Concentration dependence of the wings of a dipole-broadened magnetic resonance line in magnetically diluted lattices

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

Zobov, V. E., E-mail: rsa@iph.krasn.ru; Kucherov, M. M.

2017-01-15

The singularities of the time autocorrelation functions (ACFs) of magnetically diluted spin systems with dipole–dipole interaction (DDI), which determine the high-frequency asymptotics of autocorrelation functions and the wings of a magnetic resonance line, are studied. Using the self-consistent fluctuating local field approximation, nonlinear equations are derived for autocorrelation functions averaged over the independent random arrangement of spins (magnetic atoms) in a diamagnetic lattice with different spin concentrations. The equations take into account the specificity of the dipole–dipole interaction. First, due to its axial symmetry in a strong static magnetic field, the autocorrelation functions of longitudinal and transverse spin components aremore » described by different equations. Second, the long-range type of the dipole–dipole interaction is taken into account by separating contributions into the local field from distant and near spins. The recurrent equations are obtained for the expansion coefficients of autocorrelation functions in power series in time. From them, the numerical value of the coordinate of the nearest singularity of the autocorrelation function is found on the imaginary time axis, which is equal to the radius of convergence of these expansions. It is shown that in the strong dilution case, the logarithmic concentration dependence of the coordinate of the singularity is observed, which is caused by the presence of a cluster of near spins whose fraction is small but contribution to the modulation frequency is large. As an example a silicon crystal with different {sup 29}Si concentrations in magnetic fields directed along three crystallographic axes is considered.« less

Determination of modulation transfer function of a printer by measuring the autocorrelation of the transmission function of a printed Ronchi grating

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

Madanipour, Khosro; Tavassoly, Mohammad T

2009-02-01

We show theoretically and verify experimentally that the modulation transfer function (MTF) of a printing system can be determined by measuring the autocorrelation of a printed Ronchi grating. In practice, two similar Ronchi gratings are printed on two transparencies and the transparencies are superimposed with parallel grating lines. Then, the gratings are uniformly illuminated and the transmitted light from a large section is measured versus the displacement of one grating with respect to the other in a grating pitch interval. This measurement provides the required autocorrelation function for determination of the MTF.

Reliabilities of Intraindividual Variability Indicators with Autocorrelated Longitudinal Data: Implications for Longitudinal Study Designs.

PubMed

Du, Han; Wang, Lijuan

2018-04-23

Intraindividual variability can be measured by the intraindividual standard deviation ([Formula: see text]), intraindividual variance ([Formula: see text]), estimated hth-order autocorrelation coefficient ([Formula: see text]), and mean square successive difference ([Formula: see text]). Unresolved issues exist in the research on reliabilities of intraindividual variability indicators: (1) previous research only studied conditions with 0 autocorrelations in the longitudinal responses; (2) the reliabilities of [Formula: see text] and [Formula: see text] have not been studied. The current study investigates reliabilities of [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], and the intraindividual mean, with autocorrelated longitudinal data. Reliability estimates of the indicators were obtained through Monte Carlo simulations. The impact of influential factors on reliabilities of the intraindividual variability indicators is summarized, and the reliabilities are compared across the indicators. Generally, all the studied indicators of intraindividual variability were more reliable with a more reliable measurement scale and more assessments. The reliabilities of [Formula: see text] were generally lower than those of [Formula: see text] and [Formula: see text], the reliabilities of [Formula: see text] were usually between those of [Formula: see text] and [Formula: see text] unless the scale reliability was large and/or the interindividual standard deviation in autocorrelation coefficients was large, and the reliabilities of the intraindividual mean were generally the highest. An R function is provided for planning longitudinal studies to ensure sufficient reliabilities of the intraindividual indicators are achieved.

Diffusion in shear flow

NASA Astrophysics Data System (ADS)

Dufty, J. W.

1984-09-01

Diffusion of a tagged particle in a fluid with uniform shear flow is described. The continuity equation for the probability density describing the position of the tagged particle is considered. The diffusion tensor is identified by expanding the irreversible part of the probability current to first order in the gradient of the probability density, but with no restriction on the shear rate. The tensor is expressed as the time integral of a nonequilibrium autocorrelation function for the velocity of the tagged particle in its local fluid rest frame, generalizing the Green-Kubo expression to the nonequilibrium state. The tensor is evaluated from results obtained previously for the velocity autocorrelation function that are exact for Maxwell molecules in the Boltzmann limit. The effects of viscous heating are included and the dependence on frequency and shear rate is displayed explicitly. The mode-coupling contributions to the frequency and shear-rate dependent diffusion tensor are calculated.

Quantifying uncertainty in soot volume fraction estimates using Bayesian inference of auto-correlated laser-induced incandescence measurements

NASA Astrophysics Data System (ADS)

Hadwin, Paul J.; Sipkens, T. A.; Thomson, K. A.; Liu, F.; Daun, K. J.

2016-01-01

Auto-correlated laser-induced incandescence (AC-LII) infers the soot volume fraction (SVF) of soot particles by comparing the spectral incandescence from laser-energized particles to the pyrometrically inferred peak soot temperature. This calculation requires detailed knowledge of model parameters such as the absorption function of soot, which may vary with combustion chemistry, soot age, and the internal structure of the soot. This work presents a Bayesian methodology to quantify such uncertainties. This technique treats the additional "nuisance" model parameters, including the soot absorption function, as stochastic variables and incorporates the current state of knowledge of these parameters into the inference process through maximum entropy priors. While standard AC-LII analysis provides a point estimate of the SVF, Bayesian techniques infer the posterior probability density, which will allow scientists and engineers to better assess the reliability of AC-LII inferred SVFs in the context of environmental regulations and competing diagnostics.

Momentum conserving Brownian dynamics propagator for complex soft matter fluids

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

Padding, J. T.; Briels, W. J.

2014-12-28

We present a Galilean invariant, momentum conserving first order Brownian dynamics scheme for coarse-grained simulations of highly frictional soft matter systems. Friction forces are taken to be with respect to moving background material. The motion of the background material is described by locally averaged velocities in the neighborhood of the dissolved coarse coordinates. The velocity variables are updated by a momentum conserving scheme. The properties of the stochastic updates are derived through the Chapman-Kolmogorov and Fokker-Planck equations for the evolution of the probability distribution of coarse-grained position and velocity variables, by requiring the equilibrium distribution to be a stationary solution.more » We test our new scheme on concentrated star polymer solutions and find that the transverse current and velocity time auto-correlation functions behave as expected from hydrodynamics. In particular, the velocity auto-correlation functions display a long time tail in complete agreement with hydrodynamics.« less

Superaging and Subaging Phenomena in a Nonequilibrium Critical Behavior of the Structurally Disordered Two-Dimensional XY Model

NASA Astrophysics Data System (ADS)

Prudnikov, V. V.; Prudnikov, P. V.; Popov, I. S.

2018-03-01

A Monte Carlo numerical simulation of the specific features of nonequilibrium critical behavior is carried out for the two-dimensional structurally disordered XY model during its evolution from a low-temperature initial state. On the basis of the analysis of the two-time dependence of autocorrelation functions and dynamic susceptibility for systems with spin concentrations of p = 1.0, 0.9, and 0.6, aging phenomena characterized by a slowing down of the relaxation system with increasing waiting time and the violation of the fluctuation-dissipation theorem (FDT) are revealed. The values of the universal limiting fluctuation-dissipation ratio (FDR) are obtained for the systems considered. As a result of the analysis of the two-time scaling dependence for spin-spin and connected spin autocorrelation functions, it is found that structural defects lead to subaging phenomena in the behavior of the spin-spin autocorrelation function and superaging phenomena in the behavior of the connected spin autocorrelation function.

Estimation of the spatial autocorrelation function: consequences of sampling dynamic populations in space and time

Treesearch

Patrick C. Tobin

2004-01-01

The estimation of spatial autocorrelation in spatially- and temporally-referenced data is fundamental to understanding an organism's population biology. I used four sets of census field data, and developed an idealized space-time dynamic system, to study the behavior of spatial autocorrelation estimates when a practical method of sampling is employed. Estimates...

Using PPI network autocorrelation in hierarchical multi-label classification trees for gene function prediction.

PubMed

Stojanova, Daniela; Ceci, Michelangelo; Malerba, Donato; Dzeroski, Saso

2013-09-26

Ontologies and catalogs of gene functions, such as the Gene Ontology (GO) and MIPS-FUN, assume that functional classes are organized hierarchically, that is, general functions include more specific ones. This has recently motivated the development of several machine learning algorithms for gene function prediction that leverages on this hierarchical organization where instances may belong to multiple classes. In addition, it is possible to exploit relationships among examples, since it is plausible that related genes tend to share functional annotations. Although these relationships have been identified and extensively studied in the area of protein-protein interaction (PPI) networks, they have not received much attention in hierarchical and multi-class gene function prediction. Relations between genes introduce autocorrelation in functional annotations and violate the assumption that instances are independently and identically distributed (i.i.d.), which underlines most machine learning algorithms. Although the explicit consideration of these relations brings additional complexity to the learning process, we expect substantial benefits in predictive accuracy of learned classifiers. This article demonstrates the benefits (in terms of predictive accuracy) of considering autocorrelation in multi-class gene function prediction. We develop a tree-based algorithm for considering network autocorrelation in the setting of Hierarchical Multi-label Classification (HMC). We empirically evaluate the proposed algorithm, called NHMC (Network Hierarchical Multi-label Classification), on 12 yeast datasets using each of the MIPS-FUN and GO annotation schemes and exploiting 2 different PPI networks. The results clearly show that taking autocorrelation into account improves the predictive performance of the learned models for predicting gene function. Our newly developed method for HMC takes into account network information in the learning phase: When used for gene function prediction in the context of PPI networks, the explicit consideration of network autocorrelation increases the predictive performance of the learned models. Overall, we found that this holds for different gene features/ descriptions, functional annotation schemes, and PPI networks: Best results are achieved when the PPI network is dense and contains a large proportion of function-relevant interactions.

Hydrodynamics of confined colloidal fluids in two dimensions

NASA Astrophysics Data System (ADS)

Sané, Jimaan; Padding, Johan T.; Louis, Ard A.

2009-05-01

We apply a hybrid molecular dynamics and mesoscopic simulation technique to study the dynamics of two-dimensional colloidal disks in confined geometries. We calculate the velocity autocorrelation functions and observe the predicted t-1 long-time hydrodynamic tail that characterizes unconfined fluids, as well as more complex oscillating behavior and negative tails for strongly confined geometries. Because the t-1 tail of the velocity autocorrelation function is cut off for longer times in finite systems, the related diffusion coefficient does not diverge but instead depends logarithmically on the overall size of the system. The Langevin equation gives a poor approximation to the velocity autocorrelation function at both short and long times.

Periodicity in the autocorrelation function as a mechanism for regularly occurring zero crossings or extreme values of a Gaussian process.

PubMed

Wilson, Lorna R M; Hopcraft, Keith I

2017-12-01

The problem of zero crossings is of great historical prevalence and promises extensive application. The challenge is to establish precisely how the autocorrelation function or power spectrum of a one-dimensional continuous random process determines the density function of the intervals between the zero crossings of that process. This paper investigates the case where periodicities are incorporated into the autocorrelation function of a smooth process. Numerical simulations, and statistics about the number of crossings in a fixed interval, reveal that in this case the zero crossings segue between a random and deterministic point process depending on the relative time scales of the periodic and nonperiodic components of the autocorrelation function. By considering the Laplace transform of the density function, we show that incorporating correlation between successive intervals is essential to obtaining accurate results for the interval variance. The same method enables prediction of the density function tail in some regions, and we suggest approaches for extending this to cover all regions. In an ever-more complex world, the potential applications for this scale of regularity in a random process are far reaching and powerful.

Periodicity in the autocorrelation function as a mechanism for regularly occurring zero crossings or extreme values of a Gaussian process

NASA Astrophysics Data System (ADS)

Wilson, Lorna R. M.; Hopcraft, Keith I.

2017-12-01

The problem of zero crossings is of great historical prevalence and promises extensive application. The challenge is to establish precisely how the autocorrelation function or power spectrum of a one-dimensional continuous random process determines the density function of the intervals between the zero crossings of that process. This paper investigates the case where periodicities are incorporated into the autocorrelation function of a smooth process. Numerical simulations, and statistics about the number of crossings in a fixed interval, reveal that in this case the zero crossings segue between a random and deterministic point process depending on the relative time scales of the periodic and nonperiodic components of the autocorrelation function. By considering the Laplace transform of the density function, we show that incorporating correlation between successive intervals is essential to obtaining accurate results for the interval variance. The same method enables prediction of the density function tail in some regions, and we suggest approaches for extending this to cover all regions. In an ever-more complex world, the potential applications for this scale of regularity in a random process are far reaching and powerful.

Autocorrelation of the susceptible-infected-susceptible process on networks

NASA Astrophysics Data System (ADS)

Liu, Qiang; Van Mieghem, Piet

2018-06-01

In this paper, we focus on the autocorrelation of the susceptible-infected-susceptible (SIS) process on networks. The N -intertwined mean-field approximation (NIMFA) is applied to calculate the autocorrelation properties of the exact SIS process. We derive the autocorrelation of the infection state of each node and the fraction of infected nodes both in the steady and transient states as functions of the infection probabilities of nodes. Moreover, we show that the autocorrelation can be used to estimate the infection and curing rates of the SIS process. The theoretical results are compared with the simulation of the exact SIS process. Our work fully utilizes the potential of the mean-field method and shows that NIMFA can indeed capture the autocorrelation properties of the exact SIS process.

Method and apparatus for in-situ characterization of energy storage and energy conversion devices

DOEpatents

Christophersen, Jon P [Idaho Falls, ID; Motloch, Chester G [Idaho Falls, ID; Morrison, John L [Butte, MT; Albrecht, Weston [Layton, UT

2010-03-09

Disclosed are methods and apparatuses for determining an impedance of an energy-output device using a random noise stimulus applied to the energy-output device. A random noise signal is generated and converted to a random noise stimulus as a current source correlated to the random noise signal. A bias-reduced response of the energy-output device to the random noise stimulus is generated by comparing a voltage at the energy-output device terminal to an average voltage signal. The random noise stimulus and bias-reduced response may be periodically sampled to generate a time-varying current stimulus and a time-varying voltage response, which may be correlated to generate an autocorrelated stimulus, an autocorrelated response, and a cross-correlated response. Finally, the autocorrelated stimulus, the autocorrelated response, and the cross-correlated response may be combined to determine at least one of impedance amplitude, impedance phase, and complex impedance.

Sources of variation in Landsat autocorrelation

NASA Technical Reports Server (NTRS)

Craig, R. G.; Labovitz, M. L.

1980-01-01

Analysis of sixty-four scan lines representing diverse conditions across satellites, channels, scanners, locations and cloud cover confirms that Landsat data are autocorrelated and consistently follow an Arima (1,0,1) pattern. The AR parameter varies significantly with location and the MA coefficient with cloud cover. Maximum likelihood classification functions are considerably in error unless this autocorrelation is compensated for in sampling.

Non-Markovian spin-resolved counting statistics and an anomalous relation between autocorrelations and cross correlations in a three-terminal quantum dot

NASA Astrophysics Data System (ADS)

Luo, JunYan; Yan, Yiying; Huang, Yixiao; Yu, Li; He, Xiao-Ling; Jiao, HuJun

2017-01-01

We investigate the noise correlations of spin and charge currents through an electron spin resonance (ESR)-pumped quantum dot, which is tunnel coupled to three electrodes maintained at an equivalent chemical potential. A recursive scheme is employed with inclusion of the spin degrees of freedom to account for the spin-resolved counting statistics in the presence of non-Markovian effects due to coupling with a dissipative heat bath. For symmetric spin-up and spin-down tunneling rates, an ESR-induced spin flip mechanism generates a pure spin current without an accompanying net charge current. The stochastic tunneling of spin carriers, however, produces universal shot noises of both charge and spin currents, revealing the effective charge and spin units of quasiparticles in transport. In the case of very asymmetric tunneling rates for opposite spins, an anomalous relationship between noise autocorrelations and cross correlations is revealed, where super-Poissonian autocorrelation is observed in spite of a negative cross correlation. Remarkably, with strong dissipation strength, non-Markovian memory effects give rise to a positive cross correlation of the charge current in the absence of a super-Poissonian autocorrelation. These unique noise features may offer essential methods for exploiting internal spin dynamics and various quasiparticle tunneling processes in mesoscopic transport.

Inference for local autocorrelations in locally stationary models.

PubMed

Zhao, Zhibiao

2015-04-01

For non-stationary processes, the time-varying correlation structure provides useful insights into the underlying model dynamics. We study estimation and inferences for local autocorrelation process in locally stationary time series. Our constructed simultaneous confidence band can be used to address important hypothesis testing problems, such as whether the local autocorrelation process is indeed time-varying and whether the local autocorrelation is zero. In particular, our result provides an important generalization of the R function acf() to locally stationary Gaussian processes. Simulation studies and two empirical applications are developed. For the global temperature series, we find that the local autocorrelations are time-varying and have a "V" shape during 1910-1960. For the S&P 500 index, we conclude that the returns satisfy the efficient-market hypothesis whereas the magnitudes of returns show significant local autocorrelations.

An empirical analysis of the distribution of the duration of overshoots in a stationary gaussian stochastic process

NASA Technical Reports Server (NTRS)

Parrish, R. S.; Carter, M. C.

1974-01-01

This analysis utilizes computer simulation and statistical estimation. Realizations of stationary gaussian stochastic processes with selected autocorrelation functions are computer simulated. Analysis of the simulated data revealed that the mean and the variance of a process were functionally dependent upon the autocorrelation parameter and crossing level. Using predicted values for the mean and standard deviation, by the method of moments, the distribution parameters was estimated. Thus, given the autocorrelation parameter, crossing level, mean, and standard deviation of a process, the probability of exceeding the crossing level for a particular length of time was calculated.

Coherence solution for bidirectional reflectance distributions of surfaces with wavelength-scale statistics.

PubMed

Hoover, Brian G; Gamiz, Victor L

2006-02-01

The scalar bidirectional reflectance distribution function (BRDF) due to a perfectly conducting surface with roughness and autocorrelation width comparable with the illumination wavelength is derived from coherence theory on the assumption of a random reflective phase screen and an expansion valid for large effective roughness. A general quadratic expansion of the two-dimensional isotropic surface autocorrelation function near the origin yields representative Cauchy and Gaussian BRDF solutions and an intermediate general solution as the sum of an incoherent component and a nonspecular coherent component proportional to an integral of the plasma dispersion function in the complex plane. Plots illustrate agreement of the derived general solution with original bistatic BRDF data due to a machined aluminum surface, and comparisons are drawn with previously published data in the examination of variations with incident angle, roughness, illumination wavelength, and autocorrelation coefficients in the bistatic and monostatic geometries. The general quadratic autocorrelation expansion provides a BRDF solution that smoothly interpolates between the well-known results of the linear and parabolic approximations.

Image correlation microscopy for uniform illumination.

PubMed

Gaborski, T R; Sealander, M N; Ehrenberg, M; Waugh, R E; McGrath, J L

2010-01-01

Image cross-correlation microscopy is a technique that quantifies the motion of fluorescent features in an image by measuring the temporal autocorrelation function decay in a time-lapse image sequence. Image cross-correlation microscopy has traditionally employed laser-scanning microscopes because the technique emerged as an extension of laser-based fluorescence correlation spectroscopy. In this work, we show that image correlation can also be used to measure fluorescence dynamics in uniform illumination or wide-field imaging systems and we call our new approach uniform illumination image correlation microscopy. Wide-field microscopy is not only a simpler, less expensive imaging modality, but it offers the capability of greater temporal resolution over laser-scanning systems. In traditional laser-scanning image cross-correlation microscopy, lateral mobility is calculated from the temporal de-correlation of an image, where the characteristic length is the illuminating laser beam width. In wide-field microscopy, the diffusion length is defined by the feature size using the spatial autocorrelation function. Correlation function decay in time occurs as an object diffuses from its original position. We show that theoretical and simulated comparisons between Gaussian and uniform features indicate the temporal autocorrelation function depends strongly on particle size and not particle shape. In this report, we establish the relationships between the spatial autocorrelation function feature size, temporal autocorrelation function characteristic time and the diffusion coefficient for uniform illumination image correlation microscopy using analytical, Monte Carlo and experimental validation with particle tracking algorithms. Additionally, we demonstrate uniform illumination image correlation microscopy analysis of adhesion molecule domain aggregation and diffusion on the surface of human neutrophils.

Spatial autocorrelation of radiation measured by the Earth Radiation Budget Experiment: Scene inhomogeneity and reciprocity violation

NASA Technical Reports Server (NTRS)

Davies, Roger

1994-01-01

The spatial autocorrelation functions of broad-band longwave and shortwave radiances measured by the Earth Radiation Budget Experiment (ERBE) are analyzed as a function of view angle in an investigation of the general effects of scene inhomogeneity on radiation. For nadir views, the correlation distance of the autocorrelation function is about 900 km for longwave radiance and about 500 km for shortwave radiance, consistent with higher degrees of freedom in shortwave reflection. Both functions rise monotonically with view angle, but there is a substantial difference in the relative angular dependence of the shortwave and longwave functions, especially for view angles less than 50 deg. In this range, the increase with angle of the longwave functions is found to depend only on the expansion of pixel area with angle, whereas the shortwave functions show an additional dependence on angle that is attributed to the occlusion of inhomogeneities by cloud height variations. Beyond a view angle of about 50 deg, both longwave and shortwave functions appear to be affected by cloud sides. The shortwave autocorrelation functions do not satisfy the principle of directional reciprocity, thereby proving that the average scene is horizontally inhomogeneous over the scale of an ERBE pixel (1500 sq km). Coarse stratification of the measurements by cloud amount, however, indicates that the average cloud-free scene does satisfy directional reciprocity on this scale.

DETAILED DATA ANALYSIS OF ECHO I, ECHO II AND MOON REFLECTED SIGNALS. VOLUME 2. AUTOCORRELATION FUNCTIONS OF ECHO II REFLECTED SIGNALS,

DTIC Science & Technology

techniques is presented. Two methods for linearizing the data are given. An expression for the specular-to-spattered power ratio is derived, and the inverse ... transform of the autocorrelation function is discussed. The surface roughness of the reflector, the discrete fading rates, and fading frequencies

Usage Autocorrelation Function in the Capacity of Indicator Shape of the Signal in Acoustic Emission Testing of Intricate Castings

NASA Astrophysics Data System (ADS)

Popkov, Artem

2016-01-01

The article contains information about acoustic emission signals analysing using autocorrelation function. Operation factors were analysed, such as shape of signal, the origins time and carrier frequency. The purpose of work is estimating the validity of correlations methods analysing signals. Acoustic emission signal consist of different types of waves, which propagate on different trajectories in object of control. Acoustic emission signal is amplitude-, phase- and frequency-modeling signal. It was described by carrier frequency at a given point of time. Period of signal make up 12.5 microseconds and carrier frequency make up 80 kHz for analysing signal. Usage autocorrelation function like indicator the origin time of acoustic emission signal raises validity localization of emitters.

Employing the Hilbert-Huang Transform to analyze observed natural complex signals: Calm wind meandering cases

NASA Astrophysics Data System (ADS)

Martins, Luis Gustavo Nogueira; Stefanello, Michel Baptistella; Degrazia, Gervásio Annes; Acevedo, Otávio Costa; Puhales, Franciano Scremin; Demarco, Giuliano; Mortarini, Luca; Anfossi, Domenico; Roberti, Débora Regina; Costa, Felipe Denardin; Maldaner, Silvana

2016-11-01

In this study we analyze natural complex signals employing the Hilbert-Huang spectral analysis. Specifically, low wind meandering meteorological data are decomposed into turbulent and non turbulent components. These non turbulent movements, responsible for the absence of a preferential direction of the horizontal wind, provoke negative lobes in the meandering autocorrelation functions. The meandering characteristic time scales (meandering periods) are determined from the spectral peak provided by the Hilbert-Huang marginal spectrum. The magnitudes of the temperature and horizontal wind meandering period obtained agree with the results found from the best fit of the heuristic meandering autocorrelation functions. Therefore, the new method represents a new procedure to evaluate meandering periods that does not employ mathematical expressions to represent observed meandering autocorrelation functions.

Monitoring autocorrelated process: A geometric Brownian motion process approach

NASA Astrophysics Data System (ADS)

Li, Lee Siaw; Djauhari, Maman A.

2013-09-01

Autocorrelated process control is common in today's modern industrial process control practice. The current practice of autocorrelated process control is to eliminate the autocorrelation by using an appropriate model such as Box-Jenkins models or other models and then to conduct process control operation based on the residuals. In this paper we show that many time series are governed by a geometric Brownian motion (GBM) process. Therefore, in this case, by using the properties of a GBM process, we only need an appropriate transformation and model the transformed data to come up with the condition needs in traditional process control. An industrial example of cocoa powder production process in a Malaysian company will be presented and discussed to illustrate the advantages of the GBM approach.

Autocorrelations of stellar light and mass at z˜ 0 and ˜1: from SDSS to DEEP2

NASA Astrophysics Data System (ADS)

Li, Cheng; White, Simon D. M.; Chen, Yanmei; Coil, Alison L.; Davis, Marc; De Lucia, Gabriella; Guo, Qi; Jing, Y. P.; Kauffmann, Guinevere; Willmer, Christopher N. A.; Zhang, Wei

2012-01-01

We present measurements of projected autocorrelation functions wp(rp) for the stellar mass of galaxies and for their light in the U, B and V bands, using data from the third data release of the DEEP2 Galaxy Redshift Survey and the final data release of the Sloan Digital Sky Survey (SDSS). We investigate the clustering bias of stellar mass and light by comparing these to projected autocorrelations of dark matter estimated from the Millennium Simulations (MS) at z= 1 and 0.07, the median redshifts of our galaxy samples. All of the autocorrelation and bias functions show systematic trends with spatial scale and waveband which are impressively similar at the two redshifts. This shows that the well-established environmental dependence of stellar populations in the local Universe is already in place at z= 1. The recent MS-based galaxy formation simulation of Guo et al. reproduces the scale-dependent clustering of luminosity to an accuracy better than 30 per cent in all bands and at both redshifts, but substantially overpredicts mass autocorrelations at separations below about 2 Mpc. Further comparison of the shapes of our stellar mass bias functions with those predicted by the model suggests that both the SDSS and DEEP2 data prefer a fluctuation amplitude of σ8˜ 0.8 rather than the σ8= 0.9 assumed by the MS.

Testing Pairwise Association between Spatially Autocorrelated Variables: A New Approach Using Surrogate Lattice Data

PubMed Central

Deblauwe, Vincent; Kennel, Pol; Couteron, Pierre

2012-01-01

Background Independence between observations is a standard prerequisite of traditional statistical tests of association. This condition is, however, violated when autocorrelation is present within the data. In the case of variables that are regularly sampled in space (i.e. lattice data or images), such as those provided by remote-sensing or geographical databases, this problem is particularly acute. Because analytic derivation of the null probability distribution of the test statistic (e.g. Pearson's r) is not always possible when autocorrelation is present, we propose instead the use of a Monte Carlo simulation with surrogate data. Methodology/Principal Findings The null hypothesis that two observed mapped variables are the result of independent pattern generating processes is tested here by generating sets of random image data while preserving the autocorrelation function of the original images. Surrogates are generated by matching the dual-tree complex wavelet spectra (and hence the autocorrelation functions) of white noise images with the spectra of the original images. The generated images can then be used to build the probability distribution function of any statistic of association under the null hypothesis. We demonstrate the validity of a statistical test of association based on these surrogates with both actual and synthetic data and compare it with a corrected parametric test and three existing methods that generate surrogates (randomization, random rotations and shifts, and iterative amplitude adjusted Fourier transform). Type I error control was excellent, even with strong and long-range autocorrelation, which is not the case for alternative methods. Conclusions/Significance The wavelet-based surrogates are particularly appropriate in cases where autocorrelation appears at all scales or is direction-dependent (anisotropy). We explore the potential of the method for association tests involving a lattice of binary data and discuss its potential for validation of species distribution models. An implementation of the method in Java for the generation of wavelet-based surrogates is available online as supporting material. PMID:23144961

Studies of the micromorphology of sputtered TiN thin films by autocorrelation techniques

NASA Astrophysics Data System (ADS)

Smagoń, Kamil; Stach, Sebastian; Ţălu, Ştefan; Arman, Ali; Achour, Amine; Luna, Carlos; Ghobadi, Nader; Mardani, Mohsen; Hafezi, Fatemeh; Ahmadpourian, Azin; Ganji, Mohsen; Grayeli Korpi, Alireza

2017-12-01

Autocorrelation techniques are crucial tools for the study of the micromorphology of surfaces: They provide the description of anisotropic properties and the identification of repeated patterns on the surface, facilitating the comparison of samples. In the present investigation, some fundamental concepts of these techniques including the autocorrelation function and autocorrelation length have been reviewed and applied in the study of titanium nitride thin films by atomic force microscopy (AFM). The studied samples were grown on glass substrates by reactive magnetron sputtering at different substrate temperatures (from 25 {}°C to 400 {}°C , and their micromorphology was studied by AFM. The obtained AFM data were analyzed using MountainsMap Premium software obtaining the correlation function, the structure of isotropy and the spatial parameters according to ISO 25178 and EUR 15178N. These studies indicated that the substrate temperature during the deposition process is an important parameter to modify the micromorphology of sputtered TiN thin films and to find optimized surface properties. For instance, the autocorrelation length exhibited a maximum value for the sample prepared at a substrate temperature of 300 {}°C , and the sample obtained at 400 {}°C presented a maximum angle of the direction of the surface structure.

A general statistical test for correlations in a finite-length time series.

PubMed

Hanson, Jeffery A; Yang, Haw

2008-06-07

The statistical properties of the autocorrelation function from a time series composed of independently and identically distributed stochastic variables has been studied. Analytical expressions for the autocorrelation function's variance have been derived. It has been found that two common ways of calculating the autocorrelation, moving-average and Fourier transform, exhibit different uncertainty characteristics. For periodic time series, the Fourier transform method is preferred because it gives smaller uncertainties that are uniform through all time lags. Based on these analytical results, a statistically robust method has been proposed to test the existence of correlations in a time series. The statistical test is verified by computer simulations and an application to single-molecule fluorescence spectroscopy is discussed.

Single-channel autocorrelation functions: the effects of time interval omission.

PubMed Central

Ball, F G; Sansom, M S

1988-01-01

We present a general mathematical framework for analyzing the dynamic aspects of single channel kinetics incorporating time interval omission. An algorithm for computing model autocorrelation functions, incorporating time interval omission, is described. We show, under quite general conditions, that the form of these autocorrelations is identical to that which would be obtained if time interval omission was absent. We also show, again under quite general conditions, that zero correlations are necessarily a consequence of the underlying gating mechanism and not an artefact of time interval omission. The theory is illustrated by a numerical study of an allosteric model for the gating mechanism of the locust muscle glutamate receptor-channel. PMID:2455553

Performance of signal-to-noise ratio estimation for scanning electron microscope using autocorrelation Levinson-Durbin recursion model.

PubMed

Sim, K S; Lim, M S; Yeap, Z X

2016-07-01

A new technique to quantify signal-to-noise ratio (SNR) value of the scanning electron microscope (SEM) images is proposed. This technique is known as autocorrelation Levinson-Durbin recursion (ACLDR) model. To test the performance of this technique, the SEM image is corrupted with noise. The autocorrelation function of the original image and the noisy image are formed. The signal spectrum based on the autocorrelation function of image is formed. ACLDR is then used as an SNR estimator to quantify the signal spectrum of noisy image. The SNR values of the original image and the quantified image are calculated. The ACLDR is then compared with the three existing techniques, which are nearest neighbourhood, first-order linear interpolation and nearest neighbourhood combined with first-order linear interpolation. It is shown that ACLDR model is able to achieve higher accuracy in SNR estimation. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Spectra of empirical autocorrelation matrices: A random-matrix-theory-inspired perspective

NASA Astrophysics Data System (ADS)

Jamali, Tayeb; Jafari, G. R.

2015-07-01

We construct an autocorrelation matrix of a time series and analyze it based on the random-matrix theory (RMT) approach. The autocorrelation matrix is capable of extracting information which is not easily accessible by the direct analysis of the autocorrelation function. In order to provide a precise conclusion based on the information extracted from the autocorrelation matrix, the results must be first evaluated. In other words they need to be compared with some sort of criterion to provide a basis for the most suitable and applicable conclusions. In the context of the present study, the criterion is selected to be the well-known fractional Gaussian noise (fGn). We illustrate the applicability of our method in the context of stock markets. For the former, despite the non-Gaussianity in returns of the stock markets, a remarkable agreement with the fGn is achieved.

Global Autocorrelation Scales of the Partial Pressure of Oceanic CO2

NASA Technical Reports Server (NTRS)

Li, Zhen; Adamec, David; Takahashi, Taro; Sutherland, Stewart C.

2004-01-01

A global database of approximately 1.7 million observations of the partial pressure of carbon dioxide in surface ocean waters (pCO2) collected between 1970 and 2003 is used to estimate its spatial autocorrelation structure. The patterns of the lag distance where the autocorrelation exceeds 0.8 is similar to patterns in the spatial distribution of the first baroclinic Rossby radius of deformation indicating that ocean circulation processes play a significant role in determining the spatial variability of pCO2. For example, the global maximum of the distance at which autocorrelations exceed 0.8 averages about 140 km in the equatorial Pacific. Also, the lag distance at which the autocorrelation exceed 0.8 is greater in the vicinity of the Gulf Stream than it is near the Kuroshio, approximately 50 km near the Gulf Stream as opposed to 20 km near the Kuroshio. Separate calculations for times when the sun is north and south of the equator revealed no obvious seasonal dependence of the spatial autocorrelation scales. The pCO2 measurements at Ocean Weather Station (OWS) 'P', in the eastern subarctic Pacific (50 N, 145 W) is the only fixed location where an uninterrupted time series of sufficient length exists to calculate a meaningful temporal autocorrelation function for lags greater than a few days. The estimated temporal autocorrelation function at OWS 'P', is highly variable. A spectral analysis of the longest four pCO2 time series indicates a high level of variability occurring over periods from the atmospheric synoptic to the maximum length of the time series, in this case 42 days. It is likely that a relative peak in variability with a period of 3-6 days is related to atmospheric synoptic period variability and ocean mixing events due to wind stirring. However, the short length of available time series makes identifying temporal relationships between pCO2 and atmospheric or ocean processes problematic.

An asymptotic theory for cross-correlation between auto-correlated sequences and its application on neuroimaging data.

PubMed

Zhou, Yunyi; Tao, Chenyang; Lu, Wenlian; Feng, Jianfeng

2018-04-20

Functional connectivity is among the most important tools to study brain. The correlation coefficient, between time series of different brain areas, is the most popular method to quantify functional connectivity. Correlation coefficient in practical use assumes the data to be temporally independent. However, the time series data of brain can manifest significant temporal auto-correlation. A widely applicable method is proposed for correcting temporal auto-correlation. We considered two types of time series models: (1) auto-regressive-moving-average model, (2) nonlinear dynamical system model with noisy fluctuations, and derived their respective asymptotic distributions of correlation coefficient. These two types of models are most commonly used in neuroscience studies. We show the respective asymptotic distributions share a unified expression. We have verified the validity of our method, and shown our method exhibited sufficient statistical power for detecting true correlation on numerical experiments. Employing our method on real dataset yields more robust functional network and higher classification accuracy than conventional methods. Our method robustly controls the type I error while maintaining sufficient statistical power for detecting true correlation in numerical experiments, where existing methods measuring association (linear and nonlinear) fail. In this work, we proposed a widely applicable approach for correcting the effect of temporal auto-correlation on functional connectivity. Empirical results favor the use of our method in functional network analysis. Copyright © 2018. Published by Elsevier B.V.

Autocorrelated residuals in inverse modelling of soil hydrological processes: a reason for concern or something that can safely be ignored?

NASA Astrophysics Data System (ADS)

Scharnagl, Benedikt; Durner, Wolfgang

2013-04-01

Models are inherently imperfect because they simplify processes that are themselves imperfectly known and understood. Moreover, the input variables and parameters needed to run a model are typically subject to various sources of error. As a consequence of these imperfections, model predictions will always deviate from corresponding observations. In most applications in soil hydrology, these deviations are clearly not random but rather show a systematic structure. From a statistical point of view, this systematic mismatch may be a reason for concern because it violates one of the basic assumptions made in inverse parameter estimation: the assumption of independence of the residuals. But what are the consequences of simply ignoring the autocorrelation in the residuals, as it is current practice in soil hydrology? Are the parameter estimates still valid even though the statistical foundation they are based on is partially collapsed? Theory and practical experience from other fields of science have shown that violation of the independence assumption will result in overconfident uncertainty bounds and that in some cases it may lead to significantly different optimal parameter values. In our contribution, we present three soil hydrological case studies, in which the effect of autocorrelated residuals on the estimated parameters was investigated in detail. We explicitly accounted for autocorrelated residuals using a formal likelihood function that incorporates an autoregressive model. The inverse problem was posed in a Bayesian framework, and the posterior probability density function of the parameters was estimated using Markov chain Monte Carlo simulation. In contrast to many other studies in related fields of science, and quite surprisingly, we found that the first-order autoregressive model, often abbreviated as AR(1), did not work well in the soil hydrological setting. We showed that a second-order autoregressive, or AR(2), model performs much better in these applications, leading to parameter and uncertainty estimates that satisfy all the underlying statistical assumptions. For theoretical reasons, these estimates are deemed more reliable than those estimates based on the neglect of autocorrelation in the residuals. In compliance with theory and results reported in the literature, our results showed that parameter uncertainty bounds were substantially wider if autocorrelation in the residuals was explicitly accounted for, and also the optimal parameter vales were slightly different in this case. We argue that the autoregressive model presented here should be used as a matter of routine in inverse modeling of soil hydrological processes.

Spectrum sensing algorithm based on autocorrelation energy in cognitive radio networks

NASA Astrophysics Data System (ADS)

Ren, Shengwei; Zhang, Li; Zhang, Shibing

2016-10-01

Cognitive radio networks have wide applications in the smart home, personal communications and other wireless communication. Spectrum sensing is the main challenge in cognitive radios. This paper proposes a new spectrum sensing algorithm which is based on the autocorrelation energy of signal received. By taking the autocorrelation energy of the received signal as the statistics of spectrum sensing, the effect of the channel noise on the detection performance is reduced. Simulation results show that the algorithm is effective and performs well in low signal-to-noise ratio. Compared with the maximum generalized eigenvalue detection (MGED) algorithm, function of covariance matrix based detection (FMD) algorithm and autocorrelation-based detection (AD) algorithm, the proposed algorithm has 2 11 dB advantage.

A technique to detect periodic and non-periodic ultra-rapid flux time variations with standard radio-astronomical data

NASA Astrophysics Data System (ADS)

Borra, Ermanno F.; Romney, Jonathan D.; Trottier, Eric

2018-06-01

We demonstrate that extremely rapid and weak periodic and non-periodic signals can easily be detected by using the autocorrelation of intensity as a function of time. We use standard radio-astronomical observations that have artificial periodic and non-periodic signals generated by the electronics of terrestrial origin. The autocorrelation detects weak signals that have small amplitudes because it averages over long integration times. Another advantage is that it allows a direct visualization of the shape of the signals, while it is difficult to see the shape with a Fourier transform. Although Fourier transforms can also detect periodic signals, a novelty of this work is that we demonstrate another major advantage of the autocorrelation, that it can detect non-periodic signals while the Fourier transform cannot. Another major novelty of our work is that we use electric fields taken in a standard format with standard instrumentation at a radio observatory and therefore no specialized instrumentation is needed. Because the electric fields are sampled every 15.625 ns, they therefore allow detection of very rapid time variations. Notwithstanding the long integration times, the autocorrelation detects very rapid intensity variations as a function of time. The autocorrelation could also detect messages from Extraterrestrial Intelligence as non-periodic signals.

Partial correlation properties of pseudonoise /PN/ codes in noncoherent synchronization/detection schemes

NASA Technical Reports Server (NTRS)

Cartier, D. E.

1976-01-01

This concise paper considers the effect on the autocorrelation function of a pseudonoise (PN) code when the acquisition scheme only integrates coherently over part of the code and then noncoherently combines these results. The peak-to-null ratio of the effective PN autocorrelation function is shown to degrade to the square root of n, where n is the number of PN symbols over which coherent integration takes place.

Characteristic measurement for femtosecond laser pulses using a GaAs PIN photodiode as a two-photon photovoltaic receiver

NASA Astrophysics Data System (ADS)

Chen, Junbao; Xia, Wei; Wang, Ming

2017-06-01

Photodiodes that exhibit a two-photon absorption effect within the spectral communication band region can be useful for building an ultra-compact autocorrelator for the characteristic inspection of optical pulses. In this work, we develop an autocorrelator for measuring the temporal profile of pulses at 1550 nm from an erbium-doped fiber laser based on the two-photon photovoltaic (TPP) effect in a GaAs PIN photodiode. The temporal envelope of the autocorrelation function contains two symmetrical temporal side lobes due to the third order dispersion of the laser pulses. Moreover, the joint time-frequency distribution of the dispersive pulses and the dissimilar two-photon response spectrum of GaAs and Si result in different delays for the appearance of the temporal side lobes. Compared with Si, GaAs displays a greater sensitivity for pulse shape reconstruction at 1550 nm, benefiting from the higher signal-to-noise ratio of the side lobes and the more centralized waveform of the autocorrelation trace. We also measure the pulse width using the GaAs PIN photodiode, and the resolution of the measured full width at half maximum of the TPP autocorrelation trace is 0.89 fs, which is consistent with a conventional second-harmonic generation crystal autocorrelator. The GaAs PIN photodiode is shown to be highly suitable for real-time second-order autocorrelation measurements of femtosecond optical pulses. It is used both for the generation and detection of the autocorrelation signal, allowing the construction of a compact and inexpensive intensity autocorrelator.

Analysis of data from NASA B-57B gust gradient program

NASA Technical Reports Server (NTRS)

Frost, W.; Lin, M. C.; Chang, H. P.; Ringnes, E.

1985-01-01

Statistical analysis of the turbulence measured in flight 6 of the NASA B-57B over Denver, Colorado, from July 7 to July 23, 1982 included the calculations of average turbulence parameters, integral length scales, probability density functions, single point autocorrelation coefficients, two point autocorrelation coefficients, normalized autospectra, normalized two point autospectra, and two point cross sectra for gust velocities. The single point autocorrelation coefficients were compared with the theoretical model developed by von Karman. Theoretical analyses were developed which address the effects spanwise gust distributions, using two point spatial turbulence correlations.

Imaging the Lower Crust and Moho Beneath Long Beach, CA Using Autocorrelations

NASA Astrophysics Data System (ADS)

Clayton, R. W.

2017-12-01

Three-dimensional images of the lower crust and Moho in a 10x10 km region beneath Long Beach, CA are constructed from autocorrelations of ambient noise. The results show the Moho at a depth of 15 km at the coast and dipping at 45 degrees inland to a depth of 25 km. The shape of the Moho interface is irregular in both the coast perpendicular and parallel directions. The lower crust appears as a zone of enhanced reflectivity with numerous small-scale structures. The autocorrelations are constructed from virtual source gathers that were computed from the dense Long Beach array that were used in the Lin et al (2013) study. All near zero-offset traces within a 200 m disk are stacked to produce a single autocorrelation at that point. The stack typically is over 50-60 traces. To convert the auto correlation to reflectivity as in Claerbout (1968), the noise source autocorrelation, which is estimated as the average of all autocorrelations is subtracted from each trace. The subsurface image is then constructed with a 0.1-2 Hz filter and AGC scaling. The main features of the image are confirmed with broadband receiver functions from the LASSIE survey (Ma et al, 2016). The use of stacked autocorrelations extends ambient noise into the lower crust.

Aging Wiener-Khinchin theorem and critical exponents of 1/f^{β} noise.

PubMed

Leibovich, N; Dechant, A; Lutz, E; Barkai, E

2016-11-01

The power spectrum of a stationary process may be calculated in terms of the autocorrelation function using the Wiener-Khinchin theorem. We here generalize the Wiener-Khinchin theorem for nonstationary processes and introduce a time-dependent power spectrum 〈S_{t_{m}}(ω)〉 where t_{m} is the measurement time. For processes with an aging autocorrelation function of the form 〈I(t)I(t+τ)〉=t^{Υ}ϕ_{EA}(τ/t), where ϕ_{EA}(x) is a nonanalytic function when x is small, we find aging 1/f^{β} noise. Aging 1/f^{β} noise is characterized by five critical exponents. We derive the relations between the scaled autocorrelation function and these exponents. We show that our definition of the time-dependent spectrum retains its interpretation as a density of Fourier modes and discuss the relation to the apparent infrared divergence of 1/f^{β} noise. We illustrate our results for blinking-quantum-dot models, single-file diffusion, and Brownian motion in a logarithmic potential.

Diffusion and viscosity of liquid tin: Green-Kubo relationship-based calculations from molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Mouas, Mohamed; Gasser, Jean-Georges; Hellal, Slimane; Grosdidier, Benoît; Makradi, Ahmed; Belouettar, Salim

2012-03-01

Molecular dynamics (MD) simulations of liquid tin between its melting point and 1600 °C have been performed in order to interpret and discuss the ionic structure. The interactions between ions are described by a new accurate pair potential built within the pseudopotential formalism and the linear response theory. The calculated structure factor that reflects the main information on the local atomic order in liquids is compared to diffraction measurements. Having some confidence in the ability of this pair potential to give a good representation of the atomic structure, we then focused our attention on the investigation of the atomic transport properties through the MD computations of the velocity autocorrelation function and stress autocorrelation function. Using the Green-Kubo formula (for the first time to our knowledge for liquid tin) we determine the macroscopic transport properties from the corresponding microscopic time autocorrelation functions. The selfdiffusion coefficient and the shear viscosity as functions of temperature are found to be in good agreement with the experimental data.

Using Exponential Smoothing to Specify Intervention Models for Interrupted Time Series.

ERIC Educational Resources Information Center

Mandell, Marvin B.; Bretschneider, Stuart I.

1984-01-01

The authors demonstrate how exponential smoothing can play a role in the identification of the intervention component of an interrupted time-series design model that is analogous to the role that the sample autocorrelation and partial autocorrelation functions serve in the identification of the noise portion of such a model. (Author/BW)

Reflection Response of the Parnaíba Basin (NE Brazil) from Seismic Ambient Noise Autocorrelation Functions

NASA Astrophysics Data System (ADS)

Julià, Jordi; Schimmel, Martin; Cedraz, Victória

2017-04-01

Reflected-wave interferometry relies on the recording of transient seismic signals from random wavefields located beneath recording stations. Under vertical incidence, the recordings contain the full transmission response, which includes the direct wave as well as multiple reverberations from seismic discontinuities located between the wavefields and the receiver. It has been shown that, under those assumptions, the reflection response of the medium can be recovered from the autocorrelation function (ACF) of the transmission response at a given receiver, as if the wavefields had originated themselves at the free surface. This passive approach to seismic reflection profiling has the obvious advantage of being low-cost and non-invasive when compared to its active-source counterpart, and it has been successfully utilized in other sedimentary basins worldwide. In this paper we evaluate the ability of the autocorrelation of ambient seismic noise recorded in the Parnaíba basin - a large Paleozoic basin in NE Brazil - to recover the reflection response of the basin. The dataset was acquired by the Universidade Federal do Rio Grande do Norte during 2015 and 2016 under the Parnaíba Basin Analysis Project (PBAP), a multi-disciplinary and multi-institutional effort funded by BP Energy do Brasil aimed at improving our current understanding of the architecture of this cratonic basin. The dataset consists of about 1 year of continuous ground motion data from 10 short-period, 3-component stations located in the central portion of the basin. The stations were co-located with an existing (active-source) seismic reflection profile that was shot in 2012, making a linear array of about 100 km in aperture and about 10 km inter-station spacing. To develop the autocorrelation at a given station we considered the vertical component of ground motion only, which should result in the P-wave response. The vertical recordings were first split into 10 min-long windows, demeaned, de-trended, re-sampled, and band-pass filtered between 8 and 16 Hz before autocorrelation, and then stacked with phase-weighting to enhance coherency of the retrieved signal. The ACFs show coherent signal is recovered at lag times between 0.5 and 2 s, which we interpret as P- and S-wave energy reflected on top of an intra-sedimentary discontinuity. Our results are consistent, to first-order, with a previously developed active-source reflection response of the basin.

Dangers and uses of cross-correlation in analyzing time series in perception, performance, movement, and neuroscience: The importance of constructing transfer function autoregressive models.

PubMed

Dean, Roger T; Dunsmuir, William T M

2016-06-01

Many articles on perception, performance, psychophysiology, and neuroscience seek to relate pairs of time series through assessments of their cross-correlations. Most such series are individually autocorrelated: they do not comprise independent values. Given this situation, an unfounded reliance is often placed on cross-correlation as an indicator of relationships (e.g., referent vs. response, leading vs. following). Such cross-correlations can indicate spurious relationships, because of autocorrelation. Given these dangers, we here simulated how and why such spurious conclusions can arise, to provide an approach to resolving them. We show that when multiple pairs of series are aggregated in several different ways for a cross-correlation analysis, problems remain. Finally, even a genuine cross-correlation function does not answer key motivating questions, such as whether there are likely causal relationships between the series. Thus, we illustrate how to obtain a transfer function describing such relationships, informed by any genuine cross-correlations. We illustrate the confounds and the meaningful transfer functions by two concrete examples, one each in perception and performance, together with key elements of the R software code needed. The approach involves autocorrelation functions, the establishment of stationarity, prewhitening, the determination of cross-correlation functions, the assessment of Granger causality, and autoregressive model development. Autocorrelation also limits the interpretability of other measures of possible relationships between pairs of time series, such as mutual information. We emphasize that further complexity may be required as the appropriate analysis is pursued fully, and that causal intervention experiments will likely also be needed.

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

Davies, R.

The spatial autocorrelation functions of broad-band longwave and shortwave radiances measured by the Earth Radiation Budget Experiment (ERBE) are analyzed as a function of view angle in an investigation of the general effects of scene inhomogeneity on radiation. For nadir views, the correlation distance of the autocorrelation function is about 900 km for longwave radiance and about 500 km for shortwave radiance, consistent with higher degrees of freedom in shortwave reflection. Both functions rise monotonically with view angle, but there is a substantial difference in the relative angular dependence of the shortwave and longwave functions, especially for view angles lessmore » than 50 deg. In this range, the increase with angle of the longwave functions is found to depend only on the expansion of pixel area with angle, whereas the shortwave functions show an additional dependence on angle that is attributed to the occlusion of inhomogeneities by cloud height variations. Beyond a view angle of about 50 deg, both longwave and shortwave functions appear to be affected by cloud sides. The shortwave autocorrelation functions do not satisfy the principle of directional reciprocity, thereby proving that the average scene is horizontally inhomogeneous over the scale of an ERBE pixel (1500 sq km). Coarse stratification of the measurements by cloud amount, however, indicates that the average cloud-free scene does satisfy directional reciprocity on this scale.« less

Autocorrelation Function for Monitoring the Gap between The Steel Plates During Laser Welding

NASA Astrophysics Data System (ADS)

Mrna, Libor; Hornik, Petr

Proper alignment of the plates prior to laser welding represents an important factor that determines the quality of the resulting weld. A gap between the plates in a butt or overlap joint affects the oscillations of the keyhole and the surrounding weld pool. We present an experimental study of the butt and overlap welds with the artificial gap of the different thickness of the plates. The welds were made on a 2 kW fiber laser machine for the steel plates and the various welding parameters settings. The eigenfrequency of the keyhole oscillations and its changes were determined from the light emissions of the plasma plume using an autocorrelation function. As a result, we describe the relations between the autocorrelation characteristics, the thickness of the gap between plates and the weld geometry.

Autocorrelation exponent of conserved spin systems in the scaling regime following a critical quench.

PubMed

Sire, Clément

2004-09-24

We study the autocorrelation function of a conserved spin system following a quench at the critical temperature. Defining the correlation length L(t) approximately t(1/z), we find that for times t' and t satisfying L(t')infinity limit, we show that lambda(')(c)=d+2 and phi=z/2. We give a heuristic argument suggesting that this result is, in fact, valid for any dimension d and spin vector dimension n. We present numerical simulations for the conserved Ising model in d=1 and d=2, which are fully consistent with the present theory.

Spatial design and strength of spatial signal: Effects on covariance estimation

USGS Publications Warehouse

Irvine, Kathryn M.; Gitelman, Alix I.; Hoeting, Jennifer A.

2007-01-01

In a spatial regression context, scientists are often interested in a physical interpretation of components of the parametric covariance function. For example, spatial covariance parameter estimates in ecological settings have been interpreted to describe spatial heterogeneity or “patchiness” in a landscape that cannot be explained by measured covariates. In this article, we investigate the influence of the strength of spatial dependence on maximum likelihood (ML) and restricted maximum likelihood (REML) estimates of covariance parameters in an exponential-with-nugget model, and we also examine these influences under different sampling designs—specifically, lattice designs and more realistic random and cluster designs—at differing intensities of sampling (n=144 and 361). We find that neither ML nor REML estimates perform well when the range parameter and/or the nugget-to-sill ratio is large—ML tends to underestimate the autocorrelation function and REML produces highly variable estimates of the autocorrelation function. The best estimates of both the covariance parameters and the autocorrelation function come under the cluster sampling design and large sample sizes. As a motivating example, we consider a spatial model for stream sulfate concentration.

New approaches for calculating Moran's index of spatial autocorrelation.

PubMed

Chen, Yanguang

2013-01-01

Spatial autocorrelation plays an important role in geographical analysis; however, there is still room for improvement of this method. The formula for Moran's index is complicated, and several basic problems remain to be solved. Therefore, I will reconstruct its mathematical framework using mathematical derivation based on linear algebra and present four simple approaches to calculating Moran's index. Moran's scatterplot will be ameliorated, and new test methods will be proposed. The relationship between the global Moran's index and Geary's coefficient will be discussed from two different vantage points: spatial population and spatial sample. The sphere of applications for both Moran's index and Geary's coefficient will be clarified and defined. One of theoretical findings is that Moran's index is a characteristic parameter of spatial weight matrices, so the selection of weight functions is very significant for autocorrelation analysis of geographical systems. A case study of 29 Chinese cities in 2000 will be employed to validate the innovatory models and methods. This work is a methodological study, which will simplify the process of autocorrelation analysis. The results of this study will lay the foundation for the scaling analysis of spatial autocorrelation.

Asymmetric multiscale multifractal analysis of wind speed signals

NASA Astrophysics Data System (ADS)

Zhang, Xiaonei; Zeng, Ming; Meng, Qinghao

We develop a new method called asymmetric multiscale multifractal analysis (A-MMA) to explore the multifractality and asymmetric autocorrelations of the signals with a variable scale range. Three numerical experiments are provided to demonstrate the effectiveness of our approach. Then, the proposed method is applied to investigate multifractality and asymmetric autocorrelations of difference sequences between wind speed fluctuations with uptrends or downtrends. The results show that these sequences appear to be far more complex and contain abundant fractal dynamics information. Through analyzing the Hurst surfaces of nine difference sequences, we found that all series exhibit multifractal properties and multiscale structures. Meanwhile, the asymmetric autocorrelations are observed in all variable scale ranges and the asymmetry results are of good consistency within a certain spatial range. The sources of multifractality and asymmetry in nine difference series are further discussed using the corresponding shuffled series and surrogate series. We conclude that the multifractality of these series is due to both long-range autocorrelation and broad probability density function, but the major source of multifractality is long-range autocorrelation, and the source of asymmetry is affected by the spatial distance.

Numerical analysis for finite-range multitype stochastic contact financial market dynamic systems

NASA Astrophysics Data System (ADS)

Yang, Ge; Wang, Jun; Fang, Wen

2015-04-01

In an attempt to reproduce and study the dynamics of financial markets, a random agent-based financial price model is developed and investigated by the finite-range multitype contact dynamic system, in which the interaction and dispersal of different types of investment attitudes in a stock market are imitated by viruses spreading. With different parameters of birth rates and finite-range, the normalized return series are simulated by Monte Carlo simulation method and numerical studied by power-law distribution analysis and autocorrelation analysis. To better understand the nonlinear dynamics of the return series, a q-order autocorrelation function and a multi-autocorrelation function are also defined in this work. The comparisons of statistical behaviors of return series from the agent-based model and the daily historical market returns of Shanghai Composite Index and Shenzhen Component Index indicate that the proposed model is a reasonable qualitative explanation for the price formation process of stock market systems.

Incorporating spatial autocorrelation into species distribution models alters forecasts of climate-mediated range shifts.

PubMed

Crase, Beth; Liedloff, Adam; Vesk, Peter A; Fukuda, Yusuke; Wintle, Brendan A

2014-08-01

Species distribution models (SDMs) are widely used to forecast changes in the spatial distributions of species and communities in response to climate change. However, spatial autocorrelation (SA) is rarely accounted for in these models, despite its ubiquity in broad-scale ecological data. While spatial autocorrelation in model residuals is known to result in biased parameter estimates and the inflation of type I errors, the influence of unmodeled SA on species' range forecasts is poorly understood. Here we quantify how accounting for SA in SDMs influences the magnitude of range shift forecasts produced by SDMs for multiple climate change scenarios. SDMs were fitted to simulated data with a known autocorrelation structure, and to field observations of three mangrove communities from northern Australia displaying strong spatial autocorrelation. Three modeling approaches were implemented: environment-only models (most frequently applied in species' range forecasts), and two approaches that incorporate SA; autologistic models and residuals autocovariate (RAC) models. Differences in forecasts among modeling approaches and climate scenarios were quantified. While all model predictions at the current time closely matched that of the actual current distribution of the mangrove communities, under the climate change scenarios environment-only models forecast substantially greater range shifts than models incorporating SA. Furthermore, the magnitude of these differences intensified with increasing increments of climate change across the scenarios. When models do not account for SA, forecasts of species' range shifts indicate more extreme impacts of climate change, compared to models that explicitly account for SA. Therefore, where biological or population processes induce substantial autocorrelation in the distribution of organisms, and this is not modeled, model predictions will be inaccurate. These results have global importance for conservation efforts as inaccurate forecasts lead to ineffective prioritization of conservation activities and potentially to avoidable species extinctions. © 2014 John Wiley & Sons Ltd.

General simulation algorithm for autocorrelated binary processes.

PubMed

Serinaldi, Francesco; Lombardo, Federico

2017-02-01

The apparent ubiquity of binary random processes in physics and many other fields has attracted considerable attention from the modeling community. However, generation of binary sequences with prescribed autocorrelation is a challenging task owing to the discrete nature of the marginal distributions, which makes the application of classical spectral techniques problematic. We show that such methods can effectively be used if we focus on the parent continuous process of beta distributed transition probabilities rather than on the target binary process. This change of paradigm results in a simulation procedure effectively embedding a spectrum-based iterative amplitude-adjusted Fourier transform method devised for continuous processes. The proposed algorithm is fully general, requires minimal assumptions, and can easily simulate binary signals with power-law and exponentially decaying autocorrelation functions corresponding, for instance, to Hurst-Kolmogorov and Markov processes. An application to rainfall intermittency shows that the proposed algorithm can also simulate surrogate data preserving the empirical autocorrelation.

Data Analysis Methods for Synthetic Polymer Mass Spectrometry: Autocorrelation

PubMed Central

Wallace, William E.; Guttman, Charles M.

2002-01-01

Autocorrelation is shown to be useful in describing the periodic patterns found in high- resolution mass spectra of synthetic polymers. Examples of this usefulness are described for a simple linear homopolymer to demonstrate the method fundamentals, a condensation polymer to demonstrate its utility in understanding complex spectra with multiple repeating patterns on different mass scales, and a condensation copolymer to demonstrate how it can elegantly and efficiently reveal unexpected phenomena. It is shown that using autocorrelation to determine where the signal devolves into noise can be useful in determining molecular mass distributions of synthetic polymers, a primary focus of the NIST synthetic polymer mass spectrometry effort. The appendices describe some of the effects of transformation from time to mass space when time-of-flight mass separation is used, as well as the effects of non-trivial baselines on the autocorrelation function. PMID:27446716

On the dielectric conductivity of molecular ionic liquids.

PubMed

Schröder, Christian; Steinhauser, Othmar

2009-09-21

The contribution of the conductivity to the spectrum of the generalized dielectric constant or susceptibility of molecular ionic liquids is analyzed, both in theoretical terms and computationally by means of molecular dynamics simulation of the concrete system 1-ethyl-3-methyl-imidazolium dicyanoamide at 300 K. As a central quantity the simulated current autocorrelation function is modeled by a carefully designed fit function. This not only gives a satisfactory numerical representation but yields the correct conductivity upon integration. In addition the fit function can be Fourier-Laplace transformed analytically. Both, the real and imaginary parts of the transform show expected behavior, in particular, the right limits for zero frequency. This altogether demonstrates that the components of the fit function are of physical relevance.

Synchronous scattering and diffraction from gold nanotextured surfaces with structure factors

NASA Astrophysics Data System (ADS)

Gu, Min-Jhong; Lee, Ming-Tsang; Huang, Chien-Hsun; Wu, Chi-Chun; Chen, Yu-Bin

2018-05-01

Synchronous scattering and diffraction were demonstrated using reflectance from gold nanotextured surfaces at oblique (θi = 15° and 60°) incidence of wavelength λ = 405 nm. Two samples of unique auto-correlation functions were cost-effectively fabricated. Multiple structure factors of their profiles were confirmed with Fourier expansions. Bi-directional reflectance function (BRDF) from these samples provided experimental proofs. On the other hand, standard deviation of height and unique auto-correlation function of each sample were used to generate surfaces numerically. Comparing their BRDF with those of totally random rough surfaces further suggested that structure factors in profile could reduce specular reflection more than totally random roughness.

An empirical analysis of the distribution of overshoots in a stationary Gaussian stochastic process

NASA Technical Reports Server (NTRS)

Carter, M. C.; Madison, M. W.

1973-01-01

The frequency distribution of overshoots in a stationary Gaussian stochastic process is analyzed. The primary processes involved in this analysis are computer simulation and statistical estimation. Computer simulation is used to simulate stationary Gaussian stochastic processes that have selected autocorrelation functions. An analysis of the simulation results reveals a frequency distribution for overshoots with a functional dependence on the mean and variance of the process. Statistical estimation is then used to estimate the mean and variance of a process. It is shown that for an autocorrelation function, the mean and the variance for the number of overshoots, a frequency distribution for overshoots can be estimated.

A new estimator method for GARCH models

NASA Astrophysics Data System (ADS)

Onody, R. N.; Favaro, G. M.; Cazaroto, E. R.

2007-06-01

The GARCH (p, q) model is a very interesting stochastic process with widespread applications and a central role in empirical finance. The Markovian GARCH (1, 1) model has only 3 control parameters and a much discussed question is how to estimate them when a series of some financial asset is given. Besides the maximum likelihood estimator technique, there is another method which uses the variance, the kurtosis and the autocorrelation time to determine them. We propose here to use the standardized 6th moment. The set of parameters obtained in this way produces a very good probability density function and a much better time autocorrelation function. This is true for both studied indexes: NYSE Composite and FTSE 100. The probability of return to the origin is investigated at different time horizons for both Gaussian and Laplacian GARCH models. In spite of the fact that these models show almost identical performances with respect to the final probability density function and to the time autocorrelation function, their scaling properties are, however, very different. The Laplacian GARCH model gives a better scaling exponent for the NYSE time series, whereas the Gaussian dynamics fits better the FTSE scaling exponent.

Distribution of Reynolds stress carried by mesoscale variability in the Antarctic Circumpolar Current

NASA Technical Reports Server (NTRS)

Johnson, Thomas J.; Stewart, Robert H.; Shum, C. K.; Tapley, Byron D.

1992-01-01

Satellite altimeter data collected by the Geosat Exact Repeat Mission were used to investigate turbulent stress resulting from the variability of surface geostrophic currents in the Antarctic Circumpolar Current. The altimeter measured sea level along the subsatellite track. The variability of the along-track slope of sea level is directly proportional to the variability of surface geostrophic currents in the cross-track direction. Because the grid of crossover points is dense at high latitudes, the satellite data could be used for mapping the temporal and spatial variability of the current. Two and a half years of data were used to compute the statistical structure of the variability. The statistics included the probability distribution functions for each component of the current, the time-lagged autocorrelation functions of the variability, and the Reynolds stress produced by the variability. The results demonstrate that stress is correlated with bathymetry. In some areas the distribution of negative stress indicate that eddies contribute to an acceleration of the mean flow, strengthening the hypothesis that baroclinic instability makes important contributions to strong oceanic currents.

New Approaches for Calculating Moran’s Index of Spatial Autocorrelation

PubMed Central

Chen, Yanguang

2013-01-01

Spatial autocorrelation plays an important role in geographical analysis; however, there is still room for improvement of this method. The formula for Moran’s index is complicated, and several basic problems remain to be solved. Therefore, I will reconstruct its mathematical framework using mathematical derivation based on linear algebra and present four simple approaches to calculating Moran’s index. Moran’s scatterplot will be ameliorated, and new test methods will be proposed. The relationship between the global Moran’s index and Geary’s coefficient will be discussed from two different vantage points: spatial population and spatial sample. The sphere of applications for both Moran’s index and Geary’s coefficient will be clarified and defined. One of theoretical findings is that Moran’s index is a characteristic parameter of spatial weight matrices, so the selection of weight functions is very significant for autocorrelation analysis of geographical systems. A case study of 29 Chinese cities in 2000 will be employed to validate the innovatory models and methods. This work is a methodological study, which will simplify the process of autocorrelation analysis. The results of this study will lay the foundation for the scaling analysis of spatial autocorrelation. PMID:23874592

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.

Monte Carlo errors with less errors

NASA Astrophysics Data System (ADS)

Wolff, Ulli; Alpha Collaboration

2004-01-01

We explain in detail how to estimate mean values and assess statistical errors for arbitrary functions of elementary observables in Monte Carlo simulations. The method is to estimate and sum the relevant autocorrelation functions, which is argued to produce more certain error estimates than binning techniques and hence to help toward a better exploitation of expensive simulations. An effective integrated autocorrelation time is computed which is suitable to benchmark efficiencies of simulation algorithms with regard to specific observables of interest. A Matlab code is offered for download that implements the method. It can also combine independent runs (replica) allowing to judge their consistency.

Characterization, parameter estimation, and aircraft response statistics of atmospheric turbulence

NASA Technical Reports Server (NTRS)

Mark, W. D.

1981-01-01

A nonGaussian three component model of atmospheric turbulence is postulated that accounts for readily observable features of turbulence velocity records, their autocorrelation functions, and their spectra. Methods for computing probability density functions and mean exceedance rates of a generic aircraft response variable are developed using nonGaussian turbulence characterizations readily extracted from velocity recordings. A maximum likelihood method is developed for optimal estimation of the integral scale and intensity of records possessing von Karman transverse of longitudinal spectra. Formulas for the variances of such parameter estimates are developed. The maximum likelihood and least-square approaches are combined to yield a method for estimating the autocorrelation function parameters of a two component model for turbulence.

Skewness, long-time memory, and non-stationarity: Application to leverage effect in financial time series

NASA Astrophysics Data System (ADS)

Roman, H. E.; Porto, M.; Dose, C.

2008-10-01

We analyze daily log-returns data for a set of 1200 stocks, taken from US stock markets, over a period of 2481 trading days (January 1996-November 2005). We estimate the degree of non-stationarity in daily market volatility employing a polynomial fit, used as a detrending function. We find that the autocorrelation function of absolute detrended log-returns departs strongly from the corresponding original data autocorrelation function, while the observed leverage effect depends only weakly on trends. Such effect is shown to occur when both skewness and long-time memory are simultaneously present. A fractional derivative random walk model is discussed yielding a quantitative agreement with the empirical results.

Diffusion in Deterministic Interacting Lattice Systems

NASA Astrophysics Data System (ADS)

Medenjak, Marko; Klobas, Katja; Prosen, Tomaž

2017-09-01

We study reversible deterministic dynamics of classical charged particles on a lattice with hard-core interaction. It is rigorously shown that the system exhibits three types of transport phenomena, ranging from ballistic, through diffusive to insulating. By obtaining an exact expressions for the current time-autocorrelation function we are able to calculate the linear response transport coefficients, such as the diffusion constant and the Drude weight. Additionally, we calculate the long-time charge profile after an inhomogeneous quench and obtain diffusive profilewith the Green-Kubo diffusion constant. Exact analytical results are corroborated by Monte Carlo simulations.

Multiscale molecular dynamics/hydrodynamics implementation of two dimensional "Mercedes Benz" water model

NASA Astrophysics Data System (ADS)

Scukins, A.; Nerukh, D.; Pavlov, E.; Karabasov, S.; Markesteijn, A.

2015-09-01

A multiscale Molecular Dynamics/Hydrodynamics implementation of the 2D Mercedes Benz (MB or BN2D) [1] water model is developed and investigated. The concept and the governing equations of multiscale coupling together with the results of the two-way coupling implementation are reported. The sensitivity of the multiscale model for obtaining macroscopic and microscopic parameters of the system, such as macroscopic density and velocity fluctuations, radial distribution and velocity autocorrelation functions of MB particles, is evaluated. Critical issues for extending the current model to large systems are discussed.

The time series approach to short term load forecasting

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

Hagan, M.T.; Behr, S.M.

The application of time series analysis methods to load forecasting is reviewed. It is shown than Box and Jenkins time series models, in particular, are well suited to this application. The logical and organized procedures for model development using the autocorrelation function make these models particularly attractive. One of the drawbacks of these models is the inability to accurately represent the nonlinear relationship between load and temperature. A simple procedure for overcoming this difficulty is introduced, and several Box and Jenkins models are compared with a forecasting procedure currently used by a utility company.

Microchannel plate cross-talk mitigation for spatial autocorrelation measurements

NASA Astrophysics Data System (ADS)

Lipka, Michał; Parniak, Michał; Wasilewski, Wojciech

2018-05-01

Microchannel plates (MCP) are the basis for many spatially resolved single-particle detectors such as ICCD or I-sCMOS cameras employing image intensifiers (II), MCPs with delay-line anodes for the detection of cold gas particles or Cherenkov radiation detectors. However, the spatial characterization provided by an MCP is severely limited by cross-talk between its microchannels, rendering MCP and II ill-suited for autocorrelation measurements. Here, we present a cross-talk subtraction method experimentally exemplified for an I-sCMOS based measurement of pseudo-thermal light second-order intensity autocorrelation function at the single-photon level. The method merely requires a dark counts measurement for calibration. A reference cross-correlation measurement certifies the cross-talk subtraction. While remaining universal for MCP applications, the presented cross-talk subtraction, in particular, simplifies quantum optical setups. With the possibility of autocorrelation measurements, the signal needs no longer to be divided into two camera regions for a cross-correlation measurement, reducing the experimental setup complexity and increasing at least twofold the simultaneously employable camera sensor region.

Numerical analysis for finite-range multitype stochastic contact financial market dynamic systems

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

Yang, Ge; Wang, Jun; Fang, Wen, E-mail: fangwen@bjtu.edu.cn

In an attempt to reproduce and study the dynamics of financial markets, a random agent-based financial price model is developed and investigated by the finite-range multitype contact dynamic system, in which the interaction and dispersal of different types of investment attitudes in a stock market are imitated by viruses spreading. With different parameters of birth rates and finite-range, the normalized return series are simulated by Monte Carlo simulation method and numerical studied by power-law distribution analysis and autocorrelation analysis. To better understand the nonlinear dynamics of the return series, a q-order autocorrelation function and a multi-autocorrelation function are also definedmore » in this work. The comparisons of statistical behaviors of return series from the agent-based model and the daily historical market returns of Shanghai Composite Index and Shenzhen Component Index indicate that the proposed model is a reasonable qualitative explanation for the price formation process of stock market systems.« less

Method to manage integration error in the Green-Kubo method.

PubMed

Oliveira, Laura de Sousa; Greaney, P Alex

2017-02-01

The Green-Kubo method is a commonly used approach for predicting transport properties in a system from equilibrium molecular dynamics simulations. The approach is founded on the fluctuation dissipation theorem and relates the property of interest to the lifetime of fluctuations in its thermodynamic driving potential. For heat transport, the lattice thermal conductivity is related to the integral of the autocorrelation of the instantaneous heat flux. A principal source of error in these calculations is that the autocorrelation function requires a long averaging time to reduce remnant noise. Integrating the noise in the tail of the autocorrelation function becomes conflated with physically important slow relaxation processes. In this paper we present a method to quantify the uncertainty on transport properties computed using the Green-Kubo formulation based on recognizing that the integrated noise is a random walk, with a growing envelope of uncertainty. By characterizing the noise we can choose integration conditions to best trade off systematic truncation error with unbiased integration noise, to minimize uncertainty for a given allocation of computational resources.

Method to manage integration error in the Green-Kubo method

NASA Astrophysics Data System (ADS)

Oliveira, Laura de Sousa; Greaney, P. Alex

2017-02-01

The Green-Kubo method is a commonly used approach for predicting transport properties in a system from equilibrium molecular dynamics simulations. The approach is founded on the fluctuation dissipation theorem and relates the property of interest to the lifetime of fluctuations in its thermodynamic driving potential. For heat transport, the lattice thermal conductivity is related to the integral of the autocorrelation of the instantaneous heat flux. A principal source of error in these calculations is that the autocorrelation function requires a long averaging time to reduce remnant noise. Integrating the noise in the tail of the autocorrelation function becomes conflated with physically important slow relaxation processes. In this paper we present a method to quantify the uncertainty on transport properties computed using the Green-Kubo formulation based on recognizing that the integrated noise is a random walk, with a growing envelope of uncertainty. By characterizing the noise we can choose integration conditions to best trade off systematic truncation error with unbiased integration noise, to minimize uncertainty for a given allocation of computational resources.

Possible Noise Nature of Elsässer Variable z- in Highly Alfvénic Solar Wind Fluctuations

NASA Astrophysics Data System (ADS)

Wang, X.; Tu, C.-Y.; He, J.-S.; Wang, L.-H.; Yao, S.; Zhang, L.

2018-01-01

It has been a long-standing debate on the nature of Elsässer variable z- observed in the solar wind fluctuations. It is widely believed that z- represents inward propagating Alfvén waves and interacts nonlinearly with z+ (outward propagating Alfvén waves) to generate energy cascade. However, z- variations sometimes show a feature of convective structures. Here we present a new data analysis on autocorrelation functions of z- in order to get some definite information on its nature. We find that there is usually a large drop on the z- autocorrelation function when the solar wind fluctuations are highly Alfvénic. The large drop observed by Helios 2 spacecraft near 0.3 AU appears at the first nonzero time lag τ = 81 s, where the value of the autocorrelation coefficient drops to 25%-65% of that at τ = 0 s. Beyond the first nonzero time lag, the autocorrelation coefficient decreases gradually to zero. The drop of z- correlation function also appears in the Wind observations near 1 AU. These features of the z- correlation function may suggest that z- fluctuations consist of two components: high-frequency white noise and low-frequency pseudo structures, which correspond to flat and steep parts of z- power spectrum, respectively. This explanation is confirmed by doing a simple test on an artificial time series, which is obtained from the superposition of a random data series on its smoothed sequence. Our results suggest that in highly Alfvénic fluctuations, z- may not contribute importantly to the interactions with z+ to produce energy cascade.

Time correlation functions of simple liquids: A new insight on the underlying dynamical processes

NASA Astrophysics Data System (ADS)

Garberoglio, Giovanni; Vallauri, Renzo; Bafile, Ubaldo

2018-05-01

Extensive molecular dynamics simulations of liquid sodium have been carried out to evaluate correlation functions of several dynamical quantities. We report the results of a novel analysis of the longitudinal and transverse correlation functions obtained by evaluating directly their self- and distinct contributions at different wavevectors k. It is easily recognized that the self-contribution remains close to its k → 0 limit, which turns out to be exactly the autocorrelation function of the single particle velocity. The wavevector dependence of the longitudinal and transverse spectra and their self- and distinct parts is also presented. By making use of the decomposition of the velocity autocorrelation spectrum in terms of longitudinal and transverse parts, our analysis is able to recognize the effect of different dynamical processes in different frequency ranges.

Phase-dependent noise in Josephson junctions

NASA Astrophysics Data System (ADS)

Sheldon, Forrest; Peotta, Sebastiano; Di Ventra, Massimiliano

2018-03-01

In addition to the usual superconducting current, Josephson junctions (JJs) support a phase-dependent conductance related to the retardation effect of tunneling quasi-particles. This introduces a dissipative current with a memory-resistive (memristive) character that should also affect the current noise. By means of the microscopic theory of tunnel junctions we compute the complete current autocorrelation function of a Josephson tunnel junction and show that this memristive component gives rise to both a previously noted phase-dependent thermal noise, and an undescribed non-stationary, phase-dependent dynamic noise. As experiments are approaching ranges in which these effects may be observed, we examine the form and magnitude of these processes. Their phase dependence can be realized experimentally as a hysteresis effect and may be used to probe defects present in JJ based qubits and in other superconducting electronics applications.

Assessment of drug-induced arrhythmic risk using limit cycle and autocorrelation analysis of human iPSC-cardiomyocyte contractility

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

Kirby, R. Jason

2016-08-15

Cardiac safety assays incorporating label-free detection of human stem-cell derived cardiomyocyte contractility provide human relevance and medium throughput screening to assess compound-induced cardiotoxicity. In an effort to provide quantitative analysis of the large kinetic datasets resulting from these real-time studies, we applied bioinformatic approaches based on nonlinear dynamical system analysis, including limit cycle analysis and autocorrelation function, to systematically assess beat irregularity. The algorithms were integrated into a software program to seamlessly generate results for 96-well impedance-based data. Our approach was validated by analyzing dose- and time-dependent changes in beat patterns induced by known proarrhythmic compounds and screening a cardiotoxicitymore » library to rank order compounds based on their proarrhythmic potential. We demonstrate a strong correlation for dose-dependent beat irregularity monitored by electrical impedance and quantified by autocorrelation analysis to traditional manual patch clamp potency values for hERG blockers. In addition, our platform identifies non-hERG blockers known to cause clinical arrhythmia. Our method provides a novel suite of medium-throughput quantitative tools for assessing compound effects on cardiac contractility and predicting compounds with potential proarrhythmia and may be applied to in vitro paradigms for pre-clinical cardiac safety evaluation. - Highlights: • Impedance-based monitoring of human iPSC-derived cardiomyocyte contractility • Limit cycle analysis of impedance data identifies aberrant oscillation patterns. • Nonlinear autocorrelation function quantifies beat irregularity. • Identification of hERG and non-hERG inhibitors with known risk of arrhythmia • Automated software processes limit cycle and autocorrelation analyses of 96w data.« less

Non-isotropic noise correlation in PET data reconstructed by FBP but not by OSEM demonstrated using auto-correlation function.

PubMed

Razifar, Pasha; Lubberink, Mark; Schneider, Harald; Långström, Bengt; Bengtsson, Ewert; Bergström, Mats

2005-05-13

BACKGROUND: Positron emission tomography (PET) is a powerful imaging technique with the potential of obtaining functional or biochemical information by measuring distribution and kinetics of radiolabelled molecules in a biological system, both in vitro and in vivo. PET images can be used directly or after kinetic modelling to extract quantitative values of a desired physiological, biochemical or pharmacological entity. Because such images are generally noisy, it is essential to understand how noise affects the derived quantitative values. A pre-requisite for this understanding is that the properties of noise such as variance (magnitude) and texture (correlation) are known. METHODS: In this paper we explored the pattern of noise correlation in experimentally generated PET images, with emphasis on the angular dependence of correlation, using the autocorrelation function (ACF). Experimental PET data were acquired in 2D and 3D acquisition mode and reconstructed by analytical filtered back projection (FBP) and iterative ordered subsets expectation maximisation (OSEM) methods. The 3D data was rebinned to a 2D dataset using FOurier REbinning (FORE) followed by 2D reconstruction using either FBP or OSEM. In synthetic images we compared the ACF results with those from covariance matrix. The results were illustrated as 1D profiles and also visualized as 2D ACF images. RESULTS: We found that the autocorrelation images from PET data obtained after FBP were not fully rotationally symmetric or isotropic if the object deviated from a uniform cylindrical radioactivity distribution. In contrast, similar autocorrelation images obtained after OSEM reconstruction were isotropic even when the phantom was not circular. Simulations indicated that the noise autocorrelation is non-isotropic in images created by FBP when the level of noise in projections is angularly variable. Comparison between 1D cross profiles on autocorrelation images obtained by FBP reconstruction and covariance matrices produced almost identical results in a simulation study. CONCLUSION: With asymmetric radioactivity distribution in PET, reconstruction using FBP, in contrast to OSEM, generates images in which the noise correlation is non-isotropic when the noise magnitude is angular dependent, such as in objects with asymmetric radioactivity distribution. In this respect, iterative reconstruction is superior since it creates isotropic noise correlations in the images.

Studies in astronomical time series analysis. III - Fourier transforms, autocorrelation functions, and cross-correlation functions of unevenly spaced data

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.

Molecular dynamics test of the Brownian description of Na(+) motion in water

NASA Technical Reports Server (NTRS)

Wilson, M. A.; Pohorille, A.; Pratt, L. R.

1985-01-01

The present paper provides the results of molecular dynamics calculations on a Na(+) ion in aqueous solution. Attention is given to the sodium-oxygen and sodium-hydrogen radial distribution functions, the velocity autocorrelation function for the Na(+) ion, the autocorrelation function of the force on the stationary ion, and the accuracy of Brownian motion assumptions which are basic to hydrodynamic models of ion dyanmics in solution. It is pointed out that the presented calculations provide accurate data for testing theories of ion dynamics in solution. The conducted tests show that it is feasible to calculate Brownian friction constants for ions in aqueous solutions. It is found that for Na(+) under the considered conditions the Brownian mobility is in error by only 60 percent.

Polarization-correlation study of biotissue multifractal structure

NASA Astrophysics Data System (ADS)

Olar, O. I.; Ushenko, A. G.

2003-09-01

This paper presents the results of polarization-correlation study of multifractal collagen structure of physiologically normal and pathologically changed tissues of women"s reproductive sphere and skin. The technique of polarization selection of coherent images of biotissues with further determination of their autocorrelation functions and spectral densities is suggested. The correlation-optical criteria of early diagnostics of appearance of pathological changes in the cases of myometry (forming the germ of fibromyoma) and skin (psoriasis) are determined. This study is directed to investigate the possibilities of recognition of pathological changes of biotissue morphological structure by determining the polarization-dependent autocorrelation functions (ACF) and corresponding spectral densities of tissue coherent images.

Polarization-correlation investigation of biotissue multifractal structure and diagnostics of its pathological change

NASA Astrophysics Data System (ADS)

Angelsky, Oleg V.; Pishak, Vasyl P.; Ushenko, Alexander G.; Burkovets, Dimitry N.; Pishak, Olga V.

2001-05-01

The paper presents the results of polarization-correlation investigation of multifractal collagen structure of physiologically normal and pathologically changed tissues of women's reproductive sphere and of skin. The technique of polarization selection of coherent biotissues' images followed by determination of their autocorrelation functions and spectral densities is suggested. The correlation- optical criteria of early diagnostics of pathological changes' appearance of myometry (forming of the germ of fibromyoma) and of skin (psoriasis) are determined. The present paper examines the possibilities of diagnostics of pathological changes of biotissues' morphological structure by means of determining the polarizationally filtered autocorrelation functions (ACF) and corresponding spectral densities of their coherent images.

Dynamical analyses of the time series for three foreign exchange rates

NASA Astrophysics Data System (ADS)

Kim, Sehyun; Kim, Soo Yong; Jung, Jae-Won; Kim, Kyungsik

2012-05-01

In this study, we investigate the multifractal properties of three foreign exchange rates (USD-KRW, USD-JPY, and EUR-USD) that are quoted with different economic scales. We estimate and analyze both the generalized Hurst exponent and the autocorrelation function in three foreign exchange rates. The USD-KRW is shown to have the strongest of the Hurst exponents when compared with the other two foreign exchange rates. In particular, the autocorrelation function of the USD-KRW has the largest memory behavior among three foreign exchange rates. It also exhibits a long-memory property in the first quarter, more than those in the other quarters.

Integrated autocorrelator based on superconducting nanowires.

PubMed

Sahin, Döndü; Gaggero, Alessandro; Hoang, Thang Ba; Frucci, Giulia; Mattioli, Francesco; Leoni, Roberto; Beetz, Johannes; Lermer, Matthias; Kamp, Martin; Höfling, Sven; Fiore, Andrea

2013-05-06

We demonstrate an integrated autocorrelator based on two superconducting single-photon detectors patterned on top of a GaAs ridge waveguide. This device enables the on-chip measurement of the second-order intensity correlation function g(2)(τ). A polarization-independent device quantum efficiency in the 1% range is reported, with a timing jitter of 88 ps at 1300 nm. g(2)(τ) measurements of continuous-wave and pulsed laser excitations are demonstrated with no measurable crosstalk within our measurement accuracy.

A Possible Application of Coherent Light Scattering on Biological Fluids

NASA Astrophysics Data System (ADS)

Chicea, Dan; Chicea, Liana Maria

2007-04-01

Human urine from both healthy patients and patients with different diseases was used as scattering medium in a coherent light scattering experiment. The time variation of the light intensity in the far field speckle image was acquired using a data acquisition system on a PC and a time series resulted for each sample. The autocorrelation function for each sample was calculated and the autocorrelation time was determined. The same samples were analyzed in a medical laboratory using the standard procedure. We found so far that the autocorrelation time is differently modified by the presence of pus, albumin, urobilin and sediments. The results suggest a fast procedure that can be used as laboratory test to detect the presence not of each individual component in suspensions but of big conglomerates as albumin, cylinders, oxalate crystals.

Damage detection and isolation via autocorrelation: a step toward passive sensing

NASA Astrophysics Data System (ADS)

Chang, Y. S.; Yuan, F. G.

2018-03-01

Passive sensing technique may eliminate the need of expending power from actuators and thus provide a means of developing a compact and simple structural health monitoring system. More importantly, it may provide a solution for monitoring the aircraft subjected to environmental loading from air flow during operation. In this paper, a non-contact auto-correlation based technique is exploited as a feasibility study for passive sensing application to detect damage and isolate the damage location. Its theoretical basis bears some resemblance to reconstructing Green's function from diffusive wavefield through cross-correlation. Localized high pressure air from air compressor are randomly and continuously applied on the one side surface of the aluminum panels through the air blow gun. A laser Doppler vibrometer (LDV) was used to scan a 90 mm × 90 mm area to create a 6 × 6 2D-array signals from the opposite side of the panels. The scanned signals were auto-correlated to reconstruct a "selfimpulse response" (or Green's function). The premise for stably reconstructing the accurate Green's function requires long sensing times. For a 609.6 mm × 609.6 mm flat aluminum panel, the sensing times roughly at least four seconds is sufficient to establish converged Green's function through correlation. For the integral stiffened aluminum panel, the geometrical features of the panel expedite the formation of the diffusive wavefield and thus shorten the sensing times. The damage is simulated by gluing a magnet onto the panels. Reconstructed Green's functions (RGFs) are used for damage detection and damage isolation based on an imaging condition with mean square deviation of the RGFs from the pristine and the damaged structure and the results are shown in color maps. The auto-correlation based technique is shown to consistently detect the simulated damage, image and isolate the damage in the structure subjected to high pressure air excitation. This technique may be transformed into passive sensing applied on the aircraft during operation.

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.

Asymptotic neutron scattering laws for anomalously diffusing quantum particles

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

Kneller, Gerald R.; Université d’Orléans, Chateau de la Source-Ave. du Parc Floral, 45067 Orléans; Synchrotron-SOLEIL, L’Orme de Merisiers, 91192 Gif-sur-Yvette

2016-07-28

The paper deals with a model-free approach to the analysis of quasielastic neutron scattering intensities from anomalously diffusing quantum particles. All quantities are inferred from the asymptotic form of their time-dependent mean square displacements which grow ∝t{sup α}, with 0 ≤ α < 2. Confined diffusion (α = 0) is here explicitly included. We discuss in particular the intermediate scattering function for long times and the Fourier spectrum of the velocity autocorrelation function for small frequencies. Quantum effects enter in both cases through the general symmetry properties of quantum time correlation functions. It is shown that the fractional diffusion constantmore » can be expressed by a Green-Kubo type relation involving the real part of the velocity autocorrelation function. The theory is exact in the diffusive regime and at moderate momentum transfers.« less

MD simulations of the formation of stable clusters in mixtures of alkaline salts and imidazolium-based ionic liquids.

PubMed

Méndez-Morales, Trinidad; Carrete, Jesús; Bouzón-Capelo, Silvia; Pérez-Rodríguez, Martín; Cabeza, Óscar; Gallego, Luis J; Varela, Luis M

2013-03-21

Structural and dynamical properties of room-temperature ionic liquids containing the cation 1-butyl-3-methylimidazolium ([BMIM](+)) and three different anions (hexafluorophosphate, [PF6](-), tetrafluoroborate, [BF4](-), and bis(trifluoromethylsulfonyl)imide, [NTf2](-)) doped with several molar fractions of lithium salts with a common anion at 298.15 K and 1 atm were investigated by means of molecular dynamics simulations. The effect of the size of the salt cation was also analyzed by comparing these results with those for mixtures of [BMIM][PF6] with NaPF6. Lithium/sodium solvation and ionic mobilities were analyzed via the study of radial distribution functions, coordination numbers, cage autocorrelation functions, mean-square displacements (including the analysis of both ballistic and diffusive regimes), self-diffusion coefficients of all the ionic species, velocity and current autocorrelation functions, and ionic conductivity in all the ionic liquid/salt systems. We found that lithium and sodium cations are strongly coordinated in two different positions with the anion present in the mixture. Moreover, [Li](+) and [Na](+) cations were found to form bonded-like, long-lived aggregates with the anions in their first solvation shell, which act as very stable kinetic entities within which a marked rattling motion of salt ions takes place. With very long MD simulation runs, this phenomenon is proved to be on the basis of the decrease of self-diffusion coefficients and ionic conductivities previously reported in experimental and computational results.

Estimation of Random Medium Parameters from 2D Post-Stack Seismic Data and Its Application in Seismic Inversion

NASA Astrophysics Data System (ADS)

Yang, X.; Zhu, P.; Gu, Y.; Xu, Z.

2015-12-01

Small scale heterogeneities of subsurface medium can be characterized conveniently and effectively using a few simple random medium parameters (RMP), such as autocorrelation length, angle and roughness factor, etc. The estimation of these parameters is significant in both oil reservoir prediction and metallic mine exploration. Poor accuracy and low stability existed in current estimation approaches limit the application of random medium theory in seismic exploration. This study focuses on improving the accuracy and stability of RMP estimation from post-stacked seismic data and its application in the seismic inversion. Experiment and theory analysis indicate that, although the autocorrelation of random medium is related to those of corresponding post-stacked seismic data, the relationship is obviously affected by the seismic dominant frequency, the autocorrelation length, roughness factor and so on. Also the error of calculation of autocorrelation in the case of finite and discrete model decreases the accuracy. In order to improve the precision of estimation of RMP, we design two improved approaches. Firstly, we apply region growing algorithm, which often used in image processing, to reduce the influence of noise in the autocorrelation calculated by the power spectrum method. Secondly, the orientation of autocorrelation is used as a new constraint in the estimation algorithm. The numerical experiments proved that it is feasible. In addition, in post-stack seismic inversion of random medium, the estimated RMP may be used to constrain inverse procedure and to construct the initial model. The experiment results indicate that taking inversed model as random medium and using relatively accurate estimated RMP to construct initial model can get better inversion result, which contained more details conformed to the actual underground medium.

Microfluidic volumetric flow determination using optical coherence tomography speckle: An autocorrelation approach

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

De Pretto, Lucas R., E-mail: lucas.de.pretto@usp.br; Nogueira, Gesse E. C.; Freitas, Anderson Z.

2016-04-28

Functional modalities of Optical Coherence Tomography (OCT) based on speckle analysis are emerging in the literature. We propose a simple approach to the autocorrelation of OCT signal to enable volumetric flow rate differentiation, based on decorrelation time. Our results show that this technique could distinguish flows separated by 3 μl/min, limited by the acquisition speed of the system. We further perform a B-scan of gradient flow inside a microchannel, enabling the visualization of the drag effect on the walls.

Geomagnetic storm under laboratory conditions: randomized experiment

NASA Astrophysics Data System (ADS)

Gurfinkel, Yu I.; Vasin, A. L.; Pishchalnikov, R. Yu; Sarimov, R. M.; Sasonko, M. L.; Matveeva, T. A.

2017-10-01

The influence of the previously recorded geomagnetic storm (GS) on human cardiovascular system and microcirculation has been studied under laboratory conditions. Healthy volunteers in lying position were exposed under two artificially created conditions: quiet (Q) and storm (S). The Q regime playbacks a noise-free magnetic field (MF) which is closed to the natural geomagnetic conditions on Moscow's latitude. The S regime playbacks the initially recorded 6-h geomagnetic storm which is repeated four times sequentially. The cardiovascular response to the GS impact was assessed by measuring capillary blood velocity (CBV) and blood pressure (BP) and by the analysis of the 24-h ECG recording. A storm-to-quiet ratio for the cardio intervals (CI) and the heart rate variability (HRV) was introduced in order to reveal the average over group significant differences of HRV. An individual sensitivity to the GS was estimated using the autocorrelation function analysis of the high-frequency (HF) part of the CI spectrum. The autocorrelation analysis allowed for detection a group of subjects of study which autocorrelation functions (ACF) react differently in the Q and S regimes of exposure.

Geomagnetic storm under laboratory conditions: randomized experiment.

PubMed

Gurfinkel, Yu I; Vasin, A L; Pishchalnikov, R Yu; Sarimov, R M; Sasonko, M L; Matveeva, T A

2018-04-01

The influence of the previously recorded geomagnetic storm (GS) on human cardiovascular system and microcirculation has been studied under laboratory conditions. Healthy volunteers in lying position were exposed under two artificially created conditions: quiet (Q) and storm (S). The Q regime playbacks a noise-free magnetic field (MF) which is closed to the natural geomagnetic conditions on Moscow's latitude. The S regime playbacks the initially recorded 6-h geomagnetic storm which is repeated four times sequentially. The cardiovascular response to the GS impact was assessed by measuring capillary blood velocity (CBV) and blood pressure (BP) and by the analysis of the 24-h ECG recording. A storm-to-quiet ratio for the cardio intervals (CI) and the heart rate variability (HRV) was introduced in order to reveal the average over group significant differences of HRV. An individual sensitivity to the GS was estimated using the autocorrelation function analysis of the high-frequency (HF) part of the CI spectrum. The autocorrelation analysis allowed for detection a group of subjects of study which autocorrelation functions (ACF) react differently in the Q and S regimes of exposure.

Sign reversals of the output autocorrelation function for the stochastic Bernoulli-Verhulst equation

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

Lumi, N., E-mail: Neeme.Lumi@tlu.ee; Mankin, R., E-mail: Romi.Mankin@tlu.ee

2015-10-28

We consider a stochastic Bernoulli-Verhulst equation as a model for population growth processes. The effect of fluctuating environment on the carrying capacity of a population is modeled as colored dichotomous noise. Relying on the composite master equation an explicit expression for the stationary autocorrelation function (ACF) of population sizes is found. On the basis of this expression a nonmonotonic decay of the ACF by increasing lag-time is shown. Moreover, in a certain regime of the noise parameters the ACF demonstrates anticorrelation as well as related sign reversals at some values of the lag-time. The conditions for the appearance of thismore » highly unexpected effect are also discussed.« less

Pathogenic changes of dispersion and contrast of coherent images of biotissues

NASA Astrophysics Data System (ADS)

Pishak, Olga V.

2002-02-01

The paper presents the results of polarization-correlation investigation of multifractal collagen structure of physiologically normal and pathologically changed tissues of women's reproductive sphere and of skin. The technique of polarization selection of coherent biotissues' images with the following determination of their autocorrelation functions and spectral densities is suggested. The correlation-optical criteria of early diagnostics of pathological changes' appearance of myometry (forming of the germ of fibromyoma) and of skin(psoriasis) are determined. The suggested paper is directed to investigation of the possibilities of pathological changes of biotissues' morphological structure by means of determining the polarizationally filtered autocorrelation functions (ACF) and corresponding spectral densities of their coherent images.

The calculation of transport properties in quantum liquids using the maximum entropy numerical analytic continuation method: Application to liquid para-hydrogen

PubMed Central

Rabani, Eran; Reichman, David R.; Krilov, Goran; Berne, Bruce J.

2002-01-01

We present a method based on augmenting an exact relation between a frequency-dependent diffusion constant and the imaginary time velocity autocorrelation function, combined with the maximum entropy numerical analytic continuation approach to study transport properties in quantum liquids. The method is applied to the case of liquid para-hydrogen at two thermodynamic state points: a liquid near the triple point and a high-temperature liquid. Good agreement for the self-diffusion constant and for the real-time velocity autocorrelation function is obtained in comparison to experimental measurements and other theoretical predictions. Improvement of the methodology and future applications are discussed. PMID:11830656

Stochastic modelling of the monthly average maximum and minimum temperature patterns in India 1981-2015

NASA Astrophysics Data System (ADS)

Narasimha Murthy, K. V.; Saravana, R.; Vijaya Kumar, K.

2018-04-01

The paper investigates the stochastic modelling and forecasting of monthly average maximum and minimum temperature patterns through suitable seasonal auto regressive integrated moving average (SARIMA) model for the period 1981-2015 in India. The variations and distributions of monthly maximum and minimum temperatures are analyzed through Box plots and cumulative distribution functions. The time series plot indicates that the maximum temperature series contain sharp peaks in almost all the years, while it is not true for the minimum temperature series, so both the series are modelled separately. The possible SARIMA model has been chosen based on observing autocorrelation function (ACF), partial autocorrelation function (PACF), and inverse autocorrelation function (IACF) of the logarithmic transformed temperature series. The SARIMA (1, 0, 0) × (0, 1, 1)12 model is selected for monthly average maximum and minimum temperature series based on minimum Bayesian information criteria. The model parameters are obtained using maximum-likelihood method with the help of standard error of residuals. The adequacy of the selected model is determined using correlation diagnostic checking through ACF, PACF, IACF, and p values of Ljung-Box test statistic of residuals and using normal diagnostic checking through the kernel and normal density curves of histogram and Q-Q plot. Finally, the forecasting of monthly maximum and minimum temperature patterns of India for the next 3 years has been noticed with the help of selected model.

Crustal thickness across the Trans-European Suture Zone from ambient noise autocorrelations

NASA Astrophysics Data System (ADS)

Becker, G.; Knapmeyer-Endrun, B.

2018-02-01

We derive autocorrelations from ambient seismic noise to image the reflectivity of the subsurface and to extract the Moho depth beneath the stations for two different data sets in Central Europe. The autocorrelations are calculated by smoothing the spectrum of the data in order to suppress high amplitude, narrow-band signals of industrial origin, applying a phase autocorrelation algorithm and time-frequency domain phase-weighted stacking. The stacked autocorrelation results are filtered and analysed predominantly in the frequency range of 1-2 Hz. Moho depth is automatically picked inside uncertainty windows obtained from prior information. The processing scheme we developed is applied to data from permanent seismic stations located in different geological provinces across Europe, with varying Moho depths between 25 and 50 km, and to the mainly short period temporary PASSEQ stations along seismic profile POLONAISE P4. The autocorrelation results are spatially and temporarily stable, but show a clear correlation with the existence of cultural noise. On average, a minimum of six months of data is needed to obtain stable results. The obtained Moho depth results are in good agreement with the subsurface model provided by seismic profiling, receiver function estimates and the European Moho depth map. In addition to extracting the Moho depth, it is possible to identify an intracrustal layer along the profile, again closely matching the seismic model. For more than half of the broad-band stations, another change in reflectivity within the mantle is observed and can be correlated with the lithosphere-asthenosphere boundary to the west and a mid-lithospheric discontinuity beneath the East European Craton. With the application of the developed autocorrelation processing scheme to different stations with varying crustal thicknesses, it is shown that Moho depth can be extracted independent of subsurface structure, when station coverage is low, when no strong seismic sources are present, and when only limited amounts of data are available.

Correlation range in a supercooled liquid via Green-Kubo expression for viscosity, local atomic stresses, and MD simulations

NASA Astrophysics Data System (ADS)

Levashov, Valentin A.; Egami, Takeshi; Morris, James R.

2009-03-01

We present a new approach to the issue of correlation range in supercooled liquids based on Green-Kubo expression for viscosity. The integrand of this expression is the average stress-stress autocorrelation function. This correlation function could be rewritten in terms of correlations among local atomic stresses at different times and distances. The features of the autocorrelation function decay with time depend on temperature and correlation range. Through this approach we can study the development of spatial correlation with time, thus directly addressing the question of dynamic heterogeneity. We performed MD simulations on a single component system of particles interacting through short range pair potential. Our results indicate that even above the crossover temperature correlations extend well beyond the nearest neighbors. Surprisingly we found that the system size effects exist even on relatively large systems. We also address the role of diffusion in decay of stress-stress correlation function.

How cosmic microwave background correlations at large angles relate to mass autocorrelations in space

NASA Technical Reports Server (NTRS)

Blumenthal, George R.; Johnston, Kathryn V.

1994-01-01

The Sachs-Wolfe effect is known to produce large angular scale fluctuations in the cosmic microwave background radiation (CMBR) due to gravitational potential fluctuations. We show how the angular correlation function of the CMBR can be expressed explicitly in terms of the mass autocorrelation function xi(r) in the universe. We derive analytic expressions for the angular correlation function and its multipole moments in terms of integrals over xi(r) or its second moment, J(sub 3)(r), which does not need to satisfy the sort of integral constraint that xi(r) must. We derive similar expressions for bulk flow velocity in terms of xi and J(sub 3). One interesting result that emerges directly from this analysis is that, for all angles theta, there is a substantial contribution to the correlation function from a wide range of distance r and that radial shape of this contribution does not vary greatly with angle.

Structure of the North Anatolian Fault Zone from the Auto-Correlation of Ambient Seismic Noise Recorded at a Dense Seismometer Array

NASA Astrophysics Data System (ADS)

Taylor, D. G.; Rost, S.; Houseman, G.

2015-12-01

In recent years the technique of cross-correlating the ambient seismic noise wavefield at two seismometers to reconstruct empirical Green's Functions for the determination of Earth structure has been a powerful tool to study the Earth's interior without earthquake or man-made sources. However, far less attention has been paid to using auto-correlations of seismic noise to reveal body wave reflections from interfaces in the subsurface. In principle, the Green's functions thus derived should be comparable to the Earth's impulse response to a co-located source and receiver. We use data from a dense seismic array (Dense Array for Northern Anatolia - DANA) deployed across the northern branch of the North Anatolian Fault Zone (NAFZ) in the region of the 1999 magnitude 7.6 Izmit earthquake in western Turkey. The NAFZ is a major strike-slip system that extends ~1200 km across northern Turkey and continues to pose a high level of seismic hazard, in particular to the mega-city of Istanbul. We construct reflection images for the entire crust and upper mantle over the ~35 km by 70 km footprint of the 70-station DANA array. Using auto-correlations of vertical and horizontal components of ground motion, both P- and S-wave velocity information can be retrieved from the wavefield to constrain crustal structure further to established methods. We show that clear P-wave reflections from the crust-mantle boundary (Moho) can be retrieved using the autocorrelation technique, indicating topography on the Moho on horizontal scales of less than 10 km. Offsets in crustal structure can be identified that seem to be correlated with the surface expression of the fault zone in the region. The combined analysis of auto-correlations using vertical and horizontal components will lead to further insight into the fault zone structure throughout the crust and upper mantle.

Statistical assessment of optical phase fluctuations through turbulent mixing layers

NASA Astrophysics Data System (ADS)

Gardner, Patrick J.; Roggemann, Michael C.; Welsh, Byron M.; Bowersox, Rodney D.

1995-09-01

A lateral shearing interferometer is used to measure the slope of perturbed wavefronts after propagating through turbulent shear flows. This provides a two-dimensional flow visualization technique which is nonintrusive. The slope measurements are used to reconstruct the phase of the turbulence-corrupted wave front. Experiments were performed on a plane shear mixing layer of helium and nitrogen gas at fixed velocities, for five locations in the flow development. The two gases, having a density ratio of approximately seven, provide an effective means of simulating compressible shear layers. Statistical autocorrelation functions and structure functions are computed on the reconstructed phase maps. The autocorrelation function results indicate that the turbulence-induced phase fluctuations are not wide-sense stationary. The structure functions exhibit statistical homogeneity, indicating the phase fluctuation are stationary in first increments. However, the turbulence-corrupted phase is not isotropic. A five-thirds power law is shown to fit one-dimensional, orthogonal slices of the structure function, with scaling coefficients related to the location in the flow.

The Error Structure of the SMAP Single and Dual Channel Soil Moisture Retrievals

NASA Astrophysics Data System (ADS)

Dong, Jianzhi; Crow, Wade T.; Bindlish, Rajat

2018-01-01

Knowledge of the temporal error structure for remotely sensed surface soil moisture retrievals can improve our ability to exploit them for hydrologic and climate studies. This study employs a triple collocation analysis to investigate both the total variance and temporal autocorrelation of errors in Soil Moisture Active and Passive (SMAP) products generated from two separate soil moisture retrieval algorithms, the vertically polarized brightness temperature-based single-channel algorithm (SCA-V, the current baseline SMAP algorithm) and the dual-channel algorithm (DCA). A key assumption made in SCA-V is that real-time vegetation opacity can be accurately captured using only a climatology for vegetation opacity. Results demonstrate that while SCA-V generally outperforms DCA, SCA-V can produce larger total errors when this assumption is significantly violated by interannual variability in vegetation health and biomass. Furthermore, larger autocorrelated errors in SCA-V retrievals are found in areas with relatively large vegetation opacity deviations from climatological expectations. This implies that a significant portion of the autocorrelated error in SCA-V is attributable to the violation of its vegetation opacity climatology assumption and suggests that utilizing a real (as opposed to climatological) vegetation opacity time series in the SCA-V algorithm would reduce the magnitude of autocorrelated soil moisture retrieval errors.

Bayesian Estimates of Autocorrelations in Single-Case Designs

ERIC Educational Resources Information Center

Shadish, William R.; Rindskopf, David M.; Hedges, Larry V.; Sullivan, Kristynn J.

2012-01-01

Researchers in the single-case design tradition have debated the size and importance of the observed autocorrelations in those designs. All of the past estimates of the autocorrelation in that literature have taken the observed autocorrelation estimates as the data to be used in the debate. However, estimates of the autocorrelation are subject to…

Improvement of photon correlation spectroscopy method for measuring nanoparticle size by using attenuated total reflectance.

PubMed

Krishtop, Victor; Doronin, Ivan; Okishev, Konstantin

2012-11-05

Photon correlation spectroscopy is an effective method for measuring nanoparticle sizes and has several advantages over alternative methods. However, this method suffers from a disadvantage in that its measuring accuracy reduces in the presence of convective flows of fluid containing nanoparticles. In this paper, we propose a scheme based on attenuated total reflectance in order to reduce the influence of convection currents. The autocorrelation function for the light-scattering intensity was found for this case, and it was shown that this method afforded a significant decrease in the time required to measure the particle sizes and an increase in the measuring accuracy.

Self-diffusion and conductivity in an ultracold strongly coupled plasma: Calculation by the method of molecular dynamics

NASA Astrophysics Data System (ADS)

Zelener, B. B.; Zelener, B. V.; Manykin, E. A.; Bronin, S. Ya; Bobrov, A. A.; Khikhlukha, D. R.

2018-01-01

We present results of calculations by the method of molecular dynamics of self-diffusion and conductivity of electron and ion components of ultracold plasma in a comparison with available theoretical and experimental data. For the ion self-diffusion coefficient, good agreement was obtained with experiments on ultracold plasma. The results of the calculation of self-diffusion also agree well with other calculations performed for the same values of the coupling parameter, but at high temperatures. The difference in the results of the conductivity calculations on the basis of the current autocorrelation function and on the basis of the diffusion coefficient is discussed.

Quantitative fluorescence correlation spectroscopy on DNA in living cells

NASA Astrophysics Data System (ADS)

Hodges, Cameron; Kafle, Rudra P.; Meiners, Jens-Christian

2017-02-01

FCS is a fluorescence technique conventionally used to study the kinetics of fluorescent molecules in a dilute solution. Being a non-invasive technique, it is now drawing increasing interest for the study of more complex systems like the dynamics of DNA or proteins in living cells. Unlike an ordinary dye solution, the dynamics of macromolecules like proteins or entangled DNA in crowded environments is often slow and subdiffusive in nature. This in turn leads to longer residence times of the attached fluorophores in the excitation volume of the microscope and artifacts from photobleaching abound that can easily obscure the signature of the molecular dynamics of interest and make quantitative analysis challenging.We discuss methods and procedures to make FCS applicable to quantitative studies of the dynamics of DNA in live prokaryotic and eukaryotic cells. The intensity autocorrelation is computed function from weighted arrival times of the photons on the detector that maximizes the information content while simultaneously correcting for the effect of photobleaching to yield an autocorrelation function that reflects only the underlying dynamics of the sample. This autocorrelation function in turn is used to calculate the mean square displacement of the fluorophores attached to DNA. The displacement data is more amenable to further quantitative analysis than the raw correlation functions. By using a suitable integral transform of the mean square displacement, we can then determine the viscoelastic moduli of the DNA in its cellular environment. The entire analysis procedure is extensively calibrated and validated using model systems and computational simulations.

A statistical physics view of pitch fluctuations in the classical music from Bach to Chopin: evidence for scaling.

PubMed

Liu, Lu; Wei, Jianrong; Zhang, Huishu; Xin, Jianhong; Huang, Jiping

2013-01-01

Because classical music has greatly affected our life and culture in its long history, it has attracted extensive attention from researchers to understand laws behind it. Based on statistical physics, here we use a different method to investigate classical music, namely, by analyzing cumulative distribution functions (CDFs) and autocorrelation functions of pitch fluctuations in compositions. We analyze 1,876 compositions of five representative classical music composers across 164 years from Bach, to Mozart, to Beethoven, to Mendelsohn, and to Chopin. We report that the biggest pitch fluctuations of a composer gradually increase as time evolves from Bach time to Mendelsohn/Chopin time. In particular, for the compositions of a composer, the positive and negative tails of a CDF of pitch fluctuations are distributed not only in power laws (with the scale-free property), but also in symmetry (namely, the probability of a treble following a bass and that of a bass following a treble are basically the same for each composer). The power-law exponent decreases as time elapses. Further, we also calculate the autocorrelation function of the pitch fluctuation. The autocorrelation function shows a power-law distribution for each composer. Especially, the power-law exponents vary with the composers, indicating their different levels of long-range correlation of notes. This work not only suggests a way to understand and develop music from a viewpoint of statistical physics, but also enriches the realm of traditional statistical physics by analyzing music.

Sub-femtosecond quantum dynamics of the strong-field ionization of water to the X ̃(2)B1 and Ã(2)A1 states of the cation.

PubMed

Jayachander Rao, B; Varandas, A J C

2015-03-07

Motivated by recent efforts to achieve sub-femtosecond structural resolution in various molecular systems, we have performed a femtosecond quantum dynamics study of the water cation in the X ̃(2)B1 and Ã(2)A1 electronic states. Autocorrelation functions for H2O(+) and D2O(+) are calculated for such electronic states by solving numerically the time-dependent Schrödinger equation. From the ratio of the squared autocorrelation functions of D2O(+) and H2O(+), the high-order harmonic generation signals are calculated. Substantial vibrational dynamics is found in the Ã(2)A1 state as compared to the one in X ̃(2)B1, which supports recent experimental findings of Farrell et al., Phys. Rev. Lett., 2011, 107, 083001. Maxima in the above ratio are also predicted at ∼1.1 fs and ∼1.6 fs for the X ̃(2)B1 and Ã(2)A1 states, respectively. The expectation values of the positions of the atoms in H2O(+) as a function of time reveal a strong excitation of the bending mode in the Ã(2)A1 state, which explains the observed vibrational dynamics. The peaks in the ratios of the squared autocorrelation functions are also explained in terms of the evolving geometries of the water cation.

Advanced Sine Wave Modulation of Continuous Wave Laser System for Atmospheric CO2 Differential Absorption Measurements

NASA Technical Reports Server (NTRS)

Campbell, Joel F.; Lin, Bing; Nehrir, Amin R.

2014-01-01

NASA Langley Research Center in collaboration with ITT Exelis have been experimenting with Continuous Wave (CW) laser absorption spectrometer (LAS) as a means of performing atmospheric CO2 column measurements from space to support the Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) mission.Because range resolving Intensity Modulated (IM) CW lidar techniques presented here rely on matched filter correlations, autocorrelation properties without side lobes or other artifacts are highly desirable since the autocorrelation function is critical for the measurements of lidar return powers, laser path lengths, and CO2 column amounts. In this paper modulation techniques are investigated that improve autocorrelation properties. The modulation techniques investigated in this paper include sine waves modulated by maximum length (ML) sequences in various hardware configurations. A CW lidar system using sine waves modulated by ML pseudo random noise codes is described, which uses a time shifting approach to separate channels and make multiple, simultaneous online/offline differential absorption measurements. Unlike the pure ML sequence, this technique is useful in hardware that is band pass filtered as the IM sine wave carrier shifts the main power band. Both amplitude and Phase Shift Keying (PSK) modulated IM carriers are investigated that exibit perfect autocorrelation properties down to one cycle per code bit. In addition, a method is presented to bandwidth limit the ML sequence based on a Gaussian filter implemented in terms of Jacobi theta functions that does not seriously degrade the resolution or introduce side lobes as a means of reducing aliasing and IM carrier bandwidth.

NMR spin-rotation relaxation and diffusion of methane

NASA Astrophysics Data System (ADS)

Singer, P. M.; Asthagiri, D.; Chapman, W. G.; Hirasaki, G. J.

2018-05-01

The translational diffusion-coefficient and the spin-rotation contribution to the 1H NMR relaxation rate for methane (CH4) are investigated using MD (molecular dynamics) simulations, over a wide range of densities and temperatures, spanning the liquid, supercritical, and gas phases. The simulated diffusion-coefficients agree well with measurements, without any adjustable parameters in the interpretation of the simulations. A minimization technique is developed to compute the angular velocity for non-rigid spherical molecules, which is used to simulate the autocorrelation function for spin-rotation interactions. With increasing diffusivity, the autocorrelation function shows increasing deviations from the single-exponential decay predicted by the Langevin theory for rigid spheres, and the deviations are quantified using inverse Laplace transforms. The 1H spin-rotation relaxation rate derived from the autocorrelation function using the "kinetic model" agrees well with measurements in the supercritical/gas phase, while the relaxation rate derived using the "diffusion model" agrees well with measurements in the liquid phase. 1H spin-rotation relaxation is shown to dominate over the MD-simulated 1H-1H dipole-dipole relaxation at high diffusivity, while the opposite is found at low diffusivity. At high diffusivity, the simulated spin-rotation correlation time agrees with the kinetic collision time for gases, which is used to derive a new expression for 1H spin-rotation relaxation, without any adjustable parameters.

nMoldyn: a program package for a neutron scattering oriented analysis of molecular dynamics simulations.

PubMed

Róg, T; Murzyn, K; Hinsen, K; Kneller, G R

2003-04-15

We present a new implementation of the program nMoldyn, which has been developed for the computation and decomposition of neutron scattering intensities from Molecular Dynamics trajectories (Comp. Phys. Commun 1995, 91, 191-214). The new implementation extends the functionality of the original version, provides a much more convenient user interface (both graphical/interactive and batch), and can be used as a tool set for implementing new analysis modules. This was made possible by the use of a high-level language, Python, and of modern object-oriented programming techniques. The quantities that can be calculated by nMoldyn are the mean-square displacement, the velocity autocorrelation function as well as its Fourier transform (the density of states) and its memory function, the angular velocity autocorrelation function and its Fourier transform, the reorientational correlation function, and several functions specific to neutron scattering: the coherent and incoherent intermediate scattering functions with their Fourier transforms, the memory function of the coherent scattering function, and the elastic incoherent structure factor. The possibility to compute memory function is a new and powerful feature that allows to relate simulation results to theoretical studies. Copyright 2003 Wiley Periodicals, Inc. J Comput Chem 24: 657-667, 2003

Forecasting coconut production in the Philippines with ARIMA model

NASA Astrophysics Data System (ADS)

Lim, Cristina Teresa

2015-02-01

The study aimed to depict the situation of the coconut industry in the Philippines for the future years applying Autoregressive Integrated Moving Average (ARIMA) method. Data on coconut production, one of the major industrial crops of the country, for the period of 1990 to 2012 were analyzed using time-series methods. Autocorrelation (ACF) and partial autocorrelation functions (PACF) were calculated for the data. Appropriate Box-Jenkins autoregressive moving average model was fitted. Validity of the model was tested using standard statistical techniques. The forecasting power of autoregressive moving average (ARMA) model was used to forecast coconut production for the eight leading years.

The Superstatistical Nature and Interoccurrence Time of Atmospheric Mercury Concentration Fluctuations

EPA Science Inventory

The probability density function (PDF) of the time intervals between subsequent extreme events in atmospheric Hg0 concentration data series from different latitudes has been investigated. The Hg0 dynamic possesses a long-term memory autocorrelation function. Above a fixed thresh...

Diffraction and geometrical optical transfer functions: calculation time comparison

NASA Astrophysics Data System (ADS)

Díaz, José Antonio; Mahajan, Virendra N.

2017-08-01

In a recent paper, we compared the diffraction and geometrical optical transfer functions (OTFs) of an optical imaging system, and showed that the GOTF approximates the DOTF within 10% when a primary aberration is about two waves or larger [Appl. Opt., 55, 3241-3250 (2016)]. In this paper, we determine and compare the times to calculate the DOTF by autocorrelation or digital autocorrelation of the pupil function, and by a Fourier transform (FT) of the point-spread function (PSF); and the GOTF by a FT of the geometrical PSF and its approximation, the spot diagram. Our starting point for calculating the DOTF is the wave aberrations of the system in its pupil plane, and the ray aberrations in the image plane for the GOTF. The numerical results for primary aberrations and a typical imaging system show that the direct integrations are slow, but the calculation of the DOTF by a FT of the PSF is generally faster than the GOTF calculation by a FT of the spot diagram.

Time-series network analysis of civil aviation in Japan (1985-2005)

NASA Astrophysics Data System (ADS)

Michishita, Ryo; Xu, Bing; Yamada, Ikuho

2008-10-01

Due to the airline deregulation in 1985, a series of new airport developments in the 1990s and 2000s, and the reorganization of airline companies in the 2000s, Japan's air passenger transportation has been dramatically altered in the last two decades in many ways. In this paper, the authors examine how the network and flow structures of domestic air passenger transportation in Japan have geographically changed since 1985. For this purpose, passenger flow data in 1985, 1995, and 2005 were extracted from the Air Transportation Statistical Survey conducted by the Ministry of Land, Infrastructure and Transport, Japan. First, national and regional hub airports are identified via dominant flow and hub function analysis. Then the roles of the hub airports and individual connections over the network are examined with respect to their spatial and network autocorrelations. Spatial and network autocorrelations were evaluated both globally and locally using Moran's I and LISA statistics. The passenger flow data were first examined as a whole and then divided into 3 airline-based categories. Dominant flow and hub function enabled us to detect the hub airports. Structural processes of the hub-and-spoke network were confirmed in each airline through spatial autocorrelation analysis. Network autocorrelation analysis showed that all airlines ingeniously optimized their networks by connecting their routes with large numbers of passengers to other routes with large numbers of passengers, and routes with small numbers of passengers to other routes with small numbers of passengers. The effects of political events and the changes in the strategies of each airline on the whole networks were strongly reflected in the results of this study.

Capturing the effect of [PF3(C2F5)3]-vs. [PF6]-, flexible anion vs. rigid, and scaled charge vs. unit on the transport properties of [bmim]+-based ionic liquids: a comparative MD study.

PubMed

Kowsari, Mohammad H; Ebrahimi, Soraya

2018-05-16

Comprehensive molecular dynamics simulations are performed to study the average single-particle dynamics and the transport properties of 1-butyl-3-methylimidazolium hexafluorophosphate, [bmim][PF6], and 1-butyl-3-methylimidazolium tris(pentafluoroethyl)trifluorophosphate, [bmim][FAP], ionic liquids (ILs) at 400 K. We applied one of the most widely used nonpolarizable all-atom force fields for ILs, both with the original unit (±1) charges on each ion and with the partial charges uniformly scaled to 80-85%, taking into account the average polarizability and tracing the experimentally compatible transport properties. In all simulations, [bmim]+ was considered to be flexible, while the effect of a flexible vs. rigid structure of the anions and the effect of two applied charge sets on the calculated properties were separately investigated in detail. The simulation results showed that replacing [PF6]- with [FAP]-, considering anion flexibility, and applying the charge-scaled model significantly enhanced the ionic self-diffusion, ionic conductivity, inverse viscosity, and hyper anion preference (HAP). Both of the calculated self-diffusion coefficients from the long-time linear slope of the mean-square displacement (MSD) and from the integration of the velocity autocorrelation function (VACF) for the centers of mass of the ions were used for evaluation of the ionic transference number, HAP, ideal Nernst-Einstein ionic conductivity (σNE), and the Stokes-Einstein viscosity. In addition, for quantification of the degree of complicated ionic association (known as the Nernst-Einstein deviation parameter, Δ) and ionicity phenomena in the two studied ILs, the ionic conductivity was determined more rigorously by the Green-Kubo integral of the electric-current autocorrelation function (ECACF), and then the σGK/σNE ratio was evaluated. It was found that the correlated motion of the (cationanion) neighbors in [bmim][FAP] is smaller than in [bmim][PF6]. The relaxation times of the normalized reorientational autocorrelation functions were computed to gain a deep, molecular-level insight into the rotational motion of the ions. The geometric shape of the ion is a key factor in determining its reorientational dynamics. [bmim]+ shows faster translational and slower rotational dynamics in contrast to [PF6]-.

From fast fluorescence imaging to molecular diffusion law on live cell membranes in a commercial microscope.

PubMed

Di Rienzo, Carmine; Gratton, Enrico; Beltram, Fabio; Cardarelli, Francesco

2014-10-09

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn't need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on µm-sized membrane regions in the micro-to-milli-second time range.

Temporal and spatiotemporal autocorrelation of daily concentrations of Alnus, Betula, and Corylus pollen in Poland.

PubMed

Nowosad, J; Stach, A; Kasprzyk, I; Grewling, Ł; Latałowa, M; Puc, M; Myszkowska, D; Weryszko-Chmielewska, E; Piotrowska-Weryszko, K; Chłopek, K; Majkowska-Wojciechowska, B; Uruska, A

The aim of the study was to determine the characteristics of temporal and space-time autocorrelation of pollen counts of Alnus , Betula , and Corylus in the air of eight cities in Poland. Daily average pollen concentrations were monitored over 8 years (2001-2005 and 2009-2011) using Hirst-designed volumetric spore traps. The spatial and temporal coherence of data was investigated using the autocorrelation and cross-correlation functions. The calculation and mathematical modelling of 61 correlograms were performed for up to 25 days back. The study revealed an association between temporal variations in Alnus , Betula , and Corylus pollen counts in Poland and three main groups of factors such as: (1) air mass exchange after the passage of a single weather front (30-40 % of pollen count variation); (2) long-lasting factors (50-60 %); and (3) random factors, including diurnal variations and measurements errors (10 %). These results can help to improve the quality of forecasting models.

Building a three-dimensional model of CYP2C9 inhibition using the Autocorrelator: an autonomous model generator.

PubMed

Lardy, Matthew A; Lebrun, Laurie; Bullard, Drew; Kissinger, Charles; Gobbi, Alberto

2012-05-25

In modern day drug discovery campaigns, computational chemists have to be concerned not only about improving the potency of molecules but also reducing any off-target ADMET activity. There are a plethora of antitargets that computational chemists may have to consider. Fortunately many antitargets have crystal structures deposited in the PDB. These structures are immediately useful to our Autocorrelator: an automated model generator that optimizes variables for building computational models. This paper describes the use of the Autocorrelator to construct high quality docking models for cytochrome P450 2C9 (CYP2C9) from two publicly available crystal structures. Both models result in strong correlation coefficients (R² > 0.66) between the predicted and experimental determined log(IC₅₀) values. Results from the two models overlap well with each other, converging on the same scoring function, deprotonated charge state, and predicted the binding orientation for our collection of molecules.

Real-time autocorrelator for fluorescence correlation spectroscopy based on graphical-processor-unit architecture: method, implementation, and comparative studies

NASA Astrophysics Data System (ADS)

Laracuente, Nicholas; Grossman, Carl

2013-03-01

We developed an algorithm and software to calculate autocorrelation functions from real-time photon-counting data using the fast, parallel capabilities of graphical processor units (GPUs). Recent developments in hardware and software have allowed for general purpose computing with inexpensive GPU hardware. These devices are more suited for emulating hardware autocorrelators than traditional CPU-based software applications by emphasizing parallel throughput over sequential speed. Incoming data are binned in a standard multi-tau scheme with configurable points-per-bin size and are mapped into a GPU memory pattern to reduce time-expensive memory access. Applications include dynamic light scattering (DLS) and fluorescence correlation spectroscopy (FCS) experiments. We ran the software on a 64-core graphics pci card in a 3.2 GHz Intel i5 CPU based computer running Linux. FCS measurements were made on Alexa-546 and Texas Red dyes in a standard buffer (PBS). Software correlations were compared to hardware correlator measurements on the same signals. Supported by HHMI and Swarthmore College

Probabilistic density function method for nonlinear dynamical systems driven by colored noise.

PubMed

Barajas-Solano, David A; Tartakovsky, Alexandre M

2016-05-01

We present a probability density function (PDF) method for a system of nonlinear stochastic ordinary differential equations driven by colored noise. The method provides an integrodifferential equation for the temporal evolution of the joint PDF of the system's state, which we close by means of a modified large-eddy-diffusivity (LED) closure. In contrast to the classical LED closure, the proposed closure accounts for advective transport of the PDF in the approximate temporal deconvolution of the integrodifferential equation. In addition, we introduce the generalized local linearization approximation for deriving a computable PDF equation in the form of a second-order partial differential equation. We demonstrate that the proposed closure and localization accurately describe the dynamics of the PDF in phase space for systems driven by noise with arbitrary autocorrelation time. We apply the proposed PDF method to analyze a set of Kramers equations driven by exponentially autocorrelated Gaussian colored noise to study nonlinear oscillators and the dynamics and stability of a power grid. Numerical experiments show the PDF method is accurate when the noise autocorrelation time is either much shorter or longer than the system's relaxation time, while the accuracy decreases as the ratio of the two timescales approaches unity. Similarly, the PDF method accuracy decreases with increasing standard deviation of the noise.

Boundary versus bulk behavior of time-dependent correlation functions in one-dimensional quantum systems

NASA Astrophysics Data System (ADS)

Eliëns, I. S.; Ramos, F. B.; Xavier, J. C.; Pereira, R. G.

2016-05-01

We study the influence of reflective boundaries on time-dependent responses of one-dimensional quantum fluids at zero temperature beyond the low-energy approximation. Our analysis is based on an extension of effective mobile impurity models for nonlinear Luttinger liquids to the case of open boundary conditions. For integrable models, we show that boundary autocorrelations oscillate as a function of time with the same frequency as the corresponding bulk autocorrelations. This frequency can be identified as the band edge of elementary excitations. The amplitude of the oscillations decays as a power law with distinct exponents at the boundary and in the bulk, but boundary and bulk exponents are determined by the same coupling constant in the mobile impurity model. For nonintegrable models, we argue that the power-law decay of the oscillations is generic for autocorrelations in the bulk, but turns into an exponential decay at the boundary. Moreover, there is in general a nonuniversal shift of the boundary frequency in comparison with the band edge of bulk excitations. The predictions of our effective field theory are compared with numerical results obtained by time-dependent density matrix renormalization group (tDMRG) for both integrable and nonintegrable critical spin-S chains with S =1 /2 , 1, and 3 /2 .

Role of internal motions and molecular geometry on the NMR relaxation of hydrocarbons

NASA Astrophysics Data System (ADS)

Singer, P. M.; Asthagiri, D.; Chen, Z.; Valiya Parambathu, A.; Hirasaki, G. J.; Chapman, W. G.

2018-04-01

The role of internal motions and molecular geometry on 1H NMR relaxation rates in liquid-state hydrocarbons is investigated using MD (molecular dynamics) simulations of the autocorrelation functions for intramolecular and intermolecular 1H-1H dipole-dipole interactions. The effects of molecular geometry and internal motions on the functional form of the autocorrelation functions are studied by comparing symmetric molecules such as neopentane and benzene to corresponding straight-chain alkanes n-pentane and n-hexane, respectively. Comparison of rigid versus flexible molecules shows that internal motions cause the intramolecular and intermolecular correlation-times to get significantly shorter, and the corresponding relaxation rates to get significantly smaller, especially for longer-chain n-alkanes. Site-by-site simulations of 1H's across the chains indicate significant variations in correlation times and relaxation rates across the molecule, and comparison with measurements reveals insights into cross-relaxation effects. Furthermore, the simulations reveal new insights into the relative strength of intramolecular versus intermolecular relaxation as a function of internal motions, as a function of molecular geometry, and on a site-by-site basis across the chain.

Contribution to viscosity from the structural relaxation via the atomic scale Green-Kubo stress correlation function.

PubMed

Levashov, V A

2017-11-14

We studied the connection between the structural relaxation and viscosity for a binary model of repulsive particles in the supercooled liquid regime. The used approach is based on the decomposition of the macroscopic Green-Kubo stress correlation function into the correlation functions between the atomic level stresses. Previously we used the approach to study an iron-like single component system of particles. The role of vibrational motion has been addressed through the demonstration of the relationship between viscosity and the shear waves propagating over large distances. In our previous considerations, however, we did not discuss the role of the structural relaxation. Here we suggest that the contribution to viscosity from the structural relaxation can be taken into account through the consideration of the contribution from the atomic stress auto-correlation term only. This conclusion, however, does not mean that only the auto-correlation term represents the contribution to viscosity from the structural relaxation. Previously the role of the structural relaxation for viscosity has been addressed through the considerations of the transitions between inherent structures and within the mode-coupling theory by other authors. In the present work, we study the structural relaxation through the considerations of the parent liquid and the atomic level stress correlations in it. The comparison with the results obtained on the inherent structures also is made. Our current results suggest, as our previous observations, that in the supercooled liquid regime, the vibrational contribution to viscosity extends over the times that are much larger than the Einstein's vibrational period and much larger than the times that it takes for the shear waves to propagate over the model systems. Besides addressing the atomic level shear stress correlations, we also studied correlations between the atomic level pressure elements.

A longitudinal model for functional connectivity networks using resting-state fMRI.

PubMed

Hart, Brian; Cribben, Ivor; Fiecas, Mark

2018-06-04

Many neuroimaging studies collect functional magnetic resonance imaging (fMRI) data in a longitudinal manner. However, the current fMRI literature lacks a general framework for analyzing functional connectivity (FC) networks in fMRI data obtained from a longitudinal study. In this work, we build a novel longitudinal FC model using a variance components approach. First, for all subjects' visits, we account for the autocorrelation inherent in the fMRI time series data using a non-parametric technique. Second, we use a generalized least squares approach to estimate 1) the within-subject variance component shared across the population, 2) the baseline FC strength, and 3) the FC's longitudinal trend. Our novel method for longitudinal FC networks seeks to account for the within-subject dependence across multiple visits, the variability due to the subjects being sampled from a population, and the autocorrelation present in fMRI time series data, while restricting the number of parameters in order to make the method computationally feasible and stable. We develop a permutation testing procedure to draw valid inference on group differences in the baseline FC network and change in FC over longitudinal time between a set of patients and a comparable set of controls. To examine performance, we run a series of simulations and apply the model to longitudinal fMRI data collected from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Overall, we found no difference in the global FC network between Alzheimer's disease patients and healthy controls, but did find differing local aging patterns in the FC between the left hippocampus and the posterior cingulate cortex. Copyright © 2018 Elsevier Inc. All rights reserved.

Contribution to viscosity from the structural relaxation via the atomic scale Green-Kubo stress correlation function

NASA Astrophysics Data System (ADS)

Levashov, V. A.

2017-11-01

We studied the connection between the structural relaxation and viscosity for a binary model of repulsive particles in the supercooled liquid regime. The used approach is based on the decomposition of the macroscopic Green-Kubo stress correlation function into the correlation functions between the atomic level stresses. Previously we used the approach to study an iron-like single component system of particles. The role of vibrational motion has been addressed through the demonstration of the relationship between viscosity and the shear waves propagating over large distances. In our previous considerations, however, we did not discuss the role of the structural relaxation. Here we suggest that the contribution to viscosity from the structural relaxation can be taken into account through the consideration of the contribution from the atomic stress auto-correlation term only. This conclusion, however, does not mean that only the auto-correlation term represents the contribution to viscosity from the structural relaxation. Previously the role of the structural relaxation for viscosity has been addressed through the considerations of the transitions between inherent structures and within the mode-coupling theory by other authors. In the present work, we study the structural relaxation through the considerations of the parent liquid and the atomic level stress correlations in it. The comparison with the results obtained on the inherent structures also is made. Our current results suggest, as our previous observations, that in the supercooled liquid regime, the vibrational contribution to viscosity extends over the times that are much larger than the Einstein's vibrational period and much larger than the times that it takes for the shear waves to propagate over the model systems. Besides addressing the atomic level shear stress correlations, we also studied correlations between the atomic level pressure elements.

Identification of Piecewise Linear Uniform Motion Blur

NASA Astrophysics Data System (ADS)

Patanukhom, Karn; Nishihara, Akinori

A motion blur identification scheme is proposed for nonlinear uniform motion blurs approximated by piecewise linear models which consist of more than one linear motion component. The proposed scheme includes three modules that are a motion direction estimator, a motion length estimator and a motion combination selector. In order to identify the motion directions, the proposed scheme is based on a trial restoration by using directional forward ramp motion blurs along different directions and an analysis of directional information via frequency domain by using a Radon transform. Autocorrelation functions of image derivatives along several directions are employed for estimation of the motion lengths. A proper motion combination is identified by analyzing local autocorrelation functions of non-flat component of trial restored results. Experimental examples of simulated and real world blurred images are given to demonstrate a promising performance of the proposed scheme.

Spatial and temporal changes in the structure of groundwater nitrate concentration time series (1935 1999) as demonstrated by autoregressive modelling

NASA Astrophysics Data System (ADS)

Jones, A. L.; Smart, P. L.

2005-08-01

Autoregressive modelling is used to investigate the internal structure of long-term (1935-1999) records of nitrate concentration for five karst springs in the Mendip Hills. There is a significant short term (1-2 months) positive autocorrelation at three of the five springs due to the availability of sufficient nitrate within the soil store to maintain concentrations in winter recharge for several months. The absence of short term (1-2 months) positive autocorrelation in the other two springs is due to the marked contrast in land use between the limestone and swallet parts of the catchment, rapid concentrated recharge from the latter causing short term switching in the dominant water source at the spring and thus fluctuating nitrate concentrations. Significant negative autocorrelation is evident at lags varying from 4 to 7 months through to 14-22 months for individual springs, with positive autocorrelation at 19-20 months at one site. This variable timing is explained by moderation of the exhaustion effect in the soil by groundwater storage, which gives longer residence times in large catchments and those with a dominance of diffuse flow. The lags derived from autoregressive modelling may therefore provide an indication of average groundwater residence times. Significant differences in the structure of the autocorrelation function for successive 10-year periods are evident at Cheddar Spring, and are explained by the effect the ploughing up of grasslands during the Second World War and increased fertiliser usage on available nitrogen in the soil store. This effect is moderated by the influence of summer temperatures on rates of mineralization, and of both summer and winter rainfall on the timing and magnitude of nitrate leaching. The pattern of nitrate leaching also appears to have been perturbed by the 1976 drought.

Environmental drivers of spatial variation in whole-tree transpiration in an aspen-dominated upland-to-wetland forest gradient

NASA Astrophysics Data System (ADS)

Loranty, Michael M.; Mackay, D. Scott; Ewers, Brent E.; Adelman, Jonathan D.; Kruger, Eric L.

2008-02-01

Assumed representative center-of-stand measurements are typical inputs to models that scale forest transpiration to stand and regional extents. These inputs do not consider gradients in transpiration at stand boundaries or along moisture gradients and therefore potentially bias the large-scale estimates. We measured half-hourly sap flux (JS) for 173 trees in a spatially explicit cyclic sampling design across a topographically controlled gradient between a forested wetland and upland forest in northern Wisconsin. Our analyses focused on three dominant species in the site: quaking aspen (Populus tremuloides Michx), speckled alder (Alnus incana (DuRoi) Spreng), and white cedar (Thuja occidentalis L.). Sapwood area (AS) was used to scale JS to whole tree transpiration (EC). Because spatial patterns imply underlying processes, geostatistical analyses were employed to quantify patterns of spatial autocorrelation across the site. A simple Jarvis type model parameterized using a Monte Carlo sampling approach was used to simulate EC (EC-SIM). EC-SIM was compared with observed EC(EC-OBS) and found to reproduce both the temporal trends and spatial variance of canopy transpiration. EC-SIM was then used to examine spatial autocorrelation as a function of environmental drivers. We found no spatial autocorrelation in JS across the gradient from forested wetland to forested upland. EC was spatially autocorrelated and this was attributed to spatial variation in AS which suggests species spatial patterns are important for understanding spatial estimates of transpiration. However, the range of autocorrelation in EC-SIM decreased linearly with increasing vapor pressure deficit, implying that consideration of spatial variation in the sensitivity of canopy stomatal conductance to D is also key to accurately scaling up transpiration in space.

Using the thermal Gaussian approximation for the Boltzmann operator in semiclassical initial value time correlation functions.

PubMed

Liu, Jian; Miller, William H

2006-12-14

The thermal Gaussian approximation (TGA) recently developed by Frantsuzov et al. [Chem. Phys. Lett. 381, 117 (2003)] has been demonstrated to be a practical way for approximating the Boltzmann operator exp(-betaH) for multidimensional systems. In this paper the TGA is combined with semiclassical (SC) initial value representations (IVRs) for thermal time correlation functions. Specifically, it is used with the linearized SC-IVR (LSC-IVR, equivalent to the classical Wigner model), and the "forward-backward semiclassical dynamics" approximation developed by Shao and Makri [J. Phys. Chem. A 103, 7753 (1999); 103, 9749 (1999)]. Use of the TGA with both of these approximate SC-IVRs allows the oscillatory part of the IVR to be integrated out explicitly, providing an extremely simple result that is readily applicable to large molecular systems. Calculation of the force-force autocorrelation for a strongly anharmonic oscillator demonstrates its accuracy, and calculation of the velocity autocorrelation function (and thus the diffusion coefficient) of liquid neon demonstrates its applicability.

A comparison of chronologies from tree rings

Treesearch

Kurt H. Riitters

1990-01-01

Forty-five-year ring width index chronologies were estimated by five mean-value functions applied to 183 ring width series from four similar sites. The effects of autocorrelation on the comparisons among mean-value functions were explored by fitting box-Jenkins models to individual-tree index services prior to pooling (prewhitening), and to the pooled chronologies...

Vortex relaxation in type-II superconductors following current quenches

NASA Astrophysics Data System (ADS)

Chaturvedi, Harsh; Assi, Hiba; Dobramysl, Ulrich; Pleimling, Michel; Täuber, Uwe

2015-03-01

The mixed phase in type-II superconductors is characterized by the presence of mutually repulsive magnetic flux lines that are driven by external currents and pinned by point-like or extended material defects. We represent the disordered vortex system in the London limit by an elastic directed line model, whose relaxational dynamics we investigate numerically by means of Langevin Molecular Dynamics. We specifically study the effects of sudden changes of the driving current on the time evolution of the mean flux line gyration radius and the associated transverse displacement correlation functions. Upon quenching from the moving into the pinned glassy phase, we observe algebraically slow relaxation. The associated two-time height-autocorrelations display broken time translation invariance and can be described by a simple aging scaling form, albeit with non-universal scaling exponents. Research supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Materials Sciences and Engineering under Award DE-FG02-09ER46613.

Statistical properties of a filtered Poisson process with additive random noise: distributions, correlations and moment estimation

NASA Astrophysics Data System (ADS)

Theodorsen, A.; E Garcia, O.; Rypdal, M.

2017-05-01

Filtered Poisson processes are often used as reference models for intermittent fluctuations in physical systems. Such a process is here extended by adding a noise term, either as a purely additive term to the process or as a dynamical term in a stochastic differential equation. The lowest order moments, probability density function, auto-correlation function and power spectral density are derived and used to identify and compare the effects of the two different noise terms. Monte-Carlo studies of synthetic time series are used to investigate the accuracy of model parameter estimation and to identify methods for distinguishing the noise types. It is shown that the probability density function and the three lowest order moments provide accurate estimations of the model parameters, but are unable to separate the noise types. The auto-correlation function and the power spectral density also provide methods for estimating the model parameters, as well as being capable of identifying the noise type. The number of times the signal crosses a prescribed threshold level in the positive direction also promises to be able to differentiate the noise type.

Spot auto-focusing and spot auto-stigmation methods with high-definition auto-correlation function in high-resolution TEM.

PubMed

Isakozawa, Shigeto; Fuse, Taishi; Amano, Junpei; Baba, Norio

2018-04-01

As alternatives to the diffractogram-based method in high-resolution transmission electron microscopy, a spot auto-focusing (AF) method and a spot auto-stigmation (AS) method are presented with a unique high-definition auto-correlation function (HD-ACF). The HD-ACF clearly resolves the ACF central peak region in small amorphous-thin-film images, reflecting the phase contrast transfer function. At a 300-k magnification for a 120-kV transmission electron microscope, the smallest areas used are 64 × 64 pixels (~3 nm2) for the AF and 256 × 256 pixels for the AS. A useful advantage of these methods is that the AF function has an allowable accuracy even for a low s/n (~1.0) image. A reference database on the defocus dependency of the HD-ACF by the pre-acquisition of through-focus amorphous-thin-film images must be prepared to use these methods. This can be very beneficial because the specimens are not limited to approximations of weak phase objects but can be extended to objects outside such approximations.

Subfemtosecond quantum nuclear dynamics in water isotopomers.

PubMed

Rao, B Jayachander; Varandas, A J C

2015-05-21

Subfemtosecond quantum dynamics studies of all water isotopomers in the X̃ (2)B1 and à (2)A1 electronic states of the cation formed by Franck-Condon ionization of the neutral ground electronic state are reported. Using the ratio of the autocorrelation functions for the isotopomers as obtained from the solution of the time-dependent Schrödinger equation in a grid representation, high-order harmonic generation signals are calculated as a function of time. The results are found to be in agreement with the available experimental findings and with our earlier study for D2O(+)/H2O(+). Maxima are predicted in the autocorrelation function ratio at various times. Their origin and occurrence is explained by calculating expectation values of the bond lengths and bond angle of the water isotopomers as a function of time. The values so calculated for the (2)B1 and (2)A1 electronic states of the cation show quasiperiodic oscillations that can be associated with the time at which the nuclear wave packet reaches the minima of the potential energy surface, there being responsible for the peaks in the HHG signals.

Fetal source extraction from magnetocardiographic recordings by dependent component analysis

NASA Astrophysics Data System (ADS)

de Araujo, Draulio B.; Kardec Barros, Allan; Estombelo-Montesco, Carlos; Zhao, Hui; Roque da Silva Filho, A. C.; Baffa, Oswaldo; Wakai, Ronald; Ohnishi, Noboru

2005-10-01

Fetal magnetocardiography (fMCG) has been extensively reported in the literature as a non-invasive, prenatal technique that can be used to monitor various functions of the fetal heart. However, fMCG signals often have low signal-to-noise ratio (SNR) and are contaminated by strong interference from the mother's magnetocardiogram signal. A promising, efficient tool for extracting signals, even under low SNR conditions, is blind source separation (BSS), or independent component analysis (ICA). Herein we propose an algorithm based on a variation of ICA, where the signal of interest is extracted using a time delay obtained from an autocorrelation analysis. We model the system using autoregression, and identify the signal component of interest from the poles of the autocorrelation function. We show that the method is effective in removing the maternal signal, and is computationally efficient. We also compare our results to more established ICA methods, such as FastICA.

Statistical spatial properties of speckle patterns generated by multiple laser beams

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

Le Cain, A.; Sajer, J. M.; Riazuelo, G.

2011-08-15

This paper investigates hot spot characteristics generated by the superposition of multiple laser beams. First, properties of speckle statistics are studied in the context of only one laser beam by computing the autocorrelation function. The case of multiple laser beams is then considered. In certain conditions, it is shown that speckles have an ellipsoidal shape. Analytical expressions of hot spot radii generated by multiple laser beams are derived and compared to numerical estimates made from the autocorrelation function. They are also compared to numerical simulations performed within the paraxial approximation. Excellent agreement is found for the speckle width as wellmore » as for the speckle length. Application to the speckle patterns generated in the Laser MegaJoule configuration in the zone where all the beams overlap is presented. Influence of polarization on the size of the speckles as well as on their abundance is studied.« less

Ring polymer dynamics in curved spaces

NASA Astrophysics Data System (ADS)

Wolf, S.; Curotto, E.

2012-07-01

We formulate an extension of the ring polymer dynamics approach to curved spaces using stereographic projection coordinates. We test the theory by simulating the particle in a ring, {T}^1, mapped by a stereographic projection using three potentials. Two of these are quadratic, and one is a nonconfining sinusoidal model. We propose a new class of algorithms for the integration of the ring polymer Hamilton equations in curved spaces. These are designed to improve the energy conservation of symplectic integrators based on the split operator approach. For manifolds, the position-position autocorrelation function can be formulated in numerous ways. We find that the position-position autocorrelation function computed from configurations in the Euclidean space {R}^2 that contains {T}^1 as a submanifold has the best statistical properties. The agreement with exact results obtained with vector space methods is excellent for all three potentials, for all values of time in the interval simulated, and for a relatively broad range of temperatures.

Probabilistic density function method for nonlinear dynamical systems driven by colored noise

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

Barajas-Solano, David A.; Tartakovsky, Alexandre M.

2016-05-01

We present a probability density function (PDF) method for a system of nonlinear stochastic ordinary differential equations driven by colored noise. The method provides an integro-differential equation for the temporal evolution of the joint PDF of the system's state, which we close by means of a modified Large-Eddy-Diffusivity-type closure. Additionally, we introduce the generalized local linearization (LL) approximation for deriving a computable PDF equation in the form of the second-order partial differential equation (PDE). We demonstrate the proposed closure and localization accurately describe the dynamics of the PDF in phase space for systems driven by noise with arbitrary auto-correlation time.more » We apply the proposed PDF method to the analysis of a set of Kramers equations driven by exponentially auto-correlated Gaussian colored noise to study the dynamics and stability of a power grid.« less

Single-molecule fluorescence detection: autocorrelation criterion and experimental realization with phycoerythrin.

PubMed Central

Peck, K; Stryer, L; Glazer, A N; Mathies, R A

1989-01-01

A theory for single-molecule fluorescence detection is developed and then used to analyze data from subpicomolar solutions of B-phycoerythrin (PE). The distribution of detected counts is the convolution of a Poissonian continuous background with bursts arising from the passage of individual fluorophores through the focused laser beam. The autocorrelation function reveals single-molecule events and provides a criterion for optimizing experimental parameters. The transit time of fluorescent molecules through the 120-fl imaged volume was 800 microseconds. The optimal laser power (32 mW at 514.5 nm) gave an incident intensity of 1.8 x 10(23) photons.cm-2.s-1, corresponding to a mean time of 1.1 ns between absorptions. The mean incremental count rate was 1.5 per 100 microseconds for PE monomers and 3.0 for PE dimers above a background count rate of 1.0. The distribution of counts and the autocorrelation function for 200 fM monomer and 100 fM dimer demonstrate that single-molecule detection was achieved. At this concentration, the mean occupancy was 0.014 monomer molecules in the probed volume. A hard-wired version of this detection system was used to measure the concentration of PE down to 1 fM. This single-molecule counter is 3 orders of magnitude more sensitive than conventional fluorescence detection systems. PMID:2726766

Characterizing the functional MRI response using Tikhonov regularization.

PubMed

Vakorin, Vasily A; Borowsky, Ron; Sarty, Gordon E

2007-09-20

The problem of evaluating an averaged functional magnetic resonance imaging (fMRI) response for repeated block design experiments was considered within a semiparametric regression model with autocorrelated residuals. We applied functional data analysis (FDA) techniques that use a least-squares fitting of B-spline expansions with Tikhonov regularization. To deal with the noise autocorrelation, we proposed a regularization parameter selection method based on the idea of combining temporal smoothing with residual whitening. A criterion based on a generalized chi(2)-test of the residuals for white noise was compared with a generalized cross-validation scheme. We evaluated and compared the performance of the two criteria, based on their effect on the quality of the fMRI response. We found that the regularization parameter can be tuned to improve the noise autocorrelation structure, but the whitening criterion provides too much smoothing when compared with the cross-validation criterion. The ultimate goal of the proposed smoothing techniques is to facilitate the extraction of temporal features in the hemodynamic response for further analysis. In particular, these FDA methods allow us to compute derivatives and integrals of the fMRI signal so that fMRI data may be correlated with behavioral and physiological models. For example, positive and negative hemodynamic responses may be easily and robustly identified on the basis of the first derivative at an early time point in the response. Ultimately, these methods allow us to verify previously reported correlations between the hemodynamic response and the behavioral measures of accuracy and reaction time, showing the potential to recover new information from fMRI data. 2007 John Wiley & Sons, Ltd

Fluctuation analysis of proficient and dysgraphic handwriting in children

NASA Astrophysics Data System (ADS)

Rosenblum, S.; Roman, H. E.

2009-03-01

We analyze handwriting records from several school children with the aim of characterizing the fluctuating behavior of the writing speed. It will be concluded that remarkable differences exist between proficient and dysgraphic handwritings which were unknown so far. It is shown that in the case of proficient handwriting, the variations in handwriting speed are strongly autocorrelated within times corresponding to the completion of a single character or letter, while become uncorrelated at longer times. In the case of dysgraphia, such correlations persist on longer time scales and the autocorrelation function seems to display algebraic time decay, indicating the presence of strong anomalies in the handwriting process. Applications of the results in educational/clinical programs are envisaged.

A Comparison of Weights Matrices on Computation of Dengue Spatial Autocorrelation

NASA Astrophysics Data System (ADS)

Suryowati, K.; Bekti, R. D.; Faradila, A.

2018-04-01

Spatial autocorrelation is one of spatial analysis to identify patterns of relationship or correlation between locations. This method is very important to get information on the dispersal patterns characteristic of a region and linkages between locations. In this study, it applied on the incidence of Dengue Hemorrhagic Fever (DHF) in 17 sub districts in Sleman, Daerah Istimewa Yogyakarta Province. The link among location indicated by a spatial weight matrix. It describe the structure of neighbouring and reflects the spatial influence. According to the spatial data, type of weighting matrix can be divided into two types: point type (distance) and the neighbourhood area (contiguity). Selection weighting function is one determinant of the results of the spatial analysis. This study use queen contiguity based on first order neighbour weights, queen contiguity based on second order neighbour weights, and inverse distance weights. Queen contiguity first order and inverse distance weights shows that there is the significance spatial autocorrelation in DHF, but not by queen contiguity second order. Queen contiguity first and second order compute 68 and 86 neighbour list

Single-particle structure determination by correlations of snapshot X-ray diffraction patterns (CXIDB ID 20)

DOE Data Explorer

Starodub, D.

2013-03-25

This deposition includes the diffraction images generated by the paired polystyrene spheres in random orientations. These images were used to determine and phase the single particle diffraction volume from their autocorrelation functions.

Statistical anisotropy in free turbulence for mixing layers at high Reynolds numbers

NASA Astrophysics Data System (ADS)

Gardner, Patrick J.; Roggemann, Michael C.; Welsh, Byron M.; Bowersox, Rodney D.; Luke, Theodore E.

1996-08-01

A lateral shearing interferometer was used to measure the slope of perturbed wave fronts after propagating through free turbulent mixing layers. Shearing interferometers provide a two-dimensional flow visualization that is nonintrusive. Slope measurements were used to reconstruct the phase of the turbulence-corrupted wave front. The random phase fluctuations induced by the mixing layer were captured in a large ensemble of wave-front measurements. Experiments were performed on an unbounded, plane shear mixing layer of helium and nitrogen gas at fixed velocities and high Reynolds numbers for six locations in the flow development. Statistical autocorrelation functions and structure functions were computed on the reconstructed phase maps. The autocorrelation function results indicated that the turbulence-induced phase fluctuations were not wide-sense stationary. The structure functions exhibited statistical homogeneity, indicating that the phase fluctuations were stationary in first increments. However, the turbulence-corrupted phase was not isotropic. A five-thirds power law is shown to fit orthogonal slices of the structure function, analogous to the Kolmogorov model for isotropic turbulence. Strehl ratios were computed from the phase structure functions and compared with classical estimates that assume isotropy. The isotropic models are shown to overestimate the optical degradation by nearly 3 orders of magnitude compared with the structure function calculations.

Study of trabecular bone microstructure using spatial autocorrelation analysis

NASA Astrophysics Data System (ADS)

Wald, Michael J.; Vasilic, Branimir; Saha, Punam K.; Wehrli, Felix W.

2005-04-01

The spatial autocorrelation analysis method represents a powerful, new approach to quantitative characterization of structurally quasi-periodic anisotropic materials such as trabecular bone (TB). The method is applicable to grayscale images and thus does not require any preprocessing, such as segmentation which is difficult to achieve in the limited resolution regime of in vivo imaging. The 3D autocorrelation function (ACF) can be efficiently calculated using the Fourier transform. The resulting trabecular thickness and spacing measurements are robust to the presence of noise and produce values within the expected range as determined by other methods from μCT and μMRI datasets. TB features found from the ACF are shown to correlate well with those determined by the Fuzzy Distance transform (FDT) in the transverse plane, i.e. the plane orthogonal to bone"s major axis. The method is further shown to be applicable to in-vivo μMRI data. Using the ACF, we examine data acquired in a previous study aimed at evaluating the structural implications of male hypogonadism characterized by testosterone deficiency and reduced bone mass. Specifically, we consider the hypothesis that eugonadal and hypogonadal men differ in the anisotropy of their trabecular networks. The analysis indicates a significant difference in trabecular bone thickness and longitudinal spacing between the control group and the testosterone deficient group. We conclude that spatial autocorrelation analysis is able to characterize the 3D structure and anisotropy of trabecular bone and provides new insight into the structural changes associated with osteoporotic trabecular bone loss.

Old document image segmentation using the autocorrelation function and multiresolution analysis

NASA Astrophysics Data System (ADS)

Mehri, Maroua; Gomez-Krämer, Petra; Héroux, Pierre; Mullot, Rémy

2013-01-01

Recent progress in the digitization of heterogeneous collections of ancient documents has rekindled new challenges in information retrieval in digital libraries and document layout analysis. Therefore, in order to control the quality of historical document image digitization and to meet the need of a characterization of their content using intermediate level metadata (between image and document structure), we propose a fast automatic layout segmentation of old document images based on five descriptors. Those descriptors, based on the autocorrelation function, are obtained by multiresolution analysis and used afterwards in a specific clustering method. The method proposed in this article has the advantage that it is performed without any hypothesis on the document structure, either about the document model (physical structure), or the typographical parameters (logical structure). It is also parameter-free since it automatically adapts to the image content. In this paper, firstly, we detail our proposal to characterize the content of old documents by extracting the autocorrelation features in the different areas of a page and at several resolutions. Then, we show that is possible to automatically find the homogeneous regions defined by similar indices of autocorrelation without knowledge about the number of clusters using adapted hierarchical ascendant classification and consensus clustering approaches. To assess our method, we apply our algorithm on 316 old document images, which encompass six centuries (1200-1900) of French history, in order to demonstrate the performance of our proposal in terms of segmentation and characterization of heterogeneous corpus content. Moreover, we define a new evaluation metric, the homogeneity measure, which aims at evaluating the segmentation and characterization accuracy of our methodology. We find a 85% of mean homogeneity accuracy. Those results help to represent a document by a hierarchy of layout structure and content, and to define one or more signatures for each page, on the basis of a hierarchical representation of homogeneous blocks and their topology.

Structure of the North Anatolian Fault Zone from the Autocorrelation of Ambient Seismic Noise

NASA Astrophysics Data System (ADS)

Taylor, George; Rost, Sebastian; Houseman, Gregory

2016-04-01

In recent years the technique of cross-correlating the ambient seismic noise wavefield at two seismometers to reconstruct empirical Green's Functions for the determination of Earth structure has been a powerful tool to study the Earth's interior without earthquakes or man-made sources. However, far less attention has been paid to using auto-correlations of seismic noise to reveal body wave reflections from interfaces in the subsurface. In principle, the Green's functions thus derived should be comparable to the Earth's impulse response to a co-located source and receiver. We use data from a dense seismic array (Dense Array for Northern Anatolia - DANA) deployed across the northern branch of the North Anatolian Fault Zone (NAFZ) in the region of the 1999 magnitude 7.6 Izmit earthquake in western Turkey. The NAFZ is a major strike-slip system that extends ~1200 km across northern Turkey and continues to pose a high level of seismic hazard, in particular to the mega-city of Istanbul. We construct body wave images for the entire crust and the shallow upper mantle over the ~35 km by 70 km footprint of the 70-station DANA array. Using autocorrelations of the vertical component of ground motion, P-wave reflections can be retrieved from the wavefield to constrain crustal structure. We show that clear P-wave reflections from the crust-mantle boundary (Moho) can be retrieved using the autocorrelation technique, indicating topography on the Moho on horizontal scales of less than 10 km. Offsets in crustal structure can be identified that seem to be correlated with the surface expression of the northern branch of the fault zone, indicating that the NAFZ reaches the upper mantle as a narrow structure. The southern branch has a less clear effect on crustal structure. We also see evidence of several discontinuities in the mid-crust in addition to an upper mantle reflector that we interpret to represent the Hales discontinuity.

Holographic Measurements of Fuel Droplet Diffusion in Isotropic Turbulence

NASA Astrophysics Data System (ADS)

Gopalan, Balaji

2005-11-01

High-speed digital holographic cinematography was used to investigate the diffusion of slightly buoyant fuel droplets in locally isotropic turbulence. High turbulence levels with a weak mean velocity was generated at the center of a tank by four rotating grids. 0.3-1.5mm droplets were injected here and tracked using in-line holography. To obtain all three components of velocity, we simultaneously recorded holograms of the central 37x37x37 mm^3 volume from two perpendicular directions. These were numerically reconstructed to provide focused images of the droplets. An automated code was developed to identify the 3-D droplet trajectories from the two views, and then calculate time series of their velocity. After subtracting the local mean fluid velocity, the time series were used to obtain the 3-D Lagrangian autocorrelation function of droplet velocity. Averaging over many trajectories provided the autocorrelation functions as a function of direction and droplet sizes. As expected, the correlation was higher in the vertical direction due to the effect of gravity. Data analysis is still in progress.

Anomalous diffusion due to the non-Markovian process of the dust particle velocity in complex plasmas

NASA Astrophysics Data System (ADS)

Ghannad, Z.; Hakimi Pajouh, H.

2017-12-01

In this work, the motion of a dust particle under the influence of the random force due to dust charge fluctuations is considered as a non-Markovian stochastic process. Memory effects in the velocity process of the dust particle are studied. A model is developed based on the fractional Langevin equation for the motion of the dust grain. The fluctuation-dissipation theorem for the dust grain is derived from this equation. The mean-square displacement and the velocity autocorrelation function of the dust particle are obtained in terms of the Mittag-Leffler functions. Their asymptotic behavior and the dust particle temperature due to charge fluctuations are studied in the long-time limit. As an interesting result, it is found that the presence of memory effects in the velocity process of the dust particle as a non-Markovian process can cause an anomalous diffusion in dusty plasmas. In this case, the velocity autocorrelation function of the dust particle has a power-law decay like t - α - 2, where the exponent α take values 0 < α < 1.

Protein oligomerization monitored by fluorescence fluctuation spectroscopy: Self-assembly of Rubisco activase

USDA-ARS?s Scientific Manuscript database

A methodology is presented to characterize complex protein assembly pathways by fluorescence correlation spectroscopy. We have derived the total autocorrelation function describing the behavior of mixtures of labeled and unlabeled protein under equilibrium conditions. Our modeling approach allows us...

Statistical characteristics of MST radar echoes and its interpretation

NASA Technical Reports Server (NTRS)

Woodman, Ronald F.

1989-01-01

Two concepts of fundamental importance are reviewed: the autocorrelation function and the frequency power spectrum. In addition, some turbulence concepts, the relationship between radar signals and atmospheric medium statistics, partial reflection, and the characteristics of noise and clutter interference are discussed.

Pattern, growth, and aging in aggregation kinetics of a Vicsek-like active matter model

NASA Astrophysics Data System (ADS)

Das, Subir K.

2017-01-01

Via molecular dynamics simulations, we study kinetics in a Vicsek-like phase-separating active matter model. Quantitative results, for isotropic bicontinuous pattern, are presented on the structure, growth, and aging. These are obtained via the two-point equal-time density-density correlation function, the average domain length, and the two-time density autocorrelation function. Both the correlation functions exhibit basic scaling properties, implying self-similarity in the pattern dynamics, for which the average domain size exhibits a power-law growth in time. The equal-time correlation has a short distance behavior that provides reasonable agreement between the corresponding structure factor tail and the Porod law. The autocorrelation decay is a power-law in the average domain size. Apart from these basic similarities, the overall quantitative behavior of the above-mentioned observables is found to be vastly different from those of the corresponding passive limit of the model which also undergoes phase separation. The functional forms of these have been quantified. An exceptionally rapid growth in the active system occurs due to fast coherent motion of the particles, mean-squared-displacements of which exhibit multiple scaling regimes, including a long time ballistic one.

Time-scale effects on the gain-loss asymmetry in stock indices

NASA Astrophysics Data System (ADS)

Sándor, Bulcsú; Simonsen, Ingve; Nagy, Bálint Zsolt; Néda, Zoltán

2016-08-01

The gain-loss asymmetry, observed in the inverse statistics of stock indices is present for logarithmic return levels that are over 2 % , and it is the result of the non-Pearson-type autocorrelations in the index. These non-Pearson-type correlations can be viewed also as functionally dependent daily volatilities, extending for a finite time interval. A generalized time-window shuffling method is used to show the existence of such autocorrelations. Their characteristic time scale proves to be smaller (less than 25 trading days) than what was previously believed. It is also found that this characteristic time scale has decreased with the appearance of program trading in the stock market transactions. Connections with the leverage effect are also established.

Photon statistics and polarization correlations at telecommunications wavelengths from a warm atomic ensemble.

PubMed

Willis, R T; Becerra, F E; Orozco, L A; Rolston, S L

2011-07-18

We present measurements of the polarization correlation and photon statistics of photon pairs that emerge from a laser-pumped warm rubidium vapor cell. The photon pairs occur at 780 nm and 1367 nm and are polarization entangled. We measure the autocorrelation of each of the generated fields as well as the cross-correlation function, and observe a strong violation of the two-beam Cauchy-Schwartz inequality. We evaluate the performance of the system as source of heralded single photons at a telecommunication wavelength. We measure the heralded autocorrelation and see that coincidences are suppressed by a factor of ≈ 20 from a Poissonian source at a generation rate of 1500 s(-1), a heralding efficiency of 10%, and a narrow spectral width.

a Study of the Concentration Dependence of Macromolecular Diffusion Using Photon Correlation Spectroscopy.

NASA Astrophysics Data System (ADS)

Marlowe, Robert Lloyd

The dynamic light scattering technique of photon correlation spectroscopy has been used to investigate the dependence of the mutual diffusion coefficient of a macromolecular system upon concentration. The first part of the research was devoted to the design and construction of a single-clipping autocorrelator based on newly-developed integrated circuits. The resulting 128 channel instrument can perform real time autocorrelation for sample time intervals >(, )10 (mu)s, and batch processed autocorrelation for intervals down to 3 (mu)s. An improved design for a newer, all-digital autocorrelator is given. Homodyne light scattering experiments were then undertaken on monodisperse solutions of polystyrene spheres. The single-mode TEM(,oo) beam of an argon-ion laser ((lamda) = 5145 (ANGSTROM)) was used as the light source; all solutions were studied at room temperature. The scattering angle was varied from 30(DEGREES) to 110(DEGREES). Excellent agreement with the manufacturer's specification for the particle size was obtained from the photon correlation studies. Finally, aqueous solutions of the globular protein ovalbumin, ranging in concentration from 18.9 to 244.3 mg/ml, were illuminated under the same conditions of temperature and wavelength as before; the homodyne scattered light was detected at a fixed scattering angle of 30(DEGREES). The single-clipped photocount autocorrelation function was analyzed using the homodyne exponential integral method of Meneely et al. The resulting diffusion coefficients showed a general linear dependence upon concentration, as predicted by the generalized Stokes-Einstein equation. However, a clear peak in the data was evident at c (TURNEQ) 100 mg/ml, which could not be explained on the basis of a non -interacting particle theory. A semi-quantitative approach based on the Debye-Huckel theory of electrostatic interactions is suggested as the probable cause for the peak's rise, and an excluded volume effect for its decline.

ASSESSMENT OF SPATIAL AUTOCORRELATION IN EMPIRICAL MODELS IN ECOLOGY

EPA Science Inventory

Statistically assessing ecological models is inherently difficult because data are autocorrelated and this autocorrelation varies in an unknown fashion. At a simple level, the linking of a single species to a habitat type is a straightforward analysis. With some investigation int...

A 3D Monte Carlo model of radiation affecting cells, and its application to neuronal cells and GCR irradiation

NASA Astrophysics Data System (ADS)

Ponomarev, Artem; Sundaresan, Alamelu; Kim, Angela; Vazquez, Marcelo E.; Guida, Peter; Kim, Myung-Hee; Cucinotta, Francis A.

A 3D Monte Carlo model of radiation transport in matter is applied to study the effect of heavy ion radiation on human neuronal cells. Central nervous system effects, including cognitive impairment, are suspected from the heavy ion component of galactic cosmic radiation (GCR) during space missions. The model can count, for instance, the number of direct hits from ions, which will have the most affect on the cells. For comparison, the remote hits, which are received through δ-rays from the projectile traversing space outside the volume of the cell, are also simulated and their contribution is estimated. To simulate tissue effects from irradiation, cellular matrices of neuronal cells, which were derived from confocal microscopy, were simulated in our model. To produce this realistic model of the brain tissue, image segmentation was used to identify cells in the images of cells cultures. The segmented cells were inserted pixel by pixel into the modeled physical space, which represents a volume of interacting cells with periodic boundary conditions (PBCs). PBCs were used to extrapolate the model results to the macroscopic tissue structures. Specific spatial patterns for cell apoptosis are expected from GCR, as heavy ions produce concentrated damage along their trajectories. The apoptotic cell patterns were modeled based on the action cross sections for apoptosis, which were estimated from the available experimental data. The cell patterns were characterized with an autocorrelation function, which values are higher for non-random cell patterns, and the values of the autocorrelation function were compared for X rays and Fe ion irradiations. The autocorrelation function indicates the directionality effects present in apoptotic neuronal cells from GCR.

Intrinsic autocorrelation time of picoseconds for thermal noise in water.

PubMed

Zhu, Zhi; Sheng, Nan; Wan, Rongzheng; Fang, Haiping

2014-10-02

Whether thermal noise is colored or white is of fundamental importance. In conventional theory, thermal noise is usually treated as white noise so that there are no directional transportations in the asymmetrical systems without external inputs, since only the colored fluctuations with appropriate autocorrelation time length can lead to directional transportations in the asymmetrical systems. Here, on the basis of molecular dynamics simulations, we show that the autocorrelation time length of thermal noise in water is ~10 ps at room temperature, which indicates that thermal noise is not white in the molecular scale while thermal noise can be reasonably assumed as white in macro- and meso-scale systems. The autocorrelation time length of thermal noise is intrinsic, since the value is almost unchanged for different temperature coupling methods. Interestingly, the autocorrelation time of thermal noise is correlated with the lifetime of hydrogen bonds, suggesting that the finite autocorrelation time length of thermal noise mainly comes from the finite lifetime of the interactions between neighboring water molecules.

Principal Components of Recurrence Quantification Analysis of EMG

DTIC Science & Technology

2001-10-25

Springer, 1981, pp. 366-381. 4. M. Fraser and H. L. Swinney, “ Independent coordinates for strange attractors from mutual information ,” Phys. Rev. A...autocorrelation function of s(n), although it has also been argued that the first local minimum of the auto mutual information function is more appropriate [4...recordings from a given subject. T was taken as the lag corresponding to the first minimum of the auto mutual information function, calculated as

Physics behind the oscillation of pressure tensor autocorrelation function for nanocolloidal dispersions.

PubMed

Wang, Tao; Wang, Xinwei; Luo, Zhongyang; Cen, Kefa

2008-08-01

In this work, extensive equilibrium molecular dynamics simulations are conducted to explore the physics behind the oscillation of pressure tensor autocorrelation function (PTACF) for nanocolloidal dispersions, which leads to strong instability in viscosity calculation. By reducing the particle size and density, we find the intensity of the oscillation decreases while the frequency of the oscillation becomes higher. Careful analysis of the relationship between the oscillation and nanoparticle characteristics reveals that the stress wave scattering/reflection at the particle-liquid interface plays a critical role in PTACF oscillation while the Brownian motion/vibration of solid particles has little effect. Our modeling proves that it is practical to eliminate the PTACF oscillation through suppressing the acoustic mismatch at the solid-liquid interface by designing special nanoparticle materials. It is also found when the particle size is comparable with the wavelength of the stress wave, diffraction of stress wave happens at the interface. Such effect substantially reduces the PTACF oscillation and improves the stability of viscosity calculation.

Comparing phase-sensitive and phase-insensitive echolocation target images using a monaural audible sonar.

PubMed

Kuc, Roman

2018-04-01

This paper describes phase-sensitive and phase-insensitive processing of monaural echolocation waveforms to generate target maps. Composite waveforms containing both the emission and echoes are processed to estimate the target impulse response using an audible sonar. Phase-sensitive processing yields the composite signal envelope, while phase-insensitive processing that starts with the composite waveform power spectrum yields the envelope of the autocorrelation function. Analysis and experimental verification show that multiple echoes form an autocorrelation function that produces near-range phantom-reflector artifacts. These artifacts interfere with true target echoes when the first true echo occurs at a time that is less than the total duration of the target echoes. Initial comparison of phase-sensitive and phase-insensitive maps indicates that both display important target features, indicating that phase is not vital. A closer comparison illustrates the improved resolution of phase-sensitive processing, the near-range phantom-reflectors produced by phase-insensitive processing, and echo interference and multiple reflection artifacts that were independent of the processing.

Mesoscopic fluctuations and intermittency in aging dynamics

NASA Astrophysics Data System (ADS)

Sibani, P.

2006-01-01

Mesoscopic aging systems are characterized by large intermittent noise fluctuations. In a record dynamics scenario (Sibani P. and Dall J., Europhys. Lett., 64 (2003) 8) these events, quakes, are treated as a Poisson process with average αln (1 + t/tw), where t is the observation time, tw is the age and α is a parameter. Assuming for simplicity that quakes constitute the only source of de-correlation, we present a model for the probability density function (PDF) of the configuration autocorrelation function. Beside α, the model has the average quake size 1/q as a parameter. The model autocorrelation PDF has a Gumbel-like shape, which approaches a Gaussian for large t/tw and becomes sharply peaked in the thermodynamic limit. Its average and variance, which are given analytically, depend on t/tw as a power law and a power law with a logarithmic correction, respectively. Most predictions are in good agreement with data from the literature and with the simulations of the Edwards-Anderson spin-glass carried out as a test.

On the origin of the soft X-ray background. [in cosmological observations

NASA Technical Reports Server (NTRS)

Wang, Q. D.; Mccray, Richard

1993-01-01

The angular autocorrelation function and spectrum of the soft X-ray background is studied below a discrete source detection limit, using two deep images from the Rosat X-ray satellite. The average spectral shape of pointlike sources, which account for 40 to 60 percent of the background intensity, is determined by using the autocorrelation function. The background spectrum, in the 0.5-0.9 keV band (M band), is decomposed into a pointlike source component characterized by a power law and a diffuse component represented by a two-temperature plasma. These pointlike sources cannot contribute more than 60 percent of the X-ray background intensity in the M band without exceeding the total observed flux in the R7 band. Spectral analysis has shown that the local soft diffuse component, although dominating the background intensity at energies not greater than 0.3 keV, contributes only a small fraction of the M band background intensity. The diffuse component may represent an important constituent of the interstellar or intergalactic medium.

Scaling analysis and model estimation of solar corona index

NASA Astrophysics Data System (ADS)

Ray, Samujjwal; Ray, Rajdeep; Khondekar, Mofazzal Hossain; Ghosh, Koushik

2018-04-01

A monthly average solar green coronal index time series for the period from January 1939 to December 2008 collected from NOAA (The National Oceanic and Atmospheric Administration) has been analysed in this paper in perspective of scaling analysis and modelling. Smoothed and de-noising have been done using suitable mother wavelet as a pre-requisite. The Finite Variance Scaling Method (FVSM), Higuchi method, rescaled range (R/S) and a generalized method have been applied to calculate the scaling exponents and fractal dimensions of the time series. Autocorrelation function (ACF) is used to find autoregressive (AR) process and Partial autocorrelation function (PACF) has been used to get the order of AR model. Finally a best fit model has been proposed using Yule-Walker Method with supporting results of goodness of fit and wavelet spectrum. The results reveal an anti-persistent, Short Range Dependent (SRD), self-similar property with signatures of non-causality, non-stationarity and nonlinearity in the data series. The model shows the best fit to the data under observation.

Cross-section fluctuations in chaotic scattering systems.

PubMed

Ericson, Torleif E O; Dietz, Barbara; Richter, Achim

2016-10-01

Exact analytical expressions for the cross-section correlation functions of chaotic scattering systems have hitherto been derived only under special conditions. The objective of the present article is to provide expressions that are applicable beyond these restrictions. The derivation is based on a statistical model of Breit-Wigner type for chaotic scattering amplitudes which has been shown to describe the exact analytical results for the scattering (S)-matrix correlation functions accurately. Our results are given in the energy and in the time representations and apply in the whole range from isolated to overlapping resonances. The S-matrix contributions to the cross-section correlations are obtained in terms of explicit irreducible and reducible correlation functions. Consequently, the model can be used for a detailed exploration of the key features of the cross-section correlations and the underlying physical mechanisms. In the region of isolated resonances, the cross-section correlations contain a dominant contribution from the self-correlation term. For narrow states the self-correlations originate predominantly from widely spaced states with exceptionally large partial width. In the asymptotic region of well-overlapping resonances, the cross-section autocorrelation functions are given in terms of the S-matrix autocorrelation functions. For inelastic correlations, in particular, the Ericson fluctuations rapidly dominate in that region. Agreement with known analytical and experimental results is excellent.

Reexamination of relaxation of spins due to a magnetic field gradient: Identity of the Redfield and Torrey theories

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

Golub, R.; Rohm, Ryan M.; Swank, C. M.

2011-02-15

There is an extensive literature on magnetic-gradient-induced spin relaxation. Cates, Schaefer, and Happer, in a seminal publication, have solved the problem in the regime where diffusion theory (the Torrey equation) is applicable using an expansion of the density matrix in diffusion equation eigenfunctions and angular momentum tensors. McGregor has solved the problem in the same regime using a slightly more general formulation using the Redfield theory formulated in terms of the autocorrelation function of the fluctuating field seen by the spins and calculating the correlation functions using the diffusion-theory Green's function. The results of both calculations were shown to agreemore » for a special case. In the present work, we show that the eigenfunction expansion of the Torrey equation yields the expansion of the Green's function for the diffusion equation, thus showing the identity of this approach with that of the Redfield theory. The general solution can also be obtained directly from the Torrey equation for the density matrix. Thus, the physical content of the Redfield and Torrey approaches are identical. We then introduce a more general expression for the position autocorrelation function of particles moving in a closed cell, extending the range of applicability of the theory.« less

Dispersion relation for electromagnetic propagation in stochastic dielectric and magnetic helical photonic crystals

NASA Astrophysics Data System (ADS)

Avendaño, Carlos G.; Reyes, Arturo

2017-03-01

We theoretically study the dispersion relation for axially propagating electromagnetic waves throughout a one-dimensional helical structure whose pitch and dielectric and magnetic properties are spatial random functions with specific statistical characteristics. In the system of coordinates rotating with the helix, by using a matrix formalism, we write the set of differential equations that governs the expected value of the electromagnetic field amplitudes and we obtain the corresponding dispersion relation. We show that the dispersion relation depends strongly on the noise intensity introduced in the system and the autocorrelation length. When the autocorrelation length increases at fixed fluctuation and when the fluctuation augments at fixed autocorrelation length, the band gap widens and the attenuation coefficient of electromagnetic waves propagating in the random medium gets larger. By virtue of the degeneracy in the imaginary part of the eigenvalues associated with the propagating modes, the random medium acts as a filter for circularly polarized electromagnetic waves, in which only the propagating backward circularly polarized wave can propagate with no attenuation. Our results are valid for any kind of dielectric and magnetic structures which possess a helical-like symmetry such as cholesteric and chiral smectic-C liquid crystals, structurally chiral materials, and stressed cholesteric elastomers.

Water Quality Sensing and Spatio-Temporal Monitoring Structure with Autocorrelation Kernel Methods.

PubMed

Vizcaíno, Iván P; Carrera, Enrique V; Muñoz-Romero, Sergio; Cumbal, Luis H; Rojo-Álvarez, José Luis

2017-10-16

Pollution on water resources is usually analyzed with monitoring campaigns, which consist of programmed sampling, measurement, and recording of the most representative water quality parameters. These campaign measurements yields a non-uniform spatio-temporal sampled data structure to characterize complex dynamics phenomena. In this work, we propose an enhanced statistical interpolation method to provide water quality managers with statistically interpolated representations of spatial-temporal dynamics. Specifically, our proposal makes efficient use of the a priori available information of the quality parameter measurements through Support Vector Regression (SVR) based on Mercer's kernels. The methods are benchmarked against previously proposed methods in three segments of the Machángara River and one segment of the San Pedro River in Ecuador, and their different dynamics are shown by statistically interpolated spatial-temporal maps. The best interpolation performance in terms of mean absolute error was the SVR with Mercer's kernel given by either the Mahalanobis spatial-temporal covariance matrix or by the bivariate estimated autocorrelation function. In particular, the autocorrelation kernel provides with significant improvement of the estimation quality, consistently for all the six water quality variables, which points out the relevance of including a priori knowledge of the problem.

Water Quality Sensing and Spatio-Temporal Monitoring Structure with Autocorrelation Kernel Methods

PubMed Central

Vizcaíno, Iván P.; Muñoz-Romero, Sergio; Cumbal, Luis H.

2017-01-01

Pollution on water resources is usually analyzed with monitoring campaigns, which consist of programmed sampling, measurement, and recording of the most representative water quality parameters. These campaign measurements yields a non-uniform spatio-temporal sampled data structure to characterize complex dynamics phenomena. In this work, we propose an enhanced statistical interpolation method to provide water quality managers with statistically interpolated representations of spatial-temporal dynamics. Specifically, our proposal makes efficient use of the a priori available information of the quality parameter measurements through Support Vector Regression (SVR) based on Mercer’s kernels. The methods are benchmarked against previously proposed methods in three segments of the Machángara River and one segment of the San Pedro River in Ecuador, and their different dynamics are shown by statistically interpolated spatial-temporal maps. The best interpolation performance in terms of mean absolute error was the SVR with Mercer’s kernel given by either the Mahalanobis spatial-temporal covariance matrix or by the bivariate estimated autocorrelation function. In particular, the autocorrelation kernel provides with significant improvement of the estimation quality, consistently for all the six water quality variables, which points out the relevance of including a priori knowledge of the problem. PMID:29035333

Autocorrelated process control: Geometric Brownian Motion approach versus Box-Jenkins approach

NASA Astrophysics Data System (ADS)

Salleh, R. M.; Zawawi, N. I.; Gan, Z. F.; Nor, M. E.

2018-04-01

Existing of autocorrelation will bring a significant effect on the performance and accuracy of process control if the problem does not handle carefully. When dealing with autocorrelated process, Box-Jenkins method will be preferred because of the popularity. However, the computation of Box-Jenkins method is too complicated and challenging which cause of time-consuming. Therefore, an alternative method which known as Geometric Brownian Motion (GBM) is introduced to monitor the autocorrelated process. One real case of furnace temperature data is conducted to compare the performance of Box-Jenkins and GBM methods in monitoring autocorrelation process. Both methods give the same results in terms of model accuracy and monitoring process control. Yet, GBM is superior compared to Box-Jenkins method due to its simplicity and practically with shorter computational time.

The Complexity of Bit Retrieval

DOE PAGES

Elser, Veit

2018-09-20

Bit retrieval is the problem of reconstructing a periodic binary sequence from its periodic autocorrelation, with applications in cryptography and x-ray crystallography. After defining the problem, with and without noise, we describe and compare various algorithms for solving it. A geometrical constraint satisfaction algorithm, relaxed-reflect-reflect, is currently the best algorithm for noisy bit retrieval.

The Complexity of Bit Retrieval

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

Elser, Veit

Bit retrieval is the problem of reconstructing a periodic binary sequence from its periodic autocorrelation, with applications in cryptography and x-ray crystallography. After defining the problem, with and without noise, we describe and compare various algorithms for solving it. A geometrical constraint satisfaction algorithm, relaxed-reflect-reflect, is currently the best algorithm for noisy bit retrieval.

The investigation of time dependent flame structure by ionization probes

NASA Technical Reports Server (NTRS)

Ventura, J. M. P.; Suzuki, T.; Yule, A. J.; Ralph, S.; Chigier, N. A.

1980-01-01

Ionization probes were used to measure mean ionization current and frequency spectra, auto-correlations and cross-correlations in jet flames with variation in the initial Reynolds numbers and equivalence ratios. Special attention was paid to the transitional region between the burner exit plane and the plane of onset of turbulence.

Statistical regularities of Carbon emission trading market: Evidence from European Union allowances

NASA Astrophysics Data System (ADS)

Zheng, Zeyu; Xiao, Rui; Shi, Haibo; Li, Guihong; Zhou, Xiaofeng

2015-05-01

As an emerging financial market, the trading value of carbon emission trading market has definitely increased. In recent years, the carbon emission allowances have already become a way of investment. They are bought and sold not only by carbon emitters but also by investors. In this paper, we analyzed the price fluctuations of the European Union allowances (EUA) futures in European Climate Exchange (ECX) market from 2007 to 2011. The symmetric and power-law probability density function of return time series was displayed. We found that there are only short-range correlations in price changes (return), while long-range correlations in the absolute of price changes (volatility). Further, detrended fluctuation analysis (DFA) approach was applied with focus on long-range autocorrelations and Hurst exponent. We observed long-range power-law autocorrelations in the volatility that quantify risk, and found that they decay much more slowly than the autocorrelation of return time series. Our analysis also showed that the significant cross correlations exist between return time series of EUA and many other returns. These cross correlations exist in a wide range of fields, including stock markets, energy concerned commodities futures, and financial futures. The significant cross-correlations between energy concerned futures and EUA indicate the physical relationship between carbon emission and energy production process. Additionally, the cross-correlations between financial futures and EUA indicate that the speculation behavior may become an important factor that can affect the price of EUA. Finally we modeled the long-range volatility time series of EUA with a particular version of the GARCH process, and the result also suggests long-range volatility autocorrelations.

Retrieval of P wave Basin Response from Autocorrelation of Seismic Noise-Jakarta, Indonesia

NASA Astrophysics Data System (ADS)

Saygin, E.; Cummins, P. R.; Lumley, D. E.

2016-12-01

Indonesia's capital city, Jakarta, is home to a very large (over 10 million), vulnerable population and is proximate to known active faults, as well as to the subduction of Australian plate, which has a megathrust at abut 300 km distance, as well as intraslab seismicity extending to directly beneath the city. It is also located in a basin filled with a thick layer of unconsolidated and poorly consolidated sediment, which increases the seismic hazard the city is facing. Therefore, the information on the seismic velocity structure of the basin is crucial for increasing our knowledge of the seismic risk. We undertook a passive deployment of broadband seismographs throughout the city over a 3-month interval in 2013-2014, recording ambient seismic noise at over 90 sites for intervals of 1 month or more. Here we consider autocorrelations of the vertical component of the continuously recorded seismic wavefield across this dense network to image the shallow P wave velocity structure of Jakarta, Indonesia. Unlike the surface wave Green's functions used in ambient noise tomography, the vertical-component autocorrelograms are dominated by body wave energy that is potentially sensitive to sharp velocity contrasts, which makes them useful in seismic imaging. Results show autocorrelograms at different seismic stations with travel time variations that largely reflect changes in sediment thickness across the basin. We also confirm the validity our interpretation of the observed autocorrelation waveforms by conducting 2D finite difference full waveform numerical modeling for randomly distributed seismic sources to retrieve the reflection response through autocorrelation.

Flux line non-equilibrium relaxation kinetics following current quenches in disordered type-II superconductors

NASA Astrophysics Data System (ADS)

Chaturvedi, Harshwardhan; Assi, Hiba; Dobramysl, Ulrich; Pleimling, Michel; Täuber, Uwe

We investigate the relaxation dynamics of magnetic vortex lines in disordered type-II superconductors following rapid changes in the external driving current by means of Langevin molecular dynamics simulations for an elastic line model. A system of driven interacting flux lines in a sample with randomly distributed point pinning centers is initially relaxed to a moving non-equilibrium steady state. The current is then instantaneously decreased, such that the final stationary state resides either still in the moving regime, or in the pinned Bragg glass phase. The ensuing non-equilibrium relaxation kinetics of the vortices is studied in detail by measuring the mean flux line gyration radius and the two-time transverse height autocorrelation function. The latter allows us to investigate the physical aging properties for quenches from the moving into the glassy phase, and to compare with non-equilibrium relaxation features obtained with different initial configurations. Research supported by the U.S. Department of Energy, Office of Basic Energy Sciences, Division of Materials Sciences and Engineering under Award DE-FG02-09ER46613.

Strong Clustering of Lyman Break Galaxies around Luminous Quasars at Z ˜ 4

NASA Astrophysics Data System (ADS)

García-Vergara, Cristina; Hennawi, Joseph F.; Barrientos, L. Felipe; Rix, Hans-Walter

2017-10-01

In the standard picture of structure formation, the first massive galaxies are expected to form at the highest peaks of the density field, which constitute the cores of massive proto-clusters. Luminous quasars (QSOs) at z ˜ 4 are the most strongly clustered population known, and should thus reside in massive dark matter halos surrounded by large overdensities of galaxies, implying a strong QSO-galaxy cross-correlation function. We observed six z ˜ 4 QSO fields with VLT/FORS, exploiting a novel set of narrow-band filters custom designed to select Lyman Break Galaxies (LBGs) in a thin redshift slice of {{Δ }}z˜ 0.3, mitigating the projection effects that have limited the sensitivity of previous searches for galaxies around z≳ 4 QSOs. We find that LBGs are strongly clustered around QSOs, and present the first measurement of the QSO-LBG cross-correlation function at z ˜ 4, on scales of 0.1≲ R≲ 9 {h}-1 {Mpc} (comoving). Assuming a power-law form for the cross-correlation function ξ ={(r/{r}0{QG})}γ , we measure {r}0{QG}={8.83}-1.51+1.39 {h}-1 {Mpc} for a fixed slope of γ =2.0. This result is in agreement with the expected cross-correlation length deduced from measurements of the QSO and LBG auto-correlation function, and assuming a deterministic bias model. We also measure a strong auto-correlation of LBGs in our QSO fields, finding {r}0{GG}={21.59}-1.69+1.72 {h}-1 {Mpc} for a fixed slope of γ =1.5, which is ˜4 times larger than the LBG auto-correlation length in blank fields, providing further evidence that QSOs reside in overdensities of LBGs. Our results qualitatively support a picture where luminous QSOs inhabit exceptionally massive ({M}{halo}> {10}12 {M}⊙ ) dark matter halos at z ˜ 4.

Accounting for Non-Gaussian Sources of Spatial Correlation in Parametric Functional Magnetic Resonance Imaging Paradigms II: A Method to Obtain First-Level Analysis Residuals with Uniform and Gaussian Spatial Autocorrelation Function and Independent and Identically Distributed Time-Series.

PubMed

Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Lacey, Simon; Sathian, K

2018-02-01

In a recent study Eklund et al. have shown that cluster-wise family-wise error (FWE) rate-corrected inferences made in parametric statistical method-based functional magnetic resonance imaging (fMRI) studies over the past couple of decades may have been invalid, particularly for cluster defining thresholds less stringent than p < 0.001; principally because the spatial autocorrelation functions (sACFs) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggest otherwise. Hence, the residuals from general linear model (GLM)-based fMRI activation estimates in these studies may not have possessed a homogenously Gaussian sACF. Here we propose a method based on the assumption that heterogeneity and non-Gaussianity of the sACF of the first-level GLM analysis residuals, as well as temporal autocorrelations in the first-level voxel residual time-series, are caused by unmodeled MRI signal from neuronal and physiological processes as well as motion and other artifacts, which can be approximated by appropriate decompositions of the first-level residuals with principal component analysis (PCA), and removed. We show that application of this method yields GLM residuals with significantly reduced spatial correlation, nearly Gaussian sACF and uniform spatial smoothness across the brain, thereby allowing valid cluster-based FWE-corrected inferences based on assumption of Gaussian spatial noise. We further show that application of this method renders the voxel time-series of first-level GLM residuals independent, and identically distributed across time (which is a necessary condition for appropriate voxel-level GLM inference), without having to fit ad hoc stochastic colored noise models. Furthermore, the detection power of individual subject brain activation analysis is enhanced. This method will be especially useful for case studies, which rely on first-level GLM analysis inferences.

Role of initial state and final quench temperature on aging properties in phase-ordering kinetics.

PubMed

Corberi, Federico; Villavicencio-Sanchez, Rodrigo

2016-05-01

We study numerically the two-dimensional Ising model with nonconserved dynamics quenched from an initial equilibrium state at the temperature T_{i}≥T_{c} to a final temperature T_{f} below the critical one. By considering processes initiating both from a disordered state at infinite temperature T_{i}=∞ and from the critical configurations at T_{i}=T_{c} and spanning the range of final temperatures T_{f}∈[0,T_{c}[ we elucidate the role played by T_{i} and T_{f} on the aging properties and, in particular, on the behavior of the autocorrelation C and of the integrated response function χ. Our results show that for any choice of T_{f}, while the autocorrelation function exponent λ_{C} takes a markedly different value for T_{i}=∞ [λ_{C}(T_{i}=∞)≃5/4] or T_{i}=T_{c} [λ_{C}(T_{i}=T_{c})≃1/8] the response function exponents are unchanged. Supported by the outcome of the analytical solution of the solvable spherical model we interpret this fact as due to the different contributions provided to autocorrelation and response by the large-scale properties of the system. As changing T_{f} is considered, although this is expected to play no role in the large-scale and long-time properties of the system, we show important effects on the quantitative behavior of χ. In particular, data for quenches to T_{f}=0 are consistent with a value of the response function exponent λ_{χ}=1/2λ_{C}(T_{i}=∞)=5/8 different from the one [λ_{χ}∈(0.5-0.56)] found in a wealth of previous numerical determinations in quenches to finite final temperatures. This is interpreted as due to important preasymptotic corrections associated to T_{f}>0.

Correction of Spatial Bias in Oligonucleotide Array Data

PubMed Central

Lemieux, Sébastien

2013-01-01

Background. Oligonucleotide microarrays allow for high-throughput gene expression profiling assays. The technology relies on the fundamental assumption that observed hybridization signal intensities (HSIs) for each intended target, on average, correlate with their target's true concentration in the sample. However, systematic, nonbiological variation from several sources undermines this hypothesis. Background hybridization signal has been previously identified as one such important source, one manifestation of which appears in the form of spatial autocorrelation. Results. We propose an algorithm, pyn, for the elimination of spatial autocorrelation in HSIs, exploiting the duality of desirable mutual information shared by probes in a common probe set and undesirable mutual information shared by spatially proximate probes. We show that this correction procedure reduces spatial autocorrelation in HSIs; increases HSI reproducibility across replicate arrays; increases differentially expressed gene detection power; and performs better than previously published methods. Conclusions. The proposed algorithm increases both precision and accuracy, while requiring virtually no changes to users' current analysis pipelines: the correction consists merely of a transformation of raw HSIs (e.g., CEL files for Affymetrix arrays). A free, open-source implementation is provided as an R package, compatible with standard Bioconductor tools. The approach may also be tailored to other platform types and other sources of bias. PMID:23573083

Spatial autocorrelation in growth of undisturbed natural pine stands across Georgia

Treesearch

Raymond L. Czaplewski; Robin M. Reich; William A. Bechtold

1994-01-01

Moran's I statistic measures the spatial autocorrelation in a random variable measured at discrete locations in space. Permutation procedures test the null hypothesis that the observed Moran's I value is no greater than that expected by chance. The spatial autocorrelation of gross basal area increment is analyzed for undisturbed, naturally regenerated stands...

Propagation of mechanical waves through a stochastic medium with spherical symmetry

NASA Astrophysics Data System (ADS)

Avendaño, Carlos G.; Reyes, J. Adrián

2018-01-01

We theoretically analyze the propagation of outgoing mechanical waves through an infinite isotropic elastic medium possessing spherical symmetry whose Lamé coefficients and density are spatial random functions characterized by well-defined statistical parameters. We derive the differential equation that governs the average displacement for a system whose properties depend on the radial coordinate. We show that such an equation is an extended version of the well-known Bessel differential equation whose perturbative additional terms contain coefficients that depend directly on the squared noise intensities and the autocorrelation lengths in an exponential decay fashion. We numerically solve the second order differential equation for several values of noise intensities and autocorrelation lengths and compare the corresponding displacement profiles with that of the exact analytic solution for the case of absent inhomogeneities.

Constant-Envelope Waveform Design for Optimal Target-Detection and Autocorrelation Performances

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

Sen, Satyabrata

2013-01-01

We propose an algorithm to directly synthesize in time-domain a constant-envelope transmit waveform that achieves the optimal performance in detecting an extended target in the presence of signal-dependent interference. This approach is in contrast to the traditional indirect methods that synthesize the transmit signal following the computation of the optimal energy spectral density. Additionally, we aim to maintain a good autocorrelation property of the designed signal. Therefore, our waveform design technique solves a bi-objective optimization problem in order to simultaneously improve the detection and autocorrelation performances, which are in general conflicting in nature. We demonstrate this compromising characteristics of themore » detection and autocorrelation performances with numerical examples. Furthermore, in the absence of the autocorrelation criterion, our designed signal is shown to achieve a near-optimum detection performance.« less

Correlation functions for Hermitian many-body systems: Necessary conditions

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

Brown, E.B.

1994-02-01

Lee [Phys. Rev. B 47, 8293 (1993)] has shown that the odd-numbered derivatives of the Kubo autocorrelation function vanish at [ital t]=0. We show that this condition is based on a more general property of nondiagonal Kubo correlation functions. This general property provides that certain functional forms (e.g., simple exponential decay) are not admissible for any symmetric or antisymmetric Kubo correlation function in a Hermitian many-body system. Lee's result emerges as a special case of this result. Applications to translationally invariant systems and systems with rotational symmetries are also demonstrated.

Spatio-temporal wildland arson crime functions

Treesearch

David T. Butry; Jeffrey P. Prestemon

2005-01-01

Wildland arson creates damages to structures and timber and affects the health and safety of people living in rural and wildland urban interface areas. We develop a model that incorporates temporal autocorrelations and spatial correlations in wildland arson ignitions in Florida. A Poisson autoregressive model of order p, or PAR(p)...

Identifying variably saturated water-flow patterns in a steep hillslope under intermittent heavy rainfall

USGS Publications Warehouse

El-Kadi, A. I.; Torikai, J.D.

2001-01-01

The objective of this paper is to identify water-flow patterns in part of an active landslide, through the use of numerical simulations and data obtained during a field study. The approaches adopted include measuring rainfall events and pore-pressure responses in both saturated and unsaturated soils at the site. To account for soil variability, the Richards equation is solved within deterministic and stochastic frameworks. The deterministic simulations considered average water-retention data, adjusted retention data to account for stones or cobbles, retention functions for a heterogeneous pore structure, and continuous retention functions for preferential flow. The stochastic simulations applied the Monte Carlo approach which considers statistical distribution and autocorrelation of the saturated conductivity and its cross correlation with the retention function. Although none of the models is capable of accurately predicting field measurements, appreciable improvement in accuracy was attained using stochastic, preferential flow, and heterogeneous pore-structure models. For the current study, continuum-flow models provide reasonable accuracy for practical purposes, although they are expected to be less accurate than multi-domain preferential flow models.

Experimental evidence of the self-similarity and long-range correlations of the edge fluctuations in HT-6M tokamak

NASA Astrophysics Data System (ADS)

Wang, Wen-hao; Yu, Chang-xuan; Wen, Yi-zhi; Xu, Yu-hong; Ling, Bi-li; Gong, Xian-zu; Liu, Bao-hua; Wan, Bao-nian

2001-02-01

For a better understanding of long timescale transport dynamics, the rescaled range analysis techniques, the autocorrelation function (ACF) and the probability distribution function (PDF) are used to investigate long-range dependences in edge plasma fluctuations in an HT-6M tokamak. The results reveal the self-similar characters of the electrostatic fluctuations with self-similarity parameters (Hurst exponent) ranging from 0.64 to 0.79, taking into consideration the Er×B rotation-sheared effect. Fluctuation ACFs of both the ion saturation current and the floating potential, as well as PDF of the turbulence-induced particle flux, have two distinct timescales. One corresponds to the decorrelation timescale of local fluctuations (µs) and the other lasts to the order of the confinement time (ms). All these experimental results suggest that some of the mechanisms of the underlying turbulence are consistent with plasma transport as characterized by self-organized criticality (SOC).

The Effects of Autocorrelation on the Curve-of-Factors Growth Model

ERIC Educational Resources Information Center

Murphy, Daniel L.; Beretvas, S. Natasha; Pituch, Keenan A.

2011-01-01

This simulation study examined the performance of the curve-of-factors model (COFM) when autocorrelation and growth processes were present in the first-level factor structure. In addition to the standard curve-of factors growth model, 2 new models were examined: one COFM that included a first-order autoregressive autocorrelation parameter, and a…

Carbonaceous aerosol at two rural locations in New York State: Characterization and behavior

NASA Astrophysics Data System (ADS)

Sunder Raman, Ramya; Hopke, Philip K.; Holsen, Thomas M.

2008-06-01

Fine particle samples were collected to determine the chemical constituents in PM2.5 at two rural background sites (Potsdam and Stockton, N. Y.) in the northeastern United States from November 2002 to August 2005. Samples were collected every third day for 24 h with a speciation network sampler. The measured carbonaceous species included thermal-optical organic carbon (OC), elemental carbon (EC), pyrolytic carbon (OP), black carbon (BC), and water-soluble, short-chain (WSSC) organic acids. Concentration time series, autocorrelations, and seasonal variations of the carbonaceous species were examined. During this multiyear period, the contributions of the total carbon (OC + EC) to the measured fine particle mass were 31.2% and 31.1% at Potsdam and Stockton, respectively. The average sum of the WSSC acids carbon accounted for approximately 2.5% of the organic carbon at Potsdam and 3.0% at Stockton. At Potsdam, the seasonal differences in the autocorrelation function (ACF) and partial autocorrelation function (PACF) values for carbonaceous species suggest that secondary formation may be an important contributor to the observed concentrations of species likely to be secondary in origin, particularly during the photochemically active time of the year (May to October). This study also investigated the relationships between carbonaceous species to better understand the behavior of carbonaceous aerosol and to assess the contribution of secondary organic carbon (SOC) to the total organic carbon mass (the EC tracer method was used to estimate SOC). At Potsdam the average SOC contribution to total OC varied between 66% and 72%, while at Stockton it varied between 58% and 64%.

Analysis of stochastic characteristics of the Benue River flow process

NASA Astrophysics Data System (ADS)

Otache, Martins Y.; Bakir, Mohammad; Li, Zhijia

2008-05-01

Stochastic characteristics of the Benue River streamflow process are examined under conditions of data austerity. The streamflow process is investigated for trend, non-stationarity and seasonality for a time period of 26 years. Results of trend analyses with Mann-Kendall test show that there is no trend in the annual mean discharges. Monthly flow series examined with seasonal Kendall test indicate the presence of positive change in the trend for some months, especially the months of August, January, and February. For the stationarity test, daily and monthly flow series appear to be stationary whereas at 1%, 5%, and 10% significant levels, the stationarity alternative hypothesis is rejected for the annual flow series. Though monthly flow appears to be stationary going by this test, because of high seasonality, it could be said to exhibit periodic stationarity based on the seasonality analysis. The following conclusions are drawn: (1) There is seasonality in both the mean and variance with unimodal distribution. (2) Days with high mean also have high variance. (3) Skewness coefficients for the months within the dry season period are greater than those of the wet season period, and seasonal autocorrelations for streamflow during dry season are generally larger than those of the wet season. Precisely, they are significantly different for most of the months. (4) The autocorrelation functions estimated “over time” are greater in the absolute value for data that have not been deseasonalised but were initially normalised by logarithmic transformation only, while autocorrelation functions for i = 1, 2, ..., 365 estimated “over realisations” have their coefficients significantly different from other coefficients.

Narayanaswamy's 1971 aging theory and material time

NASA Astrophysics Data System (ADS)

Dyre, Jeppe C.

2015-09-01

The Bochkov-Kuzovlev nonlinear fluctuation-dissipation theorem is used to derive Narayanaswamy's phenomenological theory of physical aging, in which this highly nonlinear phenomenon is described by a linear material-time convolution integral. A characteristic property of the Narayanaswamy aging description is material-time translational invariance, which is here taken as the basic assumption of the derivation. It is shown that only one possible definition of the material time obeys this invariance, namely, the square of the distance travelled from a configuration of the system far back in time. The paper concludes with suggestions for computer simulations that test for consequences of material-time translational invariance. One of these is the "unique-triangles property" according to which any three points on the system's path form a triangle such that two side lengths determine the third; this is equivalent to the well-known triangular relation for time-autocorrelation functions of aging spin glasses [L. F. Cugliandolo and J. Kurchan, J. Phys. A: Math. Gen. 27, 5749 (1994)]. The unique-triangles property implies a simple geometric interpretation of out-of-equilibrium time-autocorrelation functions, which extends to aging a previously proposed framework for such functions in equilibrium [J. C. Dyre, e-print arXiv:cond-mat/9712222 (1997)].

Factors Influencing Army Accessions.

DTIC Science & Technology

1982-12-01

partial autocorrelations were examined for significant lags or a recognizable pattern such as a damped exponential or a sine wave. The TSP prugrams...decreasing function indicating nonstation- *arity or a very long sine wave where only a small portion of the wave is plotted. The partial...plot of the raw data appeared (Appendix E-1) to be either the middle of a long sine wave or a linearly decreasing function. This pattern is recognized

Parallel auto-correlative statistics with VTK.

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

Pebay, Philippe Pierre; Bennett, Janine Camille

2013-08-01

This report summarizes existing statistical engines in VTK and presents both the serial and parallel auto-correlative statistics engines. It is a sequel to [PT08, BPRT09b, PT09, BPT09, PT10] which studied the parallel descriptive, correlative, multi-correlative, principal component analysis, contingency, k-means, and order statistics engines. The ease of use of the new parallel auto-correlative statistics engine is illustrated by the means of C++ code snippets and algorithm verification is provided. This report justifies the design of the statistics engines with parallel scalability in mind, and provides scalability and speed-up analysis results for the autocorrelative statistics engine.

False alarms: How early warning signals falsely predict abrupt sea ice loss

NASA Astrophysics Data System (ADS)

Wagner, Till J. W.; Eisenman, Ian

2016-04-01

Uncovering universal early warning signals for critical transitions has become a coveted goal in diverse scientific disciplines, ranging from climate science to financial mathematics. There has been a flurry of recent research proposing such signals, with increasing autocorrelation and increasing variance being among the most widely discussed candidates. A number of studies have suggested that increasing autocorrelation alone may suffice to signal an impending transition, although some others have questioned this. Here we consider variance and autocorrelation in the context of sea ice loss in an idealized model of the global climate system. The model features no bifurcation, nor increased rate of retreat, as the ice disappears. Nonetheless, the autocorrelation of summer sea ice area is found to increase in a global warming scenario. The variance, by contrast, decreases. A simple physical mechanism is proposed to explain the occurrence of increasing autocorrelation but not variance when there is no approaching bifurcation. Additionally, a similar mechanism is shown to allow an increase in both indicators with no physically attainable bifurcation. This implies that relying on autocorrelation and variance as early warning signals can raise false alarms in the climate system, warning of "tipping points" that are not actually there.

Geometrical optical transfer function: is it worth calculating?

PubMed

Díaz, José A; Mahajan, Virendra N

2017-10-01

In this paper, we explore the merit of calculating the geometrical optical transfer function (GOTF) in optical design by comparing the time to calculate it with the time to calculate the diffraction optical transfer function (DOTF). We determine the DOTF by numerical integration of the pupil function autocorrelation (that reduces to an integration of a complex exponential of the aberration difference function), 2D digital autocorrelation of the pupil function, and the Fourier transform (FT) of the point-spread function (PSF); and we determine the GOTF by the FT of the geometrical PSF (that reduces to an integration over the pupil plane of a complex exponential that is a scalar product of the spatial frequency and transverse ray aberration vectors) and the FT of the spot diagram. Our starting point for calculating the DOTF is the wave aberrations of the system in its pupil plane, and the transverse ray aberrations in the image plane for the GOTF. Numerical results for primary aberrations and some typical imaging systems show that the direct numerical integrations are slow, but the GOTF calculation by a FT of the spot diagram is two or even three times slower than the DOTF calculation by an FT of the PSF, depending on the aberration. We conclude that the calculation of GOTF is, at best, an approximation of the DOTF and only for large aberrations; GOTF does not offer any advantage in the optical design process, and hence negates its utility.

Demonstration of a real-time interferometer as a bunch-length monitor in a high-current electron beam accelerator.

PubMed

Thangaraj, J; Andonian, G; Thurman-Keup, R; Ruan, J; Johnson, A S; Lumpkin, A; Santucci, J; Maxwell, T; Murokh, A; Ruelas, M; Ovodenko, A

2012-04-01

A real-time interferometer (RTI) has been developed to monitor the bunch length of an electron beam in an accelerator. The RTI employs spatial autocorrelation, reflective optics, and a fast response pyro-detector array to obtain a real-time autocorrelation trace of the coherent radiation from an electron beam thus providing the possibility of online bunch-length diagnostics. A complete RTI system has been commissioned at the A0 photoinjector facility to measure sub-mm bunches at 13 MeV. Bunch length variation (FWHM) between 0.8 ps (~0.24 mm) and 1.5 ps (~0.45 mm) has been measured and compared with a Martin-Puplett interferometer and a streak camera. The comparisons show that RTI is a viable, complementary bunch length diagnostic for sub-mm electron bunches. © 2012 American Institute of Physics

Violations of Assumptions in School-Based Single-Case Data: Implications for the Selection and Interpretation of Effect Sizes.

PubMed

Solomon, Benjamin George

2014-07-01

A wide variety of effect sizes (ESs) has been used in the single-case design literature. Several researchers have "stress tested" these ESs by subjecting them to various degrees of problem data (e.g., autocorrelation, slope), resulting in the conditions by which different ESs can be considered valid. However, on the back end, few researchers have considered how prevalent and severe these problems are in extant data and as a result, how concerned applied researchers should be. The current study extracted and aggregated indicators of violations of normality and independence across four domains of educational study. Significant violations were found in total and across fields, including low levels of autocorrelation and moderate levels of absolute trend. These violations affect the selection and interpretation of ESs at the individual study level and for meta-analysis. Implications and recommendations are discussed. © The Author(s) 2013.

Demonstration of a real-time interferometer as a bunch-lenght monitor in a high-current electron beam accelerator

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

Thangaraj, J.; Thurman-Keup, R.; Ruan, J.

2012-03-01

A real-time interferometer (RTI) has been developed to monitor the bunch length of an electron beam in an accelerator. The RTI employs spatial autocorrelation, reflective optics, and a fast response pyro-detector array to obtain a real-time autocorrelation trace of the coherent radiation from an electron beam thus providing the possibility of online bunch-length diagnostics. A complete RTI system has been commissioned at the A0 photoinjector facility to measure sub-mm bunches at 13 MeV. Bunch length variation (FWHM) between 0.8 ps (-0.24 mm) and 1.5 ps (-0.45 mm) has been measured and compared with a Martin-Puplett interferometer and a streak camera.more » The comparisons show that RTI is a viable, complementary bunch length diagnostic for sub-mm electron bunches.« less

Demonstration of a real-time interferometer as a bunch-length monitor in a high-current electron beam accelerator

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

Thangaraj, J.; Thurman-Keup, R.; Ruan, J.

2012-04-15

A real-time interferometer (RTI) has been developed to monitor the bunch length of an electron beam in an accelerator. The RTI employs spatial autocorrelation, reflective optics, and a fast response pyro-detector array to obtain a real-time autocorrelation trace of the coherent radiation from an electron beam thus providing the possibility of online bunch-length diagnostics. A complete RTI system has been commissioned at the A0 photoinjector facility to measure sub-mm bunches at 13 MeV. Bunch length variation (FWHM) between 0.8 ps ({approx}0.24 mm) and 1.5 ps ({approx}0.45 mm) has been measured and compared with a Martin-Puplett interferometer and a streak camera.more » The comparisons show that RTI is a viable, complementary bunch length diagnostic for sub-mm electron bunches.« less

Time-series analysis of delta13C from tree rings. I. Time trends and autocorrelation.

PubMed

Monserud, R A; Marshall, J D

2001-09-01

Univariate time-series analyses were conducted on stable carbon isotope ratios obtained from tree-ring cellulose. We looked for the presence and structure of autocorrelation. Significant autocorrelation violates the statistical independence assumption and biases hypothesis tests. Its presence would indicate the existence of lagged physiological effects that persist for longer than the current year. We analyzed data from 28 trees (60-85 years old; mean = 73 years) of western white pine (Pinus monticola Dougl.), ponderosa pine (Pinus ponderosa Laws.), and Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco var. glauca) growing in northern Idaho. Material was obtained by the stem analysis method from rings laid down in the upper portion of the crown throughout each tree's life. The sampling protocol minimized variation caused by changing light regimes within each tree. Autoregressive moving average (ARMA) models were used to describe the autocorrelation structure over time. Three time series were analyzed for each tree: the stable carbon isotope ratio (delta(13)C); discrimination (delta); and the difference between ambient and internal CO(2) concentrations (c(a) - c(i)). The effect of converting from ring cellulose to whole-leaf tissue did not affect the analysis because it was almost completely removed by the detrending that precedes time-series analysis. A simple linear or quadratic model adequately described the time trend. The residuals from the trend had a constant mean and variance, thus ensuring stationarity, a requirement for autocorrelation analysis. The trend over time for c(a) - c(i) was particularly strong (R(2) = 0.29-0.84). Autoregressive moving average analyses of the residuals from these trends indicated that two-thirds of the individual tree series contained significant autocorrelation, whereas the remaining third were random (white noise) over time. We were unable to distinguish between individuals with and without significant autocorrelation beforehand. Significant ARMA models were all of low order, with either first- or second-order (i.e., lagged 1 or 2 years, respectively) models performing well. A simple autoregressive (AR(1)), model was the most common. The most useful generalization was that the same ARMA model holds for each of the three series (delta(13)C, delta, c(a) - c(i)) for an individual tree, if the time trend has been properly removed for each series. The mean series for the two pine species were described by first-order ARMA models (1-year lags), whereas the Douglas-fir mean series were described by second-order models (2-year lags) with negligible first-order effects. Apparently, the process of constructing a mean time series for a species preserves an underlying signal related to delta(13)C while canceling some of the random individual tree variation. Furthermore, the best model for the overall mean series (e.g., for a species) cannot be inferred from a consensus of the individual tree model forms, nor can its parameters be estimated reliably from the mean of the individual tree parameters. Because two-thirds of the individual tree time series contained significant autocorrelation, the normal assumption of a random structure over time is unwarranted, even after accounting for the time trend. The residuals of an appropriate ARMA model satisfy the independence assumption, and can be used to make hypothesis tests.

A Search for Quasi-periodic Oscillations in the Blazar 1ES 1959+650

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

Li, Xiao-Pan; Luo, Yu-Hui; Yang, Hai-Yan

We have searched quasi-periodic oscillations (QPOs) in the 15 GHz light curve of the BL Lac object 1ES 1959+650 monitored by the Owens Valley Radio Observatory 40 m telescope during the period from 2008 January to 2016 February, using the Lomb–Scargle Periodogram, power spectral density (PSD), discrete autocorrelation function, and phase dispersion minimization (PDM) techniques. The red noise background has been established via the PSD method, and no QPO can be derived at the 3 σ confidence level accounting for the impact of the red noise variability. We conclude that the light curve of 1ES 1959+650 can be explained bymore » a stochastic red noise process that contributes greatly to the total observed variability amplitude, dominates the power spectrum, causes spurious bumps and wiggles in the autocorrelation function and can result in the variance of the folded light curve decreasing toward lower temporal frequencies when few-cycle, sinusoid-like patterns are present. Moreover, many early supposed periodicity claims for blazar light curves need to be reevaluated assuming red noise.« less

Statistical, time series, and fractal analysis of full stretch of river Yamuna (India) for water quality management.

PubMed

Parmar, Kulwinder Singh; Bhardwaj, Rashmi

2015-01-01

River water is a major resource of drinking water on earth. Management of river water is highly needed for surviving. Yamuna is the main river of India, and monthly variation of water quality of river Yamuna, using statistical methods have been compared at different sites for each water parameters. Regression, correlation coefficient, autoregressive integrated moving average (ARIMA), box-Jenkins, residual autocorrelation function (ACF), residual partial autocorrelation function (PACF), lag, fractal, Hurst exponent, and predictability index have been estimated to analyze trend and prediction of water quality. Predictive model is useful at 95% confidence limits and all water parameters reveal platykurtic curve. Brownian motion (true random walk) behavior exists at different sites for BOD, AMM, and total Kjeldahl nitrogen (TKN). Quality of Yamuna River water at Hathnikund is good, declines at Nizamuddin, Mazawali, Agra D/S, and regains good quality again at Juhikha. For all sites, almost all parameters except potential of hydrogen (pH), water temperature (WT) crosses the prescribed limits of World Health Organization (WHO)/United States Environmental Protection Agency (EPA).

Sound quality characteristics of refrigerator noise in real living environments with relation to psychoacoustical and autocorrelation function parameters.

PubMed

Sato, Shin-ichi; You, Jin; Jeon, Jin Yong

2007-07-01

Psychoacoustical and autocorrelation function (ACF) parameters were employed to describe the temporal fluctuations of refrigerator noise during starting, transition into/from the stationary phase and termination of operation. The temporal fluctuations of refrigerator noise include a click at start-up, followed by a rapid increase in volume, a change of pitch, and termination of the operation. Subjective evaluations of the noise of 24 different refrigerators were conducted in a real living environment. The relationship between objective measures and perceived noisiness was examined by multiple regression analysis. Sound quality indices were developed based on psychoacoustical and ACF parameters. The psychoacoustical parameters found to be important for evaluating noisiness in the stationary phase were loudness and roughness. The relationship between noisiness and ACF parameters shows that sound energy and its fluctuations are important for evaluating noisiness. Also, refrigerator sounds that had a fluctuation of pitch were rated as more annoying. The tolerance level for the starting phase of refrigerator noise was found to be 33 dBA, which is the level where 65% of the participants in the subjective tests were satisfied.

DYNAMICS OF SELF-GRAVITY WAKES IN DENSE PLANETARY RINGS. I. PITCH ANGLE

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

Michikoshi, Shugo; Kokubo, Eiichiro; Fujii, Akihiko

2015-10-20

We investigate the dynamics of self-gravity wakes in dense planetary rings. In particular, we examine how the pitch angles of self-gravity wakes depend on ring parameters using N-body simulations. We calculate the pitch angles using the two-dimensional autocorrelation function of the ring surface density. We obtain the pitch angles for the inner and outer parts of the autocorrelation function separately. We confirm that the pitch angles are 15°–30° for reasonable ring parameters, which are consistent with previous studies. We find that the inner pitch angle increases with the Saturnicentric distance, while it barely depends on the optical depth and themore » restitution coefficient of ring particles. The increase of the inner pitch angle with the Saturnicentric distance is consistent with the observations of the A ring. The outer pitch angle does not have a clear dependence on any ring parameters and is about 10°–15°. This value is consistent with the pitch angle of spiral arms in collisionless systems.« less

Statistical Approach To Extraction Of Texture In SAR

NASA Technical Reports Server (NTRS)

Rignot, Eric J.; Kwok, Ronald

1992-01-01

Improved statistical method of extraction of textural features in synthetic-aperture-radar (SAR) images takes account of effects of scheme used to sample raw SAR data, system noise, resolution of radar equipment, and speckle. Treatment of speckle incorporated into overall statistical treatment of speckle, system noise, and natural variations in texture. One computes speckle auto-correlation function from system transfer function that expresses effect of radar aperature and incorporates range and azimuth resolutions.

The use of spatio-temporal correlation to forecast critical transitions

NASA Astrophysics Data System (ADS)

Karssenberg, Derek; Bierkens, Marc F. P.

2010-05-01

Complex dynamical systems may have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been observed in systems ranging from the human body system to financial markets and the Earth system. Forecasting the timing of critical transitions before they are reached is of paramount importance because critical transitions are associated with a large shift in dynamical regime of the system under consideration. However, it is hard to forecast critical transitions, because the state of the system shows relatively little change before the threshold is reached. Recently, it was shown that increased spatio-temporal autocorrelation and variance can serve as alternative early warning signal for critical transitions. However, thus far these second order statistics have not been used for forecasting in a data assimilation framework. Here we show that the use of spatio-temporal autocorrelation and variance in the state of the system reduces the uncertainty in the predicted timing of critical transitions compared to classical approaches that use the value of the system state only. This is shown by assimilating observed spatio-temporal autocorrelation and variance into a dynamical system model using a Particle Filter. We adapt a well-studied distributed model of a logistically growing resource with a fixed grazing rate. The model describes the transition from an underexploited system with high resource biomass to overexploitation as grazing pressure crosses the critical threshold, which is a fold bifurcation. To represent limited prior information, we use a large variance in the prior probability distributions of model parameters and the system driver (grazing rate). First, we show that the rate of increase in spatio-temporal autocorrelation and variance prior to reaching the critical threshold is relatively consistent across the uncertainty range of the driver and parameter values used. This indicates that an increase in spatio-temporal autocorrelation and variance are consistent predictors of a critical transition, even under the condition of a poorly defined system. Second, we perform data assimilation experiments using an artificial exhaustive data set generated by one realization of the model. To mimic real-world sampling, an observational data set is created from this exhaustive data set. This is done by sampling on a regular spatio-temporal grid, supplemented by sampling locations at a short distance. Spatial and temporal autocorrelation in this observational data set is calculated for different spatial and temporal separation (lag) distances. To assign appropriate weights to observations (here, autocorrelation values and variance) in the Particle Filter, the covariance matrix of the error in these observations is required. This covariance matrix is estimated using Monte Carlo sampling, selecting a different random position of the sampling network relative to the exhaustive data set for each realization. At each update moment in the Particle Filter, observed autocorrelation values are assimilated into the model and the state of the model is updated. Using this approach, it is shown that the use of autocorrelation reduces the uncertainty in the forecasted timing of a critical transition compared to runs without data assimilation. The performance of the use of spatial autocorrelation versus temporal autocorrelation depends on the timing and number of observational data. This study is restricted to a single model only. However, it is becoming increasingly clear that spatio-temporal autocorrelation and variance can be used as early warning signals for a large number of systems. Thus, it is expected that spatio-temporal autocorrelation and variance are valuable in data assimilation frameworks in a large number of dynamical systems.

Inferential Precision in Single-Case Time-Series Data Streams: How Well Does the EM Procedure Perform When Missing Observations Occur in Autocorrelated Data?

PubMed Central

Smith, Justin D.; Borckardt, Jeffrey J.; Nash, Michael R.

2013-01-01

The case-based time-series design is a viable methodology for treatment outcome research. However, the literature has not fully addressed the problem of missing observations with such autocorrelated data streams. Mainly, to what extent do missing observations compromise inference when observations are not independent? Do the available missing data replacement procedures preserve inferential integrity? Does the extent of autocorrelation matter? We use Monte Carlo simulation modeling of a single-subject intervention study to address these questions. We find power sensitivity to be within acceptable limits across four proportions of missing observations (10%, 20%, 30%, and 40%) when missing data are replaced using the Expectation-Maximization Algorithm, more commonly known as the EM Procedure (Dempster, Laird, & Rubin, 1977).This applies to data streams with lag-1 autocorrelation estimates under 0.80. As autocorrelation estimates approach 0.80, the replacement procedure yields an unacceptable power profile. The implications of these findings and directions for future research are discussed. PMID:22697454

Effects of autocorrelation upon LANDSAT classification accuracy. [Richmond, Virginia and Denver, Colorado

NASA Technical Reports Server (NTRS)

Craig, R. G. (Principal Investigator)

1983-01-01

Richmond, Virginia and Denver, Colorado were study sites in an effort to determine the effect of autocorrelation on the accuracy of a parallelopiped classifier of LANDSAT digital data. The autocorrelation was assumed to decay to insignificant levels when sampled at distances of at least ten pixels. Spectral themes developed using blocks of adjacent pixels, and using groups of pixels spaced at least 10 pixels apart were used. Effects of geometric distortions were minimized by using only pixels from the interiors of land cover sections. Accuracy was evaluated for three classes; agriculture, residential and "all other"; both type 1 and type 2 errors were evaluated by means of overall classification accuracy. All classes give comparable results. Accuracy is approximately the same in both techniques; however, the variance in accuracy is significantly higher using the themes developed from autocorrelated data. The vectors of mean spectral response were nearly identical regardless of sampling method used. The estimated variances were much larger when using autocorrelated pixels.

Negligible influence of spatial autocorrelation in the assessment of fire effects in a mixed conifer forest

USGS Publications Warehouse

van Mantgem, P.J.; Schwilk, D.W.

2009-01-01

Fire is an important feature of many forest ecosystems, although the quantification of its effects is compromised by the large scale at which fire occurs and its inherent unpredictability. A recurring problem is the use of subsamples collected within individual burns, potentially resulting in spatially autocorrelated data. Using subsamples from six different fires (and three unburned control areas) we show little evidence for strong spatial autocorrelation either before or after burning for eight measures of forest conditions (both fuels and vegetation). Additionally, including a term for spatially autocorrelated errors provided little improvement for simple linear models contrasting the effects of early versus late season burning. While the effects of spatial autocorrelation should always be examined, it may not always greatly influence assessments of fire effects. If high patch scale variability is common in Sierra Nevada mixed conifer forests, even following more than a century of fire exclusion, treatments designed to encourage further heterogeneity in forest conditions prior to the reintroduction of fire will likely be unnecessary.

Calling depths of baleen whales from single sensor data: development of an autocorrelation method using multipath localization.

PubMed

Valtierra, Robert D; Glynn Holt, R; Cholewiak, Danielle; Van Parijs, Sofie M

2013-09-01

Multipath localization techniques have not previously been applied to baleen whale vocalizations due to difficulties in application to tonal vocalizations. Here it is shown that an autocorrelation method coupled with the direct reflected time difference of arrival localization technique can successfully resolve location information. A derivation was made to model the autocorrelation of a direct signal and its overlapping reflections to illustrate that an autocorrelation may be used to extract reflection information from longer duration signals containing a frequency sweep, such as some calls produced by baleen whales. An analysis was performed to characterize the difference in behavior of the autocorrelation when applied to call types with varying parameters (sweep rate, call duration). The method's feasibility was tested using data from playback transmissions to localize an acoustic transducer at a known depth and location. The method was then used to estimate the depth and range of a single North Atlantic right whale (Eubalaena glacialis) and humpback whale (Megaptera novaeangliae) from two separate experiments.

Rapid and stable measurement of respiratory rate from Doppler radar signals using time domain autocorrelation model.

PubMed

Sun, Guanghao; Matsui, Takemi

2015-01-01

Noncontact measurement of respiratory rate using Doppler radar will play a vital role in future clinical practice. Doppler radar remotely monitors the tiny chest wall movements induced by respiration activity. The most competitive advantage of this technique is to allow users fully unconstrained with no biological electrode attachments. However, the Doppler radar, unlike other contact-type sensors, is easily affected by the random body movements. In this paper, we proposed a time domain autocorrelation model to process the radar signals for rapid and stable estimation of the respiratory rate. We tested the autocorrelation model on 8 subjects in laboratory, and compared the respiratory rates detected by noncontact radar with reference contact-type respiratory effort belt. Autocorrelation model showed the effects of reducing the random body movement noise added to Doppler radar's respiration signals. Moreover, the respiratory rate can be rapidly calculated from the first main peak in the autocorrelation waveform within 10 s.

Scilab software package for the study of dynamical systems

NASA Astrophysics Data System (ADS)

Bordeianu, C. C.; Beşliu, C.; Jipa, Al.; Felea, D.; Grossu, I. V.

2008-05-01

This work presents a new software package for the study of chaotic flows and maps. The codes were written using Scilab, a software package for numerical computations providing a powerful open computing environment for engineering and scientific applications. It was found that Scilab provides various functions for ordinary differential equation solving, Fast Fourier Transform, autocorrelation, and excellent 2D and 3D graphical capabilities. The chaotic behaviors of the nonlinear dynamics systems were analyzed using phase-space maps, autocorrelation functions, power spectra, Lyapunov exponents and Kolmogorov-Sinai entropy. Various well known examples are implemented, with the capability of the users inserting their own ODE. Program summaryProgram title: Chaos Catalogue identifier: AEAP_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEAP_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 885 No. of bytes in distributed program, including test data, etc.: 5925 Distribution format: tar.gz Programming language: Scilab 3.1.1 Computer: PC-compatible running Scilab on MS Windows or Linux Operating system: Windows XP, Linux RAM: below 100 Megabytes Classification: 6.2 Nature of problem: Any physical model containing linear or nonlinear ordinary differential equations (ODE). Solution method: Numerical solving of ordinary differential equations. The chaotic behavior of the nonlinear dynamical system is analyzed using Poincaré sections, phase-space maps, autocorrelation functions, power spectra, Lyapunov exponents and Kolmogorov-Sinai entropies. Restrictions: The package routines are normally able to handle ODE systems of high orders (up to order twelve and possibly higher), depending on the nature of the problem. Running time: 10 to 20 seconds for problems that do not involve Lyapunov exponents calculation; 60 to 1000 seconds for problems that involve high orders ODE and Lyapunov exponents calculation.

Early Warning Signals for Abrupt Change Raise False Alarm During Sea Ice Loss

NASA Astrophysics Data System (ADS)

Wagner, T. J. W.; Eisenman, I.

2015-12-01

Uncovering universal early warning signals for critical transitions has become a coveted goal in diverse scientific disciplines, ranging from climate science to financial mathematics. There has been a flurry of recent research proposing such signals, with increasing autocorrelation and increasing variance being among the most widely discussed candidates. A number of studies have suggested that increasing autocorrelation alone may suffice to signal an impending transition, although some others have questioned this. Here, we consider variance and autocorrelation in the context of sea ice loss in an idealized model of the global climate system. The model features no bifurcation, nor increased rate of retreat, as the ice disappears. Nonetheless, the autocorrelation of summer sea ice area is found to increase with diminishing sea ice cover in a global warming scenario. The variance, by contrast, decreases. A simple physical mechanism is proposed to explain the occurrence of increasing autocorrelation but not variance in the model when there is no approaching bifurcation. Additionally, a similar mechanism is shown to allow an increase in both indicators with no physically attainable bifurcation. This implies that relying on autocorrelation and variance as early warning signals can raise false alarms in the climate system, warning of "tipping points" that are not actually there.

The Azimuth Structure of Nuclear Collisions — I

NASA Astrophysics Data System (ADS)

Trainor, Thomas A.; Kettler, David T.

We describe azimuth structure commonly associated with elliptic and directed flow in the context of 2D angular autocorrelations for the purpose of precise separation of so-called nonflow (mainly minijets) from flow. We extend the Fourier-transform description of azimuth structure to include power spectra and autocorrelations related by the Wiener-Khintchine theorem. We analyze several examples of conventional flow analysis in that context and question the relevance of reaction plane estimation to flow analysis. We introduce the 2D angular autocorrelation with examples from data analysis and describe a simulation exercise which demonstrates precise separation of flow and nonflow using the 2D autocorrelation method. We show that an alternative correlation measure based on Pearson's normalized covariance provides a more intuitive measure of azimuth structure.

OmpF, a nucleotide-sensing nanoprobe, computational evaluation of single channel activities

NASA Astrophysics Data System (ADS)

Abdolvahab, R. H.; Mobasheri, H.; Nikouee, A.; Ejtehadi, M. R.

2016-09-01

The results of highthroughput practical single channel experiments should be formulated and validated by signal analysis approaches to increase the recognition precision of translocating molecules. For this purpose, the activities of the single nano-pore forming protein, OmpF, in the presence of nucleotides were recorded in real time by the voltage clamp technique and used as a means for nucleotide recognition. The results were analyzed based on the permutation entropy of current Time Series (TS), fractality, autocorrelation, structure function, spectral density, and peak fraction to recognize each nucleotide, based on its signature effect on the conductance, gating frequency and voltage sensitivity of channel at different concentrations and membrane potentials. The amplitude and frequency of ion current fluctuation increased in the presence of Adenine more than Cytosine and Thymine in milli-molar (0.5 mM) concentrations. The variance of the current TS at various applied voltages showed a non-monotonic trend whose initial increasing slope in the presence of Thymine changed to a decreasing one in the second phase and was different from that of Adenine and Cytosine; e.g., by increasing the voltage from 40 to 140 mV in the 0.5 mM concentration of Adenine or Cytosine, the variance decreased by one third while for the case of Thymine it was doubled. Moreover, according to the structure function of TS, the fractality of current TS differed as a function of varying membrane potentials (pd) and nucleotide concentrations. Accordingly, the calculated permutation entropy of the TS, validated the biophysical approach defined for the recognition of different nucleotides at various concentrations, pd's and polarities. Thus, the promising outcomes of the combined experimental and theoretical methodologies presented here can be implemented as a complementary means in pore-based nucleotide recognition approaches.

Image correlation and sampling study

NASA Technical Reports Server (NTRS)

Popp, D. J.; Mccormack, D. S.; Sedwick, J. L.

1972-01-01

The development of analytical approaches for solving image correlation and image sampling of multispectral data is discussed. Relevant multispectral image statistics which are applicable to image correlation and sampling are identified. The general image statistics include intensity mean, variance, amplitude histogram, power spectral density function, and autocorrelation function. The translation problem associated with digital image registration and the analytical means for comparing commonly used correlation techniques are considered. General expressions for determining the reconstruction error for specific image sampling strategies are developed.

Understanding the determinants of volatility clustering in terms of stationary Markovian processes

NASA Astrophysics Data System (ADS)

Miccichè, S.

2016-11-01

Volatility is a key variable in the modeling of financial markets. The most striking feature of volatility is that it is a long-range correlated stochastic variable, i.e. its autocorrelation function decays like a power-law τ-β for large time lags. In the present work we investigate the determinants of such feature, starting from the empirical observation that the exponent β of a certain stock's volatility is a linear function of the average correlation of such stock's volatility with all other volatilities. We propose a simple approach consisting in diagonalizing the cross-correlation matrix of volatilities and investigating whether or not the diagonalized volatilities still keep some of the original volatility stylized facts. As a result, the diagonalized volatilities result to share with the original volatilities either the power-law decay of the probability density function and the power-law decay of the autocorrelation function. This would indicate that volatility clustering is already present in the diagonalized un-correlated volatilities. We therefore present a parsimonious univariate model based on a non-linear Langevin equation that well reproduces these two stylized facts of volatility. The model helps us in understanding that the main source of volatility clustering, once volatilities have been diagonalized, is that the economic forces driving volatility can be modeled in terms of a Smoluchowski potential with logarithmic tails.

Linking snowflake microstructure to multi-frequency radar observations

NASA Astrophysics Data System (ADS)

Leinonen, J.; Moisseev, D.; Nousiainen, T.

2013-04-01

Spherical or spheroidal particle shape models are commonly used to calculate numerically the radar backscattering properties of aggregate snowflakes. A more complicated and computationally intensive approach is to use detailed models of snowflake structure together with numerical scattering models that can operate on arbitrary particle shapes. Recent studies have shown that there can be significant differences between the results of these approaches. In this paper, an analytical model, based on the Rayleigh-Gans scattering theory, is formulated to explain this discrepancy in terms of the effect of discrete ice crystals that constitute the snowflake. The ice crystals cause small-scale inhomogeneities whose effects can be understood through the density autocorrelation function of the particle mass, which the Rayleigh-Gans theory connects to the function that gives the radar reflectivity as a function of frequency. The derived model is a weighted sum of two Gaussian functions. A term that corresponds to the average shape of the particle, similar to that given by the spheroidal shape model, dominates at low frequencies. At high frequencies, that term vanishes and is gradually replaced by the effect of the ice crystal monomers. The autocorrelation-based description of snowflake microstructure appears to be sufficient for multi-frequency radar studies. The link between multi-frequency radar observations and the particle microstructure can thus be used to infer particle properties from the observations.

Narayanaswamy’s 1971 aging theory and material time

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

Dyre, Jeppe C., E-mail: dyre@ruc.dk

2015-09-21

The Bochkov-Kuzovlev nonlinear fluctuation-dissipation theorem is used to derive Narayanaswamy’s phenomenological theory of physical aging, in which this highly nonlinear phenomenon is described by a linear material-time convolution integral. A characteristic property of the Narayanaswamy aging description is material-time translational invariance, which is here taken as the basic assumption of the derivation. It is shown that only one possible definition of the material time obeys this invariance, namely, the square of the distance travelled from a configuration of the system far back in time. The paper concludes with suggestions for computer simulations that test for consequences of material-time translational invariance.more » One of these is the “unique-triangles property” according to which any three points on the system’s path form a triangle such that two side lengths determine the third; this is equivalent to the well-known triangular relation for time-autocorrelation functions of aging spin glasses [L. F. Cugliandolo and J. Kurchan, J. Phys. A: Math. Gen. 27, 5749 (1994)]. The unique-triangles property implies a simple geometric interpretation of out-of-equilibrium time-autocorrelation functions, which extends to aging a previously proposed framework for such functions in equilibrium [J. C. Dyre, e-print arXiv:cond-mat/9712222 (1997)].« less

First-principles calculation of entropy for liquid metals.

PubMed

Desjarlais, Michael P

2013-12-01

We demonstrate the accurate calculation of entropies and free energies for a variety of liquid metals using an extension of the two-phase thermodynamic (2PT) model based on a decomposition of the velocity autocorrelation function into gas-like (hard sphere) and solid-like (harmonic) subsystems. The hard sphere model for the gas-like component is shown to give systematically high entropies for liquid metals as a direct result of the unphysical Lorentzian high-frequency tail. Using a memory function framework we derive a generally applicable velocity autocorrelation and frequency spectrum for the diffusive component which recovers the low-frequency (long-time) behavior of the hard sphere model while providing for realistic short-time coherence and high-frequency tails to the spectrum. This approach provides a significant increase in the accuracy of the calculated entropies for liquid metals and is compared to ambient pressure data for liquid sodium, aluminum, gallium, tin, and iron. The use of this method for the determination of melt boundaries is demonstrated with a calculation of the high-pressure bcc melt boundary for sodium. With the significantly improved accuracy available with the memory function treatment for softer interatomic potentials, the 2PT model for entropy calculations should find broader application in high energy density science, warm dense matter, planetary science, geophysics, and material science.

First-principles calculation of entropy for liquid metals

NASA Astrophysics Data System (ADS)

Desjarlais, Michael P.

2013-12-01

We demonstrate the accurate calculation of entropies and free energies for a variety of liquid metals using an extension of the two-phase thermodynamic (2PT) model based on a decomposition of the velocity autocorrelation function into gas-like (hard sphere) and solid-like (harmonic) subsystems. The hard sphere model for the gas-like component is shown to give systematically high entropies for liquid metals as a direct result of the unphysical Lorentzian high-frequency tail. Using a memory function framework we derive a generally applicable velocity autocorrelation and frequency spectrum for the diffusive component which recovers the low-frequency (long-time) behavior of the hard sphere model while providing for realistic short-time coherence and high-frequency tails to the spectrum. This approach provides a significant increase in the accuracy of the calculated entropies for liquid metals and is compared to ambient pressure data for liquid sodium, aluminum, gallium, tin, and iron. The use of this method for the determination of melt boundaries is demonstrated with a calculation of the high-pressure bcc melt boundary for sodium. With the significantly improved accuracy available with the memory function treatment for softer interatomic potentials, the 2PT model for entropy calculations should find broader application in high energy density science, warm dense matter, planetary science, geophysics, and material science.

Dissipative particle dynamics study of velocity autocorrelation function and self-diffusion coefficient in terms of interaction potential strength

NASA Astrophysics Data System (ADS)

Zohravi, Elnaz; Shirani, Ebrahim; Pishevar, Ahmadreza; Karimpour, Hossein

2018-07-01

This research focuses on numerically investigating the self-diffusion coefficient and velocity autocorrelation function (VACF) of a dissipative particle dynamics (DPD) fluid as a function of the conservative interaction strength. Analytic solutions to VACF and self-diffusion coefficients in DPD were obtained by many researchers in some restricted cases including ideal gases, without the account of conservative force. As departure from the ideal gas conditions are accentuated with increasing the relative proportion of conservative force, it is anticipated that the VACF should gradually deviate from its normally expected exponentially decay. This trend is confirmed through numerical simulations and an expression in terms of the conservative force parameter, density and temperature is proposed for the self-diffusion coefficient. As it concerned the VACF, the equivalent Langevin equation describing Brownian motion of particles with a harmonic potential is adapted to the problem and reveals an exponentially decaying oscillatory pattern influenced by the conservative force parameter, dissipative parameter and temperature. Although the proposed model for obtaining the self-diffusion coefficient with consideration of the conservative force could not be verified due to computational complexities, nonetheless the Arrhenius dependency of the self-diffusion coefficient to temperature and pressure permits to certify our model over a definite range of DPD parameters.

Thermal noise in confined fluids.

PubMed

Sanghi, T; Aluru, N R

2014-11-07

In this work, we discuss a combined memory function equation (MFE) and generalized Langevin equation (GLE) approach (referred to as MFE/GLE formulation) to characterize thermal noise in confined fluids. Our study reveals that for fluids confined inside nanoscale geometries, the correlation time and the time decay of the autocorrelation function of the thermal noise are not significantly different across the confinement. We show that it is the strong cross-correlation of the mean force with the molecular velocity that gives rise to the spatial anisotropy in the velocity-autocorrelation function of the confined fluids. Further, we use the MFE/GLE formulation to extract the thermal force a fluid molecule experiences in a MD simulation. Noise extraction from MD simulation suggests that the frequency distribution of the thermal force is non-Gaussian. Also, the frequency distribution of the thermal force near the confining surface is found to be different in the direction parallel and perpendicular to the confinement. We also use the formulation to compute the noise correlation time of water confined inside a (6,6) carbon-nanotube (CNT). It is observed that inside the (6,6) CNT, in which water arranges itself in a highly concerted single-file arrangement, the correlation time of thermal noise is about an order of magnitude higher than that of bulk water.

Thermal noise in confined fluids

NASA Astrophysics Data System (ADS)

Sanghi, T.; Aluru, N. R.

2014-11-01

In this work, we discuss a combined memory function equation (MFE) and generalized Langevin equation (GLE) approach (referred to as MFE/GLE formulation) to characterize thermal noise in confined fluids. Our study reveals that for fluids confined inside nanoscale geometries, the correlation time and the time decay of the autocorrelation function of the thermal noise are not significantly different across the confinement. We show that it is the strong cross-correlation of the mean force with the molecular velocity that gives rise to the spatial anisotropy in the velocity-autocorrelation function of the confined fluids. Further, we use the MFE/GLE formulation to extract the thermal force a fluid molecule experiences in a MD simulation. Noise extraction from MD simulation suggests that the frequency distribution of the thermal force is non-Gaussian. Also, the frequency distribution of the thermal force near the confining surface is found to be different in the direction parallel and perpendicular to the confinement. We also use the formulation to compute the noise correlation time of water confined inside a (6,6) carbon-nanotube (CNT). It is observed that inside the (6,6) CNT, in which water arranges itself in a highly concerted single-file arrangement, the correlation time of thermal noise is about an order of magnitude higher than that of bulk water.

Zero Autocorrelation Waveforms: A Doppler Statistic and Multifunction Problems

DTIC Science & Technology

2006-01-01

by ANSI Std Z39-18 It is natural to refer to A as the ambiguity function of u, since in the usual setting on the real line R, the analogue ambiguity...Doppler statistic |Cu,uek(j)| is excellent and provable for detecting deodorized Doppler frequency shift [11] (see Fig. 2). Also, if one graphs only

Comprehensive comparisons of geodesic acoustic mode characteristics and dynamics between Tore Supra experiments and gyrokinetic simulations

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

Storelli, A., E-mail: alexandre.storelli@lpp.polytechnique.fr; Vermare, L.; Hennequin, P.

2015-06-15

In a dedicated collisionality scan in Tore Supra, the geodesic acoustic mode (GAM) is detected and identified with the Doppler backscattering technique. Observations are compared to the results of a simulation with the gyrokinetic code GYSELA. We found that the GAM frequency in experiments is lower than predicted by simulation and theory. Moreover, the disagreement is higher in the low collisionality scenario. Bursts of non harmonic GAM oscillations have been characterized with filtering techniques, such as the Hilbert-Huang transform. When comparing this dynamical behaviour between experiments and simulation, the probability density function of GAM amplitude and the burst autocorrelation timemore » are found to be remarkably similar. In the simulation, where the radial profile of GAM frequency is continuous, we observed a phenomenon of radial phase mixing of the GAM oscillations, which could influence the burst autocorrelation time.« less

Geary autocorrelation and DCCA coefficient: Application to predict apoptosis protein subcellular localization via PSSM

NASA Astrophysics Data System (ADS)

Liang, Yunyun; Liu, Sanyang; Zhang, Shengli

2017-02-01

Apoptosis is a fundamental process controlling normal tissue homeostasis by regulating a balance between cell proliferation and death. Predicting subcellular location of apoptosis proteins is very helpful for understanding its mechanism of programmed cell death. Prediction of apoptosis protein subcellular location is still a challenging and complicated task, and existing methods mainly based on protein primary sequences. In this paper, we propose a new position-specific scoring matrix (PSSM)-based model by using Geary autocorrelation function and detrended cross-correlation coefficient (DCCA coefficient). Then a 270-dimensional (270D) feature vector is constructed on three widely used datasets: ZD98, ZW225 and CL317, and support vector machine is adopted as classifier. The overall prediction accuracies are significantly improved by rigorous jackknife test. The results show that our model offers a reliable and effective PSSM-based tool for prediction of apoptosis protein subcellular localization.

Rainfall statistics, stationarity, and climate change.

PubMed

Sun, Fubao; Roderick, Michael L; Farquhar, Graham D

2018-03-06

There is a growing research interest in the detection of changes in hydrologic and climatic time series. Stationarity can be assessed using the autocorrelation function, but this is not yet common practice in hydrology and climate. Here, we use a global land-based gridded annual precipitation (hereafter P ) database (1940-2009) and find that the lag 1 autocorrelation coefficient is statistically significant at around 14% of the global land surface, implying nonstationary behavior (90% confidence). In contrast, around 76% of the global land surface shows little or no change, implying stationary behavior. We use these results to assess change in the observed P over the most recent decade of the database. We find that the changes for most (84%) grid boxes are within the plausible bounds of no significant change at the 90% CI. The results emphasize the importance of adequately accounting for natural variability when assessing change. Copyright © 2018 the Author(s). Published by PNAS.

Rainfall statistics, stationarity, and climate change

NASA Astrophysics Data System (ADS)

Sun, Fubao; Roderick, Michael L.; Farquhar, Graham D.

2018-03-01

There is a growing research interest in the detection of changes in hydrologic and climatic time series. Stationarity can be assessed using the autocorrelation function, but this is not yet common practice in hydrology and climate. Here, we use a global land-based gridded annual precipitation (hereafter P) database (1940–2009) and find that the lag 1 autocorrelation coefficient is statistically significant at around 14% of the global land surface, implying nonstationary behavior (90% confidence). In contrast, around 76% of the global land surface shows little or no change, implying stationary behavior. We use these results to assess change in the observed P over the most recent decade of the database. We find that the changes for most (84%) grid boxes are within the plausible bounds of no significant change at the 90% CI. The results emphasize the importance of adequately accounting for natural variability when assessing change.

First-passage problems: A probabilistic dynamic analysis for degraded structures

NASA Technical Reports Server (NTRS)

Shiao, Michael C.; Chamis, Christos C.

1990-01-01

Structures subjected to random excitations with uncertain system parameters degraded by surrounding environments (a random time history) are studied. Methods are developed to determine the statistics of dynamic responses, such as the time-varying mean, the standard deviation, the autocorrelation functions, and the joint probability density function of any response and its derivative. Moreover, the first-passage problems with deterministic and stationary/evolutionary random barriers are evaluated. The time-varying (joint) mean crossing rate and the probability density function of the first-passage time for various random barriers are derived.

Very High-Frequency (VHF) ionospheric scintillation fading measurements at Lima, Peru

NASA Technical Reports Server (NTRS)

Blank, H. A.; Golden, T. S.

1972-01-01

During the spring equinox of 1970, scintillating signals at VHF (136.4 MHz) were observed at Lima, Peru. The transmission originated from ATS 3 and was observed through a pair of antennas spaced 1200 feet apart on an east-west baseline. The empirical data were digitized, reduced, and analyzed. The results include amplitude probability density and distribution functions, time autocorrelation functions, cross correlation functions for the spaced antennas, and appropriate spectral density functions. Results show estimates of the statistics of the ground diffraction pattern to gain insight into gross ionospheric irregularity size, and irregularity velocity in the antenna planes.

Ferroelectric optical image comparator

DOEpatents

Butler, M.A.; Land, C.E.; Martin, S.J.; Pfeifer, K.B.

1993-11-30

A ferroelectric optical image comparator has a lead lanthanum zirconate titanate thin-film device which is constructed with a semi-transparent or transparent conductive first electrode on one side of the thin film, a conductive metal second electrode on the other side of the thin film, and the second electrode is in contact with a nonconducting substrate. A photoinduced current in the device represents the dot product between a stored image and an image projected onto the first electrode. One-dimensional autocorrelations are performed by measuring this current while displacing the projected image. 7 figures.

Ferroelectric optical image comparator

DOEpatents

Butler, Michael A.; Land, Cecil E.; Martin, Stephen J.; Pfeifer, Kent B.

1993-01-01

A ferroelectric optical image comparator has a lead lanthanum zirconate titanate thin-film device which is constructed with a semi-transparent or transparent conductive first electrode on one side of the thin film, a conductive metal second electrode on the other side of the thin film, and the second electrode is in contact with a nonconducting substrate. A photoinduced current in the device represents the dot product between a stored image and an image projected onto the first electrode. One-dimensional autocorrelations are performed by measuring this current while displacing the projected image.

Continuous-Time Random Walk with multi-step memory: an application to market dynamics

NASA Astrophysics Data System (ADS)

Gubiec, Tomasz; Kutner, Ryszard

2017-11-01

An extended version of the Continuous-Time Random Walk (CTRW) model with memory is herein developed. This memory involves the dependence between arbitrary number of successive jumps of the process while waiting times between jumps are considered as i.i.d. random variables. This dependence was established analyzing empirical histograms for the stochastic process of a single share price on a market within the high frequency time scale. Then, it was justified theoretically by considering bid-ask bounce mechanism containing some delay characteristic for any double-auction market. Our model appeared exactly analytically solvable. Therefore, it enables a direct comparison of its predictions with their empirical counterparts, for instance, with empirical velocity autocorrelation function. Thus, the present research significantly extends capabilities of the CTRW formalism. Contribution to the Topical Issue "Continuous Time Random Walk Still Trendy: Fifty-year History, Current State and Outlook", edited by Ryszard Kutner and Jaume Masoliver.

Fourier heat conduction as a strong kinetic effect in one-dimensional hard-core gases

NASA Astrophysics Data System (ADS)

Zhao, Hanqing; Wang, Wen-ge

2018-01-01

For a one-dimensional (1D) momentum conserving system, intensive studies have shown that generally its heat current autocorrelation function (HCAF) tends to decay in a power-law manner and results in the breakdown of the Fourier heat conduction law in the thermodynamic limit. This has been recognized to be a dominant hydrodynamic effect. Here we show that, instead, the kinetic effect can be dominant in some cases and leads to the Fourier law for finite-size systems. Usually the HCAF undergoes a fast decaying kinetic stage followed by a long slowly decaying hydrodynamic tail. In a finite range of the system size, we find that whether the system follows the Fourier law depends on whether the kinetic stage dominates. Our Rapid Communication is illustrated by the 1D hard-core gas models with which the HCAF is derived analytically and verified numerically by molecular dynamics simulations.

Dynamics of Single-Photon Emission from Electrically Pumped Color Centers

NASA Astrophysics Data System (ADS)

Khramtsov, Igor A.; Agio, Mario; Fedyanin, Dmitry Yu.

2017-08-01

Low-power, high-speed, and bright electrically driven true single-photon sources, which are able to operate at room temperature, are vital for the practical realization of quantum-communication networks and optical quantum computations. Color centers in semiconductors are currently the best candidates; however, in spite of their intensive study in the past decade, the behavior of color centers in electrically controlled systems is poorly understood. Here we present a physical model and establish a theoretical approach to address single-photon emission dynamics of electrically pumped color centers, which interprets experimental results. We support our analysis with self-consistent numerical simulations of a single-photon emitting diode based on a single nitrogen-vacancy center in diamond and predict the second-order autocorrelation function and other emission characteristics. Our theoretical findings demonstrate remarkable agreement with the experimental results and pave the way to the understanding of single-electron and single-photon processes in semiconductors.

First Observation of the Earth's Permanent Free Oscillations on Ocean Bottom Seismometers

NASA Astrophysics Data System (ADS)

Deen, M.; Wielandt, E.; Stutzmann, E.; Crawford, W.; Barruol, G.; Sigloch, K.

2017-11-01

The Earth's hum is the permanent free oscillations of the Earth recorded in the absence of earthquakes, at periods above 30 s. We present the first observations of its fundamental spheroidal eigenmodes on broadband ocean bottom seismometers (OBSs) in the Indian Ocean. At the ocean bottom, the effects of ocean infragravity waves (compliance) and seafloor currents (tilt) overshadow the hum. In our experiment, data are also affected by electronic glitches. We remove these signals from the seismic trace by subtracting average glitch signals; performing a linear regression; and using frequency-dependent response functions between pressure, horizontal, and vertical seismic components. This reduces the long period noise on the OBS to the level of a good land station. Finally, by windowing the autocorrelation to include only the direct arrival, the first and second orbits around the Earth, and by calculating its Fourier transform, we clearly observe the eigenmodes at the ocean bottom.

A molecular dynamics study of liquid layering and thermal conductivity enhancement in nanoparticle suspensions

NASA Astrophysics Data System (ADS)

Paul, J.; Madhu, A. K.; Jayadeep, U. B.; Sobhan, C. B.; Peterson, G. P.

2018-03-01

Liquid layering is considered to be one of the factors contributing to the often anomalous enhancement in thermal conductivity of nanoparticle suspensions. The extent of this layering was found to be significant at lower particle sizes, as reported in an earlier work by the authors. In continuation to that work, an investigation was conducted to better understand the fundamental parameters impacting the reported anomalous enhancement in thermal conductivity of nanoparticle suspensions (nanofluids), utilizing equilibrium molecular dynamics simulations in a copper-argon system. Nanofluids containing nanoparticles of size less than 6 nm were investigated and studied analytically. The heat current auto-correlation function in the Green-Kubo formulation for thermal conductivity was decomposed into self-correlations and cross-correlations of different species and the kinetic, potential, collision and enthalpy terms of the dominant portion of the heat current vector. The presence of liquid layering around the nanoparticle was firmly established through simulations that show the dominant contribution of Ar-Ar self-correlation and the trend displayed by the kinetic-potential cross-correlation within the argon species.

Autocorrelation structure of convective rainfall in semiarid-arid climate derived from high-resolution X-Band radar estimates

NASA Astrophysics Data System (ADS)

Marra, Francesco; Morin, Efrat

2018-02-01

Small scale rainfall variability is a key factor driving runoff response in fast responding systems, such as mountainous, urban and arid catchments. In this paper, the spatial-temporal autocorrelation structure of convective rainfall is derived with extremely high resolutions (60 m, 1 min) using estimates from an X-Band weather radar recently installed in a semiarid-arid area. The 2-dimensional spatial autocorrelation of convective rainfall fields and the temporal autocorrelation of point-wise and distributed rainfall fields are examined. The autocorrelation structures are characterized by spatial anisotropy, correlation distances 1.5-2.8 km and rarely exceeding 5 km, and time-correlation distances 1.8-6.4 min and rarely exceeding 10 min. The observed spatial variability is expected to negatively affect estimates from rain gauges and microwave links rather than satellite and C-/S-Band radars; conversely, the temporal variability is expected to negatively affect remote sensing estimates rather than rain gauges. The presented results provide quantitative information for stochastic weather generators, cloud-resolving models, dryland hydrologic and agricultural models, and multi-sensor merging techniques.

Inferential precision in single-case time-series data streams: how well does the em procedure perform when missing observations occur in autocorrelated data?

PubMed

Smith, Justin D; Borckardt, Jeffrey J; Nash, Michael R

2012-09-01

The case-based time-series design is a viable methodology for treatment outcome research. However, the literature has not fully addressed the problem of missing observations with such autocorrelated data streams. Mainly, to what extent do missing observations compromise inference when observations are not independent? Do the available missing data replacement procedures preserve inferential integrity? Does the extent of autocorrelation matter? We use Monte Carlo simulation modeling of a single-subject intervention study to address these questions. We find power sensitivity to be within acceptable limits across four proportions of missing observations (10%, 20%, 30%, and 40%) when missing data are replaced using the Expectation-Maximization Algorithm, more commonly known as the EM Procedure (Dempster, Laird, & Rubin, 1977). This applies to data streams with lag-1 autocorrelation estimates under 0.80. As autocorrelation estimates approach 0.80, the replacement procedure yields an unacceptable power profile. The implications of these findings and directions for future research are discussed. Copyright © 2011. Published by Elsevier Ltd.

Field test comparison of an autocorrelation technique for determining grain size using a digital 'beachball' camera versus traditional methods

USGS Publications Warehouse

Barnard, P.L.; Rubin, D.M.; Harney, J.; Mustain, N.

2007-01-01

This extensive field test of an autocorrelation technique for determining grain size from digital images was conducted using a digital bed-sediment camera, or 'beachball' camera. Using 205 sediment samples and >1200 images from a variety of beaches on the west coast of the US, grain size ranging from sand to granules was measured from field samples using both the autocorrelation technique developed by Rubin [Rubin, D.M., 2004. A simple autocorrelation algorithm for determining grain size from digital images of sediment. Journal of Sedimentary Research, 74(1): 160-165.] and traditional methods (i.e. settling tube analysis, sieving, and point counts). To test the accuracy of the digital-image grain size algorithm, we compared results with manual point counts of an extensive image data set in the Santa Barbara littoral cell. Grain sizes calculated using the autocorrelation algorithm were highly correlated with the point counts of the same images (r2 = 0.93; n = 79) and had an error of only 1%. Comparisons of calculated grain sizes and grain sizes measured from grab samples demonstrated that the autocorrelation technique works well on high-energy dissipative beaches with well-sorted sediment such as in the Pacific Northwest (r2 ??? 0.92; n = 115). On less dissipative, more poorly sorted beaches such as Ocean Beach in San Francisco, results were not as good (r2 ??? 0.70; n = 67; within 3% accuracy). Because the algorithm works well compared with point counts of the same image, the poorer correlation with grab samples must be a result of actual spatial and vertical variability of sediment in the field; closer agreement between grain size in the images and grain size of grab samples can be achieved by increasing the sampling volume of the images (taking more images, distributed over a volume comparable to that of a grab sample). In all field tests the autocorrelation method was able to predict the mean and median grain size with ???96% accuracy, which is more than adequate for the majority of sedimentological applications, especially considering that the autocorrelation technique is estimated to be at least 100 times faster than traditional methods.

Statistical process control of mortality series in the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database: implications of the data generating process.

PubMed

Moran, John L; Solomon, Patricia J

2013-05-24

Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. Monthly mean raw mortality (at hospital discharge) time series, 1995-2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) "in-control" status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance. The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag40 and 35% had autocorrelation through to lag40; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals which were in-control with respect to EWMA control limits and one-step prediction error limits (3SE). The expected series was modelled with a multiplicative seasonal autoregressive model. The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues.

Time to burn: Modeling wildland arson as an autoregressive crime function

Treesearch

Jeffrey P. Prestemon; David T. Butry

2005-01-01

Six Poisson autoregressive models of order p [PAR(p)] of daily wildland arson ignition counts are estimated for five locations in Florida (1994-2001). In addition, a fixed effects time-series Poisson model of annual arson counts is estimated for all Florida counties (1995-2001). PAR(p) model estimates reveal highly significant arson ignition autocorrelation, lasting up...

Improved symbol rate identification method for on-off keying and advanced modulation format signals based on asynchronous delayed sampling

NASA Astrophysics Data System (ADS)

Cui, Sheng; Jin, Shang; Xia, Wenjuan; Ke, Changjian; Liu, Deming

2015-11-01

Symbol rate identification (SRI) based on asynchronous delayed sampling is accurate, cost-effective and robust to impairments. For on-off keying (OOK) signals the symbol rate can be derived from the periodicity of the second-order autocorrelation function (ACF2) of the delay tap samples. But it is found that when applied this method to advanced modulation format signals with auxiliary amplitude modulation (AAM), incorrect results may be produced because AAM has significant impact on ACF2 periodicity, which makes the symbol period harder or even unable to be correctly identified. In this paper it is demonstrated that for these signals the first order autocorrelation function (ACF1) has stronger periodicity and can be used to replace ACF2 to produce more accurate and robust results. Utilizing the characteristics of the ACFs, an improved SRI method is proposed to accommodate both OOK and advanced modulation formant signals in a transparent manner. Furthermore it is proposed that by minimizing the peak to average ratio (PAPR) of the delay tap samples with an additional tunable dispersion compensator (TDC) the limited dispersion tolerance can be expanded to desired values.

Diagnostic System Based on the Human AUDITORY-BRAIN Model for Measuring Environmental NOISE—AN Application to Railway Noise

NASA Astrophysics Data System (ADS)

SAKAI, H.; HOTEHAMA, T.; ANDO, Y.; PRODI, N.; POMPOLI, R.

2002-02-01

Measurements of railway noise were conducted by use of a diagnostic system of regional environmental noise. The system is based on the model of the human auditory-brain system. The model consists of the interplay of autocorrelators and an interaural crosscorrelator acting on the pressure signals arriving at the ear entrances, and takes into account the specialization of left and right human cerebral hemispheres. Different kinds of railway noise were measured through binaural microphones of a dummy head. To characterize the railway noise, physical factors, extracted from the autocorrelation functions (ACF) and interaural crosscorrelation function (IACF) of binaural signals, were used. The factors extracted from ACF were (1) energy represented at the origin of the delay, Φ (0), (2) effective duration of the envelope of the normalized ACF, τe, (3) the delay time of the first peak, τ1, and (4) its amplitude,ø1 . The factors extracted from IACF were (5) IACC, (6) interaural delay time at which the IACC is defined, τIACC, and (7) width of the IACF at the τIACC,WIACC . The factor Φ (0) can be represented as a geometrical mean of energies at both ears as listening level, LL.

Image correlation based method for the analysis of collagen fibers patterns

NASA Astrophysics Data System (ADS)

Rosa, Ramon G. T.; Pratavieira, Sebastião.; Kurachi, Cristina

2015-06-01

The collagen fibers are one of the most important structural proteins in skin, being responsible for its strength and flexibility. It is known that their properties, like fibers density, ordination and mean diameter can be affected by several skin conditions, what makes these properties a good parameter to be used on the diagnosis and evaluation of skin aging, cancer, healing, among other conditions. There is, however, a need for methods capable of analyzing quantitatively the organization patterns of these fibers. To address this need, we developed a method based on the autocorrelation function of the images that allows the construction of vector field plots of the fibers directions and does not require any kind of curve fitting or optimization. The analyzed images were obtained through Second Harmonic Generation Imaging Microscopy. This paper presents a concise review on the autocorrelation function and some of its applications to image processing, details the developed method and the results obtained through the analysis of hystopathological slides of landrace porcine skin. The method has high accuracy on the determination of the fibers direction and presents high performance. We look forward to perform further studies keeping track of different skin conditions over time.

Modulation transfer function of a fish-eye lens based on the sixth-order wave aberration theory.

PubMed

Jia, Han; Lu, Lijun; Cao, Yiqing

2018-01-10

A calculation program of the modulation transfer function (MTF) of a fish-eye lens is developed with the autocorrelation method, in which the sixth-order wave aberration theory of ultra-wide-angle optical systems is used to simulate the wave aberration distribution at the exit pupil of the optical systems. The autocorrelation integral is processed with the Gauss-Legendre integral, and the magnification chromatic aberration is discussed to calculate polychromatic MTF. The MTF calculation results of a given example are then compared with those previously obtained based on the fourth-order wave aberration theory of plane-symmetrical optical systems and with those from the Zemax program. The study shows that MTF based on the sixth-order wave aberration theory has satisfactory calculation accuracy even for a fish-eye lens with a large acceptance aperture. And the impacts of different types of aberrations on the MTF of a fish-eye lens are analyzed. Finally, we apply the self-adaptive and normalized real-coded genetic algorithm and the MTF developed in the paper to optimize the Nikon F/2.8 fish-eye lens; consequently, the optimized system shows better MTF performances than those of the original design.

Scattering images from autocorrelation functions of P-wave seismic velocity images: the case of Tenerife Island (Canary Islands, Spain)

NASA Astrophysics Data System (ADS)

García-Yeguas, A.; Sánchez-Alzola, A.; De Siena, L.; Prudencio, J.; Díaz-Moreno, A.; Ibáñez, J. M.

2018-03-01

We present a P-wave scattering image of the volcanic structures under Tenerife Island using the autocorrelation functions of P-wave vertical velocity fluctuations. We have applied a cluster analysis to total quality factor attenuation ( {Q}_t^{-1} ) and scattering quality factor attenuation ( {Q}_{PSc}^{-1} ) images to interpret the structures in terms of intrinsic and scattering attenuation variations on a 2D plane, corresponding to a depth of 2000 m, and check the robustness of the scattering imaging. The results show that scattering patterns are similar to total attenuation patterns in the south of the island. There are two main areas where patterns differ: at Cañadas-Teide-Pico Viejo Complex, high total attenuation and average-to-low scattering values are observed. We interpret the difference as induced by intrinsic attenuation. In the Santiago Ridge Zone (SRZ) region, high scattering values correspond to average total attenuation. In our interpretation, the anomaly is induced by an extended scatterer, geometrically related to the surficial traces of Garachico and El Chinyero historical eruptions and the area of highest seismic activity during the 2004-2008 seismic crises.

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

Shumway, R.H.; McQuarrie, A.D.

Robust statistical approaches to the problem of discriminating between regional earthquakes and explosions are developed. We compare linear discriminant analysis using descriptive features like amplitude and spectral ratios with signal discrimination techniques using the original signal waveforms and spectral approximations to the log likelihood function. Robust information theoretic techniques are proposed and all methods are applied to 8 earthquakes and 8 mining explosions in Scandinavia and to an event from Novaya Zemlya of unknown origin. It is noted that signal discrimination approaches based on discrimination information and Renyi entropy perform better in the test sample than conventional methods based onmore » spectral ratios involving the P and S phases. Two techniques for identifying the ripple-firing pattern for typical mining explosions are proposed and shown to work well on simulated data and on several Scandinavian earthquakes and explosions. We use both cepstral analysis in the frequency domain and a time domain method based on the autocorrelation and partial autocorrelation functions. The proposed approach strips off underlying smooth spectral and seasonal spectral components corresponding to the echo pattern induced by two simple ripple-fired models. For two mining explosions, a pattern is identified whereas for two earthquakes, no pattern is evident.« less

Growth history and crown vine coverage are principal factors influencing growth and mortality rates of big-leaf mahogany Swietenia macrophylla in Brazil

Treesearch

James Grogan; R. Matthew Landis

2009-01-01

1. Current efforts to model population dynamics of high-value tropical timber species largely assume that individual growth history is unimportant to population dynamics, yet growth autocorrelation is known to adversely affect model predictions. In this study, we analyse a decade of annual census data from a natural population of big-leaf mahogany Swietenia macrophylla...

Chemometric modeling of 5-Phenylthiophenecarboxylic acid derivatives as anti-rheumatic agents.

PubMed

Adhikari, Nilanjan; Jana, Dhritiman; Halder, Amit K; Mondal, Chanchal; Maiti, Milan K; Jha, Tarun

2012-09-01

Arthritis involves joint inflammation, synovial proliferation and damage of cartilage. Interleukin-1 undergoes acute and chronic inflammatory mechanisms of arthritis. Non-steroidal anti-inflammatory drugs can produce symptomatic relief but cannot act through mechanisms of arthritis. Diseases modifying anti-rheumatoid drugs reduce the symptoms of arthritis like decrease in pain and disability score, reduction of swollen joints, articular index and serum concentration of acute phage proteins. Recently, some literature references are obtained on molecular modeling of antirheumatic agents. We have tried chemometric modeling through 2D-QSAR studies on a dataset of fifty-one compounds out of which forty-four 5-Phenylthiophenecarboxylic acid derivatives have IL-1 inhibitory activity and forty-six 5-Phenylthiophenecarboxylic acid derivatives have %AIA suppressive activity. The work was done to find out the structural requirements of these anti-rheumatic agents. 2D QSAR models were generated by 2D and 3D descriptors by using multiple linear regression and partial least square method where IL-1 antagonism was considered as the biological activity parameter. Statistically significant models were developed on the training set developed by k-means cluster analysis. Sterimol parameters, electronic interaction at atom number 9, 2D autocorrelation descriptors, information content descriptor, average connectivity index chi-3, radial distribution function, Balaban 3D index and 3D-MoRSE descriptors were found to play crucial roles to modulate IL-1 inhibitory activity. 2D autocorrelation descriptors like Broto-Moreau autocorrelation of topological structure-lag 3 weighted by atomic van der Waals volumes, Geary autocorrelation-lag 7 associated with weighted atomic Sanderson electronegativities and 3D-MoRSE descriptors like 3D-MoRSE-signal 22 related to atomic van der Waals volumes, 3D-MoRSE-signal 28 related to atomic van der Waals volumes and 3D-MoRSE-signal 9 which was unweighted, were found to play important roles to model %AIA suppressive activity.

Spectral domain optical coherence tomography with dual-balanced detection

NASA Astrophysics Data System (ADS)

Bo, En; Liu, Xinyu; Chen, Si; Luo, Yuemei; Wang, Nanshuo; Wang, Xianghong; Liu, Linbo

2016-03-01

We developed a spectral domain optical coherence tomography (SD-OCT) system employing dual-balanced detection (DBD) for direct current term suppression and SNR enhancement, especially for auto-autocorrelation artifacts reduction. The DBD was achieved by using a beam splitter to building a free-space Michelson interferometer, which generated two interferometric spectra with a phase difference of π. These two phase-opposed spectra were guided to the spectrometer through two single mode fibers of the 8 fiber v-groove array and acquired by ultizing the upper two lines of a three-line CCD camera. We rotated this fiber v-groove array by 1.35 degrees to focus two spectra onto the first and second line of the CCD camera. Two spectra were aligned by optimum spectrum matching algorithm. By subtracting one spectrum from the other, this dual-balanced detection system achieved a direct current term suppression of ~30 dB, SNR enhancement of ~3 dB, and auto-autocorrelation artifacts reduction of ~10 dB experimentally. Finally we respectively validated the feasibility and performance of dual-balanced detection by imaging a glass plate and swine corneal tissue ex vivo. The quality of images obtained using dual-balanced detection was significantly improved with regard to the conventional single-detection (SD) images.

High Frequency Sampling of TTL Pulses on a Raspberry Pi for Diffuse Correlation Spectroscopy Applications.

PubMed

Tivnan, Matthew; Gurjar, Rajan; Wolf, David E; Vishwanath, Karthik

2015-08-12

Diffuse Correlation Spectroscopy (DCS) is a well-established optical technique that has been used for non-invasive measurement of blood flow in tissues. Instrumentation for DCS includes a correlation device that computes the temporal intensity autocorrelation of a coherent laser source after it has undergone diffuse scattering through a turbid medium. Typically, the signal acquisition and its autocorrelation are performed by a correlation board. These boards have dedicated hardware to acquire and compute intensity autocorrelations of rapidly varying input signal and usually are quite expensive. Here we show that a Raspberry Pi minicomputer can acquire and store a rapidly varying time-signal with high fidelity. We show that this signal collected by a Raspberry Pi device can be processed numerically to yield intensity autocorrelations well suited for DCS applications. DCS measurements made using the Raspberry Pi device were compared to those acquired using a commercial hardware autocorrelation board to investigate the stability, performance, and accuracy of the data acquired in controlled experiments. This paper represents a first step toward lowering the instrumentation cost of a DCS system and may offer the potential to make DCS become more widely used in biomedical applications.

High Frequency Sampling of TTL Pulses on a Raspberry Pi for Diffuse Correlation Spectroscopy Applications

PubMed Central

Tivnan, Matthew; Gurjar, Rajan; Wolf, David E.; Vishwanath, Karthik

2015-01-01

Diffuse Correlation Spectroscopy (DCS) is a well-established optical technique that has been used for non-invasive measurement of blood flow in tissues. Instrumentation for DCS includes a correlation device that computes the temporal intensity autocorrelation of a coherent laser source after it has undergone diffuse scattering through a turbid medium. Typically, the signal acquisition and its autocorrelation are performed by a correlation board. These boards have dedicated hardware to acquire and compute intensity autocorrelations of rapidly varying input signal and usually are quite expensive. Here we show that a Raspberry Pi minicomputer can acquire and store a rapidly varying time-signal with high fidelity. We show that this signal collected by a Raspberry Pi device can be processed numerically to yield intensity autocorrelations well suited for DCS applications. DCS measurements made using the Raspberry Pi device were compared to those acquired using a commercial hardware autocorrelation board to investigate the stability, performance, and accuracy of the data acquired in controlled experiments. This paper represents a first step toward lowering the instrumentation cost of a DCS system and may offer the potential to make DCS become more widely used in biomedical applications. PMID:26274961

Modeling continuous seismic velocity changes due to ground shaking in Chile

NASA Astrophysics Data System (ADS)

Gassenmeier, Martina; Richter, Tom; Sens-Schönfelder, Christoph; Korn, Michael; Tilmann, Frederik

2015-04-01

In order to investigate temporal seismic velocity changes due to earthquake related processes and environmental forcing, we analyze 8 years of ambient seismic noise recorded by the Integrated Plate Boundary Observatory Chile (IPOC) network in northern Chile between 18° and 25° S. The Mw 7.7 Tocopilla earthquake in 2007 and the Mw 8.1 Iquique earthquake in 2014 as well as numerous smaller events occurred in this area. By autocorrelation of the ambient seismic noise field, approximations of the Green's functions are retrieved. The recovered function represents backscattered or multiply scattered energy from the immediate neighborhood of the station. To detect relative changes of the seismic velocities we apply the stretching method, which compares individual autocorrelation functions to stretched or compressed versions of a long term averaged reference autocorrelation function. We use time windows in the coda of the autocorrelations, that contain scattered waves which are highly sensitive to minute changes in the velocity. At station PATCX we observe seasonal changes in seismic velocity as well as temporary velocity reductions in the frequency range of 4-6 Hz. The seasonal changes can be attributed to thermal stress changes in the subsurface related to variations of the atmospheric temperature. This effect can be modeled well by a sine curve and is subtracted for further analysis of short term variations. Temporary velocity reductions occur at the time of ground shaking usually caused by earthquakes and are followed by a recovery. We present an empirical model that describes the seismic velocity variations based on continuous observations of the local ground acceleration. Our hypothesis is that not only the shaking of earthquakes provokes velocity drops, but any small vibrations continuously induce minor velocity variations that are immediately compensated by healing in the steady state. We show that the shaking effect is accumulated over time and best described by the integrated envelope of the ground acceleration over 1 day which is the discretization interval of the velocity measurements. In our model the amplitude of the velocity reduction as well as the recovery time are proportional to the size of the excitation. This model with the two free scaling parameters for the shaking induced velocity variation fits the data in remarkable detail. Additionally, a linear trend is observed that might be related to a recovery process from one or more earthquakes before our measurement period. For the Tocopilla earthquake in 2007 and the Iquique earthquake in 2014 velocity reductions are also observed at other stations of the IPOC network. However, a clear relationship between the ground shaking and the induced velocity reductions is not visible at other stations. We attribute the outstanding sensitivity of PATCX to ground shaking to the special geological setting of the station, where the material consists of relatively loose conglomerate with high pore volume.

Spectral factorization of wavefields and wave operators

NASA Astrophysics Data System (ADS)

Rickett, James Edward

Spectral factorization is the problem of finding a minimum-phase function with a given power spectrum. Minimum phase functions have the property that they are causal with a causal (stable) inverse. In this thesis, I factor multidimensional systems into their minimum-phase components. Helical boundary conditions resolve any ambiguities over causality, allowing me to factor multi-dimensional systems with conventional one-dimensional spectral factorization algorithms. In the first part, I factor passive seismic wavefields recorded in two-dimensional spatial arrays. The result provides an estimate of the acoustic impulse response of the medium that has higher bandwidth than autocorrelation-derived estimates. Also, the function's minimum-phase nature mimics the physics of the system better than the zero-phase autocorrelation model. I demonstrate this on helioseismic data recorded by the satellite-based Michelson Doppler Imager (MDI) instrument, and shallow seismic data recorded at Long Beach, California. In the second part of this thesis, I take advantage of the stable-inverse property of minimum-phase functions to solve wave-equation partial differential equations. By factoring multi-dimensional finite-difference stencils into minimum-phase components, I can invert them efficiently, facilitating rapid implicit extrapolation without the azimuthal anisotropy that is observed with splitting approximations. The final part of this thesis describes how to calculate diagonal weighting functions that approximate the combined operation of seismic modeling and migration. These weighting functions capture the effects of irregular subsurface illumination, which can be the result of either the surface-recording geometry, or focusing and defocusing of the seismic wavefield as it propagates through the earth. Since they are diagonal, they can be easily both factored and inverted to compensate for uneven subsurface illumination in migrated images. Experimental results show that applying these weighting functions after migration leads to significantly improved estimates of seismic reflectivity.

Controlling for seasonal patterns and time varying confounders in time-series epidemiological models: a simulation study.

PubMed

Perrakis, Konstantinos; Gryparis, Alexandros; Schwartz, Joel; Le Tertre, Alain; Katsouyanni, Klea; Forastiere, Francesco; Stafoggia, Massimo; Samoli, Evangelia

2014-12-10

An important topic when estimating the effect of air pollutants on human health is choosing the best method to control for seasonal patterns and time varying confounders, such as temperature and humidity. Semi-parametric Poisson time-series models include smooth functions of calendar time and weather effects to control for potential confounders. Case-crossover (CC) approaches are considered efficient alternatives that control seasonal confounding by design and allow inclusion of smooth functions of weather confounders through their equivalent Poisson representations. We evaluate both methodological designs with respect to seasonal control and compare spline-based approaches, using natural splines and penalized splines, and two time-stratified CC approaches. For the spline-based methods, we consider fixed degrees of freedom, minimization of the partial autocorrelation function, and general cross-validation as smoothing criteria. Issues of model misspecification with respect to weather confounding are investigated under simulation scenarios, which allow quantifying omitted, misspecified, and irrelevant-variable bias. The simulations are based on fully parametric mechanisms designed to replicate two datasets with different mortality and atmospheric patterns. Overall, minimum partial autocorrelation function approaches provide more stable results for high mortality counts and strong seasonal trends, whereas natural splines with fixed degrees of freedom perform better for low mortality counts and weak seasonal trends followed by the time-season-stratified CC model, which performs equally well in terms of bias but yields higher standard errors. Copyright © 2014 John Wiley & Sons, Ltd.

Estimation of correlation functions by stochastic approximation.

NASA Technical Reports Server (NTRS)

Habibi, A.; Wintz, P. A.

1972-01-01

Consideration of the autocorrelation function of a zero-mean stationary random process. The techniques are applicable to processes with nonzero mean provided the mean is estimated first and subtracted. Two recursive techniques are proposed, both of which are based on the method of stochastic approximation and assume a functional form for the correlation function that depends on a number of parameters that are recursively estimated from successive records. One technique uses a standard point estimator of the correlation function to provide estimates of the parameters that minimize the mean-square error between the point estimates and the parametric function. The other technique provides estimates of the parameters that maximize a likelihood function relating the parameters of the function to the random process. Examples are presented.

Autocorrelation of location estimates and the analysis of radiotracking data

USGS Publications Warehouse

Otis, D.L.; White, Gary C.

1999-01-01

The wildlife literature has been contradictory about the importance of autocorrelation in radiotracking data used for home range estimation and hypothesis tests of habitat selection. By definition, the concept of a home range involves autocorrelated movements, but estimates or hypothesis tests based on sampling designs that predefine a time frame of interest, and that generate representative samples of an animal's movement during this time frame, should not be affected by length of the sampling interval and autocorrelation. Intensive sampling of the individual's home range and habitat use during the time frame of the study leads to improved estimates for the individual, but use of location estimates as the sample unit to compare across animals is pseudoreplication. We therefore recommend against use of habitat selection analysis techniques that use locations instead of individuals as the sample unit. We offer a general outline for sampling designs for radiotracking studies.

Assessing the significance of global and local correlations under spatial autocorrelation: a nonparametric approach.

PubMed

Viladomat, Júlia; Mazumder, Rahul; McInturff, Alex; McCauley, Douglas J; Hastie, Trevor

2014-06-01

We propose a method to test the correlation of two random fields when they are both spatially autocorrelated. In this scenario, the assumption of independence for the pair of observations in the standard test does not hold, and as a result we reject in many cases where there is no effect (the precision of the null distribution is overestimated). Our method recovers the null distribution taking into account the autocorrelation. It uses Monte-Carlo methods, and focuses on permuting, and then smoothing and scaling one of the variables to destroy the correlation with the other, while maintaining at the same time the initial autocorrelation. With this simulation model, any test based on the independence of two (or more) random fields can be constructed. This research was motivated by a project in biodiversity and conservation in the Biology Department at Stanford University. © 2014, The International Biometric Society.

Lévy flights, autocorrelation, and slow convergence

NASA Astrophysics Data System (ADS)

Figueiredo, Annibal; Gleria, Iram; Matsushita, Raul; Da Silva, Sergio

2004-06-01

Previously we have put forward that the sluggish convergence of truncated Lévy flights to a Gaussian (Phys. Rev. Lett. 73 (1994) 2946) together with the scaling power laws in their probability of return to the origin (Nature 376 (1995) 46) can be explained by autocorrelation in data (Physica A 323 (2003) 601; Phys. Lett. A 315 (2003) 51). A purpose of this paper is to improve and enlarge the scope of such a result. The role of the autocorrelations in the convergence process as well as the problem of establishing the distance of a given distribution to the Gaussian are analyzed in greater detail. We show that whereas power laws in the second moment can still be explained by linear correlation of pairs, sluggish convergence can now emerge from nonlinear autocorrelations. Our approach is exemplified with data from the British pound-US dollar exchange rate.

Determination of design and operation parameters for upper atmospheric research instrumentation to yield optimum resolution with deconvolution, appendix 2

NASA Technical Reports Server (NTRS)

Ioup, George E.; Ioup, Juliette W.

1988-01-01

This thesis reviews the technique established to clear channels in the Power Spectral Estimate by applying linear combinations of well known window functions to the autocorrelation function. The need for windowing the auto correlation function is due to the fact that the true auto correlation is not generally used to obtain the Power Spectral Estimate. When applied, the windows serve to reduce the effect that modifies the auto correlation by truncating the data and possibly the autocorrelation has on the Power Spectral Estimate. It has been shown in previous work that a single channel has been cleared, allowing for the detection of a small peak in the presence of a large peak in the Power Spectral Estimate. The utility of this method is dependent on the robustness of it on different input situations. We extend the analysis in this paper, to include clearing up to three channels. We examine the relative positions of the spikes to each other and also the effect of taking different percentages of lags of the auto correlation in the Power Spectral Estimate. This method could have application wherever the Power Spectrum is used. An example of this is beam forming for source location, where a small target can be located next to a large target. Other possibilities extend into seismic data processing. As the method becomes more automated other applications may present themselves.

Coarse-grained modeling of polyethylene melts: Effect on dynamics

DOE PAGES

Peters, Brandon L.; Salerno, K. Michael; Agrawal, Anupriya; ...

2017-05-23

The distinctive viscoelastic behavior of polymers results from a coupled interplay of motion on multiple length and time scales. Capturing the broad time and length scales of polymer motion remains a challenge. Using polyethylene (PE) as a model macromolecule, we construct coarse-grained (CG) models of PE with three to six methyl groups per CG bead and probe two critical aspects of the technique: pressure corrections required after iterative Boltzmann inversion (IBI) to generate CG potentials that match the pressure of reference fully atomistic melt simulations and the transferability of CG potentials across temperatures. While IBI produces nonbonded pair potentials thatmore » give excellent agreement between the atomistic and CG pair correlation functions, the resulting pressure for the CG models is large compared with the pressure of the atomistic system. We find that correcting the potential to match the reference pressure leads to nonbonded interactions with much deeper minima and slightly smaller effective bead diameter. However, simulations with potentials generated by IBI and pressure-corrected IBI result in similar mean-square displacements (MSDs) and stress autocorrelation functions G( t) for PE melts. While the time rescaling factor required to match CG and atomistic models is the same for pressure- and non-pressure-corrected CG models, it strongly depends on temperature. Furthermore, transferability was investigated by comparing the MSDs and stress autocorrelation functions for potentials developed at different temperatures.« less

Coarse-grained modeling of polyethylene melts: Effect on dynamics

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

Peters, Brandon L.; Salerno, K. Michael; Agrawal, Anupriya

The distinctive viscoelastic behavior of polymers results from a coupled interplay of motion on multiple length and time scales. Capturing the broad time and length scales of polymer motion remains a challenge. Using polyethylene (PE) as a model macromolecule, we construct coarse-grained (CG) models of PE with three to six methyl groups per CG bead and probe two critical aspects of the technique: pressure corrections required after iterative Boltzmann inversion (IBI) to generate CG potentials that match the pressure of reference fully atomistic melt simulations and the transferability of CG potentials across temperatures. While IBI produces nonbonded pair potentials thatmore » give excellent agreement between the atomistic and CG pair correlation functions, the resulting pressure for the CG models is large compared with the pressure of the atomistic system. We find that correcting the potential to match the reference pressure leads to nonbonded interactions with much deeper minima and slightly smaller effective bead diameter. However, simulations with potentials generated by IBI and pressure-corrected IBI result in similar mean-square displacements (MSDs) and stress autocorrelation functions G( t) for PE melts. While the time rescaling factor required to match CG and atomistic models is the same for pressure- and non-pressure-corrected CG models, it strongly depends on temperature. Furthermore, transferability was investigated by comparing the MSDs and stress autocorrelation functions for potentials developed at different temperatures.« less

Using simulations and data to evaluate mean sensitivity (ζ) as a useful statistic in dendrochronology

Treesearch

Andrew G. Bunn; Esther Jansma; Mikko Korpela; Robert D. Westfall; James Baldwin

2013-01-01

Mean sensitivity (ζ) continues to be used in dendrochronology despite a literature that shows it to be of questionable value in describing the properties of a time series. We simulate first-order autoregressive models with known parameters and show that ζ is a function of variance and autocorrelation of a time series. We then use 500 random tree-ring...

Photon antibunching from a single lithographically defined InGaAs/GaAs quantum dot.

PubMed

Verma, V B; Stevens, Martin J; Silverman, K L; Dias, N L; Garg, A; Coleman, J J; Mirin, R P

2011-02-28

We demonstrate photon antibunching from a single lithographically defined quantum dot fabricated by electron beam lithography, wet chemical etching, and overgrowth of the barrier layers by metalorganic chemical vapor deposition. Measurement of the second-order autocorrelation function indicates g(2)(0)=0.395±0.030, below the 0.5 limit necessary for classification as a single photon source.

Hydration dynamics of a lipid membrane: Hydrogen bond networks and lipid-lipid associations

NASA Astrophysics Data System (ADS)

Srivastava, Abhinav; Debnath, Ananya

2018-03-01

Dynamics of hydration layers of a dimyristoylphosphatidylcholine (DMPC) bilayer are investigated using an all atom molecular dynamics simulation. Based upon the geometric criteria, continuously residing interface water molecules which form hydrogen bonds solely among themselves and then concertedly hydrogen bonded to carbonyl, phosphate, and glycerol head groups of DMPC are identified. The interface water hydrogen bonded to lipids shows slower relaxation rates for translational and rotational dynamics compared to that of the bulk water and is found to follow sub-diffusive and non-diffusive behaviors, respectively. The mean square displacements and the reorientational auto-correlation functions are slowest for the interfacial waters hydrogen bonded to the carbonyl oxygen since these are buried deep in the hydrophobic core among all interfacial water studied. The intermittent hydrogen bond auto-correlation functions are calculated, which allows breaking and reformations of the hydrogen bonds. The auto-correlation functions for interfacial hydrogen bonded networks develop humps during a transition from cage-like motion to eventual power law behavior of t-3/2. The asymptotic t-3/2 behavior indicates translational diffusion dictated dynamics during hydrogen bond breaking and formation irrespective of the nature of the chemical confinement. Employing reactive flux correlation analysis, the forward rate constant of hydrogen bond breaking and formation is calculated which is used to obtain Gibbs energy of activation of the hydrogen bond breaking. The relaxation rates of the networks buried in the hydrophobic core are slower than the networks near the lipid-water interface which is again slower than bulk due to the higher Gibbs energy of activation. Since hydrogen bond breakage follows a translational diffusion dictated mechanism, chemically confined hydrogen bond networks need an activation energy to diffuse through water depleted hydrophobic environments. Our calculations reveal that the slow relaxation rates of interfacial waters in the vicinity of lipids are originated from the chemical confinement of concerted hydrogen bond networks. The analysis suggests that the networks in the hydration layer of membranes dynamically facilitate the water mediated lipid-lipid associations which can provide insights on the thermodynamic stability of soft interfaces relevant to biological systems in the future.

Estimation of the characteristic parameters of the multilayered film model using the patterson differential function

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

Astaf'ev, S. B., E-mail: webmaster@ns.crys.ras.ru; Shchedrin, B. M.; Yanusova, L. G.

The possibility of estimating the layered film structural parameters by constructing the autocorrelation function P{sub F}(z) (referred to as the Patterson differential function) for the derivative d{rho}/dz of electron density along the normal to the sample surface has been considered. An analytical expression P{sub F}(z) is presented for a multilayered film within the box model of the electron density profile. The possibilities of selecting structural information about layered films by analyzing the features of this function are demonstrated by model and real examples, in particular, by applying the method of shifted systems of peaks for the function P{sub F}(z).

Assessing spatial inequalities in accessing community pharmacies: a mixed geographically weighted approach.

PubMed

Domnich, Alexander; Arata, Lucia; Amicizia, Daniela; Signori, Alessio; Gasparini, Roberto; Panatto, Donatella

2016-11-16

Geographical accessibility is an important determinant for the utilisation of community pharmacies. The present study explored patterns of spatial accessibility with respect to pharmacies in Liguria, Italy, a region with particular geographical and demographic features. Municipal density of pharmacies was proxied as the number of pharmacies per capita and per km2, and spatial autocorrelation analysis was performed to identify spatial clusters. Both non-spatial and spatial models were constructed to predict the study outcome. Spatial autocorrelation analysis showed a highly significant clustered pattern in the density of pharmacies per capita (I=0.082) and per km2 (I=0.295). Potentially under-supplied areas were mostly located in the mountainous hinterland. Ordinary least-squares (OLS) regressions established a significant positive relationship between the density of pharmacies and income among municipalities located at high altitudes, while no such association was observed in lower-lying areas. However, residuals of the OLS models were spatially auto-correlated. The best-fitting mixed geographically weighted regression (GWR) models outperformed the corresponding OLS models. Pharmacies per capita were best predicted by two local predictors (altitude and proportion of immigrants) and two global ones (proportion of elderly residents and income), while the local terms population, mean altitude and rural status and the global term income functioned as independent variables predicting pharmacies per km2. The density of pharmacies in Liguria was found to be associated with both socio-economic and landscape factors. Mapping of mixed GWR results would be helpful to policy-makers.

Bounds of memory strength for power-law series.

PubMed

Guo, Fangjian; Yang, Dan; Yang, Zimo; Zhao, Zhi-Dan; Zhou, Tao

2017-05-01

Many time series produced by complex systems are empirically found to follow power-law distributions with different exponents α. By permuting the independently drawn samples from a power-law distribution, we present nontrivial bounds on the memory strength (first-order autocorrelation) as a function of α, which are markedly different from the ordinary ±1 bounds for Gaussian or uniform distributions. When 1<α≤3, as α grows bigger, the upper bound increases from 0 to +1 while the lower bound remains 0; when α>3, the upper bound remains +1 while the lower bound descends below 0. Theoretical bounds agree well with numerical simulations. Based on the posts on Twitter, ratings of MovieLens, calling records of the mobile operator Orange, and the browsing behavior of Taobao, we find that empirical power-law-distributed data produced by human activities obey such constraints. The present findings explain some observed constraints in bursty time series and scale-free networks and challenge the validity of measures such as autocorrelation and assortativity coefficient in heterogeneous systems.

High-Responsivity Graphene-Boron Nitride Photodetector and Autocorrelator in a Silicon Photonic Integrated Circuit.

PubMed

Shiue, Ren-Jye; Gao, Yuanda; Wang, Yifei; Peng, Cheng; Robertson, Alexander D; Efetov, Dmitri K; Assefa, Solomon; Koppens, Frank H L; Hone, James; Englund, Dirk

2015-11-11

Graphene and other two-dimensional (2D) materials have emerged as promising materials for broadband and ultrafast photodetection and optical modulation. These optoelectronic capabilities can augment complementary metal-oxide-semiconductor (CMOS) devices for high-speed and low-power optical interconnects. Here, we demonstrate an on-chip ultrafast photodetector based on a two-dimensional heterostructure consisting of high-quality graphene encapsulated in hexagonal boron nitride. Coupled to the optical mode of a silicon waveguide, this 2D heterostructure-based photodetector exhibits a maximum responsivity of 0.36 A/W and high-speed operation with a 3 dB cutoff at 42 GHz. From photocurrent measurements as a function of the top-gate and source-drain voltages, we conclude that the photoresponse is consistent with hot electron mediated effects. At moderate peak powers above 50 mW, we observe a saturating photocurrent consistent with the mechanisms of electron-phonon supercollision cooling. This nonlinear photoresponse enables optical on-chip autocorrelation measurements with picosecond-scale timing resolution and exceptionally low peak powers.

Blind equalization with criterion with memory nonlinearity

NASA Astrophysics Data System (ADS)

Chen, Yuanjie; Nikias, Chrysostomos L.; Proakis, John G.

1992-06-01

Blind equalization methods usually combat the linear distortion caused by a nonideal channel via a transversal filter, without resorting to the a priori known training sequences. We introduce a new criterion with memory nonlinearity (CRIMNO) for the blind equalization problem. The basic idea of this criterion is to augment the Godard [or constant modulus algorithm (CMA)] cost function with additional terms that penalize the autocorrelations of the equalizer outputs. Several variations of the CRIMNO algorithms are derived, with the variations dependent on (1) whether the empirical averages or the single point estimates are used to approximate the expectations, (2) whether the recent or the delayed equalizer coefficients are used, and (3) whether the weights applied to the autocorrelation terms are fixed or are allowed to adapt. Simulation experiments show that the CRIMNO algorithm, and especially its adaptive weight version, exhibits faster convergence speed than the Godard (or CMA) algorithm. Extensions of the CRIMNO criterion to accommodate the case of correlated inputs to the channel are also presented.

Bounds of memory strength for power-law series

NASA Astrophysics Data System (ADS)

Guo, Fangjian; Yang, Dan; Yang, Zimo; Zhao, Zhi-Dan; Zhou, Tao

2017-05-01

Many time series produced by complex systems are empirically found to follow power-law distributions with different exponents α . By permuting the independently drawn samples from a power-law distribution, we present nontrivial bounds on the memory strength (first-order autocorrelation) as a function of α , which are markedly different from the ordinary ±1 bounds for Gaussian or uniform distributions. When 1 <α ≤3 , as α grows bigger, the upper bound increases from 0 to +1 while the lower bound remains 0; when α >3 , the upper bound remains +1 while the lower bound descends below 0. Theoretical bounds agree well with numerical simulations. Based on the posts on Twitter, ratings of MovieLens, calling records of the mobile operator Orange, and the browsing behavior of Taobao, we find that empirical power-law-distributed data produced by human activities obey such constraints. The present findings explain some observed constraints in bursty time series and scale-free networks and challenge the validity of measures such as autocorrelation and assortativity coefficient in heterogeneous systems.

Design of two-dimensional zero reference codes with cross-entropy method.

PubMed

Chen, Jung-Chieh; Wen, Chao-Kai

2010-06-20

We present a cross-entropy (CE)-based method for the design of optimum two-dimensional (2D) zero reference codes (ZRCs) in order to generate a zero reference signal for a grating measurement system and achieve absolute position, a coordinate origin, or a machine home position. In the absence of diffraction effects, the 2D ZRC design problem is known as the autocorrelation approximation. Based on the properties of the autocorrelation function, the design of the 2D ZRC is first formulated as a particular combination optimization problem. The CE method is then applied to search for an optimal 2D ZRC and thus obtain the desirable zero reference signal. Computer simulation results indicate that there are 15.38% and 14.29% reductions in the second maxima value for the 16x16 grating system with n(1)=64 and the 100x100 grating system with n(1)=300, respectively, where n(1) is the number of transparent pixels, compared with those of the conventional genetic algorithm.

Autocorrelation analysis for the unbiased determination of power-law exponents in single-quantum-dot blinking.

PubMed

Houel, Julien; Doan, Quang T; Cajgfinger, Thomas; Ledoux, Gilles; Amans, David; Aubret, Antoine; Dominjon, Agnès; Ferriol, Sylvain; Barbier, Rémi; Nasilowski, Michel; Lhuillier, Emmanuel; Dubertret, Benoît; Dujardin, Christophe; Kulzer, Florian

2015-01-27

We present an unbiased and robust analysis method for power-law blinking statistics in the photoluminescence of single nanoemitters, allowing us to extract both the bright- and dark-state power-law exponents from the emitters' intensity autocorrelation functions. As opposed to the widely used threshold method, our technique therefore does not require discriminating the emission levels of bright and dark states in the experimental intensity timetraces. We rely on the simultaneous recording of 450 emission timetraces of single CdSe/CdS core/shell quantum dots at a frame rate of 250 Hz with single photon sensitivity. Under these conditions, our approach can determine ON and OFF power-law exponents with a precision of 3% from a comparison to numerical simulations, even for shot-noise-dominated emission signals with an average intensity below 1 photon per frame and per quantum dot. These capabilities pave the way for the unbiased, threshold-free determination of blinking power-law exponents at the microsecond time scale.

Real time correlation function in a single phase space integral beyond the linearized semiclassical initial value representation.

PubMed

Liu, Jian; Miller, William H

2007-06-21

It is shown how quantum mechanical time correlation functions [defined, e.g., in Eq. (1.1)] can be expressed, without approximation, in the same form as the linearized approximation of the semiclassical initial value representation (LSC-IVR), or classical Wigner model, for the correlation function [cf. Eq. (2.1)], i.e., as a phase space average (over initial conditions for trajectories) of the Wigner functions corresponding to the two operators. The difference is that the trajectories involved in the LSC-IVR evolve classically, i.e., according to the classical equations of motion, while in the exact theory they evolve according to generalized equations of motion that are derived here. Approximations to the exact equations of motion are then introduced to achieve practical methods that are applicable to complex (i.e., large) molecular systems. Four such methods are proposed in the paper--the full Wigner dynamics (full WD) and the second order WD based on "Wigner trajectories" [H. W. Lee and M. D. Scully, J. Chem. Phys. 77, 4604 (1982)] and the full Donoso-Martens dynamics (full DMD) and the second order DMD based on "Donoso-Martens trajectories" [A. Donoso and C. C. Martens, Phys. Rev. Lett. 8722, 223202 (2001)]--all of which can be viewed as generalizations of the original LSC-IVR method. Numerical tests of the four versions of this new approach are made for two anharmonic model problems, and for each the momentum autocorrelation function (i.e., operators linear in coordinate or momentum operators) and the force autocorrelation function (nonlinear operators) have been calculated. These four new approximate treatments are indeed seen to be significant improvements to the original LSC-IVR approximation.

DS/LPI autocorrelation detection in noise plus random-tone interference. [Direct Sequence Low-Probabilty of Intercept

NASA Technical Reports Server (NTRS)

Hinedi, S.; Polydoros, A.

1988-01-01

The authors present and analyze a frequency-noncoherent two-lag autocorrelation statistic for the wideband detection of random BPSK signals in noise-plus-random-multitone interference. It is shown that this detector is quite robust to the presence or absence of interference and its specific parameter values, contrary to the case of an energy detector. The rule assumes knowledge of the data rate and the active scenario under H0. It is concluded that the real-time autocorrelation domain and its samples (lags) are a viable approach for detecting random signals in dense environments.

Path integral Liouville dynamics: Applications to infrared spectra of OH, water, ammonia, and methane

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

Liu, Jian, E-mail: jianliupku@pku.edu.cn; State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871; Zhang, Zhijun

Path integral Liouville dynamics (PILD) is applied to vibrational dynamics of several simple but representative realistic molecular systems (OH, water, ammonia, and methane). The dipole-derivative autocorrelation function is employed to obtain the infrared spectrum as a function of temperature and isotopic substitution. Comparison to the exact vibrational frequency shows that PILD produces a reasonably accurate peak position with a relatively small full width at half maximum. PILD offers a potentially useful trajectory-based quantum dynamics approach to compute vibrational spectra of molecular systems.

Random packing of regular polygons and star polygons on a flat two-dimensional surface.

PubMed

Cieśla, Michał; Barbasz, Jakub

2014-08-01

Random packing of unoriented regular polygons and star polygons on a two-dimensional flat continuous surface is studied numerically using random sequential adsorption algorithm. Obtained results are analyzed to determine the saturated random packing ratio as well as its density autocorrelation function. Additionally, the kinetics of packing growth and available surface function are measured. In general, stars give lower packing ratios than polygons, but when the number of vertexes is large enough, both shapes approach disks and, therefore, properties of their packing reproduce already known results for disks.

Statistics of some atmospheric turbulence records relevant to aircraft response calculations

NASA Technical Reports Server (NTRS)

Mark, W. D.; Fischer, R. W.

1981-01-01

Methods for characterizing atmospheric turbulence are described. The methods illustrated include maximum likelihood estimation of the integral scale and intensity of records obeying the von Karman transverse power spectral form, constrained least-squares estimation of the parameters of a parametric representation of autocorrelation functions, estimation of the power spectra density of the instantaneous variance of a record with temporally fluctuating variance, and estimation of the probability density functions of various turbulence components. Descriptions of the computer programs used in the computations are given, and a full listing of these programs is included.

A method to identify differential expression profiles of time-course gene data with Fourier transformation.

PubMed

Kim, Jaehee; Ogden, Robert Todd; Kim, Haseong

2013-10-18

Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis. This work aims to identify genes that show different gene expression profiles across time. We propose a statistical procedure to discover gene groups with similar profiles using a nonparametric representation that accounts for the autocorrelation in the data. In particular, we first represent each profile in terms of a Fourier basis, and then we screen out genes that are not differentially expressed based on the Fourier coefficients. Finally, we cluster the remaining gene profiles using a model-based approach in the Fourier domain. We evaluate the screening results in terms of sensitivity, specificity, FDR and FNR, compare with the Gaussian process regression screening in a simulation study and illustrate the results by application to yeast cell-cycle microarray expression data with alpha-factor synchronization.The key elements of the proposed methodology: (i) representation of gene profiles in the Fourier domain; (ii) automatic screening of genes based on the Fourier coefficients and taking into account autocorrelation in the data, while controlling the false discovery rate (FDR); (iii) model-based clustering of the remaining gene profiles. Using this method, we identified a set of cell-cycle-regulated time-course yeast genes. The proposed method is general and can be potentially used to identify genes which have the same patterns or biological processes, and help facing the present and forthcoming challenges of data analysis in functional genomics.

Preliminary results for model identification in characterizing 2-D topographic road profiles

NASA Astrophysics Data System (ADS)

Kern, Joshua V.; Ferris, John B.

2006-05-01

Load data representing severe customer usage is needed throughout a chassis development program; the majority of these chassis loads originate with the excitation from the road. These chassis loads are increasingly derived from vehicle simulations. Simulating a vehicle traversing long roads is simply impractical, however, and a greatly reduced set of characteristic roads must be found. In order to characterize a road, certain modeling assumptions must be made. Several models have been proposed making various assumptions about the properties that road profiles possess. The literature in this field is reviewed before focusing on two modeling assumptions of particular interest: the stationarity of the signal (homogeneity of the road) and the corresponding interval over which previous data points are correlated to the current data point. In this work, 2-D topographic road profiles are considered to be signals that are realizations of a stochastic process. The objective of this work is to investigate the stationarity assumption and the interval of influence for several carefully controlled sections of highway pavement in the United States. Two statistical techniques are used in analyzing these data: the autocorrelation and the partial autocorrelation. It is shown that the road profile signals in their original form are not stationary and have an extremely long interval of influence on the order of 25m. By differencing the data, however, it is often possible to generate stationary residuals and a very short interval of influence on the order of 250mm. By examining the autocorrelation and the partial autocorrelation, various versions of ARIMA models appear to be appropriate for further modeling. Implications to modeling the signals as Markov Chains are also discussed. In this way, roads can be characterized by the model architecture and the particular parameterization of the model. Any synthetic road realized from a particular model represents all profiles in this set. Realizations of any length can be generated, allowing efficient simulation and timely information about the chassis loads that can be used for design decisions. This work provides insights for future development in the modeling and characterization of 2-D topographic road profiles.

Statistical process control of mortality series in the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database: implications of the data generating process

PubMed Central

2013-01-01

Background Statistical process control (SPC), an industrial sphere initiative, has recently been applied in health care and public health surveillance. SPC methods assume independent observations and process autocorrelation has been associated with increase in false alarm frequency. Methods Monthly mean raw mortality (at hospital discharge) time series, 1995–2009, at the individual Intensive Care unit (ICU) level, were generated from the Australia and New Zealand Intensive Care Society adult patient database. Evidence for series (i) autocorrelation and seasonality was demonstrated using (partial)-autocorrelation ((P)ACF) function displays and classical series decomposition and (ii) “in-control” status was sought using risk-adjusted (RA) exponentially weighted moving average (EWMA) control limits (3 sigma). Risk adjustment was achieved using a random coefficient (intercept as ICU site and slope as APACHE III score) logistic regression model, generating an expected mortality series. Application of time-series to an exemplar complete ICU series (1995-(end)2009) was via Box-Jenkins methodology: autoregressive moving average (ARMA) and (G)ARCH ((Generalised) Autoregressive Conditional Heteroscedasticity) models, the latter addressing volatility of the series variance. Results The overall data set, 1995-2009, consisted of 491324 records from 137 ICU sites; average raw mortality was 14.07%; average(SD) raw and expected mortalities ranged from 0.012(0.113) and 0.013(0.045) to 0.296(0.457) and 0.278(0.247) respectively. For the raw mortality series: 71 sites had continuous data for assessment up to or beyond lag40 and 35% had autocorrelation through to lag40; and of 36 sites with continuous data for ≥ 72 months, all demonstrated marked seasonality. Similar numbers and percentages were seen with the expected series. Out-of-control signalling was evident for the raw mortality series with respect to RA-EWMA control limits; a seasonal ARMA model, with GARCH effects, displayed white-noise residuals which were in-control with respect to EWMA control limits and one-step prediction error limits (3SE). The expected series was modelled with a multiplicative seasonal autoregressive model. Conclusions The data generating process of monthly raw mortality series at the ICU level displayed autocorrelation, seasonality and volatility. False-positive signalling of the raw mortality series was evident with respect to RA-EWMA control limits. A time series approach using residual control charts resolved these issues. PMID:23705957

Formation and Reconnection of Three-dimensional Current Sheets with a Guide Field in the Solar Corona

NASA Astrophysics Data System (ADS)

Edmondson, J. K.; Lynch, B. J.

2017-11-01

We analyze a series of three-dimensional magnetohydrodynamic numerical simulations of magnetic reconnection in a model solar corona to study the effect of the guide-field component on quasi-steady-state interchange reconnection in a pseudostreamer arcade configuration. This work extends the analysis of Edmondson et al. by quantifying the mass density enhancement coherency scale in the current sheet associated with magnetic island formation during the nonlinear phase of plasmoid-unstable reconnection. We compare the results of four simulations of a zero, weak, moderate, and a strong guide field, {B}{GF}/{B}0=\\{0.0,0.1,0.5,1.0\\}, to quantify the plasmoid density enhancement’s longitudinal and transverse coherency scales as a function of the guide-field strength. We derive these coherency scales from autocorrelation and wavelet analyses, and demonstrate how these scales may be used to interpret the density enhancement fluctuation’s Fourier power spectra in terms of a structure formation range, an energy continuation range, and an inertial range—each population with a distinct spectral slope. We discuss the simulation results in the context of solar and heliospheric observations of pseudostreamer solar wind outflow and possible signatures of reconnection-generated structure.

Counting the peaks in the excitation function for precompound processes

NASA Astrophysics Data System (ADS)

Bonetti, R.; Hussein, M. S.; Mello, P. A.

1983-08-01

The "counting of maxima" method of Brink and Stephen, conventionally used for the extraction of the correlation width of statistical (compound nucleus) reactions, is generalized to include precompound processes as well. It is found that this method supplies an important independent check of the results obtained from autocorrelation studies. An application is made to the reaction 25Mg(3He,p). NUCLEAR REACTIONS Statistical multistep compound processes discussed.

Communication: Symmetrical quasi-classical analysis of linear optical spectroscopy

NASA Astrophysics Data System (ADS)

Provazza, Justin; Coker, David F.

2018-05-01

The symmetrical quasi-classical approach for propagation of a many degree of freedom density matrix is explored in the context of computing linear spectra. Calculations on a simple two state model for which exact results are available suggest that the approach gives a qualitative description of peak positions, relative amplitudes, and line broadening. Short time details in the computed dipole autocorrelation function result in exaggerated tails in the spectrum.

Random sequential adsorption of cubes

NASA Astrophysics Data System (ADS)

Cieśla, Michał; Kubala, Piotr

2018-01-01

Random packings built of cubes are studied numerically using a random sequential adsorption algorithm. To compare the obtained results with previous reports, three different models of cube orientation sampling were used. Also, three different cube-cube intersection algorithms were tested to find the most efficient one. The study focuses on the mean saturated packing fraction as well as kinetics of packing growth. Microstructural properties of packings were analyzed using density autocorrelation function.

Ozone data and mission sampling analysis

NASA Technical Reports Server (NTRS)

Robbins, J. L.

1980-01-01

A methodology was developed to analyze discrete data obtained from the global distribution of ozone. Statistical analysis techniques were applied to describe the distribution of data variance in terms of empirical orthogonal functions and components of spherical harmonic models. The effects of uneven data distribution and missing data were considered. Data fill based on the autocorrelation structure of the data is described. Computer coding of the analysis techniques is included.

Effects of calcium leaching on diffusion properties of hardened and altered cement pastes

NASA Astrophysics Data System (ADS)

Kurumisawa, Kiyofumi; Haga, Kazuko; Hayashi, Daisuke; Owada, Hitoshi

2017-06-01

It is very important to predict alterations in the concrete used for fabricating disposal containers for radioactive waste. Therefore, it is necessary to understand the alteration of cementitious materials caused by calcium leaching when they are in contact with ground water in the long term. To evaluate the long-term transport characteristics of cementitious materials, the microstructural behavior of these materials should be considered. However, many predictive models of transport characteristics focus on the pore structure, while only few such models consider both, the spatial distribution of calcium silicate hydrate (C-S-H), portlandite, and the pore spaces. This study focused on the spatial distribution of these cement phases. The auto-correlation function of each phase of cementitious materials was calculated from two-dimensional backscattered electron imaging, and the three-dimensional spatial image of the cementitious material was produced using these auto-correlation functions. An attempt was made to estimate the diffusion coefficient of chloride from the three-dimensional spatial image. The estimated diffusion coefficient of the altered sample from the three-dimensional spatial image was found to be comparable to the measured value. This demonstrated that it is possible to predict the diffusion coefficient of the altered cement paste by using the proposed model.

Green-Kubo relation for viscosity tested using experimental data for a two-dimensional dusty plasma

NASA Astrophysics Data System (ADS)

Feng, Yan; Goree, J.; Liu, Bin; Cohen, E. G. D.

2011-10-01

The theoretical Green-Kubo relation for viscosity is tested using experimentally obtained data. In a dusty plasma experiment, micron-sized dust particles are introduced into a partially ionized argon plasma, where they become negatively charged. They are electrically levitated to form a single-layer Wigner crystal, which is subsequently melted using laser heating. In the liquid phase, these dust particles experience interparticle electric repulsion, laser heating, and friction from the ambient neutral argon gas, and they can be considered to be in a nonequilibrium steady state. Direct measurements of the positions and velocities of individual dust particles are then used to obtain a time series for an off-diagonal element of the stress tensor and its time autocorrelation function. This calculation also requires the interparticle potential, which was not measured experimentally but was obtained using a Debye-Hückel-type model with experimentally determined parameters. Integrating the autocorrelation function over time yields the viscosity for shearing motion among dust particles. The viscosity so obtained is found to agree with results from a previous experiment using a hydrodynamical Navier-Stokes equation. This comparison serves as a test of the Green-Kubo relation for viscosity. Our result is also compared to the predictions of several simulations.

Floquet spin states in graphene under ac-driven spin-orbit interaction

NASA Astrophysics Data System (ADS)

López, A.; Sun, Z. Z.; Schliemann, J.

2012-05-01

We study the role of periodically driven time-dependent Rashba spin-orbit coupling (RSOC) on a monolayer graphene sample. After recasting the originally 4×4 system of dynamical equations as two time-reversal related two-level problems, the quasienergy spectrum and the related dynamics are investigated via various techniques and approximations. In the static case, the system is gapped at the Dirac point. The rotating wave approximation (RWA) applied to the driven system unphysically preserves this feature, while the Magnus-Floquet approach as well as a numerically exact evaluation of the Floquet equation show that this gap is dynamically closed. In addition, a sizable oscillating pattern of the out-of-plane spin polarization is found in the driven case for states that are completely unpolarized in the static limit. Evaluation of the autocorrelation function shows that the original uniform interference pattern corresponding to time-independent RSOC gets distorted. The resulting structure can be qualitatively explained as a consequence of the transitions induced by the ac driving among the static eigenstates, i.e., these transitions modulate the relative phases that add up to give the quantum revivals of the autocorrelation function. Contrary to the static case, in the driven scenario, quantum revivals (suppressions) are correlated to spin-up (down) phases.

Molecular dynamic simulations of N2-broadened methane line shapes and comparison with experiments

NASA Astrophysics Data System (ADS)

Le, Tuong; Doménech, José-Luis; Lepère, Muriel; Tran, Ha

2017-03-01

Absorption spectra of methane transitions broadened by nitrogen have been calculated for the first time using classical molecular dynamic simulations. For that, the time evolution of the auto-correlation function of the dipole moment vector, assumed along a C-H axis, was computed using an accurate site-site intermolecular potential for CH4-N2. Quaternion coordinates were used to treat the rotation of the molecules. A requantization procedure was applied to the classical rotation and spectra were then derived as the Fourier-Laplace transform of the auto-correlation function. These computed spectra were compared with experimental ones recorded with a tunable diode laser and a difference-frequency laser spectrometer. Specifically, nine isolated methane lines broadened by nitrogen, belonging to various vibrational bands and having rotational quantum numbers J from 0 to 9, were measured at room temperature and at several pressures from 20 to 945 mbar. Comparisons between measured and calculated spectra were made through their fits using the Voigt profile. The results show that ab initio calculated spectra reproduce with very high fidelity non-Voigt effects on the measurements and that classical molecular dynamic simulations can be used to predict spectral shapes of isolated lines of methane perturbed by nitrogen.

Correlation time and diffusion coefficient imaging: application to a granular flow system.

PubMed

Caprihan, A; Seymour, J D

2000-05-01

A parametric method for spatially resolved measurements for velocity autocorrelation functions, R(u)(tau) = , expressed as a sum of exponentials, is presented. The method is applied to a granular flow system of 2-mm oil-filled spheres rotated in a half-filled horizontal cylinder, which is an Ornstein-Uhlenbeck process with velocity autocorrelation function R(u)(tau) = e(- ||tau ||/tau(c)), where tau(c) is the correlation time and D = tau(c) is the diffusion coefficient. The pulsed-field-gradient NMR method consists of applying three different gradient pulse sequences of varying motion sensitivity to distinguish the range of correlation times present for particle motion. Time-dependent apparent diffusion coefficients are measured for these three sequences and tau(c) and D are then calculated from the apparent diffusion coefficient images. For the cylinder rotation rate of 2.3 rad/s, the axial diffusion coefficient at the top center of the free surface was 5.5 x 10(-6) m(2)/s, the correlation time was 3 ms, and the velocity fluctuation or granular temperature was 1.8 x 10(-3) m(2)/s(2). This method is also applicable to study transport in systems involving turbulence and porous media flows. Copyright 2000 Academic Press.

Lithium ion dynamics in Li2S+GeS2+GeO2 glasses studied using (7)Li NMR field-cycling relaxometry and line-shape analysis.

PubMed

Gabriel, Jan; Petrov, Oleg V; Kim, Youngsik; Martin, Steve W; Vogel, Michael

2015-09-01

We use (7)Li NMR to study the ionic jump motion in ternary 0.5Li2S+0.5[(1-x)GeS2+xGeO2] glassy lithium ion conductors. Exploring the "mixed glass former effect" in this system led to the assumption of a homogeneous and random variation of diffusion barriers in this system. We exploit that combining traditional line-shape analysis with novel field-cycling relaxometry, it is possible to measure the spectral density of the ionic jump motion in broad frequency and temperature ranges and, thus, to determine the distribution of activation energies. Two models are employed to parameterize the (7)Li NMR data, namely, the multi-exponential autocorrelation function model and the power-law waiting times model. Careful evaluation of both of these models indicates a broadly inhomogeneous energy landscape for both the single (x=0.0) and the mixed (x=0.1) network former glasses. The multi-exponential autocorrelation function model can be well described by a Gaussian distribution of activation barriers. Applicability of the methods used and their sensitivity to microscopic details of ionic motion are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

Effect of the spatial autocorrelation of empty sites on the evolution of cooperation

NASA Astrophysics Data System (ADS)

Zhang, Hui; Wang, Li; Hou, Dongshuang

2016-02-01

An evolutionary game model is constructed to investigate the spatial autocorrelation of empty sites on the evolution of cooperation. Each individual is assumed to imitate the strategy of the one who scores the highest in its neighborhood including itself. Simulation results illustrate that the evolutionary dynamics based on the Prisoner's Dilemma game (PD) depends severely on the initial conditions, while the Snowdrift game (SD) is hardly affected by that. A high degree of autocorrelation of empty sites is beneficial for the evolution of cooperation in the PD, whereas it shows diversification effects depending on the parameter of temptation to defect in the SD. Moreover, for the repeated game with three strategies, 'always defect' (ALLD), 'tit-for-tat' (TFT), and 'always cooperate' (ALLC), simulations reveal that an amazing evolutionary diversity appears for varying of parameters of the temptation to defect and the probability of playing in the next round of the game. The spatial autocorrelation of empty sites can have profound effects on evolutionary dynamics (equilibrium and oscillation) and spatial distribution.

Dynamical Correlation In Some Liquid Alkaline Earth Metals Near Melting

NASA Astrophysics Data System (ADS)

Thakore, B. Y.; Suthar, P. H.; Khambholja, S. G.; Gajjar, P. N.; Jani, A. R.

2010-12-01

The study of dynamical variables: velocity autocorrelation function (VACF) and power spectrum of liquid alkaline earth metals (Ca, Sr, and Ba) have been presented based on the static harmonic well approximation. The effective interatomic potential for liquid metals is computed using our well recognized model potential with the exchange correlation functions due to Hartree, Taylor, Ichimaru and Utsumi, Farid et al. and Sarkar et al. It is observed that the VACF computed using Sarkar et al. gives the good agreement with available molecular dynamics simulation (MD) results [Phys Rev. B 62, 14818 (2000)]. The shoulder of the power spectrum depends upon the type of local field correlation function used.

First spectra from a new, wide band, hybrid digital correlator spectrometer for the FIRST-HIFI instrument.

NASA Astrophysics Data System (ADS)

Cais, P.; Ravera, L.; Lagrange, D.; Giard, M.; Baudry, A.; Mayvial, J. Y.

1998-11-01

The authors have designed and built a new, wide band, modulable resolution spectrometer, in view of full astronomical qualifying tests, and to prepare future models for the FIRST satellite's heterodyne instrument. The spectrometer, a hybrid digital autocorrelator, offers flexibility in terms of bandwidth (from 170 MHz to 680 MHz) and resolution (from 700 kHz to 3 MHz). This spectrometer required the development of a dedicated analog filter bank, homemade samplers, and the design of full custom GaAs integrated circuits. Laboratory tests have shown excellent agreement with expected performances and observations performed with the IRAM 30-m radiotelescope have qualified its capabilities. Despite the relatively limited number of channels of the current prototype compared to other spectrometers, the main advantages are its stability (inherent to digital technique), and its spectral versatility. Microelectronics advances and rad-tolerance of the spectrometer components are used to prepare a new, compact, and low power consumption autocorrelator in view of a flight model for HIFI, the heterodyne instrument on the ESA cornerstone mission FIRST.

Non-Markovian properties and multiscale hidden Markovian network buried in single molecule time series

NASA Astrophysics Data System (ADS)

Sultana, Tahmina; Takagi, Hiroaki; Morimatsu, Miki; Teramoto, Hiroshi; Li, Chun-Biu; Sako, Yasushi; Komatsuzaki, Tamiki

2013-12-01

We present a novel scheme to extract a multiscale state space network (SSN) from single-molecule time series. The multiscale SSN is a type of hidden Markov model that takes into account both multiple states buried in the measurement and memory effects in the process of the observable whenever they exist. Most biological systems function in a nonstationary manner across multiple timescales. Combined with a recently established nonlinear time series analysis based on information theory, a simple scheme is proposed to deal with the properties of multiscale and nonstationarity for a discrete time series. We derived an explicit analytical expression of the autocorrelation function in terms of the SSN. To demonstrate the potential of our scheme, we investigated single-molecule time series of dissociation and association kinetics between epidermal growth factor receptor (EGFR) on the plasma membrane and its adaptor protein Ash/Grb2 (Grb2) in an in vitro reconstituted system. We found that our formula successfully reproduces their autocorrelation function for a wide range of timescales (up to 3 s), and the underlying SSNs change their topographical structure as a function of the timescale; while the corresponding SSN is simple at the short timescale (0.033-0.1 s), the SSN at the longer timescales (0.1 s to ˜3 s) becomes rather complex in order to capture multiscale nonstationary kinetics emerging at longer timescales. It is also found that visiting the unbound form of the EGFR-Grb2 system approximately resets all information of history or memory of the process.

Commercial counterboard for 10 ns software correlator for photon and fluorescence correlation spectroscopy.

PubMed

Molteni, Matteo; Ferri, Fabio

2016-11-01

A 10 ns time resolution, multi-tau software correlator, capable of computing simultaneous autocorrelation (A-A, B-B) and cross (A-B) correlation functions at count rates up to ∼10 MHz, with no data loss, has been developed in LabVIEW and C++ by using the National Instrument timer/counterboard (NI PCIe-6612) and a fast Personal Computer (PC) (Intel Core i7-4790 Processor 3.60 GHz ). The correlator works by using two algorithms: for large lag times (τ ≳ 1 μs), a classical time-mode scheme, based on the measure of the number of pulses per time interval, is used; differently, for τ ≲ 1 μs a photon-mode (PM) scheme is adopted and the correlation function is retrieved from the sequence of the photon arrival times. Single auto- and cross-correlation functions can be processed online in full real time up to count rates of ∼1.8 MHz and ∼1.2 MHz, respectively. Two autocorrelation (A-A, B-B) and a cross correlation (A-B) functions can be simultaneously processed in full real time only up to count rates of ∼750 kHz. At higher count rates, the online processing takes place in a delayed modality, but with no data loss. When tested with simulated correlation data and latex spheres solutions, the overall performances of the correlator appear to be comparable with those of commercial hardware correlators, but with several nontrivial advantages related to its flexibility, low cost, and easy adaptability to future developments of PC and data acquisition technology.

Commercial counterboard for 10 ns software correlator for photon and fluorescence correlation spectroscopy

NASA Astrophysics Data System (ADS)

Molteni, Matteo; Ferri, Fabio

2016-11-01

A 10 ns time resolution, multi-tau software correlator, capable of computing simultaneous autocorrelation (A-A, B-B) and cross (A-B) correlation functions at count rates up to ˜10 MHz, with no data loss, has been developed in LabVIEW and C++ by using the National Instrument timer/counterboard (NI PCIe-6612) and a fast Personal Computer (PC) (Intel Core i7-4790 Processor 3.60 GHz ). The correlator works by using two algorithms: for large lag times (τ ≳ 1 μs), a classical time-mode scheme, based on the measure of the number of pulses per time interval, is used; differently, for τ ≲ 1 μs a photon-mode (PM) scheme is adopted and the correlation function is retrieved from the sequence of the photon arrival times. Single auto- and cross-correlation functions can be processed online in full real time up to count rates of ˜1.8 MHz and ˜1.2 MHz, respectively. Two autocorrelation (A-A, B-B) and a cross correlation (A-B) functions can be simultaneously processed in full real time only up to count rates of ˜750 kHz. At higher count rates, the online processing takes place in a delayed modality, but with no data loss. When tested with simulated correlation data and latex spheres solutions, the overall performances of the correlator appear to be comparable with those of commercial hardware correlators, but with several nontrivial advantages related to its flexibility, low cost, and easy adaptability to future developments of PC and data acquisition technology.

The faint galaxy contribution to the diffuse extragalactic background light

NASA Technical Reports Server (NTRS)

Cole, Shaun; Treyer, Marie-Agnes; Silk, Joseph

1992-01-01

Models of the faint galaxy contribution to the diffuse extragalactic background light are presented, which are consistent with current data on faint galaxy number counts and redshifts. The autocorrelation function of surface brightness fluctuations in the extragalactic diffuse light is predicted, and the way in which these predictions depend on the cosmological model and assumptions of biasing is determined. It is confirmed that the recent deep infrared number counts are most compatible with a high density universe (Omega-0 is approximately equal to 1) and that the steep blue counts then require an extra population of rapidly evolving blue galaxies. The faintest presently detectable galaxies produce an interesting contribution to the extragalactic diffuse light, and still fainter galaxies may also produce a significant contribution. These faint galaxies still only produce a small fraction of the total optical diffuse background light, but on scales of a few arcminutes to a few degrees, they produce a substantial fraction of the fluctuations in the diffuse light.

Preliminary rotor wake measurements with a laser velocimeter

NASA Technical Reports Server (NTRS)

Hoad, D. R.; Rhodes, D. B.; Meyers, J. F.

1983-01-01

A laser velocimeter (LV) was used to determine rotor wake characteristics. The effect of various fuselage widths and rotor-fuselage spacings on time averaged and detailed time dependent rotor wake velocity characteristics was defined. Definition of time dependent velocity characteristics was attempted with the LV by associating a rotor azimuth position with each velocity measurement. Results were discouraging in that no apparent time dependent velocity characteristics could be discerned from the LV measurements. Since the LV is a relatively new instrument in the rotor wake measurement field, the cause of this lack of periodicity is as important as the basic research objectives. An attempt was made to identify the problem by simulated acquisition of LV-type data for a predicted rotor wake velocity time history. Power spectral density and autocorrelation function estimation techniques were used to substantiate the conclusion that the primary cause of the lack of time dependent velocity characteristics was the nonstationary flow condition generated by the periodic turbulence level that currently exists in the open throat configuration of the wind tunnel.

Kepler Observations of Rapid Optical Variability in the BL Lac Object W2r192+42

NASA Technical Reports Server (NTRS)

R.Edelson; Mushotzky, R.; Vaughn, S.; Scargle, J.; Gandhi, P.; Malkan, M.; Baumgartner, W.

2013-01-01

We present the first Kepler monitoring of a strongly variable BL Lac, W2R1926+42. The light curve covers 181 days with approx. 0.2% errors, 30 minute sampling and >90% duty cycle, showing numerous delta-I/I > 25% flares over timescales as short as a day. The flux distribution is highly skewed and non-Gaussian. The variability shows a strong rms-flux correlation with the clearest evidence to date for non-linearity in this relation. We introduce a method to measure periodograms from the discrete autocorrelation function, an approach that may be well-suited to a wide range of Kepler data. The periodogram is not consistent with a simple power-law, but shows a flattening at frequencies below 7x10(exp -5) Hz. Simple models of the power spectrum, such as a broken power law, do not produce acceptable fits, indicating that the Kepler blazar light curve requires more sophisticated mathematical and physical descriptions than currently in use.

Comparison of two fractal interpolation methods

NASA Astrophysics Data System (ADS)

Fu, Yang; Zheng, Zeyu; Xiao, Rui; Shi, Haibo

2017-03-01

As a tool for studying complex shapes and structures in nature, fractal theory plays a critical role in revealing the organizational structure of the complex phenomenon. Numerous fractal interpolation methods have been proposed over the past few decades, but they differ substantially in the form features and statistical properties. In this study, we simulated one- and two-dimensional fractal surfaces by using the midpoint displacement method and the Weierstrass-Mandelbrot fractal function method, and observed great differences between the two methods in the statistical characteristics and autocorrelation features. From the aspect of form features, the simulations of the midpoint displacement method showed a relatively flat surface which appears to have peaks with different height as the fractal dimension increases. While the simulations of the Weierstrass-Mandelbrot fractal function method showed a rough surface which appears to have dense and highly similar peaks as the fractal dimension increases. From the aspect of statistical properties, the peak heights from the Weierstrass-Mandelbrot simulations are greater than those of the middle point displacement method with the same fractal dimension, and the variances are approximately two times larger. When the fractal dimension equals to 1.2, 1.4, 1.6, and 1.8, the skewness is positive with the midpoint displacement method and the peaks are all convex, but for the Weierstrass-Mandelbrot fractal function method the skewness is both positive and negative with values fluctuating in the vicinity of zero. The kurtosis is less than one with the midpoint displacement method, and generally less than that of the Weierstrass-Mandelbrot fractal function method. The autocorrelation analysis indicated that the simulation of the midpoint displacement method is not periodic with prominent randomness, which is suitable for simulating aperiodic surface. While the simulation of the Weierstrass-Mandelbrot fractal function method has strong periodicity, which is suitable for simulating periodic surface.

Shannon entropy in the research on stationary regimes and the evolution of complexity

NASA Astrophysics Data System (ADS)

Eskov, V. M.; Eskov, V. V.; Vochmina, Yu. V.; Gorbunov, D. V.; Ilyashenko, L. K.

2017-05-01

The questions of the identification of complex biological systems (complexity) as special self-organizing systems or systems of the third type first defined by W. Weaver in 1948 continue to be of interest. No reports on the evaluation of entropy for systems of the third type were found among the publications currently available to the authors. The present study addresses the parameters of muscle biopotentials recorded using surface interference electromyography and presents the results of calculation of the Shannon entropy, autocorrelation functions, and statistical distribution functions for electromyograms of subjects in different physiological states (rest and tension of muscles). The results do not allow for statistically reliable discrimination between the functional states of muscles. However, the data obtained by calculating electromyogram quasiatttractor parameters and matrices of paired comparisons of electromyogram samples (calculation of the number k of "coinciding" pairs among the electromyogram samples) provide an integral characteristic that allows the identification of substantial differences between the state of rest and the different states of functional activity. Modifications and implementation of new methods in combination with the novel methods of the theory of chaos and self-organization are obviously essential. The stochastic approach paradigm is not applicable to systems of the third type due to continuous and chaotic changes of the parameters of the state vector x( t) of an organism or the contrasting constancy of these parameters (in the case of entropy).

Analysis of spatial autocorrelation patterns of heavy and super-heavy rainfall in Iran

NASA Astrophysics Data System (ADS)

Rousta, Iman; Doostkamian, Mehdi; Haghighi, Esmaeil; Ghafarian Malamiri, Hamid Reza; Yarahmadi, Parvane

2017-09-01

Rainfall is a highly variable climatic element, and rainfall-related changes occur in spatial and temporal dimensions within a regional climate. The purpose of this study is to investigate the spatial autocorrelation changes of Iran's heavy and super-heavy rainfall over the past 40 years. For this purpose, the daily rainfall data of 664 meteorological stations between 1971 and 2011 are used. To analyze the changes in rainfall within a decade, geostatistical techniques like spatial autocorrelation analysis of hot spots, based on the Getis-Ord G i statistic, are employed. Furthermore, programming features in MATLAB, Surfer, and GIS are used. The results indicate that the Caspian coast, the northwest and west of the western foothills of the Zagros Mountains of Iran, the inner regions of Iran, and southern parts of Southeast and Northeast Iran, have the highest likelihood of heavy and super-heavy rainfall. The spatial pattern of heavy rainfall shows that, despite its oscillation in different periods, the maximum positive spatial autocorrelation pattern of heavy rainfall includes areas of the west, northwest and west coast of the Caspian Sea. On the other hand, a negative spatial autocorrelation pattern of heavy rainfall is observed in central Iran and parts of the east, particularly in Zabul. Finally, it is found that patterns of super-heavy rainfall are similar to those of heavy rainfall.

Time series analyses of hydrological parameter variations and their correlations at a coastal area in Busan, South Korea

NASA Astrophysics Data System (ADS)

Chung, Sang Yong; Senapathi, Venkatramanan; Sekar, Selvam; Kim, Tae Hyung

2018-02-01

Monitoring and time-series analysis of the hydrological parameters electrical conductivity (EC), water pressure, precipitation and tide were carried out, to understand the characteristics of the parameter variations and their correlations at a coastal area in Busan, South Korea. The monitoring data were collected at a sharp interface between freshwater and saline water at the depth of 25 m below ground. Two well-logging profiles showed that seawater intrusion has largely expanded (progressed inland), and has greatly affected the groundwater quality in a coastal aquifer of tuffaceous sedimentary rock over a 9-year period. According to the time series analyses, the periodograms of the hydrological parameters present very similar trends to the power spectral densities (PSD) of the hydrological parameters. Autocorrelation functions (ACF) and partial autocorrelation functions (PACF) of the hydrological parameters were produced to evaluate their self-correlations. The ACFs of all hydrologic parameters showed very good correlation over the entire time lag, but the PACF revealed that the correlations were good only at time lag 1. Crosscorrelation functions (CCF) were used to evaluate the correlations between the hydrological parameters and the characteristics of seawater intrusion in the coastal aquifer system. The CCFs showed that EC had a close relationship with water pressure and precipitation rather than tide. The CCFs of water pressure with tide and precipitation were in inverse proportion, and the CCF of water pressure with precipitation was larger than that with tide.

The Generalized Multilevel Facets Model for Longitudinal Data

ERIC Educational Resources Information Center

Hung, Lai-Fa; Wang, Wen-Chung

2012-01-01

In the human sciences, ability tests or psychological inventories are often repeatedly conducted to measure growth. Standard item response models do not take into account possible autocorrelation in longitudinal data. In this study, the authors propose an item response model to account for autocorrelation. The proposed three-level model consists…

Exploring Online Learning Data Using Fractal Dimensions. Research Report. ETS RR-17-15

ERIC Educational Resources Information Center

Guo, Hongwen

2017-01-01

Data collected from online learning and tutoring systems for individual students showed strong autocorrelation or dependence because of content connection, knowledge-based dependency, or persistence of learning behavior. When the response data show little dependence or negative autocorrelations for individual students, it is suspected that…

VizieR Online Data Catalog: Molecular clumps in W51 giant molecular cloud (Parsons+, 2012)

NASA Astrophysics Data System (ADS)

Parsons, H.; Thompson, M. A.; Clark, J. S.; Chrysostomou, A.

2013-04-01

The W51 GMC was mapped using the Heterodyne Array Receiver Programme (HARP) receiver with the back-end digital autocorrelator spectrometer Auto-Correlation Spectral Imaging System (ACSIS) on the James Clerk Maxwell Telescope (JCMT). Data were taken in 2008 May. (2 data files).

Spatial Autocorrelation And Autoregressive Models In Ecology

Treesearch

Jeremy W. Lichstein; Theodore R. Simons; Susan A. Shriner; Kathleen E. Franzreb

2003-01-01

Abstract. Recognition and analysis of spatial autocorrelation has defined a new paradigm in ecology. Attention to spatial pattern can lead to insights that would have been otherwise overlooked, while ignoring space may lead to false conclusions about ecological relationships. We used Gaussian spatial autoregressive models, fit with widely available...

Measurement and data processing approach for detecting anisotropic spatial statistics of the turbulence-induced index of refraction fluctuations in the upper atmosphere.

PubMed

Havens, Timothy C; Roggemann, Michael C; Schulz, Timothy J; Brown, Wade W; Beyer, Jeff T; Otten, L John

2002-05-20

We discuss a method of data reduction and analysis that has been developed for a novel experiment to detect anisotropic turbulence in the tropopause and to measure the spatial statistics of these flows. The experimental concept is to make measurements of temperature at 15 points on a hexagonal grid for altitudes from 12,000 to 18,000 m while suspended from a balloon performing a controlled descent. From the temperature data, we estimate the index of refraction and study the spatial statistics of the turbulence-induced index of refraction fluctuations. We present and evaluate the performance of a processing approach to estimate the parameters of an anisotropic model for the spatial power spectrum of the turbulence-induced index of refraction fluctuations. A Gaussian correlation model and a least-squares optimization routine are used to estimate the parameters of the model from the measurements. In addition, we implemented a quick-look algorithm to have a computationally nonintensive way of viewing the autocorrelation function of the index fluctuations. The autocorrelation of the index of refraction fluctuations is binned and interpolated onto a uniform grid from the sparse points that exist in our experiment. This allows the autocorrelation to be viewed with a three-dimensional plot to determine whether anisotropy exists in a specific data slab. Simulation results presented here show that, in the presence of the anticipated levels of measurement noise, the least-squares estimation technique allows turbulence parameters to be estimated with low rms error.

Decorrelation Times of Photospheric Fields and Flows

NASA Technical Reports Server (NTRS)

Welsch, B. T.; Kusano, K.; Yamamoto, T. T.; Muglach, K.

2012-01-01

We use autocorrelation to investigate evolution in flow fields inferred by applying Fourier Local Correlation Tracking (FLCT) to a sequence of high-resolution (0.3 "), high-cadence (approx = 2 min) line-of-sight magnetograms of NOAA active region (AR) 10930 recorded by the Narrowband Filter Imager (NFI) of the Solar Optical Telescope (SOT) aboard the Hinode satellite over 12 - 13 December 2006. To baseline the timescales of flow evolution, we also autocorrelated the magnetograms, at several spatial binnings, to characterize the lifetimes of active region magnetic structures versus spatial scale. Autocorrelation of flow maps can be used to optimize tracking parameters, to understand tracking algorithms f susceptibility to noise, and to estimate flow lifetimes. Tracking parameters varied include: time interval Delta t between magnetogram pairs tracked, spatial binning applied to the magnetograms, and windowing parameter sigma used in FLCT. Flow structures vary over a range of spatial and temporal scales (including unresolved scales), so tracked flows represent a local average of the flow over a particular range of space and time. We define flow lifetime to be the flow decorrelation time, tau . For Delta t > tau, tracking results represent the average velocity over one or more flow lifetimes. We analyze lifetimes of flow components, divergences, and curls as functions of magnetic field strength and spatial scale. We find a significant trend of increasing lifetimes of flow components, divergences, and curls with field strength, consistent with Lorentz forces partially governing flows in the active photosphere, as well as strong trends of increasing flow lifetime and decreasing magnitudes with increases in both spatial scale and Delta t.

Exploring spatial heterogeneity and resilience in northern peatlands

NASA Astrophysics Data System (ADS)

Malhotra, A.; Roulet, N. T.

2011-12-01

Northern peatlands cover only 3% of the worlds land area while storing approximately 30% of the world's soil carbon making them important players in the global and regional carbon (C) cycle (Gorham 1991). Current peatland research attempts to predict changes in peatland biogeochemistry given climate change scenarios. However, the focus is primarily on linear responses to changes rather than on self regulation properties that are present in complex systems. Studying peatlands as complex adaptive systems (CAS) is important to fully understand peatland resilience and therefore to better predict response to disturbances. Peatlands possess properties of CAS such as spatial heterogeneity (SH), localized flows, self-organizing structures and non-linearity (Belyea and Baird 2006). The broad hypothesis of our proposed research is that SH in peatlands is positively connected with ecosystem resilience. To address our broad hypothesis we propose to 1) characterize SH in peatlands (using two visible indices of microtopography [MT] and vegetation structure [VEG]), 2) quantify the auto-correlation between visible SH and biogeochemical parameters and 3) investigate short term resilience using the response of biogeochemical parameters to environmental changes. The selection of biogeochemical parameters is based on prevalent theories on the persistence of MT in peatlands and parameters are related to peat accumulation (function of decomposition and net primary production; NPP), hydrology and nutrients (Swanson and Grigal 1988, Belyea and Clymo 2001, Eppinga et al. 2009). Field measurements will be conducted in the Stordalen mire in Abisko, Sweden. This site provides a steep environmental gradient with the presence of 3 peatland types- palsa, bog and fen. Each of these peatland types have varying degrees of spatial heterogeneity, exogenous controls (related to hydrology and permafrost), and therefore hypothesized varying degrees of resilience. Measurements will include nutrients, NPP, decomposition, surface topography, vegetation distribution, hydrology and environmental parameters. Preliminary data will be presented on the auto-correlation between MT, VEG and plant tissue nutrient in bog, fen and palsa peatland subtypes in Stordalen. We hypothesize a tighter auto-correlation between SH and nutrients in the more self-regulated system (bog) vs less self-regulated systems (palsa and fen). This research aims to provide insight into peatland self-regulation as well as improve current peatland models by generating high resolution spatial data on SH and biogeochemical parameters. Belyea, LR Baird, A. (2006). Beyond "the limits to peat bog growth": Cross-scale feedback in peatland development. Ecological Monographs, 76(3), 299-322 Belyea, L R, & Clymo, R S. (2001). Feedback control of the rate of peat formation. Proceedings. Biological sciences / The Royal Society, 268(1473), 1315-21 Eppinga, M. B., Ruiter, P. C. de, Wassen, Martin J, & Rietkerk, Max. (2009). Nutrients and hydrology indicate the driving mechanisms of peatland surface patterning. The American naturalist, 173(6), 803-18 Gorham, E. (1991). Northern Peatlands : Role in the Carbon Cycle and Probable Responses to Climatic Warming. Ecological Applications, 1(2), 182-195 Swanson, D. K., & Grigal, D. F. (1988). A Simulation Model of Mire Patterning. Oikos, 53(3), 309

Molecular dynamics of liquid SiO2 under high pressure

NASA Technical Reports Server (NTRS)

Rustad, James R.; Yuen, David A.; Spera, Frank J.

1990-01-01

The molecular dynamics of pure SiO2 liquids was investigated up to pressures of 20 GPa at 4000 K using 252, 498, 864, and 1371 particles. The results obtained suggest that the pressure-induced maxima in the self-diffusion coefficients of both oxygen and silicon are dependent on the system size. In the case of larger systems, the maximum decreases and shifts to lower pressures. Changes in the velocity autocorrelation function with increasing pressure are described. The populations of anomalously coordinated silicon and oxygen are then discussed as a function of pressure and system size.

The effects of organizational stress on inpatient psychiatric medication patterns.

PubMed

Gouse, A S

1984-07-01

The effect of organizational stress on the antipsychotic medication levels of patients was assessed over a 1-year period. Through the use of autocorrelational techniques, medication use was shown to function as a dynamic homeostasis: Continuous adjustments and counter-adjustments resulted in an approximation of equilibrium centering around an idealized dose level. Graphically, these homeostatic oscillations resembled a sinusoidal function with distinct amplitude and periodicity. Organizational stress significantly increased the amplitude of dose level oscillations and shortened the periodicity of each oscillation. Uncontrolled, this situation could lead to a state of extreme overmedication followed sharply by extreme undermedication .

Only marginal alignment of disc galaxies

NASA Astrophysics Data System (ADS)

Andrae, René; Jahnke, Knud

2011-12-01

Testing theories of angular-momentum acquisition of rotationally supported disc galaxies is the key to understanding the formation of this type of galaxies. The tidal-torque theory aims to explain this acquisition process in a cosmological framework and predicts positive autocorrelations of angular-momentum orientation and spiral-arm handedness, i.e. alignment of disc galaxies, on short distance scales of 1 Mpc h-1. This disc alignment can also cause systematic effects in weak-lensing measurements. Previous observations claimed discovering these correlations but are overly optimistic in the reported level of statistical significance of the detections. Errors in redshift, ellipticity and morphological classifications were not taken into account, although they have a significant impact. We explain how to rigorously propagate all the important errors through the estimation process. Analysing disc galaxies in the Sloan Digital Sky Survey (SDSS) data base, we find that positive autocorrelations of spiral-arm handedness and angular-momentum orientations on distance scales of 1 Mpc h-1 are plausible but not statistically significant. Current data appear not good enough to constrain parameters of theory. This result agrees with a simple hypothesis test in the Local Group, where we also find no evidence for disc alignment. Moreover, we demonstrate that ellipticity estimates based on second moments are strongly biased by galactic bulges even for Scd galaxies, thereby corrupting correlation estimates and overestimating the impact of disc alignment on weak-lensing studies. Finally, we discuss the potential of future sky surveys. We argue that photometric redshifts have too large errors, i.e. PanSTARRS and LSST cannot be used. Conversely, the EUCLID project will not cover the relevant redshift regime. We also discuss the potentials and problems of front-edge classifications of galaxy discs in order to improve the autocorrelation estimates of angular-momentum orientation.

Dynamical Resilience Indicators in Time Series of Self-Rated Health Correspond to Frailty Levels in Older Adults.

PubMed

Gijzel, Sanne M W; van de Leemput, Ingrid A; Scheffer, Marten; Roppolo, Mattia; Olde Rikkert, Marcel G M; Melis, René J F

2017-07-01

We currently still lack valid methods to dynamically measure resilience for stressors before the appearance of adverse health outcomes that hamper well-being. Quantifying an older adult's resilience in an early stage would aid complex decision-making in health care. Translating complex dynamical systems theory to humans, we hypothesized that three dynamical indicators of resilience (variance, temporal autocorrelation, and cross-correlation) in time series of self-rated physical, mental, and social health were associated with frailty levels in older adults. We monitored self-rated physical, mental, and social health during 100 days using daily visual analogue scale questions in 22 institutionalized older adults (mean age 84.0, SD: 5.9 years). Frailty was determined by the Survey of Health, Ageing and Retirement in Europe (SHARE) frailty index. The resilience indicators (variance, temporal autocorrelation, and cross-correlation) were calculated using multilevel models. The self-rated health time series of frail elderly exhibited significantly elevated variance in the physical, mental, and social domain, as well as significantly stronger cross-correlations between all three domains, as compared to the nonfrail group (all P < 0.001). Temporal autocorrelation was not significantly associated with frailty. We found supporting evidence for two out of three hypothesized resilience indicators to be related to frailty levels in older adults. By mirroring the dynamical resilience indicators to a frailty index, we delivered a first empirical base to validate and quantify the construct of systemic resilience in older adults in a dynamic way. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Investment Dynamics with Natural Expectations.

PubMed

Fuster, Andreas; Hebert, Benjamin; Laibson, David

2010-01-01

We study an investment model in which agents have the wrong beliefs about the dynamic properties of fundamentals. Specifically, we assume that agents underestimate the rate of mean reversion. The model exhibits the following six properties: (i) Beliefs are excessively optimistic in good times and excessively pessimistic in bad times. (ii) Asset prices are too volatile. (iii) Excess returns are negatively autocorrelated. (iv) High levels of corporate profits predict negative future excess returns. (v) Real economic activity is excessively volatile; the economy experiences amplified investment cycles. (vi) Corporate profits are positively autocorrelated in the short run and negatively autocorrelated in the medium run. The paper provides an illustrative model of animal spirits, amplified business cycles, and excess volatility.

Complete chirp analysis of a gain-switched pulse using an interferometric two-photon absorption autocorrelation.

PubMed

Chin, Sang Hoon; Kim, Young Jae; Song, Ho Seong; Kim, Dug Young

2006-10-10

We propose a simple but powerful scheme for the complete analysis of the frequency chirp of a gain-switched optical pulse using a fringe-resolved interferometric two-photon absorption autocorrelator. A frequency chirp imposed on the gain-switched pulse from a laser diode was retrieved from both the intensity autocorrelation trace and the envelope of the second-harmonic interference fringe pattern. To verify the accuracy of the proposed phase retrieval method, we have performed an optical pulse compression experiment by using dispersion-compensating fibers with different lengths. We have obtained close agreement by less than a 1% error between the compressed pulse widths and numerically calculated pulse widths.

Noise-tolerant instantaneous heart rate and R-peak detection using short-term autocorrelation for wearable healthcare systems.

PubMed

Fujii, Takahide; Nakano, Masanao; Yamashita, Ken; Konishi, Toshihiro; Izumi, Shintaro; Kawaguchi, Hiroshi; Yoshimoto, Masahiko

2013-01-01

This paper describes a robust method of Instantaneous Heart Rate (IHR) and R-peak detection from noisy electrocardiogram (ECG) signals. Generally, the IHR is calculated from the R-wave interval. Then, the R-waves are extracted from the ECG using a threshold. However, in wearable bio-signal monitoring systems, noise increases the incidence of misdetection and false detection of R-peaks. To prevent incorrect detection, we introduce a short-term autocorrelation (STAC) technique and a small-window autocorrelation (SWAC) technique, which leverages the similarity of QRS complex waveforms. Simulation results show that the proposed method improves the noise tolerance of R-peak detection.

Investment Dynamics with Natural Expectations*

PubMed Central

Fuster, Andreas; Hebert, Benjamin; Laibson, David

2012-01-01

We study an investment model in which agents have the wrong beliefs about the dynamic properties of fundamentals. Specifically, we assume that agents underestimate the rate of mean reversion. The model exhibits the following six properties: (i) Beliefs are excessively optimistic in good times and excessively pessimistic in bad times. (ii) Asset prices are too volatile. (iii) Excess returns are negatively autocorrelated. (iv) High levels of corporate profits predict negative future excess returns. (v) Real economic activity is excessively volatile; the economy experiences amplified investment cycles. (vi) Corporate profits are positively autocorrelated in the short run and negatively autocorrelated in the medium run. The paper provides an illustrative model of animal spirits, amplified business cycles, and excess volatility. PMID:23243469

15 pixels digital autocorrelation spectrometer system

NASA Astrophysics Data System (ADS)

Lee, Changhoon; Kim, Hyo-Ryung; Kim, Kwang-Dong; Chung, Mun-Hee; Timoc, C.

2006-06-01

In this paper describes the system configuration and the some performance test results of the 15 pixels digital autocorrelation spectrometer to be used at the Taeduk Radio Astronomy Observatory (TRAO) of Korea. This autocorrelation spectrometer instrument enclosed in a 3-slot VXI module and controlled via a USB port by a backend PC. This spectrometer system consists of the 4 band-pass filters unit, the digitizer, the 512 lags correlator, the clock distribution unit, and USB controller. And here we describe the frequency accuracy and the root-mean-square noise characteristic of this spectrometer. After some calibration procedure, this spectrometer can be use as the back-end system at TRAO for the 3x5 focal plane array receivers.

Elephants in space and time

Treesearch

Samuel A. Cushman; Michael Chase; Curtice Griffin

2005-01-01

Autocorrelation in animal movements can be both a serious nuisance to analysis and a source of valuable information about the scale and patterns of animal behavior, depending on the question and the techniques employed. In this paper we present an approach to analyzing the patterns of autocorrelation in animal movements that provides a detailed picture of seasonal...

Estimating the Autocorrelated Error Model with Trended Data: Further Results,

DTIC Science & Technology

1979-11-01

Perhaps the most serious deficiency of OLS in the presence of autocorrelation is not inefficiency but bias in its estimated standard errors--a bias...k for all t has variance var(b) = o2/ Tk2 2This refutes Maeshiro’s (1976) conjecture that "an estimator utilizing relevant extraneous information

Logistic regression for southern pine beetle outbreaks with spatial and temporal autocorrelation

Treesearch

M. L. Gumpertz; C.-T. Wu; John M. Pye

2000-01-01

Regional outbreaks of southern pine beetle (Dendroctonus frontalis Zimm.) show marked spatial and temporal patterns. While these patterns are of interest in themselves, we focus on statistical methods for estimating the effects of underlying environmental factors in the presence of spatial and temporal autocorrelation. The most comprehensive available information on...

An improved triple collocation algorithm for decomposing autocorrelated and white soil moisture retrieval errors

USDA-ARS?s Scientific Manuscript database

If not properly account for, auto-correlated errors in observations can lead to inaccurate results in soil moisture data analysis and reanalysis. Here, we propose a more generalized form of the triple collocation algorithm (GTC) capable of decomposing the total error variance of remotely-sensed surf...

Exploratory spatial data analysis of global MODIS active fire data

NASA Astrophysics Data System (ADS)

Oom, D.; Pereira, J. M. C.

2013-04-01

We performed an exploratory spatial data analysis (ESDA) of autocorrelation patterns in the NASA MODIS MCD14ML Collection 5 active fire dataset, for the period 2001-2009, at the global scale. The dataset was screened, resulting in an annual rate of false alarms and non-vegetation fires ranging from a minimum of 3.1% in 2003 to a maximum of 4.4% in 2001. Hot bare soils and gas flares were the major sources of false alarms and non-vegetation fires. The data were aggregated at 0.5° resolution for the global and local spatial autocorrelation Fire counts were found to be positively correlated up to distances of around 200 km, and negatively for larger distances. A value of 0.80 (p = 0.001, α = 0.05) for Moran's I indicates strong spatial autocorrelation between fires at global scale, with 60% of all cells displaying significant positive or negative spatial correlation. Different types of spatial autocorrelation were mapped and regression diagnostics allowed for the identification of spatial outlier cells, with fire counts much higher or lower than expected, considering their spatial context.

Modified Exponential Weighted Moving Average (EWMA) Control Chart on Autocorrelation Data

NASA Astrophysics Data System (ADS)

Herdiani, Erna Tri; Fandrilla, Geysa; Sunusi, Nurtiti

2018-03-01

In general, observations of the statistical process control are assumed to be mutually independence. However, this assumption is often violated in practice. Consequently, statistical process controls were developed for interrelated processes, including Shewhart, Cumulative Sum (CUSUM), and exponentially weighted moving average (EWMA) control charts in the data that were autocorrelation. One researcher stated that this chart is not suitable if the same control limits are used in the case of independent variables. For this reason, it is necessary to apply the time series model in building the control chart. A classical control chart for independent variables is usually applied to residual processes. This procedure is permitted provided that residuals are independent. In 1978, Shewhart modification for the autoregressive process was introduced by using the distance between the sample mean and the target value compared to the standard deviation of the autocorrelation process. In this paper we will examine the mean of EWMA for autocorrelation process derived from Montgomery and Patel. Performance to be investigated was investigated by examining Average Run Length (ARL) based on the Markov Chain Method.

The calculation of the viscosity from the autocorrelation function using molecular and atomic stress tensors

NASA Astrophysics Data System (ADS)

Cui, S. T.

The stress-stress correlation function and the viscosity of a united-atom model of liquid decane are studied by equilibrium molecular dynamics simulation using two different formalisms for the stress tensor: the atomic and the molecular formalisms. The atomic and molecular correlation functions show dramatic difference in short-time behaviour. The integrals of the two correlation functions, however, become identical after a short transient period whichis significantly shorter than the rotational relaxation time of the molecule. Both reach the same plateau value in a time period corresponding to this relaxation time. These results provide a convenient guide for the choice of the upper integral time limit in calculating the viscosity by the Green-Kubo formula.

Spatial occupancy models applied to atlas data show Southern Ground Hornbills strongly depend on protected areas.

PubMed

Broms, Kristin M; Johnson, Devin S; Altwegg, Res; Conquest, Loveday L

2014-03-01

Determining the range of a species and exploring species--habitat associations are central questions in ecology and can be answered by analyzing presence--absence data. Often, both the sampling of sites and the desired area of inference involve neighboring sites; thus, positive spatial autocorrelation between these sites is expected. Using survey data for the Southern Ground Hornbill (Bucorvus leadbeateri) from the Southern African Bird Atlas Project, we compared advantages and disadvantages of three increasingly complex models for species occupancy: an occupancy model that accounted for nondetection but assumed all sites were independent, and two spatial occupancy models that accounted for both nondetection and spatial autocorrelation. We modeled the spatial autocorrelation with an intrinsic conditional autoregressive (ICAR) model and with a restricted spatial regression (RSR) model. Both spatial models can readily be applied to any other gridded, presence--absence data set using a newly introduced R package. The RSR model provided the best inference and was able to capture small-scale variation that the other models did not. It showed that ground hornbills are strongly dependent on protected areas in the north of their South African range, but less so further south. The ICAR models did not capture any spatial autocorrelation in the data, and they took an order, of magnitude longer than the RSR models to run. Thus, the RSR occupancy model appears to be an attractive choice for modeling occurrences at large spatial domains, while accounting for imperfect detection and spatial autocorrelation.

Cobble cam: Grain-size measurements of sand to boulder from digital photographs and autocorrelation analyses

USGS Publications Warehouse

Warrick, J.A.; Rubin, D.M.; Ruggiero, P.; Harney, J.N.; Draut, A.E.; Buscombe, D.

2009-01-01

A new application of the autocorrelation grain size analysis technique for mixed to coarse sediment settings has been investigated. Photographs of sand- to boulder-sized sediment along the Elwha River delta beach were taken from approximately 1??2 m above the ground surface, and detailed grain size measurements were made from 32 of these sites for calibration and validation. Digital photographs were found to provide accurate estimates of the long and intermediate axes of the surface sediment (r2 > 0??98), but poor estimates of the short axes (r2 = 0??68), suggesting that these short axes were naturally oriented in the vertical dimension. The autocorrelation method was successfully applied resulting in total irreducible error of 14% over a range of mean grain sizes of 1 to 200 mm. Compared with reported edge and object-detection results, it is noted that the autocorrelation method presented here has lower error and can be applied to a much broader range of mean grain sizes without altering the physical set-up of the camera (~200-fold versus ~6-fold). The approach is considerably less sensitive to lighting conditions than object-detection methods, although autocorrelation estimates do improve when measures are taken to shade sediments from direct sunlight. The effects of wet and dry conditions are also evaluated and discussed. The technique provides an estimate of grain size sorting from the easily calculated autocorrelation standard error, which is correlated with the graphical standard deviation at an r2 of 0??69. The technique is transferable to other sites when calibrated with linear corrections based on photo-based measurements, as shown by excellent grain-size analysis results (r2 = 0??97, irreducible error = 16%) from samples from the mixed grain size beaches of Kachemak Bay, Alaska. Thus, a method has been developed to measure mean grain size and sorting properties of coarse sediments. ?? 2009 John Wiley & Sons, Ltd.

Estimation of neural energy in microelectrode signals

NASA Astrophysics Data System (ADS)

Gaumond, R. P.; Clement, R.; Silva, R.; Sander, D.

2004-09-01

We considered the problem of determining the neural contribution to the signal recorded by an intracortical electrode. We developed a linear least-squares approach to determine the energy fraction of a signal attributable to an arbitrary number of autocorrelation-defined signals buried in noise. Application of the method requires estimation of autocorrelation functions Rap(tgr) characterizing the action potential (AP) waveforms and Rn(tgr) characterizing background noise. This method was applied to the analysis of chronically implanted microelectrode signals from motor cortex of rat. We found that neural (AP) energy consisted of a large-signal component which grows linearly with the number of threshold-detected neural events and a small-signal component unrelated to the count of threshold-detected AP signals. The addition of pseudorandom noise to electrode signals demonstrated the algorithm's effectiveness for a wide range of noise-to-signal energy ratios (0.08 to 39). We suggest, therefore, that the method could be of use in providing a measure of neural response in situations where clearly identified spike waveforms cannot be isolated, or in providing an additional 'background' measure of microelectrode neural activity to supplement the traditional AP spike count.

Preliminary evidence for the influence of physiography and scale upon the autocorrelation function of remotely sensed data

NASA Technical Reports Server (NTRS)

Labovitz, M. L.; Toll, D. L.; Kennard, R. E.

1980-01-01

Previously established results demonstrate that LANDSAT data are autocorrelated and can be described by a univariate linear stochastic process known as auto-regressive-integrated-moving-average model of degree 1, 0, 1 or ARIMA (1, 0, 1). This model has two coefficients of interest for interpretation phi(1) and theta(1). In a comparison of LANDSAT thematic mapper simulator (TMS) data and LANDSAT MSS data several results were established: (1) The form of the relatedness as described by this model is not dependent upon system look angle or pixel size. (2) The phi(1) coefficient increases with decreasing pixel size and increasing topographic complexity. (3) Changes in topography have a greater influence upon phi(1) than changes in land cover class. (4) The theta(1) seems to vary with the amount of atmospheric haze. These patterns of variation in phi(1) and theta(1) are potentially exploitable by the remote sensing community to yield stochastically independent sets of observations, characterize topography, and reduce the number of bytes needed to store remotely sensed data.

An evaluation of random analysis methods for the determination of panel damping

NASA Technical Reports Server (NTRS)

Bhat, W. V.; Wilby, J. F.

1972-01-01

An analysis is made of steady-state and non-steady-state methods for the measurement of panel damping. Particular emphasis is placed on the use of random process techniques in conjunction with digital data reduction methods. The steady-state methods considered use the response power spectral density, response autocorrelation, excitation-response crosspower spectral density, or single-sided Fourier transform (SSFT) of the response autocorrelation function. Non-steady-state methods are associated mainly with the use of rapid frequency sweep excitation. Problems associated with the practical application of each method are evaluated with specific reference to the case of a panel exposed to a turbulent airflow, and two methods, the power spectral density and the single-sided Fourier transform methods, are selected as being the most suitable. These two methods are demonstrated experimentally, and it is shown that the power spectral density method is satisfactory under most conditions, provided that appropriate corrections are applied to account for filter bandwidth and background noise errors. Thus, the response power spectral density method is recommended for the measurement of the damping of panels exposed to a moving airflow.

An alternative respiratory sounds classification system utilizing artificial neural networks.

PubMed

Oweis, Rami J; Abdulhay, Enas W; Khayal, Amer; Awad, Areen

2015-01-01

Computerized lung sound analysis involves recording lung sound via an electronic device, followed by computer analysis and classification based on specific signal characteristics as non-linearity and nonstationarity caused by air turbulence. An automatic analysis is necessary to avoid dependence on expert skills. This work revolves around exploiting autocorrelation in the feature extraction stage. All process stages were implemented in MATLAB. The classification process was performed comparatively using both artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFIS) toolboxes. The methods have been applied to 10 different respiratory sounds for classification. The ANN was superior to the ANFIS system and returned superior performance parameters. Its accuracy, specificity, and sensitivity were 98.6%, 100%, and 97.8%, respectively. The obtained parameters showed superiority to many recent approaches. The promising proposed method is an efficient fast tool for the intended purpose as manifested in the performance parameters, specifically, accuracy, specificity, and sensitivity. Furthermore, it may be added that utilizing the autocorrelation function in the feature extraction in such applications results in enhanced performance and avoids undesired computation complexities compared to other techniques.

High-Responsivity Graphene–Boron Nitride Photodetector and Autocorrelator in a Silicon Photonic Integrated Circuit

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

Shiue, Ren-Jye; Gao, Yuanda; Wang, Yifei

2015-11-11

Graphene and other two-dimensional (2D) materials have emerged as promising materials for broadband and ultrafast photodetection and optical modulation. These optoelectronic capabilities can augment complementary metal–oxide–semiconductor (CMOS) devices for high-speed and low-power optical interconnects. Here, we demonstrate an on-chip ultrafast photodetector based on a two-dimensional heterostructure consisting of high-quality graphene encapsulated in hexagonal boron nitride. Coupled to the optical mode of a silicon waveguide, this 2D heterostructure-based photodetector exhibits a maximum responsivity of 0.36 A/W and high-speed operation with a 3 dB cutoff at 42 GHz. From photocurrent measurements as a function of the top-gate and source-drain voltages, we concludemore » that the photoresponse is consistent with hot electron mediated effects. At moderate peak powers above 50 mW, we observe a saturating photocurrent consistent with the mechanisms of electron–phonon supercollision cooling. This nonlinear photoresponse enables optical on-chip autocorrelation measurements with picosecond-scale timing resolution and exceptionally low peak powers.« less

Prediction of hourly PM2.5 using a space-time support vector regression model

NASA Astrophysics Data System (ADS)

Yang, Wentao; Deng, Min; Xu, Feng; Wang, Hang

2018-05-01

Real-time air quality prediction has been an active field of research in atmospheric environmental science. The existing methods of machine learning are widely used to predict pollutant concentrations because of their enhanced ability to handle complex non-linear relationships. However, because pollutant concentration data, as typical geospatial data, also exhibit spatial heterogeneity and spatial dependence, they may violate the assumptions of independent and identically distributed random variables in most of the machine learning methods. As a result, a space-time support vector regression model is proposed to predict hourly PM2.5 concentrations. First, to address spatial heterogeneity, spatial clustering is executed to divide the study area into several homogeneous or quasi-homogeneous subareas. To handle spatial dependence, a Gauss vector weight function is then developed to determine spatial autocorrelation variables as part of the input features. Finally, a local support vector regression model with spatial autocorrelation variables is established for each subarea. Experimental data on PM2.5 concentrations in Beijing are used to verify whether the results of the proposed model are superior to those of other methods.

A DS-UWB Cognitive Radio System Based on Bridge Function Smart Codes

NASA Astrophysics Data System (ADS)

Xu, Yafei; Hong, Sheng; Zhao, Guodong; Zhang, Fengyuan; di, Jinshan; Zhang, Qishan

This paper proposes a direct-sequence UWB Gaussian pulse of cognitive radio systems based on bridge function smart sequence matrix and the Gaussian pulse. As the system uses the spreading sequence code, that is the bridge function smart code sequence, the zero correlation zones (ZCZs) which the bridge function sequences' auto-correlation functions had, could reduce multipath fading of the pulse interference. The Modulated channel signal was sent into the IEEE 802.15.3a UWB channel. We analysis the ZCZs's inhibition to the interference multipath interference (MPI), as one of the main system sources interferences. The simulation in SIMULINK/MATLAB is described in detail. The result shows the system has better performance by comparison with that employing Walsh sequence square matrix, and it was verified by the formula in principle.

The Clustering of High-redshift (2.9 ≤ z ≤ 5.1) Quasars in SDSS Stripe 82

NASA Astrophysics Data System (ADS)

Timlin, John D.; Ross, Nicholas P.; Richards, Gordon T.; Myers, Adam D.; Pellegrino, Andrew; Bauer, Franz E.; Lacy, Mark; Schneider, Donald P.; Wollack, Edward J.; Zakamska, Nadia L.

2018-05-01

We present a measurement of the two-point autocorrelation function of photometrically selected high-z quasars over ∼100 deg2 on the Sloan Digital Sky Survey Stripe 82 field. Selection is performed using three machine-learning algorithms in a six-dimensional optical/mid-infrared color space. Optical data from the Sloan Digital Sky Survey are combined with overlapping deep mid-infrared data from the Spitzer IRAC Equatorial Survey and the Spitzer-HETDEX Exploratory Large-Area survey. Our selection algorithms are trained on the colors of known high-z quasars. The selected quasar sample consists of 1378 objects and contains both spectroscopically confirmed quasars and photometrically selected quasar candidates. These objects span a redshift range of 2.9 ≤ z ≤ 5.1 and are generally fainter than i = 20.2, a regime that has lacked sufficient number density to perform autocorrelation function measurements of photometrically classified quasars. We compute the angular correlation function of these data, marginally detecting quasar clustering. We fit a single power law with an index of δ = 1.39 ± 0.618 and amplitude of θ 0 = 0.‧71 ± 0.‧546 . A dark matter model is fit to the angular correlation function to estimate the linear bias. At the average redshift of our survey (< z> =3.38), the bias is b = 6.78 ± 1.79. Using this bias, we calculate a characteristic dark matter halo mass of 1.70–9.83× {10}12{h}-1 {M}ȯ . Our bias estimate suggests that quasar feedback intermittently shuts down the accretion of gas onto the central supermassive black hole at early times. If confirmed, these results hint at a level of luminosity dependence in the clustering of quasars at high-z.

Rheological Predictions of Network Systems Swollen with Entangled Solvent

DTIC Science & Technology

2014-04-01

represent binary entanglements and the crosses represent cross-links. Both of which are fixed in space for Green– Kubo calculations or moved affinely for...Two types of calculations can be performed, equilibrium (or Green– Kubo ) calculations in which the rate of deformation tensor21,22 is set to zero and the...autocorrelation function of stress at equilibrium is followed; or flow calculations in which a specific flow field is applied and the stress as a

Analysis of EEG activity during sleep - brain hemisphere symmetry of two classes of sleep spindles

NASA Astrophysics Data System (ADS)

Smolen, Magdalena M.

2009-01-01

This paper presents automatic analysis of some selected human electroencephalographic patterns during deep sleep using the Matching Pursuit (MP) algorithm. The periodicity of deep sleep EEG patterns was observed by calculating autocorrelation functions of their percentage contributions. The study confirmed the increasing trend of amplitude-weighted average frequency of sleep spindles from frontal to posterior derivations. The dominant frequencies from the left and the right brain hemisphere were strongly correlated.

Radial dependence of self-organized criticality behavior in TCABR tokamak

NASA Astrophysics Data System (ADS)

dos Santos Lima, G. Z.; Iarosz, K. C.; Batista, A. M.; Guimarães-Filho, Z. O.; Caldas, I. L.; Kuznetsov, Y. K.; Nascimento, I. C.; Viana, R. L.; Lopes, S. R.

2011-03-01

In this work we present evidence of the self-organized criticality behavior of the plasma edge electrostatic turbulence in the tokamak TCABR. Analyzing fluctuation data measured by Langmuir probes, we verify the radial dependence of self-organized criticality behavior at the plasma edge and scrape-off layer. We identify evidence of this radial criticality in statistical properties of the laminar period distribution function, power spectral density, autocorrelation, and Hurst parameter for the analyzed fluctuations.

A rotation-translation invariant molecular descriptor of partial charges and its use in ligand-based virtual screening

PubMed Central

2014-01-01

Background Measures of similarity for chemical molecules have been developed since the dawn of chemoinformatics. Molecular similarity has been measured by a variety of methods including molecular descriptor based similarity, common molecular fragments, graph matching and 3D methods such as shape matching. Similarity measures are widespread in practice and have proven to be useful in drug discovery. Because of our interest in electrostatics and high throughput ligand-based virtual screening, we sought to exploit the information contained in atomic coordinates and partial charges of a molecule. Results A new molecular descriptor based on partial charges is proposed. It uses the autocorrelation function and linear binning to encode all atoms of a molecule into two rotation-translation invariant vectors. Combined with a scoring function, the descriptor allows to rank-order a database of compounds versus a query molecule. The proposed implementation is called ACPC (AutoCorrelation of Partial Charges) and released in open source. Extensive retrospective ligand-based virtual screening experiments were performed and other methods were compared with in order to validate the method and associated protocol. Conclusions While it is a simple method, it performed remarkably well in experiments. At an average speed of 1649 molecules per second, it reached an average median area under the curve of 0.81 on 40 different targets; hence validating the proposed protocol and implementation. PMID:24887178

Measurement of Regional Environmental Noise by Use of a Pc-Based System. A Application to the Noise Near Airport ``G. Marconi'' in Bologna

NASA Astrophysics Data System (ADS)

Sakai, H.; Sato, S.; Prodi, N.; Pompoli, R.

2001-03-01

Measurements of aircraft noise were made at the airport "G. Marconi" in Bologna by using a measurement system for regional environmental noise. The system is based on the model of the human auditory-brain system, which is based on the interplay of autocorrelators and an interaural cross-correlator acting on the pressure signals arriving at the ear entrances, and takes into account the specialization of left and right human cerebral hemispheres (see reference [8]). Measurements were taken through dual microphones at ear entrances of a dummy head. The aircraft noise was characterized with the following physical factors calculated from the autocorrelation function (ACF) and interaural cross-correlation function (IACF) for binaural signals. From the ACF analysis, (1) energy represented at the origin of delay,Φ (0), (2) effective duration of the envelope of the normalized ACF, τe, (3) the delay time of the first peak, τ1, and (4) its amplitude, φ1were extracted. From the IACF analysis, (5) IACC, (6) interaural delay time at which the IACC is defined, τIACC, and (7) width of the IACF at the τIACC, WIACCwere extracted. The factorΦ (0) can be represented as the geometrical mean of the energies at both ears. A noise source may be identified by these factors as timbre.

Measuring the Autocorrelation Function of Nanoscale Three-Dimensional Density Distribution in Individual Cells Using Scanning Transmission Electron Microscopy, Atomic Force Microscopy, and a New Deconvolution Algorithm.

PubMed

Li, Yue; Zhang, Di; Capoglu, Ilker; Hujsak, Karl A; Damania, Dhwanil; Cherkezyan, Lusik; Roth, Eric; Bleher, Reiner; Wu, Jinsong S; Subramanian, Hariharan; Dravid, Vinayak P; Backman, Vadim

2017-06-01

Essentially all biological processes are highly dependent on the nanoscale architecture of the cellular components where these processes take place. Statistical measures, such as the autocorrelation function (ACF) of the three-dimensional (3D) mass-density distribution, are widely used to characterize cellular nanostructure. However, conventional methods of reconstruction of the deterministic 3D mass-density distribution, from which these statistical measures can be calculated, have been inadequate for thick biological structures, such as whole cells, due to the conflict between the need for nanoscale resolution and its inverse relationship with thickness after conventional tomographic reconstruction. To tackle the problem, we have developed a robust method to calculate the ACF of the 3D mass-density distribution without tomography. Assuming the biological mass distribution is isotropic, our method allows for accurate statistical characterization of the 3D mass-density distribution by ACF with two data sets: a single projection image by scanning transmission electron microscopy and a thickness map by atomic force microscopy. Here we present validation of the ACF reconstruction algorithm, as well as its application to calculate the statistics of the 3D distribution of mass-density in a region containing the nucleus of an entire mammalian cell. This method may provide important insights into architectural changes that accompany cellular processes.

Auto-correlation in the motor/imaginary human EEG signals: A vision about the FDFA fluctuations.

PubMed

Zebende, Gilney Figueira; Oliveira Filho, Florêncio Mendes; Leyva Cruz, Juan Alberto

2017-01-01

In this paper we analyzed, by the FDFA root mean square fluctuation (rms) function, the motor/imaginary human activity produced by a 64-channel electroencephalography (EEG). We utilized the Physionet on-line databank, a publicly available database of human EEG signals, as a standardized reference database for this study. Herein, we report the use of detrended fluctuation analysis (DFA) method for EEG analysis. We show that the complex time series of the EEG exhibits characteristic fluctuations depending on the analyzed channel in the scalp-recorded EEG. In order to demonstrate the effectiveness of the proposed technique, we analyzed four distinct channels represented here by F332, F637 (frontal region of the head) and P349, P654 (parietal region of the head). We verified that the amplitude of the FDFA rms function is greater for the frontal channels than for the parietal. To tabulate this information in a better way, we define and calculate the difference between FDFA (in log scale) for the channels, thus defining a new path for analysis of EEG signals. Finally, related to the studied EEG signals, we obtain the auto-correlation exponent, αDFA by DFA method, that reveals self-affinity at specific time scale. Our results shows that this strategy can be applied to study the human brain activity in EEG processing.

Dynamical properties of a tumor growth system in the presence of immunization and colored cross-correlated noises

NASA Astrophysics Data System (ADS)

Jia, Zheng-Lin; Mei, Dong-Cheng

2010-05-01

We investigate the effects of the noise parameters and immunization strength β on the dynamical properties of a tumor growth system with both immunization and colored cross-correlated noises. The analytical expressions for the associated relaxation time TC and the normalized correlation function C(s) are derived by means of the projection operator method. The results indicate that: (i) TC as a function of the multiplicative noise intensity α shows resonance-like behavior, i.e. the curves of TC versus α exhibit a single-peak structure and its peak position changes with increasing correlation strength between noises λ, the autocorrelation time of multiplicative noise τ1, the autocorrelation time of additive noise τ2 and the cross-correlation time τ3. This behavior can be understood in terms of the noise-enhanced stability effect and the influence of the memory effects on it. (ii) The increasing λ, τ1, τ2 and the additive noise intensity D slow down the fluctuation decay of the tumor population, whereas the increasing τ3 and β speed it up. (iii) C(s) increases as λ, τ1, τ2 and β increase, while it decreases with τ3 increasing. Our study shows that the effects of some noise parameters on tumor growth can be modified due to the presence of the immunization effect.

Measuring the Autocorrelation Function of Nanoscale Three-Dimensional Density Distribution in Individual Cells Using Scanning Transmission Electron Microscopy, Atomic Force Microscopy, and a New Deconvolution Algorithm

PubMed Central

Li, Yue; Zhang, Di; Capoglu, Ilker; Hujsak, Karl A.; Damania, Dhwanil; Cherkezyan, Lusik; Roth, Eric; Bleher, Reiner; Wu, Jinsong S.; Subramanian, Hariharan; Dravid, Vinayak P.; Backman, Vadim

2018-01-01

Essentially all biological processes are highly dependent on the nanoscale architecture of the cellular components where these processes take place. Statistical measures, such as the autocorrelation function (ACF) of the three-dimensional (3D) mass–density distribution, are widely used to characterize cellular nanostructure. However, conventional methods of reconstruction of the deterministic 3D mass–density distribution, from which these statistical measures can be calculated, have been inadequate for thick biological structures, such as whole cells, due to the conflict between the need for nanoscale resolution and its inverse relationship with thickness after conventional tomographic reconstruction. To tackle the problem, we have developed a robust method to calculate the ACF of the 3D mass–density distribution without tomography. Assuming the biological mass distribution is isotropic, our method allows for accurate statistical characterization of the 3D mass–density distribution by ACF with two data sets: a single projection image by scanning transmission electron microscopy and a thickness map by atomic force microscopy. Here we present validation of the ACF reconstruction algorithm, as well as its application to calculate the statistics of the 3D distribution of mass–density in a region containing the nucleus of an entire mammalian cell. This method may provide important insights into architectural changes that accompany cellular processes. PMID:28416035

On the non-stationary generalized Langevin equation

NASA Astrophysics Data System (ADS)

Meyer, Hugues; Voigtmann, Thomas; Schilling, Tanja

2017-12-01

In molecular dynamics simulations and single molecule experiments, observables are usually measured along dynamic trajectories and then averaged over an ensemble ("bundle") of trajectories. Under stationary conditions, the time-evolution of such averages is described by the generalized Langevin equation. By contrast, if the dynamics is not stationary, it is not a priori clear which form the equation of motion for an averaged observable has. We employ the formalism of time-dependent projection operator techniques to derive the equation of motion for a non-equilibrium trajectory-averaged observable as well as for its non-stationary auto-correlation function. The equation is similar in structure to the generalized Langevin equation but exhibits a time-dependent memory kernel as well as a fluctuating force that implicitly depends on the initial conditions of the process. We also derive a relation between this memory kernel and the autocorrelation function of the fluctuating force that has a structure similar to a fluctuation-dissipation relation. In addition, we show how the choice of the projection operator allows us to relate the Taylor expansion of the memory kernel to data that are accessible in MD simulations and experiments, thus allowing us to construct the equation of motion. As a numerical example, the procedure is applied to Brownian motion initialized in non-equilibrium conditions and is shown to be consistent with direct measurements from simulations.

Frequency-feature based antistrong-disturbance signal processing method and system for vortex flowmeter with single sensor

NASA Astrophysics Data System (ADS)

Xu, Ke-Jun; Luo, Qing-Lin; Wang, Gang; Liu, San-Shan; Kang, Yi-Bo

2010-07-01

Digital signal processing methods have been applied to vortex flowmeter for extracting the useful information from noisy output of the vortex flow sensor. But these approaches are unavailable when the power of the mechanical vibration noise is larger than that of the vortex flow signal. In order to solve this problem, an antistrong-disturbance signal processing method is proposed based on frequency features of the vortex flow signal and mechanical vibration noise for the vortex flowmeter with single sensor. The frequency bandwidth of the vortex flow signal is different from that of the mechanical vibration noise. The autocorrelation function can represent bandwidth features of the signal and noise. The output of the vortex flow sensor is processed by the spectrum analysis, filtered by bandpass filters, and calculated by autocorrelation function at the fixed delaying time and at τ =0 to obtain ratios. The frequency corresponding to the minimal ratio is regarded as the vortex flow frequency. With an ultralow-power microcontroller, a digital signal processing system is developed to implement the antistrong-disturbance algorithm, and at the same time to ensure low-power and two-wire mode for meeting the requirement of process instrumentation. The water flow-rate calibration and vibration test experiments are conducted, and the experimental results show that both the algorithm and system are effective.

Frequency-feature based antistrong-disturbance signal processing method and system for vortex flowmeter with single sensor.

PubMed

Xu, Ke-Jun; Luo, Qing-Lin; Wang, Gang; Liu, San-Shan; Kang, Yi-Bo

2010-07-01

Digital signal processing methods have been applied to vortex flowmeter for extracting the useful information from noisy output of the vortex flow sensor. But these approaches are unavailable when the power of the mechanical vibration noise is larger than that of the vortex flow signal. In order to solve this problem, an antistrong-disturbance signal processing method is proposed based on frequency features of the vortex flow signal and mechanical vibration noise for the vortex flowmeter with single sensor. The frequency bandwidth of the vortex flow signal is different from that of the mechanical vibration noise. The autocorrelation function can represent bandwidth features of the signal and noise. The output of the vortex flow sensor is processed by the spectrum analysis, filtered by bandpass filters, and calculated by autocorrelation function at the fixed delaying time and at tau=0 to obtain ratios. The frequency corresponding to the minimal ratio is regarded as the vortex flow frequency. With an ultralow-power microcontroller, a digital signal processing system is developed to implement the antistrong-disturbance algorithm, and at the same time to ensure low-power and two-wire mode for meeting the requirement of process instrumentation. The water flow-rate calibration and vibration test experiments are conducted, and the experimental results show that both the algorithm and system are effective.

The Latent Curve ARMA (P, Q) Panel Model: Longitudinal Data Analysis in Educational Research and Evaluation

ERIC Educational Resources Information Center

Sivo, Stephen; Fan, Xitao

2008-01-01

Autocorrelated residuals in longitudinal data are widely reported as common to longitudinal data. Yet few, if any, researchers modeling growth processes evaluate a priori whether their data have this feature. Sivo, Fan, and Witta (2005) found that not modeling autocorrelated residuals present in longitudinal data severely biases latent curve…

The Use of Time Series Analysis and t Tests with Serially Correlated Data Tests.

ERIC Educational Resources Information Center

Nicolich, Mark J.; Weinstein, Carol S.

1981-01-01

Results of three methods of analysis applied to simulated autocorrelated data sets with an intervention point (varying in autocorrelation degree, variance of error term, and magnitude of intervention effect) are compared and presented. The three methods are: t tests; maximum likelihood Box-Jenkins (ARIMA); and Bayesian Box Jenkins. (Author/AEF)

Lag-One Autocorrelation in Short Series: Estimation and Hypotheses Testing

ERIC Educational Resources Information Center

Solanas, Antonio; Manolov, Rumen; Sierra, Vicenta

2010-01-01

In the first part of the study, nine estimators of the first-order autoregressive parameter are reviewed and a new estimator is proposed. The relationships and discrepancies between the estimators are discussed in order to achieve a clear differentiation. In the second part of the study, the precision in the estimation of autocorrelation is…

Autocorrelation as a source of truncated Lévy flights in foreign exchange rates

NASA Astrophysics Data System (ADS)

Figueiredo, Annibal; Gleria, Iram; Matsushita, Raul; Da Silva, Sergio

2003-05-01

We suggest that the ultraslow speed of convergence associated with truncated Lévy flights (Phys. Rev. Lett. 73 (1994) 2946) may well be explained by autocorrelations in data. We show how a particular type of autocorrelation generates power laws consistent with a truncated Lévy flight. Stock exchanges have been suggested to be modeled by a truncated Lévy flight (Nature 376 (1995) 46; Physica A 297 (2001) 509; Econom. Bull. 7 (2002) 1). Here foreign exchange rate data are taken instead. Scaling power laws in the “probability of return to the origin” are shown to emerge for most currencies. A novel approach to measure how distant a process is from a Gaussian regime is presented.

Why GPS makes distances bigger than they are

PubMed Central

Ranacher, Peter; Brunauer, Richard; Trutschnig, Wolfgang; Van der Spek, Stefan; Reich, Siegfried

2016-01-01

ABSTRACT Global navigation satellite systems such as the Global Positioning System (GPS) is one of the most important sensors for movement analysis. GPS is widely used to record the trajectories of vehicles, animals and human beings. However, all GPS movement data are affected by both measurement and interpolation errors. In this article we show that measurement error causes a systematic bias in distances recorded with a GPS; the distance between two points recorded with a GPS is – on average – bigger than the true distance between these points. This systematic ‘overestimation of distance’ becomes relevant if the influence of interpolation error can be neglected, which in practice is the case for movement sampled at high frequencies. We provide a mathematical explanation of this phenomenon and illustrate that it functionally depends on the autocorrelation of GPS measurement error (C). We argue that C can be interpreted as a quality measure for movement data recorded with a GPS. If there is a strong autocorrelation between any two consecutive position estimates, they have very similar error. This error cancels out when average speed, distance or direction is calculated along the trajectory. Based on our theoretical findings we introduce a novel approach to determine C in real-world GPS movement data sampled at high frequencies. We apply our approach to pedestrian trajectories and car trajectories. We found that the measurement error in the data was strongly spatially and temporally autocorrelated and give a quality estimate of the data. Most importantly, our findings are not limited to GPS alone. The systematic bias and its implications are bound to occur in any movement data collected with absolute positioning if interpolation error can be neglected. PMID:27019610

Decay of the supersonic turbulent wakes from micro-ramps

NASA Astrophysics Data System (ADS)

Sun, Z.; Schrijer, F. F. J.; Scarano, F.; van Oudheusden, B. W.

2014-02-01

The wakes resulting from micro-ramps immersed in a supersonic turbulent boundary layer at Ma = 2.0 are investigated by means of particle image velocimetry. Two micro-ramps are investigated with height of 60% and 80% of the undisturbed boundary layer, respectively. The measurement domain is placed at the symmetry plane of the ramp and encompasses the range from 10 to 32 ramp heights downstream of the ramp. The decay of the flow field properties is evaluated in terms of time-averaged and root-mean-square (RMS) statistics. In the time-averaged flow field, the recovery from the imparted momentum deficit and the decay of upwash motion are analyzed. The RMS fluctuations of the velocity components exhibit strong anisotropy at the most upstream location and develop into a more isotropic regime downstream. The self-similarity properties of velocity components and fluctuation components along wall-normal direction are followed. The investigation of the unsteady large scale motion is carried out by means of snapshot analysis and by a statistical approach based on the spatial auto-correlation function. The Kelvin-Helmholtz (K-H) instability at the upper shear layer is observed to develop further with the onset of vortex pairing. The average distance between vortices is statistically estimated using the spatial auto-correlation. A marked transition with the wavelength increase is observed across the pairing regime. The K-H instability, initially observed only at the upper shear layer also begins to appear in the lower shear layer as soon as the wake is elevated sufficiently off the wall. The auto-correlation statistics confirm the coherence of counter-rotating vortices from the upper and lower sides, indicating the formation of vortex rings downstream of the pairing region.

Extension of the spatial autocorrelation (SPAC) method to mixed-component correlations of surface waves

USGS Publications Warehouse

Haney, Matthew M.; Mikesell, T. Dylan; van Wijk, Kasper; Nakahara, Hisashi

2012-01-01

Using ambient seismic noise for imaging subsurface structure dates back to the development of the spatial autocorrelation (SPAC) method in the 1950s. We present a theoretical analysis of the SPAC method for multicomponent recordings of surface waves to determine the complete 3 × 3 matrix of correlations between all pairs of three-component motions, called the correlation matrix. In the case of isotropic incidence, when either Rayleigh or Love waves arrive from all directions with equal power, the only non-zero off-diagonal terms in the matrix are the vertical–radial (ZR) and radial–vertical (RZ) correlations in the presence of Rayleigh waves. Such combinations were not considered in the development of the SPAC method. The method originally addressed the vertical–vertical (ZZ), RR and TT correlations, hence the name spatial autocorrelation. The theoretical expressions we derive for the ZR and RZ correlations offer additional ways to measure Rayleigh wave dispersion within the SPAC framework. Expanding on the results for isotropic incidence, we derive the complete correlation matrix in the case of generally anisotropic incidence. We show that the ZR and RZ correlations have advantageous properties in the presence of an out-of-plane directional wavefield compared to ZZ and RR correlations. We apply the results for mixed-component correlations to a data set from Akutan Volcano, Alaska and find consistent estimates of Rayleigh wave phase velocity from ZR compared to ZZ correlations. This work together with the recently discovered connections between the SPAC method and time-domain correlations of ambient noise provide further insights into the retrieval of surface wave Green’s functions from seismic noise.

Spectral density mapping at multiple magnetic fields suitable for 13C NMR relaxation studies

NASA Astrophysics Data System (ADS)

Kadeřávek, Pavel; Zapletal, Vojtěch; Fiala, Radovan; Srb, Pavel; Padrta, Petr; Přecechtělová, Jana Pavlíková; Šoltésová, Mária; Kowalewski, Jozef; Widmalm, Göran; Chmelík, Josef; Sklenář, Vladimír; Žídek, Lukáš

2016-05-01

Standard spectral density mapping protocols, well suited for the analysis of 15N relaxation rates, introduce significant systematic errors when applied to 13C relaxation data, especially if the dynamics is dominated by motions with short correlation times (small molecules, dynamic residues of macromolecules). A possibility to improve the accuracy by employing cross-correlated relaxation rates and on measurements taken at several magnetic fields has been examined. A suite of protocols for analyzing such data has been developed and their performance tested. Applicability of the proposed protocols is documented in two case studies, spectral density mapping of a uniformly labeled RNA hairpin and of a selectively labeled disaccharide exhibiting highly anisotropic tumbling. Combination of auto- and cross-correlated relaxation data acquired at three magnetic fields was applied in the former case in order to separate effects of fast motions and conformational or chemical exchange. An approach using auto-correlated relaxation rates acquired at five magnetic fields, applicable to anisotropically moving molecules, was used in the latter case. The results were compared with a more advanced analysis of data obtained by interpolation of auto-correlated relaxation rates measured at seven magnetic fields, and with the spectral density mapping of cross-correlated relaxation rates. The results showed that sufficiently accurate values of auto- and cross-correlated spectral density functions at zero and 13C frequencies can be obtained from data acquired at three magnetic fields for uniformly 13C -labeled molecules with a moderate anisotropy of the rotational diffusion tensor. Analysis of auto-correlated relaxation rates at five magnetic fields represents an alternative for molecules undergoing highly anisotropic motions.

Switchgrass and Miscanthus Biomass and Theoretical Ethanol Production from Reclaimed Mine Lands in West Virginia

NASA Astrophysics Data System (ADS)

Scagline, Steffany M.

Near infrared stimulation or Low Level Laser Therapy (LLLT) is an innovative technique shown to effect the microvasculature hemodynamics. The aim of this study is to use Diffused Correlation Spectroscopy (DCS) to evaluate the physiological effects of LLLT on blood perfusion. This study is divided into two parts: the fist part is the development of DCS system and the second part is investigating the effects of LLLT on biological tissue. DCS is an emerging non-invasive technique to probe deep tissue hemodynamics. DCS uses time-averaged intensity autocorrelation function for the fluctuations caused due to the moving scatterers (RBCs) in biological tissue. We present a software based autocorrelator system to complete the acquisition and processing parts. We conducted validation studies on an intralipid phantom and human forearm. Both the studies proved smooth decay curves which help in getting a better curve fitting and as a result more accurate blood flow index (BFI). We show that the software based autocorrelation system can be an alternative to the conventional hardware based correlators in DCS systems with benefits such as flexibility in raw photon count data processing and low cost. The objective of the second part of this study is evaluating how a single session of LLLT alters the hemodynamics in the microvasculature. We performed an experiment where the subjects forearm was stimulated with LLLT and the corresponding changes were recorded using DCS system. The results obtained shows significant hemodynamic changes in response to LLLT with a 95%confidence interval. The results in this study indicate that LLLT could lead to the development of non-invasive technique to help in rehabilitation and performance-enhancing of healthy humans.

Statistical procedures for evaluating daily and monthly hydrologic model predictions

USGS Publications Warehouse

Coffey, M.E.; Workman, S.R.; Taraba, J.L.; Fogle, A.W.

2004-01-01

The overall study objective was to evaluate the applicability of different qualitative and quantitative methods for comparing daily and monthly SWAT computer model hydrologic streamflow predictions to observed data, and to recommend statistical methods for use in future model evaluations. Statistical methods were tested using daily streamflows and monthly equivalent runoff depths. The statistical techniques included linear regression, Nash-Sutcliffe efficiency, nonparametric tests, t-test, objective functions, autocorrelation, and cross-correlation. None of the methods specifically applied to the non-normal distribution and dependence between data points for the daily predicted and observed data. Of the tested methods, median objective functions, sign test, autocorrelation, and cross-correlation were most applicable for the daily data. The robust coefficient of determination (CD*) and robust modeling efficiency (EF*) objective functions were the preferred methods for daily model results due to the ease of comparing these values with a fixed ideal reference value of one. Predicted and observed monthly totals were more normally distributed, and there was less dependence between individual monthly totals than was observed for the corresponding predicted and observed daily values. More statistical methods were available for comparing SWAT model-predicted and observed monthly totals. The 1995 monthly SWAT model predictions and observed data had a regression Rr2 of 0.70, a Nash-Sutcliffe efficiency of 0.41, and the t-test failed to reject the equal data means hypothesis. The Nash-Sutcliffe coefficient and the R r2 coefficient were the preferred methods for monthly results due to the ability to compare these coefficients to a set ideal value of one.

A method to identify differential expression profiles of time-course gene data with Fourier transformation

PubMed Central

2013-01-01

Background Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis. Results This work aims to identify genes that show different gene expression profiles across time. We propose a statistical procedure to discover gene groups with similar profiles using a nonparametric representation that accounts for the autocorrelation in the data. In particular, we first represent each profile in terms of a Fourier basis, and then we screen out genes that are not differentially expressed based on the Fourier coefficients. Finally, we cluster the remaining gene profiles using a model-based approach in the Fourier domain. We evaluate the screening results in terms of sensitivity, specificity, FDR and FNR, compare with the Gaussian process regression screening in a simulation study and illustrate the results by application to yeast cell-cycle microarray expression data with alpha-factor synchronization. The key elements of the proposed methodology: (i) representation of gene profiles in the Fourier domain; (ii) automatic screening of genes based on the Fourier coefficients and taking into account autocorrelation in the data, while controlling the false discovery rate (FDR); (iii) model-based clustering of the remaining gene profiles. Conclusions Using this method, we identified a set of cell-cycle-regulated time-course yeast genes. The proposed method is general and can be potentially used to identify genes which have the same patterns or biological processes, and help facing the present and forthcoming challenges of data analysis in functional genomics. PMID:24134721

Linking landscape characteristics to local grizzly bear abundance using multiple detection methods in a hierarchical model

USGS Publications Warehouse

Graves, T.A.; Kendall, Katherine C.; Royle, J. Andrew; Stetz, J.B.; Macleod, A.C.

2011-01-01

Few studies link habitat to grizzly bear Ursus arctos abundance and these have not accounted for the variation in detection or spatial autocorrelation. We collected and genotyped bear hair in and around Glacier National Park in northwestern Montana during the summer of 2000. We developed a hierarchical Markov chain Monte Carlo model that extends the existing occupancy and count models by accounting for (1) spatially explicit variables that we hypothesized might influence abundance; (2) separate sub-models of detection probability for two distinct sampling methods (hair traps and rub trees) targeting different segments of the population; (3) covariates to explain variation in each sub-model of detection; (4) a conditional autoregressive term to account for spatial autocorrelation; (5) weights to identify most important variables. Road density and per cent mesic habitat best explained variation in female grizzly bear abundance; spatial autocorrelation was not supported. More female bears were predicted in places with lower road density and with more mesic habitat. Detection rates of females increased with rub tree sampling effort. Road density best explained variation in male grizzly bear abundance and spatial autocorrelation was supported. More male bears were predicted in areas of low road density. Detection rates of males increased with rub tree and hair trap sampling effort and decreased over the sampling period. We provide a new method to (1) incorporate multiple detection methods into hierarchical models of abundance; (2) determine whether spatial autocorrelation should be included in final models. Our results suggest that the influence of landscape variables is consistent between habitat selection and abundance in this system.

The Effect of Alcohol on Emotional Inertia: A Test of Alcohol Myopia

PubMed Central

Fairbairn, Catharine E.; Sayette, Michael A.

2017-01-01

Alcohol Myopia (AM) has emerged as one of the most widely-researched theories of alcohol’s effects on emotional experience. Given this theory’s popularity it is notable that a central tenet of AM has not been tested—namely, that alcohol creates a myopic focus on the present moment, limiting the extent to which the present is permeated by emotions derived from prior experience. We aimed to test the impact of alcohol on moment-to-moment fluctuations in affect, applying advances in emotion assessment and statistical analysis to test this aspect of AM without drawing the attention of participants to their own emotional experiences. We measured emotional fluctuations using autocorrelation, a statistic borrowed from time-series analysis measuring the correlation between successive observations in time. High emotion autocorrelation is termed “emotional inertia” and linked to negative mood outcomes. Seven-hundred-twenty social drinkers consumed alcohol, placebo, or control beverages in groups of three over a 36-min group formation task. We indexed affect using the Duchenne smile, recorded continuously during the interaction (34.9 million video frames) according to Paul Ekman’s Facial Action Coding System. Autocorrelation of Duchenne smiling emerged as the most consistent predictor of self-reported mood and social bonding when compared with Duchenne smiling mean, standard deviation, and linear trend. Alcohol reduced affective autocorrelation, and autocorrelation mediated the link between alcohol and self-reported mood and social outcomes. Findings suggest that alcohol enhances our ability to freely enjoy the present moment untethered by past experience and highlight the importance of emotion dynamics in research examining affective correlates of psychopathology. PMID:24016015

The method of trend analysis of parameters time series of gas-turbine engine state

NASA Astrophysics Data System (ADS)

Hvozdeva, I.; Myrhorod, V.; Derenh, Y.

2017-10-01

This research substantiates an approach to interval estimation of time series trend component. The well-known methods of spectral and trend analysis are used for multidimensional data arrays. The interval estimation of trend component is proposed for the time series whose autocorrelation matrix possesses a prevailing eigenvalue. The properties of time series autocorrelation matrix are identified.

[Temporal and spatial characteristics of ecological risk in Shunyi, Beijing, China based on landscape structure.

PubMed

Qing, Feng Ting; Peng, Yu

2016-05-01

Based on the remote sensing data in 1997, 2001, 2005, 2009 and 2013, this article classified the landscape types of Shunyi, and the ecological risk index was built based on landscape disturbance index and landscape fragility. The spatial auto-correlation and geostatistical analysis by GS + and ArcGIS was used to study temporal and spatial changes of ecological risk. The results showed that eco-risk degree in the study region had positive spatial correlation which decreased with the increasing grain size. Within a certain grain range (<12 km), the spatial auto-correlation had an obvious dependence on scale. The random variation of spatial heterogeneity was less than spatial auto-correlation variation from 1997 to 2013, which meant the auto-correlation had a dominant role in spatial heterogeneity. The ecological risk of Shunyi was mainly at moderate level during the study period. The area of the district with higher and lower ecological risk increased, while that of mode-rate ecological risk decreased. The area with low ecological risk was mainly located in the airport region and forest of southeast Shunyi, while that with high ecological risk was mainly concentrated in the water landscape, such as the banks of Chaobai River.

Intensity fluctuations in bimodal micropillar lasers enhanced by quantum-dot gain competition

NASA Astrophysics Data System (ADS)

Leymann, H. A. M.; Hopfmann, C.; Albert, F.; Foerster, A.; Khanbekyan, M.; Schneider, C.; Höfling, S.; Forchel, A.; Kamp, M.; Wiersig, J.; Reitzenstein, S.

2013-05-01

We investigate correlations between orthogonally polarized cavity modes of a bimodal micropillar laser with a single layer of self-assembled quantum dots in the active region. While one emission mode of the microlaser demonstrates a characteristic S-shaped input-output curve, the output intensity of the second mode saturates and even decreases with increasing injection current above threshold. Measuring the photon autocorrelation function g(2)(τ) of the light emission confirms the onset of lasing in the first mode with g(2)(0) approaching unity above threshold. In contrast, strong photon bunching associated with superthermal values of g(2)(0) is detected for the other mode for currents above threshold. This behavior is attributed to gain competition of the two modes induced by the common gain material, which is confirmed by photon cross-correlation measurements revealing a clear anticorrelation between emission events of the two modes. The experimental studies are in qualitative agreement with theoretical studies based on a microscopic semiconductor theory, which we extend to the case of two modes interacting with the common gain medium. Moreover, we treat the problem by a phenomenological birth-death model extended to two interacting modes, which reveals that the photon probability distribution of each mode has a double-peak structure, indicating switching behavior of the modes for pump rates around threshold.

A NEW METHOD FOR FINDING POINT SOURCES IN HIGH-ENERGY NEUTRINO DATA

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

Fang, Ke; Miller, M. Coleman

The IceCube collaboration has reported the first detection of high-energy astrophysical neutrinos, including ∼50 high-energy starting events, but no individual sources have been identified. It is therefore important to develop the most sensitive and efficient possible algorithms to identify the point sources of these neutrinos. The most popular current method works by exploring a dense grid of possible directions to individual sources, and identifying the single direction with the maximum probability of having produced multiple detected neutrinos. This method has numerous strengths, but it is computationally intensive and because it focuses on the single best location for a point source,more » additional point sources are not included in the evidence. We propose a new maximum likelihood method that uses the angular separations between all pairs of neutrinos in the data. Unlike existing autocorrelation methods for this type of analysis, which also use angular separations between neutrino pairs, our method incorporates information about the point-spread function and can identify individual point sources. We find that if the angular resolution is a few degrees or better, then this approach reduces both false positive and false negative errors compared to the current method, and is also more computationally efficient up to, potentially, hundreds of thousands of detected neutrinos.« less

On the decay of correlations in Sinai billiards with infinite horizon

NASA Astrophysics Data System (ADS)

Dahlqvist, Per; Artuso, Roberto

1996-02-01

We compute the decay of the autocorrelation function of the observable | vx| in the Sinai billiard and of the observable vx in the associated Lorentz gas with an approximation due to Baladi, Eckmann and Ruelle. We consider the standard configuration where the disk is centered inside a unit square. The asymptotic decay is found to be C( t) ∼ c( R)/ t. An explicit expression is given for the prefactor c( R) as a function of the radius of the scatterer. For the small scatterer case we also present expressions for the preasymptotic regime. Our findings are supported by numerical computations.

Amplitude and phase fluctuations of Van der Pol oscillator under external random forcing

NASA Astrophysics Data System (ADS)

Singh, Aman K.; Yadava, R. D. S.

2018-05-01

The paper presents an analytical study of noise in Van der Pol oscillator output subjected to an external force noise assumed to be characterized by delta function (white noise). The external fluctuations are assumed to be small in comparison to the average response of the noise free system. The autocorrelation function and power spectrum are calculated under the condition of weak nonlinearity. The latter ensures limit cycle oscillations. The total spectral power density is dominated by the contributions from the phase fluctuations. The amplitude fluctuations are at least two orders of magnitude smaller. The analysis is shown to be useful to interpretation microcantilever based biosensing data.

3D Time-lapse Imaging and Quantification of Mitochondrial Dynamics

NASA Astrophysics Data System (ADS)

Sison, Miguel; Chakrabortty, Sabyasachi; Extermann, Jérôme; Nahas, Amir; James Marchand, Paul; Lopez, Antonio; Weil, Tanja; Lasser, Theo

2017-02-01

We present a 3D time-lapse imaging method for monitoring mitochondrial dynamics in living HeLa cells based on photothermal optical coherence microscopy and using novel surface functionalization of gold nanoparticles. The biocompatible protein-based biopolymer coating contains multiple functional groups which impart better cellular uptake and mitochondria targeting efficiency. The high stability of the gold nanoparticles allows continuous imaging over an extended time up to 3000 seconds without significant cell damage. By combining temporal autocorrelation analysis with a classical diffusion model, we quantify mitochondrial dynamics and cast these results into 3D maps showing the heterogeneity of diffusion parameters across the whole cell volume.

Spatial structure, sampling design and scale in remotely-sensed imagery of a California savanna woodland

NASA Technical Reports Server (NTRS)

Mcgwire, K.; Friedl, M.; Estes, J. E.

1993-01-01

This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.

Frequency regularities of acoustic modes and multi-colour mode identification in rapidly rotating stars

NASA Astrophysics Data System (ADS)

Reese, D. R.; Lignières, F.; Ballot, J.; Dupret, M.-A.; Barban, C.; van't Veer-Menneret, C.; MacGregor, K. B.

2017-05-01

Context. Mode identification has remained a major obstacle in the interpretation of pulsation spectra in rapidly rotating stars. This has motivated recent work on calculating realistic multi-colour mode visibilities in this type of star. Aims: We would like to test mode identification methods and seismic diagnostics in rapidly rotating stars, using oscillation spectra that are based on these new theoretical predictions. Methods: We investigate the auto-correlation function and Fourier transform of theoretically calculated frequency spectra, in which modes are selected according to their visibilities. Given that intrinsic mode amplitudes are determined by non-linear saturation and cannot currently be theoretically predicted, we experimented with various ad-hoc prescriptions for setting the mode amplitudes, including using random values. Furthermore, we analyse the ratios between mode amplitudes observed in different photometric bands to see up to what extent they can identify modes. Results: When non-random intrinsic mode amplitudes are used, our results show that it is possible to extract a mean value for the large frequency separation or half its value and, sometimes, twice the rotation rate, from the auto-correlation of the frequency spectra. Furthermore, the Fourier transforms are mostly sensitive to the large frequency separation or half its value. The combination of the two methods may therefore measure and distinguish the two types of separations. When the intrinsic mode amplitudes include random factors, which seems more representative of real stars, the results are far less favourable. It is only when the large separation or half its value coincides with twice the rotation rate, that it might be possible to detect the signature of a frequency regularity. We also find that amplitude ratios are a good way of grouping together modes with similar characteristics. By analysing the frequencies of these groups, it is possible to constrain mode identification, as well as determine the large frequency separation and the rotation rate.

Density fingering in spatially modulated Hele-Shaw cells

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

Toth, Tamara; Horvath, Dezso; Toth, Agota

Density fingering of the chlorite-tetrathionate reaction has been studied experimentally in a periodically heterogeneous Hele-Shaw cell where the heterogeneity is introduced in the form of spatial modulation of gap width along the front. Depending on the spatial wavelength, gap width, and chemical composition, three types of cellular structures have been observed. The initial evolution is characterized by dispersion curves, while the long time behavior is described by the change in the autocorrelation function of the front profile and in the mixing length of the patterns.

Effect of Oxide Interface Roughness on the Threshold Voltage Fluctuations in Decanano MOSFETs with Ultrathin Gate Oxides

NASA Technical Reports Server (NTRS)

Asenov, Asen; Kaya, S.

2000-01-01

In this paper we use the Density Gradient (DG) simulation approach to study, in 3-D, the effect of local oxide thickness fluctuations on the threshold voltage of decanano MOSFETs on a statistical scale. The random 2-D surfaces used to represent the interface are constructed using the standard assumptions for the auto-correlation function of the interface. The importance of the Quantum Mechanical effects when studying oxide thickness fluctuations are illustrated in several simulation examples.

Low-frequency dynamics of autonomic regulation of circulatory system in healthy subjects

NASA Astrophysics Data System (ADS)

Skazkina, V. V.; Borovkova, E. I.; Galushko, T. A.; Khorev, V. S.; Kiselev, A. R.

2018-04-01

The paper is devoted to the analysis of dynamic of interactions between signals of autonomic circulatory regulation. We investigated two-hour experimental records of 30 healthy people. Phase synchronization was studied using the signals of the electrocardiogram and the photoplethysmogram of vessels. We found the presence of long synchronous intervals in some subjects. For analysis of the dynamic we calculated autocorrelation functions. The analysis made it possible to reveal indirect signs of the influence of the humoral regulation system.

A Bayesian Approach for Summarizing and Modeling Time-Series Exposure Data with Left Censoring.

PubMed

Houseman, E Andres; Virji, M Abbas

2017-08-01

Direct reading instruments are valuable tools for measuring exposure as they provide real-time measurements for rapid decision making. However, their use is limited to general survey applications in part due to issues related to their performance. Moreover, statistical analysis of real-time data is complicated by autocorrelation among successive measurements, non-stationary time series, and the presence of left-censoring due to limit-of-detection (LOD). A Bayesian framework is proposed that accounts for non-stationary autocorrelation and LOD issues in exposure time-series data in order to model workplace factors that affect exposure and estimate summary statistics for tasks or other covariates of interest. A spline-based approach is used to model non-stationary autocorrelation with relatively few assumptions about autocorrelation structure. Left-censoring is addressed by integrating over the left tail of the distribution. The model is fit using Markov-Chain Monte Carlo within a Bayesian paradigm. The method can flexibly account for hierarchical relationships, random effects and fixed effects of covariates. The method is implemented using the rjags package in R, and is illustrated by applying it to real-time exposure data. Estimates for task means and covariates from the Bayesian model are compared to those from conventional frequentist models including linear regression, mixed-effects, and time-series models with different autocorrelation structures. Simulations studies are also conducted to evaluate method performance. Simulation studies with percent of measurements below the LOD ranging from 0 to 50% showed lowest root mean squared errors for task means and the least biased standard deviations from the Bayesian model compared to the frequentist models across all levels of LOD. In the application, task means from the Bayesian model were similar to means from the frequentist models, while the standard deviations were different. Parameter estimates for covariates were significant in some frequentist models, but in the Bayesian model their credible intervals contained zero; such discrepancies were observed in multiple datasets. Variance components from the Bayesian model reflected substantial autocorrelation, consistent with the frequentist models, except for the auto-regressive moving average model. Plots of means from the Bayesian model showed good fit to the observed data. The proposed Bayesian model provides an approach for modeling non-stationary autocorrelation in a hierarchical modeling framework to estimate task means, standard deviations, quantiles, and parameter estimates for covariates that are less biased and have better performance characteristics than some of the contemporary methods. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2017.

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.

An Expert System for the Evaluation of Cost Models

DTIC Science & Technology

1990-09-01

contrast to the condition of equal error variance, called homoscedasticity. (Reference: Applied Linear Regression Models by John Neter - page 423...normal. (Reference: Applied Linear Regression Models by John Neter - page 125) Click Here to continue -> Autocorrelation Click Here for the index - Index...over time. Error terms correlated over time are said to be autocorrelated or serially correlated. (REFERENCE: Applied Linear Regression Models by John

The Spatial Distribution of Adult Obesity Prevalence in Denver County, Colorado: An Empirical Bayes Approach to Adjust EHR-Derived Small Area Estimates.

PubMed

Tabano, David C; Bol, Kirk; Newcomer, Sophia R; Barrow, Jennifer C; Daley, Matthew F

2017-12-06

Measuring obesity prevalence across geographic areas should account for environmental and socioeconomic factors that contribute to spatial autocorrelation, the dependency of values in estimates across neighboring areas, to mitigate the bias in measures and risk of type I errors in hypothesis testing. Dependency among observations across geographic areas violates statistical independence assumptions and may result in biased estimates. Empirical Bayes (EB) estimators reduce the variability of estimates with spatial autocorrelation, which limits the overall mean square-error and controls for sample bias. Using the Colorado Body Mass Index (BMI) Monitoring System, we modeled the spatial autocorrelation of adult (≥ 18 years old) obesity (BMI ≥ 30 kg m 2 ) measurements using patient-level electronic health record data from encounters between January 1, 2009, and December 31, 2011. Obesity prevalence was estimated among census tracts with >=10 observations in Denver County census tracts during the study period. We calculated the Moran's I statistic to test for spatial autocorrelation across census tracts, and mapped crude and EB obesity prevalence across geographic areas. In Denver County, there were 143 census tracts with 10 or more observations, representing a total of 97,710 adults with a valid BMI. The crude obesity prevalence for adults in Denver County was 29.8 percent (95% CI 28.4-31.1%) and ranged from 12.8 to 45.2 percent across individual census tracts. EB obesity prevalence was 30.2 percent (95% CI 28.9-31.5%) and ranged from 15.3 to 44.3 percent across census tracts. Statistical tests using the Moran's I statistic suggest adult obesity prevalence in Denver County was distributed in a non-random pattern. Clusters of EB obesity estimates were highly significant (alpha=0.05) in neighboring census tracts. Concentrations of obesity estimates were primarily in the west and north in Denver County. Statistical tests reveal adult obesity prevalence exhibit spatial autocorrelation in Denver County at the census tract level. EB estimates for obesity prevalence can be used to control for spatial autocorrelation between neighboring census tracts and may produce less biased estimates of obesity prevalence.

Moho depth across the Trans-European Suture Zone from ambient vibration autocorrelations

NASA Astrophysics Data System (ADS)

Becker, Gesa; Knapmeyer-Endrun, Brigitte

2017-04-01

In 2018 the InSight mission to Mars will deploy a seismic station on the planet. This seismic station will consist of a three-component very broadband seismic sensor and a collocated three-component short period seismometer. Single station methods are therefore needed to extract information from the data and learn more about the interior structure of Mars. One potential method is the extraction of reflected phases from autocorrelations. Here autocorrelations are derived from ambient seismic noise to make the most of the data expected, as seismicity on Mars is likely less abundant than on Earth. These autocorrelations are calculated using a phase autocorrelation algorithm and time-frequency domain phase-weighted stacking as the main processing steps in addition to smoothing the spectrum of the data with a short term-long term average algorithm. Afterward the obtained results are filtered and analyzed in the frequency range of 1-2 Hz. The developed processing scheme is applied to data from permanent seismic stations located in different geological provinces across Europe, i.e. the Upper Rhine Graben, Central European Platform, Bohemian Massif, Northern German and Polish Basin, and the East European Craton, with varying Moho depths between 25-50 km. These crustal thicknesses are comparable to various estimates for Mars, therefore providing a good reference and indication of resolvability for Moho depths that might be encountered at the landing site. Changes in reflectivity can be observed in the calculated autocorrelations. The lag times of these changes are converted into depths with the help of available velocity information (EPcrust and local models for Poland and the Czech Republic, respectively) and the results are compared to existing information on Moho depths, which show good agreement. The results are temporarily stable, but show a clear correlation with the existence of cultural noise. Based on the closely located broadband and short period stations of the GERESS-array, it is shown that the processing scheme is also applicable to short period stations. Subsequently it is applied to the mainly short period and temporary stations of the PASSEQ network along the seismic profile POLONAISE P4, running from Eastern Germany to Lithuania crossing the Trans-European Suture Zone.

Source localization of narrow band signals in multipath environments, with application to marine mammals

NASA Astrophysics Data System (ADS)

Valtierra, Robert Daniel

Passive acoustic localization has benefited from many major developments and has become an increasingly important focus point in marine mammal research. Several challenges still remain. This work seeks to address several of these challenges such as tracking the calling depths of baleen whales. In this work, data from an array of widely spaced Marine Acoustic Recording Units (MARUs) was used to achieve three dimensional localization by combining the methods Time Difference of Arrival (TDOA) and Direct-Reflected Time Difference of Arrival (DRTD) along with a newly developed autocorrelation technique. TDOA was applied to data for two dimensional (latitude and longitude) localization and depth was resolved using DRTD. Previously, DRTD had been limited to pulsed broadband signals, such as sperm whale or dolphin echolocation, where individual direct and reflected signals are separated in time. Due to the length of typical baleen whale vocalizations, individual multipath signal arrivals can overlap making time differences of arrival difficult to resolve. This problem can be solved using an autocorrelation, which can extract reflection information from overlapping signals. To establish this technique, a derivation was made to model the autocorrelation of a direct signal and its overlapping reflection. The model was exploited to derive performance limits allowing for prediction of the minimum resolvable direct-reflected time difference for a known signal type. The dependence on signal parameters (sweep rate, call duration) was also investigated. The model was then verified using both recorded and simulated data from two analysis cases for North Atlantic right whales (NARWs, Eubalaena glacialis) and humpback whales (Megaptera noveaengliae). The newly developed autocorrelation technique was then combined with DRTD and tested using data from playback transmissions to localize an acoustic transducer at a known depth and location. The combined DRTD-autocorrelation methods enabled calling depth and range estimations of a vocalizing NARW and humpback whale in two separate cases. The DRTD-autocorrelation method was then combined with TDOA to create a three dimensional track of a NARW in the Stellwagen Bank National Marine Sanctuary. Results from these experiments illustrated the potential of the combined methods to successfully resolve baleen calling depths in three dimensions.

Queues with Dropping Functions and General Arrival Processes

PubMed Central

Chydzinski, Andrzej; Mrozowski, Pawel

2016-01-01

In a queueing system with the dropping function the arriving customer can be denied service (dropped) with the probability that is a function of the queue length at the time of arrival of this customer. The potential applicability of such mechanism is very wide due to the fact that by choosing the shape of this function one can easily manipulate several performance characteristics of the queueing system. In this paper we carry out analysis of the queueing system with the dropping function and a very general model of arrival process—the model which includes batch arrivals and the interarrival time autocorrelation, and allows for fitting the actual shape of the interarrival time distribution and its moments. For such a system we obtain formulas for the distribution of the queue length and the overall customer loss ratio. The analytical results are accompanied with numerical examples computed for several dropping functions. PMID:26943171

On a method to detect long-latency excitations and inhibitions of single hand muscle motoneurons in man.

PubMed

Awiszus, F; Feistner, H; Schäfer, S S

1991-01-01

The peri-stimulus-time histogram (PSTH) analysis of stimulus-related neuronal spike train data is usually regarded as a method to detect stimulus-induced excitations or inhibitions. However, for a fairly regularly discharging neuron such as the human alpha-motoneuron, long-latency modulations of a PSTH are difficult to interpret as PSTH modulations can also occur as a consequence of a modulated neuronal autocorrelation. The experiments reported here were made (i) to investigate the extent to which a PSTH of a human hand-muscle motoneuron may be contaminated by features of the autocorrelation and (ii) to develop methods that display the motoneuronal excitations and inhibitions without such contamination. Responses of 29 single motor units to electrical ulnar nerve stimulation below motor threshold were investigated in the first dorsal interosseous muscle of three healthy volunteers using an experimental protocol capable of demonstrating the presence of autocorrelative modulations in the neuronal response. It was found for all units that the PSTH as well as the cumulative sum (CUSUM) derived from these responses were severely affected by the presence of autocorrelative features. On the other hand, calculating the CUSUM in a slightly modified form yielded--for all units investigated--a neuronal output feature sensitive only to motoneuronal excitations and inhibitions induced by the afferent volley. The price that has to be paid to arrive at such a modified CUSUM (mCUSUM) was a high computational effort prohibiting the on-line availability of this output feature during the experiment. It was found, however, that an interspike interval superposition plot (IISP)--easily obtainable during the experiment--is also free of autocorrelative features.(ABSTRACT TRUNCATED AT 250 WORDS)

Life expectancy impacts due to heating energy utilization in China: Distribution, relations, and policy implications.

PubMed

Wang, Shaobin; Luo, Kunli

2018-01-01

The relation between life expectancy and energy utilization is of particular concern. Different viewpoints concerned the health impacts of heating policy in China. However, it is still obscure that what kind of heating energy or what pattern of heating methods is the most related with the difference of life expectancies in China. The aim of this paper is to comprehensively investigate the spatial relations between life expectancy at birth (LEB) and different heating energy utilization in China by using spatial autocorrelation models including global spatial autocorrelation, local spatial autocorrelation and hot spot analysis. The results showed that: (1) Most of heating energy exhibit a distinct north-south difference, such as central heating supply, stalks and domestic coal. Whereas spatial distribution of domestic natural gas and electricity exhibited west-east differences. (2) Consumption of central heating, stalks and domestic coal show obvious spatial dependence. Whereas firewood, natural gas and electricity did not show significant spatial autocorrelation. It exhibited an extinct south-north difference of heat supply, stalks and domestic coal which were identified to show significant positive spatial autocorrelation. (3) Central heating, residential boilers and natural gas did not show any significant correlations with LEB. While, the utilization of domestic coal and biomass showed significant negative correlations with LEB, and household electricity shows positive correlations. The utilization of domestic coal in China showed a negative effect on LEB, rather than central heating. To improve the solid fuel stoves and control consumption of domestic coal consumption and other low quality solid fuel is imperative to improve the public health level in China in the future. Copyright © 2017 Elsevier B.V. All rights reserved.

[Characteristics of temporal-spatial differentiation in landscape pattern vulnerability in Nansihu Lake wetland, China.

PubMed

Liang, Jia Xin; Li, Xin Ju

2018-02-01

With remote sensing images from 1985, 2000 Lantsat 5 TM and 2015 Lantsat 8 OLI as data sources, we tried to select the suitable research scale and examine the temporal-spatial diffe-rentiation with such scale in the Nansihu Lake wetland by using landscape pattern vulnerability index constructed by sensitivity index and adaptability index, and combined with space statistics such as semivariogram and spatial autocorrelation. The results showed that 1 km × 1 km equidistant grid was the suitable research scale, which could eliminate the influence of spatial heterogeneity induced by random factors. From 1985 to 2015, the landscape pattern vulnerability in the Nansihu Lake wetland deteriorated gradually. The high-risk area of landscape pattern vulnerability dramatically expanded with time. The spatial heterogeneity of landscape pattern vulnerability increased, and the influence of non-structural factors on landscape pattern vulnerability strengthened. Spatial variability affected by spatial autocorrelation slightly weakened. Landscape pattern vulnerability had strong general spatial positive correlation, with the significant form of spatial agglomeration. The positive spatial autocorrelation continued to increase and the phenomenon of spatial concentration was more and more obvious over time. The local autocorrelation mainly based on high-high accumulation zone and low-low accumulation zone had stronger spatial autocorrelation among neighboring space units. The high-high accumulation areas showed the strongest level of significance, and the significant level of low-low accumulation zone increased with time. Natural factors, such as temperature and precipitation, affected water-level and landscape distribution, and thus changed the landscape patterns vulnerability of Nansihu Lake wetland. The dominant driver for the deterioration of landscape patterns vulnerability was human activities, including social economy activity and policy system.

The relationship between affective state and the rhythmicity of activity in bipolar disorder.

PubMed

Gonzalez, Robert; Tamminga, Carol A; Tohen, Mauricio; Suppes, Trisha

2014-04-01

The aim of this study was to test the relationships between mood state and rhythm disturbances as measured via actigraphy in bipolar disorder by assessing the correlations between manic and depressive symptoms as measured via Young Mania Rating Scale (YMRS) and 30-item Inventory for Depressive Symptomatology, Clinician-Rated (IDS-C-30) scores and the actigraphic measurements of rhythm, the 24-hour autocorrelation coefficient and circadian quotient. The research was conducted at the University of Texas Southwestern Medical Center at Dallas from February 2, 2009, to March 30, 2010. 42 patients with a DSM-IV-TR diagnosis of bipolar I disorder were included in the study. YMRS and the IDS-C-30 were used to determine symptom severity. Subjects wore the actigraph continuously for 7 days. The 24-hour autocorrelation coefficient was used as an indicator of overall rhythmicity. The circadian quotient was used to characterize the strength of a circadian rhythm. A greater severity of manic symptoms correlated with a lower degree of rhythmicity and less robust rhythms of locomotor activity as indicated by lower 24-hour autocorrelation (r = -0.3406, P = .03) and circadian quotient (r = -0.5485, P = .0002) variables, respectively. No relationship was noted between the degree of depression and 24-hour autocorrelation scores (r = -0.1190, P = .45) or circadian quotient (r = 0.0083, P = .96). Correlation was noted between the 24-hour autocorrelation and circadian quotient scores (r = 0.6347, P < .0001). These results support the notion that circadian rhythm disturbances are associated with bipolar disorder and that these disturbances may be associated with clinical signatures of the disorder. Further assessment of rhythm disturbances in bipolar disorder is warranted. © Copyright 2014 Physicians Postgraduate Press, Inc.

Quantitative structural modeling on the wavelength interval (Δλ) in synchronous fluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Samari, Fayezeh; Yousefinejad, Saeed

2017-11-01

Emission fluorescence spectroscopy has an extremely restricted scope of application to analyze of complex mixtures since its selectivity is reduced by the extensive spectral overlap. Synchronous fluorescence spectroscopy (SFS) is a technique enables us to analyze complex mixtures with overlapped emission and/or excitation spectra. The difference of excitation and emission wavelength of compounds (interval wavelength or Δλ) is an important characteristic in SFS. Thus a multi-parameter model was constructed to predict Δλ in 63 fluorescent compounds and the regression coefficient in training set, cross validation and test set were 0.88, 0.85 and 0.91 respectively. Furthermore, the applicability and validity of model were evaluated using different statistical methods such as y-scrambling and applicability domain. It was concluded that increasing average valence connectivity, number of Al2-NH functional group and Geary autocorrelation (lag 4) with electronegative weights can lead to increasing Δλ in the fluorescent compounds. The current study obtained an insight into the structural properties of compounds effective on their Δλ as an important parameter in SFS.

Stock markets and criticality in the current economic crisis

NASA Astrophysics Data System (ADS)

da Silva, Roberto; Zembrzuski, Marcelo; Correa, Fabio C.; Lamb, Luis C.

2010-12-01

We show that the current economic crisis has led the market to exhibit a non-critical behavior. We do so by analyzing the quantitative parameters of time series from the main assets of the Brazilian Stock Market BOVESPA. By monitoring global persistence we show a deviation of power law behavior during the crisis in a strong analogy with spin systems (from where this concept was originally conceived). Such behavior is corroborated by an emergent heavy tail of absolute return distribution and also by the magnitude autocorrelation exponent. Comparisons with universal exponents obtained in the international stock markets are also performed. This suggests how a thorough analysis of suitable exponents can bring a possible way of forecasting market crises characterized by non-criticality.

A recursive linear predictive vocoder

NASA Astrophysics Data System (ADS)

Janssen, W. A.

1983-12-01

A non-real time 10 pole recursive autocorrelation linear predictive coding vocoder was created for use in studying effects of recursive autocorrelation on speech. The vocoder is composed of two interchangeable pitch detectors, a speech analyzer, and speech synthesizer. The time between updating filter coefficients is allowed to vary from .125 msec to 20 msec. The best quality was found using .125 msec between each update. The greatest change in quality was noted when changing from 20 msec/update to 10 msec/update. Pitch period plots for the center clipping autocorrelation pitch detector and simplified inverse filtering technique are provided. Plots of speech into and out of the vocoder are given. Formant versus time three dimensional plots are shown. Effects of noise on pitch detection and formants are shown. Noise effects the voiced/unvoiced decision process causing voiced speech to be re-constructed as unvoiced.

Quantum state reconstruction and photon number statistics for low dimensional semiconductor opto-electronic devices

NASA Astrophysics Data System (ADS)

Böhm, Fabian; Grosse, Nicolai B.; Kolarczik, Mirco; Herzog, Bastian; Achtstein, Alexander; Owschimikow, Nina; Woggon, Ulrike

2017-09-01

Quantum state tomography and the reconstruction of the photon number distribution are techniques to extract the properties of a light field from measurements of its mean and fluctuations. These techniques are particularly useful when dealing with macroscopic or mesoscopic systems, where a description limited to the second order autocorrelation soon becomes inadequate. In particular, the emission of nonclassical light is expected from mesoscopic quantum dot systems strongly coupled to a cavity or in systems with large optical nonlinearities. We analyze the emission of a quantum dot-semiconductor optical amplifier system by quantifying the modifications of a femtosecond laser pulse propagating through the device. Using a balanced detection scheme in a self-heterodyning setup, we achieve precise measurements of the quadrature components and their fluctuations at the quantum noise limit1. We resolve the photon number distribution and the thermal-to-coherent evolution in the photon statistics of the emission. The interferometric detection achieves a high sensitivity in the few photon limit. From our data, we can also reconstruct the second order autocorrelation function with higher precision and time resolution compared with classical Hanbury Brown-Twiss experiments.

Effect of endotoxin on ventilation and breath variability: role of cyclooxygenase pathway.

PubMed

Preas, H L; Jubran, A; Vandivier, R W; Reda, D; Godin, P J; Banks, S M; Tobin, M J; Suffredini, A F

2001-08-15

To evaluate the effects of endotoxemia on respiratory controller function, 12 subjects were randomized to receive endotoxin or saline; six also received ibuprofen, a cyclooxygenase inhibitor, and six received placebo. Administration of endotoxin produced fever, increased respiratory frequency, decreased inspiratory time, and widened alveolar-arterial oxygen tension gradient (all p < or = 0.001); these responses were blocked by ibuprofen. Independent of ibuprofen, endotoxin produced dyspnea, and it increased fractional inspiratory time, minute ventilation, and mean inspiratory flow (all p < or = 0.025). Endotoxin altered the autocorrelative behavior of respiratory frequency by increasing its autocorrelation coefficient at a lag of one breath, the number of breath lags with significant serial correlations, and its correlated fraction (all p < 0.05); these responses were blocked by ibuprofen. Changes in correlated behavior of respiratory frequency were related to changes in arterial carbon dioxide tension (r = 0.86; p < 0.03). Endotoxin decreased the oscillatory fraction of inspiratory time in both the placebo (p < 0.05) and ibuprofen groups (p = 0.06). In conclusion, endotoxin produced increases in respiratory motor output and dyspnea independent of fever and symptoms, and it curtailed the freedom to vary respiratory timing-a response that appears to be mediated by the cyclooxygenase pathway.

Theory for long memory in supply and demand

NASA Astrophysics Data System (ADS)

Lillo, Fabrizio; Mike, Szabolcs; Farmer, J. Doyne

2005-06-01

Recent empirical studies have demonstrated long-memory in the signs of orders to buy or sell in financial markets [J.-P. Bouchaud, Y. Gefen, M. Potters, and M. Wyart, Quant. Finance 4, 176 (2004); F. Lillo and J. D. Farmer Dyn. Syst. Appl. 8, 3 (2004)]. We show how this can be caused by delays in market clearing. Under the common practice of order splitting, large orders are broken up into pieces and executed incrementally. If the size of such large orders is power-law distributed, this gives rise to power-law decaying autocorrelations in the signs of executed orders. More specifically, we show that if the cumulative distribution of large orders of volume v is proportional to v-α and the size of executed orders is constant, the autocorrelation of order signs as a function of the lag τ is asymptotically proportional to τ-(α-1) . This is a long-memory process when α<2 . With a few caveats, this gives a good match to the data. A version of the model also shows long-memory fluctuations in order execution rates, which may be relevant for explaining the long memory of price diffusion rates.

Theory for long memory in supply and demand.

PubMed

Lillo, Fabrizio; Mike, Szabolcs; Farmer, J Doyne

2005-06-01

Recent empirical studies have demonstrated long-memory in the signs of orders to buy or sell in financial markets [J.-P. Bouchaud, Y. Gefen, M. Potters, and M. Wyart, Quant. Finance 4, 176 (2004); F. Lillo and J. D. Farmer Dyn. Syst. Appl. 8, 3 (2004)]. We show how this can be caused by delays in market clearing. Under the common practice of order splitting, large orders are broken up into pieces and executed incrementally. If the size of such large orders is power-law distributed, this gives rise to power-law decaying autocorrelations in the signs of executed orders. More specifically, we show that if the cumulative distribution of large orders of volume v is proportional to v(-alpha) and the size of executed orders is constant, the autocorrelation of order signs as a function of the lag tau is asymptotically proportional to tau(-(alpha-1)). This is a long-memory process when alpha < 2. With a few caveats, this gives a good match to the data. A version of the model also shows long-memory fluctuations in order execution rates, which may be relevant for explaining the long memory of price diffusion rates.

Generalizability Assessment of Autocorrelated Direct Observation Data: The Applicability of the Tiao-Tan Method and Alternative.

ERIC Educational Resources Information Center

Suen, Hoi K.; And Others

The applicability is explored of the Bayesian random-effect analysis of variance (ANOVA) model developed by G. C. Tiao and W. Y. Tan (1966) and a method suggested by H. K. Suen and P. S. Lee (1987) for the generalizability analysis of autocorrelated data. According to Tiao and Tan, if time series data could be described as a first-order…

Geostatistical Prediction of Microbial Water Quality Throughout a Stream Network Using Meteorology, Land Cover, and Spatiotemporal Autocorrelation.

PubMed

Holcomb, David A; Messier, Kyle P; Serre, Marc L; Rowny, Jakob G; Stewart, Jill R

2018-06-25

Predictive modeling is promising as an inexpensive tool to assess water quality. We developed geostatistical predictive models of microbial water quality that empirically modeled spatiotemporal autocorrelation in measured fecal coliform (FC) bacteria concentrations to improve prediction. We compared five geostatistical models featuring different autocorrelation structures, fit to 676 observations from 19 locations in North Carolina's Jordan Lake watershed using meteorological and land cover predictor variables. Though stream distance metrics (with and without flow-weighting) failed to improve prediction over the Euclidean distance metric, incorporating temporal autocorrelation substantially improved prediction over the space-only models. We predicted FC throughout the stream network daily for one year, designating locations "impaired", "unimpaired", or "unassessed" if the probability of exceeding the state standard was ≥90%, ≤10%, or >10% but <90%, respectively. We could assign impairment status to more of the stream network on days any FC were measured, suggesting frequent sample-based monitoring remains necessary, though implementing spatiotemporal predictive models may reduce the number of concurrent sampling locations required to adequately assess water quality. Together, these results suggest that prioritizing sampling at different times and conditions using geographically sparse monitoring networks is adequate to build robust and informative geostatistical models of water quality impairment.

Interferometric Near-Infrared Spectroscopy (iNIRS) for determination of optical and dynamical properties of turbid media

PubMed Central

Borycki, Dawid; Kholiqov, Oybek; Chong, Shau Poh; Srinivasan, Vivek J.

2016-01-01

We introduce and implement interferometric near-infrared spectroscopy (iNIRS), which simultaneously extracts optical and dynamical properties of turbid media through analysis of a spectral interference fringe pattern. The spectral interference fringe pattern is measured using a Mach-Zehnder interferometer with a frequency-swept narrow linewidth laser. Fourier analysis of the detected signal is used to determine time-of-flight (TOF)-resolved intensity, which is then analyzed over time to yield TOF-resolved intensity autocorrelations. This approach enables quantification of optical properties, which is not possible in conventional, continuous-wave near-infrared spectroscopy (NIRS). Furthermore, iNIRS quantifies scatterer motion based on TOF-resolved autocorrelations, which is a feature inaccessible by well-established diffuse correlation spectroscopy (DCS) techniques. We prove this by determining TOF-resolved intensity and temporal autocorrelations for light transmitted through diffusive fluid phantoms with optical thicknesses of up to 55 reduced mean free paths (approximately 120 scattering events). The TOF-resolved intensity is used to determine optical properties with time-resolved diffusion theory, while the TOF-resolved intensity autocorrelations are used to determine dynamics with diffusing wave spectroscopy. iNIRS advances the capabilities of diffuse optical methods and is suitable for in vivo tissue characterization. Moreover, iNIRS combines NIRS and DCS capabilities into a single modality. PMID:26832264

Bridging the gulf between correlated random walks and Lévy walks: autocorrelation as a source of Lévy walk movement patterns.

PubMed

Reynolds, Andy M

2010-12-06

For many years, the dominant conceptual framework for describing non-oriented animal movement patterns has been the correlated random walk (CRW) model in which an individual's trajectory through space is represented by a sequence of distinct, independent randomly oriented 'moves'. It has long been recognized that the transformation of an animal's continuous movement path into a broken line is necessarily arbitrary and that probability distributions of move lengths and turning angles are model artefacts. Continuous-time analogues of CRWs that overcome this inherent shortcoming have appeared in the literature and are gaining prominence. In these models, velocities evolve as a Markovian process and have exponential autocorrelation. Integration of the velocity process gives the position process. Here, through a simple scaling argument and through an exact analytical analysis, it is shown that autocorrelation inevitably leads to Lévy walk (LW) movement patterns on timescales less than the autocorrelation timescale. This is significant because over recent years there has been an accumulation of evidence from a variety of experimental and theoretical studies that many organisms have movement patterns that can be approximated by LWs, and there is now intense debate about the relative merits of CRWs and LWs as representations of non-orientated animal movement patterns.

Emission from quantum-dot high-β microcavities: transition from spontaneous emission to lasing and the effects of superradiant emitter coupling

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

Kreinberg, Sören; Chow, Weng W.; Wolters, Janik

Measured and calculated results are presented for the emission properties of a new class of emitters operating in the cavity quantum electrodynamics regime. The structures are based on high-finesse GaAs/AlAs micropillar cavities, each with an active medium consisting of a layer of InGaAs quantum dots (QDs) and the distinguishing feature of having a substantial fraction of spontaneous emission channeled into one cavity mode (high β-factor). This paper demonstrates that the usual criterion for lasing with a conventional (low β-factor) cavity, that is, a sharp non-linearity in the input–output curve accompanied by noticeable linewidth narrowing, has to be reinforced by themore » equal-time second-order photon autocorrelation function to confirm lasing. The article also shows that the equal-time second-order photon autocorrelation function is useful for recognizing superradiance, a manifestation of the correlations possible in high-β microcavities operating with QDs. In terms of consolidating the collected data and identifying the physics underlying laser action, both theory and experiment suggest a sole dependence on intracavity photon number. Evidence for this assertion comes from all our measured and calculated data on emission coherence and fluctuation, for devices ranging from light-emitting diodes (LEDs) and cavity-enhanced LEDs to lasers, lying on the same two curves: one for linewidth narrowing versus intracavity photon number and the other for g( 2)(0) versus intracavity photon number.« less

Perception and psychological evaluation for visual and auditory environment based on the correlation mechanisms

NASA Astrophysics Data System (ADS)

Fujii, Kenji

2002-06-01

In this dissertation, the correlation mechanism in modeling the process in the visual perception is introduced. It has been well described that the correlation mechanism is effective for describing subjective attributes in auditory perception. The main result is that it is possible to apply the correlation mechanism to the process in temporal vision and spatial vision, as well as in audition. (1) The psychophysical experiment was performed on subjective flicker rates for complex waveforms. A remarkable result is that the phenomenon of missing fundamental is found in temporal vision as analogous to the auditory pitch perception. This implies the existence of correlation mechanism in visual system. (2) For spatial vision, the autocorrelation analysis provides useful measures for describing three primary perceptual properties of visual texture: contrast, coarseness, and regularity. Another experiment showed that the degree of regularity is a salient cue for texture preference judgment. (3) In addition, the autocorrelation function (ACF) and inter-aural cross-correlation function (IACF) were applied for analysis of the temporal and spatial properties of environmental noise. It was confirmed that the acoustical properties of aircraft noise and traffic noise are well described. These analyses provided useful parameters extracted from the ACF and IACF in assessing the subjective annoyance for noise. Thesis advisor: Yoichi Ando Copies of this thesis written in English can be obtained from Junko Atagi, 6813 Mosonou, Saijo-cho, Higashi-Hiroshima 739-0024, Japan. E-mail address: atagi\\@urban.ne.jp.

Reversible geminate recombination of hydrogen-bonded water molecule pair

NASA Astrophysics Data System (ADS)

Markovitch, Omer; Agmon, Noam

2008-08-01

The (history independent) autocorrelation function for a hydrogen-bonded water molecule pair, calculated from classical molecular dynamics trajectories of liquid water, exhibits a t-3/2 asymptotic tail. Its whole time dependence agrees quantitatively with the solution for reversible diffusion-influenced geminate recombination derived by Agmon and Weiss [J. Chem. Phys. 91, 6937 (1989)]. Agreement with diffusion theory is independent of the precise definition of the bound state. Given the water self-diffusion constant, this theory enables us to determine the dissociation and bimolecular recombination rate parameters for a water dimer. (The theory is indispensable for obtaining the bimolecular rate coefficient.) Interestingly, the activation energies obtained from the temperature dependence of these rate coefficients are similar, rather than differing by the hydrogen-bond (HB) strength. This suggests that recombination requires displacing another water molecule, which meanwhile occupied the binding site. Because these activation energies are about twice the HB strength, cleavage of two HBs may be required to allow pair separation. The autocorrelation function without the HB angular restriction yields a recombination rate coefficient that is larger than that for rebinding to all four tetrahedral water sites (with angular restrictions), suggesting the additional participation of interstitial sites. Following dissociation, the probability of the pair to be unbound but within the reaction sphere rises more slowly than expected, possibly because binding to the interstitial sites delays pair separation. An extended diffusion model, which includes an additional binding site, can account for this behavior.

Emission from quantum-dot high-β microcavities: transition from spontaneous emission to lasing and the effects of superradiant emitter coupling

DOE PAGES

Kreinberg, Sören; Chow, Weng W.; Wolters, Janik; ...

2017-02-28

Measured and calculated results are presented for the emission properties of a new class of emitters operating in the cavity quantum electrodynamics regime. The structures are based on high-finesse GaAs/AlAs micropillar cavities, each with an active medium consisting of a layer of InGaAs quantum dots (QDs) and the distinguishing feature of having a substantial fraction of spontaneous emission channeled into one cavity mode (high β-factor). This paper demonstrates that the usual criterion for lasing with a conventional (low β-factor) cavity, that is, a sharp non-linearity in the input–output curve accompanied by noticeable linewidth narrowing, has to be reinforced by themore » equal-time second-order photon autocorrelation function to confirm lasing. The article also shows that the equal-time second-order photon autocorrelation function is useful for recognizing superradiance, a manifestation of the correlations possible in high-β microcavities operating with QDs. In terms of consolidating the collected data and identifying the physics underlying laser action, both theory and experiment suggest a sole dependence on intracavity photon number. Evidence for this assertion comes from all our measured and calculated data on emission coherence and fluctuation, for devices ranging from light-emitting diodes (LEDs) and cavity-enhanced LEDs to lasers, lying on the same two curves: one for linewidth narrowing versus intracavity photon number and the other for g( 2)(0) versus intracavity photon number.« less

A longitudinal model for disease progression was developed and applied to multiple sclerosis

PubMed Central

Lawton, Michael; Tilling, Kate; Robertson, Neil; Tremlett, Helen; Zhu, Feng; Harding, Katharine; Oger, Joel; Ben-Shlomo, Yoav

2015-01-01

Objectives To develop a model of disease progression using multiple sclerosis (MS) as an exemplar. Study Design and Settings Two observational cohorts, the University of Wales MS (UoWMS), UK (1976), and British Columbia MS (BCMS) database, Canada (1980), with longitudinal disability data [the Expanded Disability Status Scale (EDSS)] were used; individuals potentially eligible for MS disease-modifying drugs treatments, but who were unexposed, were selected. Multilevel modeling was used to estimate the EDSS trajectory over time in one data set and validated in the other; challenges addressed included the choice and function of time axis, complex observation-level variation, adjustments for MS relapses, and autocorrelation. Results The best-fitting model for the UoWMS cohort (404 individuals, and 2,290 EDSS observations) included a nonlinear function of time since onset. Measurement error decreased over time and ad hoc methods reduced autocorrelation and the effect of relapse. Replication within the BCMS cohort (978 individuals and 7,335 EDSS observations) led to a model with similar time (years) coefficients, time [0.22 (95% confidence interval {CI}: 0.19, 0.26), 0.16 (95% CI: 0.10, 0.22)] and log time [−0.13 (95% CI: −0.39, 0.14), −0.15 (95% CI: −0.70, 0.40)] for BCMS and UoWMS, respectively. Conclusion It is possible to develop robust models of disability progression for chronic disease. However, explicit validation is important given the complex methodological challenges faced. PMID:26071892

A novel technique for fetal heart rate estimation from Doppler ultrasound signal

PubMed Central

2011-01-01

Background The currently used fetal monitoring instrumentation that is based on Doppler ultrasound technique provides the fetal heart rate (FHR) signal with limited accuracy. It is particularly noticeable as significant decrease of clinically important feature - the variability of FHR signal. The aim of our work was to develop a novel efficient technique for processing of the ultrasound signal, which could estimate the cardiac cycle duration with accuracy comparable to a direct electrocardiography. Methods We have proposed a new technique which provides the true beat-to-beat values of the FHR signal through multiple measurement of a given cardiac cycle in the ultrasound signal. The method consists in three steps: the dynamic adjustment of autocorrelation window, the adaptive autocorrelation peak detection and determination of beat-to-beat intervals. The estimated fetal heart rate values and calculated indices describing variability of FHR, were compared to the reference data obtained from the direct fetal electrocardiogram, as well as to another method for FHR estimation. Results The results revealed that our method increases the accuracy in comparison to currently used fetal monitoring instrumentation, and thus enables to calculate reliable parameters describing the variability of FHR. Relating these results to the other method for FHR estimation we showed that in our approach a much lower number of measured cardiac cycles was rejected as being invalid. Conclusions The proposed method for fetal heart rate determination on a beat-to-beat basis offers a high accuracy of the heart interval measurement enabling reliable quantitative assessment of the FHR variability, at the same time reducing the number of invalid cardiac cycle measurements. PMID:21999764

On the wrong inference of long-range correlations in climate data; the case of the solar and volcanic forcing over the Tropical Pacific

NASA Astrophysics Data System (ADS)

Varotsos, Costas A.; Efstathiou, Maria N.

2017-05-01

A substantial weakness of several climate studies on long-range dependence is the conclusion of long-term memory of the climate conditions, without considering it necessary to establish the power-law scaling and to reject a simple exponential decay of the autocorrelation function. We herewith show one paradigmatic case, where a strong long-range dependence could be wrongly inferred from incomplete data analysis. We firstly apply the DFA method on the solar and volcanic forcing time series over the tropical Pacific, during the past 1000 years and the results obtained show that a statistically significant straight line fit to the fluctuation function in a log-log representation is revealed with slope higher than 0.5, which wrongly may be assumed as an indication of persistent long-range correlations in the time series. We argue that the long-range dependence cannot be concluded just from this straight line fit, but it requires the fulfilment of the two additional prerequisites i.e. reject the exponential decay of the autocorrelation function and establish the power-law scaling. In fact, the investigation of the validity of these prerequisites showed that the DFA exponent higher than 0.5 does not justify the existence of persistent long-range correlations in the temporal evolution of the solar and volcanic forcing during last millennium. In other words, we show that empirical analyses, based on these two prerequisites must not be considered as panacea for a direct proof of scaling, but only as evidence that the scaling hypothesis is plausible. We also discuss the scaling behaviour of solar and volcanic forcing data based on the Haar tool, which recently proved its ability to reliably detect the existence of the scaling effect in climate series.

Seismic Structure of Perth Basin (Australia) and surroundings from Passive Seismic Deployments

NASA Astrophysics Data System (ADS)

Issa, N.; Saygin, E.; Lumley, D. E.; Hoskin, T. E.

2016-12-01

We image the subsurface structure of Perth Basin, Western Australia and surroundings by using ambient seismic noise data from 14 seismic stations recently deployed by University of Western Australia (UWA) and other available permanent stations from Geoscience Australia seismic network and the Australian Seismometers in Schools program. Each of these 14 UWA seismic stations comprises a broadband sensor and a high fidelity 3-component 10 Hz geophone, recording in tandem at 250 Hz and 1000 Hz. The other stations used in this study are equipped with short period and broadband sensors. In addition, one shallow borehole station is operated with eight 3 component geophones at depths of between 2 and 44 m. The network is deployed to characterize natural seismicity in the basin and to try and identify any microseismic activity across Darling Fault Zone (DFZ), bounding the basin to the east. The DFZ stretches to approximately 1000 km north-south in Western Australia, and is one of the longest fault zones on the earth with a limited number of detected earthquakes. We use seismic noise cross- and auto-correlation methods to map seismic velocity perturbations across the basin and the transition from DFZ to the basin. Retrieved Green's functions are stable and show clear dispersed waveforms. Travel times of the surface wave Green's functions from noise cross-correlations are inverted with a two-step probabilistic framework to map the absolute shear wave velocities as a function of depth. The single station auto-correlations from the seismic noise yields P wave reflectivity under each station, marking the major discontinuities. Resulting images show the shear velocity perturbations across the region. We also quantify the variation of ambient seismic noise at different depths in the near surface using the geophones in the shallow borehole array.

Non-equilibrium dynamics from RPMD and CMD.

PubMed

Welsch, Ralph; Song, Kai; Shi, Qiang; Althorpe, Stuart C; Miller, Thomas F

2016-11-28

We investigate the calculation of approximate non-equilibrium quantum time correlation functions (TCFs) using two popular path-integral-based molecular dynamics methods, ring-polymer molecular dynamics (RPMD) and centroid molecular dynamics (CMD). It is shown that for the cases of a sudden vertical excitation and an initial momentum impulse, both RPMD and CMD yield non-equilibrium TCFs for linear operators that are exact for high temperatures, in the t = 0 limit, and for harmonic potentials; the subset of these conditions that are preserved for non-equilibrium TCFs of non-linear operators is also discussed. Furthermore, it is shown that for these non-equilibrium initial conditions, both methods retain the connection to Matsubara dynamics that has previously been established for equilibrium initial conditions. Comparison of non-equilibrium TCFs from RPMD and CMD to Matsubara dynamics at short times reveals the orders in time to which the methods agree. Specifically, for the position-autocorrelation function associated with sudden vertical excitation, RPMD and CMD agree with Matsubara dynamics up to O(t 4 ) and O(t 1 ), respectively; for the position-autocorrelation function associated with an initial momentum impulse, RPMD and CMD agree with Matsubara dynamics up to O(t 5 ) and O(t 2 ), respectively. Numerical tests using model potentials for a wide range of non-equilibrium initial conditions show that RPMD and CMD yield non-equilibrium TCFs with an accuracy that is comparable to that for equilibrium TCFs. RPMD is also used to investigate excited-state proton transfer in a system-bath model, and it is compared to numerically exact calculations performed using a recently developed version of the Liouville space hierarchical equation of motion approach; again, similar accuracy is observed for non-equilibrium and equilibrium initial conditions.

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.

Deciphering the adjustment between environment and life history in annuals: lessons from a geographically-explicit approach in Arabidopsis thaliana.

PubMed

Manzano-Piedras, Esperanza; Marcer, Arnald; Alonso-Blanco, Carlos; Picó, F Xavier

2014-01-01

The role that different life-history traits may have in the process of adaptation caused by divergent selection can be assessed by using extensive collections of geographically-explicit populations. This is because adaptive phenotypic variation shifts gradually across space as a result of the geographic patterns of variation in environmental selective pressures. Hence, large-scale experiments are needed to identify relevant adaptive life-history traits as well as their relationships with putative selective agents. We conducted a field experiment with 279 geo-referenced accessions of the annual plant Arabidopsis thaliana collected across a native region of its distribution range, the Iberian Peninsula. We quantified variation in life-history traits throughout the entire life cycle. We built a geographic information system to generate an environmental data set encompassing climate, vegetation and soil data. We analysed the spatial autocorrelation patterns of environmental variables and life-history traits, as well as the relationship between environmental and phenotypic data. Almost all environmental variables were significantly spatially autocorrelated. By contrast, only two life-history traits, seed weight and flowering time, exhibited significant spatial autocorrelation. Flowering time, and to a lower extent seed weight, were the life-history traits with the highest significant correlation coefficients with environmental factors, in particular with annual mean temperature. In general, individual fitness was higher for accessions with more vigorous seed germination, higher recruitment and later flowering times. Variation in flowering time mediated by temperature appears to be the main life-history trait by which A. thaliana adjusts its life history to the varying Iberian environmental conditions. The use of extensive geographically-explicit data sets obtained from field experiments represents a powerful approach to unravel adaptive patterns of variation. In a context of current global warming, geographically-explicit approaches, evaluating the match between organisms and the environments where they live, may contribute to better assess and predict the consequences of global warming.

The geographic distribution patterns of HIV-, HCV- and co-infections among drug users in a national methadone maintenance treatment program in Southwest China.

PubMed

Zhou, Yi-Biao; Liang, Song; Wang, Qi-Xing; Gong, Yu-Han; Nie, Shi-Jiao; Nan, Lei; Yang, Ai-Hui; Liao, Qiang; Song, Xiu-Xia; Jiang, Qing-Wu

2014-03-10

HIV-, HCV- and HIV/HCV co-infections among drug users have become a rapidly emerging global public health problem. In order to constrain the dual epidemics of HIV/AIDS and drug use, China has adopted a methadone maintenance treatment program (MMTP) since 2004. Studies of the geographic heterogeneity of HIV and HCV infections at a local scale are sparse, which has critical implications for future MMTP implementation and health policies covering both HIV and HCV prevention among drug users in China. This study aimed to characterize geographic patterns of HIV and HCV prevalence at the township level among drug users in a Yi Autonomous Prefecture, Southwest of China. Data on demographic and clinical characteristics of all clients in the 11 MMTP clinics of the Yi Autonomous Prefecture from March 2004 to December 2012 were collected. A GIS-based geographic analysis involving geographic autocorrelation analysis and geographic scan statistics were employed to identify the geographic distribution pattern of HIV-, HCV- and co-infections among drug users. A total of 6690 MMTP clients was analyzed. The prevalence of HIV-, HCV- and co-infections were 25.2%, 30.8%, and 10.9% respectively. There were significant global and local geographic autocorrelations for HIV-, HCV-, and co-infection. The Moran's I was 0.3015, 0.3449, and 0.3155, respectively (P < 0.0001). Both the geographic autocorrelation analysis and the geographic scan statistical analysis showed that HIV-, HCV-, and co-infections in the prefecture exhibited significant geographic clustering at the township level. The geographic distribution pattern of each infection group was different. HIV-, HCV-, and co-infections among drug users in the Yi Autonomous Prefecture all exhibited substantial geographic heterogeneity at the township level. The geographic distribution patterns of the three groups were different. These findings imply that it may be necessary to inform or invent site-specific intervention strategies to better devote currently limited resource to combat these two viruses.

Increasing Accuracy of Tissue Shear Modulus Reconstruction Using Ultrasonic Strain Tensor Measurement

NASA Astrophysics Data System (ADS)

Sumi, C.

Previously, we developed three displacement vector measurement methods, i.e., the multidimensional cross-spectrum phase gradient method (MCSPGM), the multidimensional autocorrelation method (MAM), and the multidimensional Doppler method (MDM). To increase the accuracies and stabilities of lateral and elevational displacement measurements, we also developed spatially variant, displacement component-dependent regularization. In particular, the regularization of only the lateral/elevational displacements is advantageous for the lateral unmodulated case. The demonstrated measurements of the displacement vector distributions in experiments using an inhomogeneous shear modulus agar phantom confirm that displacement-component-dependent regularization enables more stable shear modulus reconstruction. In this report, we also review our developed lateral modulation methods that use Parabolic functions, Hanning windows, and Gaussian functions in the apodization function and the optimized apodization function that realizes the designed point spread function (PSF). The modulations significantly increase the accuracy of the strain tensor measurement and shear modulus reconstruction (demonstrated using an agar phantom).

An approach for generating trajectory-based dynamics which conserves the canonical distribution in the phase space formulation of quantum mechanics. II. Thermal correlation functions.

PubMed

Liu, Jian; Miller, William H

2011-03-14

We show the exact expression of the quantum mechanical time correlation function in the phase space formulation of quantum mechanics. The trajectory-based dynamics that conserves the quantum canonical distribution-equilibrium Liouville dynamics (ELD) proposed in Paper I is then used to approximately evaluate the exact expression. It gives exact thermal correlation functions (of even nonlinear operators, i.e., nonlinear functions of position or momentum operators) in the classical, high temperature, and harmonic limits. Various methods have been presented for the implementation of ELD. Numerical tests of the ELD approach in the Wigner or Husimi phase space have been made for a harmonic oscillator and two strongly anharmonic model problems, for each potential autocorrelation functions of both linear and nonlinear operators have been calculated. It suggests ELD can be a potentially useful approach for describing quantum effects for complex systems in condense phase.

Speckle interferometry of asteroids. I - 433 Eros

NASA Technical Reports Server (NTRS)

Drummond, J. D.; Cocke, W. J.; Hege, E. K.; Strittmatter, P. A.; Lambert, J. V.

1985-01-01

Analytical expressions are derived for the semimajor and semiminor axes and orientation angle of the ellipse projected by a triaxial asteroid, and the results are applied speckle-interferometry observations of the 433 Eros asteroid. The expressions were calculated as functions of the dimensions and pole of the body and of the asterocentric position of the earth and the sun. On the basis of the analytical expressions, the dimensions of 433 Eros are obtained. The light curve from December 18, 1981 is compared to the dimensions to obtain a geometric albedo of 0.156 (+ or - 0.010). A series of two-dimensional power spectra and autocorrelation functions for 433 Eros show that it is spinning in space.

Increasing market efficiency in the stock markets

NASA Astrophysics Data System (ADS)

Yang, Jae-Suk; Kwak, Wooseop; Kaizoji, Taisei; Kim, In-Mook

2008-01-01

We study the temporal evolutions of three stock markets; Standard and Poor's 500 index, Nikkei 225 Stock Average, and the Korea Composite Stock Price Index. We observe that the probability density function of the log-return has a fat tail but the tail index has been increasing continuously in recent years. We have also found that the variance of the autocorrelation function, the scaling exponent of the standard deviation, and the statistical complexity decrease, but that the entropy density increases as time goes over time. We introduce a modified microscopic spin model and simulate the model to confirm such increasing and decreasing tendencies in statistical quantities. These findings indicate that these three stock markets are becoming more efficient.

UWB communication receiver feedback loop

DOEpatents

Spiridon, Alex; Benzel, Dave; Dowla, Farid U.; Nekoogar, Faranak; Rosenbury, Erwin T.

2007-12-04

A novel technique and structure that maximizes the extraction of information from reference pulses for UWB-TR receivers is introduced. The scheme efficiently processes an incoming signal to suppress different types of UWB as well as non-UWB interference prior to signal detection. Such a method and system adds a feedback loop mechanism to enhance the signal-to-noise ratio of reference pulses in a conventional TR receiver. Moreover, sampling the second order statistical function such as, for example, the autocorrelation function (ACF) of the received signal and matching it to the ACF samples of the original pulses for each transmitted bit provides a more robust UWB communications method and system in the presence of channel distortions.

An investigation of turbulent transport in the extreme lower atmosphere

NASA Technical Reports Server (NTRS)

Koper, C. A., Jr.; Sadeh, W. Z.

1975-01-01

A model in which the Lagrangian autocorrelation is expressed by a domain integral over a set of usual Eulerian autocorrelations acquired concurrently at all points within a turbulence box is proposed along with a method for ascertaining the statistical stationarity of turbulent velocity by creating an equivalent ensemble to investigate the flow in the extreme lower atmosphere. Simultaneous measurements of turbulent velocity on a turbulence line along the wake axis were carried out utilizing a longitudinal array of five hot-wire anemometers remotely operated. The stationarity test revealed that the turbulent velocity is approximated as a realization of a weakly self-stationary random process. Based on the Lagrangian autocorrelation it is found that: (1) large diffusion time predominated; (2) ratios of Lagrangian to Eulerian time and spatial scales were smaller than unity; and, (3) short and long diffusion time scales and diffusion spatial scales were constrained within their Eulerian counterparts.

Detection limit used for early warning in public health surveillance.

PubMed

Kobari, Tsuyoshi; Iwaki, Kazuo; Nagashima, Tomomi; Ishii, Fumiyoshi; Hayashi, Yuzuru; Yajima, Takehiko

2009-06-01

A theory of detection limit, developed in analytical chemistry, is applied to public health surveillance to detect an outbreak of national emergencies such as natural disaster and bioterrorism. In this investigation, the influenza epidemic around the Tokyo area from 2003 to 2006 is taken as a model of normal and large-scale epidemics. The detection limit of the normal epidemic is used as a threshold with a specified level of significance to identify a sign of the abnormal epidemic among the daily variation in anti-influenza drug sales at community pharmacies. While auto-correlation of data is often an obstacle to an unbiased estimator of standard deviation involved in the detection limit, the analytical theory (FUMI) can successfully treat the auto-correlation of the drug sales in the same way as the auto-correlation appearing as 1/f noise in many analytical instruments.

The influence of autocorrelation in signature extraction: An example from a geobotanical investigation of Cotter Basin, Montana

NASA Technical Reports Server (NTRS)

Labovitz, M. L.; Masuoka, E. J. (Principal Investigator)

1981-01-01

The presence of positive serial correlation (autocorrelation) in remotely sensed data results in an underestimate of the variance-covariance matrix when calculated using contiguous pixels. This underestimate produces an inflation in F statistics. For a set of Thematic Mapper Simulator data (TMS), used to test the ability to discriminate a known geobotanical anomaly from its background, the inflation in F statistics related to serial correlation is between 7 and 70 times. This means that significance tests of means of the spectral bands initially appear to suggest that the anomalous site is very different in spectral reflectance and emittance from its background sites. However, this difference often disappears and is always dramatically reduced when compared to frequency distributions of test statistics produced by the comparison of simulated training sets possessing equal means, but which are composed of autocorrelated observations.

Autocorrelation and cross-correlation in time series of homicide and attempted homicide

NASA Astrophysics Data System (ADS)

Machado Filho, A.; da Silva, M. F.; Zebende, G. F.

2014-04-01

We propose in this paper to establish the relationship between homicides and attempted homicides by a non-stationary time-series analysis. This analysis will be carried out by Detrended Fluctuation Analysis (DFA), Detrended Cross-Correlation Analysis (DCCA), and DCCA cross-correlation coefficient, ρ(n). Through this analysis we can identify a positive cross-correlation between homicides and attempted homicides. At the same time, looked at from the point of view of autocorrelation (DFA), this analysis can be more informative depending on time scale. For short scale (days), we cannot identify auto-correlations, on the scale of weeks DFA presents anti-persistent behavior, and for long time scales (n>90 days) DFA presents a persistent behavior. Finally, the application of this new type of statistical analysis proved to be efficient and, in this sense, this paper can contribute to a more accurate descriptive statistics of crime.

Evaluation of terrain complexity by autocorrelation. [geomorphology and geobotany

NASA Technical Reports Server (NTRS)

Craig, R. G.

1982-01-01

The topographic complexity of various sections of the Ozark, Appalachian, and Interior Low Plateaus, as well as of the New England, Piedmont, Blue Ridge, Ouachita, and Valley and Ridge Provinces of the Eastern United States were characterized. The variability of autocorrelation within a small area (7 1/2-ft quadrangle) to the variability at widely separated and diverse areas within the same physiographic region was compared to measure the degree of uniformity of the processes which can be expected to be encountered within a given physiographic province. The variability of autocorrelation across the eight geomorphic regions was compared and contrasted. The total study area was partitioned into subareas homogeneous in terrain complexity. The relation between the complexity measured, the geomorphic process mix implied, and the way in which geobotanical information is modified into a more or less recognizable entity is demonstrated. Sampling strategy is described.

Coherent optical processing using noncoherent light after source masking.

PubMed

Boopathi, V; Vasu, R M

1992-01-10

Coherent optical processing starting with spatially noncoherent illumination is described. Good spatial coherence is introduced in the far field by modulating a noncoherent source when masks with sharp autocorrelation are used. The far-field mutual coherence function of light is measured and it is seen that, for the masks and the source size used here, we get a fairly large area over which the mutual coherence function is high and flat. We demonstrate traditional coherent processing operations such as Fourier transformation and image deblurring when coherent light that is produced in the above fashion is used. A coherence-redundancy merit function is defined for this type of processing system. It is experimentally demonstrated that the processing system introduced here has superior blemish tolerance compared with a traditional processor that uses coherent illumination.

Leading indicators of mosquito-borne disease elimination.

PubMed

O'Regan, Suzanne M; Lillie, Jonathan W; Drake, John M

Mosquito-borne diseases contribute significantly to the global disease burden. High-profile elimination campaigns are currently underway for many parasites, e.g., Plasmodium spp., the causal agent of malaria. Sustaining momentum near the end of elimination programs is often difficult to achieve and consequently quantitative tools that enable monitoring the effectiveness of elimination activities after the initial reduction of cases has occurred are needed. Documenting progress in vector-borne disease elimination is a potentially important application for the theory of critical transitions. Non-parametric approaches that are independent of model-fitting would advance infectious disease forecasting significantly. In this paper, we consider compartmental Ross-McDonald models that are slowly forced through a critical transition through gradually deployed control measures. We derive expressions for the behavior of candidate indicators, including the autocorrelation coefficient, variance, and coefficient of variation in the number of human cases during the approach to elimination. We conducted a simulation study to test the performance of each summary statistic as an early warning system of mosquito-borne disease elimination. Variance and coefficient of variation were highly predictive of elimination but autocorrelation performed poorly as an indicator in some control contexts. Our results suggest that tipping points (bifurcations) in mosquito-borne infectious disease systems may be foreshadowed by characteristic temporal patterns of disease prevalence.

Poor environmental tracking can make extinction risk insensitive to the colour of environmental noise

PubMed Central

van de Pol, Martijn; Vindenes, Yngvild; Sæther, Bernt-Erik; Engen, Steinar; Ens, Bruno J.; Oosterbeek, Kees; Tinbergen, Joost M.

2011-01-01

The relative importance of environmental colour for extinction risk compared with other aspects of environmental noise (mean and interannual variability) is poorly understood. Such knowledge is currently relevant, as climate change can cause the mean, variability and temporal autocorrelation of environmental variables to change. Here, we predict that the extinction risk of a shorebird population increases with the colour of a key environmental variable: winter temperature. However, the effect is weak compared with the impact of changes in the mean and interannual variability of temperature. Extinction risk was largely insensitive to noise colour, because demographic rates are poor in tracking the colour of the environment. We show that three mechanisms—which probably act in many species—can cause poor environmental tracking: (i) demographic rates that depend nonlinearly on environmental variables filter the noise colour, (ii) demographic rates typically depend on several environmental signals that do not change colour synchronously, and (iii) demographic stochasticity whitens the colour of demographic rates at low population size. We argue that the common practice of assuming perfect environmental tracking may result in overemphasizing the importance of noise colour for extinction risk. Consequently, ignoring environmental autocorrelation in population viability analysis could be less problematic than generally thought. PMID:21561978

Virtual sensor models for real-time applications

NASA Astrophysics Data System (ADS)

Hirsenkorn, Nils; Hanke, Timo; Rauch, Andreas; Dehlink, Bernhard; Rasshofer, Ralph; Biebl, Erwin

2016-09-01

Increased complexity and severity of future driver assistance systems demand extensive testing and validation. As supplement to road tests, driving simulations offer various benefits. For driver assistance functions the perception of the sensors is crucial. Therefore, sensors also have to be modeled. In this contribution, a statistical data-driven sensor-model, is described. The state-space based method is capable of modeling various types behavior. In this contribution, the modeling of the position estimation of an automotive radar system, including autocorrelations, is presented. For rendering real-time capability, an efficient implementation is presented.

Event-chain algorithm for the Heisenberg model: Evidence for z≃1 dynamic scaling.

PubMed

Nishikawa, Yoshihiko; Michel, Manon; Krauth, Werner; Hukushima, Koji

2015-12-01

We apply the event-chain Monte Carlo algorithm to the three-dimensional ferromagnetic Heisenberg model. The algorithm is rejection-free and also realizes an irreversible Markov chain that satisfies global balance. The autocorrelation functions of the magnetic susceptibility and the energy indicate a dynamical critical exponent z≈1 at the critical temperature, while that of the magnetization does not measure the performance of the algorithm. We show that the event-chain Monte Carlo algorithm substantially reduces the dynamical critical exponent from the conventional value of z≃2.

Copulas and time series with long-ranged dependencies.

PubMed

Chicheportiche, Rémy; Chakraborti, Anirban

2014-04-01

We review ideas on temporal dependencies and recurrences in discrete time series from several areas of natural and social sciences. We revisit existing studies and redefine the relevant observables in the language of copulas (joint laws of the ranks). We propose that copulas provide an appropriate mathematical framework to study nonlinear time dependencies and related concepts-like aftershocks, Omori law, recurrences, and waiting times. We also critically argue, using this global approach, that previous phenomenological attempts involving only a long-ranged autocorrelation function lacked complexity in that they were essentially monoscale.

The scaling of weak field phase-only control in Markovian dynamics

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

Am-Shallem, Morag; Kosloff, Ronnie

We consider population transfer in open quantum systems, which are described by quantum dynamical semigroups (QDS). Using second order perturbation theory of the Lindblad equation, we show that it depends on a weak external field only through the field's autocorrelation function, which is phase independent. Therefore, for leading order in perturbation, QDS cannot support dependence of the population transfer on the phase properties of weak fields. We examine an example of weak-field phase-dependent population transfer, and show that the phase-dependence comes from the next order in the perturbation.

Stress as an order parameter for the glass transition

NASA Astrophysics Data System (ADS)

Visscher, P. B.; Logan, W. T.

1990-09-01

The stress tensor has been considered as a possible order parameter for the liquid-glass transition, and its autocorrelation matrix (elements of which are the integrands in the Green-Kubo formulas for bulk and shear viscosity) have been measured in simulations. However, only the k=0 spatial Fourier component has apparently been previously measured. We have measured four Fourier components of all matrix elements of the stress-stress correlation function, and we find that some of those with nonzero wave vector are significantly more persistent (slower decaying) than the k=0 component.

Single photon emission from charged excitons in CdTe/ZnTe quantum dots

NASA Astrophysics Data System (ADS)

Belyaev, K. G.; Rakhlin, M. V.; Sorokin, S. V.; Klimko, G. V.; Gronin, S. V.; Sedova, I. V.; Mukhin, I. S.; Ivanov, S. V.; Toropov, A. A.

2017-11-01

We report on micro-photoluminescence studies of individual self-organized CdTe/ZnTe quantum dots intended for single-photon-source applications in a visible spectral range. The quantum dots surface density below 1010 per cm2 was achieved by using a thermally activated regime of molecular beam epitaxy that allowed fabrication of etched mesa-structures containing only a few emitting quantum dots. The single photon emission with the autocorrelation function g(2)(0)<0.2 was detected and identified as recombination of charged excitons in the individual quantum dot.

Taylor dispersion of colloidal particles in narrow channels

NASA Astrophysics Data System (ADS)

Sané, Jimaan; Padding, Johan T.; Louis, Ard A.

2015-09-01

We use a mesoscopic particle-based simulation technique to study the classic convection-diffusion problem of Taylor dispersion for colloidal discs in confined flow. When the disc diameter becomes non-negligible compared to the diameter of the pipe, there are important corrections to the original Taylor picture. For example, the colloids can flow more rapidly than the underlying fluid, and their Taylor dispersion coefficient is decreased. For narrow pipes, there are also further hydrodynamic wall effects. The long-time tails in the velocity autocorrelation functions are altered by the Poiseuille flow.

Modified Beer-Lambert law for blood flow.

PubMed

Baker, Wesley B; Parthasarathy, Ashwin B; Busch, David R; Mesquita, Rickson C; Greenberg, Joel H; Yodh, A G

2014-11-01

We develop and validate a Modified Beer-Lambert law for blood flow based on diffuse correlation spectroscopy (DCS) measurements. The new formulation enables blood flow monitoring from temporal intensity autocorrelation function data taken at single or multiple delay-times. Consequentially, the speed of the optical blood flow measurement can be substantially increased. The scheme facilitates blood flow monitoring of highly scattering tissues in geometries wherein light propagation is diffusive or non-diffusive, and it is particularly well-suited for utilization with pressure measurement paradigms that employ differential flow signals to reduce contributions of superficial tissues.

Mid-infrared two photon absorption sensitivity of commercial detectors

NASA Astrophysics Data System (ADS)

Boiko, D. L.; Antonov, A. V.; Kuritsyn, D. I.; Yablonskiy, A. N.; Sergeev, S. M.; Orlova, E. E.; Vaks, V. V.

2017-10-01

We report on broad-band two-photon absorption (TPA) in several commercially available MIR inter-band bulk semiconductor photodetectors with the spectral cutoff in the range of 4.5-6 μm. The highest TPA responsivity of 2 × 10-5 A.mm2/W2 is measured for a nitrogen-cooled InSb photovoltaic detector. Its performance as a two-photon detector is validated by measuring the second-order interferometric autocorrelation function of a multimode quantum cascade laser emitting at the wavelength of 8 μm.

Use of high-order spectral moments in Doppler weather radar

NASA Astrophysics Data System (ADS)

di Vito, A.; Galati, G.; Veredice, A.

Three techniques to estimate the skewness and curtosis of measured precipitation spectra are evaluated. These are: (1) an extension of the pulse-pair technique, (2) fitting the autocorrelation function with a least square polynomial and differentiating it, and (3) the autoregressive spectral estimation. The third technique provides the best results but has an exceedingly large computation burden. The first technique does not supply any useful results due to the crude approximation of the derivatives of the ACF. The second technique requires further study to reduce its variance.

Relaxation and collective excitations of cluster nano-plasmas

NASA Astrophysics Data System (ADS)

Reinholz, Heidi; Röpke, Gerd; Broda, Ingrid; Morozov, Igor; Bystryi, Roman; Lavrinenko, Yaroslav

2018-01-01

Nano-plasmas produced, for example, in clusters after short-pulse laser irradiation, can show collective excitations, as derived from the time evolution of fluctuations in thermodynamic equilibrium. Molecular dynamical simulations are performed for various cluster sizes. New data are obtained for the minimum value of the stationary cluster charge. The bi-local autocorrelation function gives the spatial structure of the eigenmodes, for which energy eigenvalues are obtained. By varying the cluster size, starting from a few-particle cluster, the emergence of macroscopic properties such as collective excitations is shown.

Accounting for autocorrelation in multi-drug resistant tuberculosis predictors using a set of parsimonious orthogonal eigenvectors aggregated in geographic space.

PubMed

Jacob, Benjamin J; Krapp, Fiorella; Ponce, Mario; Gottuzzo, Eduardo; Griffith, Daniel A; Novak, Robert J

2010-05-01

Spatial autocorrelation is problematic for classical hierarchical cluster detection tests commonly used in multi-drug resistant tuberculosis (MDR-TB) analyses as considerable random error can occur. Therefore, when MDRTB clusters are spatially autocorrelated the assumption that the clusters are independently random is invalid. In this research, a product moment correlation coefficient (i.e., the Moran's coefficient) was used to quantify local spatial variation in multiple clinical and environmental predictor variables sampled in San Juan de Lurigancho, Lima, Peru. Initially, QuickBird 0.61 m data, encompassing visible bands and the near infra-red bands, were selected to synthesize images of land cover attributes of the study site. Data of residential addresses of individual patients with smear-positive MDR-TB were geocoded, prevalence rates calculated and then digitally overlaid onto the satellite data within a 2 km buffer of 31 georeferenced health centers, using a 10 m2 grid-based algorithm. Geographical information system (GIS)-gridded measurements of each health center were generated based on preliminary base maps of the georeferenced data aggregated to block groups and census tracts within each buffered area. A three-dimensional model of the study site was constructed based on a digital elevation model (DEM) to determine terrain covariates associated with the sampled MDR-TB covariates. Pearson's correlation was used to evaluate the linear relationship between the DEM and the sampled MDR-TB data. A SAS/GIS(R) module was then used to calculate univariate statistics and to perform linear and non-linear regression analyses using the sampled predictor variables. The estimates generated from a global autocorrelation analyses were then spatially decomposed into empirical orthogonal bases using a negative binomial regression with a non-homogeneous mean. Results of the DEM analyses indicated a statistically non-significant, linear relationship between georeferenced health centers and the sampled covariate elevation. The data exhibited positive spatial autocorrelation and the decomposition of Moran's coefficient into uncorrelated, orthogonal map pattern components revealed global spatial heterogeneities necessary to capture latent autocorrelation in the MDR-TB model. It was thus shown that Poisson regression analyses and spatial eigenvector mapping can elucidate the mechanics of MDR-TB transmission by prioritizing clinical and environmental-sampled predictor variables for identifying high risk populations.

User's guide to Monte Carlo methods for evaluating path integrals

NASA Astrophysics Data System (ADS)

Westbroek, Marise J. E.; King, Peter R.; Vvedensky, Dimitri D.; Dürr, Stephan

2018-04-01

We give an introduction to the calculation of path integrals on a lattice, with the quantum harmonic oscillator as an example. In addition to providing an explicit computational setup and corresponding pseudocode, we pay particular attention to the existence of autocorrelations and the calculation of reliable errors. The over-relaxation technique is presented as a way to counter strong autocorrelations. The simulation methods can be extended to compute observables for path integrals in other settings.

Testing algorithms for critical slowing down

NASA Astrophysics Data System (ADS)

Cossu, Guido; Boyle, Peter; Christ, Norman; Jung, Chulwoo; Jüttner, Andreas; Sanfilippo, Francesco

2018-03-01

We present the preliminary tests on two modifications of the Hybrid Monte Carlo (HMC) algorithm. Both algorithms are designed to travel much farther in the Hamiltonian phase space for each trajectory and reduce the autocorrelations among physical observables thus tackling the critical slowing down towards the continuum limit. We present a comparison of costs of the new algorithms with the standard HMC evolution for pure gauge fields, studying the autocorrelation times for various quantities including the topological charge.

The effects of spatial autoregressive dependencies on inference in ordinary least squares: a geometric approach

NASA Astrophysics Data System (ADS)

Smith, Tony E.; Lee, Ka Lok

2012-01-01

There is a common belief that the presence of residual spatial autocorrelation in ordinary least squares (OLS) regression leads to inflated significance levels in beta coefficients and, in particular, inflated levels relative to the more efficient spatial error model (SEM). However, our simulations show that this is not always the case. Hence, the purpose of this paper is to examine this question from a geometric viewpoint. The key idea is to characterize the OLS test statistic in terms of angle cosines and examine the geometric implications of this characterization. Our first result is to show that if the explanatory variables in the regression exhibit no spatial autocorrelation, then the distribution of test statistics for individual beta coefficients in OLS is independent of any spatial autocorrelation in the error term. Hence, inferences about betas exhibit all the optimality properties of the classic uncorrelated error case. However, a second more important series of results show that if spatial autocorrelation is present in both the dependent and explanatory variables, then the conventional wisdom is correct. In particular, even when an explanatory variable is statistically independent of the dependent variable, such joint spatial dependencies tend to produce "spurious correlation" that results in over-rejection of the null hypothesis. The underlying geometric nature of this problem is clarified by illustrative examples. The paper concludes with a brief discussion of some possible remedies for this problem.

A new radial strain and strain rate estimation method using autocorrelation for carotid artery

NASA Astrophysics Data System (ADS)

Ye, Jihui; Kim, Hoonmin; Park, Jongho; Yeo, Sunmi; Shim, Hwan; Lim, Hyungjoon; Yoo, Yangmo

2014-03-01

Atherosclerosis is a leading cause of cardiovascular disease. The early diagnosis of atherosclerosis is of clinical interest since it can prevent any adverse effects of atherosclerotic vascular diseases. In this paper, a new carotid artery radial strain estimation method based on autocorrelation is presented. In the proposed method, the strain is first estimated by the autocorrelation of two complex signals from the consecutive frames. Then, the angular phase from autocorrelation is converted to strain and strain rate and they are analyzed over time. In addition, a 2D strain image over region of interest in a carotid artery can be displayed. To evaluate the feasibility of the proposed radial strain estimation method, radiofrequency (RF) data of 408 frames in the carotid artery of a volunteer were acquired by a commercial ultrasound system equipped with a research package (V10, Samsung Medison, Korea) by using a L5-13IS linear array transducer. From in vivo carotid artery data, the mean strain estimate was -0.1372 while its minimum and maximum values were -2.961 and 0.909, respectively. Moreover, the overall strain estimates are highly correlated with the reconstructed M-mode trace. Similar results were obtained from the estimation of the strain rate change over time. These results indicate that the proposed carotid artery radial strain estimation method is useful for assessing the arterial wall's stiffness noninvasively without increasing the computational complexity.

Two Point Autocorrelation Analysis of Auger Highest Energy Events Backtracked in Galactic Magnetic Field

NASA Astrophysics Data System (ADS)

Petrov, Yevgeniy

2009-10-01

Searches for sources of the highest-energy cosmic rays traditionally have included looking for clusters of event arrival directions on the sky. The smallest cluster is a pair of events falling within some angular window. In contrast to the standard two point (2-pt) autocorrelation analysis, this work takes into account influence of the galactic magnetic field (GMF). The highest energy events, those above 50EeV, collected by the surface detector of the Pierre Auger Observatory between January 1, 2004 and May 31, 2009 are used in the analysis. Having assumed protons as primaries, events are backtracked through BSS/S, BSS/A, ASS/S and ASS/A versions of Harari-Mollerach-Roulet (HMR) model of the GMF. For each version of the model, a 2-pt autocorrelation analysis is applied to the backtracked events and to 105 isotropic Monte Carlo realizations weighted by the Auger exposure. Scans in energy, separation angular window and different model parameters reveal clustering at different angular scales. Small angle clustering at 2-3 deg is particularly interesting and it is compared between different field scenarios. The strength of the autocorrelation signal at those angular scales differs between BSS and ASS versions of the HMR model. The BSS versions of the model tend to defocus protons as they arrive to Earth whereas for the ASS, in contrary, it is more likely to focus them.

Partitioning the impact of environment and spatial structure on alpha and beta components of taxonomic, functional, and phylogenetic diversity in European ants.

PubMed

Arnan, Xavier; Cerdá, Xim; Retana, Javier

2015-01-01

We analyze the relative contribution of environmental and spatial variables to the alpha and beta components of taxonomic (TD), phylogenetic (PD), and functional (FD) diversity in ant communities found along different climate and anthropogenic disturbance gradients across western and central Europe, in order to assess the mechanisms structuring ant biodiversity. To this aim we calculated alpha and beta TD, PD, and FD for 349 ant communities, which included a total of 155 ant species; we examined 10 functional traits and phylogenetic relatedness. Variation partitioning was used to examine how much variation in ant diversity was explained by environmental and spatial variables. Autocorrelation in diversity measures and each trait's phylogenetic signal were also analyzed. We found strong autocorrelation in diversity measures. Both environmental and spatial variables significantly contributed to variation in TD, PD, and FD at both alpha and beta scales; spatial structure had the larger influence. The different facets of diversity showed similar patterns along environmental gradients. Environment explained a much larger percentage of variation in FD than in TD or PD. All traits demonstrated strong phylogenetic signals. Our results indicate that environmental filtering and dispersal limitations structure all types of diversity in ant communities. Strong dispersal limitations appear to have led to clustering of TD, PD, and FD in western and central Europe, probably because different historical and evolutionary processes generated different pools of species. Remarkably, these three facets of diversity showed parallel patterns along environmental gradients. Trait-mediated species sorting and niche conservatism appear to structure ant diversity, as evidenced by the fact that more variation was explained for FD and that all traits had strong phylogenetic signals. Since environmental variables explained much more variation in FD than in PD, functional diversity should be a better indicator of community assembly processes than phylogenetic diversity.

Removal of a hazardous heavy metal from aqueous solution using functionalized graphene and boron nitride nanosheets: Insights from simulations.

PubMed

Azamat, Jafar; Sattary, Batoul Shirforush; Khataee, Alireza; Joo, Sang Woo

2015-09-01

A computer simulation was performed to investigate the removal of Zn(2+) as a heavy metal from aqueous solution using the functionalized pore of a graphene nanosheet and boron nitride nanosheet (BNNS). The simulated systems were comprised of a graphene nanosheet or BNNS with a functionalized pore containing an aqueous ionic solution of zinc chloride. In order to remove heavy metal from an aqueous solution using the functionalized pore of a graphene nanosheet and BNNS, an external voltage was applied along the z-axis of the simulated box. For the selective removal of zinc ions, the pores of graphene and BNNS were functionalized by passivating each atom at the pore edge with appropriate atoms. For complete analysis systems, we calculated the potential of the mean force of ions, the radial distribution function of ion-water, the residence time of ions, the hydrogen bond, and the autocorrelation function of the hydrogen bond. Copyright © 2015 Elsevier Inc. All rights reserved.

Broadband distortion modeling in Lyman-α forest BAO fitting

DOE PAGES

Blomqvist, Michael; Kirkby, David; Bautista, Julian E.; ...

2015-11-23

Recently, the Lyman-α absorption observed in the spectra of high-redshift quasars has been used as a tracer of large-scale structure by means of the three-dimensional Lyman-α forest auto-correlation function at redshift z≃ 2.3, but the need to fit the quasar continuum in every absorption spectrum introduces a broadband distortion that is difficult to correct and causes a systematic error for measuring any broadband properties. Here, we describe a k-space model for this broadband distortion based on a multiplicative correction to the power spectrum of the transmitted flux fraction that suppresses power on scales corresponding to the typical length of amore » Lyman-α forest spectrum. In implementing the distortion model in fits for the baryon acoustic oscillation (BAO) peak position in the Lyman-α forest auto-correlation, we find that the fitting method recovers the input values of the linear bias parameter b F and the redshift-space distortion parameter β F for mock data sets with a systematic error of less than 0.5%. Applied to the auto-correlation measured for BOSS Data Release 11, our method improves on the previous treatment of broadband distortions in BAO fitting by providing a better fit to the data using fewer parameters and reducing the statistical errors on βF and the combination b F(1+β F) by more than a factor of seven. The measured values at redshift z=2.3 are βF=1.39 +0.11 +0.24 +0.38 -0.10 -0.19 -0.28 and bF(1+βF)=-0.374 +0.007 +0.013 +0.020 -0.007 -0.014 -0.022 (1σ, 2σ and 3σ statistical errors). Our fitting software and the input files needed to reproduce our main results are publicly available.« less

Broadband distortion modeling in Lyman-α forest BAO fitting

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

Blomqvist, Michael; Kirkby, David; Margala, Daniel, E-mail: cblomqvi@uci.edu, E-mail: dkirkby@uci.edu, E-mail: dmargala@uci.edu

2015-11-01

In recent years, the Lyman-α absorption observed in the spectra of high-redshift quasars has been used as a tracer of large-scale structure by means of the three-dimensional Lyman-α forest auto-correlation function at redshift z≅ 2.3, but the need to fit the quasar continuum in every absorption spectrum introduces a broadband distortion that is difficult to correct and causes a systematic error for measuring any broadband properties. We describe a k-space model for this broadband distortion based on a multiplicative correction to the power spectrum of the transmitted flux fraction that suppresses power on scales corresponding to the typical length of amore » Lyman-α forest spectrum. Implementing the distortion model in fits for the baryon acoustic oscillation (BAO) peak position in the Lyman-α forest auto-correlation, we find that the fitting method recovers the input values of the linear bias parameter b{sub F} and the redshift-space distortion parameter β{sub F} for mock data sets with a systematic error of less than 0.5%. Applied to the auto-correlation measured for BOSS Data Release 11, our method improves on the previous treatment of broadband distortions in BAO fitting by providing a better fit to the data using fewer parameters and reducing the statistical errors on β{sub F} and the combination b{sub F}(1+β{sub F}) by more than a factor of seven. The measured values at redshift z=2.3 are β{sub F}=1.39{sup +0.11 +0.24 +0.38}{sub −0.10 −0.19 −0.28} and b{sub F}(1+β{sub F})=−0.374{sup +0.007 +0.013 +0.020}{sub −0.007 −0.014 −0.022} (1σ, 2σ and 3σ statistical errors). Our fitting software and the input files needed to reproduce our main results are publicly available.« less

Autocorrelation analysis of the infrared spectra of synthetic and biogenic carbonates along the calcite-dolomite join

NASA Astrophysics Data System (ADS)

Jenkins, David M.; Holmes, Zachary F.; Ishida, Kiyotaka; Manuel, Phillip D.

2018-01-01

Autocorrelation analysis of infrared spectra can provide insights on the strain energy associated with cation substitutions along a solid-solution compositional join which to date has been applied primarily to silicate minerals. In this study, the method is applied to carbonates synthesized at 10 mol% increments along the calcite-dolomite (CaCO3-CaMg(CO3)2) join in the range of 1000-1150 °C and 0.6-2.5 GPa for the purpose of determining how the band broadening in both the far- and mid-infrared ranges, as represented by the autocorrelation parameter δΔCorr, compares with the existing enthalpy of mixing data for this join. It was found that the carbonate internal vibration ν2 (out-of-plane bending) in the mid-infrared range, and the sum of the three internal vibration modes ν4 + ν2 + ν3 most closely matched the enthalpy of mixing data for the synthetic carbonates. Autocorrelation analysis of a series of biogenic carbonates in the mid-infrared range showed only a systematic variation for the ν2 band. Using the biogenic carbonate with the lowest Mg content for reference, the trend in δΔCorr for biogenic carbonates shows a steady increase with increasing Mg content suggesting a steady increase in solubility with Mg content. The results from this study indicate that autocorrelation analysis of carbonates in the mid-infrared range provides an independent and reliable assessment of the crystallographic strain energy of carbonates. In particular, inorganic carbonates in the range of 0-17 mol% MgCO3 experience a minimum in strain energy and a corresponding minimum in the enthalpy of mixing, whereas biogenic carbonates show a steady increase in strain energy with increasing MgCO3 content. In the event of increasing ocean acidification, biogenic carbonates in the range of 0-17 mol% MgCO3 will dissolve more readily than the compositionally equivalent inorganic carbonates.

A Predictive Risk Model for A(H7N9) Human Infections Based on Spatial-Temporal Autocorrelation and Risk Factors: China, 2013–2014

PubMed Central

Dong, Wen; Yang, Kun; Xu, Quan-Li; Yang, Yu-Lian

2015-01-01

This study investigated the spatial distribution, spatial autocorrelation, temporal cluster, spatial-temporal autocorrelation and probable risk factors of H7N9 outbreaks in humans from March 2013 to December 2014 in China. The results showed that the epidemic spread with significant spatial-temporal autocorrelation. In order to describe the spatial-temporal autocorrelation of H7N9, an improved model was developed by introducing a spatial-temporal factor in this paper. Logistic regression analyses were utilized to investigate the risk factors associated with their distribution, and nine risk factors were significantly associated with the occurrence of A(H7N9) human infections: the spatial-temporal factor φ (OR = 2546669.382, p < 0.001), migration route (OR = 0.993, p < 0.01), river (OR = 0.861, p < 0.001), lake(OR = 0.992, p < 0.001), road (OR = 0.906, p < 0.001), railway (OR = 0.980, p < 0.001), temperature (OR = 1.170, p < 0.01), precipitation (OR = 0.615, p < 0.001) and relative humidity (OR = 1.337, p < 0.001). The improved model obtained a better prediction performance and a higher fitting accuracy than the traditional model: in the improved model 90.1% (91/101) of the cases during February 2014 occurred in the high risk areas (the predictive risk > 0.70) of the predictive risk map, whereas 44.6% (45/101) of which overlaid on the high risk areas (the predictive risk > 0.70) for the traditional model, and the fitting accuracy of the improved model was 91.6% which was superior to the traditional model (86.1%). The predictive risk map generated based on the improved model revealed that the east and southeast of China were the high risk areas of A(H7N9) human infections in February 2014. These results provided baseline data for the control and prevention of future human infections. PMID:26633446

Autocorrelation analysis of the infrared spectra of synthetic and biogenic carbonates along the calcite-dolomite join

NASA Astrophysics Data System (ADS)

Jenkins, David M.; Holmes, Zachary F.; Ishida, Kiyotaka; Manuel, Phillip D.

2018-06-01

Autocorrelation analysis of infrared spectra can provide insights on the strain energy associated with cation substitutions along a solid-solution compositional join which to date has been applied primarily to silicate minerals. In this study, the method is applied to carbonates synthesized at 10 mol% increments along the calcite-dolomite (CaCO3-CaMg(CO3)2) join in the range of 1000-1150 °C and 0.6-2.5 GPa for the purpose of determining how the band broadening in both the far- and mid-infrared ranges, as represented by the autocorrelation parameter δΔCorr, compares with the existing enthalpy of mixing data for this join. It was found that the carbonate internal vibration ν2 (out-of-plane bending) in the mid-infrared range, and the sum of the three internal vibration modes ν4 + ν2 + ν3 most closely matched the enthalpy of mixing data for the synthetic carbonates. Autocorrelation analysis of a series of biogenic carbonates in the mid-infrared range showed only a systematic variation for the ν2 band. Using the biogenic carbonate with the lowest Mg content for reference, the trend in δΔCorr for biogenic carbonates shows a steady increase with increasing Mg content suggesting a steady increase in solubility with Mg content. The results from this study indicate that autocorrelation analysis of carbonates in the mid-infrared range provides an independent and reliable assessment of the crystallographic strain energy of carbonates. In particular, inorganic carbonates in the range of 0-17 mol% MgCO3 experience a minimum in strain energy and a corresponding minimum in the enthalpy of mixing, whereas biogenic carbonates show a steady increase in strain energy with increasing MgCO3 content. In the event of increasing ocean acidification, biogenic carbonates in the range of 0-17 mol% MgCO3 will dissolve more readily than the compositionally equivalent inorganic carbonates.

The use of copula functions for predictive analysis of correlations between extreme storm tides

NASA Astrophysics Data System (ADS)

Domino, Krzysztof; Błachowicz, Tomasz; Ciupak, Maurycy

2014-11-01

In this paper we present a method used in quantitative description of weakly predictable hydrological, extreme events at inland sea. Investigations for correlations between variations of individual measuring points, employing combined statistical methods, were carried out. As a main tool for this analysis we used a two-dimensional copula function sensitive for correlated extreme effects. Additionally, a new proposed methodology, based on Detrended Fluctuations Analysis (DFA) and Anomalous Diffusion (AD), was used for the prediction of negative and positive auto-correlations and associated optimum choice of copula functions. As a practical example we analysed maximum storm tides data recorded at five spatially separated places at the Baltic Sea. For the analysis we used Gumbel, Clayton, and Frank copula functions and introduced the reversed Clayton copula. The application of our research model is associated with modelling the risk of high storm tides and possible storm flooding.

On the linearity of tracer bias around voids

NASA Astrophysics Data System (ADS)

Pollina, Giorgia; Hamaus, Nico; Dolag, Klaus; Weller, Jochen; Baldi, Marco; Moscardini, Lauro

2017-07-01

The large-scale structure of the Universe can be observed only via luminous tracers of the dark matter. However, the clustering statistics of tracers are biased and depend on various properties, such as their host-halo mass and assembly history. On very large scales, this tracer bias results in a constant offset in the clustering amplitude, known as linear bias. Towards smaller non-linear scales, this is no longer the case and tracer bias becomes a complicated function of scale and time. We focus on tracer bias centred on cosmic voids, I.e. depressions of the density field that spatially dominate the Universe. We consider three types of tracers: galaxies, galaxy clusters and active galactic nuclei, extracted from the hydrodynamical simulation Magneticum Pathfinder. In contrast to common clustering statistics that focus on auto-correlations of tracers, we find that void-tracer cross-correlations are successfully described by a linear bias relation. The tracer-density profile of voids can thus be related to their matter-density profile by a single number. We show that it coincides with the linear tracer bias extracted from the large-scale auto-correlation function and expectations from theory, if sufficiently large voids are considered. For smaller voids we observe a shift towards higher values. This has important consequences on cosmological parameter inference, as the problem of unknown tracer bias is alleviated up to a constant number. The smallest scales in existing data sets become accessible to simpler models, providing numerous modes of the density field that have been disregarded so far, but may help to further reduce statistical errors in constraining cosmology.

Spatial statistical network models for stream and river temperature in New England, USA

NASA Astrophysics Data System (ADS)

Detenbeck, Naomi E.; Morrison, Alisa C.; Abele, Ralph W.; Kopp, Darin A.

2016-08-01

Watershed managers are challenged by the need for predictive temperature models with sufficient accuracy and geographic breadth for practical use. We described thermal regimes of New England rivers and streams based on a reduced set of metrics for the May-September growing season (July or August median temperature, diurnal rate of change, and magnitude and timing of growing season maximum) chosen through principal component analysis of 78 candidate metrics. We then developed and assessed spatial statistical models for each of these metrics, incorporating spatial autocorrelation based on both distance along the flow network and Euclidean distance between points. Calculation of spatial autocorrelation based on travel or retention time in place of network distance yielded tighter-fitting Torgegrams with less scatter but did not improve overall model prediction accuracy. We predicted monthly median July or August stream temperatures as a function of median air temperature, estimated urban heat island effect, shaded solar radiation, main channel slope, watershed storage (percent lake and wetland area), percent coarse-grained surficial deposits, and presence or maximum depth of a lake immediately upstream, with an overall root-mean-square prediction error of 1.4 and 1.5°C, respectively. Growing season maximum water temperature varied as a function of air temperature, local channel slope, shaded August solar radiation, imperviousness, and watershed storage. Predictive models for July or August daily range, maximum daily rate of change, and timing of growing season maximum were statistically significant but explained a much lower proportion of variance than the above models (5-14% of total).

Assessment of sacrococcygeal pressure ulcers using diffuse correlation spectroscopy

NASA Astrophysics Data System (ADS)

Diaz, David; Lafontant, Alec; Neidrauer, Michael; Weingarten, Michael S.; DiMaria-Ghalili, Rose Ann; Fried, Guy W.; Rece, Julianne; Lewin, Peter A.; Zubkov, Leonid

2016-03-01

Microcirculation is essential for proper supply of oxygen and nutritive substances to the biological tissue and the removal of waste products of metabolism. The determination of microcirculatory blood flow (mBF) is therefore of substantial interest to clinicians for assessing tissue health; particularly in pressure ulceration and suspected deep tissue injury. The goal of this pilot clinical study was to assess deep-tissue pressure ulceration by non-invasively measuring mBF using Diffuse Correlation Spectroscopy (DCS). DCS provides information about the flow of red blood cells in the capillary network by measuring the temporal autocorrelation function of scattering light intensity. A novel optical probe was developed in order to obtain measurements under the load of the subject's body as pressure is applied (ischemia) and then released (reperfusion) on sacrococcygeal tissue in a hospital bed. Prior to loading measurements, baseline readings of the sacral region were obtained by measuring the subjects in a side-lying position. DCS measurements from the sacral region of twenty healthy volunteers have been compared to those of two patients who initially had similar non-blanchable redness. The temporal autocorrelation function of scattering light intensity of the patient whose redness later disappeared was similar to that of the average healthy subject. The second patient, whose redness developed into an advanced pressure ulcer two weeks later, had a substantial decrease in blood flow while under the loading position compared to healthy subjects. Preliminary results suggest the developed system may potentially predict whether non-blanchable redness will manifest itself as advanced ulceration or dissipate over time.

Generalized Langevin dynamics of a nanoparticle using a finite element approach: Thermostating with correlated noise

NASA Astrophysics Data System (ADS)

Uma, B.; Swaminathan, T. N.; Ayyaswamy, P. S.; Eckmann, D. M.; Radhakrishnan, R.

2011-09-01

A direct numerical simulation (DNS) procedure is employed to study the thermal motion of a nanoparticle in an incompressible Newtonian stationary fluid medium with the generalized Langevin approach. We consider both the Markovian (white noise) and non-Markovian (Ornstein-Uhlenbeck noise and Mittag-Leffler noise) processes. Initial locations of the particle are at various distances from the bounding wall to delineate wall effects. At thermal equilibrium, the numerical results are validated by comparing the calculated translational and rotational temperatures of the particle with those obtained from the equipartition theorem. The nature of the hydrodynamic interactions is verified by comparing the velocity autocorrelation functions and mean square displacements with analytical results. Numerical predictions of wall interactions with the particle in terms of mean square displacements are compared with analytical results. In the non-Markovian Langevin approach, an appropriate choice of colored noise is required to satisfy the power-law decay in the velocity autocorrelation function at long times. The results obtained by using non-Markovian Mittag-Leffler noise simultaneously satisfy the equipartition theorem and the long-time behavior of the hydrodynamic correlations for a range of memory correlation times. The Ornstein-Uhlenbeck process does not provide the appropriate hydrodynamic correlations. Comparing our DNS results to the solution of an one-dimensional generalized Langevin equation, it is observed that where the thermostat adheres to the equipartition theorem, the characteristic memory time in the noise is consistent with the inherent time scale of the memory kernel. The performance of the thermostat with respect to equilibrium and dynamic properties for various noise schemes is discussed.

Modified Beer-Lambert law for blood flow

NASA Astrophysics Data System (ADS)

Baker, Wesley B.; Parthasarathy, Ashwin B.; Busch, David R.; Mesquita, Rickson C.; Greenberg, Joel H.; Yodh, A. G.

2015-03-01

The modified Beer-Lambert law is among the most widely used approaches for analysis of near-infrared spectroscopy (NIRS) reflectance signals for measurements of tissue blood volume and oxygenation. Briefly, the modified Beer-Lambert paradigm is a scheme to derive changes in tissue optical properties based on continuous-wave (CW) diffuse optical intensity measurements. In its simplest form, the scheme relates differential changes in light transmission (in any geometry) to differential changes in tissue absorption. Here we extend this paradigm to the measurement of tissue blood flow by diffuse correlation spectroscopy (DCS). In the new approach, differential changes of the intensity temporal auto-correlation function at a single delay-time are related to differential changes in blood flow. The key theoretical results for measurement of blood flow changes in any tissue geometry are derived, and we demonstrate the new method to monitor cerebral blood flow in a pig under conditions wherein the semi-infinite geometry approximation is fairly good. Specifically, the drug dinitrophenol was injected in the pig to induce a gradual 200% increase in cerebral blood flow, as measured with MRI velocity flow mapping and by DCS. The modified Beer-Lambert law for flow accurately recovered these flow changes using only a single delay-time in the intensity auto-correlation function curve. The scheme offers increased DCS measurement speed of blood flow. Further, the same techniques using the modified Beer-Lambert law to filter out superficial tissue effects in NIRS measurements of deep tissues can be applied to the DCS modified Beer-Lambert law for blood flow monitoring of deep tissues.

Correction of motion artifacts and serial correlations for real-time functional near-infrared spectroscopy

PubMed Central

Barker, Jeffrey W.; Rosso, Andrea L.; Sparto, Patrick J.; Huppert, Theodore J.

2016-01-01

Abstract. Functional near-infrared spectroscopy (fNIRS) is a relatively low-cost, portable, noninvasive neuroimaging technique for measuring task-evoked hemodynamic changes in the brain. Because fNIRS can be applied to a wide range of populations, such as children or infants, and under a variety of study conditions, including those involving physical movement, gait, or balance, fNIRS data are often confounded by motion artifacts. Furthermore, the high sampling rate of fNIRS leads to high temporal autocorrelation due to systemic physiology. These two factors can reduce the sensitivity and specificity of detecting hemodynamic changes. In a previous work, we showed that these factors could be mitigated by autoregressive-based prewhitening followed by the application of an iterative reweighted least squares algorithm offline. This current work extends these same ideas to real-time analysis of brain signals by modifying the linear Kalman filter, resulting in an algorithm for online estimation that is robust to systemic physiology and motion artifacts. We evaluated the performance of the proposed method via simulations of evoked hemodynamics that were added to experimental resting-state data, which provided realistic fNIRS noise. Last, we applied the method post hoc to data from a standing balance task. Overall, the new method showed good agreement with the analogous offline algorithm, in which both methods outperformed ordinary least squares methods. PMID:27226974

A novel approach for introducing cloud spatial structure into cloud radiative transfer parameterizations

NASA Astrophysics Data System (ADS)

Huang, Dong; Liu, Yangang

2014-12-01

Subgrid-scale variability is one of the main reasons why parameterizations are needed in large-scale models. Although some parameterizations started to address the issue of subgrid variability by introducing a subgrid probability distribution function for relevant quantities, the spatial structure has been typically ignored and thus the subgrid-scale interactions cannot be accounted for physically. Here we present a new statistical-physics-like approach whereby the spatial autocorrelation function can be used to physically capture the net effects of subgrid cloud interaction with radiation. The new approach is able to faithfully reproduce the Monte Carlo 3D simulation results with several orders less computational cost, allowing for more realistic representation of cloud radiation interactions in large-scale models.

Coherent light depolarization by multiple scattering media and tissues: some fundamentals and applications

NASA Astrophysics Data System (ADS)

Zimnyakov, Dmitry A.; Tuchin, Valery V.; Yodh, Arjun G.; Mishin, Alexey A.; Peretochkin, Igor S.

1998-04-01

Relationships between decorrelation and depolarization of coherent light scattered by disordered media are examined by using the conception of the photon paths distribution functions. Analysis of behavior of the autocorrelation functions of the scattered field fluctuations and their polarization properties allows us to introduce generalized parameter of scattering media such as specific correlation time. Determination of specific correlation time has been carried out for phantom scattering media (water suspensions of polystyrene spheres). Results of statistical, correlation and polarization analysis of static and dynamic speckle patterns carried out in the experiments with human sclera with artificially controlled optical transmittance are presented. Some possibilities of applications of such polarization- correlation technique for monitoring and visualization of non- single scattering tissue structures are discussed.

Fluctuation correlation models for receptor immobilization

NASA Astrophysics Data System (ADS)

Fourcade, B.

2017-12-01

Nanoscale dynamics with cycles of receptor diffusion and immobilization by cell-external-or-internal factors is a key process in living cell adhesion phenomena at the origin of a plethora of signal transduction pathways. Motivated by modern correlation microscopy approaches, the receptor correlation functions in physical models based on diffusion-influenced reaction is studied. Using analytical and stochastic modeling, this paper focuses on the hybrid regime where diffusion and reaction are not truly separable. The time receptor autocorrelation functions are shown to be indexed by different time scales and their asymptotic expansions are given. Stochastic simulations show that this analysis can be extended to situations with a small number of molecules. It is also demonstrated that this analysis applies when receptor immobilization is coupled to environmental noise.

Numerical tests of local scale invariance in ageing q-state Potts models

NASA Astrophysics Data System (ADS)

Lorenz, E.; Janke, W.

2007-01-01

Much effort has been spent over the last years to achieve a coherent theoretical description of ageing as a non-linear dynamics process. Long supposed to be a consequence of the slow dynamics of glassy systems only, ageing phenomena could also be identified in the phase-ordering kinetics of simple ferromagnets. As a phenomenological approach Henkel et al. developed a group of local scale transformations under which two-time autocorrelation and response functions should transform covariantly. This work is to extend previous numerical tests of the predicted scaling functions for the Ising model by Monte Carlo simulations of two-dimensional q-state Potts models with q=3 and 8, which, in equilibrium, undergo temperature-driven phase transitions of second and first order, respectively.

Burst and inter-burst duration statistics as empirical test of long-range memory in the financial markets

NASA Astrophysics Data System (ADS)

Gontis, V.; Kononovicius, A.

2017-10-01

We address the problem of long-range memory in the financial markets. There are two conceptually different ways to reproduce power-law decay of auto-correlation function: using fractional Brownian motion as well as non-linear stochastic differential equations. In this contribution we address this problem by analyzing empirical return and trading activity time series from the Forex. From the empirical time series we obtain probability density functions of burst and inter-burst duration. Our analysis reveals that the power-law exponents of the obtained probability density functions are close to 3 / 2, which is a characteristic feature of the one-dimensional stochastic processes. This is in a good agreement with earlier proposed model of absolute return based on the non-linear stochastic differential equations derived from the agent-based herding model.

Systematic errors in transport calculations of shear viscosity using the Green-Kubo formalism

NASA Astrophysics Data System (ADS)

Rose, J. B.; Torres-Rincon, J. M.; Oliinychenko, D.; Schäfer, A.; Petersen, H.

2018-05-01

The purpose of this study is to provide a reproducible framework in the use of the Green-Kubo formalism to extract transport coefficients. More specifically, in the case of shear viscosity, we investigate the limitations and technical details of fitting the auto-correlation function to a decaying exponential. This fitting procedure is found to be applicable for systems interacting both through constant and energy-dependent cross-sections, although this is only true for sufficiently dilute systems in the latter case. We find that the optimal fit technique consists in simultaneously fixing the intercept of the correlation function and use a fitting interval constrained by the relative error on the correlation function. The formalism is then applied to the full hadron gas, for which we obtain the shear viscosity to entropy ratio.

Generalized Green's function molecular dynamics for canonical ensemble simulations

NASA Astrophysics Data System (ADS)

Coluci, V. R.; Dantas, S. O.; Tewary, V. K.

2018-05-01

The need of small integration time steps (˜1 fs) in conventional molecular dynamics simulations is an important issue that inhibits the study of physical, chemical, and biological systems in real timescales. Additionally, to simulate those systems in contact with a thermal bath, thermostating techniques are usually applied. In this work, we generalize the Green's function molecular dynamics technique to allow simulations within the canonical ensemble. By applying this technique to one-dimensional systems, we were able to correctly describe important thermodynamic properties such as the temperature fluctuations, the temperature distribution, and the velocity autocorrelation function. We show that the proposed technique also allows the use of time steps one order of magnitude larger than those typically used in conventional molecular dynamics simulations. We expect that this technique can be used in long-timescale molecular dynamics simulations.

Robust estimation of fetal heart rate from US Doppler signals

NASA Astrophysics Data System (ADS)

Voicu, Iulian; Girault, Jean-Marc; Roussel, Catherine; Decock, Aliette; Kouame, Denis

2010-01-01

Introduction: In utero, Monitoring of fetal wellbeing or suffering is today an open challenge, due to the high number of clinical parameters to be considered. An automatic monitoring of fetal activity, dedicated for quantifying fetal wellbeing, becomes necessary. For this purpose and in a view to supply an alternative for the Manning test, we used an ultrasound multitransducer multigate Doppler system. One important issue (and first step in our investigation) is the accurate estimation of fetal heart rate (FHR). An estimation of the FHR is obtained by evaluating the autocorrelation function of the Doppler signals for ills and healthiness foetus. However, this estimator is not enough robust since about 20% of FHR are not detected in comparison to a reference system. These non detections are principally due to the fact that the Doppler signal generated by the fetal moving is strongly disturbed by the presence of others several Doppler sources (mother' s moving, pseudo breathing, etc.). By modifying the existing method (autocorrelation method) and by proposing new time and frequency estimators used in the audio' s domain, we reduce to 5% the probability of non-detection of the fetal heart rate. These results are really encouraging and they enable us to plan the use of automatic classification techniques in order to discriminate between healthy and in suffering foetus.

Modeling Seasonal Influenza Transmission and Its Association with Climate Factors in Thailand Using Time-Series and ARIMAX Analyses.

PubMed

Chadsuthi, Sudarat; Iamsirithaworn, Sopon; Triampo, Wannapong; Modchang, Charin

2015-01-01

Influenza is a worldwide respiratory infectious disease that easily spreads from one person to another. Previous research has found that the influenza transmission process is often associated with climate variables. In this study, we used autocorrelation and partial autocorrelation plots to determine the appropriate autoregressive integrated moving average (ARIMA) model for influenza transmission in the central and southern regions of Thailand. The relationships between reported influenza cases and the climate data, such as the amount of rainfall, average temperature, average maximum relative humidity, average minimum relative humidity, and average relative humidity, were evaluated using cross-correlation function. Based on the available data of suspected influenza cases and climate variables, the most appropriate ARIMA(X) model for each region was obtained. We found that the average temperature correlated with influenza cases in both central and southern regions, but average minimum relative humidity played an important role only in the southern region. The ARIMAX model that includes the average temperature with a 4-month lag and the minimum relative humidity with a 2-month lag is the appropriate model for the central region, whereas including the minimum relative humidity with a 4-month lag results in the best model for the southern region.

An Evaluation of Fractal Surface Measurement Methods for Characterizing Landscape Complexity from Remote-Sensing Imagery

NASA Technical Reports Server (NTRS)

Lam, Nina Siu-Ngan; Qiu, Hong-Lie; Quattrochi, Dale A.; Emerson, Charles W.; Arnold, James E. (Technical Monitor)

2001-01-01

The rapid increase in digital data volumes from new and existing sensors necessitates the need for efficient analytical tools for extracting information. We developed an integrated software package called ICAMS (Image Characterization and Modeling System) to provide specialized spatial analytical functions for interpreting remote sensing data. This paper evaluates the three fractal dimension measurement methods: isarithm, variogram, and triangular prism, along with the spatial autocorrelation measurement methods Moran's I and Geary's C, that have been implemented in ICAMS. A modified triangular prism method was proposed and implemented. Results from analyzing 25 simulated surfaces having known fractal dimensions show that both the isarithm and triangular prism methods can accurately measure a range of fractal surfaces. The triangular prism method is most accurate at estimating the fractal dimension of higher spatial complexity, but it is sensitive to contrast stretching. The variogram method is a comparatively poor estimator for all of the surfaces, particularly those with higher fractal dimensions. Similar to the fractal techniques, the spatial autocorrelation techniques are found to be useful to measure complex images but not images with low dimensionality. These fractal measurement methods can be applied directly to unclassified images and could serve as a tool for change detection and data mining.

A heterogeneous artificial stock market model can benefit people against another financial crisis

PubMed Central

2018-01-01

This paper presents results of an artificial stock market and tries to make it more consistent with the statistical features of real stock data. Based on the SFI-ASM, a novel model is proposed to make agents more close to the real world. Agents are divided into four kinds in terms of different learning speeds, strategy-sizes, utility functions, and level of intelligence; and a crucial parameter has been found to ensure system stability. So, some parameters are appended to make the model which contains zero-intelligent and less-intelligent agents run steadily. Moreover, considering real stock markets change violently due to the financial crisis; the real stock markets are divided into two segments, before the financial crisis and after it. The optimal modified model before the financial crisis fails to replicate the statistical features of the real market after the financial crisis. Then, the optimal model after the financial crisis is shown. The experiments indicate that the optimal model after the financial crisis is able to replicate several of real market phenomena, including the first-order autocorrelation, kurtosis, standard deviation of yield series and first-order autocorrelation of yield square. We point out that there is a structural change in stock markets after the financial crisis, which can benefit people forecast the financial crisis. PMID:29912893

The Chaotic Light Curves of Accreting Black Holes

NASA Technical Reports Server (NTRS)

Kazanas, Demosthenes

2007-01-01

We present model light curves for accreting Black Hole Candidates (BHC) based on a recently developed model of these sources. According to this model, the observed light curves and aperiodic variability of BHC are due to a series of soft photon injections at random (Poisson) intervals and the stochastic nature of the Comptonization process in converting these soft photons to the observed high energy radiation. The additional assumption of our model is that the Comptonization process takes place in an extended but non-uniform hot plasma corona surrounding the compact object. We compute the corresponding Power Spectral Densities (PSD), autocorrelation functions, time skewness of the light curves and time lags between the light curves of the sources at different photon energies and compare our results to observation. Our model reproduces the observed light curves well, in that it provides good fits to their overall morphology (as manifest by the autocorrelation and time skewness) and also to their PSDs and time lags, by producing most of the variability power at time scales 2 a few seconds, while at the same time allowing for shots of a few msec in duration, in accordance with observation. We suggest that refinement of this type of model along with spectral and phase lag information can be used to probe the structure of this class of high energy sources.

Superthermal photon bunching in terms of simple probability distributions

NASA Astrophysics Data System (ADS)

Lettau, T.; Leymann, H. A. M.; Melcher, B.; Wiersig, J.

2018-05-01

We analyze the second-order photon autocorrelation function g(2 ) with respect to the photon probability distribution and discuss the generic features of a distribution that results in superthermal photon bunching [g(2 )(0 ) >2 ]. Superthermal photon bunching has been reported for a number of optical microcavity systems that exhibit processes such as superradiance or mode competition. We show that a superthermal photon number distribution cannot be constructed from the principle of maximum entropy if only the intensity and the second-order autocorrelation are given. However, for bimodal systems, an unbiased superthermal distribution can be constructed from second-order correlations and the intensities alone. Our findings suggest modeling superthermal single-mode distributions by a mixture of a thermal and a lasinglike state and thus reveal a generic mechanism in the photon probability distribution responsible for creating superthermal photon bunching. We relate our general considerations to a physical system, i.e., a (single-emitter) bimodal laser, and show that its statistics can be approximated and understood within our proposed model. Furthermore, the excellent agreement of the statistics of the bimodal laser and our model reveals that the bimodal laser is an ideal source of bunched photons, in the sense that it can generate statistics that contain no other features but the superthermal bunching.

Optical binding of two microparticles levitated in vacuum

NASA Astrophysics Data System (ADS)

Arita, Yoshihiko; Wright, Ewan M.; Dholakia, Kishan

2017-04-01

Optical binding refers to an optically mediated inter-particle interaction that creates new equilibrium positions for closely spaced particles [1-5]. Optical binding of mesoscopic particles levitated in vacuum can pave the way towards the realisation of a large scale quantum bound array in cavity-optomechanics [6-9]. Recently we have demonstrated trapping and rotation of two mesoscopic particles in vacuum using a spatial-light-modulator-based approach to trap more than one particle, induce controlled rotation of individual particles, and mediate interparticle separation [10]. By trapping and rotating two vaterite particles, we observe intensity modulation of the scattered light at the sum and difference frequencies with respect to the individual rotation rates. This first demonstration of optical interference between two microparticles in vacuum has lead to a platform to explore optical binding. Here we demonstrate for the first time optically bound two microparticles mediated by light scattering in vacuum. We investigate autocorrelations between the two normal modes of oscillation, which are determined by the centre-of-mass and the relative positions of the two-particle system. In situ determination of the optical restoring force acting on the bound particles are based on measurement of the oscillation frequencies of the autocorrelation functions of the two normal modes, thereby providing a powerful and original platform to explore multiparticle entanglement in cavity-optomechanics.

A heterogeneous artificial stock market model can benefit people against another financial crisis.

PubMed

Yang, Haijun; Chen, Shuheng

2018-01-01

This paper presents results of an artificial stock market and tries to make it more consistent with the statistical features of real stock data. Based on the SFI-ASM, a novel model is proposed to make agents more close to the real world. Agents are divided into four kinds in terms of different learning speeds, strategy-sizes, utility functions, and level of intelligence; and a crucial parameter has been found to ensure system stability. So, some parameters are appended to make the model which contains zero-intelligent and less-intelligent agents run steadily. Moreover, considering real stock markets change violently due to the financial crisis; the real stock markets are divided into two segments, before the financial crisis and after it. The optimal modified model before the financial crisis fails to replicate the statistical features of the real market after the financial crisis. Then, the optimal model after the financial crisis is shown. The experiments indicate that the optimal model after the financial crisis is able to replicate several of real market phenomena, including the first-order autocorrelation, kurtosis, standard deviation of yield series and first-order autocorrelation of yield square. We point out that there is a structural change in stock markets after the financial crisis, which can benefit people forecast the financial crisis.

Establishing the diffuse correlation spectroscopy signal relationship with blood flow.

PubMed

Boas, David A; Sakadžić, Sava; Selb, Juliette; Farzam, Parisa; Franceschini, Maria Angela; Carp, Stefan A

2016-07-01

Diffuse correlation spectroscopy (DCS) measurements of blood flow rely on the sensitivity of the temporal autocorrelation function of diffusively scattered light to red blood cell (RBC) mean square displacement (MSD). For RBCs flowing with convective velocity [Formula: see text], the autocorrelation is expected to decay exponentially with [Formula: see text], where [Formula: see text] is the delay time. RBCs also experience shear-induced diffusion with a diffusion coefficient [Formula: see text] and an MSD of [Formula: see text]. Surprisingly, experimental data primarily reflect diffusive behavior. To provide quantitative estimates of the relative contributions of convective and diffusive movements, we performed Monte Carlo simulations of light scattering through tissue of varying vessel densities. We assumed laminar vessel flow profiles and accounted for shear-induced diffusion effects. In agreement with experimental data, we found that diffusive motion dominates the correlation decay for typical DCS measurement parameters. Furthermore, our model offers a quantitative relationship between the RBC diffusion coefficient and absolute tissue blood flow. We thus offer, for the first time, theoretical support for the empirically accepted ability of the DCS blood flow index ([Formula: see text]) to quantify tissue perfusion. We find [Formula: see text] to be linearly proportional to blood flow, but with a proportionality modulated by the hemoglobin concentration and the average blood vessel diameter.

Use of autocorrelation scanning in DNA copy number analysis.

PubMed

Zhang, Liangcai; Zhang, Li

2013-11-01

Data quality is a critical issue in the analyses of DNA copy number alterations obtained from microarrays. It is commonly assumed that copy number alteration data can be modeled as piecewise constant and the measurement errors of different probes are independent. However, these assumptions do not always hold in practice. In some published datasets, we find that measurement errors are highly correlated between probes that interrogate nearby genomic loci, and the piecewise-constant model does not fit the data well. The correlated errors cause problems in downstream analysis, leading to a large number of DNA segments falsely identified as having copy number gains and losses. We developed a simple tool, called autocorrelation scanning profile, to assess the dependence of measurement error between neighboring probes. Autocorrelation scanning profile can be used to check data quality and refine the analysis of DNA copy number data, which we demonstrate in some typical datasets. lzhangli@mdanderson.org. Supplementary data are available at Bioinformatics online.

Environmental variability uncovers disruptive effects of species' interactions on population dynamics.

PubMed

Gudmundson, Sara; Eklöf, Anna; Wennergren, Uno

2015-08-07

How species respond to changes in environmental variability has been shown for single species, but the question remains whether these results are transferable to species when incorporated in ecological communities. Here, we address this issue by analysing the same species exposed to a range of environmental variabilities when (i) isolated or (ii) embedded in a food web. We find that all species in food webs exposed to temporally uncorrelated environments (white noise) show the same type of dynamics as isolated species, whereas species in food webs exposed to positively autocorrelated environments (red noise) can respond completely differently compared with isolated species. This is owing to species following their equilibrium densities in a positively autocorrelated environment that in turn enables species-species interactions to come into play. Our results give new insights into species' response to environmental variation. They especially highlight the importance of considering both species' interactions and environmental autocorrelation when studying population dynamics in a fluctuating environment. © 2015 The Author(s).

Environmental variability uncovers disruptive effects of species' interactions on population dynamics

PubMed Central

Gudmundson, Sara; Eklöf, Anna; Wennergren, Uno

2015-01-01

How species respond to changes in environmental variability has been shown for single species, but the question remains whether these results are transferable to species when incorporated in ecological communities. Here, we address this issue by analysing the same species exposed to a range of environmental variabilities when (i) isolated or (ii) embedded in a food web. We find that all species in food webs exposed to temporally uncorrelated environments (white noise) show the same type of dynamics as isolated species, whereas species in food webs exposed to positively autocorrelated environments (red noise) can respond completely differently compared with isolated species. This is owing to species following their equilibrium densities in a positively autocorrelated environment that in turn enables species–species interactions to come into play. Our results give new insights into species' response to environmental variation. They especially highlight the importance of considering both species' interactions and environmental autocorrelation when studying population dynamics in a fluctuating environment. PMID:26224705

Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage

USGS Publications Warehouse

Mattsson, Brady J.; Zipkin, Elise F.; Gardner, Beth; Blank, Peter J.; Sauer, John R.; Royle, J. Andrew

2013-01-01

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

Map LineUps: Effects of spatial structure on graphical inference.

PubMed

Beecham, Roger; Dykes, Jason; Meulemans, Wouter; Slingsby, Aidan; Turkay, Cagatay; Wood, Jo

2017-01-01

Fundamental to the effective use of visualization as an analytic and descriptive tool is the assurance that presenting data visually provides the capability of making inferences from what we see. This paper explores two related approaches to quantifying the confidence we may have in making visual inferences from mapped geospatial data. We adapt Wickham et al.'s 'Visual Line-up' method as a direct analogy with Null Hypothesis Significance Testing (NHST) and propose a new approach for generating more credible spatial null hypotheses. Rather than using as a spatial null hypothesis the unrealistic assumption of complete spatial randomness, we propose spatially autocorrelated simulations as alternative nulls. We conduct a set of crowdsourced experiments (n=361) to determine the just noticeable difference (JND) between pairs of choropleth maps of geographic units controlling for spatial autocorrelation (Moran's I statistic) and geometric configuration (variance in spatial unit area). Results indicate that people's abilities to perceive differences in spatial autocorrelation vary with baseline autocorrelation structure and the geometric configuration of geographic units. These results allow us, for the first time, to construct a visual equivalent of statistical power for geospatial data. Our JND results add to those provided in recent years by Klippel et al. (2011), Harrison et al. (2014) and Kay & Heer (2015) for correlation visualization. Importantly, they provide an empirical basis for an improved construction of visual line-ups for maps and the development of theory to inform geospatial tests of graphical inference.

Explaining local-scale species distributions: relative contributions of spatial autocorrelation and landscape heterogeneity for an avian assemblage.

PubMed

Mattsson, Brady J; Zipkin, Elise F; Gardner, Beth; Blank, Peter J; Sauer, John R; Royle, J Andrew

2013-01-01

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition.

Explaining Local-Scale Species Distributions: Relative Contributions of Spatial Autocorrelation and Landscape Heterogeneity for an Avian Assemblage

PubMed Central

Mattsson, Brady J.; Zipkin, Elise F.; Gardner, Beth; Blank, Peter J.; Sauer, John R.; Royle, J. Andrew

2013-01-01

Understanding interactions between mobile species distributions and landcover characteristics remains an outstanding challenge in ecology. Multiple factors could explain species distributions including endogenous evolutionary traits leading to conspecific clustering and endogenous habitat features that support life history requirements. Birds are a useful taxon for examining hypotheses about the relative importance of these factors among species in a community. We developed a hierarchical Bayes approach to model the relationships between bird species occupancy and local landcover variables accounting for spatial autocorrelation, species similarities, and partial observability. We fit alternative occupancy models to detections of 90 bird species observed during repeat visits to 316 point-counts forming a 400-m grid throughout the Patuxent Wildlife Research Refuge in Maryland, USA. Models with landcover variables performed significantly better than our autologistic and null models, supporting the hypothesis that local landcover heterogeneity is important as an exogenous driver for species distributions. Conspecific clustering alone was a comparatively poor descriptor of local community composition, but there was evidence for spatial autocorrelation in all species. Considerable uncertainty remains whether landcover combined with spatial autocorrelation is most parsimonious for describing bird species distributions at a local scale. Spatial structuring may be weaker at intermediate scales within which dispersal is less frequent, information flows are localized, and landcover types become spatially diversified and therefore exhibit little aggregation. Examining such hypotheses across species assemblages contributes to our understanding of community-level associations with conspecifics and landscape composition. PMID:23393564