czechowski, Tomasz; Krzyminiewski, Ryszard; Jurga, Jan; Chlewicki, Wojciech

2008-01-01

The CW-EPR method of image reconstruction is based on sample rotation in a magnetic field with a constant gradient (50 G/cm). In order to obtain a projection (radical density distribution) along a given direction, the EPR spectra are recorded with and without the gradient. Deconvolution, then gives the distribution of the spin density. Projection at 36 different angles gives the information that is necessary for reconstruction of the radical distribution. The problem becomes more complex when there are at least two types of radicals in the sample, because the deconvolution procedure does not give satisfactory results. We propose a method to calculate the projections for each radical, based on iterative procedures. The images of density distribution for each radical obtained by our procedure have proved that the method of deconvolution, in combination with iterative fitting, provides correct results. The test was performed on a sample of polymer PPS Br 111 ( p-phenylene sulphide) with glass fibres and minerals. The results indicated a heterogeneous distribution of radicals in the sample volume. The images obtained were in agreement with the known shape of the sample.

Accelerating atomic structure search with cluster regularization

NASA Astrophysics Data System (ADS)

Sørensen, K. H.; Jørgensen, M. S.; Bruix, A.; Hammer, B.

2018-06-01

We present a method for accelerating the global structure optimization of atomic compounds. The method is demonstrated to speed up the finding of the anatase TiO2(001)-(1 × 4) surface reconstruction within a density functional tight-binding theory framework using an evolutionary algorithm. As a key element of the method, we use unsupervised machine learning techniques to categorize atoms present in a diverse set of partially disordered surface structures into clusters of atoms having similar local atomic environments. Analysis of more than 1000 different structures shows that the total energy of the structures correlates with the summed distances of the atomic environments to their respective cluster centers in feature space, where the sum runs over all atoms in each structure. Our method is formulated as a gradient based minimization of this summed cluster distance for a given structure and alternates with a standard gradient based energy minimization. While the latter minimization ensures local relaxation within a given energy basin, the former enables escapes from meta-stable basins and hence increases the overall performance of the global optimization.

Systematic Interpolation Method Predicts Antibody Monomer-Dimer Separation by Gradient Elution Chromatography at High Protein Loads.

PubMed

Creasy, Arch; Reck, Jason; Pabst, Timothy; Hunter, Alan; Barker, Gregory; Carta, Giorgio

2018-05-29

A previously developed empirical interpolation (EI) method is extended to predict highly overloaded multicomponent elution behavior on a cation exchange (CEX) column based on batch isotherm data. Instead of a fully mechanistic model, the EI method employs an empirically modified multicomponent Langmuir equation to correlate two-component adsorption isotherm data at different salt concentrations. Piecewise cubic interpolating polynomials are then used to predict competitive binding at intermediate salt concentrations. The approach is tested for the separation of monoclonal antibody monomer and dimer mixtures by gradient elution on the cation exchange resin Nuvia HR-S. Adsorption isotherms are obtained over a range of salt concentrations with varying monomer and dimer concentrations. Coupled with a lumped kinetic model, the interpolated isotherms predict the column behavior for highly overloaded conditions. Predictions based on the EI method showed good agreement with experimental elution curves for protein loads up to 40 mg/mL column or about 50% of the column binding capacity. The approach can be extended to other chromatographic modalities and to more than two components. This article is protected by copyright. All rights reserved.

Research on Aircraft Target Detection Algorithm Based on Improved Radial Gradient Transformation

NASA Astrophysics Data System (ADS)

Zhao, Z. M.; Gao, X. M.; Jiang, D. N.; Zhang, Y. Q.

2018-04-01

Aiming at the problem that the target may have different orientation in the unmanned aerial vehicle (UAV) image, the target detection algorithm based on the rotation invariant feature is studied, and this paper proposes a method of RIFF (Rotation-Invariant Fast Features) based on look up table and polar coordinate acceleration to be used for aircraft target detection. The experiment shows that the detection performance of this method is basically equal to the RIFF, and the operation efficiency is greatly improved.

Demarcation of continental-oceanic transition zone using angular differences between gradients of geophysical fields

NASA Astrophysics Data System (ADS)

Jilinski, Pavel; Meju, Max A.; Fontes, Sergio L.

2013-10-01

The commonest technique for determination of the continental-oceanic crustal boundary or transition (COB) zone is based on locating and visually correlating bathymetric and potential field anomalies and constructing crustal models constrained by seismic data. In this paper, we present a simple method for spatial correlation of bathymetric and potential field geophysical anomalies. Angular differences between gradient directions are used to determine different types of correlation between gravity and bathymetric or magnetic data. It is found that the relationship between bathymetry and gravity anomalies can be correctly identified using this method. It is demonstrated, by comparison with previously published models for the southwest African margin, that this method enables the demarcation of the zone of transition from oceanic to continental crust assuming that this it is associated with geophysical anomalies, which can be correlated using gradient directions rather than magnitudes. We also applied this method, supported by 2-D gravity modelling, to the more complex Liberia and Cote d'Ivoire-Ghana sectors of the West African transform margin and obtained results that are in remarkable agreement with past predictions of the COB in that region. We suggest the use of this method for a first-pass interpretation as a prelude to rigorous modelling of the COB in frontier areas.

Research on infrared ship detection method in sea-sky background

NASA Astrophysics Data System (ADS)

Tang, Da; Sun, Gang; Wang, Ding-he; Niu, Zhao-dong; Chen, Zeng-ping

2013-09-01

An approach to infrared ship detection based on sea-sky-line(SSL) detection, ROI extraction and feature recognition is proposed in this paper. Firstly, considering that far ships are expected to be adjacent to the SSL, SSL is detected to find potential target areas. Radon transform is performed on gradient image to choose candidate SSLs, and detection result is given by fuzzy synthetic evaluation values. Secondly, in view of recognizable condition that there should be enough differences between target and background in infrared image, two gradient masks have been created and improved as practical guidelines in eliminating false alarm. Thirdly, extract ROI near the SSL by using multi-grade segmentation and fusion method after image sharpening, and unsuitable candidates are screened out according to the gradient masks and ROI shape. Finally, we segment the rest of ROIs by two-stage modified OTSU, and calculate target confidence as a standard measuring the facticity of target. Compared with other ship detection methods, proposed method is suitable for bipolar targets, which offers a good practicability and accuracy, and achieves a satisfying detection speed. Detection experiments with 200 thousand frames show that the proposed method is widely applicable, powerful in resistance to interferences and noises with a detection rate of above 95%, which satisfies the engineering needs commendably.

Limited-memory BFGS based least-squares pre-stack Kirchhoff depth migration

NASA Astrophysics Data System (ADS)

Wu, Shaojiang; Wang, Yibo; Zheng, Yikang; Chang, Xu

2015-08-01

Least-squares migration (LSM) is a linearized inversion technique for subsurface reflectivity estimation. Compared to conventional migration algorithms, it can improve spatial resolution significantly with a few iterative calculations. There are three key steps in LSM, (1) calculate data residuals between observed data and demigrated data using the inverted reflectivity model; (2) migrate data residuals to form reflectivity gradient and (3) update reflectivity model using optimization methods. In order to obtain an accurate and high-resolution inversion result, the good estimation of inverse Hessian matrix plays a crucial role. However, due to the large size of Hessian matrix, the inverse matrix calculation is always a tough task. The limited-memory BFGS (L-BFGS) method can evaluate the Hessian matrix indirectly using a limited amount of computer memory which only maintains a history of the past m gradients (often m < 10). We combine the L-BFGS method with least-squares pre-stack Kirchhoff depth migration. Then, we validate the introduced approach by the 2-D Marmousi synthetic data set and a 2-D marine data set. The results show that the introduced method can effectively obtain reflectivity model and has a faster convergence rate with two comparison gradient methods. It might be significant for general complex subsurface imaging.

Pressure Gradient Effects on Hypersonic Cavity Flow Heating

NASA Technical Reports Server (NTRS)

Everhart, Joel L.; Alter, Stephen J.; Merski, N. Ronald; Wood, William A.; Prabhu, Ramadas K.

2006-01-01

The effect of a pressure gradient on the local heating disturbance of rectangular cavities tested at hypersonic freestream conditions has been globally assessed using the two-color phosphor thermography method. These experiments were conducted in the Langley 31-Inch Mach 10 Tunnel and were initiated in support of the Space Shuttle Return-To-Flight Program. Two blunted-nose test surface geometries were developed, including an expansion plate test surface with nearly constant negative pressure gradient and a flat plate surface with nearly zero pressure gradient. The test surface designs and flow characterizations were performed using two-dimensional laminar computational methods, while the experimental boundary layer state conditions were inferred using the measured heating distributions. Three-dimensional computational predictions of the entire model geometry were used as a check on the design process. Both open-flow and closed-flow cavities were tested on each test surface. The cavity design parameters and the test condition matrix were established using the computational predictions. Preliminary conclusions based on an analysis of only the cavity centerline data indicate that the presence of the pressure gradient did not alter the open cavity heating for laminar-entry/laminar-exit flows, but did raise the average floor heating for closed cavities. The results of these risk-reduction studies will be used to formulate a heating assessment of potential damage scenarios occurring during future Space Shuttle flights.

Pressure Gradient Effects on Hypersonic Cavity Flow Heating

NASA Technical Reports Server (NTRS)

Everhart, Joel L.; Alter, Stephen J.; Merski, N. Ronald; Wood, William A.; Prabhu, Ramdas K.

2007-01-01

The effect of a pressure gradient on the local heating disturbance of rectangular cavities tested at hypersonic freestream conditions has been globally assessed using the two-color phosphor thermography method. These experiments were conducted in the Langley 31-Inch Mach 10 Tunnel and were initiated in support of the Space Shuttle Return-To-Flight Program. Two blunted-nose test surface geometries were developed, including an expansion plate test surface with nearly constant negative pressure gradient and a flat plate surface with nearly zero pressure gradient. The test surface designs and flow characterizations were performed using two-dimensional laminar computational methods, while the experimental boundary layer state conditions were inferred using the measured heating distributions. Three-dimensional computational predictions of the entire model geometry were used as a check on the design process. Both open-flow and closed-flow cavities were tested on each test surface. The cavity design parameters and the test condition matrix were established using the computational predictions. Preliminary conclusions based on an analysis of only the cavity centerline data indicate that the presence of the pressure gradient did not alter the open cavity heating for laminar-entry/laminar-exit flows, but did raise the average floor heating for closed cavities. The results of these risk-reduction studies will be used to formulate a heating assessment of potential damage scenarios occurring during future Space Shuttle flights.

Method and apparatus for determining vertical heat flux of geothermal field

DOEpatents

Poppendiek, Heinz F.

1982-01-01

A method and apparatus for determining vertical heat flux of a geothermal field, and mapping the entire field, is based upon an elongated heat-flux transducer (10) comprised of a length of tubing (12) of relatively low thermal conductivity with a thermopile (20) inside for measuring the thermal gradient between the ends of the transducer after it has been positioned in a borehole for a period sufficient for the tube to reach thermal equilibrium. The transducer is thermally coupled to the surrounding earth by a fluid annulus, preferably water or mud. A second transducer comprised of a length of tubing of relatively high thermal conductivity is used for a second thermal gradient measurement. The ratio of the first measurement to the second is then used to determine the earth's thermal conductivity, k.sub..infin., from a precalculated graph, and using the value of thermal conductivity thus determined, then determining the vertical earth temperature gradient, b, from predetermined steady state heat balance equations which relate the undisturbed vertical earth temperature distributions at some distance from the borehole and earth thermal conductivity to the temperature gradients in the transducers and their thermal conductivity. The product of the earth's thermal conductivity, k.sub..infin., and the earth's undisturbed vertical temperature gradient, b, then determines the earth's vertical heat flux. The process can be repeated many times for boreholes of a geothermal field to map vertical heat flux.

Environment-based pin-power reconstruction method for homogeneous core calculations

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

Leroyer, H.; Brosselard, C.; Girardi, E.

2012-07-01

Core calculation schemes are usually based on a classical two-step approach associated with assembly and core calculations. During the first step, infinite lattice assemblies calculations relying on a fundamental mode approach are used to generate cross-sections libraries for PWRs core calculations. This fundamental mode hypothesis may be questioned when dealing with loading patterns involving several types of assemblies (UOX, MOX), burnable poisons, control rods and burn-up gradients. This paper proposes a calculation method able to take into account the heterogeneous environment of the assemblies when using homogeneous core calculations and an appropriate pin-power reconstruction. This methodology is applied to MOXmore » assemblies, computed within an environment of UOX assemblies. The new environment-based pin-power reconstruction is then used on various clusters of 3x3 assemblies showing burn-up gradients and UOX/MOX interfaces, and compared to reference calculations performed with APOLLO-2. The results show that UOX/MOX interfaces are much better calculated with the environment-based calculation scheme when compared to the usual pin-power reconstruction method. The power peak is always better located and calculated with the environment-based pin-power reconstruction method on every cluster configuration studied. This study shows that taking into account the environment in transport calculations can significantly improve the pin-power reconstruction so far as it is consistent with the core loading pattern. (authors)« less

A new method of determining moisture gradient in wood

Treesearch

Zhiyong Cai

2008-01-01

Moisture gradient in wood and wood composites is one of most important factors that affects both physical stability and mechanical performance. This paper describes a method for measuring moisture gradient in lumber and engineering wood composites as it varies across material thickness. This innovative method employs a collimated radiation beam (x rays or [gamma] rays...

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.

GOCE gravity gradient data for lithospheric modeling and geophysical exploration research

NASA Astrophysics Data System (ADS)

Bouman, Johannes; Ebbing, Jörg; Meekes, Sjef; Lieb, Verena; Fuchs, Martin; Schmidt, Michael; Fattah, Rader Abdul; Gradmann, Sofie; Haagmans, Roger

2013-04-01

GOCE gravity gradient data can improve modeling of the Earth's lithosphere and upper mantle, contributing to a better understanding of the Earth's dynamic processes. We present a method to compute user-friendly GOCE gravity gradient grids at mean satellite altitude, which are easier to use than the original GOCE gradients that are given in a rotating instrument frame. In addition, the GOCE gradients are combined with terrestrial gravity data to obtain high resolution grids of gravity field information close to the Earth's surface. We also present a case study for the North-East Atlantic margin, where we analyze the use of satellite gravity gradients by comparison with a well-constrained 3D density model that provides a detailed picture from the upper mantle to the top basement (base of sediments). We demonstrate how gravity gradients can increase confidence in the modeled structures by calculating the sensitvity of model geometry and applied densities at different observation heights; e.g. satellite height and near surface. Finally, this sensitivity analysis is used as input to study the Rub' al Khali desert in Saudi Arabia. In terms of modeling and data availability this is a frontier area. Here gravity gradient data help especially to set up the regional crustal structure, which in turn allows to refine sedimentary thickness estimates and the regional heat-flow pattern. This can have implications for hydrocarbon exploration in the region.

Prediction of gradient retention data for hydrophilic interaction liquid chromatographic separation of native and fluorescently labeled oligosaccharides.

PubMed

Vaňková, Nikola; Česla, Petr

2017-02-17

In this work, we have investigated the predictive properties of mixed-mode retention model and oligomeric mixed-mode model, taking into account the contribution of monomeric units to the retention, in hydrophilic interaction liquid chromatography. The gradient retention times of native maltooligosaccharides and their fluorescent derivatives were predicted in the oligomeric series with number of monomeric glucose units in the range from two to seven. The maltooligosaccharides were separated on a packed column with carbamoyl-bonded silica stationary phase and 15 gradient profiles with different initial and final mobile phase composition were used with the gradient times 5; 7.5 and 10min. The predicted gradient retention times were compared for calculations based on isocratic retention data and gradient retention data, which provided better accuracy of the results. By comparing two different mobile phase additives, the more accurate retention times were predicted in mobile phases containing ammonium acetate. The acidic derivatives, prepared by reaction of an oligosaccharide with 2-aminobenzoic acid or 8-aminonaphthalene-1,3,6-trisulfonic acid, provided more accurate predictions of the retention data in comparison to native oligosaccharides or their neutral derivatives. The oligomeric mixed-mode model allowed prediction of gradient retention times using only one gradient profile, which significantly speeded-up the method development. Copyright © 2017 Elsevier B.V. All rights reserved.

Accelerated gradient methods for the x-ray imaging of solar flares

NASA Astrophysics Data System (ADS)

Bonettini, S.; Prato, M.

2014-05-01

In this paper we present new optimization strategies for the reconstruction of x-ray images of solar flares by means of the data collected by the Reuven Ramaty high energy solar spectroscopic imager. The imaging concept of the satellite is based on rotating modulation collimator instruments, which allow the use of both Fourier imaging approaches and reconstruction techniques based on the straightforward inversion of the modulated count profiles. Although in the last decade, greater attention has been devoted to the former strategies due to their very limited computational cost, here we consider the latter model and investigate the effectiveness of different accelerated gradient methods for the solution of the corresponding constrained minimization problem. Moreover, regularization is introduced through either an early stopping of the iterative procedure, or a Tikhonov term added to the discrepancy function by means of a discrepancy principle accounting for the Poisson nature of the noise affecting the data.

On the application of the partition of unity method for nonlocal response of low-dimensional structures

NASA Astrophysics Data System (ADS)

Natarajan, Sundararajan

2014-12-01

The main objectives of the paper are to (1) present an overview of nonlocal integral elasticity and Aifantis gradient elasticity theory and (2) discuss the application of partition of unity methods to study the response of low-dimensional structures. We present different choices of approximation functions for gradient elasticity, namely Lagrange intepolants, moving least-squares approximants and non-uniform rational B-splines. Next, we employ these approximation functions to study the response of nanobeams based on Euler-Bernoulli and Timoshenko theories as well as to study nanoplates based on first-order shear deformation theory. The response of nanobeams and nanoplates is studied using Eringen's nonlocal elasticity theory. The influence of the nonlocal parameter, the beam and the plate aspect ratio and the boundary conditions on the global response is numerically studied. The influence of a crack on the axial vibration and buckling characteristics of nanobeams is also numerically studied.

Analysis of low molecular weight acids by monolithic immobilized pH gradient-based capillary isoelectric focusing coupled with mass spectrometry.

PubMed

Wang, Tingting; Fekete, Agnes; Gaspar, Andras; Ma, Junfeng; Liang, Zhen; Yuan, Huiming; Zhang, Lihua; Schmitt-Kopplin, Philippe; Zhang, Yukui

2011-02-01

A novel method for the separation and detection of low molecular weight (LMW) acids was developed using monolithic immobilized pH gradient-based capillary isoelectric focusing coupled with mass spectrometry. Two main parameters, focusing conditions and delivery buffer conditions, which might affect separation efficiency, were optimized with the focusing time of 7 min at 350 V/cm and the delivery buffer of 50% (v/v) acetonitrile in 10 mmol/L ammonium formate (pH 3.0). Under these conditions, the linear correlation between the volume of delivery solvent and the pK(a) of the model components was observed. In addition, the separation mechanism of LMW acids was proposed as well. We suppose that this method may provide a useful tool for the characterization of LMW components (e.g. natural organic matter of different origins). Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dependence of nuclear quadrupole resonance transitions on the electric field gradient asymmetry parameter for nuclides with half-integer spins

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

Cho, Herman

2016-09-01

Allowed transition energies and eigenstate expansions have been calculated and tabulated in numerical form as functions of the electric field gradient asymmetry parameter for the zero field Hamiltonian of quadrupolar nuclides with I = 3/2, 5/2, 7/2, and 9/2. These results may be used to interpret nuclear quadrupole resonance (NQR) spectra and extract accurate values of the electric field gradient tensors. Applications of NQR methods to studies of electronic structure in heavy element systems are proposed. This material is based upon work supported by the U.S. Department of Energy Office of Science, Office of Basic Energy Sciences, Heavy Element Chemistrymore » program.« less

Artifacts Quantification of Metal Implants in MRI

NASA Astrophysics Data System (ADS)

Vrachnis, I. N.; Vlachopoulos, G. F.; Maris, T. G.; Costaridou, L. I.

2017-11-01

The presence of materials with different magnetic properties, such as metal implants, causes distortion of the magnetic field locally, resulting in signal voids and pile ups, i.e. susceptibility artifacts in MRI. Quantitative and unbiased measurement of the artifact is prerequisite for optimization of acquisition parameters. In this study an image gradient based segmentation method is proposed for susceptibility artifact quantification. The method captures abrupt signal alterations by calculation of the image gradient. Then the artifact is quantified in terms of its extent by an automated cross entropy thresholding method as image area percentage. The proposed method for artifact quantification was tested in phantoms containing two orthopedic implants with significantly different magnetic permeabilities. The method was compared against a method proposed in the literature, considered as a reference, demonstrating moderate to good correlation (Spearman’s rho = 0.62 and 0.802 in case of titanium and stainless steel implants). The automated character of the proposed quantification method seems promising towards MRI acquisition parameter optimization.

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

PubMed

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

2012-11-01

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

Fifty shades of gradients: does the pressure gradient in venous sinus stenting for idiopathic intracranial hypertension matter? A systematic review.

PubMed

McDougall, Cameron M; Ban, Vin Shen; Beecher, Jeffrey; Pride, Lee; Welch, Babu G

2018-03-02

OBJECTIVE The role of venous sinus stenting (VSS) for idiopathic intracranial hypertension (IIH) is not well understood. The aim of this systematic review is to attempt to identify subsets of patients with IIH who will benefit from VSS based on the pressure gradients of their venous sinus stenosis. METHODS MEDLINE/PubMed was searched for studies reporting venous pressure gradients across the stenotic segment of the venous sinus, pre- and post-stent pressure gradients, and clinical outcomes after VSS. Findings are reported according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. RESULTS From 32 eligible studies, a total of 186 patients were included in the analysis. Patients who had favorable outcomes had higher mean pressure gradients (22.8 ± 11.5 mm Hg vs 17.4 ± 8.0 mm Hg, p = 0.033) and higher changes in pressure gradients after stent placement (19.4 ± 10.0 mm Hg vs 12.0 ± 6.0 mm Hg, p = 0.006) compared with those with unfavorable outcomes. The post-stent pressure gradients between the 2 groups were not significantly different (2.8 ± 4.0 mm Hg vs 2.7 ± 2.0 mm Hg, p = 0.934). In a multivariate stepwise logistic regression controlling for age, sex, body mass index, CSF opening pressure, pre-stent pressure gradient, and post-stent pressure gradient, the change in pressure gradient with stent placement was found to be an independent predictor of favorable outcome (p = 0.028). Using a pressure gradient of 21 as a cutoff, 81/86 (94.2%) of patients with a gradient > 21 achieved favorable outcomes, compared with 82/100 (82.0%) of patients with a gradient ≤ 21 (p = 0.022). CONCLUSIONS There appears to be a relationship between the pressure gradient of venous sinus stenosis and the success of VSS in IIH. A randomized controlled trial would help elucidate this relationship and potentially guide patient selection.

[Fast optimization of stepwise gradient conditions for ternary mobile phase in reversed-phase high performance liquid chromatography].

PubMed

Shan, Yi-chu; Zhang, Yu-kui; Zhao, Rui-huan

2002-07-01

In high performance liquid chromatography, it is necessary to apply multi-composition gradient elution for the separation of complex samples such as environmental and biological samples. Multivariate stepwise gradient elution is one of the most efficient elution modes, because it combines the high selectivity of multi-composition mobile phase and shorter analysis time of gradient elution. In practical separations, the separation selectivity of samples can be effectively adjusted by using ternary mobile phase. For the optimization of these parameters, the retention equation of samples must be obtained at first. Traditionally, several isocratic experiments are used to get the retention equation of solute. However, it is time consuming especially for the separation of complex samples with a wide range of polarity. A new method for the fast optimization of ternary stepwise gradient elution was proposed based on the migration rule of solute in column. First, the coefficients of retention equation of solute are obtained by running several linear gradient experiments, then the optimal separation conditions are searched according to the hierarchical chromatography response function which acts as the optimization criterion. For each kind of organic modifier, two initial linear gradient experiments are used to obtain the primary coefficients of retention equation of each solute. For ternary mobile phase, only four linear gradient runs are needed to get the coefficients of retention equation. Then the retention times of solutes under arbitrary mobile phase composition can be predicted. The initial optimal mobile phase composition is obtained by resolution mapping for all of the solutes. A hierarchical chromatography response function is used to evaluate the separation efficiencies and search the optimal elution conditions. In subsequent optimization, the migrating distance of solute in the column is considered to decide the mobile phase composition and sustaining time of the latter steps until all the solutes are eluted out. Thus the first stepwise gradient elution conditions are predicted. If the resolution of samples under the predicted optimal separation conditions is satisfactory, the optimization procedure is stopped; otherwise, the coefficients of retention equation are adjusted according to the experimental results under the previously predicted elution conditions. Then the new stepwise gradient elution conditions are predicted repeatedly until satisfactory resolution is obtained. Normally, the satisfactory separation conditions can be found only after six experiments by using the proposed method. In comparison with the traditional optimization method, the time needed to finish the optimization procedure can be greatly reduced. The method has been validated by its application to the separation of several samples such as amino acid derivatives, aromatic amines, in which satisfactory separations were obtained with predicted resolution.

Improving the FLORIS wind plant model for compatibility with gradient-based optimization

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

Thomas, Jared J.; Gebraad, Pieter MO; Ning, Andrew

The FLORIS (FLOw Redirection and Induction in Steady-state) model, a parametric wind turbine wake model that predicts steady-state wake characteristics based on wind turbine position and yaw angle, was developed for optimization of control settings and turbine locations. This article provides details on changes made to the FLORIS model to make the model more suitable for gradient-based optimization. Changes to the FLORIS model were made to remove discontinuities and add curvature to regions of non-physical zero gradient. Exact gradients for the FLORIS model were obtained using algorithmic differentiation. A set of three case studies demonstrate that using exact gradients withmore » gradient-based optimization reduces the number of function calls by several orders of magnitude. The case studies also show that adding curvature improves convergence behavior, allowing gradient-based optimization algorithms used with the FLORIS model to more reliably find better solutions to wind farm optimization problems.« less

Identification of ecological thresholds from variations in phytoplankton communities among lakes: contribution to the definition of environmental standards.

PubMed

Roubeix, Vincent; Danis, Pierre-Alain; Feret, Thibaut; Baudoin, Jean-Marc

2016-04-01

In aquatic ecosystems, the identification of ecological thresholds may be useful for managers as it can help to diagnose ecosystem health and to identify key levers to enable the success of preservation and restoration measures. A recent statistical method, gradient forest, based on random forests, was used to detect thresholds of phytoplankton community change in lakes along different environmental gradients. It performs exploratory analyses of multivariate biological and environmental data to estimate the location and importance of community thresholds along gradients. The method was applied to a data set of 224 French lakes which were characterized by 29 environmental variables and the mean abundances of 196 phytoplankton species. Results showed the high importance of geographic variables for the prediction of species abundances at the scale of the study. A second analysis was performed on a subset of lakes defined by geographic thresholds and presenting a higher biological homogeneity. Community thresholds were identified for the most important physico-chemical variables including water transparency, total phosphorus, ammonia, nitrates, and dissolved organic carbon. Gradient forest appeared as a powerful method at a first exploratory step, to detect ecological thresholds at large spatial scale. The thresholds that were identified here must be reinforced by the separate analysis of other aquatic communities and may be used then to set protective environmental standards after consideration of natural variability among lakes.

Investigation on Physicochemical Characteristics of a Nanoliposome-Based System for Dual Drug Delivery

NASA Astrophysics Data System (ADS)

Nam, Jae Hyun; Kim, So-Yeon; Seong, Hasoo

2018-04-01

Synergistic effects of multiple drugs with different modes of action are utilized for combinatorial chemotherapy of intractable cancers. Translation of in vitro synergistic effects into the clinic can be realized using an efficient delivery system of the drugs. Despite a few studies on nano-sized liposomes containing erlotinib (ERL) and doxorubicin (DOX) in a single liposome vesicle, reliable and reproducible preparation methods as well as physicochemical characteristics of a non-PEGylated nanoliposome co-encapsulated with ERL and DOX have not been yet elucidated. In this study, ERL-encapsulated nanoliposomes were prepared using the lipid film-hydration method. By ultrasonication using a probe sonicator, the liposome diameter was reduced to less than 200 nm. DOX was loaded into the ERL-encapsulated nanoliposomes using ammonium sulfate (AS)-gradient or pH-gradient method. Effects of DOX-loading conditions on encapsulation efficiency (EE) of the DOX were investigated to determine an efficient drug-loading method. In the EE of DOX, AS-gradient method was more effective than pH gradient. The dual drug-encapsulated nanoliposomes had more than 90% EE of DOX and 30% EE of ERL, respectively. Transmission electron microscopy and selected area electron diffraction analyses of the dual drug-encapsulated nanoliposomes verified the highly oriented DOX-sulfate crystals inside the liposome as well as the less oriented small crystals of ERL in the outermost region of the nanoliposome. The nanoliposomes were stable at different temperatures without an increase of the nanoliposome diameter. The dual drug-encapsulated nanoliposomes showed a time-differential release of ERL and DOX, implying proper sequential releases for their synergism. The preparation methods and the physicochemical characteristics of the dual drug delivery system contribute to the development of the optimal process and more advanced systems for translational researches.

A comparison of methods for computing the sigma-coordinate pressure gradient force for flow over sloped terrain in a hybrid theta-sigma model

NASA Technical Reports Server (NTRS)

Johnson, D. R.; Uccellini, L. W.

1983-01-01

In connection with the employment of the sigma coordinates introduced by Phillips (1957), problems can arise regarding an accurate finite-difference computation of the pressure gradient force. Over steeply sloped terrain, the calculation of the sigma-coordinate pressure gradient force involves computing the difference between two large terms of opposite sign which results in large truncation error. To reduce the truncation error, several finite-difference methods have been designed and implemented. The present investigation has the objective to provide another method of computing the sigma-coordinate pressure gradient force. Phillips' method is applied for the elimination of a hydrostatic component to a flux formulation. The new technique is compared with four other methods for computing the pressure gradient force. The work is motivated by the desire to use an isentropic and sigma-coordinate hybrid model for experiments designed to study flow near mountainous terrain.

Biological Image-Guided Radiotherapy in Rectal Cancer: Challenges and Pitfalls

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

Roels, Sarah; Slagmolen, Pieter; Nuyts, Johan

2009-11-01

Purpose: To investigate the feasibility of integrating multiple imaging modalities for image-guided radiotherapy in rectal cancer. Patients and Methods: Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT) were performed before, during, and after preoperative chemoradiotherapy (CRT) in patients with resectable rectal cancer. The FDG-PET signals were segmented with an adaptive threshold-based and a gradient-based method. Magnetic resonance tumor volumes (TVs) were manually delineated. A nonrigid registration algorithm was applied to register the images, and mismatch analyses were carried out between MR and FDG-PET TVs and between TVs over time. Tumor volumes delineated on the images after CRTmore » were compared with the pathologic TV. Results: Forty-five FDG-PET/CT and 45 MR images were analyzed from 15 patients. The mean MRI and FDG-PET TVs showed a tendency to shrink during and after CRT. In general, MRI showed larger TVs than FDG-PET. There was an approximately 50% mismatch between the FDG-PET TV and the MRI TV at baseline and during CRT. Sixty-one percent of the FDG-PET TV and 76% of the MRI TV obtained after 10 fractions of CRT remained inside the corresponding baseline TV. On MRI, residual tumor was still suspected in all 6 patients with a pathologic complete response, whereas FDG-PET showed a metabolic complete response in 3 of them. The FDG-PET TVs delineated with the gradient-based method matched closest with pathologic findings. Conclusions: Integration of MRI and FDG-PET into radiotherapy seems feasible. Gradient-based segmentation is recommended for FDG-PET. Spatial variance between MRI and FDG-PET TVs should be taken into account for target definition.« less

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.

The evolution of distributed sensing and collective computation in animal populations

PubMed Central

Hein, Andrew M; Rosenthal, Sara Brin; Hagstrom, George I; Berdahl, Andrew; Torney, Colin J; Couzin, Iain D

2015-01-01

Many animal groups exhibit rapid, coordinated collective motion. Yet, the evolutionary forces that cause such collective responses to evolve are poorly understood. Here, we develop analytical methods and evolutionary simulations based on experimental data from schooling fish. We use these methods to investigate how populations evolve within unpredictable, time-varying resource environments. We show that populations evolve toward a distinctive regime in behavioral phenotype space, where small responses of individuals to local environmental cues cause spontaneous changes in the collective state of groups. These changes resemble phase transitions in physical systems. Through these transitions, individuals evolve the emergent capacity to sense and respond to resource gradients (i.e. individuals perceive gradients via social interactions, rather than sensing gradients directly), and to allocate themselves among distinct, distant resource patches. Our results yield new insight into how natural selection, acting on selfish individuals, results in the highly effective collective responses evident in nature. DOI: http://dx.doi.org/10.7554/eLife.10955.001 PMID:26652003

High-throughput growth temperature optimization of ferroelectric SrxBa1-xNb2O6 epitaxial thin films using a temperature gradient method

NASA Astrophysics Data System (ADS)

Ohkubo, I.; Christen, H. M.; Kalinin, Sergei V.; Jellison, G. E.; Rouleau, C. M.; Lowndes, D. H.

2004-02-01

We have developed a multisample film growth method on a temperature-gradient substrate holder to quickly optimize the film growth temperature in pulsed-laser deposition. A smooth temperature gradient is achieved, covering a range of temperatures from 200 to 830 °C. In a single growth run, the optimal growth temperature for SrxBa1-xNb2O6 thin films on MgO(001) substrates was determined to be 750 °C, based on results from ellipsometry and piezoresponse force microscopy. Variations in optical properties and ferroelectric domains structures were clearly observed as function of growth temperature, and these physical properties can be related to their different crystalline quality. Piezoresponse force microscopy indicated the formation of uniform ferroelectric film for deposition temperatures above 750 °C. At 660 °C, isolated micron-sized ferroelectric islands were observed, while samples deposited below 550 °C did not exhibit clear piezoelectric contrast.

Aspects of the "Design Space" in high pressure liquid chromatography method development.

PubMed

Molnár, I; Rieger, H-J; Monks, K E

2010-05-07

The present paper describes a multifactorial optimization of 4 critical HPLC method parameters, i.e. gradient time (t(G)), temperature (T), pH and ternary composition (B(1):B(2)) based on 36 experiments. The effect of these experimental variables on critical resolution and selectivity was carried out in such a way as to systematically vary all four factors simultaneously. The basic element is a gradient time-temperature (t(G)-T) plane, which is repeated at three different pH's of the eluent A and at three different ternary compositions of eluent B between methanol and acetonitrile. The so-defined volume enables the investigation of the critical resolution for a part of the Design Space of a given sample. Further improvement of the analysis time, with conservation of the previously optimized selectivity, was possible by reducing the gradient time and increasing the flow rate. Multidimensional robust regions were successfully defined and graphically depicted. Copyright (c) 2010 Elsevier B.V. All rights reserved.

Gaussian process regression to accelerate geometry optimizations relying on numerical differentiation

NASA Astrophysics Data System (ADS)

Schmitz, Gunnar; Christiansen, Ove

2018-06-01

We study how with means of Gaussian Process Regression (GPR) geometry optimizations, which rely on numerical gradients, can be accelerated. The GPR interpolates a local potential energy surface on which the structure is optimized. It is found to be efficient to combine results on a low computational level (HF or MP2) with the GPR-calculated gradient of the difference between the low level method and the target method, which is a variant of explicitly correlated Coupled Cluster Singles and Doubles with perturbative Triples correction CCSD(F12*)(T) in this study. Overall convergence is achieved if both the potential and the geometry are converged. Compared to numerical gradient-based algorithms, the number of required single point calculations is reduced. Although introducing an error due to the interpolation, the optimized structures are sufficiently close to the minimum of the target level of theory meaning that the reference and predicted minimum only vary energetically in the μEh regime.

Analysis of Correlation between Ionospheric Spatial Gradients and Space Weather Intensity under Nominal Conditions for Ground-Based Augmentation Systems

NASA Astrophysics Data System (ADS)

Lee, J.

2013-12-01

Ground-Based Augmentation Systems (GBAS) support aircraft precision approach and landing by providing differential GPS corrections to aviation users. For GBAS applications, most of ionospheric errors are removed by applying the differential corrections. However, ionospheric correction errors may exist due to ionosphere spatial decorrelation between GBAS ground facility and users. Thus, the standard deviation of ionosphere spatial decorrelation (σvig) is estimated and included in the computation of error bounds on user position solution. The σvig of 4mm/km, derived for the Conterminous United States (CONUS), bounds one-sigma ionospheric spatial gradients under nominal conditions (including active, but not stormy condition) with an adequate safety margin [1]. The conservatism residing in the current σvig by fixing it to a constant value for all non-stormy conditions could be mitigated by subdividing ionospheric conditions into several classes and using different σvig for each class. This new concept, real-time σvig adaptation, will be possible if the level of ionospheric activity can be well classified based on space weather intensity. This paper studies correlation between the statistics of nominal ionospheric spatial gradients and space weather indices. The analysis was carried out using two sets of data collected from Continuous Operating Reference Station (CORS) Network; 9 consecutive (nominal and ionospherically active) days in 2004 and 19 consecutive (relatively 'quiet') days in 2010. Precise ionospheric delay estimates are obtained using the simplified truth processing method and vertical ionospheric gradients are computed using the well-known 'station pair method' [2]. The remaining biases which include carrier-phase leveling errors and Inter-frequency Bias (IFB) calibration errors are reduced by applying linear slip detection thresholds. The σvig was inflated to overbound the distribution of vertical ionospheric gradients with the required confidence level. Using the daily maximum values of σvig, day-to-day variations of spatial gradients are compared to those of two space weather indices; Disturbance, Storm Time (Dst) index and Interplanetary Magnetic Field Bz (IMF Bz). The day-to-day variations of both space weather indices showed a good agreement with those of daily maximum σvig. The results demonstrate that ionospheric gradient statistics are highly correlated with space weather indices on nominal and off-nominal days. Further investigation on this relationship would facilitate prediction of upcoming ionospheric behavior based on space weather information and adjusting σvig in real time. Consequently it will improve GBAS availability by adding external information to operation. [1] Lee, J., S. Pullen, S. Datta-Barua, and P. Enge (2007), Assessment of ionosphere spatial decorrelation for GPS-based aircraft landing systems, J. Aircraft, 44(5), 1662-1669, doi:10.2514/1.28199. [2] Jung, S., and J. Lee (2012), Long-term ionospheric anomaly monitoring for ground based augmentation systems, Radio Sci., 47, RS4006, doi:10.1029/2012RS005016.

Origami-inspired active graphene-based paper for programmable instant self-folding walking devices.

PubMed

Mu, Jiuke; Hou, Chengyi; Wang, Hongzhi; Li, Yaogang; Zhang, Qinghong; Zhu, Meifang

2015-11-01

Origami-inspired active graphene-based paper with programmed gradients in vertical and lateral directions is developed to address many of the limitations of polymer active materials including slow response and violent operation methods. Specifically, we used function-designed graphene oxide as nanoscale building blocks to fabricate an all-graphene self-folding paper that has a single-component gradient structure. A functional device composed of this graphene paper can (i) adopt predesigned shapes, (ii) walk, and (iii) turn a corner. These processes can be remote-controlled by gentle light or heating. We believe that this self-folding material holds potential for a wide range of applications such as sensing, artificial muscles, and robotics.

Biomaterials with persistent growth factor gradients in vivo accelerate vascularized tissue formation.

PubMed

Akar, Banu; Jiang, Bin; Somo, Sami I; Appel, Alyssa A; Larson, Jeffery C; Tichauer, Kenneth M; Brey, Eric M

2015-12-01

Gradients of soluble factors play an important role in many biological processes, including blood vessel assembly. Gradients can be studied in detail in vitro, but methods that enable the study of spatially distributed soluble factors and multi-cellular processes in vivo are limited. Here, we report on a method for the generation of persistent in vivo gradients of growth factors in a three-dimensional (3D) biomaterial system. Fibrin loaded porous poly (ethylene glycol) (PEG) scaffolds were generated using a particulate leaching method. Platelet derived growth factor BB (PDGF-BB) was encapsulated into poly (lactic-co-glycolic acid) (PLGA) microspheres which were placed distal to the tissue-material interface. PLGA provides sustained release of PDGF-BB and its diffusion through the porous structure results in gradient formation. Gradients within the scaffold were confirmed in vivo using near-infrared fluorescence imaging and gradients were present for more than 3 weeks. The diffusion of PDGF-BB was modeled and verified with in vivo imaging findings. The depth of tissue invasion and density of blood vessels formed in response to the biomaterial increased with magnitude of the gradient. This biomaterial system allows for generation of sustained growth factor gradients for the study of tissue response to gradients in vivo. Published by Elsevier Ltd.

Dexamethasone levels and base to apex concentration gradients in scala tympani perilymph following intracochlear delivery in the guinea pig

PubMed Central

Hahn, Hartmut; Salt, Alec N.; Biegner, Thorsten; Kammerer, Bernd; Delabar, Ursular; Hartsock, Jared; Plontke, Stefan K.

2012-01-01

Hypothesis To determine whether intracochlearly applied dexamethasone will lead to better control of drug levels, higher peak concentrations and lower base-to apex concentration gradients in scala tympani (ST) of the guinea pig than after intratympanic (round window, RW) application. Background Local application of drugs to the RW results in substantial variation of intracochlear drug levels and significant base-to apex concentration gradients in ST. Methods Two μL of dexamethasone-phosphate (10 mg/mL) were injected into ST either through the RW membrane which was covered with 1% sodium hyaluronate gel or through a cochleostomy with a fluid tight seal of the micropipette. Perilymph was sequentially sampled from the apex at a single time point for each animal, at 20, 80, or 200 min after the injection ended. Results were mathematically interpreted by the means of an established computer model and compared with prior experiments performed by our group with the same experimental techniques but using intratympanic applications. Results Single intracochlear injections over 20 min resulted in approximately ten times higher peak concentrations (on average) than 2-3 hours of intratympanic application to the round window niche. Intracochlear drug levels were less variable and could be measured for at least up to 220 min. Concentration gradients along scala tympani were less pronounced. The remaining variability in intracochlear drug levels was attributable to perilymph and drug leak from the injection site. Conclusion With significantly higher, less variable drug levels and smaller base-to apex concentration gradients, intracochlear applications have advantages to intratympanic injections. For further development of this technique, it is of importance to control leaks of perilymph and drug from the injection site and to evaluate its clinical feasibility and associated risks. PMID:22588238

Improved Conjugate Gradient Bundle Adjustment of Dunhuang Wall Painting Images

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

MODFLOW equipped with a new method for the accurate simulation of axisymmetric flow

NASA Astrophysics Data System (ADS)

Samani, N.; Kompani-Zare, M.; Barry, D. A.

2004-01-01

Axisymmetric flow to a well is an important topic of groundwater hydraulics, the simulation of which depends on accurate computation of head gradients. Groundwater numerical models with conventional rectilinear grid geometry such as MODFLOW (in contrast to analytical models) generally have not been used to simulate aquifer test results at a pumping well because they are not designed or expected to closely simulate the head gradient near the well. A scaling method is proposed based on mapping the governing flow equation from cylindrical to Cartesian coordinates, and vice versa. A set of relationships and scales is derived to implement the conversion. The proposed scaling method is then embedded in MODFLOW 2000. To verify the accuracy of the method steady and unsteady flows in confined and unconfined aquifers with fully or partially penetrating pumping wells are simulated and compared with the corresponding analytical solutions. In all cases a high degree of accuracy is achieved.

A Fast Gradient Method for Nonnegative Sparse Regression With Self-Dictionary

NASA Astrophysics Data System (ADS)

Gillis, Nicolas; Luce, Robert

2018-01-01

A nonnegative matrix factorization (NMF) can be computed efficiently under the separability assumption, which asserts that all the columns of the given input data matrix belong to the cone generated by a (small) subset of them. The provably most robust methods to identify these conic basis columns are based on nonnegative sparse regression and self dictionaries, and require the solution of large-scale convex optimization problems. In this paper we study a particular nonnegative sparse regression model with self dictionary. As opposed to previously proposed models, this model yields a smooth optimization problem where the sparsity is enforced through linear constraints. We show that the Euclidean projection on the polyhedron defined by these constraints can be computed efficiently, and propose a fast gradient method to solve our model. We compare our algorithm with several state-of-the-art methods on synthetic data sets and real-world hyperspectral images.

ShinyKGode: an interactive application for ODE parameter inference using gradient matching.

PubMed

Wandy, Joe; Niu, Mu; Giurghita, Diana; Daly, Rónán; Rogers, Simon; Husmeier, Dirk

2018-07-01

Mathematical modelling based on ordinary differential equations (ODEs) is widely used to describe the dynamics of biological systems, particularly in systems and pathway biology. Often the kinetic parameters of these ODE systems are unknown and have to be inferred from the data. Approximate parameter inference methods based on gradient matching (which do not require performing computationally expensive numerical integration of the ODEs) have been getting popular in recent years, but many implementations are difficult to run without expert knowledge. Here, we introduce ShinyKGode, an interactive web application to perform fast parameter inference on ODEs using gradient matching. ShinyKGode can be used to infer ODE parameters on simulated and observed data using gradient matching. Users can easily load their own models in Systems Biology Markup Language format, and a set of pre-defined ODE benchmark models are provided in the application. Inferred parameters are visualized alongside diagnostic plots to assess convergence. The R package for ShinyKGode can be installed through the Comprehensive R Archive Network (CRAN). Installation instructions, as well as tutorial videos and source code are available at https://joewandy.github.io/shinyKGode. Supplementary data are available at Bioinformatics online.

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.

Selective isolation of magnetic nanoparticle-mediated heterogeneity subpopulation of circulating tumor cells using magnetic gradient based microfluidic system.

PubMed

Kwak, Bongseop; Lee, Jaehun; Lee, Dongkyu; Lee, Kangho; Kwon, Ohwon; Kang, Shinwon; Kim, Youngwoo

2017-02-15

Relocation mechanisms of the circulating tumor cells (CTCs) from the primary site to the secondary site through the blood vessel network cause tumor metastasis. Despite of the importance to diagnose the cancer metastasis by CTCs, still it is formidable challenge to use in the clinical purpose because of the rarity and the heterogeneity of CTCs in the cancer patient's peripheral blood sample. In this study we have developed magnetic force gradient based microfluidic chip (Mag-Gradient Chip) for isolating the total number of CTCs in the sample and characterizing the state of CTCs simultaneously with respect to the epithelial cell adhesion molecule (EpCAM) expression level. We have synthesized magnetic nanoparticles (MNPs) using hydrothermal method and functionalized anti-EpCAM on their surface for the specific binding with CTCs. The Mag-Gradient Chip designed to isolate and classify the CTCs by isolating at the different location in the chip using magnetic force differences depending on the EpCAM expression level. We observed 95.7% of EpCAM positive and 79.3% of EpCAM negative CTCs isolated in the Mag-Gradient Chip. At the same time, the 71.3% of isolated EpCAM positive CTCs were isolated at the first half area whereas the 76.9% of EpCAM negative CTCs were collected at the latter half area. The Mag-Gradient Chip can isolate the 3ml of heterogeneous CTCs sample in 1h with high isolating yield. The EpCAM expression level dose not means essential condition of the metastatic CTCs, but the Mag-Gradient Chip can shorten the date to diagnose the cancer metastasis in clinic. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

Simple method provides resolution of albumin, lipoprotein, free fraction, and chylomicron to enhance the utility of protein binding assays.

PubMed

Brockman, Adam H; Oller, Haley R; Moreau, Benoît; Kriksciukaite, Kristina; Bilodeau, Mark T

2015-02-12

Medicinal chemists have been encouraged in recent years to embrace high speed protein binding assays. These methods employ dialysis membranes in 96-well format or spin filters. Membrane-based methods do not separate lipoprotein binding from albumin binding and introduce interference despite membrane binding controls. Ultracentrifugation methods, in contrast, do not introduce interference if density gradients can be avoided and they resolve lipoprotein from albumin. A new generation of compact, fast ultracentrifuges facilitates the rapid and fully informative separation of plasma into albumin, albumin/fatty acid complex, lipoprotein, protein-free, and chylomicron fractions with no need of salt or sugar density gradients. We present a simple and fast ultracentrifuge method here for two platinum compounds and a taxane that otherwise bound irreversibly to dialysis membranes and which exhibited distinctive lipoprotein binding behaviors. This new generation of ultracentrifugation methods underscores a need to further discuss protein binding assessments as they relate to medicinal chemistry efforts.

Evaluation of retrieval methods of daytime convective boundary layer height based on lidar data

NASA Astrophysics Data System (ADS)

Li, Hong; Yang, Yi; Hu, Xiao-Ming; Huang, Zhongwei; Wang, Guoyin; Zhang, Beidou; Zhang, Tiejun

2017-04-01

The atmospheric boundary layer height is a basic parameter in describing the structure of the lower atmosphere. Because of their high temporal resolution, ground-based lidar data are widely used to determine the daytime convective boundary layer height (CBLH), but the currently available retrieval methods have their advantages and drawbacks. In this paper, four methods of retrieving the CBLH (i.e., the gradient method, the idealized backscatter method, and two forms of the wavelet covariance transform method) from lidar normalized relative backscatter are evaluated, using two artificial cases (an idealized profile and a case similar to real profile), to test their stability and accuracy. The results show that the gradient method is suitable for high signal-to-noise ratio conditions. The idealized backscatter method is less sensitive to the first estimate of the CBLH; however, it is computationally expensive. The results obtained from the two forms of the wavelet covariance transform method are influenced by the selection of the initial input value of the wavelet amplitude. Further sensitivity analysis using real profiles under different orders of magnitude of background counts show that when different initial input values are set, the idealized backscatter method always obtains consistent CBLH. For two wavelet methods, the different CBLH are always obtained with the increase in the wavelet amplitude when noise is significant. Finally, the CBLHs as measured by three lidar-based methods are evaluated by as measured from L-band soundings. The boundary layer heights from two instruments coincide with ±200 m in most situations.

Video-based noncooperative iris image segmentation.

PubMed

Du, Yingzi; Arslanturk, Emrah; Zhou, Zhi; Belcher, Craig

2011-02-01

In this paper, we propose a video-based noncooperative iris image segmentation scheme that incorporates a quality filter to quickly eliminate images without an eye, employs a coarse-to-fine segmentation scheme to improve the overall efficiency, uses a direct least squares fitting of ellipses method to model the deformed pupil and limbic boundaries, and develops a window gradient-based method to remove noise in the iris region. A remote iris acquisition system is set up to collect noncooperative iris video images. An objective method is used to quantitatively evaluate the accuracy of the segmentation results. The experimental results demonstrate the effectiveness of this method. The proposed method would make noncooperative iris recognition or iris surveillance possible.

Coherent gradient sensing method and system for measuring surface curvature

NASA Technical Reports Server (NTRS)

Rosakis, Ares J. (Inventor); Moore, Jr., Nicholas R. (Inventor); Singh, Ramen P. (Inventor); Kolawa, Elizabeth (Inventor)

2000-01-01

A system and method for determining a curvature of a specularly reflective surface based on optical interference. Two optical gratings are used to produce a spatial displacement in an interference field of two different diffraction components produced by one grating from different diffraction components produced by another grating. Thus, the curvature of the surface can be determined.

Developing operation algorithms for vision subsystems in autonomous mobile robots

NASA Astrophysics Data System (ADS)

Shikhman, M. V.; Shidlovskiy, S. V.

2018-05-01

The paper analyzes algorithms for selecting keypoints on the image for the subsequent automatic detection of people and obstacles. The algorithm is based on the histogram of oriented gradients and the support vector method. The combination of these methods allows successful selection of dynamic and static objects. The algorithm can be applied in various autonomous mobile robots.

Application of an online ion-chromatography-based instrument for gradient flux measurements of speciated nitrogen and sulfur

NASA Astrophysics Data System (ADS)

Rumsey, Ian C.; Walker, John T.

2016-06-01

The dry component of total nitrogen and sulfur atmospheric deposition remains uncertain. The lack of measurements of sufficient chemical speciation and temporal extent make it difficult to develop accurate mass budgets and sufficient process level detail is not available to improve current air-surface exchange models. Over the past decade, significant advances have been made in the development of continuous air sampling measurement techniques, resulting with instruments of sufficient sensitivity and temporal resolution to directly quantify air-surface exchange of nitrogen and sulfur compounds. However, their applicability is generally restricted to only one or a few of the compounds within the deposition budget. Here, the performance of the Monitor for AeRosols and GAses in ambient air (MARGA 2S), a commercially available online ion-chromatography-based analyzer is characterized for the first time as applied for air-surface exchange measurements of HNO3, NH3, NH4+, NO3-, SO2 and SO42-. Analytical accuracy and precision are assessed under field conditions. Chemical concentrations gradient precision are determined at the same sampling site. Flux uncertainty measured by the aerodynamic gradient method is determined for a representative 3-week period in fall 2012 over a grass field. Analytical precision and chemical concentration gradient precision were found to compare favorably in comparison to previous studies. During the 3-week period, percentages of hourly chemical concentration gradients greater than the corresponding chemical concentration gradient detection limit were 86, 42, 82, 73, 74 and 69 % for NH3, NH4+, HNO3, NO3-, SO2 and SO42-, respectively. As expected, percentages were lowest for aerosol species, owing to their relatively low deposition velocities and correspondingly smaller gradients relative to gas phase species. Relative hourly median flux uncertainties were 31, 121, 42, 43, 67 and 56 % for NH3, NH4+, HNO3, NO3-, SO2 and SO42-, respectively. Flux uncertainty is dominated by uncertainty in the chemical concentrations gradients during the day but uncertainty in the chemical concentration gradients and transfer velocity are of the same order at night. Results show the instrument is sufficiently precise for flux gradient applications.

The discrete adjoint method for parameter identification in multibody system dynamics.

PubMed

Lauß, Thomas; Oberpeilsteiner, Stefan; Steiner, Wolfgang; Nachbagauer, Karin

2018-01-01

The adjoint method is an elegant approach for the computation of the gradient of a cost function to identify a set of parameters. An additional set of differential equations has to be solved to compute the adjoint variables, which are further used for the gradient computation. However, the accuracy of the numerical solution of the adjoint differential equation has a great impact on the gradient. Hence, an alternative approach is the discrete adjoint method , where the adjoint differential equations are replaced by algebraic equations. Therefore, a finite difference scheme is constructed for the adjoint system directly from the numerical time integration method. The method provides the exact gradient of the discretized cost function subjected to the discretized equations of motion.

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.

An automated method for the determination of deoxyribonuclease activity as exemplified by fractionation of the components of the medicament Varidase®

PubMed Central

Locke, I. C.; Ramsey, M. P.; Hill, S. S.; Carpenter, B. G.

1993-01-01

The activity of most deoxyribonuclease enzymes can be monitored by measuring the change in absorbance at 260 nm which accompanies the breakdown of the double-stranded structure of native DNA. An automated method for determining deoxyribonuclease activity, based on such an absorbance change, which can overcome problems of inhibition arising from the presence of inorganic cations, is described. Variations in inorganic cation concentration is a particular problem when measuring the activity of chromatographic fractions eluted via a salt gradient. A comparison is made between the automated and a manual method for the assay of deoxyribonuclease active constituents, of the medicament ‘Varidase’, eluted from a Cellex-D (Bio-Rad Laboratories Ltd) anionic exchange resin using a 0.05-1.0 M sodium chloride gradient. PMID:18924962

Effects of breast and colorectal cancer on labour market outcomes-average effects and educational gradients.

PubMed

Heinesen, Eskil; Kolodziejczyk, Christophe

2013-12-01

We estimate causal effects of breast and colorectal cancer on labour market outcomes 1-3 years after the diagnosis. Based on Danish administrative data we estimate average treatment effects on the treated by propensity score weighting methods using persons with no cancer diagnosis as control group. We conduct robustness checks using matching, difference-in-differences methods and an alternative control group of later cancer patients. The different methods give approximately the same results. Cancer increases the risks of leaving the labour force and receiving disability pension, and the effects are larger for the less educated. Effects on income are small and mostly insignificant. We investigate some of the mechanisms which may be important in explaining the educational gradient in effects of cancer on labour market attachment. Copyright © 2013 Elsevier B.V. All rights reserved.

Technical Note: Interleaved Bipolar Acquisition and Low-rank Reconstruction for Water-Fat Separation in MRI.

PubMed

Cho, JaeJin; Park, HyunWook

2018-05-17

To acquire interleaved bipolar data and reconstruct the full data using low-rank property for water fat separation. Bipolar acquisition suffers from issues related to gradient switching, the opposite gradient polarities, and other system imperfections, which prevent accurate water-fat separation. In this study, an interleaved bipolar acquisition scheme and a low-rank reconstruction method were proposed to reduce issues from the bipolar gradients while achieving a short imaging time. The proposed interleaved bipolar acquisition scheme collects echo-time signals from both gradient polarities; however, the sequence increases the imaging time. To reduce the imaging time, the signals were subsampled at every dimension of k-space. The low-rank property of the bipolar acquisition was defined and exploited to estimate the full data from the acquired subsampled data. To eliminate the bipolar issues, in the proposed method, the water-fat separation was performed separately for each gradient polarity, and the results for the positive and negative gradient polarities were combined after the water-fat separation. A phantom study and in-vivo experiments were conducted on a 3T Siemens Verio system. The results for the proposed method were compared with the results of the fully sampled interleaved bipolar acquisition and Soliman's method, which was the previous water-fat separation approach for reducing the issues of bipolar gradients and accelerating the interleaved bipolar acquisition. The proposed method provided accurate water and fat images without the issues of bipolar gradients and demonstrated a better performance compared with the results of the previous methods. The water-fat separation using the bipolar acquisition has several benefits including a short echo-spacing time. However, it suffers from bipolar-gradient issues such as strong gradient switching, system imperfection, and eddy current effects. This study demonstrated that accurate water-fat separated images can be obtained using the proposed interleaved bipolar acquisition and low-rank reconstruction by using the benefits of the bipolar acquisition while reducing the bipolar-gradient issues with a short imaging time. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

A Single-Lap Joint Adhesive Bonding Optimization Method Using Gradient and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Smeltzer, Stanley S., III; Finckenor, Jeffrey L.

1999-01-01

A natural process for any engineer, scientist, educator, etc. is to seek the most efficient method for accomplishing a given task. In the case of structural design, an area that has a significant impact on the structural efficiency is joint design. Unless the structure is machined from a solid block of material, the individual components which compose the overall structure must be joined together. The method for joining a structure varies depending on the applied loads, material, assembly and disassembly requirements, service life, environment, etc. Using both metallic and fiber reinforced plastic materials limits the user to two methods or a combination of these methods for joining the components into one structure. The first is mechanical fastening and the second is adhesive bonding. Mechanical fastening is by far the most popular joining technique; however, in terms of structural efficiency, adhesive bonding provides a superior joint since the load is distributed uniformly across the joint. The purpose of this paper is to develop a method for optimizing single-lap joint adhesive bonded structures using both gradient and genetic algorithms and comparing the solution process for each method. The goal of the single-lap joint optimization is to find the most efficient structure that meets the imposed requirements while still remaining as lightweight, economical, and reliable as possible. For the single-lap joint, an optimum joint is determined by minimizing the weight of the overall joint based on constraints from adhesive strengths as well as empirically derived rules. The analytical solution of the sin-le-lap joint is determined using the classical Goland-Reissner technique for case 2 type adhesive joints. Joint weight minimization is achieved using a commercially available routine, Design Optimization Tool (DOT), for the gradient solution while an author developed method is used for the genetic algorithm solution. Results illustrate the critical design variables as a function of adhesive properties and convergences of different joints based on the two optimization methods.

Simulation of co-phase error correction of optical multi-aperture imaging system based on stochastic parallel gradient decent algorithm

NASA Astrophysics Data System (ADS)

He, Xiaojun; Ma, Haotong; Luo, Chuanxin

2016-10-01

The optical multi-aperture imaging system is an effective way to magnify the aperture and increase the resolution of telescope optical system, the difficulty of which lies in detecting and correcting of co-phase error. This paper presents a method based on stochastic parallel gradient decent algorithm (SPGD) to correct the co-phase error. Compared with the current method, SPGD method can avoid detecting the co-phase error. This paper analyzed the influence of piston error and tilt error on image quality based on double-aperture imaging system, introduced the basic principle of SPGD algorithm, and discuss the influence of SPGD algorithm's key parameters (the gain coefficient and the disturbance amplitude) on error control performance. The results show that SPGD can efficiently correct the co-phase error. The convergence speed of the SPGD algorithm is improved with the increase of gain coefficient and disturbance amplitude, but the stability of the algorithm reduced. The adaptive gain coefficient can solve this problem appropriately. This paper's results can provide the theoretical reference for the co-phase error correction of the multi-aperture imaging system.

Spiral bacterial foraging optimization method: Algorithm, evaluation and convergence analysis

NASA Astrophysics Data System (ADS)

Kasaiezadeh, Alireza; Khajepour, Amir; Waslander, Steven L.

2014-04-01

A biologically-inspired algorithm called Spiral Bacterial Foraging Optimization (SBFO) is investigated in this article. SBFO, previously proposed by the same authors, is a multi-agent, gradient-based algorithm that minimizes both the main objective function (local cost) and the distance between each agent and a temporary central point (global cost). A random jump is included normal to the connecting line of each agent to the central point, which produces a vortex around the temporary central point. This random jump is also suitable to cope with premature convergence, which is a feature of swarm-based optimization methods. The most important advantages of this algorithm are as follows: First, this algorithm involves a stochastic type of search with a deterministic convergence. Second, as gradient-based methods are employed, faster convergence is demonstrated over GA, DE, BFO, etc. Third, the algorithm can be implemented in a parallel fashion in order to decentralize large-scale computation. Fourth, the algorithm has a limited number of tunable parameters, and finally SBFO has a strong certainty of convergence which is rare in existing global optimization algorithms. A detailed convergence analysis of SBFO for continuously differentiable objective functions has also been investigated in this article.

Focus measure method based on the modulus of the gradient of the color planes for digital microscopy

NASA Astrophysics Data System (ADS)

Hurtado-Pérez, Román; Toxqui-Quitl, Carina; Padilla-Vivanco, Alfonso; Aguilar-Valdez, J. Félix; Ortega-Mendoza, Gabriel

2018-02-01

The modulus of the gradient of the color planes (MGC) is implemented to transform multichannel information to a grayscale image. This digital technique is used in two applications: (a) focus measurements during autofocusing (AF) process and (b) extending the depth of field (EDoF) by means of multifocus image fusion. In the first case, the MGC procedure is based on an edge detection technique and is implemented in over 15 focus metrics that are typically handled in digital microscopy. The MGC approach is tested on color images of histological sections for the selection of in-focus images. An appealing attribute of all the AF metrics working in the MGC space is their monotonic behavior even up to a magnification of 100×. An advantage of the MGC method is its computational simplicity and inherent parallelism. In the second application, a multifocus image fusion algorithm based on the MGC approach has been implemented on graphics processing units (GPUs). The resulting fused images are evaluated using a nonreference image quality metric. The proposed fusion method reveals a high-quality image independently of faulty illumination during the image acquisition. Finally, the three-dimensional visualization of the in-focus image is shown.

Fast and Robust Registration of Multimodal Remote Sensing Images via Dense Orientated Gradient Feature

NASA Astrophysics Data System (ADS)

Ye, Y.

2017-09-01

This paper presents a fast and robust method for the registration of multimodal remote sensing data (e.g., optical, LiDAR, SAR and map). The proposed method is based on the hypothesis that structural similarity between images is preserved across different modalities. In the definition of the proposed method, we first develop a pixel-wise feature descriptor named Dense Orientated Gradient Histogram (DOGH), which can be computed effectively at every pixel and is robust to non-linear intensity differences between images. Then a fast similarity metric based on DOGH is built in frequency domain using the Fast Fourier Transform (FFT) technique. Finally, a template matching scheme is applied to detect tie points between images. Experimental results on different types of multimodal remote sensing images show that the proposed similarity metric has the superior matching performance and computational efficiency than the state-of-the-art methods. Moreover, based on the proposed similarity metric, we also design a fast and robust automatic registration system for multimodal images. This system has been evaluated using a pair of very large SAR and optical images (more than 20000 × 20000 pixels). Experimental results show that our system outperforms the two popular commercial software systems (i.e. ENVI and ERDAS) in both registration accuracy and computational efficiency.

Finding Dantzig Selectors with a Proximity Operator based Fixed-point Algorithm

DTIC Science & Technology

2014-11-01

experiments showed that this method usually outperforms the method in [2] in terms of CPU time while producing solutions of comparable quality. The... method proposed in [19]. To alleviate the difficulty caused by the subprob- lem without a closed form solution , a linearized ADM was proposed for the...a closed form solution , but the β-related subproblem does not and is solved approximately by using the nonmonotone gradient method in [18]. The

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.

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.

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

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

Algorithm for ion beam figuring of low-gradient mirrors.

PubMed

Jiao, Changjun; Li, Shengyi; Xie, Xuhui

2009-07-20

Ion beam figuring technology for low-gradient mirrors is discussed. Ion beam figuring is a noncontact machining technique in which a beam of high-energy ions is directed toward a target workpiece to remove material in a predetermined and controlled fashion. Owing to this noncontact mode of material removal, problems associated with tool wear and edge effects, which are common in conventional contact polishing processes, are avoided. Based on the Bayesian principle, an iterative dwell time algorithm for planar mirrors is deduced from the computer-controlled optical surfacing (CCOS) principle. With the properties of the removal function, the shaping process of low-gradient mirrors can be approximated by the linear model for planar mirrors. With these discussions, the error surface figuring technology for low-gradient mirrors with a linear path is set up. With the near-Gaussian property of the removal function, the figuring process with a spiral path can be described by the conventional linear CCOS principle, and a Bayesian-based iterative algorithm can be used to deconvolute the dwell time. Moreover, the selection criterion of the spiral parameter is given. Ion beam figuring technology with a spiral scan path based on these methods can be used to figure mirrors with non-axis-symmetrical errors. Experiments on SiC chemical vapor deposition planar and Zerodur paraboloid samples are made, and the final surface errors are all below 1/100 lambda.

Analyzing chromatographic data using multilevel modeling.

PubMed

Wiczling, Paweł

2018-06-01

It is relatively easy to collect chromatographic measurements for a large number of analytes, especially with gradient chromatographic methods coupled with mass spectrometry detection. Such data often have a hierarchical or clustered structure. For example, analytes with similar hydrophobicity and dissociation constant tend to be more alike in their retention than a randomly chosen set of analytes. Multilevel models recognize the existence of such data structures by assigning a model for each parameter, with its parameters also estimated from data. In this work, a multilevel model is proposed to describe retention time data obtained from a series of wide linear organic modifier gradients of different gradient duration and different mobile phase pH for a large set of acids and bases. The multilevel model consists of (1) the same deterministic equation describing the relationship between retention time and analyte-specific and instrument-specific parameters, (2) covariance relationships relating various physicochemical properties of the analyte to chromatographically specific parameters through quantitative structure-retention relationship based equations, and (3) stochastic components of intra-analyte and interanalyte variability. The model was implemented in Stan, which provides full Bayesian inference for continuous-variable models through Markov chain Monte Carlo methods. Graphical abstract Relationships between log k and MeOH content for acidic, basic, and neutral compounds with different log P. CI credible interval, PSA polar surface area.

Modeling nonlinear ultrasound propagation in heterogeneous media with power law absorption using a k-space pseudospectral method.

PubMed

Treeby, Bradley E; Jaros, Jiri; Rendell, Alistair P; Cox, B T

2012-06-01

The simulation of nonlinear ultrasound propagation through tissue realistic media has a wide range of practical applications. However, this is a computationally difficult problem due to the large size of the computational domain compared to the acoustic wavelength. Here, the k-space pseudospectral method is used to reduce the number of grid points required per wavelength for accurate simulations. The model is based on coupled first-order acoustic equations valid for nonlinear wave propagation in heterogeneous media with power law absorption. These are derived from the equations of fluid mechanics and include a pressure-density relation that incorporates the effects of nonlinearity, power law absorption, and medium heterogeneities. The additional terms accounting for convective nonlinearity and power law absorption are expressed as spatial gradients making them efficient to numerically encode. The governing equations are then discretized using a k-space pseudospectral technique in which the spatial gradients are computed using the Fourier-collocation method. This increases the accuracy of the gradient calculation and thus relaxes the requirement for dense computational grids compared to conventional finite difference methods. The accuracy and utility of the developed model is demonstrated via several numerical experiments, including the 3D simulation of the beam pattern from a clinical ultrasound probe.

Microparticles controllable accumulation, arrangement, and spatial shaping performed by tapered-fiber-based laser-induced convection flow.

PubMed

Zhang, Yu; Lei, Jiaojie; Zhang, Yaxun; Liu, Zhihai; Zhang, Jianzhong; Yang, Xinghua; Yang, Jun; Yuan, Libo

2017-10-30

The ability to arrange cells and/or microparticles into the desired pattern is critical in biological, chemical, and metamaterial studies and other applications. Researchers have developed a variety of patterning techniques, which either have a limited capacity to simultaneously trap massive particles or lack the spatial resolution necessary to manipulate individual particle. Several approaches have been proposed that combine both high spatial selectivity and high throughput simultaneously. However, those methods are complex and difficult to fabricate. In this article, we propose and demonstrate a simple method that combines the laser-induced convection flow and fiber-based optical trapping methods to perform both regular and special spatial shaping arrangement. Essentially, we combine a light field with a large optical intensity gradient distribution and a thermal field with a large temperature gradient distribution to perform the microparticles shaping arrangement. The tapered-fiber-based laser-induced convection flow provides not only the batch manipulation of massive particles, but also the finer manipulation of special one or several particles, which break out the limit of single-fiber-based massive/individual particles photothermal manipulation. The combination technique allows for microparticles quick accumulation, single-layer and multilayer arrangement; special spatial shaping arrangement/adjustment, and microparticles sorting.

Quantification of susceptibility change at high-concentrated SPIO-labeled target by characteristic phase gradient recognition.

PubMed

Zhu, Haitao; Nie, Binbin; Liu, Hua; Guo, Hua; Demachi, Kazuyuki; Sekino, Masaki; Shan, Baoci

2016-05-01

Phase map cross-correlation detection and quantification may produce highlighted signal at superparamagnetic iron oxide nanoparticles, and distinguish them from other hypointensities. The method may quantify susceptibility change by performing least squares analysis between a theoretically generated magnetic field template and an experimentally scanned phase image. Because characteristic phase recognition requires the removal of phase wrap and phase background, additional steps of phase unwrapping and filtering may increase the chance of computing error and enlarge the inconsistence among algorithms. To solve problem, phase gradient cross-correlation and quantification method is developed by recognizing characteristic phase gradient pattern instead of phase image because phase gradient operation inherently includes unwrapping and filtering functions. However, few studies have mentioned the detectable limit of currently used phase gradient calculation algorithms. The limit may lead to an underestimation of large magnetic susceptibility change caused by high-concentrated iron accumulation. In this study, mathematical derivation points out the value of maximum detectable phase gradient calculated by differential chain algorithm in both spatial and Fourier domain. To break through the limit, a modified quantification method is proposed by using unwrapped forward differentiation for phase gradient generation. The method enlarges the detectable range of phase gradient measurement and avoids the underestimation of magnetic susceptibility. Simulation and phantom experiments were used to quantitatively compare different methods. In vivo application performs MRI scanning on nude mice implanted by iron-labeled human cancer cells. Results validate the limit of detectable phase gradient and the consequent susceptibility underestimation. Results also demonstrate the advantage of unwrapped forward differentiation compared with differential chain algorithms for susceptibility quantification at high-concentrated iron accumulation. Copyright © 2015 Elsevier Inc. All rights reserved.

Measurement and Perturbation of Morphogen Lifetime: Effects on Gradient Shape

PubMed Central

Drocco, Jeffrey A.; Grimm, Oliver; Tank, David W.; Wieschaus, Eric

2011-01-01

Protein lifetime is of critical importance for most biological processes and plays a central role in cell signaling and embryonic development, where it impacts the absolute concentration of signaling molecules and, potentially, the shape of morphogen gradients. Early conceptual and mathematical models of gradient formation proposed that steady-state gradients are established by an equilibration between the lifetime of a morphogen and its rates of synthesis and diffusion, though whether gradients in fact reach steady state before being read out is a matter of controversy. In any case, this class of models predicts that protein lifetime is a key determinant of both the time to steady state and the spatial extent of a gradient. Using a method that employs repeated photoswitching of a fusion of the morphogen Bicoid (Bcd) and the photoconvertible fluorescent protein Dronpa, we measure and modify the lifetime of Dronpa-Bcd in living Drosophila embryos. We find that the lifetime of Bcd is dynamic, changing from 50 min before mitotic cycle 14 to 15 min during cellularization. Moreover, by measuring total quantities of Bcd over time, we find that the gradient does not reach steady state. Finally, using a nearly continuous low-level conversion to the dark state of Dronpa-Bcd to mimic the effect of increased degradation, we demonstrate that perturbation of protein lifetime changes the characteristic length of the gradient, providing direct support for a mechanism based on synthesis, diffusion, and degradation. PMID:22004733

Quality-by-design-based ultra high performance liquid chromatography related substances method development by establishing the proficient design space for sumatriptan and naproxen combination.

PubMed

Patel, Prinesh N; Karakam, Vijaya Saradhi; Samanthula, Gananadhamu; Ragampeta, Srinivas

2015-10-01

Quality-by-design-based methods hold greater level of confidence for variations and greater success in method transfer. A quality-by-design-based ultra high performance liquid chromatography method was developed for the simultaneous assay of sumatriptan and naproxen along with their related substances. The first screening was performed by fractional factorial design comprising 44 experiments for reversed-phase stationary phases, pH, and organic modifiers. The results of screening design experiments suggested phenyl hexyl column and acetonitrile were the best combination. The method was further optimized for flow rate, temperature, and gradient time by experimental design of 20 experiments and the knowledge space was generated for effect of variable on response (number of peaks ≥ 1.50 - resolution). Proficient design space was generated from knowledge space by applying Monte Carlo simulation to successfully integrate quantitative robustness metrics during optimization stage itself. The final method provided the robust performance which was verified and validated. Final conditions comprised Waters® Acquity phenyl hexyl column with gradient elution using ammonium acetate (pH 4.12, 0.02 M) buffer and acetonitrile at 0.355 mL/min flow rate and 30°C. The developed method separates all 13 analytes within a 15 min run time with fewer experiments compared to the traditional quality-by-testing approach. ©2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An iterative method for the Helmholtz equation

NASA Technical Reports Server (NTRS)

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

1983-01-01

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

Theoretical analysis of degradation mechanisms in the formation of morphogen gradients

NASA Astrophysics Data System (ADS)

Bozorgui, Behnaz; Teimouri, Hamid; Kolomeisky, Anatoly B.

2015-07-01

Fundamental biological processes of development of tissues and organs in multicellular organisms are governed by various signaling molecules, which are called morphogens. It is known that spatial and temporal variations in the concentration profiles of signaling molecules, which are frequently referred as morphogen gradients, lead to a cell differentiation via activating specific genes in a concentration-dependent manner. It is widely accepted that the establishment of the morphogen gradients involves multiple biochemical reactions and diffusion processes. One of the critical elements in the formation of morphogen gradients is a degradation of signaling molecules. We develop a new theoretical approach that provides a comprehensive description of the degradation mechanisms. It is based on the idea that the degradation works as an effective potential that drives the signaling molecules away from the source region. Utilizing the method of first-passage processes, the dynamics of the formation of morphogen gradients for various degradation mechanisms is explicitly evaluated. It is found that linear degradation processes lead to a dynamic behavior specified by times to form the morphogen gradients that depend linearly on the distance from the source. This is because the effective potential due to the degradation is quite strong. At the same time, nonlinear degradation mechanisms yield a quadratic scaling in the morphogen gradients formation times since the effective potentials are much weaker. Physical-chemical explanations of these phenomena are presented.

The Effect of Concomitant Fields in Fast Spin Echo Acquisition on Asymmetric MRI Gradient Systems

PubMed Central

Tao, Shengzhen; Weavers, Paul T.; Trzasko, Joshua D.; Huston, John; Shu, Yunhong; Gray, Erin M.; Foo, Thomas K.F.; Bernstein, Matt A.

2017-01-01

Purpose To investigate the effect of the asymmetric gradient concomitant fields (CF) with zeroth and first-order spatial dependence on fast/turbo spin-echo acquisitions, and to demonstrate the effectiveness of their real-time compensation. Methods After briefly reviewing the CF produced by asymmetric gradients, the effects of the additional zeroth and first-order CFs on these systems are investigated using extended-phase graph simulations. Phantom and in vivo experiments are performed to corroborate the simulation. Experiments are performed before and after the real-time compensations using frequency tracking and gradient pre-emphasis to demonstrate their effectiveness in correcting the additional CFs. The interaction between the CFs and prescan-based correction to compensate for eddy currents is also investigated. Results It is demonstrated that, unlike the second-order CFs on conventional gradients, the additional zeroth/first-order CFs on asymmetric gradients cause substantial signal loss and dark banding in fast spin-echo acquisitions within a typical brain-scan field of view. They can confound the prescan correction for eddy currents and degrade image quality. Performing real-time compensation successfully eliminates the artifacts. Conclusions We demonstrate that the zeroth/first-order CFs specific to asymmetric gradients can cause substantial artifacts, including signal loss and dark bands for brain imaging. These effects can be corrected using real-time compensation. PMID:28643408

Retinal Microaneurysms Detection Using Gradient Vector Analysis and Class Imbalance Classification.

PubMed

Dai, Baisheng; Wu, Xiangqian; Bu, Wei

2016-01-01

Retinal microaneurysms (MAs) are the earliest clinically observable lesions of diabetic retinopathy. Reliable automated MAs detection is thus critical for early diagnosis of diabetic retinopathy. This paper proposes a novel method for the automated MAs detection in color fundus images based on gradient vector analysis and class imbalance classification, which is composed of two stages, i.e. candidate MAs extraction and classification. In the first stage, a candidate MAs extraction algorithm is devised by analyzing the gradient field of the image, in which a multi-scale log condition number map is computed based on the gradient vectors for vessel removal, and then the candidate MAs are localized according to the second order directional derivatives computed in different directions. Due to the complexity of fundus image, besides a small number of true MAs, there are also a large amount of non-MAs in the extracted candidates. Classifying the true MAs and the non-MAs is an extremely class imbalanced classification problem. Therefore, in the second stage, several types of features including geometry, contrast, intensity, edge, texture, region descriptors and other features are extracted from the candidate MAs and a class imbalance classifier, i.e., RUSBoost, is trained for the MAs classification. With the Retinopathy Online Challenge (ROC) criterion, the proposed method achieves an average sensitivity of 0.433 at 1/8, 1/4, 1/2, 1, 2, 4 and 8 false positives per image on the ROC database, which is comparable with the state-of-the-art approaches, and 0.321 on the DiaRetDB1 V2.1 database, which outperforms the state-of-the-art approaches.

On the Use of Nonlinear Regularization in Inverse Methods for the Solar Tachocline Profile Determination

NASA Astrophysics Data System (ADS)

Corbard, T.; Berthomieu, G.; Provost, J.; Blanc-Feraud, L.

Inferring the solar rotation from observed frequency splittings represents an ill-posed problem in the sense of Hadamard and the traditional approach used to override this difficulty consists in regularizing the problem by adding some a priori information on the global smoothness of the solution defined as the norm of its first or second derivative. Nevertheless, inversions of rotational splittings (e.g. Corbard et al., 1998; Schou et al., 1998) have shown that the surface layers and the so-called solar tachocline (Spiegel & Zahn 1992) at the base of the convection zone are regions in which high radial gradients of the rotation rate occur. %there exist high gradients in the solar rotation profile near %the surface and at the base of the convection zone (e.g. Corbard et al. 1998) %in the so-called solar tachocline (Spiegel & Zahn 1992). Therefore, the global smoothness a-priori which tends to smooth out every high gradient in the solution may not be appropriate for the study of a zone like the tachocline which is of particular interest for the study of solar dynamics (e.g. Elliot 1997). In order to infer the fine structure of such regions with high gradients by inverting helioseismic data, we have to find a way to preserve these zones in the inversion process. Setting a more adapted constraint on the solution leads to non-linear regularization methods that are in current use for edge-preserving regularization in computed imaging (e.g. Blanc-Feraud et al. 1995). In this work, we investigate their use in the helioseismic context of rotational inversions.

Combined Yamamoto approach for simultaneous estimation of adsorption isotherm and kinetic parameters in ion-exchange chromatography.

PubMed

Rüdt, Matthias; Gillet, Florian; Heege, Stefanie; Hitzler, Julian; Kalbfuss, Bernd; Guélat, Bertrand

2015-09-25

Application of model-based design is appealing to support the development of protein chromatography in the biopharmaceutical industry. However, the required efforts for parameter estimation are frequently perceived as time-consuming and expensive. In order to speed-up this work, a new parameter estimation approach for modelling ion-exchange chromatography in linear conditions was developed. It aims at reducing the time and protein demand for the model calibration. The method combines the estimation of kinetic and thermodynamic parameters based on the simultaneous variation of the gradient slope and the residence time in a set of five linear gradient elutions. The parameters are estimated from a Yamamoto plot and a gradient-adjusted Van Deemter plot. The combined approach increases the information extracted per experiment compared to the individual methods. As a proof of concept, the combined approach was successfully applied for a monoclonal antibody on a cation-exchanger and for a Fc-fusion protein on an anion-exchange resin. The individual parameter estimations for the mAb confirmed that the new approach maintained the accuracy of the usual Yamamoto and Van Deemter plots. In the second case, offline size-exclusion chromatography was performed in order to estimate the thermodynamic parameters of an impurity (high molecular weight species) simultaneously with the main product. Finally, the parameters obtained from the combined approach were used in a lumped kinetic model to simulate the chromatography runs. The simulated chromatograms obtained for a wide range of gradient lengths and residence times showed only small deviations compared to the experimental data. Copyright © 2015 Elsevier B.V. All rights reserved.

A comparison of two closely-related approaches to aerodynamic design optimization

NASA Technical Reports Server (NTRS)

Shubin, G. R.; Frank, P. D.

1991-01-01

Two related methods for aerodynamic design optimization are compared. The methods, called the implicit gradient approach and the variational (or optimal control) approach, both attempt to obtain gradients necessary for numerical optimization at a cost significantly less than that of the usual black-box approach that employs finite difference gradients. While the two methods are seemingly quite different, they are shown to differ (essentially) in that the order of discretizing the continuous problem, and of applying calculus, is interchanged. Under certain circumstances, the two methods turn out to be identical. We explore the relationship between these methods by applying them to a model problem for duct flow that has many features in common with transonic flow over an airfoil. We find that the gradients computed by the variational method can sometimes be sufficiently inaccurate to cause the optimization to fail.

Algorithms for Solvents and Spectral Factors of Matrix Polynomials

DTIC Science & Technology

1981-01-01

spectral factors of matrix polynomials LEANG S. SHIEHt, YIH T. TSAYt and NORMAN P. COLEMANt A generalized Newton method , based on the contracted gradient...of a matrix poly- nomial, is derived for solving the right (left) solvents and spectral factors of matrix polynomials. Two methods of selecting initial...estimates for rapid convergence of the newly developed numerical method are proposed. Also, new algorithms for solving complete sets of the right