Properties of the Magnitude Terms of Orthogonal Scaling Functions.
Tay, Peter C; Havlicek, Joseph P; Acton, Scott T; Hossack, John A
2010-09-01
The spectrum of the convolution of two continuous functions can be determined as the continuous Fourier transform of the cross-correlation function. The same can be said about the spectrum of the convolution of two infinite discrete sequences, which can be determined as the discrete time Fourier transform of the cross-correlation function of the two sequences. In current digital signal processing, the spectrum of the contiuous Fourier transform and the discrete time Fourier transform are approximately determined by numerical integration or by densely taking the discrete Fourier transform. It has been shown that all three transforms share many analogous properties. In this paper we will show another useful property of determining the spectrum terms of the convolution of two finite length sequences by determining the discrete Fourier transform of the modified cross-correlation function. In addition, two properties of the magnitude terms of orthogonal wavelet scaling functions are developed. These properties are used as constraints for an exhaustive search to determine an robust lower bound on conjoint localization of orthogonal scaling functions.
Elucidation of spin echo small angle neutron scattering correlation functions through model studies.
Shew, Chwen-Yang; Chen, Wei-Ren
2012-02-14
Several single-modal Debye correlation functions to approximate part of the overall Debey correlation function of liquids are closely examined for elucidating their behavior in the corresponding spin echo small angle neutron scattering (SESANS) correlation functions. We find that the maximum length scale of a Debye correlation function is identical to that of its SESANS correlation function. For discrete Debye correlation functions, the peak of SESANS correlation function emerges at their first discrete point, whereas for continuous Debye correlation functions with greater width, the peak position shifts to a greater value. In both cases, the intensity and shape of the peak of the SESANS correlation function are determined by the width of the Debye correlation functions. Furthermore, we mimic the intramolecular and intermolecular Debye correlation functions of liquids composed of interacting particles based on a simple model to elucidate their competition in the SESANS correlation function. Our calculations show that the first local minimum of a SESANS correlation function can be negative and positive. By adjusting the spatial distribution of the intermolecular Debye function in the model, the calculated SESANS spectra exhibit the profile consistent with that of hard-sphere and sticky-hard-sphere liquids predicted by more sophisticated liquid state theory and computer simulation. © 2012 American Institute of Physics
Pair correlation functions for identifying spatial correlation in discrete domains
NASA Astrophysics Data System (ADS)
Gavagnin, Enrico; Owen, Jennifer P.; Yates, Christian A.
2018-06-01
Identifying and quantifying spatial correlation are important aspects of studying the collective behavior of multiagent systems. Pair correlation functions (PCFs) are powerful statistical tools that can provide qualitative and quantitative information about correlation between pairs of agents. Despite the numerous PCFs defined for off-lattice domains, only a few recent studies have considered a PCF for discrete domains. Our work extends the study of spatial correlation in discrete domains by defining a new set of PCFs using two natural and intuitive definitions of distance for a square lattice: the taxicab and uniform metric. We show how these PCFs improve upon previous attempts and compare between the quantitative data acquired. We also extend our definitions of the PCF to other types of regular tessellation that have not been studied before, including hexagonal, triangular, and cuboidal. Finally, we provide a comprehensive PCF for any tessellation and metric, allowing investigation of spatial correlation in irregular lattices for which recognizing correlation is less intuitive.
A Discrete Probability Function Method for the Equation of Radiative Transfer
NASA Technical Reports Server (NTRS)
Sivathanu, Y. R.; Gore, J. P.
1993-01-01
A discrete probability function (DPF) method for the equation of radiative transfer is derived. The DPF is defined as the integral of the probability density function (PDF) over a discrete interval. The derivation allows the evaluation of the PDF of intensities leaving desired radiation paths including turbulence-radiation interactions without the use of computer intensive stochastic methods. The DPF method has a distinct advantage over conventional PDF methods since the creation of a partial differential equation from the equation of transfer is avoided. Further, convergence of all moments of intensity is guaranteed at the basic level of simulation unlike the stochastic method where the number of realizations for convergence of higher order moments increases rapidly. The DPF method is described for a representative path with approximately integral-length scale-sized spatial discretization. The results show good agreement with measurements in a propylene/air flame except for the effects of intermittency resulting from highly correlated realizations. The method can be extended to the treatment of spatial correlations as described in the Appendix. However, information regarding spatial correlations in turbulent flames is needed prior to the execution of this extension.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Behbahani, Siavosh R.; /SLAC /Stanford U., Phys. Dept. /Boston U.; Dymarsky, Anatoly
2012-06-06
We apply the Effective Field Theory of Inflation to study the case where the continuous shift symmetry of the Goldstone boson {pi} is softly broken to a discrete subgroup. This case includes and generalizes recently proposed String Theory inspired models of Inflation based on Axion Monodromy. The models we study have the property that the 2-point function oscillates as a function of the wavenumber, leading to oscillations in the CMB power spectrum. The non-linear realization of time diffeomorphisms induces some self-interactions for the Goldstone boson that lead to a peculiar non-Gaussianity whose shape oscillates as a function of the wavenumber.more » We find that in the regime of validity of the effective theory, the oscillatory signal contained in the n-point correlation functions, with n > 2, is smaller than the one contained in the 2-point function, implying that the signature of oscillations, if ever detected, will be easier to find first in the 2-point function, and only then in the higher order correlation functions. Still the signal contained in higher-order correlation functions, that we study here in generality, could be detected at a subleading level, providing a very compelling consistency check for an approximate discrete shift symmetry being realized during inflation.« less
Stochastic dynamics of time correlation in complex systems with discrete time
NASA Astrophysics Data System (ADS)
Yulmetyev, Renat; Hänggi, Peter; Gafarov, Fail
2000-11-01
In this paper we present the concept of description of random processes in complex systems with discrete time. It involves the description of kinetics of discrete processes by means of the chain of finite-difference non-Markov equations for time correlation functions (TCFs). We have introduced the dynamic (time dependent) information Shannon entropy Si(t) where i=0,1,2,3,..., as an information measure of stochastic dynamics of time correlation (i=0) and time memory (i=1,2,3,...). The set of functions Si(t) constitute the quantitative measure of time correlation disorder (i=0) and time memory disorder (i=1,2,3,...) in complex system. The theory developed started from the careful analysis of time correlation involving dynamics of vectors set of various chaotic states. We examine two stochastic processes involving the creation and annihilation of time correlation (or time memory) in details. We carry out the analysis of vectors' dynamics employing finite-difference equations for random variables and the evolution operator describing their natural motion. The existence of TCF results in the construction of the set of projection operators by the usage of scalar product operation. Harnessing the infinite set of orthogonal dynamic random variables on a basis of Gram-Shmidt orthogonalization procedure tends to creation of infinite chain of finite-difference non-Markov kinetic equations for discrete TCFs and memory functions (MFs). The solution of the equations above thereof brings to the recurrence relations between the TCF and MF of senior and junior orders. This offers new opportunities for detecting the frequency spectra of power of entropy function Si(t) for time correlation (i=0) and time memory (i=1,2,3,...). The results obtained offer considerable scope for attack on stochastic dynamics of discrete random processes in a complex systems. Application of this technique on the analysis of stochastic dynamics of RR intervals from human ECG's shows convincing evidence for a non-Markovian phenomemena associated with a peculiarities in short- and long-range scaling. This method may be of use in distinguishing healthy from pathologic data sets based in differences in these non-Markovian properties.
Exact Asymptotics of the Freezing Transition of a Logarithmically Correlated Random Energy Model
NASA Astrophysics Data System (ADS)
Webb, Christian
2011-12-01
We consider a logarithmically correlated random energy model, namely a model for directed polymers on a Cayley tree, which was introduced by Derrida and Spohn. We prove asymptotic properties of a generating function of the partition function of the model by studying a discrete time analogy of the KPP-equation—thus translating Bramson's work on the KPP-equation into a discrete time case. We also discuss connections to extreme value statistics of a branching random walk and a rescaled multiplicative cascade measure beyond the critical point.
Ways to improve your correlation functions
NASA Technical Reports Server (NTRS)
Hamilton, A. J. S.
1993-01-01
This paper describes a number of ways to improve on the standard method for measuring the two-point correlation function of large scale structure in the Universe. Issues addressed are: (1) the problem of the mean density, and how to solve it; (2) how to estimate the uncertainty in a measured correlation function; (3) minimum variance pair weighting; (4) unbiased estimation of the selection function when magnitudes are discrete; and (5) analytic computation of angular integrals in background pair counts.
Percolation analysis for cosmic web with discrete points
NASA Astrophysics Data System (ADS)
Zhang, Jiajun; Cheng, Dalong; Chu, Ming-Chung
2016-03-01
Percolation analysis has long been used to quantify the connectivity of the cosmic web. Unlike most of the previous works using density field on grids, we have studied percolation analysis based on discrete points. Using a Friends-of-Friends (FoF) algorithm, we generate the S-bb relation, between the fractional mass of the largest connected group (S) and the FoF linking length (bb). We propose a new model, the Probability Cloud Cluster Expansion Theory (PCCET) to relate the S-bb relation with correlation functions. We show that the S-bb relation reflects a combination of all orders of correlation functions. We have studied the S-bb relation with simulation and find that the S-bb relation is robust against redshift distortion and incompleteness in observation. From the Bolshoi simulation, with Halo Abundance Matching (HAM), we have generated a mock galaxy catalogue. Good matching of the projected two-point correlation function with observation is confirmed. However, comparing the mock catalogue with the latest galaxy catalogue from SDSS DR12, we have found significant differences in their S-bb relations. This indicates that the mock catalogue cannot accurately recover higher order correlation functions than the two-point correlation function, which reveals the limit of HAM method.
Tail shortening by discrete hydrodynamics
NASA Astrophysics Data System (ADS)
Kiefer, J.; Visscher, P. B.
1982-02-01
A discrete formulation of hydrodynamics was recently introduced, whose most important feature is that it is exactly renormalizable. Previous numerical work has found that it provides a more efficient and rapidly convergent method for calculating transport coefficients than the usual Green-Kubo method. The latter's convergence difficulties are due to the well-known "long-time tail" of the time correlation function which must be integrated over time. The purpose of the present paper is to present additional evidence that these difficulties are really absent in the discrete equation of motion approach. The "memory" terms in the equation of motion are calculated accurately, and shown to decay much more rapidly with time than the equilibrium time correlations do.
Assessing the role of spatial correlations during collective cell spreading
Treloar, Katrina K.; Simpson, Matthew J.; Binder, Benjamin J.; McElwain, D. L. Sean; Baker, Ruth E.
2014-01-01
Spreading cell fronts are essential features of development, repair and disease processes. Many mathematical models used to describe the motion of cell fronts, such as Fisher's equation, invoke a mean–field assumption which implies that there is no spatial structure, such as cell clustering, present. Here, we examine the presence of spatial structure using a combination of in vitro circular barrier assays, discrete random walk simulations and pair correlation functions. In particular, we analyse discrete simulation data using pair correlation functions to show that spatial structure can form in a spreading population of cells either through sufficiently strong cell–to–cell adhesion or sufficiently rapid cell proliferation. We analyse images from a circular barrier assay describing the spreading of a population of MM127 melanoma cells using the same pair correlation functions. Our results indicate that the spreading melanoma cell populations remain very close to spatially uniform, suggesting that the strength of cell–to–cell adhesion and the rate of cell proliferation are both sufficiently small so as not to induce any spatial patterning in the spreading populations. PMID:25026987
NASA Technical Reports Server (NTRS)
Ma, Q.; Tipping, R. H.; Lavrentieva, N. N.
2012-01-01
By adopting a concept from signal processing, instead of starting from the correlation functions which are even, one considers the causal correlation functions whose Fourier transforms become complex. Their real and imaginary parts multiplied by 2 are the Fourier transforms of the original correlations and the subsequent Hilbert transforms, respectively. Thus, by taking this step one can complete the two previously needed transforms. However, to obviate performing the Cauchy principal integrations required in the Hilbert transforms is the greatest advantage. Meanwhile, because the causal correlations are well-bounded within the time domain and band limited in the frequency domain, one can replace their Fourier transforms by the discrete Fourier transforms and the latter can be carried out with the FFT algorithm. This replacement is justified by sampling theory because the Fourier transforms can be derived from the discrete Fourier transforms with the Nyquis rate without any distortions. We apply this method in calculating pressure induced shifts of H2O lines and obtain more reliable values. By comparing the calculated shifts with those in HITRAN 2008 and by screening both of them with the pair identity and the smooth variation rules, one can conclude many of shift values in HITRAN are not correct.
Coarse-grained hydrodynamics from correlation functions
NASA Astrophysics Data System (ADS)
Palmer, Bruce
2018-02-01
This paper will describe a formalism for using correlation functions between different grid cells as the basis for determining coarse-grained hydrodynamic equations for modeling the behavior of mesoscopic fluid systems. Configurations from a molecular dynamics simulation or other atomistic simulation are projected onto basis functions representing grid cells in a continuum hydrodynamic simulation. Equilibrium correlation functions between different grid cells are evaluated from the molecular simulation and used to determine the evolution operator for the coarse-grained hydrodynamic system. The formalism is demonstrated on a discrete particle simulation of diffusion with a spatially dependent diffusion coefficient. Correlation functions are calculated from the particle simulation and the spatially varying diffusion coefficient is recovered using a fitting procedure.
Statistics of primordial density perturbations from discrete seed masses
NASA Technical Reports Server (NTRS)
Scherrer, Robert J.; Bertschinger, Edmund
1991-01-01
The statistics of density perturbations for general distributions of seed masses with arbitrary matter accretion is examined. Formal expressions for the power spectrum, the N-point correlation functions, and the density distribution function are derived. These results are applied to the case of uncorrelated seed masses, and power spectra are derived for accretion of both hot and cold dark matter plus baryons. The reduced moments (cumulants) of the density distribution are computed and used to obtain a series expansion for the density distribution function. Analytic results are obtained for the density distribution function in the case of a distribution of seed masses with a spherical top-hat accretion pattern. More generally, the formalism makes it possible to give a complete characterization of the statistical properties of any random field generated from a discrete linear superposition of kernels. In particular, the results can be applied to density fields derived by smoothing a discrete set of points with a window function.
Effect of the image resolution on the statistical descriptors of heterogeneous media.
Ledesma-Alonso, René; Barbosa, Romeli; Ortegón, Jaime
2018-02-01
The characterization and reconstruction of heterogeneous materials, such as porous media and electrode materials, involve the application of image processing methods to data acquired by scanning electron microscopy or other microscopy techniques. Among them, binarization and decimation are critical in order to compute the correlation functions that characterize the microstructure of the above-mentioned materials. In this study, we present a theoretical analysis of the effects of the image-size reduction, due to the progressive and sequential decimation of the original image. Three different decimation procedures (random, bilinear, and bicubic) were implemented and their consequences on the discrete correlation functions (two-point, line-path, and pore-size distribution) and the coarseness (derived from the local volume fraction) are reported and analyzed. The chosen statistical descriptors (correlation functions and coarseness) are typically employed to characterize and reconstruct heterogeneous materials. A normalization for each of the correlation functions has been performed. When the loss of statistical information has not been significant for a decimated image, its normalized correlation function is forecast by the trend of the original image (reference function). In contrast, when the decimated image does not hold statistical evidence of the original one, the normalized correlation function diverts from the reference function. Moreover, the equally weighted sum of the average of the squared difference, between the discrete correlation functions of the decimated images and the reference functions, leads to a definition of an overall error. During the first stages of the gradual decimation, the error remains relatively small and independent of the decimation procedure. Above a threshold defined by the correlation length of the reference function, the error becomes a function of the number of decimation steps. At this stage, some statistical information is lost and the error becomes dependent on the decimation procedure. These results may help us to restrict the amount of information that one can afford to lose during a decimation process, in order to reduce the computational and memory cost, when one aims to diminish the time consumed by a characterization or reconstruction technique, yet maintaining the statistical quality of the digitized sample.
Effect of the image resolution on the statistical descriptors of heterogeneous media
NASA Astrophysics Data System (ADS)
Ledesma-Alonso, René; Barbosa, Romeli; Ortegón, Jaime
2018-02-01
The characterization and reconstruction of heterogeneous materials, such as porous media and electrode materials, involve the application of image processing methods to data acquired by scanning electron microscopy or other microscopy techniques. Among them, binarization and decimation are critical in order to compute the correlation functions that characterize the microstructure of the above-mentioned materials. In this study, we present a theoretical analysis of the effects of the image-size reduction, due to the progressive and sequential decimation of the original image. Three different decimation procedures (random, bilinear, and bicubic) were implemented and their consequences on the discrete correlation functions (two-point, line-path, and pore-size distribution) and the coarseness (derived from the local volume fraction) are reported and analyzed. The chosen statistical descriptors (correlation functions and coarseness) are typically employed to characterize and reconstruct heterogeneous materials. A normalization for each of the correlation functions has been performed. When the loss of statistical information has not been significant for a decimated image, its normalized correlation function is forecast by the trend of the original image (reference function). In contrast, when the decimated image does not hold statistical evidence of the original one, the normalized correlation function diverts from the reference function. Moreover, the equally weighted sum of the average of the squared difference, between the discrete correlation functions of the decimated images and the reference functions, leads to a definition of an overall error. During the first stages of the gradual decimation, the error remains relatively small and independent of the decimation procedure. Above a threshold defined by the correlation length of the reference function, the error becomes a function of the number of decimation steps. At this stage, some statistical information is lost and the error becomes dependent on the decimation procedure. These results may help us to restrict the amount of information that one can afford to lose during a decimation process, in order to reduce the computational and memory cost, when one aims to diminish the time consumed by a characterization or reconstruction technique, yet maintaining the statistical quality of the digitized sample.
Percolation analysis for cosmic web with discrete points
NASA Astrophysics Data System (ADS)
Zhang, Jiajun; Cheng, Dalong; Chu, Ming-Chung
2018-01-01
Percolation analysis has long been used to quantify the connectivity of the cosmic web. Most of the previous work is based on density fields on grids. By smoothing into fields, we lose information about galaxy properties like shape or luminosity. The lack of mathematical modeling also limits our understanding for the percolation analysis. To overcome these difficulties, we have studied percolation analysis based on discrete points. Using a friends-of-friends (FoF) algorithm, we generate the S -b b relation, between the fractional mass of the largest connected group (S ) and the FoF linking length (b b ). We propose a new model, the probability cloud cluster expansion theory to relate the S -b b relation with correlation functions. We show that the S -b b relation reflects a combination of all orders of correlation functions. Using N-body simulation, we find that the S -b b relation is robust against redshift distortion and incompleteness in observation. From the Bolshoi simulation, with halo abundance matching (HAM), we have generated a mock galaxy catalog. Good matching of the projected two-point correlation function with observation is confirmed. However, comparing the mock catalog with the latest galaxy catalog from Sloan Digital Sky Survey (SDSS) Data Release (DR)12, we have found significant differences in their S -b b relations. This indicates that the mock galaxy catalog cannot accurately retain higher-order correlation functions than the two-point correlation function, which reveals the limit of the HAM method. As a new measurement, the S -b b relation is applicable to a wide range of data types, fast to compute, and robust against redshift distortion and incompleteness and contains information of all orders of correlation functions.
NASA Technical Reports Server (NTRS)
Mcclelland, J.; Silk, J.
1978-01-01
Higher-order correlation functions for the large-scale distribution of galaxies in space are investigated. It is demonstrated that the three-point correlation function observed by Peebles and Groth (1975) is not consistent with a distribution of perturbations that at present are randomly distributed in space. The two-point correlation function is shown to be independent of how the perturbations are distributed spatially, and a model of clustered perturbations is developed which incorporates a nonuniform perturbation distribution and which explains the three-point correlation function. A model with hierarchical perturbations incorporating the same nonuniform distribution is also constructed; it is found that this model also explains the three-point correlation function, but predicts different results for the four-point and higher-order correlation functions than does the model with clustered perturbations. It is suggested that the model of hierarchical perturbations might be explained by the single assumption of having density fluctuations or discrete objects all of the same mass randomly placed at some initial epoch.
Multifractal analysis of time series generated by discrete Ito equations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Telesca, Luciano; Czechowski, Zbigniew; Lovallo, Michele
2015-06-15
In this study, we show that discrete Ito equations with short-tail Gaussian marginal distribution function generate multifractal time series. The multifractality is due to the nonlinear correlations, which are hidden in Markov processes and are generated by the interrelation between the drift and the multiplicative stochastic forces in the Ito equation. A link between the range of the generalized Hurst exponents and the mean of the squares of all averaged net forces is suggested.
NASA Astrophysics Data System (ADS)
Sudharsanan, Subramania I.; Mahalanobis, Abhijit; Sundareshan, Malur K.
1990-12-01
Discrete frequency domain design of Minimum Average Correlation Energy filters for optical pattern recognition introduces an implementational limitation of circular correlation. An alternative methodology which uses space domain computations to overcome this problem is presented. The technique is generalized to construct an improved synthetic discriminant function which satisfies the conflicting requirements of reduced noise variance and sharp correlation peaks to facilitate ease of detection. A quantitative evaluation of the performance characteristics of the new filter is conducted and is shown to compare favorably with the well known Minimum Variance Synthetic Discriminant Function and the space domain Minimum Average Correlation Energy filter, which are special cases of the present design.
NASA Technical Reports Server (NTRS)
Scargle, Jeffrey D.
1989-01-01
This paper develops techniques to evaluate the discrete Fourier transform (DFT), the autocorrelation function (ACF), and the cross-correlation function (CCF) of time series which are not evenly sampled. The series may consist of quantized point data (e.g., yes/no processes such as photon arrival). The DFT, which can be inverted to recover the original data and the sampling, is used to compute correlation functions by means of a procedure which is effectively, but not explicitly, an interpolation. The CCF can be computed for two time series not even sampled at the same set of times. Techniques for removing the distortion of the correlation functions caused by the sampling, determining the value of a constant component to the data, and treating unequally weighted data are also discussed. FORTRAN code for the Fourier transform algorithm and numerical examples of the techniques are given.
Syed, Maleeha F; Lindquist, Martin A; Pillai, Jay J; Agarwal, Shruti; Gujar, Sachin K; Choe, Ann S; Caffo, Brian; Sair, Haris I
2017-12-01
Functional connectivity in resting-state functional magnetic resonance imaging (rs-fMRI) has received substantial attention since the initial findings of Biswal et al. Traditional network correlation metrics assume that the functional connectivity in the brain remains stationary over time. However, recent studies have shown that robust temporal fluctuations of functional connectivity among as well as within functional networks exist, challenging this assumption. In this study, these dynamic correlation differences were investigated between the dorsal and ventral sensorimotor networks by applying the dynamic conditional correlation model to rs-fMRI data of 20 healthy subjects. k-Means clustering was used to determine an optimal number of discrete connectivity states (k = 10) of the sensorimotor system across all subjects. Our analysis confirms the existence of differences in dynamic correlation between the dorsal and ventral networks, with highest connectivity found within the ventral motor network.
Models for discrete-time self-similar vector processes with application to network traffic
NASA Astrophysics Data System (ADS)
Lee, Seungsin; Rao, Raghuveer M.; Narasimha, Rajesh
2003-07-01
The paper defines self-similarity for vector processes by employing the discrete-time continuous-dilation operation which has successfully been used previously by the authors to define 1-D discrete-time stochastic self-similar processes. To define self-similarity of vector processes, it is required to consider the cross-correlation functions between different 1-D processes as well as the autocorrelation function of each constituent 1-D process in it. System models to synthesize self-similar vector processes are constructed based on the definition. With these systems, it is possible to generate self-similar vector processes from white noise inputs. An important aspect of the proposed models is that they can be used to synthesize various types of self-similar vector processes by choosing proper parameters. Additionally, the paper presents evidence of vector self-similarity in two-channel wireless LAN data and applies the aforementioned systems to simulate the corresponding network traffic traces.
Wakamiya, Eiji; Okumura, Tomohito; Nakanishi, Makoto; Takeshita, Takashi; Mizuta, Mekumi; Kurimoto, Naoko; Tamai, Hiroshi
2011-06-01
To clarify whether rapid naming ability itself is a main underpinning factor of rapid automatized naming tests (RAN) and how deep an influence the discrete decoding process has on reading, we performed discrete naming tasks and discrete hiragana reading tasks as well as sequential naming tasks and sequential hiragana reading tasks with 38 Japanese schoolchildren with reading difficulty. There were high correlations between both discrete and sequential hiragana reading and sentence reading, suggesting that some mechanism which automatizes hiragana reading makes sentence reading fluent. In object and color tasks, there were moderate correlations between sentence reading and sequential naming, and between sequential naming and discrete naming. But no correlation was found between reading tasks and discrete naming tasks. The influence of rapid naming ability of objects and colors upon reading seemed relatively small, and multi-item processing may work in relation to these. In contrast, in the digit naming task there was moderate correlation between sentence reading and discrete naming, while no correlation was seen between sequential naming and discrete naming. There was moderate correlation between reading tasks and sequential digit naming tasks. Digit rapid naming ability has more direct effect on reading while its effect on RAN is relatively limited. The ratio of how rapid naming ability influences RAN and reading seems to vary according to kind of the stimuli used. An assumption about components in RAN which influence reading is discussed in the context of both sequential processing and discrete naming speed. Copyright © 2010 The Japanese Society of Child Neurology. Published by Elsevier B.V. All rights reserved.
A phase screen model for simulating numerically the propagation of a laser beam in rain
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lukin, I P; Rychkov, D S; Falits, A V
2009-09-30
The method based on the generalisation of the phase screen method for a continuous random medium is proposed for simulating numerically the propagation of laser radiation in a turbulent atmosphere with precipitation. In the phase screen model for a discrete component of a heterogeneous 'air-rain droplet' medium, the amplitude screen describing the scattering of an optical field by discrete particles of the medium is replaced by an equivalent phase screen with a spectrum of the correlation function of the effective dielectric constant fluctuations that is similar to the spectrum of a discrete scattering component - water droplets in air. Themore » 'turbulent' phase screen is constructed on the basis of the Kolmogorov model, while the 'rain' screen model utiises the exponential distribution of the number of rain drops with respect to their radii as a function of the rain intensity. Theresults of the numerical simulation are compared with the known theoretical estimates for a large-scale discrete scattering medium. (propagation of laser radiation in matter)« less
Learning Discriminative Binary Codes for Large-scale Cross-modal Retrieval.
Xu, Xing; Shen, Fumin; Yang, Yang; Shen, Heng Tao; Li, Xuelong
2017-05-01
Hashing based methods have attracted considerable attention for efficient cross-modal retrieval on large-scale multimedia data. The core problem of cross-modal hashing is how to learn compact binary codes that construct the underlying correlations between heterogeneous features from different modalities. A majority of recent approaches aim at learning hash functions to preserve the pairwise similarities defined by given class labels. However, these methods fail to explicitly explore the discriminative property of class labels during hash function learning. In addition, they usually discard the discrete constraints imposed on the to-be-learned binary codes, and compromise to solve a relaxed problem with quantization to obtain the approximate binary solution. Therefore, the binary codes generated by these methods are suboptimal and less discriminative to different classes. To overcome these drawbacks, we propose a novel cross-modal hashing method, termed discrete cross-modal hashing (DCH), which directly learns discriminative binary codes while retaining the discrete constraints. Specifically, DCH learns modality-specific hash functions for generating unified binary codes, and these binary codes are viewed as representative features for discriminative classification with class labels. An effective discrete optimization algorithm is developed for DCH to jointly learn the modality-specific hash function and the unified binary codes. Extensive experiments on three benchmark data sets highlight the superiority of DCH under various cross-modal scenarios and show its state-of-the-art performance.
NASA Technical Reports Server (NTRS)
Hewes, C. R.; Bosshart, P. W.; Eversole, W. L.; Dewit, M.; Buss, D. D.
1976-01-01
Two CCD techniques were discussed for performing an N-point sampled data correlation between an input signal and an electronically programmable reference function. The design and experimental performance of an implementation of the direct time correlator utilizing two analog CCDs and MOS multipliers on a single IC were evaluated. The performance of a CCD implementation of the chirp z transform was described, and the design of a new CCD integrated circuit for performing correlation by multiplication in the frequency domain was presented. This chip provides a discrete Fourier transform (DFT) or inverse DFT, multipliers, and complete support circuitry for the CCD CZT. The two correlation techniques are compared.
Cyber-Physical Correlations for Infrastructure Resilience: A Game-Theoretic Approach
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rao, Nageswara S; He, Fei; Ma, Chris Y. T.
In several critical infrastructures, the cyber and physical parts are correlated so that disruptions to one affect the other and hence the whole system. These correlations may be exploited to strategically launch components attacks, and hence must be accounted for ensuring the infrastructure resilience, specified by its survival probability. We characterize the cyber-physical interactions at two levels: (i) the failure correlation function specifies the conditional survival probability of cyber sub-infrastructure given the physical sub-infrastructure as a function of their marginal probabilities, and (ii) the individual survival probabilities of both sub-infrastructures are characterized by first-order differential conditions. We formulate a resiliencemore » problem for infrastructures composed of discrete components as a game between the provider and attacker, wherein their utility functions consist of an infrastructure survival probability term and a cost term expressed in terms of the number of components attacked and reinforced. We derive Nash Equilibrium conditions and sensitivity functions that highlight the dependence of infrastructure resilience on the cost term, correlation function and sub-infrastructure survival probabilities. These results generalize earlier ones based on linear failure correlation functions and independent component failures. We apply the results to models of cloud computing infrastructures and energy grids.« less
Dynamical potentials for nonequilibrium quantum many-body phases
NASA Astrophysics Data System (ADS)
Roy, Sthitadhi; Lazarides, Achilleas; Heyl, Markus; Moessner, Roderich
2018-05-01
Out of equilibrium phases of matter exhibiting order in individual eigenstates, such as many-body localized spin glasses and discrete time crystals, can be characterized by inherently dynamical quantities such as spatiotemporal correlation functions. In this paper, we introduce dynamical potentials which act as generating functions for such correlations and capture eigenstate phases and order. These potentials show formal similarities to their equilibrium counterparts, namely thermodynamic potentials. We provide three representative examples: a disordered XXZ chain showing many-body localization, a disordered Ising chain exhibiting spin-glass order, and its periodically-driven cousin exhibiting time-crystalline order.
Persistence of non-Markovian Gaussian stationary processes in discrete time
NASA Astrophysics Data System (ADS)
Nyberg, Markus; Lizana, Ludvig
2018-04-01
The persistence of a stochastic variable is the probability that it does not cross a given level during a fixed time interval. Although persistence is a simple concept to understand, it is in general hard to calculate. Here we consider zero mean Gaussian stationary processes in discrete time n . Few results are known for the persistence P0(n ) in discrete time, except the large time behavior which is characterized by the nontrivial constant θ through P0(n ) ˜θn . Using a modified version of the independent interval approximation (IIA) that we developed before, we are able to calculate P0(n ) analytically in z -transform space in terms of the autocorrelation function A (n ) . If A (n )→0 as n →∞ , we extract θ numerically, while if A (n )=0 , for finite n >N , we find θ exactly (within the IIA). We apply our results to three special cases: the nearest-neighbor-correlated "first order moving average process", where A (n )=0 for n >1 , the double exponential-correlated "second order autoregressive process", where A (n ) =c1λ1n+c2λ2n , and power-law-correlated variables, where A (n ) ˜n-μ . Apart from the power-law case when μ <5 , we find excellent agreement with simulations.
On the Importance of Both Dimensional and Discrete Models of Emotion.
Harmon-Jones, Eddie; Harmon-Jones, Cindy; Summerell, Elizabeth
2017-09-29
We review research on the structure and functions of emotions that has benefitted from a serious consideration of both discrete and dimensional perspectives on emotion. To illustrate this point, we review research that demonstrates: (1) how affective valence within discrete emotions differs as a function of individuals and situations, and how these differences relate to various functions; (2) that anger (and other emotional states) should be considered as a discrete emotion but there are dimensions around and within anger; (3) that similarities exist between approach-related positive and negative discrete emotions and they have unique motivational functions; (4) that discrete emotions and broad dimensions of emotions both have unique functions; and (5) evidence that a "new" discrete emotion with discrete functions exists within a broader emotion family. We hope that this consideration of both discrete and dimensional perspectives on emotion will assist in understanding the functions of emotions.
On the Importance of Both Dimensional and Discrete Models of Emotion
Harmon-Jones, Eddie
2017-01-01
We review research on the structure and functions of emotions that has benefitted from a serious consideration of both discrete and dimensional perspectives on emotion. To illustrate this point, we review research that demonstrates: (1) how affective valence within discrete emotions differs as a function of individuals and situations, and how these differences relate to various functions; (2) that anger (and other emotional states) should be considered as a discrete emotion but there are dimensions around and within anger; (3) that similarities exist between approach-related positive and negative discrete emotions and they have unique motivational functions; (4) that discrete emotions and broad dimensions of emotions both have unique functions; and (5) evidence that a “new” discrete emotion with discrete functions exists within a broader emotion family. We hope that this consideration of both discrete and dimensional perspectives on emotion will assist in understanding the functions of emotions. PMID:28961185
Defense Strategies for Asymmetric Networked Systems with Discrete Components.
Rao, Nageswara S V; Ma, Chris Y T; Hausken, Kjell; He, Fei; Yau, David K Y; Zhuang, Jun
2018-05-03
We consider infrastructures consisting of a network of systems, each composed of discrete components. The network provides the vital connectivity between the systems and hence plays a critical, asymmetric role in the infrastructure operations. The individual components of the systems can be attacked by cyber and physical means and can be appropriately reinforced to withstand these attacks. We formulate the problem of ensuring the infrastructure performance as a game between an attacker and a provider, who choose the numbers of the components of the systems and network to attack and reinforce, respectively. The costs and benefits of attacks and reinforcements are characterized using the sum-form, product-form and composite utility functions, each composed of a survival probability term and a component cost term. We present a two-level characterization of the correlations within the infrastructure: (i) the aggregate failure correlation function specifies the infrastructure failure probability given the failure of an individual system or network, and (ii) the survival probabilities of the systems and network satisfy first-order differential conditions that capture the component-level correlations using multiplier functions. We derive Nash equilibrium conditions that provide expressions for individual system survival probabilities and also the expected infrastructure capacity specified by the total number of operational components. We apply these results to derive and analyze defense strategies for distributed cloud computing infrastructures using cyber-physical models.
Functional transformations of odor inputs in the mouse olfactory bulb.
Adam, Yoav; Livneh, Yoav; Miyamichi, Kazunari; Groysman, Maya; Luo, Liqun; Mizrahi, Adi
2014-01-01
Sensory inputs from the nasal epithelium to the olfactory bulb (OB) are organized as a discrete map in the glomerular layer (GL). This map is then modulated by distinct types of local neurons and transmitted to higher brain areas via mitral and tufted cells. Little is known about the functional organization of the circuits downstream of glomeruli. We used in vivo two-photon calcium imaging for large scale functional mapping of distinct neuronal populations in the mouse OB, at single cell resolution. Specifically, we imaged odor responses of mitral cells (MCs), tufted cells (TCs) and glomerular interneurons (GL-INs). Mitral cells population activity was heterogeneous and only mildly correlated with the olfactory receptor neuron (ORN) inputs, supporting the view that discrete input maps undergo significant transformations at the output level of the OB. In contrast, population activity profiles of TCs were dense, and highly correlated with the odor inputs in both space and time. Glomerular interneurons were also highly correlated with the ORN inputs, but showed higher activation thresholds suggesting that these neurons are driven by strongly activated glomeruli. Temporally, upon persistent odor exposure, TCs quickly adapted. In contrast, both MCs and GL-INs showed diverse temporal response patterns, suggesting that GL-INs could contribute to the transformations MCs undergo at slow time scales. Our data suggest that sensory odor maps are transformed by TCs and MCs in different ways forming two distinct and parallel information streams.
Defense Strategies for Asymmetric Networked Systems with Discrete Components
Rao, Nageswara S. V.; Ma, Chris Y. T.; Hausken, Kjell; He, Fei; Yau, David K. Y.
2018-01-01
We consider infrastructures consisting of a network of systems, each composed of discrete components. The network provides the vital connectivity between the systems and hence plays a critical, asymmetric role in the infrastructure operations. The individual components of the systems can be attacked by cyber and physical means and can be appropriately reinforced to withstand these attacks. We formulate the problem of ensuring the infrastructure performance as a game between an attacker and a provider, who choose the numbers of the components of the systems and network to attack and reinforce, respectively. The costs and benefits of attacks and reinforcements are characterized using the sum-form, product-form and composite utility functions, each composed of a survival probability term and a component cost term. We present a two-level characterization of the correlations within the infrastructure: (i) the aggregate failure correlation function specifies the infrastructure failure probability given the failure of an individual system or network, and (ii) the survival probabilities of the systems and network satisfy first-order differential conditions that capture the component-level correlations using multiplier functions. We derive Nash equilibrium conditions that provide expressions for individual system survival probabilities and also the expected infrastructure capacity specified by the total number of operational components. We apply these results to derive and analyze defense strategies for distributed cloud computing infrastructures using cyber-physical models. PMID:29751588
Multiple Scattering of Waves in Discrete Random Media.
1987-12-31
expanding the two body correlation functions in Legendre polynomials. This permits us to consider the angular correlations that exist for non-spherical...a scat- of the translation matrix after the angular and radial parts have terer fixed at it. been absorbed in the integration. Expressions for them...Approach New York: Pergamon Press. 1980 ’" close to the actual values for FeO, in isolation since they 171 A R. Edmonds. Angular Momentum in Quantum . h(pa
ERIC Educational Resources Information Center
O'Connell, Redmond G.; Bellgrove, Mark A.; Dockree, Paul M.; Lau, Adam; Hester, Robert; Garavan, Hugh; Fitzgerald, Michael; Foxe, John J.; Robertson, Ian H.
2009-01-01
The ability to detect and correct errors is critical to adaptive control of behaviour and represents a discrete neuropsychological function. A number of studies have highlighted that attention-deficit hyperactivity disorder (ADHD) is associated with abnormalities in behavioural and neural responsiveness to performance errors. One limitation of…
NASA Technical Reports Server (NTRS)
Whitfield, C. E.
1977-01-01
An open rotor was considered as a process for converting an unsteady velocity inflow into sound radiation. With the aid of crude assumptions, aero-acoustic transfer functions were defined theoretically for both discrete frequency and broad band noise. A study of the validity of these transfer functions yielded results which show good agreement at discrete frequencies though slightly less good for broad band noise. Agreement in both cases holds over three or more decades of the relevant parameters. A rotating hot wire anemometry system consisting of a single hot wire probe mounted in the nose cone of the rotor was used to quantify fluctuations in the airflow onto a single rotor blade for the transfer function results. Further theoretical analysis revealed that the sound field can be expressed in terms of blade-to-blade correlations in the airflow, and results from two probes rotating simultaneously were modelled mathematically and inserted in the theory. Preliminary results snow encouraging agreement with experimental data.
Montoya-Castillo, Andrés; Reichman, David R
2017-01-14
We derive a semi-analytical form for the Wigner transform for the canonical density operator of a discrete system coupled to a harmonic bath based on the path integral expansion of the Boltzmann factor. The introduction of this simple and controllable approach allows for the exact rendering of the canonical distribution and permits systematic convergence of static properties with respect to the number of path integral steps. In addition, the expressions derived here provide an exact and facile interface with quasi- and semi-classical dynamical methods, which enables the direct calculation of equilibrium time correlation functions within a wide array of approaches. We demonstrate that the present method represents a practical path for the calculation of thermodynamic data for the spin-boson and related systems. We illustrate the power of the present approach by detailing the improvement of the quality of Ehrenfest theory for the correlation function C zz (t)=Re⟨σ z (0)σ z (t)⟩ for the spin-boson model with systematic convergence to the exact sampling function. Importantly, the numerically exact nature of the scheme presented here and its compatibility with semiclassical methods allows for the systematic testing of commonly used approximations for the Wigner-transformed canonical density.
Recio-Spinoso, Alberto; Fan, Yun-Hui; Ruggero, Mario A
2011-05-01
Basilar-membrane responses to white Gaussian noise were recorded using laser velocimetry at basal sites of the chinchilla cochlea with characteristic frequencies near 10 kHz and first-order Wiener kernels were computed by cross correlation of the stimuli and the responses. The presence or absence of minimum-phase behavior was explored by fitting the kernels with discrete linear filters with rational transfer functions. Excellent fits to the kernels were obtained with filters with transfer functions including zeroes located outside the unit circle, implying nonminimum-phase behavior. These filters accurately predicted basilar-membrane responses to other noise stimuli presented at the same level as the stimulus for the kernel computation. Fits with all-pole and other minimum-phase discrete filters were inferior to fits with nonminimum-phase filters. Minimum-phase functions predicted from the amplitude functions of the Wiener kernels by Hilbert transforms were different from the measured phase curves. These results, which suggest that basilar-membrane responses do not have the minimum-phase property, challenge the validity of models of cochlear processing, which incorporate minimum-phase behavior. © 2011 IEEE
NASA Astrophysics Data System (ADS)
Hyman, J.; Aldrich, G. A.; Viswanathan, H. S.; Makedonska, N.; Karra, S.
2016-12-01
We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semi-correlation, and non-correlation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected so that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same.We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. These observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.
NASA Astrophysics Data System (ADS)
Nelson, D. J.
2007-09-01
In the basic correlation process a sequence of time-lag-indexed correlation coefficients are computed as the inner or dot product of segments of two signals. The time-lag(s) for which the magnitude of the correlation coefficient sequence is maximized is the estimated relative time delay of the two signals. For discrete sampled signals, the delay estimated in this manner is quantized with the same relative accuracy as the clock used in sampling the signals. In addition, the correlation coefficients are real if the input signals are real. There have been many methods proposed to estimate signal delay to more accuracy than the sample interval of the digitizer clock, with some success. These methods include interpolation of the correlation coefficients, estimation of the signal delay from the group delay function, and beam forming techniques, such as the MUSIC algorithm. For spectral estimation, techniques based on phase differentiation have been popular, but these techniques have apparently not been applied to the correlation problem . We propose a phase based delay estimation method (PBDEM) based on the phase of the correlation function that provides a significant improvement of the accuracy of time delay estimation. In the process, the standard correlation function is first calculated. A time lag error function is then calculated from the correlation phase and is used to interpolate the correlation function. The signal delay is shown to be accurately estimated as the zero crossing of the correlation phase near the index of the peak correlation magnitude. This process is nearly as fast as the conventional correlation function on which it is based. For real valued signals, a simple modification is provided, which results in the same correlation accuracy as is obtained for complex valued signals.
On defense strategies for system of systems using aggregated correlations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rao, Nageswara S.; Imam, Neena; Ma, Chris Y. T.
2017-04-01
We consider a System of Systems (SoS) wherein each system Si, i = 1; 2; ... ;N, is composed of discrete cyber and physical components which can be attacked and reinforced. We characterize the disruptions using aggregate failure correlation functions given by the conditional failure probability of SoS given the failure of an individual system. We formulate the problem of ensuring the survival of SoS as a game between an attacker and a provider, each with a utility function composed of asurvival probability term and a cost term, both expressed in terms of the number of components attacked and reinforced.more » The survival probabilities of systems satisfy simple product-form, first-order differential conditions, which simplify the Nash Equilibrium (NE) conditions. We derive the sensitivity functions that highlight the dependence of SoS survival probability at NE on cost terms, correlation functions, and individual system survival probabilities.We apply these results to a simplified model of distributed cloud computing infrastructure.« less
Discrete Roughness Transition for Hypersonic Flight Vehicles
NASA Technical Reports Server (NTRS)
Berry, Scott A.; Horvath, Thomas J.
2007-01-01
The importance of discrete roughness and the correlations developed to predict the onset of boundary layer transition on hypersonic flight vehicles are discussed. The paper is organized by hypersonic vehicle applications characterized in a general sense by the boundary layer: slender with hypersonic conditions at the edge of the boundary layer, moderately blunt with supersonic, and blunt with subsonic. This paper is intended to be a review of recent discrete roughness transition work completed at NASA Langley Research Center in support of agency flight test programs. First, a review is provided of discrete roughness wind tunnel data and the resulting correlations that were developed. Then, results obtained from flight vehicles, in particular the recently flown Hyper-X and Shuttle missions, are discussed and compared to the ground-based correlations.
Generalized Reduction Formula for Discrete Wigner Functions of Multiqubit Systems
NASA Astrophysics Data System (ADS)
Srinivasan, K.; Raghavan, G.
2018-03-01
Density matrices and Discrete Wigner Functions are equally valid representations of multiqubit quantum states. For density matrices, the partial trace operation is used to obtain the quantum state of subsystems, but an analogous prescription is not available for discrete Wigner Functions. Further, the discrete Wigner function corresponding to a density matrix is not unique but depends on the choice of the quantum net used for its reconstruction. In the present work, we derive a reduction formula for discrete Wigner functions of a general multiqubit state which works for arbitrary quantum nets. These results would be useful for the analysis and classification of entangled states and the study of decoherence purely in a discrete phase space setting and also in applications to quantum computing.
Location of acoustic emission sources generated by air flow
Kosel; Grabec; Muzic
2000-03-01
The location of continuous acoustic emission sources is a difficult problem of non-destructive testing. This article describes one-dimensional location of continuous acoustic emission sources by using an intelligent locator. The intelligent locator solves a location problem based on learning from examples. To verify whether continuous acoustic emission caused by leakage air flow can be located accurately by the intelligent locator, an experiment on a thin aluminum band was performed. Results show that it is possible to determine an accurate location by using a combination of a cross-correlation function with an appropriate bandpass filter. By using this combination, discrete and continuous acoustic emission sources can be located by using discrete acoustic emission sources for locator learning.
Weight-lattice discretization of Weyl-orbit functions
NASA Astrophysics Data System (ADS)
Hrivnák, Jiří; Walton, Mark A.
2016-08-01
Weyl-orbit functions have been defined for each simple Lie algebra, and permit Fourier-like analysis on the fundamental region of the corresponding affine Weyl group. They have also been discretized, using a refinement of the coweight lattice, so that digitized data on the fundamental region can be Fourier-analyzed. The discretized orbit function has arguments that are redundant if related by the affine Weyl group, while its labels, the Weyl-orbit representatives, invoke the dual affine Weyl group. Here we discretize the orbit functions in a novel way, by using the weight lattice. A cleaner theory results with symmetry between the arguments and labels of the discretized orbit functions. Orthogonality of the new discretized orbit functions is proved, and leads to the construction of unitary, symmetric matrices with Weyl-orbit-valued elements. For one type of orbit function, the matrix coincides with the Kac-Peterson modular S matrix, important for Wess-Zumino-Novikov-Witten conformal field theory.
Duan, Jin-Long; Zhang, Xue-Lei
2012-10-01
Taking Zhengzhou City, the capital of Henan Province in Central China, as the study area, and by using the theories and methodologies of diversity, a discreteness evaluation on the regional surface water, normalized difference vegetation index (NDVI), and land surface temperature (LST) distribution was conducted in a 2 km x 2 km grid scale. Both the NDVI and the LST were divided into 4 levels, their spatial distribution diversity indices were calculated, and their connections were explored. The results showed that it was of operability and practical significance to use the theories and methodologies of diversity in the discreteness evaluation of the spatial distribution of regional thermal environment. There was a higher overlap of location between the distributions of surface water and the lowest temperature region, and the high vegetation coverage was often accompanied by low land surface temperature. In 1988-2009, the discreteness of the surface water distribution in the City had an obvious decreasing trend. The discreteness of the surface water distribution had a close correlation with the discreteness of the temperature region distribution, while the discreteness of the NDVI classification distribution had a more complicated correlation with the discreteness of the temperature region distribution. Therefore, more environmental factors were needed to be included for a better evaluation.
Preserved re-experience of discrete emotions: Amnesia and executive function.
Stanciu, Marian Andrei; Rafal, Robert D; Turnbull, Oliver H
2018-02-07
Amnesic patients can re-experience emotions elicited by forgotten events, suggesting that brain systems for episodic and emotional memory are independent. However, the range of such emotional memories remains under-investigated (most studies employing just positive-negative emotion dyads), and executive function may also play a role in the re-experience of emotions. This is the first investigation of the intensity of the emotional re-experience of a range of discrete emotions (anger, fear, sadness, and happiness) for a group of amnesic patients. Twenty Korsakoff syndrome (KS) patients and 20 neurologically normal controls listened to four novel emotional vignettes selectively eliciting the four basic emotions. Emotional experience was measured using pen-and-paper Visual Analogue Mood Scales and episodic memory using verbal recollections. After 30 min, the recollection of stories was severely impaired for the patient group, but the emotional re-experience was no different from that of controls. Notably, there was no relationship between episodic recall and the intensity of the four emotions, such that even profoundly amnesic patients reported moderate levels of the target emotion. Exploratory analyses revealed negative correlations between the intensity of basic emotions and executive functions (e.g., cognitive flexibility and response inhibition) for controls but not patients. The results suggest that discrete emotions can be re-experienced independently of episodic memory, and that the re-experience of certain discrete emotions appears to be dampened by executive control. KS patients with absent or mild cognitive symptoms should benefit from emotion-regulation interventions aimed at reducing the recognized affective burden associated with their episodic memory deficit. © 2018 The British Psychological Society.
Evaluation of the Utility of a Discrete-Trial Functional Analysis in Early Intervention Classrooms
ERIC Educational Resources Information Center
Kodak, Tiffany; Fisher, Wayne W.; Paden, Amber; Dickes, Nitasha
2013-01-01
We evaluated a discrete-trial functional analysis implemented by regular classroom staff in a classroom setting. The results suggest that the discrete-trial functional analysis identified a social function for each participant and may require fewer staff than standard functional analysis procedures.
ERIC Educational Resources Information Center
Chezan, Laura C.; Drasgow, Erik; Martin, Christian A.
2014-01-01
We conducted a sequence of two studies on the use of discrete-trial functional analysis and functional communication training. First, we used discrete-trial functional analysis (DTFA) to identify the function of problem behavior in three adults with intellectual disabilities and problem behavior. Results indicated clear patterns of problem…
Algebraic perturbation theory for dense liquids with discrete potentials
NASA Astrophysics Data System (ADS)
Adib, Artur B.
2007-06-01
A simple theory for the leading-order correction g1(r) to the structure of a hard-sphere liquid with discrete (e.g., square-well) potential perturbations is proposed. The theory makes use of a general approximation that effectively eliminates four-particle correlations from g1(r) with good accuracy at high densities. For the particular case of discrete perturbations, the remaining three-particle correlations can be modeled with a simple volume-exclusion argument, resulting in an algebraic and surprisingly accurate expression for g1(r) . The structure of a discrete “core-softened” model for liquids with anomalous thermodynamic properties is reproduced as an application.
Lench, Heather C; Flores, Sarah A; Bench, Shane W
2011-09-01
Our purpose in the present meta-analysis was to examine the extent to which discrete emotions elicit changes in cognition, judgment, experience, behavior, and physiology; whether these changes are correlated as would be expected if emotions organize responses across these systems; and which factors moderate the magnitude of these effects. Studies (687; 4,946 effects, 49,473 participants) were included that elicited the discrete emotions of happiness, sadness, anger, and anxiety as independent variables with adults. Consistent with discrete emotion theory, there were (a) moderate differences among discrete emotions; (b) differences among discrete negative emotions; and (c) correlated changes in behavior, experience, and physiology (cognition and judgment were mostly not correlated with other changes). Valence, valence-arousal, and approach-avoidance models of emotion were not as clearly supported. There was evidence that these factors are likely important components of emotion but that they could not fully account for the pattern of results. Most emotion elicitations were effective, although the efficacy varied with the emotions being compared. Picture presentations were overall the most effective elicitor of discrete emotions. Stronger effects of emotion elicitations were associated with happiness versus negative emotions, self-reported experience, a greater proportion of women (for elicitations of happiness and sadness), omission of a cover story, and participants alone versus in groups. Conclusions are limited by the inclusion of only some discrete emotions, exclusion of studies that did not elicit discrete emotions, few available effect sizes for some contrasts and moderators, and the methodological rigor of included studies. (PsycINFO Database Record (c) 2011 APA, all rights reserved).
Weight-lattice discretization of Weyl-orbit functions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hrivnák, Jiří, E-mail: jiri.hrivnak@fjfi.cvut.cz, E-mail: walton@uleth.ca; Walton, Mark A., E-mail: jiri.hrivnak@fjfi.cvut.cz, E-mail: walton@uleth.ca
Weyl-orbit functions have been defined for each simple Lie algebra, and permit Fourier-like analysis on the fundamental region of the corresponding affine Weyl group. They have also been discretized, using a refinement of the coweight lattice, so that digitized data on the fundamental region can be Fourier-analyzed. The discretized orbit function has arguments that are redundant if related by the affine Weyl group, while its labels, the Weyl-orbit representatives, invoke the dual affine Weyl group. Here we discretize the orbit functions in a novel way, by using the weight lattice. A cleaner theory results with symmetry between the arguments andmore » labels of the discretized orbit functions. Orthogonality of the new discretized orbit functions is proved, and leads to the construction of unitary, symmetric matrices with Weyl-orbit-valued elements. For one type of orbit function, the matrix coincides with the Kac-Peterson modular S matrix, important for Wess-Zumino-Novikov-Witten conformal field theory.« less
Spectral analysis of pair-correlation bandwidth: application to cell biology images.
Binder, Benjamin J; Simpson, Matthew J
2015-02-01
Images from cell biology experiments often indicate the presence of cell clustering, which can provide insight into the mechanisms driving the collective cell behaviour. Pair-correlation functions provide quantitative information about the presence, or absence, of clustering in a spatial distribution of cells. This is because the pair-correlation function describes the ratio of the abundance of pairs of cells, separated by a particular distance, relative to a randomly distributed reference population. Pair-correlation functions are often presented as a kernel density estimate where the frequency of pairs of objects are grouped using a particular bandwidth (or bin width), Δ>0. The choice of bandwidth has a dramatic impact: choosing Δ too large produces a pair-correlation function that contains insufficient information, whereas choosing Δ too small produces a pair-correlation signal dominated by fluctuations. Presently, there is little guidance available regarding how to make an objective choice of Δ. We present a new technique to choose Δ by analysing the power spectrum of the discrete Fourier transform of the pair-correlation function. Using synthetic simulation data, we confirm that our approach allows us to objectively choose Δ such that the appropriately binned pair-correlation function captures known features in uniform and clustered synthetic images. We also apply our technique to images from two different cell biology assays. The first assay corresponds to an approximately uniform distribution of cells, while the second assay involves a time series of images of a cell population which forms aggregates over time. The appropriately binned pair-correlation function allows us to make quantitative inferences about the average aggregate size, as well as quantifying how the average aggregate size changes with time.
Macular pigment spatial distribution effects on glare disability.
Putnam, Christopher M; Bassi, Carl J
2015-01-01
This project explored the relationship of the macular pigment optical density (MPOD) spatial profile with measures of glare disability (GD) across the macula. A novel device was used to measure MPOD across the central 16° of retina along four radii using customized heterochromatic flicker photometry (cHFP)at eccentricities of 0°, 2°, 4°, 6° and 8°. MPOD was measured as discrete and integrated values at all measured retinal loci. GD was calculated as a difference in contrast sensitivity (CS) between no glare and glare conditions using identical stimuli presented at the same eccentricities. GD was defined as [(CSNo Glare-CSGlare)/CSNo Glare] in order to isolate the glare attenuation effects of MPOD by controlling for CS variability among the subject sample. Correlations of the discrete and integrated MPOD with GD were compared. The cHFP identified reliable MPOD spatial distribution maps demonstrating a 1st-order exponential decay as a function of increasing eccentricity. There was a significant negative correlation between both measures of foveal MPOD and GD using 6 cycles per degree (cpd) and 9 cpd stimuli. Significant correlations were found between corresponding parafoveal MPOD measures and GD at 2 and 4° of eccentricity using 9 cpd stimuli with greater MPOD associated with less glare disability. These results are consistent with the glare attenuation effects of MP at higher spatial frequencies and support the hypothesis that discrete and integrated measures of MPOD have similar correlations with glare attenuation effects across the macula. Additionally, peak foveal MPOD appears to influence GD across the macula. Copyright © 2014 Spanish General Council of Optometry. Published by Elsevier Espana. All rights reserved.
Evaluation of the utility of a discrete-trial functional analysis in early intervention classrooms.
Kodak, Tiffany; Fisher, Wayne W; Paden, Amber; Dickes, Nitasha
2013-01-01
We evaluated a discrete-trial functional analysis implemented by regular classroom staff in a classroom setting. The results suggest that the discrete-trial functional analysis identified a social function for each participant and may require fewer staff than standard functional analysis procedures. © Society for the Experimental Analysis of Behavior.
Nimphius, Sophia; McGuigan, Michael R; Suchomel, Timothy J; Newton, Robert U
2016-06-01
This study assessed reliability of discrete ground reaction force (GRF) variables over multiple pitching trials, investigated the relationships between discrete GRF variables and pitch velocity (PV) and assessed the variability of the "force signature" or continuous force-time curve during the pitching motion of windmill softball pitchers. Intraclass correlation coefficient (ICC) for all discrete variables was high (0.86-0.99) while the coefficient of variance (CV) was low (1.4-5.2%). Two discrete variables were significantly correlated to PV; second vertical peak force (r(5)=0.81, p=0.03) and time between peak forces (r(5)=-0.79; p=0.03). High ICCs and low CVs support the reliability of discrete GRF and PV variables over multiple trials and significant correlations indicate there is a relationship between the ability to produce force and the timing of this force production with PV. The mean of all pitchers' curve-average standard deviation of their continuous force-time curves demonstrated low variability (CV=4.4%) indicating a repeatable and identifiable "force signature" pattern during this motion. As such, the continuous force-time curve in addition to discrete GRF variables should be examined in future research as a potential method to monitor or explain changes in pitching performance. Copyright © 2016 Elsevier B.V. All rights reserved.
Dimers in Piecewise Temperleyan Domains
NASA Astrophysics Data System (ADS)
Russkikh, Marianna
2018-03-01
We study the large-scale behavior of the height function in the dimer model on the square lattice. Richard Kenyon has shown that the fluctuations of the height function on Temperleyan discretizations of a planar domain converge in the scaling limit (as the mesh size tends to zero) to the Gaussian Free Field with Dirichlet boundary conditions. We extend Kenyon's result to a more general class of discretizations. Moreover, we introduce a new factorization of the coupling function of the double-dimer model into two discrete holomorphic functions, which are similar to discrete fermions defined in Smirnov (Proceedings of the international congress of mathematicians (ICM), Madrid, Spain, 2006; Ann Math (2) 172:1435-1467, 2010). For Temperleyan discretizations with appropriate boundary modifications, the results of Kenyon imply that the expectation of the double-dimer height function converges to a harmonic function in the scaling limit. We use the above factorization to extend this result to the class of all polygonal discretizations, that are not necessarily Temperleyan. Furthermore, we show that, quite surprisingly, the expectation of the double-dimer height function in the Temperleyan case is exactly discrete harmonic (for an appropriate choice of Laplacian) even before taking the scaling limit.
Gallienne, Jacqueline; Gregg, Caroline; LeBlanc, Evan; Yaakob, Norazlin; Wu, Di; Davies, Kate; Rawlings, Norman; Pierson, Roger; Deardon, Rob; Bartlewski, Pawel
2012-05-01
Associations between physical characteristics and functionality of corpora lutea (CL) have previously been reported in monovulatory species, albeit several studies in cattle and humans have refuted the existence of temporal relationships between CL size, echotexture and serum progesterone (P(4)) concentrations. The main objective of the present study was to examine whether or not there were correlations between ultrasonographic image attributes of CL and systemic concentrations of P(4) during the discrete stages of the luteal phase in two breeds of sheep differing in ovulation rates (non-prolific Western White Face [WWF] ewes and prolific Finn [F] sheep). Transrectal ovarian ultrasonography utilized a 7.5-MHz linear-array transducer connected to a portable scanner (Aloka SSD-500) and the images were analyzed using commercially available image analytical software (Image ProPlus(®)) validated for the present application in sheep. The correlations were assessed using the Pearson's Product Moment (PPM) analysis and also, to increase the accuracy of statistical tests, the analysis of covariance (ANCOVA), with the number of CL as a co-factor. In WWF ewes, serum concentrations of P(4) correlated significantly with the total luteal area (TLA) during the CL growth phase (days 3-6; day 0 = ovulation) and functional luteolysis (days 12-15), and with numerical pixel values (NPVs--pixel intensity) during luteolysis; the results obtained by using two different statistical methods were generally similar. In prolific F ewes, serum P(4) concentrations were directly correlated with TLA during CL growth (days 3-6; ANCOVA), functional luteolysis (days 13-14; PPM), and structural CL regression (days 11-14; PPM and ANCOVA), and with NPVs during functional luteolysis (PPM and ANCOVA). We concluded that systemic P(4) concentrations could only be accurately predicted from the changes in luteal area during CL growth and regression, and from NPVs during luteolysis, in both prolific and non-prolific ewes, but the changes in size and echotexture of the luteal glands at mid-cycle were not indicative of serum P(4) concentrations in sheep.
Defense strategies for asymmetric networked systems under composite utilities
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rao, Nageswara S.; Ma, Chris Y. T.; Hausken, Kjell
We consider an infrastructure of networked systems with discrete components that can be reinforced at certain costs to guard against attacks. The communications network plays a critical, asymmetric role of providing the vital connectivity between the systems. We characterize the correlations within this infrastructure at two levels using (a) aggregate failure correlation function that specifies the infrastructure failure probability giventhe failure of an individual system or network, and (b) first order differential conditions on system survival probabilities that characterize component-level correlations. We formulate an infrastructure survival game between an attacker and a provider, who attacks and reinforces individual components, respectively.more » They use the composite utility functions composed of a survival probability term and a cost term, and the previously studiedsum-form and product-form utility functions are their special cases. At Nash Equilibrium, we derive expressions for individual system survival probabilities and the expected total number of operational components. We apply and discuss these estimates for a simplified model of distributed cloud computing infrastructure« less
NASA Astrophysics Data System (ADS)
Hyman, J. D.; Aldrich, G.; Viswanathan, H.; Makedonska, N.; Karra, S.
2016-08-01
We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semicorrelation, and noncorrelation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected so that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same. We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. These observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.
Spectral functions of strongly correlated extended systems via an exact quantum embedding
NASA Astrophysics Data System (ADS)
Booth, George H.; Chan, Garnet Kin-Lic
2015-04-01
Density matrix embedding theory (DMET) [Phys. Rev. Lett. 109, 186404 (2012), 10.1103/PhysRevLett.109.186404], introduced an approach to quantum cluster embedding methods whereby the mapping of strongly correlated bulk problems to an impurity with finite set of bath states was rigorously formulated to exactly reproduce the entanglement of the ground state. The formalism provided similar physics to dynamical mean-field theory at a tiny fraction of the cost but was inherently limited by the construction of a bath designed to reproduce ground-state, static properties. Here, we generalize the concept of quantum embedding to dynamic properties and demonstrate accurate bulk spectral functions at similarly small computational cost. The proposed spectral DMET utilizes the Schmidt decomposition of a response vector, mapping the bulk dynamic correlation functions to that of a quantum impurity cluster coupled to a set of frequency-dependent bath states. The resultant spectral functions are obtained on the real-frequency axis, without bath discretization error, and allows for the construction of arbitrary dynamic correlation functions. We demonstrate the method on the one- (1D) and two-dimensional (2D) Hubbard model, where we obtain zero temperature and thermodynamic limit spectral functions, and show the trivial extension to two-particle Green's functions. This advance therefore extends the scope and applicability of DMET in condensed-matter problems as a computationally tractable route to correlated spectral functions of extended systems and provides a competitive alternative to dynamical mean-field theory for dynamic quantities.
Spectral phase measurement of a Fano resonance using tunable attosecond pulses
Kotur, M.; Guénot, D.; Jiménez-Galán, Á; Kroon, D.; Larsen, E. W.; Louisy, M.; Bengtsson, S.; Miranda, M.; Mauritsson, J.; Arnold, C. L.; Canton, S. E.; Gisselbrecht, M.; Carette, T.; Dahlström, J. M.; Lindroth, E.; Maquet, A.; Argenti, L.; Martín, F.; L'Huillier, A.
2016-01-01
Electron dynamics induced by resonant absorption of light is of fundamental importance in nature and has been the subject of countless studies in many scientific areas. Above the ionization threshold of atomic or molecular systems, the presence of discrete states leads to autoionization, which is an interference between two quantum paths: direct ionization and excitation of the discrete state coupled to the continuum. Traditionally studied with synchrotron radiation, the probability for autoionization exhibits a universal Fano intensity profile as a function of excitation energy. However, without additional phase information, the full temporal dynamics cannot be recovered. Here we use tunable attosecond pulses combined with weak infrared radiation in an interferometric setup to measure not only the intensity but also the phase variation of the photoionization amplitude across an autoionization resonance in argon. The phase variation can be used as a fingerprint of the interactions between the discrete state and the ionization continua, indicating a new route towards monitoring electron correlations in time. PMID:26887682
Del Prete, Valeria; Treves, Alessandro
2002-04-01
In a previous paper we have evaluated analytically the mutual information between the firing rates of N independent units and a set of multidimensional continuous and discrete stimuli, for a finite population size and in the limit of large noise. Here, we extend the analysis to the case of two interconnected populations, where input units activate output ones via Gaussian weights and a threshold linear transfer function. We evaluate the information carried by a population of M output units, again about continuous and discrete correlates. The mutual information is evaluated solving saddle-point equations under the assumption of replica symmetry, a method that, by taking into account only the term linear in N of the input information, is equivalent to assuming the noise to be large. Within this limitation, we analyze the dependence of the information on the ratio M/N, on the selectivity of the input units and on the level of the output noise. We show analytically, and confirm numerically, that in the limit of a linear transfer function and of a small ratio between output and input noise, the output information approaches asymptotically the information carried in input. Finally, we show that the information loss in output does not depend much on the structure of the stimulus, whether purely continuous, purely discrete or mixed, but only on the position of the threshold nonlinearity, and on the ratio between input and output noise.
Pair and triple correlations in the A+B-->B diffusion-controlled reaction
NASA Astrophysics Data System (ADS)
Kuzovkov, Vladimir; Kotomin, Eugene
1994-03-01
An exact solution for the one-dimensional kinetics of the diffusion-controlled reaction A+B-->B is obtained by means of the three-particle correlation functions. Because of a lattice discreteness each site could be occupied by a single particle only which leads to the so-called ``bus effect'': Recombination of any particle A is defined by a spatial configuration of two nearest particles B only surrounding A from its left and right. This results in the unusual algebraic decay law, n(t)~t-1, which asymptotically (as t-->∞) does not depend on the trap B concentration.
Comparative analysis of two discretizations of Ricci curvature for complex networks.
Samal, Areejit; Sreejith, R P; Gu, Jiao; Liu, Shiping; Saucan, Emil; Jost, Jürgen
2018-06-05
We have performed an empirical comparison of two distinct notions of discrete Ricci curvature for graphs or networks, namely, the Forman-Ricci curvature and Ollivier-Ricci curvature. Importantly, these two discretizations of the Ricci curvature were developed based on different properties of the classical smooth notion, and thus, the two notions shed light on different aspects of network structure and behavior. Nevertheless, our extensive computational analysis in a wide range of both model and real-world networks shows that the two discretizations of Ricci curvature are highly correlated in many networks. Moreover, we show that if one considers the augmented Forman-Ricci curvature which also accounts for the two-dimensional simplicial complexes arising in graphs, the observed correlation between the two discretizations is even higher, especially, in real networks. Besides the potential theoretical implications of these observations, the close relationship between the two discretizations has practical implications whereby Forman-Ricci curvature can be employed in place of Ollivier-Ricci curvature for faster computation in larger real-world networks whenever coarse analysis suffices.
NASA Astrophysics Data System (ADS)
Zierenberg, Johannes; Fricke, Niklas; Marenz, Martin; Spitzner, F. P.; Blavatska, Viktoria; Janke, Wolfhard
2017-12-01
We study long-range power-law correlated disorder on square and cubic lattices. In particular, we present high-precision results for the percolation thresholds and the fractal dimension of the largest clusters as a function of the correlation strength. The correlations are generated using a discrete version of the Fourier filtering method. We consider two different metrics to set the length scales over which the correlations decay, showing that the percolation thresholds are highly sensitive to such system details. By contrast, we verify that the fractal dimension df is a universal quantity and unaffected by the choice of metric. We also show that for weak correlations, its value coincides with that for the uncorrelated system. In two dimensions we observe a clear increase of the fractal dimension with increasing correlation strength, approaching df→2 . The onset of this change does not seem to be determined by the extended Harris criterion.
Long-range correlations in time series generated by time-fractional diffusion: A numerical study
NASA Astrophysics Data System (ADS)
Barbieri, Davide; Vivoli, Alessandro
2005-09-01
Time series models showing power law tails in autocorrelation functions are common in econometrics. A special non-Markovian model for such kind of time series is provided by the random walk introduced by Gorenflo et al. as a discretization of time fractional diffusion. The time series so obtained are analyzed here from a numerical point of view in terms of autocorrelations and covariance matrices.
On E-discretization of tori of compact simple Lie groups. II
NASA Astrophysics Data System (ADS)
Hrivnák, Jiří; Juránek, Michal
2017-10-01
Ten types of discrete Fourier transforms of Weyl orbit functions are developed. Generalizing one-dimensional cosine, sine, and exponential, each type of the Weyl orbit function represents an exponential symmetrized with respect to a subgroup of the Weyl group. Fundamental domains of even affine and dual even affine Weyl groups, governing the argument and label symmetries of the even orbit functions, are determined. The discrete orthogonality relations are formulated on finite sets of points from the refinements of the dual weight lattices. Explicit counting formulas for the number of points of the discrete transforms are deduced. Real-valued Hartley orbit functions are introduced, and all ten types of the corresponding discrete Hartley transforms are detailed.
NASA Astrophysics Data System (ADS)
Žukovič, Milan; Hristopulos, Dionissios T.
2009-02-01
A current problem of practical significance is how to analyze large, spatially distributed, environmental data sets. The problem is more challenging for variables that follow non-Gaussian distributions. We show by means of numerical simulations that the spatial correlations between variables can be captured by interactions between 'spins'. The spins represent multilevel discretizations of environmental variables with respect to a number of pre-defined thresholds. The spatial dependence between the 'spins' is imposed by means of short-range interactions. We present two approaches, inspired by the Ising and Potts models, that generate conditional simulations of spatially distributed variables from samples with missing data. Currently, the sampling and simulation points are assumed to be at the nodes of a regular grid. The conditional simulations of the 'spin system' are forced to respect locally the sample values and the system statistics globally. The second constraint is enforced by minimizing a cost function representing the deviation between normalized correlation energies of the simulated and the sample distributions. In the approach based on the Nc-state Potts model, each point is assigned to one of Nc classes. The interactions involve all the points simultaneously. In the Ising model approach, a sequential simulation scheme is used: the discretization at each simulation level is binomial (i.e., ± 1). Information propagates from lower to higher levels as the simulation proceeds. We compare the two approaches in terms of their ability to reproduce the target statistics (e.g., the histogram and the variogram of the sample distribution), to predict data at unsampled locations, as well as in terms of their computational complexity. The comparison is based on a non-Gaussian data set (derived from a digital elevation model of the Walker Lake area, Nevada, USA). We discuss the impact of relevant simulation parameters, such as the domain size, the number of discretization levels, and the initial conditions.
Multivariate localization methods for ensemble Kalman filtering
NASA Astrophysics Data System (ADS)
Roh, S.; Jun, M.; Szunyogh, I.; Genton, M. G.
2015-05-01
In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (entry-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.
Adaptive Microwave Staring Correlated Imaging for Targets Appearing in Discrete Clusters.
Tian, Chao; Jiang, Zheng; Chen, Weidong; Wang, Dongjin
2017-10-21
Microwave staring correlated imaging (MSCI) can achieve ultra-high resolution in real aperture staring radar imaging using the correlated imaging process (CIP) under all-weather and all-day circumstances. The CIP must combine the received echo signal with the temporal-spatial stochastic radiation field. However, a precondition of the CIP is that the continuous imaging region must be discretized to a fine grid, and the measurement matrix should be accurately computed, which makes the imaging process highly complex when the MSCI system observes a wide area. This paper proposes an adaptive imaging approach for the targets in discrete clusters to reduce the complexity of the CIP. The approach is divided into two main stages. First, as discrete clustered targets are distributed in different range strips in the imaging region, the transmitters of the MSCI emit narrow-pulse waveforms to separate the echoes of the targets in different strips in the time domain; using spectral entropy, a modified method robust against noise is put forward to detect the echoes of the discrete clustered targets, based on which the strips with targets can be adaptively located. Second, in a strip with targets, the matched filter reconstruction algorithm is used to locate the regions with targets, and only the regions of interest are discretized to a fine grid; sparse recovery is used, and the band exclusion is used to maintain the non-correlation of the dictionary. Simulation results are presented to demonstrate that the proposed approach can accurately and adaptively locate the regions with targets and obtain high-quality reconstructed images.
Sliding Mode Control for Discrete-Time Systems With Markovian Packet Dropouts.
Song, Heran; Chen, Shih-Chi; Yam, Yeung
2017-11-01
This paper presents the design of a sliding mode controller for networked control systems subject to successive Markovian packet dropouts. This paper adopts the Gilbert-Elliott channel model to describe the temporal correlation among packet losses, and proposes an update scheme to select the assumed available states for use in a sliding mode control law. A technique used in the theory of discrete-time Markov jump linear systems is applied to tackle the effect of the packet losses. This involves introducing a couple of Lyapunov functions dependent on the indicator functions of the instantaneous packet loss, and proving that the sliding mode controller is able to drive the system state trajectories into the neighborhood of the designed integral sliding surface in mean-square sense given that the corresponding Lyapunov inequalities are satisfied. The system is guaranteed thereafter to remain inside the neighborhood of the sliding surface. Simulated case studies are presented to illustrate the effectiveness of the control law.
Design considerations for a real-time ocular counterroll instrument
NASA Technical Reports Server (NTRS)
Hatamian, M.; Anderson, D. J.
1983-01-01
A real-time algorithm for measuring three-dimensional movement of the human eye, especially torsional movement, is presented. As its input, the system uses images of the eyeball taken at video rate. The amount of horizontal and vertical movement is extracted using a pupil tracking technique. The torsional movement is then measured by computing the discrete cross-correlation function between the circular samples of successive images of the iris patterns and searching for the position of the peak of the function. A local least square interpolation around the peak of the cross-correlation function is used to produce nearly unbiased estimates of torsion angle with accuracy of about 3-4 arcmin. Accuracies of better than 0.03 deg are achievable in torsional measurement with SNR higher than 36 dB. Horizontal and vertical rotations of up to + or - 13 deg can occur simultaneously with torsion without introducing any appreciable error in the counterrolling measurement process.
Characterizing decision-making and reward processing in bipolar disorder: A cluster analysis.
Jiménez, E; Solé, B; Arias, B; Mitjans, M; Varo, C; Reinares, M; Bonnín, C M; Salagre, E; Ruíz, V; Torres, I; Tomioka, Y; Sáiz, P A; García-Portilla, M P; Burón, P; Bobes, J; Martínez-Arán, A; Torrent, C; Vieta, E; Benabarre, A
2018-05-25
The presence of abnormalities in emotional decision-making and reward processing among bipolar patients (BP) has been well rehearsed. These disturbances are not limited to acute phases and are common even during remission. In recent years, the existence of discrete cognitive profiles in this psychiatric population has been replicated. However, emotional decision making and reward processing domains have barely been studied. Therefore, our aim was to explore the existence of different profiles on the aforementioned cognitive dimensions in BP. The sample consisted of 126 euthymic BP. Main sociodemographic, clinical, functioning, and neurocognitive variables were gathered. A hierarchical-clustering technique was used to identify discrete neurocognitive profiles based on the performance in the Iowa Gambling Task. Afterward, the resulting clusters were compared using ANOVA or Chi-squared Test, as appropriate. Evidence for the existence of three different profiles was provided. Cluster 1 was mainly characterized by poor decision ability. Cluster 2 presented the lowest sensitivity to punishment. Finally, cluster 3 presented the best decision-making ability and the highest levels of punishment sensitivity. Comparison between the three clusters indicated that cluster 2 was the most functionally impaired group. The poorest outcomes in attention, executive function domains, and social cognition were also observed within the same group. In conclusion, similarly to that observed in "cold cognitive" domains, our results suggest the existence of three discrete cognitive profiles concerning emotional decision making and reward processing. Amongst all the indexes explored, low punishment sensitivity emerge as a potential correlate of poorer cognitive and functional outcomes in bipolar disorder. Copyright © 2018 Elsevier B.V. and ECNP. All rights reserved.
Remarks on a New Possible Discretization Scheme for Gauge Theories
NASA Astrophysics Data System (ADS)
Magnot, Jean-Pierre
2018-03-01
We propose here a new discretization method for a class of continuum gauge theories which action functionals are polynomials of the curvature. Based on the notion of holonomy, this discretization procedure appears gauge-invariant for discretized analogs of Yang-Mills theories, and hence gauge-fixing is fully rigorous for these discretized action functionals. Heuristic parts are forwarded to the quantization procedure via Feynman integrals and the meaning of the heuristic infinite dimensional Lebesgue integral is questioned.
Remarks on a New Possible Discretization Scheme for Gauge Theories
NASA Astrophysics Data System (ADS)
Magnot, Jean-Pierre
2018-07-01
We propose here a new discretization method for a class of continuum gauge theories which action functionals are polynomials of the curvature. Based on the notion of holonomy, this discretization procedure appears gauge-invariant for discretized analogs of Yang-Mills theories, and hence gauge-fixing is fully rigorous for these discretized action functionals. Heuristic parts are forwarded to the quantization procedure via Feynman integrals and the meaning of the heuristic infinite dimensional Lebesgue integral is questioned.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bergin, C.J.; Bell, D.Y.; Coblentz, C.L.
1989-06-01
The appearances of the lungs on radiographs and computed tomographic (CT) scans were correlated with degree of uptake on gallium scans and results of pulmonary function tests (PFTs) in 27 patients with sarcoidosis. CT scans were evaluated both qualitatively and quantitatively. Patients were divided into five categories on the basis of the pattern of abnormality at CT: 1 = normal (n = 4); 2 = segmental air-space disease (n = 4); 3 = spherical (alveolar) masslike opacities (n = 4); 4 = multiple, discrete, small nodules (n = 6); and 5 = distortion of parenchymal structures (fibrotic end-stage sarcoidosis) (nmore » = 9). The percentage of the volume judged to be abnormal (CT grade) was correlated with PFT results for each CT and radiographic category. CT grades were also correlated with gallium scanning results and percentage of lymphocytes recovered from bronchoalveolar lavage (BAL). Patients in CT categories 1 and 2 had normal lung function, those in category 3 had mild functional impairment, and those in categories 4 and 5 showed moderate to severe dysfunction. The overall CT grade correlated well with PFT results expressed as a percentage of the predicted value. In five patients, CT scans showed extensive parenchymal disease not seen on radiographs. CT grades did not correlate with the results of gallium scanning or BAL lymphocytes. The authors conclude that patterns of parenchymal sarcoidosis seen at CT correlate with the PFT results and can be used to indicate respiratory impairment.« less
Estimating and Identifying Unspecified Correlation Structure for Longitudinal Data
Hu, Jianhua; Wang, Peng; Qu, Annie
2014-01-01
Identifying correlation structure is important to achieving estimation efficiency in analyzing longitudinal data, and is also crucial for drawing valid statistical inference for large size clustered data. In this paper, we propose a nonparametric method to estimate the correlation structure, which is applicable for discrete longitudinal data. We utilize eigenvector-based basis matrices to approximate the inverse of the empirical correlation matrix and determine the number of basis matrices via model selection. A penalized objective function based on the difference between the empirical and model approximation of the correlation matrices is adopted to select an informative structure for the correlation matrix. The eigenvector representation of the correlation estimation is capable of reducing the risk of model misspecification, and also provides useful information on the specific within-cluster correlation pattern of the data. We show that the proposed method possesses the oracle property and selects the true correlation structure consistently. The proposed method is illustrated through simulations and two data examples on air pollution and sonar signal studies. PMID:26361433
ERIC Educational Resources Information Center
Raykov, Tenko; Marcoulides, George A.
2015-01-01
A latent variable modeling procedure that can be used to evaluate intraclass correlation coefficients in two-level settings with discrete response variables is discussed. The approach is readily applied when the purpose is to furnish confidence intervals at prespecified confidence levels for these coefficients in setups with binary or ordinal…
Discrete cosine and sine transforms generalized to honeycomb lattice
NASA Astrophysics Data System (ADS)
Hrivnák, Jiří; Motlochová, Lenka
2018-06-01
The discrete cosine and sine transforms are generalized to a triangular fragment of the honeycomb lattice. The honeycomb point sets are constructed by subtracting the root lattice from the weight lattice points of the crystallographic root system A2. The two-variable orbit functions of the Weyl group of A2, discretized simultaneously on the weight and root lattices, induce a novel parametric family of extended Weyl orbit functions. The periodicity and von Neumann and Dirichlet boundary properties of the extended Weyl orbit functions are detailed. Three types of discrete complex Fourier-Weyl transforms and real-valued Hartley-Weyl transforms are described. Unitary transform matrices and interpolating behavior of the discrete transforms are exemplified. Consequences of the developed discrete transforms for transversal eigenvibrations of the mechanical graphene model are discussed.
Initial Data of Digital Correlation ECE with a Giga Hertz Sampling Digitizer
NASA Astrophysics Data System (ADS)
Tsuchiya, Hayato; Inagaki, Shigeru; Tokuzawa, Tokihiko; Nagayama, Yoshio
2015-03-01
The proposed Digital Correlation ECE (DCECE) technique is applied in Large Helical Device. DCECE is realized by the use of the Giga Hertz Sampling Digitizer. The waveform of intermediate frequency band of ECE, whose frequency is several giga hertz, can be discretized and saved directly. The discretized IF data can be used for the analysis of correlation ECE with arbitrary parameter of spatial resolution and temporal resolution. In this paper, the characteristic of DCECE and initial Data in LHD is introduced.
Hyman, Jeffrey De'Haven; Aldrich, Garrett Allen; Viswanathan, Hari S.; ...
2016-08-01
We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semicorrelation, and noncorrelation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected somore » that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same. We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. Lastly, these observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hyman, Jeffrey De'Haven; Aldrich, Garrett Allen; Viswanathan, Hari S.
We characterize how different fracture size-transmissivity relationships influence flow and transport simulations through sparse three-dimensional discrete fracture networks. Although it is generally accepted that there is a positive correlation between a fracture's size and its transmissivity/aperture, the functional form of that relationship remains a matter of debate. Relationships that assume perfect correlation, semicorrelation, and noncorrelation between the two have been proposed. To study the impact that adopting one of these relationships has on transport properties, we generate multiple sparse fracture networks composed of circular fractures whose radii follow a truncated power law distribution. The distribution of transmissivities are selected somore » that the mean transmissivity of the fracture networks are the same and the distributions of aperture and transmissivity in models that include a stochastic term are also the same. We observe that adopting a correlation between a fracture size and its transmissivity leads to earlier breakthrough times and higher effective permeability when compared to networks where no correlation is used. While fracture network geometry plays the principal role in determining where transport occurs within the network, the relationship between size and transmissivity controls the flow speed. Lastly, these observations indicate DFN modelers should be aware that breakthrough times and effective permeabilities can be strongly influenced by such a relationship in addition to fracture and network statistics.« less
Efficient genetic algorithms using discretization scheduling.
McLay, Laura A; Goldberg, David E
2005-01-01
In many applications of genetic algorithms, there is a tradeoff between speed and accuracy in fitness evaluations when evaluations use numerical methods with varying discretization. In these types of applications, the cost and accuracy vary from discretization errors when implicit or explicit quadrature is used to estimate the function evaluations. This paper examines discretization scheduling, or how to vary the discretization within the genetic algorithm in order to use the least amount of computation time for a solution of a desired quality. The effectiveness of discretization scheduling can be determined by comparing its computation time to the computation time of a GA using a constant discretization. There are three ingredients for the discretization scheduling: population sizing, estimated time for each function evaluation and predicted convergence time analysis. Idealized one- and two-dimensional experiments and an inverse groundwater application illustrate the computational savings to be achieved from using discretization scheduling.
Robinson, A. M.; Fishman, A. J.; Bendok, B. R.; Richter, C.-P.
2015-01-01
This study compared functional and physical collateral damage to a nerve when operating a Codman MALIS Bipolar Electrosurgical System CMC-III or a CO2 laser coupled to a laser, with correlation to an in vitro model of heating profiles created by the devices in thermochromic ink agarose. Functional damage of the rat sciatic nerve after operating the MALIS or CO2 laser at various power settings and proximities to the nerve was measured by electrically evoked nerve action potentials, and histology of the nerve was used to assess physical damage. Thermochromic ink dissolved in agarose was used to model the spatial and temporal profile of the collateral heating zone of the electrosurgical system and the laser ablation cone. We found that this laser can be operated at 2 W directly above the nerve with minimal damage, while power settings of 5 W and 10 W resulted in acute functional and physical nerve damage, correlating with the maximal heating cone in the thermochromic ink model. MALIS settings up to 40 (11 W) did not result in major functional or physical nerve damage until the nerve was between the forceps tips, correlating with the hottest zone, localized discretely between the tips. PMID:25699266
106-17 Telemetry Standards Recorder and Reproducer Command and Control Chapter 6
2017-07-01
6-35 6.3 MIL-STD-1553 Remote Terminal Command and Control ..................................... 6-36 6.4 Discrete Command and...6-6 Figure 6-9. Required Discrete Control Functions...6-36 Figure 6-10. Discrete Control and Indicator Functional Diagram .......................................... 6-37 Telemetry Standards
Integrable Floquet dynamics, generalized exclusion processes and "fused" matrix ansatz
NASA Astrophysics Data System (ADS)
Vanicat, Matthieu
2018-04-01
We present a general method for constructing integrable stochastic processes, with two-step discrete time Floquet dynamics, from the transfer matrix formalism. The models can be interpreted as a discrete time parallel update. The method can be applied for both periodic and open boundary conditions. We also show how the stationary distribution can be built as a matrix product state. As an illustration we construct parallel discrete time dynamics associated with the R-matrix of the SSEP and of the ASEP, and provide the associated stationary distributions in a matrix product form. We use this general framework to introduce new integrable generalized exclusion processes, where a fixed number of particles is allowed on each lattice site in opposition to the (single particle) exclusion process models. They are constructed using the fusion procedure of R-matrices (and K-matrices for open boundary conditions) for the SSEP and ASEP. We develop a new method, that we named "fused" matrix ansatz, to build explicitly the stationary distribution in a matrix product form. We use this algebraic structure to compute physical observables such as the correlation functions and the mean particle current.
Multivariate localization methods for ensemble Kalman filtering
NASA Astrophysics Data System (ADS)
Roh, S.; Jun, M.; Szunyogh, I.; Genton, M. G.
2015-12-01
In ensemble Kalman filtering (EnKF), the small number of ensemble members that is feasible to use in a practical data assimilation application leads to sampling variability of the estimates of the background error covariances. The standard approach to reducing the effects of this sampling variability, which has also been found to be highly efficient in improving the performance of EnKF, is the localization of the estimates of the covariances. One family of localization techniques is based on taking the Schur (element-wise) product of the ensemble-based sample covariance matrix and a correlation matrix whose entries are obtained by the discretization of a distance-dependent correlation function. While the proper definition of the localization function for a single state variable has been extensively investigated, a rigorous definition of the localization function for multiple state variables that exist at the same locations has been seldom considered. This paper introduces two strategies for the construction of localization functions for multiple state variables. The proposed localization functions are tested by assimilating simulated observations experiments into the bivariate Lorenz 95 model with their help.
Cendagorta, Joseph R; Bačić, Zlatko; Tuckerman, Mark E
2018-03-14
We introduce a scheme for approximating quantum time correlation functions numerically within the Feynman path integral formulation. Starting with the symmetrized version of the correlation function expressed as a discretized path integral, we introduce a change of integration variables often used in the derivation of trajectory-based semiclassical methods. In particular, we transform to sum and difference variables between forward and backward complex-time propagation paths. Once the transformation is performed, the potential energy is expanded in powers of the difference variables, which allows us to perform the integrals over these variables analytically. The manner in which this procedure is carried out results in an open-chain path integral (in the remaining sum variables) with a modified potential that is evaluated using imaginary-time path-integral sampling rather than requiring the generation of a large ensemble of trajectories. Consequently, any number of path integral sampling schemes can be employed to compute the remaining path integral, including Monte Carlo, path-integral molecular dynamics, or enhanced path-integral molecular dynamics. We believe that this approach constitutes a different perspective in semiclassical-type approximations to quantum time correlation functions. Importantly, we argue that our approximation can be systematically improved within a cumulant expansion formalism. We test this approximation on a set of one-dimensional problems that are commonly used to benchmark approximate quantum dynamical schemes. We show that the method is at least as accurate as the popular ring-polymer molecular dynamics technique and linearized semiclassical initial value representation for correlation functions of linear operators in most of these examples and improves the accuracy of correlation functions of nonlinear operators.
NASA Astrophysics Data System (ADS)
Cendagorta, Joseph R.; Bačić, Zlatko; Tuckerman, Mark E.
2018-03-01
We introduce a scheme for approximating quantum time correlation functions numerically within the Feynman path integral formulation. Starting with the symmetrized version of the correlation function expressed as a discretized path integral, we introduce a change of integration variables often used in the derivation of trajectory-based semiclassical methods. In particular, we transform to sum and difference variables between forward and backward complex-time propagation paths. Once the transformation is performed, the potential energy is expanded in powers of the difference variables, which allows us to perform the integrals over these variables analytically. The manner in which this procedure is carried out results in an open-chain path integral (in the remaining sum variables) with a modified potential that is evaluated using imaginary-time path-integral sampling rather than requiring the generation of a large ensemble of trajectories. Consequently, any number of path integral sampling schemes can be employed to compute the remaining path integral, including Monte Carlo, path-integral molecular dynamics, or enhanced path-integral molecular dynamics. We believe that this approach constitutes a different perspective in semiclassical-type approximations to quantum time correlation functions. Importantly, we argue that our approximation can be systematically improved within a cumulant expansion formalism. We test this approximation on a set of one-dimensional problems that are commonly used to benchmark approximate quantum dynamical schemes. We show that the method is at least as accurate as the popular ring-polymer molecular dynamics technique and linearized semiclassical initial value representation for correlation functions of linear operators in most of these examples and improves the accuracy of correlation functions of nonlinear operators.
Models for twistable elastic polymers in Brownian dynamics, and their implementation for LAMMPS.
Brackley, C A; Morozov, A N; Marenduzzo, D
2014-04-07
An elastic rod model for semi-flexible polymers is presented. Theory for a continuum rod is reviewed, and it is shown that a popular discretised model used in numerical simulations gives the correct continuum limit. Correlation functions relating to both bending and twisting of the rod are derived for both continuous and discrete cases, and results are compared with numerical simulations. Finally, two possible implementations of the discretised model in the multi-purpose molecular dynamics software package LAMMPS are described.
Discrete Roughness Effects on Shuttle Orbiter at Mach 6
NASA Technical Reports Server (NTRS)
Berry, Scott A.; Hamilton, H. Harris, II
2002-01-01
Discrete roughness boundary layer transition results on a Shuttle Orbiter model in the NASA Langley Research Center 20-Inch Mach 6 Air Tunnel have been reanalyzed with new boundary layer calculations to provide consistency for comparison to other published results. The experimental results were previously obtained utilizing the phosphor thermography system to monitor the status of the boundary layer via global heat transfer images of the Orbiter windward surface. The size and location of discrete roughness elements were systematically varied along the centerline of the 0.0075-scale model at an angle of attack of 40 deg and the boundary layer response recorded. Various correlative approaches were attempted, with the roughness transition correlations based on edge properties providing the most reliable results. When a consistent computational method is used to compute edge conditions, transition datasets for different configurations at several angles of attack have been shown to collapse to a well-behaved correlation.
Revisiting Temporal Markov Chains for Continuum modeling of Transport in Porous Media
NASA Astrophysics Data System (ADS)
Delgoshaie, A. H.; Jenny, P.; Tchelepi, H.
2017-12-01
The transport of fluids in porous media is dominated by flow-field heterogeneity resulting from the underlying permeability field. Due to the high uncertainty in the permeability field, many realizations of the reference geological model are used to describe the statistics of the transport phenomena in a Monte Carlo (MC) framework. There has been strong interest in working with stochastic formulations of the transport that are different from the standard MC approach. Several stochastic models based on a velocity process for tracer particle trajectories have been proposed. Previous studies have shown that for high variances of the log-conductivity, the stochastic models need to account for correlations between consecutive velocity transitions to predict dispersion accurately. The correlated velocity models proposed in the literature can be divided into two general classes of temporal and spatial Markov models. Temporal Markov models have been applied successfully to tracer transport in both the longitudinal and transverse directions. These temporal models are Stochastic Differential Equations (SDEs) with very specific drift and diffusion terms tailored for a specific permeability correlation structure. The drift and diffusion functions devised for a certain setup would not necessarily be suitable for a different scenario, (e.g., a different permeability correlation structure). The spatial Markov models are simple discrete Markov chains that do not require case specific assumptions. However, transverse spreading of contaminant plumes has not been successfully modeled with the available correlated spatial models. Here, we propose a temporal discrete Markov chain to model both the longitudinal and transverse dispersion in a two-dimensional domain. We demonstrate that these temporal Markov models are valid for different correlation structures without modification. Similar to the temporal SDEs, the proposed model respects the limited asymptotic transverse spreading of the plume in two-dimensional problems.
Wavelet filtered shifted phase-encoded joint transform correlation for face recognition
NASA Astrophysics Data System (ADS)
Moniruzzaman, Md.; Alam, Mohammad S.
2017-05-01
A new wavelet-filtered-based Shifted- phase-encoded Joint Transform Correlation (WPJTC) technique has been proposed for efficient face recognition. The proposed technique uses discrete wavelet decomposition for preprocessing and can effectively accommodate various 3D facial distortions, effects of noise, and illumination variations. After analyzing different forms of wavelet basis functions, an optimal method has been proposed by considering the discrimination capability and processing speed as performance trade-offs. The proposed technique yields better correlation discrimination compared to alternate pattern recognition techniques such as phase-shifted phase-encoded fringe-adjusted joint transform correlator. The performance of the proposed WPJTC has been tested using the Yale facial database and extended Yale facial database under different environments such as illumination variation, noise, and 3D changes in facial expressions. Test results show that the proposed WPJTC yields better performance compared to alternate JTC based face recognition techniques.
Takada; Komatsu; Futamase
2000-04-20
We investigate the weak gravitational lensing effect that is due to the large-scale structure of the universe on two-point correlations of local maxima (hot spots) in the two-dimensional sky map of the cosmic microwave background (CMB) anisotropy. According to the Gaussian random statistics, as most inflationary scenarios predict, the hot spots are discretely distributed, with some characteristic angular separations on the last scattering surface that are due to oscillations of the CMB angular power spectrum. The weak lensing then causes pairs of hot spots, which are separated with the characteristic scale, to be observed with various separations. We found that the lensing fairly smooths out the oscillatory features of the two-point correlation function of hot spots. This indicates that the hot spot correlations can be a new statistical tool for measuring the shape and normalization of the power spectrum of matter fluctuations from the lensing signatures.
Exact Analytical Solutions for Elastodynamic Impact
2015-11-30
corroborated by derivation of exact discrete solutions from recursive equations for the impact problems. 15. SUBJECT TERMS One-dimensional impact; Elastic...wave propagation; Laplace transform; Floor function; Discrete solutions 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT UU 18...impact Elastic wave propagation Laplace transform Floor function Discrete solutionsWe consider the one-dimensional impact problem in which a semi
NASA Astrophysics Data System (ADS)
Adrian, S. B.; Andriulli, F. P.; Eibert, T. F.
2017-02-01
A new hierarchical basis preconditioner for the electric field integral equation (EFIE) operator is introduced. In contrast to existing hierarchical basis preconditioners, it works on arbitrary meshes and preconditions both the vector and the scalar potential within the EFIE operator. This is obtained by taking into account that the vector and the scalar potential discretized with loop-star basis functions are related to the hypersingular and the single layer operator (i.e., the well known integral operators from acoustics). For the single layer operator discretized with piecewise constant functions, a hierarchical preconditioner can easily be constructed. Thus the strategy we propose in this work for preconditioning the EFIE is the transformation of the scalar and the vector potential into operators equivalent to the single layer operator and to its inverse. More specifically, when the scalar potential is discretized with star functions as source and testing functions, the resulting matrix is a single layer operator discretized with piecewise constant functions and multiplied left and right with two additional graph Laplacian matrices. By inverting these graph Laplacian matrices, the discretized single layer operator is obtained, which can be preconditioned with the hierarchical basis. Dually, when the vector potential is discretized with loop functions, the resulting matrix can be interpreted as a hypersingular operator discretized with piecewise linear functions. By leveraging on a scalar Calderón identity, we can interpret this operator as spectrally equivalent to the inverse single layer operator. Then we use a linear-in-complexity, closed-form inverse of the dual hierarchical basis to precondition the hypersingular operator. The numerical results show the effectiveness of the proposed preconditioner and the practical impact of theoretical developments in real case scenarios.
The neural correlates of reciprocity are sensitive to prior experience of reciprocity.
Cáceda, Ricardo; Prendes-Alvarez, Stefania; Hsu, Jung-Jiin; Tripathi, Shanti P; Kilts, Clint D; James, G Andrew
2017-08-14
Reciprocity is central to human relationships and is strongly influenced by multiple factors including the nature of social exchanges and their attendant emotional reactions. Despite recent advances in the field, the neural processes involved in this modulation of reciprocal behavior by ongoing social interaction are poorly understood. We hypothesized that activity within a discrete set of neural networks including a putative moral cognitive neural network is associated with reciprocity behavior. Nineteen healthy adults underwent functional magnetic resonance imaging scanning while playing the trustee role in the Trust Game. Personality traits and moral development were assessed. Independent component analysis was used to identify task-related functional brain networks and assess their relationship to behavior. The saliency network (insula and anterior cingulate) was positively correlated with reciprocity behavior. A consistent array of brain regions supports the engagement of emotional, self-referential and planning processes during social reciprocity behavior. Published by Elsevier B.V.
Coupled π π , K K ¯ scattering in P -wave and the ρ resonance from lattice QCD
Wilson, David J.; Briceño, Raúl A.; Dudek, Jozef J.; ...
2015-11-02
In this study, we determine elastic and coupled-channel amplitudes for isospin-1 meson-meson scattering inmore » $P$-wave, by calculating correlation functions using lattice QCD with light quark masses such that $$m_\\pi = 236$$ MeV in a cubic volume of $$\\sim (4 \\,\\mathrm{fm})^3$$. Variational analyses of large matrices of correlation functions computed using operator constructions resembling $$\\pi\\pi$$, $$K\\overline{K}$$ and $$q\\bar{q}$$, in several moving frames and several lattice irreducible representations, leads to discrete energy spectra from which scattering amplitudes are extracted. In the elastic $$\\pi\\pi$$ scattering region we obtain a detailed energy-dependence for the phase-shift, corresponding to a $$\\rho$$ resonance, and we extend the analysis into the coupled-channel $$K\\overline{K}$$ region for the first time, finding a small coupling between the channels.« less
Reflectance of topologically disordered photonic-crystal films
NASA Astrophysics Data System (ADS)
Vigneron, Jean-Pol; Lousse, Virginie M.; Biro, Laszlo P.; Vertesy, Zofia; Balint, Zolt
2005-04-01
Periodicity implies the creation of discretely diffracted beams while various departures from periodicity lead to broadened scattering angles. This effect is investigated for disturbed lattices exhibiting randomly varying periods. In the Born approximation, the diffused reflection is shown to be related to a pair correlation function constructed from the distribution of the film scattering power. The technique is first applied to a natural photonic crystal found on the ventral side of the wings of the butterfly Cyanophrys remus, where scanning electron microscopy reveals the formation of polycrystalline photonic structures. Second, the disorder in the distribution of the cross-ribs on the scales another butterfly, Lycaena virgaureae, is investigated. The irregular arrangement of scatterers found in chitin structure of this insect produces light reflection in the long-wavelength part of the visible range, with a quite unusual broad directionality. The use of the pair correlation function allows to propose estimates of the diffusive spreading in these very different systems.
NASA Astrophysics Data System (ADS)
Choi, Sun-Woo; Byun, Young Tae
2018-03-01
The correlation between platinum (Pt) functionalization and chlorine (Cl2) sensing capability in single-walled carbon nanotubes (SWCNTs) was investigated. Utilizing a photoreduction technique via ultraviolet (UV) irradiation, the Pt nanoparticles (NPs) with various diameters of 7-80 nm, which were controlled by Pt precursor concentrations, were successfully functionalized on the sidewalls of SWCNTs. The discrete Pt NP-loaded SWCNTs exhibited significantly enhanced response value (-(ΔR/R0) × 100 = 33.8%) for 1 ppm Cl2 at room temperature (25 °C) compared with that (no response) of pure SWCNTs. On the other hand, in case of continuous Pt NP-loaded SWCNTs, Cl2 sensing capabilities were significantly degraded. The Cl2 sensing capabilities of fabricated sensors tended to correlate with geometric configurations of the catalytic Pt NPs on the sidewalls of SWCNTs, due to differences in the electron pathway.
ERIC Educational Resources Information Center
Schmidt, Jonathan D.; Drasgow, Erik; Halle, James W.; Martin, Christian A.; Bliss, Sacha A.
2014-01-01
Discrete-trial functional analysis (DTFA) is an experimental method for determining the variables maintaining problem behavior in the context of natural routines. Functional communication training (FCT) is an effective method for replacing problem behavior, once identified, with a functionally equivalent response. We implemented these procedures…
Nonperturbative Treatment of non-Markovian Dynamics of Open Quantum Systems
NASA Astrophysics Data System (ADS)
Tamascelli, D.; Smirne, A.; Huelga, S. F.; Plenio, M. B.
2018-01-01
We identify the conditions that guarantee equivalence of the reduced dynamics of an open quantum system (OQS) for two different types of environments—one a continuous bosonic environment leading to a unitary system-environment evolution and the other a discrete-mode bosonic environment resulting in a system-mode (nonunitary) Lindbladian evolution. Assuming initial Gaussian states for the environments, we prove that the two OQS dynamics are equivalent if both the expectation values and two-time correlation functions of the environmental interaction operators are the same at all times for the two configurations. Since the numerical and analytical description of a discrete-mode environment undergoing a Lindbladian evolution is significantly more efficient than that of a continuous bosonic environment in a unitary evolution, our result represents a powerful, nonperturbative tool to describe complex and possibly highly non-Markovian dynamics. As a special application, we recover and generalize the well-known pseudomodes approach to open-system dynamics.
Galaxy Redshifts from Discrete Optimization of Correlation Functions
NASA Astrophysics Data System (ADS)
Lee, Benjamin C. G.; Budavári, Tamás; Basu, Amitabh; Rahman, Mubdi
2016-12-01
We propose a new method of constraining the redshifts of individual extragalactic sources based on celestial coordinates and their ensemble statistics. Techniques from integer linear programming (ILP) are utilized to optimize simultaneously for the angular two-point cross- and autocorrelation functions. Our novel formalism introduced here not only transforms the otherwise hopelessly expensive, brute-force combinatorial search into a linear system with integer constraints but also is readily implementable in off-the-shelf solvers. We adopt Gurobi, a commercial optimization solver, and use Python to build the cost function dynamically. The preliminary results on simulated data show potential for future applications to sky surveys by complementing and enhancing photometric redshift estimators. Our approach is the first application of ILP to astronomical analysis.
Persistence Probabilities of Two-Sided (Integrated) Sums of Correlated Stationary Gaussian Sequences
NASA Astrophysics Data System (ADS)
Aurzada, Frank; Buck, Micha
2018-02-01
We study the persistence probability for some two-sided, discrete-time Gaussian sequences that are discrete-time analogues of fractional Brownian motion and integrated fractional Brownian motion, respectively. Our results extend the corresponding ones in continuous time in Molchan (Commun Math Phys 205(1):97-111, 1999) and Molchan (J Stat Phys 167(6):1546-1554, 2017) to a wide class of discrete-time processes.
Novel wavelet threshold denoising method in axle press-fit zone ultrasonic detection
NASA Astrophysics Data System (ADS)
Peng, Chaoyong; Gao, Xiaorong; Peng, Jianping; Wang, Ai
2017-02-01
Axles are important part of railway locomotives and vehicles. Periodic ultrasonic inspection of axles can effectively detect and monitor axle fatigue cracks. However, in the axle press-fit zone, the complex interface contact condition reduces the signal-noise ratio (SNR). Therefore, the probability of false positives and false negatives increases. In this work, a novel wavelet threshold function is created to remove noise and suppress press-fit interface echoes in axle ultrasonic defect detection. The novel wavelet threshold function with two variables is designed to ensure the precision of optimum searching process. Based on the positive correlation between the correlation coefficient and SNR and with the experiment phenomenon that the defect and the press-fit interface echo have different axle-circumferential correlation characteristics, a discrete optimum searching process for two undetermined variables in novel wavelet threshold function is conducted. The performance of the proposed method is assessed by comparing it with traditional threshold methods using real data. The statistic results of the amplitude and the peak SNR of defect echoes show that the proposed wavelet threshold denoising method not only maintains the amplitude of defect echoes but also has a higher peak SNR.
Determining A Purely Symbolic Transfer Function from Symbol Streams: Theory and Algorithms
DOE Office of Scientific and Technical Information (OSTI.GOV)
Griffin, Christopher H
Transfer function modeling is a \\emph{standard technique} in classical Linear Time Invariant and Statistical Process Control. The work of Box and Jenkins was seminal in developing methods for identifying parameters associated with classicalmore » $(r,s,k)$$ transfer functions. Discrete event systems are often \\emph{used} for modeling hybrid control structures and high-level decision problems. \\emph{Examples include} discrete time, discrete strategy repeated games. For these games, a \\emph{discrete transfer function in the form of} an accurate hidden Markov model of input-output relations \\emph{could be used to derive optimal response strategies.} In this paper, we develop an algorithm \\emph{for} creating probabilistic \\textit{Mealy machines} that act as transfer function models for discrete event dynamic systems (DEDS). Our models are defined by three parameters, $$(l_1, l_2, k)$ just as the Box-Jenkins transfer function models. Here $$l_1$$ is the maximal input history lengths to consider, $$l_2$$ is the maximal output history lengths to consider and $k$ is the response lag. Using related results, We show that our Mealy machine transfer functions are optimal in the sense that they maximize the mutual information between the current known state of the DEDS and the next observed input/output pair.« less
Principles of Discrete Time Mechanics
NASA Astrophysics Data System (ADS)
Jaroszkiewicz, George
2014-04-01
1. Introduction; 2. The physics of discreteness; 3. The road to calculus; 4. Temporal discretization; 5. Discrete time dynamics architecture; 6. Some models; 7. Classical cellular automata; 8. The action sum; 9. Worked examples; 10. Lee's approach to discrete time mechanics; 11. Elliptic billiards; 12. The construction of system functions; 13. The classical discrete time oscillator; 14. Type 2 temporal discretization; 15. Intermission; 16. Discrete time quantum mechanics; 17. The quantized discrete time oscillator; 18. Path integrals; 19. Quantum encoding; 20. Discrete time classical field equations; 21. The discrete time Schrodinger equation; 22. The discrete time Klein-Gordon equation; 23. The discrete time Dirac equation; 24. Discrete time Maxwell's equations; 25. The discrete time Skyrme model; 26. Discrete time quantum field theory; 27. Interacting discrete time scalar fields; 28. Space, time and gravitation; 29. Causality and observation; 30. Concluding remarks; Appendix A. Coherent states; Appendix B. The time-dependent oscillator; Appendix C. Quaternions; Appendix D. Quantum registers; References; Index.
Graph-cut based discrete-valued image reconstruction.
Tuysuzoglu, Ahmet; Karl, W Clem; Stojanovic, Ivana; Castañòn, David; Ünlü, M Selim
2015-05-01
Efficient graph-cut methods have been used with great success for labeling and denoising problems occurring in computer vision. Unfortunately, the presence of linear image mappings has prevented the use of these techniques in most discrete-amplitude image reconstruction problems. In this paper, we develop a graph-cut based framework for the direct solution of discrete amplitude linear image reconstruction problems cast as regularized energy function minimizations. We first analyze the structure of discrete linear inverse problem cost functions to show that the obstacle to the application of graph-cut methods to their solution is the variable mixing caused by the presence of the linear sensing operator. We then propose to use a surrogate energy functional that overcomes the challenges imposed by the sensing operator yet can be utilized efficiently in existing graph-cut frameworks. We use this surrogate energy functional to devise a monotonic iterative algorithm for the solution of discrete valued inverse problems. We first provide experiments using local convolutional operators and show the robustness of the proposed technique to noise and stability to changes in regularization parameter. Then we focus on nonlocal, tomographic examples where we consider limited-angle data problems. We compare our technique with state-of-the-art discrete and continuous image reconstruction techniques. Experiments show that the proposed method outperforms state-of-the-art techniques in challenging scenarios involving discrete valued unknowns.
Yokoi, Isao; Komatsu, Hidehiko
2010-09-01
Visual grouping of discrete elements is an important function for object recognition. We recently conducted an experiment to study neural correlates of visual grouping. We recorded neuronal activities while monkeys performed a grouping detection task in which they discriminated visual patterns composed of discrete dots arranged in a cross and detected targets in which dots with the same contrast were aligned horizontally or vertically. We found that some neurons in the lateral bank of the intraparietal sulcus exhibit activity related to visual grouping. In the present study, we analyzed how different types of neurons contribute to visual grouping. We classified the recorded neurons as putative pyramidal neurons or putative interneurons, depending on the duration of their action potentials. We found that putative pyramidal neurons exhibited selectivity for the orientation of the target, and this selectivity was enhanced by attention to a particular target orientation. By contrast, putative interneurons responded more strongly to the target stimuli than to the nontargets, regardless of the orientation of the target. These results suggest that different classes of parietal neurons contribute differently to the grouping of discrete elements.
Cortical Neural Computation by Discrete Results Hypothesis
Castejon, Carlos; Nuñez, Angel
2016-01-01
One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called “Discrete Results” (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of “Discrete Results” is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel “Discrete Results” concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS) interneuron may be a key element in our hypothesis providing the basis for this computation. PMID:27807408
Cortical Neural Computation by Discrete Results Hypothesis.
Castejon, Carlos; Nuñez, Angel
2016-01-01
One of the most challenging problems we face in neuroscience is to understand how the cortex performs computations. There is increasing evidence that the power of the cortical processing is produced by populations of neurons forming dynamic neuronal ensembles. Theoretical proposals and multineuronal experimental studies have revealed that ensembles of neurons can form emergent functional units. However, how these ensembles are implicated in cortical computations is still a mystery. Although cell ensembles have been associated with brain rhythms, the functional interaction remains largely unclear. It is still unknown how spatially distributed neuronal activity can be temporally integrated to contribute to cortical computations. A theoretical explanation integrating spatial and temporal aspects of cortical processing is still lacking. In this Hypothesis and Theory article, we propose a new functional theoretical framework to explain the computational roles of these ensembles in cortical processing. We suggest that complex neural computations underlying cortical processing could be temporally discrete and that sensory information would need to be quantized to be computed by the cerebral cortex. Accordingly, we propose that cortical processing is produced by the computation of discrete spatio-temporal functional units that we have called "Discrete Results" (Discrete Results Hypothesis). This hypothesis represents a novel functional mechanism by which information processing is computed in the cortex. Furthermore, we propose that precise dynamic sequences of "Discrete Results" is the mechanism used by the cortex to extract, code, memorize and transmit neural information. The novel "Discrete Results" concept has the ability to match the spatial and temporal aspects of cortical processing. We discuss the possible neural underpinnings of these functional computational units and describe the empirical evidence supporting our hypothesis. We propose that fast-spiking (FS) interneuron may be a key element in our hypothesis providing the basis for this computation.
Photon losses depending on polarization mixedness
NASA Astrophysics Data System (ADS)
Memarzadeh, L.; Mancini, S.
2010-01-01
We introduce a quantum channel describing photon losses depending on the degree of polarization mixedness. This can be regarded as a model of quantum channel with correlated errors between discrete and continuous degrees of freedom. We consider classical information over a continuous alphabet encoded on weak coherent states as well as classical information over a discrete alphabet encoded on single photons using dual rail representation. In both cases we study the one-shot capacity of the channel and its behaviour in terms of correlation between losses and polarization mixedness.
Celeste, Ricardo; Maringolo, Milena P; Comar, Moacyr; Viana, Rommel B; Guimarães, Amanda R; Haiduke, Roberto L A; da Silva, Albérico B F
2015-10-01
Accurate Gaussian basis sets for atoms from H to Ba were obtained by means of the generator coordinate Hartree-Fock (GCHF) method based on a polynomial expansion to discretize the Griffin-Wheeler-Hartree-Fock equations (GWHF). The discretization of the GWHF equations in this procedure is based on a mesh of points not equally distributed in contrast with the original GCHF method. The results of atomic Hartree-Fock energies demonstrate the capability of these polynomial expansions in designing compact and accurate basis sets to be used in molecular calculations and the maximum error found when compared to numerical values is only 0.788 mHartree for indium. Some test calculations with the B3LYP exchange-correlation functional for N2, F2, CO, NO, HF, and HCN show that total energies within 1.0 to 2.4 mHartree compared to the cc-pV5Z basis sets are attained with our contracted bases with a much smaller number of polarization functions (2p1d and 2d1f for hydrogen and heavier atoms, respectively). Other molecular calculations performed here are also in very good accordance with experimental and cc-pV5Z results. The most important point to be mentioned here is that our generator coordinate basis sets required only a tiny fraction of the computational time when compared to B3LYP/cc-pV5Z calculations.
Photon strength and the low-energy enhancement
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wiedeking, M.; Bernstein, L. A.; Bleuel, D. L.
2014-08-14
Several measurements in medium mass nuclei have reported a low-energy enhancement in the photon strength function. Although, much effort has been invested in unraveling the mysteries of this effect, its physical origin is still not conclusively understood. Here, a completely model-independent experimental approach to investigate the existence of this enhancement is presented. The experiment was designed to study statistical feeding from the quasi-continuum (below the neutron separation energy) to individual low-lying discrete levels in {sup 95}Mo produced in the (d, p) reaction. A key aspect to successfully study gamma decay from the region of high-level density is the detection andmore » extraction of correlated particle-gamma-gamma events which was accomplished using an array of Clover HPGe detectors and large area annular silicon detectors. The entrance channel excitation energy into the residual nucleus produced in the reaction was inferred from the detected proton energies in the silicon detectors. Gating on gamma-transitions originating from low-lying discrete levels specifies the state fed by statistical gamma-rays. Any particle-gamma-gamma event in combination with specific energy sum requirements ensures a clean and unambiguous determination of the initial and final state of the observed gamma rays. With these requirements the statistical feeding to individual discrete levels is extracted on an event-by-event basis. The results are presented and compared to {sup 95}Mo photon strength function data measured at the University of Oslo.« less
Yang, L M; Shu, C; Wang, Y
2016-03-01
In this work, a discrete gas-kinetic scheme (DGKS) is presented for simulation of two-dimensional viscous incompressible and compressible flows. This scheme is developed from the circular function-based GKS, which was recently proposed by Shu and his co-workers [L. M. Yang, C. Shu, and J. Wu, J. Comput. Phys. 274, 611 (2014)]. For the circular function-based GKS, the integrals for conservation forms of moments in the infinity domain for the Maxwellian function-based GKS are simplified to those integrals along the circle. As a result, the explicit formulations of conservative variables and fluxes are derived. However, these explicit formulations of circular function-based GKS for viscous flows are still complicated, which may not be easy for the application by new users. By using certain discrete points to represent the circle in the phase velocity space, the complicated formulations can be replaced by a simple solution process. The basic requirement is that the conservation forms of moments for the circular function-based GKS can be accurately satisfied by weighted summation of distribution functions at discrete points. In this work, it is shown that integral quadrature by four discrete points on the circle, which forms the D2Q4 discrete velocity model, can exactly match the integrals. Numerical results showed that the present scheme can provide accurate numerical results for incompressible and compressible viscous flows with roughly the same computational cost as that needed by the Roe scheme.
Loop series for discrete statistical models on graphs
NASA Astrophysics Data System (ADS)
Chertkov, Michael; Chernyak, Vladimir Y.
2006-06-01
In this paper we present the derivation details, logic, and motivation for the three loop calculus introduced in Chertkov and Chernyak (2006 Phys. Rev. E 73 065102(R)). Generating functions for each of the three interrelated discrete statistical models are expressed in terms of a finite series. The first term in the series corresponds to the Bethe-Peierls belief-propagation (BP) contribution; the other terms are labelled by loops on the factor graph. All loop contributions are simple rational functions of spin correlation functions calculated within the BP approach. We discuss two alternative derivations of the loop series. One approach implements a set of local auxiliary integrations over continuous fields with the BP contribution corresponding to an integrand saddle-point value. The integrals are replaced by sums in the complementary approach, briefly explained in Chertkov and Chernyak (2006 Phys. Rev. E 73 065102(R)). Local gauge symmetry transformations that clarify an important invariant feature of the BP solution are revealed in both approaches. The individual terms change under the gauge transformation while the partition function remains invariant. The requirement for all individual terms to be nonzero only for closed loops in the factor graph (as opposed to paths with loose ends) is equivalent to fixing the first term in the series to be exactly equal to the BP contribution. Further applications of the loop calculus to problems in statistical physics, computer and information sciences are discussed.
Beta oscillations define discrete perceptual cycles in the somatosensory domain.
Baumgarten, Thomas J; Schnitzler, Alfons; Lange, Joachim
2015-09-29
Whether seeing a movie, listening to a song, or feeling a breeze on the skin, we coherently experience these stimuli as continuous, seamless percepts. However, there are rare perceptual phenomena that argue against continuous perception but, instead, suggest discrete processing of sensory input. Empirical evidence supporting such a discrete mechanism, however, remains scarce and comes entirely from the visual domain. Here, we demonstrate compelling evidence for discrete perceptual sampling in the somatosensory domain. Using magnetoencephalography (MEG) and a tactile temporal discrimination task in humans, we find that oscillatory alpha- and low beta-band (8-20 Hz) cycles in primary somatosensory cortex represent neurophysiological correlates of discrete perceptual cycles. Our results agree with several theoretical concepts of discrete perceptual sampling and empirical evidence of perceptual cycles in the visual domain. Critically, these results show that discrete perceptual cycles are not domain-specific, and thus restricted to the visual domain, but extend to the somatosensory domain.
Surface and finite size effect on fluctuations dynamics in nanoparticles with long-range order
NASA Astrophysics Data System (ADS)
Morozovska, A. N.; Eliseev, E. A.
2010-02-01
The influence of surface and finite size on the dynamics of the order parameter fluctuations and critical phenomena in the three-dimensional (3D)-confined systems with long-range order was not considered theoretically. In this paper, we study the influence of surface and finite size on the dynamics of the order parameter fluctuations in the particles of arbitrary shape. We consider concrete examples of the spherical and cylindrical ferroic nanoparticles within Landau-Ginzburg-Devonshire phenomenological approach. Allowing for the strong surface energy contribution in micro and nanoparticles, the analytical expressions derived for the Ornstein-Zernike correlator of the long-range order parameter spatial-temporal fluctuations, dynamic generalized susceptibility, relaxation times, and correlation radii discrete spectra are different from those known for bulk systems. Obtained analytical expressions for the correlation function of the order parameter spatial-temporal fluctuations in micro and nanosized systems can be useful for the quantitative analysis of the dynamical structural factors determined from magnetic resonance diffraction and scattering spectra. Besides the practical importance of the correlation function for the analysis of the experimental data, derived expressions for the fluctuations strength determine the fundamental limits of phenomenological theories applicability for 3D-confined systems.
NASA Astrophysics Data System (ADS)
Hu, Xing-Biao; Li, Shi-Hao
2017-07-01
The relationship between matrix integrals and integrable systems was revealed more than 20 years ago. As is known, matrix integrals over a Gaussian ensemble used in random matrix theory could act as the τ-function of several hierarchies of integrable systems. In this article, we will show that the time-dependent partition function of the Bures ensemble, whose measure has many interesting geometric properties, could act as the τ-function of BKP and DKP hierarchies. In addition, if discrete time variables are introduced, then this partition function could act as the τ-function of discrete BKP and DKP hierarchies. In particular, there are some links between the partition function of the Bures ensemble and Toda-type equations.
Greco, Cristina; Jiang, Ying; Chen, Jeff Z Y; Kremer, Kurt; Daoulas, Kostas Ch
2016-11-14
Self Consistent Field (SCF) theory serves as an efficient tool for studying mesoscale structure and thermodynamics of polymeric liquid crystals (LC). We investigate how some of the intrinsic approximations of SCF affect the description of the thermodynamics of polymeric LC, using a coarse-grained model. Polymer nematics are represented as discrete worm-like chains (WLC) where non-bonded interactions are defined combining an isotropic repulsive and an anisotropic attractive Maier-Saupe (MS) potential. The range of the potentials, σ, controls the strength of correlations due to non-bonded interactions. Increasing σ (which can be seen as an increase of coarse-graining) while preserving the integrated strength of the potentials reduces correlations. The model is studied with particle-based Monte Carlo (MC) simulations and SCF theory which uses partial enumeration to describe discrete WLC. In MC simulations the Helmholtz free energy is calculated as a function of strength of MS interactions to obtain reference thermodynamic data. To calculate the free energy of the nematic branch with respect to the disordered melt, we employ a special thermodynamic integration (TI) scheme invoking an external field to bypass the first-order isotropic-nematic transition. Methodological aspects which have not been discussed in earlier implementations of the TI to LC are considered. Special attention is given to the rotational Goldstone mode. The free-energy landscape in MC and SCF is directly compared. For moderate σ the differences highlight the importance of local non-bonded orientation correlations between segments, which SCF neglects. Simple renormalization of parameters in SCF cannot compensate the missing correlations. Increasing σ reduces correlations and SCF reproduces well the free energy in MC simulations.
Game-theoretic strategies for asymmetric networked systems
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rao, Nageswara S.; Ma, Chris Y. T.; Hausken, Kjell
Abstract—We consider an infrastructure consisting of a network of systems each composed of discrete components that can be reinforced at a certain cost to guard against attacks. The network provides the vital connectivity between systems, and hence plays a critical, asymmetric role in the infrastructure operations. We characterize the system-level correlations using the aggregate failure correlation function that specifies the infrastructure failure probability given the failure of an individual system or network. The survival probabilities of systems and network satisfy first-order differential conditions that capture the component-level correlations. We formulate the problem of ensuring the infrastructure survival as a gamemore » between anattacker and a provider, using the sum-form and product-form utility functions, each composed of a survival probability term and a cost term. We derive Nash Equilibrium conditions which provide expressions for individual system survival probabilities, and also the expected capacity specified by the total number of operational components. These expressions differ only in a single term for the sum-form and product-form utilities, despite their significant differences.We apply these results to simplified models of distributed cloud computing infrastructures.« less
Using Stocking or Harvesting to Reverse Period-Doubling Bifurcations in Discrete Population Models
James F. Selgrade
1998-01-01
This study considers a general class of 2-dimensional, discrete population models where each per capita transition function (fitness) depends on a linear combination of the densities of the interacting populations. The fitness functions are either monotone decreasing functions (pioneer fitnesses) or one-humped functions (climax fitnesses). Four sets of necessary...
On pseudo-spectral time discretizations in summation-by-parts form
NASA Astrophysics Data System (ADS)
Ruggiu, Andrea A.; Nordström, Jan
2018-05-01
Fully-implicit discrete formulations in summation-by-parts form for initial-boundary value problems must be invertible in order to provide well functioning procedures. We prove that, under mild assumptions, pseudo-spectral collocation methods for the time derivative lead to invertible discrete systems when energy-stable spatial discretizations are used.
The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.
Sakhanenko, Nikita A; Kunert-Graf, James; Galas, David J
2017-12-01
The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. We present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discrete variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis-that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. We illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.
Program for the analysis of time series. [by means of fast Fourier transform algorithm
NASA Technical Reports Server (NTRS)
Brown, T. J.; Brown, C. G.; Hardin, J. C.
1974-01-01
A digital computer program for the Fourier analysis of discrete time data is described. The program was designed to handle multiple channels of digitized data on general purpose computer systems. It is written, primarily, in a version of FORTRAN 2 currently in use on CDC 6000 series computers. Some small portions are written in CDC COMPASS, an assembler level code. However, functional descriptions of these portions are provided so that the program may be adapted for use on any facility possessing a FORTRAN compiler and random-access capability. Properly formatted digital data are windowed and analyzed by means of a fast Fourier transform algorithm to generate the following functions: (1) auto and/or cross power spectra, (2) autocorrelations and/or cross correlations, (3) Fourier coefficients, (4) coherence functions, (5) transfer functions, and (6) histograms.
Towards spinning Mellin amplitudes
NASA Astrophysics Data System (ADS)
Chen, Heng-Yu; Kuo, En-Jui; Kyono, Hideki
2018-06-01
We construct the Mellin representation of four point conformal correlation function with external primary operators with arbitrary integer spacetime spins, and obtain a natural proposal for spinning Mellin amplitudes. By restricting to the exchange of symmetric traceless primaries, we generalize the Mellin transform for scalar case to introduce discrete Mellin variables for incorporating spin degrees of freedom. Based on the structures about spinning three and four point Witten diagrams, we also obtain a generalization of the Mack polynomial which can be regarded as a natural kinematical polynomial basis for computing spinning Mellin amplitudes using different choices of interaction vertices.
The Pathway Coexpression Network: Revealing pathway relationships
Tanzi, Rudolph E.
2018-01-01
A goal of genomics is to understand the relationships between biological processes. Pathways contribute to functional interplay within biological processes through complex but poorly understood interactions. However, limited functional references for global pathway relationships exist. Pathways from databases such as KEGG and Reactome provide discrete annotations of biological processes. Their relationships are currently either inferred from gene set enrichment within specific experiments, or by simple overlap, linking pathway annotations that have genes in common. Here, we provide a unifying interpretation of functional interaction between pathways by systematically quantifying coexpression between 1,330 canonical pathways from the Molecular Signatures Database (MSigDB) to establish the Pathway Coexpression Network (PCxN). We estimated the correlation between canonical pathways valid in a broad context using a curated collection of 3,207 microarrays from 72 normal human tissues. PCxN accounts for shared genes between annotations to estimate significant correlations between pathways with related functions rather than with similar annotations. We demonstrate that PCxN provides novel insight into mechanisms of complex diseases using an Alzheimer’s Disease (AD) case study. PCxN retrieved pathways significantly correlated with an expert curated AD gene list. These pathways have known associations with AD and were significantly enriched for genes independently associated with AD. As a further step, we show how PCxN complements the results of gene set enrichment methods by revealing relationships between enriched pathways, and by identifying additional highly correlated pathways. PCxN revealed that correlated pathways from an AD expression profiling study include functional clusters involved in cell adhesion and oxidative stress. PCxN provides expanded connections to pathways from the extracellular matrix. PCxN provides a powerful new framework for interrogation of global pathway relationships. Comprehensive exploration of PCxN can be performed at http://pcxn.org/. PMID:29554099
Stochastic modeling and simulation of reaction-diffusion system with Hill function dynamics.
Chen, Minghan; Li, Fei; Wang, Shuo; Cao, Young
2017-03-14
Stochastic simulation of reaction-diffusion systems presents great challenges for spatiotemporal biological modeling and simulation. One widely used framework for stochastic simulation of reaction-diffusion systems is reaction diffusion master equation (RDME). Previous studies have discovered that for the RDME, when discretization size approaches zero, reaction time for bimolecular reactions in high dimensional domains tends to infinity. In this paper, we demonstrate that in the 1D domain, highly nonlinear reaction dynamics given by Hill function may also have dramatic change when discretization size is smaller than a critical value. Moreover, we discuss methods to avoid this problem: smoothing over space, fixed length smoothing over space and a hybrid method. Our analysis reveals that the switch-like Hill dynamics reduces to a linear function of discretization size when the discretization size is small enough. The three proposed methods could correctly (under certain precision) simulate Hill function dynamics in the microscopic RDME system.
A Discretization Algorithm for Meteorological Data and its Parallelization Based on Hadoop
NASA Astrophysics Data System (ADS)
Liu, Chao; Jin, Wen; Yu, Yuting; Qiu, Taorong; Bai, Xiaoming; Zou, Shuilong
2017-10-01
In view of the large amount of meteorological observation data, the property is more and the attribute values are continuous values, the correlation between the elements is the need for the application of meteorological data, this paper is devoted to solving the problem of how to better discretize large meteorological data to more effectively dig out the hidden knowledge in meteorological data and research on the improvement of discretization algorithm for large scale data, in order to achieve data in the large meteorological data discretization for the follow-up to better provide knowledge to provide protection, a discretization algorithm based on information entropy and inconsistency of meteorological attributes is proposed and the algorithm is parallelized under Hadoop platform. Finally, the comparison test validates the effectiveness of the proposed algorithm for discretization in the area of meteorological large data.
Statistical Analysis of Large Scale Structure by the Discrete Wavelet Transform
NASA Astrophysics Data System (ADS)
Pando, Jesus
1997-10-01
The discrete wavelet transform (DWT) is developed as a general statistical tool for the study of large scale structures (LSS) in astrophysics. The DWT is used in all aspects of structure identification including cluster analysis, spectrum and two-point correlation studies, scale-scale correlation analysis and to measure deviations from Gaussian behavior. The techniques developed are demonstrated on 'academic' signals, on simulated models of the Lymanα (Lyα) forests, and on observational data of the Lyα forests. This technique can detect clustering in the Ly-α clouds where traditional techniques such as the two-point correlation function have failed. The position and strength of these clusters in both real and simulated data is determined and it is shown that clusters exist on scales as large as at least 20 h-1 Mpc at significance levels of 2-4 σ. Furthermore, it is found that the strength distribution of the clusters can be used to distinguish between real data and simulated samples even where other traditional methods have failed to detect differences. Second, a method for measuring the power spectrum of a density field using the DWT is developed. All common features determined by the usual Fourier power spectrum can be calculated by the DWT. These features, such as the index of a power law or typical scales, can be detected even when the samples are geometrically complex, the samples are incomplete, or the mean density on larger scales is not known (the infrared uncertainty). Using this method the spectra of Ly-α forests in both simulated and real samples is calculated. Third, a method for measuring hierarchical clustering is introduced. Because hierarchical evolution is characterized by a set of rules of how larger dark matter halos are formed by the merging of smaller halos, scale-scale correlations of the density field should be one of the most sensitive quantities in determining the merging history. We show that these correlations can be completely determined by the correlations between discrete wavelet coefficients on adjacent scales and at nearly the same spatial position, Cj,j+12/cdot2. Scale-scale correlations on two samples of the QSO Ly-α forests absorption spectra are computed. Lastly, higher order statistics are developed to detect deviations from Gaussian behavior. These higher order statistics are necessary to fully characterize the Ly-α forests because the usual 2nd order statistics, such as the two-point correlation function or power spectrum, give inconclusive results. It is shown how this technique takes advantage of the locality of the DWT to circumvent the central limit theorem. A non-Gaussian spectrum is defined and this spectrum reveals not only the magnitude, but the scales of non-Gaussianity. When applied to simulated and observational samples of the Ly-α clouds, it is found that different popular models of structure formation have different spectra while two, independent observational data sets, have the same spectra. Moreover, the non-Gaussian spectra of real data sets are significantly different from the spectra of various possible random samples. (Abstract shortened by UMI.)
Nmf9 Encodes a Highly Conserved Protein Important to Neurological Function in Mice and Flies.
Zhang, Shuxiao; Ross, Kevin D; Seidner, Glen A; Gorman, Michael R; Poon, Tiffany H; Wang, Xiaobo; Keithley, Elizabeth M; Lee, Patricia N; Martindale, Mark Q; Joiner, William J; Hamilton, Bruce A
2015-07-01
Many protein-coding genes identified by genome sequencing remain without functional annotation or biological context. Here we define a novel protein-coding gene, Nmf9, based on a forward genetic screen for neurological function. ENU-induced and genome-edited null mutations in mice produce deficits in vestibular function, fear learning and circadian behavior, which correlated with Nmf9 expression in inner ear, amygdala, and suprachiasmatic nuclei. Homologous genes from unicellular organisms and invertebrate animals predict interactions with small GTPases, but the corresponding domains are absent in mammalian Nmf9. Intriguingly, homozygotes for null mutations in the Drosophila homolog, CG45058, show profound locomotor defects and premature death, while heterozygotes show striking effects on sleep and activity phenotypes. These results link a novel gene orthology group to discrete neurological functions, and show conserved requirement across wide phylogenetic distance and domain level structural changes.
Wave functions of symmetry-protected topological phases from conformal field theories
NASA Astrophysics Data System (ADS)
Scaffidi, Thomas; Ringel, Zohar
2016-03-01
We propose a method for analyzing two-dimensional symmetry-protected topological (SPT) wave functions using a correspondence with conformal field theories (CFTs) and integrable lattice models. This method generalizes the CFT approach for the fractional quantum Hall effect wherein the wave-function amplitude is written as a many-operator correlator in the CFT. Adopting a bottom-up approach, we start from various known microscopic wave functions of SPTs with discrete symmetries and show how the CFT description emerges at large scale, thereby revealing a deep connection between group cocycles and critical, sometimes integrable, models. We show that the CFT describing the bulk wave function is often also the one describing the entanglement spectrum, but not always. Using a plasma analogy, we also prove the existence of hidden quasi-long-range order for a large class of SPTs. Finally, we show how response to symmetry fluxes is easily described in terms of the CFT.
Discrete Painlevé equations for a class of PVI τ-functions given as U(N) averages
NASA Astrophysics Data System (ADS)
Forrester, P. J.; Witte, N. S.
2005-09-01
In a recent work, difference equations (Laguerre-Freud equations) for the bi-orthogonal polynomials and related quantities corresponding to the weight on the unit circle w(z)=\\prod^m_{j=1}(z-z_j(t))^{\\rho_j} were derived. It is shown here that in the case m = 3, these difference equations, when applied to the calculation of the underlying U(N) average, reduce to a coupled system identifiable with that obtained by Adler and van Moerbeke, using the methods of the Toeplitz lattice and Virasoro constraints. Moreover, it is shown that this coupled system can be reduced to yield the discrete fifth Painlevé equation dPV as it occurs in the theory of the sixth Painlevé system. Methods based on affine Weyl group symmetries of Bäcklund transformations have previously yielded the dPV equation, but with different parameters for the same problem. We find an explicit mapping between the two forms. Applications of our results are made to give recurrences for the gap probabilities and moments in the circular unitary ensemble of random matrices, and to the diagonal spin-spin correlation function of the square lattice Ising model.
Stabilisation of discrete-time polynomial fuzzy systems via a polynomial lyapunov approach
NASA Astrophysics Data System (ADS)
Nasiri, Alireza; Nguang, Sing Kiong; Swain, Akshya; Almakhles, Dhafer
2018-02-01
This paper deals with the problem of designing a controller for a class of discrete-time nonlinear systems which is represented by discrete-time polynomial fuzzy model. Most of the existing control design methods for discrete-time fuzzy polynomial systems cannot guarantee their Lyapunov function to be a radially unbounded polynomial function, hence the global stability cannot be assured. The proposed control design in this paper guarantees a radially unbounded polynomial Lyapunov functions which ensures global stability. In the proposed design, state feedback structure is considered and non-convexity problem is solved by incorporating an integrator into the controller. Sufficient conditions of stability are derived in terms of polynomial matrix inequalities which are solved via SOSTOOLS in MATLAB. A numerical example is presented to illustrate the effectiveness of the proposed controller.
Federal Register 2010, 2011, 2012, 2013, 2014
2012-03-28
... 20. * * * The plumbing fixtures in all the restrooms perform a discrete and critical function in the... fixtures in the hotel building perform a discrete and critical function in the operation of the plumbing...
Quantum circuit dynamics via path integrals: Is there a classical action for discrete-time paths?
NASA Astrophysics Data System (ADS)
Penney, Mark D.; Enshan Koh, Dax; Spekkens, Robert W.
2017-07-01
It is straightforward to compute the transition amplitudes of a quantum circuit using the sum-over-paths methodology when the gates in the circuit are balanced, where a balanced gate is one for which all non-zero transition amplitudes are of equal magnitude. Here we consider the question of whether, for such circuits, the relative phases of different discrete-time paths through the configuration space can be defined in terms of a classical action, as they are for continuous-time paths. We show how to do so for certain kinds of quantum circuits, namely, Clifford circuits where the elementary systems are continuous-variable systems or discrete systems of odd-prime dimension. These types of circuit are distinguished by having phase-space representations that serve to define their classical counterparts. For discrete systems, the phase-space coordinates are also discrete variables. We show that for each gate in the generating set, one can associate a symplectomorphism on the phase-space and to each of these one can associate a generating function, defined on two copies of the configuration space. For discrete systems, the latter association is achieved using tools from algebraic geometry. Finally, we show that if the action functional for a discrete-time path through a sequence of gates is defined using the sum of the corresponding generating functions, then it yields the correct relative phases for the path-sum expression. These results are likely to be relevant for quantizing physical theories where time is fundamentally discrete, characterizing the classical limit of discrete-time quantum dynamics, and proving complexity results for quantum circuits.
NASA Technical Reports Server (NTRS)
Houbolt, John C; Kordes, Eldon E
1954-01-01
An analysis is made of the structural response to gusts of an airplane having the degrees of freedom of vertical motion and wing bending flexibility and basic parameters are established. A convenient and accurate numerical solution of the response equations is developed for the case of discrete-gust encounter, an exact solution is made for the simpler case of continuous-sinusoidal-gust encounter, and the procedure is outlined for treating the more realistic condition of continuous random atmospheric turbulence, based on the methods of generalized harmonic analysis. Correlation studies between flight and calculated results are then given to evaluate the influence of wing bending flexibility on the structural response to gusts of two twin-engine transports and one four-engine bomber. It is shown that calculated results obtained by means of a discrete-gust approach reveal the general nature of the flexibility effects and lead to qualitative correlation with flight results. In contrast, calculations by means of the continuous-turbulence approach show good quantitative correlation with flight results and indicate a much greater degree of resolution of the flexibility effects.
Infant differential behavioral responding to discrete emotions.
Walle, Eric A; Reschke, Peter J; Camras, Linda A; Campos, Joseph J
2017-10-01
Emotional communication regulates the behaviors of social partners. Research on individuals' responding to others' emotions typically compares responses to a single negative emotion compared with responses to a neutral or positive emotion. Furthermore, coding of such responses routinely measure surface level features of the behavior (e.g., approach vs. avoidance) rather than its underlying function (e.g., the goal of the approach or avoidant behavior). This investigation examined infants' responding to others' emotional displays across 5 discrete emotions: joy, sadness, fear, anger, and disgust. Specifically, 16-, 19-, and 24-month-old infants observed an adult communicate a discrete emotion toward a stimulus during a naturalistic interaction. Infants' responses were coded to capture the function of their behaviors (e.g., exploration, prosocial behavior, and security seeking). The results revealed a number of instances indicating that infants use different functional behaviors in response to discrete emotions. Differences in behaviors across emotions were clearest in the 24-month-old infants, though younger infants also demonstrated some differential use of behaviors in response to discrete emotions. This is the first comprehensive study to identify differences in how infants respond with goal-directed behaviors to discrete emotions. Additionally, the inclusion of a function-based coding scheme and interpersonal paradigms may be informative for future emotion research with children and adults. Possible developmental accounts for the observed behaviors and the benefits of coding techniques emphasizing the function of social behavior over their form are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
NASA Astrophysics Data System (ADS)
Ushio, Toshimitsu; Takai, Shigemasa
Supervisory control is a general framework of logical control of discrete event systems. A supervisor assigns a set of control-disabled controllable events based on observed events so that the controlled discrete event system generates specified languages. In conventional supervisory control, it is assumed that observed events are determined by internal events deterministically. But, this assumption does not hold in a discrete event system with sensor errors and a mobile system, where each observed event depends on not only an internal event but also a state just before the occurrence of the internal event. In this paper, we model such a discrete event system by a Mealy automaton with a nondeterministic output function. We introduce two kinds of supervisors: one assigns each control action based on a permissive policy and the other based on an anti-permissive one. We show necessary and sufficient conditions for the existence of each supervisor. Moreover, we discuss the relationship between the supervisors in the case that the output function is determinisitic.
Assessing Upper Extremity Motor Function in Practice of Virtual Activities of Daily Living
Adams, Richard J.; Lichter, Matthew D.; Krepkovich, Eileen T.; Ellington, Allison; White, Marga; Diamond, Paul T.
2015-01-01
A study was conducted to investigate the criterion validity of measures of upper extremity (UE) motor function derived during practice of virtual activities of daily living (ADLs). Fourteen hemiparetic stroke patients employed a Virtual Occupational Therapy Assistant (VOTA), consisting of a high-fidelity virtual world and a Kinect™ sensor, in four sessions of approximately one hour in duration. An Unscented Kalman Filter-based human motion tracking algorithm estimated UE joint kinematics in real-time during performance of virtual ADL activities, enabling both animation of the user’s avatar and automated generation of metrics related to speed and smoothness of motion. These metrics, aggregated over discrete sub-task elements during performance of virtual ADLs, were compared to scores from an established assessment of UE motor performance, the Wolf Motor Function Test (WMFT). Spearman’s rank correlation analysis indicates a moderate correlation between VOTA-derived metrics and the time-based WMFT assessments, supporting the criterion validity of VOTA measures as a means of tracking patient progress during an UE rehabilitation program that includes practice of virtual ADLs. PMID:25265612
Assessing upper extremity motor function in practice of virtual activities of daily living.
Adams, Richard J; Lichter, Matthew D; Krepkovich, Eileen T; Ellington, Allison; White, Marga; Diamond, Paul T
2015-03-01
A study was conducted to investigate the criterion validity of measures of upper extremity (UE) motor function derived during practice of virtual activities of daily living (ADLs). Fourteen hemiparetic stroke patients employed a Virtual Occupational Therapy Assistant (VOTA), consisting of a high-fidelity virtual world and a Kinect™ sensor, in four sessions of approximately one hour in duration. An unscented Kalman Filter-based human motion tracking algorithm estimated UE joint kinematics in real-time during performance of virtual ADL activities, enabling both animation of the user's avatar and automated generation of metrics related to speed and smoothness of motion. These metrics, aggregated over discrete sub-task elements during performance of virtual ADLs, were compared to scores from an established assessment of UE motor performance, the Wolf Motor Function Test (WMFT). Spearman's rank correlation analysis indicates a moderate correlation between VOTA-derived metrics and the time-based WMFT assessments, supporting the criterion validity of VOTA measures as a means of tracking patient progress during an UE rehabilitation program that includes practice of virtual ADLs.
Contractor, Kaiyumars B; Kenny, Laura M; Coombes, Charles R; Turkheimer, Federico E; Aboagye, Eric O; Rosso, Lula
2012-03-24
Quantification of kinetic parameters of positron emission tomography (PET) imaging agents normally requires collecting arterial blood samples which is inconvenient for patients and difficult to implement in routine clinical practice. The aim of this study was to investigate whether a population-based input function (POP-IF) reliant on only a few individual discrete samples allows accurate estimates of tumour proliferation using [18F]fluorothymidine (FLT). Thirty-six historical FLT-PET data with concurrent arterial sampling were available for this study. A population average of baseline scans blood data was constructed using leave-one-out cross-validation for each scan and used in conjunction with individual blood samples. Three limited sampling protocols were investigated including, respectively, only seven (POP-IF7), five (POP-IF5) and three (POP-IF3) discrete samples of the historical dataset. Additionally, using the three-point protocol, we derived a POP-IF3M, the only input function which was not corrected for the fraction of radiolabelled metabolites present in blood. The kinetic parameter for net FLT retention at steady state, Ki, was derived using the modified Patlak plot and compared with the original full arterial set for validation. Small percentage differences in the area under the curve between all the POP-IFs and full arterial sampling IF was found over 60 min (4.2%-5.7%), while there were, as expected, larger differences in the peak position and peak height.A high correlation between Ki values calculated using the original arterial input function and all the population-derived IFs was observed (R2 = 0.85-0.98). The population-based input showed good intra-subject reproducibility of Ki values (R2 = 0.81-0.94) and good correlation (R2 = 0.60-0.85) with Ki-67. Input functions generated using these simplified protocols over scan duration of 60 min estimate net PET-FLT retention with reasonable accuracy.
NASA Astrophysics Data System (ADS)
Ji, Songsong; Yang, Yibo; Pang, Gang; Antoine, Xavier
2018-01-01
The aim of this paper is to design some accurate artificial boundary conditions for the semi-discretized linear Schrödinger and heat equations in rectangular domains. The Laplace transform in time and discrete Fourier transform in space are applied to get Green's functions of the semi-discretized equations in unbounded domains with single-source. An algorithm is given to compute these Green's functions accurately through some recurrence relations. Furthermore, the finite-difference method is used to discretize the reduced problem with accurate boundary conditions. Numerical simulations are presented to illustrate the accuracy of our method in the case of the linear Schrödinger and heat equations. It is shown that the reflection at the corners is correctly eliminated.
A Discrete Fracture Network Model with Stress-Driven Nucleation and Growth
NASA Astrophysics Data System (ADS)
Lavoine, E.; Darcel, C.; Munier, R.; Davy, P.
2017-12-01
The realism of Discrete Fracture Network (DFN) models, beyond the bulk statistical properties, relies on the spatial organization of fractures, which is not issued by purely stochastic DFN models. The realism can be improved by injecting prior information in DFN from a better knowledge of the geological fracturing processes. We first develop a model using simple kinematic rules for mimicking the growth of fractures from nucleation to arrest, in order to evaluate the consequences of the DFN structure on the network connectivity and flow properties. The model generates fracture networks with power-law scaling distributions and a percentage of T-intersections that are consistent with field observations. Nevertheless, a larger complexity relying on the spatial variability of natural fractures positions cannot be explained by the random nucleation process. We propose to introduce a stress-driven nucleation in the timewise process of this kinematic model to study the correlations between nucleation, growth and existing fracture patterns. The method uses the stress field generated by existing fractures and remote stress as an input for a Monte-Carlo sampling of nuclei centers at each time step. Networks so generated are found to have correlations over a large range of scales, with a correlation dimension that varies with time and with the function that relates the nucleation probability to stress. A sensibility analysis of input parameters has been performed in 3D to quantify the influence of fractures and remote stress field orientations.
An integrative and functional framework for the study of animal emotion and mood
Mendl, Michael; Burman, Oliver H. P.; Paul, Elizabeth S.
2010-01-01
A better understanding of animal emotion is an important goal in disciplines ranging from neuroscience to animal welfare science. The conscious experience of emotion cannot be assessed directly, but neural, behavioural and physiological indicators of emotion can be measured. Researchers have used these measures to characterize how animals respond to situations assumed to induce discrete emotional states (e.g. fear). While advancing our understanding of specific emotions, this discrete emotion approach lacks an overarching framework that can incorporate and integrate the wide range of possible emotional states. Dimensional approaches that conceptualize emotions in terms of universal core affective characteristics (e.g. valence (positivity versus negativity) and arousal) can provide such a framework. Here, we bring together discrete and dimensional approaches to: (i) offer a structure for integrating different discrete emotions that provides a functional perspective on the adaptive value of emotional states, (ii) suggest how long-term mood states arise from short-term discrete emotions, how they also influence these discrete emotions through a bi-directional relationship and how they may function to guide decision-making, and (iii) generate novel hypothesis-driven measures of animal emotion and mood. PMID:20685706
An integrative and functional framework for the study of animal emotion and mood.
Mendl, Michael; Burman, Oliver H P; Paul, Elizabeth S
2010-10-07
A better understanding of animal emotion is an important goal in disciplines ranging from neuroscience to animal welfare science. The conscious experience of emotion cannot be assessed directly, but neural, behavioural and physiological indicators of emotion can be measured. Researchers have used these measures to characterize how animals respond to situations assumed to induce discrete emotional states (e.g. fear). While advancing our understanding of specific emotions, this discrete emotion approach lacks an overarching framework that can incorporate and integrate the wide range of possible emotional states. Dimensional approaches that conceptualize emotions in terms of universal core affective characteristics (e.g. valence (positivity versus negativity) and arousal) can provide such a framework. Here, we bring together discrete and dimensional approaches to: (i) offer a structure for integrating different discrete emotions that provides a functional perspective on the adaptive value of emotional states, (ii) suggest how long-term mood states arise from short-term discrete emotions, how they also influence these discrete emotions through a bi-directional relationship and how they may function to guide decision-making, and (iii) generate novel hypothesis-driven measures of animal emotion and mood.
Universal scaling function in discrete time asymmetric exclusion processes
NASA Astrophysics Data System (ADS)
Chia, Nicholas; Bundschuh, Ralf
2005-03-01
In the universality class of the one dimensional Kardar-Parisi-Zhang surface growth, Derrida and Lebowitz conjectured the universality of not only the scaling exponents, but of an entire scaling function. Since Derrida and Lebowitz' original publication this universality has been verified for a variety of continuous time systems in the KPZ universality class. We study the Derrida-Lebowitz scaling function for multi-particle versions of the discrete time Asymmetric Exclusion Process. We find that in this discrete time system the Derrida-Lebowitz scaling function not only properly characterizes the large system size limit, but even accurately describes surprisingly small systems. These results have immediate applications in searching biological sequence databases.
NASA Astrophysics Data System (ADS)
Darcel, C.; Davy, P.; Le Goc, R.; Maillot, J.; Selroos, J. O.
2017-12-01
We present progress on Discrete Fracture Network (DFN) flow modeling, including realistic advanced DFN spatial structures and local fracture transmissivity properties, through an application to the Forsmark site in Sweden. DFN models are a framework to combine fracture datasets from different sources and scales and to interpolate them in combining statistical distributions and stereological relations. The resulting DFN upscaling function - size density distribution - is a model component key to extrapolating fracture size densities between data gaps, from borehole core up to site scale. Another important feature of DFN models lays in the spatial correlations between fractures, with still unevaluated consequences on flow predictions. Indeed, although common Poisson (i.e. spatially random) models are widely used, they do not reflect these geological evidences for more complex structures. To model them, we define a DFN growth process from kinematic rules for nucleation, growth and stopping conditions. It mimics in a simplified way the geological fracturing processes and produces DFN characteristics -both upscaling function and spatial correlations- fully consistent with field observations. DFN structures are first compared for constant transmissivities. Flow simulations for the kinematic and equivalent Poisson DFN models show striking differences: with the kinematic DFN, connectivity and permeability are significantly smaller, down to a difference of one order of magnitude, and flow is much more channelized. Further flow analyses are performed with more realistic transmissivity distribution conditions (sealed parts, relations to fracture sizes, orientations and in-situ stress field). The relative importance of the overall DFN structure in the final flow predictions is discussed.
Wu, Xiang; He, Sheng; Bushara, Khalaf; Zeng, Feiyan; Liu, Ying; Zhang, Daren
2012-10-01
Object recognition occurs even when environmental information is incomplete. Illusory contours (ICs), in which a contour is perceived though the contour edges are incomplete, have been extensively studied as an example of such a visual completion phenomenon. Despite the neural activity in response to ICs in visual cortical areas from low (V1 and V2) to high (LOC: the lateral occipital cortex) levels, the details of the neural processing underlying IC perception are largely not clarified. For example, how do the visual areas function in IC perception and how do they interact to archive the coherent contour perception? IC perception involves the process of completing the local discrete contour edges (contour completion) and the process of representing the global completed contour information (contour representation). Here, functional magnetic resonance imaging was used to dissociate contour completion and contour representation by varying each in opposite directions. The results show that the neural activity was stronger to stimuli with more contour completion than to stimuli with more contour representation in V1 and V2, which was the reverse of that in the LOC. When inspecting the neural activity change across the visual pathway, the activation remained high for the stimuli with more contour completion and increased for the stimuli with more contour representation. These results suggest distinct neural correlates of contour completion and contour representation, and the possible collaboration between the two processes during IC perception, indicating a neural connection between the discrete retinal input and the coherent visual percept. Copyright © 2011 Wiley Periodicals, Inc.
A study of discrete control signal fault conditions in the shuttle DPS
NASA Technical Reports Server (NTRS)
Reddi, S. S.; Retter, C. T.
1976-01-01
An analysis of the effects of discrete failures on the data processing subsystem is presented. A functional description of each discrete together with a list of software modules that use this discrete are included. A qualitative description of the consequences that may ensue due to discrete failures is given followed by a probabilistic reliability analysis of the data processing subsystem. Based on the investigation conducted, recommendations were made to improve the reliability of the subsystem.
Structure and Kinematics of the BLR: What We have Learned and Where We Are
NASA Astrophysics Data System (ADS)
Gaskell, C. Martin
What has been learned from variability studies of the BLR is reviewded. The majority of our knowledge has ceom from determining only the first moment of the transfer function (the "lag"). Details of the method most widely used for determining the first moment, i.e., the partial interpolation cross correlation function (PICCF) method, are discussed. The much higher efficiency of the PICCF method compared to the discrete correlation function (DCF) method is emphasized. Recovering much beyond the first moment of the transfer function is difficult, and a plateau seems to ahve been reached in what we can learn from our present style of monitoring campaign. Directions are suggested for future observing campaigns. Obtaining simultaneous X-ray light curves is very important. Quasars with unusual double-peaked emission lines vlearly need ot be understoo as do ones with strong optical Fe II emission. Theoretical problems mentioned include (1) the reconciliation of the apparent lack of radial outflow with the blueshifting of high-ionization lines, (2) the role of electron scattering, and (3) the small apparent sizes seen in 3C 273 and some high-luminosity quasars. Continuum anisotropy offers a natural solution to the last problem.
Applying Multivariate Discrete Distributions to Genetically Informative Count Data.
Kirkpatrick, Robert M; Neale, Michael C
2016-03-01
We present a novel method of conducting biometric analysis of twin data when the phenotypes are integer-valued counts, which often show an L-shaped distribution. Monte Carlo simulation is used to compare five likelihood-based approaches to modeling: our multivariate discrete method, when its distributional assumptions are correct, when they are incorrect, and three other methods in common use. With data simulated from a skewed discrete distribution, recovery of twin correlations and proportions of additive genetic and common environment variance was generally poor for the Normal, Lognormal and Ordinal models, but good for the two discrete models. Sex-separate applications to substance-use data from twins in the Minnesota Twin Family Study showed superior performance of two discrete models. The new methods are implemented using R and OpenMx and are freely available.
Spectral simplicity of apparent complexity. II. Exact complexities and complexity spectra
NASA Astrophysics Data System (ADS)
Riechers, Paul M.; Crutchfield, James P.
2018-03-01
The meromorphic functional calculus developed in Part I overcomes the nondiagonalizability of linear operators that arises often in the temporal evolution of complex systems and is generic to the metadynamics of predicting their behavior. Using the resulting spectral decomposition, we derive closed-form expressions for correlation functions, finite-length Shannon entropy-rate approximates, asymptotic entropy rate, excess entropy, transient information, transient and asymptotic state uncertainties, and synchronization information of stochastic processes generated by finite-state hidden Markov models. This introduces analytical tractability to investigating information processing in discrete-event stochastic processes, symbolic dynamics, and chaotic dynamical systems. Comparisons reveal mathematical similarities between complexity measures originally thought to capture distinct informational and computational properties. We also introduce a new kind of spectral analysis via coronal spectrograms and the frequency-dependent spectra of past-future mutual information. We analyze a number of examples to illustrate the methods, emphasizing processes with multivariate dependencies beyond pairwise correlation. This includes spectral decomposition calculations for one representative example in full detail.
Grupe, D W; Wielgosz, J; Davidson, R J; Nitschke, J B
2016-07-01
Previous research in post-traumatic stress disorder (PTSD) has identified disrupted ventromedial prefrontal cortex (vmPFC) function in those with v. without PTSD. It is unclear whether this brain region is uniformly affected in all individuals with PTSD, or whether vmPFC dysfunction is related to individual differences in discrete features of this heterogeneous disorder. In a sample of 51 male veterans of Operation Enduring Freedom/Operation Iraqi Freedom, we collected functional magnetic resonance imaging data during a novel threat anticipation task with crossed factors of threat condition and temporal unpredictability. Voxelwise regression analyses related anticipatory brain activation to individual differences in overall PTSD symptom severity, as well as individual differences in discrete symptom subscales (re-experiencing, emotional numbing/avoidance, and hyperarousal). The vmPFC showed greater anticipatory responses for safety relative to threat, driven primarily by deactivation during threat anticipation. During unpredictable threat anticipation, increased PTSD symptoms were associated with relatively greater activation for threat v. However, simultaneous regression on individual symptom subscales demonstrated that this effect was driven specifically by individual differences in hyperarousal symptoms. Furthermore, this analysis revealed an additional, anatomically distinct region of the vmPFC in which re-experiencing symptoms were associated with greater activation during threat anticipation. Increased anticipatory responses to unpredictable threat in distinct vmPFC subregions were uniquely associated with elevated hyperarousal and re-experiencing symptoms in combat veterans. These results underscore the disruptive impact of uncertainty for veterans, and suggest that investigating individual differences in discrete aspects of PTSD may advance our understanding of underlying neurobiological mechanisms.
Langevin dynamics for vector variables driven by multiplicative white noise: A functional formalism
NASA Astrophysics Data System (ADS)
Moreno, Miguel Vera; Arenas, Zochil González; Barci, Daniel G.
2015-04-01
We discuss general multidimensional stochastic processes driven by a system of Langevin equations with multiplicative white noise. In particular, we address the problem of how time reversal diffusion processes are affected by the variety of conventions available to deal with stochastic integrals. We present a functional formalism to build up the generating functional of correlation functions without any type of discretization of the Langevin equations at any intermediate step. The generating functional is characterized by a functional integration over two sets of commuting variables, as well as Grassmann variables. In this representation, time reversal transformation became a linear transformation in the extended variables, simplifying in this way the complexity introduced by the mixture of prescriptions and the associated calculus rules. The stochastic calculus is codified in our formalism in the structure of the Grassmann algebra. We study some examples such as higher order derivative Langevin equations and the functional representation of the micromagnetic stochastic Landau-Lifshitz-Gilbert equation.
Segmentation of discrete vector fields.
Li, Hongyu; Chen, Wenbin; Shen, I-Fan
2006-01-01
In this paper, we propose an approach for 2D discrete vector field segmentation based on the Green function and normalized cut. The method is inspired by discrete Hodge Decomposition such that a discrete vector field can be broken down into three simpler components, namely, curl-free, divergence-free, and harmonic components. We show that the Green Function Method (GFM) can be used to approximate the curl-free and the divergence-free components to achieve our goal of the vector field segmentation. The final segmentation curves that represent the boundaries of the influence region of singularities are obtained from the optimal vector field segmentations. These curves are composed of piecewise smooth contours or streamlines. Our method is applicable to both linear and nonlinear discrete vector fields. Experiments show that the segmentations obtained using our approach essentially agree with human perceptual judgement.
2000-11-01
Discrete Math . 115, 141-152. [7] Edmonds J., Giles R. (1977) A Min-Max relation for submodular functions on graphs, Annals of Discrete Math . 1, 185...projective planes, handwritten man- uscript, published: (1990) Polyhedral Combinatorics (W. Cook, P.D. Seymour eds.), DIMACS Series in Discrete Math . and...Theoretical Computer Science 1, 101-105. [11] Lovasz L. (1972) Normal hypergraphs and the perfect graph conjecture, Discrete Math . 2, 253-267. [12
Discrete linear canonical transforms based on dilated Hermite functions.
Pei, Soo-Chang; Lai, Yun-Chiu
2011-08-01
Linear canonical transform (LCT) is very useful and powerful in signal processing and optics. In this paper, discrete LCT (DLCT) is proposed to approximate LCT by utilizing the discrete dilated Hermite functions. The Wigner distribution function is also used to investigate DLCT performances in the time-frequency domain. Compared with the existing digital computation of LCT, our proposed DLCT possess additivity and reversibility properties with no oversampling involved. In addition, the length of input/output signals will not be changed before and after the DLCT transformations, which is consistent with the time-frequency area-preserving nature of LCT; meanwhile, the proposed DLCT has very good approximation of continuous LCT.
Discrete shaped strain sensors for intelligent structures
NASA Technical Reports Server (NTRS)
Andersson, Mark S.; Crawley, Edward F.
1992-01-01
Design of discrete, highly distributed sensor systems for intelligent structures has been studied. Data obtained indicate that discrete strain-averaging sensors satisfy the functional requirements for distributed sensing of intelligent structures. Bartlett and Gauss-Hanning sensors, in particular, provide good wavenumber characteristics while meeting the functional requirements. They are characterized by good rolloff rates and positive Fourier transforms for all wavenumbers. For the numerical integration schemes, Simpson's rule is considered to be very simple to implement and consistently provides accurate results for five sensors or more. It is shown that a sensor system that satisfies the functional requirements can be applied to a structure that supports mode shapes with purely sinusoidal curvature.
Linear diffusion-wave channel routing using a discrete Hayami convolution method
Li Wang; Joan Q. Wu; William J. Elliot; Fritz R. Feidler; Sergey Lapin
2014-01-01
The convolution of an input with a response function has been widely used in hydrology as a means to solve various problems analytically. Due to the high computation demand in solving the functions using numerical integration, it is often advantageous to use the discrete convolution instead of the integration of the continuous functions. This approach greatly reduces...
The Relation of Finite Element and Finite Difference Methods
NASA Technical Reports Server (NTRS)
Vinokur, M.
1976-01-01
Finite element and finite difference methods are examined in order to bring out their relationship. It is shown that both methods use two types of discrete representations of continuous functions. They differ in that finite difference methods emphasize the discretization of independent variable, while finite element methods emphasize the discretization of dependent variable (referred to as functional approximations). An important point is that finite element methods use global piecewise functional approximations, while finite difference methods normally use local functional approximations. A general conclusion is that finite element methods are best designed to handle complex boundaries, while finite difference methods are superior for complex equations. It is also shown that finite volume difference methods possess many of the advantages attributed to finite element methods.
Computational complexity of Boolean functions
NASA Astrophysics Data System (ADS)
Korshunov, Aleksei D.
2012-02-01
Boolean functions are among the fundamental objects of discrete mathematics, especially in those of its subdisciplines which fall under mathematical logic and mathematical cybernetics. The language of Boolean functions is convenient for describing the operation of many discrete systems such as contact networks, Boolean circuits, branching programs, and some others. An important parameter of discrete systems of this kind is their complexity. This characteristic has been actively investigated starting from Shannon's works. There is a large body of scientific literature presenting many fundamental results. The purpose of this survey is to give an account of the main results over the last sixty years related to the complexity of computation (realization) of Boolean functions by contact networks, Boolean circuits, and Boolean circuits without branching. Bibliography: 165 titles.
Power-law Exponent in Multiplicative Langevin Equation with Temporally Correlated Noise
NASA Astrophysics Data System (ADS)
Morita, Satoru
2018-05-01
Power-law distributions are ubiquitous in nature. Random multiplicative processes are a basic model for the generation of power-law distributions. For discrete-time systems, the power-law exponent is known to decrease as the autocorrelation time of the multiplier increases. However, for continuous-time systems, it is not yet clear how the temporal correlation affects the power-law behavior. Herein, we analytically investigated a multiplicative Langevin equation with colored noise. We show that the power-law exponent depends on the details of the multiplicative noise, in contrast to the case of discrete-time systems.
Discrete sonic jets used as boundary-layer trips at Mach numbers of 6 and 8.5
NASA Technical Reports Server (NTRS)
Stone, D. R.; Cary, A. M., Jr.
1972-01-01
The effect of discrete three-dimensional sonic jets used to promote transition on a sharp-leading-edge flat plate at Mach numbers of 6 and 8.5 and unit Reynolds numbers as high as 2.5 x 100,000 per cm in the Langley 20-inch hypersonic tunnels is discussed. An examination of the downstream flow-field distortions associated with the discrete jets for the Mach 8.5 flow was also conducted. Jet trips are found to produce lengths of turbulent flow comparable to those obtained for spherical-roughness-element trips while significantly reducing the downstream flow distortions. A Reynolds number based upon secondary jet penetration into a supersonic main flow is used to correlate jet-trip effectiveness just as a Reynolds number based upon roughness height is used to correlate spherical-trip effectiveness. Measured heat-transfer data are in agreement with the predictions.
Federal Register 2010, 2011, 2012, 2013, 2014
2013-07-25
... bear no direct correlation to military-specific applications in accordance with the stated intention... logical correlation to the way that discrete microwave transistors and MMIC technologies actually work...
A priori discretization error metrics for distributed hydrologic modeling applications
NASA Astrophysics Data System (ADS)
Liu, Hongli; Tolson, Bryan A.; Craig, James R.; Shafii, Mahyar
2016-12-01
Watershed spatial discretization is an important step in developing a distributed hydrologic model. A key difficulty in the spatial discretization process is maintaining a balance between the aggregation-induced information loss and the increase in computational burden caused by the inclusion of additional computational units. Objective identification of an appropriate discretization scheme still remains a challenge, in part because of the lack of quantitative measures for assessing discretization quality, particularly prior to simulation. This study proposes a priori discretization error metrics to quantify the information loss of any candidate discretization scheme without having to run and calibrate a hydrologic model. These error metrics are applicable to multi-variable and multi-site discretization evaluation and provide directly interpretable information to the hydrologic modeler about discretization quality. The first metric, a subbasin error metric, quantifies the routing information loss from discretization, and the second, a hydrological response unit (HRU) error metric, improves upon existing a priori metrics by quantifying the information loss due to changes in land cover or soil type property aggregation. The metrics are straightforward to understand and easy to recode. Informed by the error metrics, a two-step discretization decision-making approach is proposed with the advantage of reducing extreme errors and meeting the user-specified discretization error targets. The metrics and decision-making approach are applied to the discretization of the Grand River watershed in Ontario, Canada. Results show that information loss increases as discretization gets coarser. Moreover, results help to explain the modeling difficulties associated with smaller upstream subbasins since the worst discretization errors and highest error variability appear in smaller upstream areas instead of larger downstream drainage areas. Hydrologic modeling experiments under candidate discretization schemes validate the strong correlation between the proposed discretization error metrics and hydrologic simulation responses. Discretization decision-making results show that the common and convenient approach of making uniform discretization decisions across the watershed performs worse than the proposed non-uniform discretization approach in terms of preserving spatial heterogeneity under the same computational cost.
Fast and Accurate Learning When Making Discrete Numerical Estimates.
Sanborn, Adam N; Beierholm, Ulrik R
2016-04-01
Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates.
Fast and Accurate Learning When Making Discrete Numerical Estimates
Sanborn, Adam N.; Beierholm, Ulrik R.
2016-01-01
Many everyday estimation tasks have an inherently discrete nature, whether the task is counting objects (e.g., a number of paint buckets) or estimating discretized continuous variables (e.g., the number of paint buckets needed to paint a room). While Bayesian inference is often used for modeling estimates made along continuous scales, discrete numerical estimates have not received as much attention, despite their common everyday occurrence. Using two tasks, a numerosity task and an area estimation task, we invoke Bayesian decision theory to characterize how people learn discrete numerical distributions and make numerical estimates. Across three experiments with novel stimulus distributions we found that participants fell between two common decision functions for converting their uncertain representation into a response: drawing a sample from their posterior distribution and taking the maximum of their posterior distribution. While this was consistent with the decision function found in previous work using continuous estimation tasks, surprisingly the prior distributions learned by participants in our experiments were much more adaptive: When making continuous estimates, participants have required thousands of trials to learn bimodal priors, but in our tasks participants learned discrete bimodal and even discrete quadrimodal priors within a few hundred trials. This makes discrete numerical estimation tasks good testbeds for investigating how people learn and make estimates. PMID:27070155
Current Density and Continuity in Discretized Models
ERIC Educational Resources Information Center
Boykin, Timothy B.; Luisier, Mathieu; Klimeck, Gerhard
2010-01-01
Discrete approaches have long been used in numerical modelling of physical systems in both research and teaching. Discrete versions of the Schrodinger equation employing either one or several basis functions per mesh point are often used by senior undergraduates and beginning graduate students in computational physics projects. In studying…
Discrete-to-continuous transition in quantum phase estimation
NASA Astrophysics Data System (ADS)
Rządkowski, Wojciech; Demkowicz-Dobrzański, Rafał
2017-09-01
We analyze the problem of quantum phase estimation in which the set of allowed phases forms a discrete N -element subset of the whole [0 ,2 π ] interval, φn=2 π n /N , n =0 ,⋯,N -1 , and study the discrete-to-continuous transition N →∞ for various cost functions as well as the mutual information. We also analyze the relation between the problems of phase discrimination and estimation by considering a step cost function of a given width σ around the true estimated value. We show that in general a direct application of the theory of covariant measurements for a discrete subgroup of the U(1 ) group leads to suboptimal strategies due to an implicit requirement of estimating only the phases that appear in the prior distribution. We develop the theory of subcovariant measurements to remedy this situation and demonstrate truly optimal estimation strategies when performing a transition from discrete to continuous phase estimation.
Implementation of quantum and classical discrete fractional Fourier transforms.
Weimann, Steffen; Perez-Leija, Armando; Lebugle, Maxime; Keil, Robert; Tichy, Malte; Gräfe, Markus; Heilmann, René; Nolte, Stefan; Moya-Cessa, Hector; Weihs, Gregor; Christodoulides, Demetrios N; Szameit, Alexander
2016-03-23
Fourier transforms, integer and fractional, are ubiquitous mathematical tools in basic and applied science. Certainly, since the ordinary Fourier transform is merely a particular case of a continuous set of fractional Fourier domains, every property and application of the ordinary Fourier transform becomes a special case of the fractional Fourier transform. Despite the great practical importance of the discrete Fourier transform, implementation of fractional orders of the corresponding discrete operation has been elusive. Here we report classical and quantum optical realizations of the discrete fractional Fourier transform. In the context of classical optics, we implement discrete fractional Fourier transforms of exemplary wave functions and experimentally demonstrate the shift theorem. Moreover, we apply this approach in the quantum realm to Fourier transform separable and path-entangled biphoton wave functions. The proposed approach is versatile and could find applications in various fields where Fourier transforms are essential tools.
NASA Technical Reports Server (NTRS)
Nielsen, Eric J.; Kleb, William L.
2005-01-01
A methodology is developed and implemented to mitigate the lengthy software development cycle typically associated with constructing a discrete adjoint solver for aerodynamic simulations. The approach is based on a complex-variable formulation that enables straightforward differentiation of complicated real-valued functions. An automated scripting process is used to create the complex-variable form of the set of discrete equations. An efficient method for assembling the residual and cost function linearizations is developed. The accuracy of the implementation is verified through comparisons with a discrete direct method as well as a previously developed handcoded discrete adjoint approach. Comparisons are also shown for a large-scale configuration to establish the computational efficiency of the present scheme. To ultimately demonstrate the power of the approach, the implementation is extended to high temperature gas flows in chemical nonequilibrium. Finally, several fruitful research and development avenues enabled by the current work are suggested.
Efficient Construction of Discrete Adjoint Operators on Unstructured Grids Using Complex Variables
NASA Technical Reports Server (NTRS)
Nielsen, Eric J.; Kleb, William L.
2005-01-01
A methodology is developed and implemented to mitigate the lengthy software development cycle typically associated with constructing a discrete adjoint solver for aerodynamic simulations. The approach is based on a complex-variable formulation that enables straightforward differentiation of complicated real-valued functions. An automated scripting process is used to create the complex-variable form of the set of discrete equations. An efficient method for assembling the residual and cost function linearizations is developed. The accuracy of the implementation is verified through comparisons with a discrete direct method as well as a previously developed handcoded discrete adjoint approach. Comparisons are also shown for a large-scale configuration to establish the computational efficiency of the present scheme. To ultimately demonstrate the power of the approach, the implementation is extended to high temperature gas flows in chemical nonequilibrium. Finally, several fruitful research and development avenues enabled by the current work are suggested.
Implementation of quantum and classical discrete fractional Fourier transforms
Weimann, Steffen; Perez-Leija, Armando; Lebugle, Maxime; Keil, Robert; Tichy, Malte; Gräfe, Markus; Heilmann, René; Nolte, Stefan; Moya-Cessa, Hector; Weihs, Gregor; Christodoulides, Demetrios N.; Szameit, Alexander
2016-01-01
Fourier transforms, integer and fractional, are ubiquitous mathematical tools in basic and applied science. Certainly, since the ordinary Fourier transform is merely a particular case of a continuous set of fractional Fourier domains, every property and application of the ordinary Fourier transform becomes a special case of the fractional Fourier transform. Despite the great practical importance of the discrete Fourier transform, implementation of fractional orders of the corresponding discrete operation has been elusive. Here we report classical and quantum optical realizations of the discrete fractional Fourier transform. In the context of classical optics, we implement discrete fractional Fourier transforms of exemplary wave functions and experimentally demonstrate the shift theorem. Moreover, we apply this approach in the quantum realm to Fourier transform separable and path-entangled biphoton wave functions. The proposed approach is versatile and could find applications in various fields where Fourier transforms are essential tools. PMID:27006089
Chord-length and free-path distribution functions for many-body systems
NASA Astrophysics Data System (ADS)
Lu, Binglin; Torquato, S.
1993-04-01
We study fundamental morphological descriptors of disordered media (e.g., heterogeneous materials, liquids, and amorphous solids): the chord-length distribution function p(z) and the free-path distribution function p(z,a). For concreteness, we will speak in the language of heterogeneous materials composed of two different materials or ``phases.'' The probability density function p(z) describes the distribution of chord lengths in the sample and is of great interest in stereology. For example, the first moment of p(z) is the ``mean intercept length'' or ``mean chord length.'' The chord-length distribution function is of importance in transport phenomena and problems involving ``discrete free paths'' of point particles (e.g., Knudsen diffusion and radiative transport). The free-path distribution function p(z,a) takes into account the finite size of a simple particle of radius a undergoing discrete free-path motion in the heterogeneous material and we show that it is actually the chord-length distribution function for the system in which the ``pore space'' is the space available to a finite-sized particle of radius a. Thus it is shown that p(z)=p(z,0). We demonstrate that the functions p(z) and p(z,a) are related to another fundamentally important morphological descriptor of disordered media, namely, the so-called lineal-path function L(z) studied by us in previous work [Phys. Rev. A 45, 922 (1992)]. The lineal path function gives the probability of finding a line segment of length z wholly in one of the ``phases'' when randomly thrown into the sample. We derive exact series representations of the chord-length and free-path distribution functions for systems of spheres with a polydispersivity in size in arbitrary dimension D. For the special case of spatially uncorrelated spheres (i.e., fully penetrable spheres) we evaluate exactly the aforementioned functions, the mean chord length, and the mean free path. We also obtain corresponding analytical formulas for the case of mutually impenetrable (i.e., spatially correlated) polydispersed spheres.
Sliding mode control-based linear functional observers for discrete-time stochastic systems
NASA Astrophysics Data System (ADS)
Singh, Satnesh; Janardhanan, Sivaramakrishnan
2017-11-01
Sliding mode control (SMC) is one of the most popular techniques to stabilise linear discrete-time stochastic systems. However, application of SMC becomes difficult when the system states are not available for feedback. This paper presents a new approach to design a SMC-based functional observer for discrete-time stochastic systems. The functional observer is based on the Kronecker product approach. Existence conditions and stability analysis of the proposed observer are given. The control input is estimated by a novel linear functional observer. This approach leads to a non-switching type of control, thereby eliminating the fundamental cause of chatter. Furthermore, the functional observer is designed in such a way that the effect of process and measurement noise is minimised. Simulation example is given to illustrate and validate the proposed design method.
Discrete ellipsoidal statistical BGK model and Burnett equations
NASA Astrophysics Data System (ADS)
Zhang, Yu-Dong; Xu, Ai-Guo; Zhang, Guang-Cai; Chen, Zhi-Hua; Wang, Pei
2018-06-01
A new discrete Boltzmann model, the discrete ellipsoidal statistical Bhatnagar-Gross-Krook (ESBGK) model, is proposed to simulate nonequilibrium compressible flows. Compared with the original discrete BGK model, the discrete ES-BGK has a flexible Prandtl number. For the discrete ES-BGK model in the Burnett level, two kinds of discrete velocity model are introduced and the relations between nonequilibrium quantities and the viscous stress and heat flux in the Burnett level are established. The model is verified via four benchmark tests. In addition, a new idea is introduced to recover the actual distribution function through the macroscopic quantities and their space derivatives. The recovery scheme works not only for discrete Boltzmann simulation but also for hydrodynamic ones, for example, those based on the Navier-Stokes or the Burnett equations.
A Domain-Specific Language for Discrete Mathematics
NASA Astrophysics Data System (ADS)
Jha, Rohit; Samuel, Alfy; Pawar, Ashmee; Kiruthika, M.
2013-05-01
This paper discusses a Domain Specific Language (DSL) that has been developed to enable implementation of concepts of discrete mathematics. A library of data types and functions provides functionality which is frequently required by users. Covering the areas of Mathematical Logic, Set Theory, Functions, Graph Theory, Number Theory, Linear Algebra and Combinatorics, the language's syntax is close to the actual notation used in the specific fields.
New method for identifying features of an image on a digital video display
NASA Astrophysics Data System (ADS)
Doyle, Michael D.
1991-04-01
The MetaMap process extends the concept of direct manipulation human-computer interfaces to new limits. Its specific capabilities include the correlation of discrete image elements to relevant text information and the correlation of these image features to other images as well as to program control mechanisms. The correlation is accomplished through reprogramming of both the color map and the image so that discrete image elements comprise unique sets of color indices. This process allows the correlation to be accomplished with very efficient data storage and program execution times. Image databases adapted to this process become object-oriented as a result. Very sophisticated interrelationships can be set up between images text and program control mechanisms using this process. An application of this interfacing process to the design of an interactive atlas of medical histology as well as other possible applications are described. The MetaMap process is protected by U. S. patent #4
Hybrid Discrete-Continuous Markov Decision Processes
NASA Technical Reports Server (NTRS)
Feng, Zhengzhu; Dearden, Richard; Meuleau, Nicholas; Washington, Rich
2003-01-01
This paper proposes a Markov decision process (MDP) model that features both discrete and continuous state variables. We extend previous work by Boyan and Littman on the mono-dimensional time-dependent MDP to multiple dimensions. We present the principle of lazy discretization, and piecewise constant and linear approximations of the model. Having to deal with several continuous dimensions raises several new problems that require new solutions. In the (piecewise) linear case, we use techniques from partially- observable MDPs (POMDPS) to represent value functions as sets of linear functions attached to different partitions of the state space.
Parametric instability of spinning elastic rings excited by fluctuating space-fixed stiffnesses
NASA Astrophysics Data System (ADS)
Liu, Chunguang; Cooley, Christopher G.; Parker, Robert G.
2017-07-01
This study investigates the vibration of rotating elastic rings that are dynamically excited by an arbitrary number of space-fixed discrete stiffnesses with periodically fluctuating stiffnesses. The rotating, elastic ring is modeled using thin-ring theory with radial and tangential deformations. Primary and combination instability regions are determined in closed-form using the method of multiple scales. The ratio of peak-to-peak fluctuation to average discrete stiffness is used as the perturbation parameter, so the resulting perturbation analysis is not limited to small mean values of discrete stiffnesses. The natural frequencies and vibration modes are determined by discretizing the governing equations using Galerkin's method. Results are demonstrated for compliant gear applications. The perturbation results are validated by direct numerical integration of the equations of motion and Floquet theory. The bandwidths of the instability regions correlate with the fractional strain energy stored in the discrete stiffnesses. For rings with multiple discrete stiffnesses, the phase differences between them can eliminate large amplitude response under certain conditions.
The discrete adjoint method for parameter identification in multibody system dynamics.
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.
Height growth of solutions and a discrete Painlevé equation
NASA Astrophysics Data System (ADS)
Al-Ghassani, A.; Halburd, R. G.
2015-07-01
Consider the discrete equation where the right side is of degree two in yn and where the coefficients an, bn and cn are rational functions of n with rational coefficients. Suppose that there is a solution such that for all sufficiently large n, y_n\\in{Q} and the height of yn dominates the height of the coefficient functions an, bn and cn. We show that if the logarithmic height of yn grows no faster than a power of n then either the equation is a well known discrete Painlevé equation dPII or its autonomous version or yn is also an admissible solution of a discrete Riccati equation. This provides further evidence that slow height growth is a good detector of integrability.
Autonomous learning by simple dynamical systems with a discrete-time formulation
NASA Astrophysics Data System (ADS)
Bilen, Agustín M.; Kaluza, Pablo
2017-05-01
We present a discrete-time formulation for the autonomous learning conjecture. The main feature of this formulation is the possibility to apply the autonomous learning scheme to systems in which the errors with respect to target functions are not well-defined for all times. This restriction for the evaluation of functionality is a typical feature in systems that need a finite time interval to process a unit piece of information. We illustrate its application on an artificial neural network with feed-forward architecture for classification and a phase oscillator system with synchronization properties. The main characteristics of the discrete-time formulation are shown by constructing these systems with predefined functions.
Bifurcations in a discrete time model composed of Beverton-Holt function and Ricker function.
Shang, Jin; Li, Bingtuan; Barnard, Michael R
2015-05-01
We provide rigorous analysis for a discrete-time model composed of the Ricker function and Beverton-Holt function. This model was proposed by Lewis and Li [Bull. Math. Biol. 74 (2012) 2383-2402] in the study of a population in which reproduction occurs at a discrete instant of time whereas death and competition take place continuously during the season. We show analytically that there exists a period-doubling bifurcation curve in the model. The bifurcation curve divides the parameter space into the region of stability and the region of instability. We demonstrate through numerical bifurcation diagrams that the regions of periodic cycles are intermixed with the regions of chaos. We also study the global stability of the model. Copyright © 2015 Elsevier Inc. All rights reserved.
Yu, Fajun
2015-03-01
We present the nonautonomous discrete bright soliton solutions and their interactions in the discrete Ablowitz-Ladik (DAL) equation with variable coefficients, which possesses complicated wave propagation in time and differs from the usual bright soliton waves. The differential-difference similarity transformation allows us to relate the discrete bright soliton solutions of the inhomogeneous DAL equation to the solutions of the homogeneous DAL equation. Propagation and interaction behaviors of the nonautonomous discrete solitons are analyzed through the one- and two-soliton solutions. We study the discrete snaking behaviors, parabolic behaviors, and interaction behaviors of the discrete solitons. In addition, the interaction management with free functions and dynamic behaviors of these solutions is investigated analytically, which have certain applications in electrical and optical systems.
Stability of radiomic features in CT perfusion maps
NASA Astrophysics Data System (ADS)
Bogowicz, M.; Riesterer, O.; Bundschuh, R. A.; Veit-Haibach, P.; Hüllner, M.; Studer, G.; Stieb, S.; Glatz, S.; Pruschy, M.; Guckenberger, M.; Tanadini-Lang, S.
2016-12-01
This study aimed to identify a set of stable radiomic parameters in CT perfusion (CTP) maps with respect to CTP calculation factors and image discretization, as an input for future prognostic models for local tumor response to chemo-radiotherapy. Pre-treatment CTP images of eleven patients with oropharyngeal carcinoma and eleven patients with non-small cell lung cancer (NSCLC) were analyzed. 315 radiomic parameters were studied per perfusion map (blood volume, blood flow and mean transit time). Radiomics robustness was investigated regarding the potentially standardizable (image discretization method, Hounsfield unit (HU) threshold, voxel size and temporal resolution) and non-standardizable (artery contouring and noise threshold) perfusion calculation factors using the intraclass correlation (ICC). To gain added value for our model radiomic parameters correlated with tumor volume, a well-known predictive factor for local tumor response to chemo-radiotherapy, were excluded from the analysis. The remaining stable radiomic parameters were grouped according to inter-parameter Spearman correlations and for each group the parameter with the highest ICC was included in the final set. The acceptance level was 0.9 and 0.7 for the ICC and correlation, respectively. The image discretization method using fixed number of bins or fixed intervals gave a similar number of stable radiomic parameters (around 40%). The potentially standardizable factors introduced more variability into radiomic parameters than the non-standardizable ones with 56-98% and 43-58% instability rates, respectively. The highest variability was observed for voxel size (instability rate >97% for both patient cohorts). Without standardization of CTP calculation factors none of the studied radiomic parameters were stable. After standardization with respect to non-standardizable factors ten radiomic parameters were stable for both patient cohorts after correction for inter-parameter correlations. Voxel size, image discretization, HU threshold and temporal resolution have to be standardized to build a reliable predictive model based on CTP radiomics analysis.
K. R. Sherrill; M. A. Lefsky; J. B. Bradford; M. G. Ryan
2008-01-01
This study evaluates the relative ability of simple light detection and ranging (lidar) indices (i.e., mean and maximum heights) and statistically derived canonical correlation analysis (CCA) variables attained from discrete-return lidar to estimate forest structure and forest biomass variables for three temperate subalpine forest sites. Both lidar and CCA explanatory...
What Discrete and Serial Rapid Automatized Naming Can Reveal about Reading
ERIC Educational Resources Information Center
de Jong, Peter F.
2011-01-01
Serial rapid automized naming (RAN) has been often found to correlate more strongly with reading than discrete RAN. This study aimed to demonstrate that the strength of the RAN-reading fluency relationship is dependent on the format of both RAN and the reading task if the reading task consists of sight words. Seventy-one first-grade, 74…
ERIC Educational Resources Information Center
Lench, Heather C.; Flores, Sarah A.; Bench, Shane W.
2011-01-01
Our purpose in the present meta-analysis was to examine the extent to which discrete emotions elicit changes in cognition, judgment, experience, behavior, and physiology; whether these changes are correlated as would be expected if emotions organize responses across these systems; and which factors moderate the magnitude of these effects. Studies…
K.R. Sherrill; M.A. Lefsky; J.B. Bradford; M.G. Ryan
2008-01-01
This study evaluates the relative ability of simple light detection and ranging (lidar) indices (i.e., mean and maximum heights) and statistically derived canonical correlation analysis (CCA) variables attained from discrete-return lidar to estimate forest structure and forest biomass variables for three temperate subalpine forest sites. Both lidar and CCA explanatory...
Teach Children with Autism with the Discrete-Trial Approach.
ERIC Educational Resources Information Center
Din, Feng S.; McLaughlin, Donna
This paper discusses the outcomes of a study that investigated whether applying the discrete-trial approach is effective in teaching children with autism to learn functional and pre-academic skills. Participants were four young children with autism (ages 3-4) attending a preschool special education program of an urban public school. Discrete-trial…
Discrete-continuous variable structural synthesis using dual methods
NASA Technical Reports Server (NTRS)
Schmit, L. A.; Fleury, C.
1980-01-01
Approximation concepts and dual methods are extended to solve structural synthesis problems involving a mix of discrete and continuous sizing type of design variables. Pure discrete and pure continuous variable problems can be handled as special cases. The basic mathematical programming statement of the structural synthesis problem is converted into a sequence of explicit approximate primal problems of separable form. These problems are solved by constructing continuous explicit dual functions, which are maximized subject to simple nonnegativity constraints on the dual variables. A newly devised gradient projection type of algorithm called DUAL 1, which includes special features for handling dual function gradient discontinuities that arise from the discrete primal variables, is used to find the solution of each dual problem. Computational implementation is accomplished by incorporating the DUAL 1 algorithm into the ACCESS 3 program as a new optimizer option. The power of the method set forth is demonstrated by presenting numerical results for several example problems, including a pure discrete variable treatment of a metallic swept wing and a mixed discrete-continuous variable solution for a thin delta wing with fiber composite skins.
N -tag probability law of the symmetric exclusion process
NASA Astrophysics Data System (ADS)
Poncet, Alexis; Bénichou, Olivier; Démery, Vincent; Oshanin, Gleb
2018-06-01
The symmetric exclusion process (SEP), in which particles hop symmetrically on a discrete line with hard-core constraints, is a paradigmatic model of subdiffusion in confined systems. This anomalous behavior is a direct consequence of strong spatial correlations induced by the requirement that the particles cannot overtake each other. Even if this fact has been recognized qualitatively for a long time, up to now there has been no full quantitative determination of these correlations. Here we study the joint probability distribution of an arbitrary number of tagged particles in the SEP. We determine analytically its large-time limit for an arbitrary density of particles, and its full dynamics in the high-density limit. In this limit, we obtain the time-dependent large deviation function of the problem and unveil a universal scaling form shared by the cumulants.
NASA Astrophysics Data System (ADS)
Afshordi, Niayesh; Mohayaee, Roya; Bertschinger, Edmund
2009-04-01
Most of the mass content of dark matter haloes is expected to be in the form of tidal debris. The density of debris is not constant, but rather can grow due to formation of caustics at the apocenters and pericenters of the orbit, or decay as a result of phase mixing. In the phase space, the debris assemble in a hierarchy that is truncated by the primordial temperature of dark matter. Understanding this phase structure can be of significant importance for the interpretation of many astrophysical observations and, in particular, dark matter detection experiments. With this purpose in mind, we develop a general theoretical framework to describe the hierarchical structure of the phase space of cold dark matter haloes. We do not make any assumption of spherical symmetry and/or smooth and continuous accretion. Instead, working with correlation functions in the action-angle space, we can fully account for the hierarchical structure (predicting a two-point correlation function ∝ΔJ-1.6 in the action space), as well as the primordial discreteness of the phase space. As an application, we estimate the boost to the dark matter annihilation signal due to the structure of the phase space within virial radius: the boost due to the hierarchical tidal debris is of order unity, whereas the primordial discreteness of the phase structure can boost the total annihilation signal by up to an order of magnitude. The latter is dominated by the regions beyond 20% of the virial radius, and is largest for the recently formed haloes with the least degree of phase mixing. Nevertheless, as we argue in a companion paper, the boost due to small gravitationally-bound substructure can dominate this effect at low redshifts.
Wang, Jinling; Jiang, Haijun; Ma, Tianlong; Hu, Cheng
2018-05-01
This paper considers the delay-dependent stability of memristive complex-valued neural networks (MCVNNs). A novel linear mapping function is presented to transform the complex-valued system into the real-valued system. Under such mapping function, both continuous-time and discrete-time MCVNNs are analyzed in this paper. Firstly, when activation functions are continuous but not Lipschitz continuous, an extended matrix inequality is proved to ensure the stability of continuous-time MCVNNs. Furthermore, if activation functions are discontinuous, a discontinuous adaptive controller is designed to acquire its stability by applying Lyapunov-Krasovskii functionals. Secondly, compared with techniques in continuous-time MCVNNs, the Halanay-type inequality and comparison principle are firstly used to exploit the dynamical behaviors of discrete-time MCVNNs. Finally, the effectiveness of theoretical results is illustrated through numerical examples. Copyright © 2018 Elsevier Ltd. All rights reserved.
Flt-1 (VEGFR-1) coordinates discrete stages of blood vessel formation
Chappell, John C.; Cluceru, Julia G.; Nesmith, Jessica E.; Mouillesseaux, Kevin P.; Bradley, Vanessa B.; Hartland, Caitlin M.; Hashambhoy-Ramsay, Yasmin L.; Walpole, Joseph; Peirce, Shayn M.; Mac Gabhann, Feilim; Bautch, Victoria L.
2016-01-01
Aims In developing blood vessel networks, the overall level of vessel branching often correlates with angiogenic sprout initiations, but in some pathological situations, increased sprout initiations paradoxically lead to reduced vessel branching and impaired vascular function. We examine the hypothesis that defects in the discrete stages of angiogenesis can uniquely contribute to vessel branching outcomes. Methods and results Time-lapse movies of mammalian blood vessel development were used to define and quantify the dynamics of angiogenic sprouting. We characterized the formation of new functional conduits by classifying discrete sequential stages—sprout initiation, extension, connection, and stability—that are differentially affected by manipulation of vascular endothelial growth factor-A (VEGF-A) signalling via genetic loss of the receptor flt-1 (vegfr1). In mouse embryonic stem cell-derived vessels genetically lacking flt-1, overall branching is significantly decreased while sprout initiations are significantly increased. Flt-1−/− mutant sprouts are less likely to retract, and they form increased numbers of connections with other vessels. However, loss of flt-1 also leads to vessel collapse, which reduces the number of new stable conduits. Computational simulations predict that loss of flt-1 results in ectopic Flk-1 signalling in connecting sprouts post-fusion, causing protrusion of cell processes into avascular gaps and collapse of branches. Thus, defects in stabilization of new vessel connections offset increased sprout initiations and connectivity in flt-1−/− vascular networks, with an overall outcome of reduced numbers of new conduits. Conclusions These results show that VEGF-A signalling has stage-specific effects on vascular morphogenesis, and that understanding these effects on dynamic stages of angiogenesis and how they integrate to expand a vessel network may suggest new therapeutic strategies. PMID:27142980
Discrete Gust Model for Launch Vehicle Assessments
NASA Technical Reports Server (NTRS)
Leahy, Frank B.
2008-01-01
Analysis of spacecraft vehicle responses to atmospheric wind gusts during flight is important in the establishment of vehicle design structural requirements and operational capability. Typically, wind gust models can be either a spectral type determined by a random process having a wide range of wavelengths, or a discrete type having a single gust of predetermined magnitude and shape. Classical discrete models used by NASA during the Apollo and Space Shuttle Programs included a 9 m/sec quasi-square-wave gust with variable wavelength from 60 to 300 m. A later study derived discrete gust from a military specification (MIL-SPEC) document that used a "1-cosine" shape. The MIL-SPEC document contains a curve of non-dimensional gust magnitude as a function of non-dimensional gust half-wavelength based on the Dryden spectral model, but fails to list the equation necessary to reproduce the curve. Therefore, previous studies could only estimate a value of gust magnitude from the curve, or attempt to fit a function to it. This paper presents the development of the MIL-SPEC curve, and provides the necessary information to calculate discrete gust magnitudes as a function of both gust half-wavelength and the desired probability level of exceeding a specified gust magnitude.
Adaptive NN controller design for a class of nonlinear MIMO discrete-time systems.
Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip
2015-05-01
An adaptive neural network tracking control is studied for a class of multiple-input multiple-output (MIMO) nonlinear systems. The studied systems are in discrete-time form and the discretized dead-zone inputs are considered. In addition, the studied MIMO systems are composed of N subsystems, and each subsystem contains unknown functions and external disturbance. Due to the complicated framework of the discrete-time systems, the existence of the dead zone and the noncausal problem in discrete-time, it brings about difficulties for controlling such a class of systems. To overcome the noncausal problem, by defining the coordinate transformations, the studied systems are transformed into a special form, which is suitable for the backstepping design. The radial basis functions NNs are utilized to approximate the unknown functions of the systems. The adaptation laws and the controllers are designed based on the transformed systems. By using the Lyapunov method, it is proved that the closed-loop system is stable in the sense that the semiglobally uniformly ultimately bounded of all the signals and the tracking errors converge to a bounded compact set. The simulation examples and the comparisons with previous approaches are provided to illustrate the effectiveness of the proposed control algorithm.
Vertical discretization with finite elements for a global hydrostatic model on the cubed sphere
NASA Astrophysics Data System (ADS)
Yi, Tae-Hyeong; Park, Ja-Rin
2017-06-01
A formulation of Galerkin finite element with basis-spline functions on a hybrid sigma-pressure coordinate is presented to discretize the vertical terms of global Eulerian hydrostatic equations employed in a numerical weather prediction system, which is horizontally discretized with high-order spectral elements on a cubed sphere grid. This replaces the vertical discretization of conventional central finite difference that is first-order accurate in non-uniform grids and causes numerical instability in advection-dominant flows. Therefore, a model remains in the framework of Galerkin finite elements for both the horizontal and vertical spatial terms. The basis-spline functions, obtained from the de-Boor algorithm, are employed to derive both the vertical derivative and integral operators, since Eulerian advection terms are involved. These operators are used to discretize the vertical terms of the prognostic and diagnostic equations. To verify the vertical discretization schemes and compare their performance, various two- and three-dimensional idealized cases and a hindcast case with full physics are performed in terms of accuracy and stability. It was shown that the vertical finite element with the cubic basis-spline function is more accurate and stable than that of the vertical finite difference, as indicated by faster residual convergence, fewer statistical errors, and reduction in computational mode. This leads to the general conclusion that the overall performance of a global hydrostatic model might be significantly improved with the vertical finite element.
Rights, Jason D; Sterba, Sonya K
2016-11-01
Multilevel data structures are common in the social sciences. Often, such nested data are analysed with multilevel models (MLMs) in which heterogeneity between clusters is modelled by continuously distributed random intercepts and/or slopes. Alternatively, the non-parametric multilevel regression mixture model (NPMM) can accommodate the same nested data structures through discrete latent class variation. The purpose of this article is to delineate analytic relationships between NPMM and MLM parameters that are useful for understanding the indirect interpretation of the NPMM as a non-parametric approximation of the MLM, with relaxed distributional assumptions. We define how seven standard and non-standard MLM specifications can be indirectly approximated by particular NPMM specifications. We provide formulas showing how the NPMM can serve as an approximation of the MLM in terms of intraclass correlation, random coefficient means and (co)variances, heteroscedasticity of residuals at level 1, and heteroscedasticity of residuals at level 2. Further, we discuss how these relationships can be useful in practice. The specific relationships are illustrated with simulated graphical demonstrations, and direct and indirect interpretations of NPMM classes are contrasted. We provide an R function to aid in implementing and visualizing an indirect interpretation of NPMM classes. An empirical example is presented and future directions are discussed. © 2016 The British Psychological Society.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stamatikos, Michael; Band, David L.; JCA/UMBC, Baltimore, MD 21250
2006-05-19
We describe the theoretical modeling and analysis techniques associated with a preliminary search for correlated neutrino emission from GRB980703a, which triggered the Burst and Transient Source Experiment (BATSE GRB trigger 6891), using archived data from the Antarctic Muon and Neutrino Detector Array (AMANDA-B10). Under the assumption of associated hadronic acceleration, the expected observed neutrino energy flux is directly derived, based upon confronting the fireball phenomenology with the discrete set of observed electromagnetic parameters of GRB980703a, gleaned from ground-based and satellite observations, for four models, corrected for oscillations. Models 1 and 2, based upon spectral analysis featuring a prompt photon energymore » fit to the Band function, utilize an observed spectroscopic redshift, for isotropic and anisotropic emission geometry, respectively. Model 3 is based upon averaged burst parameters, assuming isotropic emission. Model 4 based upon a Band fit, features an estimated redshift from the lag-luminosity relation, with isotropic emission. Consistent with our AMANDA-II analysis of GRB030329, which resulted in a flux upper limit of {approx} 0.150GeV /cm2/s for model 1, we find differences in excess of an order of magnitude in the response of AMANDA-B10, among the various models for GRB980703a. Implications for future searches in the era of Swift and IceCube are discussed.« less
Boltzmann-conserving classical dynamics in quantum time-correlation functions: "Matsubara dynamics".
Hele, Timothy J H; Willatt, Michael J; Muolo, Andrea; Althorpe, Stuart C
2015-04-07
We show that a single change in the derivation of the linearized semiclassical-initial value representation (LSC-IVR or "classical Wigner approximation") results in a classical dynamics which conserves the quantum Boltzmann distribution. We rederive the (standard) LSC-IVR approach by writing the (exact) quantum time-correlation function in terms of the normal modes of a free ring-polymer (i.e., a discrete imaginary-time Feynman path), taking the limit that the number of polymer beads N → ∞, such that the lowest normal-mode frequencies take their "Matsubara" values. The change we propose is to truncate the quantum Liouvillian, not explicitly in powers of ħ(2) at ħ(0) (which gives back the standard LSC-IVR approximation), but in the normal-mode derivatives corresponding to the lowest Matsubara frequencies. The resulting "Matsubara" dynamics is inherently classical (since all terms O(ħ(2)) disappear from the Matsubara Liouvillian in the limit N → ∞) and conserves the quantum Boltzmann distribution because the Matsubara Hamiltonian is symmetric with respect to imaginary-time translation. Numerical tests show that the Matsubara approximation to the quantum time-correlation function converges with respect to the number of modes and gives better agreement than LSC-IVR with the exact quantum result. Matsubara dynamics is too computationally expensive to be applied to complex systems, but its further approximation may lead to practical methods.
Efficient scheme for parametric fitting of data in arbitrary dimensions.
Pang, Ning-Ning; Tzeng, Wen-Jer; Kao, Hisen-Ching
2008-07-01
We propose an efficient scheme for parametric fitting expressed in terms of the Legendre polynomials. For continuous systems, our scheme is exact and the derived explicit expression is very helpful for further analytical studies. For discrete systems, our scheme is almost as accurate as the method of singular value decomposition. Through a few numerical examples, we show that our algorithm costs much less CPU time and memory space than the method of singular value decomposition. Thus, our algorithm is very suitable for a large amount of data fitting. In addition, the proposed scheme can also be used to extract the global structure of fluctuating systems. We then derive the exact relation between the correlation function and the detrended variance function of fluctuating systems in arbitrary dimensions and give a general scaling analysis.
A Scale-Invariant ``Discrete-Time'' Balitsky--Kovchegov Equation
NASA Astrophysics Data System (ADS)
Bialas, A.; Peschanski, R.
2005-06-01
We consider a version of QCD dipole cascading corresponding to a finite number n of discrete Δ Y steps of branching in rapidity. Using the discretization scheme preserving the holomorphic factorizability and scale-invariance in position space of the dipole splitting function, we derive an exact recurrence formula from step to step which plays the rôle of a ``discrete-time'' Balitsky--Kovchegov equation. The BK solutions are recovered in the limit n=∞ and Δ Y=0.
On reinitializing level set functions
NASA Astrophysics Data System (ADS)
Min, Chohong
2010-04-01
In this paper, we consider reinitializing level functions through equation ϕt+sgn(ϕ0)(‖∇ϕ‖-1)=0[16]. The method of Russo and Smereka [11] is taken in the spatial discretization of the equation. The spatial discretization is, simply speaking, the second order ENO finite difference with subcell resolution near the interface. Our main interest is on the temporal discretization of the equation. We compare the three temporal discretizations: the second order Runge-Kutta method, the forward Euler method, and a Gauss-Seidel iteration of the forward Euler method. The fact that the time in the equation is fictitious makes a hypothesis that all the temporal discretizations result in the same result in their stationary states. The fact that the absolute stability region of the forward Euler method is not wide enough to include all the eigenvalues of the linearized semi-discrete system of the second order ENO spatial discretization makes another hypothesis that the forward Euler temporal discretization should invoke numerical instability. Our results in this paper contradict both the hypotheses. The Runge-Kutta and Gauss-Seidel methods obtain the second order accuracy, and the forward Euler method converges with order between one and two. Examining all their properties, we conclude that the Gauss-Seidel method is the best among the three. Compared to the Runge-Kutta, it is twice faster and requires memory two times less with the same accuracy.
Hints of correlation between broad-line and radio variations for 3C 120
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, H. T.; Bai, J. M.; Li, S. K.
2014-01-01
In this paper, we investigate the correlation between broad-line and radio variations for the broad-line radio galaxy 3C 120. By the z-transformed discrete correlation function method and the model-independent flux randomization/random subset selection (FR/RSS) Monte Carlo method, we find that broad Hβ line variations lead the 15 GHz variations. The FR/RSS method shows that the Hβ line variations lead the radio variations by a factor of τ{sub ob} = 0.34 ± 0.01 yr. This time lag can be used to locate the position of the emitting region of radio outbursts in the jet, on the order of ∼5 lt-yr frommore » the central engine. This distance is much larger than the size of the broad-line region. The large separation of the radio outburst emitting region from the broad-line region will observably influence the gamma-ray emission in 3C 120.« less
A mimetic finite difference method for the Stokes problem with elected edge bubbles
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lipnikov, K; Berirao, L
2009-01-01
A new mimetic finite difference method for the Stokes problem is proposed and analyzed. The unstable P{sub 1}-P{sub 0} discretization is stabilized by adding a small number of bubble functions to selected mesh edges. A simple strategy for selecting such edges is proposed and verified with numerical experiments. The discretizations schemes for Stokes and Navier-Stokes equations must satisfy the celebrated inf-sup (or the LBB) stability condition. The stability condition implies a balance between discrete spaces for velocity and pressure. In finite elements, this balance is frequently achieved by adding bubble functions to the velocity space. The goal of this articlemore » is to show that the stabilizing edge bubble functions can be added only to a small set of mesh edges. This results in a smaller algebraic system and potentially in a faster calculations. We employ the mimetic finite difference (MFD) discretization technique that works for general polyhedral meshes and can accomodate non-uniform distribution of stabilizing bubbles.« less
Non-autonomous equations with unpredictable solutions
NASA Astrophysics Data System (ADS)
Akhmet, Marat; Fen, Mehmet Onur
2018-06-01
To make research of chaos more amenable to investigating differential and discrete equations, we introduce the concepts of an unpredictable function and sequence. The topology of uniform convergence on compact sets is applied to define unpredictable functions [1,2]. The unpredictable sequence is defined as a specific unpredictable function on the set of integers. The definitions are convenient to be verified as solutions of differential and discrete equations. The topology is metrizable and easy for applications with integral operators. To demonstrate the effectiveness of the approach, the existence and uniqueness of the unpredictable solution for a delay differential equation are proved as well as for quasilinear discrete systems. As a corollary of the theorem, a similar assertion for a quasilinear ordinary differential equation is formulated. The results are demonstrated numerically, and an application to Hopfield neural networks is provided. In particular, Poincaré chaos near periodic orbits is observed. The completed research contributes to the theory of chaos as well as to the theory of differential and discrete equations, considering unpredictable solutions.
Real-Time and Memory Correlation via Acousto-Optic Processing,
1978-06-01
acousto - optic technology as an answer to these requirements appears very attractive. Three fundamental signal-processing schemes using the acousto ... optic interaction have been investigated: (i) real-time correlation and convolution, (ii) Fourier and discrete Fourier transformation, and (iii
The Information Content of Discrete Functions and Their Application in Genetic Data Analysis
Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.
2017-10-13
The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less
The Information Content of Discrete Functions and Their Application in Genetic Data Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sakhanenko, Nikita A.; Kunert-Graf, James; Galas, David J.
The complex of central problems in data analysis consists of three components: (1) detecting the dependence of variables using quantitative measures, (2) defining the significance of these dependence measures, and (3) inferring the functional relationships among dependent variables. We have argued previously that an information theory approach allows separation of the detection problem from the inference of functional form problem. We approach here the third component of inferring functional forms based on information encoded in the functions. Here, we present here a direct method for classifying the functional forms of discrete functions of three variables represented in data sets. Discretemore » variables are frequently encountered in data analysis, both as the result of inherently categorical variables and from the binning of continuous numerical variables into discrete alphabets of values. The fundamental question of how much information is contained in a given function is answered for these discrete functions, and their surprisingly complex relationships are illustrated. The all-important effect of noise on the inference of function classes is found to be highly heterogeneous and reveals some unexpected patterns. We apply this classification approach to an important area of biological data analysis—that of inference of genetic interactions. Genetic analysis provides a rich source of real and complex biological data analysis problems, and our general methods provide an analytical basis and tools for characterizing genetic problems and for analyzing genetic data. Finally, we illustrate the functional description and the classes of a number of common genetic interaction modes and also show how different modes vary widely in their sensitivity to noise.« less
A study of stationarity in time series by using wavelet transform
NASA Astrophysics Data System (ADS)
Dghais, Amel Abdoullah Ahmed; Ismail, Mohd Tahir
2014-07-01
In this work the core objective is to apply discrete wavelet transform (DWT) functions namely Haar, Daubechies, Symmlet, Coiflet and discrete approximation of the meyer wavelets in non-stationary financial time series data from US stock market (DJIA30). The data consists of 2048 daily data of closing index starting from December 17, 2004 until October 23, 2012. From the unit root test the results show that the data is non stationary in the level. In order to study the stationarity of a time series, the autocorrelation function (ACF) is used. Results indicate that, Haar function is the lowest function to obtain noisy series as compared to Daubechies, Symmlet, Coiflet and discrete approximation of the meyer wavelets. In addition, the original data after decomposition by DWT is less noisy series than decomposition by DWT for return time series.
Level Density in the Complex Scaling Method
NASA Astrophysics Data System (ADS)
Suzuki, R.; Myo, T.; Katō, K.
2005-06-01
It is shown that the continuum level density (CLD) at unbound energies can be calculated with the complex scaling method (CSM), in which the energy spectra of bound states, resonances and continuum states are obtained in terms of L(2) basis functions. In this method, the extended completeness relation is applied to the calculation of the Green functions, and the continuum-state part is approximately expressed in terms of discretized complex scaled continuum solutions. The obtained result is compared with the CLD calculated exactly from the scattering phase shift. The discretization in the CSM is shown to give a very good description of continuum states. We discuss how the scattering phase shifts can inversely be calculated from the discretized CLD using a basis function technique in the CSM.
SPIR: The potential spreaders involved SIR model for information diffusion in social networks
NASA Astrophysics Data System (ADS)
Rui, Xiaobin; Meng, Fanrong; Wang, Zhixiao; Yuan, Guan; Du, Changjiang
2018-09-01
The Susceptible-Infective-Removed (SIR) model is one of the most widely used models for the information diffusion research in social networks. Many researchers have devoted themselves to improving the classic SIR model in different aspects. However, on the one hand, the equations of these improved models are regarded as continuous functions, while the corresponding simulation experiments use discrete time, leading to the mismatch between numerical solutions got from mathematical method and experimental results obtained by simulating the spreading behaviour of each node. On the other hand, if the equations of these improved models are solved discretely, susceptible nodes will be calculated repeatedly, resulting in a big deviation from the actual value. In order to solve the above problem, this paper proposes a Susceptible-Potential-Infective-Removed (SPIR) model that analyses the diffusion process based on the discrete time according to simulation. Besides, this model also introduces a potential spreader set which solve the problem of repeated calculation effectively. To test the SPIR model, various experiments have been carried out from different angles on both artificial networks and real world networks. The Pearson correlation coefficient between numerical solutions of our SPIR equations and corresponding simulation results is mostly bigger than 0.95, which reveals that the proposed SPIR model is able to depict the information diffusion process with high accuracy.
Adjoint-Based Methodology for Time-Dependent Optimization
NASA Technical Reports Server (NTRS)
Yamaleev, N. K.; Diskin, B.; Nielsen, E. J.
2008-01-01
This paper presents a discrete adjoint method for a broad class of time-dependent optimization problems. The time-dependent adjoint equations are derived in terms of the discrete residual of an arbitrary finite volume scheme which approximates unsteady conservation law equations. Although only the 2-D unsteady Euler equations are considered in the present analysis, this time-dependent adjoint method is applicable to the 3-D unsteady Reynolds-averaged Navier-Stokes equations with minor modifications. The discrete adjoint operators involving the derivatives of the discrete residual and the cost functional with respect to the flow variables are computed using a complex-variable approach, which provides discrete consistency and drastically reduces the implementation and debugging cycle. The implementation of the time-dependent adjoint method is validated by comparing the sensitivity derivative with that obtained by forward mode differentiation. Our numerical results show that O(10) optimization iterations of the steepest descent method are needed to reduce the objective functional by 3-6 orders of magnitude for test problems considered.
Energy- and time-resolved detection of prompt gamma-rays for proton range verification.
Verburg, Joost M; Riley, Kent; Bortfeld, Thomas; Seco, Joao
2013-10-21
In this work, we present experimental results of a novel prompt gamma-ray detector for proton beam range verification. The detection system features an actively shielded cerium-doped lanthanum(III) bromide scintillator, coupled to a digital data acquisition system. The acquisition was synchronized to the cyclotron radio frequency to separate the prompt gamma-ray signals from the later-arriving neutron-induced background. We designed the detector to provide a high energy resolution and an effective reduction of background events, enabling discrete proton-induced prompt gamma lines to be resolved. Measuring discrete prompt gamma lines has several benefits for range verification. As the discrete energies correspond to specific nuclear transitions, the magnitudes of the different gamma lines have unique correlations with the proton energy and can be directly related to nuclear reaction cross sections. The quantification of discrete gamma lines also enables elemental analysis of tissue in the beam path, providing a better prediction of prompt gamma-ray yields. We present the results of experiments in which a water phantom was irradiated with proton pencil-beams in a clinical proton therapy gantry. A slit collimator was used to collimate the prompt gamma-rays, and measurements were performed at 27 positions along the path of proton beams with ranges of 9, 16 and 23 g cm(-2) in water. The magnitudes of discrete gamma lines at 4.44, 5.2 and 6.13 MeV were quantified. The prompt gamma lines were found to be clearly resolved in dimensions of energy and time, and had a reproducible correlation with the proton depth-dose curve. We conclude that the measurement of discrete prompt gamma-rays for in vivo range verification of clinical proton beams is feasible, and plan to further study methods and detector designs for clinical use.
Using galaxy pairs to investigate the three-point correlation function in the squeezed limit
NASA Astrophysics Data System (ADS)
Yuan, Sihan; Eisenstein, Daniel J.; Garrison, Lehman H.
2017-11-01
We investigate the three-point correlation function (3PCF) in the squeezed limit by considering galaxy pairs as discrete objects and cross-correlating them with the galaxy field. We develop an efficient algorithm using fast Fourier transforms to compute such cross-correlations and their associated pair-galaxy bias bp, g and the squeezed 3PCF coefficient Qeff. We implement our method using N-body cosmological simulations and a fiducial halo occupation distribution (HOD) and present the results in both the real space and redshift space. In real space, we observe a peak in bp, g and Qeff at pair separation of ∼2 Mpc, attributed to the fact that galaxy pairs at 2 Mpc separation trace the most massive dark matter haloes. We also see strong anisotropy in the bp, g and Qeff signals that track the large-scale filamentary structure. In redshift space, both the 2 Mpc peak and the anisotropy are significantly smeared out along the line of sight due to finger-of-God effect. In both the real space and redshift space, the squeezed 3PCF shows a factor of 2 variation, contradicting the hierarchical ansatz, but offering rich information on the galaxy-halo connection. Thus, we explore the possibility of using the squeezed 3PCF to constrain the HOD. When we compare two simple HOD models that are closely matched in their projected two-point correlation function (2PCF), we do not yet see a strong variation in the 3PCF that is clearly disentangled from variations in the projected 2PCF. Nevertheless, we propose that more complicated HOD models, e.g. those incorporating assembly bias, can break degeneracies in the 2PCF and show a distinguishable squeezed 3PCF signal.
Gomez, E; Buckingham, D W; Brindle, J; Lanzafame, F; Irvine, D S; Aitken, R J
1996-01-01
A method has been developed for quantifying the residual cytoplasm present in the midpiece of human spermatozoa, based upon the imaging of NADH oxidoreductase activity. This procedure used NADH and nitroblue tetrazolium as electron donor and acceptor, respectively, and resulted in the discrete staining of the entire midpiece area, including the residual cytoplasm. Image analysis techniques were then used to generate binary images of the midpiece, from which objective measurements of this cellular domain could be undertaken. Such data were found to be highly correlated with biochemical markers of the cytoplasmic space, such as creatine kinase (CK) and glucose-6-phosphate dehydrogenase (G-6-PDH), in sperm populations depleted of detectable leukocyte contamination. Morphometric analysis of the sperm midpiece was also found to reflect semen quality in that it predicted the proportion of the ejaculate that would be recovered from the high-density region of Percoll gradients and was negatively correlated with the movement and morphology of the spermatozoa in semen. Variation in the retention of excess residual cytoplasm was also associated with differences in the functional competence of washed sperm preparations, both within and between ejaculates. Thus, within-ejaculate comparisons of high- and low-density sperm subpopulations revealed a relative disruption of sperm function in the low-density fraction. This disruption was associated with the presence of excess residual cytoplasm in the midpiece, high concentrations of cytoplasmic enzymes, and the enhanced-generation reactive oxygen species (ROS). Functional differences between individual high-density Percoll preparations were also negatively correlated with the area of the midpiece and the corresponding capacity of the spermatozoa to generate ROS. These findings suggest that one of the factors involved in the etiology of defective sperm function is the incomplete extrusion of germ cell cytoplasm during spermiogenesis as a consequence of which the spermatozoa experience a loss of function associated with the induction of oxidative stress.
Geometric interpretations of the Discrete Fourier Transform (DFT)
NASA Technical Reports Server (NTRS)
Campbell, C. W.
1984-01-01
One, two, and three dimensional Discrete Fourier Transforms (DFT) and geometric interpretations of their periodicities are presented. These operators are examined for their relationship with the two sided, continuous Fourier transform. Discrete or continuous transforms of real functions have certain symmetry properties. The symmetries are examined for the one, two, and three dimensional cases. Extension to higher dimension is straight forward.
Variable Weight Fractional Collisions for Multiple Species Mixtures
2017-08-28
DISTRIBUTION A: APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED; PA #17517 6 / 21 VARIABLE WEIGHTS FOR DYNAMIC RANGE Continuum to Discrete ...Representation: Many Particles →̃ Continuous Distribution Discretized VDF Yields Vlasov But Collision Integral Still a Problem Particle Methods VDF to Delta...Function Set Collisions between Discrete Velocities But Poorly Resolved Tail (Tail Critical to Inelastic Collisions) Variable Weights Permit Extra DOF in
Telemetry Standards, IRIG Standard 106-17. Chapter 10. Digital Recording Standard
2017-07-01
10-28 10.7.9 Required Discrete Control Functions...1553 data bus, time, analog, video, Aeronautical Radio, Inc. 429, discrete , and Universal Asynchronous Receiver and Transmitter containing...Interfaces 10.3, 10.4 Fibre Channel and/or IEEE 1394b Data Download Port 10.3, 10.7 Discrete Lines and/or RS-232 and 422 Full Duplex Communication 10.3
Finite Element Aircraft Simulation of Turbulence
NASA Technical Reports Server (NTRS)
McFarland, R. E.
1997-01-01
A turbulence model has been developed for realtime aircraft simulation that accommodates stochastic turbulence and distributed discrete gusts as a function of the terrain. This model is applicable to conventional aircraft, V/STOL aircraft, and disc rotor model helicopter simulations. Vehicle angular activity in response to turbulence is computed from geometrical and temporal relationships rather than by using the conventional continuum approximations that assume uniform gust immersion and low frequency responses. By using techniques similar to those recently developed for blade-element rotor models, the angular-rate filters of conventional turbulence models are not required. The model produces rotational rates as well as air mass translational velocities in response to both stochastic and deterministic disturbances, where the discrete gusts and turbulence magnitudes may be correlated with significant terrain features or ship models. Assuming isotropy, a two-dimensional vertical turbulence field is created. A novel Gaussian interpolation technique is used to distribute vertical turbulence on the wing span or lateral rotor disc, and this distribution is used to compute roll responses. Air mass velocities are applied at significant centers of pressure in the computation of the aircraft's pitch and roll responses.
Game Theoretic Approaches to Protect Cyberspace
2010-04-20
security problems. 3.1 Definitions Game A description of the strategic interaction between opposing, or co-operating, interests where the con ...that involves probabilistic transitions through several states of the system. The game pro - gresses as a sequence of states. The game begins with a...eventually leads to a discretized model. The reaction functions uniquely minimize the strictly con - vex cost functions. After discretization, this
Neural Representation of Subjective Sexual Arousal in Men and Women.
Parada, Mayte; Gérard, Marina; Larcher, Kevin; Dagher, Alain; Binik, Yitzchak M
2016-10-01
Studies investigating brain indices of sexual arousal have begun to elucidate the brain's role in processing subjective arousal; however, most research has focused on men, used discrete ratings of subjective arousal, and used stimuli too short to induce significant arousal in women. To examine brain regions modulated by changes in subjective sexual arousal (SSA) rating intensity in men and women. Two groups (20 men, 20 women) viewed movie clips (erotic or humorous) while continuously evaluating changes in their SSA using a Likert-like scale (0 = not aroused, 10 = most aroused) and answering discrete questions about liking the movies and wanting sexual stimulation. Brain activity was measured using functional magnetic resonance imaging. Blood oxygen level-dependent responses and continuous and discrete measurements of sexual arousal. Erotic movies induced significant SSA in men and women. No sex difference in mean SSA was found in response to the erotic movies on continuous or discrete measurements. Several brain regions were correlated with changes in SSA. Parametric modulation with rating intensity showed a specific group of regions within the parietal lobe that showed significant differences in activity among low, medium, and high SSA. Multiple regions were concordant with changes in SSA; however, a subset of regions in men and women was modulated by SSA intensity, a subset previously linked to attentional processes, monitoring of internal body representation, and processing of sensory information from the genitals. This study highlights that similar brain regions are activated during subjective assessment of sexual arousal in men and women. The data further highlight the fact that SSA is a complex phenomenon made up of multiple interoceptive and attentional processes. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Yang, L. M.; Shu, C.; Wang, Y.; Sun, Y.
2016-08-01
The sphere function-based gas kinetic scheme (GKS), which was presented by Shu and his coworkers [23] for simulation of inviscid compressible flows, is extended to simulate 3D viscous incompressible and compressible flows in this work. Firstly, we use certain discrete points to represent the spherical surface in the phase velocity space. Then, integrals along the spherical surface for conservation forms of moments, which are needed to recover 3D Navier-Stokes equations, are approximated by integral quadrature. The basic requirement is that these conservation forms of moments can be exactly satisfied by weighted summation of distribution functions at discrete points. It was found that the integral quadrature by eight discrete points on the spherical surface, which forms the D3Q8 discrete velocity model, can exactly match the integral. In this way, the conservative variables and numerical fluxes can be computed by weighted summation of distribution functions at eight discrete points. That is, the application of complicated formulations resultant from integrals can be replaced by a simple solution process. Several numerical examples including laminar flat plate boundary layer, 3D lid-driven cavity flow, steady flow through a 90° bending square duct, transonic flow around DPW-W1 wing and supersonic flow around NACA0012 airfoil are chosen to validate the proposed scheme. Numerical results demonstrate that the present scheme can provide reasonable numerical results for 3D viscous flows.
Chen, Weisheng
2009-07-01
This paper focuses on the problem of adaptive neural network tracking control for a class of discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints. Two novel state-feedback and output-feedback dynamic control laws are established where the function tanh(.) is employed to solve the saturation constraint problem. Implicit function theorem and mean value theorem are exploited to deal with non-affine variables that are used as actual control. Radial basis function neural networks are used to approximate the desired input function. Discrete Nussbaum gain is used to estimate the unknown sign of control gain. The uniform boundedness of all closed-loop signals is guaranteed. The tracking error is proved to converge to a small residual set around the origin. A simulation example is provided to illustrate the effectiveness of control schemes proposed in this paper.
NASA Astrophysics Data System (ADS)
Liska, Sebastian; Colonius, Tim
2017-02-01
A new parallel, computationally efficient immersed boundary method for solving three-dimensional, viscous, incompressible flows on unbounded domains is presented. Immersed surfaces with prescribed motions are generated using the interpolation and regularization operators obtained from the discrete delta function approach of the original (Peskin's) immersed boundary method. Unlike Peskin's method, boundary forces are regarded as Lagrange multipliers that are used to satisfy the no-slip condition. The incompressible Navier-Stokes equations are discretized on an unbounded staggered Cartesian grid and are solved in a finite number of operations using lattice Green's function techniques. These techniques are used to automatically enforce the natural free-space boundary conditions and to implement a novel block-wise adaptive grid that significantly reduces the run-time cost of solutions by limiting operations to grid cells in the immediate vicinity and near-wake region of the immersed surface. These techniques also enable the construction of practical discrete viscous integrating factors that are used in combination with specialized half-explicit Runge-Kutta schemes to accurately and efficiently solve the differential algebraic equations describing the discrete momentum equation, incompressibility constraint, and no-slip constraint. Linear systems of equations resulting from the time integration scheme are efficiently solved using an approximation-free nested projection technique. The algebraic properties of the discrete operators are used to reduce projection steps to simple discrete elliptic problems, e.g. discrete Poisson problems, that are compatible with recent parallel fast multipole methods for difference equations. Numerical experiments on low-aspect-ratio flat plates and spheres at Reynolds numbers up to 3700 are used to verify the accuracy and physical fidelity of the formulation.
Natural convection in symmetrically heated vertical parallel plates with discrete heat sources
DOE Office of Scientific and Technical Information (OSTI.GOV)
Manca, O.; Nardini, S.; Naso, V.
Laminar air natural convection in a symmetrically heated vertical channel with uniform flush-mounted discrete heat sources has been experimentally investigated. The effects of heated strips location and of their number are pointed out in terms of the maximum wall temperatures. A flow visualization in the entrance region of the channel was carried out and air temperatures and velocities in two cross sections have been measured. Dimensionless local heat transfer coefficients have been evaluated and monomial correlations among relevant parameters have bee derived in the local Rayleigh number range 10--10{sup 6}. Channel Nusselt number has been correlated in a polynomial formmore » in terms of channel Rayleigh number.« less
NASA Astrophysics Data System (ADS)
Naine, Tarun Bharath; Gundawar, Manoj Kumar
2017-09-01
We demonstrate a very powerful correlation between the discrete probability of distances of neighboring cells and thermal wave propagation rate, for a system of cells spread on a one-dimensional chain. A gamma distribution is employed to model the distances of neighboring cells. In the absence of an analytical solution and the differences in ignition times of adjacent reaction cells following non-Markovian statistics, invariably the solution for thermal wave propagation rate for a one-dimensional system with randomly distributed cells is obtained by numerical simulations. However, such simulations which are based on Monte-Carlo methods require several iterations of calculations for different realizations of distribution of adjacent cells. For several one-dimensional systems, differing in the value of shaping parameter of the gamma distribution, we show that the average reaction front propagation rates obtained by a discrete probability between two limits, shows excellent agreement with those obtained numerically. With the upper limit at 1.3, the lower limit depends on the non-dimensional ignition temperature. Additionally, this approach also facilitates the prediction of burning limits of heterogeneous thermal mixtures. The proposed method completely eliminates the need for laborious, time intensive numerical calculations where the thermal wave propagation rates can now be calculated based only on macroscopic entity of discrete probability.
Data approximation using a blending type spline construction
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dalmo, Rune; Bratlie, Jostein
2014-11-18
Generalized expo-rational B-splines (GERBS) is a blending type spline construction where local functions at each knot are blended together by C{sup k}-smooth basis functions. One way of approximating discrete regular data using GERBS is by partitioning the data set into subsets and fit a local function to each subset. Partitioning and fitting strategies can be devised such that important or interesting data points are interpolated in order to preserve certain features. We present a method for fitting discrete data using a tensor product GERBS construction. The method is based on detection of feature points using differential geometry. Derivatives, which aremore » necessary for feature point detection and used to construct local surface patches, are approximated from the discrete data using finite differences.« less
The Designed Environment and How it Affects Brain Morphology and Mental Health.
Golembiewski, Jan A
2016-01-01
The environment is inextricably related to mental health. Recent research replicates findings of a significant, linear correlation between a childhood exposure to the urban environment and psychosis. Related studies also correlate the urban environment and aberrant brain morphologies. These findings challenge common beliefs that the mind and brain remain neutral in the face of worldly experience. There is a signature within these neurological findings that suggests that specific features of design cause and trigger mental illness. The objective in this article is to work backward from the molecular dynamics to identify features of the designed environment that may either trigger mental illness or protect against it. This review analyzes the discrete functions putatively assigned to the affected brain areas and a neurotransmitter called dopamine, which is the primary target of most antipsychotic medications. The intention is to establish what the correlations mean in functional terms, and more specifically, how this relates to the phenomenology of urban experience. In doing so, environmental mental illness risk factors are identified. Having established these relationships, the review makes practical recommendations for those in public health who wish to use the environment itself as a tool to improve the mental health of a community through design. © The Author(s) 2015.
Characterizing Atomistic Geometries and Potential Functions Using Strain Functionals
NASA Astrophysics Data System (ADS)
Kober, Edward; Mathew, Nithin; Rudin, Sven
2017-06-01
We demonstrate the use of strain tensor functionals for characterizing arbitrarily ordered atomistic structures. This approach defines a Gaussian-weighted neighborhood around each atom and characterizes that local geometry in terms of n-th order strain tensors, which are equivalent to the n-th order moments/derivatives of the neighborhood. Fourth order expansions can distinguish the cubic structures (and deformations thereof), but sixth order expansions are required to fully characterize hexagonal structures. These functions are continuous and smooth and much less sensitive to thermal fluctuations than other descriptors based on discrete neighborhoods. Reducing these metrics to rotational invariant descriptors allows a large number of defect structures to be readily identified and forms the basis of a classification scheme that allows molecular dynamics simulations to be readily analyzed. Applications to the analysis of shock waves impinging on samples of Cu, Ta and Ti will be presented. The method has been extended to vector fields as well, enabling the local stress to be cast in terms of rotationally invariant functions as well. The stress-strain correlations can then be used as the basis for developing and analyzing potential functions.
Identification of Linear and Nonlinear Aerodynamic Impulse Responses Using Digital Filter Techniques
NASA Technical Reports Server (NTRS)
Silva, Walter A.
1997-01-01
This paper discusses the mathematical existence and the numerically-correct identification of linear and nonlinear aerodynamic impulse response functions. Differences between continuous-time and discrete-time system theories, which permit the identification and efficient use of these functions, will be detailed. Important input/output definitions and the concept of linear and nonlinear systems with memory will also be discussed. It will be shown that indicial (step or steady) responses (such as Wagner's function), forced harmonic responses (such as Theodorsen's function or those from doublet lattice theory), and responses to random inputs (such as gusts) can all be obtained from an aerodynamic impulse response function. This paper establishes the aerodynamic impulse response function as the most fundamental, and, therefore, the most computationally efficient, aerodynamic function that can be extracted from any given discrete-time, aerodynamic system. The results presented in this paper help to unify the understanding of classical two-dimensional continuous-time theories with modern three-dimensional, discrete-time theories. First, the method is applied to the nonlinear viscous Burger's equation as an example. Next the method is applied to a three-dimensional aeroelastic model using the CAP-TSD (Computational Aeroelasticity Program - Transonic Small Disturbance) code and then to a two-dimensional model using the CFL3D Navier-Stokes code. Comparisons of accuracy and computational cost savings are presented. Because of its mathematical generality, an important attribute of this methodology is that it is applicable to a wide range of nonlinear, discrete-time problems.
Identification of Linear and Nonlinear Aerodynamic Impulse Responses Using Digital Filter Techniques
NASA Technical Reports Server (NTRS)
Silva, Walter A.
1997-01-01
This paper discusses the mathematical existence and the numerically-correct identification of linear and nonlinear aerodynamic impulse response functions. Differences between continuous-time and discrete-time system theories, which permit the identification and efficient use of these functions, will be detailed. Important input/output definitions and the concept of linear and nonlinear systems with memory will also be discussed. It will be shown that indicial (step or steady) responses (such as Wagner's function), forced harmonic responses (such as Tbeodorsen's function or those from doublet lattice theory), and responses to random inputs (such as gusts) can all be obtained from an aerodynamic impulse response function. This paper establishes the aerodynamic impulse response function as the most fundamental, and, therefore, the most computationally efficient, aerodynamic function that can be extracted from any given discrete-time, aerodynamic system. The results presented in this paper help to unify the understanding of classical two-dimensional continuous-time theories with modem three-dimensional, discrete-time theories. First, the method is applied to the nonlinear viscous Burger's equation as an example. Next the method is applied to a three-dimensional aeroelastic model using the CAP-TSD (Computational Aeroelasticity Program - Transonic Small Disturbance) code and then to a two-dimensional model using the CFL3D Navier-Stokes code. Comparisons of accuracy and computational cost savings are presented. Because of its mathematical generality, an important attribute of this methodology is that it is applicable to a wide range of nonlinear, discrete-time problems.
Stimuli inevitably generated by behavior that avoids electric shock are inherently reinforcing.
Dinsmoor, J A
2001-01-01
A molecular analysis based on the termination of stimuli that are positively correlated with shock and the production of stimuli that are negatively correlated with shock provides a parsimonious count for both traditional discrete-trial avoidance behavior and the data derived from more recent free-operant procedures. The necessary stimuli are provided by the intrinsic feedback generated by the subject's behavior, in addition to those presented by the experimenter. Moreover, all data compatible with the molar principle of shock-frequency reduction as reinforcement are also compatible with a delay-of-shock gradient, but some data compatible with the delay gradient are not compatible with frequency reduction. The delay gradient corresponds to functions relating magnitude of behavioral effect to the time between conditional and unconditional stimuli, the time between conditioned and primary reinforcers, and the time between responses and positive reinforcers. PMID:11453621
Predicting catalyst-support interactions between metal nanoparticles and amorphous silica supports
NASA Astrophysics Data System (ADS)
Ewing, Christopher S.; Veser, Götz; McCarthy, Joseph J.; Lambrecht, Daniel S.; Johnson, J. Karl
2016-10-01
Metal-support interactions significantly affect the stability and activity of supported catalytic nanoparticles (NPs), yet there is no simple and reliable method for estimating NP-support interactions, especially for amorphous supports. We present an approach for rapid prediction of catalyst-support interactions between Pt NPs and amorphous silica supports for NPs of various sizes and shapes. We use density functional theory calculations of 13 atom Pt clusters on model amorphous silica supports to determine linear correlations relating catalyst properties to NP-support interactions. We show that these correlations can be combined with fast discrete element method simulations to predict adhesion energy and NP net charge for NPs of larger sizes and different shapes. Furthermore, we demonstrate that this approach can be successfully transferred to Pd, Au, Ni, and Fe NPs. This approach can be used to quickly screen stability and net charge transfer and leads to a better fundamental understanding of catalyst-support interactions.
Control System for Prosthetic Devices
NASA Technical Reports Server (NTRS)
Bozeman, Richard J. (Inventor)
1996-01-01
A control system and method for prosthetic devices is provided. The control system comprises a transducer for receiving movement from a body part for generating a sensing signal associated with that of movement. The sensing signal is processed by a linearizer for linearizing the sensing signal to be a linear function of the magnitude of the distance moved by the body part. The linearized sensing signal is normalized to be a function of the entire range of body part movement from the no-shrug position of the moveable body part through the full-shrg position of the moveable body part. The normalized signal is divided into a plurality of discrete command signals. The discrete command signals are used by typical converter devices which are in operational association with the prosthetic device. The converter device uses the discrete command signals for driving the moveable portions of the prosthetic device and its sub-prosthesis. The method for controlling a prosthetic device associated with the present invention comprises the steps of receiving the movement from the body part, generating a sensing signal in association with the movement of the body part, linearizing the sensing signal to be a linear function of the magnitude of the distance moved by the body part, normalizing the linear signal to be a function of the entire range of the body part movement, dividing the normalized signal into a plurality of discrete command signals, and implementing the plurality of discrete command signals for driving the respective moveable prosthesis device and its sub-prosthesis.
Control method for prosthetic devices
NASA Technical Reports Server (NTRS)
Bozeman, Richard J., Jr. (Inventor)
1995-01-01
A control system and method for prosthetic devices is provided. The control system comprises a transducer for receiving movement from a body part for generating a sensing signal associated with that movement. The sensing signal is processed by a linearizer for linearizing the sensing signal to be a linear function of the magnitude of the distance moved by the body part. The linearized sensing signal is normalized to be a function of the entire range of body part movement from the no-shrug position of the moveable body part. The normalized signal is divided into a plurality of discrete command signals. The discrete command signals are used by typical converter devices which are in operational association with the prosthetic device. The converter device uses the discrete command signals for driving the moveable portions of the prosthetic device and its sub-prosthesis. The method for controlling a prosthetic device associated with the present invention comprises the steps of receiving the movement from the body part, generating a sensing signal in association with the movement of the body part, linearizing the sensing signal to be a linear function of the magnitude of the distance moved by the body part, normalizing the linear signal to be a function of the entire range of the body part movement, dividing the normalized signal into a plurality of discrete command signals, and implementing the plurality of discrete command signals for driving the respective moveable prosthesis device and its sub-prosthesis.
Control system and method for prosthetic devices
NASA Technical Reports Server (NTRS)
Bozeman, Richard J., Jr. (Inventor)
1992-01-01
A control system and method for prosthetic devices is provided. The control system comprises a transducer for receiving movement from a body part for generating a sensing signal associated with that movement. The sensing signal is processed by a linearizer for linearizing the sensing signal to be a linear function of the magnitude of the distance moved by the body part. The linearized sensing signal is normalized to be a function of the entire range of body part movement from the no-shrug position of the movable body part through the full-shrug position of the movable body part. The normalized signal is divided into a plurality of discrete command signals. The discrete command signals are used by typical converter devices which are in operational association with the prosthetic device. The converter device uses the discrete command signals for driving the movable portions of the prosthetic device and its sub-prosthesis. The method for controlling a prosthetic device associated with the present invention comprises the steps of receiving the movement from the body part, generating a sensing signal in association with the movement of the body part, linearizing the sensing signal to be a linear function of the magnitude of the distance moved by the body part, normalizing the linear signal to be a function of the entire range of the body part movement, dividing the normalized signal into a plurality of discrete command signals, and implementing the plurality of discrete command signals for driving the respective movable prosthesis device and its sub-prosthesis.
Mathematical construction and perturbation analysis of Zernike discrete orthogonal points.
Shi, Zhenguang; Sui, Yongxin; Liu, Zhenyu; Peng, Ji; Yang, Huaijiang
2012-06-20
Zernike functions are orthogonal within the unit circle, but they are not over the discrete points such as CCD arrays or finite element grids. This will result in reconstruction errors for loss of orthogonality. By using roots of Legendre polynomials, a set of points within the unit circle can be constructed so that Zernike functions over the set are discretely orthogonal. Besides that, the location tolerances of the points are studied by perturbation analysis, and the requirements of the positioning precision are not very strict. Computer simulations show that this approach provides a very accurate wavefront reconstruction with the proposed sampling set.
NASA Astrophysics Data System (ADS)
Gromov, Yu Yu; Minin, Yu V.; Ivanova, O. G.; Morozova, O. N.
2018-03-01
Multidimensional discrete distributions of probabilities of independent random values were received. Their one-dimensional distribution is widely used in probability theory. Producing functions of those multidimensional distributions were also received.
Seok, Junhee; Seon Kang, Yeong
2015-01-01
Mutual information, a general measure of the relatedness between two random variables, has been actively used in the analysis of biomedical data. The mutual information between two discrete variables is conventionally calculated by their joint probabilities estimated from the frequency of observed samples in each combination of variable categories. However, this conventional approach is no longer efficient for discrete variables with many categories, which can be easily found in large-scale biomedical data such as diagnosis codes, drug compounds, and genotypes. Here, we propose a method to provide stable estimations for the mutual information between discrete variables with many categories. Simulation studies showed that the proposed method reduced the estimation errors by 45 folds and improved the correlation coefficients with true values by 99 folds, compared with the conventional calculation of mutual information. The proposed method was also demonstrated through a case study for diagnostic data in electronic health records. This method is expected to be useful in the analysis of various biomedical data with discrete variables. PMID:26046461
NASA Technical Reports Server (NTRS)
Repa, B. S.; Zucker, R. S.; Wierwille, W. W.
1977-01-01
The influence of vehicle transient response characteristics on driver-vehicle performance in discrete maneuvers as measured by integral performance criteria was investigated. A group of eight ordinary drivers was presented with a series of eight vehicle transfer function configurations in a driving simulator. Performance in two discrete maneuvers was analyzed by means of integral performance criteria. Results are presented.
Energy Criterion for the Spectral Stability of Discrete Breathers.
Kevrekidis, Panayotis G; Cuevas-Maraver, Jesús; Pelinovsky, Dmitry E
2016-08-26
Discrete breathers are ubiquitous structures in nonlinear anharmonic models ranging from the prototypical example of the Fermi-Pasta-Ulam model to Klein-Gordon nonlinear lattices, among many others. We propose a general criterion for the emergence of instabilities of discrete breathers analogous to the well-established Vakhitov-Kolokolov criterion for solitary waves. The criterion involves the change of monotonicity of the discrete breather's energy as a function of the breather frequency. Our analysis suggests and numerical results corroborate that breathers with increasing (decreasing) energy-frequency dependence are generically unstable in soft (hard) nonlinear potentials.
Distinct Functional Modules for Discrete and Rhythmic Forelimb Movements in the Mouse Motor Cortex.
Hira, Riichiro; Terada, Shin-Ichiro; Kondo, Masashi; Matsuzaki, Masanori
2015-09-30
Movements of animals are composed of two fundamental dynamics: discrete and rhythmic movements. Although the movements with distinct dynamics are thought to be differently processed in the CNS, it is unclear how they are represented in the cerebral cortex. Here, we investigated the cortical representation of movement dynamics by developing prolonged transcranial optogenetic stimulation (pTOS) using awake, channelrhodopsin-2 transgenic mice. We found two domains that induced discrete forelimb movements in the forward and backward directions, and these sandwiched a domain that generated rhythmic forelimb movements. The forward discrete movement had an intrinsic velocity profile and the rhythmic movement had an intrinsic oscillation frequency. Each of the forward discrete and rhythmic domains possessed intracortical synaptic connections within its own domain, independently projected to the spinal cord, and weakened the neuronal activity and movement induction of the other domain. pTOS-induced movements were also classified as ethologically relevant movements. Forepaw-to-mouth movement was mapped in a part of the forward discrete domain, while locomotion-like movement was in a part of the rhythmic domain. Interestingly, photostimulation of the rhythmic domain resulted in a nonrhythmic, continuous lever-pull movement when a lever was present. The motor cortex possesses functional modules for distinct movement dynamics, and these can adapt to environmental constraints for purposeful movements. Significance statement: Animal behavior has discrete and rhythmic components, such as reaching and locomotion. It is unclear how these movements with distinct dynamics are represented in the cerebral cortex. We investigated the dynamics of movements induced by long-duration transcranial photostimulation on the dorsal cortex of awake channelrhodopsin-2 transgenic mice. We found two domains causing forward and backward discrete forelimb movements and a domain for rhythmic forelimb movements. A domain for forward discrete movement and a domain for rhythmic movement mutually weakened neuronal activity and movement size. The photostimulation of the rhythmic domain also induced nonrhythmic, lever-pull movement, when the lever was present. Thus, the motor cortex has functional modules with distinct dynamics, and each module retains flexibility for adaptation to different environments. Copyright © 2015 the authors 0270-6474/15/3513311-12$15.00/0.
Hemolytic potential of hydrodynamic cavitation.
Chambers, S D; Bartlett, R H; Ceccio, S L
2000-08-01
The purpose of this study was to determine the hemolytic potentials of discrete bubble cavitation and attached cavitation. To generate controlled cavitation events, a venturigeometry hydrodynamic device, called a Cavitation Susceptibility Meter (CSM), was constructed. A comparison between the hemolytic potential of discrete bubble cavitation and attached cavitation was investigated with a single-pass flow apparatus and a recirculating flow apparatus, both utilizing the CSM. An analytical model, based on spherical bubble dynamics, was developed for predicting the hemolysis caused by discrete bubble cavitation. Experimentally, discrete bubble cavitation did not correlate with a measurable increase in plasma-free hemoglobin (PFHb), as predicted by the analytical model. However, attached cavitation did result in significant PFHb generation. The rate of PFHb generation scaled inversely with the Cavitation number at a constant flow rate, suggesting that the size of the attached cavity was the dominant hemolytic factor.
Oyama, Kei; Tateyama, Yukina; Hernádi, István; Tobler, Philippe N; Iijima, Toshio; Tsutsui, Ken-Ichiro
2015-11-01
To investigate how the striatum integrates sensory information with reward information for behavioral guidance, we recorded single-unit activity in the dorsal striatum of head-fixed rats participating in a probabilistic Pavlovian conditioning task with auditory conditioned stimuli (CSs) in which reward probability was fixed for each CS but parametrically varied across CSs. We found that the activity of many neurons was linearly correlated with the reward probability indicated by the CSs. The recorded neurons could be classified according to their firing patterns into functional subtypes coding reward probability in different forms such as stimulus value, reward expectation, and reward prediction error. These results suggest that several functional subgroups of dorsal striatal neurons represent different kinds of information formed through extensive prior exposure to CS-reward contingencies. Copyright © 2015 the American Physiological Society.
Oyama, Kei; Tateyama, Yukina; Hernádi, István; Tobler, Philippe N.; Iijima, Toshio
2015-01-01
To investigate how the striatum integrates sensory information with reward information for behavioral guidance, we recorded single-unit activity in the dorsal striatum of head-fixed rats participating in a probabilistic Pavlovian conditioning task with auditory conditioned stimuli (CSs) in which reward probability was fixed for each CS but parametrically varied across CSs. We found that the activity of many neurons was linearly correlated with the reward probability indicated by the CSs. The recorded neurons could be classified according to their firing patterns into functional subtypes coding reward probability in different forms such as stimulus value, reward expectation, and reward prediction error. These results suggest that several functional subgroups of dorsal striatal neurons represent different kinds of information formed through extensive prior exposure to CS-reward contingencies. PMID:26378201
Elementary exact calculations of degree growth and entropy for discrete equations.
Halburd, R G
2017-05-01
Second-order discrete equations are studied over the field of rational functions [Formula: see text], where z is a variable not appearing in the equation. The exact degree of each iterate as a function of z can be calculated easily using the standard calculations that arise in singularity confinement analysis, even when the singularities are not confined. This produces elementary yet rigorous entropy calculations.
Lens elliptic gamma function solution of the Yang-Baxter equation at roots of unity
NASA Astrophysics Data System (ADS)
Kels, Andrew P.; Yamazaki, Masahito
2018-02-01
We study the root of unity limit of the lens elliptic gamma function solution of the star-triangle relation, for an integrable model with continuous and discrete spin variables. This limit involves taking an elliptic nome to a primitive rNth root of unity, where r is an existing integer parameter of the lens elliptic gamma function, and N is an additional integer parameter. This is a singular limit of the star-triangle relation, and at subleading order of an asymptotic expansion, another star-triangle relation is obtained for a model with discrete spin variables in {Z}rN . Some special choices of solutions of equation of motion are shown to result in well-known discrete spin solutions of the star-triangle relation. The saddle point equations themselves are identified with three-leg forms of ‘3D-consistent’ classical discrete integrable equations, known as Q4 and Q3(δ=0) . We also comment on the implications for supersymmetric gauge theories, and in particular comment on a close parallel with the works of Nekrasov and Shatashvili.
Liu, Wenyu; An, Dongmei; Tong, Xin; Niu, Running; Gong, Qiyong; Zhou, Dong
2017-10-01
Periventricular nodular heterotopia (PNH) is an important cause of chronic epilepsy. The purpose of this study was to evaluate region-specific connectivity in PNH patients with epilepsy and assess correlation between connectivity strength and clinical factors including duration and prognosis. Diffusion tensor imaging (DTI) and resting state functional MRI (fMRI) were performed in 28 subjects (mean age 27.4years; range 9-56years). The structural connectivity of fiber bundles passing through the manually-selected segmented nodules and other brain regions were analyzed by tractography. Cortical lobes showing functional correlations to nodules were also determined. For all heterotopic gray matter nodules, including at least one in each subject, the most frequent segments to which nodular heterotopia showed structural (132/151) and functional (146/151) connectivity were discrete regions of the ipsilateral overlying cortex. Agreement between diffusion tensor tractography and functional connectivity analyses was conserved in 81% of all nodules (122/151). In patients with longer duration or refractory epilepsy, the connectivity was significantly stronger, particularly to the frontal and temporal lobes (P<0.05). Nodules in PNH were structurally and functionally connected to the cortex. The extent is stronger in patients with longstanding or intractable epilepsy. These findings suggest the region-specific interactions may help better evaluate prognosis and seek medical or surgical interventions of PNH-related epilepsy. Copyright © 2017 Elsevier B.V. All rights reserved.
Differential porosimetry and permeametry for random porous media.
Hilfer, R; Lemmer, A
2015-07-01
Accurate determination of geometrical and physical properties of natural porous materials is notoriously difficult. Continuum multiscale modeling has provided carefully calibrated realistic microstructure models of reservoir rocks with floating point accuracy. Previous measurements using synthetic microcomputed tomography (μ-CT) were based on extrapolation of resolution-dependent properties for discrete digitized approximations of the continuum microstructure. This paper reports continuum measurements of volume and specific surface with full floating point precision. It also corrects an incomplete description of rotations in earlier publications. More importantly, the methods of differential permeametry and differential porosimetry are introduced as precision tools. The continuum microstructure chosen to exemplify the methods is a homogeneous, carefully calibrated and characterized model for Fontainebleau sandstone. The sample has been publicly available since 2010 on the worldwide web as a benchmark for methodical studies of correlated random media. High-precision porosimetry gives the volume and internal surface area of the sample with floating point accuracy. Continuum results with floating point precision are compared to discrete approximations. Differential porosities and differential surface area densities allow geometrical fluctuations to be discriminated from discretization effects and numerical noise. Differential porosimetry and Fourier analysis reveal subtle periodic correlations. The findings uncover small oscillatory correlations with a period of roughly 850μm, thus implying that the sample is not strictly stationary. The correlations are attributed to the deposition algorithm that was used to ensure the grain overlap constraint. Differential permeabilities are introduced and studied. Differential porosities and permeabilities provide scale-dependent information on geometry fluctuations, thereby allowing quantitative error estimates.
Krüger, Melanie; Straube, Andreas; Eggert, Thomas
2017-01-01
In recent years, theory-building in motor neuroscience and our understanding of the synergistic control of the redundant human motor system has significantly profited from the emergence of a range of different mathematical approaches to analyze the structure of movement variability. Approaches such as the Uncontrolled Manifold method or the Noise-Tolerance-Covariance decomposition method allow to detect and interpret changes in movement coordination due to e.g., learning, external task constraints or disease, by analyzing the structure of within-subject, inter-trial movement variability. Whereas, for cyclical movements (e.g., locomotion), mathematical approaches exist to investigate the propagation of movement variability in time (e.g., time series analysis), similar approaches are missing for discrete, goal-directed movements, such as reaching. Here, we propose canonical correlation analysis as a suitable method to analyze the propagation of within-subject variability across different time points during the execution of discrete movements. While similar analyses have already been applied for discrete movements with only one degree of freedom (DoF; e.g., Pearson's product-moment correlation), canonical correlation analysis allows to evaluate the coupling of inter-trial variability across different time points along the movement trajectory for multiple DoF-effector systems, such as the arm. The theoretical analysis is illustrated by empirical data from a study on reaching movements under normal and disturbed proprioception. The results show increased movement duration, decreased movement amplitude, as well as altered movement coordination under ischemia, which results in a reduced complexity of movement control. Movement endpoint variability is not increased under ischemia. This suggests that healthy adults are able to immediately and efficiently adjust the control of complex reaching movements to compensate for the loss of proprioceptive information. Further, it is shown that, by using canonical correlation analysis, alterations in movement coordination that indicate changes in the control strategy concerning the use of motor redundancy can be detected, which represents an important methodical advance in the context of neuromechanics.
High-resolution maps of Jupiter at five microns.
NASA Technical Reports Server (NTRS)
Keay, C. S. L.; Low, F. J.; Rieke, G. H.; Minton, R. B.
1973-01-01
The distribution of 5-micron radiation, emitted from a large number of discrete sources from Jupiter, was observed during the 1972 apparition. These sources are less bright than those observed by Westphal (1969). At least 50 discrete sources having brightness temperatures exceeding 227 K were revealed which were mainly located within three narrow-latitude bands. Strong correlation exists between the 5-micron brightness temperatures of Jovian features and their colors as recorded photographically.
NASA Astrophysics Data System (ADS)
Frampton, A.; Hyman, J.; Zou, L.
2017-12-01
Analysing flow and transport in sparsely fractured media is important for understanding how crystalline bedrock environments function as barriers to transport of contaminants, with important applications towards subsurface repositories for storage of spent nuclear fuel. Crystalline bedrocks are particularly favourable due to their geological stability, low advective flow and strong hydrogeochemical retention properties, which can delay transport of radionuclides, allowing decay to limit release to the biosphere. There are however many challenges involved in quantifying and modelling subsurface flow and transport in fractured media, largely due to geological complexity and heterogeneity, where the interplay between advective and dispersive flow strongly impacts both inert and reactive transport. A key to modelling transport in a Lagrangian framework involves quantifying pathway travel times and the hydrodynamic control of retention, and both these quantities strongly depend on heterogeneity of the fracture network at different scales. In this contribution, we present recent analysis of flow and transport considering fracture networks with single-fracture heterogeneity described by different multivariate normal distributions. A coherent triad of fields with identical correlation length and variance are created but which greatly differ in structure, corresponding to textures with well-connected low, medium and high permeability structures. Through numerical modelling of multiple scales in a stochastic setting we quantify the relative impact of texture type and correlation length against network topological measures, and identify key thresholds for cases where flow dispersion is controlled by single-fracture heterogeneity versus network-scale heterogeneity. This is achieved by using a recently developed novel numerical discrete fracture network model. Furthermore, we highlight enhanced flow channelling for cases where correlation structure continues across intersections in a network, and discuss application to realistic fracture networks using field data of sparsely fractured crystalline rock from the Swedish candidate repository site for spent nuclear fuel.
Neural correlates of improvements in personality and behavior following a neurological event.
King, Marcie L; Manzel, Kenneth; Bruss, Joel; Tranel, Daniel
2017-11-21
Research on changes in personality and behavior following brain damage has focused largely on negative outcomes, such as increased irritability, moodiness, and social inappropriateness. However, clinical observations suggest that some patients may actually show positive personality and behavioral changes following a neurological event. In the current work, we investigated neuroanatomical correlates of positive personality and behavioral changes following a discrete neurological event (e.g., stroke, benign tumor resection). Patients (N = 97) were rated by a well-known family member or friend on five domains of personality and behavior: social behavior, irascibility, hypo-emotionality, distress, and executive functioning. Ratings were acquired during the chronic epoch of recovery, when psychological status was stabilized. We identified patients who showed positive changes in personality and behavior in one or more domains of functioning. Lesion analyses indicated that positive changes in personality and behavior were most consistently related to damage to the bilateral frontal polar regions and the right anterior dorsolateral prefrontal region. These findings support the conclusion that improvements in personality and behavior can occur after a neurological event, and that such changes have systematic neuroanatomical correlates. Patients who showed positive changes in personality and behavior following a neurological event were rated as having more disturbed functioning prior to the event. Our study may be taken as preliminary evidence that improvements in personality and behavior following a neurological event may involve dampening of (premorbidly) more extreme expressions of emotion. Copyright © 2017 Elsevier Ltd. All rights reserved.
Activity Diagrams for DEVS Models: A Case Study Modeling Health Care Behavior
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ozmen, Ozgur; Nutaro, James J
Discrete Event Systems Specification (DEVS) is a widely used formalism for modeling and simulation of discrete and continuous systems. While DEVS provides a sound mathematical representation of discrete systems, its practical use can suffer when models become complex. Five main functions, which construct the core of atomic modules in DEVS, can realize the behaviors that modelers want to represent. The integration of these functions is handled by the simulation routine, however modelers can implement each function in various ways. Therefore, there is a need for graphical representations of complex models to simplify their implementation and facilitate their reproduction. In thismore » work, we illustrate the use of activity diagrams for this purpose in the context of a health care behavior model, which is developed with an agent-based modeling paradigm.« less
Relating zeta functions of discrete and quantum graphs
NASA Astrophysics Data System (ADS)
Harrison, Jonathan; Weyand, Tracy
2018-02-01
We write the spectral zeta function of the Laplace operator on an equilateral metric graph in terms of the spectral zeta function of the normalized Laplace operator on the corresponding discrete graph. To do this, we apply a relation between the spectrum of the Laplacian on a discrete graph and that of the Laplacian on an equilateral metric graph. As a by-product, we determine how the multiplicity of eigenvalues of the quantum graph, that are also in the spectrum of the graph with Dirichlet conditions at the vertices, depends on the graph geometry. Finally we apply the result to calculate the vacuum energy and spectral determinant of a complete bipartite graph and compare our results with those for a star graph, a graph in which all vertices are connected to a central vertex by a single edge.
Discrete Regularization for Calibration of Geologic Facies Against Dynamic Flow Data
NASA Astrophysics Data System (ADS)
Khaninezhad, Mohammad-Reza; Golmohammadi, Azarang; Jafarpour, Behnam
2018-04-01
Subsurface flow model calibration involves many more unknowns than measurements, leading to ill-posed problems with nonunique solutions. To alleviate nonuniqueness, the problem is regularized by constraining the solution space using prior knowledge. In certain sedimentary environments, such as fluvial systems, the contrast in hydraulic properties of different facies types tends to dominate the flow and transport behavior, making the effect of within facies heterogeneity less significant. Hence, flow model calibration in those formations reduces to delineating the spatial structure and connectivity of different lithofacies types and their boundaries. A major difficulty in calibrating such models is honoring the discrete, or piecewise constant, nature of facies distribution. The problem becomes more challenging when complex spatial connectivity patterns with higher-order statistics are involved. This paper introduces a novel formulation for calibration of complex geologic facies by imposing appropriate constraints to recover plausible solutions that honor the spatial connectivity and discreteness of facies models. To incorporate prior connectivity patterns, plausible geologic features are learned from available training models. This is achieved by learning spatial patterns from training data, e.g., k-SVD sparse learning or the traditional Principal Component Analysis. Discrete regularization is introduced as a penalty functions to impose solution discreteness while minimizing the mismatch between observed and predicted data. An efficient gradient-based alternating directions algorithm is combined with variable splitting to minimize the resulting regularized nonlinear least squares objective function. Numerical results show that imposing learned facies connectivity and discreteness as regularization functions leads to geologically consistent solutions that improve facies calibration quality.
Quasi-periodic solutions to the hierarchy of four-component Toda lattices
NASA Astrophysics Data System (ADS)
Wei, Jiao; Geng, Xianguo; Zeng, Xin
2016-08-01
Starting from a discrete 3×3 matrix spectral problem, the hierarchy of four-component Toda lattices is derived by using the stationary discrete zero-curvature equation. Resorting to the characteristic polynomial of the Lax matrix for the hierarchy, we introduce a trigonal curve Km-2 of genus m - 2 and present the related Baker-Akhiezer function and meromorphic function on it. Asymptotic expansions for the Baker-Akhiezer function and meromorphic function are given near three infinite points on the trigonal curve, from which explicit quasi-periodic solutions for the hierarchy of four-component Toda lattices are obtained in terms of the Riemann theta function.
NASA Technical Reports Server (NTRS)
Mukhopadhyay, A. K.
1978-01-01
The Data Storage Subsystem Simulator (DSSSIM) simulating (by ground software) occurrence of discrete events in the Voyager mission is described. Functional requirements for Data Storage Subsystems (DSS) simulation are discussed, and discrete event simulation/DSSSIM processing is covered. Four types of outputs associated with a typical DSSSIM run are presented, and DSSSIM limitations and constraints are outlined.
A radial basis function Galerkin method for inhomogeneous nonlocal diffusion
Lehoucq, Richard B.; Rowe, Stephen T.
2016-02-01
We introduce a discretization for a nonlocal diffusion problem using a localized basis of radial basis functions. The stiffness matrix entries are assembled by a special quadrature routine unique to the localized basis. Combining the quadrature method with the localized basis produces a well-conditioned, sparse, symmetric positive definite stiffness matrix. We demonstrate that both the continuum and discrete problems are well-posed and present numerical results for the convergence behavior of the radial basis function method. As a result, we explore approximating the solution to anisotropic differential equations by solving anisotropic nonlocal integral equations using the radial basis function method.
Eggins, Peta S; Hatton, Sean N; Hermens, Daniel F; Hickie, Ian B; Lagopoulos, Jim
2018-01-30
The aim of this study was to investigate differences in subcortical and hippocampal volumes between healthy controls, young people at an early stage of affective and psychotic disorders and those in more advanced stages, to identify markers associated with functional outcomes and illness severity. Young people presenting to youth mental health services with admixtures of depressive, manic and psychotic symptoms (n = 141), and healthy counterparts (n = 49), aged 18-25 were recruited. Participants underwent magnetic resonance imaging, clinical assessments and were rated as to their current clinical stage. Eighty-four patients were classified at the attenuated syndrome stage (Stage 1b) and 57 were classified as having discrete and persistent disorders (Stage 2+). Automated segmentation was performed using NeuroQuant® to determine volumes of subcortical and hippocampus structures which were compared between groups and correlated with clinical and functional outcomes. Compared to healthy controls, Stage 2+ patients showed significantly reduced right amygdala volumes. Whereas Stage 1b patients showed significantly reduced left caudate volumes compared to healthy controls. Smaller left caudate volume correlated with greater psychological distress and impaired functioning. This study shows a clinical application for an automated program to identify and track subcortical changes evident in young people with emerging psychopathology. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.
Song, Xiaowen; Huang, Fei; Liu, Juanjuan; Li, Chengjun; Gao, Shanshan; Wu, Wei; Zhai, Mengfan; Yu, Xiaojuan; Xiong, Wenfeng; Xie, Jia
2017-01-01
Abstract Cytosine DNA methylation is a vital epigenetic regulator of eukaryotic development. Whether this epigenetic modification occurs in Tribolium castaneum has been controversial, its distribution pattern and functions have not been established. Here, using bisulphite sequencing (BS-Seq), we confirmed the existence of DNA methylation and described the methylation profiles of the four life stages of T. castaneum. In the T. castaneum genome, both symmetrical CpG and non-CpG methylcytosines were observed. Symmetrical CpG methylation, which was catalysed by DNMT1 and occupied a small part in T. castaneum methylome, was primarily enriched in gene bodies and was positively correlated with gene expression levels. Asymmetrical non-CpG methylation, which was predominant in the methylome, was strongly concentrated in intergenic regions and introns but absent from exons. Gene body methylation was negatively correlated with gene expression levels. The distribution pattern and functions of this type of methylation were similar only to the methylome of Drosophila melanogaster, which further supports the existence of a novel methyltransferase in the two species responsible for this type of methylation. This first life-cycle methylome of T. castaneum reveals a novel and unique methylation pattern, which will contribute to the further understanding of the variety and functions of DNA methylation in eukaryotes. PMID:28449092
Requirements analysis for a hardware, discrete-event, simulation engine accelerator
NASA Astrophysics Data System (ADS)
Taylor, Paul J., Jr.
1991-12-01
An analysis of a general Discrete Event Simulation (DES), executing on the distributed architecture of an eight mode Intel PSC/2 hypercube, was performed. The most time consuming portions of the general DES algorithm were determined to be the functions associated with message passing of required simulation data between processing nodes of the hypercube architecture. A behavioral description, using the IEEE standard VHSIC Hardware Description and Design Language (VHDL), for a general DES hardware accelerator is presented. The behavioral description specifies the operational requirements for a DES coprocessor to augment the hypercube's execution of DES simulations. The DES coprocessor design implements the functions necessary to perform distributed discrete event simulations using a conservative time synchronization protocol.
NASA Astrophysics Data System (ADS)
Cai, Li; Wen, Ji-Hong; Yu, Dian-Long; Lu, Zhi-Miao; Wen, Xi-Sen
2014-09-01
Acoustic cloak based on coordinate transformation is of great topical interest and has promise in potential applications such as sound transparency and insulation. The frequency response of acoustic cloaks with a quantity of discrete homogeneous layers is analyzed by the acoustic scattering theory. The effect of coordinate transformation function on the acoustic total scattering cross section is discussed to achieve low scattering with only a few layers of anisotropic metamaterials. Also, the physics of acoustic wave interaction with the interfaces between the discrete layers inside the cloak shell is discussed. These results provide a better way of designing a multilayered acoustic cloak with fewer layers.
NASA Astrophysics Data System (ADS)
Sepehrinia, Reza; Niry, M. D.; Bozorg, B.; Tabar, M. Reza Rahimi; Sahimi, Muhammad
2008-03-01
A mapping is developed between the linearized equation of motion for the dynamics of the transverse modes at T=0 of the Heisenberg-Mattis model of one-dimensional (1D) spin glasses and the (discretized) random wave equation. The mapping is used to derive an exact expression for the Lyapunov exponent (LE) of the magnon modes of spin glasses and to show that it follows anomalous scaling at low magnon frequencies. In addition, through numerical simulations, the differences between the LE and the density of states of the wave equation in a discrete 1D model of randomly disordered media (those with a finite correlation length) and that of continuous media (with a zero correlation length) are demonstrated and emphasized.
Stadthagen-González, Hans; Ferré, Pilar; Pérez-Sánchez, Miguel A; Imbault, Constance; Hinojosa, José Antonio
2017-09-18
The discrete emotion theory proposes that affective experiences can be reduced to a limited set of universal "basic" emotions, most commonly identified as happiness, sadness, anger, fear, and disgust. Here we present norms for 10,491 Spanish words for those five discrete emotions collected from a total of 2,010 native speakers, making it the largest set of norms for discrete emotions in any language to date. When used in conjunction with the norms from Hinojosa, Martínez-García et al. (Behavior Research Methods, 48, 272-284, 2016) and Ferré, Guasch, Martínez-García, Fraga, & Hinojosa (Behavior Research Methods, 49, 1082-1094, 2017), researchers now have access to ratings of discrete emotions for 13,633 Spanish words. Our norms show a high degree of inter-rater reliability and correlate highly with those from Ferré et al. (2017). Our exploration of the relationship between the five discrete emotions and relevant lexical and emotional variables confirmed findings of previous studies conducted with smaller datasets. The availability of such large set of norms will greatly facilitate the study of emotion, language and related fields. The norms are available as supplementary materials to this article.
Maximum-entropy probability distributions under Lp-norm constraints
NASA Technical Reports Server (NTRS)
Dolinar, S.
1991-01-01
Continuous probability density functions and discrete probability mass functions are tabulated which maximize the differential entropy or absolute entropy, respectively, among all probability distributions with a given L sub p norm (i.e., a given pth absolute moment when p is a finite integer) and unconstrained or constrained value set. Expressions for the maximum entropy are evaluated as functions of the L sub p norm. The most interesting results are obtained and plotted for unconstrained (real valued) continuous random variables and for integer valued discrete random variables. The maximum entropy expressions are obtained in closed form for unconstrained continuous random variables, and in this case there is a simple straight line relationship between the maximum differential entropy and the logarithm of the L sub p norm. Corresponding expressions for arbitrary discrete and constrained continuous random variables are given parametrically; closed form expressions are available only for special cases. However, simpler alternative bounds on the maximum entropy of integer valued discrete random variables are obtained by applying the differential entropy results to continuous random variables which approximate the integer valued random variables in a natural manner. All the results are presented in an integrated framework that includes continuous and discrete random variables, constraints on the permissible value set, and all possible values of p. Understanding such as this is useful in evaluating the performance of data compression schemes.
Interfacial properties in a discrete model for tumor growth
NASA Astrophysics Data System (ADS)
Moglia, Belén; Guisoni, Nara; Albano, Ezequiel V.
2013-03-01
We propose and study, by means of Monte Carlo numerical simulations, a minimal discrete model for avascular tumor growth, which can also be applied for the description of cell cultures in vitro. The interface of the tumor is self-affine and its width can be characterized by the following exponents: (i) the growth exponent β=0.32(2) that governs the early time regime, (ii) the roughness exponent α=0.49(2) related to the fluctuations in the stationary regime, and (iii) the dynamic exponent z=α/β≃1.49(2), which measures the propagation of correlations in the direction parallel to the interface, e.g., ξ∝t1/z, where ξ is the parallel correlation length. Therefore, the interface belongs to the Kardar-Parisi-Zhang universality class, in agreement with recent experiments of cell cultures in vitro. Furthermore, density profiles of the growing cells are rationalized in terms of traveling waves that are solutions of the Fisher-Kolmogorov equation. In this way, we achieved excellent agreement between the simulation results of the discrete model and the continuous description of the growth front of the culture or tumor.
Observation of a discrete time crystal
NASA Astrophysics Data System (ADS)
Zhang, J.; Hess, P. W.; Kyprianidis, A.; Becker, P.; Lee, A.; Smith, J.; Pagano, G.; Potirniche, I.-D.; Potter, A. C.; Vishwanath, A.; Yao, N. Y.; Monroe, C.
2017-03-01
Spontaneous symmetry breaking is a fundamental concept in many areas of physics, including cosmology, particle physics and condensed matter. An example is the breaking of spatial translational symmetry, which underlies the formation of crystals and the phase transition from liquid to solid. Using the analogy of crystals in space, the breaking of translational symmetry in time and the emergence of a ‘time crystal’ was recently proposed, but was later shown to be forbidden in thermal equilibrium. However, non-equilibrium Floquet systems, which are subject to a periodic drive, can exhibit persistent time correlations at an emergent subharmonic frequency. This new phase of matter has been dubbed a ‘discrete time crystal’. Here we present the experimental observation of a discrete time crystal, in an interacting spin chain of trapped atomic ions. We apply a periodic Hamiltonian to the system under many-body localization conditions, and observe a subharmonic temporal response that is robust to external perturbations. The observation of such a time crystal opens the door to the study of systems with long-range spatio-temporal correlations and novel phases of matter that emerge under intrinsically non-equilibrium conditions.
Observation of a discrete time crystal.
Zhang, J; Hess, P W; Kyprianidis, A; Becker, P; Lee, A; Smith, J; Pagano, G; Potirniche, I-D; Potter, A C; Vishwanath, A; Yao, N Y; Monroe, C
2017-03-08
Spontaneous symmetry breaking is a fundamental concept in many areas of physics, including cosmology, particle physics and condensed matter. An example is the breaking of spatial translational symmetry, which underlies the formation of crystals and the phase transition from liquid to solid. Using the analogy of crystals in space, the breaking of translational symmetry in time and the emergence of a 'time crystal' was recently proposed, but was later shown to be forbidden in thermal equilibrium. However, non-equilibrium Floquet systems, which are subject to a periodic drive, can exhibit persistent time correlations at an emergent subharmonic frequency. This new phase of matter has been dubbed a 'discrete time crystal'. Here we present the experimental observation of a discrete time crystal, in an interacting spin chain of trapped atomic ions. We apply a periodic Hamiltonian to the system under many-body localization conditions, and observe a subharmonic temporal response that is robust to external perturbations. The observation of such a time crystal opens the door to the study of systems with long-range spatio-temporal correlations and novel phases of matter that emerge under intrinsically non-equilibrium conditions.
NASA Astrophysics Data System (ADS)
Papalexiou, Simon Michael
2018-05-01
Hydroclimatic processes come in all "shapes and sizes". They are characterized by different spatiotemporal correlation structures and probability distributions that can be continuous, mixed-type, discrete or even binary. Simulating such processes by reproducing precisely their marginal distribution and linear correlation structure, including features like intermittency, can greatly improve hydrological analysis and design. Traditionally, modelling schemes are case specific and typically attempt to preserve few statistical moments providing inadequate and potentially risky distribution approximations. Here, a single framework is proposed that unifies, extends, and improves a general-purpose modelling strategy, based on the assumption that any process can emerge by transforming a specific "parent" Gaussian process. A novel mathematical representation of this scheme, introducing parametric correlation transformation functions, enables straightforward estimation of the parent-Gaussian process yielding the target process after the marginal back transformation, while it provides a general description that supersedes previous specific parameterizations, offering a simple, fast and efficient simulation procedure for every stationary process at any spatiotemporal scale. This framework, also applicable for cyclostationary and multivariate modelling, is augmented with flexible parametric correlation structures that parsimoniously describe observed correlations. Real-world simulations of various hydroclimatic processes with different correlation structures and marginals, such as precipitation, river discharge, wind speed, humidity, extreme events per year, etc., as well as a multivariate example, highlight the flexibility, advantages, and complete generality of the method.
Actinide migration in Johnston Atoll soil
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wolf, S. F.; Bates, J. K.; Buck, E. C.
1997-02-01
Characterization of the actinide content of a sample of contaminated coral soil from Johnston Atoll, the site of three non-nuclear destructs of nuclear warhead-carrying THOR missiles in 1962, revealed that >99% of the total actinide content is associated with discrete bomb fragments. After removal of these fragments, there was an inverse correlation between actinide content and soil particle size in particles from 43 to 0.4 {micro}m diameter. Detailed analyses of this remaining soil revealed no discrete actinide phase in these soil particles, despite measurable actinide content. Observations indicate that exposure to the environment has caused the conversion of relatively insolublemore » actinide oxides to the more soluble actinyl oxides and actinyl carbonate coordinated complexes. This process has led to dissolution of actinides from discrete particles and migration to the surrounding soil surfaces, resulting in a dispersion greater than would be expected by physical transport of discrete particles alone.« less
High-order nonuniformly correlated beams
NASA Astrophysics Data System (ADS)
Wu, Dan; Wang, Fei; Cai, Yangjian
2018-02-01
We have introduced a class of partially coherent beams with spatially varying correlations named high-order nonuniformly correlated (HNUC) beams, as an extension of conventional nonuniformly correlated (NUC) beams. Such beams bring a new parameter (mode order) which is used to tailor the spatial coherence properties. The behavior of the spectral density of the HNUC beams on propagation has been investigated through numerical examples with the help of discrete model decomposition and fast Fourier transform (FFT) algorithm. Our results reveal that by selecting the mode order appropriately, the more sharpened intensity maxima can be achieved at a certain propagation distance compared to that of the NUC beams, and the lateral shift of the intensity maxima on propagation is closed related to the mode order. Furthermore, analytical expressions for the r.m.s width and the propagation factor of the HNUC beams on free-space propagation are derived by means of Wigner distribution function. The influence of initial beam parameters on the evolution of the r.m.s width and the propagation factor, and the relation between the r.m.s width and the occurring of the sharpened intensity maxima on propagation have been studied and discussed in detail.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Woods, M. P.; Centre for Quantum Technologies, National University of Singapore; QuTech, Delft University of Technology, Lorentzweg 1, 2611 CJ Delft
2016-02-15
Instances of discrete quantum systems coupled to a continuum of oscillators are ubiquitous in physics. Often the continua are approximated by a discrete set of modes. We derive error bounds on expectation values of system observables that have been time evolved under such discretised Hamiltonians. These bounds take on the form of a function of time and the number of discrete modes, where the discrete modes are chosen according to Gauss quadrature rules. The derivation makes use of tools from the field of Lieb-Robinson bounds and the theory of orthonormal polynomials.
Wavelet transforms with discrete-time continuous-dilation wavelets
NASA Astrophysics Data System (ADS)
Zhao, Wei; Rao, Raghuveer M.
1999-03-01
Wavelet constructions and transforms have been confined principally to the continuous-time domain. Even the discrete wavelet transform implemented through multirate filter banks is based on continuous-time wavelet functions that provide orthogonal or biorthogonal decompositions. This paper provides a novel wavelet transform construction based on the definition of discrete-time wavelets that can undergo continuous parameter dilations. The result is a transformation that has the advantage of discrete-time or digital implementation while circumventing the problem of inadequate scaling resolution seen with conventional dyadic or M-channel constructions. Examples of constructing such wavelets are presented.
Absence of Quantum Time Crystals.
Watanabe, Haruki; Oshikawa, Masaki
2015-06-26
In analogy with crystalline solids around us, Wilczek recently proposed the idea of "time crystals" as phases that spontaneously break the continuous time translation into a discrete subgroup. The proposal stimulated further studies and vigorous debates whether it can be realized in a physical system. However, a precise definition of the time crystal is needed to resolve the issue. Here we first present a definition of time crystals based on the time-dependent correlation functions of the order parameter. We then prove a no-go theorem that rules out the possibility of time crystals defined as such, in the ground state or in the canonical ensemble of a general Hamiltonian, which consists of not-too-long-range interactions.
Molecular Theory for Electrokinetic Transport in pH-Regulated Nanochannels.
Kong, Xian; Jiang, Jian; Lu, Diannan; Liu, Zheng; Wu, Jianzhong
2014-09-04
Ion transport through nanochannels depends on various external driving forces as well as the structural and hydrodynamic inhomogeneity of the confined fluid inside of the pore. Conventional models of electrokinetic transport neglect the discrete nature of ionic species and electrostatic correlations important at the boundary and often lead to inconsistent predictions of the surface potential and the surface charge density. Here, we demonstrate that the electrokinetic phenomena can be successfully described by the classical density functional theory in conjunction with the Navier-Stokes equation for the fluid flow. The new theoretical procedure predicts ion conductivity in various pH-regulated nanochannels under different driving forces, in excellent agreement with experimental data.
NASA Astrophysics Data System (ADS)
Kanaun, S.; Markov, A.
2017-06-01
An efficient numerical method for solution of static problems of elasticity for an infinite homogeneous medium containing inhomogeneities (cracks and inclusions) is developed. Finite number of heterogeneous inclusions and planar parallel cracks of arbitrary shapes is considered. The problem is reduced to a system of surface integral equations for crack opening vectors and volume integral equations for stress tensors inside the inclusions. For the numerical solution of these equations, a class of Gaussian approximating functions is used. The method based on these functions is mesh free. For such functions, the elements of the matrix of the discretized system are combinations of explicit analytical functions and five standard 1D-integrals that can be tabulated. Thus, the numerical integration is excluded from the construction of the matrix of the discretized problem. For regular node grids, the matrix of the discretized system has Toeplitz's properties, and Fast Fourier Transform technique can be used for calculation matrix-vector products of such matrices.
Discrete-time BAM neural networks with variable delays
NASA Astrophysics Data System (ADS)
Liu, Xin-Ge; Tang, Mei-Lan; Martin, Ralph; Liu, Xin-Bi
2007-07-01
This Letter deals with the global exponential stability of discrete-time bidirectional associative memory (BAM) neural networks with variable delays. Using a Lyapunov functional, and linear matrix inequality techniques (LMI), we derive a new delay-dependent exponential stability criterion for BAM neural networks with variable delays. As this criterion has no extra constraints on the variable delay functions, it can be applied to quite general BAM neural networks with a broad range of time delay functions. It is also easy to use in practice. An example is provided to illustrate the theoretical development.
Cognitive-motor interactions of the basal ganglia in development
Leisman, Gerry; Braun-Benjamin, Orit; Melillo, Robert
2014-01-01
Neural circuits linking activity in anatomically segregated populations of neurons in subcortical structures and the neocortex throughout the human brain regulate complex behaviors such as walking, talking, language comprehension, and other cognitive functions associated with frontal lobes. The basal ganglia, which regulate motor control, are also crucial elements in the circuits that confer human reasoning and adaptive function. The basal ganglia are key elements in the control of reward-based learning, sequencing, discrete elements that constitute a complete motor act, and cognitive function. Imaging studies of intact human subjects and electrophysiologic and tracer studies of the brains and behavior of other species confirm these findings. We know that the relation between the basal ganglia and the cerebral cortical region allows for connections organized into discrete circuits. Rather than serving as a means for widespread cortical areas to gain access to the motor system, these loops reciprocally interconnect a large and diverse set of cerebral cortical areas with the basal ganglia. Neuronal activity within the basal ganglia associated with motor areas of the cerebral cortex is highly correlated with parameters of movement. Neuronal activity within the basal ganglia and cerebellar loops associated with the prefrontal cortex is related to the aspects of cognitive function. Thus, individual loops appear to be involved in distinct behavioral functions. Damage to the basal ganglia of circuits with motor areas of the cortex leads to motor symptoms, whereas damage to the subcortical components of circuits with non-motor areas of the cortex causes higher-order deficits. In this report, we review some of the anatomic, physiologic, and behavioral findings that have contributed to a reappraisal of function concerning the basal ganglia and cerebellar loops with the cerebral cortex and apply it in clinical applications to attention deficit/hyperactivity disorder (ADHD) with biomechanics and a discussion of retention of primitive reflexes being highly associated with the condition. PMID:24592214
Convergence behavior of delayed discrete cellular neural network without periodic coefficients.
Wang, Jinling; Jiang, Haijun; Hu, Cheng; Ma, Tianlong
2014-05-01
In this paper, we study convergence behaviors of delayed discrete cellular neural networks without periodic coefficients. Some sufficient conditions are derived to ensure all solutions of delayed discrete cellular neural network without periodic coefficients converge to a periodic function, by applying mathematical analysis techniques and the properties of inequalities. Finally, some examples showing the effectiveness of the provided criterion are given. Copyright © 2014 Elsevier Ltd. All rights reserved.
Teaching Math More Effectively, Through the Design of Calculational Proofs.
1994-03-01
typically taught in a first discrete math course -e.g. set theory, mathematical induction, a theory of integers, finc- tions and relations, combinatorics...by all who want to teach mathematics effectively. 4 4 The authors’ 500-pape text A Logical Approach to Discrete Math (Springer Verlag NY, 1993) uses...the appr,.., h described in this article in teaching the usual topics in discrete math -logic, set theory, & theory of integers, induct,., functions
Madurga, Sergio; Martín-Molina, Alberto; Vilaseca, Eudald; Mas, Francesc; Quesada-Pérez, Manuel
2007-06-21
The structure of the electric double layer in contact with discrete and continuously charged planar surfaces is studied within the framework of the primitive model through Monte Carlo simulations. Three different discretization models are considered together with the case of uniform distribution. The effect of discreteness is analyzed in terms of charge density profiles. For point surface groups, a complete equivalence with the situation of uniformly distributed charge is found if profiles are exclusively analyzed as a function of the distance to the charged surface. However, some differences are observed moving parallel to the surface. Significant discrepancies with approaches that do not account for discreteness are reported if charge sites of finite size placed on the surface are considered.
High Grazing Angle and High Resolution Sea Clutter: Correlation and Polarisation Analyses
2007-03-01
the azimuthal correlation. The correlation between the HH and VV sea clutter data is low. A CA-CFAR ( cell average constant false-alarm rate...to calculate the power spectra of correlation profiles. The frequency interval of the traditional Discrete Fourier Transform is NT1 Hz, where N and...sea spikes, the Entropy-Alpha decomposition of sea spikes is shown in Figure 30. The process first locates spikes using a cell -average constant false
Ma, Q; Tipping, R H; Boulet, C
2006-01-07
By introducing the coordinate representation, the derivation of the perturbation expansion of the Liouville S matrix is formulated in terms of classically behaved autocorrelation functions. Because these functions are characterized by a pair of irreducible tensors, their number is limited to a few. They represent how the overlaps of the potential components change with a time displacement, and under normal conditions, their magnitudes decrease by several orders of magnitude when the displacement reaches several picoseconds. The correlation functions contain all dynamical information of the collision processes necessary in calculating half-widths and shifts and can be easily derived with high accuracy. Their well-behaved profiles, especially the rapid decrease of the magnitude, enables one to transform easily the dynamical information contained in them from the time domain to the frequency domain. More specifically, because these correlation functions are well time limited, their continuous Fourier transforms should be band limited. Then, the latter can be accurately replaced by discrete Fourier transforms and calculated with a standard fast Fourier transform method. Besides, one can easily calculate their Cauchy principal integrations and derive all functions necessary in calculating half-widths and shifts. A great advantage resulting from introducing the coordinate representation and choosing the correlation functions as the starting point is that one is able to calculate the half-widths and shifts with high accuracy, no matter how complicated the potential models are and no matter what kind of trajectories are chosen. In any case, the convergence of the calculated results is always guaranteed. As a result, with this new method, one can remove some uncertainties incorporated in the current width and shift studies. As a test, we present calculated Raman Q linewidths for the N2-N2 pair based on several trajectories, including the more accurate "exact" ones. Finally, by using this new method as a benchmark, we have carried out convergence checks for calculated values based on usual methods and have found that some results in the literature are not converged.
Calculation of power spectrums from digital time series with missing data points
NASA Technical Reports Server (NTRS)
Murray, C. W., Jr.
1980-01-01
Two algorithms are developed for calculating power spectrums from the autocorrelation function when there are missing data points in the time series. Both methods use an average sampling interval to compute lagged products. One method, the correlation function power spectrum, takes the discrete Fourier transform of the lagged products directly to obtain the spectrum, while the other, the modified Blackman-Tukey power spectrum, takes the Fourier transform of the mean lagged products. Both techniques require fewer calculations than other procedures since only 50% to 80% of the maximum lags need be calculated. The algorithms are compared with the Fourier transform power spectrum and two least squares procedures (all for an arbitrary data spacing). Examples are given showing recovery of frequency components from simulated periodic data where portions of the time series are missing and random noise has been added to both the time points and to values of the function. In addition the methods are compared using real data. All procedures performed equally well in detecting periodicities in the data.
2014-04-01
The CG and DG horizontal discretization employs high-order nodal basis functions associated with Lagrange polynomials based on Gauss-Lobatto- Legendre ...and DG horizontal discretization employs high-order nodal basis functions 29 associated with Lagrange polynomials based on Gauss-Lobatto- Legendre ...Inside 235 each element we build ( 1)N + Gauss-Lobatto- Legendre (GLL) quadrature points, where N 236 indicate the polynomial order of the basis
NASA Astrophysics Data System (ADS)
Vogelgesang, Jonas; Schorr, Christian
2016-12-01
We present a semi-discrete Landweber-Kaczmarz method for solving linear ill-posed problems and its application to Cone Beam tomography and laminography. Using a basis function-type discretization in the image domain, we derive a semi-discrete model of the underlying scanning system. Based on this model, the proposed method provides an approximate solution of the reconstruction problem, i.e. reconstructing the density function of a given object from its projections, in suitable subspaces equipped with basis function-dependent weights. This approach intuitively allows the incorporation of additional information about the inspected object leading to a more accurate model of the X-rays through the object. Also, physical conditions of the scanning geometry, like flat detectors in computerized tomography as used in non-destructive testing applications as well as non-regular scanning curves e.g. appearing in computed laminography (CL) applications, are directly taken into account during the modeling process. Finally, numerical experiments of a typical CL application in three dimensions are provided to verify the proposed method. The introduction of geometric prior information leads to a significantly increased image quality and superior reconstructions compared to standard iterative methods.
Theory of Stochastic Laplacian Growth
NASA Astrophysics Data System (ADS)
Alekseev, Oleg; Mineev-Weinstein, Mark
2017-07-01
We generalize the diffusion-limited aggregation by issuing many randomly-walking particles, which stick to a cluster at the discrete time unit providing its growth. Using simple combinatorial arguments we determine probabilities of different growth scenarios and prove that the most probable evolution is governed by the deterministic Laplacian growth equation. A potential-theoretical analysis of the growth probabilities reveals connections with the tau-function of the integrable dispersionless limit of the two-dimensional Toda hierarchy, normal matrix ensembles, and the two-dimensional Dyson gas confined in a non-uniform magnetic field. We introduce the time-dependent Hamiltonian, which generates transitions between different classes of equivalence of closed curves, and prove the Hamiltonian structure of the interface dynamics. Finally, we propose a relation between probabilities of growth scenarios and the semi-classical limit of certain correlation functions of "light" exponential operators in the Liouville conformal field theory on a pseudosphere.
Gu, Ai-Di; Wang, Yunqi; Lin, Lin; Zhang, Song S; Wan, Yisong Y
2012-01-17
TGF-β modulates immune response by suppressing non-regulatory T (Treg) function and promoting Treg function. The question of whether TGF-β achieves distinct effects on non-Treg and Treg cells through discrete signaling pathways remains outstanding. In this study, we investigated the requirements of Smad-dependent and -independent TGF-β signaling for T-cell function. Smad2 and Smad3 double deficiency in T cells led to lethal inflammatory disorder in mice. Non-Treg cells were spontaneously activated and produced effector cytokines in vivo on deletion of both Smad2 and Smad3. In addition, TGF-β failed to suppress T helper differentiation efficiently and to promote induced Treg generation of non-Treg cells lacking both Smad2 and Smad3, suggesting that Smad-dependent signaling is obligatory to mediate TGF-β function in non-Treg cells. Unexpectedly, however, the development, homeostasis, and function of Treg cells remained intact in the absence of Smad2 and Smad3, suggesting that the Smad-independent pathway is important for Treg function. Indeed, Treg-specific deletion of TGF-β-activated kinase 1 led to failed Treg homeostasis and lethal immune disorder in mice. Therefore, Smad-dependent and -independent TGF-β signaling discretely controls non-Treg and Treg function to modulate immune tolerance and immune homeostasis.
NASA Technical Reports Server (NTRS)
Ko, William L.; Fleischer, Van Tran
2012-01-01
In the formulations of earlier Displacement Transfer Functions for structure shape predictions, the surface strain distributions, along a strain-sensing line, were represented with piecewise linear functions. To improve the shape-prediction accuracies, Improved Displacement Transfer Functions were formulated using piecewise nonlinear strain representations. Through discretization of an embedded beam (depth-wise cross section of a structure along a strain-sensing line) into multiple small domains, piecewise nonlinear functions were used to describe the surface strain distributions along the discretized embedded beam. Such piecewise approach enabled the piecewise integrations of the embedded beam curvature equations to yield slope and deflection equations in recursive forms. The resulting Improved Displacement Transfer Functions, written in summation forms, were expressed in terms of beam geometrical parameters and surface strains along the strain-sensing line. By feeding the surface strains into the Improved Displacement Transfer Functions, structural deflections could be calculated at multiple points for mapping out the overall structural deformed shapes for visual display. The shape-prediction accuracies of the Improved Displacement Transfer Functions were then examined in view of finite-element-calculated deflections using different tapered cantilever tubular beams. It was found that by using the piecewise nonlinear strain representations, the shape-prediction accuracies could be greatly improved, especially for highly-tapered cantilever tubular beams.
Experiments in a flighted conveyor comparing shear rates in compressed versus free surface flows
NASA Astrophysics Data System (ADS)
Pohlman, Nicholas; Higgins, Hannah; Krupiarz, Kamila; O'Connor, Ryan
2017-11-01
Uniformity of granular flow rate is critical in industry. Experiments in a flighted conveyor system aim to fill a gap in knowledge of achieving steady mass flow rate by correlating velocity profile data with mass flow rate measurements. High speed images were collected for uniformly-shaped particles in a bottom-driven flow conveyor belt system from which the velocity profiles can be generated. The correlation of mass flow rates from the velocity profiles to the time-dependent mass measurements will determine energy dissipation rates as a function of operating conditions. The velocity profiles as a function of the size of the particles, speed of the belt, and outlet size, will be compared to shear rate relationships found in past experiments that focused on gravity-driven systems. The dimension of the linear shear and type of decaying transition to the stationary bed may appear different due to the compression versus dilation space in open flows. The application of this research can serve to validate simulations in discrete element modeling and physically demonstrate a process that can be further developed and customized for industry applications, such as feeding a biomass conversion reactor. Sponsored by NIU's Office of Student Engagement and Experiential Learning.
Brandao, Livia M; Monhart, Matthias; Schötzau, Andreas; Ledolter, Anna A; Palmowski-Wolfe, Anja M
2017-08-01
To further improve analysis of the two-flash multifocal electroretinogram (2F-mfERG) in glaucoma in regard to structure-function analysis, using discrete wavelet transform (DWT) analysis. Sixty subjects [35 controls and 25 primary open-angle glaucoma (POAG)] underwent 2F-mfERG. Responses were analyzed with the DWT. The DWT level that could best separate POAG from controls was compared to the root-mean-square (RMS) calculations previously used in the analysis of the 2F-mfERG. In a subgroup analysis, structure-function correlation was assessed between DWT, optical coherence tomography and automated perimetry (mf103 customized pattern) for the central 15°. Frequency level 4 of the wavelet variance analysis (144 Hz, WVA-144) was most sensitive (p < 0.003). It correlated positively with RMS but had a better AUC. Positive relations were found between visual field, WVA-144 and GCIPL thickness. The highest predictive factor for glaucoma diagnostic was seen in the GCIPL, but this improved further by adding the mean sensitivity and WVA-144. mfERG using WVA analysis improves glaucoma diagnosis, especially when combined with GCIPL and MS.
Response of discrete linear systems to forcing functions with inequality constraints.
NASA Technical Reports Server (NTRS)
Michalopoulos, C. D.; Riley, T. A.
1972-01-01
An analysis is made of the maximum response of discrete, linear mechanical systems to arbitrary forcing functions which lie within specified bounds. Primary attention is focused on the complete determination of the forcing function which will engender maximum displacement to any particular mass element of a multi-degree-of-freedom system. In general, the desired forcing function is found to be a bang-bang type function, i.e., a function which switches from the maximum to the minimum bound and vice-versa at certain instants of time. Examples of two-degree-of-freedom systems, with and without damping, are presented in detail. Conclusions are drawn concerning the effect of damping on the switching times and the general procedure for finding these times is discussed.
Computer simulation of surface and film processes
NASA Technical Reports Server (NTRS)
Tiller, W. A.; Halicioglu, M. T.
1983-01-01
Adequate computer methods, based on interactions between discrete particles, provide information leading to an atomic level understanding of various physical processes. The success of these simulation methods, however, is related to the accuracy of the potential energy function representing the interactions among the particles. The development of a potential energy function for crystalline SiO2 forms that can be employed in lengthy computer modelling procedures was investigated. In many of the simulation methods which deal with discrete particles, semiempirical two body potentials were employed to analyze energy and structure related properties of the system. Many body interactions are required for a proper representation of the total energy for many systems. Many body interactions for simulations based on discrete particles are discussed.
Zhou, Q.; Salve, R.; Liu, H.-H.; Wang, J.S.Y.; Hudson, D.
2006-01-01
A mesoscale (21??m in flow distance) infiltration and seepage test was recently conducted in a deep, unsaturated fractured rock system at the crossover point of two underground tunnels. Water was released from a 3??m ?? 4??m infiltration plot on the floor of an alcove in the upper tunnel, and seepage was collected from the ceiling of a niche in the lower tunnel. Significant temporal and (particularly) spatial variabilities were observed in both measured infiltration and seepage rates. To analyze the test results, a three-dimensional unsaturated flow model was used. A column-based scheme was developed to capture heterogeneous hydraulic properties reflected by these spatial variabilities observed. Fracture permeability and van Genuchten ?? parameter [van Genuchten, M.T., 1980. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J. 44, 892-898] were calibrated for each rock column in the upper and lower hydrogeologic units in the test bed. The calibrated fracture properties for the infiltration and seepage zone enabled a good match between simulated and measured (spatially varying) seepage rates. The numerical model was also able to capture the general trend of the highly transient seepage processes through a discrete fracture network. The calibrated properties and measured infiltration/seepage rates were further compared with mapped discrete fracture patterns at the top and bottom boundaries. The measured infiltration rates and calibrated fracture permeability of the upper unit were found to be partially controlled by the fracture patterns on the infiltration plot (as indicated by their positive correlations with fracture density). However, no correlation could be established between measured seepage rates and density of fractures mapped on the niche ceiling. This lack of correlation indicates the complexity of (preferential) unsaturated flow within the discrete fracture network. This also indicates that continuum-based modeling of unsaturated flow in fractured rock at mesoscale or a larger scale is not necessarily conditional explicitly on discrete fracture patterns. ?? 2006 Elsevier B.V. All rights reserved.
Discrete Tchebycheff orthonormal polynomials and applications
NASA Technical Reports Server (NTRS)
Lear, W. M.
1980-01-01
Discrete Tchebycheff orthonormal polynomials offer a convenient way to make least squares polynomial fits of uniformly spaced discrete data. Computer programs to do so are simple and fast, and appear to be less affected by computer roundoff error, for the higher order fits, than conventional least squares programs. They are useful for any application of polynomial least squares fits: approximation of mathematical functions, noise analysis of radar data, and real time smoothing of noisy data, to name a few.
THE STATISTICAL ANALYSIS OF DISCRETE AND CONTINUOUS OUTCOMES USING DESIRABILITY FUNCTIONS.
Multiple types of outcomes are sometimes measured on each animal in toxicology dose-response experiments. In this paper we introduce a method of deriving a composite score for a dose-response experiment that combines information from discrete and continuous outcomes through the ...
NASA Technical Reports Server (NTRS)
Nixon, Douglas D.
2009-01-01
Discrete/Continuous (D/C) control theory is a new generalized theory of discrete-time control that expands the concept of conventional (exact) discrete-time control to create a framework for design and implementation of discretetime control systems that include a continuous-time command function generator so that actuator commands need not be constant between control decisions, but can be more generally defined and implemented as functions that vary with time across sample period. Because the plant/control system construct contains two linear subsystems arranged in tandem, a novel dual-kernel counter-flow convolution integral appears in the formulation. As part of the D/C system design and implementation process, numerical evaluation of that integral over the sample period is required. Three fundamentally different evaluation methods and associated algorithms are derived for the constant-coefficient case. Numerical results are matched against three available examples that have closed-form solutions.
Meshes optimized for discrete exterior calculus (DEC).
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mousley, Sarah C.; Deakin, Michael; Knupp, Patrick
We study the optimization of an energy function used by the meshing community to measure and improve mesh quality. This energy is non-traditional because it is dependent on both the primal triangulation and its dual Voronoi (power) diagram. The energy is a measure of the mesh's quality for usage in Discrete Exterior Calculus (DEC), a method for numerically solving PDEs. In DEC, the PDE domain is triangulated and this mesh is used to obtain discrete approximations of the continuous operators in the PDE. The energy of a mesh gives an upper bound on the error of the discrete diagonal approximationmore » of the Hodge star operator. In practice, one begins with an initial mesh and then makes adjustments to produce a mesh of lower energy. However, we have discovered several shortcomings in directly optimizing this energy, e.g. its non-convexity, and we show that the search for an optimized mesh may lead to mesh inversion (malformed triangles). We propose a new energy function to address some of these issues.« less
Flexural waves induced by electro-impulse deicing forces
NASA Technical Reports Server (NTRS)
Gien, P. H.
1990-01-01
The generation, reflection and propagation of flexural waves created by electroimpulsive deicing forces are demonstrated both experimentally and analytically in a thin circular plate and a thin semicylindrical shell. Analytical prediction of these waves with finite element models shows good correlation with acceleration and displacement measurements at discrete points on the structures studied. However, sensitivity to spurious flexural waves resulting from the spatial discretization of the structures is shown to be significant. Consideration is also given to composite structures as an extension of these studies.
Dilution jet mixing program, phase 3
NASA Technical Reports Server (NTRS)
Srinivasan, R.; Coleman, E.; Myers, G.; White, C.
1985-01-01
The main objectives for the NASA Jet Mixing Phase 3 program were: extension of the data base on the mixing of single sided rows of jets in a confined cross flow to discrete slots, including streamlined, bluff, and angled injections; quantification of the effects of geometrical and flow parameters on penetration and mixing of multiple rows of jets into a confined flow; investigation of in-line, staggered, and dissimilar hole configurations; and development of empirical correlations for predicting temperature distributions for discrete slots and multiple rows of dilution holes.
Mohamed Yacin, S; Srinivasa Chakravarthy, V; Manivannan, M
2011-11-01
Extraction of extra-cardiac information from photoplethysmography (PPG) signal is a challenging research problem with significant clinical applications. In this study, radial basis function neural network (RBFNN) is used to reconstruct the gastric myoelectric activity (GMA) slow wave from finger PPG signal. Finger PPG and GMA (measured using Electrogastrogram, EGG) signals were acquired simultaneously at the sampling rate of 100 Hz from ten healthy subjects. Discrete wavelet transform (DWT) was used to extract slow wave (0-0.1953 Hz) component from the finger PPG signal; this slow wave PPG was used to reconstruct EGG. A RBFNN is trained on signals obtained from six subjects in both fasting and postprandial conditions. The trained network is tested on data obtained from the remaining four subjects. In the earlier study, we have shown the presence of GMA information in finger PPG signal using DWT and cross-correlation method. In this study, we explicitly reconstruct gastric slow wave from finger PPG signal by the proposed RBFNN-based method. It was found that the network-reconstructed slow wave provided significantly higher (P < 0.0001) correlation (≥ 0.9) with the subject's EGG slow wave than the correlation obtained (≈0.7) between the PPG slow wave from DWT and the EEG slow wave. Our results showed that a simple finger PPG signal can be used to reconstruct gastric slow wave using RBFNN method.
Statistical characteristics of the sequential detection of signals in correlated noise
NASA Astrophysics Data System (ADS)
Averochkin, V. A.; Baranov, P. E.
1985-10-01
A solution is given to the problem of determining the distribution of the duration of the sequential two-threshold Wald rule for the time-discrete detection of determinate and Gaussian correlated signals on a background of Gaussian correlated noise. Expressions are obtained for the joint probability densities of the likelihood ratio logarithms, and an analysis is made of the effect of correlation and SNR on the duration distribution and the detection efficiency. Comparison is made with Neumann-Pearson detection.
Dual Formulations of Mixed Finite Element Methods with Applications
Gillette, Andrew; Bajaj, Chandrajit
2011-01-01
Mixed finite element methods solve a PDE using two or more variables. The theory of Discrete Exterior Calculus explains why the degrees of freedom associated to the different variables should be stored on both primal and dual domain meshes with a discrete Hodge star used to transfer information between the meshes. We show through analysis and examples that the choice of discrete Hodge star is essential to the numerical stability of the method. Additionally, we define interpolation functions and discrete Hodge stars on dual meshes which can be used to create previously unconsidered mixed methods. Examples from magnetostatics and Darcy flow are examined in detail. PMID:21984841
Discrete time-crystalline order in black diamond
NASA Astrophysics Data System (ADS)
Zhou, Hengyun; Choi, Soonwon; Choi, Joonhee; Landig, Renate; Kucsko, Georg; Isoya, Junichi; Jelezko, Fedor; Onoda, Shinobu; Sumiya, Hitoshi; Khemani, Vedika; von Keyserlingk, Curt; Yao, Norman; Demler, Eugene; Lukin, Mikhail D.
2017-04-01
The interplay of periodic driving, disorder, and strong interactions has recently been predicted to result in exotic ``time-crystalline'' phases, which spontaneously break the discrete time-translation symmetry of the underlying drive. Here, we report the experimental observation of such discrete time-crystalline order in a driven, disordered ensemble of 106 dipolar spin impurities in diamond at room-temperature. We observe long-lived temporal correlations at integer multiples of the fundamental driving period, experimentally identify the phase boundary and find that the temporal order is protected by strong interactions; this order is remarkably stable against perturbations, even in the presence of slow thermalization. Our work opens the door to exploring dynamical phases of matter and controlling interacting, disordered many-body systems.
Shape functions for velocity interpolation in general hexahedral cells
Naff, R.L.; Russell, T.F.; Wilson, J.D.
2002-01-01
Numerical methods for grids with irregular cells require discrete shape functions to approximate the distribution of quantities across cells. For control-volume mixed finite-element (CVMFE) methods, vector shape functions approximate velocities and vector test functions enforce a discrete form of Darcy's law. In this paper, a new vector shape function is developed for use with irregular, hexahedral cells (trilinear images of cubes). It interpolates velocities and fluxes quadratically, because as shown here, the usual Piola-transformed shape functions, which interpolate linearly, cannot match uniform flow on general hexahedral cells. Truncation-error estimates for the shape function are demonstrated. CVMFE simulations of uniform and non-uniform flow with irregular meshes show first- and second-order convergence of fluxes in the L2 norm in the presence and absence of singularities, respectively.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stück, Arthur, E-mail: arthur.stueck@dlr.de
2015-11-15
Inconsistent discrete expressions in the boundary treatment of Navier–Stokes solvers and in the definition of force objective functionals can lead to discrete-adjoint boundary treatments that are not a valid representation of the boundary conditions to the corresponding adjoint partial differential equations. The underlying problem is studied for an elementary 1D advection–diffusion problem first using a node-centred finite-volume discretisation. The defect of the boundary operators in the inconsistently defined discrete-adjoint problem leads to oscillations and becomes evident with the additional insight of the continuous-adjoint approach. A homogenisation of the discretisations for the primal boundary treatment and the force objective functional yieldsmore » second-order functional accuracy and eliminates the defect in the discrete-adjoint boundary treatment. Subsequently, the issue is studied for aerodynamic Reynolds-averaged Navier–Stokes problems in conjunction with a standard finite-volume discretisation on median-dual grids and a strong implementation of noslip walls, found in many unstructured general-purpose flow solvers. Going out from a base-line discretisation of force objective functionals which is independent of the boundary treatment in the flow solver, two improved flux-consistent schemes are presented; based on either body wall-defined or farfield-defined control-volumes they resolve the dual inconsistency. The behaviour of the schemes is investigated on a sequence of grids in 2D and 3D.« less
Time Series Analysis of the Quasar PKS 1749+096
NASA Astrophysics Data System (ADS)
Lam, Michael T.; Balonek, T. J.
2011-01-01
Multiple timescales of variability are observed in quasars at a variety of wavelengths, the nature of which is not fully understood. In 2007 and 2008, the quasar 1749+096 underwent two unprecedented optical outbursts, reaching a brightness never before seen in our twenty years of monitoring. Much lower level activity had been seen prior to these two outbursts. We present an analysis of the timescales of variability over the two regimes using a variety of statistical techniques. An IDL software package developed at Colgate University over the summer of 2010, the Quasar User Interface (QUI), provides effective computation of four time series functions for analyzing underlying trends present in generic, discretely sampled data sets. Using the Autocorrelation Function, Structure Function, and Power Spectrum, we are able to quickly identify possible variability timescales. QUI is also capable of computing the Cross-Correlation Function for comparing variability at different wavelengths. We apply these algorithms to 1749+096 and present our analysis of the timescales for this object. Funding for this project was received from Colgate University, the Justus and Jayne Schlichting Student Research Fund, and the NASA / New York Space Grant.
General optical discrete z transform: design and application.
Ngo, Nam Quoc
2016-12-20
This paper presents a generalization of the discrete z transform algorithm. It is shown that the GOD-ZT algorithm is a generalization of several important conventional discrete transforms. Based on the GOD-ZT algorithm, a tunable general optical discrete z transform (GOD-ZT) processor is synthesized using the silica-based finite impulse response transversal filter. To demonstrate the effectiveness of the method, the design and simulation of a tunable optical discrete Fourier transform (ODFT) processor as a special case of the synthesized GOD-ZT processor is presented. It is also shown that the ODFT processor can function as a real-time optical spectrum analyzer. The tunable ODFT has an important potential application as a tunable optical demultiplexer at the receiver end of an optical orthogonal frequency-division multiplexing transmission system.
The interactive digital video interface
NASA Technical Reports Server (NTRS)
Doyle, Michael D.
1989-01-01
A frequent complaint in the computer oriented trade journals is that current hardware technology is progressing so quickly that software developers cannot keep up. A example of this phenomenon can be seen in the field of microcomputer graphics. To exploit the advantages of new mechanisms of information storage and retrieval, new approaches must be made towards incorporating existing programs as well as developing entirely new applications. A particular area of need is the correlation of discrete image elements to textural information. The interactive digital video (IDV) interface embodies a new concept in software design which addresses these needs. The IDV interface is a patented device and language independent process for identifying image features on a digital video display and which allows a number of different processes to be keyed to that identification. Its capabilities include the correlation of discrete image elements to relevant text information and the correlation of these image features to other images as well as to program control mechanisms. Sophisticated interrelationships can be set up between images, text, and program control mechanisms.
Investigators are frequently confronted with data sets that include both discrete observations and extended time series of environmental data that had been collected by autonomous recorders. Evaluating the relationships between these two kinds of data is challenging. A common a...
Mathematics and Computer Science: Exploring a Symbiotic Relationship
ERIC Educational Resources Information Center
Bravaco, Ralph; Simonson, Shai
2004-01-01
This paper describes a "learning community" designed for sophomore computer science majors who are simultaneously studying discrete mathematics. The learning community consists of three courses: Discrete Mathematics, Data Structures and an Integrative Seminar/Lab. The seminar functions as a link that integrates the two disciplines. Participation…
NASA Technical Reports Server (NTRS)
Springer, P.
1993-01-01
This paper discusses the method in which the Cascade-Correlation algorithm was parallelized in such a way that it could be run using the Time Warp Operating System (TWOS). TWOS is a special purpose operating system designed to run parellel discrete event simulations with maximum efficiency on parallel or distributed computers.
Global exponential stability of BAM neural networks with time-varying delays: The discrete-time case
NASA Astrophysics Data System (ADS)
Raja, R.; Marshal Anthoni, S.
2011-02-01
This paper deals with the problem of stability analysis for a class of discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. By employing the Lyapunov functional and linear matrix inequality (LMI) approach, a new sufficient conditions is proposed for the global exponential stability of discrete-time BAM neural networks. The proposed LMI based results can be easily checked by LMI control toolbox. Moreover, an example is also provided to demonstrate the effectiveness of the proposed method.
Seleson, Pablo; Du, Qiang; Parks, Michael L.
2016-08-16
The peridynamic theory of solid mechanics is a nonlocal reformulation of the classical continuum mechanics theory. At the continuum level, it has been demonstrated that classical (local) elasticity is a special case of peridynamics. Such a connection between these theories has not been extensively explored at the discrete level. This paper investigates the consistency between nearest-neighbor discretizations of linear elastic peridynamic models and finite difference discretizations of the Navier–Cauchy equation of classical elasticity. While nearest-neighbor discretizations in peridynamics have been numerically observed to present grid-dependent crack paths or spurious microcracks, this paper focuses on a different, analytical aspect of suchmore » discretizations. We demonstrate that, even in the absence of cracks, such discretizations may be problematic unless a proper selection of weights is used. Specifically, we demonstrate that using the standard meshfree approach in peridynamics, nearest-neighbor discretizations do not reduce, in general, to discretizations of corresponding classical models. We study nodal-based quadratures for the discretization of peridynamic models, and we derive quadrature weights that result in consistency between nearest-neighbor discretizations of peridynamic models and discretized classical models. The quadrature weights that lead to such consistency are, however, model-/discretization-dependent. We motivate the choice of those quadrature weights through a quadratic approximation of displacement fields. The stability of nearest-neighbor peridynamic schemes is demonstrated through a Fourier mode analysis. Finally, an approach based on a normalization of peridynamic constitutive constants at the discrete level is explored. This approach results in the desired consistency for one-dimensional models, but does not work in higher dimensions. The results of the work presented in this paper suggest that even though nearest-neighbor discretizations should be avoided in peridynamic simulations involving cracks, such discretizations are viable, for example for verification or validation purposes, in problems characterized by smooth deformations. Furthermore, we demonstrate that better quadrature rules in peridynamics can be obtained based on the functional form of solutions.« less
Non-Gaussian bias: insights from discrete density peaks
DOE Office of Scientific and Technical Information (OSTI.GOV)
Desjacques, Vincent; Riotto, Antonio; Gong, Jinn-Ouk, E-mail: Vincent.Desjacques@unige.ch, E-mail: jinn-ouk.gong@apctp.org, E-mail: Antonio.Riotto@unige.ch
2013-09-01
Corrections induced by primordial non-Gaussianity to the linear halo bias can be computed from a peak-background split or the widespread local bias model. However, numerical simulations clearly support the prediction of the former, in which the non-Gaussian amplitude is proportional to the linear halo bias. To understand better the reasons behind the failure of standard Lagrangian local bias, in which the halo overdensity is a function of the local mass overdensity only, we explore the effect of a primordial bispectrum on the 2-point correlation of discrete density peaks. We show that the effective local bias expansion to peak clustering vastlymore » simplifies the calculation. We generalize this approach to excursion set peaks and demonstrate that the resulting non-Gaussian amplitude, which is a weighted sum of quadratic bias factors, precisely agrees with the peak-background split expectation, which is a logarithmic derivative of the halo mass function with respect to the normalisation amplitude. We point out that statistics of thresholded regions can be computed using the same formalism. Our results suggest that halo clustering statistics can be modelled consistently (in the sense that the Gaussian and non-Gaussian bias factors agree with peak-background split expectations) from a Lagrangian bias relation only if the latter is specified as a set of constraints imposed on the linear density field. This is clearly not the case of standard Lagrangian local bias. Therefore, one is led to consider additional variables beyond the local mass overdensity.« less
The structure and health correlates of trait repetitive thought in older adults.
Segerstrom, Suzanne C; Roach, Abbey R; Evans, Daniel R; Schipper, Lindsey J; Darville, Audrey K
2010-09-01
Repetitive thought (RT) involves frequent or prolonged thoughts about oneself and one's world, encompassing discrete forms such as trait worry, rumination, processing, and reminiscing. These forms of RT can be described using 3 basic, underlying qualities: total propensity for RT of all types, valence (positive vs. negative content), and purpose (searching or uncertainty vs. solving or certainty). The adaptiveness of discrete forms with regard to health is likely to be related to these qualities, particularly valence and total propensity. The present study confirmed the model and identified the relationship of these qualities of RT to subjective psychological, physical, and cognitive health in older adults aged 60-94 (N = 179). As predicted, more negatively valenced trait RT was associated with worse psychological, physical, and cognitive health. More total propensity for RT was associated only with worse psychological health. Searching purpose was associated only with worse cognitive health. In turn, negatively valenced RT was predicted by poorer executive functions, suggesting that such functions may be important for directing this quality of RT. The valence of older adults' RT is important insofar as it may contribute to their sense of good or ill health. However, the propensity for all kinds of RT to associate with poorer psychological health may reflect the co-occurrence of negative and positive RT, such as rumination and emotional processing. Although RT has not been extensively investigated in older adults, it appears to play an important role in their subjective health. (c) 2010 APA, all rights reserved.
Mechanisms of chaos in billiards: dispersing, defocusing and nothing else
NASA Astrophysics Data System (ADS)
Bunimovich, Leonid A.
2018-02-01
We explain and justify that the only mechanisms of chaotic dynamics for billiards are dispersing and defocusing. We also introduce boomerang billiards which dynamics demonstrate that two rather broadly accepted views about some features of nonlinear dynamics are actually wrong. Namely correlations in billiards having focusing components of the boundary can decay exponentially, and continuous time correlations for a billiard flow may decay faster than discrete time correlations for a billiard map.
Retention capacity of correlated surfaces.
Schrenk, K J; Araújo, N A M; Ziff, R M; Herrmann, H J
2014-06-01
We extend the water retention model [C. L. Knecht et al., Phys. Rev. Lett. 108, 045703 (2012)] to correlated random surfaces. We find that the retention capacity of discrete random landscapes is strongly affected by spatial correlations among the heights. This phenomenon is related to the emergence of power-law scaling in the lake volume distribution. We also solve the uncorrelated case exactly for a small lattice and present bounds on the retention of uncorrelated landscapes.
Parada, Mayte; Gérard, Marina; Larcher, Kevin; Dagher, Alain; Binik, Yitzchak M
2018-02-01
The few studies that have examined the neural correlates of genital arousal have focused on men and are methodologically hard to compare. To investigate the neural correlates of peripheral physiologic sexual arousal using identical methodology for men and women. 2 groups (20 men, 20 women) viewed movie clips (erotic, humor) while genital temperature was continuously measured using infrared thermal imaging. Participants also continuously evaluated changes in their subjective arousal and answered discrete questions about liking the movies and wanting sexual stimulation. Brain activity, indicated by blood oxygen level-dependent (BOLD) response, was measured using functional magnetic resonance imaging. BOLD responses, genital temperature, and subjective sexual arousal. BOLD activity in a number of brain regions was correlated with changes in genital temperature in men and women; however, activation in women appeared to be more extensive than in men, including the anterior and posterior cingulate cortex, right cerebellum, insula, frontal operculum, and paracingulate gyrus. Examination of the strength of the correlation between BOLD response and genital temperature showed that women had a stronger brain-genital relation compared with men in a number of regions. There were no brain regions in men with stronger brain-genital correlations than in women. Our findings shed light on the neurophysiologic processes involved in genital arousal for men and women. Further research examining the specific brain regions that mediate our findings is necessary to pave the way for clinical application. A strength of the study is the use of thermography, which allows for a direct comparison of the neural correlates of genital arousal in men and women. This study has the common limitations of most laboratory-based sexual arousal research, including sampling bias, lack of ecologic validity, and equipment limitations, and those common to neuroimaging research, including BOLD signal interpretation and neuroimaging analysis issues. Our findings provide direct sex comparisons of the neural correlates of genital arousal in men and women and suggest that brain-genital correlations could be stronger in women. Parada M, Gérard M, Larcher K, et al. How Hot Are They? Neural Correlates of Genital Arousal: An Infrared Thermographic and Functional Magnetic Resonance Imaging Study of Sexual Arousal in Men and Women. J Sex Med 2018;15:217-229. Copyright © 2017 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.
Regions of absolute ultimate boundedness for discrete-time systems.
NASA Technical Reports Server (NTRS)
Siljak, D. D.; Weissenberger, S.
1972-01-01
This paper considers discrete-time systems of the Lur'e-Postnikov class where the linear part is not asymptotically stable and the nonlinear characteristic satisfies only partially the usual sector condition. Estimates of the resulting finite regions of absolute ultimate boundedness are calculated by means of a quadratic Liapunov function.
Using a Card Trick to Teach Discrete Mathematics
ERIC Educational Resources Information Center
Simonson, Shai; Holm, Tara S.
2003-01-01
We present a card trick that can be used to review or teach a variety of topics in discrete mathematics. We address many subjects, including permutations, combinations, functions, graphs, depth first search, the pigeonhole principle, greedy algorithms, and concepts from number theory. Moreover, the trick motivates the use of computers in…
NASA Technical Reports Server (NTRS)
Karmarkar, J. S.
1972-01-01
Proposal of an algorithmic procedure, based on mathematical programming methods, to design compensators for hyperstable discrete model-reference adaptive systems (MRAS). The objective of the compensator is to render the MRAS insensitive to initial parameter estimates within a maximized hypercube in the model parameter space.
2007-01-01
differentiability, fluid-solid interaction, error estimation, re-discretization, moving meshes 16. SECURITY CLASSIFICATION OF: 17 . LIMITATION OF 18. NUMBER...method the weight function is an indepen- dent function v = 0 6 4Ph , with v = 0 on F, if W = W0 on F1. 2. Galerkin method (GM): If Wh is an approximation...This can be demonstrated by considering a simple I-D case (like described above) in which the discretization 17 is uniform with characteristic length
NASA Astrophysics Data System (ADS)
Vásquez Lavín, F. A.; Hernandez, J. I.; Ponce, R. D.; Orrego, S. A.
2017-07-01
During recent decades, water demand estimation has gained considerable attention from scholars. From an econometric perspective, the most used functional forms include log-log and linear specifications. Despite the advances in this field and the relevance for policymaking, little attention has been paid to the functional forms used in these estimations, and most authors have not provided justifications for their selection of functional forms. A discrete continuous choice model of the residential water demand is estimated using six functional forms (log-log, full-log, log-quadratic, semilog, linear, and Stone-Geary), and the expected consumption and price elasticity are evaluated. From a policy perspective, our results highlight the relevance of functional form selection for both the expected consumption and price elasticity.
Multi-level adaptive finite element methods. 1: Variation problems
NASA Technical Reports Server (NTRS)
Brandt, A.
1979-01-01
A general numerical strategy for solving partial differential equations and other functional problems by cycling between coarser and finer levels of discretization is described. Optimal discretization schemes are provided together with very fast general solvers. It is described in terms of finite element discretizations of general nonlinear minimization problems. The basic processes (relaxation sweeps, fine-grid-to-coarse-grid transfers of residuals, coarse-to-fine interpolations of corrections) are directly and naturally determined by the objective functional and the sequence of approximation spaces. The natural processes, however, are not always optimal. Concrete examples are given and some new techniques are reviewed. Including the local truncation extrapolation and a multilevel procedure for inexpensively solving chains of many boundary value problems, such as those arising in the solution of time-dependent problems.
NASA Astrophysics Data System (ADS)
Kiss, Gellért Zsolt; Borbély, Sándor; Nagy, Ladislau
2017-12-01
We have presented here an efficient numerical approach for the ab initio numerical solution of the time-dependent Schrödinger Equation describing diatomic molecules, which interact with ultrafast laser pulses. During the construction of the model we have assumed a frozen nuclear configuration and a single active electron. In order to increase efficiency our system was described using prolate spheroidal coordinates, where the wave function was discretized using the finite-element discrete variable representation (FE-DVR) method. The discretized wave functions were efficiently propagated in time using the short-iterative Lanczos algorithm. As a first test we have studied here how the laser induced bound state dynamics in H2+ is influenced by the strength of the driving laser field.
NASA Astrophysics Data System (ADS)
Burke, Mark E.
2010-11-01
Dubois coined the term incursion, for an inclusive or implicit recursion, to describe a discrete-time anticipatory system which computes its future states by reference to its future states as well as its current and past states. In this paper, we look at a model which has been proposed in the context of a social system which has functionally differentiated subsystems. The model is derived from a discrete-time compartmental SIS epidemic model. We analyse a low order instance of the model both in its form as a recursion with no anticipatory capacity, and also as an incursion with associated anticipatory capacity. The properties of the incursion are compared and contrasted with those of the underlying recursion.
Nonlinear Control and Discrete Event Systems
NASA Technical Reports Server (NTRS)
Meyer, George; Null, Cynthia H. (Technical Monitor)
1995-01-01
As the operation of large systems becomes ever more dependent on extensive automation, the need for an effective solution to the problem of design and validation of the underlying software becomes more critical. Large systems possesses much detailed structure, typically hierarchical, and they are hybrid. Information processing at the top of the hierarchy is by means of formal logic and sentences; on the bottom it is by means of simple scalar differential equations and functions of time; and in the middle it is by an interacting mix of nonlinear multi-axis differential equations and automata, and functions of time and discrete events. The lecture will address the overall problem as it relates to flight vehicle management, describe the middle level, and offer a design approach that is based on Differential Geometry and Discrete Event Dynamic Systems Theory.
Unitary irreducible representations of SL(2,C) in discrete and continuous SU(1,1) bases
DOE Office of Scientific and Technical Information (OSTI.GOV)
Conrady, Florian; Hnybida, Jeff; Department of Physics, University of Waterloo, Waterloo, Ontario
2011-01-15
We derive the matrix elements of generators of unitary irreducible representations of SL(2,C) with respect to basis states arising from a decomposition into irreducible representations of SU(1,1). This is done with regard to a discrete basis diagonalized by J{sup 3} and a continuous basis diagonalized by K{sup 1}, and for both the discrete and continuous series of SU(1,1). For completeness, we also treat the more conventional SU(2) decomposition as a fifth case. The derivation proceeds in a functional/differential framework and exploits the fact that state functions and differential operators have a similar structure in all five cases. The states aremore » defined explicitly and related to SU(1,1) and SU(2) matrix elements.« less
Quasi-periodic solutions of the Belov-Chaltikian lattice hierarchy
NASA Astrophysics Data System (ADS)
Geng, Xianguo; Zeng, Xin
Utilizing the characteristic polynomial of Lax matrix for the Belov-Chaltikian (BC) lattice hierarchy associated with a 3 × 3 discrete matrix spectral problem, we introduce a trigonal curve with three infinite points, from which we establish the associated Dubrovin-type equations. The essential properties of the Baker-Akhiezer function and the meromorphic function are discussed, that include their asymptotic behavior near three infinite points on the trigonal curve and the divisor of the meromorphic function. The Abel map is introduced to straighten out the continuous flow and the discrete flow in the Jacobian variety, from which the quasi-periodic solutions of the entire BC lattice hierarchy are obtained in terms of the Riemann theta function.
Observation of discrete time-crystalline order in a disordered dipolar many-body system
NASA Astrophysics Data System (ADS)
Choi, Soonwon; Choi, Joonhee; Landig, Renate; Kucsko, Georg; Zhou, Hengyun; Isoya, Junichi; Jelezko, Fedor; Onoda, Shinobu; Sumiya, Hitoshi; Khemani, Vedika; von Keyserlingk, Curt; Yao, Norman Y.; Demler, Eugene; Lukin, Mikhail D.
2017-03-01
Understanding quantum dynamics away from equilibrium is an outstanding challenge in the modern physical sciences. Out-of-equilibrium systems can display a rich variety of phenomena, including self-organized synchronization and dynamical phase transitions. More recently, advances in the controlled manipulation of isolated many-body systems have enabled detailed studies of non-equilibrium phases in strongly interacting quantum matter; for example, the interplay between periodic driving, disorder and strong interactions has been predicted to result in exotic ‘time-crystalline’ phases, in which a system exhibits temporal correlations at integer multiples of the fundamental driving period, breaking the discrete time-translational symmetry of the underlying drive. Here we report the experimental observation of such discrete time-crystalline order in a driven, disordered ensemble of about one million dipolar spin impurities in diamond at room temperature. We observe long-lived temporal correlations, experimentally identify the phase boundary and find that the temporal order is protected by strong interactions. This order is remarkably stable to perturbations, even in the presence of slow thermalization. Our work opens the door to exploring dynamical phases of matter and controlling interacting, disordered many-body systems.
Discrete Calculus as a Bridge between Scales
NASA Astrophysics Data System (ADS)
Degiuli, Eric; McElwaine, Jim
2012-02-01
Understanding how continuum descriptions of disordered media emerge from the microscopic scale is a fundamental challenge in condensed matter physics. In many systems, it is necessary to coarse-grain balance equations at the microscopic scale to obtain macroscopic equations. We report development of an exact, discrete calculus, which allows identification of discrete microscopic equations with their continuum equivalent [1]. This allows the application of powerful techniques of calculus, such as the Helmholtz decomposition, the Divergence Theorem, and Stokes' Theorem. We illustrate our results with granular materials. In particular, we show how Newton's laws for a single grain reproduce their continuum equivalent in the calculus. This allows introduction of a discrete Airy stress function, exactly as in the continuum. As an application of the formalism, we show how these results give the natural mean-field variation of discrete quantities, in agreement with numerical simulations. The discrete calculus thus acts as a bridge between discrete microscale quantities and continuous macroscale quantities. [4pt] [1] E. DeGiuli & J. McElwaine, PRE 2011. doi: 10.1103/PhysRevE.84.041310
NASA Astrophysics Data System (ADS)
Gwinn, C. R.; Popov, M. V.; Bartel, N.; Andrianov, A. S.; Johnson, M. D.; Joshi, B. C.; Kardashev, N. S.; Karuppusamy, R.; Kovalev, Y. Y.; Kramer, M.; Rudnitskii, A. G.; Safutdinov, E. R.; Shishov, V. I.; Smirnova, T. V.; Soglasnov, V. A.; Steinmassl, S. F.; Zensus, J. A.; Zhuravlev, V. I.
2016-05-01
We discovered fine-scale structure within the scattering disk of PSR B0329+54 in observations with the RadioAstron ground-space radio interferometer. Here we describe this phenomenon, characterize it with averages and correlation functions, and interpret it as the result of decorrelation of the impulse-response function of interstellar scattering between the widely separated antennas. This instrument included the 10 m Space Radio Telescope, the 110 m Green Bank Telescope, the 14 × 25 m Westerbork Synthesis Radio Telescope, and the 64 m Kalyazin Radio Telescope. The observations were performed at 324 MHz on baselines of up to 235,000 km in 2012 November and 2014 January. In the delay domain, on long baselines the interferometric visibility consists of many discrete spikes within a limited range of delays. On short baselines it consists of a sharp spike surrounded by lower spikes. The average envelope of correlations of the visibility function shows two exponential scales, with characteristic delays of {τ }1=4.1+/- 0.3 μ {{s}} and {τ }2=23+/- 3 μ {{s}}, indicating the presence of two scales of scattering in the interstellar medium. These two scales are present in the pulse-broadening function. The longer scale contains 0.38 times the scattered power of the shorter one. We suggest that the longer tail arises from highly scattered paths, possibly from anisotropic scattering or from substructure at large angles.
The function of dart behavior in the paper wasp, Polistes fuscatus.
Sumana, A; Starks, Philip T
2004-05-01
Dominance behavior in Polistes wasps is a composite trait consisting of various discrete behaviors such as darts, lunges, bites, and mounts. The majority of these behaviors are considered "aggressive", and these aggressive behaviors are considered to form a continuum from mild (e.g., darts) to severe (e.g., falling fights). In this paper we focus on darts, the most common of the dominance behaviors, and investigate their function in un-manipulated post-emergent colonies of the primitively eusocial wasp P. fuscatus. Here we show that darts are correlated with the more severe dominance behaviors, and that dominance ranks do not change with the addition or exclusion of darts. We find no correlation, however, between receiving darts and receiving more severe dominance behaviors. This result suggests that darts are not indicative of aggressive reinforcement of dominance, but rather may serve a different function. Our data suggest that the function of darts is to regulate activity on nests. Both foundresses and workers dart inactive workers significantly more often than by chance, and workers respond to a foundress's (but not a worker's) dart by becoming less inactive. We also found that active workers who receive a dart from either a foundress or worker respond mostly by switching from one activity to another. Thus, our data suggest that darts are not aggressive behaviors, that foundresses use this signal to initiate activity, and that foundresses and workers both use the signal to regulate worker activity.
Bayesian functional integral method for inferring continuous data from discrete measurements.
Heuett, William J; Miller, Bernard V; Racette, Susan B; Holloszy, John O; Chow, Carson C; Periwal, Vipul
2012-02-08
Inference of the insulin secretion rate (ISR) from C-peptide measurements as a quantification of pancreatic β-cell function is clinically important in diseases related to reduced insulin sensitivity and insulin action. ISR derived from C-peptide concentration is an example of nonparametric Bayesian model selection where a proposed ISR time-course is considered to be a "model". An inferred value of inaccessible continuous variables from discrete observable data is often problematic in biology and medicine, because it is a priori unclear how robust the inference is to the deletion of data points, and a closely related question, how much smoothness or continuity the data actually support. Predictions weighted by the posterior distribution can be cast as functional integrals as used in statistical field theory. Functional integrals are generally difficult to evaluate, especially for nonanalytic constraints such as positivity of the estimated parameters. We propose a computationally tractable method that uses the exact solution of an associated likelihood function as a prior probability distribution for a Markov-chain Monte Carlo evaluation of the posterior for the full model. As a concrete application of our method, we calculate the ISR from actual clinical C-peptide measurements in human subjects with varying degrees of insulin sensitivity. Our method demonstrates the feasibility of functional integral Bayesian model selection as a practical method for such data-driven inference, allowing the data to determine the smoothing timescale and the width of the prior probability distribution on the space of models. In particular, our model comparison method determines the discrete time-step for interpolation of the unobservable continuous variable that is supported by the data. Attempts to go to finer discrete time-steps lead to less likely models. Copyright © 2012 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Radial restricted solid-on-solid and etching interface-growth models
NASA Astrophysics Data System (ADS)
Alves, Sidiney G.
2018-03-01
An approach to generate radial interfaces is presented. A radial network recursively obtained is used to implement discrete model rules designed originally for the investigation in flat substrates. I used the restricted solid-on-solid and etching models as to test the proposed scheme. The results indicate the Kardar, Parisi, and Zhang conjecture is completely verified leading to a good agreement between the interface radius fluctuation distribution and the Gaussian unitary ensemble. The evolution of the radius agrees well with the generalized conjecture, and the two-point correlation function exhibits also a good agreement with the covariance of the Airy2 process. The approach can be used to investigate radial interfaces evolution for many other classes of universality.
Radial restricted solid-on-solid and etching interface-growth models.
Alves, Sidiney G
2018-03-01
An approach to generate radial interfaces is presented. A radial network recursively obtained is used to implement discrete model rules designed originally for the investigation in flat substrates. I used the restricted solid-on-solid and etching models as to test the proposed scheme. The results indicate the Kardar, Parisi, and Zhang conjecture is completely verified leading to a good agreement between the interface radius fluctuation distribution and the Gaussian unitary ensemble. The evolution of the radius agrees well with the generalized conjecture, and the two-point correlation function exhibits also a good agreement with the covariance of the Airy_{2} process. The approach can be used to investigate radial interfaces evolution for many other classes of universality.
Physical and chemical characterization of actinides in soil from Johnston Atoll
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wolf, S.F.; Bates, J.K.; Buck, E.C.
1997-02-01
Characterization of the actinide content of a sample of contaminated coral soil from Johnston Atoll, the site of three non-nuclear destructs of nuclear warhead-carrying THOR missiles in 1962, revealed that >99% of the total actinide content is associated with discrete bomb fragments. After removal of these fragments, there was an inverse correlation between actinide content and soil particle size in particles from 43 to 0.4 {mu}m diameter. Detailed analyses of this remaining soil revealed no discrete actinide phase in these soil particles, despite measurable actinide content. Observations indicate that exposure to the environment has caused the conversion of relatively insolublemore » actinide oxides to the more soluble actinyl oxides and actinyl carbonate coordinated complexes. This process has led to dissolution of actinides from discrete particles and migration to the surrounding soil surfaces, resulting in a dispersion greater than would be expected by physical transport of discrete particles alone. 26 refs., 4 figs., 1 tab.« less
NASA Astrophysics Data System (ADS)
Fujisawa, Takeshi; Saitoh, Kunimasa
2017-06-01
Group delay spread of coupled three-core fiber is investigated based on coupled-wave theory. The differences between supermode and discrete core mode models are thoroughly investigated to reveal applicability of both models for specific fiber bending condition. A macrobending with random twisting is taken into account for random modal mixing in the fiber. It is found that for weakly bent condition, both supermode and discrete core mode models are applicable. On the other hand, for strongly bent condition, the discrete core mode model should be used to account for increased differential modal group delay for the fiber without twisting and short correlation length, which were experimentally observed recently. Results presented in this paper indicate the discrete core mode model is superior to the supermode model for the analysis of coupled-multicore fibers for various bent condition. Also, for estimating GDS of coupled-multicore fiber, it is critically important to take into account the fiber bending condition.
Training shelter volunteers to teach dog compliance.
Howard, Veronica J; DiGennaro Reed, Florence D
2014-01-01
This study examined the degree to which training procedures influenced the integrity of behaviorally based dog training implemented by volunteers of an animal shelter. Volunteers were taught to implement discrete-trial obedience training to teach 2 skills (sit and wait) to dogs. Procedural integrity during the baseline and written instructions conditions was low across all participants. Although performance increased with use of a video model, integrity did not reach criterion levels until performance feedback and modeling were provided. Moreover, the integrity of the discrete-trial training procedure was significantly and positively correlated with dog compliance to instructions for all dyads. Correct implementation and compliance were observed when participants were paired with a novel dog and trainer, respectively, although generalization of procedural integrity from the discrete-trial sit procedure to the discrete-trial wait procedure was not observed. Shelter consumers rated the behavior change in dogs and trainers as socially significant. Implications of these findings and future directions for research are discussed. © Society for the Experimental Analysis of Behavior.
1986-01-01
The UV-induced, C3H fibrosarcoma, 1591, expresses at least three unique MHC class I antigens not found on normal C3H tissue. Here we report the complete DNA sequence of the three novel class I genes encoding these molecules, and describe in detail the recognition of the individual products by tumor-reactive and allospecific CTL. Remarkably, although C3H does not appear to express H-2L locus information, this C3H tumor expresses two distinct antigens, termed A149 and A166, which are extremely homologous to each other and to the H-2Ld antigen from BALB/c. The gene encoding the third novel class I antigen from 1591, A216, is quite homologous to H-2Kk) throughout its 3' end. Since all three of these genes account for polymorphic restriction fragments not found in C3H, it is likely that they were derived by recombination from the endogenous class I genes of C3H. The DNA sequence homology of A149, A166, and H-2Ld is especially significant given the functional conservation observed between the products of these genes. Limited sequence substitutions appear to correlate with some of the discrete serological differences observed between these molecules. In addition, both A149 and A166 crossreact, but to differing extents, with H-2Ld at the level of T cell recognition. Our results are consistent with the view that CTL recognize complex conformational determinants on class I molecules, but extend previous observations by comparing a set of antigens with discrete and overlapping structural and functional differences. PMID:3489061
Discretization of Continuous Time Discrete Scale Invariant Processes: Estimation and Spectra
NASA Astrophysics Data System (ADS)
Rezakhah, Saeid; Maleki, Yasaman
2016-07-01
Imposing some flexible sampling scheme we provide some discretization of continuous time discrete scale invariant (DSI) processes which is a subsidiary discrete time DSI process. Then by introducing some simple random measure we provide a second continuous time DSI process which provides a proper approximation of the first one. This enables us to provide a bilateral relation between covariance functions of the subsidiary process and the new continuous time processes. The time varying spectral representation of such continuous time DSI process is characterized, and its spectrum is estimated. Also, a new method for estimation time dependent Hurst parameter of such processes is provided which gives a more accurate estimation. The performance of this estimation method is studied via simulation. Finally this method is applied to the real data of S & P500 and Dow Jones indices for some special periods.
NASA Astrophysics Data System (ADS)
Wang, Tong; Ding, Yongsheng; Zhang, Lei; Hao, Kuangrong
2016-08-01
This paper considered the synchronisation of continuous complex dynamical networks with discrete-time communications and delayed nodes. The nodes in the dynamical networks act in the continuous manner, while the communications between nodes are discrete-time; that is, they communicate with others only at discrete time instants. The communication intervals in communication period can be uncertain and variable. By using a piecewise Lyapunov-Krasovskii function to govern the characteristics of the discrete communication instants, we investigate the adaptive feedback synchronisation and a criterion is derived to guarantee the existence of the desired controllers. The globally exponential synchronisation can be achieved by the controllers under the updating laws. Finally, two numerical examples including globally coupled network and nearest-neighbour coupled networks are presented to demonstrate the validity and effectiveness of the proposed control scheme.
Stinchcombe, Adam R; Peskin, Charles S; Tranchina, Daniel
2012-06-01
We present a generalization of a population density approach for modeling and analysis of stochastic gene expression. In the model, the gene of interest fluctuates stochastically between an inactive state, in which transcription cannot occur, and an active state, in which discrete transcription events occur; and the individual mRNA molecules are degraded stochastically in an independent manner. This sort of model in simplest form with exponential dwell times has been used to explain experimental estimates of the discrete distribution of random mRNA copy number. In our generalization, the random dwell times in the inactive and active states, T_{0} and T_{1}, respectively, are independent random variables drawn from any specified distributions. Consequently, the probability per unit time of switching out of a state depends on the time since entering that state. Our method exploits a connection between the fully discrete random process and a related continuous process. We present numerical methods for computing steady-state mRNA distributions and an analytical derivation of the mRNA autocovariance function. We find that empirical estimates of the steady-state mRNA probability mass function from Monte Carlo simulations of laboratory data do not allow one to distinguish between underlying models with exponential and nonexponential dwell times in some relevant parameter regimes. However, in these parameter regimes and where the autocovariance function has negative lobes, the autocovariance function disambiguates the two types of models. Our results strongly suggest that temporal data beyond the autocovariance function is required in general to characterize gene switching.
Exploration Supply Chain Simulation
NASA Technical Reports Server (NTRS)
2008-01-01
The Exploration Supply Chain Simulation project was chartered by the NASA Exploration Systems Mission Directorate to develop a software tool, with proper data, to quantitatively analyze supply chains for future program planning. This tool is a discrete-event simulation that uses the basic supply chain concepts of planning, sourcing, making, delivering, and returning. This supply chain perspective is combined with other discrete or continuous simulation factors. Discrete resource events (such as launch or delivery reviews) are represented as organizational functional units. Continuous resources (such as civil service or contractor program functions) are defined as enabling functional units. Concepts of fixed and variable costs are included in the model to allow the discrete events to interact with cost calculations. The definition file is intrinsic to the model, but a blank start can be initiated at any time. The current definition file is an Orion Ares I crew launch vehicle. Parameters stretch from Kennedy Space Center across and into other program entities (Michaud Assembly Facility, Aliant Techsystems, Stennis Space Center, Johnson Space Center, etc.) though these will only gain detail as the file continues to evolve. The Orion Ares I file definition in the tool continues to evolve, and analysis from this tool is expected in 2008. This is the first application of such business-driven modeling to a NASA/government-- aerospace contractor endeavor.
Dense image registration through MRFs and efficient linear programming.
Glocker, Ben; Komodakis, Nikos; Tziritas, Georgios; Navab, Nassir; Paragios, Nikos
2008-12-01
In this paper, we introduce a novel and efficient approach to dense image registration, which does not require a derivative of the employed cost function. In such a context, the registration problem is formulated using a discrete Markov random field objective function. First, towards dimensionality reduction on the variables we assume that the dense deformation field can be expressed using a small number of control points (registration grid) and an interpolation strategy. Then, the registration cost is expressed using a discrete sum over image costs (using an arbitrary similarity measure) projected on the control points, and a smoothness term that penalizes local deviations on the deformation field according to a neighborhood system on the grid. Towards a discrete approach, the search space is quantized resulting in a fully discrete model. In order to account for large deformations and produce results on a high resolution level, a multi-scale incremental approach is considered where the optimal solution is iteratively updated. This is done through successive morphings of the source towards the target image. Efficient linear programming using the primal dual principles is considered to recover the lowest potential of the cost function. Very promising results using synthetic data with known deformations and real data demonstrate the potentials of our approach.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Berzi, Diego; Vescovi, Dalila
2015-01-15
We use previous results from discrete element simulations of simple shear flows of rigid, identical spheres in the collisional regime to show that the volume fraction-dependence of the stresses is singular at the shear rigidity. Here, we identify the shear rigidity, which is a decreasing function of the interparticle friction, as the maximum volume fraction beyond which a random collisional assembly of grains cannot be sheared without developing force chains that span the entire domain. In the framework of extended kinetic theory, i.e., kinetic theory that accounts for the decreasing in the collisional dissipation due to the breaking of molecularmore » chaos at volume fractions larger than 0.49, we also show that the volume fraction-dependence of the correlation length (measure of the velocity correlation) is singular at random close packing, independent of the interparticle friction. The difference in the singularities ensures that the ratio of the shear stress to the pressure at shear rigidity is different from zero even in the case of frictionless spheres: we identify that with the yield stress ratio of granular materials, and we show that the theoretical predictions, once the different singularities are inserted into the functions of extended kinetic theory, are in excellent agreement with the results of numerical simulations.« less
Song, Xiaowen; Huang, Fei; Liu, Juanjuan; Li, Chengjun; Gao, Shanshan; Wu, Wei; Zhai, Mengfan; Yu, Xiaojuan; Xiong, Wenfeng; Xie, Jia; Li, Bin
2017-10-01
Cytosine DNA methylation is a vital epigenetic regulator of eukaryotic development. Whether this epigenetic modification occurs in Tribolium castaneum has been controversial, its distribution pattern and functions have not been established. Here, using bisulphite sequencing (BS-Seq), we confirmed the existence of DNA methylation and described the methylation profiles of the four life stages of T. castaneum. In the T. castaneum genome, both symmetrical CpG and non-CpG methylcytosines were observed. Symmetrical CpG methylation, which was catalysed by DNMT1 and occupied a small part in T. castaneum methylome, was primarily enriched in gene bodies and was positively correlated with gene expression levels. Asymmetrical non-CpG methylation, which was predominant in the methylome, was strongly concentrated in intergenic regions and introns but absent from exons. Gene body methylation was negatively correlated with gene expression levels. The distribution pattern and functions of this type of methylation were similar only to the methylome of Drosophila melanogaster, which further supports the existence of a novel methyltransferase in the two species responsible for this type of methylation. This first life-cycle methylome of T. castaneum reveals a novel and unique methylation pattern, which will contribute to the further understanding of the variety and functions of DNA methylation in eukaryotes. © The Author 2017. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.
Nonparametric probability density estimation by optimization theoretic techniques
NASA Technical Reports Server (NTRS)
Scott, D. W.
1976-01-01
Two nonparametric probability density estimators are considered. The first is the kernel estimator. The problem of choosing the kernel scaling factor based solely on a random sample is addressed. An interactive mode is discussed and an algorithm proposed to choose the scaling factor automatically. The second nonparametric probability estimate uses penalty function techniques with the maximum likelihood criterion. A discrete maximum penalized likelihood estimator is proposed and is shown to be consistent in the mean square error. A numerical implementation technique for the discrete solution is discussed and examples displayed. An extensive simulation study compares the integrated mean square error of the discrete and kernel estimators. The robustness of the discrete estimator is demonstrated graphically.
Antoniou, Christos-Konstantinos; Chrysohoou, Christina; Lerakis, Stamatios; Manolakou, Panagiota; Pitsavos, Christos; Tsioufis, Konstantinos; Stefanadis, Christodoulos; Tousoulis, Dimitrios
2015-11-15
Ventriculoarterial coupling (VAC) status relates to tissue perfusion and its optimization may improve organ function and energy efficiency (EE) of the cardiovascular system. The effects of non-invasively calculated VAC improvement on echocardiographic parameters, renal function indices and EE improvement in patients with acute decompensated systolic heart failure were studied. Furthermore, effects of different treatment modalities on VAC, renal function and echocardiographic parameters were compared. Systolic heart failure patients with ejection fraction <50% were studied, who, at the treating physician's discretion, received 8-hour infusions of: high dose furosemide (20mg/h), low dose furosemide (5mg/h) or dopamine (5μg/kg/min) combined with furosemide (5mg/h). Echocardiographic assessments were performed at 0 and 24h. Renal function was evaluated using serum creatinine and creatinine clearance. VAC and EE were assessed noninvasively, by echocardiography. Significant correlations were noted between VAC improvement and improvements in EE and serum creatinine (rho=0.96, p<0.001, rho=0.32, p=0.04 respectively). Dopamine-furosemide combination had a borderline effect on creatinine (p=0.08) and led to significant improvements in e', E/e' ratio (p=0.015 and p=0.009 respectively) and VAC (value closer to 1). VAC improvement correlated with EE and creatinine improvement, regardless of treatment, supporting a potential role for VAC status assessment and improvement in acute decompensated systolic heart failure. Dopamine and furosemide combination seemed to improve VAC and diastolic function but only had a borderline effect on renal function. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Ion association at discretely-charged dielectric interfaces: Giant charge inversion
NASA Astrophysics Data System (ADS)
Wang, Zhi-Yong; Wu, Jianzhong
2017-07-01
Giant charge reversal has been identified for the first time by Monte Carlo simulation for a discretely charged surface in contact with a trivalent electrolyte solution. It takes place regardless of the surface charge density under study and the monovalent salt. In stark contrast to earlier predictions based on the 2-dimensional Wigner crystal model to describe strong correlation of counterions at the macroion surface, we find that giant charge reversal reflects an intricate interplay of ionic volume effects, electrostatic correlations, surface charge heterogeneity, and the dielectric response of the confined fluids. While the novel phenomenon is yet to be confirmed with experiment, the simulation results appear in excellent agreement with a wide range of existing observations in the subregime of charge inversion. Our findings may have far-reaching implications to understanding complex electrochemical phenomena entailing ionic fluids under dielectric confinements.
Ho, B T; Tsai, M J; Wei, J; Ma, M; Saipetch, P
1996-01-01
A new method of video compression for angiographic images has been developed to achieve high compression ratio (~20:1) while eliminating block artifacts which leads to loss of diagnostic accuracy. This method adopts motion picture experts group's (MPEGs) motion compensated prediction to takes advantage of frame to frame correlation. However, in contrast to MPEG, the error images arising from mismatches in the motion estimation are encoded by discrete wavelet transform (DWT) rather than block discrete cosine transform (DCT). Furthermore, the authors developed a classification scheme which label each block in an image as intra, error, or background type and encode it accordingly. This hybrid coding can significantly improve the compression efficiency in certain eases. This method can be generalized for any dynamic image sequences applications sensitive to block artifacts.
X-33 Hypersonic Boundary Layer Transition
NASA Technical Reports Server (NTRS)
Berry, Scott A.; Horvath, Thomas J.; Hollis, Brian R.; Thompson, Richard A.; Hamilton, H. Harris, II
1999-01-01
Boundary layer and aeroheating characteristics of several X-33 configurations have been experimentally examined in the Langley 20-Inch Mach 6 Air Tunnel. Global surface heat transfer distributions, surface streamline patterns, and shock shapes were measured on 0.013-scale models at Mach 6 in air. Parametric variations include angles-of-attack of 20-deg, 30-deg, and 40-deg; Reynolds numbers based on model length of 0.9 to 6.6 million; and body-flap deflections of 0, 10 and 20-deg. The effects of discrete and distributed roughness elements on boundary layer transition, which included trip height, size, location, and distribution, both on and off the windward centerline, were investigated. The discrete roughness results on centerline were used to provide a transition correlation for the X-33 flight vehicle that was applicable across the range of reentry angles of attack. The attachment line discrete roughness results were shown to be consistent with the centerline results, as no increased sensitivity to roughness along the attachment line was identified. The effect of bowed panels was qualitatively shown to be less effective than the discrete trips; however, the distributed nature of the bowed panels affected a larger percent of the aft-body windward surface than a single discrete trip.
Concerted and mosaic evolution of functional modules in songbird brains
DeVoogd, Timothy J.
2017-01-01
Vertebrate brains differ in overall size, composition and functional capacities, but the evolutionary processes linking these traits are unclear. Two leading models offer opposing views: the concerted model ascribes major dimensions of covariation in brain structures to developmental events, whereas the mosaic model relates divergent structures to functional capabilities. The models are often cast as incompatible, but they must be unified to explain how adaptive changes in brain structure arise from pre-existing architectures and developmental mechanisms. Here we show that variation in the sizes of discrete neural systems in songbirds, a species-rich group exhibiting diverse behavioural and ecological specializations, supports major elements of both models. In accordance with the concerted model, most variation in nucleus volumes is shared across functional domains and allometry is related to developmental sequence. Per the mosaic model, residual variation in nucleus volumes is correlated within functional systems and predicts specific behavioural capabilities. These comparisons indicate that oscine brains evolved primarily as a coordinated whole but also experienced significant, independent modifications to dedicated systems from specific selection pressures. Finally, patterns of covariation between species and brain areas hint at underlying developmental mechanisms. PMID:28490627
A Legendre–Fourier spectral method with exact conservation laws for the Vlasov–Poisson system
DOE Office of Scientific and Technical Information (OSTI.GOV)
Manzini, Gianmarco; Delzanno, Gian Luca; Vencels, Juris
In this study, we present the design and implementation of an L 2-stable spectral method for the discretization of the Vlasov–Poisson model of a collisionless plasma in one space and velocity dimension. The velocity and space dependence of the Vlasov equation are resolved through a truncated spectral expansion based on Legendre and Fourier basis functions, respectively. The Poisson equation, which is coupled to the Vlasov equation, is also resolved through a Fourier expansion. The resulting system of ordinary differential equation is discretized by the implicit second-order accurate Crank–Nicolson time discretization. The non-linear dependence between the Vlasov and Poisson equations ismore » iteratively solved at any time cycle by a Jacobian-Free Newton–Krylov method. In this work we analyze the structure of the main conservation laws of the resulting Legendre–Fourier model, e.g., mass, momentum, and energy, and prove that they are exactly satisfied in the semi-discrete and discrete setting. The L 2-stability of the method is ensured by discretizing the boundary conditions of the distribution function at the boundaries of the velocity domain by a suitable penalty term. The impact of the penalty term on the conservation properties is investigated theoretically and numerically. An implementation of the penalty term that does not affect the conservation of mass, momentum and energy, is also proposed and studied. A collisional term is introduced in the discrete model to control the filamentation effect, but does not affect the conservation properties of the system. Numerical results on a set of standard test problems illustrate the performance of the method.« less
A Legendre–Fourier spectral method with exact conservation laws for the Vlasov–Poisson system
Manzini, Gianmarco; Delzanno, Gian Luca; Vencels, Juris; ...
2016-04-22
In this study, we present the design and implementation of an L 2-stable spectral method for the discretization of the Vlasov–Poisson model of a collisionless plasma in one space and velocity dimension. The velocity and space dependence of the Vlasov equation are resolved through a truncated spectral expansion based on Legendre and Fourier basis functions, respectively. The Poisson equation, which is coupled to the Vlasov equation, is also resolved through a Fourier expansion. The resulting system of ordinary differential equation is discretized by the implicit second-order accurate Crank–Nicolson time discretization. The non-linear dependence between the Vlasov and Poisson equations ismore » iteratively solved at any time cycle by a Jacobian-Free Newton–Krylov method. In this work we analyze the structure of the main conservation laws of the resulting Legendre–Fourier model, e.g., mass, momentum, and energy, and prove that they are exactly satisfied in the semi-discrete and discrete setting. The L 2-stability of the method is ensured by discretizing the boundary conditions of the distribution function at the boundaries of the velocity domain by a suitable penalty term. The impact of the penalty term on the conservation properties is investigated theoretically and numerically. An implementation of the penalty term that does not affect the conservation of mass, momentum and energy, is also proposed and studied. A collisional term is introduced in the discrete model to control the filamentation effect, but does not affect the conservation properties of the system. Numerical results on a set of standard test problems illustrate the performance of the method.« less
Wei, Qinglai; Liu, Derong; Lin, Qiao
In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.In this paper, a novel local value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems. The focuses of this paper are to study admissibility properties and the termination criteria of discrete-time local value iteration ADP algorithms. In the discrete-time local value iteration ADP algorithm, the iterative value functions and the iterative control laws are both updated in a given subset of the state space in each iteration, instead of the whole state space. For the first time, admissibility properties of iterative control laws are analyzed for the local value iteration ADP algorithm. New termination criteria are established, which terminate the iterative local ADP algorithm with an admissible approximate optimal control law. Finally, simulation results are given to illustrate the performance of the developed algorithm.
Zhang, Jian-Hua; Xia, Jia-Jun; Garibaldi, Jonathan M; Groumpos, Petros P; Wang, Ru-Bin
2017-06-01
In human-machine (HM) hybrid control systems, human operator and machine cooperate to achieve the control objectives. To enhance the overall HM system performance, the discrete manual control task-load by the operator must be dynamically allocated in accordance with continuous-time fluctuation of psychophysiological functional status of the operator, so-called operator functional state (OFS). The behavior of the HM system is hybrid in nature due to the co-existence of discrete task-load (control) variable and continuous operator performance (system output) variable. Petri net is an effective tool for modeling discrete event systems, but for hybrid system involving discrete dynamics, generally Petri net model has to be extended. Instead of using different tools to represent continuous and discrete components of a hybrid system, this paper proposed a method of fuzzy inference Petri nets (FIPN) to represent the HM hybrid system comprising a Mamdani-type fuzzy model of OFS and a logical switching controller in a unified framework, in which the task-load level is dynamically reallocated between the operator and machine based on the model-predicted OFS. Furthermore, this paper used a multi-model approach to predict the operator performance based on three electroencephalographic (EEG) input variables (features) via the Wang-Mendel (WM) fuzzy modeling method. The membership function parameters of fuzzy OFS model for each experimental participant were optimized using artificial bee colony (ABC) evolutionary algorithm. Three performance indices, RMSE, MRE, and EPR, were computed to evaluate the overall modeling accuracy. Experiment data from six participants are analyzed. The results show that the proposed method (FIPN with adaptive task allocation) yields lower breakdown rate (from 14.8% to 3.27%) and higher human performance (from 90.30% to 91.99%). The simulation results of the FIPN-based adaptive HM (AHM) system on six experimental participants demonstrate that the FIPN framework provides an effective way to model and regulate/optimize the OFS in HM hybrid systems composed of continuous-time OFS model and discrete-event switching controller. Copyright © 2017 Elsevier B.V. All rights reserved.
Discrete Data Qualification System and Method Comprising Noise Series Fault Detection
NASA Technical Reports Server (NTRS)
Fulton, Christopher; Wong, Edmond; Melcher, Kevin; Bickford, Randall
2013-01-01
A Sensor Data Qualification (SDQ) function has been developed that allows the onboard flight computers on NASA s launch vehicles to determine the validity of sensor data to ensure that critical safety and operational decisions are not based on faulty sensor data. This SDQ function includes a novel noise series fault detection algorithm for qualification of the output data from LO2 and LH2 low-level liquid sensors. These sensors are positioned in a launch vehicle s propellant tanks in order to detect propellant depletion during a rocket engine s boost operating phase. This detection capability can prevent the catastrophic situation where the engine operates without propellant. The output from each LO2 and LH2 low-level liquid sensor is a discrete valued signal that is expected to be in either of two states, depending on whether the sensor is immersed (wet) or exposed (dry). Conventional methods for sensor data qualification, such as threshold limit checking, are not effective for this type of signal due to its discrete binary-state nature. To address this data qualification challenge, a noise computation and evaluation method, also known as a noise fault detector, was developed to detect unreasonable statistical characteristics in the discrete data stream. The method operates on a time series of discrete data observations over a moving window of data points and performs a continuous examination of the resulting observation stream to identify the presence of anomalous characteristics. If the method determines the existence of anomalous results, the data from the sensor is disqualified for use by other monitoring or control functions.
VMF3/GPT3: refined discrete and empirical troposphere mapping functions
NASA Astrophysics Data System (ADS)
Landskron, Daniel; Böhm, Johannes
2018-04-01
Incorrect modeling of troposphere delays is one of the major error sources for space geodetic techniques such as Global Navigation Satellite Systems (GNSS) or Very Long Baseline Interferometry (VLBI). Over the years, many approaches have been devised which aim at mapping the delay of radio waves from zenith direction down to the observed elevation angle, so-called mapping functions. This paper contains a new approach intended to refine the currently most important discrete mapping function, the Vienna Mapping Functions 1 (VMF1), which is successively referred to as Vienna Mapping Functions 3 (VMF3). It is designed in such a way as to eliminate shortcomings in the empirical coefficients b and c and in the tuning for the specific elevation angle of 3°. Ray-traced delays of the ray-tracer RADIATE serve as the basis for the calculation of new mapping function coefficients. Comparisons of modeled slant delays demonstrate the ability of VMF3 to approximate the underlying ray-traced delays more accurately than VMF1 does, in particular at low elevation angles. In other words, when requiring highest precision, VMF3 is to be preferable to VMF1. Aside from revising the discrete form of mapping functions, we also present a new empirical model named Global Pressure and Temperature 3 (GPT3) on a 5°× 5° as well as a 1°× 1° global grid, which is generally based on the same data. Its main components are hydrostatic and wet empirical mapping function coefficients derived from special averaging techniques of the respective (discrete) VMF3 data. In addition, GPT3 also contains a set of meteorological quantities which are adopted as they stand from their predecessor, Global Pressure and Temperature 2 wet. Thus, GPT3 represents a very comprehensive troposphere model which can be used for a series of geodetic as well as meteorological and climatological purposes and is fully consistent with VMF3.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dominy, Stephen; Brown, Joseph N.; Ryder, Mark I.
The prevalence of HIV-associated neurocognitive disorders (HAND) remains high despite effective antiretroviral therapies. Multiple etiologies have been proposed over the last few years to account for this phenomenon, including the neurotoxic effects of antiretrovirals and co-morbid substance abuse. However, no underlying molecular mechanism has been identified. Emerging evidence in several fields has linked the gut to brain diseases, but the effect of the gut on the brain during HIV infection has not been explored. Saliva is the most accessible gut biofluid, and is therefore of great scientific interest for diagnostic and prognostic purposes. This study presents a longitudinal, liquid chromatography-massmore » spectrometry-based quantitative proteomics study investigating saliva samples taken from 8 HIV-positive (HIV+) and 11 -negative (HIV-) heroin addicts. In the HIV+ group, 58 proteins were identified that show significant correlations with cognitive scores and that implicate disruption of protein quality control pathways by HIV. Notably, no proteins from the HIV- heroin addict cohort showed significant correlations with cognitive scores. In addition, the majority of correlated proteins have been shown to be associated with exosomes, allowing us to propose that the salivary glands and/or oral epithelium may modulate brain function during HIV infection through the release of discrete packets of proteins in the form of exosomes.« less
Rolland, C; Danchin, E; de Fraipont, M
1998-06-01
Coloniality in birds has been intensively studied under the cost and benefit approach, but no general conclusion can be given concerning its evolutionary function. Here, we report on a comparative analysis carried out on 320 species of birds using the general method of comparative analysis for discrete variables and the contrast method to analyze the evolution of coloniality. Showing a mean of 23 convergences and 10 reversals, coloniality appears to be a rather labile trait. Colonial breeding appears strongly correlated with the absence of feeding territory, the aquatic habitat, and nest exposure to predators but was not correlated with changes in life-history traits (body mass and clutch size). The correlation of coloniality with the aquatic habitat is in fact explained by a strong correlation with the marine habitat. Unexpectedly, we found that the evolution toward a marine habitat in birds was contingent on coloniality and that coloniality evolved before the passage to a marine life. These results-along with the lack of transitions from the nonmarine to marine habitat in solitary species and the precedence of the loss of feeding territoriality on the passage to a marine life-contradict most of the hypotheses classically accepted to explain coloniality and suggest that we use a different framework to study this evolutionary enigma.
Analysis of Discrete-Source Damage Progression in a Tensile Stiffened Composite Panel
NASA Technical Reports Server (NTRS)
Wang, John T.; Lotts, Christine G.; Sleight, David W.
1999-01-01
This paper demonstrates the progressive failure analysis capability in NASA Langley s COMET-AR finite element analysis code on a large-scale built-up composite structure. A large-scale five stringer composite panel with a 7-in. long discrete source damage was analyzed from initial loading to final failure including the geometric and material nonlinearities. Predictions using different mesh sizes, different saw cut modeling approaches, and different failure criteria were performed and assessed. All failure predictions have a reasonably good correlation with the test result.
2011-03-24
equates to N < 2.237×108 samples . For the hardware used in this paper where B ≈ 370MHz [29], the limit on the correlation time becomes T < 0.30 s. This...When implementing the digital correlator in the time domain, each discrete sample of the reference signal, sref , must be interpolated based on the...through digital correlation comes from the number of samples in the measurement vector, L. The computational re- quirements grow with L. As Figure 2.9
Stability of discrete time recurrent neural networks and nonlinear optimization problems.
Singh, Jayant; Barabanov, Nikita
2016-02-01
We consider the method of Reduction of Dissipativity Domain to prove global Lyapunov stability of Discrete Time Recurrent Neural Networks. The standard and advanced criteria for Absolute Stability of these essentially nonlinear systems produce rather weak results. The method mentioned above is proved to be more powerful. It involves a multi-step procedure with maximization of special nonconvex functions over polytopes on every step. We derive conditions which guarantee an existence of at most one point of local maximum for such functions over every hyperplane. This nontrivial result is valid for wide range of neuron transfer functions. Copyright © 2015 Elsevier Ltd. All rights reserved.
Continuum limit of electrostatic gyrokinetic absolute equilibrium
NASA Astrophysics Data System (ADS)
Zhu, Jian-Zhou
2012-06-01
Electrostatic gyrokinetic absolute equilibria with continuum velocity field are obtained through the partition function and through the Green function of the functional integral. The new results justify and explain the prescription for quantization/discretization or taking the continuum limit of velocity. The mistakes in the Appendix D of our earlier work [J.-Z. Zhu and G. W. Hammett, Phys. Plasmas 17, 122307 (2010)] are explained and corrected. If the lattice spacing for discretizing velocity is big enough, all the invariants could concentrate at the lowest Fourier modes in a negative-temperature state, which might indicate a possible variation of the dual cascade picture in 2D plasma turbulence.
Multilayer neural networks with extensively many hidden units.
Rosen-Zvi, M; Engel, A; Kanter, I
2001-08-13
The information processing abilities of a multilayer neural network with a number of hidden units scaling as the input dimension are studied using statistical mechanics methods. The mapping from the input layer to the hidden units is performed by general symmetric Boolean functions, whereas the hidden layer is connected to the output by either discrete or continuous couplings. Introducing an overlap in the space of Boolean functions as order parameter, the storage capacity is found to scale with the logarithm of the number of implementable Boolean functions. The generalization behavior is smooth for continuous couplings and shows a discontinuous transition to perfect generalization for discrete ones.
NASA Astrophysics Data System (ADS)
Kriz, Igor; Loebl, Martin; Somberg, Petr
2013-05-01
We study various mathematical aspects of discrete models on graphs, specifically the Dimer and the Ising models. We focus on proving gluing formulas for individual summands of the partition function. We also obtain partial results regarding conjectured limits realized by fermions in rational conformal field theories.
Modified Discrete Grey Wolf Optimizer Algorithm for Multilevel Image Thresholding
Sun, Lijuan; Guo, Jian; Xu, Bin; Li, Shujing
2017-01-01
The computation of image segmentation has become more complicated with the increasing number of thresholds, and the option and application of the thresholds in image thresholding fields have become an NP problem at the same time. The paper puts forward the modified discrete grey wolf optimizer algorithm (MDGWO), which improves on the optimal solution updating mechanism of the search agent by the weights. Taking Kapur's entropy as the optimized function and based on the discreteness of threshold in image segmentation, the paper firstly discretizes the grey wolf optimizer (GWO) and then proposes a new attack strategy by using the weight coefficient to replace the search formula for optimal solution used in the original algorithm. The experimental results show that MDGWO can search out the optimal thresholds efficiently and precisely, which are very close to the result examined by exhaustive searches. In comparison with the electromagnetism optimization (EMO), the differential evolution (DE), the Artifical Bee Colony (ABC), and the classical GWO, it is concluded that MDGWO has advantages over the latter four in terms of image segmentation quality and objective function values and their stability. PMID:28127305
Skeletonization and Partitioning of Digital Images Using Discrete Morse Theory.
Delgado-Friedrichs, Olaf; Robins, Vanessa; Sheppard, Adrian
2015-03-01
We show how discrete Morse theory provides a rigorous and unifying foundation for defining skeletons and partitions of grayscale digital images. We model a grayscale image as a cubical complex with a real-valued function defined on its vertices (the voxel values). This function is extended to a discrete gradient vector field using the algorithm presented in Robins, Wood, Sheppard TPAMI 33:1646 (2011). In the current paper we define basins (the building blocks of a partition) and segments of the skeleton using the stable and unstable sets associated with critical cells. The natural connection between Morse theory and homology allows us to prove the topological validity of these constructions; for example, that the skeleton is homotopic to the initial object. We simplify the basins and skeletons via Morse-theoretic cancellation of critical cells in the discrete gradient vector field using a strategy informed by persistent homology. Simple working Python code for our algorithms for efficient vector field traversal is included. Example data are taken from micro-CT images of porous materials, an application area where accurate topological models of pore connectivity are vital for fluid-flow modelling.
Gibbsian Stationary Non-equilibrium States
NASA Astrophysics Data System (ADS)
De Carlo, Leonardo; Gabrielli, Davide
2017-09-01
We study the structure of stationary non-equilibrium states for interacting particle systems from a microscopic viewpoint. In particular we discuss two different discrete geometric constructions. We apply both of them to determine non reversible transition rates corresponding to a fixed invariant measure. The first one uses the equivalence of this problem with the construction of divergence free flows on the transition graph. Since divergence free flows are characterized by cyclic decompositions we can generate families of models from elementary cycles on the configuration space. The second construction is a functional discrete Hodge decomposition for translational covariant discrete vector fields. According to this, for example, the instantaneous current of any interacting particle system on a finite torus can be canonically decomposed in a gradient part, a circulation term and an harmonic component. All the three components are associated with functions on the configuration space. This decomposition is unique and constructive. The stationary condition can be interpreted as an orthogonality condition with respect to an harmonic discrete vector field and we use this decomposition to construct models having a fixed invariant measure.
Gröbner Bases and Generation of Difference Schemes for Partial Differential Equations
NASA Astrophysics Data System (ADS)
Gerdt, Vladimir P.; Blinkov, Yuri A.; Mozzhilkin, Vladimir V.
2006-05-01
In this paper we present an algorithmic approach to the generation of fully conservative difference schemes for linear partial differential equations. The approach is based on enlargement of the equations in their integral conservation law form by extra integral relations between unknown functions and their derivatives, and on discretization of the obtained system. The structure of the discrete system depends on numerical approximation methods for the integrals occurring in the enlarged system. As a result of the discretization, a system of linear polynomial difference equations is derived for the unknown functions and their partial derivatives. A difference scheme is constructed by elimination of all the partial derivatives. The elimination can be achieved by selecting a proper elimination ranking and by computing a Gröbner basis of the linear difference ideal generated by the polynomials in the discrete system. For these purposes we use the difference form of Janet-like Gröbner bases and their implementation in Maple. As illustration of the described methods and algorithms, we construct a number of difference schemes for Burgers and Falkowich-Karman equations and discuss their numerical properties.
Higher-order adaptive finite-element methods for Kohn–Sham density functional theory
DOE Office of Scientific and Technical Information (OSTI.GOV)
Motamarri, P.; Nowak, M.R.; Leiter, K.
2013-11-15
We present an efficient computational approach to perform real-space electronic structure calculations using an adaptive higher-order finite-element discretization of Kohn–Sham density-functional theory (DFT). To this end, we develop an a priori mesh-adaption technique to construct a close to optimal finite-element discretization of the problem. We further propose an efficient solution strategy for solving the discrete eigenvalue problem by using spectral finite-elements in conjunction with Gauss–Lobatto quadrature, and a Chebyshev acceleration technique for computing the occupied eigenspace. The proposed approach has been observed to provide a staggering 100–200-fold computational advantage over the solution of a generalized eigenvalue problem. Using the proposedmore » solution procedure, we investigate the computational efficiency afforded by higher-order finite-element discretizations of the Kohn–Sham DFT problem. Our studies suggest that staggering computational savings—of the order of 1000-fold—relative to linear finite-elements can be realized, for both all-electron and local pseudopotential calculations, by using higher-order finite-element discretizations. On all the benchmark systems studied, we observe diminishing returns in computational savings beyond the sixth-order for accuracies commensurate with chemical accuracy, suggesting that the hexic spectral-element may be an optimal choice for the finite-element discretization of the Kohn–Sham DFT problem. A comparative study of the computational efficiency of the proposed higher-order finite-element discretizations suggests that the performance of finite-element basis is competing with the plane-wave discretization for non-periodic local pseudopotential calculations, and compares to the Gaussian basis for all-electron calculations to within an order of magnitude. Further, we demonstrate the capability of the proposed approach to compute the electronic structure of a metallic system containing 1688 atoms using modest computational resources, and good scalability of the present implementation up to 192 processors.« less
Loop transfer recovery for general nonminimum phase discrete time systems. I - Analysis
NASA Technical Reports Server (NTRS)
Chen, Ben M.; Saberi, Ali; Sannuti, Peddapullaiah; Shamash, Yacov
1992-01-01
A complete analysis of loop transfer recovery (LTR) for general nonstrictly proper, not necessarily minimum phase discrete time systems is presented. Three different observer-based controllers, namely, `prediction estimator' and full or reduced-order type `current estimator' based controllers, are used. The analysis corresponding to all these three controllers is unified into a single mathematical framework. The LTR analysis given here focuses on three fundamental issues: (1) the recoverability of a target loop when it is arbitrarily given, (2) the recoverability of a target loop while taking into account its specific characteristics, and (3) the establishment of necessary and sufficient conditions on the given system so that it has at least one recoverable target loop transfer function or sensitivity function. Various differences that arise in LTR analysis of continuous and discrete systems are pointed out.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Ju, E-mail: jliu@ices.utexas.edu; Gomez, Hector; Evans, John A.
2013-09-01
We propose a new methodology for the numerical solution of the isothermal Navier–Stokes–Korteweg equations. Our methodology is based on a semi-discrete Galerkin method invoking functional entropy variables, a generalization of classical entropy variables, and a new time integration scheme. We show that the resulting fully discrete scheme is unconditionally stable-in-energy, second-order time-accurate, and mass-conservative. We utilize isogeometric analysis for spatial discretization and verify the aforementioned properties by adopting the method of manufactured solutions and comparing coarse mesh solutions with overkill solutions. Various problems are simulated to show the capability of the method. Our methodology provides a means of constructing unconditionallymore » stable numerical schemes for nonlinear non-convex hyperbolic systems of conservation laws.« less
Entropic lattice Boltzmann representations required to recover Navier-Stokes flows.
Keating, Brian; Vahala, George; Yepez, Jeffrey; Soe, Min; Vahala, Linda
2007-03-01
There are two disparate formulations of the entropic lattice Boltzmann scheme: one of these theories revolves around the analog of the discrete Boltzmann H function of standard extensive statistical mechanics, while the other revolves around the nonextensive Tsallis entropy. It is shown here that it is the nonenforcement of the pressure tensor moment constraints that lead to extremizations of entropy resulting in Tsallis-like forms. However, with the imposition of the pressure tensor moment constraint, as is fundamentally necessary for the recovery of the Navier-Stokes equations, it is proved that the entropy function must be of the discrete Boltzmann form. Three-dimensional simulations are performed which illustrate some of the differences between standard lattice Boltzmann and entropic lattice Boltzmann schemes, as well as the role played by the number of phase-space velocities used in the discretization.
Solórzano, S; Mendoza, M; Succi, S; Herrmann, H J
2018-01-01
We present a numerical scheme to solve the Wigner equation, based on a lattice discretization of momentum space. The moments of the Wigner function are recovered exactly, up to the desired order given by the number of discrete momenta retained in the discretization, which also determines the accuracy of the method. The Wigner equation is equipped with an additional collision operator, designed in such a way as to ensure numerical stability without affecting the evolution of the relevant moments of the Wigner function. The lattice Wigner scheme is validated for the case of quantum harmonic and anharmonic potentials, showing good agreement with theoretical results. It is further applied to the study of the transport properties of one- and two-dimensional open quantum systems with potential barriers. Finally, the computational viability of the scheme for the case of three-dimensional open systems is also illustrated.
NASA Astrophysics Data System (ADS)
Solórzano, S.; Mendoza, M.; Succi, S.; Herrmann, H. J.
2018-01-01
We present a numerical scheme to solve the Wigner equation, based on a lattice discretization of momentum space. The moments of the Wigner function are recovered exactly, up to the desired order given by the number of discrete momenta retained in the discretization, which also determines the accuracy of the method. The Wigner equation is equipped with an additional collision operator, designed in such a way as to ensure numerical stability without affecting the evolution of the relevant moments of the Wigner function. The lattice Wigner scheme is validated for the case of quantum harmonic and anharmonic potentials, showing good agreement with theoretical results. It is further applied to the study of the transport properties of one- and two-dimensional open quantum systems with potential barriers. Finally, the computational viability of the scheme for the case of three-dimensional open systems is also illustrated.
Robust passivity analysis for discrete-time recurrent neural networks with mixed delays
NASA Astrophysics Data System (ADS)
Huang, Chuan-Kuei; Shu, Yu-Jeng; Chang, Koan-Yuh; Shou, Ho-Nien; Lu, Chien-Yu
2015-02-01
This article considers the robust passivity analysis for a class of discrete-time recurrent neural networks (DRNNs) with mixed time-delays and uncertain parameters. The mixed time-delays that consist of both the discrete time-varying and distributed time-delays in a given range are presented, and the uncertain parameters are norm-bounded. The activation functions are assumed to be globally Lipschitz continuous. Based on new bounding technique and appropriate type of Lyapunov functional, a sufficient condition is investigated to guarantee the existence of the desired robust passivity condition for the DRNNs, which can be derived in terms of a family of linear matrix inequality (LMI). Some free-weighting matrices are introduced to reduce the conservatism of the criterion by using the bounding technique. A numerical example is given to illustrate the effectiveness and applicability.
Uher, Vojtěch; Gajdoš, Petr; Radecký, Michal; Snášel, Václav
2016-01-01
The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price. It is popular for its simplicity and robustness. This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed. The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants. However, the DE has a great potential in the spatial data analysis and pattern recognition. This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions. It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs). The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs. The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population. A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced. The algorithm is tested on several spatial datasets and optimization problems. The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds.
Utilization of the Discrete Differential Evolution for Optimization in Multidimensional Point Clouds
Radecký, Michal; Snášel, Václav
2016-01-01
The Differential Evolution (DE) is a widely used bioinspired optimization algorithm developed by Storn and Price. It is popular for its simplicity and robustness. This algorithm was primarily designed for real-valued problems and continuous functions, but several modified versions optimizing both integer and discrete-valued problems have been developed. The discrete-coded DE has been mostly used for combinatorial problems in a set of enumerative variants. However, the DE has a great potential in the spatial data analysis and pattern recognition. This paper formulates the problem as a search of a combination of distinct vertices which meet the specified conditions. It proposes a novel approach called the Multidimensional Discrete Differential Evolution (MDDE) applying the principle of the discrete-coded DE in discrete point clouds (PCs). The paper examines the local searching abilities of the MDDE and its convergence to the global optimum in the PCs. The multidimensional discrete vertices cannot be simply ordered to get a convenient course of the discrete data, which is crucial for good convergence of a population. A novel mutation operator utilizing linear ordering of spatial data based on the space filling curves is introduced. The algorithm is tested on several spatial datasets and optimization problems. The experiments show that the MDDE is an efficient and fast method for discrete optimizations in the multidimensional point clouds. PMID:27974884
RINGMesh: A programming library for developing mesh-based geomodeling applications
NASA Astrophysics Data System (ADS)
Pellerin, Jeanne; Botella, Arnaud; Bonneau, François; Mazuyer, Antoine; Chauvin, Benjamin; Lévy, Bruno; Caumon, Guillaume
2017-07-01
RINGMesh is a C++ open-source programming library for manipulating discretized geological models. It is designed to ease the development of applications and workflows that use discretized 3D models. It is neither a geomodeler, nor a meshing software. RINGMesh implements functionalities to read discretized surface-based or volumetric structural models and to check their validity. The models can be then exported in various file formats. RINGMesh provides data structures to represent geological structural models, either defined by their discretized boundary surfaces, and/or by discretized volumes. A programming interface allows to develop of new geomodeling methods, and to plug in external software. The goal of RINGMesh is to help researchers to focus on the implementation of their specific method rather than on tedious tasks common to many applications. The documented code is open-source and distributed under the modified BSD license. It is available at https://www.ring-team.org/index.php/software/ringmesh.
Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo
2017-07-01
This paper presents the design of a novel adaptive event-triggered control method based on the heuristic dynamic programming (HDP) technique for nonlinear discrete-time systems with unknown system dynamics. In the proposed method, the control law is only updated when the event-triggered condition is violated. Compared with the periodic updates in the traditional adaptive dynamic programming (ADP) control, the proposed method can reduce the computation and transmission cost. An actor-critic framework is used to learn the optimal event-triggered control law and the value function. Furthermore, a model network is designed to estimate the system state vector. The main contribution of this paper is to design a new trigger threshold for discrete-time systems. A detailed Lyapunov stability analysis shows that our proposed event-triggered controller can asymptotically stabilize the discrete-time systems. Finally, we test our method on two different discrete-time systems, and the simulation results are included.
Geometric description of a discrete power function associated with the sixth Painlevé equation.
Joshi, Nalini; Kajiwara, Kenji; Masuda, Tetsu; Nakazono, Nobutaka; Shi, Yang
2017-11-01
In this paper, we consider the discrete power function associated with the sixth Painlevé equation. This function is a special solution of the so-called cross-ratio equation with a similarity constraint. We show in this paper that this system is embedded in a cubic lattice with [Formula: see text] symmetry. By constructing the action of [Formula: see text] as a subgroup of [Formula: see text], i.e. the symmetry group of P VI , we show how to relate [Formula: see text] to the symmetry group of the lattice. Moreover, by using translations in [Formula: see text], we explain the odd-even structure appearing in previously known explicit formulae in terms of the τ function.
NASA Technical Reports Server (NTRS)
Kuo, B. C.; Singh, G.
1974-01-01
The dynamics of the Large Space Telescope (LST) control system were studied in order to arrive at a simplified model for computer simulation without loss of accuracy. The frictional nonlinearity of the Control Moment Gyroscope (CMG) Control Loop was analyzed in a model to obtain data for the following: (1) a continuous describing function for the gimbal friction nonlinearity; (2) a describing function of the CMG nonlinearity using an analytical torque equation; and (3) the discrete describing function and function plots for CMG functional linearity. Preliminary computer simulations are shown for the simplified LST system, first without, and then with analytical torque expressions. Transfer functions of the sampled-data LST system are also described. A final computer simulation is presented which uses elements of the simplified sampled-data LST system with analytical CMG frictional torque expressions.
Error due to unresolved scales in estimation problems for atmospheric data assimilation
NASA Astrophysics Data System (ADS)
Janjic, Tijana
The error arising due to unresolved scales in data assimilation procedures is examined. The problem of estimating the projection of the state of a passive scalar undergoing advection at a sequence of times is considered. The projection belongs to a finite- dimensional function space and is defined on the continuum. Using the continuum projection of the state of a passive scalar, a mathematical definition is obtained for the error arising due to the presence, in the continuum system, of scales unresolved by the discrete dynamical model. This error affects the estimation procedure through point observations that include the unresolved scales. In this work, two approximate methods for taking into account the error due to unresolved scales and the resulting correlations are developed and employed in the estimation procedure. The resulting formulas resemble the Schmidt-Kalman filter and the usual discrete Kalman filter, respectively. For this reason, the newly developed filters are called the Schmidt-Kalman filter and the traditional filter. In order to test the assimilation methods, a two- dimensional advection model with nonstationary spectrum was developed for passive scalar transport in the atmosphere. An analytical solution on the sphere was found depicting the model dynamics evolution. Using this analytical solution the model error is avoided, and the error due to unresolved scales is the only error left in the estimation problem. It is demonstrated that the traditional and the Schmidt- Kalman filter work well provided the exact covariance function of the unresolved scales is known. However, this requirement is not satisfied in practice, and the covariance function must be modeled. The Schmidt-Kalman filter cannot be computed in practice without further approximations. Therefore, the traditional filter is better suited for practical use. Also, the traditional filter does not require modeling of the full covariance function of the unresolved scales, but only modeling of the covariance matrix obtained by evaluating the covariance function at the observation points. We first assumed that this covariance matrix is stationary and that the unresolved scales are not correlated between the observation points, i.e., the matrix is diagonal, and that the values along the diagonal are constant. Tests with these assumptions were unsuccessful, indicating that a more sophisticated model of the covariance is needed for assimilation of data with nonstationary spectrum. A new method for modeling the covariance matrix based on an extended set of modeling assumptions is proposed. First, it is assumed that the covariance matrix is diagonal, that is, that the unresolved scales are not correlated between the observation points. It is postulated that the values on the diagonal depend on a wavenumber that is characteristic for the unresolved part of the spectrum. It is further postulated that this characteristic wavenumber can be diagnosed from the observations and from the estimate of the projection of the state that is being estimated. It is demonstrated that the new method successfully overcomes previously encountered difficulties.
On Extended Dissipativity of Discrete-Time Neural Networks With Time Delay.
Feng, Zhiguang; Zheng, Wei Xing
2015-12-01
In this brief, the problem of extended dissipativity analysis for discrete-time neural networks with time-varying delay is investigated. The definition of extended dissipativity of discrete-time neural networks is proposed, which unifies several performance measures, such as the H∞ performance, passivity, l2 - l∞ performance, and dissipativity. By introducing a triple-summable term in Lyapunov function, the reciprocally convex approach is utilized to bound the forward difference of the triple-summable term and then the extended dissipativity criterion for discrete-time neural networks with time-varying delay is established. The derived condition guarantees not only the extended dissipativity but also the stability of the neural networks. Two numerical examples are given to demonstrate the reduced conservatism and effectiveness of the obtained results.
NASA Astrophysics Data System (ADS)
Liu, Zeyu; Xia, Tiecheng; Wang, Jinbo
2018-03-01
We propose a new fractional two-dimensional triangle function combination discrete chaotic map (2D-TFCDM) with the discrete fractional difference. Moreover, the chaos behaviors of the proposed map are observed and the bifurcation diagrams, the largest Lyapunov exponent plot, and the phase portraits are derived, respectively. Finally, with the secret keys generated by Menezes–Vanstone elliptic curve cryptosystem, we apply the discrete fractional map into color image encryption. After that, the image encryption algorithm is analyzed in four aspects and the result indicates that the proposed algorithm is more superior than the other algorithms. Project supported by the National Natural Science Foundation of China (Grant Nos. 61072147 and 11271008).
Uniform sparse bounds for discrete quadratic phase Hilbert transforms
NASA Astrophysics Data System (ADS)
Kesler, Robert; Arias, Darío Mena
2017-09-01
For each α \\in T consider the discrete quadratic phase Hilbert transform acting on finitely supported functions f : Z → C according to H^{α }f(n):= \\sum _{m ≠ 0} e^{iα m^2} f(n - m)/m. We prove that, uniformly in α \\in T , there is a sparse bound for the bilinear form < H^{α } f , g > for every pair of finitely supported functions f,g : Z→ C . The sparse bound implies several mapping properties such as weighted inequalities in an intersection of Muckenhoupt and reverse Hölder classes.
Spectral Discrete Probability Density Function of Measured Wind Turbine Noise in the Far Field
Ashtiani, Payam; Denison, Adelaide
2015-01-01
Of interest is the spectral character of wind turbine noise at typical residential set-back distances. In this paper, a spectral statistical analysis has been applied to immission measurements conducted at three locations. This method provides discrete probability density functions for the Turbine ONLY component of the measured noise. This analysis is completed for one-third octave sound levels, at integer wind speeds, and is compared to existing metrics for measuring acoustic comfort as well as previous discussions on low-frequency noise sources. PMID:25905097
Sampling rare fluctuations of discrete-time Markov chains
NASA Astrophysics Data System (ADS)
Whitelam, Stephen
2018-03-01
We describe a simple method that can be used to sample the rare fluctuations of discrete-time Markov chains. We focus on the case of Markov chains with well-defined steady-state measures, and derive expressions for the large-deviation rate functions (and upper bounds on such functions) for dynamical quantities extensive in the length of the Markov chain. We illustrate the method using a series of simple examples, and use it to study the fluctuations of a lattice-based model of active matter that can undergo motility-induced phase separation.
Sampling rare fluctuations of discrete-time Markov chains.
Whitelam, Stephen
2018-03-01
We describe a simple method that can be used to sample the rare fluctuations of discrete-time Markov chains. We focus on the case of Markov chains with well-defined steady-state measures, and derive expressions for the large-deviation rate functions (and upper bounds on such functions) for dynamical quantities extensive in the length of the Markov chain. We illustrate the method using a series of simple examples, and use it to study the fluctuations of a lattice-based model of active matter that can undergo motility-induced phase separation.
Angular Distributions of Discrete Mesoscale Mapping Functions
NASA Astrophysics Data System (ADS)
Kroszczyński, Krzysztof
2015-08-01
The paper presents the results of analyses of numerical experiments concerning GPS signal propagation delays in the atmosphere and the discrete mapping functions defined on their basis. The delays were determined using data from the mesoscale non-hydrostatic weather model operated in the Centre of Applied Geomatics, Military University of Technology. A special attention was paid to investigating angular characteristics of GPS slant delays for low angles of elevation. The investigation proved that the temporal and spatial variability of the slant delays depends to a large extent on current weather conditions.
On Weak and Strong 2k- bent Boolean Functions
2016-01-01
U.S.A. Email: pstanica@nps.edu Abstract—In this paper we introduce a sequence of discrete Fourier transforms and define new versions of bent...denotes the complex conjugate of z. An important tool in our analysis is the discrete Fourier transform , known in Boolean functions literature, as Walsh...Hadamard, or Walsh–Hadamard transform , which is the func- tion Wf : Fn2 → C, defined by Wf (u) = 2− n 2 ∑ x∈Vn (−1)f(x)⊕u·x. Any f ∈ Bn can be
Generation of Synthetic Spike Trains with Defined Pairwise Correlations
Niebur, Ernst
2008-01-01
Recent technological advances as well as progress in theoretical understanding of neural systems have created a need for synthetic spike trains with controlled mean rate and pairwise cross-correlation. This report introduces and analyzes a novel algorithm for the generation of discretized spike trains with arbitrary mean rates and controlled cross correlation. Pairs of spike trains with any pairwise correlation can be generated, and higher-order correlations are compatible with common synaptic input. Relations between allowable mean rates and correlations within a population are discussed. The algorithm is highly efficient, its complexity increasing linearly with the number of spike trains generated and therefore inversely with the number of cross-correlated pairs. PMID:17521277
A Bayesian hierarchical model for discrete choice data in health care.
Antonio, Anna Liza M; Weiss, Robert E; Saigal, Christopher S; Dahan, Ely; Crespi, Catherine M
2017-01-01
In discrete choice experiments, patients are presented with sets of health states described by various attributes and asked to make choices from among them. Discrete choice experiments allow health care researchers to study the preferences of individual patients by eliciting trade-offs between different aspects of health-related quality of life. However, many discrete choice experiments yield data with incomplete ranking information and sparsity due to the limited number of choice sets presented to each patient, making it challenging to estimate patient preferences. Moreover, methods to identify outliers in discrete choice data are lacking. We develop a Bayesian hierarchical random effects rank-ordered multinomial logit model for discrete choice data. Missing ranks are accounted for by marginalizing over all possible permutations of unranked alternatives to estimate individual patient preferences, which are modeled as a function of patient covariates. We provide a Bayesian version of relative attribute importance, and adapt the use of the conditional predictive ordinate to identify outlying choice sets and outlying individuals with unusual preferences compared to the population. The model is applied to data from a study using a discrete choice experiment to estimate individual patient preferences for health states related to prostate cancer treatment.
A novel iris patterns matching algorithm of weighted polar frequency correlation
NASA Astrophysics Data System (ADS)
Zhao, Weijie; Jiang, Linhua
2014-11-01
Iris recognition is recognized as one of the most accurate techniques for biometric authentication. In this paper, we present a novel correlation method - Weighted Polar Frequency Correlation(WPFC) - to match and evaluate two iris images, actually it can also be used for evaluating the similarity of any two images. The WPFC method is a novel matching and evaluating method for iris image matching, which is complete different from the conventional methods. For instance, the classical John Daugman's method of iris recognition uses 2D Gabor wavelets to extract features of iris image into a compact bit stream, and then matching two bit streams with hamming distance. Our new method is based on the correlation in the polar coordinate system in frequency domain with regulated weights. The new method is motivated by the observation that the pattern of iris that contains far more information for recognition is fine structure at high frequency other than the gross shapes of iris images. Therefore, we transform iris images into frequency domain and set different weights to frequencies. Then calculate the correlation of two iris images in frequency domain. We evaluate the iris images by summing the discrete correlation values with regulated weights, comparing the value with preset threshold to tell whether these two iris images are captured from the same person or not. Experiments are carried out on both CASIA database and self-obtained images. The results show that our method is functional and reliable. Our method provides a new prospect for iris recognition system.
Research of generalized wavelet transformations of Haar correctness in remote sensing of the Earth
NASA Astrophysics Data System (ADS)
Kazaryan, Maretta; Shakhramanyan, Mihail; Nedkov, Roumen; Richter, Andrey; Borisova, Denitsa; Stankova, Nataliya; Ivanova, Iva; Zaharinova, Mariana
2017-10-01
In this paper, Haar's generalized wavelet functions are applied to the problem of ecological monitoring by the method of remote sensing of the Earth. We study generalized Haar wavelet series and suggest the use of Tikhonov's regularization method for investigating them for correctness. In the solution of this problem, an important role is played by classes of functions that were introduced and described in detail by I.M. Sobol for studying multidimensional quadrature formulas and it contains functions with rapidly convergent series of wavelet Haar. A theorem on the stability and uniform convergence of the regularized summation function of the generalized wavelet-Haar series of a function from this class with approximate coefficients is proved. The article also examines the problem of using orthogonal transformations in Earth remote sensing technologies for environmental monitoring. Remote sensing of the Earth allows to receive from spacecrafts information of medium, high spatial resolution and to conduct hyperspectral measurements. Spacecrafts have tens or hundreds of spectral channels. To process the images, the device of discrete orthogonal transforms, and namely, wavelet transforms, was used. The aim of the work is to apply the regularization method in one of the problems associated with remote sensing of the Earth and subsequently to process the satellite images through discrete orthogonal transformations, in particular, generalized Haar wavelet transforms. General methods of research. In this paper, Tikhonov's regularization method, the elements of mathematical analysis, the theory of discrete orthogonal transformations, and methods for decoding of satellite images are used. Scientific novelty. The task of processing of archival satellite snapshots (images), in particular, signal filtering, was investigated from the point of view of an incorrectly posed problem. The regularization parameters for discrete orthogonal transformations were determined.
Clustering and variable selection in the presence of mixed variable types and missing data.
Storlie, C B; Myers, S M; Katusic, S K; Weaver, A L; Voigt, R G; Croarkin, P E; Stoeckel, R E; Port, J D
2018-05-17
We consider the problem of model-based clustering in the presence of many correlated, mixed continuous, and discrete variables, some of which may have missing values. Discrete variables are treated with a latent continuous variable approach, and the Dirichlet process is used to construct a mixture model with an unknown number of components. Variable selection is also performed to identify the variables that are most influential for determining cluster membership. The work is motivated by the need to cluster patients thought to potentially have autism spectrum disorder on the basis of many cognitive and/or behavioral test scores. There are a modest number of patients (486) in the data set along with many (55) test score variables (many of which are discrete valued and/or missing). The goal of the work is to (1) cluster these patients into similar groups to help identify those with similar clinical presentation and (2) identify a sparse subset of tests that inform the clusters in order to eliminate unnecessary testing. The proposed approach compares very favorably with other methods via simulation of problems of this type. The results of the autism spectrum disorder analysis suggested 3 clusters to be most likely, while only 4 test scores had high (>0.5) posterior probability of being informative. This will result in much more efficient and informative testing. The need to cluster observations on the basis of many correlated, continuous/discrete variables with missing values is a common problem in the health sciences as well as in many other disciplines. Copyright © 2018 John Wiley & Sons, Ltd.
Nielsen, J D; Dean, C B
2008-09-01
A flexible semiparametric model for analyzing longitudinal panel count data arising from mixtures is presented. Panel count data refers here to count data on recurrent events collected as the number of events that have occurred within specific follow-up periods. The model assumes that the counts for each subject are generated by mixtures of nonhomogeneous Poisson processes with smooth intensity functions modeled with penalized splines. Time-dependent covariate effects are also incorporated into the process intensity using splines. Discrete mixtures of these nonhomogeneous Poisson process spline models extract functional information from underlying clusters representing hidden subpopulations. The motivating application is an experiment to test the effectiveness of pheromones in disrupting the mating pattern of the cherry bark tortrix moth. Mature moths arise from hidden, but distinct, subpopulations and monitoring the subpopulation responses was of interest. Within-cluster random effects are used to account for correlation structures and heterogeneity common to this type of data. An estimating equation approach to inference requiring only low moment assumptions is developed and the finite sample properties of the proposed estimating functions are investigated empirically by simulation.
Galaxies and gas in a cold dark matter universe
NASA Technical Reports Server (NTRS)
Katz, Neal; Hernquist, Lars; Weinberg, David H.
1992-01-01
We use a combined gravity/hydrodynamics code to simulate the formation of structure in a random 22 Mpc cube of a cold dark matter universe. Adiabatic compression and shocks heat much of the gas to temperatures of 10 exp 6 - 10 exp 7 K, but a fraction of the gas cools radiatively to about 10 exp 4 K and condenses into discrete, highly overdense lumps. We identify these lumps with galaxies. The high-mass end of their baryonic mass function fits the form of the observed galaxy luminosity function. They retain independent identities after their dark halos merge, so gravitational clustering produces groups of galaxies embedded in relatively smooth envelopes of hot gas and dark matter. The galaxy correlation function is approximately an r exp -2.1 power law from separations of 35 kpc to 7 Mpc. Galaxy fluctuations are biased relative to dark matter fluctuations by a factor b about 1.5. We find no significant 'velocity bias' between galaxies and dark matter particles. However, virial analysis of the simulation's richest group leads to an estimated Omega of about 0.3, even though the simulation adopts Omega = 1.
Theory of L -edge spectroscopy of strongly correlated systems
NASA Astrophysics Data System (ADS)
Lüder, Johann; Schött, Johan; Brena, Barbara; Haverkort, Maurits W.; Thunström, Patrik; Eriksson, Olle; Sanyal, Biplab; Di Marco, Igor; Kvashnin, Yaroslav O.
2017-12-01
X-ray absorption spectroscopy measured at the L edge of transition metals (TMs) is a powerful element-selective tool providing direct information about the correlation effects in the 3 d states. The theoretical modeling of the 2 p →3 d excitation processes remains to be challenging for contemporary ab initio electronic structure techniques, due to strong core-hole and multiplet effects influencing the spectra. In this work, we present a realization of the method combining the density-functional theory with multiplet ligand field theory, proposed in Haverkort et al. [Phys. Rev. B 85, 165113 (2012), 10.1103/PhysRevB.85.165113]. In this approach, a single-impurity Anderson model (SIAM) is constructed, with almost all parameters obtained from first principles, and then solved to obtain the spectra. In our implementation, we adopt the language of the dynamical mean-field theory and utilize the local density of states and the hybridization function, projected onto TM 3 d states, in order to construct the SIAM. The developed computational scheme is applied to calculate the L -edge spectra for several TM monoxides. A very good agreement between the theory and experiment is found for all studied systems. The effect of core-hole relaxation, hybridization discretization, possible extensions of the method as well as its limitations are discussed.
Liu, Yan-Jun; Gao, Ying; Tong, Shaocheng; Chen, C L Philip
2016-01-01
In this paper, an effective adaptive control approach is constructed to stabilize a class of nonlinear discrete-time systems, which contain unknown functions, unknown dead-zone input, and unknown control direction. Different from linear dead zone, the dead zone, in this paper, is a kind of nonlinear dead zone. To overcome the noncausal problem, which leads to the control scheme infeasible, the systems can be transformed into a m -step-ahead predictor. Due to nonlinear dead-zone appearance, the transformed predictor still contains the nonaffine function. In addition, it is assumed that the gain function of dead-zone input and the control direction are unknown. These conditions bring about the difficulties and the complicacy in the controller design. Thus, the implicit function theorem is applied to deal with nonaffine dead-zone appearance, the problem caused by the unknown control direction can be resolved through applying the discrete Nussbaum gain, and the neural networks are used to approximate the unknown function. Based on the Lyapunov theory, all the signals of the resulting closed-loop system are proved to be semiglobal uniformly ultimately bounded. Moreover, the tracking error is proved to be regulated to a small neighborhood around zero. The feasibility of the proposed approach is demonstrated by a simulation example.
NASA Astrophysics Data System (ADS)
Proklov, V. V.; Rezvov, Yu. G.
2018-01-01
An analytical solution for the transmission function of noncoherent wideband radiation is obtained under acousto-optic (AO) filtering using a discrete set of monochromatic AO waves with a small spectral overlap. We studied characteristics of the AO transformation of a continuous spectrum of noncoherent radiation into a given set of discrete narrow bands of spectral transmission by excitation of a discrete set of sound frequencies. We carried out the analysis of transmission functions of individual channels taking into account a partial overlap of their spectra and possible intermodulation distortions. It is shown that a stationary value of the root-mean-square light power is found at the electronic output due to the photoelectric transformation and detecting diffracted light. Based on this, a necessary stationary, multiband, and nearly equidistant transmission function of a device can be formed by using a relevant spectrum of acoustic excitation. Peculiarities of this way of forming the multiband transmission function are revealed: the limitation of diffraction efficiency for an individual channel, the possibility of decoupling side lobes of adjacent channels, etc. A multiband acousto-optic filter (MAOF) was simulated that was based on a paratellurite monocrystal (TeO2), which was previously used for experimental optical encoding. The theoretical and experimental results are in gratifying agreement.
Explicit asymmetric bounds for robust stability of continuous and discrete-time systems
NASA Technical Reports Server (NTRS)
Gao, Zhiqiang; Antsaklis, Panos J.
1993-01-01
The problem of robust stability in linear systems with parametric uncertainties is considered. Explicit stability bounds on uncertain parameters are derived and expressed in terms of linear inequalities for continuous systems, and inequalities with quadratic terms for discrete-times systems. Cases where system parameters are nonlinear functions of an uncertainty are also examined.
ERIC Educational Resources Information Center
Dail, Teresa K.; Christina, Robert W.
2004-01-01
This study examined judgments of learning and the long-term retention of a discrete motor task (golf putting) as a function of practice distribution. The results indicated that participants in the distributed practice group performed more proficiently than those in the massed practice group during both acquisition and retention phases. No…
On the Computational Complexity of Stochastic Scheduling Problems,
1981-09-01
Survey": 1979, Ann. Discrete Math . 5, pp. 287-326. i I (.4) Karp, R.M., "Reducibility Among Combinatorial Problems": 1972, R.E. Miller and J.W...Weighted Completion Time Subject to Precedence Constraints": 1978, Ann. Discrete Math . 2, pp. 75-90. (8) Lawler, E.L. and J.W. Moore, "A Functional
A fast solver for the Helmholtz equation based on the generalized multiscale finite-element method
NASA Astrophysics Data System (ADS)
Fu, Shubin; Gao, Kai
2017-11-01
Conventional finite-element methods for solving the acoustic-wave Helmholtz equation in highly heterogeneous media usually require finely discretized mesh to represent the medium property variations with sufficient accuracy. Computational costs for solving the Helmholtz equation can therefore be considerably expensive for complicated and large geological models. Based on the generalized multiscale finite-element theory, we develop a novel continuous Galerkin method to solve the Helmholtz equation in acoustic media with spatially variable velocity and mass density. Instead of using conventional polynomial basis functions, we use multiscale basis functions to form the approximation space on the coarse mesh. The multiscale basis functions are obtained from multiplying the eigenfunctions of a carefully designed local spectral problem with an appropriate multiscale partition of unity. These multiscale basis functions can effectively incorporate the characteristics of heterogeneous media's fine-scale variations, thus enable us to obtain accurate solution to the Helmholtz equation without directly solving the large discrete system formed on the fine mesh. Numerical results show that our new solver can significantly reduce the dimension of the discrete Helmholtz equation system, and can also obviously reduce the computational time.
Radiative transfer models for retrieval of cloud parameters from EPIC/DSCOVR measurements
NASA Astrophysics Data System (ADS)
Molina García, Víctor; Sasi, Sruthy; Efremenko, Dmitry S.; Doicu, Adrian; Loyola, Diego
2018-07-01
In this paper we analyze the accuracy and efficiency of several radiative transfer models for inferring cloud parameters from radiances measured by the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR). The radiative transfer models are the exact discrete ordinate and matrix operator methods with matrix exponential, and the approximate asymptotic and equivalent Lambertian cloud models. To deal with the computationally expensive radiative transfer calculations, several acceleration techniques such as, for example, the telescoping technique, the method of false discrete ordinate, the correlated k-distribution method and the principal component analysis (PCA) are used. We found that, for the EPIC oxygen A-band absorption channel at 764 nm, the exact models using the correlated k-distribution in conjunction with PCA yield an accuracy better than 1.5% and a computation time of 18 s for radiance calculations at 5 viewing zenith angles.
Improved Subcell Model for the Prediction of Braided Composite Response
NASA Technical Reports Server (NTRS)
Cater, Christopher R.; Xinran, Xiao; Goldberg, Robert K.; Kohlman, Lee W.
2013-01-01
In this work, the modeling of triaxially braided composites was explored through a semi-analytical discretization. Four unique subcells, each approximated by a "mosaic" stacking of unidirectional composite plies, were modeled through the use of layered-shell elements within the explicit finite element code LS-DYNA. Two subcell discretizations were investigated: a model explicitly capturing pure matrix regions, and a novel model which absorbed pure matrix pockets into neighboring tow plies. The in-plane stiffness properties of both models, computed using bottom-up micromechanics, correlated well to experimental data. The absorbed matrix model, however, was found to best capture out-of- plane flexural properties by comparing numerical simulations of the out-of-plane displacements from single-ply tension tests to experimental full field data. This strong correlation of out-of-plane characteristics supports the current modeling approach as a viable candidate for future work involving impact simulations.
Wildberger, H
1984-10-31
The contrast evoked potentials (VEPs) to different check sizes were recorded in about 200 cases of discrete optic neuropathies (ON) of different origin. Differential light threshold (DLT) was tested with the computer perimeter OCTOPUS. Saturated and desaturated tests were applied to evaluate the degree of acquired color vision deficiency. Delayed VEP responses are not confined to optic neuritis (RBN) alone and the different latency times obtained from other ON are confluent. The delay may be due to demyelination, to an increasing dominance of paramacular VEP subcomponents or to an increasing dominance of the upper half-field responses. Recording with smaller check sizes has the advantage that discrete dysfunctions in the visual field (VF) center are more easily detected: a correlation between amplitudes and visual acuity is best in strabismic amblyopias, is less expressed in maculopathies of the retina and weak in ON. The absence or reduction of amplitudes to smaller check sizes, however, is an important indication of a disorder in the VF center of ON in an early or recovered stage. Acquired color vision defects of the tritan-like type are more confined to discrete ON, whereas the red/green type is reserved to more severe ON. The DLT of the VF center is reduced in a different, significant and non significant extent in discrete optic neuropathies and the correlation between DLT and visual acuity is weak. A careful numerical analysis is needed in types of discrete ON where the central DLT lies within normal statistical limits: a side difference of the DLT between the affected and the normal fellow eye is always present. Evaluation of visual fatigue effects and of the relative sensitivity loss of VF center and VF periphery may provide further diagnostic information.
NASA Astrophysics Data System (ADS)
Macías-Díaz, J. E.
2018-06-01
In this work, we investigate numerically a model governed by a multidimensional nonlinear wave equation with damping and fractional diffusion. The governing partial differential equation considers the presence of Riesz space-fractional derivatives of orders in (1, 2], and homogeneous Dirichlet boundary data are imposed on a closed and bounded spatial domain. The model under investigation possesses an energy function which is preserved in the undamped regime. In the damped case, we establish the property of energy dissipation of the model using arguments from functional analysis. Motivated by these results, we propose an explicit finite-difference discretization of our fractional model based on the use of fractional centered differences. Associated to our discrete model, we also propose discretizations of the energy quantities. We establish that the discrete energy is conserved in the undamped regime, and that it dissipates in the damped scenario. Among the most important numerical features of our scheme, we show that the method has a consistency of second order, that it is stable and that it has a quadratic order of convergence. Some one- and two-dimensional simulations are shown in this work to illustrate the fact that the technique is capable of preserving the discrete energy in the undamped regime. For the sake of convenience, we provide a Matlab implementation of our method for the one-dimensional scenario.
Numerical time-domain electromagnetics based on finite-difference and convolution
NASA Astrophysics Data System (ADS)
Lin, Yuanqu
Time-domain methods posses a number of advantages over their frequency-domain counterparts for the solution of wideband, nonlinear, and time varying electromagnetic scattering and radiation phenomenon. Time domain integral equation (TDIE)-based methods, which incorporate the beneficial properties of integral equation method, are thus well suited for solving broadband scattering problems for homogeneous scatterers. Widespread adoption of TDIE solvers has been retarded relative to other techniques by their inefficiency, inaccuracy and instability. Moreover, two-dimensional (2D) problems are especially problematic, because 2D Green's functions have infinite temporal support, exacerbating these difficulties. This thesis proposes a finite difference delay modeling (FDDM) scheme for the solution of the integral equations of 2D transient electromagnetic scattering problems. The method discretizes the integral equations temporally using first- and second-order finite differences to map Laplace-domain equations into the Z domain before transforming to the discrete time domain. The resulting procedure is unconditionally stable because of the nature of the Laplace- to Z-domain mapping. The first FDDM method developed in this thesis uses second-order Lagrange basis functions with Galerkin's method for spatial discretization. The second application of the FDDM method discretizes the space using a locally-corrected Nystrom method, which accelerates the precomputation phase and achieves high order accuracy. The Fast Fourier Transform (FFT) is applied to accelerate the marching-on-time process in both methods. While FDDM methods demonstrate impressive accuracy and stability in solving wideband scattering problems for homogeneous scatterers, they still have limitations in analyzing interactions between several inhomogenous scatterers. Therefore, this thesis devises a multi-region finite-difference time-domain (MR-FDTD) scheme based on domain-optimal Green's functions for solving sparsely-populated problems. The scheme uses a discrete Green's function (DGF) on the FDTD lattice to truncate the local subregions, and thus reduces reflection error on the local boundary. A continuous Green's function (CGF) is implemented to pass the influence of external fields into each FDTD region which mitigates the numerical dispersion and anisotropy of standard FDTD. Numerical results will illustrate the accuracy and stability of the proposed techniques.
Li, Min; Zhang, Junying; Dang, Wenqiang; Cushing, Scott K; Guo, Dong; Wu, Nianqiang; Yin, Penggang
2013-10-14
The correlation of the electronic band structure with the photocatalytic activity of AgTaO3 has been studied by simulation and experiments. Doping wide band gap oxide semiconductors usually introduces discrete mid-gap states, which extends the light absorption but has limited benefit for photocatalytic activity. Density functional theory (DFT) calculations show that compensated co-doping in AgTaO3 can overcome this problem by increasing the light absorption and simultaneously improving the charge carrier mobility. N/H and N/F co-doping can delocalize the discrete mid-gap states created by sole N doping in AgTaO3, which increases the band curvature and the electron-to-hole effective mass ratio. In particular, N/F co-doping creates a continuum of states that extend the valence band of AgTaO3. N/F co-doping thus improves the light absorption without creating the mid-gap states, maintaining the necessary redox potentials for water splitting and preventing from charge carrier trapping. The experimental results have confirmed that the N/F-codoped AgTaO3 exhibits a red-shift of the absorption edge in comparison with the undoped AgTaO3, leading to remarkable enhancement of photocatalytic activity toward hydrogen generation from water.
Ostashev, Vladimir E; Wilson, D Keith; Muhlestein, Michael B; Attenborough, Keith
2018-02-01
Although sound propagation in a forest is important in several applications, there are currently no rigorous yet computationally tractable prediction methods. Due to the complexity of sound scattering in a forest, it is natural to formulate the problem stochastically. In this paper, it is demonstrated that the equations for the statistical moments of the sound field propagating in a forest have the same form as those for sound propagation in a turbulent atmosphere if the scattering properties of the two media are expressed in terms of the differential scattering and total cross sections. Using the existing theories for sound propagation in a turbulent atmosphere, this analogy enables the derivation of several results for predicting forest acoustics. In particular, the second-moment parabolic equation is formulated for the spatial correlation function of the sound field propagating above an impedance ground in a forest with micrometeorology. Effective numerical techniques for solving this equation have been developed in atmospheric acoustics. In another example, formulas are obtained that describe the effect of a forest on the interference between the direct and ground-reflected waves. The formulated correspondence between wave propagation in discrete and continuous random media can also be used in other fields of physics.
Multi-functional composite structures
Mulligan, Anthony C.; Halloran, John; Popovich, Dragan; Rigali, Mark J.; Sutaria, Manish P.; Vaidyanathan, K. Ranji; Fulcher, Michael L.; Knittel, Kenneth L.
2004-10-19
Fibrous monolith processing techniques to fabricate multifunctional structures capable of performing more than one discrete function such as structures capable of bearing structural loads and mechanical stresses in service and also capable of performing at least one additional non-structural function.
Multi-functional composite structures
Mulligan, Anthony C.; Halloran, John; Popovich, Dragan; Rigali, Mark J.; Sutaria, Manish P.; Vaidyanathan, K. Ranji; Fulcher, Michael L.; Knittel, Kenneth L.
2010-04-27
Fibrous monolith processing techniques to fabricate multifunctional structures capable of performing more than one discrete function such as structures capable of bearing structural loads and mechanical stresses in service and also capable of performing at least one additional non-structural function.
Li, Huijuan; Liu, Anping; Zhang, Linli
2018-06-01
In this paper, we propose new sufficient criteria for input-to-state stability (ISS) of time-varying nonlinear discrete-time systems via indefinite difference Lyapunov functions. The proposed sufficient conditions for ISS of system are more relaxed than for ISS with respect to Lyapunov functions with negative definite difference. We prove system is ISS by two methods. The first way is to prove system is ISS by indefinite difference ISS Lyapunov functions. The second method is to prove system is ISS via introducing an auxiliary system and indefinite difference robust Lyapunov functions. The comparison of the sufficient conditions for ISS obtained via the two methods is discussed. The effectiveness of our results is illustrated by three numerical examples. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Specification of the utility function in discrete choice experiments.
van der Pol, Marjon; Currie, Gillian; Kromm, Seija; Ryan, Mandy
2014-03-01
The specification of the utility function has received limited attention within the discrete choice experiment (DCE) literature. This lack of investigation is surprising given that evidence from the contingent valuation literature suggests that welfare estimates are sensitive to different specifications of the utility function. This study investigates the effect of different specifications of the utility function on results within a DCE. The DCE elicited the public's preferences for waiting time for hip and knee replacement and estimated willingness to wait (WTW). The results showed that the WTW for the different patient profiles varied considerably across the three different specifications of the utility function. Assuming a linear utility function led to much higher estimates of marginal rates of substitution (WTWs) than with nonlinear specifications. The goodness-of-fit measures indicated that nonlinear specifications were superior. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Wei, Linyang; Qi, Hong; Sun, Jianping; Ren, Yatao; Ruan, Liming
2017-05-01
The spectral collocation method (SCM) is employed to solve the radiative transfer in multi-layer semitransparent medium with graded index. A new flexible angular discretization scheme is employed to discretize the solid angle domain freely to overcome the limit of the number of discrete radiative direction when adopting traditional SN discrete ordinate scheme. Three radial basis function interpolation approaches, named as multi-quadric (MQ), inverse multi-quadric (IMQ) and inverse quadratic (IQ) interpolation, are employed to couple the radiative intensity at the interface between two adjacent layers and numerical experiments show that MQ interpolation has the highest accuracy and best stability. Variable radiative transfer problems in double-layer semitransparent media with different thermophysical properties are investigated and the influence of these thermophysical properties on the radiative transfer procedure in double-layer semitransparent media is also analyzed. All the simulated results show that the present SCM with the new angular discretization scheme can predict the radiative transfer in multi-layer semitransparent medium with graded index efficiently and accurately.
Distinct timing mechanisms produce discrete and continuous movements.
Huys, Raoul; Studenka, Breanna E; Rheaume, Nicole L; Zelaznik, Howard N; Jirsa, Viktor K
2008-04-25
The differentiation of discrete and continuous movement is one of the pillars of motor behavior classification. Discrete movements have a definite beginning and end, whereas continuous movements do not have such discriminable end points. In the past decade there has been vigorous debate whether this classification implies different control processes. This debate up until the present has been empirically based. Here, we present an unambiguous non-empirical classification based on theorems in dynamical system theory that sets discrete and continuous movements apart. Through computational simulations of representative modes of each class and topological analysis of the flow in state space, we show that distinct control mechanisms underwrite discrete and fast rhythmic movements. In particular, we demonstrate that discrete movements require a time keeper while fast rhythmic movements do not. We validate our computational findings experimentally using a behavioral paradigm in which human participants performed finger flexion-extension movements at various movement paces and under different instructions. Our results demonstrate that the human motor system employs different timing control mechanisms (presumably via differential recruitment of neural subsystems) to accomplish varying behavioral functions such as speed constraints.
Self-reported psychological demands, skill discretion and decision authority at work: A twin study.
Theorell, Töres; De Manzano, Örjan; Lennartsson, Anna-Karin; Pedersen, Nancy L; Ullén, Fredrik
2016-06-01
To examine the contribution of genetic factors to self-reported psychological demands (PD), skill discretion (SD) and decision authority (DA) and the possible importance of such influence on the association between these work variables and depressive symptoms. 11,543 participants aged 27-54 in the Swedish Twin Registry participated in a web survey. First of all, in multiple regressions, phenotypic associations between each one of the three work environment variables and depressive symptoms were analysed. Secondly, by means of classical twin analysis, the genetic contribution to PD, SD and DA was assessed. After this, cross-twin cross-trait correlations were computed between PD, SD and DA, on the one hand, and depressive symptom score, on the other hand. The genetic contribution to self-reported PD, DS and DA ranged from 18% for decision authority to 30% for skill discretion. Cross-twin cross-trait correlations were very weak (r values < .1) and non-significant for dizygotic twins, and we lacked power to analyse the genetic architecture of the phenotypic associations using bivariate twin modelling. However, substantial genetic contribution to these associations seems unlikely. CONCLUSIONS GENETIC CONTRIBUTIONS TO THE SELF-REPORTED WORK ENVIRONMENT SCORES WERE 18-30%. © 2016 the Nordic Societies of Public Health.
Abraham, Leandro; Bromberg, Facundo; Forradellas, Raymundo
2018-04-01
Muscle activation level is currently being captured using impractical and expensive devices which make their use in telemedicine settings extremely difficult. To address this issue, a prototype is presented of a non-invasive, easy-to-install system for the estimation of a discrete level of muscle activation of the biceps muscle from 3D point clouds captured with RGB-D cameras. A methodology is proposed that uses the ensemble of shape functions point cloud descriptor for the geometric characterization of 3D point clouds, together with support vector machines to learn a classifier that, based on this geometric characterization for some points of view of the biceps, provides a model for the estimation of muscle activation for all neighboring points of view. This results in a classifier that is robust to small perturbations in the point of view of the capturing device, greatly simplifying the installation process for end-users. In the discrimination of five levels of effort with values up to the maximum voluntary contraction (MVC) of the biceps muscle (3800 g), the best variant of the proposed methodology achieved mean absolute errors of about 9.21% MVC - an acceptable performance for telemedicine settings where the electric measurement of muscle activation is impractical. The results prove that the correlations between the external geometry of the arm and biceps muscle activation are strong enough to consider computer vision and supervised learning an alternative with great potential for practical applications in tele-physiotherapy. Copyright © 2018 Elsevier Ltd. All rights reserved.
Health-Related Quality of Life in Men with Erectile Dysfunction
Litwin, Mark S; Nied, Robert J; Dhanani, Nasreen
1998-01-01
OBJECTIVE To assess health-related quality of life (HRQOL) in men with erectile dysfunction. DESIGN Descriptive survey with general and disease-specific measures. The instrument contained three established, validated HRQOL measures, a validated comorbidity checklist, and sociodemographics. The RAND 36-Item Health Survey 1.0 (SF-36) was used to assess general HRQOL. Sexual function and sexual bother were assessed using the UCLA Prostate Cancer Index. The marital interaction scale from the Cancer Rehabilitation Evaluation System Short Form (CARES-SF) was used to assess each patient's relationship with his sexual partner. SETTING Urology clinics at a university medical center and the affiliated Veterans Affairs (VA) Medical Center. PARTICIPANTS Thirty-five (67%) of 54 consecutive university patients presenting for erectile dysfunction and 22 (42%) of 52 VA patients who were awaiting a previously prescribed vacuum erection device participated. MAIN RESULTS The university respondents scored slightly lower than population normals in social function, role limitations due to emotional problems, and emotional well-being. The VA respondents scored lower than expected in all eight domains. Scores for the VA population were significantly lower than those for the university population in physical function, role limitations due to physical problems, bodily pain, and social function. A significant correlation was seen between marital interaction and sexual function (r = −.33, p = .01) but not between marital interaction and sexual bother (r = −.15, p = .26) in the total sample. Sexual function also correlated significantly with general health perceptions (r = .34, p = .01), role limitations due to physical problems (r = .29, p = .03), and role limitations due to emotional problems (r = .30, p = .03). Sexual bother did not correlate with any of the general HRQOL domains. Affluent men reported better sexual function (p = .03). CONCLUSIONS The emotional domains of the SF-36 are associated with more profound impairment than are the physical domains in men with erectile dysfunction. Erectile dysfunction and the bother it causes are discrete domains of HRQOL and distinct from each other in these patients. With increased attention to patient-centered medical outcomes, greater emphasis has been placed on such variables as HRQOL. This should be particularly true for a patient-driven symptom, such as erectile dysfunction. PMID:9541372
NASA Astrophysics Data System (ADS)
Ward, A. J.; Pendry, J. B.
2000-06-01
In this paper we present an updated version of our ONYX program for calculating photonic band structures using a non-orthogonal finite difference time domain method. This new version employs the same transparent formalism as the first version with the same capabilities for calculating photonic band structures or causal Green's functions but also includes extra subroutines for the calculation of transmission and reflection coefficients. Both the electric and magnetic fields are placed onto a discrete lattice by approximating the spacial and temporal derivatives with finite differences. This results in discrete versions of Maxwell's equations which can be used to integrate the fields forwards in time. The time required for a calculation using this method scales linearly with the number of real space points used in the discretization so the technique is ideally suited to handling systems with large and complicated unit cells.
The Knowledge Program: an Innovative, Comprehensive Electronic Data Capture System and Warehouse
Katzan, Irene; Speck, Micheal; Dopler, Chris; Urchek, John; Bielawski, Kay; Dunphy, Cheryl; Jehi, Lara; Bae, Charles; Parchman, Alandra
2011-01-01
Data contained in the electronic health record (EHR) present a tremendous opportunity to improve quality-of-care and enhance research capabilities. However, the EHR is not structured to provide data for such purposes: most clinical information is entered as free text and content varies substantially between providers. Discrete information on patients’ functional status is typically not collected. Data extraction tools are often unavailable. We have developed the Knowledge Program (KP), a comprehensive initiative to improve the collection of discrete clinical information into the EHR and the retrievability of data for use in research, quality, and patient care. A distinct feature of the KP is the systematic collection of patient-reported outcomes, which is captured discretely, allowing more refined analyses of care outcomes. The KP capitalizes on features of the Epic EHR and utilizes an external IT infrastructure distinct from Epic for enhanced functionality. Here, we describe the development and implementation of the KP. PMID:22195124
Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors.
Wei, Qinglai; Li, Benkai; Song, Ruizhuo
2018-04-01
In this paper, a generalized policy iteration (GPI) algorithm with approximation errors is developed for solving infinite horizon optimal control problems for nonlinear systems. The developed stable GPI algorithm provides a general structure of discrete-time iterative adaptive dynamic programming algorithms, by which most of the discrete-time reinforcement learning algorithms can be described using the GPI structure. It is for the first time that approximation errors are explicitly considered in the GPI algorithm. The properties of the stable GPI algorithm with approximation errors are analyzed. The admissibility of the approximate iterative control law can be guaranteed if the approximation errors satisfy the admissibility criteria. The convergence of the developed algorithm is established, which shows that the iterative value function is convergent to a finite neighborhood of the optimal performance index function, if the approximate errors satisfy the convergence criterion. Finally, numerical examples and comparisons are presented.
Effect of angle of deposition on the Fractal properties of ZnO thin film surface
NASA Astrophysics Data System (ADS)
Yadav, R. P.; Agarwal, D. C.; Kumar, Manvendra; Rajput, Parasmani; Tomar, D. S.; Pandey, S. N.; Priya, P. K.; Mittal, A. K.
2017-09-01
Zinc oxide (ZnO) thin films were prepared by atom beam sputtering at various deposition angles in the range of 20-75°. The deposited thin films were examined by glancing angle X-ray diffraction and atomic force microscopy (AFM). Scaling law analysis was performed on AFM images to show that the thin film surfaces are self-affine. Fractal dimension of each of the 256 vertical sections along the fast scan direction of a discretized surface, obtained from the AFM height data, was estimated using the Higuchi's algorithm. Hurst exponent was computed from the fractal dimension. The grain sizes, as determined by applying self-correlation function on AFM micrographs, varied with the deposition angle in the same manner as the Hurst exponent.
A statistical analysis of the elastic distortion and dislocation density fields in deformed crystals
Mohamed, Mamdouh S.; Larson, Bennett C.; Tischler, Jonathan Z.; ...
2015-05-18
The statistical properties of the elastic distortion fields of dislocations in deforming crystals are investigated using the method of discrete dislocation dynamics to simulate dislocation structures and dislocation density evolution under tensile loading. Probability distribution functions (PDF) and pair correlation functions (PCF) of the simulated internal elastic strains and lattice rotations are generated for tensile strain levels up to 0.85%. The PDFs of simulated lattice rotation are compared with sub-micrometer resolution three-dimensional X-ray microscopy measurements of rotation magnitudes and deformation length scales in 1.0% and 2.3% compression strained Cu single crystals to explore the linkage between experiment and the theoreticalmore » analysis. The statistical properties of the deformation simulations are analyzed through determinations of the Nye and Kr ner dislocation density tensors. The significance of the magnitudes and the length scales of the elastic strain and the rotation parts of dislocation density tensors are demonstrated, and their relevance to understanding the fundamental aspects of deformation is discussed.« less
Microglial brain region-dependent diversity and selective regional sensitivities to ageing
Grabert, Kathleen; Michoel, Tom; Karavolos, Michail H; Clohisey, Sara; Baillie, J Kenneth; Stevens, Mark P; Freeman, Tom C; Summers, Kim M; McColl, Barry W
2015-01-01
Microglia play critical roles in neural development, homeostasis and neuroinflammation and are increasingly implicated in age-related neurological dysfunction. Neurodegeneration often occurs in disease-specific spatially-restricted patterns, the origins of which are unknown. We performed the first genome-wide analysis of microglia from discrete brain regions across the adult lifespan of the mouse and reveal that microglia have distinct region-dependent transcriptional identities and age in a regionally variable manner. In the young adult brain, differences in bioenergetic and immunoregulatory pathways were the major sources of heterogeneity and suggested that cerebellar and hippocampal microglia exist in a more immune vigilant state. Immune function correlated with regional transcriptional patterns. Augmentation of the distinct cerebellar immunophenotype and a contrasting loss in distinction of the hippocampal phenotype among forebrain regions were key features during ageing. Microglial diversity may enable regionally localised homeostatic functions but could also underlie region-specific sensitivities to microglial dysregulation and involvement in age-related neurodegeneration. PMID:26780511
Network structure of brain atrophy in de novo Parkinson's disease
Zeighami, Yashar; Ulla, Miguel; Iturria-Medina, Yasser; Dadar, Mahsa; Zhang, Yu; Larcher, Kevin Michel-Herve; Fonov, Vladimir; Evans, Alan C; Collins, D Louis; Dagher, Alain
2015-01-01
We mapped the distribution of atrophy in Parkinson's disease (PD) using magnetic resonance imaging (MRI) and clinical data from 232 PD patients and 117 controls from the Parkinson's Progression Markers Initiative. Deformation-based morphometry and independent component analysis identified PD-specific atrophy in the midbrain, basal ganglia, basal forebrain, medial temporal lobe, and discrete cortical regions. The degree of atrophy reflected clinical measures of disease severity. The spatial pattern of atrophy demonstrated overlap with intrinsic networks present in healthy brain, as derived from functional MRI. Moreover, the degree of atrophy in each brain region reflected its functional and anatomical proximity to a presumed disease epicenter in the substantia nigra, compatible with a trans-neuronal spread of the disease. These results support a network-spread mechanism in PD. Finally, the atrophy pattern in PD was also seen in healthy aging, where it also correlated with the loss of striatal dopaminergic innervation. DOI: http://dx.doi.org/10.7554/eLife.08440.001 PMID:26344547
NASA Technical Reports Server (NTRS)
Vandermeulen, Ryan A.; Mannino, Antonio; Neeley, Aimee; Werdell, Jeremy; Arnone, Robert
2017-01-01
Using a modified geostatistical technique, empirical variograms were constructed from the first derivative of several diverse remote sensing reflectance and phytoplankton absorbance spectra to describe how data points are correlated with distance across the spectra. The maximum rate of information gain is measured as a function of the kurtosis associated with the Gaussian structure of the output, and is determined for discrete segments of spectra obtained from a variety of water types (turbid river filaments, coastal waters, shelf waters, a dense Microcystis bloom, and oligotrophic waters), as well as individual and mixed phytoplankton functional types (PFTs; diatoms, chlorophytes, cyanobacteria, coccolithophores). Results show that a continuous spectrum of 5 to 7 nm spectral resolution is optimal to resolve the variability across mixed reflectance and absorbance spectra. In addition, the impact of uncertainty on subsequent derivative analysis is assessed, showing that a limit of 3 Gaussian noise (SNR 66) is tolerated without smoothing the spectrum, and 13 (SNR 15) noise is tolerated with smoothing.
Lagrangian approach to the Barrett-Crane spin foam model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bonzom, Valentin; Laboratoire de Physique, ENS Lyon, CNRS UMR 5672, 46 Allee d'Italie, 69007 Lyon; Livine, Etera R.
2009-03-15
We provide the Barrett-Crane spin foam model for quantum gravity with a discrete action principle, consisting in the usual BF term with discretized simplicity constraints which in the continuum turn topological BF theory into gravity. The setting is the same as usually considered in the literature: space-time is cut into 4-simplices, the connection describes how to glue these 4-simplices together and the action is a sum of terms depending on the holonomies around each triangle. We impose the discretized simplicity constraints on disjoint tetrahedra and we show how the Lagrange multipliers distort the parallel transport and the correlations between neighboringmore » simplices. We then construct the discretized BF action using a noncommutative * product between SU(2) plane waves. We show how this naturally leads to the Barrett-Crane model. This clears up the geometrical meaning of the model. We discuss the natural generalization of this action principle and the spin foam models it leads to. We show how the recently introduced spin foam fusion coefficients emerge with a nontrivial measure. In particular, we recover the Engle-Pereira-Rovelli spin foam model by weakening the discretized simplicity constraints. Finally, we identify the two sectors of Plebanski's theory and we give the analog of the Barrett-Crane model in the nongeometric sector.« less
Controlling the Shannon Entropy of Quantum Systems
Xing, Yifan; Wu, Jun
2013-01-01
This paper proposes a new quantum control method which controls the Shannon entropy of quantum systems. For both discrete and continuous entropies, controller design methods are proposed based on probability density function control, which can drive the quantum state to any target state. To drive the entropy to any target at any prespecified time, another discretization method is proposed for the discrete entropy case, and the conditions under which the entropy can be increased or decreased are discussed. Simulations are done on both two- and three-dimensional quantum systems, where division and prediction are used to achieve more accurate tracking. PMID:23818819
The Investigation of Optimal Discrete Approximations for Real Time Flight Simulations
NASA Technical Reports Server (NTRS)
Parrish, E. A.; Mcvey, E. S.; Cook, G.; Henderson, K. C.
1976-01-01
The results are presented of an investigation of discrete approximations for real time flight simulation. Major topics discussed include: (1) consideration of the particular problem of approximation of continuous autopilots by digital autopilots; (2) use of Bode plots and synthesis of transfer functions by asymptotic fits in a warped frequency domain; (3) an investigation of the various substitution formulas, including the effects of nonlinearities; (4) use of pade approximation to the solution of the matrix exponential arising from the discrete state equations; and (5) an analytical integration of the state equation using interpolated input.
Controlling the shannon entropy of quantum systems.
Xing, Yifan; Wu, Jun
2013-01-01
This paper proposes a new quantum control method which controls the Shannon entropy of quantum systems. For both discrete and continuous entropies, controller design methods are proposed based on probability density function control, which can drive the quantum state to any target state. To drive the entropy to any target at any prespecified time, another discretization method is proposed for the discrete entropy case, and the conditions under which the entropy can be increased or decreased are discussed. Simulations are done on both two- and three-dimensional quantum systems, where division and prediction are used to achieve more accurate tracking.
Longo, Julie M; Sanford, Maria J; Coates, Geoffrey W
2016-12-28
Polyesters synthesized through the alternating copolymerization of epoxides and cyclic anhydrides compose a growing class of polymers that exhibit an impressive array of chemical and physical properties. Because they are synthesized through the chain-growth polymerization of two variable monomers, their syntheses can be controlled by discrete metal complexes, and the resulting materials vary widely in their functionality and physical properties. This polymer-focused review gives a perspective on the current state of the field of epoxide/anhydride copolymerization mediated by discrete catalysts and the relationships between the structures and properties of these polyesters.
Fronts in extended systems of bistable maps coupled via convolutions
NASA Astrophysics Data System (ADS)
Coutinho, Ricardo; Fernandez, Bastien
2004-01-01
An analysis of front dynamics in discrete time and spatially extended systems with general bistable nonlinearity is presented. The spatial coupling is given by the convolution with distribution functions. It allows us to treat in a unified way discrete, continuous or partly discrete and partly continuous diffusive interactions. We prove the existence of fronts and the uniqueness of their velocity. We also prove that the front velocity depends continuously on the parameters of the system. Finally, we show that every initial configuration that is an interface between the stable phases propagates asymptotically with the front velocity.
NASA Astrophysics Data System (ADS)
Fadakar Alghalandis, Younes
2017-05-01
Rapidly growing topic, the discrete fracture network engineering (DFNE), has already attracted many talents from diverse disciplines in academia and industry around the world to challenge difficult problems related to mining, geothermal, civil, oil and gas, water and many other projects. Although, there are few commercial software capable of providing some useful functionalities fundamental for DFNE, their costs, closed code (black box) distributions and hence limited programmability and tractability encouraged us to respond to this rising demand with a new solution. This paper introduces an open source comprehensive software package for stochastic modeling of fracture networks in two- and three-dimension in discrete formulation. Functionalities included are geometric modeling (e.g., complex polygonal fracture faces, and utilizing directional statistics), simulations, characterizations (e.g., intersection, clustering and connectivity analyses) and applications (e.g., fluid flow). The package is completely written in Matlab scripting language. Significant efforts have been made to bring maximum flexibility to the functions in order to solve problems in both two- and three-dimensions in an easy and united way that is suitable for beginners, advanced and experienced users.
Digital fabrication of multi-material biomedical objects.
Cheung, H H; Choi, S H
2009-12-01
This paper describes a multi-material virtual prototyping (MMVP) system for modelling and digital fabrication of discrete and functionally graded multi-material objects for biomedical applications. The MMVP system consists of a DMMVP module, an FGMVP module and a virtual reality (VR) simulation module. The DMMVP module is used to model discrete multi-material (DMM) objects, while the FGMVP module is for functionally graded multi-material (FGM) objects. The VR simulation module integrates these two modules to perform digital fabrication of multi-material objects, which can be subsequently visualized and analysed in a virtual environment to optimize MMLM processes for fabrication of product prototypes. Using the MMVP system, two biomedical objects, including a DMM human spine and an FGM intervertebral disc spacer are modelled and digitally fabricated for visualization and analysis in a VR environment. These studies show that the MMVP system is a practical tool for modelling, visualization, and subsequent fabrication of biomedical objects of discrete and functionally graded multi-materials for biomedical applications. The system may be adapted to control MMLM machines with appropriate hardware for physical fabrication of biomedical objects.
Efficiency optimization of a fast Poisson solver in beam dynamics simulation
NASA Astrophysics Data System (ADS)
Zheng, Dawei; Pöplau, Gisela; van Rienen, Ursula
2016-01-01
Calculating the solution of Poisson's equation relating to space charge force is still the major time consumption in beam dynamics simulations and calls for further improvement. In this paper, we summarize a classical fast Poisson solver in beam dynamics simulations: the integrated Green's function method. We introduce three optimization steps of the classical Poisson solver routine: using the reduced integrated Green's function instead of the integrated Green's function; using the discrete cosine transform instead of discrete Fourier transform for the Green's function; using a novel fast convolution routine instead of an explicitly zero-padded convolution. The new Poisson solver routine preserves the advantages of fast computation and high accuracy. This provides a fast routine for high performance calculation of the space charge effect in accelerators.
Nonperturbative β function of eight-flavor SU(3) gauge theory
NASA Astrophysics Data System (ADS)
Hasenfratz, Anna; Schaich, David; Veernala, Aarti
2015-06-01
We present a new lattice study of the discrete β function for SU(3) gauge theory with N f = 8 massless flavors of fermions in the fundamental representation. Using the gradient flow running coupling, and comparing two different nHYP-smeared staggered lattice actions, we calculate the 8-flavor step-scaling function at significantly stronger couplings than were previously accessible. Our continuum-extrapolated results for the discrete β function show no sign of an IR fixed point up to couplings of g 2 ≈ 14. At the same time, we find that the gradient flow coupling runs much more slowly than predicted by two-loop perturbation theory, reinforcing previous indications that the 8-flavor system possesses nontrivial strongly coupled IR dynamics with relevance to BSM phenomenology.
Olson, Sheryl L.; Sameroff, Arnold J.; Lansford, Jennifer E.; Sexton, Holly; Davis-Kean, Pamela; Bates, John E.; Pettit, Gregory S.; Dodge, Kenneth A.
2013-01-01
The purpose of this study was to determine whether five subcomponents of children's externalizing behavior showed distinctive patterns of long-term growth and predictive correlates. We examined growth in teachers' ratings of overt aggression, covert aggression, oppositional defiance, impulsivity/inattention, and emotion dysregulation across three developmental periods spanning kindergarten through Grade 8 (ages 5–13 years). We also determined whether three salient background characteristics, family socioeconomic status, child ethnicity, and child gender, differentially predicted growth in discrete categories of child externalizing symptoms across development. Participants were 543 kindergarten-age children (52% male, 81% European American, 17% African American) whose problem behaviors were rated by teachers each successive year of development through Grade 8. Latent growth curve analyses were performed for each component scale, contrasting with overall externalizing, in a piecewise fashion encompassing three developmental periods: kindergarten–Grade 2, Grades 3–5, and Grades 6–8. We found that most subconstructs of externalizing behavior increased significantly across the early school age period relative to middle childhood and early adolescence. However, overt aggression did not show early positive growth, and emotion dysregulation significantly increased across middle childhood. Advantages of using subscales were most clear in relation to illustrating different growth functions between the discrete developmental periods. Moreover, growth in some discrete subcomponents was differentially associated with variations in family socioeconomic status and ethnicity. Our findings strongly affirmed the necessity of adopting a developmental approach to the analysis of growth in children's externalizing behavior and provided unique data concerning similarities and differences in growth between subconstructs of child and adolescent externalizing behavior. PMID:23880394
Roles of Engineering Correlations in Hypersonic Entry Boundary Layer Transition Prediction
NASA Technical Reports Server (NTRS)
Campbell, Charles H.; King, Rudolph A.; Kergerise, Michael A.; Berry, Scott A.; Horvath, Thomas J.
2010-01-01
Efforts to design and operate hypersonic entry vehicles are constrained by many considerations that involve all aspects of an entry vehicle system. One of the more significant physical phenomenon that affect entry trajectory and thermal protection system design is the occurrence of boundary layer transition from a laminar to turbulent state. During the Space Shuttle Return To Flight activity following the loss of Columbia and her crew of seven, NASA's entry aerothermodynamics community implemented an engineering correlation based framework for the prediction of boundary layer transition on the Orbiter. The methodology for this implementation relies upon the framework of correlation techniques that have been in use for several decades. What makes the Orbiter boundary layer transition correlation implementation unique is that a statistically significant data set was acquired in multiple ground test facilities, flight data exists to assist in establishing a better correlation and the framework was founded upon state of the art chemical nonequilibrium Navier Stokes flow field simulations. The basic tenets that guided the formulation and implementation of the Orbiter Return To Flight boundary layer transition prediction capability will be reviewed as a recommended format for future empirical correlation efforts. The validity of this approach has since been demonstrated by very favorable comparison of recent entry flight testing performed with the Orbiter Discovery, which will be graphically summarized. These flight data can provide a means to validate discrete protuberance engineering correlation approaches as well as high fidelity prediction methods to higher confidence. The results of these Orbiter engineering and flight test activities only serve to reinforce the essential role that engineering correlations currently exercise in the design and operation of entry vehicles. The framework of information-related to the Orbiter empirical boundary layer transition prediction capability will be utilized to establish a fresh perspective on this role, to illustrate how quantitative statistical evaluations of empirical correlations can and should be used to assess accuracy and to discuss what the authors' perceive as a recent heightened interest in the application of high fidelity numerical modeling of boundary layer transition. Concrete results will also be developed related to empirical boundary layer transition onset correlations. This will include assessment of the discrete protuberance boundary layer transition onset data assembled for the Orbiter configuration during post-Columbia Return To Flight. Assessment of these data will conclude that momentum thickness Reynolds number based correlations have superior coefficients and uncertainty in comparison to roughness height based Reynolds numbers, aka Re(sub k) or Re(sub kk). In addition, linear regression results from roughness height Reynolds number based correlations will be evaluated, leading to a hypothesis that non-continuum effects play a role in the processes associated with incipient boundary layer transition on discrete protuberances.
Tracking quasi-stationary flow of weak fluorescent signals by adaptive multi-frame correlation.
Ji, L; Danuser, G
2005-12-01
We have developed a novel cross-correlation technique to probe quasi-stationary flow of fluorescent signals in live cells at a spatial resolution that is close to single particle tracking. By correlating image blocks between pairs of consecutive frames and integrating their correlation scores over multiple frame pairs, uncertainty in identifying a globally significant maximum in the correlation score function has been greatly reduced as compared with conventional correlation-based tracking using the signal of only two consecutive frames. This approach proves robust and very effective in analysing images with a weak, noise-perturbed signal contrast where texture characteristics cannot be matched between only a pair of frames. It can also be applied to images that lack prominent features that could be utilized for particle tracking or feature-based template matching. Furthermore, owing to the integration of correlation scores over multiple frames, the method can handle signals with substantial frame-to-frame intensity variation where conventional correlation-based tracking fails. We tested the performance of the method by tracking polymer flow in actin and microtubule cytoskeleton structures labelled at various fluorophore densities providing imagery with a broad range of signal modulation and noise. In applications to fluorescent speckle microscopy (FSM), where the fluorophore density is sufficiently low to reveal patterns of discrete fluorescent marks referred to as speckles, we combined the multi-frame correlation approach proposed above with particle tracking. This hybrid approach allowed us to follow single speckles robustly in areas of high speckle density and fast flow, where previously published FSM analysis methods were unsuccessful. Thus, we can now probe cytoskeleton polymer dynamics in living cells at an entirely new level of complexity and with unprecedented detail.
Measurement of Entropy of a Multiparticle System: a ``Do-List''
NASA Astrophysics Data System (ADS)
Bialas, A.; Czyz, W.
2000-03-01
An algorithm for measurement of entropy in multiparticle systems, based on the recently published proposal of the present authors is given. Dependence on discretization of the system and effects of multiparticle correlations are discussed in some detail.
Electromagnetic radiation screening of microcircuits for long life applications
NASA Technical Reports Server (NTRS)
Brammer, W. G.; Erickson, J. J.; Levy, M. E.
1974-01-01
The utility of X-rays as a stimulus for screening high reliability semiconductor microcircuits was studied. The theory of the interaction of X-rays with semiconductor materials and devices was considered. Experimental measurements of photovoltages, photocurrents, and effects on specified parameters were made on discrete devices and on microcircuits. The test specimens included discrete devices with certain types of identified flaws and symptoms of flaws, and microcircuits exhibiting deviant electrical behavior. With a necessarily limited sample of test specimens, no useful correlation could be found between the X-ray-induced electrical response and the known or suspected presence of flaws.
A discrete mathematical model for the aggregation of β-Amyloid.
Dayeh, Maher A; Livadiotis, George; Elaydi, Saber
2018-01-01
Dementia associated with the Alzheimer's disease is thought to be correlated with the conversion of the β - Amyloid (Aβ) peptides from soluble monomers to aggregated oligomers and insoluble fibrils. We present a discrete-time mathematical model for the aggregation of Aβ monomers into oligomers using concepts from chemical kinetics and population dynamics. Conditions for the stability and instability of the equilibria of the model are established. A formula for the number of monomers that is required for producing oligomers is also given. This may provide compound designers a mechanism to inhibit the Aβ aggregation.
Modelling discrete choice variables in assessment of teaching staff work satisfaction.
Mieilă, Mihai; Popescu, Constanţa; Tudorache, Ana-Maria; Toplicianu, Valerică
2015-01-01
Levels of self-reported job satisfaction and motivation were measured by survey in a sample of 286 teachers. Using the discrete choice framework, the paper tries to assess the relevance of the considered indicators (demographic, social, motivational) in overall teaching work satisfaction. The findings provide evidence that job satisfaction is correlated significantly with level of university degree held by the teacher, type of secondary school where the teacher is enrolled, revenues, and salary-tasks adequacy. This is important for the Romanian economy, since the education system is expected to provide future human resources with enhanced skills and abilities.
Modelling Discrete Choice Variables in Assessment of Teaching Staff Work Satisfaction
2015-01-01
Levels of self-reported job satisfaction and motivation were measured by survey in a sample of 286 teachers. Using the discrete choice framework, the paper tries to assess the relevance of the considered indicators (demographic, social, motivational) in overall teaching work satisfaction. The findings provide evidence that job satisfaction is correlated significantly with level of university degree held by the teacher, type of secondary school where the teacher is enrolled, revenues, and salary-tasks adequacy. This is important for the Romanian economy, since the education system is expected to provide future human resources with enhanced skills and abilities. PMID:25849295
A description of discrete internal representation schemes for visual pattern discrimination.
Foster, D H
1980-01-01
A general description of a class of schemes for pattern vision is outlined in which the visual system is assumed to form a discrete internal representation of the stimulus. These representations are discrete in that they are considered to comprise finite combinations of "components" which are selected from a fixed and finite repertoire, and which designate certain simple pattern properties or features. In the proposed description it is supposed that the construction of an internal representation is a probabilistic process. A relationship is then formulated associating the probability density functions governing this construction and performance in visually discriminating patterns when differences in pattern shape are small. Some questions related to the application of this relationship to the experimental investigation of discrete internal representations are briefly discussed.
High-order solution methods for grey discrete ordinates thermal radiative transfer
DOE Office of Scientific and Technical Information (OSTI.GOV)
Maginot, Peter G., E-mail: maginot1@llnl.gov; Ragusa, Jean C., E-mail: jean.ragusa@tamu.edu; Morel, Jim E., E-mail: morel@tamu.edu
This work presents a solution methodology for solving the grey radiative transfer equations that is both spatially and temporally more accurate than the canonical radiative transfer solution technique of linear discontinuous finite element discretization in space with implicit Euler integration in time. We solve the grey radiative transfer equations by fully converging the nonlinear temperature dependence of the material specific heat, material opacities, and Planck function. The grey radiative transfer equations are discretized in space using arbitrary-order self-lumping discontinuous finite elements and integrated in time with arbitrary-order diagonally implicit Runge–Kutta time integration techniques. Iterative convergence of the radiation equation ismore » accelerated using a modified interior penalty diffusion operator to precondition the full discrete ordinates transport operator.« less
High-order solution methods for grey discrete ordinates thermal radiative transfer
DOE Office of Scientific and Technical Information (OSTI.GOV)
Maginot, Peter G.; Ragusa, Jean C.; Morel, Jim E.
This paper presents a solution methodology for solving the grey radiative transfer equations that is both spatially and temporally more accurate than the canonical radiative transfer solution technique of linear discontinuous finite element discretization in space with implicit Euler integration in time. We solve the grey radiative transfer equations by fully converging the nonlinear temperature dependence of the material specific heat, material opacities, and Planck function. The grey radiative transfer equations are discretized in space using arbitrary-order self-lumping discontinuous finite elements and integrated in time with arbitrary-order diagonally implicit Runge–Kutta time integration techniques. Iterative convergence of the radiation equation ismore » accelerated using a modified interior penalty diffusion operator to precondition the full discrete ordinates transport operator.« less
High-order solution methods for grey discrete ordinates thermal radiative transfer
Maginot, Peter G.; Ragusa, Jean C.; Morel, Jim E.
2016-09-29
This paper presents a solution methodology for solving the grey radiative transfer equations that is both spatially and temporally more accurate than the canonical radiative transfer solution technique of linear discontinuous finite element discretization in space with implicit Euler integration in time. We solve the grey radiative transfer equations by fully converging the nonlinear temperature dependence of the material specific heat, material opacities, and Planck function. The grey radiative transfer equations are discretized in space using arbitrary-order self-lumping discontinuous finite elements and integrated in time with arbitrary-order diagonally implicit Runge–Kutta time integration techniques. Iterative convergence of the radiation equation ismore » accelerated using a modified interior penalty diffusion operator to precondition the full discrete ordinates transport operator.« less
NASA Astrophysics Data System (ADS)
Chodera, John D.; Noé, Frank
2010-09-01
Discrete-state Markov (or master equation) models provide a useful simplified representation for characterizing the long-time statistical evolution of biomolecules in a manner that allows direct comparison with experiments as well as the elucidation of mechanistic pathways for an inherently stochastic process. A vital part of meaningful comparison with experiment is the characterization of the statistical uncertainty in the predicted experimental measurement, which may take the form of an equilibrium measurement of some spectroscopic signal, the time-evolution of this signal following a perturbation, or the observation of some statistic (such as the correlation function) of the equilibrium dynamics of a single molecule. Without meaningful error bars (which arise from both approximation and statistical error), there is no way to determine whether the deviations between model and experiment are statistically meaningful. Previous work has demonstrated that a Bayesian method that enforces microscopic reversibility can be used to characterize the statistical component of correlated uncertainties in state-to-state transition probabilities (and functions thereof) for a model inferred from molecular simulation data. Here, we extend this approach to include the uncertainty in observables that are functions of molecular conformation (such as surrogate spectroscopic signals) characterizing each state, permitting the full statistical uncertainty in computed spectroscopic experiments to be assessed. We test the approach in a simple model system to demonstrate that the computed uncertainties provide a useful indicator of statistical variation, and then apply it to the computation of the fluorescence autocorrelation function measured for a dye-labeled peptide previously studied by both experiment and simulation.
Systems approach provides management control of complex programs
NASA Technical Reports Server (NTRS)
Dudek, E. F., Jr.; Mc Carthy, J. F., Jr.
1970-01-01
Integrated program management process provides management visual assistance through three interrelated charts - system model that identifies each function to be performed, matrix that identifies personnel responsibilities for these functions, process chart that breaks down the functions into discrete tasks.
A homogenization-based quasi-discrete method for the fracture of heterogeneous materials
NASA Astrophysics Data System (ADS)
Berke, P. Z.; Peerlings, R. H. J.; Massart, T. J.; Geers, M. G. D.
2014-05-01
The understanding and the prediction of the failure behaviour of materials with pronounced microstructural effects is of crucial importance. This paper presents a novel computational methodology for the handling of fracture on the basis of the microscale behaviour. The basic principles presented here allow the incorporation of an adaptive discretization scheme of the structure as a function of the evolution of strain localization in the underlying microstructure. The proposed quasi-discrete methodology bridges two scales: the scale of the material microstructure, modelled with a continuum type description; and the structural scale, where a discrete description of the material is adopted. The damaging material at the structural scale is divided into unit volumes, called cells, which are represented as a discrete network of points. The scale transition is inspired by computational homogenization techniques; however it does not rely on classical averaging theorems. The structural discrete equilibrium problem is formulated in terms of the underlying fine scale computations. Particular boundary conditions are developed on the scale of the material microstructure to address damage localization problems. The performance of this quasi-discrete method with the enhanced boundary conditions is assessed using different computational test cases. The predictions of the quasi-discrete scheme agree well with reference solutions obtained through direct numerical simulations, both in terms of crack patterns and load versus displacement responses.
ERIC Educational Resources Information Center
Wilson, Yvette M.; Murphy, Mark
2009-01-01
There is no clear identification of the neurons involved in fear conditioning in the amygdala. To search for these neurons, we have used a genetic approach, the "fos-tau-lacZ" (FTL) mouse, to map functionally activated expression in neurons following contextual fear conditioning. We have identified a discrete population of neurons in the lateral…
NASA Astrophysics Data System (ADS)
Macías-Díaz, J. E.
2017-12-01
In this manuscript, we consider an initial-boundary-value problem governed by a (1 + 1)-dimensional hyperbolic partial differential equation with constant damping that generalizes many nonlinear wave equations from mathematical physics. The model considers the presence of a spatial Laplacian of fractional order which is defined in terms of Riesz fractional derivatives, as well as the inclusion of a generic continuously differentiable potential. It is known that the undamped regime has an associated positive energy functional, and we show here that it is preserved throughout time under suitable boundary conditions. To approximate the solutions of this model, we propose a finite-difference discretization based on fractional centered differences. Some discrete quantities are proposed in this work to estimate the energy functional, and we show that the numerical method is capable of conserving the discrete energy under the same boundary conditions for which the continuous model is conservative. Moreover, we establish suitable computational constraints under which the discrete energy of the system is positive. The method is consistent of second order, and is both stable and convergent. The numerical simulations shown here illustrate the most important features of our numerical methodology.
A toolbox for discrete modelling of cell signalling dynamics.
Paterson, Yasmin Z; Shorthouse, David; Pleijzier, Markus W; Piterman, Nir; Bendtsen, Claus; Hall, Benjamin A; Fisher, Jasmin
2018-06-18
In an age where the volume of data regarding biological systems exceeds our ability to analyse it, many researchers are looking towards systems biology and computational modelling to help unravel the complexities of gene and protein regulatory networks. In particular, the use of discrete modelling allows generation of signalling networks in the absence of full quantitative descriptions of systems, which are necessary for ordinary differential equation (ODE) models. In order to make such techniques more accessible to mainstream researchers, tools such as the BioModelAnalyzer (BMA) have been developed to provide a user-friendly graphical interface for discrete modelling of biological systems. Here we use the BMA to build a library of discrete target functions of known canonical molecular interactions, translated from ordinary differential equations (ODEs). We then show that these BMA target functions can be used to reconstruct complex networks, which can correctly predict many known genetic perturbations. This new library supports the accessibility ethos behind the creation of BMA, providing a toolbox for the construction of complex cell signalling models without the need for extensive experience in computer programming or mathematical modelling, and allows for construction and simulation of complex biological systems with only small amounts of quantitative data.
A discrete Fourier-encoded, diagonal-free experiment to simplify homonuclear 2D NMR correlations.
Huang, Zebin; Guan, Quanshuai; Chen, Zhong; Frydman, Lucio; Lin, Yulan
2017-07-21
Nuclear magnetic resonance (NMR) spectroscopy has long served as an irreplaceable, versatile tool in physics, chemistry, biology, and materials sciences, owing to its ability to study molecular structure and dynamics in detail. In particular, the connectivity of chemical sites within molecules, and thereby molecular structure, becomes visible by multi-dimensional NMR. Homonuclear correlation experiments are a powerful tool for identifying coupled spins. Generally, diagonal peaks in these correlation spectra display the strongest intensities and do not offer any new information beyond the standard one-dimensional spectrum, whereas weaker, symmetrically placed cross peaks contain most of the coupling information. The cross peaks near the diagonal are often affected by the tails of strong diagonal peaks or even obscured entirely by the diagonal. In this paper, we demonstrate a homonuclear encoding approach based on imparting a discrete phase modulation of the targeted cross peaks and combine it with a site-selective sculpting scheme, capable of simplifying the patterns arising in these 2D correlation spectra. The theoretical principles of the new methods are laid out, and experimental observations are rationalized on the basis of theoretical analyses. The ensuing techniques provide a new way to retrieve 2D coupling information within homonuclear spin systems, with enhanced sensitivity, speed, and clarity.
A discrete Fourier-encoded, diagonal-free experiment to simplify homonuclear 2D NMR correlations
NASA Astrophysics Data System (ADS)
Huang, Zebin; Guan, Quanshuai; Chen, Zhong; Frydman, Lucio; Lin, Yulan
2017-07-01
Nuclear magnetic resonance (NMR) spectroscopy has long served as an irreplaceable, versatile tool in physics, chemistry, biology, and materials sciences, owing to its ability to study molecular structure and dynamics in detail. In particular, the connectivity of chemical sites within molecules, and thereby molecular structure, becomes visible by multi-dimensional NMR. Homonuclear correlation experiments are a powerful tool for identifying coupled spins. Generally, diagonal peaks in these correlation spectra display the strongest intensities and do not offer any new information beyond the standard one-dimensional spectrum, whereas weaker, symmetrically placed cross peaks contain most of the coupling information. The cross peaks near the diagonal are often affected by the tails of strong diagonal peaks or even obscured entirely by the diagonal. In this paper, we demonstrate a homonuclear encoding approach based on imparting a discrete phase modulation of the targeted cross peaks and combine it with a site-selective sculpting scheme, capable of simplifying the patterns arising in these 2D correlation spectra. The theoretical principles of the new methods are laid out, and experimental observations are rationalized on the basis of theoretical analyses. The ensuing techniques provide a new way to retrieve 2D coupling information within homonuclear spin systems, with enhanced sensitivity, speed, and clarity.
Rational Ruijsenaars Schneider hierarchy and bispectral difference operators
NASA Astrophysics Data System (ADS)
Iliev, Plamen
2007-05-01
We show that a monic polynomial in a discrete variable n, with coefficients depending on time variables t1,t2,…, is a τ-function for the discrete Kadomtsev-Petviashvili hierarchy if and only if the motion of its zeros is governed by a hierarchy of Ruijsenaars-Schneider systems. These τ-functions were considered in [L. Haine, P. Iliev, Commutative rings of difference operators and an adelic flag manifold, Int. Math. Res. Not. 2000 (6) (2000) 281-323], where it was proved that they parametrize rank one solutions to a difference-differential version of the bispectral problem.
NASA Astrophysics Data System (ADS)
Zhang, Hai; Ye, Renyu; Liu, Song; Cao, Jinde; Alsaedi, Ahmad; Li, Xiaodi
2018-02-01
This paper is concerned with the asymptotic stability of the Riemann-Liouville fractional-order neural networks with discrete and distributed delays. By constructing a suitable Lyapunov functional, two sufficient conditions are derived to ensure that the addressed neural network is asymptotically stable. The presented stability criteria are described in terms of the linear matrix inequalities. The advantage of the proposed method is that one may avoid calculating the fractional-order derivative of the Lyapunov functional. Finally, a numerical example is given to show the validity and feasibility of the theoretical results.
Multi-Level Adaptive Techniques (MLAT) for singular-perturbation problems
NASA Technical Reports Server (NTRS)
Brandt, A.
1978-01-01
The multilevel (multigrid) adaptive technique, a general strategy of solving continuous problems by cycling between coarser and finer levels of discretization is described. It provides very fast general solvers, together with adaptive, nearly optimal discretization schemes. In the process, boundary layers are automatically either resolved or skipped, depending on a control function which expresses the computational goal. The global error decreases exponentially as a function of the overall computational work, in a uniform rate independent of the magnitude of the singular-perturbation terms. The key is high-order uniformly stable difference equations, and uniformly smoothing relaxation schemes.
Acosta-Mesa, Héctor-Gabriel; Rechy-Ramírez, Fernando; Mezura-Montes, Efrén; Cruz-Ramírez, Nicandro; Hernández Jiménez, Rodolfo
2014-06-01
In this work, we present a novel application of time series discretization using evolutionary programming for the classification of precancerous cervical lesions. The approach optimizes the number of intervals in which the length and amplitude of the time series should be compressed, preserving the important information for classification purposes. Using evolutionary programming, the search for a good discretization scheme is guided by a cost function which considers three criteria: the entropy regarding the classification, the complexity measured as the number of different strings needed to represent the complete data set, and the compression rate assessed as the length of the discrete representation. This discretization approach is evaluated using a time series data based on temporal patterns observed during a classical test used in cervical cancer detection; the classification accuracy reached by our method is compared with the well-known times series discretization algorithm SAX and the dimensionality reduction method PCA. Statistical analysis of the classification accuracy shows that the discrete representation is as efficient as the complete raw representation for the present application, reducing the dimensionality of the time series length by 97%. This representation is also very competitive in terms of classification accuracy when compared with similar approaches. Copyright © 2014 Elsevier Inc. All rights reserved.
Astrelin, A V; Sokolov, M V; Behnisch, T; Reymann, K G; Voronin, L L
1997-04-25
A statistical approach to analysis of amplitude fluctuations of postsynaptic responses is described. This includes (1) using a L1-metric in the space of distribution functions for minimisation with application of linear programming methods to decompose amplitude distributions into a convolution of Gaussian and discrete distributions; (2) deconvolution of the resulting discrete distribution with determination of the release probabilities and the quantal amplitude for cases with a small number (< 5) of discrete components. The methods were tested against simulated data over a range of sample sizes and signal-to-noise ratios which mimicked those observed in physiological experiments. In computer simulation experiments, comparisons were made with other methods of 'unconstrained' (generalized) and constrained reconstruction of discrete components from convolutions. The simulation results provided additional criteria for improving the solutions to overcome 'over-fitting phenomena' and to constrain the number of components with small probabilities. Application of the programme to recordings from hippocampal neurones demonstrated its usefulness for the analysis of amplitude distributions of postsynaptic responses.
NASA Astrophysics Data System (ADS)
Mousavi, Seyed Jamshid; Mahdizadeh, Kourosh; Afshar, Abbas
2004-08-01
Application of stochastic dynamic programming (SDP) models to reservoir optimization calls for state variables discretization. As an important variable discretization of reservoir storage volume has a pronounced effect on the computational efforts. The error caused by storage volume discretization is examined by considering it as a fuzzy state variable. In this approach, the point-to-point transitions between storage volumes at the beginning and end of each period are replaced by transitions between storage intervals. This is achieved by using fuzzy arithmetic operations with fuzzy numbers. In this approach, instead of aggregating single-valued crisp numbers, the membership functions of fuzzy numbers are combined. Running a simulated model with optimal release policies derived from fuzzy and non-fuzzy SDP models shows that a fuzzy SDP with a coarse discretization scheme performs as well as a classical SDP having much finer discretized space. It is believed that this advantage in the fuzzy SDP model is due to the smooth transitions between storage intervals which benefit from soft boundaries.
NASA Astrophysics Data System (ADS)
Aquilanti, Vincenzo; Marinelli, Dimitri; Marzuoli, Annalisa
2013-05-01
The action of the quantum mechanical volume operator, introduced in connection with a symmetric representation of the three-body problem and recently recognized to play a fundamental role in discretized quantum gravity models, can be given as a second-order difference equation which, by a complex phase change, we turn into a discrete Schrödinger-like equation. The introduction of discrete potential-like functions reveals the surprising crucial role here of hidden symmetries, first discovered by Regge for the quantum mechanical 6j symbols; insight is provided into the underlying geometric features. The spectrum and wavefunctions of the volume operator are discussed from the viewpoint of the Hamiltonian evolution of an elementary ‘quantum of space’, and a transparent asymptotic picture of the semiclassical and classical regimes emerges. The definition of coordinates adapted to the Regge symmetry is exploited for the construction of a novel set of discrete orthogonal polynomials, characterizing the oscillatory components of torsion-like modes.
Ran, Du; Hu, Chang-Sheng; Yang, Zhen-Biao
2016-01-01
We study the entanglement transfer from a two-mode continuous variable system (initially in the two-mode SU(2) cat states) to a couple of discrete two-state systems (initially in an arbitrary mixed state), by use of the resonant Jaynes-Cummings (JC) interaction. We first quantitatively connect the entanglement transfer to non-Gaussianity of the two-mode SU(2) cat states and find a positive correlation between them. We then investigate the behaviors of the entanglement transfer and find that it is dependent on the initial state of the discrete systems. We also find that the largest possible value of the transferred entanglement exhibits a variety of behaviors for different photon number as well as for the phase angle of the two-mode SU(2) cat states. We finally consider the influences of the noise on the transferred entanglement. PMID:27553881
Ewald Electrostatics for Mixtures of Point and Continuous Line Charges.
Antila, Hanne S; Tassel, Paul R Van; Sammalkorpi, Maria
2015-10-15
Many charged macro- or supramolecular systems, such as DNA, are approximately rod-shaped and, to the lowest order, may be treated as continuous line charges. However, the standard method used to calculate electrostatics in molecular simulation, the Ewald summation, is designed to treat systems of point charges. We extend the Ewald concept to a hybrid system containing both point charges and continuous line charges. We find the calculated force between a point charge and (i) a continuous line charge and (ii) a discrete line charge consisting of uniformly spaced point charges to be numerically equivalent when the separation greatly exceeds the discretization length. At shorter separations, discretization induces deviations in the force and energy, and point charge-point charge correlation effects. Because significant computational savings are also possible, the continuous line charge Ewald method presented here offers the possibility of accurate and efficient electrostatic calculations.
NASA Astrophysics Data System (ADS)
Hiesmayr, Beatrix C.
2015-07-01
About 50 years ago John St. Bell published his famous Bell theorem that initiated a new field in physics. This contribution discusses how discrete symmetries relate to the big open questions of quantum mechanics, in particular: (i) how correlations stronger than those predicted by theories sharing randomness (Bell's theorem) relate to the violation of the CP symmetry and the P symmetry; and its relation to the security of quantum cryptography, (ii) how the measurement problem (“why do we observe no tables in superposition?”) can be polled in weakly decaying systems, (iii) how strongly and weakly interacting quantum systems are affected by Newton's self gravitation. These presented preliminary results show that the meson-antimeson systems and the hyperon- antihyperon systems are a unique laboratory to tackle deep fundamental questions and to contribute to the understand what impact the violation of discrete symmetries has.
NASA Astrophysics Data System (ADS)
Soobiah, Y. I. J.; Espley, J. R.; Connerney, J. E. P.; Gruesbeck, J.; DiBraccio, G. A.; Schneider, N.; Jain, S.; Brain, D.; Andersson, L.; Halekas, J. S.; Lillis, R. J.; McFadden, J. P.; Mitchell, D. L.; Mazelle, C. X.; Deighan, J.; McClintock, W. E.; Ergun, R.; Jakosky, B. M.
2016-12-01
NASA's Mars Atmosphere and Volatile EvolutioN (MAVEN) spacecraft has observed a variety of aurora at Mars and related processes that impact the escape of the Martian atmosphere. So far MAVEN's Imaging Ultraviolet Spectrograph (IUVS) instrument has observed 1) Diffuse aurora over widespread regions of Mars' northern hemisphere; 2) Discrete aurora that is spatially confined to localized patches around regions of crustal magnetic field; and 3) Proton aurora from the limb brightening of Lyman-α emission. MAVEN's Solar Energetic Particle (SEP) instrument has shown the diffuse aurora to be coincident with outbursts of solar energetic particles and disturbed solar wind and magnetospheric conditions. MAVEN Particle and Fields Package (PFP) Solar Wind Ion Analyzer (SWIA) has shown the limb brightening of Lyman-α to correlate with increased upstream solar wind dynamic pressure as associated with increased penetrating protons. So far a conclusive explanation for the discrete aurora has yet to be determined. This study aims to explore the plasma processes related to discrete Martian aurora in greater detail by presenting an overview of PFP measurements during orbits when IUVS observed discrete aurora at Mars. Initial observations from orbit 1600 of MAVEN has shown the almost side-by-side occurrence of a crustal magnetic field associated current sheet measured by MAVEN's Magnetometer Investigation (MAG) near the Mars terminator and IUVS limb observations of discrete aurora in Mars shadow (similar co-latitudes but separated by nearly 1800 km across longitude). This study includes further analysis of magnetic field current sheets and the particle acceleration/energization to investigate the space plasma processes involved in discrete aurora at Mars.
Lisman, John
2005-01-01
In the hippocampus, oscillations in the theta and gamma frequency range occur together and interact in several ways, indicating that they are part of a common functional system. It is argued that these oscillations form a coding scheme that is used in the hippocampus to organize the readout from long-term memory of the discrete sequence of upcoming places, as cued by current position. This readout of place cells has been analyzed in several ways. First, plots of the theta phase of spikes vs. position on a track show a systematic progression of phase as rats run through a place field. This is termed the phase precession. Second, two cells with nearby place fields have a systematic difference in phase, as indicated by a cross-correlation having a peak with a temporal offset that is a significant fraction of a theta cycle. Third, several different decoding algorithms demonstrate the information content of theta phase in predicting the animal's position. It appears that small phase differences corresponding to jitter within a gamma cycle do not carry information. This evidence, together with the finding that principle cells fire preferentially at a given gamma phase, supports the concept of theta/gamma coding: a given place is encoded by the spatial pattern of neurons that fire in a given gamma cycle (the exact timing within a gamma cycle being unimportant); sequential places are encoded in sequential gamma subcycles of the theta cycle (i.e., with different discrete theta phase). It appears that this general form of coding is not restricted to readout of information from long-term memory in the hippocampus because similar patterns of theta/gamma oscillations have been observed in multiple brain regions, including regions involved in working memory and sensory integration. It is suggested that dual oscillations serve a general function: the encoding of multiple units of information (items) in a way that preserves their serial order. The relationship of such coding to that proposed by Singer and von der Malsburg is discussed; in their scheme, theta is not considered. It is argued that what theta provides is the absolute phase reference needed for encoding order. Theta/gamma coding therefore bears some relationship to the concept of "word" in digital computers, with word length corresponding to the number of gamma cycles within a theta cycle, and discrete phase corresponding to the ordered "place" within a word. Copyright 2005 Wiley-Liss, Inc.
NASA Astrophysics Data System (ADS)
Liland, Kristian Hovde; Snipen, Lars
When a series of Bernoulli trials occur within a fixed time frame or limited space, it is often interesting to assess if the successful outcomes have occurred completely at random, or if they tend to group together. One example, in genetics, is detecting grouping of genes within a genome. Approximations of the distribution of successes are possible, but they become inaccurate for small sample sizes. In this article, we describe the exact distribution of time between random, non-overlapping successes in discrete time of fixed length. A complete description of the probability mass function, the cumulative distribution function, mean, variance and recurrence relation is included. We propose an associated test for the over-representation of short distances and illustrate the methodology through relevant examples. The theory is implemented in an R package including probability mass, cumulative distribution, quantile function, random number generator, simulation functions, and functions for testing.
Optimal estimation for discrete time jump processes
NASA Technical Reports Server (NTRS)
Vaca, M. V.; Tretter, S. A.
1977-01-01
Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are obtained. The approach is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. A general representation for optimum estimates and recursive equations for minimum mean squared error (MMSE) estimates are obtained. MMSE estimates are nonlinear functions of the observations. The problem of estimating the rate of a DTJP when the rate is a random variable with a probability density function of the form cx super K (l-x) super m and show that the MMSE estimates are linear in this case. This class of density functions explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.
Optimal estimation for discrete time jump processes
NASA Technical Reports Server (NTRS)
Vaca, M. V.; Tretter, S. A.
1978-01-01
Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are derived. The approach used is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. Thus a general representation is obtained for optimum estimates, and recursive equations are derived for minimum mean-squared error (MMSE) estimates. In general, MMSE estimates are nonlinear functions of the observations. The problem is considered of estimating the rate of a DTJP when the rate is a random variable with a beta probability density function and the jump amplitudes are binomially distributed. It is shown that the MMSE estimates are linear. The class of beta density functions is rather rich and explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.
NASA Technical Reports Server (NTRS)
Dean, Bruce H. (Inventor); Smith, Jeffrey Scott (Inventor); Aronstein, David L. (Inventor)
2012-01-01
Disclosed herein are systems, methods, and non-transitory computer-readable storage media for simulating propagation of an electromagnetic field, performing phase retrieval, or sampling a band-limited function. A system practicing the method generates transformed data using a discrete Fourier transform which samples a band-limited function f(x) without interpolating or modifying received data associated with the function f(x), wherein an interval between repeated copies in a periodic extension of the function f(x) obtained from the discrete Fourier transform is associated with a sampling ratio Q, defined as a ratio of a sampling frequency to a band-limited frequency, and wherein Q is assigned a value between 1 and 2 such that substantially no aliasing occurs in the transformed data, and retrieves a phase in the received data based on the transformed data, wherein the phase is used as feedback to an optical system.
DOE Office of Scientific and Technical Information (OSTI.GOV)
McEneaney, William M.
2004-08-15
Stochastic games under imperfect information are typically computationally intractable even in the discrete-time/discrete-state case considered here. We consider a problem where one player has perfect information.A function of a conditional probability distribution is proposed as an information state.In the problem form here, the payoff is only a function of the terminal state of the system,and the initial information state is either linear ora sum of max-plus delta functions.When the initial information state belongs to these classes, its propagation is finite-dimensional.The state feedback value function is also finite-dimensional,and obtained via dynamic programming,but has a nonstandard form due to the necessity ofmore » an expanded state variable.Under a saddle point assumption,Certainty Equivalence is obtained and the proposed function is indeed an information state.« less
Weinmann, Andreas; Storath, Martin
2015-01-01
Signals with discontinuities appear in many problems in the applied sciences ranging from mechanics, electrical engineering to biology and medicine. The concrete data acquired are typically discrete, indirect and noisy measurements of some quantities describing the signal under consideration. The task is to restore the signal and, in particular, the discontinuities. In this respect, classical methods perform rather poor, whereas non-convex non-smooth variational methods seem to be the correct choice. Examples are methods based on Mumford–Shah and piecewise constant Mumford–Shah functionals and discretized versions which are known as Blake–Zisserman and Potts functionals. Owing to their non-convexity, minimization of such functionals is challenging. In this paper, we propose a new iterative minimization strategy for Blake–Zisserman as well as Potts functionals and a related jump-sparsity problem dealing with indirect, noisy measurements. We provide a convergence analysis and underpin our findings with numerical experiments. PMID:27547074
Moon, Clara; Stupp, Gregory S; Su, Andrew I; Wolan, Dennis W
2018-02-01
Metaproteomics can greatly assist established high-throughput sequencing methodologies to provide systems biological insights into the alterations of microbial protein functionalities correlated with disease-associated dysbiosis of the intestinal microbiota. Here, the authors utilize the well-characterized murine T cell transfer model of colitis to find specific changes within the intestinal luminal proteome associated with inflammation. MS proteomic analysis of colonic samples permitted the identification of ≈10 000-12 000 unique peptides that corresponded to 5610 protein clusters identified across three groups, including the colitic Rag1 -/- T cell recipients, isogenic Rag1 -/- controls, and wild-type mice. The authors demonstrate that the colitic mice exhibited a significant increase in Proteobacteria and Verrucomicrobia and show that such alterations in the microbial communities contributed to the enrichment of specific proteins with transcription and translation gene ontology terms. In combination with 16S sequencing, the authors' metaproteomics-based microbiome studies provide a foundation for assessing alterations in intestinal luminal protein functionalities in a robust and well-characterized mouse model of colitis, and set the stage for future studies to further explore the functional mechanisms of altered protein functionalities associated with dysbiosis and inflammation. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Biomolecular Assembly of Gold Nanocrystals
DOE Office of Scientific and Technical Information (OSTI.GOV)
Micheel, Christine Marya
2005-05-20
Over the past ten years, methods have been developed to construct discrete nanostructures using nanocrystals and biomolecules. While these frequently consist of gold nanocrystals and DNA, semiconductor nanocrystals as well as antibodies and enzymes have also been used. One example of discrete nanostructures is dimers of gold nanocrystals linked together with complementary DNA. This type of nanostructure is also known as a nanocrystal molecule. Discrete nanostructures of this kind have a number of potential applications, from highly parallel self-assembly of electronics components and rapid read-out of DNA computations to biological imaging and a variety of bioassays. My research focused inmore » three main areas. The first area, the refinement of electrophoresis as a purification and characterization method, included application of agarose gel electrophoresis to the purification of discrete gold nanocrystal/DNA conjugates and nanocrystal molecules, as well as development of a more detailed understanding of the hydrodynamic behavior of these materials in gels. The second area, the development of methods for quantitative analysis of transmission electron microscope data, used computer programs written to find pair correlations as well as higher order correlations. With these programs, it is possible to reliably locate and measure nanocrystal molecules in TEM images. The final area of research explored the use of DNA ligase in the formation of nanocrystal molecules. Synthesis of dimers of gold particles linked with a single strand of DNA possible through the use of DNA ligase opens the possibility for amplification of nanostructures in a manner similar to polymerase chain reaction. These three areas are discussed in the context of the work in the Alivisatos group, as well as the field as a whole.« less
Harju, Seth M.; Olson, Chad V.; Dzialak, Matthew R.; Mudd, James P.; Winstead, Jeff B.
2013-01-01
Connectivity of animal populations is an increasingly prominent concern in fragmented landscapes, yet existing methodological and conceptual approaches implicitly assume the presence of, or need for, discrete corridors. We tested this assumption by developing a flexible conceptual approach that does not assume, but allows for, the presence of discrete movement corridors. We quantified functional connectivity habitat for greater sage-grouse (Centrocercus urophasianus) across a large landscape in central western North America. We assigned sample locations to a movement state (encamped, traveling and relocating), and used Global Positioning System (GPS) location data and conditional logistic regression to estimate state-specific resource selection functions. Patterns of resource selection during different movement states reflected selection for sagebrush and general avoidance of rough topography and anthropogenic features. Distinct connectivity corridors were not common in the 5,625 km2 study area. Rather, broad areas functioned as generally high or low quality connectivity habitat. A comprehensive map predicting the quality of connectivity habitat across the study area validated well based on a set of GPS locations from independent greater sage-grouse. The functional relationship between greater sage-grouse and the landscape did not always conform to the idea of a discrete corridor. A more flexible consideration of landscape connectivity may improve the efficacy of management actions by aligning those actions with the spatial patterns by which animals interact with the landscape. PMID:24349241
Harju, Seth M; Olson, Chad V; Dzialak, Matthew R; Mudd, James P; Winstead, Jeff B
2013-01-01
Connectivity of animal populations is an increasingly prominent concern in fragmented landscapes, yet existing methodological and conceptual approaches implicitly assume the presence of, or need for, discrete corridors. We tested this assumption by developing a flexible conceptual approach that does not assume, but allows for, the presence of discrete movement corridors. We quantified functional connectivity habitat for greater sage-grouse (Centrocercus urophasianus) across a large landscape in central western North America. We assigned sample locations to a movement state (encamped, traveling and relocating), and used Global Positioning System (GPS) location data and conditional logistic regression to estimate state-specific resource selection functions. Patterns of resource selection during different movement states reflected selection for sagebrush and general avoidance of rough topography and anthropogenic features. Distinct connectivity corridors were not common in the 5,625 km(2) study area. Rather, broad areas functioned as generally high or low quality connectivity habitat. A comprehensive map predicting the quality of connectivity habitat across the study area validated well based on a set of GPS locations from independent greater sage-grouse. The functional relationship between greater sage-grouse and the landscape did not always conform to the idea of a discrete corridor. A more flexible consideration of landscape connectivity may improve the efficacy of management actions by aligning those actions with the spatial patterns by which animals interact with the landscape.
Wavepacket dynamics and the multi-configurational time-dependent Hartree approach
NASA Astrophysics Data System (ADS)
Manthe, Uwe
2017-06-01
Multi-configurational time-dependent Hartree (MCTDH) based approaches are efficient, accurate, and versatile methods for high-dimensional quantum dynamics simulations. Applications range from detailed investigations of polyatomic reaction processes in the gas phase to high-dimensional simulations studying the dynamics of condensed phase systems described by typical solid state physics model Hamiltonians. The present article presents an overview of the different areas of application and provides a comprehensive review of the underlying theory. The concepts and guiding ideas underlying the MCTDH approach and its multi-mode and multi-layer extensions are discussed in detail. The general structure of the equations of motion is highlighted. The representation of the Hamiltonian and the correlated discrete variable representation (CDVR), which provides an efficient multi-dimensional quadrature in MCTDH calculations, are discussed. Methods which facilitate the calculation of eigenstates, the evaluation of correlation functions, and the efficient representation of thermal ensembles in MCTDH calculations are described. Different schemes for the treatment of indistinguishable particles in MCTDH calculations and recent developments towards a unified multi-layer MCTDH theory for systems including bosons and fermions are discussed.
A Fast Optimization Method for General Binary Code Learning.
Shen, Fumin; Zhou, Xiang; Yang, Yang; Song, Jingkuan; Shen, Heng; Tao, Dacheng
2016-09-22
Hashing or binary code learning has been recognized to accomplish efficient near neighbor search, and has thus attracted broad interests in recent retrieval, vision and learning studies. One main challenge of learning to hash arises from the involvement of discrete variables in binary code optimization. While the widely-used continuous relaxation may achieve high learning efficiency, the pursued codes are typically less effective due to accumulated quantization error. In this work, we propose a novel binary code optimization method, dubbed Discrete Proximal Linearized Minimization (DPLM), which directly handles the discrete constraints during the learning process. Specifically, the discrete (thus nonsmooth nonconvex) problem is reformulated as minimizing the sum of a smooth loss term with a nonsmooth indicator function. The obtained problem is then efficiently solved by an iterative procedure with each iteration admitting an analytical discrete solution, which is thus shown to converge very fast. In addition, the proposed method supports a large family of empirical loss functions, which is particularly instantiated in this work by both a supervised and an unsupervised hashing losses, together with the bits uncorrelation and balance constraints. In particular, the proposed DPLM with a supervised `2 loss encodes the whole NUS-WIDE database into 64-bit binary codes within 10 seconds on a standard desktop computer. The proposed approach is extensively evaluated on several large-scale datasets and the generated binary codes are shown to achieve very promising results on both retrieval and classification tasks.
Gan, Zecheng; Xing, Xiangjun; Xu, Zhenli
2012-07-21
We investigate the effects of image charges, interfacial charge discreteness, and surface roughness on spherical electric double layer structures in electrolyte solutions with divalent counterions in the setting of the primitive model. By using Monte Carlo simulations and the image charge method, the zeta potential profile and the integrated charge distribution function are computed for varying surface charge strengths and salt concentrations. Systematic comparisons were carried out between three distinct models for interfacial charges: (1) SURF1 with uniform surface charges, (2) SURF2 with discrete point charges on the interface, and (3) SURF3 with discrete interfacial charges and finite excluded volume. By comparing the integrated charge distribution function and the zeta potential profile, we argue that the potential at the distance of one ion diameter from the macroion surface is a suitable location to define the zeta potential. In SURF2 model, we find that image charge effects strongly enhance charge inversion for monovalent interfacial charges, and strongly suppress charge inversion for multivalent interfacial charges. For SURF3, the image charge effect becomes much smaller. Finally, with image charges in action, we find that excluded volumes (in SURF3) suppress charge inversion for monovalent interfacial charges and enhance charge inversion for multivalent interfacial charges. Overall, our results demonstrate that all these aspects, i.e., image charges, interfacial charge discreteness, their excluding volumes, have significant impacts on zeta potentials of electric double layers.
Dimension-independent likelihood-informed MCMC
Cui, Tiangang; Law, Kody J. H.; Marzouk, Youssef M.
2015-10-08
Many Bayesian inference problems require exploring the posterior distribution of highdimensional parameters that represent the discretization of an underlying function. Our work introduces a family of Markov chain Monte Carlo (MCMC) samplers that can adapt to the particular structure of a posterior distribution over functions. There are two distinct lines of research that intersect in the methods we develop here. First, we introduce a general class of operator-weighted proposal distributions that are well defined on function space, such that the performance of the resulting MCMC samplers is independent of the discretization of the function. Second, by exploiting local Hessian informationmore » and any associated lowdimensional structure in the change from prior to posterior distributions, we develop an inhomogeneous discretization scheme for the Langevin stochastic differential equation that yields operator-weighted proposals adapted to the non-Gaussian structure of the posterior. The resulting dimension-independent and likelihood-informed (DILI) MCMC samplers may be useful for a large class of high-dimensional problems where the target probability measure has a density with respect to a Gaussian reference measure. Finally, we use two nonlinear inverse problems in order to demonstrate the efficiency of these DILI samplers: an elliptic PDE coefficient inverse problem and path reconstruction in a conditioned diffusion.« less
Adaptive Decision Making Using Probabilistic Programming and Stochastic Optimization
2018-01-01
world optimization problems (and hence 16 Approved for Public Release (PA); Distribution Unlimited Pred. demand (uncertain; discrete ...simplify the setting, we further assume that the demands are discrete , taking on values d1, . . . , dk with probabilities (conditional on x) (pθ)i ≡ p...Tyrrell Rockafellar. Implicit functions and solution mappings. Springer Monogr. Math ., 2009. Anthony V Fiacco and Yo Ishizuka. Sensitivity and stability
Codimension-Two Bifurcation, Chaos and Control in a Discrete-Time Information Diffusion Model
NASA Astrophysics Data System (ADS)
Ren, Jingli; Yu, Liping
2016-12-01
In this paper, we present a discrete model to illustrate how two pieces of information interact with online social networks and investigate the dynamics of discrete-time information diffusion model in three types: reverse type, intervention type and mutualistic type. It is found that the model has orbits with period 2, 4, 6, 8, 12, 16, 20, 30, quasiperiodic orbit, and undergoes heteroclinic bifurcation near 1:2 point, a homoclinic structure near 1:3 resonance point and an invariant cycle bifurcated by period 4 orbit near 1:4 resonance point. Moreover, in order to regulate information diffusion process and information security, we give two control strategies, the hybrid control method and the feedback controller of polynomial functions, to control chaos, flip bifurcation, 1:2, 1:3 and 1:4 resonances, respectively, in the two-dimensional discrete system.
Convergence of Spectral Discretizations of the Vlasov--Poisson System
Manzini, G.; Funaro, D.; Delzanno, G. L.
2017-09-26
Here we prove the convergence of a spectral discretization of the Vlasov-Poisson system. The velocity term of the Vlasov equation is discretized using either Hermite functions on the infinite domain or Legendre polynomials on a bounded domain. The spatial term of the Vlasov and Poisson equations is discretized using periodic Fourier expansions. Boundary conditions are treated in weak form through a penalty type term that can be applied also in the Hermite case. As a matter of fact, stability properties of the approximated scheme descend from this added term. The convergence analysis is carried out in detail for the 1D-1Vmore » case, but results can be generalized to multidimensional domains, obtained as Cartesian product, in both space and velocity. The error estimates show the spectral convergence under suitable regularity assumptions on the exact solution.« less
A necessary condition for dispersal driven growth of populations with discrete patch dynamics.
Guiver, Chris; Packman, David; Townley, Stuart
2017-07-07
We revisit the question of when can dispersal-induced coupling between discrete sink populations cause overall population growth? Such a phenomenon is called dispersal driven growth and provides a simple explanation of how dispersal can allow populations to persist across discrete, spatially heterogeneous, environments even when individual patches are adverse or unfavourable. For two classes of mathematical models, one linear and one non-linear, we provide necessary conditions for dispersal driven growth in terms of the non-existence of a common linear Lyapunov function, which we describe. Our approach draws heavily upon the underlying positive dynamical systems structure. Our results apply to both discrete- and continuous-time models. The theory is illustrated with examples and both biological and mathematical conclusions are drawn. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.