Multifractal detrended fluctuation analysis of sheep livestock prices in origin

NASA Astrophysics Data System (ADS)

Pavón-Domínguez, P.; Serrano, S.; Jiménez-Hornero, F. J.; Jiménez-Hornero, J. E.; Gutiérrez de Ravé, E.; Ariza-Villaverde, A. B.

2013-10-01

The multifractal detrended fluctuation analysis (MF-DFA) is used to verify whether or not the returns of time series of prices paid to farmers in original markets can be described by the multifractal approach. By way of example, 5 weekly time series of prices of different breeds, slaughter weight and market differentiation from 2000 to 2012 are analyzed. Results obtained from the multifractal parameters and multifractal spectra show that the price series of livestock products are of a multifractal nature. The Hurst exponent shows that these time series are stationary signals, some of which exhibit long memory (Merino milk-fed in Seville and Segureña paschal in Jaen), short memory (Merino paschal in Cordoba and Segureña milk-fed in Jaen) or even are close to an uncorrelated signals (Merino paschal in Seville). MF-DFA is able to discern the different underlying dynamics that play an important role in different types of sheep livestock markets, such as degree and source of multifractality. In addition, the main source of multifractality of these time series is due to the broadness of the probability function, instead of the long-range correlation properties between small and large fluctuations, which play a clearly secondary role.

Automated classification of Permanent Scatterers time-series based on statistical characterization tests

NASA Astrophysics Data System (ADS)

Berti, Matteo; Corsini, Alessandro; Franceschini, Silvia; Iannacone, Jean Pascal

2013-04-01

The application of space borne synthetic aperture radar interferometry has progressed, over the last two decades, from the pioneer use of single interferograms for analyzing changes on the earth's surface to the development of advanced multi-interferogram techniques to analyze any sort of natural phenomena which involves movements of the ground. The success of multi-interferograms techniques in the analysis of natural hazards such as landslides and subsidence is widely documented in the scientific literature and demonstrated by the consensus among the end-users. Despite the great potential of this technique, radar interpretation of slope movements is generally based on the sole analysis of average displacement velocities, while the information embraced in multi interferogram time series is often overlooked if not completely neglected. The underuse of PS time series is probably due to the detrimental effect of residual atmospheric errors, which make the PS time series characterized by erratic, irregular fluctuations often difficult to interpret, and also to the difficulty of performing a visual, supervised analysis of the time series for a large dataset. In this work is we present a procedure for automatic classification of PS time series based on a series of statistical characterization tests. The procedure allows to classify the time series into six distinctive target trends (0=uncorrelated; 1=linear; 2=quadratic; 3=bilinear; 4=discontinuous without constant velocity; 5=discontinuous with change in velocity) and retrieve for each trend a series of descriptive parameters which can be efficiently used to characterize the temporal changes of ground motion. The classification algorithms were developed and tested using an ENVISAT datasets available in the frame of EPRS-E project (Extraordinary Plan of Environmental Remote Sensing) of the Italian Ministry of Environment (track "Modena", Northern Apennines). This dataset was generated using standard processing, then the time series are typically affected by a significant noise to signal ratio. The results of the analysis show that even with such a rough-quality dataset, our automated classification procedure can greatly improve radar interpretation of mass movements. In general, uncorrelated PS (type 0) are concentrated in flat areas such as fluvial terraces and valley bottoms, and along stable watershed divides; linear PS (type 1) are mainly located on slopes (both inside or outside mapped landslides) or near the edge of scarps or steep slopes; non-linear PS (types 2 to 5) typically fall inside landslide deposits or in the surrounding areas. The spatial distribution of classified PS allows to detect deformation phenomena not visible by considering the average velocity alone, and provide important information on the temporal evolution of the phenomena such as acceleration, deceleration, seasonal fluctuations, abrupt or continuous changes of the displacement rate. Based on these encouraging results we integrated all the classification algorithms into a Graphical User Interface (called PSTime) which is freely available as a standalone application.

Self-affinity in the dengue fever time series

NASA Astrophysics Data System (ADS)

Azevedo, S. M.; Saba, H.; Miranda, J. G. V.; Filho, A. S. Nascimento; Moret, M. A.

2016-06-01

Dengue is a complex public health problem that is common in tropical and subtropical regions. This disease has risen substantially in the last three decades, and the physical symptoms depict the self-affine behavior of the occurrences of reported dengue cases in Bahia, Brazil. This study uses detrended fluctuation analysis (DFA) to verify the scale behavior in a time series of dengue cases and to evaluate the long-range correlations that are characterized by the power law α exponent for different cities in Bahia, Brazil. The scaling exponent (α) presents different long-range correlations, i.e. uncorrelated, anti-persistent, persistent and diffusive behaviors. The long-range correlations highlight the complex behavior of the time series of this disease. The findings show that there are two distinct types of scale behavior. In the first behavior, the time series presents a persistent α exponent for a one-month period. For large periods, the time series signal approaches subdiffusive behavior. The hypothesis of the long-range correlations in the time series of the occurrences of reported dengue cases was validated. The observed self-affinity is useful as a forecasting tool for future periods through extrapolation of the α exponent behavior. This complex system has a higher predictability in a relatively short time (approximately one month), and it suggests a new tool in epidemiological control strategies. However, predictions for large periods using DFA are hidden by the subdiffusive behavior.

Studies in astronomical time series analysis. IV - Modeling chaotic and random processes with linear filters

NASA Technical Reports Server (NTRS)

Scargle, Jeffrey D.

1990-01-01

While chaos arises only in nonlinear systems, standard linear time series models are nevertheless useful for analyzing data from chaotic processes. This paper introduces such a model, the chaotic moving average. This time-domain model is based on the theorem that any chaotic process can be represented as the convolution of a linear filter with an uncorrelated process called the chaotic innovation. A technique, minimum phase-volume deconvolution, is introduced to estimate the filter and innovation. The algorithm measures the quality of a model using the volume covered by the phase-portrait of the innovation process. Experiments on synthetic data demonstrate that the algorithm accurately recovers the parameters of simple chaotic processes. Though tailored for chaos, the algorithm can detect both chaos and randomness, distinguish them from each other, and separate them if both are present. It can also recover nonminimum-delay pulse shapes in non-Gaussian processes, both random and chaotic.

Dynamical glucometry: Use of multiscale entropy analysis in diabetes

NASA Astrophysics Data System (ADS)

Costa, Madalena D.; Henriques, Teresa; Munshi, Medha N.; Segal, Alissa R.; Goldberger, Ary L.

2014-09-01

Diabetes mellitus (DM) is one of the world's most prevalent medical conditions. Contemporary management focuses on lowering mean blood glucose values toward a normal range, but largely ignores the dynamics of glucose fluctuations. We probed analyte time series obtained from continuous glucose monitor (CGM) sensors. We show that the fluctuations in CGM values sampled every 5 min are not uncorrelated noise. Next, using multiscale entropy analysis, we quantified the complexity of the temporal structure of the CGM time series from a group of elderly subjects with type 2 DM and age-matched controls. We further probed the structure of these CGM time series using detrended fluctuation analysis. Our findings indicate that the dynamics of glucose fluctuations from control subjects are more complex than those of subjects with type 2 DM over time scales ranging from about 5 min to 5 h. These findings support consideration of a new framework, dynamical glucometry, to guide mechanistic research and to help assess and compare therapeutic interventions, which should enhance complexity of glucose fluctuations and not just lower mean and variance of blood glucose levels.

Global and system-specific resting-state fMRI fluctuations are uncorrelated: principal component analysis reveals anti-correlated networks.

PubMed

Carbonell, Felix; Bellec, Pierre; Shmuel, Amir

2011-01-01

The influence of the global average signal (GAS) on functional-magnetic resonance imaging (fMRI)-based resting-state functional connectivity is a matter of ongoing debate. The global average fluctuations increase the correlation between functional systems beyond the correlation that reflects their specific functional connectivity. Hence, removal of the GAS is a common practice for facilitating the observation of network-specific functional connectivity. This strategy relies on the implicit assumption of a linear-additive model according to which global fluctuations, irrespective of their origin, and network-specific fluctuations are super-positioned. However, removal of the GAS introduces spurious negative correlations between functional systems, bringing into question the validity of previous findings of negative correlations between fluctuations in the default-mode and the task-positive networks. Here we present an alternative method for estimating global fluctuations, immune to the complications associated with the GAS. Principal components analysis was applied to resting-state fMRI time-series. A global-signal effect estimator was defined as the principal component (PC) that correlated best with the GAS. The mean correlation coefficient between our proposed PC-based global effect estimator and the GAS was 0.97±0.05, demonstrating that our estimator successfully approximated the GAS. In 66 out of 68 runs, the PC that showed the highest correlation with the GAS was the first PC. Since PCs are orthogonal, our method provides an estimator of the global fluctuations, which is uncorrelated to the remaining, network-specific fluctuations. Moreover, unlike the regression of the GAS, the regression of the PC-based global effect estimator does not introduce spurious anti-correlations beyond the decrease in seed-based correlation values allowed by the assumed additive model. After regressing this PC-based estimator out of the original time-series, we observed robust anti-correlations between resting-state fluctuations in the default-mode and the task-positive networks. We conclude that resting-state global fluctuations and network-specific fluctuations are uncorrelated, supporting a Resting-State Linear-Additive Model. In addition, we conclude that the network-specific resting-state fluctuations of the default-mode and task-positive networks show artifact-free anti-correlations.

Gaussian mixture clustering and imputation of microarray data.

PubMed

Ouyang, Ming; Welsh, William J; Georgopoulos, Panos

2004-04-12

In microarray experiments, missing entries arise from blemishes on the chips. In large-scale studies, virtually every chip contains some missing entries and more than 90% of the genes are affected. Many analysis methods require a full set of data. Either those genes with missing entries are excluded, or the missing entries are filled with estimates prior to the analyses. This study compares methods of missing value estimation. Two evaluation metrics of imputation accuracy are employed. First, the root mean squared error measures the difference between the true values and the imputed values. Second, the number of mis-clustered genes measures the difference between clustering with true values and that with imputed values; it examines the bias introduced by imputation to clustering. The Gaussian mixture clustering with model averaging imputation is superior to all other imputation methods, according to both evaluation metrics, on both time-series (correlated) and non-time series (uncorrelated) data sets.

Intermittent electron density and temperature fluctuations and associated fluxes in the Alcator C-Mod scrape-off layer

NASA Astrophysics Data System (ADS)

Kube, R.; Garcia, O. E.; Theodorsen, A.; Brunner, D.; Kuang, A. Q.; LaBombard, B.; Terry, J. L.

2018-06-01

The Alcator C-Mod mirror Langmuir probe system has been used to sample data time series of fluctuating plasma parameters in the outboard mid-plane far scrape-off layer. We present a statistical analysis of one second long time series of electron density, temperature, radial electric drift velocity and the corresponding particle and electron heat fluxes. These are sampled during stationary plasma conditions in an ohmically heated, lower single null diverted discharge. The electron density and temperature are strongly correlated and feature fluctuation statistics similar to the ion saturation current. Both electron density and temperature time series are dominated by intermittent, large-amplitude burst with an exponential distribution of both burst amplitudes and waiting times between them. The characteristic time scale of the large-amplitude bursts is approximately 15 μ {{s}}. Large-amplitude velocity fluctuations feature a slightly faster characteristic time scale and appear at a faster rate than electron density and temperature fluctuations. Describing these time series as a superposition of uncorrelated exponential pulses, we find that probability distribution functions, power spectral densities as well as auto-correlation functions of the data time series agree well with predictions from the stochastic model. The electron particle and heat fluxes present large-amplitude fluctuations. For this low-density plasma, the radial electron heat flux is dominated by convection, that is, correlations of fluctuations in the electron density and radial velocity. Hot and dense blobs contribute only a minute fraction of the total fluctuation driven heat flux.

Detection and Characterization of Ground Displacement Sources from Variational Bayesian Independent Component Analysis of GPS Time Series

NASA Astrophysics Data System (ADS)

Gualandi, A.; Serpelloni, E.; Belardinelli, M. E.

2014-12-01

A critical point in the analysis of ground displacements time series is the development of data driven methods that allow to discern and characterize the different sources that generate the observed displacements. A widely used multivariate statistical technique is the Principal Component Analysis (PCA), which allows to reduce the dimensionality of the data space maintaining most of the variance of the dataset explained. It reproduces the original data using a limited number of Principal Components, but it also shows some deficiencies. Indeed, PCA does not perform well in finding the solution to the so-called Blind Source Separation (BSS) problem, i.e. in recovering and separating the original sources that generated the observed data. This is mainly due to the assumptions on which PCA relies: it looks for a new Euclidean space where the projected data are uncorrelated. Usually, the uncorrelation condition is not strong enough and it has been proven that the BSS problem can be tackled imposing on the components to be independent. The Independent Component Analysis (ICA) is, in fact, another popular technique adopted to approach this problem, and it can be used in all those fields where PCA is also applied. An ICA approach enables us to explain the time series imposing a fewer number of constraints on the model, and to reveal anomalies in the data such as transient signals. However, the independence condition is not easy to impose, and it is often necessary to introduce some approximations. To work around this problem, we use a variational bayesian ICA (vbICA) method, which models the probability density function (pdf) of each source signal using a mix of Gaussian distributions. This technique allows for more flexibility in the description of the pdf of the sources, giving a more reliable estimate of them. Here we present the application of the vbICA technique to GPS position time series. First, we use vbICA on synthetic data that simulate a seismic cycle (interseismic + coseismic + postseismic + seasonal + noise), and study the ability of the algorithm to recover the original (known) sources of deformation. Secondly, we apply vbICA to different tectonically active scenarios, such as earthquakes in central and northern Italy, as well as the study of slow slip events in Cascadia.

Neural Networks for Signal Processing 5. Proceedings of the 1995 IEEE Workshop (5th) Held in Cambridge, MA on 31 Aug-2 Sep 95.

DTIC Science & Technology

1995-01-01

expensive) option is to track the mean and variance of each input feature instead of the min and max. Then a sigmoid is the natural choice for a mapping...Scaling Down: Applying Large Vocabulary Hybrid HMM-MLP Methods to Telephone Recognition of Digits and Natural Numbers 223 Kristine Ma, Nelson Morgan...1 if Yt > 1 Yt + I if Yt < 0 where ct is uncorrelated Gaussian noise with a variance of o-2 = 0.01. Figure 2 (left) shows the time series. Figure 2

Effective degree Markov-chain approach for discrete-time epidemic processes on uncorrelated networks.

PubMed

Cai, Chao-Ran; Wu, Zhi-Xi; Guan, Jian-Yue

2014-11-01

Recently, Gómez et al. proposed a microscopic Markov-chain approach (MMCA) [S. Gómez, J. Gómez-Gardeñes, Y. Moreno, and A. Arenas, Phys. Rev. E 84, 036105 (2011)PLEEE81539-375510.1103/PhysRevE.84.036105] to the discrete-time susceptible-infected-susceptible (SIS) epidemic process and found that the epidemic prevalence obtained by this approach agrees well with that by simulations. However, we found that the approach cannot be straightforwardly extended to a susceptible-infected-recovered (SIR) epidemic process (due to its irreversible property), and the epidemic prevalences obtained by MMCA and Monte Carlo simulations do not match well when the infection probability is just slightly above the epidemic threshold. In this contribution we extend the effective degree Markov-chain approach, proposed for analyzing continuous-time epidemic processes [J. Lindquist, J. Ma, P. Driessche, and F. Willeboordse, J. Math. Biol. 62, 143 (2011)JMBLAJ0303-681210.1007/s00285-010-0331-2], to address discrete-time binary-state (SIS) or three-state (SIR) epidemic processes on uncorrelated complex networks. It is shown that the final epidemic size as well as the time series of infected individuals obtained from this approach agree very well with those by Monte Carlo simulations. Our results are robust to the change of different parameters, including the total population size, the infection probability, the recovery probability, the average degree, and the degree distribution of the underlying networks.

Evaluation of physiologic complexity in time series using generalized sample entropy and surrogate data analysis

NASA Astrophysics Data System (ADS)

Eduardo Virgilio Silva, Luiz; Otavio Murta, Luiz

2012-12-01

Complexity in time series is an intriguing feature of living dynamical systems, with potential use for identification of system state. Although various methods have been proposed for measuring physiologic complexity, uncorrelated time series are often assigned high values of complexity, errouneously classifying them as a complex physiological signals. Here, we propose and discuss a method for complex system analysis based on generalized statistical formalism and surrogate time series. Sample entropy (SampEn) was rewritten inspired in Tsallis generalized entropy, as function of q parameter (qSampEn). qSDiff curves were calculated, which consist of differences between original and surrogate series qSampEn. We evaluated qSDiff for 125 real heart rate variability (HRV) dynamics, divided into groups of 70 healthy, 44 congestive heart failure (CHF), and 11 atrial fibrillation (AF) subjects, and for simulated series of stochastic and chaotic process. The evaluations showed that, for nonperiodic signals, qSDiff curves have a maximum point (qSDiffmax) for q ≠1. Values of q where the maximum point occurs and where qSDiff is zero were also evaluated. Only qSDiffmax values were capable of distinguish HRV groups (p-values 5.10×10-3, 1.11×10-7, and 5.50×10-7 for healthy vs. CHF, healthy vs. AF, and CHF vs. AF, respectively), consistently with the concept of physiologic complexity, and suggests a potential use for chaotic system analysis.

Global and System-Specific Resting-State fMRI Fluctuations Are Uncorrelated: Principal Component Analysis Reveals Anti-Correlated Networks

PubMed Central

Carbonell, Felix; Bellec, Pierre

2011-01-01

Abstract The influence of the global average signal (GAS) on functional-magnetic resonance imaging (fMRI)–based resting-state functional connectivity is a matter of ongoing debate. The global average fluctuations increase the correlation between functional systems beyond the correlation that reflects their specific functional connectivity. Hence, removal of the GAS is a common practice for facilitating the observation of network-specific functional connectivity. This strategy relies on the implicit assumption of a linear-additive model according to which global fluctuations, irrespective of their origin, and network-specific fluctuations are super-positioned. However, removal of the GAS introduces spurious negative correlations between functional systems, bringing into question the validity of previous findings of negative correlations between fluctuations in the default-mode and the task-positive networks. Here we present an alternative method for estimating global fluctuations, immune to the complications associated with the GAS. Principal components analysis was applied to resting-state fMRI time-series. A global-signal effect estimator was defined as the principal component (PC) that correlated best with the GAS. The mean correlation coefficient between our proposed PC-based global effect estimator and the GAS was 0.97±0.05, demonstrating that our estimator successfully approximated the GAS. In 66 out of 68 runs, the PC that showed the highest correlation with the GAS was the first PC. Since PCs are orthogonal, our method provides an estimator of the global fluctuations, which is uncorrelated to the remaining, network-specific fluctuations. Moreover, unlike the regression of the GAS, the regression of the PC-based global effect estimator does not introduce spurious anti-correlations beyond the decrease in seed-based correlation values allowed by the assumed additive model. After regressing this PC-based estimator out of the original time-series, we observed robust anti-correlations between resting-state fluctuations in the default-mode and the task-positive networks. We conclude that resting-state global fluctuations and network-specific fluctuations are uncorrelated, supporting a Resting-State Linear-Additive Model. In addition, we conclude that the network-specific resting-state fluctuations of the default-mode and task-positive networks show artifact-free anti-correlations. PMID:22444074

Linear and quadratic models of point process systems: contributions of patterned input to output.

PubMed

Lindsay, K A; Rosenberg, J R

2012-08-01

In the 1880's Volterra characterised a nonlinear system using a functional series connecting continuous input and continuous output. Norbert Wiener, in the 1940's, circumvented problems associated with the application of Volterra series to physical problems by deriving from it a new series of terms that are mutually uncorrelated with respect to Gaussian processes. Subsequently, Brillinger, in the 1970's, introduced a point-process analogue of Volterra's series connecting point-process inputs to the instantaneous rate of point-process output. We derive here a new series from this analogue in which its terms are mutually uncorrelated with respect to Poisson processes. This new series expresses how patterned input in a spike train, represented by third-order cross-cumulants, is converted into the instantaneous rate of an output point-process. Given experimental records of suitable duration, the contribution of arbitrary patterned input to an output process can, in principle, be determined. Solutions for linear and quadratic point-process models with one and two inputs and a single output are investigated. Our theoretical results are applied to isolated muscle spindle data in which the spike trains from the primary and secondary endings from the same muscle spindle are recorded in response to stimulation of one and then two static fusimotor axons in the absence and presence of a random length change imposed on the parent muscle. For a fixed mean rate of input spikes, the analysis of the experimental data makes explicit which patterns of two input spikes contribute to an output spike. Copyright © 2012 Elsevier Ltd. All rights reserved.

Evolution of record-breaking high and low monthly mean temperatures

NASA Astrophysics Data System (ADS)

Anderson, A. L.; Kostinski, A. B.

2011-12-01

We examine the ratio of record-breaking highs to record-breaking lows with respect to extent of time-series for monthly mean temperatures within the continental United States (1900-2006) and ask the following question. How are record-breaking high and low surface temperatures in the United States affected by time period? We find that the ratio of record-breaking highs to lows in 2006 increases as the time-series extend further into the past. For example: in 2006, the ratio of record-breaking highs to record-breaking lows is ≈ 13 : 1 with 1950 as the first year and ≈ 25 : 1 with 1900 as the first year; both ratios are an order of magnitude greater than 3-σ for stationary simulations. We also find record-breaking events are more sensitive to trends in time-series of monthly averages than time-series of corresponding daily values. When we consider the ratio as it evolves with respect to a fixed start year, we find it is strongly correlated with the ensemble mean. Correlation coefficients are 0.76 and 0.82 for 1900-2006 and 1950-2006 respectively; 3-σ = 0.3 for pairs of uncorrelated stationary time-series. We find similar values for globally distributed time-series: 0.87 and 0.92 for 1900-2006 and 1950-2006 respectively. However, the ratios evolve differently: global ratios increase throughout (1920-2006) while continental United States ratios decrease from about 1940 to 1970. (Based on Anderson and Kostinski (2011), Evolution and distribution of record-breaking high and low monthly mean temperatures. Journal of Applied Meteorology and Climatology. doi: 10.1175/JAMC-D-10-05025.1)

Effects of Correlated and Uncorrelated Gamma Rays on Neutron Multiplicity Counting

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

Cowles, Christian C.; Behling, Richard S.; Imel, George R.

Neutron multiplicity counting relies on time correlation between neutron events to assay the fissile mass, (α,n) to spontaneous fission neutron ratio, and neutron self-multiplication of samples. Gamma-ray sensitive neutron multiplicity counters may misidentify gamma rays as neutrons and therefore miscalculate sample characteristics. Time correlated and uncorrelated gamma-ray-like signals were added into gamma-ray free neutron multiplicity counter data to examine the effects of gamma ray signals being misidentified as neutron signals on assaying sample characteristics. Multiplicity counter measurements with and without gamma-ray-like signals were compared to determine the assay error associated with gamma-ray-like signals at various gamma-ray and neutron rates. Correlatedmore » and uncorrelated gamma-ray signals each produced consistent but different measurement errors. Correlated gamma-ray signals most strongly led to fissile mass overestimates, whereas uncorrelated gamma-ray signals most strongly lead to (α,n) neutron overestimates. Gamma-ray sensitive neutron multiplicity counters may be able to account for the effects of gamma-rays on measurements to mitigate measurement uncertainties.« less

Detection and Correction of Step Discontinuities in Kepler Flux Time Series

NASA Technical Reports Server (NTRS)

Kolodziejczak, J. J.; Morris, R. L.

2011-01-01

PDC 8.0 includes an implementation of a new algorithm to detect and correct step discontinuities appearing in roughly one of every 20 stellar light curves during a given quarter. The majority of such discontinuities are believed to result from high-energy particles (either cosmic or solar in origin) striking the photometer and causing permanent local changes (typically -0.5%) in quantum efficiency, though a partial exponential recovery is often observed [1]. Since these features, dubbed sudden pixel sensitivity dropouts (SPSDs), are uncorrelated across targets they cannot be properly accounted for by the current detrending algorithm. PDC detrending is based on the assumption that features in flux time series are due either to intrinsic stellar phenomena or to systematic errors and that systematics will exhibit measurable correlations across targets. SPSD events violate these assumptions and their successful removal not only rectifies the flux values of affected targets, but demonstrably improves the overall performance of PDC detrending [1].

Does red noise increase or decrease extinction risk? Single extreme events versus series of unfavorable conditions.

PubMed

Schwager, Monika; Johst, Karin; Jeltsch, Florian

2006-06-01

Recent theoretical studies have shown contrasting effects of temporal correlation of environmental fluctuations (red noise) on the risk of population extinction. It is still debated whether and under which conditions red noise increases or decreases extinction risk compared with uncorrelated (white) noise. Here, we explain the opposing effects by introducing two features of red noise time series. On the one hand, positive autocorrelation increases the probability of series of poor environmental conditions, implying increasing extinction risk. On the other hand, for a given time period, the probability of at least one extremely bad year ("catastrophe") is reduced compared with white noise, implying decreasing extinction risk. Which of these two features determines extinction risk depends on the strength of environmental fluctuations and the sensitivity of population dynamics to these fluctuations. If extreme (catastrophic) events can occur (strong noise) or sensitivity is high (overcompensatory density dependence), then temporal correlation decreases extinction risk; otherwise, it increases it. Thus, our results provide a simple explanation for the contrasting previous findings and are a crucial step toward a general understanding of the effect of noise color on extinction risk.

Inverse statistics and information content

NASA Astrophysics Data System (ADS)

Ebadi, H.; Bolgorian, Meysam; Jafari, G. R.

2010-12-01

Inverse statistics analysis studies the distribution of investment horizons to achieve a predefined level of return. This distribution provides a maximum investment horizon which determines the most likely horizon for gaining a specific return. There exists a significant difference between inverse statistics of financial market data and a fractional Brownian motion (fBm) as an uncorrelated time-series, which is a suitable criteria to measure information content in financial data. In this paper we perform this analysis for the DJIA and S&P500 as two developed markets and Tehran price index (TEPIX) as an emerging market. We also compare these probability distributions with fBm probability, to detect when the behavior of the stocks are the same as fBm.

Time-Series Analysis of Supergranule Characterstics at Solar Minimum

NASA Technical Reports Server (NTRS)

Williams, Peter E.; Pesnell, W. Dean

2013-01-01

Sixty days of Doppler images from the Solar and Heliospheric Observatory (SOHO) / Michelson Doppler Imager (MDI) investigation during the 1996 and 2008 solar minima have been analyzed to show that certain supergranule characteristics (size, size range, and horizontal velocity) exhibit fluctuations of three to five days. Cross-correlating parameters showed a good, positive correlation between supergranulation size and size range, and a moderate, negative correlation between size range and velocity. The size and velocity do exhibit a moderate, negative correlation, but with a small time lag (less than 12 hours). Supergranule sizes during five days of co-temporal data from MDI and the Solar Dynamics Observatory (SDO) / Helioseismic Magnetic Imager (HMI) exhibit similar fluctuations with a high level of correlation between them. This verifies the solar origin of the fluctuations, which cannot be caused by instrumental artifacts according to these observations. Similar fluctuations are also observed in data simulations that model the evolution of the MDI Doppler pattern over a 60-day period. Correlations between the supergranule size and size range time-series derived from the simulated data are similar to those seen in MDI data. A simple toy-model using cumulative, uncorrelated exponential growth and decay patterns at random emergence times produces a time-series similar to the data simulations. The qualitative similarities between the simulated and the observed time-series suggest that the fluctuations arise from stochastic processes occurring within the solar convection zone. This behavior, propagating to surface manifestations of supergranulation, may assist our understanding of magnetic-field-line advection, evolution, and interaction.

Is walking a random walk? Evidence for long-range correlations in stride interval of human gait

NASA Technical Reports Server (NTRS)

Hausdorff, Jeffrey M.; Peng, C.-K.; Ladin, Zvi; Wei, Jeanne Y.; Goldberger, Ary L.

1995-01-01

Complex fluctuation of unknown origin appear in the normal gait pattern. These fluctuations might be described as being (1) uncorrelated white noise, (2) short-range correlations, or (3) long-range correlations with power-law scaling. To test these possibilities, the stride interval of 10 healthy young men was measured as they walked for 9 min at their usual rate. From these time series we calculated scaling indexes by using a modified random walk analysis and power spectral analysis. Both indexes indicated the presence of long-range self-similar correlations extending over hundreds of steps; the stride interval at any time depended on the stride interval at remote previous times, and this dependence decayed in a scale-free (fractallike) power-law fashion. These scaling indexes were significantly different from those obtained after random shuffling of the original time series, indicating the importance of the sequential ordering of the stride interval. We demonstrate that conventional models of gait generation fail to reproduce the observed scaling behavior and introduce a new type of central pattern generator model that sucessfully accounts for the experimentally observed long-range correlations.

From moonlight to movement and synchronized randomness: Fourier and wavelet analyses of animal location time series data

PubMed Central

Polansky, Leo; Wittemyer, George; Cross, Paul C.; Tambling, Craig J.; Getz, Wayne M.

2011-01-01

High-resolution animal location data are increasingly available, requiring analytical approaches and statistical tools that can accommodate the temporal structure and transient dynamics (non-stationarity) inherent in natural systems. Traditional analyses often assume uncorrelated or weakly correlated temporal structure in the velocity (net displacement) time series constructed using sequential location data. We propose that frequency and time–frequency domain methods, embodied by Fourier and wavelet transforms, can serve as useful probes in early investigations of animal movement data, stimulating new ecological insight and questions. We introduce a novel movement model with time-varying parameters to study these methods in an animal movement context. Simulation studies show that the spectral signature given by these methods provides a useful approach for statistically detecting and characterizing temporal dependency in animal movement data. In addition, our simulations provide a connection between the spectral signatures observed in empirical data with null hypotheses about expected animal activity. Our analyses also show that there is not a specific one-to-one relationship between the spectral signatures and behavior type and that departures from the anticipated signatures are also informative. Box plots of net displacement arranged by time of day and conditioned on common spectral properties can help interpret the spectral signatures of empirical data. The first case study is based on the movement trajectory of a lion (Panthera leo) that shows several characteristic daily activity sequences, including an active–rest cycle that is correlated with moonlight brightness. A second example based on six pairs of African buffalo (Syncerus caffer) illustrates the use of wavelet coherency to show that their movements synchronize when they are within ∼1 km of each other, even when individual movement was best described as an uncorrelated random walk, providing an important spatial baseline of movement synchrony and suggesting that local behavioral cues play a strong role in driving movement patterns. We conclude with a discussion about the role these methods may have in guiding appropriately flexible probabilistic models connecting movement with biotic and abiotic covariates. PMID:20503882

Characterization of Ground Displacement Sources from Variational Bayesian Independent Component Analysis of Space Geodetic Time Series

NASA Astrophysics Data System (ADS)

Gualandi, Adriano; Serpelloni, Enrico; Elina Belardinelli, Maria; Bonafede, Maurizio; Pezzo, Giuseppe; Tolomei, Cristiano

2015-04-01

A critical point in the analysis of ground displacement time series, as those measured by modern space geodetic techniques (primarly continuous GPS/GNSS and InSAR) is the development of data driven methods that allow to discern and characterize the different sources that generate the observed displacements. A widely used multivariate statistical technique is the Principal Component Analysis (PCA), which allows to reduce the dimensionality of the data space maintaining most of the variance of the dataset explained. It reproduces the original data using a limited number of Principal Components, but it also shows some deficiencies, since PCA does not perform well in finding the solution to the so-called Blind Source Separation (BSS) problem. The recovering and separation of the different sources that generate the observed ground deformation is a fundamental task in order to provide a physical meaning to the possible different sources. PCA fails in the BSS problem since it looks for a new Euclidean space where the projected data are uncorrelated. Usually, the uncorrelation condition is not strong enough and it has been proven that the BSS problem can be tackled imposing on the components to be independent. The Independent Component Analysis (ICA) is, in fact, another popular technique adopted to approach this problem, and it can be used in all those fields where PCA is also applied. An ICA approach enables us to explain the displacement time series imposing a fewer number of constraints on the model, and to reveal anomalies in the data such as transient deformation signals. However, the independence condition is not easy to impose, and it is often necessary to introduce some approximations. To work around this problem, we use a variational bayesian ICA (vbICA) method, which models the probability density function (pdf) of each source signal using a mix of Gaussian distributions. This technique allows for more flexibility in the description of the pdf of the sources, giving a more reliable estimate of them. Here we introduce the vbICA technique and present its application on synthetic data that simulate a GPS network recording ground deformation in a tectonically active region, with synthetic time-series containing interseismic, coseismic, and postseismic deformation, plus seasonal deformation, and white and coloured noise. We study the ability of the algorithm to recover the original (known) sources of deformation, and then apply it to a real scenario: the Emilia seismic sequence (2012, northern Italy), which is an example of seismic sequence occurred in a slowly converging tectonic setting, characterized by several local to regional anthropogenic or natural sources of deformation, mainly subsidence due to fluid withdrawal and sediments compaction. We apply both PCA and vbICA to displacement time-series recorded by continuous GPS and InSAR (Pezzo et al., EGU2015-8950).

Variance of discharge estimates sampled using acoustic Doppler current profilers from moving boats

USGS Publications Warehouse

Garcia, Carlos M.; Tarrab, Leticia; Oberg, Kevin; Szupiany, Ricardo; Cantero, Mariano I.

2012-01-01

This paper presents a model for quantifying the random errors (i.e., variance) of acoustic Doppler current profiler (ADCP) discharge measurements from moving boats for different sampling times. The model focuses on the random processes in the sampled flow field and has been developed using statistical methods currently available for uncertainty analysis of velocity time series. Analysis of field data collected using ADCP from moving boats from three natural rivers of varying sizes and flow conditions shows that, even though the estimate of the integral time scale of the actual turbulent flow field is larger than the sampling interval, the integral time scale of the sampled flow field is on the order of the sampling interval. Thus, an equation for computing the variance error in discharge measurements associated with different sampling times, assuming uncorrelated flow fields is appropriate. The approach is used to help define optimal sampling strategies by choosing the exposure time required for ADCPs to accurately measure flow discharge.

Temporal evolution of financial-market correlations.

PubMed

Fenn, Daniel J; Porter, Mason A; Williams, Stacy; McDonald, Mark; Johnson, Neil F; Jones, Nick S

2011-08-01

We investigate financial market correlations using random matrix theory and principal component analysis. We use random matrix theory to demonstrate that correlation matrices of asset price changes contain structure that is incompatible with uncorrelated random price changes. We then identify the principal components of these correlation matrices and demonstrate that a small number of components accounts for a large proportion of the variability of the markets that we consider. We characterize the time-evolving relationships between the different assets by investigating the correlations between the asset price time series and principal components. Using this approach, we uncover notable changes that occurred in financial markets and identify the assets that were significantly affected by these changes. We show in particular that there was an increase in the strength of the relationships between several different markets following the 2007-2008 credit and liquidity crisis.

Temporal evolution of financial-market correlations

NASA Astrophysics Data System (ADS)

Fenn, Daniel J.; Porter, Mason A.; Williams, Stacy; McDonald, Mark; Johnson, Neil F.; Jones, Nick S.

2011-08-01

We investigate financial market correlations using random matrix theory and principal component analysis. We use random matrix theory to demonstrate that correlation matrices of asset price changes contain structure that is incompatible with uncorrelated random price changes. We then identify the principal components of these correlation matrices and demonstrate that a small number of components accounts for a large proportion of the variability of the markets that we consider. We characterize the time-evolving relationships between the different assets by investigating the correlations between the asset price time series and principal components. Using this approach, we uncover notable changes that occurred in financial markets and identify the assets that were significantly affected by these changes. We show in particular that there was an increase in the strength of the relationships between several different markets following the 2007-2008 credit and liquidity crisis.

Analysis and Forecasting of Shoreline Position

NASA Astrophysics Data System (ADS)

Barton, C. C.; Tebbens, S. F.

2007-12-01

Analysis of historical shoreline positions on sandy coasts, in the geologic record, and study of sea-level rise curves reveals that the dynamics of the underlying processes produce temporal/spatial signals that exhibit power scaling and are therefore self-affine fractals. Self-affine time series signals can be quantified over many orders of magnitude in time and space in terms of persistence, a measure of the degree of correlation between adjacent values in the stochastic portion of a time series. Fractal statistics developed for self-affine time series are used to forecast a probability envelope bounding future shoreline positions. The envelope provides the standard deviation as a function of three variables: persistence, a constant equal to the value of the power spectral density when 1/period equals 1, and the number of time increments. The persistence of a twenty-year time series of the mean-high-water (MHW) shoreline positions was measured for four profiles surveyed at Duck, NC at the Field Research Facility (FRF) by the U.S. Army Corps of Engineers. The four MHW shoreline time series signals are self-affine with persistence ranging between 0.8 and 0.9, which indicates that the shoreline position time series is weakly persistent (where zero is uncorrelated), and has highly varying trends for all time intervals sampled. Forecasts of a probability envelope for future MHW positions are made for the 20 years of record and beyond to 50 years from the start of the data records. The forecasts describe the twenty-year data sets well and indicate that within a 96% confidence envelope, future decadal MHW shoreline excursions should be within 14.6 m of the position at the start of data collection. This is a stable-oscillatory shoreline. The forecasting method introduced here includes the stochastic portion of the time series while the traditional method of predicting shoreline change reduces the time series to a linear trend line fit to historic shoreline positions and extrapolated linearly to forecast future positions with a linearly increasing mean that breaks the confidence envelope eight years into the future and continues to increase. The traditional method is a poor representation of the observed shoreline position time series and is a poor basis for extrapolating future shoreline positions.

Estimating rate uncertainty with maximum likelihood: differences between power-law and flicker–random-walk models

USGS Publications Warehouse

Langbein, John O.

2012-01-01

Recent studies have documented that global positioning system (GPS) time series of position estimates have temporal correlations which have been modeled as a combination of power-law and white noise processes. When estimating quantities such as a constant rate from GPS time series data, the estimated uncertainties on these quantities are more realistic when using a noise model that includes temporal correlations than simply assuming temporally uncorrelated noise. However, the choice of the specific representation of correlated noise can affect the estimate of uncertainty. For many GPS time series, the background noise can be represented by either: (1) a sum of flicker and random-walk noise or, (2) as a power-law noise model that represents an average of the flicker and random-walk noise. For instance, if the underlying noise model is a combination of flicker and random-walk noise, then incorrectly choosing the power-law model could underestimate the rate uncertainty by a factor of two. Distinguishing between the two alternate noise models is difficult since the flicker component can dominate the assessment of the noise properties because it is spread over a significant portion of the measurable frequency band. But, although not necessarily detectable, the random-walk component can be a major constituent of the estimated rate uncertainty. None the less, it is possible to determine the upper bound on the random-walk noise.

Quantification of correlations in quantum many-particle systems.

PubMed

Byczuk, Krzysztof; Kuneš, Jan; Hofstetter, Walter; Vollhardt, Dieter

2012-02-24

We introduce a well-defined and unbiased measure of the strength of correlations in quantum many-particle systems which is based on the relative von Neumann entropy computed from the density operator of correlated and uncorrelated states. The usefulness of this general concept is demonstrated by quantifying correlations of interacting electrons in the Hubbard model and in a series of transition-metal oxides using dynamical mean-field theory.

ENSO and cholera: a nonstationary link related to climate change?

PubMed

Rodo, Xavier; Pascual, Mercedes; Fuchs, George; Faruque, A S G

2002-10-01

We present here quantitative evidence for an increased role of interannual climate variability on the temporal dynamics of an infectious disease. The evidence is based on time-series analyses of the relationship between El Niño/Southern Oscillation (ENSO) and cholera prevalence in Bangladesh (formerly Bengal) during two different time periods. A strong and consistent signature of ENSO is apparent in the last two decades (1980-2001), while it is weaker and eventually uncorrelated during the first parts of the last century (1893-1920 and 1920-1940, respectively). Concomitant with these changes, the Southern Oscillation Index (SOI) undergoes shifts in its frequency spectrum. These changes include an intensification of the approximately 4-yr cycle during the recent interval as a response to the well documented Pacific basin regime shift of 1976. This change in remote ENSO modulation alone can only partially serve to substantiate the differences observed in cholera. Regional or basin-wide changes possibly linked to global warming must be invoked that seem to facilitate ENSO transmission. For the recent cholera series and during specific time intervals corresponding to local maxima in ENSO, this climate phenomenon accounts for over 70% of disease variance. This strong association is discontinuous in time and can only be captured with a technique designed to isolate transient couplings.

ENSO and cholera: A nonstationary link related to climate change?

PubMed Central

Rodó, Xavier; Pascual, Mercedes; Fuchs, George; Faruque, A. S. G.

2002-01-01

We present here quantitative evidence for an increased role of interannual climate variability on the temporal dynamics of an infectious disease. The evidence is based on time-series analyses of the relationship between El Niño/Southern Oscillation (ENSO) and cholera prevalence in Bangladesh (formerly Bengal) during two different time periods. A strong and consistent signature of ENSO is apparent in the last two decades (1980–2001), while it is weaker and eventually uncorrelated during the first parts of the last century (1893–1920 and 1920–1940, respectively). Concomitant with these changes, the Southern Oscillation Index (SOI) undergoes shifts in its frequency spectrum. These changes include an intensification of the approximately 4-yr cycle during the recent interval as a response to the well documented Pacific basin regime shift of 1976. This change in remote ENSO modulation alone can only partially serve to substantiate the differences observed in cholera. Regional or basin-wide changes possibly linked to global warming must be invoked that seem to facilitate ENSO transmission. For the recent cholera series and during specific time intervals corresponding to local maxima in ENSO, this climate phenomenon accounts for over 70% of disease variance. This strong association is discontinuous in time and can only be captured with a technique designed to isolate transient couplings. PMID:12228724

The application of a shift theorem analysis technique to multipoint measurements

NASA Astrophysics Data System (ADS)

Dieckmann, M. E.; Chapman, S. C.

1999-03-01

A Fourier domain technique has been proposed previously which, in principle, quantifies the extent to which multipoint in-situ measurements can identify whether or not an observed structure is time stationary in its rest frame. Once a structure, sampled for example by four spacecraft, is shown to be quasi-stationary in its rest frame, the structure's velocity vector can be determined with respect to the sampling spacecraft. We investigate the properties of this technique, which we will refer to as a stationarity test, by applying it to two point measurements of a simulated boundary layer. The boundary layer was evolved using a PIC (particle in cell) electromagnetic code. Initial and boundary conditions were chosen such, that two cases could be considered, i.e. a spacecraft pair moving through (1) a time stationary boundary structure and (2) a boundary structure which is evolving (expanding) in time. The code also introduces noise in the simulated data time series which is uncorrelated between the two spacecraft. We demonstrate that, provided that the time series is Hanning windowed, the test is effective in determining the relative velocity between the boundary layer and spacecraft and in determining the range of frequencies over which the data can be treated as time stationary or time evolving. This work presents a first step towards understanding the effectiveness of this technique, as required in order for it to be applied to multispacecraft data.

The Analysis and Suppression of the spike noise in vibrator record

NASA Astrophysics Data System (ADS)

Jia, H.; Jiang, T.; Xu, X.; Ge, L.; Lin, J.; Yang, Z.

2013-12-01

During the seismic exploration with vibrator, seismic recording systems have often been affected by random spike noise in the background, which leads to strong data distortions as a result of the cross-correlation processing of the vibrator method. Partial or total loss of the desired seismic information is possible if no automatic spike reduction is available in the field prior to correlation of the field record. Generally speaking, original record of vibrator is uncorrelated data, in which the signal is non-wavelet form. In order to obtain the seismic record similar to explosive source, the signal of uncorrelated data needs to use the correlation algorithm to compress into wavelet form. The correlation process results in that the interference of spike in correlated data is not only being suppressed, but also being expanded. So the spike noise suppression of vibrator is indispensable. According to numerical simulation results, the effect of spike in the vibrator record is mainly affected by the amplitude and proportional points in the uncorrelated record. When the spike noise ratio in uncorrelated record reaches 1.5% and the average amplitude exceeds 200, it will make the SNR(signal-to-noise ratio) of the correlated record lower than 0dB, so that it is difficult to separate the signal. While the amplitude and ratio is determined by the intensity of background noise. Therefore, when the noise level is strong, in order to improve SNR of the seismic data, the uncorrelated record of vibrator need to take necessary steps to suppress spike noise. For the sake of reducing the influence of the spike noise, we need to make the detection and suppression of spike noise process for the uncorrelated record. Because vibrator works by inputting sweep signal into the underground long time, ideally, the peak and valley values of each trace have little change. On the basis of the peak and valley values, we can get a reference amplitude value. Then the spike can be detected and suppressed. After this process, it can reduce the effection of spike noise in the uncorrelated record to improve the SNR. At present, because the memory space of vibrator uncorrelated data is always very large, in order to reduce acquisition costs, we usually record correlated data directly. It's reasonable if there is no strong spike sneaking into uncorrelated record. However, due to the fact that the random spike in the background is not avoidable in the acquisition process, and the instantaneous input energy of the vibrator is probably smaller than spike noise, which makes the uncorrelated data contain a certain amount of spike noise, it severely reduces the acquisition quality of vibrator if there is no noise suppression module beforehand. Of course, the suppressing process of spike noise can be carried out in the field acquisition or data processing stage. In the field of vibrator acquisition system, we can use the spike noise suppression before the correlated module, so that it can directly record correlated data without the spike affection. If in the stage of data processing, it is necessary to record uncorrelated data.

High-frequency signal and noise estimates of CSR GRACE RL04

NASA Astrophysics Data System (ADS)

Bonin, Jennifer A.; Bettadpur, Srinivas; Tapley, Byron D.

2012-12-01

A sliding window technique is used to create daily-sampled Gravity Recovery and Climate Experiment (GRACE) solutions with the same background processing as the official CSR RL04 monthly series. By estimating over shorter time spans, more frequent solutions are made using uncorrelated data, allowing for higher frequency resolution in addition to daily sampling. Using these data sets, high-frequency GRACE errors are computed using two different techniques: assuming the GRACE high-frequency signal in a quiet area of the ocean is the true error, and computing the variance of differences between multiple high-frequency GRACE series from different centers. While the signal-to-noise ratios prove to be sufficiently high for confidence at annual and lower frequencies, at frequencies above 3 cycles/year the signal-to-noise ratios in the large hydrological basins looked at here are near 1.0. Comparisons with the GLDAS hydrological model and high frequency GRACE series developed at other centers confirm CSR GRACE RL04's poor ability to accurately and reliably measure hydrological signal above 3-9 cycles/year, due to the low power of the large-scale hydrological signal typical at those frequencies compared to the GRACE errors.

Price dynamics in political prediction markets

PubMed Central

Majumder, Saikat Ray; Diermeier, Daniel; Rietz, Thomas A.; Amaral, Luís A. Nunes

2009-01-01

Prediction markets, in which contract prices are used to forecast future events, are increasingly applied to various domains ranging from political contests to scientific breakthroughs. However, the dynamics of such markets are not well understood. Here, we study the return dynamics of the oldest, most data-rich prediction markets, the Iowa Electronic Presidential Election “winner-takes-all” markets. As with other financial markets, we find uncorrelated returns, power-law decaying volatility correlations, and, usually, power-law decaying distributions of returns. However, unlike other financial markets, we find conditional diverging volatilities as the contract settlement date approaches. We propose a dynamic binary option model that captures all features of the empirical data and can potentially provide a tool with which one may extract true information events from a price time series. PMID:19155442

Additive noise-induced Turing transitions in spatial systems with application to neural fields and the Swift Hohenberg equation

NASA Astrophysics Data System (ADS)

Hutt, Axel; Longtin, Andre; Schimansky-Geier, Lutz

2008-05-01

This work studies the spatio-temporal dynamics of a generic integral-differential equation subject to additive random fluctuations. It introduces a combination of the stochastic center manifold approach for stochastic differential equations and the adiabatic elimination for Fokker-Planck equations, and studies analytically the systems’ stability near Turing bifurcations. In addition two types of fluctuation are studied, namely fluctuations uncorrelated in space and time, and global fluctuations, which are constant in space but uncorrelated in time. We show that the global fluctuations shift the Turing bifurcation threshold. This shift is proportional to the fluctuation variance. Applications to a neural field equation and the Swift-Hohenberg equation reveal the shift of the bifurcation to larger control parameters, which represents a stabilization of the system. All analytical results are confirmed by numerical simulations of the occurring mode equations and the full stochastic integral-differential equation. To gain some insight into experimental manifestations, the sum of uncorrelated and global additive fluctuations is studied numerically and the analytical results on global fluctuations are confirmed qualitatively.

Statistical properties of online avatar numbers in a massive multiplayer online role-playing game

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Ren, Fei; Gu, Gao-Feng; Tan, Qun-Zhao; Zhou, Wei-Xing

2010-02-01

Massive multiplayer online role-playing games (MMORPGs) have been very popular in the past few years. The profit of an MMORPG company is proportional to how many users registered, and the instant number of online avatars is a key factor to assess how popular an MMORPG is. We use the online-offline logs on an MMORPG server to reconstruct the instant number of online avatars per second and investigate its statistical properties. We find that the online avatar number exhibits one-day periodic behavior and clear intraday pattern, the fluctuation distribution of the online avatar numbers has a leptokurtic non-Gaussian shape with power-law tails, and the increments of online avatar numbers after removing the intraday pattern are uncorrelated and the associated absolute values have long-term correlation. In addition, both time series exhibit multifractal nature.

Quench field sensitivity of two-particle correlation in a Hubbard model

PubMed Central

Zhang, X. Z.; Lin, S.; Song, Z.

2016-01-01

Short-range interaction can give rise to particle pairing with a short-range correlation, which may be destroyed in the presence of an external field. We study the transition between correlated and uncorrelated particle states in the framework of one- dimensional Hubbard model driven by a field. We show that the long time-scale transfer rate from an initial correlated state to final uncorrelated particle states is sensitive to the quench field strength and exhibits a periodic behavior. This process involves an irreversible energy transfer from the field to particles, leading to a quantum electrothermal effect. PMID:27250080

Level crossings and excess times due to a superposition of uncorrelated exponential pulses

NASA Astrophysics Data System (ADS)

Theodorsen, A.; Garcia, O. E.

2018-01-01

A well-known stochastic model for intermittent fluctuations in physical systems is investigated. The model is given by a superposition of uncorrelated exponential pulses, and the degree of pulse overlap is interpreted as an intermittency parameter. Expressions for excess time statistics, that is, the rate of level crossings above a given threshold and the average time spent above the threshold, are derived from the joint distribution of the process and its derivative. Limits of both high and low intermittency are investigated and compared to previously known results. In the case of a strongly intermittent process, the distribution of times spent above threshold is obtained analytically. This expression is verified numerically, and the distribution of times above threshold is explored for other intermittency regimes. The numerical simulations compare favorably to known results for the distribution of times above the mean threshold for an Ornstein-Uhlenbeck process. This contribution generalizes the excess time statistics for the stochastic model, which find applications in a wide diversity of natural and technological systems.

Scaling range of power laws that originate from fluctuation analysis

NASA Astrophysics Data System (ADS)

Grech, Dariusz; Mazur, Zygmunt

2013-05-01

We extend our previous study of scaling range properties performed for detrended fluctuation analysis (DFA) [Physica A0378-437110.1016/j.physa.2013.01.049 392, 2384 (2013)] to other techniques of fluctuation analysis (FA). The new technique, called modified detrended moving average analysis (MDMA), is introduced, and its scaling range properties are examined and compared with those of detrended moving average analysis (DMA) and DFA. It is shown that contrary to DFA, DMA and MDMA techniques exhibit power law dependence of the scaling range with respect to the length of the searched signal and with respect to the accuracy R2 of the fit to the considered scaling law imposed by DMA or MDMA methods. This power law dependence is satisfied for both uncorrelated and autocorrelated data. We find also a simple generalization of this power law relation for series with a different level of autocorrelations measured in terms of the Hurst exponent. Basic relations between scaling ranges for different techniques are also discussed. Our findings should be particularly useful for local FA in, e.g., econophysics, finances, or physiology, where the huge number of short time series has to be examined at once and wherever the preliminary check of the scaling range regime for each of the series separately is neither effective nor possible.

Minding Impacting Events in a Model of Stochastic Variance

PubMed Central

Duarte Queirós, Sílvio M.; Curado, Evaldo M. F.; Nobre, Fernando D.

2011-01-01

We introduce a generalization of the well-known ARCH process, widely used for generating uncorrelated stochastic time series with long-term non-Gaussian distributions and long-lasting correlations in the (instantaneous) standard deviation exhibiting a clustering profile. Specifically, inspired by the fact that in a variety of systems impacting events are hardly forgot, we split the process into two different regimes: a first one for regular periods where the average volatility of the fluctuations within a certain period of time is below a certain threshold, , and another one when the local standard deviation outnumbers . In the former situation we use standard rules for heteroscedastic processes whereas in the latter case the system starts recalling past values that surpassed the threshold. Our results show that for appropriate parameter values the model is able to provide fat tailed probability density functions and strong persistence of the instantaneous variance characterized by large values of the Hurst exponent (), which are ubiquitous features in complex systems. PMID:21483864

Experimental phase synchronization detection in non-phase coherent chaotic systems by using the discrete complex wavelet approach

NASA Astrophysics Data System (ADS)

Ferreira, Maria Teodora; Follmann, Rosangela; Domingues, Margarete O.; Macau, Elbert E. N.; Kiss, István Z.

2017-08-01

Phase synchronization may emerge from mutually interacting non-linear oscillators, even under weak coupling, when phase differences are bounded, while amplitudes remain uncorrelated. However, the detection of this phenomenon can be a challenging problem to tackle. In this work, we apply the Discrete Complex Wavelet Approach (DCWA) for phase assignment, considering signals from coupled chaotic systems and experimental data. The DCWA is based on the Dual-Tree Complex Wavelet Transform (DT-CWT), which is a discrete transformation. Due to its multi-scale properties in the context of phase characterization, it is possible to obtain very good results from scalar time series, even with non-phase-coherent chaotic systems without state space reconstruction or pre-processing. The method correctly predicts the phase synchronization for a chemical experiment with three locally coupled, non-phase-coherent chaotic processes. The impact of different time-scales is demonstrated on the synchronization process that outlines the advantages of DCWA for analysis of experimental data.

Comparison of data transformation procedures to enhance topographical accuracy in time-series analysis of the human EEG.

PubMed

Hauk, O; Keil, A; Elbert, T; Müller, M M

2002-01-30

We describe a methodology to apply current source density (CSD) and minimum norm (MN) estimation as pre-processing tools for time-series analysis of single trial EEG data. The performance of these methods is compared for the case of wavelet time-frequency analysis of simulated gamma-band activity. A reasonable comparison of CSD and MN on the single trial level requires regularization such that the corresponding transformed data sets have similar signal-to-noise ratios (SNRs). For region-of-interest approaches, it should be possible to optimize the SNR for single estimates rather than for the whole distributed solution. An effective implementation of the MN method is described. Simulated data sets were created by modulating the strengths of a radial and a tangential test dipole with wavelets in the frequency range of the gamma band, superimposed with simulated spatially uncorrelated noise. The MN and CSD transformed data sets as well as the average reference (AR) representation were subjected to wavelet frequency-domain analysis, and power spectra were mapped for relevant frequency bands. For both CSD and MN, the influence of noise can be sufficiently suppressed by regularization to yield meaningful information, but only MN represents both radial and tangential dipole sources appropriately as single peaks. Therefore, when relating wavelet power spectrum topographies to their neuronal generators, MN should be preferred.

Resistance to Change and Frequency of Response-Dependent Stimuli Uncorrelated with Reinforcement

ERIC Educational Resources Information Center

Podlesnik, Christopher A.; Jimenez-Gomez, Corina; Ward, Ryan D.; Shahan, Timothy A.

2009-01-01

Stimuli uncorrelated with reinforcement have been shown to enhance response rates and resistance to disruption; however, the effects of different rates of stimulus presentations have not been assessed. In two experiments, we assessed the effects of adding different rates of response-dependent brief stimuli uncorrelated with primary reinforcement…

Regional Landslide Mapping Aided by Automated Classification of SqueeSAR™ Time Series (Northern Apennines, Italy)

NASA Astrophysics Data System (ADS)

Iannacone, J.; Berti, M.; Allievi, J.; Del Conte, S.; Corsini, A.

2013-12-01

Space borne InSAR has proven to be very valuable for landslides detection. In particular, extremely slow landslides (Cruden and Varnes, 1996) can be now clearly identified, thanks to the millimetric precision reached by recent multi-interferometric algorithms. The typical approach in radar interpretation for landslides mapping is based on average annual velocity of the deformation which is calculated over the entire times series. The Hotspot and Cluster Analysis (Lu et al., 2012) and the PSI-based matrix approach (Cigna et al., 2013) are examples of landslides mapping techniques based on average annual velocities. However, slope movements can be affected by non-linear deformation trends, (i.e. reactivation of dormant landslides, deceleration due to natural or man-made slope stabilization, seasonal activity, etc). Therefore, analyzing deformation time series is crucial in order to fully characterize slope dynamics. While this is relatively simple to be carried out manually when dealing with small dataset, the time series analysis over regional scale dataset requires automated classification procedures. Berti et al. (2013) developed an automatic procedure for the analysis of InSAR time series based on a sequence of statistical tests. The analysis allows to classify the time series into six distinctive target trends (0=uncorrelated; 1=linear; 2=quadratic; 3=bilinear; 4=discontinuous without constant velocity; 5=discontinuous with change in velocity) which are likely to represent different slope processes. The analysis also provides a series of descriptive parameters which can be used to characterize the temporal changes of ground motion. All the classification algorithms were integrated into a Graphical User Interface called PSTime. We investigated an area of about 2000 km2 in the Northern Apennines of Italy by using SqueeSAR™ algorithm (Ferretti et al., 2011). Two Radarsat-1 data stack, comprising of 112 scenes in descending orbit and 124 scenes in ascending orbit, were processed. The time coverage lasts from April 2003 to November 2012, with an average temporal frequency of 1 scene/month. Radar interpretation has been carried out by considering average annual velocities as well as acceleration/deceleration trends evidenced by PSTime. Altogether, from ascending and descending geometries respectively, this approach allowed detecting of 115 and 112 potential landslides on the basis of average displacement rate and 77 and 79 landslides on the basis of acceleration trends. In conclusion, time series analysis resulted to be very valuable for landslide mapping. In particular it highlighted areas with marked acceleration in a specific period in time while still being affected by low average annual velocity over the entire analysis period. On the other hand, even in areas with high average annual velocity, time series analysis was of primary importance to characterize the slope dynamics in terms of acceleration events.

Truncated Lévy walks and an emerging market economic index

NASA Astrophysics Data System (ADS)

Miranda, L. Couto; Riera, R.

2001-08-01

In this paper, we perform a statistical analysis of the major stock index in Latin America, the São Paulo Stock Exchange Index in Brazil (IBOVESPA). Database contains daily records for the 15-year period 1986-2000. We find that the time evolution of the index of share prices is well described by an Exponentially Truncated Lévy Flight (ETLF) characterized by a Lévy exponent α≃1.6-1.7 and a cutoff exponent λ≃1.7. The ETLF statistics accounts for the observed short-term large fluctuations of the financial data time series and describes the long-term convergence to the Gaussian regime. We derive the characteristic crossover time scale Nc dependence on α and λ according to this model as well as the volatility dependence on α, λ and Nc. We find an uncorrelated behaviour of the historical data and Nc≃20 trading days which are in numerical agreement with the analytical results. This dynamic model provides a framework within which it is possible to develop an efficient risk management and option pricing practice for emerging economies.

Two-Dimensional DOA and Polarization Estimation for a Mixture of Uncorrelated and Coherent Sources with Sparsely-Distributed Vector Sensor Array

PubMed Central

Si, Weijian; Zhao, Pinjiao; Qu, Zhiyu

2016-01-01

This paper presents an L-shaped sparsely-distributed vector sensor (SD-VS) array with four different antenna compositions. With the proposed SD-VS array, a novel two-dimensional (2-D) direction of arrival (DOA) and polarization estimation method is proposed to handle the scenario where uncorrelated and coherent sources coexist. The uncorrelated and coherent sources are separated based on the moduli of the eigenvalues. For the uncorrelated sources, coarse estimates are acquired by extracting the DOA information embedded in the steering vectors from estimated array response matrix of the uncorrelated sources, and they serve as coarse references to disambiguate fine estimates with cyclical ambiguity obtained from the spatial phase factors. For the coherent sources, four Hankel matrices are constructed, with which the coherent sources are resolved in a similar way as for the uncorrelated sources. The proposed SD-VS array requires only two collocated antennas for each vector sensor, thus the mutual coupling effects across the collocated antennas are reduced greatly. Moreover, the inter-sensor spacings are allowed beyond a half-wavelength, which results in an extended array aperture. Simulation results demonstrate the effectiveness and favorable performance of the proposed method. PMID:27258271

Developing a complex independent component analysis technique to extract non-stationary patterns from geophysical time-series

NASA Astrophysics Data System (ADS)

Forootan, Ehsan; Kusche, Jürgen

2016-04-01

Geodetic/geophysical observations, such as the time series of global terrestrial water storage change or sea level and temperature change, represent samples of physical processes and therefore contain information about complex physical interactionswith many inherent time scales. Extracting relevant information from these samples, for example quantifying the seasonality of a physical process or its variability due to large-scale ocean-atmosphere interactions, is not possible by rendering simple time series approaches. In the last decades, decomposition techniques have found increasing interest for extracting patterns from geophysical observations. Traditionally, principal component analysis (PCA) and more recently independent component analysis (ICA) are common techniques to extract statistical orthogonal (uncorrelated) and independent modes that represent the maximum variance of observations, respectively. PCA and ICA can be classified as stationary signal decomposition techniques since they are based on decomposing the auto-covariance matrix or diagonalizing higher (than two)-order statistical tensors from centered time series. However, the stationary assumption is obviously not justifiable for many geophysical and climate variables even after removing cyclic components e.g., the seasonal cycles. In this paper, we present a new decomposition method, the complex independent component analysis (CICA, Forootan, PhD-2014), which can be applied to extract to non-stationary (changing in space and time) patterns from geophysical time series. Here, CICA is derived as an extension of real-valued ICA (Forootan and Kusche, JoG-2012), where we (i) define a new complex data set using a Hilbert transformation. The complex time series contain the observed values in their real part, and the temporal rate of variability in their imaginary part. (ii) An ICA algorithm based on diagonalization of fourth-order cumulants is then applied to decompose the new complex data set in (i). (iii) Dominant non-stationary patterns are recognized as independent complex patterns that can be used to represent the space and time amplitude and phase propagations. We present the results of CICA on simulated and real cases e.g., for quantifying the impact of large-scale ocean-atmosphere interaction on global mass changes. Forootan (PhD-2014) Statistical signal decomposition techniques for analyzing time-variable satellite gravimetry data, PhD Thesis, University of Bonn, http://hss.ulb.uni-bonn.de/2014/3766/3766.htm Forootan and Kusche (JoG-2012) Separation of global time-variable gravity signals into maximally independent components, Journal of Geodesy 86 (7), 477-497, doi: 10.1007/s00190-011-0532-5

Code-Time Diversity for Direct Sequence Spread Spectrum Systems

PubMed Central

Hassan, A. Y.

2014-01-01

Time diversity is achieved in direct sequence spread spectrum by receiving different faded delayed copies of the transmitted symbols from different uncorrelated channel paths when the transmission signal bandwidth is greater than the coherence bandwidth of the channel. In this paper, a new time diversity scheme is proposed for spread spectrum systems. It is called code-time diversity. In this new scheme, N spreading codes are used to transmit one data symbol over N successive symbols interval. The diversity order in the proposed scheme equals to the number of the used spreading codes N multiplied by the number of the uncorrelated paths of the channel L. The paper represents the transmitted signal model. Two demodulators structures will be proposed based on the received signal models from Rayleigh flat and frequency selective fading channels. Probability of error in the proposed diversity scheme is also calculated for the same two fading channels. Finally, simulation results are represented and compared with that of maximal ration combiner (MRC) and multiple-input and multiple-output (MIMO) systems. PMID:24982925

Coadding Techniques for Image-based Wavefront Sensing for Segmented-mirror Telescopes

NASA Technical Reports Server (NTRS)

Smith, Scott; Aronstein, David; Dean, Bruce; Acton, Scott

2007-01-01

Image-based wavefront sensing algorithms are being used to characterize optical performance for a variety of current and planned astronomical telescopes. Phase retrieval recovers the optical wavefront that correlates to a series of diversity-defocused point-spread functions (PSFs), where multiple frames can be acquired at each defocus setting. Multiple frames of data can be coadded in different ways; two extremes are in "image-plane space," to average the frames for each defocused PSF and use phase retrieval once on the averaged images, or in "pupil-plane space," to use phase retrieval on every set of PSFs individually and average the resulting wavefronts. The choice of coadd methodology is particularly noteworthy for segmented-mirror telescopes that are subject to noise that causes uncorrelated motions between groups of segments. Using data collected on and simulations of the James Webb Space Telescope Testbed Telescope (TBT) commissioned at Ball Aerospace, we show how different sources of noise (uncorrelated segment jitter, turbulence, and common-mode noise) and different parts of the optical wavefront, segment and global aberrations, contribute to choosing the coadd method. Of particular interest, segment piston is more accurately recovered in "image-plane space" coadding, while segment tip/tilt is recovered in "pupil-plane space" coadding.

Application of a deconvolution method for identifying burst amplitudes and arrival times in Alcator C-Mod far SOL plasma fluctuations

NASA Astrophysics Data System (ADS)

Theodorsen, Audun; Garcia, Odd Erik; Kube, Ralph; Labombard, Brian; Terry, Jim

2017-10-01

In the far scrape-off layer (SOL), radial motion of filamentary structures leads to excess transport of particles and heat. Amplitudes and arrival times of these filaments have previously been studied by conditional averaging in single-point measurements from Langmuir Probes and Gas Puff Imaging (GPI). Conditional averaging can be problematic: the cutoff for large amplitudes is mostly chosen by convention; the conditional windows used may influence the arrival time distribution; and the amplitudes cannot be separated from a background. Previous work has shown that SOL fluctuations are well described by a stochastic model consisting of a super-position of pulses with fixed shape and randomly distributed amplitudes and arrival times. The model can be formulated as a pulse shape convolved with a train of delta pulses. By choosing a pulse shape consistent with the power spectrum of the fluctuation time series, Richardson-Lucy deconvolution can be used to recover the underlying amplitudes and arrival times of the delta pulses. We apply this technique to both L and H-mode GPI data from the Alcator C-Mod tokamak. The pulse arrival times are shown to be uncorrelated and uniformly distributed, consistent with a Poisson process, and the amplitude distribution has an exponential tail.

Smoking, Discount Rates, and Returns to Education

ERIC Educational Resources Information Center

Fersterer, Josef; Winter-Ebmer, Rudolf

2003-01-01

Individual time preference determines schooling enrolment. Moreover, smoking behavior in early ages has been shown to be highly related to time preference rates. Insofar as discount rates are uncorrelated to ability, predicting school enrolment by discount rates can get rid of the ability bias in an earnings regression. Accordingly, we use smoking…

Stochastic modelling of intermittent fluctuations in the scrape-off layer: Correlations, distributions, level crossings, and moment estimation

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

Garcia, O. E., E-mail: odd.erik.garcia@uit.no; Kube, R.; Theodorsen, A.

A stochastic model is presented for intermittent fluctuations in the scrape-off layer of magnetically confined plasmas. The fluctuations in the plasma density are modeled by a super-position of uncorrelated pulses with fixed shape and duration, describing radial motion of blob-like structures. In the case of an exponential pulse shape and exponentially distributed pulse amplitudes, predictions are given for the lowest order moments, probability density function, auto-correlation function, level crossings, and average times for periods spent above and below a given threshold level. Also, the mean squared errors on estimators of sample mean and variance for realizations of the process bymore » finite time series are obtained. These results are discussed in the context of single-point measurements of fluctuations in the scrape-off layer, broad density profiles, and implications for plasma–wall interactions due to the transient transport events in fusion grade plasmas. The results may also have wide applications for modelling fluctuations in other magnetized plasmas such as basic laboratory experiments and ionospheric irregularities.« less

The Weighted-Average Lagged Ensemble.

PubMed

DelSole, T; Trenary, L; Tippett, M K

2017-11-01

A lagged ensemble is an ensemble of forecasts from the same model initialized at different times but verifying at the same time. The skill of a lagged ensemble mean can be improved by assigning weights to different forecasts in such a way as to maximize skill. If the forecasts are bias corrected, then an unbiased weighted lagged ensemble requires the weights to sum to one. Such a scheme is called a weighted-average lagged ensemble. In the limit of uncorrelated errors, the optimal weights are positive and decay monotonically with lead time, so that the least skillful forecasts have the least weight. In more realistic applications, the optimal weights do not always behave this way. This paper presents a series of analytic examples designed to illuminate conditions under which the weights of an optimal weighted-average lagged ensemble become negative or depend nonmonotonically on lead time. It is shown that negative weights are most likely to occur when the errors grow rapidly and are highly correlated across lead time. The weights are most likely to behave nonmonotonically when the mean square error is approximately constant over the range forecasts included in the lagged ensemble. An extreme example of the latter behavior is presented in which the optimal weights vanish everywhere except at the shortest and longest lead times.

Nonlinear temperature effects on multifractal complexity of metabolic rate of mice

PubMed Central

Bogdanovich, Jose M.; Bozinovic, Francisco

2016-01-01

Complex physiological dynamics have been argued to be a signature of healthy physiological function. Here we test whether the complexity of metabolic rate fluctuations in small endotherms decreases with lower environmental temperatures. To do so, we examine the multifractal temporal scaling properties of the rate of change in oxygen consumption r(VO2), in the laboratory mouse Mus musculus, assessing their long range correlation properties across seven different environmental temperatures, ranging from 0 °C to 30 °C. To do so, we applied multifractal detrended fluctuation analysis (MF-DFA), finding that r(VO2) fluctuations show two scaling regimes. For small time scales below the crossover time (approximately 102 s), either monofractal or weak multifractal dynamics are observed depending on whether Ta < 15 °C or Ta > 15 °C respectively. For larger time scales, r(VO2) fluctuations are characterized by an asymptotic scaling exponent that indicates multifractal anti-persistent or uncorrelated dynamics. For both scaling regimes, a generalization of the multiplicative cascade model provides very good fits for the Renyi exponents τ(q), showing that the infinite number of exponents h(q) can be described by only two independent parameters, a and b. We also show that the long-range correlation structure of r(VO2) time series differs from randomly shuffled series, and may not be explained as an artifact of stochastic sampling of a linear frequency spectrum. These results show that metabolic rate dynamics in a well studied micro-endotherm are consistent with a highly non-linear feedback control system. PMID:27781179

Nonlinear temperature effects on multifractal complexity of metabolic rate of mice.

PubMed

Labra, Fabio A; Bogdanovich, Jose M; Bozinovic, Francisco

2016-01-01

Complex physiological dynamics have been argued to be a signature of healthy physiological function. Here we test whether the complexity of metabolic rate fluctuations in small endotherms decreases with lower environmental temperatures. To do so, we examine the multifractal temporal scaling properties of the rate of change in oxygen consumption r ( VO 2 ), in the laboratory mouse Mus musculus , assessing their long range correlation properties across seven different environmental temperatures, ranging from 0 °C to 30 °C. To do so, we applied multifractal detrended fluctuation analysis (MF-DFA), finding that r(VO 2 ) fluctuations show two scaling regimes. For small time scales below the crossover time (approximately 10 2 s), either monofractal or weak multifractal dynamics are observed depending on whether T a < 15 °C or T a > 15 °C respectively. For larger time scales, r(VO 2 ) fluctuations are characterized by an asymptotic scaling exponent that indicates multifractal anti-persistent or uncorrelated dynamics. For both scaling regimes, a generalization of the multiplicative cascade model provides very good fits for the Renyi exponents τ ( q ), showing that the infinite number of exponents h(q) can be described by only two independent parameters, a and b . We also show that the long-range correlation structure of r(VO 2 ) time series differs from randomly shuffled series, and may not be explained as an artifact of stochastic sampling of a linear frequency spectrum. These results show that metabolic rate dynamics in a well studied micro-endotherm are consistent with a highly non-linear feedback control system.

Developing a Complex Independent Component Analysis (CICA) Technique to Extract Non-stationary Patterns from Geophysical Time Series

NASA Astrophysics Data System (ADS)

Forootan, Ehsan; Kusche, Jürgen; Talpe, Matthieu; Shum, C. K.; Schmidt, Michael

2017-12-01

In recent decades, decomposition techniques have enabled increasingly more applications for dimension reduction, as well as extraction of additional information from geophysical time series. Traditionally, the principal component analysis (PCA)/empirical orthogonal function (EOF) method and more recently the independent component analysis (ICA) have been applied to extract, statistical orthogonal (uncorrelated), and independent modes that represent the maximum variance of time series, respectively. PCA and ICA can be classified as stationary signal decomposition techniques since they are based on decomposing the autocovariance matrix and diagonalizing higher (than two) order statistical tensors from centered time series, respectively. However, the stationarity assumption in these techniques is not justified for many geophysical and climate variables even after removing cyclic components, e.g., the commonly removed dominant seasonal cycles. In this paper, we present a novel decomposition method, the complex independent component analysis (CICA), which can be applied to extract non-stationary (changing in space and time) patterns from geophysical time series. Here, CICA is derived as an extension of real-valued ICA, where (a) we first define a new complex dataset that contains the observed time series in its real part, and their Hilbert transformed series as its imaginary part, (b) an ICA algorithm based on diagonalization of fourth-order cumulants is then applied to decompose the new complex dataset in (a), and finally, (c) the dominant independent complex modes are extracted and used to represent the dominant space and time amplitudes and associated phase propagation patterns. The performance of CICA is examined by analyzing synthetic data constructed from multiple physically meaningful modes in a simulation framework, with known truth. Next, global terrestrial water storage (TWS) data from the Gravity Recovery And Climate Experiment (GRACE) gravimetry mission (2003-2016), and satellite radiometric sea surface temperature (SST) data (1982-2016) over the Atlantic and Pacific Oceans are used with the aim of demonstrating signal separations of the North Atlantic Oscillation (NAO) from the Atlantic Multi-decadal Oscillation (AMO), and the El Niño Southern Oscillation (ENSO) from the Pacific Decadal Oscillation (PDO). CICA results indicate that ENSO-related patterns can be extracted from the Gravity Recovery And Climate Experiment Terrestrial Water Storage (GRACE TWS) with an accuracy of 0.5-1 cm in terms of equivalent water height (EWH). The magnitude of errors in extracting NAO or AMO from SST data using the complex EOF (CEOF) approach reaches up to 50% of the signal itself, while it is reduced to 16% when applying CICA. Larger errors with magnitudes of 100% and 30% of the signal itself are found while separating ENSO from PDO using CEOF and CICA, respectively. We thus conclude that the CICA is more effective than CEOF in separating non-stationary patterns.

Facebook and Twitter vaccine sentiment in response to measles outbreaks.

PubMed

Deiner, Michael S; Fathy, Cherie; Kim, Jessica; Niemeyer, Katherine; Ramirez, David; Ackley, Sarah F; Liu, Fengchen; Lietman, Thomas M; Porco, Travis C

2017-11-01

Social media posts regarding measles vaccination were classified as pro-vaccination, expressing vaccine hesitancy, uncertain, or irrelevant. Spearman correlations with Centers for Disease Control and Prevention-reported measles cases and differenced smoothed cumulative case counts over this period were reported (using time series bootstrap confidence intervals). A total of 58,078 Facebook posts and 82,993 tweets were identified from 4 January 2009 to 27 August 2016. Pro-vaccination posts were correlated with the US weekly reported cases (Facebook: Spearman correlation 0.22 (95% confidence interval: 0.09 to 0.34), Twitter: 0.21 (95% confidence interval: 0.06 to 0.34)). Vaccine-hesitant posts, however, were uncorrelated with measles cases in the United States (Facebook: 0.01 (95% confidence interval: -0.13 to 0.14), Twitter: 0.0011 (95% confidence interval: -0.12 to 0.12)). These findings may result from more consistent social media engagement by individuals expressing vaccine hesitancy, contrasted with media- or event-driven episodic interest on the part of individuals favoring current policy.

Electrophysiological and psychophysical asymmetries in sensitivity to interaural correlation gaps and implications for binaural integration time.

PubMed

Lüddemann, Helge; Kollmeier, Birger; Riedel, Helmut

2016-02-01

Brief deviations of interaural correlation (IAC) can provide valuable cues for detection, segregation and localization of acoustic signals. This study investigated the processing of such "binaural gaps" in continuously running noise (100-2000 Hz), in comparison to silent "monaural gaps", by measuring late auditory evoked potentials (LAEPs) and perceptual thresholds with novel, iteratively optimized stimuli. Mean perceptual binaural gap duration thresholds exhibited a major asymmetry: they were substantially shorter for uncorrelated gaps in correlated and anticorrelated reference noise (1.75 ms and 4.1 ms) than for correlated and anticorrelated gaps in uncorrelated reference noise (26.5 ms and 39.0 ms). The thresholds also showed a minor asymmetry: they were shorter in the positive than in the negative IAC range. The mean behavioral threshold for monaural gaps was 5.5 ms. For all five gap types, the amplitude of LAEP components N1 and P2 increased linearly with the logarithm of gap duration. While perceptual and electrophysiological thresholds matched for monaural gaps, LAEP thresholds were about twice as long as perceptual thresholds for uncorrelated gaps, but half as long for correlated and anticorrelated gaps. Nevertheless, LAEP thresholds showed the same asymmetries as perceptual thresholds. For gap durations below 30 ms, LAEPs were dominated by the processing of the leading edge of a gap. For longer gap durations, in contrast, both the leading and the lagging edge of a gap contributed to the evoked response. Formulae for the equivalent rectangular duration (ERD) of the binaural system's temporal window were derived for three common window shapes. The psychophysical ERD was 68 ms for diotic and about 40 ms for anti- and uncorrelated noise. After a nonlinear Z-transform of the stimulus IAC prior to temporal integration, ERDs were about 10 ms for reference correlations of ±1 and 80 ms for uncorrelated reference. Hence, a physiologically motivated peripheral nonlinearity changed the rank order of ERDs across experimental conditions in a plausible manner. Copyright © 2015 Elsevier B.V. All rights reserved.

Co-adding techniques for image-based wavefront sensing for segmented-mirror telescopes

NASA Astrophysics Data System (ADS)

Smith, J. S.; Aronstein, David L.; Dean, Bruce H.; Acton, D. S.

2007-09-01

Image-based wavefront sensing algorithms are being used to characterize the optical performance for a variety of current and planned astronomical telescopes. Phase retrieval recovers the optical wavefront that correlates to a series of diversity-defocused point-spread functions (PSFs), where multiple frames can be acquired at each defocus setting. Multiple frames of data can be co-added in different ways; two extremes are in "image-plane space," to average the frames for each defocused PSF and use phase retrieval once on the averaged images, or in "pupil-plane space," to use phase retrieval on each PSF frame individually and average the resulting wavefronts. The choice of co-add methodology is particularly noteworthy for segmented-mirror telescopes that are subject to noise that causes uncorrelated motions between groups of segments. Using models and data from the James Webb Space Telescope (JWST) Testbed Telescope (TBT), we show how different sources of noise (uncorrelated segment jitter, turbulence, and common-mode noise) and different parts of the optical wavefront, segment and global aberrations, contribute to choosing the co-add method. Of particular interest, segment piston is more accurately recovered in "image-plane space" co-adding, while segment tip/tilt is recovered in "pupil-plane space" co-adding.

DCCA analysis of renewable and conventional energy prices

NASA Astrophysics Data System (ADS)

Paiva, Aureliano Sancho Souza; Rivera-Castro, Miguel Angel; Andrade, Roberto Fernandes Silva

2018-01-01

Here we investigate the inter-influence of oil prices and renewable energy sources. The non-stationary time series are scrutinized within the Detrended Cross-Correlation Analysis (DCCA) framework, where the resulting DCCA coefficient provides a useful and reliable index to the evaluate the cross correlation between events at the same time instant as well as at a suitably chosen time lags. The analysis is based on the quotient of two successive daily closing oil prices and composite indices of renewable energy sources in USA and Europe in the period 2006-2015, which was subject to several social and economic driving forces, as the increase of social pressure in favor of the use of non-fossil energy sources and the worldwide economic crisis that started in 2008. The DCCA coefficient is evaluated for different window sizes, extracting information for short and long term correlation between the indices. Particularly, strong correlation between the behavior of the two distinct economic sectors are observed for large time intervals during the worst period of the economic crisis (2008-2012), hinting at a very cautious behavior of the economic agents. Before and after this period, the behavior of two economic sectors are overwhelmingly uncorrelated or very weakly correlated. The results reported here may be useful to select proper strategies in future similar scenarios.

Effect of removing the common mode errors on linear regression analysis of noise amplitudes in position time series of a regional GPS network & a case study of GPS stations in Southern California

NASA Astrophysics Data System (ADS)

Jiang, Weiping; Ma, Jun; Li, Zhao; Zhou, Xiaohui; Zhou, Boye

2018-05-01

The analysis of the correlations between the noise in different components of GPS stations has positive significance to those trying to obtain more accurate uncertainty of velocity with respect to station motion. Previous research into noise in GPS position time series focused mainly on single component evaluation, which affects the acquisition of precise station positions, the velocity field, and its uncertainty. In this study, before and after removing the common-mode error (CME), we performed one-dimensional linear regression analysis of the noise amplitude vectors in different components of 126 GPS stations with a combination of white noise, flicker noise, and random walking noise in Southern California. The results show that, on the one hand, there are above-moderate degrees of correlation between the white noise amplitude vectors in all components of the stations before and after removal of the CME, while the correlations between flicker noise amplitude vectors in horizontal and vertical components are enhanced from un-correlated to moderately correlated by removing the CME. On the other hand, the significance tests show that, all of the obtained linear regression equations, which represent a unique function of the noise amplitude in any two components, are of practical value after removing the CME. According to the noise amplitude estimates in two components and the linear regression equations, more accurate noise amplitudes can be acquired in the two components.

Sequential parallel comparison design with binary and time-to-event outcomes.

PubMed

Silverman, Rachel Kloss; Ivanova, Anastasia; Fine, Jason

2018-04-30

Sequential parallel comparison design (SPCD) has been proposed to increase the likelihood of success of clinical trials especially trials with possibly high placebo effect. Sequential parallel comparison design is conducted with 2 stages. Participants are randomized between active therapy and placebo in stage 1. Then, stage 1 placebo nonresponders are rerandomized between active therapy and placebo. Data from the 2 stages are pooled to yield a single P value. We consider SPCD with binary and with time-to-event outcomes. For time-to-event outcomes, response is defined as a favorable event prior to the end of follow-up for a given stage of SPCD. We show that for these cases, the usual test statistics from stages 1 and 2 are asymptotically normal and uncorrelated under the null hypothesis, leading to a straightforward combined testing procedure. In addition, we show that the estimators of the treatment effects from the 2 stages are asymptotically normal and uncorrelated under the null and alternative hypothesis, yielding confidence interval procedures with correct coverage. Simulations and real data analysis demonstrate the utility of the binary and time-to-event SPCD. Copyright © 2018 John Wiley & Sons, Ltd.

Density-based clustering: A 'landscape view' of multi-channel neural data for inference and dynamic complexity analysis.

PubMed

Baglietto, Gabriel; Gigante, Guido; Del Giudice, Paolo

2017-01-01

Two, partially interwoven, hot topics in the analysis and statistical modeling of neural data, are the development of efficient and informative representations of the time series derived from multiple neural recordings, and the extraction of information about the connectivity structure of the underlying neural network from the recorded neural activities. In the present paper we show that state-space clustering can provide an easy and effective option for reducing the dimensionality of multiple neural time series, that it can improve inference of synaptic couplings from neural activities, and that it can also allow the construction of a compact representation of the multi-dimensional dynamics, that easily lends itself to complexity measures. We apply a variant of the 'mean-shift' algorithm to perform state-space clustering, and validate it on an Hopfield network in the glassy phase, in which metastable states are largely uncorrelated from memories embedded in the synaptic matrix. In this context, we show that the neural states identified as clusters' centroids offer a parsimonious parametrization of the synaptic matrix, which allows a significant improvement in inferring the synaptic couplings from the neural activities. Moving to the more realistic case of a multi-modular spiking network, with spike-frequency adaptation inducing history-dependent effects, we propose a procedure inspired by Boltzmann learning, but extending its domain of application, to learn inter-module synaptic couplings so that the spiking network reproduces a prescribed pattern of spatial correlations; we then illustrate, in the spiking network, how clustering is effective in extracting relevant features of the network's state-space landscape. Finally, we show that the knowledge of the cluster structure allows casting the multi-dimensional neural dynamics in the form of a symbolic dynamics of transitions between clusters; as an illustration of the potential of such reduction, we define and analyze a measure of complexity of the neural time series.

Thermal stability analysis and modelling of advanced perpendicular magnetic tunnel junctions

NASA Astrophysics Data System (ADS)

Van Beek, Simon; Martens, Koen; Roussel, Philippe; Wu, Yueh Chang; Kim, Woojin; Rao, Siddharth; Swerts, Johan; Crotti, Davide; Linten, Dimitri; Kar, Gouri Sankar; Groeseneken, Guido

2018-05-01

STT-MRAM is a promising non-volatile memory for high speed applications. The thermal stability factor (Δ = Eb/kT) is a measure for the information retention time, and an accurate determination of the thermal stability is crucial. Recent studies show that a significant error is made using the conventional methods for Δ extraction. We investigate the origin of the low accuracy. To reduce the error down to 5%, 1000 cycles or multiple ramp rates are necessary. Furthermore, the thermal stabilities extracted from current switching and magnetic field switching appear to be uncorrelated and this cannot be explained by a macrospin model. Measurements at different temperatures show that self-heating together with a domain wall model can explain these uncorrelated Δ. Characterizing self-heating properties is therefore crucial to correctly determine the thermal stability.

Wood phenology, not carbon input, controls the interannual variability of wood growth in a temperate oak forest.

PubMed

Delpierre, Nicolas; Berveiller, Daniel; Granda, Elena; Dufrêne, Eric

2016-04-01

Although the analysis of flux data has increased our understanding of the interannual variability of carbon inputs into forest ecosystems, we still know little about the determinants of wood growth. Here, we aimed to identify which drivers control the interannual variability of wood growth in a mesic temperate deciduous forest. We analysed a 9-yr time series of carbon fluxes and aboveground wood growth (AWG), reconstructed at a weekly time-scale through the combination of dendrometer and wood density data. Carbon inputs and AWG anomalies appeared to be uncorrelated from the seasonal to interannual scales. More than 90% of the interannual variability of AWG was explained by a combination of the growth intensity during a first 'critical period' of the wood growing season, occurring close to the seasonal maximum, and the timing of the first summer growth halt. Both atmospheric and soil water stress exerted a strong control on the interannual variability of AWG at the study site, despite its mesic conditions, whilst not affecting carbon inputs. Carbon sink activity, not carbon inputs, determined the interannual variations in wood growth at the study site. Our results provide a functional understanding of the dependence of radial growth on precipitation observed in dendrological studies. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Fractal Dynamics of Heartbeat Interval Fluctuations in Health and Disease

NASA Astrophysics Data System (ADS)

Meyer, M.; Marconi, C.; Rahmel, A.; Grassi, B.; Ferretti, G.; Skinner, J. E.; Cerretelli, P.

The dynamics of heartbeat interval time series were studied by a modified random walk analysis recently introduced as Detrended Fluctuation Analysis. In this analysis, the intrinsic fractal long-range power-law correlation properties of beat-to-beat fluctuations generated by the dynamical system (i.e. cardiac rhythm generator), after decomposition from extrinsic uncorrelated sources, can be quantified by the scaling exponent which, in healthy subjects, is about 1.0. The finding of a scaling coefficient of 1.0, indicating scale-invariant long-range power-law correlations (1/ƒnoise) of heartbeat fluctuations, would reflect a genuinely self-similar fractal process that typically generates fluctuations on a wide range of time scales. Lack of a characteristic time scale suggests that the neuroautonomic system underlying the control of heart rate dynamics helps prevent excessive mode-locking (error tolerance) that would restrict its functional responsiveness (plasticity) to environmental stimuli. The 1/ƒ dynamics of heartbeat interval fluctuations are unaffected by exposure to chronic hypoxia suggesting that the neuroautonomic cardiac control system is preadapted to hypoxia. Functional (hypothermia, cardiac disease) and/or structural (cardiac transplantation, early cardiac development) inactivation of neuroautonomic control is associated with the breakdown or absence of fractal complexity reflected by anticorrelated random walk-like dynamics, indicating that in these conditions the heart is unadapted to its environment.

Modeling spatiotemporal covariance for magnetoencephalography or electroencephalography source analysis.

PubMed

Plis, Sergey M; George, J S; Jun, S C; Paré-Blagoev, J; Ranken, D M; Wood, C C; Schmidt, D M

2007-01-01

We propose a new model to approximate spatiotemporal noise covariance for use in neural electromagnetic source analysis, which better captures temporal variability in background activity. As with other existing formalisms, our model employs a Kronecker product of matrices representing temporal and spatial covariance. In our model, spatial components are allowed to have differing temporal covariances. Variability is represented as a series of Kronecker products of spatial component covariances and corresponding temporal covariances. Unlike previous attempts to model covariance through a sum of Kronecker products, our model is designed to have a computationally manageable inverse. Despite increased descriptive power, inversion of the model is fast, making it useful in source analysis. We have explored two versions of the model. One is estimated based on the assumption that spatial components of background noise have uncorrelated time courses. Another version, which gives closer approximation, is based on the assumption that time courses are statistically independent. The accuracy of the structural approximation is compared to an existing model, based on a single Kronecker product, using both Frobenius norm of the difference between spatiotemporal sample covariance and a model, and scatter plots. Performance of ours and previous models is compared in source analysis of a large number of single dipole problems with simulated time courses and with background from authentic magnetoencephalography data.

A stochastic approach to noise modeling for barometric altimeters.

PubMed

Sabatini, Angelo Maria; Genovese, Vincenzo

2013-11-18

The question whether barometric altimeters can be applied to accurately track human motions is still debated, since their measurement performance are rather poor due to either coarse resolution or drifting behavior problems. As a step toward accurate short-time tracking of changes in height (up to few minutes), we develop a stochastic model that attempts to capture some statistical properties of the barometric altimeter noise. The barometric altimeter noise is decomposed in three components with different physical origin and properties: a deterministic time-varying mean, mainly correlated with global environment changes, and a first-order Gauss-Markov (GM) random process, mainly accounting for short-term, local environment changes, the effects of which are prominent, respectively, for long-time and short-time motion tracking; an uncorrelated random process, mainly due to wideband electronic noise, including quantization noise. Autoregressive-moving average (ARMA) system identification techniques are used to capture the correlation structure of the piecewise stationary GM component, and to estimate its standard deviation, together with the standard deviation of the uncorrelated component. M-point moving average filters used alone or in combination with whitening filters learnt from ARMA model parameters are further tested in few dynamic motion experiments and discussed for their capability of short-time tracking small-amplitude, low-frequency motions.

Electric Field Encephalography as a tool for functional brain research: a modeling study.

PubMed

Petrov, Yury; Sridhar, Srinivas

2013-01-01

We introduce the notion of Electric Field Encephalography (EFEG) based on measuring electric fields of the brain and demonstrate, using computer modeling, that given the appropriate electric field sensors this technique may have significant advantages over the current EEG technique. Unlike EEG, EFEG can be used to measure brain activity in a contactless and reference-free manner at significant distances from the head surface. Principal component analysis using simulated cortical sources demonstrated that electric field sensors positioned 3 cm away from the scalp and characterized by the same signal-to-noise ratio as EEG sensors provided the same number of uncorrelated signals as scalp EEG. When positioned on the scalp, EFEG sensors provided 2-3 times more uncorrelated signals. This significant increase in the number of uncorrelated signals can be used for more accurate assessment of brain states for non-invasive brain-computer interfaces and neurofeedback applications. It also may lead to major improvements in source localization precision. Source localization simulations for the spherical and Boundary Element Method (BEM) head models demonstrated that the localization errors are reduced two-fold when using electric fields instead of electric potentials. We have identified several techniques that could be adapted for the measurement of the electric field vector required for EFEG and anticipate that this study will stimulate new experimental approaches to utilize this new tool for functional brain research.

On the degree distribution of horizontal visibility graphs associated with Markov processes and dynamical systems: diagrammatic and variational approaches

NASA Astrophysics Data System (ADS)

Lacasa, Lucas

2014-09-01

Dynamical processes can be transformed into graphs through a family of mappings called visibility algorithms, enabling the possibility of (i) making empirical time series analysis and signal processing and (ii) characterizing classes of dynamical systems and stochastic processes using the tools of graph theory. Recent works show that the degree distribution of these graphs encapsulates much information on the signals' variability, and therefore constitutes a fundamental feature for statistical learning purposes. However, exact solutions for the degree distributions are only known in a few cases, such as for uncorrelated random processes. Here we analytically explore these distributions in a list of situations. We present a diagrammatic formalism which computes for all degrees their corresponding probability as a series expansion in a coupling constant which is the number of hidden variables. We offer a constructive solution for general Markovian stochastic processes and deterministic maps. As case tests we focus on Ornstein-Uhlenbeck processes, fully chaotic and quasiperiodic maps. Whereas only for certain degree probabilities can all diagrams be summed exactly, in the general case we show that the perturbation theory converges. In a second part, we make use of a variational technique to predict the complete degree distribution for special classes of Markovian dynamics with fast-decaying correlations. In every case we compare the theory with numerical experiments.

Recurrence time statistics of landslide events simulated by a cellular automaton model

NASA Astrophysics Data System (ADS)

Piegari, Ester; Di Maio, Rosa; Avella, Adolfo

2014-05-01

The recurrence time statistics of a cellular automaton modelling landslide events is analyzed by performing a numerical analysis in the parameter space and estimating Fano factor behaviors. The model is an extended version of the OFC model, which is a paradigm for SOC in non-conserved systems, but it works differently from the original OFC model as a finite value of the driving rate is applied. By driving the system to instability with different rates, the model exhibits a smooth transition from a correlated to an uncorrelated regime as the effect of a change in predominant mechanisms to propagate instability. If the rate at which instability is approached is small, chain processes dominate the landslide dynamics, and power laws govern probability distributions. However, the power-law regime typical of SOC-like systems is found in a range of return intervals that becomes shorter and shorter by increasing the values of the driving rates. Indeed, if the rates at which instability is approached are large, domino processes are no longer active in propagating instability, and large events simply occur because a large number of cells simultaneously reach instability. Such a gradual loss of the effectiveness of the chain propagation mechanism causes the system gradually enter to an uncorrelated regime where recurrence time distributions are characterized by Weibull behaviors. Simulation results are qualitatively compared with those from a recent analysis performed by Witt et al.(Earth Surf. Process. Landforms, 35, 1138, 2010) for the first complete databases of landslide occurrences over a period as large as fifty years. From the comparison with the extensive landslide data set, the numerical analysis suggests that statistics of such landslide data seem to be described by a crossover region between a correlated regime and an uncorrelated regime, where recurrence time distributions are characterized by power-law and Weibull behaviors for short and long return times, respectively. Finally, in such a region of the parameter space, clear indications of temporal correlations and clustering by the Fano factor behaviors support, at least in part, the analysis performed by Witt et al. (2010).

The Importance of the Assumption of Uncorrelated Errors in Psychometric Theory

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.; Patelis, Thanos

2015-01-01

A critical discussion of the assumption of uncorrelated errors in classical psychometric theory and its applications is provided. It is pointed out that this assumption is essential for a number of fundamental results and underlies the concept of parallel tests, the Spearman-Brown's prophecy and the correction for attenuation formulas as well as…

Wavelet analysis for the study of the relations among soil radon anomalies, volcanic and seismic events: the case of Mt. Etna (Italy)

NASA Astrophysics Data System (ADS)

Ferrera, Elisabetta; Giammanco, Salvatore; Cannata, Andrea; Montalto, Placido

2013-04-01

From November 2009 to April 2011 soil radon activity was continuously monitored using a Barasol® probe located on the upper NE flank of Mt. Etna volcano, close either to the Piano Provenzana fault or to the NE-Rift. Seismic and volcanological data have been analyzed together with radon data. We also analyzed air and soil temperature, barometric pressure, snow and rain fall data. In order to find possible correlations among the above parameters, and hence to reveal possible anomalies in the radon time-series, we used different statistical methods: i) multivariate linear regression; ii) cross-correlation; iii) coherence analysis through wavelet transform. Multivariate regression indicated a modest influence on soil radon from environmental parameters (R2 = 0.31). When using 100-days time windows, the R2 values showed wide variations in time, reaching their maxima (~0.63-0.66) during summer. Cross-correlation analysis over 100-days moving averages showed that, similar to multivariate linear regression analysis, the summer period is characterised by the best correlation between radon data and environmental parameters. Lastly, the wavelet coherence analysis allowed a multi-resolution coherence analysis of the time series acquired. This approach allows to study the relations among different signals either in time or frequency domain. It confirmed the results of the previous methods, but also allowed to recognize correlations between radon and environmental parameters at different observation scales (e.g., radon activity changed during strong precipitations, but also during anomalous variations of soil temperature uncorrelated with seasonal fluctuations). Our work suggests that in order to make an accurate analysis of the relations among distinct signals it is necessary to use different techniques that give complementary analytical information. In particular, the wavelet analysis showed to be very effective in discriminating radon changes due to environmental influences from those correlated with impending seismic or volcanic events.

Intermittent fluctuations in the Alcator C-Mod scrape-off layer for ohmic and high confinement mode plasmas

NASA Astrophysics Data System (ADS)

Garcia, O. E.; Kube, R.; Theodorsen, A.; LaBombard, B.; Terry, J. L.

2018-05-01

Plasma fluctuations in the scrape-off layer of the Alcator C-Mod tokamak in ohmic and high confinement modes have been analyzed using gas puff imaging data. In all cases investigated, the time series of emission from a single spatially resolved view into the gas puff are dominated by large-amplitude bursts, attributed to blob-like filament structures moving radially outwards and poloidally. There is a remarkable similarity of the fluctuation statistics in ohmic plasmas and in edge localized mode-free and enhanced D-alpha high confinement mode plasmas. Conditionally averaged waveforms have a two-sided exponential shape with comparable temporal scales and asymmetry, while the burst amplitudes and the waiting times between them are exponentially distributed. The probability density functions and the frequency power spectral densities are similar for all these confinement modes. These results provide strong evidence in support of a stochastic model describing the plasma fluctuations in the scrape-off layer as a super-position of uncorrelated exponential pulses. Predictions of this model are in excellent agreement with experimental measurements in both ohmic and high confinement mode plasmas. The stochastic model thus provides a valuable tool for predicting fluctuation-induced plasma-wall interactions in magnetically confined fusion plasmas.

Exciton Correlations in Intramolecular Singlet Fission

DOE PAGES

Sanders, Samuel N.; Kumarasamy, Elango; Pun, Andrew B.; ...

2016-05-16

We have synthesized a series of asymmetric pentacene-tetracene heterodimers with a variable-length conjugated bridge that undergo fast and efficient intramolecular singlet fission (iSF). These compounds have distinct singlet and triplet energies, which allow us to study the spatial dynamics of excitons during the iSF process, including the significant role of exciton correlations in promoting triplet pair generation and recombination. We demonstrate that the primary photoexcitations in conjugated dimers are delocalized singlets that enable fast and efficient iSF. However, in these asymmetric dimers, the singlet becomes more localized on the lower energy unit as the length of the bridge is increased,more » slowing down iSF relative to analogous symmetric dimers. We resolve the recombination kinetics of the inequivalent triplets produced via iSF, and find that they primarily decay via concerted processes. By identifying different decay channels, including delayed fluorescence via triplet-triplet annihilation, we can separate transient species corresponding to both correlated triplet pairs and uncorrelated triplets. Recombination of the triplet pair proceeds rapidly despite our experimental and theoretical demonstration that individual triplets are highly localized and unable to be transported across the conjugated linker. In this class of compounds, the rate of formation and yield of uncorrelated triplets increases with bridge length. Overall, these constrained, asymmetric systems provide a unique platform to isolate and study transient species essential for singlet fission, which are otherwise difficult to observe in symmetric dimers or condensed phases.« less

The Expected Sample Variance of Uncorrelated Random Variables with a Common Mean and Some Applications in Unbalanced Random Effects Models

ERIC Educational Resources Information Center

Vardeman, Stephen B.; Wendelberger, Joanne R.

2005-01-01

There is a little-known but very simple generalization of the standard result that for uncorrelated random variables with common mean [mu] and variance [sigma][superscript 2], the expected value of the sample variance is [sigma][superscript 2]. The generalization justifies the use of the usual standard error of the sample mean in possibly…

Encounter Models for the Littoral Regions of the National Airspace System

DTIC Science & Technology

2010-09-15

Jeff Richardson, Steven Schimmelpfennig, Richard Whitlock, Lt. Han Saydam, Lt. Tanuxay Keooudom, James Evans, TSgt. Christopher Cosper, Lt. Luke Marron...24 17 Correlated geometric feature comparison. 25 A- l Aircraft vertical rate in uncorrelated encounters. 31 A-2 Uncorrelated continuous feature...in correlated encounters. 35 B- l Approach angle (/3) and bearing (x) definition. 39 C- l Horizontal plane encounter initialization. 42 C-2

TU-F-CAMPUS-J-05: Effect of Uncorrelated Noise Texture On Computed Tomography Quantitative Image Features

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

Oliver, J; Budzevich, M; Moros, E

Purpose: To investigate the relationship between quantitative image features (i.e. radiomics) and statistical fluctuations (i.e. electronic noise) in clinical Computed Tomography (CT) using the standardized American College of Radiology (ACR) CT accreditation phantom and patient images. Methods: Three levels of uncorrelated Gaussian noise were added to CT images of phantom and patients (20) acquired in static mode and respiratory tracking mode. We calculated the noise-power spectrum (NPS) of the original CT images of the phantom, and of the phantom images with added Gaussian noise with means of 50, 80, and 120 HU. Concurrently, on patient images (original and noise-added images),more » image features were calculated: 14 shape, 19 intensity (1st order statistics from intensity volume histograms), 18 GLCM features (2nd order statistics from grey level co-occurrence matrices) and 11 RLM features (2nd order statistics from run-length matrices). These features provide the underlying structural information of the images. GLCM (size 128x128) was calculated with a step size of 1 voxel in 13 directions and averaged. RLM feature calculation was performed in 13 directions with grey levels binning into 128 levels. Results: Adding the electronic noise to the images modified the quality of the NPS, shifting the noise from mostly correlated to mostly uncorrelated voxels. The dramatic increase in noise texture did not affect image structure/contours significantly for patient images. However, it did affect the image features and textures significantly as demonstrated by GLCM differences. Conclusion: Image features are sensitive to acquisition factors (simulated by adding uncorrelated Gaussian noise). We speculate that image features will be more difficult to detect in the presence of electronic noise (an uncorrelated noise contributor) or, for that matter, any other highly correlated image noise. This work focuses on the effect of electronic, uncorrelated, noise and future work shall examine the influence of changes in quantum noise on the features. J. Oliver was supported by NSF FGLSAMP BD award HRD #1139850 and the McKnight Doctoral Fellowship.« less

Impact of degree heterogeneity on the behavior of trapping in Koch networks

NASA Astrophysics Data System (ADS)

Zhang, Zhongzhi; Gao, Shuyang; Xie, Wenlei

2010-12-01

Previous work shows that the mean first-passage time (MFPT) for random walks to a given hub node (node with maximum degree) in uncorrelated random scale-free networks is closely related to the exponent γ of power-law degree distribution P(k )˜k-γ, which describes the extent of heterogeneity of scale-free network structure. However, extensive empirical research indicates that real networked systems also display ubiquitous degree correlations. In this paper, we address the trapping issue on the Koch networks, which is a special random walk with one trap fixed at a hub node. The Koch networks are power-law with the characteristic exponent γ in the range between 2 and 3, they are either assortative or disassortative. We calculate exactly the MFPT that is the average of first-passage time from all other nodes to the trap. The obtained explicit solution shows that in large networks the MFPT varies lineally with node number N, which is obviously independent of γ and is sharp contrast to the scaling behavior of MFPT observed for uncorrelated random scale-free networks, where γ influences qualitatively the MFPT of trapping problem.

An intercomparison of aircraft instrumentation for tropospheric measurements of sulfur dioxide

NASA Technical Reports Server (NTRS)

Gregory, Gerald L.; Davis, Douglas D.; Beltz, Nobert; Bandy, Alan R.; Ferek, Ronald J.; Thornton, Donald C.

1993-01-01

As part of the NASA Tropospheric Chemistry Program, a series of field intercomparisons have been conducted to evaluate the state-of-the art for measuring key tropospheric species. One of the objectives of the third intercomparison campaign in this series, Chemical Instrumentation Test and Evaluation 3 (CITE 3), was to evaluate instrumentation for making reliable tropospheric aircraft measurements of sulfur dioxide, dimethyl sulfide, hydrogen sulfide, carbon disulfide, and carbonyl sulfide. This paper reports the results of the intercomparisons of five sulfur dioxide measurement methods ranging from filter techniques, in which samples collected in flight are returned to the laboratory for analyses (chemiluminescent or ion chromatographic), to near real-time, in-flight measurements via gas chromatographic, mass spectrometric, and chemiluminescent techniques. All techniques showed some tendency to track sizeable changes in ambient SO2 such as those associated with altitude changes. For SO2 mixing ratios in the range of 200 pptv to a few ppbv, agreement among the techniques varies from about 30% to several orders of magnitude, depending upon the pair of measurements intercompared. For SO2 mixing ratios less than 200 pptv, measurements from the techniques are uncorrelated. In general, observed differences in the measurement of standards do not account for the flight results. The CITE 3 results do not unambiguously identify one or more of the measurement techniques as providing valid or invalid SO2 measurements, but identify the range of 'potential' uncertainty in SO2 measurements reported by currently available instrumentation and as measured under realistic aircraft environments.

Above the Noise: The Search for Periodicities in the Inner Heliosphere

NASA Astrophysics Data System (ADS)

Threlfall, James; De Moortel, Ineke; Conlon, Thomas

2017-11-01

Remote sensing of coronal and heliospheric periodicities can provide vital insight into the local conditions and dynamics of the solar atmosphere. We seek to trace long (one hour or longer) periodic oscillatory signatures (previously identified above the limb in the corona by, e.g., Telloni et al. in Astrophys. J. 767, 138, 2013) from their origin at the solar surface out into the heliosphere. To do this, we combined on-disk measurements taken by the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) and concurrent extreme ultra-violet (EUV) and coronagraph data from one of the Solar Terrestrial Relations Observatory (STEREO) spacecraft to study the evolution of two active regions in the vicinity of an equatorial coronal hole over several days in early 2011. Fourier and wavelet analysis of signals were performed. Applying white-noise-based confidence levels to the power spectra associated with detrended intensity time series yields detections of oscillatory signatures with periods from 6 - 13 hours in both AIA and STEREO data. As was found by Telloni et al. (2013), these signatures are aligned with local magnetic structures. However, typical spectral power densities all vary substantially as a function of period, indicating spectra dominated by red (rather than white) noise. Contrary to the white-noise-based results, applying global confidence levels based on a generic background-noise model (allowing a combination of white noise, red noise, and transients following Auchère et al. in Astrophys. J. 825, 110, 2016) without detrending the time series uncovers only sporadic, spatially uncorrelated evidence of periodic signatures in either instrument. Automating this method to individual pixels in the STEREO/COR coronagraph field of view is non-trivial. Efforts to identify and implement a more robust automatic background noise model fitting procedure are needed.

Investigation of market efficiency and Financial Stability between S&P 500 and London Stock Exchange: Monthly and yearly Forecasting of Time Series Stock Returns using ARMA model

NASA Astrophysics Data System (ADS)

Rounaghi, Mohammad Mahdi; Nassir Zadeh, Farzaneh

2016-08-01

We investigated the presence and changes in, long memory features in the returns and volatility dynamics of S&P 500 and London Stock Exchange using ARMA model. Recently, multifractal analysis has been evolved as an important way to explain the complexity of financial markets which can hardly be described by linear methods of efficient market theory. In financial markets, the weak form of the efficient market hypothesis implies that price returns are serially uncorrelated sequences. In other words, prices should follow a random walk behavior. The random walk hypothesis is evaluated against alternatives accommodating either unifractality or multifractality. Several studies find that the return volatility of stocks tends to exhibit long-range dependence, heavy tails, and clustering. Because stochastic processes with self-similarity possess long-range dependence and heavy tails, it has been suggested that self-similar processes be employed to capture these characteristics in return volatility modeling. The present study applies monthly and yearly forecasting of Time Series Stock Returns in S&P 500 and London Stock Exchange using ARMA model. The statistical analysis of S&P 500 shows that the ARMA model for S&P 500 outperforms the London stock exchange and it is capable for predicting medium or long horizons using real known values. The statistical analysis in London Stock Exchange shows that the ARMA model for monthly stock returns outperforms the yearly. ​A comparison between S&P 500 and London Stock Exchange shows that both markets are efficient and have Financial Stability during periods of boom and bust.

Balance of baryon number in the quark coalescence model

NASA Astrophysics Data System (ADS)

Bialas, A.; Rafelski, J.

2006-02-01

The charge and baryon balance functions are studied in the coalescence hadronization mechanism of quark-gluon plasma. Assuming that in the plasma phase the qqbar pairs form uncorrelated clusters whose decay is also uncorrelated, one can understand the observed small width of the charge balance function in the Gaussian approximation. The coalescence model predicts even smaller width of the baryon-antibaryon balance function: σBBbar /σ+ - =√{ 2 / 3 }.

Resistance to change and frequency of response-dependent stimuli uncorrelated with reinforcement.

PubMed

Podlesnik, Christopher A; Jimenez-Gomez, Corina; Ward, Ryan D; Shahan, Timothy A

2009-09-01

Stimuli uncorrelated with reinforcement have been shown to enhance response rates and resistance to disruption; however, the effects of different rates of stimulus presentations have not been assessed. In two experiments, we assessed the effects of adding different rates of response-dependent brief stimuli uncorrelated with primary reinforcement on relative response rates and resistance to change. In both experiments, pigeons responded on variable-interval 60-s schedules of food reinforcement in two components of a multiple schedule, and brief response-dependent keylight-color changes were added to one or both components. Although relative response rates were not systematically affected in either experiment, relative resistance to presession feeding and extinction were. In Experiment 1, adding stimuli on a variable-interval schedule to one component of a multiple schedule either at a low rate (1 per min) for one group or at a high rate (4 per min) for another group similarly increased resistance to disruption in the components with added stimuli. When high and low rates of stimuli were presented across components (i.e., within subjects) in Experiment 2, however, relative resistance to disruption was greater in the component presenting stimuli at a lower rate. These results suggest that stimuli uncorrelated with food reinforcement do not strengthen responding in the same way as primary reinforcers.

Decreased resting-state brain activity complexity in schizophrenia characterized by both increased regularity and randomness.

PubMed

Yang, Albert C; Hong, Chen-Jee; Liou, Yin-Jay; Huang, Kai-Lin; Huang, Chu-Chung; Liu, Mu-En; Lo, Men-Tzung; Huang, Norden E; Peng, Chung-Kang; Lin, Ching-Po; Tsai, Shih-Jen

2015-06-01

Schizophrenia is characterized by heterogeneous pathophysiology. Using multiscale entropy (MSE) analysis, which enables capturing complex dynamics of time series, we characterized MSE patterns of blood-oxygen-level-dependent (BOLD) signals across different time scales and determined whether BOLD activity in patients with schizophrenia exhibits increased complexity (increased entropy in all time scales), decreased complexity toward regularity (decreased entropy in all time scales), or decreased complexity toward uncorrelated randomness (high entropy in short time scales followed by decayed entropy as the time scale increases). We recruited 105 patients with schizophrenia with an age of onset between 18 and 35 years and 210 age- and sex-matched healthy volunteers. Results showed that MSE of BOLD signals in patients with schizophrenia exhibited two routes of decreased BOLD complexity toward either regular or random patterns. Reduced BOLD complexity toward regular patterns was observed in the cerebellum and temporal, middle, and superior frontal regions, and reduced BOLD complexity toward randomness was observed extensively in the inferior frontal, occipital, and postcentral cortices as well as in the insula and middle cingulum. Furthermore, we determined that the two types of complexity change were associated differently with psychopathology; specifically, the regular type of BOLD complexity change was associated with positive symptoms of schizophrenia, whereas the randomness type of BOLD complexity was associated with negative symptoms of the illness. These results collectively suggested that resting-state dynamics in schizophrenia exhibit two routes of pathologic change toward regular or random patterns, which contribute to the differences in syndrome domains of psychosis in patients with schizophrenia. © 2015 Wiley Periodicals, Inc.

More superimposition for contrast-modulated than luminance-modulated stimuli during binocular rivalry.

PubMed

Skerswetat, Jan; Formankiewicz, Monika A; Waugh, Sarah J

2018-01-01

Luminance-modulated noise (LM) and contrast-modulated noise (CM) gratings were presented with interocularly correlated, uncorrelated and anti-correlated binary noise to investigate their contributions to mixed percepts, specifically piecemeal and superimposition, during binocular rivalry. Stimuli were sine-wave gratings of 2 c/deg presented within 2 deg circular apertures. The LM stimulus contrast was 0.1 and the CM stimulus modulation depth was 1.0, equating to approximately 5 and 7 times detection threshold, respectively. Twelve 45 s trials, per noise configuration, were carried out. Fifteen participants with normal vision indicated via button presses whether an exclusive, piecemeal or superimposed percept was seen. For all noise conditions LM stimuli generated more exclusive visibility, and lower proportions of superimposition. CM stimuli led to greater proportions and longer periods of superimposition. For both stimulus types, correlated interocular noise generated more superimposition than did anti- or uncorrelated interocular noise. No significant effect of stimulus type (LM vs CM) or noise configuration (correlated, uncorrelated, anti-correlated) on piecemeal perception was found. Exclusive visibility was greater in proportion, and perceptual changes more numerous, during binocular rivalry for CM stimuli when interocular noise was not correlated. This suggests that mutual inhibition, initiated by non-correlated noise CM gratings, occurs between neurons processing luminance noise (first-order component), as well as those processing gratings (second-order component). Therefore, first- and second-order components can contribute to overall binocular rivalry responses. We suggest the addition of a new well to the current energy landscape model for binocular rivalry that takes superimposition into account. Copyright © 2017 Elsevier Ltd. All rights reserved.

Blind source separation problem in GPS time series

NASA Astrophysics Data System (ADS)

Gualandi, A.; Serpelloni, E.; Belardinelli, M. E.

2016-04-01

A critical point in the analysis of ground displacement time series, as those recorded by space geodetic techniques, is the development of data-driven methods that allow the different sources of deformation to be discerned and characterized in the space and time domains. Multivariate statistic includes several approaches that can be considered as a part of data-driven methods. A widely used technique is the principal component analysis (PCA), which allows us to reduce the dimensionality of the data space while maintaining most of the variance of the dataset explained. However, PCA does not perform well in finding the solution to the so-called blind source separation (BSS) problem, i.e., in recovering and separating the original sources that generate the observed data. This is mainly due to the fact that PCA minimizes the misfit calculated using an L2 norm (χ 2), looking for a new Euclidean space where the projected data are uncorrelated. The independent component analysis (ICA) is a popular technique adopted to approach the BSS problem. However, the independence condition is not easy to impose, and it is often necessary to introduce some approximations. To work around this problem, we test the use of a modified variational Bayesian ICA (vbICA) method to recover the multiple sources of ground deformation even in the presence of missing data. The vbICA method models the probability density function (pdf) of each source signal using a mix of Gaussian distributions, allowing for more flexibility in the description of the pdf of the sources with respect to standard ICA, and giving a more reliable estimate of them. Here we present its application to synthetic global positioning system (GPS) position time series, generated by simulating deformation near an active fault, including inter-seismic, co-seismic, and post-seismic signals, plus seasonal signals and noise, and an additional time-dependent volcanic source. We evaluate the ability of the PCA and ICA decomposition techniques in explaining the data and in recovering the original (known) sources. Using the same number of components, we find that the vbICA method fits the data almost as well as a PCA method, since the χ 2 increase is less than 10 % the value calculated using a PCA decomposition. Unlike PCA, the vbICA algorithm is found to correctly separate the sources if the correlation of the dataset is low (<0.67) and the geodetic network is sufficiently dense (ten continuous GPS stations within a box of side equal to two times the locking depth of a fault where an earthquake of Mw >6 occurred). We also provide a cookbook for the use of the vbICA algorithm in analyses of position time series for tectonic and non-tectonic applications.

Retention capacity of correlated surfaces.

PubMed

Schrenk, K J; Araújo, N A M; Ziff, R M; Herrmann, H J

2014-06-01

We extend the water retention model [C. L. Knecht et al., Phys. Rev. Lett. 108, 045703 (2012)] to correlated random surfaces. We find that the retention capacity of discrete random landscapes is strongly affected by spatial correlations among the heights. This phenomenon is related to the emergence of power-law scaling in the lake volume distribution. We also solve the uncorrelated case exactly for a small lattice and present bounds on the retention of uncorrelated landscapes.

Role of protein fluctuation correlations in electron transfer in photosynthetic complexes.

PubMed

Nesterov, Alexander I; Berman, Gennady P

2015-04-01

We consider the dependence of the electron transfer in photosynthetic complexes on correlation properties of random fluctuations of the protein environment. The electron subsystem is modeled by a finite network of connected electron (exciton) sites. The fluctuations of the protein environment are modeled by random telegraph processes, which act either collectively (correlated) or independently (uncorrelated) on the electron sites. We derived an exact closed system of first-order linear differential equations with constant coefficients, for the average density matrix elements and for their first moments. Under some conditions, we obtained analytic expressions for the electron transfer rates and found the range of parameters for their applicability by comparing with the exact numerical simulations. We also compared the correlated and uncorrelated regimes and demonstrated numerically that the uncorrelated fluctuations of the protein environment can, under some conditions, either increase or decrease the electron transfer rates.

SER Analysis of MPPM-Coded MIMO-FSO System over Uncorrelated and Correlated Gamma-Gamma Atmospheric Turbulence Channels

NASA Astrophysics Data System (ADS)

Khallaf, Haitham S.; Garrido-Balsells, José M.; Shalaby, Hossam M. H.; Sampei, Seiichi

2015-12-01

The performance of multiple-input multiple-output free space optical (MIMO-FSO) communication systems, that adopt multipulse pulse position modulation (MPPM) techniques, is analyzed. Both exact and approximate symbol-error rates (SERs) are derived for both cases of uncorrelated and correlated channels. The effects of background noise, receiver shot-noise, and atmospheric turbulence are taken into consideration in our analysis. The random fluctuations of the received optical irradiance, produced by the atmospheric turbulence, is modeled by the widely used gamma-gamma statistical distribution. Uncorrelated MIMO channels are modeled by the α-μ distribution. A closed-form expression for the probability density function of the optical received irradiance is derived for the case of correlated MIMO channels. Using our analytical expressions, the degradation of the system performance with the increment of the correlation coefficients between MIMO channels is corroborated.

How is spatial context learning integrated over signal versus noise? A primacy effect in contextual cueing.

PubMed

Jungé, Justin A; Scholl, Brian J; Chun, Marvin M

2007-01-01

Over repeated exposure to particular visual search displays, subjects are able to implicitly extract regularities that then make search more efficient-a phenomenon known as contextual cueing. Here we explore how the learning involved in contextual cueing is formed, maintained, and updated over experience. During an initial training phase, a group of signal first subjects searched through a series of predictive displays (where distractor locations were perfectly correlated with the target location), followed with no overt break by a series of unpredictive displays (where repeated contexts were uncorrelated with target locations). A second noise first group of subjects encountered the unpredictive displays followed by the predictive displays. Despite the fact that both groups had the same overall exposure to signal and noise, only the signal first group demonstrated subsequent contextual cueing. This primacy effect indicates that initial experience can result in hypotheses about regularities in displays-or the lack thereof-which then become resistant to updating. The absence of regularities in early stages of training even blocked observers from learning predictive regularities later on.

How is spatial context learning integrated over signal versus noise? A primacy effect in contextual cueing

PubMed Central

Jungé, Justin A.; Scholl, Brian J.; Chun, Marvin M.

2008-01-01

Over repeated exposure to particular visual search displays, subjects are able to implicitly extract regularities that then make search more efficient—a phenomenon known as contextual cueing. Here we explore how the learning involved in contextual cueing is formed, maintained, and updated over experience. During an initial training phase, a group of signal first subjects searched through a series of predictive displays (where distractor locations were perfectly correlated with the target location), followed with no overt break by a series of unpredictive displays (where repeated contexts were uncorrelated with target locations). A second noise first group of subjects encountered the unpredictive displays followed by the predictive displays. Despite the fact that both groups had the same overall exposure to signal and noise, only the signal first group demonstrated subsequent contextual cueing. This primacy effect indicates that initial experience can result in hypotheses about regularities in displays—or the lack thereof—which then become resistant to updating. The absence of regularities in early stages of training even blocked observers from learning predictive regularities later on. PMID:18725966

Anomalies in the Spectra of the Uncorrelated Components of the Electric Field of the Earth at Frequencies that are Multiples of the Frequencies of Rotation of Relativistic Binary Star Systems

NASA Astrophysics Data System (ADS)

Grunskaya, L. V.; Isakevich, V. V.; Isakevich, D. V.

2018-05-01

A system is constructed, which, on the basis of extensive experimental material and the use of eigenoscopy, has allowed us to detect anomalies in the spectra of uncorrelated components localized near the rotation frequencies and twice the rotation frequencies of relativistic binary star systems with vanishingly low probability of false alarm, not exceeding 10-17.

Tests of Hypotheses Arising In the Correlated Random Coefficient Model*

PubMed Central

Heckman, James J.; Schmierer, Daniel

2010-01-01

This paper examines the correlated random coefficient model. It extends the analysis of Swamy (1971), who pioneered the uncorrelated random coefficient model in economics. We develop the properties of the correlated random coefficient model and derive a new representation of the variance of the instrumental variable estimator for that model. We develop tests of the validity of the correlated random coefficient model against the null hypothesis of the uncorrelated random coefficient model. PMID:21170148

Index-Based Insurance Contracts to FOSTER Cooperation Between Agents Exposed to Uncorrelated Drought and Flooding Risks

NASA Astrophysics Data System (ADS)

Denaro, S.; Giuliani, M.; Castelletti, A.; Characklis, G. W.

2017-12-01

Worldwide, conflict over shared water resources is exacerbated by population growth, economic development and climate change. In multi-purpose water systems, stakeholders can face higher financial risks as a consequence of increased hydrological uncertainty and recurrent extreme events. In this context, a financial hedging tool able to bundle together the uncorrelated risks faced by different stakeholders may be an efficient solution to both foster cooperation and manage the financial losses associated with extreme events. In this work we explore the potential of risk diversification strategies involving index-based insurance joint contract solutions, to manage financial risk in a multi-purpose water system prone to both drought and flood risk. Risk diversification can allow for reduced insurance premiums in situations in which the bundled risks are entirely, or mostly, uncorrelated. Jointly covering flood and drought related risks from competing users in the same geographic area represents a novel application. The approach is demonstrated using a case study on Lake Maggiore, a regulated lake whose management is highly controversial due to numerous and competing human activities. In particular we focus on the ongoing conflict among the lakeshore population, affected by flood risk, and the downstream farmers' districts, facing drought related losses. Results are promising and indicate that bundling uncorrelated risks from competing users is beneficial to both promoting insurance premium affordability and facilitating collaboration schemes at the catchment scale.

Wide-band profile domain pulsar timing analysis

NASA Astrophysics Data System (ADS)

Lentati, L.; Kerr, M.; Dai, S.; Hobson, M. P.; Shannon, R. M.; Hobbs, G.; Bailes, M.; Bhat, N. D. Ramesh; Burke-Spolaor, S.; Coles, W.; Dempsey, J.; Lasky, P. D.; Levin, Y.; Manchester, R. N.; Osłowski, S.; Ravi, V.; Reardon, D. J.; Rosado, P. A.; Spiewak, R.; van Straten, W.; Toomey, L.; Wang, J.; Wen, L.; You, X.; Zhu, X.

2017-04-01

We extend profile domain pulsar timing to incorporate wide-band effects such as frequency-dependent profile evolution and broad-band shape variation in the pulse profile. We also incorporate models for temporal variations in both pulse width and in the separation in phase of the main pulse and interpulse. We perform the analysis with both nested sampling and Hamiltonian Monte Carlo methods. In the latter case, we introduce a new parametrization of the posterior that is extremely efficient in the low signal-to-noise regime and can be readily applied to a wide range of scientific problems. We apply this methodology to a series of simulations, and to between seven and nine years of observations for PSRs J1713+0747, J1744-1134 and J1909-3744 with frequency coverage that spans 700-3600 Mhz. We use a smooth model for profile evolution across the full frequency range, and compare smooth and piecewise models for the temporal variations in dispersion measure (DM). We find that the profile domain framework consistently results in improved timing precision compared to the standard analysis paradigm by as much as 40 per cent for timing parameters. Incorporating smoothness in the DM variations into the model further improves timing precision by as much as 30 per cent. For PSR J1713+0747, we also detect pulse shape variation uncorrelated between epochs, which we attribute to variation intrinsic to the pulsar at a level consistent with previously published analyses. Not accounting for this shape variation biases the measured arrival times at the level of ˜30 ns, the same order of magnitude as the expected shift due to gravitational waves in the pulsar timing band.

A link between prompt optical and prompt gamma-ray emission in gamma-ray bursts.

PubMed

Vestrand, W T; Wozniak, P R; Wren, J A; Fenimore, E E; Sakamoto, T; White, R R; Casperson, D; Davis, H; Evans, S; Galassi, M; McGowan, K E; Schier, J A; Asa, J W; Barthelmy, S D; Cummings, J R; Gehrels, N; Hullinger, D; Krimm, H A; Markwardt, C B; McLean, K; Palmer, D; Parsons, A; Tueller, J

2005-05-12

The prompt optical emission that arrives with the gamma-rays from a cosmic gamma-ray burst (GRB) is a signature of the engine powering the burst, the properties of the ultra-relativistic ejecta of the explosion, and the ejecta's interactions with the surroundings. Until now, only GRB 990123 had been detected at optical wavelengths during the burst phase. Its prompt optical emission was variable and uncorrelated with the prompt gamma-ray emission, suggesting that the optical emission was generated by a reverse shock arising from the ejecta's collision with surrounding material. Here we report prompt optical emission from GRB 041219a. It is variable and correlated with the prompt gamma-rays, indicating a common origin for the optical light and the gamma-rays. Within the context of the standard fireball model of GRBs, we attribute this new optical component to internal shocks driven into the burst ejecta by variations of the inner engine. The correlated optical emission is a direct probe of the jet isolated from the medium. The timing of the uncorrelated optical emission is strongly dependent on the nature of the medium.

Equivalence of time and aperture domain additive noise in ultrasound coherence.

PubMed

Bottenus, Nick B; Trahey, Gregg E

2015-01-01

Ultrasonic echoes backscattered from diffuse media, recorded by an array transducer and appropriately focused, demonstrate coherence predicted by the van Cittert-Zernike theorem. Additive noise signals from off-axis scattering, reverberation, phase aberration, and electronic (thermal) noise can all superimpose incoherent or partially coherent signals onto the recorded echoes, altering the measured coherence. An expression is derived to describe the effect of uncorrelated random channel noise in terms of the noise-to-signal ratio. Equivalent descriptions are made in the aperture dimension to describe uncorrelated magnitude and phase apodizations of the array. Binary apodization is specifically described as an example of magnitude apodization and adjustments are presented to minimize the artifacts caused by finite signal length. The effects of additive noise are explored in short-lag spatial coherence imaging, an image formation technique that integrates the calculated coherence curve of acquired signals up to a small fraction of the array length for each lateral and axial location. A derivation of the expected contrast as a function of noise-to-signal ratio is provided and validation is performed in simulation.

FBK Optical Data Association in a Multi-Hypothesis Framework with Maneuvers

NASA Astrophysics Data System (ADS)

Faber, W. R.; Hussein, I. I.; Kent, J. T.; Bhattacharjee, S. Jah, M. K.

In Space Situational Awareness (SSA), one may encounter scenarios where the measurements received at a certain time do not correlate to a known Resident Space Object (RSO). Without information that uniquely assigns the measurement to a particular RSO there can be no certainty on the identity of the object. It could be that the measurement was produced by clutter or perhaps a newly birthed RSO. It is also a possibility that the measurement came from a previously known object that maneuvered away from its predicted location. Typically, tracking methods tend to associate uncorrelated measurements to new objects and wait for more information to determine the true RSO population. This can lead to the loss of object custody. The goal of this paper is to utilize a multiple hypothesis framework coupled with some knowledge of RSO maneuvers that allows the user to maintain object custody in scenarios with uncorrelated optical measurement returns. This is achieved by fitting a Fisher-Bingham-Kent type distribution to the hypothesized maneuvers for accurate data association using directional discriminant analysis.

The localization of focal heart activity via body surface potential measurements: tests in a heterogeneous torso phantom

NASA Astrophysics Data System (ADS)

Wetterling, F.; Liehr, M.; Schimpf, P.; Liu, H.; Haueisen, J.

2009-09-01

The non-invasive localization of focal heart activity via body surface potential measurements (BSPM) could greatly benefit the understanding and treatment of arrhythmic heart diseases. However, the in vivo validation of source localization algorithms is rather difficult with currently available measurement techniques. In this study, we used a physical torso phantom composed of different conductive compartments and seven dipoles, which were placed in the anatomical position of the human heart in order to assess the performance of the Recursively Applied and Projected Multiple Signal Classification (RAP-MUSIC) algorithm. Electric potentials were measured on the torso surface for single dipoles with and without further uncorrelated or correlated dipole activity. The localization error averaged 11 ± 5 mm over 22 dipoles, which shows the ability of RAP-MUSIC to distinguish an uncorrelated dipole from surrounding sources activity. For the first time, real computational modelling errors could be included within the validation procedure due to the physically modelled heterogeneities. In conclusion, the introduced heterogeneous torso phantom can be used to validate state-of-the-art algorithms under nearly realistic measurement conditions.

Polar ice magnetization: Comparison of results from NorthGRIP (Greenland) and Vostok (Antarctica) ice cores

NASA Astrophysics Data System (ADS)

Lanci, L.; Kent, D. V.

2007-12-01

Low temperature measurements of isothermal remanent magnetization (IRM) in Greenland ice spanning the last glacial and Holocene have shown that ice samples contain a measurable concentration of magnetic minerals which are part of the atmospheric aerosol. Assuming that the source materials do not change much with time, the concentration of magnetic minerals should be proportional to the measured concentration of dust in ice. We have indeed found a consistent linear relationship with the contents of dust. However, the linear relationship between low temperature ice magnetization vs. dust concentration has an offset, which when extrapolated to zero dust concentration would seemingly indicate that a significantly large magnetization corresponds to a null amount of dust in ice. Thermal relaxation experiments have shown that magnetic grains of nanometric size carry virtually all the uncorrelated magnetization. Magnetic measurements in Antarctic ice cores confirm the existence of a similar nanometric-size magnetic fraction, which also appear uncorrelated with measured aerosol concentration. The magnitude of the uncorrelated magnetization from Vostok is similar to that measured in NorthGRIP ice. Measurements of IRM at 250K suggest that the SP magnetic particles are in the size range of about 7-17 nm, which is compatible with the expected size of particles produced by ablation and subsequent condensation of meteorites in the atmosphere. The concentration of extraterrestrial material in NorthGRIP ice was estimated from the magnetic relaxation data based on a crude estimate of chondritic Ms. The resulting concentration of 0.78±0.22 ppb for Greenland is in good agreement with the outcome based on published iridium concentrations; a virtually identical concentration of 0.53±0.18 ppb has been measured in Vostok ice core.

Relations among soil radon, environmental parameters, volcanic and seismic events at Mt. Etna (Italy)

NASA Astrophysics Data System (ADS)

Giammanco, S.; Ferrera, E.; Cannata, A.; Montalto, P.; Neri, M.

2013-12-01

From November 2009 to April 2011 soil radon activity was continuously monitored using a Barasol probe located on the upper NE flank of Mt. Etna volcano (Italy), close both to the Piano Provenzana fault and to the NE-Rift. Seismic, volcanological and radon data were analysed together with data on environmental parameters, such as air and soil temperature, barometric pressure, snow and rain fall. In order to find possible correlations among the above parameters, and hence to reveal possible anomalous trends in the radon time-series, we used different statistical methods: i) multivariate linear regression; ii) cross-correlation; iii) coherence analysis through wavelet transform. Multivariate regression indicated a modest influence on soil radon from environmental parameters (R2 = 0.31). When using 100-day time windows, the R2 values showed wide variations in time, reaching their maxima (~0.63-0.66) during summer. Cross-correlation analysis over 100-day moving averages showed that, similar to multivariate linear regression analysis, the summer period was characterised by the best correlation between radon data and environmental parameters. Lastly, the wavelet coherence analysis allowed a multi-resolution coherence analysis of the time series acquired. This approach allowed to study the relations among different signals either in the time or in the frequency domain. It confirmed the results of the previous methods, but also allowed to recognize correlations between radon and environmental parameters at different observation scales (e.g., radon activity changed during strong precipitations, but also during anomalous variations of soil temperature uncorrelated with seasonal fluctuations). Using the above analysis, two periods were recognized when radon variations were significantly correlated with marked soil temperature changes and also with local seismic or volcanic activity. This allowed to produce two different physical models of soil gas transport that explain the observed anomalies. Our work suggests that in order to make an accurate analysis of the relations among different signals it is necessary to use different techniques that give complementary analytical information. In particular, the wavelet analysis showed to be the most effective in discriminating radon changes due to environmental influences from those correlated with impending seismic or volcanic events.

Scaling of the space-time correlation function of particle currents in a suspension of hard-sphere-like particles: exposing when the motion of particles is Brownian.

PubMed

van Megen, W; Martinez, V A; Bryant, G

2009-12-18

The current correlation function is determined from dynamic light scattering measurements of a suspension of particles with hard spherelike interactions. For suspensions in thermodynamic equilibrium we find scaling of the space and time variables of the current correlation function. This finding supports the notion that the movement of suspended particles can be described in terms of uncorrelated Brownian encounters. However, in the metastable fluid, at volume fractions above freezing, this scaling fails.

Long- and short-time analysis of heartbeat sequences: correlation with mortality risk in congestive heart failure patients.

PubMed

Allegrini, P; Balocchi, R; Chillemi, S; Grigolini, P; Hamilton, P; Maestri, R; Palatella, L; Raffaelli, G

2003-06-01

We analyze RR heartbeat sequences with a dynamic model that satisfactorily reproduces both the long- and the short-time statistical properties of heart beating. These properties are expressed quantitatively by means of two significant parameters, the scaling delta concerning the asymptotic effects of long-range correlation, and the quantity 1-pi establishing the amount of uncorrelated fluctuations. We find a correlation between the position in the phase space (delta, pi) of patients with congestive heart failure and their mortality risk.

Separation of the low-frequency atmospheric variability into non-Gaussian multidimensional sources by Independent Subspace Analysis

NASA Astrophysics Data System (ADS)

Pires, Carlos; Ribeiro, Andreia

2016-04-01

An efficient nonlinear method of statistical source separation of space-distributed non-Gaussian distributed data is proposed. The method relies in the so called Independent Subspace Analysis (ISA), being tested on a long time-series of the stream-function field of an atmospheric quasi-geostrophic 3-level model (QG3) simulating the winter's monthly variability of the Northern Hemisphere. ISA generalizes the Independent Component Analysis (ICA) by looking for multidimensional and minimally dependent, uncorrelated and non-Gaussian distributed statistical sources among the rotated projections or subspaces of the multivariate probability distribution of the leading principal components of the working field whereas ICA restrict to scalar sources. The rationale of that technique relies upon the projection pursuit technique, looking for data projections of enhanced interest. In order to accomplish the decomposition, we maximize measures of the sources' non-Gaussianity by contrast functions which are given by squares of nonlinear, cross-cumulant-based correlations involving the variables spanning the sources. Therefore sources are sought matching certain nonlinear data structures. The maximized contrast function is built in such a way that it provides the minimization of the mean square of the residuals of certain nonlinear regressions. The issuing residuals, followed by spherization, provide a new set of nonlinear variable changes that are at once uncorrelated, quasi-independent and quasi-Gaussian, representing an advantage with respect to the Independent Components (scalar sources) obtained by ICA where the non-Gaussianity is concentrated into the non-Gaussian scalar sources. The new scalar sources obtained by the above process encompass the attractor's curvature thus providing improved nonlinear model indices of the low-frequency atmospheric variability which is useful since large circulation indices are nonlinearly correlated. The non-Gaussian tested sources (dyads and triads, respectively of two and three dimensions) lead to a dense data concentration along certain curves or surfaces, nearby which the clusters' centroids of the joint probability density function tend to be located. That favors a better splitting of the QG3 atmospheric model's weather regimes: the positive and negative phases of the Arctic Oscillation and positive and negative phases of the North Atlantic Oscillation. The leading model's non-Gaussian dyad is associated to a positive correlation between: 1) the squared anomaly of the extratropical jet-stream and 2) the meridional jet-stream meandering. Triadic sources coming from maximized third-order cross cumulants between pairwise uncorrelated components reveal situations of triadic wave resonance and nonlinear triadic teleconnections, only possible thanks to joint non-Gaussianity. That kind of triadic synergies are accounted for an Information-Theoretic measure: the Interaction Information. The dominant model's triad occurs between anomalies of: 1) the North Pole anomaly pressure 2) the jet-stream intensity at the Eastern North-American boundary and 3) the jet-stream intensity at the Eastern Asian boundary. Publication supported by project FCT UID/GEO/50019/2013 - Instituto Dom Luiz.

Possible biomechanical origins of the long-range correlations in stride intervals of walking

NASA Astrophysics Data System (ADS)

Gates, Deanna H.; Su, Jimmy L.; Dingwell, Jonathan B.

2007-07-01

When humans walk, the time duration of each stride varies from one stride to the next. These temporal fluctuations exhibit long-range correlations. It has been suggested that these correlations stem from higher nervous system centers in the brain that control gait cycle timing. Existing proposed models of this phenomenon have focused on neurophysiological mechanisms that might give rise to these long-range correlations, and generally ignored potential alternative mechanical explanations. We hypothesized that a simple mechanical system could also generate similar long-range correlations in stride times. We modified a very simple passive dynamic model of bipedal walking to incorporate forward propulsion through an impulsive force applied to the trailing leg at each push-off. Push-off forces were varied from step to step by incorporating both “sensory” and “motor” noise terms that were regulated by a simple proportional feedback controller. We generated 400 simulations of walking, with different combinations of sensory noise, motor noise, and feedback gain. The stride time data from each simulation were analyzed using detrended fluctuation analysis to compute a scaling exponent, α. This exponent quantified how each stride interval was correlated with previous and subsequent stride intervals over different time scales. For different variations of the noise terms and feedback gain, we obtained short-range correlations (α<0.5), uncorrelated time series (α=0.5), long-range correlations (0.5<α<1.0), or Brownian motion (α>1.0). Our results indicate that a simple biomechanical model of walking can generate long-range correlations and thus perhaps these correlations are not a complex result of higher level neuronal control, as has been previously suggested.

High Annular Resolution Stellar Interferometry.

DTIC Science & Technology

1985-07-31

correlation is separable, C3 (Ax,At) = C1 (Ax) C2 (At), then the spatial structure and time evolution are uncorrelated and under these conditions one would...the following one. Reference 6 points out the bias obtained on the shape of the normalised spatial correlation function of dynamic speckle under the...MS student) 1982 H Daum (U1 assistant) 1981 C S ________ 20. 6. MUPID This appendix oontains oopies of the 20 publioations produced under this

Interference of Multi-Mode Gaussian States and "non Appearance" of Quantum Correlations

NASA Astrophysics Data System (ADS)

Olivares, Stefano

2012-01-01

We theoretically investigate bilinear, mode-mixing interactions involving two modes of uncorrelated multi-mode Gaussian states. In particular, we introduce the notion of "locally the same states" (LSS) and prove that two uncorrelated LSS modes are invariant under the mode mixing, i.e. the interaction does not lead to the birth of correlations between the outgoing modes. We also study the interference of orthogonally polarized Gaussian states by means of an interferometric scheme based on a beam splitter, rotators of polarization and polarization filters.

Is there evidence for the existence of nonlinear behavior within the interplanetary solar sector structure?

NASA Astrophysics Data System (ADS)

Brown, A. G.; Francis, N. M.; Broomhead, D. S.; Cannon, P. S.; Akram, A.

1999-06-01

Using data from the Sweden and Britain Radar Experiment (SABRE) VHF coherent radar, Yeoman et al. [1990] found evidence for two and four sector structures during the declining phase of solar cycle (SC) 21. No such obvious harmonic features were present during the ascending phase of SC 22. It was suggested that the structure of the heliospheric current sheet might exhibit nonlinear behavior during the latter period. A direct test of this suggestion, using established nonlinear methods, would require the computation of the fractal dimension of the data, for example. However, the quality of the SABRE data is insufficient for this purpose. Therefore we have tried to answer a simpler question: Is there any evidence that the SABRE data was generated by a (low-dimensional) nonlinear process? If this were the case, it would be a powerful indicator of nonlinear behavior in the solar current sheet. Our approach has been to use a system of orthogonal linear filters to separate the data into linearly uncorrelated time series. We then look for nonlinear dynamical relationships between these time series, using radial basis function models (which can be thought of as a class of neural networks). The presence of such a relationship, indicated by the ability to model one filter output given another, would equate to the presence of nonlinear properties within the data. Using this technique, evidence is found for the presence of low-level nonlinear behavior during both phases of the solar cycle investigated in this study. The evidence for nonlinear behavior is stronger during the descending phase of SC 21. However, it is not possible to distinguish between nonlinear dynamics and a nonlinearly transformed colored Gaussian noise process in either instance, using the available data. Therefore, in conclusion, we find insufficient evidence within the SABRE data set to support the suggestion of increased nonlinear dynamical behavior during the ascending phase of SC 22. In fact, nonlinear dynamics would seem to exert very little influence within the measurement time series at all, given the observed data. Therefore it is likely that stochastic or unresolved high-dimensional nonlinear mechanisms are responsible for the observed spectrum complexity during the ascending phase of SC 22.

Rainfall effects on rare annual plants

USGS Publications Warehouse

Levine, J.M.; McEachern, A.K.; Cowan, C.

2008-01-01

Variation in climate is predicted to increase over much of the planet this century. Forecasting species persistence with climate change thus requires understanding of how populations respond to climate variability, and the mechanisms underlying this response. Variable rainfall is well known to drive fluctuations in annual plant populations, yet the degree to which population response is driven by between-year variation in germination cueing, water limitation or competitive suppression is poorly understood.We used demographic monitoring and population models to examine how three seed banking, rare annual plants of the California Channel Islands respond to natural variation in precipitation and their competitive environments. Island plants are particularly threatened by climate change because their current ranges are unlikely to overlap regions that are climatically favourable in the future.Species showed 9 to 100-fold between-year variation in plant density over the 5–12 years of censusing, including a severe drought and a wet El Niño year. During the drought, population sizes were low for all species. However, even in non-drought years, population sizes and per capita growth rates showed considerable temporal variation, variation that was uncorrelated with total rainfall. These population fluctuations were instead correlated with the temperature after the first major storm event of the season, a germination cue for annual plants.Temporal variation in the density of the focal species was uncorrelated with the total vegetative cover in the surrounding community, suggesting that variation in competitive environments does not strongly determine population fluctuations. At the same time, the uncorrelated responses of the focal species and their competitors to environmental variation may favour persistence via the storage effect.Population growth rate analyses suggested differential endangerment of the focal annuals. Elasticity analyses and life table response experiments indicated that variation in germination has the same potential as the seeds produced per germinant to drive variation in population growth rates, but only the former was clearly related to rainfall.Synthesis. Our work suggests that future changes in the timing and temperatures associated with the first major rains, acting through germination, may more strongly affect population persistence than changes in season-long rainfall.

Time scale dependence of the center of pressure entropy: What characteristics of the neuromuscular postural control system influence stabilographic entropic half-life?

PubMed

Federolf, Peter; Zandiyeh, Payam; von Tscharner, Vinzenz

2015-12-01

The center of pressure (COP) movement in studies of postural control reveals a highly regular structure (low entropy) over short time periods and a highly irregular structure over large time scales (high entropy). Entropic half-life (EnHL) is a novel measure that quantifies the time over which short-term temporal correlations in a time series deteriorate to an uncorrelated, random structure. The current study suggested and tested three hypotheses about how characteristics of the neuromuscular postural control system may affect stabilometric EnHL: (H1) control system activity hypothesis: EnHL decreases with increased frequency of control system interventions adjusting COP motion; (H2) abundance of states hypothesis: EnHL decreases with increased number of mechanically equivalent states available to the postural system; and (H3) neurologic process hierarchy hypothesis: EnHL increases if postural control functions shift from the spinal level to the motor cortex. Thirty healthy participants performed quiet stance tests for 90 s in 18 different conditions: stance (bipedal, one-legged, and tandem); footwear (bare foot, regular sports shoe, and rocker sole shoes); and simultaneous cognitive task (two-back working memory task, no challenge). A four-way repeated-measures ANOVA revealed significant changes in EnHL for the different stance positions and for different movement directions (medio-lateral, anterior-posterior). These changes support H1 and H2. Significant differences were also found between rocker sole shoes and normal or barefoot standing, which supports H3. This study contributes to the understanding of how and why EnHL is a useful measure to monitor neuromuscular control of balance.

The Alternative Omen Effect: Illusory negative correlation between the outcomes of choice options.

PubMed

Marciano-Romm, Déborah; Romm, Assaf; Bourgeois-Gironde, Sacha; Deouell, Leon Y

2016-01-01

In situations of choice between uncertain options, one might get feedback on both the outcome of the chosen option and the outcome of the unchosen option ("the alternative"). Extensive research has shown that when both outcomes are eventually revealed, the alternative's outcome influences the way people evaluate their own outcome. In a series of experiments, we examined whether the outcome of the alternative plays an additional role in the decision-making process by creating expectations regarding the outcome of the chosen option. Specifically, we hypothesized that people see a good (bad) alternative's outcome as a bad (good) sign regarding their own outcome when the two outcomes are in fact uncorrelated, a phenomenon we call the "Alternative Omen Effect" (ALOE). Subjects had to repeatedly choose between two boxes, the outcomes of which were then sequentially revealed. In Experiments 1 and 2 the alternative's outcome was presented first, and we assessed the individual's prediction of their own outcome. In Experiment 3, subjects had to predict the alternative's outcome after seeing their own. We find that even though the two outcomes were in fact uncorrelated, people tended to see a good (bad) alternative outcome as a bad (good) sign regarding their own outcome. Importantly, this illusory negative correlation affected subsequent behavior and led to irrational choices. Furthermore, the order of presentation was critical: when the outcome of the chosen option was presented first, the effect disappeared, suggesting that this illusory negative correlation is influenced by self-relevance. We discuss the possible sources of this illusory correlation as well as its implications for research on counterfactual thinking. Copyright © 2015 Elsevier B.V. All rights reserved.

Development of an advanced undergraduate course in acoustics

NASA Astrophysics Data System (ADS)

Gee, Kent L.; Neilsen, Tracianne B.; Sommerfeldt, Scott D.

2016-03-01

Within many physics undergraduate programs, acoustics is given only a cursory treatment, usually within an introductory course. Because acoustics is a natural vehicle for students to develop intuition about wave phenomena, an advanced undergraduate acoustics course has been developed at Brigham Young University. Although it remains an elective course, enrollment has increased steadily since its inception. The course has been taken by students in physics, applied physics, physics teaching, and mechanical and electrical engineering. In addition to providing training for students motivated by interest in undergraduate research, internship, employment, and graduate schooling opportunities in acoustics, the course facilitates connections between various areas of physics. Explicit connections are made to mechanics, electricity and magnetism, thermodynamics, optics, quantum mechanics, and experimental and computational laboratory courses. Active learning is emphasized through Just-in-Time-Teaching and course structure. Homework exercises are both theoretical and practical and often require making and interpreting of graphs. For example, students may model traffic noise as a series of uncorrelated monopoles or examine highway barrier effectiveness using Fresnel diffraction techniques. Additionally, students participate in resumé-building measurements and learn to report their results in the form of technical memoranda. Course evaluations and post-graduation student surveys rate it among the most valuable undergraduate student courses offered.

Reconfigurable metasurface aperture for security screening and microwave imaging

NASA Astrophysics Data System (ADS)

Sleasman, Timothy; Imani, Mohammadreza F.; Boyarsky, Michael; Pulido-Mancera, Laura; Reynolds, Matthew S.; Smith, David R.

2017-05-01

Microwave imaging systems have seen growing interest in recent decades for applications ranging from security screening to space/earth observation. However, hardware architectures commonly used for this purpose have not seen drastic changes. With the advent of metamaterials a wealth of opportunities have emerged for honing metasurface apertures for microwave imaging systems. Recent thrusts have introduced dynamic reconfigurability directly into the aperture layer, providing powerful capabilities from a physical layer with considerable simplicity. The waveforms generated from such dynamic metasurfaces make them suitable for application in synthetic aperture radar (SAR) and, more generally, computational imaging. In this paper, we investigate a dynamic metasurface aperture capable of performing microwave imaging in the K-band (17.5-26.5 GHz). The proposed aperture is planar and promises an inexpensive fabrication process via printed circuit board techniques. These traits are further augmented by the tunability of dynamic metasurfaces, which provides the dexterity necessary to generate field patterns ranging from a sequence of steered beams to a series of uncorrelated radiation patterns. Imaging is experimentally demonstrated with a voltage-tunable metasurface aperture. We also demonstrate the aperture's utility in real-time measurements and perform volumetric SAR imaging. The capabilities of a prototype are detailed and the future prospects of general dynamic metasurface apertures are discussed.

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.

Proceedings of the Annual Precise Time and Time Interval (PTTI) Applications and Planning Meeting (15th) Held at Washington, DC on 6-8 December 1983,

DTIC Science & Technology

1984-04-02

clock is an absolute technique with a 14 0 • ,4 precision of about 0.1 )us The results of the portable clock experiment indicate that LF sync...also gains direct access to the U. S. primary frequency standard, NBS-6. Access to1 BS-6 makes it possible to set an absolute limit of one part in 10...of the components in these equations are uncorrelated we may take vari- ances of each of these equations and the cross terms will average to zero 117

Poisson mixture model for measurements using counting.

PubMed

Miller, Guthrie; Justus, Alan; Vostrotin, Vadim; Dry, Donald; Bertelli, Luiz

2010-03-01

Starting with the basic Poisson statistical model of a counting measurement process, 'extraPoisson' variance or 'overdispersion' are included by assuming that the Poisson parameter representing the mean number of counts itself comes from another distribution. The Poisson parameter is assumed to be given by the quantity of interest in the inference process multiplied by a lognormally distributed normalising coefficient plus an additional lognormal background that might be correlated with the normalising coefficient (shared uncertainty). The example of lognormal environmental background in uranium urine data is discussed. An additional uncorrelated background is also included. The uncorrelated background is estimated from a background count measurement using Bayesian arguments. The rather complex formulas are validated using Monte Carlo. An analytical expression is obtained for the probability distribution of gross counts coming from the uncorrelated background, which allows straightforward calculation of a classical decision level in the form of a gross-count alarm point with a desired false-positive rate. The main purpose of this paper is to derive formulas for exact likelihood calculations in the case of various kinds of backgrounds.

Analyzing student conceptual understanding of resistor networks using binary, descriptive, and computational questions

NASA Astrophysics Data System (ADS)

Mujtaba, Abid H.

2018-02-01

This paper presents a case study assessing and analyzing student engagement with and responses to binary, descriptive, and computational questions testing the concepts underlying resistor networks (series and parallel combinations). The participants of the study were undergraduate students enrolled in a university in Pakistan. The majority of students struggled with the descriptive question, and while successfully answering the binary and computational ones, they failed to build an expectation for the answer, and betrayed significant lack of conceptual understanding in the process. The data collected was also used to analyze the relative efficacy of the three questions as a means of assessing conceptual understanding. The three questions were revealed to be uncorrelated and unlikely to be testing the same construct. The ability to answer the binary or computational question was observed to be divorced from a deeper understanding of the concepts involved.

A Hubble Space Telescope survey for novae in M87.I. light and color curves, spatial distributions, and the nova rate

DOE PAGES

Shara, Michael M.; Doyle, Trisha F.; Lauer, Tod R.; ...

2016-11-08

The Hubble Space Telescope has imaged the central part of M87 over a 10 week span, leading to the discovery of 32 classical novae (CNe) and nine fainter, likely very slow, and/or symbiotic novae. In this first paper of a series, we present the M87 nova finder charts, and the light and color curves of the novae. We demonstrate that the rise and decline times, and the colors of M87 novae are uncorrelated with each other and with position in the galaxy. The spatial distribution of the M87 novae follows the light of the galaxy, suggesting that novae accreted by M87 during cannibalistic episodes are well-mixed. Conservatively using only the 32 brightest CNe we derive a nova rate for M87:more » $${363}_{-45}^{+33}$$ novae yr –1. We also derive the luminosity-specific classical nova rate for this galaxy, which is $${7.88}_{-2.6}^{+2.3}\\,{\\mathrm{yr}}^{-1}/{10}^{10}\\,{L}_{\\odot }{,}_{K}$$. Both rates are 3–4 times higher than those reported for M87 in the past, and similarly higher than those reported for all other galaxies. As a result, we suggest that most previous ground-based surveys for novae in external galaxies, including M87, miss most faint, fast novae, and almost all slow novae near the centers of galaxies.« less

Geographic isolation drives divergence of uncorrelated genetic and song variation in the Ruddy-capped Nightingale-Thrush (Catharus frantzii; Aves: Turdidae).

PubMed

Ortiz-Ramírez, Marco F; Andersen, Michael J; Zaldívar-Riverón, Alejandro; Ornelas, Juan Francisco; Navarro-Sigüenza, Adolfo G

2016-01-01

Montane barriers influence the evolutionary history of lineages by promoting isolation of populations. The effects of these historical processes are evident in patterns of differentiation among extant populations, which are often expressed as genetic and behavioral variation between populations. We investigated the effects of geographic barriers on the evolutionary history of a Mesoamerican bird by studying patterns of genetic and vocal variation in the Ruddy-capped Nightingale-Thrush (Turdidae: Catharus frantzii), a non-migratory oscine bird that inhabits montane forests from central Mexico to Panama. We reconstructed the phylogeographic history and estimated divergence times between populations using Bayesian and maximum likelihood methods. We found strong support for the existence of four mitochondrial lineages of C. frantzii corresponding to isolated mountain ranges: Sierra Madre Oriental; Sierra Madre del Sur; the highlands of Chiapas, Guatemala, and El Salvador; and the Talamanca Cordillera. Vocal features in C. frantzii were highly variable among the four observed clades, but vocal variation and genetic variation were uncorrelated. Song variation in C. frantzii suggests that sexual selection and cultural drift could be important factors driving song differentiation in C. frantzii. Copyright © 2015 Elsevier Inc. All rights reserved.

Communication: Localized molecular orbital analysis of the effect of electron correlation on the anomalous isotope effect in the NMR spin-spin coupling constant in methane

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

Zarycz, M. Natalia C., E-mail: mnzarycz@gmail.com; Provasi, Patricio F., E-mail: patricio@unne.edu.ar; Sauer, Stephan P. A., E-mail: sauer@kiku.dk

2014-10-21

We discuss the effect of electron correlation on the unexpected differential sensitivity (UDS) in the {sup 1}J(C–H) coupling constant of CH{sub 4} using a decomposition into contributions from localized molecular orbitals and compare with the {sup 1}J(N–H) coupling constant in NH{sub 3}. In particular, we discuss the well known fact that uncorrelated coupled Hartree-Fock (CHF) calculations are not able to reproduce the UDS in methane. For this purpose we have implemented for the first time a localized molecular orbital analysis for the second order polarization propagator approximation with coupled cluster singles and doubles amplitudes—SOPPA(CCSD) in the DALTON program. Comparing themore » changes in the localized orbital contributions at the correlated SOPPA and SOPPA(CCSD) levels and at the uncorrelated CHF level, we find that the latter overestimates the effect of stretching the bond between the coupled atoms on the contribution to the coupling from the localized bonding orbital between these atoms. This disturbs the subtle balance between the molecular orbital contributions, which lead to the UDS in methane.« less

X-ray Luminosity and Absorption Column Fluctuations in the H2O Maser Galaxy NGC 4258 from Weeks to Years

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

Argon, A.

2004-07-30

The authors report monitoring of the 0.3-10 keV spectrum of NGC 4258 with the XMM-Newton observatory at five epochs over 1.5 years. They also report reprocessing of an overlapping four epoch series of archival Chandra observations (0.5-10 keV). By including earlier ASCA and Beppo-SAX observations, they present a new, nine year time-series of models fit to the X-ray spectrum of NGC 4258. They model the Chandra and XMM-Newton data self-consistently with partially absorbed, hard power-law, soft thermal plasma, and soft power-law components. Over the nine years, the photo-electric absorbing column ({approx} 10{sup 23} cm{sup -2}) did not vary detectably, exceptmore » for a {approx} 40% drop between two ASCA epochs separated by 3 years (in 1993 and 1996) and a {approx} 60% rise between two XMM-Newton epochs separated by just 5 months (in 2001 and 2002). In contrast, factor of 2-3 changes are seen in absorbed flux on the timescale of years. These are uncorrelated with changes in absorbing column and indicative of central engine variability. The most rapid change in luminosity (5-10 keV) that the authors detect (with XMM-Newton and Chandra) is on the order of 30% over 19 days. The warped disk that is a known source of H{sub 2}O maser emission in NGC 4258 is believed to cross the line of sight to the central engine. They propose that the variations in absorbing column arise from inhomogeneities in the rotating disk, as they sweep across the line of sight. They estimate that the inhomogeneities are {approx} 10{sup 15} cm in size.« less

Entanglement and purity of two-mode Gaussian states in noisy channels

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

Serafini, Alessio; Illuminati, Fabrizio; De Siena, Silvio

2004-02-01

We study the evolution of purity, entanglement, and total correlations of general two-mode continuous variable Gaussian states in arbitrary uncorrelated Gaussian environments. The time evolution of purity, von Neumann entropy, logarithmic negativity, and mutual information is analyzed for a wide range of initial conditions. In general, we find that a local squeezing of the bath leads to a faster degradation of purity and entanglement, while it can help to preserve the mutual information between the modes.

USING RUNNING DIFFERENCE IMAGES TO TRACK PROPER MOTIONS OF XUV CORONAL INTENSITY ON THE SUN

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

Sheeley, N. R. Jr.; Warren, H. P.; Lee, J., E-mail: neil.sheeley@nrl.navy.mil, E-mail: harry.warren@nrl.navy.mil

2014-12-20

We have developed a procedure for observing and tracking proper motions of faint XUV coronal intensity on the Sun and have applied this procedure to study the collective motions of cellular plumes and the shorter-period waves in sunspots. Our space/time maps of cellular plumes show a series of tracks with the same 5-8 minute repetition times and ∼100 km s{sup –1} sky-plane speeds found previously in active-region fans and in coronal hole plumes. By synchronizing movies and space/time maps, we find that the tracks are produced by elongated ejections from the unipolar flux concentrations at the bases of the cellular plumes and thatmore » the phases of these ejections are uncorrelated from cell to cell. Thus, the large-scale motion is not a continuous flow, but is more like a system of independent conveyor belts all moving in the same direction along the magnetic field. In contrast, the proper motions in sunspots are clearly waves resulting from periodic disturbances in the sunspot umbras. The periods are ∼2.6 minutes, but the sky-plane speeds and wavelengths depend on the heights of the waves above the sunspot. In the chromosphere, the waves decelerate from 35-45 km s{sup –1} in the umbra to 7-8 km s{sup –1} toward the outer edge of the penumbra, but in the corona, the waves accelerate to ∼60-100 km s{sup –1}. Because chromospheric and coronal tracks originate from the same space/time locations, the coronal waves must emerge from the same umbral flashes that produce the chromospheric waves.« less

Extracting factors for interest rate scenarios

NASA Astrophysics Data System (ADS)

Molgedey, L.; Galic, E.

2001-04-01

Factor based interest rate models are widely used for risk managing purposes, for option pricing and for identifying and capturing yield curve anomalies. The movements of a term structure of interest rates are commonly assumed to be driven by a small number of orthogonal factors such as SHIFT, TWIST and BUTTERFLY (BOW). These factors are usually obtained by a Principal Component Analysis (PCA) of historical bond prices (interest rates). Although PCA diagonalizes the covariance matrix of either the interest rates or the interest rate changes, it does not use both covariance matrices simultaneously. Furthermore higher linear and nonlinear correlations are neglected. These correlations as well as the mean reverting properties of the interest rates become crucial, if one is interested in a longer time horizon (infrequent hedging or trading). We will show that Independent Component Analysis (ICA) is a more appropriate tool than PCA, since ICA uses the covariance matrix of the interest rates as well as the covariance matrix of the interest rate changes simultaneously. Additionally higher linear and nonlinear correlations may be easily incorporated. The resulting factors are uncorrelated for various time delays, approximately independent but nonorthogonal. This is in contrast to the factors obtained from the PCA, which are orthogonal and uncorrelated for identical times only. Although factors from the ICA are nonorthogonal, it is sufficient to consider only a few factors in order to explain most of the variation in the original data. Finally we will present examples that ICA based hedges outperforms PCA based hedges specifically if the portfolio is sensitive to structural changes of the yield curve.

Reducing Sensor Noise in MEG and EEG Recordings Using Oversampled Temporal Projection.

PubMed

Larson, Eric; Taulu, Samu

2018-05-01

Here, we review the theory of suppression of spatially uncorrelated, sensor-specific noise in electro- and magentoencephalography (EEG and MEG) arrays, and introduce a novel method for suppression. Our method requires only that the signals of interest are spatially oversampled, which is a reasonable assumption for many EEG and MEG systems. Our method is based on a leave-one-out procedure using overlapping temporal windows in a mathematical framework to project spatially uncorrelated noise in the temporal domain. This method, termed "oversampled temporal projection" (OTP), has four advantages over existing methods. First, sparse channel-specific artifacts are suppressed while limiting mixing with other channels, whereas existing linear, time-invariant spatial operators can spread such artifacts to other channels with a spatial distribution which can be mistaken for one produced by an electrophysiological source. Second, OTP minimizes distortion of the spatial configuration of the data. During source localization (e.g., dipole fitting), many spatial methods require corresponding modification of the forward model to avoid bias, while OTP does not. Third, noise suppression factors at the sensor level are maintained during source localization, whereas bias compensation removes the denoising benefit for spatial methods that require such compensation. Fourth, OTP uses a time-window duration parameter to control the tradeoff between noise suppression and adaptation to time-varying sensor characteristics. OTP efficiently optimizes noise suppression performance while controlling for spatial bias of the signal of interest. This is important in applications where sensor noise significantly limits the signal-to-noise ratio, such as high-frequency brain oscillations.

Mapping gravitational-wave backgrounds using methods from CMB analysis: Application to pulsar timing arrays

NASA Astrophysics Data System (ADS)

Gair, Jonathan; Romano, Joseph D.; Taylor, Stephen; Mingarelli, Chiara M. F.

2014-10-01

We describe an alternative approach to the analysis of gravitational-wave backgrounds, based on the formalism used to characterize the polarization of the cosmic microwave background. In contrast to standard analyses, this approach makes no assumptions about the nature of the background and so has the potential to reveal much more about the physical processes that generated it. An arbitrary background can be decomposed into modes whose angular dependence on the sky is given by gradients and curls of spherical harmonics. We derive the pulsar timing overlap reduction functions for the individual modes, which are given by simple combinations of spherical harmonics evaluated at the pulsar locations. We show how these can be used to recover the components of an arbitrary background, giving explicit results for both isotropic and anisotropic uncorrelated backgrounds. We also find that the response of a pulsar timing array to curl modes is identically zero, so half of the gravitational-wave sky will never be observed using pulsar timing, no matter how many pulsars are included in the array. An isotropic, unpolarized and uncorrelated background can be accurately represented using only three modes, and so a search of this type will be only slightly more complicated than the standard cross-correlation search using the Hellings and Downs overlap reduction function. However, by measuring the components of individual modes of the background and checking for consistency with isotropy, this approach has the potential to reveal much more information. Each individual mode on its own describes a background that is correlated between different points on the sky. A measurement of the components that indicates the presence of correlations in the background on large angular scales would suggest startling new physics.

Relaxed clocks and inferences of heterogeneous patterns of nucleotide substitution and divergence time estimates across whales and dolphins (Mammalia: Cetacea).

PubMed

Dornburg, Alex; Brandley, Matthew C; McGowen, Michael R; Near, Thomas J

2012-02-01

Various nucleotide substitution models have been developed to accommodate among lineage rate heterogeneity, thereby relaxing the assumptions of the strict molecular clock. Recently developed "uncorrelated relaxed clock" and "random local clock" (RLC) models allow decoupling of nucleotide substitution rates between descendant lineages and are thus predicted to perform better in the presence of lineage-specific rate heterogeneity. However, it is uncertain how these models perform in the presence of punctuated shifts in substitution rate, especially between closely related clades. Using cetaceans (whales and dolphins) as a case study, we test the performance of these two substitution models in estimating both molecular rates and divergence times in the presence of substantial lineage-specific rate heterogeneity. Our RLC analyses of whole mitochondrial genome alignments find evidence for up to ten clade-specific nucleotide substitution rate shifts in cetaceans. We provide evidence that in the uncorrelated relaxed clock framework, a punctuated shift in the rate of molecular evolution within a subclade results in posterior rate estimates that are either misled or intermediate between the disparate rate classes present in baleen and toothed whales. Using simulations, we demonstrate abrupt changes in rate isolated to one or a few lineages in the phylogeny can mislead rate and age estimation, even when the node of interest is calibrated. We further demonstrate how increasing prior age uncertainty can bias rate and age estimates, even while the 95% highest posterior density around age estimates decreases; in other words, increased precision for an inaccurate estimate. We interpret the use of external calibrations in divergence time studies in light of these results, suggesting that rate shifts at deep time scales may mislead inferences of absolute molecular rates and ages.

Activity cycles in members of young loose stellar associations

NASA Astrophysics Data System (ADS)

Distefano, E.; Lanzafame, A. C.; Lanza, A. F.; Messina, S.; Spada, F.

2017-10-01

Context. Magnetic cycles analogous to the solar cycle have been detected in tens of solar-like stars by analyzing long-term time series of different magnetic activity indexes. The relationship between the cycle properties and global stellar parameters is not fully understood yet. One reason for this is the lack of long-term time series for stars covering a wide range of stellar parameters. Aims: We searched for activity cycles in a sample of 90 young solar-like stars with ages between 4 and 95 Myr with the aim to investigate the properties of activity cycles in this age range. Methods: We measured the length Pcyc of a given cycle by analyzing the long-term time series of three different activity indexes: the period of rotational modulation, the amplitude of the rotational modulation and the median magnitude in the V band. For each star, we also computed the global magnetic activity index ⟨ IQR ⟩ that is proportional to the amplitude of the rotational modulation and can be regarded as a proxy of the mean level of the surface magnetic activity. Results: We detected activity cycles in 67 stars. Secondary cycles were also detected in 32 stars of the sample. The lack of correlation between Pcyc and Prot and the position of our targets in the Pcyc/Prot-Ro-1 diagram suggest that these stars belong to the so-called transitional branch and that the dynamo acting in these stars is different from the solar dynamo and from that acting in the older Mt. Wilson stars. This statement is also supported by the analysis of the butterfly diagrams whose patterns are very different from those seen in the solar case. We computed the Spearman correlation coefficient rS between Pcyc, ⟨ IQR ⟩ and various stellar parameters. We found that Pcyc in our sample is uncorrelated with all the investigated parameters. The ⟨ IQR ⟩ index is positively correlated with the convective turnover timescale, the magnetic diffusivity timescale τdiff, and the dynamo number DN, whereas it is anti-correlated with the effective temperature Teff, the photometric shear ΔΩphot and the radius RC at which the convective zone is located. We investigated how Pcyc and ⟨ IQR ⟩ evolve with the stellar age. We found that Pcyc is about constant and that ⟨ IQR ⟩ decreases with the stellare age in the range 4-95 Myr. Finally we investigated the magnetic activity of the star AB Dor A by merging All Sky Automatic Survey (ASAS) time series with previous long-term photometric data. We estimated the length of the AB Dor A primary cycle as Pcyc = 16.78 ± 2 yr and we also found shorter secondary cycles with lengths of 400 d, 190 d, and 90 d, respectively. Tables 2 and 3 and Time series are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/606/A58

Novel particle tracking algorithm based on the Random Sample Consensus Model for the Active Target Time Projection Chamber (AT-TPC)

NASA Astrophysics Data System (ADS)

Ayyad, Yassid; Mittig, Wolfgang; Bazin, Daniel; Beceiro-Novo, Saul; Cortesi, Marco

2018-02-01

The three-dimensional reconstruction of particle tracks in a time projection chamber is a challenging task that requires advanced classification and fitting algorithms. In this work, we have developed and implemented a novel algorithm based on the Random Sample Consensus Model (RANSAC). The RANSAC is used to classify tracks including pile-up, to remove uncorrelated noise hits, as well as to reconstruct the vertex of the reaction. The algorithm, developed within the Active Target Time Projection Chamber (AT-TPC) framework, was tested and validated by analyzing the 4He+4He reaction. Results, performance and quality of the proposed algorithm are presented and discussed in detail.

Increased task-uncorrelated muscle activity in childhood dystonia.

PubMed

Lunardini, Francesca; Maggioni, Serena; Casellato, Claudia; Bertucco, Matteo; Pedrocchi, Alessandra L G; Sanger, Terence D

2015-06-12

Even if movement abnormalities in dystonia are obvious on observation-based examinations, objective measures to characterize dystonia and to gain insights into its pathophysiology are still strongly needed. We hypothesize that motor abnormalities in childhood dystonia are partially due to the inability to suppress involuntary variable muscle activity irrelevant to the achievement of the desired motor task, resulting in the superposition of unwanted motion components on the desired movement. However, it is difficult to separate and quantify appropriate and inappropriate motor signals combined in the same muscle, especially during movement. We devise an innovative and practical method to objectively measure movement abnormalities during the performance of a continuous figure-eight writing task in 7 children with dystonia and 9 age-matched healthy controls. During the execution of a continuous writing task, muscle contractions should occur at frequencies that match the frequencies of the writing outcome. We compare the power spectra of kinematic trajectories and electromyographic signals of 8 upper limb muscles to separate muscle activity with the same frequency content of the figure-eight movement (task-correlated) from activity occurring at frequencies extraneous to the task (task-uncorrelated). Children with dystonia present a greater magnitude of task-uncorrelated muscle components. The motor performance achieved by children with dystonia is characterized by an overall lower quality, with high spatial and temporal variability and an altered trade-off between speed and accuracy. Findings are consistent with the hypothesis that, in childhood dystonia, the ability to appropriately suppress variable and uncorrelated elements of movement is impaired. Here we present a proof-of-concept of a promising tool to characterize the phenomenology of movement disorders and to inform the design of neurorehabilitation therapies.

Interocular velocity difference contributes to stereomotion speed perception

NASA Technical Reports Server (NTRS)

Brooks, Kevin R.

2002-01-01

Two experiments are presented assessing the contributions of the rate of change of disparity (CD) and interocular velocity difference (IOVD) cues to stereomotion speed perception. Using a two-interval forced-choice paradigm, the perceived speed of directly approaching and receding stereomotion and of monocular lateral motion in random dot stereogram (RDS) targets was measured. Prior adaptation using dysjunctively moving random dot stimuli induced a velocity aftereffect (VAE). The degree of interocular correlation in the adapting images was manipulated to assess the effectiveness of each cue. While correlated adaptation involved a conventional RDS stimulus, containing both IOVD and CD cues, uncorrelated adaptation featured an independent dot array in each monocular half-image, and hence lacked a coherent disparity signal. Adaptation produced a larger VAE for stereomotion than for monocular lateral motion, implying effects at neural sites beyond that of binocular combination. For motion passing through the horopter, correlated and uncorrelated adaptation stimuli produced equivalent stereomotion VAEs. The possibility that these results were due to the adaptation of a CD mechanism through random matches in the uncorrelated stimulus was discounted in a control experiment. Here both simultaneous and sequential adaptation of left and right eyes produced similar stereomotion VAEs. Motion at uncrossed disparities was also affected by both correlated and uncorrelated adaptation stimuli, but showed a significantly greater VAE in response to the former. These results show that (1) there are two separate, specialised mechanisms for encoding stereomotion: one through IOVD, the other through CD; (2) the IOVD cue dominates the perception of stereomotion speed for stimuli passing through the horopter; and (3) at a disparity pedestal both the IOVD and the CD cues have a significant influence.

Neutrino masses and cosmological parameters from a Euclid-like survey: Markov Chain Monte Carlo forecasts including theoretical errors

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

Audren, Benjamin; Lesgourgues, Julien; Bird, Simeon

2013-01-01

We present forecasts for the accuracy of determining the parameters of a minimal cosmological model and the total neutrino mass based on combined mock data for a future Euclid-like galaxy survey and Planck. We consider two different galaxy surveys: a spectroscopic redshift survey and a cosmic shear survey. We make use of the Monte Carlo Markov Chains (MCMC) technique and assume two sets of theoretical errors. The first error is meant to account for uncertainties in the modelling of the effect of neutrinos on the non-linear galaxy power spectrum and we assume this error to be fully correlated in Fouriermore » space. The second error is meant to parametrize the overall residual uncertainties in modelling the non-linear galaxy power spectrum at small scales, and is conservatively assumed to be uncorrelated and to increase with the ratio of a given scale to the scale of non-linearity. It hence increases with wavenumber and decreases with redshift. With these two assumptions for the errors and assuming further conservatively that the uncorrelated error rises above 2% at k = 0.4 h/Mpc and z = 0.5, we find that a future Euclid-like cosmic shear/galaxy survey achieves a 1-σ error on M{sub ν} close to 32 meV/25 meV, sufficient for detecting the total neutrino mass with good significance. If the residual uncorrelated errors indeed rises rapidly towards smaller scales in the non-linear regime as we have assumed here then the data on non-linear scales does not increase the sensitivity to the total neutrino mass. Assuming instead a ten times smaller theoretical error with the same scale dependence, the error on the total neutrino mass decreases moderately from σ(M{sub ν}) = 18 meV to 14 meV when mildly non-linear scales with 0.1 h/Mpc < k < 0.6 h/Mpc are included in the analysis of the galaxy survey data.« less

Dynamic density functional theory with hydrodynamic interactions and fluctuations

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

Donev, Aleksandar, E-mail: donev@courant.nyu.edu; Vanden-Eijnden, Eric, E-mail: eve2@courant.nyu.edu

2014-06-21

We derive a closed equation for the empirical concentration of colloidal particles in the presence of both hydrodynamic and direct interactions. The ensemble average of our functional Langevin equation reproduces known deterministic Dynamic Density Functional Theory (DDFT) [M. Rex and H. Löwen, “Dynamical density functional theory with hydrodynamic interactions and colloids in unstable traps,” Phys. Rev. Lett. 101(14), 148302 (2008)], and, at the same time, it also describes the microscopic fluctuations around the mean behavior. We suggest separating the ideal (non-interacting) contribution from additional corrections due to pairwise interactions. We find that, for an incompressible fluid and in the absencemore » of direct interactions, the mean concentration follows Fick's law just as for uncorrelated walkers. At the same time, the nature of the stochastic terms in fluctuating DDFT is shown to be distinctly different for hydrodynamically-correlated and uncorrelated walkers. This leads to striking differences in the behavior of the fluctuations around Fick's law, even in the absence of pairwise interactions. We connect our own prior work [A. Donev, T. G. Fai, and E. Vanden-Eijnden, “A reversible mesoscopic model of diffusion in liquids: from giant fluctuations to Fick's law,” J. Stat. Mech.: Theory Exp. (2014) P04004] on fluctuating hydrodynamics of diffusion in liquids to the DDFT literature, and demonstrate that the fluid cannot easily be eliminated from consideration if one wants to describe the collective diffusion in colloidal suspensions.« less

Characterization of transient noise in Advanced LIGO relevant to gravitational wave signal GW150914

NASA Astrophysics Data System (ADS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adamo, M.; Adams, C.; Adams, T.; Addesso, P.; Adhikari, R. X.; Adya, V. B.; Affeldt, C.; Agathos, M.; Agatsuma, K.; Aggarwal, N.; Aguiar, O. D.; Aiello, L.; Ain, A.; Ajith, P.; Allen, B.; Allocca, A.; Altin, P. A.; Anderson, S. B.; Anderson, W. G.; Arai, K.; Araya, M. C.; Arceneaux, C. C.; Areeda, J. S.; Arnaud, N.; Arun, K. G.; Ascenzi, S.; Ashton, G.; Ast, M.; Aston, S. M.; Astone, P.; Aufmuth, P.; Aulbert, C.; Babak, S.; Bacon, P.; Bader, M. K. M.; Baker, P. T.; Baldaccini, F.; Ballardin, G.; Ballmer, S. W.; Barayoga, J. C.; Barclay, S. E.; Barish, B. C.; Barker, D.; Barone, F.; Barr, B.; Barsotti, L.; Barsuglia, M.; Barta, D.; Bartlett, J.; Bartos, I.; Bassiri, R.; Basti, A.; Batch, J. C.; Baune, C.; Bavigadda, V.; Bazzan, M.; Behnke, B.; Bejger, M.; Bell, A. S.; Bell, C. J.; Berger, B. K.; Bergman, J.; Bergmann, G.; Berry, C. P. L.; Bersanetti, D.; Bertolini, A.; Betzwieser, J.; Bhagwat, S.; Bhandare, R.; Bilenko, I. A.; Billingsley, G.; Birch, J.; Birney, R.; Biscans, S.; Bisht, A.; Bitossi, M.; Biwer, C.; Bizouard, M. A.; Blackburn, J. K.; Blackburn, L.; Blair, C. D.; Blair, D. G.; Blair, R. M.; Bloemen, S.; Bock, O.; Bodiya, T. P.; Boer, M.; Bogaert, G.; Bogan, C.; Bohe, A.; Bojtos, P.; Bond, C.; Bondu, F.; Bonnand, R.; Boom, B. A.; Bork, R.; Boschi, V.; Bose, S.; Bouffanais, Y.; Bozzi, A.; Bradaschia, C.; Brady, P. R.; Braginsky, V. B.; Branchesi, M.; Brau, J. E.; Briant, T.; Brillet, A.; Brinkmann, M.; Brisson, V.; Brockill, P.; Brooks, A. F.; Brown, D. A.; Brown, D. D.; Brown, N. M.; Buchanan, C. C.; Buikema, A.; Bulik, T.; Bulten, H. J.; Buonanno, A.; Buskulic, D.; Buy, C.; Byer, R. L.; Cadonati, L.; Cagnoli, G.; Cahillane, C.; Calderón Bustillo, J.; Callister, T.; Calloni, E.; Camp, J. B.; Cannon, K. C.; Cao, J.; Capano, C. D.; Capocasa, E.; Carbognani, F.; Caride, S.; Casanueva Diaz, J.; Casentini, C.; Caudill, S.; Cavaglià, M.; Cavalier, F.; Cavalieri, R.; Cella, G.; Cepeda, C. B.; Cerboni Baiardi, L.; Cerretani, G.; Cesarini, E.; Chakraborty, R.; Chalermsongsak, T.; Chamberlin, S. J.; Chan, M.; Chao, S.; Charlton, P.; Chassande-Mottin, E.; Chatterji, S.; Chen, H. Y.; Chen, Y.; Cheng, C.; Chincarini, A.; Chiummo, A.; Cho, H. S.; Cho, M.; Chow, J. H.; Christensen, N.; Chu, Q.; Chua, S.; Chung, S.; Ciani, G.; Clara, F.; Clark, J. A.; Cleva, F.; Coccia, E.; Cohadon, P.-F.; Colla, A.; Collette, C. G.; Cominsky, L.; Conte, A.; Conti, L.; Cook, D.; Corbitt, T. R.; Cornish, N.; Corsi, A.; Cortese, S.; Costa, C. A.; Coughlin, M. W.; Coughlin, S. B.; Coulon, J.-P.; Countryman, S. T.; Couvares, P.; Cowan, E. E.; Coward, D. M.; Cowart, M. J.; Coyne, D. C.; Coyne, R.; Craig, K.; Creighton, J. D. E.; Cripe, J.; Crowder, S. G.; Cumming, A.; Cunningham, L.; Cuoco, E.; Dal Canton, T.; Danilishin, S. L.; D'Antonio, S.; Danzmann, K.; Darman, N. S.; Dattilo, V.; Dave, I.; Daveloza, H. P.; Davier, M.; Davies, G. S.; Daw, E. J.; Day, R.; DeBra, D.; Debreczeni, G.; Degallaix, J.; De Laurentis, M.; Deléglise, S.; Del Pozzo, W.; Denker, T.; Dent, T.; Dereli, H.; Dergachev, V.; DeRosa, R. T.; De Rosa, R.; DeSalvo, R.; Dhurandhar, S.; Díaz, M. C.; Di Fiore, L.; Di Giovanni, M.; Di Lieto, A.; Di Pace, S.; Di Palma, I.; Di Virgilio, A.; Dojcinoski, G.; Dolique, V.; Donovan, F.; Dooley, K. L.; Doravari, S.; Douglas, R.; Downes, T. P.; Drago, M.; Drever, R. W. P.; Driggers, J. C.; Du, Z.; Ducrot, M.; Dwyer, S. E.; Edo, T. B.; Edwards, M. C.; Effler, A.; Eggenstein, H.-B.; Ehrens, P.; Eichholz, J.; Eikenberry, S. S.; Engels, W.; Essick, R. C.; Etzel, T.; Evans, M.; Evans, T. M.; Everett, R.; Factourovich, M.; Fafone, V.; Fair, H.; Fairhurst, S.; Fan, X.; Fang, Q.; Farinon, S.; Farr, B.; Farr, W. M.; Favata, M.; Fays, M.; Fehrmann, H.; Fejer, M. M.; Ferrante, I.; Ferreira, E. C.; Ferrini, F.; Fidecaro, F.; Fiori, I.; Fiorucci, D.; Fisher, R. P.; Flaminio, R.; Fletcher, M.; Fournier, J.-D.; Franco, S.; Frasca, S.; Frasconi, F.; Frei, Z.; Freise, A.; Frey, R.; Frey, V.; Fricke, T. T.; Fritschel, P.; Frolov, V. V.; Fulda, P.; Fyffe, M.; Gabbard, H. A. G.; Gair, J. R.; Gammaitoni, L.; Gaonkar, S. G.; Garufi, F.; Gatto, A.; Gaur, G.; Gehrels, N.; Gemme, G.; Gendre, B.; Genin, E.; Gennai, A.; George, J.; Gergely, L.; Germain, V.; Ghosh, Archisman; Ghosh, S.; Giaime, J. A.; Giardina, K. D.; Giazotto, A.; Gill, K.; Glaefke, A.; Goetz, E.; Goetz, R.; Gondan, L.; González, G.; Gonzalez Castro, J. M.; Gopakumar, A.; Gordon, N. A.; Gorodetsky, M. L.; Gossan, S. E.; Gosselin, M.; Gouaty, R.; Graef, C.; Graff, P. B.; Granata, M.; Grant, A.; Gras, S.; Gray, C.; Greco, G.; Green, A. C.; Groot, P.; Grote, H.; Grunewald, S.; Guidi, G. M.; Guo, X.; Gupta, A.; Gupta, M. K.; Gushwa, K. E.; Gustafson, E. K.; Gustafson, R.; Hacker, J. J.; Hall, B. R.; Hall, E. D.; Hammond, G.; Haney, M.; Hanke, M. M.; Hanks, J.; Hanna, C.; Hannam, M. D.; Hanson, J.; Hardwick, T.; Harms, J.; Harry, G. M.; Harry, I. W.; Hart, M. J.; Hartman, M. T.; Haster, C.-J.; Haughian, K.; Heidmann, A.; Heintze, M. C.; Heitmann, H.; Hello, P.; Hemming, G.; Hendry, M.; Heng, I. S.; Hennig, J.; Heptonstall, A. W.; Heurs, M.; Hild, S.; Hoak, D.; Hodge, K. A.; Hofman, D.; Hollitt, S. E.; Holt, K.; Holz, D. E.; Hopkins, P.; Hosken, D. J.; Hough, J.; Houston, E. A.; Howell, E. J.; Hu, Y. M.; Huang, S.; Huerta, E. A.; Huet, D.; Hughey, B.; Husa, S.; Huttner, S. H.; Huynh-Dinh, T.; Idrisy, A.; Indik, N.; Ingram, D. R.; Inta, R.; Isa, H. N.; Isac, J.-M.; Isi, M.; Islas, G.; Isogai, T.; Iyer, B. R.; Izumi, K.; Jacqmin, T.; Jang, H.; Jani, K.; Jaranowski, P.; Jawahar, S.; Jiménez-Forteza, F.; Johnson, W. W.; Jones, D. I.; Jones, R.; Jonker, R. J. G.; Ju, L.; K, Haris; Kalaghatgi, C. V.; Kalogera, V.; Kandhasamy, S.; Kang, G.; Kanner, J. B.; Karki, S.; Kasprzack, M.; Katsavounidis, E.; Katzman, W.; Kaufer, S.; Kaur, T.; Kawabe, K.; Kawazoe, F.; Kéfélian, F.; Kehl, M. S.; Keitel, D.; Kelley, D. B.; Kells, W.; Kennedy, R.; Key, J. S.; Khalaidovski, A.; Khalili, F. Y.; Khan, I.; Khan, S.; Khan, Z.; Khazanov, E. A.; Kijbunchoo, N.; Kim, C.; Kim, J.; Kim, K.; Kim, Nam-Gyu; Kim, Namjun; Kim, Y.-M.; King, E. J.; King, P. J.; Kinzel, D. L.; Kissel, J. S.; Kleybolte, L.; Klimenko, S.; Koehlenbeck, S. M.; Kokeyama, K.; Koley, S.; Kondrashov, V.; Kontos, A.; Korobko, M.; Korth, W. Z.; Kowalska, I.; Kozak, D. B.; Kringel, V.; Krishnan, B.; Królak, A.; Krueger, C.; Kuehn, G.; Kumar, P.; Kuo, L.; Kutynia, A.; Lackey, B. D.; Landry, M.; Lange, J.; Lantz, B.; Lasky, P. D.; Lazzarini, A.; Lazzaro, C.; Leaci, P.; Leavey, S.; Lebigot, E. O.; Lee, C. H.; Lee, H. K.; Lee, H. M.; Lee, K.; Lenon, A.; Leonardi, M.; Leong, J. R.; Leroy, N.; Letendre, N.; Levin, Y.; Levine, B. M.; Li, T. G. F.; Libson, A.; Littenberg, T. B.; Lockerbie, N. A.; Logue, J.; Lombardi, A. L.; Lord, J. E.; Lorenzini, M.; Loriette, V.; Lormand, M.; Losurdo, G.; Lough, J. D.; Lück, H.; Lundgren, A. P.; Luo, J.; Lynch, R.; Ma, Y.; MacDonald, T.; Machenschalk, B.; MacInnis, M.; Macleod, D. M.; Magaña-Sandoval, F.; Magee, R. M.; Mageswaran, M.; Majorana, E.; Maksimovic, I.; Malvezzi, V.; Man, N.; Mandel, I.; Mandic, V.; Mangano, V.; Mansell, G. L.; Manske, M.; Mantovani, M.; Marchesoni, F.; Marion, F.; Márka, S.; Márka, Z.; Markosyan, A. S.; Maros, E.; Martelli, F.; Martellini, L.; Martin, I. W.; Martin, R. M.; Martynov, D. V.; Marx, J. N.; Mason, K.; Masserot, A.; Massinger, T. J.; Masso-Reid, M.; Matichard, F.; Matone, L.; Mavalvala, N.; Mazumder, N.; Mazzolo, G.; McCarthy, R.; McClelland, D. E.; McCormick, S.; McGuire, S. C.; McIntyre, G.; McIver, J.; McManus, D. J.; McWilliams, S. T.; Meacher, D.; Meadors, G. D.; Meidam, J.; Melatos, A.; Mendell, G.; Mendoza-Gandara, D.; Mercer, R. A.; Merilh, E.; Merzougui, M.; Meshkov, S.; Messenger, C.; Messick, C.; Meyers, P. M.; Mezzani, F.; Miao, H.; Michel, C.; Middleton, H.; Mikhailov, E. E.; Milano, L.; Miller, J.; Millhouse, M.; Minenkov, Y.; Ming, J.; Mirshekari, S.; Mishra, C.; Mitra, S.; Mitrofanov, V. P.; Mitselmakher, G.; Mittleman, R.; Moggi, A.; Mohan, M.; Mohapatra, S. R. P.; Montani, M.; Moore, B. C.; Moore, C. J.; Moraru, D.; Moreno, G.; Morriss, S. R.; Mossavi, K.; Mours, B.; Mow-Lowry, C. M.; Mueller, C. L.; Mueller, G.; Muir, A. W.; Mukherjee, Arunava; Mukherjee, D.; Mukherjee, S.; Mukund, N.; Mullavey, A.; Munch, J.; Murphy, D. J.; Murray, P. G.; Mytidis, A.; Nardecchia, I.; Naticchioni, L.; Nayak, R. K.; Necula, V.; Nedkova, K.; Nelemans, G.; Neri, M.; Neunzert, A.; Newton, G.; Nguyen, T. T.; Nielsen, A. B.; Nissanke, S.; Nitz, A.; Nocera, F.; Nolting, D.; Normandin, M. E.; Nuttall, L. K.; Oberling, J.; Ochsner, E.; O'Dell, J.; Oelker, E.; Ogin, G. H.; Oh, J. J.; Oh, S. H.; Ohme, F.; Oliver, M.; Oppermann, P.; Oram, Richard J.; O'Reilly, B.; O'Shaughnessy, R.; Ottaway, D. J.; Ottens, R. S.; Overmier, H.; Owen, B. J.; Pai, A.; Pai, S. A.; Palamos, J. R.; Palashov, O.; Palomba, C.; Pal-Singh, A.; Pan, H.; Pankow, C.; Pannarale, F.; Pant, B. C.; Paoletti, F.; Paoli, A.; Papa, M. A.; Paris, H. R.; Parker, W.; Pascucci, D.; Pasqualetti, A.; Passaquieti, R.; Passuello, D.; Patricelli, B.; Patrick, Z.; Pearlstone, B. L.; Pedraza, M.; Pedurand, R.; Pekowsky, L.; Pele, A.; Penn, S.; Perreca, A.; Phelps, M.; Piccinni, O.; Pichot, M.; Piergiovanni, F.; Pierro, V.; Pillant, G.; Pinard, L.; Pinto, I. M.; Pitkin, M.; Poggiani, R.; Popolizio, P.; Post, A.; Powell, J.; Prasad, J.; Predoi, V.; Premachandra, S. S.; Prestegard, T.; Price, L. R.; Prijatelj, M.; Principe, M.; Privitera, S.; Prodi, G. A.; Prokhorov, L.; Puncken, O.; Punturo, M.; Puppo, P.; Pürrer, M.; Qi, H.; Qin, J.; Quetschke, V.; Quintero, E. A.; Quitzow-James, R.; Raab, F. J.; Rabeling, D. S.; Radkins, H.; Raffai, P.; Raja, S.; Rakhmanov, M.; Rapagnani, P.; Raymond, V.; Razzano, M.; Re, V.; Read, J.; Reed, C. M.; Regimbau, T.; Rei, L.; Reid, S.; Reitze, D. H.; Rew, H.; Reyes, S. D.; Ricci, F.; Riles, K.; Robertson, N. A.; Robie, R.; Robinet, F.; Rocchi, A.; Rolland, L.; Rollins, J. G.; Roma, V. J.; Romano, R.; Romanov, G.; Romie, J. H.; Rosińska, D.; Rowan, S.; Rüdiger, A.; Ruggi, P.; Ryan, K.; Sachdev, S.; Sadecki, T.; Sadeghian, L.; Salconi, L.; Saleem, M.; Salemi, F.; Samajdar, A.; Sammut, L.; Sanchez, E. J.; Sandberg, V.; Sandeen, B.; Sanders, J. R.; Sassolas, B.; Sathyaprakash, B. S.; Saulson, P. R.; Sauter, O.; Savage, R. L.; Sawadsky, A.; Schale, P.; Schilling, R.; Schmidt, J.; Schmidt, P.; Schnabel, R.; Schofield, R. M. S.; Schönbeck, A.; Schreiber, E.; Schuette, D.; Schutz, B. F.; Scott, J.; Scott, S. M.; Sellers, D.; Sengupta, A. S.; Sentenac, D.; Sequino, V.; Sergeev, A.; Serna, G.; Setyawati, Y.; Sevigny, A.; Shaddock, D. A.; Shah, S.; Shahriar, M. S.; Shaltev, M.; Shao, Z.; Shapiro, B.; Shawhan, P.; Sheperd, A.; Shoemaker, D. H.; Shoemaker, D. M.; Siellez, K.; Siemens, X.; Sigg, D.; Silva, A. D.; Simakov, D.; Singer, A.; Singer, L. P.; Singh, A.; Singh, R.; Singhal, A.; Sintes, A. M.; Slagmolen, B. J. J.; Slutsky, J.; Smith, J. R.; Smith, N. D.; Smith, R. J. E.; Son, E. J.; Sorazu, B.; Sorrentino, F.; Souradeep, T.; Srivastava, A. K.; Staley, A.; Steinke, M.; Steinlechner, J.; Steinlechner, S.; Steinmeyer, D.; Stephens, B. C.; Stone, R.; Strain, K. A.; Straniero, N.; Stratta, G.; Strauss, N. A.; Strigin, S.; Sturani, R.; Stuver, A. L.; Summerscales, T. Z.; Sun, L.; Sutton, P. J.; Swinkels, B. L.; Szczepańczyk, M. J.; Tacca, M.; Talukder, D.; Tanner, D. B.; Tápai, M.; Tarabrin, S. P.; Taracchini, A.; Taylor, R.; Theeg, T.; Thirugnanasambandam, M. P.; Thomas, E. G.; Thomas, M.; Thomas, P.; Thorne, K. A.; Thorne, K. S.; Thrane, E.; Tiwari, S.; Tiwari, V.; Tokmakov, K. V.; Tomlinson, C.; Tonelli, M.; Torres, C. V.; Torrie, C. I.; Töyrä, D.; Travasso, F.; Traylor, G.; Trifirò, D.; Tringali, M. C.; Trozzo, L.; Tse, M.; Turconi, M.; Tuyenbayev, D.; Ugolini, D.; Unnikrishnan, C. S.; Urban, A. L.; Usman, S. A.; Vahlbruch, H.; Vajente, G.; Valdes, G.; van Bakel, N.; van Beuzekom, M.; van den Brand, J. F. J.; Van Den Broeck, C.; Vander-Hyde, D. C.; van der Schaaf, L.; van Heijningen, J. V.; van Veggel, A. A.; Vardaro, M.; Vass, S.; Vasúth, M.; Vaulin, R.; Vecchio, A.; Vedovato, G.; Veitch, J.; Veitch, P. J.; Venkateswara, K.; Verkindt, D.; Vetrano, F.; Viceré, A.; Vinciguerra, S.; Vine, D. J.; Vinet, J.-Y.; Vitale, S.; Vo, T.; Vocca, H.; Vorvick, C.; Voss, D.; Vousden, W. D.; Vyatchanin, S. P.; Wade, A. R.; Wade, L. E.; Wade, M.; Walker, M.; Wallace, L.; Walsh, S.; Wang, G.; Wang, H.; Wang, M.; Wang, X.; Wang, Y.; Ward, R. L.; Warner, J.; Was, M.; Weaver, B.; Wei, L.-W.; Weinert, M.; Weinstein, A. J.; Weiss, R.; Welborn, T.; Wen, L.; Weßels, P.; Westphal, T.; Wette, K.; Whelan, J. T.; Whitcomb, S.; White, D. J.; Whiting, B. F.; Williams, R. D.; Williamson, A. R.; Willis, J. L.; Willke, B.; Wimmer, M. H.; Winkler, W.; Wipf, C. C.; Wittel, H.; Woan, G.; Worden, J.; Wright, J. L.; Wu, G.; Yablon, J.; Yam, W.; Yamamoto, H.; Yancey, C. C.; Yap, M. J.; Yu, H.; Yvert, M.; Zadrożny, A.; Zangrando, L.; Zanolin, M.; Zendri, J.-P.; Zevin, M.; Zhang, F.; Zhang, L.; Zhang, M.; Zhang, Y.; Zhao, C.; Zhou, M.; Zhou, Z.; Zhu, X. J.; Zotov, N.; Zucker, M. E.; Zuraw, S. E.; Zweizig, J.; LIGO Scientific Collaboration; Virgo Collaboration

2016-07-01

On 14 September 2015, a gravitational wave signal from a coalescing black hole binary system was observed by the Advanced LIGO detectors. This paper describes the transient noise backgrounds used to determine the significance of the event (designated GW150914) and presents the results of investigations into potential correlated or uncorrelated sources of transient noise in the detectors around the time of the event. The detectors were operating nominally at the time of GW150914. We have ruled out environmental influences and non-Gaussian instrument noise at either LIGO detector as the cause of the observed gravitational wave signal.

Characterization of Transient Noise in Advanced LIGO Relevant to Gravitational Wave Signal GW150914

NASA Technical Reports Server (NTRS)

Abbott, B. P.; Abbott, R.; Abbott, T. D.; Abernathy, M. R.; Acernese, F.; Ackley, K.; Adamo, M.; Adams, C.; Adams, T.; Camp, Jordan B.

2016-01-01

On 14 September 2015, a gravitational wave signal from a coalescing black hole binary system was observed by the Advanced LIGO detectors. This paper describes the transient noise backgrounds used to determine the significance of the event (designated GW150914) and presents the results of investigations into potential correlated or uncorrelated sources of transient noise in the detectors around the time of the event. The detectors were operating nominally at the time of GW150914. We have ruled out environmental influences and non-Gaussian instrument noise at either LIGO detector as the cause of the observed gravitational wave signal.

Modeling of digital mammograms using bicubic spline functions and additive noise

NASA Astrophysics Data System (ADS)

Graffigne, Christine; Maintournam, Aboubakar; Strauss, Anne

1998-09-01

The purpose of our work is the microcalcifications detection on digital mammograms. In order to do so, we model the grey levels of digital mammograms by the sum of a surface trend (bicubic spline function) and an additive noise or texture. We also introduce a robust estimation method in order to overcome the bias introduced by the microcalcifications. After the estimation we consider the subtraction image values as noise. If the noise is not correlated, we adjust its distribution probability by the Pearson's system of densities. It allows us to threshold accurately the images of subtraction and therefore to detect the microcalcifications. If the noise is correlated, a unilateral autoregressive process is used and its coefficients are again estimated by the least squares method. We then consider non overlapping windows on the residues image. In each window the texture residue is computed and compared with an a priori threshold. This provides correct localization of the microcalcifications clusters. However this technique is definitely more time consuming that then automatic threshold assuming uncorrelated noise and does not lead to significantly better results. As a conclusion, even if the assumption of uncorrelated noise is not correct, the automatic thresholding based on the Pearson's system performs quite well on most of our images.

Physiological and content considerations for a second low frequency channel for bass management, subwoofers, and low frequency enhancement (LFE)

NASA Astrophysics Data System (ADS)

Miller, Robert E. (Robin)

2005-04-01

Perception of very low frequencies (VLF) below 125 Hz reproduced by large woofers and subwoofers (SW), encompassing 3 octaves of the 10 regarded as audible, has physiological and content aspects. Large room acoustics and vibrato add VLF fluctuations, modulating audible carrier frequencies to >1 Hz. By convention, sounds below 90 Hz produce no interaural cues useful for spatial perception or localization, therefore bass management redirects the VLF range from main channels to a single (monaural) subwoofer channel, even if to more than one subwoofer. Yet subjects claim they hear a difference between a single subwoofer channel and two (stereo bass). If recordings contain spatial VLF content, is it possible physiologically to perceive interaural time/phase difference (ITD/IPD) between 16 and 125 Hz? To what extent does this perception have a lifelike quality; to what extent is it localization? If a first approximation of localization, would binaural SWs allow a higher crossover frequency (smaller satellite speakers)? Reported research supports the Jeffress model of ITD determination in brain structures, and extending the accepted lower frequency limit of IPD. Meanwhile, uncorrelated very low frequencies exist in all tested multi-channel music and movie content. The audibility, recording, and reproduction of uncorrelated VLF are explored in theory and experiments.

A Range Correction for Icesat and Its Potential Impact on Ice-sheet Mass Balance Studies

NASA Technical Reports Server (NTRS)

Borsa, A. A.; Moholdt, G.; Fricker, H. A.; Brunt, Kelly M.

2014-01-01

We report on a previously undocumented range error in NASA's Ice, Cloud and land Elevation Satellite (ICESat) that degrades elevation precision and introduces a small but significant elevation trend over the ICESat mission period. This range error (the Gaussian-Centroid or 'G-C'offset) varies on a shot-to-shot basis and exhibits increasing scatter when laser transmit energies fall below 20 mJ. Although the G-C offset is uncorrelated over periods less than1 day, it evolves over the life of each of ICESat's three lasers in a series of ramps and jumps that give rise to spurious elevation trends of -0.92 to -1.90 cm yr(exp -1), depending on the time period considered. Using ICESat data over the Ross and Filchner-Ronne ice shelves we show that (1) the G-C offset introduces significant biases in ice-shelf mass balance estimates, and (2) the mass balance bias can vary between regions because of different temporal samplings of ICESat.We can reproduce the effect of the G-C offset over these two ice shelves by fitting trends to sample-weighted mean G-C offsets for each campaign, suggesting that it may not be necessary to fully repeat earlier ICESat studies to determine the impact of the G-C offset on ice-sheet mass balance estimates.

Estimating free-body modal parameters from tests of a constrained structure

NASA Technical Reports Server (NTRS)

Cooley, Victor M.

1993-01-01

Hardware advances in suspension technology for ground tests of large space structures provide near on-orbit boundary conditions for modal testing. Further advances in determining free-body modal properties of constrained large space structures have been made, on the analysis side, by using time domain parameter estimation and perturbing the stiffness of the constraints over multiple sub-tests. In this manner, passive suspension constraint forces, which are fully correlated and therefore not usable for spectral averaging techniques, are made effectively uncorrelated. The technique is demonstrated with simulated test data.

35 GHz mode-locking of 1.3 μm quantum dot lasers

NASA Astrophysics Data System (ADS)

Kuntz, M.; Fiol, G.; Lämmlin, M.; Bimberg, D.; Thompson, M. G.; Tan, K. T.; Marinelli, C.; Penty, R. V.; White, I. H.; Ustinov, V. M.; Zhukov, A. E.; Shernyakov, Yu. M.; Kovsh, A. R.

2004-08-01

35GHz passive mode-locking of 1.3μm (InGa)As/GaAs quantum dot lasers is reported. Hybrid mode-locking was achieved at frequencies up to 20GHz. The minimum pulse width of the Fourier-limited pulses was 7ps with a peak power of 6mW. Low uncorrelated timing jitter below 1ps was found in cross correlation experiments. High-frequency operation of the lasers was eased by a ridge waveguide design that includes etching through the active layer.

Time Delay and Accretion Disk Size Measurements in the Lensed Quasar SBS 0909+532 from Multiwavelength Microlensing Analysis

DTIC Science & Technology

2013-09-01

of the cosmic microwave background dipole velocity onto the lens plane, as done by Kochanek (2004). We compare the simulated light curves to the...observer, the background source, the foreground lens galaxy, and its stars cause uncorrelated variations in the source magnification as a function of...hereafter SBS 0909; αJ2000 = 09h13m01.s05, δJ2000 = +52d59m28.s83) is a doubly-imaged quasar lens sys- tem in which the background quasar has redshift

Football fever: goal distributions and non-Gaussian statistics

NASA Astrophysics Data System (ADS)

Bittner, E.; Nußbaumer, A.; Janke, W.; Weigel, M.

2009-02-01

Analyzing football score data with statistical techniques, we investigate how the not purely random, but highly co-operative nature of the game is reflected in averaged properties such as the probability distributions of scored goals for the home and away teams. As it turns out, especially the tails of the distributions are not well described by the Poissonian or binomial model resulting from the assumption of uncorrelated random events. Instead, a good effective description of the data is provided by less basic distributions such as the negative binomial one or the probability densities of extreme value statistics. To understand this behavior from a microscopical point of view, however, no waiting time problem or extremal process need be invoked. Instead, modifying the Bernoulli random process underlying the Poissonian model to include a simple component of self-affirmation seems to describe the data surprisingly well and allows to understand the observed deviation from Gaussian statistics. The phenomenological distributions used before can be understood as special cases within this framework. We analyzed historical football score data from many leagues in Europe as well as from international tournaments, including data from all past tournaments of the “FIFA World Cup” series, and found the proposed models to be applicable rather universally. In particular, here we analyze the results of the German women’s premier football league and consider the two separate German men’s premier leagues in the East and West during the cold war times as well as the unified league after 1990 to see how scoring in football and the component of self-affirmation depend on cultural and political circumstances.

Why would we use the Sediment Isotope Tomography (SIT) model to establish a 210Pb-based chronology in recent-sediment cores?

PubMed

Abril Hernández, José-María

2015-05-01

After half a century, the use of unsupported (210)Pb ((210)Pbexc) is still far off from being a well established dating tool for recent sediments with widespread applicability. Recent results from the statistical analysis of time series of fluxes, mass sediment accumulation rates (SAR), and initial activities, derived from varved sediments, place serious constraints to the assumption of constant fluxes, which is widely used in dating models. The Sediment Isotope Tomography (SIT) model, under the assumption of non post-depositional redistribution, is used for dating recent sediments in scenarios in that fluxes and SAR are uncorrelated and both vary with time. By using a simple graphical analysis, this paper shows that under the above assumptions, any given (210)Pbexc profile, even with the restriction of a discrete set of reference points, is compatible with an infinite number of chronological lines, and thus generating an infinite number of mathematically exact solutions for histories of initial activity concentrations, SAR and fluxes onto the SWI, with these two last ranging from zero up to infinity. Particularly, SIT results, without additional assumptions, cannot contain any statistically significant difference with respect to the exact solutions consisting in intervals of constant SAR or constant fluxes (both being consistent with the reference points). Therefore, there is not any benefit in its use as a dating tool without the explicit introduction of additional restrictive assumptions about fluxes, SAR and/or their interrelationship. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Hubble Space Telescope Survey for Novae in M87. I. Light and Color Curves, Spatial Distributions, and the Nova Rate

NASA Astrophysics Data System (ADS)

Shara, Michael M.; Doyle, Trisha F.; Lauer, Tod R.; Zurek, David; Neill, J. D.; Madrid, Juan P.; Mikołajewska, Joanna; Welch, D. L.; Baltz, Edward A.

2016-11-01

The Hubble Space Telescope has imaged the central part of M87 over a 10 week span, leading to the discovery of 32 classical novae (CNe) and nine fainter, likely very slow, and/or symbiotic novae. In this first paper of a series, we present the M87 nova finder charts, and the light and color curves of the novae. We demonstrate that the rise and decline times, and the colors of M87 novae are uncorrelated with each other and with position in the galaxy. The spatial distribution of the M87 novae follows the light of the galaxy, suggesting that novae accreted by M87 during cannibalistic episodes are well-mixed. Conservatively using only the 32 brightest CNe we derive a nova rate for M87: {363}-45+33 novae yr‑1. We also derive the luminosity-specific classical nova rate for this galaxy, which is {7.88}-2.6+2.3 {yr}}-1/{10}10 {L}ȯ {,}K. Both rates are 3–4 times higher than those reported for M87 in the past, and similarly higher than those reported for all other galaxies. We suggest that most previous ground-based surveys for novae in external galaxies, including M87, miss most faint, fast novae, and almost all slow novae near the centers of galaxies. Based on observations with the NASA/ESA Hubble Space Telescope, obtained at the Space Telescope Science Institute, which is operated by AURA, Inc., under NASA contract NAS 5-26555.

A radial map of multi-whisker correlation selectivity in the rat barrel cortex

PubMed Central

Estebanez, Luc; Bertherat, Julien; Shulz, Daniel E.; Bourdieu, Laurent; Léger, Jean- François

2016-01-01

In the barrel cortex, several features of single-whisker stimuli are organized in functional maps. The barrel cortex also encodes spatio-temporal correlation patterns of multi-whisker inputs, but so far the cortical mapping of neurons tuned to such input statistics is unknown. Here we report that layer 2/3 of the rat barrel cortex contains an additional functional map based on neuronal tuning to correlated versus uncorrelated multi-whisker stimuli: neuron responses to uncorrelated multi-whisker stimulation are strongest above barrel centres, whereas neuron responses to correlated and anti-correlated multi-whisker stimulation peak above the barrel–septal borders, forming rings of multi-whisker synchrony-preferring cells. PMID:27869114

A radial map of multi-whisker correlation selectivity in the rat barrel cortex.

PubMed

Estebanez, Luc; Bertherat, Julien; Shulz, Daniel E; Bourdieu, Laurent; Léger, Jean-François

2016-11-21

In the barrel cortex, several features of single-whisker stimuli are organized in functional maps. The barrel cortex also encodes spatio-temporal correlation patterns of multi-whisker inputs, but so far the cortical mapping of neurons tuned to such input statistics is unknown. Here we report that layer 2/3 of the rat barrel cortex contains an additional functional map based on neuronal tuning to correlated versus uncorrelated multi-whisker stimuli: neuron responses to uncorrelated multi-whisker stimulation are strongest above barrel centres, whereas neuron responses to correlated and anti-correlated multi-whisker stimulation peak above the barrel-septal borders, forming rings of multi-whisker synchrony-preferring cells.

A novel x-ray detector design with higher DQE and reduced aliasing: Theoretical analysis of x-ray reabsoprtion in detector converter material

NASA Astrophysics Data System (ADS)

Nano, Tomi; Escartin, Terenz; Karim, Karim S.; Cunningham, Ian A.

2016-03-01

The ability to improve visualization of structural information in digital radiography without increasing radiation exposures requires improved image quality across all spatial frequencies, especially at high frequencies. The detective quantum efficiency (DQE) as a function of spatial frequency quantifies image quality given by an x-ray detector. We present a method of increasing DQE at high spatial frequencies by improving the modulation transfer function (MTF) and reducing noise aliasing. The Apodized Aperature Pixel (AAP) design uses a detector with micro-elements to synthesize desired pixels and provide higher DQE than conventional detector designs. A cascaded system analysis (CSA) that incorporates x-ray interactions is used for comparison of the theoretical MTF, noise power spectrum (NPS), and DQE. Signal and noise transfer through the converter material is shown to consist of correlated an uncorrelated terms. The AAP design was shown to improve the DQE of both material types that have predominantly correlated transfer (such as CsI) and predominantly uncorrelated transfer (such as Se). Improvement in the MTF by 50% and the DQE by 100% at the sampling cut-off frequency is obtained when uncorrelated transfer is prevalent through the converter material. Optimizing high-frequency DQE results in improved image contrast and visualization of small structures and fine-detail.

On the efficacy of spatial sampling using manual scanning paths to determine the spatial average sound pressure level in rooms.

PubMed

Hopkins, Carl

2011-05-01

In architectural acoustics, noise control and environmental noise, there are often steady-state signals for which it is necessary to measure the spatial average, sound pressure level inside rooms. This requires using fixed microphone positions, mechanical scanning devices, or manual scanning. In comparison with mechanical scanning devices, the human body allows manual scanning to trace out complex geometrical paths in three-dimensional space. To determine the efficacy of manual scanning paths in terms of an equivalent number of uncorrelated samples, an analytical approach is solved numerically. The benchmark used to assess these paths is a minimum of five uncorrelated fixed microphone positions at frequencies above 200 Hz. For paths involving an operator walking across the room, potential problems exist with walking noise and non-uniform scanning speeds. Hence, paths are considered based on a fixed standing position or rotation of the body about a fixed point. In empty rooms, it is shown that a circle, helix, or cylindrical-type path satisfy the benchmark requirement with the latter two paths being highly efficient at generating large number of uncorrelated samples. In furnished rooms where there is limited space for the operator to move, an efficient path comprises three semicircles with 45°-60° separations.

Feature-to-Feature Inference Under Conditions of Cue Restriction and Dimensional Correlation.

PubMed

Lancaster, Matthew E; Homa, Donald

2017-01-01

The present study explored feature-to-feature and label-to-feature inference in a category task for different category structures. In the correlated condition, each of the 4 dimensions comprising the category was positively correlated to each other and to the category label. In the uncorrelated condition, no correlation existed between the 4 dimensions comprising the category, although the dimension to category label correlation matched that of the correlated condition. After learning, participants made inference judgments of a missing feature, given 1, 2, or 3 feature cues; on half the trials, the category label was also included as a cue. The results showed superior inference of features following training on the correlated structure, with accurate inference when only a single feature was presented. In contrast, a single-feature cue resulted in chance levels of inference for the uncorrelated structure. Feature inference systematically improved with number of cues after training on the correlated structure. Surprisingly, a similar outcome was obtained for the uncorrelated structure, an outcome that must have reflected mediation via the category label. A descriptive model is briefly introduced to explain the results, with a suggestion that this paradigm might be profitably extended to hierarchical structures where the levels of feature-to-feature inference might vary with the depth of the hierarchy.

Phase Distribution and Selection of Partially Correlated Persistent Scatterers

NASA Astrophysics Data System (ADS)

Lien, J.; Zebker, H. A.

2012-12-01

Interferometric synthetic aperture radar (InSAR) time-series methods can effectively estimate temporal surface changes induced by geophysical phenomena. However, such methods are susceptible to decorrelation due to spatial and temporal baselines (radar pass separation), changes in orbital geometries, atmosphere, and noise. These effects limit the number of interferograms that can be used for differential analysis and obscure the deformation signal. InSAR decorrelation effects may be ameliorated by exploiting pixels that exhibit phase stability across the stack of interferograms. These so-called persistent scatterer (PS) pixels are dominated by a single point-like scatterer that remains phase-stable over the spatial and temporal baseline. By identifying a network of PS pixels for use in phase unwrapping, reliable deformation measurements may be obtained even in areas of low correlation, where traditional InSAR techniques fail to produce useful observations. Many additional pixels can be added to the PS list if we are able to identify those in which a dominant scatterer exhibits partial, rather than complete, correlation across all radar scenes. In this work, we quantify and exploit the phase stability of partially correlated PS pixels. We present a new system model for producing interferometric pixel values from a complex surface backscatter function characterized by signal-to-clutter ratio (SCR). From this model, we derive the joint probabilistic distribution for PS pixel phases in a stack of interferograms as a function of SCR and spatial baselines. This PS phase distribution generalizes previous results that assume the clutter phase contribution is uncorrelated between radar passes. We verify the analytic distribution through a series of radar scattering simulations. We use the derived joint PS phase distribution with maximum-likelihood SCR estimation to analyze an area of the Hayward Fault Zone in the San Francisco Bay Area. We obtain a series of 38 interferometric images of the area from C-band ERS radar satellite passes between May 1995 and December 2000. We compare the estimated SCRs to those calculated with previously derived PS phase distributions. Finally, we examine the PS network density resulting from varying selection thresholds of SCR and compare to other PS identification techniques.

Statistics of primordial density perturbations from discrete seed masses

NASA Technical Reports Server (NTRS)

Scherrer, Robert J.; Bertschinger, Edmund

1991-01-01

The statistics of density perturbations for general distributions of seed masses with arbitrary matter accretion is examined. Formal expressions for the power spectrum, the N-point correlation functions, and the density distribution function are derived. These results are applied to the case of uncorrelated seed masses, and power spectra are derived for accretion of both hot and cold dark matter plus baryons. The reduced moments (cumulants) of the density distribution are computed and used to obtain a series expansion for the density distribution function. Analytic results are obtained for the density distribution function in the case of a distribution of seed masses with a spherical top-hat accretion pattern. More generally, the formalism makes it possible to give a complete characterization of the statistical properties of any random field generated from a discrete linear superposition of kernels. In particular, the results can be applied to density fields derived by smoothing a discrete set of points with a window function.

Weak interfaces for UV cure nanoimprint lithography

NASA Astrophysics Data System (ADS)

Houle, Frances; Fornof, Ann; Simonyi, Eva; Miller, Dolores; Truong, Hoa

2008-03-01

Nanoimprint lithography using a photocurable organic resist provides a means of patterning substrates with a spatial resolution in the few nm range. The usefulness of the technique is limited by defect generation during template removal, which involves fracture at the interface between the template and the newly cured polymer. Although it is critical to have the lowest possible interfacial fracture toughness (Gc less than 0.1 Jm-2) to avoid cohesive failure in the polymer, there is little understanding on how to achieve this using reacting low viscosity resist fluids. Studies of debonding of a series of free-radical cured polyhedral silsesquioxane crosslinker formulations containing selected reactive diluents from fluorosilane-coated quartz template materials will be described. At constant diluent fraction the storage modulus of cured resists follows trends in initial reaction rate, not diluent Tg. Adhesion is uncorrelated with both Tg and storage modulus. XPS studies of near-interface compositions indicate that component segregation within the resist fluid on contact with the template, prior to cure, plays a significant role in controlling the fracture process.

Identification of Correlated GRACE Monthly Harmonic Coefficients Using Pattern Recognition and Neural Networks

NASA Astrophysics Data System (ADS)

Piretzidis, D.; Sra, G.; Sideris, M. G.

2016-12-01

This study explores new methods for identifying correlation errors in harmonic coefficients derived from monthly solutions of the Gravity Recovery and Climate Experiment (GRACE) satellite mission using pattern recognition and neural network algorithms. These correlation errors are evidenced in the differences between monthly solutions and can be suppressed using a de-correlation filter. In all studies so far, the implementation of the de-correlation filter starts from a specific minimum order (i.e., 11 for RL04 and 38 for RL05) until the maximum order of the monthly solution examined. This implementation method has two disadvantages, namely, the omission of filtering correlated coefficients of order less than the minimum order and the filtering of uncorrelated coefficients of order higher than the minimum order. In the first case, the filtered solution is not completely free of correlated errors, whereas the second case results in a monthly solution that suffers from loss of geophysical signal. In the present study, a new method of implementing the de-correlation filter is suggested, by identifying and filtering only the coefficients that show indications of high correlation. Several numerical and geometric properties of the harmonic coefficient series of all orders are examined. Extreme cases of both correlated and uncorrelated coefficients are selected, and their corresponding properties are used to train a two-layer feed-forward neural network. The objective of the neural network is to identify and quantify the correlation by providing the probability of an order of coefficients to be correlated. Results show good performance of the neural network, both in the validation stage of the training procedure and in the subsequent use of the trained network to classify independent coefficients. The neural network is also capable of identifying correlated coefficients even when a small number of training samples and neurons are used (e.g.,100 and 10, respectively).

Model identification using stochastic differential equation grey-box models in diabetes.

PubMed

Duun-Henriksen, Anne Katrine; Schmidt, Signe; Røge, Rikke Meldgaard; Møller, Jonas Bech; Nørgaard, Kirsten; Jørgensen, John Bagterp; Madsen, Henrik

2013-03-01

The acceptance of virtual preclinical testing of control algorithms is growing and thus also the need for robust and reliable models. Models based on ordinary differential equations (ODEs) can rarely be validated with standard statistical tools. Stochastic differential equations (SDEs) offer the possibility of building models that can be validated statistically and that are capable of predicting not only a realistic trajectory, but also the uncertainty of the prediction. In an SDE, the prediction error is split into two noise terms. This separation ensures that the errors are uncorrelated and provides the possibility to pinpoint model deficiencies. An identifiable model of the glucoregulatory system in a type 1 diabetes mellitus (T1DM) patient is used as the basis for development of a stochastic-differential-equation-based grey-box model (SDE-GB). The parameters are estimated on clinical data from four T1DM patients. The optimal SDE-GB is determined from likelihood-ratio tests. Finally, parameter tracking is used to track the variation in the "time to peak of meal response" parameter. We found that the transformation of the ODE model into an SDE-GB resulted in a significant improvement in the prediction and uncorrelated errors. Tracking of the "peak time of meal absorption" parameter showed that the absorption rate varied according to meal type. This study shows the potential of using SDE-GBs in diabetes modeling. Improved model predictions were obtained due to the separation of the prediction error. SDE-GBs offer a solid framework for using statistical tools for model validation and model development. © 2013 Diabetes Technology Society.

Wave Extremes in the Northeast Atlantic from Ensemble Forecasts

NASA Astrophysics Data System (ADS)

Breivik, Øyvind; Aarnes, Ole Johan; Bidlot, Jean-Raymond; Carrasco, Ana; Saetra, Øyvind

2013-10-01

A method for estimating return values from ensembles of forecasts at advanced lead times is presented. Return values of significant wave height in the North-East Atlantic, the Norwegian Sea and the North Sea are computed from archived +240-h forecasts of the ECMWF ensemble prediction system (EPS) from 1999 to 2009. We make three assumptions: First, each forecast is representative of a six-hour interval and collectively the data set is then comparable to a time period of 226 years. Second, the model climate matches the observed distribution, which we confirm by comparing with buoy data. Third, the ensemble members are sufficiently uncorrelated to be considered independent realizations of the model climate. We find anomaly correlations of 0.20, but peak events (>P97) are entirely uncorrelated. By comparing return values from individual members with return values of subsamples of the data set we also find that the estimates follow the same distribution and appear unaffected by correlations in the ensemble. The annual mean and variance over the 11-year archived period exhibit no significant departures from stationarity compared with a recent reforecast, i.e., there is no spurious trend due to model upgrades. EPS yields significantly higher return values than ERA-40 and ERA-Interim and is in good agreement with the high-resolution hindcast NORA10, except in the lee of unresolved islands where EPS overestimates and in enclosed seas where it is biased low. Confidence intervals are half the width of those found for ERA-Interim due to the magnitude of the data set.

Phobos laser ranging: Numerical Geodesy experiments for Martian system science

NASA Astrophysics Data System (ADS)

Dirkx, D.; Vermeersen, L. L. A.; Noomen, R.; Visser, P. N. A. M.

2014-09-01

Laser ranging is emerging as a technology for use over (inter)planetary distances, having the advantage of high (mm-cm) precision and accuracy and low mass and power consumption. We have performed numerical simulations to assess the science return in terms of geodetic observables of a hypothetical Phobos lander performing active two-way laser ranging with Earth-based stations. We focus our analysis on the estimation of Phobos and Mars gravitational, tidal and rotational parameters. We explicitly include systematic error sources in addition to uncorrelated random observation errors. This is achieved through the use of consider covariance parameters, specifically the ground station position and observation biases. Uncertainties for the consider parameters are set at 5 mm and at 1 mm for the Gaussian uncorrelated observation noise (for an observation integration time of 60 s). We perform the analysis for a mission duration up to 5 years. It is shown that a Phobos Laser Ranging (PLR) can contribute to a better understanding of the Martian system, opening the possibility for improved determination of a variety of physical parameters of Mars and Phobos. The simulations show that the mission concept is especially suited for estimating Mars tidal deformation parameters, estimating degree 2 Love numbers with absolute uncertainties at the 10-2 to 10-4 level after 1 and 4 years, respectively and providing separate estimates for the Martian quality factors at Sun and Phobos-forced frequencies. The estimation of Phobos libration amplitudes and gravity field coefficients provides an estimate of Phobos' relative equatorial and polar moments of inertia with an absolute uncertainty of 10-4 and 10-7, respectively, after 1 year. The observation of Phobos tidal deformation will be able to differentiate between a rubble pile and monolithic interior within 2 years. For all parameters, systematic errors have a much stronger influence (per unit uncertainty) than the uncorrelated Gaussian observation noise. This indicates the need for the inclusion of systematic errors in simulation studies and special attention to the mitigation of these errors in mission and system design.

Temporal correlation measurements of pulsed dual CO2 lidar returns. [for atmospheric pollution detection

NASA Technical Reports Server (NTRS)

Menyuk, N.; Killinger, D. K.

1981-01-01

A pulsed dual-laser direct-detection differential-absorption lidar DIAL system, operating near 10.6 microns, is used to measure the temporal correlation and statistical properties of backscattered returns from specular and diffuse topographic targets. Results show that atmospheric-turbulence fluctuations can effectively be frozen for pulse separation times on the order of 1-3 msec or less. The diffuse target returns, however, yielded a much lower correlation than that obtained with the specular targets; this being due to uncorrelated system noise effects and different statistics for the two types of target returns.

Long and Short Range Correlations in Healthy and Pathologic Human Cardiac Prosses

NASA Astrophysics Data System (ADS)

Bunde, Armin

2001-03-01

Healthy sleep consists of several stages: deep sleep, light sleep and REM sleep. In this talk, recent work on the characterization of heart-rates in the three stages by long-range correlations is presented. Only in REM sleep, long-range correlations reminiscent to the wake phase occur, and the heart-rates show multifractal behaviour. In contrast, in non-REM phases, the heart-rates are uncorrelated above the typical breathing cycle time, pointing to a random regulation of the heartbeat during non-REM sleep. In deep sleep, the heart-rates show simple multifractal behaviour.

Spectral properties of the Preisach hysteresis model with random input. II. Universality classes for symmetric elementary loops

NASA Astrophysics Data System (ADS)

Radons, Günter

2008-06-01

The Preisach model with symmetric elementary hysteresis loops and uncorrelated input is treated analytically in detail. It is shown that the appearance of long-time tails in the output correlations is a quite general feature of this model. The exponent η of the algebraic decay t-η , which may take any positive value, is determined by the tails of the input and the Preisach density. We identify the system classes leading to identical algebraic tails. These results imply the occurrence of 1/f noise for a large class of hysteretic systems.

"Juice Monsters": Sub-Ohm Vaping and Toxic Volatile Aldehyde Emissions.

PubMed

Talih, Soha; Salman, Rola; Karaoghlanian, Nareg; El-Hellani, Ahmad; Saliba, Najat; Eissenberg, Thomas; Shihadeh, Alan

2017-10-16

An emerging category of electronic cigarettes (ECIGs) is sub-Ohm devices (SODs) that operate at ten or more times the power of conventional ECIGs. Because carcinogenic volatile aldehyde (VA) emissions increase sharply with power, SODs may expose users to greater VAs. In this study, we compared VA emissions from several SODs and found that across device, VAs and power were uncorrelated unless power was normalized by coil surface area. VA emissions and liquid consumed were correlated highly. Analyzed in light of EU regulations limiting ECIG liquid nicotine concentration, these findings suggest potential regulatory levers and pitfalls for protecting public health.

Uncorrelated measurements of the cosmic expansion history and dark energy from supernovae

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

Wang Yun; Tegmark, Max; Department of Physics, University of Pennsylvania, Philadelphia, Pennsylvania 19104

We present a method for measuring the cosmic expansion history H(z) in uncorrelated redshift bins, and apply it to current and simulated type Ia supernova data assuming spatial flatness. If the matter density parameter {omega}{sub m} can be accurately measured from other data, then the dark-energy density history X(z)={rho}{sub X}(z)/{rho}{sub X}(0) can trivially be derived from this expansion history H(z). In contrast to customary 'black box' parameter fitting, our method is transparent and easy to interpret: the measurement of H(z){sup -1} in a redshift bin is simply a linear combination of the measured comoving distances for supernovae in that bin,more » making it obvious how systematic errors propagate from input to output. We find the Riess et al. (2004) gold sample to be consistent with the vanilla concordance model where the dark energy is a cosmological constant. We compare two mission concepts for the NASA/DOE Joint Dark-Energy Mission (JDEM), the Joint Efficient Dark-energy Investigation (JEDI), and the Supernova Accelaration Probe (SNAP), using simulated data including the effect of weak lensing (based on numerical simulations) and a systematic bias from K corrections. Estimating H(z) in seven uncorrelated redshift bins, we find that both provide dramatic improvements over current data: JEDI can measure H(z) to about 10% accuracy and SNAP to 30%-40% accuracy.« less

Observation of Brownian motion in liquids at short times: instantaneous velocity and memory loss.

PubMed

Kheifets, Simon; Simha, Akarsh; Melin, Kevin; Li, Tongcang; Raizen, Mark G

2014-03-28

Measurement of the instantaneous velocity of Brownian motion of suspended particles in liquid probes the microscopic foundations of statistical mechanics in soft condensed matter. However, instantaneous velocity has eluded experimental observation for more than a century since Einstein's prediction of the small length and time scales involved. We report shot-noise-limited, high-bandwidth measurements of Brownian motion of micrometer-sized beads suspended in water and acetone by an optical tweezer. We observe the hydrodynamic instantaneous velocity of Brownian motion in a liquid, which follows a modified energy equipartition theorem that accounts for the kinetic energy of the fluid displaced by the moving bead. We also observe an anticorrelated thermal force, which is conventionally assumed to be uncorrelated.

Research of facial feature extraction based on MMC

NASA Astrophysics Data System (ADS)

Xue, Donglin; Zhao, Jiufen; Tang, Qinhong; Shi, Shaokun

2017-07-01

Based on the maximum margin criterion (MMC), a new algorithm of statistically uncorrelated optimal discriminant vectors and a new algorithm of orthogonal optimal discriminant vectors for feature extraction were proposed. The purpose of the maximum margin criterion is to maximize the inter-class scatter while simultaneously minimizing the intra-class scatter after the projection. Compared with original MMC method and principal component analysis (PCA) method, the proposed methods are better in terms of reducing or eliminating the statistically correlation between features and improving recognition rate. The experiment results on Olivetti Research Laboratory (ORL) face database shows that the new feature extraction method of statistically uncorrelated maximum margin criterion (SUMMC) are better in terms of recognition rate and stability. Besides, the relations between maximum margin criterion and Fisher criterion for feature extraction were revealed.

Pulsed source of spectrally uncorrelated and indistinguishable photons at telecom wavelengths.

PubMed

Bruno, N; Martin, A; Guerreiro, T; Sanguinetti, B; Thew, R T

2014-07-14

We report on the generation of indistinguishable photon pairs at telecom wavelengths based on a type-II parametric down conversion process in a periodically poled potassium titanyl phosphate (PPKTP) crystal. The phase matching, pump laser characteristics and coupling geometry are optimised to obtain spectrally uncorrelated photons with high coupling efficiencies. Four photons are generated by a counter-propagating pump in the same crystal and anlysed via two photon interference experiments between photons from each pair source as well as joint spectral and g((2)) measurements. We obtain a spectral purity of 0.91 and coupling efficiencies around 90% for all four photons without any filtering. These pure indistinguishable photon sources at telecom wavelengths are perfectly adapted for quantum network demonstrations and other multi-photon protocols.

Publisher Correction: Imaging the square of the correlated two-electron wave function of a hydrogen molecule.

PubMed

Waitz, M; Bello, R Y; Metz, D; Lower, J; Trinter, F; Schober, C; Keiling, M; Lenz, U; Pitzer, M; Mertens, K; Martins, M; Viefhaus, J; Klumpp, S; Weber, T; Schmidt, L Ph H; Williams, J B; Schöffler, M S; Serov, V V; Kheifets, A S; Argenti, L; Palacios, A; Martín, F; Jahnke, T; Dörner, R

2018-06-05

The original version of this Article contained an error in the fifth sentence of the first paragraph of the 'Application on H 2 ' section of the Results, which incorrectly read 'The role of electron correlation is quite apparent in this presentation: Fig. 1a is empty for the uncorrelated Hartree-Fock wave function, since projection of the latter wave function onto the 2pσ u orbital is exactly zero, while this is not the case for the fully correlated wave function (Fig. 1d); also, Fig. 1b, c for the uncorrelated description are identical, while Fig. 1e, f for the correlated case are significantly different.' The correct version replaces 'Fig. 1e, f' with 'Fig. 2e and f'.

Protecting clean critical points by local disorder correlations

NASA Astrophysics Data System (ADS)

Hoyos, J. A.; Laflorencie, Nicolas; Vieira, André.; Vojta, Thomas

2011-03-01

We show that a broad class of quantum critical points can be stable against locally correlated disorder even if they are unstable against uncorrelated disorder. Although this result seemingly contradicts the Harris criterion, it follows naturally from the absence of a random-mass term in the associated order-parameter field theory. We illustrate the general concept with explicit calculations for quantum spin-chain models. Instead of the infinite-randomness physics induced by uncorrelated disorder, we find that weak locally correlated disorder is irrelevant. For larger disorder, we find a line of critical points with unusual properties such as an increase of the entanglement entropy with the disorder strength. We also propose experimental realizations in the context of quantum magnetism and cold-atom physics. Financial support: Fapesp, CNPq, NSF, and Research Corporation.

Random matrix approach to cross correlations in financial data

NASA Astrophysics Data System (ADS)

Plerou, Vasiliki; Gopikrishnan, Parameswaran; Rosenow, Bernd; Amaral, Luís A.; Guhr, Thomas; Stanley, H. Eugene

2002-06-01

We analyze cross correlations between price fluctuations of different stocks using methods of random matrix theory (RMT). Using two large databases, we calculate cross-correlation matrices C of returns constructed from (i) 30-min returns of 1000 US stocks for the 2-yr period 1994-1995, (ii) 30-min returns of 881 US stocks for the 2-yr period 1996-1997, and (iii) 1-day returns of 422 US stocks for the 35-yr period 1962-1996. We test the statistics of the eigenvalues λi of C against a ``null hypothesis'' - a random correlation matrix constructed from mutually uncorrelated time series. We find that a majority of the eigenvalues of C fall within the RMT bounds [λ-,λ+] for the eigenvalues of random correlation matrices. We test the eigenvalues of C within the RMT bound for universal properties of random matrices and find good agreement with the results for the Gaussian orthogonal ensemble of random matrices-implying a large degree of randomness in the measured cross-correlation coefficients. Further, we find that the distribution of eigenvector components for the eigenvectors corresponding to the eigenvalues outside the RMT bound display systematic deviations from the RMT prediction. In addition, we find that these ``deviating eigenvectors'' are stable in time. We analyze the components of the deviating eigenvectors and find that the largest eigenvalue corresponds to an influence common to all stocks. Our analysis of the remaining deviating eigenvectors shows distinct groups, whose identities correspond to conventionally identified business sectors. Finally, we discuss applications to the construction of portfolios of stocks that have a stable ratio of risk to return.

A source-synchronous filter for uncorrelated receiver traces from a swept-frequency seismic source

DOE PAGES

Lord, Neal; Wang, Herbert; Fratta, Dante

2016-09-01

We have developed a novel algorithm to reduce noise in signals obtained from swept-frequency sources by removing out-of-band external noise sources and distortion caused from unwanted harmonics. The algorithm is designed to condition nonstationary signals for which traditional frequency-domain methods for removing noise have been less effective. The source synchronous filter (SSF) is a time-varying narrow band filter, which is synchronized with the frequency of the source signal at all times. Because the bandwidth of the filter needs to account for the source-to-receiver propagation delay and the sweep rate, SSF works best with slow sweep rates and moveout-adjusted waveforms tomore » compensate for source-receiver delays. The SSF algorithm was applied to data collected during a field test at the University of California Santa Barbara’s Garner Valley downhole array site in Southern California. At the site, a 45 kN shaker was mounted on top of a one-story structure and swept from 0 to 10 Hz and back over 60 s (producing useful seismic waves greater than 1.6 Hz). The seismic data were captured with small accelerometer and geophone arrays and with a distributed acoustic sensing array, which is a fiber-optic-based technique for the monitoring of elastic waves. The result of the application of SSF on the field data is a set of undistorted and uncorrelated traces that can be used in different applications, such as measuring phase velocities of surface waves or applying convolution operations with the encoder source function to obtain traveltimes. Lastly, the results from the SSF were used with a visual phase alignment tool to facilitate developing dispersion curves and as a prefilter to improve the interpretation of the data.« less

Deep Space Wide Area Search Strategies

NASA Astrophysics Data System (ADS)

Capps, M.; McCafferty, J.

There is an urgent need to expand the space situational awareness (SSA) mission beyond catalog maintenance to providing near real-time indications and warnings of emerging events. While building and maintaining a catalog of space objects is essential to SSA, this does not address the threat of uncatalogued and uncorrelated deep space objects. The Air Force therefore has an interest in transformative technologies to scan the geostationary (GEO) belt for uncorrelated space objects. Traditional ground based electro-optical sensors are challenged in simultaneously detecting dim objects while covering large areas of the sky using current CCD technology. Time delayed integration (TDI) scanning has the potential to enable significantly larger coverage rates while maintaining sensitivity for detecting near-GEO objects. This paper investigates strategies of employing TDI sensing technology from a ground based electro-optical telescope, toward providing tactical indications and warnings of deep space threats. We present results of a notional wide area search TDI sensor that scans the GEO belt from three locations: Maui, New Mexico, and Diego Garcia. Deep space objects in the NASA 2030 debris catalog are propagated over multiple nights as an indicative data set to emulate notional uncatalogued near-GEO orbits which may be encountered by the TDI sensor. Multiple scan patterns are designed and simulated, to compare and contrast performance based on 1) efficiency in coverage, 2) number of objects detected, and 3) rate at which detections occur, to enable follow-up observations by other space surveillance network (SSN) sensors. A step-stare approach is also modeled using a dedicated, co-located sensor notionally similar to the Ground-Based Electro-Optical Deep Space Surveillance (GEODSS) tower. Equivalent sensitivities are assumed. This analysis quantifies the relative benefit of TDI scanning for the wide area search mission.

Correlated environmental corrections in TOPEX/POSEIDON, with a note on ionospheric accuracy

NASA Technical Reports Server (NTRS)

Zlotnicki, V.

1994-01-01

Estimates of the effectiveness of an altimetric correction, and interpretation of sea level variability as a response to atmospheric forcing, both depend upon assuming that residual errors in altimetric corrections are uncorrelated among themselves and with residual sea level, or knowing the correlations. Not surprisingly, many corrections are highly correlated since they involve atmospheric properties and the ocean surface's response to them. The full corrections (including their geographically varying time mean values), show correlations between electromagnetic bias (mostly the height of wind waves) and either atmospheric pressure or water vapor of -40%, and between atmospheric pressure and water vapor of 28%. In the more commonly used collinear differences (after removal of the geographically varying time mean), atmospheric pressure and wave height show a -30% correlation, atmospheric pressure and water vapor a -10% correlation, both pressure and water vapor a 7% correlation with residual sea level, and a bit surprisingly, ionospheric electron content and wave height a 15% correlation. Only the ocean tide is totally uncorrelated with other corrections or residual sea level. The effectiveness of three ionospheric corrections (TOPEX dual-frequency, a smoothed version of the TOPEX dual-frequency, and Doppler orbitography and radiopositioning integrated by satellite (DORIS) is also evaluated in terms of their reduction in variance of residual sea level. Smooth (90-200 km along-track) versions of the dual-frequency altimeter ionosphere perform best both globally and within 20 deg in latitude from the equator. The noise variance in the 1/s TOPEX inospheric samples is approximately (11 mm) squared, about the same as noise in the DORIS-based correction; however, the latter has its error over scales of order 10(exp 3) km. Within 20 deg of the equator, the DORIS-based correction adds (14 mm) squared to the residual sea level variance.

A source-synchronous filter for uncorrelated receiver traces from a swept-frequency seismic source

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

Lord, Neal; Wang, Herbert; Fratta, Dante

We have developed a novel algorithm to reduce noise in signals obtained from swept-frequency sources by removing out-of-band external noise sources and distortion caused from unwanted harmonics. The algorithm is designed to condition nonstationary signals for which traditional frequency-domain methods for removing noise have been less effective. The source synchronous filter (SSF) is a time-varying narrow band filter, which is synchronized with the frequency of the source signal at all times. Because the bandwidth of the filter needs to account for the source-to-receiver propagation delay and the sweep rate, SSF works best with slow sweep rates and moveout-adjusted waveforms tomore » compensate for source-receiver delays. The SSF algorithm was applied to data collected during a field test at the University of California Santa Barbara’s Garner Valley downhole array site in Southern California. At the site, a 45 kN shaker was mounted on top of a one-story structure and swept from 0 to 10 Hz and back over 60 s (producing useful seismic waves greater than 1.6 Hz). The seismic data were captured with small accelerometer and geophone arrays and with a distributed acoustic sensing array, which is a fiber-optic-based technique for the monitoring of elastic waves. The result of the application of SSF on the field data is a set of undistorted and uncorrelated traces that can be used in different applications, such as measuring phase velocities of surface waves or applying convolution operations with the encoder source function to obtain traveltimes. Lastly, the results from the SSF were used with a visual phase alignment tool to facilitate developing dispersion curves and as a prefilter to improve the interpretation of the data.« less

Fluoride abundance and controls in fresh groundwater in Quaternary deposits and bedrock fractures in an area with fluorine-rich granitoid rocks.

PubMed

Berger, Tobias; Mathurin, Frédéric A; Drake, Henrik; Åström, Mats E

2016-11-01

This study focuses on fluoride (F(-)) concentrations in groundwater in an area in northern Europe (Laxemar, southeast Sweden) where high F(-) concentrations have previously been found in surface waters such as streams and quarries. Fluoride concentrations were determined over time in groundwater in the Quaternary deposits ("regolith groundwater"), and with different sampling techniques from just beneath the ground surface to nearly -700m in the bedrock (fracture) groundwater. A number of potential controls of dissolved F(-) were studied, including geological variables, mineralogy, mineral chemistry and hydrology. In the regolith groundwater the F(-) concentrations (0.3-4.2mg/L) were relatively stable over time at each sampling site but varied widely among the sampling sites. In these groundwaters, the F(-) concentrations were uncorrelated with sample (filter) depth and the water table in meters above sea level (masl), with the thicknesses of the groundwater column and the regolith, and with the distribution of soil types at the sampling sites. Fluoride concentrations were, however, correlated with the anticipated spatial distribution of erosional material (till) derived from a F-rich circular granite intrusion. Abundant release of F(-) from such material is thus suggested, primarily via dissolution of fluorite and weathering of biotite. In the fresh fracture groundwater, the F(-) concentrations (1.2-7.4mg/L) were generally higher than in the regolith groundwater, and were uncorrelated with depth and with location relative to the granite intrusion. Two mechanisms explaining the overall high F(-) levels in the fracture groundwater were addressed. First, weathering/dissolution of fluorite, bastnäsite and apophyllite, which are secondary minerals formed in the fractures during past hydrothermal events, and biotite which is a primary mineral exposed on fracture walls. Second, long water-residence times, favoring water-rock interaction and build-up of high dissolved F(-) concentrations. The findings are relevant in contexts of extraction of groundwater for drinking-water purposes. Copyright © 2016 Elsevier B.V. All rights reserved.

Separation system suitability (3S): a new criterion of chromatogram classification in HPLC based on cross-evaluation of separation capacity/peak symmetry and its application to complex mixtures of anthraquinones.

PubMed

Nowik, Witold; Héron, Sylvie; Bonose, Myriam; Tchapla, Alain

2013-10-07

A comparison of chromatograms obtained in a series of separation conditions for a given complex mixture may be done with a series of chromatographic descriptors. In this study, we used two descriptors: the number of critical pairs and symmetry of peaks, further rescaled and converted to the corresponding critical pairs' coefficient (CPc) and symmetry coefficient (Sc). Considering the difficulty of appreciating global separation quality using CPc and Sc criteria separately, as their respective values are usually uncorrelated, a double-criteria cross-evaluation system was required. For that purpose we tested the commonly used multi-criteria decision-making method - Derringer's desirability function (D) - as well as the recently introduced sum of ranking differences (SRD). To facilitate the graphical comparison of both approaches, the desirability function (D) was used in the inverse form (Dinv). The advantages and drawbacks of both evaluation methods, especially the respective under- or over-evaluation of outliers, caused us to introduce a new ranking approach, separation system suitability (3S). The obtained suitability rankings for the three tested approaches (Dinv, SRD and 3S) are different; nevertheless, 3S appears to be the most balanced and the easiest to interpret as well. The approach developed for selection of suitable systems was applied to the problem of separation of complex mixtures through the analysis of a series of standards of anthraquinone derivatives. To judge the pertinence of this evaluation, a sample containing a number of natural anthraquinones extracted from the bark of Indian mulberry (Morinda citrifolia) was analysed. In conclusion, the proposed methodology for the cross-evaluation of the series of chromatograms using single specific descriptors (CPc and Sc) through a global composite descriptor (3S) significantly simplifies the decision that separation systems are the most suitable for the separation of complex target mixtures of compounds.

Gaussian memory in kinematic matrix theory for self-propellers.

PubMed

Nourhani, Amir; Crespi, Vincent H; Lammert, Paul E

2014-12-01

We extend the kinematic matrix ("kinematrix") formalism [Phys. Rev. E 89, 062304 (2014)], which via simple matrix algebra accesses ensemble properties of self-propellers influenced by uncorrelated noise, to treat Gaussian correlated noises. This extension brings into reach many real-world biological and biomimetic self-propellers for which inertia is significant. Applying the formalism, we analyze in detail ensemble behaviors of a 2D self-propeller with velocity fluctuations and orientation evolution driven by an Ornstein-Uhlenbeck process. On the basis of exact results, a variety of dynamical regimes determined by the inertial, speed-fluctuation, orientational diffusion, and emergent disorientation time scales are delineated and discussed.

Nonlinear dynamics of the cellular-automaton ``game of Life''

NASA Astrophysics Data System (ADS)

Garcia, J. B. C.; Gomes, M. A. F.; Jyh, T. I.; Ren, T. I.; Sales, T. R. M.

1993-11-01

A statistical analysis of the ``game of Life'' due to Conway [Berlekamp, Conway, and Guy, Winning Ways for Your Mathematical Plays (Academic, New York, 1982), Vol. 2] is reported. The results are based on extensive computer simulations starting with uncorrelated distributions of live sites at t=0. The number n(s,t) of clusters of s live sites at time t, the mean cluster size s¯(t), and the diversity of sizes among other statistical functions are obtained. The dependence of the statistical functions with the initial density of live sites is examined. Several scaling relations as well as static and dynamic critical exponents are found.

Variability of the Tropical Ocean Surface Temperatures at Decadal-Multidecadal Timescales. Part I: The Atlantic Ocean.

NASA Astrophysics Data System (ADS)

Mehta, Vikram M.

1998-09-01

Gridded time series from the Global Ocean Surface Temperature Atlas were analyzed with a variety of techniques to identify spatial structures and oscillation periods of the tropical Atlantic sea surface temperature (SST) variations at decadal timescales, and to develop physical interpretations of statistical patterns of decadal SST variations. Each time series was 110 yr (1882-1991) long. The tropical Atlantic SST variations were compared with decadal variations in a 74-yr-long (1912-85) north Nordeste Brazil rainfall time series and a 106-yr-long (1886-1991) tropical Atlantic cyclone activity index time series. The tropical Atlantic SST variations were also compared with decadal variations in the extratropical Atlantic SST.Multiyear to multidecadal variations in the cross-equatorial dipole pattern identified as a dominant empirical pattern of the tropical Atlantic SST variations in earlier and present studies are shown to be variations in the approximately north-south gradient of SST anomalies. It is also shown that there was no dynamical-thermodynamical, dipole mode of SST variations during the analysis period. There was a distinct decadal timescale (12-13 yr) of SST variations in the tropical South Atlantic, whereas no distinct decadal timescale was found in the tropical North Atlantic SST variations. Approximately 80% of the coherent decadal variance in the cross-equatorial SST gradient was `explained' by coherent decadal oscillations in the tropical South Atlantic SSTs. There were three, possibly physical, modes of decadal variations in the tropical Atlantic SSTs during the analysis period. In the more energetic mode of the North Atlantic decadal SST variations, anomalies traveled into the tropical North Atlantic from the extratropical North Atlantic along the eastern boundary of the basin. The anomalies strengthened and resided in the tropical North Atlantic for several years, then frequently traveled northward into the mid-high-latitude North Atlantic along the western boundary of the basin, and completed a clockwise rotation around the North Atlantic basin. In the less energetic North Atlantic decadal mode, SST anomalies originated in the tropical-subtropical North Atlantic near the African coast, and traveled northwestward and southward. In the South Atlantic decadal SST mode, anomalies either developed in situ or traveled into the tropical South Atlantic from the subtropical South Atlantic along the eastern boundary of the basin. The anomalies strengthened and resided in the tropical South Atlantic for several years, then frequently traveled southward into the subtropical South Atlantic along the western boundary of the basin, and completed a counterclockwise rotation around the South Atlantic basin. These decadal modes were not a permanent feature of the tropical Atlantic SST variations. The tropical North and South Atlantic SST anomalies frequently extended across the equator. Uncorrelated alignments of decadal SST anomalies having opposite signs on two sides of the equator occasionally created the apperance of a dipole.Independent analyses of the north Nordeste Brazil rainfall showed physical consistency and high coherence with the cross-equatorial SST gradient oscillations at 12-13-yr period. The tropical Atlantic cyclone index showed physical consistency but moderate coherence with the tropical North Atlantic decadal SST variations. The quasi-regularity of the 12-13-yr oscillations in the cross-equatorial SST gradient may provide an opportunity for long lead-time, skillful predictions of climate anomalies in the tropical Atlantic sector.

Phase noise characterization of a QD-based diode laser frequency comb.

PubMed

Vedala, Govind; Al-Qadi, Mustafa; O'Sullivan, Maurice; Cartledge, John; Hui, Rongqing

2017-07-10

We measure, simultaneously, the phases of a large set of comb lines from a passively mode locked, InAs/InP, quantum dot laser frequency comb (QDLFC) by comparing the lines to a stable comb reference using multi-heterodyne coherent detection. Simultaneity permits the separation of differential and common mode phase noise and a straightforward determination of the wavelength corresponding to the minimum width of the comb line. We find that the common mode and differential phases are uncorrelated, and measure for the first time for a QDLFC that the intrinsic differential-mode phase (IDMP) between adjacent subcarriers is substantially the same for all subcarrier pairs. The latter observation supports an interpretation of 4.4ps as the standard deviation of IDMP on a 200µs time interval for this laser.

Spread of epidemic disease on networks

NASA Astrophysics Data System (ADS)

Newman, M. E.

2002-07-01

The study of social networks, and in particular the spread of disease on networks, has attracted considerable recent attention in the physics community. In this paper, we show that a large class of standard epidemiological models, the so-called susceptible/infective/removed (SIR) models can be solved exactly on a wide variety of networks. In addition to the standard but unrealistic case of fixed infectiveness time and fixed and uncorrelated probability of transmission between all pairs of individuals, we solve cases in which times and probabilities are nonuniform and correlated. We also consider one simple case of an epidemic in a structured population, that of a sexually transmitted disease in a population divided into men and women. We confirm the correctness of our exact solutions with numerical simulations of SIR epidemics on networks.

Energy correlations of photon pairs generated by a silicon microring resonator probed by Stimulated Four Wave Mixing.

PubMed

Grassani, Davide; Simbula, Angelica; Pirotta, Stefano; Galli, Matteo; Menotti, Matteo; Harris, Nicholas C; Baehr-Jones, Tom; Hochberg, Michael; Galland, Christophe; Liscidini, Marco; Bajoni, Daniele

2016-04-01

Compact silicon integrated devices, such as micro-ring resonators, have recently been demonstrated as efficient sources of quantum correlated photon pairs. The mass production of integrated devices demands the implementation of fast and reliable techniques to monitor the device performances. In the case of time-energy correlations, this is particularly challenging, as it requires high spectral resolution that is not currently achievable in coincidence measurements. Here we reconstruct the joint spectral density of photons pairs generated by spontaneous four-wave mixing in a silicon ring resonator by studying the corresponding stimulated process, namely stimulated four wave mixing. We show that this approach, featuring high spectral resolution and short measurement times, allows one to discriminate between nearly-uncorrelated and highly-correlated photon pairs.

Revisiting the Role of Bad News in Maintaining Human Observing Behavior

PubMed Central

Fantino, Edmund; Silberberg, Alan

2010-01-01

Results from studies of observing responses have suggested that stimuli maintain observing owing to their special relationship to primary reinforcement (the conditioned-reinforcement hypothesis), and not because they predict the availability and nonavailability of reinforcement (the information hypothesis). The present article first reviews a study that challenges that conclusion and then reports a series of five brief experiments that provide further support for the conditioned-reinforcement view. In Experiments 1 through 3, participants preferred occasional good news (a stimulus correlated with reinforcement) or no news (a stimulus uncorrelated with reinforcement) to occasional bad news (a stimulus negatively correlated with reinforcement). In Experiment 4 bad news was preferred to no news when the absence of stimulus change following a response to the bad-news option was reliably associated with good news. When this association was weakened in Experiment 5 the results were intermediate. The results support the conclusion that information is reinforcing only when it is positive or useful. As required by the conditioned-reinforcement hypothesis, useless information does not maintain observing. PMID:20885808

A two-stage model of fracture of rocks

USGS Publications Warehouse

Kuksenko, V.; Tomilin, N.; Damaskinskaya, E.; Lockner, D.

1996-01-01

In this paper we propose a two-stage model of rock fracture. In the first stage, cracks or local regions of failure are uncorrelated occur randomly throughout the rock in response to loading of pre-existing flaws. As damage accumulates in the rock, there is a gradual increase in the probability that large clusters of closely spaced cracks or local failure sites will develop. Based on statistical arguments, a critical density of damage will occur where clusters of flaws become large enough to lead to larger-scale failure of the rock (stage two). While crack interaction and cooperative failure is expected to occur within clusters of closely spaced cracks, the initial development of clusters is predicted based on the random variation in pre-existing Saw populations. Thus the onset of the unstable second stage in the model can be computed from the generation of random, uncorrelated damage. The proposed model incorporates notions of the kinetic (and therefore time-dependent) nature of the strength of solids as well as the discrete hierarchic structure of rocks and the flaw populations that lead to damage accumulation. The advantage offered by this model is that its salient features are valid for fracture processes occurring over a wide range of scales including earthquake processes. A notion of the rank of fracture (fracture size) is introduced, and criteria are presented for both fracture nucleation and the transition of the failure process from one scale to another.

Dynamic Steering for Improved Sensor Autonomy and Catalogue Maintenance

NASA Astrophysics Data System (ADS)

Hobson, T.; Gordon, N.; Clarkson, I.; Rutten, M.; Bessell, T.

A number of international agencies endeavour to maintain catalogues of the man-made resident space objects (RSOs) currently orbiting the Earth. Such catalogues are primarily created to anticipate and avoid destructive collisions involving important space assets such as manned missions and active satellites. An agencys ability to achieve this objective is dependent on the accuracy, reliability and timeliness of the information used to update its catalogue. A primary means for gathering this information is by regularly making direct observations of the tens-of-thousands of currently detectable RSOs via networks of space surveillance sensors. But operational constraints sometimes prevent accurate and timely reacquisition of all known RSOs, which can cause them to become lost to the tracking system. Furthermore, when comprehensive acquisition of new objects does not occur, these objects, in addition to the lost RSOs, result in uncorrelated detections when next observed. Due to the rising number of space-missions and the introduction of newer, more capable space-sensors, the number of uncorrelated targets is at an all-time high. The process of differentiating uncorrelated detections caused by once-acquired now-lost RSOs from newly detected RSOs is a difficult and often labour intensive task. Current methods for overcoming this challenge focus on advancements in orbit propagation and object characterisation to improve prediction accuracy and target identification. In this paper, we describe a complementary approach that incorporates increased awareness of error and failed observations into the RSO tracking solution. Our methodology employs a technique called dynamic steering to improve the autonomy and capability of a space surveillance networks steerable sensors. By co-situating each sensor with a low-cost high-performance computer, the steerable sensor can quickly and intelligently decide how to steer itself. The sensor-system uses a dedicated parallel-processing architecture to enable it to compute a high-fidelity estimate of the targets prior state error distribution in real-time. Negative information, such as when an RSO is targeted for observation but it is not observed, is incorporated to improve the likelihood of reacquiring the target when attempting to observe the target in future. The sensor is consequently capable of improving its utility by planning each observation using a sensor steering solution that is informed by all prior attempts at observing the target. We describe the practical implementation of a single experimental sensor and offer the results of recent field trials. These trials involved reacquisition and constrained Initial Orbit Determination of RSOs, a number of months after prior observation and initial detection. Using the proposed approach, the system is capable of using targeting information that would be unusable by existing space surveillance networks. The system consequently offers a means of enhancing space surveillance for SSA via increased system capacity, a higher degree of autonomy and the ability to reacquire objects whose dynamics are insufficiently modelled to cue a conventional space surveillance system for observation and tracking.

The role of spurious correlation in the development of a komatiite alteration model

NASA Astrophysics Data System (ADS)

Butler, John C.

1986-03-01

Current procedures for assessing the degree of alteration in komatiites stress the construction of variation diagrams in which ratios of molecular proportions of the oxides are the axes of reference. For example, it has been argued that unaltered komatiites related to each other by olivine fractionation will display a linear variation with a slope of 0.5 in the space defined by [SiO2/TiO2] and [(MgO+FeO)/TiO2]. Extensive metasomatism is expected to destroy such a consistent pattern. Previous workers have tended to make use of ratios that have a common denominator. It has been known for a long time that ratios formed from uncorrelated variables will be correlated (a so-called spurious correlation) if both ratios have a common denominator. The magnitude of this spurious correlation is a function of the coefficients of variation of the measured amounts of the variables. If the denominator component has a coefficient of variation that is larger than those of the numerator components, the spurious correlation will be close to unity; that is, there will be nearly a straight-line relationship. As a demonstration, a fictitious data set has been simulated so that the means and variances of SiO2, TiO2, and (MgO + FeO) match those of an observed data set but the components themselves are uncorrelated. A plot of (SiO2/TiO2) versus [(MgO + FeO)/TiO2] of these simulated data produces a distribution of points that appears every bit as convincing an illustration of the lack of significant metasomatism as does the plot of the observed data. The assessment of the strength of linear association is a test of the observed correlation against an expected value (the null value) of zero. When a spurious correlation arises as a result of the formulation of ratios with a common denominator, zero is clearly an inappropriate choice as the null. It can be argued that the spurious correlation is, in fact, a more suitable null value. An analysis of komatiites from Gorgona Island and the Barberton suite reveals that the strong linear association could have been produced by forming ratios from uncorrelated starting chemical components. Ratios without parts in common are to be preferred in the construction of petrogenetic models.

Self-similar crack-generation effects in the fracture process in brittle materials

NASA Astrophysics Data System (ADS)

Hilarov, V. L.

1998-07-01

Using acoustic-emission data banks we have computed time and space correlation functions for the purpose of investigation of crack-propagation self-similarity during the fracture process in brittle materials. It is shown that the whole fracture process may be represented as a two-stage process. In the first stage, the crack propagation is uniform and uncorrelated in space, having a time spectral density of the white-noise type and a correlation fractal dimension approximately equal to that of 3D Euclidean space. In the second stage, this fractal dimension decreases significantly, reaching the value of 2.2-2.4, characteristic for the fracture surfaces, while the time spectral density exhibits a significant low-frequency increase becoming of 0965-0393/6/4/002/img1-noise type. The resulting fractal shows no multifractal behaviour, appearing to be a single fractal.

On retrodictions of global mantle flow with assimilated surface velocities

NASA Astrophysics Data System (ADS)

Colli, Lorenzo; Bunge, Hans-Peter; Schuberth, Bernhard S. A.

2016-04-01

Modeling past states of Earth's mantle and relating them to geologic observations such as continental-scale uplift and subsidence is an effective method for testing mantle convection models. However, mantle convection is chaotic and two identical mantle models initialized with slightly different temperature fields diverge exponentially in time until they become uncorrelated, thus limiting retrodictions (i.e., reconstructions of past states of Earth's mantle obtained using present information) to the recent past. We show with 3-D spherical mantle convection models that retrodictions of mantle flow can be extended significantly if knowledge of the surface velocity field is available. Assimilating surface velocities produces in some cases negative Lyapunov times (i.e., e-folding times), implying that even a severely perturbed initial condition may evolve toward the reference state. A history of the surface velocity field for Earth can be obtained from past plate motion reconstructions for time periods of a mantle overturn, suggesting that mantle flow can be reconstructed over comparable times.

On retrodictions of global mantle flow with assimilated surface velocities

NASA Astrophysics Data System (ADS)

Colli, Lorenzo; Bunge, Hans-Peter; Schuberth, Bernhard S. A.

2015-10-01

Modeling past states of Earth's mantle and relating them to geologic observations such as continental-scale uplift and subsidence is an effective method for testing mantle convection models. However, mantle convection is chaotic and two identical mantle models initialized with slightly different temperature fields diverge exponentially in time until they become uncorrelated, thus limiting retrodictions (i.e., reconstructions of past states of Earth's mantle obtained using present information) to the recent past. We show with 3-D spherical mantle convection models that retrodictions of mantle flow can be extended significantly if knowledge of the surface velocity field is available. Assimilating surface velocities produces in some cases negative Lyapunov times (i.e., e-folding times), implying that even a severely perturbed initial condition may evolve toward the reference state. A history of the surface velocity field for Earth can be obtained from past plate motion reconstructions for time periods of a mantle overturn, suggesting that mantle flow can be reconstructed over comparable times.

The Crab pulsar in the visible and ultraviolet with 20 microsecond effective time resolution

NASA Technical Reports Server (NTRS)

Percival, J. W.; Biggs, J. D.; Dolan, J. F.; Robinson, E. L.; Taylor, M. J.; Bless, R. C.; Elliot, J. L.; Nelson, M. J.; Ramseyer, T. F.; Van Citters, G. W.

1993-01-01

Observations of PSR 0531+21 with the High Speed Photometer on the HST in the visible in October 1991 and in the UV in January 1992 are presented. The time resolution of the instrument was 10.74 microsec; the effective time resolution of the light curves folded modulo the pulsar period was 21.5 microsec. The main pulse arrival time is the same in the UV as in the visible and radio to within the accuracy of the establishment of the spacecraft clock, +/- 1.05 ms. The peak of the main pulse is resolved in time. Corrected for reddening, the intensity spectral index of the Crab pulsar from 1680 to 7400 A is 0.11 +/- 0.13. The pulsed flux has an intensity less than 0.9 percent of the peak flux just before the onset of the main pulse. The variations in intensity of individual main and secondary pulses are uncorrelated, even within the same rotational period.

The Ising model coupled to 2d orders

NASA Astrophysics Data System (ADS)

Glaser, Lisa

2018-04-01

In this article we make first steps in coupling matter to causal set theory in the path integral. We explore the case of the Ising model coupled to the 2d discrete Einstein Hilbert action, restricted to the 2d orders. We probe the phase diagram in terms of the Wick rotation parameter β and the Ising coupling j and find that the matter and the causal sets together give rise to an interesting phase structure. The couplings give rise to five different phases. The causal sets take on random or crystalline characteristics as described in Surya (2012 Class. Quantum Grav. 29 132001) and the Ising model can be correlated or uncorrelated on the random orders and correlated, uncorrelated or anti-correlated on the crystalline orders. We find that at least one new phase transition arises, in which the Ising spins push the causal set into the crystalline phase.

Probabilistic finite elements for transient analysis in nonlinear continua

NASA Technical Reports Server (NTRS)

Liu, W. K.; Belytschko, T.; Mani, A.

1985-01-01

The probabilistic finite element method (PFEM), which is a combination of finite element methods and second-moment analysis, is formulated for linear and nonlinear continua with inhomogeneous random fields. Analogous to the discretization of the displacement field in finite element methods, the random field is also discretized. The formulation is simplified by transforming the correlated variables to a set of uncorrelated variables through an eigenvalue orthogonalization. Furthermore, it is shown that a reduced set of the uncorrelated variables is sufficient for the second-moment analysis. Based on the linear formulation of the PFEM, the method is then extended to transient analysis in nonlinear continua. The accuracy and efficiency of the method is demonstrated by application to a one-dimensional, elastic/plastic wave propagation problem. The moments calculated compare favorably with those obtained by Monte Carlo simulation. Also, the procedure is amenable to implementation in deterministic FEM based computer programs.

Shannon entropies and Fisher information of K-shell electrons of neutral atoms

NASA Astrophysics Data System (ADS)

Sekh, Golam Ali; Saha, Aparna; Talukdar, Benoy

2018-02-01

We represent the two K-shell electrons of neutral atoms by Hylleraas-type wave function which fulfils the exact behavior at the electron-electron and electron-nucleus coalescence points and, derive a simple method to construct expressions for single-particle position- and momentum-space charge densities, ρ (r) and γ (p) respectively. We make use of the results for ρ (r) and γ (p) to critically examine the effect of correlation on bare (uncorrelated) values of Shannon information entropies (S) and of Fisher information (F) for the K-shell electrons of atoms from helium to neon. Due to inter-electronic repulsion the values of the uncorrelated Shannon position-space entropies are augmented while those of the momentum-space entropies are reduced. The corresponding Fisher information are found to exhibit opposite behavior in respect of this. Attempts are made to provide some plausible explanation for the observed response of S and F to electronic correlation.

Stochastic acceleration of electrons from multiple uncorrelated plasma waves

NASA Astrophysics Data System (ADS)

Gee, David; Michel, Pierre; Wurtele, Jonathan

2017-10-01

One-dimensional theory puts a strict limit on the maximum energy attainable by an electron trapped and accelerated by an electron plasma wave (EPW). However, experimental measurements of hot electron distributions accelerated by stimulated Raman scattering (SRS) in ICF experiments typically show a thermal distribution with temperatures of the order of the kinetic energy of the resonant EPW's (Thot mvp2 , where vp is the phase velocity of the EPW's driven by SRS) and no clear cutoff at high energies. In this project, we are investigating conditions under which electrons can be stochastically accelerated by multiple uncorrelated EPW's, such as those generated by incoherent laser speckles in large laser spots like the ones used on NIF ( mm-size), and reproduce distributions similar to those observed in experiments. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract No. DE-AC52-07NA27344.

A modal separation measurement technique for broadband noise propagating inside circular ducts

NASA Technical Reports Server (NTRS)

Kerschen, E. J.; Johnston, J. P.

1981-01-01

A measurement technique which separates broadband noise propagating inside circular ducts into the acoustic duct modes is developed. The technique is also applicable to discrete frequency noise. The acoustic modes are produced by weighted combinations of the instantaneous outputs of microphones spaced around the duct circumference. The technique is compared with the cross spectral density approach presently available and found to have certain advantages, and disadvantages. Considerable simplification of both the new technique and the cross spectral density approach occurs when no correlation exists between different circumferential mode orders. The properties leading to uncorrelated modes and experimental tests which verify this condition are discussed. The modal measurement technique is applied to the case of broadband noise generated by flow through a coaxial obstruction (nozzle or orifice) in a pipe. Different circumferential mode orders are shown to be uncorrelated for this type of noise source.

Force, Torque and Stiffness: Interactions in Perceptual Discrimination

PubMed Central

Wu, Bing; Klatzky, Roberta L.; Hollis, Ralph L.

2011-01-01

Three experiments investigated whether force and torque cues interact in haptic discrimination of force, torque and stiffness, and if so, how. The statistical relation between force and torque was manipulated across four experimental conditions: Either one type of cue varied while the other was constant, or both varied so as to be positively correlated, negatively correlated, or uncorrelated. Experiment 1 showed that the subjects’ ability to discriminate force was improved by positively correlated torque but impaired with uncorrelated torque, as compared to the constant torque condition. Corresponding effects were found in Experiment 2 for the influence of force on torque discrimination. These findings indicate that force and torque are integrated in perception, rather than being processed as separate dimensions. A further experiment demonstrated facilitation of stiffness discrimination by correlated force and torque, whether the correlation was positive or negative. The findings suggest new means of augmenting haptic feedback to facilitate perception of the properties of soft objects. PMID:21359137

Impact of line edge roughness on the performance of 14-nm FinFET: Device-circuit Co-design

NASA Astrophysics Data System (ADS)

Rathore, Rituraj Singh; Rana, Ashwani K.

2018-01-01

With the evolution of sub-20 nm FinFET technology, line edge roughness (LER) has been identified as a critical problem and may result in critical device parameter variation and performance limitation in the future VLSI circuit application. In the present work, an analytical model of fin-LER has been presented, which shows the impact of correlated and uncorrelated LER on FinFET structure. Further, the influence of correlated and uncorrelated fin- LER on all electrical performance parameters is thoroughly investigated using the three-dimensional (3-D) Technology Computer Aided Design (TCAD) simulations for 14-nm technology node. Moreover, the impact of all possible fin shapes on threshold voltage (VTH), drain induced barrier lowering (DIBL), on-current (ION), and off-current (IOFF) has been compared with the well calibrated rectangular FinFET structure. In addition, the influence of all possible fin geometries on the read stability of six-transistor (6-T) Static-Random-Access-Memory (SRAM) has been investigated. The study reveals that fin-LER plays a vital role as it directly governs the electrostatics of the FinFET structure. This has been found that there is a high degree of fluctuations in all performance parameters for uncorrelated fin-LER type FinFETs as compared to correlated fin-LER with respect to rectangular FinFET structure. This paper gives physical insight of FinFET design, especially in sub-20 nm technology nodes by concluding that the impact of LER on electrical parameters are minimum for correlated LER.

Spatial and temporal dimensions of landscape fragmentation across the Brazilian Amazon.

PubMed

Rosa, Isabel M D; Gabriel, Cristina; Carreiras, Joāo M B

2017-01-01

The Brazilian Amazon in the past decades has been suffering severe landscape alteration, mainly due to anthropogenic activities, such as road building and land clearing for agriculture. Using a high-resolution time series of land cover maps (classified as mature forest, non-forest, secondary forest) spanning from 1984 through 2011, and four uncorrelated fragmentation metrics (edge density, clumpiness index, area-weighted mean patch size and shape index), we examined the temporal and spatial dynamics of forest fragmentation in three study areas across the Brazilian Amazon (Manaus, Santarém and Machadinho d'Oeste), inside and outside conservation units. Moreover, we compared the impacts on the landscape of: (1) different land uses (e.g. cattle ranching, crop production), (2) occupation processes (spontaneous vs. planned settlements) and (3) implementation of conservation units. By 2010/2011, municipalities located along the Arc of Deforestation had more than 55% of the remaining mature forest strictly confined to conservation units. Further, the planned settlement showed a higher rate of forest loss, a more persistent increase in deforested areas and a higher relative incidence of deforestation inside conservation units. Distinct agricultural activities did not lead to significantly different landscape structures; the accessibility of the municipality showed greater influence in the degree of degradation of the landscapes. Even with a high proportion of the landscapes covered by conservation units, which showed a strong inhibitory effect on forest fragmentation, we show that dynamic agriculturally driven economic activities, in municipalities with extensive road development, led to more regularly shaped, heavily fragmented landscapes, with higher densities of forest edge.

Integration of altimetric lake levels and GRACE gravimetry over Africa: Inferences for terrestrial water storage change 2003-2011

NASA Astrophysics Data System (ADS)

Moore, P.; Williams, S. D. P.

2014-12-01

Terrestrial water storage (TWS) change for 2003-2011 is estimated over Africa from GRACE gravimetric data. The signatures from change in water of the major lakes are removed by utilizing kernel functions with lake heights recovered from retracked ENVISAT satellite altimetry. In addition, the contribution of gravimetric change due to soil moisture and biomass is removed from the total GRACE signal by utilizing the GLDAS land surface model. The residual TWS time series, namely groundwater and the surface waters in rivers, wetlands, and small lakes, are investigated for trends and the seasonal cycle using linear regression. Typically, such analyses assume that the data are temporally uncorrelated but this has been shown to lead to erroneous inferences in related studies concerning the linear rate and acceleration. In this study, we utilize autocorrelation and investigate the appropriate stochastic model. The results show the proper distribution of TWS change and identify the spatial distribution of significant rates and accelerations. The effect of surface water in the major lakes is shown to contribute significantly to the trend and seasonal variation in TWS in the lake basin. Lake Volta, a managed reservoir in Ghana, is seen to have a contribution to the linear trend that is a factor of three greater than that of Lake Victoria despite having a surface area one-eighth of that of Lake Victoria. Analysis also shows the confidence levels of the deterministic trend and acceleration identifying areas where the signatures are most likely due to a physical deterministic cause and not simply stochastic variations.

SUN-LIKE MAGNETIC CYCLES IN THE RAPIDLY ROTATING YOUNG SOLAR ANALOG HD 30495

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

Egeland, Ricky; Metcalfe, Travis S.; Hall, Jeffrey C.

A growing body of evidence suggests that multiple dynamo mechanisms can drive magnetic variability on different timescales, not only in the Sun but also in other stars. Many solar activity proxies exhibit a quasi-biennial (∼2 year) variation, which is superimposed upon the dominant 11 year cycle. A well-characterized stellar sample suggests at least two different relationships between rotation period and cycle period, with some stars exhibiting long and short cycles simultaneously. Within this sample, the solar cycle periods are typical of a more rapidly rotating star, implying that the Sun might be in a transitional state or that it hasmore » an unusual evolutionary history. In this work, we present new and archival observations of dual magnetic cycles in the young solar analog HD 30495, a ∼1 Gyr old G1.5 V star with a rotation period near 11 days. This star falls squarely on the relationships established by the broader stellar sample, with short-period variations at ∼1.7 years and a long cycle of ∼12 years. We measure three individual long-period cycles and find durations ranging from 9.6 to 15.5 years. We find the short-term variability to be intermittent, but present throughout the majority of the time series, though its occurrence and amplitude are uncorrelated with the longer cycle. These essentially solar-like variations occur in a Sun-like star with more rapid rotation, though surface differential rotation measurements leave open the possibility of a solar equivalence.« less

Multiresolution analysis of the spatiotemporal variability in global radiation observed by a dense network of 99 pyranometers

NASA Astrophysics Data System (ADS)

Lakshmi Madhavan, Bomidi; Deneke, Hartwig; Witthuhn, Jonas; Macke, Andreas

2017-03-01

The time series of global radiation observed by a dense network of 99 autonomous pyranometers during the HOPE campaign around Jülich, Germany, are investigated with a multiresolution analysis based on the maximum overlap discrete wavelet transform and the Haar wavelet. For different sky conditions, typical wavelet power spectra are calculated to quantify the timescale dependence of variability in global transmittance. Distinctly higher variability is observed at all frequencies in the power spectra of global transmittance under broken-cloud conditions compared to clear, cirrus, or overcast skies. The spatial autocorrelation function including its frequency dependence is determined to quantify the degree of similarity of two time series measurements as a function of their spatial separation. Distances ranging from 100 m to 10 km are considered, and a rapid decrease of the autocorrelation function is found with increasing frequency and distance. For frequencies above 1/3 min-1 and points separated by more than 1 km, variations in transmittance become completely uncorrelated. A method is introduced to estimate the deviation between a point measurement and a spatially averaged value for a surrounding domain, which takes into account domain size and averaging period, and is used to explore the representativeness of a single pyranometer observation for its surrounding region. Two distinct mechanisms are identified, which limit the representativeness; on the one hand, spatial averaging reduces variability and thus modifies the shape of the power spectrum. On the other hand, the correlation of variations of the spatially averaged field and a point measurement decreases rapidly with increasing temporal frequency. For a grid box of 10 km × 10 km and averaging periods of 1.5-3 h, the deviation of global transmittance between a point measurement and an area-averaged value depends on the prevailing sky conditions: 2.8 (clear), 1.8 (cirrus), 1.5 (overcast), and 4.2 % (broken clouds). The solar global radiation observed at a single station is found to deviate from the spatial average by as much as 14-23 (clear), 8-26 (cirrus), 4-23 (overcast), and 31-79 W m-2 (broken clouds) from domain averages ranging from 1 km × 1 km to 10 km × 10 km in area.

Scaling properties of marathon races

NASA Astrophysics Data System (ADS)

Alvarez-Ramirez, Jose; Rodriguez, Eduardo

2006-06-01

Some regularities in popular marathon races are identified in this paper. It is found for high-performance participants (i.e., racing times in the range [2:15,3:15] h), the average velocity as a function of the marathoner's ranking behaves as a power-law, which may be suggesting the presence of critical phenomena. Elite marathoners with racing times below 2:15 h can be considered as outliers with respect to this behavior. For the main marathon pack (i.e., racing times in the range [3:00,6:00] h), the average velocity as a function of the marathoner's ranking behaves linearly. For this racing times, the interpersonal velocity, defined as the difference of velocities between consecutive runners, displays a continuum of scaling behavior ranging from uncorrelated noise for small scales to correlated 1/f-noise for large scales. It is a matter of fact that 1/f-noise is characterized by correlations extended over a wide range of scales, a clear indication of some sort of cooperative effect.

Generalized Minimum-Time Follow-up Approaches Applied to Tasking Electro-Optical Sensor Tasking

NASA Astrophysics Data System (ADS)

Murphy, T. S.; Holzinger, M. J.

This work proposes a methodology for tasking of sensors to search an area of state space for a particular object, group of objects, or class of objects. This work creates a general unified mathematical framework for analyzing reacquisition, search, scheduling, and custody operations. In particular, this work looks at searching for unknown space object(s) with prior knowledge in the form of a set, which can be defined via an uncorrelated track, region of state space, or a variety of other methods. The follow-up tasking can occur from a variable location and time, which often requires searching a large region of the sky. This work analyzes the area of a search region over time to inform a time optimal search method. Simulation work looks at analyzing search regions relative to a particular sensor, and testing a tasking algorithm to search through the region. The tasking algorithm is also validated on a reacquisition problem with a telescope system at Georgia Tech.

Anti-correlations in the degree distribution increase stimulus detection performance in noisy spiking neural networks.

PubMed

Martens, Marijn B; Houweling, Arthur R; E Tiesinga, Paul H

2017-02-01

Neuronal circuits in the rodent barrel cortex are characterized by stable low firing rates. However, recent experiments show that short spike trains elicited by electrical stimulation in single neurons can induce behavioral responses. Hence, the underlying neural networks provide stability against internal fluctuations in the firing rate, while simultaneously making the circuits sensitive to small external perturbations. Here we studied whether stability and sensitivity are affected by the connectivity structure in recurrently connected spiking networks. We found that anti-correlation between the number of afferent (in-degree) and efferent (out-degree) synaptic connections of neurons increases stability against pathological bursting, relative to networks where the degrees were either positively correlated or uncorrelated. In the stable network state, stimulation of a few cells could lead to a detectable change in the firing rate. To quantify the ability of networks to detect the stimulation, we used a receiver operating characteristic (ROC) analysis. For a given level of background noise, networks with anti-correlated degrees displayed the lowest false positive rates, and consequently had the highest stimulus detection performance. We propose that anti-correlation in the degree distribution may be a computational strategy employed by sensory cortices to increase the detectability of external stimuli. We show that networks with anti-correlated degrees can in principle be formed by applying learning rules comprised of a combination of spike-timing dependent plasticity, homeostatic plasticity and pruning to networks with uncorrelated degrees. To test our prediction we suggest a novel experimental method to estimate correlations in the degree distribution.

Low-dose 4D cardiac imaging in small animals using dual source micro-CT

NASA Astrophysics Data System (ADS)

Holbrook, M.; Clark, D. P.; Badea, C. T.

2018-01-01

Micro-CT is widely used in preclinical studies, generating substantial interest in extending its capabilities in functional imaging applications such as blood perfusion and cardiac function. However, imaging cardiac structure and function in mice is challenging due to their small size and rapid heart rate. To overcome these challenges, we propose and compare improvements on two strategies for cardiac gating in dual-source, preclinical micro-CT: fast prospective gating (PG) and uncorrelated retrospective gating (RG). These sampling strategies combined with a sophisticated iterative image reconstruction algorithm provide faster acquisitions and high image quality in low-dose 4D (i.e. 3D  +  Time) cardiac micro-CT. Fast PG is performed under continuous subject rotation which results in interleaved projection angles between cardiac phases. Thus, fast PG provides a well-sampled temporal average image for use as a prior in iterative reconstruction. Uncorrelated RG incorporates random delays during sampling to prevent correlations between heart rate and sampling rate. We have performed both simulations and animal studies to validate these new sampling protocols. Sampling times for 1000 projections using fast PG and RG were 2 and 3 min, respectively, and the total dose was 170 mGy each. Reconstructions were performed using a 4D iterative reconstruction technique based on the split Bregman method. To examine undersampling robustness, subsets of 500 and 250 projections were also used for reconstruction. Both sampling strategies in conjunction with our iterative reconstruction method are capable of resolving cardiac phases and provide high image quality. In general, for equal numbers of projections, fast PG shows fewer errors than RG and is more robust to undersampling. Our results indicate that only 1000-projection based reconstruction with fast PG satisfies a 5% error criterion in left ventricular volume estimation. These methods promise low-dose imaging with a wide range of preclinical applications in cardiac imaging.

A new interpretation and validation of variance based importance measures for models with correlated inputs

NASA Astrophysics Data System (ADS)

Hao, Wenrui; Lu, Zhenzhou; Li, Luyi

2013-05-01

In order to explore the contributions by correlated input variables to the variance of the output, a novel interpretation framework of importance measure indices is proposed for a model with correlated inputs, which includes the indices of the total correlated contribution and the total uncorrelated contribution. The proposed indices accurately describe the connotations of the contributions by the correlated input to the variance of output, and they can be viewed as the complement and correction of the interpretation about the contributions by the correlated inputs presented in "Estimation of global sensitivity indices for models with dependent variables, Computer Physics Communications, 183 (2012) 937-946". Both of them contain the independent contribution by an individual input. Taking the general form of quadratic polynomial as an illustration, the total correlated contribution and the independent contribution by an individual input are derived analytically, from which the components and their origins of both contributions of correlated input can be clarified without any ambiguity. In the special case that no square term is included in the quadratic polynomial model, the total correlated contribution by the input can be further decomposed into the variance contribution related to the correlation of the input with other inputs and the independent contribution by the input itself, and the total uncorrelated contribution can be further decomposed into the independent part by interaction between the input and others and the independent part by the input itself. Numerical examples are employed and their results demonstrate that the derived analytical expressions of the variance-based importance measure are correct, and the clarification of the correlated input contribution to model output by the analytical derivation is very important for expanding the theory and solutions of uncorrelated input to those of the correlated one.

Opposing Responses of Bird Functional Diversity to Vegetation Structural Diversity in Wet and Dry Forest.

PubMed

Sitters, Holly; York, Alan; Swan, Matthew; Christie, Fiona; Di Stefano, Julian

2016-01-01

Disturbance regimes are changing worldwide, and the consequences for ecosystem function and resilience are largely unknown. Functional diversity (FD) provides a surrogate measure of ecosystem function by capturing the range, abundance and distribution of trait values in a community. Enhanced understanding of the responses of FD to measures of vegetation structure at landscape scales is needed to guide conservation management. To address this knowledge gap, we used a whole-of-landscape sampling approach to examine relationships between bird FD, vegetation diversity and time since fire. We surveyed birds and measured vegetation at 36 landscape sampling units in dry and wet forest in southeast Australia during 2010 and 2011. Four uncorrelated indices of bird FD (richness, evenness, divergence and dispersion) were derived from six bird traits, and we investigated responses of these indices and species richness to both vertical and horizontal vegetation diversity using linear mixed models. We also considered the extent to which the mean and diversity of time since fire were related to vegetation diversity. Results showed opposing responses of FD to vegetation diversity in dry and wet forest. In dry forest, where fire is frequent, species richness and two FD indices (richness and dispersion) were positively related to vertical vegetation diversity, consistent with theory relating to environmental variation and coexistence. However, in wet forest subject to infrequent fire, the same three response variables were negatively associated with vertical diversity. We suggest that competitive dominance by species results in lower FD as vegetation diversity increases in wet forest. The responses of functional evenness were opposite to those of species richness, functional richness and dispersion in both forest types, highlighting the value of examining multiple FD metrics at management-relevant scales. The mean and diversity of time since fire were uncorrelated with vegetation diversity in wet forest, but positively correlated with vegetation diversity in dry forest. We therefore suggest that protection of older vegetation is important, but controlled application of low-severity fire in dry forest may sustain ecosystem function by enhancing different elements of FD.

Opposing Responses of Bird Functional Diversity to Vegetation Structural Diversity in Wet and Dry Forest

PubMed Central

York, Alan; Swan, Matthew; Christie, Fiona; Di Stefano, Julian

2016-01-01

Disturbance regimes are changing worldwide, and the consequences for ecosystem function and resilience are largely unknown. Functional diversity (FD) provides a surrogate measure of ecosystem function by capturing the range, abundance and distribution of trait values in a community. Enhanced understanding of the responses of FD to measures of vegetation structure at landscape scales is needed to guide conservation management. To address this knowledge gap, we used a whole-of-landscape sampling approach to examine relationships between bird FD, vegetation diversity and time since fire. We surveyed birds and measured vegetation at 36 landscape sampling units in dry and wet forest in southeast Australia during 2010 and 2011. Four uncorrelated indices of bird FD (richness, evenness, divergence and dispersion) were derived from six bird traits, and we investigated responses of these indices and species richness to both vertical and horizontal vegetation diversity using linear mixed models. We also considered the extent to which the mean and diversity of time since fire were related to vegetation diversity. Results showed opposing responses of FD to vegetation diversity in dry and wet forest. In dry forest, where fire is frequent, species richness and two FD indices (richness and dispersion) were positively related to vertical vegetation diversity, consistent with theory relating to environmental variation and coexistence. However, in wet forest subject to infrequent fire, the same three response variables were negatively associated with vertical diversity. We suggest that competitive dominance by species results in lower FD as vegetation diversity increases in wet forest. The responses of functional evenness were opposite to those of species richness, functional richness and dispersion in both forest types, highlighting the value of examining multiple FD metrics at management-relevant scales. The mean and diversity of time since fire were uncorrelated with vegetation diversity in wet forest, but positively correlated with vegetation diversity in dry forest. We therefore suggest that protection of older vegetation is important, but controlled application of low-severity fire in dry forest may sustain ecosystem function by enhancing different elements of FD. PMID:27741290

Residual Structures in Latent Growth Curve Modeling

ERIC Educational Resources Information Center

Grimm, Kevin J.; Widaman, Keith F.

2010-01-01

Several alternatives are available for specifying the residual structure in latent growth curve modeling. Two specifications involve uncorrelated residuals and represent the most commonly used residual structures. The first, building on repeated measures analysis of variance and common specifications in multilevel models, forces residual variances…

On the integration of personality assessment methods: the Rorschach and MMPI.

PubMed

Meyer, G J

1997-04-01

Despite being the most studied and used personality assessment tools, data from the Rorschach and MMPI generally disagree (Archer & Krishnamurthy, 1993a, 1993b). Independence is proposed to result from at least 3 factors: (a) the methods tap unique levels of personality, (b) personality has a complex organization, and (c) response styles generate considerable method variance that must be considered in nomothetic research. These ideas led to 5 hypotheses, each of which received support. Rorschach and MMPI response styles are uncorrelated, although response styles are quite consistent within a method family. MMPI-2 and Rorschach constructs of dysphoria, psychosis, or wariness are uncorrelated when response styles are ignored. However, robust convergent validity is evident when patients have similar response styles on each method (e.g., for dysphoria, M r = .59) and dysphoria is expressed in opposing ways on each method when response styles are discordant (i.e., M r = -.54). Data from the latter analyses were correlated with genuine clinical phenomena and implications were discussed for clinical practice and research.

Do bioclimate variables improve performance of climate envelope models?

USGS Publications Warehouse

Watling, James I.; Romañach, Stephanie S.; Bucklin, David N.; Speroterra, Carolina; Brandt, Laura A.; Pearlstine, Leonard G.; Mazzotti, Frank J.

2012-01-01

Climate envelope models are widely used to forecast potential effects of climate change on species distributions. A key issue in climate envelope modeling is the selection of predictor variables that most directly influence species. To determine whether model performance and spatial predictions were related to the selection of predictor variables, we compared models using bioclimate variables with models constructed from monthly climate data for twelve terrestrial vertebrate species in the southeastern USA using two different algorithms (random forests or generalized linear models), and two model selection techniques (using uncorrelated predictors or a subset of user-defined biologically relevant predictor variables). There were no differences in performance between models created with bioclimate or monthly variables, but one metric of model performance was significantly greater using the random forest algorithm compared with generalized linear models. Spatial predictions between maps using bioclimate and monthly variables were very consistent using the random forest algorithm with uncorrelated predictors, whereas we observed greater variability in predictions using generalized linear models.

Realizing Ultrafast Electron Pulse Self-Compression by Femtosecond Pulse Shaping Technique.

PubMed

Qi, Yingpeng; Pei, Minjie; Qi, Dalong; Yang, Yan; Jia, Tianqing; Zhang, Shian; Sun, Zhenrong

2015-10-01

Uncorrelated position and velocity distribution of the electron bunch at the photocathode from the residual energy greatly limit the transverse coherent length and the recompression ability. Here we first propose a femtosecond pulse-shaping method to realize the electron pulse self-compression in ultrafast electron diffraction system based on a point-to-point space-charge model. The positively chirped femtosecond laser pulse can correspondingly create the positively chirped electron bunch at the photocathode (such as metal-insulator heterojunction), and such a shaped electron pulse can realize the self-compression in the subsequent propagation process. The greatest advantage for our proposed scheme is that no additional components are introduced into the ultrafast electron diffraction system, which therefore does not affect the electron bunch shape. More importantly, this scheme can break the limitation that the electron pulse via postphotocathode static compression schemes is not shorter than the excitation laser pulse due to the uncorrelated position and velocity distribution of the initial electron bunch.

A Constrained Least Squares Approach to Mobile Positioning: Algorithms and Optimality

NASA Astrophysics Data System (ADS)

Cheung, KW; So, HC; Ma, W.-K.; Chan, YT

2006-12-01

The problem of locating a mobile terminal has received significant attention in the field of wireless communications. Time-of-arrival (TOA), received signal strength (RSS), time-difference-of-arrival (TDOA), and angle-of-arrival (AOA) are commonly used measurements for estimating the position of the mobile station. In this paper, we present a constrained weighted least squares (CWLS) mobile positioning approach that encompasses all the above described measurement cases. The advantages of CWLS include performance optimality and capability of extension to hybrid measurement cases (e.g., mobile positioning using TDOA and AOA measurements jointly). Assuming zero-mean uncorrelated measurement errors, we show by mean and variance analysis that all the developed CWLS location estimators achieve zero bias and the Cramér-Rao lower bound approximately when measurement error variances are small. The asymptotic optimum performance is also confirmed by simulation results.

Computational Models of Protein Kinematics and Dynamics: Beyond Simulation

PubMed Central

Gipson, Bryant; Hsu, David; Kavraki, Lydia E.; Latombe, Jean-Claude

2016-01-01

Physics-based simulation represents a powerful method for investigating the time-varying behavior of dynamic protein systems at high spatial and temporal resolution. Such simulations, however, can be prohibitively difficult or lengthy for large proteins or when probing the lower-resolution, long-timescale behaviors of proteins generally. Importantly, not all questions about a protein system require full space and time resolution to produce an informative answer. For instance, by avoiding the simulation of uncorrelated, high-frequency atomic movements, a larger, domain-level picture of protein dynamics can be revealed. The purpose of this review is to highlight the growing body of complementary work that goes beyond simulation. In particular, this review focuses on methods that address kinematics and dynamics, as well as those that address larger organizational questions and can quickly yield useful information about the long-timescale behavior of a protein. PMID:22524225

Coherent noise reduction in digital holographic microscopy by averaging multiple holograms recorded with a multimode laser.

PubMed

Pan, Feng; Yang, Lizhi; Xiao, Wen

2017-09-04

In digital holographic microscopy (DHM), it is undesirable to observe coherent noise in the reconstructed images. The sources of the noise are mainly the parasitic interference fringes caused by multiple reflections and the speckle pattern caused by the optical scattering on the object surface. Here we propose a noise reduction approach in DHM by averaging multiple holograms recorded with a multimode laser. Based on the periodicity of the temporal coherence of a multimode semiconductor laser, we acquire a series of holograms by changing the optical path length difference between the reference beam and object beam. Because of the use of low coherence light, we can remove the parasitic interference fringes caused by multiple reflections in the holograms. In addition, the coherent noise patterns change in this process due to the different optical paths. Therefore, the coherent noise can be reduced by averaging the multiple reconstructions with uncorrelated noise patterns. Several experiments have been carried out to validate the effectiveness of the proposed approach for coherent noise reduction in DHM. It is shown a remarkable improvement both in amplitude imaging quality and phase measurement accuracy.

Investigation of scale effects in the TRF determined by VLBI

NASA Astrophysics Data System (ADS)

Wahl, Daniel; Heinkelmann, Robert; Schuh, Harald

2017-04-01

The improvement of the International Terrestrial Reference Frame (ITRF) is of great significance for Earth sciences and one of the major tasks in geodesy. The translation, rotation and the scale-factor, as well as their linear rates, are solved in a 14-parameter transformation between individual frames of each space geodetic technique and the combined frame. In ITRF2008, as well as in the current release ITRF2014, the scale-factor is provided by Very Long Baseline Interferometry (VLBI) and Satellite Laser Ranging (SLR) in equal shares. Since VLBI measures extremely precise group delays that are transformed to baseline lengths by the velocity of light, a natural constant, VLBI is the most suitable method for providing the scale. The aim of the current work is to identify possible shortcomings in the VLBI scale contribution to ITRF2008. For developing recommendations for an enhanced estimation, scale effects in the Terrestrial Reference Frame (TRF) determined with VLBI are considered in detail and compared to ITRF2008. In contrast to station coordinates, where the scale is defined by a geocentric position vector, pointing from the origin of the reference frame to the station, baselines are not related to the origin. They are describing the absolute scale independently from the datum. The more accurate a baseline length, and consequently the scale, is estimated by VLBI, the better the scale contribution to the ITRF. Considering time series of baseline length between different stations, a non-linear periodic signal can clearly be recognized, caused by seasonal effects at observation sites. Modeling these seasonal effects and subtracting them from the original data enhances the repeatability of single baselines significantly. Other effects influencing the scale strongly, are jumps in the time series of baseline length, mainly evoked by major earthquakes. Co- and post-seismic effects can be identified in the data, having a non-linear character likewise. Modeling the non-linear motion or completely excluding affected stations is another important step for an improved scale determination. In addition to the investigation of single baseline repeatabilities also the spatial transformation, which is performed for determining parameters of the ITRF2008, are considered. Since the reliability of the resulting transformation parameters is higher the more identical points are used in the transformation, an approach where all possible stations are used as control points is comprehensible. Experiments that examine the scale-factor and its spatial behavior between control points in ITRF2008 and coordinates determined by VLBI only showed that the network geometry has a large influence on the outcome as well. Introducing an unequally distributed network for the datum configuration, the correlations between translation parameters and the scale-factor can become remarkably high. Only a homogeneous spatial distribution of participating stations yields a maximally uncorrelated scale-factor that can be interpreted independent from other parameters. In the current release of the ITRF, the ITRF2014, for the first time, non-linear effects in the time series of station coordinates are taken into account. The present work shows the importance and the right direction of the modification of the ITRF calculation. But also further improvements were found which lead to an enhanced scale determination.

US stock market efficiency over weekly, monthly, quarterly and yearly time scales

NASA Astrophysics Data System (ADS)

Rodriguez, E.; Aguilar-Cornejo, M.; Femat, R.; Alvarez-Ramirez, J.

2014-11-01

In financial markets, the weak form of the efficient market hypothesis implies that price returns are serially uncorrelated sequences. In other words, prices should follow a random walk behavior. Recent developments in evolutionary economic theory (Lo, 2004) have tailored the concept of adaptive market hypothesis (AMH) by proposing that market efficiency is not an all-or-none concept, but rather market efficiency is a characteristic that varies continuously over time and across markets. Within the AMH framework, this work considers the Dow Jones Index Average (DJIA) for studying the deviations from the random walk behavior over time. It is found that the market efficiency also varies over different time scales, from weeks to years. The well-known detrended fluctuation analysis was used for the characterization of the serial correlations of the return sequences. The results from the empirical showed that interday and intraday returns are more serially correlated than overnight returns. Also, some insights in the presence of business cycles (e.g., Juglar and Kuznets) are provided in terms of time variations of the scaling exponent.

Singlet-triplet splittings from the virial theorem and single-particle excitation energies

NASA Astrophysics Data System (ADS)

Becke, Axel D.

2018-01-01

The zeroth-order (uncorrelated) singlet-triplet energy difference in single-particle excited configurations is 2Kif, where Kif is the Coulomb self-energy of the product of the transition orbitals. Here we present a non-empirical, virial-theorem argument that the correlated singlet-triplet energy difference should be half of this, namely, Kif. This incredibly simple result gives vertical HOMO-LUMO excitation energies in small-molecule benchmarks as good as the popular TD-B3LYP time-dependent approach to excited states. For linear acenes and nonlinear polycyclic aromatic hydrocarbons, the performance is significantly better than TD-B3LYP. In addition to the virial theorem, the derivation borrows intuitive pair-density concepts from density-functional theory.

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

Esterlis, I.; Nosarzewski, B.; Huang, E. W.

The superconducting (SC) and charge-density-wave (CDW) susceptibilities of the two-dimensional Holstein model are computed using determinant quantum Monte Carlo, and compared with results computed using the Migdal-Eliashberg (ME) approach. We access temperatures as low as 25 times less than the Fermi energy, E F, which are still above the SC transition. We find that the SC susceptibility at low T agrees quantitatively with the ME theory up to a dimensionless electron-phonon coupling λ 0 ≈ 0.4 but deviates dramatically for larger λ 0. We find that for large λ 0 and small phonon frequency ω 0 << E F CDWmore » ordering is favored and the preferred CDW ordering vector is uncorrelated with any obvious feature of the Fermi surface.« less

Spin-Orbit-Coupled Interferometry with Ring-Trapped Bose-Einstein Condensates

NASA Astrophysics Data System (ADS)

Helm, J. L.; Billam, T. P.; Rakonjac, A.; Cornish, S. L.; Gardiner, S. A.

2018-02-01

We propose a method of atom interferometry using a spinor Bose-Einstein condensate with a time-varying magnetic field acting as a coherent beam splitter. Our protocol creates long-lived superpositional counterflow states, which are of fundamental interest and can be made sensitive to both the Sagnac effect and magnetic fields on the sub-μ G scale. We split a ring-trapped condensate, initially in the mf=0 hyperfine state, into superpositions of internal mf=±1 states and condensate superflow, which are spin-orbit coupled. After interrogation, the relative phase accumulation can be inferred from a population transfer to the mf=±1 states. The counterflow generation protocol is adiabatically deterministic and does not rely on coupling to additional optical fields or mechanical stirring techniques. Our protocol can maximize the classical Fisher information for any rotation, magnetic field, or interrogation time and so has the maximum sensitivity available to uncorrelated particles. Precision can increase with the interrogation time and so is limited only by the lifetime of the condensate.

Characteristics of bilateral hand function in individuals with unilateral dystonia due to perinatal stroke: sensory and motor aspects.

PubMed

de Campos, Ana Carolina; Kukke, Sahana N; Hallett, Mark; Alter, Katharine E; Damiano, Diane L

2014-05-01

The authors assessed bilateral motor and sensory function in individuals with upper limb dystonia due to unilateral perinatal stroke and explored interrelationships of motor function and sensory ability. Reach kinematics and tactile sensation were measured in 7 participants with dystonia and 9 healthy volunteers. The dystonia group had poorer motor (hold time, reach time, shoulder/elbow correlation) and sensory (spatial discrimination, stereognosis) outcomes than the control group on the nondominant side. On the dominant side, only sensation (spatial discrimination, stereognosis) was poorer in the dystonia group compared with the control group. In the dystonia group, although sensory and motor outcomes were uncorrelated, dystonia severity was related to poorer stereognosis, longer hold and reach times, and decreased shoulder/elbow coordination. Findings of bilateral sensory deficits in dystonia can be explained by neural reorganization. Visual compensation for somatosensory changes in the nonstroke hemisphere may explain the lack of bilateral impairments in reaching.

Characteristics of bilateral hand function in individuals with unilateral dystonia due to perinatal stroke: sensory and motor aspects

PubMed Central

de Campos, Ana Carolina; Kukke, Sahana N.; Hallett, Mark; Alter, Katharine E.; Damiano, Diane L.

2014-01-01

We assessed bilateral motor and sensory function in individuals with upper limb dystonia due to unilateral perinatal stroke and explored interrelationships of motor function and sensory ability. Reach kinematics and tactile sensation were measured in seven participants with dystonia and nine healthy volunteers. The dystonia group had poorer motor (hold time, reach time, shoulder/elbow correlation) and sensory (spatial discrimination, stereognosis) outcomes than the control group on the non-dominant side. On the dominant side, only sensation (spatial discrimination, stereognosis) was poorer in the dystonia group compared to the control group. In the dystonia group, although sensory and motor outcomes were uncorrelated, dystonia severity was related to poorer stereognosis, longer hold and reach times, and decreased shoulder/elbow coordination. Findings of bilateral sensory deficits in dystonia may be explained by neural reorganization. Visual compensation for somatosensory changes in the non-stroke hemisphere may explain the lack of bilateral impairments in reaching. PMID:24396131

Epidemic spreading on activity-driven networks with attractiveness.

PubMed

Pozzana, Iacopo; Sun, Kaiyuan; Perra, Nicola

2017-10-01

We study SIS epidemic spreading processes unfolding on a recent generalization of the activity-driven modeling framework. In this model of time-varying networks, each node is described by two variables: activity and attractiveness. The first describes the propensity to form connections, while the second defines the propensity to attract them. We derive analytically the epidemic threshold considering the time scale driving the evolution of contacts and the contagion as comparable. The solutions are general and hold for any joint distribution of activity and attractiveness. The theoretical picture is confirmed via large-scale numerical simulations performed considering heterogeneous distributions and different correlations between the two variables. We find that heterogeneous distributions of attractiveness alter the contagion process. In particular, in the case of uncorrelated and positive correlations between the two variables, heterogeneous attractiveness facilitates the spreading. On the contrary, negative correlations between activity and attractiveness hamper the spreading. The results presented contribute to the understanding of the dynamical properties of time-varying networks and their effects on contagion phenomena unfolding on their fabric.

A temporal and spatial analysis of ground-water levels for effective monitoring in Huron County, Michigan

USGS Publications Warehouse

Holtschlag, David J.; Sweat, M.J.

1999-01-01

Quarterly water-level measurements were analyzed to assess the effectiveness of a monitoring network of 26 wells in Huron County, Michigan. Trends were identified as constant levels and autoregressive components were computed at all wells on the basis of data collected from 1993 to 1997, using structural time series analysis. Fixed seasonal components were identified at 22 wells and outliers were identified at 23 wells. The 95- percent confidence intervals were forecast for water-levels during the first and second quarters of 1998. Intervals in the first quarter were consistent with 92.3 percent of the measured values. In the second quarter, measured values were within the forecast intervals only 65.4 percent of the time. Unusually low precipitation during the second quarter is thought to have contributed to the reduced reliability of the second-quarter forecasts. Spatial interrelations among wells were investigated on the basis of the autoregressive components, which were filtered to create a set of innovation sequences that were temporally uncorrelated. The empirical covariance among the innovation sequences indicated both positive and negative spatial interrelations. The negative covariance components are considered to be physically implausible and to have resulted from random sampling error. Graphical modeling, a form of multivariate analysis, was used to model the covariance structure. Results indicate that only 29 of the 325 possible partial correlations among the water-level innovations were statistically significant. The model covariance matrix, corresponding to the model partial correlation structure, contained only positive elements. This model covariance was sequentially partitioned to compute a set of partial covariance matrices that were used to rank the effectiveness of the 26 monitoring wells from greatest to least. Results, for example, indicate that about 50 percent of the uncertainty of the water-level innovations currently monitored by the 26- well network could be described by the 6 most effective wells.

MIX: a computer program to evaluate interaction between chemicals

Treesearch

Jacqueline L. Robertson; Kimberly C. Smith

1989-01-01

A computer program, MIX, was designed to identify pairs of chemicals whose interaction results in a response that departs significantly from the model predicated on the assumption of independent, uncorrelated joint action. This report describes the MIX program, its statistical basis, and instructions for its use.

Impact of aggregation on scaling behavior of Internet backbone traffic

NASA Astrophysics Data System (ADS)

Zhang, Zhi-Li; Ribeiro, Vinay J.; Moon, Sue B.; Diot, Christophe

2002-07-01

We study the impact of aggregation on the scaling behavior of Internet backbone tra ffic, based on traces collected from OC3 and OC12 links in a tier-1 ISP. We make two striking observations regarding the sub-second small time scaling behaviors of Internet backbone traffic: 1) for a majority of these traces, the Hurst parameters at small time scales (1ms - 100ms) are fairly close to 0.5. Hence the traffic at these time scales are nearly uncorrelated; 2) the scaling behaviors at small time scales are link-dependent, and stay fairly invariant over changing utilization and time. To understand the scaling behavior of network traffic, we develop analytical models and employ them to demonstrate how traffic composition -- aggregation of traffic with different characteristics -- affects the small-time scalings of network traffic. The degree of aggregation and burst correlation structure are two major factors in traffic composition. Our trace-based data analysis confirms this. Furthermore, we discover that traffic composition on a backbone link stays fairly consistent over time and changing utilization, which we believe is the cause for the invariant small-time scalings we observe in the traces.

Uncovering the Internal Structure of the Indian Financial Market: Large Cross-correlation Behavior in the NSE

NASA Astrophysics Data System (ADS)

Sinha, Sitabhra; Pan, Raj Kumar

The cross-correlations between price fluctuations of 201 frequently traded stocks in the National Stock Exchange (NSE) of India are analyzed in this paper. We use daily closing prices for the period 1996-2006, which coincides with the period of rapid transformation of the market following liberalization. The eigenvalue distribution of the cross-correlation matrix, C, of NSE is found to be similar to that of developed markets, such as the New York Stock Exchange (NYSE): the majority of eigenvalues fall within the bounds expected for a random matrix constructed from mutually uncorrelated time series. Of the few largest eigenvalues that deviate from the bulk, the largest is identified with market-wide movements. The intermediate eigenvalues that occur between the largest and the bulk have been associated in NYSE with specific business sectors with strong intra-group interactions. However, in the Indian market, these deviating eigenvalues are comparatively very few and lie much closer to the bulk. We propose that this is because of the relative lack of distinct sector identity in the market, with the movement of stocks dominantly influenced by the overall market trend. This is shown by explicit construction of the interaction network in the market, first by generating the minimum spanning tree from the unfiltered correlation matrix, and later, using an improved method of generating the graph after filtering out the market mode and random effects from the data. Both methods show, compared to developed markets, the relative absence of clusters of co-moving stocks that belong to the same business sector. This is consistent with the general belief that emerging markets tend to be more correlated than developed markets.

Overcoming equifinality: Leveraging long time series for stream metabolism estimation

USGS Publications Warehouse

Appling, Alison; Hall, Robert O.; Yackulic, Charles B.; Arroita, Maite

2018-01-01

The foundational ecosystem processes of gross primary production (GPP) and ecosystem respiration (ER) cannot be measured directly but can be modeled in aquatic ecosystems from subdaily patterns of oxygen (O2) concentrations. Because rivers and streams constantly exchange O2 with the atmosphere, models must either use empirical estimates of the gas exchange rate coefficient (K600) or solve for all three parameters (GPP, ER, and K600) simultaneously. Empirical measurements of K600 require substantial field work and can still be inaccurate. Three-parameter models have suffered from equifinality, where good fits to O2 data are achieved by many different parameter values, some unrealistic. We developed a new three-parameter, multiday model that ensures similar values for K600 among days with similar physical conditions (e.g., discharge). Our new model overcomes the equifinality problem by (1) flexibly relating K600 to discharge while permitting moderate daily deviations and (2) avoiding the oft-violated assumption that residuals in O2 predictions are uncorrelated. We implemented this hierarchical state-space model and several competitor models in an open-source R package, streamMetabolizer. We then tested the models against both simulated and field data. Our new model reduces error by as much as 70% in daily estimates of K600, GPP, and ER. Further, accuracy benefits of multiday data sets require as few as 3 days of data. This approach facilitates more accurate metabolism estimates for more streams and days, enabling researchers to better quantify carbon fluxes, compare streams by their metabolic regimes, and investigate controls on aquatic activity.

Latent stereopsis for motion in depth in strabismic amblyopia.

PubMed

Hess, Robert F; Mansouri, Behzad; Thompson, Benjamin; Gheorghiu, Elena

2009-10-01

To investigate the residual stereo function of a group of 15 patients with strabismic amblyopia, by using motion-in-depth stimuli that allow discrimination of contributions from local disparity as opposed to those from local velocity mechanisms as a function of the rate of depth change. The stereo performance (percentage correct) was measured as a function of the rate of depth change for dynamic random dot stimuli that were either temporally correlated or uncorrelated. Residual stereoscopic function was demonstrated for motion in depth based on local disparity information in 2 of the 15 observers with strabismic amblyopia. The use of a neutral-density (ND) filter in front of the fixing eye enhanced motion-in-depth performance in four subjects randomly selected from the group that originally displayed only chance performance. This finding was true across temporal rate and for correlated and uncorrelated stimuli, suggesting that it was disparity based. The opposite occurred in a group of normal subjects. In a separate experiment, the hypothesis was that the beneficial effect of the ND filter is due to its contrast and/or mean luminance-reducing effects rather than any interocular time delay that it may introduce and that it is specific to motion-in-depth performance, as similar improvements were not found for static stereopsis. A small proportion of observers with strabismic amblyopia exhibit residual performance for motion in depth, and it is disparity based. Furthermore, some observers with strabismic amblyopia who do not display any significant stereo performance for motion in depth under normal binocular viewing may display above-chance stereo performance if the degree of interocular suppression is reduced. The authors term this phenomenon latent stereopsis.

Nonlinear Principal Components Analysis: Introduction and Application

ERIC Educational Resources Information Center

Linting, Marielle; Meulman, Jacqueline J.; Groenen, Patrick J. F.; van der Koojj, Anita J.

2007-01-01

The authors provide a didactic treatment of nonlinear (categorical) principal components analysis (PCA). This method is the nonlinear equivalent of standard PCA and reduces the observed variables to a number of uncorrelated principal components. The most important advantages of nonlinear over linear PCA are that it incorporates nominal and ordinal…

Insects, vegetation, and the control of laughing gulls (Larus atricilla) at Kennedy International Airport, New York

USGS Publications Warehouse

Buckley, P.A.; McCarthy, M.

1994-01-01

1. In response to a purported 'bird-strike problem' at J.F. Kennedy International Airport in New York City, we examined short (5 cm) and long (45 cm) grass heights as gull deterrents, in a randomized-block experiment. 2. Vegetative cover, numbers of adult insects and of larval beetles (suspected on-airport food of the gulls) were sampled in the six-block, 36-plot study area, as well as gut contents of adult and downy young gulls in the immediately adjacent colony in the Jamaica Bay Wildlife Refuge. 3. We found that (i) Oriental beetle larvae were the most numerous and concentrated in one experimental block; (ii) beetle larvae numbers were uncorrelated with grass height; (iii) adult beetles were also uncorrelated with grass height; (iv) laughing gulls were distributed across blocks irrespective of percentage cover; (v) within blocks, laughing gulls were selecting short grass and avoiding long grass plots; (vi) laughing gull numbers were positively associated with numbers of Oriental beetle larvae; (vii) adult laughing gulls on the airport were eating lower-nutrition food of terrestrial origin (74-83% adult beetles, mostly Oriental plus green June and ground beetles); (viii) on the other hand, gull chicks in the adjacent breeding colony were being fed more easily digested, higher-protein food of marine origin (86-88% fishes, crustacea and molluscs); (ix) laughing gulls on the airport were taking their adult beetles only in short-grass plots, ignoring large numbers in adjacent long grass; (x) during the summer, on-airport gulls shifted from performing largely maintenance activities on pavement to feeding actively for beetles on newly mown short grass, the change coinciding with adult beetle emergence; (xi) standing water on the airport attracted significantly more gulls than dry areas all summer long. 4. We recommend a series of ecologically compatible, but aggressive habitat management actions for controlling laughing gulls on Kennedy Airport by rendering the airport unattractive to them, notably by implementing an airport-wide programme of long-grass encouragement, draining standing water and improving runoff in water-collecting areas, and controlling beetles. 5. We conclude by outlining the necessity for airport-wide bird, vegetation and habitat management programmes fully integrated into airport operation and planning activities.

Speech Intelligibility in Various Noise Conditions with the Nucleus® 5 CP810 Sound Processor.

PubMed

Dillier, Norbert; Lai, Wai Kong

2015-06-11

The Nucleus(®) 5 System Sound Processor (CP810, Cochlear™, Macquarie University, NSW, Australia) contains two omnidirectional microphones. They can be configured as a fixed directional microphone combination (called Zoom) or as an adaptive beamformer (called Beam), which adjusts the directivity continuously to maximally reduce the interfering noise. Initial evaluation studies with the CP810 had compared performance and usability of the new processor in comparison with the Freedom™ Sound Processor (Cochlear™) for speech in quiet and noise for a subset of the processing options. This study compares the two processing options suggested to be used in noisy environments, Zoom and Beam, for various sound field conditions using a standardized speech in noise matrix test (Oldenburg sentences test). Nine German-speaking subjects who previously had been using the Freedom speech processor and subsequently were upgraded to the CP810 device participated in this series of additional evaluation tests. The speech reception threshold (SRT for 50% speech intelligibility in noise) was determined using sentences presented via loudspeaker at 65 dB SPL in front of the listener and noise presented either via the same loudspeaker (S0N0) or at 90 degrees at either the ear with the sound processor (S0NCI+) or the opposite unaided ear (S0NCI-). The fourth noise condition consisted of three uncorrelated noise sources placed at 90, 180 and 270 degrees. The noise level was adjusted through an adaptive procedure to yield a signal to noise ratio where 50% of the words in the sentences were correctly understood. In spatially separated speech and noise conditions both Zoom and Beam could improve the SRT significantly. For single noise sources, either ipsilateral or contralateral to the cochlear implant sound processor, average improvements with Beam of 12.9 and 7.9 dB in SRT were found. The average SRT of -8 dB for Beam in the diffuse noise condition (uncorrelated noise from both sides and back) is truly remarkable and comparable to the performance of normal hearing listeners in the same test environment. The static directivity (Zoom) option in the diffuse noise condition still provides a significant benefit of 5.9 dB in comparison with the standard omnidirectional microphone setting. These results indicate that CI recipients may improve their speech recognition in noisy environments significantly using these directional microphone-processing options.

A test of multiple correlation temporal window characteristic of non-Markov processes

NASA Astrophysics Data System (ADS)

Arecchi, F. T.; Farini, A.; Megna, N.

2016-03-01

We introduce a sensitive test of memory effects in successive events. The test consists of a combination K of binary correlations at successive times. K decays monotonically from K = 1 for uncorrelated events as a Markov process. For a monotonic memory fading, K<1 always. Here we report evidence of a K>1 temporal window in cognitive tasks consisting of the visual identification of the front face of the Necker cube after a previous presentation of the same. We speculate that memory effects provide a temporal window with K>1 and this experiment could be a possible first step towards a better comprehension of this phenomenon. The K>1 behaviour is maximal at an inter-measurement time τ around 2s with inter-subject differences. The K>1 persists over a time window of 1s around τ; outside this window the K<1 behaviour is recovered. The universal occurrence of a K>1 window in pairs of successive perceptions suggests that, at variance with single visual stimuli eliciting a suitable response, a pair of stimuli shortly separated in time displays mutual correlations.

Input-output relationship in social communications characterized by spike train analysis

NASA Astrophysics Data System (ADS)

Aoki, Takaaki; Takaguchi, Taro; Kobayashi, Ryota; Lambiotte, Renaud

2016-10-01

We study the dynamical properties of human communication through different channels, i.e., short messages, phone calls, and emails, adopting techniques from neuronal spike train analysis in order to characterize the temporal fluctuations of successive interevent times. We first measure the so-called local variation (LV) of incoming and outgoing event sequences of users and find that these in- and out-LV values are positively correlated for short messages and uncorrelated for phone calls and emails. Second, we analyze the response-time distribution after receiving a message to focus on the input-output relationship in each of these channels. We find that the time scales and amplitudes of response differ between the three channels. To understand the effects of the response-time distribution on the correlations between the LV values, we develop a point process model whose activity rate is modulated by incoming and outgoing events. Numerical simulations of the model indicate that a quick response to incoming events and a refractory effect after outgoing events are key factors to reproduce the positive LV correlations.

Skin Cancer, Irradiation, and Sunspots: The Solar Cycle Effect

PubMed Central

Zurbenko, Igor

2014-01-01

Skin cancer is diagnosed in more than 2 million individuals annually in the United States. It is strongly associated with ultraviolet exposure, with melanoma risk doubling after five or more sunburns. Solar activity, characterized by features such as irradiance and sunspots, undergoes an 11-year solar cycle. This fingerprint frequency accounts for relatively small variation on Earth when compared to other uncorrelated time scales such as daily and seasonal cycles. Kolmogorov-Zurbenko filters, applied to the solar cycle and skin cancer data, separate the components of different time scales to detect weaker long term signals and investigate the relationships between long term trends. Analyses of crosscorrelations reveal epidemiologically consistent latencies between variables which can then be used for regression analysis to calculate a coefficient of influence. This method reveals that strong numerical associations, with correlations >0.5, exist between these small but distinct long term trends in the solar cycle and skin cancer. This improves modeling skin cancer trends on long time scales despite the stronger variation in other time scales and the destructive presence of noise. PMID:25126567

High-Speed PLIF Imaging of Hypersonic Transition over Discrete Cylindrical Roughness

NASA Technical Reports Server (NTRS)

Danehy, P. M.; Ivey, C. B.; Inman, J. A.; Bathel, B. F.; Jones, S. B.; McCrea, A. C.; Jiang, N.; Webster, M.; Lempert, W.; Miller, J.;

Outburst OH maser activity in the envelopes of S Persei and VX Sagittarii *

NASA Astrophysics Data System (ADS)

Szymczak, M.; Wolak, P.; Gérard, E.; Richards, A. M. S.

2010-12-01

Context. OH masers from the envelopes of M-type supergiants show a significant degree of polarization, implying magnetic fields of a few mG. Nothing is known about the temporal characteristics of the magnetic fields or how such changes may affect stellar mass loss. Aims: We therefore observed two supergiant stars in order to quantify the long-term polarization behaviour of the maser emission. Methods: Full-polarization spectra at 1612 and 1667 MHz were obtained with the Nançay radio telescope at intervals over periods of 4 and 6 years for S Per and VX Sgr, respectively. Results: Time series of OH maser full polarization spectra are presented. Semiregular variations of the integrated flux densities generally follow the visual light curves as expected for radiative pumping cycles. For both sources the variability indices of individual features are higher at 1667 MHz than at 1612 MHz and their extreme values occur for the blue-shifted emission. The degrees of polarization at 1667 MHz show diverse behaviours usually uncorrelated with the total flux, whereas those at 1612 MHz are commonly stable on time scales of 4-6 yr. Several outbursts of the 1667 MHz emission on time scales of 0.5-2 yr were found in both targets. The bursting features are highly polarized and show drifts in velocity. Small changes of the degrees of polarization and smooth variations of position angle of linear polarization during the bursts were observed in S Per but they are more dramatic in VX Sgr. Conclusions: The OH outbursts do not seem to have any direct link to stellar events, but seem to be localized in the wind. Appendices A and B are only available in electronic form via http://www.edpsciences.orgA complete catalogue of the data in all four Stokes parameters is only available in electronic form at CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/viz-bin/qcat?J/A+A/524/A99

Anderson Localization in Quark-Gluon Plasma

NASA Astrophysics Data System (ADS)

Kovács, Tamás G.; Pittler, Ferenc

2010-11-01

At low temperature the low end of the QCD Dirac spectrum is well described by chiral random matrix theory. In contrast, at high temperature there is no similar statistical description of the spectrum. We show that at high temperature the lowest part of the spectrum consists of a band of statistically uncorrelated eigenvalues obeying essentially Poisson statistics and the corresponding eigenvectors are extremely localized. Going up in the spectrum the spectral density rapidly increases and the eigenvectors become more and more delocalized. At the same time the spectral statistics gradually crosses over to the bulk statistics expected from the corresponding random matrix ensemble. This phenomenon is reminiscent of Anderson localization in disordered conductors. Our findings are based on staggered Dirac spectra in quenched lattice simulations with the SU(2) gauge group.

Two-photon absorption by spectrally shaped entangled photons

NASA Astrophysics Data System (ADS)

Oka, Hisaki

2018-03-01

We theoretically investigate two-photon excitation by spectrally shaped entangled photons with energy anticorrelation in terms of how the real excitation of an intermediate state affects two-photon absorption by entangled photons. Spectral holes are introduced in the entangled photons around the energy levels of an intermediate state so that two-step excitation via the real excitation of the intermediated state can be suppressed. Using a three-level atomic system as an example, we show that the spectral holes well suppress the real excitation of the intermediate state and recover two-photon absorption via a virtual state. Furthermore, for a short pulse close to a monocycle, we show that the excitation efficiency by the spectrally shaped entangled photons can be enhanced a thousand times as large as that by uncorrelated photons.

A Simple Method for Automated Equilibration Detection in Molecular Simulations.

PubMed

Chodera, John D

2016-04-12

Molecular simulations intended to compute equilibrium properties are often initiated from configurations that are highly atypical of equilibrium samples, a practice which can generate a distinct initial transient in mechanical observables computed from the simulation trajectory. Traditional practice in simulation data analysis recommends this initial portion be discarded to equilibration, but no simple, general, and automated procedure for this process exists. Here, we suggest a conceptually simple automated procedure that does not make strict assumptions about the distribution of the observable of interest in which the equilibration time is chosen to maximize the number of effectively uncorrelated samples in the production timespan used to compute equilibrium averages. We present a simple Python reference implementation of this procedure and demonstrate its utility on typical molecular simulation data.

Breakdown of the Migdal-Eliashberg theory: A determinant quantum Monte Carlo study

DOE PAGES

Esterlis, I.; Nosarzewski, B.; Huang, E. W.; ...

2018-04-02

The superconducting (SC) and charge-density-wave (CDW) susceptibilities of the two-dimensional Holstein model are computed using determinant quantum Monte Carlo, and compared with results computed using the Migdal-Eliashberg (ME) approach. We access temperatures as low as 25 times less than the Fermi energy, E F, which are still above the SC transition. We find that the SC susceptibility at low T agrees quantitatively with the ME theory up to a dimensionless electron-phonon coupling λ 0 ≈ 0.4 but deviates dramatically for larger λ 0. We find that for large λ 0 and small phonon frequency ω 0 << E F CDWmore » ordering is favored and the preferred CDW ordering vector is uncorrelated with any obvious feature of the Fermi surface.« less

A simple method for automated equilibration detection in molecular simulations

PubMed Central

Chodera, John D.

2016-01-01

Molecular simulations intended to compute equilibrium properties are often initiated from configurations that are highly atypical of equilibrium samples, a practice which can generate a distinct initial transient in mechanical observables computed from the simulation trajectory. Traditional practice in simulation data analysis recommends this initial portion be discarded to equilibration, but no simple, general, and automated procedure for this process exists. Here, we suggest a conceptually simple automated procedure that does not make strict assumptions about the distribution of the observable of interest, in which the equilibration time is chosen to maximize the number of effectively uncorrelated samples in the production timespan used to compute equilibrium averages. We present a simple Python reference implementation of this procedure, and demonstrate its utility on typical molecular simulation data. PMID:26771390

Synchrotron X-ray fluorescence analyses of stratospheric cosmic dust - New results for chondritic and low-nickel particles

NASA Technical Reports Server (NTRS)

Flynn, G. J.; Sutton, S. R.

1990-01-01

Trace element abundance determinations were performed using synchrotron X-ray fluorescence on nine particles collected from the stratosphere and classified as cosmic. Improvements to the Synchrotron Light Source allowed the detection of all elements between Cr and Mo, with the exceptions of Co and As, in our largest particle. The minor and trace element abundance patterns of three Ni-depleted particles were remarkably similar to those of extraterrestrial igneous rocks. Fe/Ni and Fe/Mn ratios suggest that one of these may be of lunar origin. All nine particles exhibited an enrichment in Br, ranging from 1.3 to 38 times the C1 concentration. Br concentrations were uncorrelated with particle size, as would be expected for a surface correlated component acquires from the stratosphere.

Breakdown of the Migdal-Eliashberg theory: A determinant quantum Monte Carlo study

NASA Astrophysics Data System (ADS)

Esterlis, I.; Nosarzewski, B.; Huang, E. W.; Moritz, B.; Devereaux, T. P.; Scalapino, D. J.; Kivelson, S. A.

2018-04-01

The superconducting (SC) and charge-density-wave (CDW) susceptibilities of the two-dimensional Holstein model are computed using determinant quantum Monte Carlo, and compared with results computed using the Migdal-Eliashberg (ME) approach. We access temperatures as low as 25 times less than the Fermi energy, EF, which are still above the SC transition. We find that the SC susceptibility at low T agrees quantitatively with the ME theory up to a dimensionless electron-phonon coupling λ0≈0.4 but deviates dramatically for larger λ0. We find that for large λ0 and small phonon frequency ω0≪EF CDW ordering is favored and the preferred CDW ordering vector is uncorrelated with any obvious feature of the Fermi surface.

Correlated and uncorrelated heart rate fluctuations during relaxing visualization

NASA Astrophysics Data System (ADS)

Papasimakis, N.; Pallikari, F.

2010-05-01

The heart rate variability (HRV) of healthy subjects practicing relaxing visualization is studied by use of three multiscale analysis techniques: the detrended fluctuation analysis (DFA), the entropy in natural time (ENT) and the average wavelet (AWC) coefficient. The scaling exponent of normal interbeat interval increments exhibits characteristics of the presence of long-range correlations. During relaxing visualization the HRV dynamics change in the sense that two new features emerge independent of each other: a respiration-induced periodicity that often dominates the HRV at short scales (<40 interbeat intervals) and the decrease of the scaling exponent at longer scales (40-512 interbeat intervals). In certain cases, the scaling exponent during relaxing visualization indicates the breakdown of long-range correlations. These characteristics have been previously seen in the HRV dynamics during non-REM sleep.

Posttraumatic Growth and Depreciation as Independent Experiences and Predictors of Well-Being

ERIC Educational Resources Information Center

Cann, Arnie; Calhoun, Lawrence G.; Tedeschi, Richard G.; Solomon, David T.

2010-01-01

Positive changes (posttraumatic growth [PTG]) and negative changes (posttraumatic depreciation [PTD]) were assessed using the PTGI-42 with persons reporting changes from a stressful event. PTG and PTD were uncorrelated, and PTG was much greater than PTD. PTG was positively related to disruption of core beliefs and recent deliberate rumination and…

Pure Perceptual-Based Sequence Learning: A Role for Visuospatial Attention

ERIC Educational Resources Information Center

Remillard, Gilbert

2009-01-01

Learning the structure of a sequence of target locations when target location is not the response dimension and the sequence of target locations is uncorrelated with the sequence of responses is called pure perceptual-based sequence learning. The paradigm introduced by G. Remillard (2003) was used to determine whether orienting of visuospatial…

Factorial Structure of the French Version of the Rosenberg Self-Esteem Scale among the Elderly

ERIC Educational Resources Information Center

Gana, Kamel; Alaphilippe, Daniel; Bailly, Nathalie

2005-01-01

Ten different confirmatory factor analysis models, including ones with correlated traits correlated methods, correlated traits correlated uniqueness, and correlated traits uncorrelated methods, were proposed to examine the factorial structure of the French version of the Rosenberg Self-Esteem Scale (Rosenberg, 1965). In line with previous studies…

Variational Approach to Monte Carlo Renormalization Group

NASA Astrophysics Data System (ADS)

Wu, Yantao; Car, Roberto

2017-12-01

We present a Monte Carlo method for computing the renormalized coupling constants and the critical exponents within renormalization theory. The scheme, which derives from a variational principle, overcomes critical slowing down, by means of a bias potential that renders the coarse grained variables uncorrelated. The two-dimensional Ising model is used to illustrate the method.

Separating Turbofan Engine Noise Sources Using Auto and Cross Spectra from Four Microphones

NASA Technical Reports Server (NTRS)

Miles, Jeffrey Hilton

2008-01-01

The study of core noise from turbofan engines has become more important as noise from other sources such as the fan and jet were reduced. A multiple-microphone and acoustic-source modeling method to separate correlated and uncorrelated sources is discussed. The auto- and cross spectra in the frequency range below 1000 Hz are fitted with a noise propagation model based on a source couplet consisting of a single incoherent monopole source with a single coherent monopole source or a source triplet consisting of a single incoherent monopole source with two coherent monopole point sources. Examples are presented using data from a Pratt& Whitney PW4098 turbofan engine. The method separates the low-frequency jet noise from the core noise at the nozzle exit. It is shown that at low power settings, the core noise is a major contributor to the noise. Even at higher power settings, it can be more important than jet noise. However, at low frequencies, uncorrelated broadband noise and jet noise become the important factors as the engine power setting is increased.

How random is a random vector?

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2015-12-01

Over 80 years ago Samuel Wilks proposed that the "generalized variance" of a random vector is the determinant of its covariance matrix. To date, the notion and use of the generalized variance is confined only to very specific niches in statistics. In this paper we establish that the "Wilks standard deviation" -the square root of the generalized variance-is indeed the standard deviation of a random vector. We further establish that the "uncorrelation index" -a derivative of the Wilks standard deviation-is a measure of the overall correlation between the components of a random vector. Both the Wilks standard deviation and the uncorrelation index are, respectively, special cases of two general notions that we introduce: "randomness measures" and "independence indices" of random vectors. In turn, these general notions give rise to "randomness diagrams"-tangible planar visualizations that answer the question: How random is a random vector? The notion of "independence indices" yields a novel measure of correlation for Lévy laws. In general, the concepts and results presented in this paper are applicable to any field of science and engineering with random-vectors empirical data.

Removal of EOG Artifacts from EEG Recordings Using Stationary Subspace Analysis

PubMed Central

Zeng, Hong; Song, Aiguo

2014-01-01

An effective approach is proposed in this paper to remove ocular artifacts from the raw EEG recording. The proposed approach first conducts the blind source separation on the raw EEG recording by the stationary subspace analysis (SSA) algorithm. Unlike the classic blind source separation algorithms, SSA is explicitly tailored to the understanding of distribution changes, where both the mean and the covariance matrix are taken into account. In addition, neither independency nor uncorrelation is required among the sources by SSA. Thereby, it can concentrate artifacts in fewer components than the representative blind source separation methods. Next, the components that are determined to be related to the ocular artifacts are projected back to be subtracted from EEG signals, producing the clean EEG data eventually. The experimental results on both the artificially contaminated EEG data and real EEG data have demonstrated the effectiveness of the proposed method, in particular for the cases where limited number of electrodes are used for the recording, as well as when the artifact contaminated signal is highly nonstationary and the underlying sources cannot be assumed to be independent or uncorrelated. PMID:24550696

The convergence of European business cycles 1978-2000

NASA Astrophysics Data System (ADS)

Ormerod, Paul; Mounfield, Craig

2002-05-01

The degree of convergence of the business cycles of the economies of the European Union (EU) is a key policy issue. In particular, a substantial degree of convergence is needed if the European Central Bank is to be capable of setting a monetary policy which is appropriate to the stage of the cycle of the Euro zone economies. We consider the annual rates of real GDP growth on a quarterly basis in the large core economies of the EU (France, Germany and Italy, plus The Netherlands) over the period 1978Q1-2000Q3. An important empirical question is the degree to which the correlations between these growth rates contain true information rather than noise. The technique of random matrix theory is able to answer this question, and has been recently applied successfully in the physics journals to financial markets data. We find that the correlations between the growth rates of the core EU economies contain substantial amounts of true information, and exhibit considerable stability over time. Even in the late 1970s and early 1980s, these economies moved together closely over the course of the business cycle. There was a slight loosening at the time of German re-unification, but the economies are now, if anything, even more closely correlated. As a benchmark for comparison, we add a series to the EU core data set which by construction is uncorrelated with these business cycles. We then analyse the EU core plus Spain, a country which has attached great importance to greater integration with Europe. In the early part of the period examined, the results are very similar to those obtained with the data set of the EU core plus the random series. However, there is a clear trend in the results, which provide strong evidence to support the view that the Spanish economy has now become closely converged with the core EU economies in terms of its movements over the business cycle. In contrast, the results obtained with a data set of the EU core plus the UK show no such trend. In the late 1970s and early 1980s, the UK economy did exhibit some degree of correlation with those of the core EU. However, there is no clear evidence to suggest that the UK business cycle has moved more closely into line with that of the core EU economies over the 1978-2000 period.

Associated reactions during a visual pursuit position tracking task in hemiplegic and quadriplegic cerebral palsy.

PubMed

Chiu, Hsiu-Ching; Halaki, Mark; O'Dwyer, Nicholas

2013-04-30

Most previous studies of associated reactions (ARs) in people with cerebral palsy have used observation scales, such as recording the degree of movement through observation. The sensitive quantitative method can detect ARs that are not amply visible. The aim of this study was to provide quantitative measures of ARs during a visual pursuit position tracking task. Twenty-three hemiplegia (H) (mean +/- SD: 21y 8m +/- 11y 10m), twelve quadriplegia (Q) (21y 5m +/- 10y 3m) and twenty-two subjects with normal development (N) (21y 2m +/- 10y 10m) participated in the study. An upper limb visual pursuit tracking task was used to study ARs. The participants were required to follow a moving target with a response cursor via elbow flexion and extension movements. The occurrence of ARs was quantified by the overall coherence between the movements of tracking and non-tracking limbs and the amount of movement due to ARs was quantified by the amplitude of movement the non-tracking limbs. The amplitude of movement of the non-tracking limb indicated that the amount of ARs was larger in the Q group than the H and N groups with no significant differences between the H and N groups. The amplitude of movement of the non-tracking limb was larger during non-dominant than dominant tracking in all three groups. Some movements in the non-tracking limb were correlated with the tracking limb (correlated ARs) and some movements that were not correlated with the tracking limb (uncorrelated ARs). The correlated ARs comprised less than 40% of the total ARs for all three groups. Correlated ARs were negatively associated with clinical evaluations, but not the uncorrelated ARs. The correlated and uncorrelated ARs appear to have different relationships with clinical evaluations, implying the effect of ARs on upper limb activities could be varied.

Real-Time Neural Signals Decoding onto Off-the-Shelf DSP Processors for Neuroprosthetic Applications.

PubMed

Pani, Danilo; Barabino, Gianluca; Citi, Luca; Meloni, Paolo; Raspopovic, Stanisa; Micera, Silvestro; Raffo, Luigi

2016-09-01

The control of upper limb neuroprostheses through the peripheral nervous system (PNS) can allow restoring motor functions in amputees. At present, the important aspect of the real-time implementation of neural decoding algorithms on embedded systems has been often overlooked, notwithstanding the impact that limited hardware resources have on the efficiency/effectiveness of any given algorithm. Present study is addressing the optimization of a template matching based algorithm for PNS signals decoding that is a milestone for its real-time, full implementation onto a floating-point digital signal processor (DSP). The proposed optimized real-time algorithm achieves up to 96% of correct classification on real PNS signals acquired through LIFE electrodes on animals, and can correctly sort spikes of a synthetic cortical dataset with sufficiently uncorrelated spike morphologies (93% average correct classification) comparably to the results obtained with top spike sorter (94% on average on the same dataset). The power consumption enables more than 24 h processing at the maximum load, and latency model has been derived to enable a fair performance assessment. The final embodiment demonstrates the real-time performance onto a low-power off-the-shelf DSP, opening to experiments exploiting the efferent signals to control a motor neuroprosthesis.

Randoms Counter Analysis

NASA Astrophysics Data System (ADS)

Hensley, Winston; Giovanetti, Kevin

2008-10-01

A 1 ppm precision measurement of the muon lifetime is being conducted by the MULAN collaboration. The reason for this new measurement lies in recent advances in theory that have reduced the uncertainty in calculating the Fermi Coupling Constant from the measured lifetime to a few tenths ppm. The largest uncertainty is now experimental. To achieve a 1ppm level of precision it is necessary to control all sources of systematic error and to understand their influences on the lifetime measurement. James Madison University is contributing by examine the response of the timing system to uncorrelated events, randoms. A radioactive source was placed in front of paired detectors similar to those in the main experiment. These detectors were integrated in an identical fashion into the data acquisition and measurement system and data from these detectors was recorded during the entire experiment. The pair were placed in a shielded enclosure away from the main experiment to minimize interference. The data from these detectors should have a flat time spectrum as the decay of a radioactive source is a random event and has no time correlation. Thus the spectrum can be used as an important diagnostic in studying the method of determining event times and timing system performance.

Protein-Backbone Thermodynamics across the Membrane Interface.

PubMed

Bereau, Tristan; Kremer, Kurt

2016-07-07

The thermodynamics of insertion of a protein in a membrane depends on the fine interplay between backbone and side-chain contributions interacting with the lipid environment. Using computer simulations, we probe how different descriptions of the backbone glycyl unit affect the thermodynamics of insertion of individual residues, dipeptides, and entire transmembrane helices. Due to the lack of reference data, we first introduce an efficient methodology to estimate atomistic potential of mean force (PMF) curves from a series of representative and uncorrelated coarse-grained (CG) snapshots. We find strong discrepancies between two CG models, Martini and PLUM, against reference atomistic PMFs and experiments. Atomistic simulations suggest a weak free energy of insertion between water and a POPC membrane for the glycyl unit, in overall agreement with experimental results despite severe assumptions in our calculations. We show that refining the backbone contribution in PLUM significantly improves the PMF of insertion of the WALP16 transmembrane peptide. An improper balance between the glycyl backbone and the attached side chain will lead to energetic artifacts, rationalizing Martini's overstabilization of WALP's adsorbed interfacial state. It illustrates difficulties associated with free-energy-based parametrizations of single-residue models, as the relevant free energy of partitioning used for force-field parametrization does not arise from the entire residue but rather the solvent-accessible chemical groups.

Large-Angular-Scale Anisotropy in the Cosmic Background Radiation

DOE R&D Accomplishments Database

Gorenstein, M. V.; Smoot, G. F.

1980-05-01

We report the results of an extended series of airborne measurements of large-angular-scale anisotropy in the 3 K cosmic background radiation. Observations were carried out with a dual-antenna microwave radiometer operating at 33 GHz (.089 cm wavelength) flown on board a U-2 aircraft to 20 km altitude. In eleven flights, between December 1976 and May 1978, the radiometer measured differential intensity between pairs of directions distributed over most of the northern hemisphere with an rms sensitivity of 47 mK Hz{sup 1?}. The measurements how clear evidence of anisotropy that is readily interpreted as due to the solar motion relative to the sources of the radiation. The anisotropy is well fit by a first order spherical harmonic of amplitude 360{+ or -}50km sec{sup -1} toward the direction 11.2{+ or -}0.5 hours of right ascension and 19 {+ or -}8 degrees declination. A simultaneous fit to a combined hypotheses of dipole and quadrupole angular distributions places a 1 mK limit on the amplitude of most components of quadrupole anisotropy with 90% confidence. Additional analysis places a 0.5 mK limit on uncorrelated fluctuations (sky-roughness) in the 3 K background on an angular scale of the antenna beam width, about 7 degrees.

Disentangling Global Warming, Multidecadal Variability, and El Niño in Pacific Temperatures

NASA Astrophysics Data System (ADS)

Wills, Robert C.; Schneider, Tapio; Wallace, John M.; Battisti, David S.; Hartmann, Dennis L.

2018-03-01

A key challenge in climate science is to separate observed temperature changes into components due to internal variability and responses to external forcing. Extended integrations of forced and unforced climate models are often used for this purpose. Here we demonstrate a novel method to separate modes of internal variability from global warming based on differences in time scale and spatial pattern, without relying on climate models. We identify uncorrelated components of Pacific sea surface temperature variability due to global warming, the Pacific Decadal Oscillation (PDO), and the El Niño-Southern Oscillation (ENSO). Our results give statistical representations of PDO and ENSO that are consistent with their being separate processes, operating on different time scales, but are otherwise consistent with canonical definitions. We isolate the multidecadal variability of the PDO and find that it is confined to midlatitudes; tropical sea surface temperatures and their teleconnections mix in higher-frequency variability. This implies that midlatitude PDO anomalies are more persistent than previously thought.

Exploding microbubbles driving a simple electrochemical micropump

NASA Astrophysics Data System (ADS)

Uvarov, Ilia V.; Lemekhov, Sergey S.; Melenev, Artem E.; Svetovoy, Vitaly B.

2017-10-01

Electrochemical microactuators and micropumps are too slow for many applications. The use of the alternating polarity electrolysis can strongly reduce the response time of such devices. We investigate a powerful pumping regime of a simple valveless micropump made from polydimethylsiloxane on a glass substrate. Microsecond dynamics of the gas bubbles in the chamber is monitored with fast cameras. After an incubation period of 10-100 ms a microbubble filling the entire chamber pops up in less than 100~μ s and disappears in 10 ms. This bubble pushes liquid out and drives the pump. The phenomenon is interpreted as an explosion of the microbubble containing a mixture of H2 and O2 gases. For higher amplitude of the driving pulses the incubation time can be as short as 1-2 ms but many uncorrelated microbubbles are formed in the chamber, and disappear in 1 ms. As the result a less powerful but faster pumping is possible. A few principles allowing further improve the micropump characteristics are formulated.

First measurements of high frequency cross-spectra from a pair of large Michelson interferometers

DOE PAGES

Chou, Aaron S.; Gustafson, Richard; Hogan, Craig; ...

2016-09-09

Here, measurements are reported of the cross-correlation of spectra of differential position signals from the Fermilab Holometer, a pair of colocated 39 m long, high power Michelson interferometers with flat broadband frequency response in the MHz range. The instrument obtains sensitivity to high frequency correlated signals far exceeding any previous measurement in a broad frequency band extending beyond the 3.8 MHz inverse light-crossing time of the apparatus. The dominant but uncorrelated shot noise is averaged down over 2 × 10 8 independent spectral measurements with 381 Hz frequency resolution to obtain 2.1 × 10 -20m/ √Hz sensitivity to stationary signals. For signal bandwidthsmore » Δf > 11 kHz, the sensitivity to strain h or shear power spectral density of classical or exotic origin surpasses a milestone PSD δh < t p where t p = 5.39 × 10 -44/ Hz is the Planck time.« less

Multi-input multioutput orthogonal frequency division multiplexing radar waveform design for improving the detection performance of space-time adaptive processing

NASA Astrophysics Data System (ADS)

Wang, Hongyan

2017-04-01

This paper addresses the waveform optimization problem for improving the detection performance of multi-input multioutput (MIMO) orthogonal frequency division multiplexing (OFDM) radar-based space-time adaptive processing (STAP) in the complex environment. By maximizing the output signal-to-interference-and-noise-ratio (SINR) criterion, the waveform optimization problem for improving the detection performance of STAP, which is subjected to the constant modulus constraint, is derived. To tackle the resultant nonlinear and complicated optimization issue, a diagonal loading-based method is proposed to reformulate the issue as a semidefinite programming one; thereby, this problem can be solved very efficiently. In what follows, the optimized waveform can be obtained to maximize the output SINR of MIMO-OFDM such that the detection performance of STAP can be improved. The simulation results show that the proposed method can improve the output SINR detection performance considerably as compared with that of uncorrelated waveforms and the existing MIMO-based STAP method.

Linearized spectrum correlation analysis for line emission measurements

NASA Astrophysics Data System (ADS)

Nishizawa, T.; Nornberg, M. D.; Den Hartog, D. J.; Sarff, J. S.

2017-08-01

A new spectral analysis method, Linearized Spectrum Correlation Analysis (LSCA), for charge exchange and passive ion Doppler spectroscopy is introduced to provide a means of measuring fast spectral line shape changes associated with ion-scale micro-instabilities. This analysis method is designed to resolve the fluctuations in the emission line shape from a stationary ion-scale wave. The method linearizes the fluctuations around a time-averaged line shape (e.g., Gaussian) and subdivides the spectral output channels into two sets to reduce contributions from uncorrelated fluctuations without averaging over the fast time dynamics. In principle, small fluctuations in the parameters used for a line shape model can be measured by evaluating the cross spectrum between different channel groupings to isolate a particular fluctuating quantity. High-frequency ion velocity measurements (100-200 kHz) were made by using this method. We also conducted simulations to compare LSCA with a moment analysis technique under a low photon count condition. Both experimental and synthetic measurements demonstrate the effectiveness of LSCA.

Uncertainties associated with parameter estimation in atmospheric infrasound arrays.

PubMed

Szuberla, Curt A L; Olson, John V

2004-01-01

This study describes a method for determining the statistical confidence in estimates of direction-of-arrival and trace velocity stemming from signals present in atmospheric infrasound data. It is assumed that the signal source is far enough removed from the infrasound sensor array that a plane-wave approximation holds, and that multipath and multiple source effects are not present. Propagation path and medium inhomogeneities are assumed not to be known at the time of signal detection, but the ensemble of time delays of signal arrivals between array sensor pairs is estimable and corrupted by uncorrelated Gaussian noise. The method results in a set of practical uncertainties that lend themselves to a geometric interpretation. Although quite general, this method is intended for use by analysts interpreting data from atmospheric acoustic arrays, or those interested in designing and deploying them. The method is applied to infrasound arrays typical of those deployed as a part of the International Monitoring System of the Comprehensive Nuclear-Test-Ban Treaty Organization.

Tempo and rates of diversification in the South American cichlid genus Apistogramma (Teleostei: Perciformes: Cichlidae).

PubMed

Tougard, Christelle; García Dávila, Carmen R; Römer, Uwe; Duponchelle, Fabrice; Cerqueira, Frédérique; Paradis, Emmanuel; Guinand, Bruno; Angulo Chávez, Carlos; Salas, Vanessa; Quérouil, Sophie; Sirvas, Susana; Renno, Jean-François

2017-01-01

Evaluating biodiversity and understanding the processes involved in diversification are noticeable conservation issues in fishes subject to large, sometimes illegal, ornamental trade purposes. Here, the diversity and evolutionary history of the Neotropical dwarf cichlid genus Apistogramma from several South American countries are investigated. Mitochondrial and nuclear markers are used to infer phylogenetic relationships between 31 genetically identified species. The monophyly of Apistogramma is suggested, and Apistogramma species are distributed into four clades, corresponding to three morphological lineages. Divergence times estimated with the Yule process and an uncorrelated lognormal clock dated the Apistogramma origin to the beginning of the Eocene (≈ 50 Myr) suggesting that diversification might be related to marine incursions. Our molecular dating also suggests that the Quaternary glacial cycles coincide with the phases leading to Apistogramma speciation. These past events did not influence diversification rates in the speciose genus Apistogramma, since diversification appeared low and constant through time. Further characterization of processes involved in recent Apistogramma diversity will be necessary.

Tempo and rates of diversification in the South American cichlid genus Apistogramma (Teleostei: Perciformes: Cichlidae)

PubMed Central

García Dávila, Carmen R.; Römer, Uwe; Duponchelle, Fabrice; Cerqueira, Frédérique; Paradis, Emmanuel; Guinand, Bruno; Angulo Chávez, Carlos; Salas, Vanessa; Quérouil, Sophie; Sirvas, Susana; Renno, Jean-François

2017-01-01

Evaluating biodiversity and understanding the processes involved in diversification are noticeable conservation issues in fishes subject to large, sometimes illegal, ornamental trade purposes. Here, the diversity and evolutionary history of the Neotropical dwarf cichlid genus Apistogramma from several South American countries are investigated. Mitochondrial and nuclear markers are used to infer phylogenetic relationships between 31 genetically identified species. The monophyly of Apistogramma is suggested, and Apistogramma species are distributed into four clades, corresponding to three morphological lineages. Divergence times estimated with the Yule process and an uncorrelated lognormal clock dated the Apistogramma origin to the beginning of the Eocene (≈ 50 Myr) suggesting that diversification might be related to marine incursions. Our molecular dating also suggests that the Quaternary glacial cycles coincide with the phases leading to Apistogramma speciation. These past events did not influence diversification rates in the speciose genus Apistogramma, since diversification appeared low and constant through time. Further characterization of processes involved in recent Apistogramma diversity will be necessary. PMID:28873089

Mammalian chiasma frequencies as a test of two theories of recombination.

PubMed

Burt, A; Bell, G

A broad survey of asexuality in the animal kingdom is sufficient to reject all theories of sex and recombination except two: the Red Queen and the Tangled Bank. The Red Queen theory states that an organism's biotic environment tends to be 'contrary', consistently evolving to the detriment of the organism; sex and recombination result in progeny genetically distinct from their parents and grandparents and thus less susceptible to the antagonistic advances made during the previous generations, particularly by their parasites. The alternative theory, the Tangled Bank, states that sex and recombination function to diversify the progeny from each other, thus reducing competition between them. An extensive survey of mammalian recombination shows that the total number of chiasmata in excess of one per bivalent is strongly correlated with generation time but uncorrelated with fecundity. We conclude that crossing-over may function to combat antagonists with short generation times but does not function to reduce sib competition. Chromosome number is selectively neutral with respect to these factors.

A causal contiguity effect that persists across time scales.

PubMed

Kiliç, Asli; Criss, Amy H; Howard, Marc W

2013-01-01

The contiguity effect refers to the tendency to recall an item from nearby study positions of the just recalled item. Causal models of contiguity suggest that recalled items are used as probes, causing a change in the memory state for subsequent recall attempts. Noncausal models of the contiguity effect assume the memory state is unaffected by recall per se, relying instead on the correlation between the memory states at study and at test to drive contiguity. We examined the contiguity effect in a probed recall task in which the correlation between the study context and the test context was disrupted. After study of several lists of words, participants were given probe words in a random order and were instructed to recall a word from the same list as the probe. The results showed both short-term and long-term contiguity effects. Because study order and test order are uncorrelated, these contiguity effects require a causal contiguity mechanism that operates across time scales.

First Measurements of High Frequency Cross-Spectra from a Pair of Large Michelson Interferometers.

PubMed

Chou, Aaron S; Gustafson, Richard; Hogan, Craig; Kamai, Brittany; Kwon, Ohkyung; Lanza, Robert; McCuller, Lee; Meyer, Stephan S; Richardson, Jonathan; Stoughton, Chris; Tomlin, Raymond; Waldman, Samuel; Weiss, Rainer

2016-09-09

Measurements are reported of the cross-correlation of spectra of differential position signals from the Fermilab Holometer, a pair of colocated 39 m long, high power Michelson interferometers with flat broadband frequency response in the MHz range. The instrument obtains sensitivity to high frequency correlated signals far exceeding any previous measurement in a broad frequency band extending beyond the 3.8 MHz inverse light-crossing time of the apparatus. The dominant but uncorrelated shot noise is averaged down over 2×10^{8} independent spectral measurements with 381 Hz frequency resolution to obtain 2.1×10^{-20}m/sqrt[Hz] sensitivity to stationary signals. For signal bandwidths Δf>11  kHz, the sensitivity to strain h or shear power spectral density of classical or exotic origin surpasses a milestone PSD_{δh}

Efficient strategies for leave-one-out cross validation for genomic best linear unbiased prediction.

PubMed

Cheng, Hao; Garrick, Dorian J; Fernando, Rohan L

2017-01-01

A random multiple-regression model that simultaneously fit all allele substitution effects for additive markers or haplotypes as uncorrelated random effects was proposed for Best Linear Unbiased Prediction, using whole-genome data. Leave-one-out cross validation can be used to quantify the predictive ability of a statistical model. Naive application of Leave-one-out cross validation is computationally intensive because the training and validation analyses need to be repeated n times, once for each observation. Efficient Leave-one-out cross validation strategies are presented here, requiring little more effort than a single analysis. Efficient Leave-one-out cross validation strategies is 786 times faster than the naive application for a simulated dataset with 1,000 observations and 10,000 markers and 99 times faster with 1,000 observations and 100 markers. These efficiencies relative to the naive approach using the same model will increase with increases in the number of observations. Efficient Leave-one-out cross validation strategies are presented here, requiring little more effort than a single analysis.

A Comparison of Composite Reliability Estimators: Coefficient Omega Confidence Intervals in the Current Literature

ERIC Educational Resources Information Center

Padilla, Miguel A.; Divers, Jasmin

2016-01-01

Coefficient omega and alpha are both measures of the composite reliability for a set of items. Unlike coefficient alpha, coefficient omega remains unbiased with congeneric items with uncorrelated errors. Despite this ability, coefficient omega is not as widely used and cited in the literature as coefficient alpha. Reasons for coefficient omega's…

Face Recognition via Ensemble SIFT Matching of Uncorrelated Hyperspectral Bands and Spectral PCTs

DTIC Science & Technology

2011-06-01

Operational Sciences Graduate School of Engineering and Management Air Force Institute of Technology Air University Air...Education and Training Command In Partial Fulfillment of the Requirements for the Degree of Master of Science in Operations Research...Comparison of performance against different categories of probes (Phillips, Moon, Rauss, & Rizvi, 1997, p. 141

Identifying presence of correlated errors in GRACE monthly harmonic coefficients using machine learning algorithms

NASA Astrophysics Data System (ADS)

Piretzidis, Dimitrios; Sra, Gurveer; Karantaidis, George; Sideris, Michael G.

2017-04-01

A new method for identifying correlated errors in Gravity Recovery and Climate Experiment (GRACE) monthly harmonic coefficients has been developed and tested. Correlated errors are present in the differences between monthly GRACE solutions, and can be suppressed using a de-correlation filter. In principle, the de-correlation filter should be implemented only on coefficient series with correlated errors to avoid losing useful geophysical information. In previous studies, two main methods of implementing the de-correlation filter have been utilized. In the first one, the de-correlation filter is implemented starting from a specific minimum order until the maximum order of the monthly solution examined. In the second one, the de-correlation filter is implemented only on specific coefficient series, the selection of which is based on statistical testing. The method proposed in the present study exploits the capabilities of supervised machine learning algorithms such as neural networks and support vector machines (SVMs). The pattern of correlated errors can be described by several numerical and geometric features of the harmonic coefficient series. The features of extreme cases of both correlated and uncorrelated coefficients are extracted and used for the training of the machine learning algorithms. The trained machine learning algorithms are later used to identify correlated errors and provide the probability of a coefficient series to be correlated. Regarding SVMs algorithms, an extensive study is performed with various kernel functions in order to find the optimal training model for prediction. The selection of the optimal training model is based on the classification accuracy of the trained SVM algorithm on the same samples used for training. Results show excellent performance of all algorithms with a classification accuracy of 97% - 100% on a pre-selected set of training samples, both in the validation stage of the training procedure and in the subsequent use of the trained algorithms to classify independent coefficients. This accuracy is also confirmed by the external validation of the trained algorithms using the hydrology model GLDAS NOAH. The proposed method meet the requirement of identifying and de-correlating only coefficients with correlated errors. Also, there is no need of applying statistical testing or other techniques that require prior de-correlation of the harmonic coefficients.

Stimulated Raman and Brillouin scattering of polarization-smoothed and temporally smoothed laser beams

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

Berger, R.L.; Lefebvre, E.; Langdon, A.B.

1999-04-01

Control of filamentation and stimulated Raman and Brillouin scattering is shown to be possible by use of both spatial and temporal smoothing schemes. The spatial smoothing is accomplished by the use of phase plates [Y. Kato and K. Mima, Appl. Phys. {bold 329}, 186 (1982)] and polarization smoothing [Lefebvre {ital et al.}, Phys. Plasmas {bold 5}, 2701 (1998)] in which the plasma is irradiated with two orthogonally polarized, uncorrelated speckle patterns. The temporal smoothing considered here is smoothing by spectral dispersion [Skupsky {ital et al.}, J. Appl. Phys. {bold 66}, 3456 (1989)] in which the speckle pattern changes on themore » laser coherence time scale. At the high instability gains relevant to laser fusion experiments, the effect of smoothing must include the competition among all three instabilities. {copyright} {ital 1999 American Institute of Physics.}« less

Effects of collision cascade density on radiation defect dynamics in 3C-SiC

PubMed Central

Bayu Aji, L. B.; Wallace, J. B.; Kucheyev, S. O.

2017-01-01

Effects of the collision cascade density on radiation damage in SiC remain poorly understood. Here, we study damage buildup and defect interaction dynamics in 3C-SiC bombarded at 100 °C with either continuous or pulsed beams of 500 keV Ne, Ar, Kr, or Xe ions. We find that bombardment with heavier ions, which create denser collision cascades, results in a decrease in the dynamic annealing efficiency and an increase in both the amorphization cross-section constant and the time constant of dynamic annealing. The cascade density behavior of these parameters is non-linear and appears to be uncorrelated. These results demonstrate clearly (and quantitatively) an important role of the collision cascade density in dynamic radiation defect processes in 3C-SiC. PMID:28304397

Effects of collision cascade density on radiation defect dynamics in 3C-SiC

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

Bayu Aji, L. B.; Wallace, J. B.; Kucheyev, S. O.

Effects of the collision cascade density on radiation damage in SiC remain poorly understood. We study damage buildup and defect interaction dynamics in 3C-SiC bombarded at 100 °C with either continuous or pulsed beams of 500 keV Ne, Ar, Kr, or Xe ions. Here, we find that bombardment with heavier ions, which create denser collision cascades, results in a decrease in the dynamic annealing efficiency and an increase in both the amorphization cross-section constant and the time constant of dynamic annealing. The cascade density behavior of these parameters is non-linear and appears to be uncorrelated. Our results demonstrate clearly (andmore » quantitatively) an important role of the collision cascade density in dynamic radiation defect processes in 3C-SiC.« less

Rigidity in Gender-Typed Behaviors in Early Childhood: A Longitudinal Study of Ethnic Minority Children

PubMed Central

Ruble, Diane; Tamis-LeMonda, Catherine; Shrout, Patrick E.

2014-01-01

A key prediction of cognitive theories of gender development concerns developmental trajectories in the relative strength or rigidity of gender typing. To examine these trajectories in early childhood, 229 children (African American, Mexican, Dominican) were followed annually from age 3 to 5 and gender-stereotypical appearance, dress-up play, toy play, and sex segregation were examined. High gender-typing was found across ethnic group, and most behaviors increased in rigidity, especially from age 3 to 4. In addressing controversy surrounding the stability and structure of gender-typing it was found that from year to year, most behaviors showed moderately stable individual differences. Behaviors were uncorrelated within age, but showed more concordance in change across time, suggesting that aspects of gender-typing are multidimensional but still show coherence. PMID:23432471

Hierarchical learning induces two simultaneous, but separable, prediction errors in human basal ganglia.

PubMed

Diuk, Carlos; Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew; Niv, Yael

2013-03-27

Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously.

Accelerated numerical processing of electronically recorded holograms with reduced speckle noise.

PubMed

Trujillo, Carlos; Garcia-Sucerquia, Jorge

2013-09-01

The numerical reconstruction of digitally recorded holograms suffers from speckle noise. An accelerated method that uses general-purpose computing in graphics processing units to reduce that noise is shown. The proposed methodology utilizes parallelized algorithms to record, reconstruct, and superimpose multiple uncorrelated holograms of a static scene. For the best tradeoff between reduction of the speckle noise and processing time, the method records, reconstructs, and superimposes six holograms of 1024 × 1024 pixels in 68 ms; for this case, the methodology reduces the speckle noise by 58% compared with that exhibited by a single hologram. The fully parallelized method running on a commodity graphics processing unit is one order of magnitude faster than the same technique implemented on a regular CPU using its multithreading capabilities. Experimental results are shown to validate the proposal.

Effects of collision cascade density on radiation defect dynamics in 3C-SiC

DOE PAGES

Bayu Aji, L. B.; Wallace, J. B.; Kucheyev, S. O.

2017-03-17

Effects of the collision cascade density on radiation damage in SiC remain poorly understood. We study damage buildup and defect interaction dynamics in 3C-SiC bombarded at 100 °C with either continuous or pulsed beams of 500 keV Ne, Ar, Kr, or Xe ions. Here, we find that bombardment with heavier ions, which create denser collision cascades, results in a decrease in the dynamic annealing efficiency and an increase in both the amorphization cross-section constant and the time constant of dynamic annealing. The cascade density behavior of these parameters is non-linear and appears to be uncorrelated. Our results demonstrate clearly (andmore » quantitatively) an important role of the collision cascade density in dynamic radiation defect processes in 3C-SiC.« less

Robust reliable sampled-data control for switched systems with application to flight control

NASA Astrophysics Data System (ADS)

Sakthivel, R.; Joby, Maya; Shi, P.; Mathiyalagan, K.

2016-11-01

This paper addresses the robust reliable stabilisation problem for a class of uncertain switched systems with random delays and norm bounded uncertainties. The main aim of this paper is to obtain the reliable robust sampled-data control design which involves random time delay with an appropriate gain control matrix for achieving the robust exponential stabilisation for uncertain switched system against actuator failures. In particular, the involved delays are assumed to be randomly time-varying which obeys certain mutually uncorrelated Bernoulli distributed white noise sequences. By constructing an appropriate Lyapunov-Krasovskii functional (LKF) and employing an average-dwell time approach, a new set of criteria is derived for ensuring the robust exponential stability of the closed-loop switched system. More precisely, the Schur complement and Jensen's integral inequality are used in derivation of stabilisation criteria. By considering the relationship among the random time-varying delay and its lower and upper bounds, a new set of sufficient condition is established for the existence of reliable robust sampled-data control in terms of solution to linear matrix inequalities (LMIs). Finally, an illustrative example based on the F-18 aircraft model is provided to show the effectiveness of the proposed design procedures.

Selectivity of Electronic Coherence and Attosecond Ionization Delays in Strong-Field Double Ionization

NASA Astrophysics Data System (ADS)

Kobayashi, Yuki; Reduzzi, Maurizio; Chang, Kristina F.; Timmers, Henry; Neumark, Daniel M.; Leone, Stephen R.

2018-06-01

Experiments are presented on real-time probing of coherent electron dynamics in xenon initiated by strong-field double ionization. Attosecond transient absorption measurements allow for characterization of electronic coherences as well as relative ionization timings in multiple electronic states of Xe+ and Xe2 + . A high degree of coherence g =0.4 is observed between P3 2 0-P3 0 0 of Xe2 + , whereas for other possible pairs of states the coherences are below the detection limits of the experiments. A comparison of the experimental results with numerical simulations based on an uncorrelated electron-emission model shows that the coherences produced by strong-field double ionization are more selective than predicted. Surprisingly short ionization time delays, 0.85 fs, 0.64 fs, and 0.75 fs relative to Xe+ formation, are also measured for the P2 3 , P0 3 , and P1 3 states of Xe2 + , respectively. Both the unpredicted selectivity in the formation of coherence and the subfemtosecond time delays of specific states provide new insight into correlated electron dynamics in strong-field double ionization.

Out-of-equilibrium relaxation of the thermal Casimir effect in a model polarizable material

NASA Astrophysics Data System (ADS)

Dean, David S.; Démery, Vincent; Parsegian, V. Adrian; Podgornik, Rudolf

2012-03-01

Relaxation of the thermal Casimir or van der Waals force (the high temperature limit of the Casimir force) for a model dielectric medium is investigated. We start with a model of interacting polarization fields with a dynamics that leads to a frequency dependent dielectric constant of the Debye form. In the static limit, the usual zero frequency Matsubara mode component of the Casimir force is recovered. We then consider the out-of-equilibrium relaxation of the van der Waals force to its equilibrium value when two initially uncorrelated dielectric bodies are brought into sudden proximity. For the interaction between dielectric slabs, it is found that the spatial dependence of the out-of-equilibrium force is the same as the equilibrium one, but it has a time dependent amplitude, or Hamaker coefficient, which increases in time to its equilibrium value. The final relaxation of the force to its equilibrium value is exponential in systems with a single or finite number of polarization field relaxation times. However, in systems, such as those described by the Havriliak-Negami dielectric constant with a broad distribution of relaxation times, we observe a much slower power law decay to the equilibrium value.

Why didn't Box-Jenkins win (again)

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

Pack, D.J.; Downing, D.J.

This paper focuses on the forecasting performance of the Box-Jenkins methodology applied to the 111 time series of the Makridakis competition. It considers the influence of the following factors: (1) time series length, (2) time-series information (autocorrelation) content, (3) time-series outliers or structural changes, (4) averaging results over time series, and (5) forecast time origin choice. It is found that the 111 time series contain substantial numbers of very short series, series with obvious structural change, and series whose histories are relatively uninformative. If these series are typical of those that one must face in practice, the real message ofmore » the competition is that univariate time series extrapolations will frequently fail regardless of the methodology employed to produce them.« less

Multifractal analysis of visibility graph-based Ito-related connectivity time series.

PubMed

Czechowski, Zbigniew; Lovallo, Michele; Telesca, Luciano

2016-02-01

In this study, we investigate multifractal properties of connectivity time series resulting from the visibility graph applied to normally distributed time series generated by the Ito equations with multiplicative power-law noise. We show that multifractality of the connectivity time series (i.e., the series of numbers of links outgoing any node) increases with the exponent of the power-law noise. The multifractality of the connectivity time series could be due to the width of connectivity degree distribution that can be related to the exit time of the associated Ito time series. Furthermore, the connectivity time series are characterized by persistence, although the original Ito time series are random; this is due to the procedure of visibility graph that, connecting the values of the time series, generates persistence but destroys most of the nonlinear correlations. Moreover, the visibility graph is sensitive for detecting wide "depressions" in input time series.

Detection of regional infrasound signals using array data: Testing, tuning, and physical interpretation

DOE PAGES

Park, Junghyun; Stump, Brian W.; Hayward, Chris; ...

2016-07-14

This work quantifies the physical characteristics of infrasound signal and noise, assesses their temporal variations, and determines the degree to which these effects can be predicted by time-varying atmospheric models to estimate array and network performance. An automated detector that accounts for both correlated and uncorrelated noise is applied to infrasound data from three seismo-acoustic arrays in South Korea (BRDAR, CHNAR, and KSGAR), cooperatively operated by Korea Institute of Geoscience and Mineral Resources (KIGAM) and Southern Methodist University (SMU). Arrays located on an island and near the coast have higher noise power, consistent with both higher wind speeds and seasonablymore » variable ocean wave contributions. On the basis of the adaptive F-detector quantification of time variable environmental effects, the time-dependent scaling variable is shown to be dependent on both weather conditions and local site effects. Significant seasonal variations in infrasound detections including daily time of occurrence, detection numbers, and phase velocity/azimuth estimates are documented. These time-dependent effects are strongly correlated with atmospheric winds and temperatures and are predicted by available atmospheric specifications. As a result, this suggests that commonly available atmospheric specifications can be used to predict both station and network detection performance, and an appropriate forward model improves location capabilities as a function of time.« less

Detection of regional infrasound signals using array data: Testing, tuning, and physical interpretation.

PubMed

Park, Junghyun; Stump, Brian W; Hayward, Chris; Arrowsmith, Stephen J; Che, Il-Young; Drob, Douglas P

2016-07-01

This work quantifies the physical characteristics of infrasound signal and noise, assesses their temporal variations, and determines the degree to which these effects can be predicted by time-varying atmospheric models to estimate array and network performance. An automated detector that accounts for both correlated and uncorrelated noise is applied to infrasound data from three seismo-acoustic arrays in South Korea (BRDAR, CHNAR, and KSGAR), cooperatively operated by Korea Institute of Geoscience and Mineral Resources (KIGAM) and Southern Methodist University (SMU). Arrays located on an island and near the coast have higher noise power, consistent with both higher wind speeds and seasonably variable ocean wave contributions. On the basis of the adaptive F-detector quantification of time variable environmental effects, the time-dependent scaling variable is shown to be dependent on both weather conditions and local site effects. Significant seasonal variations in infrasound detections including daily time of occurrence, detection numbers, and phase velocity/azimuth estimates are documented. These time-dependent effects are strongly correlated with atmospheric winds and temperatures and are predicted by available atmospheric specifications. This suggests that commonly available atmospheric specifications can be used to predict both station and network detection performance, and an appropriate forward model improves location capabilities as a function of time.

How Variables Uncorrelated with the Dependent Variable Can Actually Make Excellent Predictors: The Important Suppressor Variable Case.

ERIC Educational Resources Information Center

Woolley, Kristin K.

Many researchers are unfamiliar with suppressor variables and how they operate in multiple regression analyses. This paper describes the role suppressor variables play in a multiple regression model and provides practical examples that explain how they can change research results. A variable that when added as another predictor increases the total…

Experimental generation of optical coherence lattices

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

Chen, Yahong; Cai, Yangjian, E-mail: serpo@dal.ca, E-mail: yangjiancai@suda.edu.cn; Key Lab of Advanced Optical Manufacturing Technologies of Jiangsu Province and Key Lab of Modern Optical Technologies of Education Ministry of China, Soochow University, Suzhou 215006

2016-08-08

We report experimental generation and measurement of recently introduced optical coherence lattices. The presented optical coherence lattice realization technique hinges on a superposition of mutually uncorrelated partially coherent Schell-model beams with tailored coherence properties. We show theoretically that information can be encoded into and, in principle, recovered from the lattice degree of coherence. Our results can find applications to image transmission and optical encryption.

Stochastic analog neutron transport with TRIPOLI-4 and FREYA: Bayesian uncertainty quantification for neutron multiplicity counting

DOE PAGES

Verbeke, J. M.; Petit, O.

2016-06-01

From nuclear safeguards to homeland security applications, the need for the better modeling of nuclear interactions has grown over the past decades. Current Monte Carlo radiation transport codes compute average quantities with great accuracy and performance; however, performance and averaging come at the price of limited interaction-by-interaction modeling. These codes often lack the capability of modeling interactions exactly: for a given collision, energy is not conserved, energies of emitted particles are uncorrelated, and multiplicities of prompt fission neutrons and photons are uncorrelated. Many modern applications require more exclusive quantities than averages, such as the fluctuations in certain observables (e.g., themore » neutron multiplicity) and correlations between neutrons and photons. In an effort to meet this need, the radiation transport Monte Carlo code TRIPOLI-4® was modified to provide a specific mode that models nuclear interactions in a full analog way, replicating as much as possible the underlying physical process. Furthermore, the computational model FREYA (Fission Reaction Event Yield Algorithm) was coupled with TRIPOLI-4 to model complete fission events. As a result, FREYA automatically includes fluctuations as well as correlations resulting from conservation of energy and momentum.« less

Estimating the instabilities of N clocks by means of comparison measurements

NASA Technical Reports Server (NTRS)

Premoli, Amedeo; Tavella, Patrizia

1993-01-01

The estimation of individual instabilities of N clocks, compared by measuring the differences of their readings, is considered without assuming a priori any hypotheses on their uncorrelation. Instabilities of the N clocks are described by a complete (non-diagonal) N x N covariance matrix R. Only differences of clock readings are available in order to estimate R. Statistical processing of these data allows one to calculate the (N-1)x(N-l) covariance matrix S of the differences relative to the N-th(reference) clock. By analyzing the relationships tying R and S, several pieces of information can be inferred and, in particular, the conditions for the validity of the uncorrelation hypothesis are established. The estimation of R from S is not unique: in any case R must be positive definite. A theorem states that R is positive definite if and only if its determinant is positive. Nevertheless infinitely many acceptable choices of R still fulfill the condition of positive definiteness. This paper shows that, by increasing the number N of compared clocks, the amount of arbitrariness in estimating R is reduced. The analysis of some experimental data illustrates the capability of the method.

Regenerating time series from ordinal networks.

PubMed

McCullough, Michael; Sakellariou, Konstantinos; Stemler, Thomas; Small, Michael

2017-03-01

Recently proposed ordinal networks not only afford novel methods of nonlinear time series analysis but also constitute stochastic approximations of the deterministic flow time series from which the network models are constructed. In this paper, we construct ordinal networks from discrete sampled continuous chaotic time series and then regenerate new time series by taking random walks on the ordinal network. We then investigate the extent to which the dynamics of the original time series are encoded in the ordinal networks and retained through the process of regenerating new time series by using several distinct quantitative approaches. First, we use recurrence quantification analysis on traditional recurrence plots and order recurrence plots to compare the temporal structure of the original time series with random walk surrogate time series. Second, we estimate the largest Lyapunov exponent from the original time series and investigate the extent to which this invariant measure can be estimated from the surrogate time series. Finally, estimates of correlation dimension are computed to compare the topological properties of the original and surrogate time series dynamics. Our findings show that ordinal networks constructed from univariate time series data constitute stochastic models which approximate important dynamical properties of the original systems.

Regenerating time series from ordinal networks

NASA Astrophysics Data System (ADS)

McCullough, Michael; Sakellariou, Konstantinos; Stemler, Thomas; Small, Michael

2017-03-01

Recently proposed ordinal networks not only afford novel methods of nonlinear time series analysis but also constitute stochastic approximations of the deterministic flow time series from which the network models are constructed. In this paper, we construct ordinal networks from discrete sampled continuous chaotic time series and then regenerate new time series by taking random walks on the ordinal network. We then investigate the extent to which the dynamics of the original time series are encoded in the ordinal networks and retained through the process of regenerating new time series by using several distinct quantitative approaches. First, we use recurrence quantification analysis on traditional recurrence plots and order recurrence plots to compare the temporal structure of the original time series with random walk surrogate time series. Second, we estimate the largest Lyapunov exponent from the original time series and investigate the extent to which this invariant measure can be estimated from the surrogate time series. Finally, estimates of correlation dimension are computed to compare the topological properties of the original and surrogate time series dynamics. Our findings show that ordinal networks constructed from univariate time series data constitute stochastic models which approximate important dynamical properties of the original systems.

GPS Position Time Series @ JPL

NASA Technical Reports Server (NTRS)

Owen, Susan; Moore, Angelyn; Kedar, Sharon; Liu, Zhen; Webb, Frank; Heflin, Mike; Desai, Shailen

2013-01-01

Different flavors of GPS time series analysis at JPL - Use same GPS Precise Point Positioning Analysis raw time series - Variations in time series analysis/post-processing driven by different users. center dot JPL Global Time Series/Velocities - researchers studying reference frame, combining with VLBI/SLR/DORIS center dot JPL/SOPAC Combined Time Series/Velocities - crustal deformation for tectonic, volcanic, ground water studies center dot ARIA Time Series/Coseismic Data Products - Hazard monitoring and response focused center dot ARIA data system designed to integrate GPS and InSAR - GPS tropospheric delay used for correcting InSAR - Caltech's GIANT time series analysis uses GPS to correct orbital errors in InSAR - Zhen Liu's talking tomorrow on InSAR Time Series analysis

A general framework for time series data mining based on event analysis: application to the medical domains of electroencephalography and stabilometry.

PubMed

Lara, Juan A; Lizcano, David; Pérez, Aurora; Valente, Juan P

2014-10-01

There are now domains where information is recorded over a period of time, leading to sequences of data known as time series. In many domains, like medicine, time series analysis requires to focus on certain regions of interest, known as events, rather than analyzing the whole time series. In this paper, we propose a framework for knowledge discovery in both one-dimensional and multidimensional time series containing events. We show how our approach can be used to classify medical time series by means of a process that identifies events in time series, generates time series reference models of representative events and compares two time series by analyzing the events they have in common. We have applied our framework on time series generated in the areas of electroencephalography (EEG) and stabilometry. Framework performance was evaluated in terms of classification accuracy, and the results confirmed that the proposed schema has potential for classifying EEG and stabilometric signals. The proposed framework is useful for discovering knowledge from medical time series containing events, such as stabilometric and electroencephalographic time series. These results would be equally applicable to other medical domains generating iconographic time series, such as, for example, electrocardiography (ECG). Copyright © 2014 Elsevier Inc. All rights reserved.

A space-time multifractal analysis on radar rainfall sequences from central Poland

NASA Astrophysics Data System (ADS)

Licznar, Paweł; Deidda, Roberto

2014-05-01

Rainfall downscaling belongs to most important tasks of modern hydrology. Especially from the perspective of urban hydrology there is real need for development of practical tools for possible rainfall scenarios generation. Rainfall scenarios of fine temporal scale reaching single minutes are indispensable as inputs for hydrological models. Assumption of probabilistic philosophy of drainage systems design and functioning leads to widespread application of hydrodynamic models in engineering practice. However models like these covering large areas could not be supplied with only uncorrelated point-rainfall time series. They should be rather supplied with space time rainfall scenarios displaying statistical properties of local natural rainfall fields. Implementation of a Space-Time Rainfall (STRAIN) model for hydrometeorological applications in Polish conditions, such as rainfall downscaling from the large scales of meteorological models to the scale of interest for rainfall-runoff processes is the long-distance aim of our research. As an introduction part of our study we verify the veracity of the following STRAIN model assumptions: rainfall fields are isotropic and statistically homogeneous in space; self-similarity holds (so that, after having rescaled the time by the advection velocity, rainfall is a fully homogeneous and isotropic process in the space-time domain); statistical properties of rainfall are characterized by an "a priori" known multifractal behavior. We conduct a space-time multifractal analysis on radar rainfall sequences selected from the Polish national radar system POLRAD. Radar rainfall sequences covering the area of 256 km x 256 km of original 2 km x 2 km spatial resolution and 15 minutes temporal resolution are used as study material. Attention is mainly focused on most severe summer convective rainfalls. It is shown that space-time rainfall can be considered with a good approximation to be a self-similar multifractal process. Multifractal analysis is carried out assuming Taylor's hypothesis to hold and the advection velocity needed to rescale the time dimension is assumed to be equal about 16 km/h. This assumption is verified by the analysis of autocorrelation functions along the x and y directions of "rainfall cubes" and along the time axis rescaled with assumed advection velocity. In general for analyzed rainfall sequences scaling is observed for spatial scales ranging from 4 to 256 km and for timescales from 15 min to 16 hours. However in most cases scaling break is identified for spatial scales between 4 and 8, corresponding to spatial dimensions of 16 km to 32 km. It is assumed that the scaling break occurrence at these particular scales in central Poland conditions could be at least partly explained by the rainfall mesoscale gap (on the edge of meso-gamma, storm-scale and meso-beta scale).

Detection of a sudden change of the field time series based on the Lorenz system.

PubMed

Da, ChaoJiu; Li, Fang; Shen, BingLu; Yan, PengCheng; Song, Jian; Ma, DeShan

2017-01-01

We conducted an exploratory study of the detection of a sudden change of the field time series based on the numerical solution of the Lorenz system. First, the time when the Lorenz path jumped between the regions on the left and right of the equilibrium point of the Lorenz system was quantitatively marked and the sudden change time of the Lorenz system was obtained. Second, the numerical solution of the Lorenz system was regarded as a vector; thus, this solution could be considered as a vector time series. We transformed the vector time series into a time series using the vector inner product, considering the geometric and topological features of the Lorenz system path. Third, the sudden change of the resulting time series was detected using the sliding t-test method. Comparing the test results with the quantitatively marked time indicated that the method could detect every sudden change of the Lorenz path, thus the method is effective. Finally, we used the method to detect the sudden change of the pressure field time series and temperature field time series, and obtained good results for both series, which indicates that the method can apply to high-dimension vector time series. Mathematically, there is no essential difference between the field time series and vector time series; thus, we provide a new method for the detection of the sudden change of the field time series.

Using GPS Imaging to Unravel Vertical Land Motions in the Interior Pacific Northwest

NASA Astrophysics Data System (ADS)

Overacker, J.; Hammond, W. C.; Kraner, M.; Blewitt, G.

2017-12-01

GPS Imaging uses robust trends in time series of GPS positions to create a velocity field that can reveal rates and patterns of vertical motions that would be otherwise difficult to detect. We have constructed an image of vertical land velocities within the interior Pacific Northwest region of the United States using GPS Imaging. The image shows a 50-250 km wide swath of approximately 2 mm/yr of subsidence seemingly unrelated to topographic features of the region. The extent of the signal roughly corresponds to the Juan de Fuca plate subduction latitudes and longitude of the Cascade arc. This suggests that the signal could be associated with ongoing crustal deformation possibly related to plate-scale geodynamic forces arising from interseismic coupling, long term plate boundary tractions, volcanic loading, and/or mantle flow. However, hydrological loading from accumulating precipitation in the Cascades and in the region's groundwater basins, and possible effects from Glacial Isostatic Adjustment (GIA) near its hinge line cannot be discounted as potential contributors to the observed subsidence signal. Here we attempt to unravel the contributions of hydrological loading and GIA to the vertical GPS signal observed within the interior Pacific Northwest. In order to determine the non-tectonic contributions to the observed vertical GPS Image, we will examine how the subsidence rate changes over time using early and late period comparisons. GPS, GRACE, and climatic data will be used in conjunction to disentangle the hydrological effect from the GPS Image. GIA models of the Western Cordillera will be compared with the patterns in the GPS Image to assess whether the signal can be explained with current models of GIA. Our presentation will document the signals, uncertainties, and hypotheses for the possible mechanisms behind this subsidence and attempt to quantify their relation and contribution to the observed deformation signal. Figure 1: Pacific Northwest GPS Imaging result of vertical velocity field plotted over topographic relief map. Red is up, blue is down. GPS station locations are shown in green. Greatest amount of subsidence shown by GPS Imaging appear uncorrelated with topographic features.

[Establishing and applying of autoregressive integrated moving average model to predict the incidence rate of dysentery in Shanghai].

PubMed

Li, Jian; Wu, Huan-Yu; Li, Yan-Ting; Jin, Hui-Ming; Gu, Bao-Ke; Yuan, Zheng-An

2010-01-01

To explore the feasibility of establishing and applying of autoregressive integrated moving average (ARIMA) model to predict the incidence rate of dysentery in Shanghai, so as to provide the theoretical basis for prevention and control of dysentery. ARIMA model was established based on the monthly incidence rate of dysentery of Shanghai from 1990 to 2007. The parameters of model were estimated through unconditional least squares method, the structure was determined according to criteria of residual un-correlation and conclusion, and the model goodness-of-fit was determined through Akaike information criterion (AIC) and Schwarz Bayesian criterion (SBC). The constructed optimal model was applied to predict the incidence rate of dysentery of Shanghai in 2008 and evaluate the validity of model through comparing the difference of predicted incidence rate and actual one. The incidence rate of dysentery in 2010 was predicted by ARIMA model based on the incidence rate from January 1990 to June 2009. The model ARIMA (1, 1, 1) (0, 1, 2)(12) had a good fitness to the incidence rate with both autoregressive coefficient (AR1 = 0.443) during the past time series, moving average coefficient (MA1 = 0.806) and seasonal moving average coefficient (SMA1 = 0.543, SMA2 = 0.321) being statistically significant (P < 0.01). AIC and SBC were 2.878 and 16.131 respectively and predicting error was white noise. The mathematic function was (1-0.443B) (1-B) (1-B(12))Z(t) = (1-0.806B) (1-0.543B(12)) (1-0.321B(2) x 12) micro(t). The predicted incidence rate in 2008 was consistent with the actual one, with the relative error of 6.78%. The predicted incidence rate of dysentery in 2010 based on the incidence rate from January 1990 to June 2009 would be 9.390 per 100 thousand. ARIMA model can be used to fit the changes of incidence rate of dysentery and to forecast the future incidence rate in Shanghai. It is a predicted model of high precision for short-time forecast.

Duality between Time Series and Networks

PubMed Central

Campanharo, Andriana S. L. O.; Sirer, M. Irmak; Malmgren, R. Dean; Ramos, Fernando M.; Amaral, Luís A. Nunes.

2011-01-01

Studying the interaction between a system's components and the temporal evolution of the system are two common ways to uncover and characterize its internal workings. Recently, several maps from a time series to a network have been proposed with the intent of using network metrics to characterize time series. Although these maps demonstrate that different time series result in networks with distinct topological properties, it remains unclear how these topological properties relate to the original time series. Here, we propose a map from a time series to a network with an approximate inverse operation, making it possible to use network statistics to characterize time series and time series statistics to characterize networks. As a proof of concept, we generate an ensemble of time series ranging from periodic to random and confirm that application of the proposed map retains much of the information encoded in the original time series (or networks) after application of the map (or its inverse). Our results suggest that network analysis can be used to distinguish different dynamic regimes in time series and, perhaps more importantly, time series analysis can provide a powerful set of tools that augment the traditional network analysis toolkit to quantify networks in new and useful ways. PMID:21858093

Principal Component Analysis in the Spectral Analysis of the Dynamic Laser Speckle Patterns

NASA Astrophysics Data System (ADS)

Ribeiro, K. M.; Braga, R. A., Jr.; Horgan, G. W.; Ferreira, D. D.; Safadi, T.

2014-02-01

Dynamic laser speckle is a phenomenon that interprets an optical patterns formed by illuminating a surface under changes with coherent light. Therefore, the dynamic change of the speckle patterns caused by biological material is known as biospeckle. Usually, these patterns of optical interference evolving in time are analyzed by graphical or numerical methods, and the analysis in frequency domain has also been an option, however involving large computational requirements which demands new approaches to filter the images in time. Principal component analysis (PCA) works with the statistical decorrelation of data and it can be used as a data filtering. In this context, the present work evaluated the PCA technique to filter in time the data from the biospeckle images aiming the reduction of time computer consuming and improving the robustness of the filtering. It was used 64 images of biospeckle in time observed in a maize seed. The images were arranged in a data matrix and statistically uncorrelated by PCA technique, and the reconstructed signals were analyzed using the routine graphical and numerical methods to analyze the biospeckle. Results showed the potential of the PCA tool in filtering the dynamic laser speckle data, with the definition of markers of principal components related to the biological phenomena and with the advantage of fast computational processing.

Perturbations from cosmic strings in cold dark matter

NASA Technical Reports Server (NTRS)

Albrecht, Andreas; Stebbins, Albert

1992-01-01

A systematic linear analysis of the perturbations induced by cosmic strings in cold dark matter is presented. The power spectrum is calculated and it is found that the strings produce a great deal of power on small scales. It is shown that the perturbations on interesting scales are the result of many uncorrelated string motions, which indicates a much more Gaussian distribution than was previously supposed.

STATLIB: NSWC Library of Statistical Programs and Subroutines

DTIC Science & Technology

1989-08-01

Uncorrelated Weighted Polynomial Regression 41 .WEPORC Correlated Weighted Polynomial Regression 45 MROP Multiple Regression Using Orthogonal Polynomials ...could not and should not be con- NSWC TR 89-97 verted to the new general purpose computer (the current CDC 995). Some were designed tu compute...personal computers. They are referred to as SPSSPC+, BMDPC, and SASPC and in general are less comprehensive than their mainframe counterparts. The basic

A Direct Method for Obtaining Approximate Standard Error and Confidence Interval of Maximal Reliability for Composites with Congeneric Measures

ERIC Educational Resources Information Center

Raykov, Tenko; Penev, Spiridon

2006-01-01

Unlike a substantial part of reliability literature in the past, this article is concerned with weighted combinations of a given set of congeneric measures with uncorrelated errors. The relationship between maximal coefficient alpha and maximal reliability for such composites is initially dealt with, and it is shown that the former is a lower…

Manifold Learning for 3D Shape Description and Classification

DTIC Science & Technology

2014-06-09

sportswear, personal protection clothing and equipment, office and health care device, etc. Therefore it is desirable to develop an effective shape...Modeling Figure 2: Toy example for submanifold decomposition. (a) The original data on the top are fused by two uncorrelated manifolds, blue and red... developed which is effective to extract two linear submanifolds. We demonstrated that comparing with existing manifold learning methods that only

Perturbations from cosmic strings in cold dark matter

NASA Technical Reports Server (NTRS)

Albrecht, Andreas; Stebbins, Albert

1991-01-01

A systematic linear analysis of the perturbations induced by cosmic strings in cold dark matter is presented. The power spectrum is calculated and it is found that the strings produce a great deal of power on small scales. It is shown that the perturbations on interesting scales are the result of many uncorrelated string motions, which indicates a much more Gaussian distribution than was previously supposed.

How avian nest site selection responds to predation risk: Testing an 'adaptive peak hypothesis'

Treesearch

Quresh S. Latif; Sacha K. Heath; John T. Rotenberry

2012-01-01

1. Nest predation limits avian fitness, so birds should favour nest sites that minimize predation risk. Nevertheless, preferred nest microhabitat features are often uncorrelated with apparent variation in predation rates. 2. This lack of congruence between theory-based expectation and empirical data may arise when birds already occupy ‘adaptive peaks’. If birds nest...

Verbal and Math Self-Concepts: An Extension of the Internal/External Frame of Reference Model.

ERIC Educational Resources Information Center

Marsh, Herbert W.; Byrne, Barbara M.

The internal/external (I/E) frame of reference model describes relations among Verbal self-concept (VSC), Math self-concept (MSC), and corresponding achievement scores (VACH, MACH). In support of the model Marsh (1986) found that: (1) VSC and MSC were nearly uncorrelated; (2) the effect of VACH on VSC, and of MACH on MSC, were positive; but (3)…

An Expert System for Processing Uncorrelated Satellite Tracks

DTIC Science & Technology

1992-12-17

earthworms with much intellect e\\en though they routinely carry out this same function. One definition given artificial intelligence is "the study of mental...Networks: Benchmarking Studies ," Proceedings from the IEEE International Conference on Neural Networkv. pp. 64-65, 1988. 229 Lyddane, R., "Small...reverse if necessary and rdenqtl_ by block number, Field Group Subgroup Artificial Intelligence, Expert Systems, Neural Networks. Orbital Mechanics

Effect of genomic long-range correlations on DNA persistence length: from theory to single molecule experiments.

PubMed

Moukhtar, Julien; Faivre-Moskalenko, Cendrine; Milani, Pascale; Audit, Benjamin; Vaillant, Cedric; Fontaine, Emeline; Mongelard, Fabien; Lavorel, Guillaume; St-Jean, Philippe; Bouvet, Philippe; Argoul, Françoise; Arneodo, Alain

2010-04-22

Sequence dependency of DNA intrinsic bending properties has been emphasized as a possible key ingredient to in vivo chromatin organization. We use atomic force microscopy (AFM) in air and liquid to image intrinsically straight (synthetic), uncorrelated (hepatitis C RNA virus) and persistent long-range correlated (human) DNA fragments in various ionic conditions such that the molecules freely equilibrate on the mica surface before being captured in a particular conformation. 2D thermodynamic equilibrium is experimentally verified by a detailed statistical analysis of the Gaussian nature of the DNA bend angle fluctuations. We show that the worm-like chain (WLC) model, commonly used to describe the average conformation of long semiflexible polymers, reproduces remarkably well the persistence length estimates for the first two molecules as consistently obtained from (i) mean square end-to-end distance measurement and (ii) mean projection of the end-to-end vector on the initial orientation. Whatever the operating conditions (air or liquid, concentration of metal cations Mg(2+) and/or Ni(2+)), the persistence length found for the uncorrelated viral DNA underestimates the value obtained for the straight DNA. We show that this systematic difference is the signature of the presence of an uncorrelated structural intrinsic disorder in the hepatitis C virus (HCV) DNA fragment that superimposes on local curvatures induced by thermal fluctuations and that only the entropic disorder depends upon experimental conditions. In contrast, the WLC model fails to describe the human DNA conformations. We use a mean-field extension of the WLC model to account for the presence of long-range correlations (LRC) in the intrinsic curvature disorder of human genomic DNA: the stronger the LRC, the smaller the persistence length. The comparison of AFM imaging of human DNA with LRC DNA simulations confirms that the rather small mean square end-to-end distance observed, particularly for G+C-rich human DNA molecules, more likely results from a large-scale intrinsic curvature due to a persistent distribution of DNA curvature sites than from some increased flexibility.

Attenuation and velocity dispersion in the exploration seismic frequency band

NASA Astrophysics Data System (ADS)

Sun, Langqiu

In an anelastic medium, seismic waves are distorted by attenuation and velocity dispersion, which depend on petrophysical properties of reservoir rocks. The effective attenuation and velocity dispersion is a combination of intrinsic attenuation and apparent attenuation due to scattering, transmission response, and data acquisition system. Velocity dispersion is usually neglected in seismic data processing partly because of insufficient observations in the exploration seismic frequency band. This thesis investigates the methods of measuring velocity dispersion in the exploration seismic frequency band and interprets the velocity dispersion data in terms of petrophysical properties. Broadband, uncorrelated vibrator data are suitable for measuring velocity dispersion in the exploration seismic frequency band, and a broad bandwidth optimizes the observability of velocity dispersion. Four methods of measuring velocity dispersion in uncorrelated vibrator VSP data are investigated, which are the sliding window crosscorrelation (SWCC) method, the instantaneous phase method, the spectral decomposition method, and the cross spectrum method. Among them, the SWCC method is a new method and has satisfactory robustness, accuracy, and efficiency. Using the SWCC method, velocity dispersion is measured in the uncorrelated vibrator VSP data from three areas with different geological settings, i.e., Mallik gas hydrate zone, McArthur River uranium mines, and Outokumpu crystalline rocks. The observed velocity dispersion is fitted to a straight line with respect to log frequency for a constant (frequency-independent) Q value. This provides an alternative method for calculating Q. A constant Q value does not directly link to petrophysical properties. A modeling study is implemented for the Mallik and McArthur River data to interpret the velocity dispersion observations in terms of petrophysical properties. The detailed multi-parameter petrophysical reservoir models are built according to the well logs; the models' parameters are adjusted by fitting the synthetic data to the observed data. In this way, seismic attenuation and velocity dispersion provide new insight into petrophysics properties at the Mallik and McArthur River sites. Potentially, observations of attenuation and velocity dispersion in the exploration seismic frequency band can improve the deconvolution process for vibrator data, Q-compensation, near-surface analysis, and first break picking for seismic data.

Detection of a sudden change of the field time series based on the Lorenz system

PubMed Central

Li, Fang; Shen, BingLu; Yan, PengCheng; Song, Jian; Ma, DeShan

2017-01-01

We conducted an exploratory study of the detection of a sudden change of the field time series based on the numerical solution of the Lorenz system. First, the time when the Lorenz path jumped between the regions on the left and right of the equilibrium point of the Lorenz system was quantitatively marked and the sudden change time of the Lorenz system was obtained. Second, the numerical solution of the Lorenz system was regarded as a vector; thus, this solution could be considered as a vector time series. We transformed the vector time series into a time series using the vector inner product, considering the geometric and topological features of the Lorenz system path. Third, the sudden change of the resulting time series was detected using the sliding t-test method. Comparing the test results with the quantitatively marked time indicated that the method could detect every sudden change of the Lorenz path, thus the method is effective. Finally, we used the method to detect the sudden change of the pressure field time series and temperature field time series, and obtained good results for both series, which indicates that the method can apply to high-dimension vector time series. Mathematically, there is no essential difference between the field time series and vector time series; thus, we provide a new method for the detection of the sudden change of the field time series. PMID:28141832

Performance monitoring during associative learning and its relation to obsessive-compulsive characteristics.

PubMed

Doñamayor, Nuria; Dinani, Jakob; Römisch, Manuel; Ye, Zheng; Münte, Thomas F

2014-10-01

Neural responses to performance errors and external feedback have been suggested to be altered in obsessive-compulsive disorder. In the current study, an associative learning task was used in healthy participants assessed for obsessive-compulsive symptoms by the OCI-R questionnaire. The task included a condition with equivocal feedback that did not inform about the participants' performance. Following incorrect responses, an error-related negativity and an error positivity were observed. In the feedback phase, the largest feedback-related negativity was observed following equivocal feedback. Theta and beta oscillatory components were found following incorrect and correct responses, respectively, and an increase in theta power was associated with negative and equivocal feedback. Changes over time were also explored as an indicator for possible learning effects. Finally, event-related potentials and oscillatory components were found to be uncorrelated with OCI-R scores in the current non-clinical sample. Copyright © 2014 Elsevier B.V. All rights reserved.

Dielectric spectroscopy of polymer-metal composites across the percolation threshold

NASA Astrophysics Data System (ADS)

Panda, Maheswar; Srinivas, V.; Thakur, A. K.

2014-11-01

Polymer (polar/nonpolar)/metal composites (PMC) were prepared under different process conditions. In polar PMC, dipolar relaxation plays a predominant role below percolation threshold (fc) and anomalous low frequency dispersion (ALFD) becomes dominant above fc while ALFD is the only likely possibility for nonpolar PMC above fc. The magnitude of relaxation exponents "m", "p" and "n", evaluated from the experimental results using Jonscher's universal dielectric response (JUDR) laws, falls within the universal limit [0, 1] with additional feature of strong dependence on volume fraction of conductor (fcon). The decrease in the relaxation exponent "m" with an increase of fcon is directly linked with decrease in the number of dipoles of the polymer in the composite and is accompanied by a distribution of relaxation time due to increased heterogeneity of the system. The magnitude of the relaxation exponent "n" decreases at fc, due to the prevalence of Maxwell-Wagner-Sillar polarization contributed by uncorrelated electrons.

Coordinated ultraviolet and radio observations of selected nearby stars

NASA Technical Reports Server (NTRS)

Lang, Kenneth R.

1987-01-01

All of the US2 shifts assigned were successfully completed with simultaneous International Ultraviolet Explorer (IUE) and the Very Large Array (VLA) observations of the proposed target stars. The target stars included dwarf M flare stars and RS CVn stars. The combined ultraviolet (IUE) and microwave (VLA) observations have provided important new insights to the radiation mechanisms at these two widely-separated regions of the electromagnetic spectrum. The VLA results included the discovery of narrow-band microwave radiation and rapid time variations in the microwave radiation of dwarf M flare stars. The results indicate that conventional radiation mechanisms cannot explain the microwave emission from these stars. In general, ultraviolet variations and bursts occur when no similar variations are detected at microwave wavelengths and vice versa. Although these is some overlap, the variations in these two spectral regions are usually uncorrelated, suggesting that there is little interaction between the activity centers at the two associated atmospheric levels.

Rigidity in gender-typed behaviors in early childhood: a longitudinal study of ethnic minority children.

PubMed

Halim, May Ling; Ruble, Diane; Tamis-LeMonda, Catherine; Shrout, Patrick E

2013-01-01

A key prediction of cognitive theories of gender development concerns developmental trajectories in the relative strength or rigidity of gender typing. To examine these trajectories in early childhood, 229 children (African American, Mexican American, and Dominican American) were followed annually from age 3 to 5 years, and gender-stereotypical appearance, dress-up play, toy play, and sex segregation were examined. High gender-typing was found across ethnic groups, and most behaviors increased in rigidity, especially from age 3 to 4 years. In addressing controversy surrounding the stability and structure of gender-typing it was found that from year to year, most behaviors showed moderately stable individual differences. Behaviors were uncorrelated within age but showed more concordance in change across time, suggesting that aspects of gender-typing are multidimensional, but still show coherence. © 2013 The Authors. Child Development © 2013 Society for Research in Child Development, Inc.

Hierarchical Learning Induces Two Simultaneous, But Separable, Prediction Errors in Human Basal Ganglia

PubMed Central

Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew

2013-01-01

Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously. PMID:23536092

Photon entanglement signatures in difference-frequency-generation

PubMed Central

Roslyak, Oleksiy; Mukamel, Shaul

2010-01-01

In response to quantum optical fields, pairs of molecules generate coherent nonlinear spectroscopy signals. Homodyne signals are given by sums over terms each being a product of Liouville space pathways of the pair of molecules times the corresponding optical field correlation function. For classical fields all field correlation functions may be factorized and become identical products of field amplitudes. The signal is then given by the absolute square of a susceptibility which in turn is a sum over pathways of a single molecule. The molecular pathways of different molecules in the pair are uncorrelated in this case (each path of a given molecule can be accompanied by any path of the other). However, entangled photons create an entanglement between the molecular pathways. We use the superoperator nonequlibrium Green’s functions formalism to demonstrate the signatures of this pathway-entanglement in the difference frequency generation signal. Comparison is made with an analogous incoherent two-photon fluorescence signal. PMID:19158927

The effect of dropout on the efficiency of D-optimal designs of linear mixed models.

PubMed

Ortega-Azurduy, S A; Tan, F E S; Berger, M P F

2008-06-30

Dropout is often encountered in longitudinal data. Optimal designs will usually not remain optimal in the presence of dropout. In this paper, we study D-optimal designs for linear mixed models where dropout is encountered. Moreover, we estimate the efficiency loss in cases where a D-optimal design for complete data is chosen instead of that for data with dropout. Two types of monotonically decreasing response probability functions are investigated to describe dropout. Our results show that the location of D-optimal design points for the dropout case will shift with respect to that for the complete and uncorrelated data case. Owing to this shift, the information collected at the D-optimal design points for the complete data case does not correspond to the smallest variance. We show that the size of the displacement of the time points depends on the linear mixed model and that the efficiency loss is moderate.

Development and validation of the Single Item Narcissism Scale (SINS).

PubMed

Konrath, Sara; Meier, Brian P; Bushman, Brad J

2014-01-01

The narcissistic personality is characterized by grandiosity, entitlement, and low empathy. This paper describes the development and validation of the Single Item Narcissism Scale (SINS). Although the use of longer instruments is superior in most circumstances, we recommend the SINS in some circumstances (e.g. under serious time constraints, online studies). In 11 independent studies (total N = 2,250), we demonstrate the SINS' psychometric properties. The SINS is significantly correlated with longer narcissism scales, but uncorrelated with self-esteem. It also has high test-retest reliability. We validate the SINS in a variety of samples (e.g., undergraduates, nationally representative adults), intrapersonal correlates (e.g., positive affect, depression), and interpersonal correlates (e.g., aggression, relationship quality, prosocial behavior). The SINS taps into the more fragile and less desirable components of narcissism. The SINS can be a useful tool for researchers, especially when it is important to measure narcissism with constraints preventing the use of longer measures.

Solution to urn models of pairwise interaction with application to social, physical, and biological sciences

NASA Astrophysics Data System (ADS)

Pickering, William; Lim, Chjan

2017-07-01

We investigate a family of urn models that correspond to one-dimensional random walks with quadratic transition probabilities that have highly diverse applications. Well-known instances of these two-urn models are the Ehrenfest model of molecular diffusion, the voter model of social influence, and the Moran model of population genetics. We also provide a generating function method for diagonalizing the corresponding transition matrix that is valid if and only if the underlying mean density satisfies a linear differential equation and express the eigenvector components as terms of ordinary hypergeometric functions. The nature of the models lead to a natural extension to interaction between agents in a general network topology. We analyze the dynamics on uncorrelated heterogeneous degree sequence networks and relate the convergence times to the moments of the degree sequences for various pairwise interaction mechanisms.

Singlet-to-triplet intermediates and triplet exciton dynamics in pentacene thinfilms

NASA Astrophysics Data System (ADS)

Thorsmolle, Verner; Korber, Michael; Obergfell, Emanuel; Kuhlman, Thomas; Campbell, Ian; Crone, Brian; Taylor, Antoinette; Averitt, Richard; Demsar, Jure

Singlet-to-triplet fission in organic semiconductors is a spin-conserving multiexciton process in which one spin-zero singlet excitation is converted into two spin-one triplet excitations on an ultrafast timescale. Current scientific interest into this carrier multiplication process is largely driven by prospects of enhancing the efficiency in photovoltaic applications by generating two long-lived triplet excitons by one photon. The fission process is known to involve intermediate states, known as correlated triplet pairs, with an overall singlet character, before being interchanged into uncorrelated triplets. Here we use broadband femtosecond real-time spectroscopy to study the excited state dynamics in pentacene thin films, elucidating the fission process and the role of intermediate triplet states. VKT and AJT acknowledge support by the LDRD program at Los Alamos National Laboratory and the Department of Energy, Grant No. DE-FG02-04ER118. MK, MO and JD acknowledge support by the Alexander von Humboldt Foundation.

Superdiffusive transport and energy localization in disordered granular crystals

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

Martinez, Alejandro J.; Kevrekidis, Panagiotis G.; Porter, Mason A.

We study the spreading of initially localized excitations in one-dimensional disordered granular crystals. We thereby investigate localization phenomena in strongly nonlinear systems, which we demonstrate to be fundamentally different from localization in linear and weakly nonlinear systems. We conduct a thorough comparison of wave dynamics in chains with three different types of disorder: an uncorrelated (Anderson-like) disorder and two types of correlated disorders (which are produced by random dimer arrangements), and for two families of initial conditions: displacement perturbations and velocity perturbations. We find for strongly precompressed (i.e., weakly nonlinear) chains that the dynamics strongly depends on the initial condition.more » Furthermore, for displacement perturbations, the long-time asymptotic behavior of the second moment m ~2 has oscillations that depend on the type of disorder, with a complex trend that is markedly different from a power law and which is particularly evident for an Anderson-like disorder.« less

Inclusion of electron correlation for the target wave function in low- to intermediate-energy e-N2 scattering

NASA Technical Reports Server (NTRS)

Weatherford, C. A.; Brown, F. B.; Temkin, A.

1987-01-01

In a recent calculation, an exact exchange method was developed for use in the partial-differential-equation approach to electron-molecule scattering and was applied to e-N2 scattering in the fixed-nuclei approximation with an adiabatic polarization potential at low energies (0-10 eV). Integrated elastic cross sections were calculated and found to be lower than experiment at energies both below and above the Pi(g) resonance. It was speculated at that time that improved experimental agreement could be obtained if a correlated target representation were used in place of the uncorrelated one. The present paper implements this suggestion and demonstrates the improved agreement. These calculations are also extended to higher energies (0-30 eV) so asd to include the Sigma(u) resonance. Some discrepancies among the experiments and between experiment and the various calculations at very low energy are noted.

The nature and perception of fluctuations in human musical rhythms

NASA Astrophysics Data System (ADS)

Hennig, Holger; Fleischmann, Ragnar; Fredebohm, Anneke; Hagmayer, York; Nagler, Jan; Witt, Annette; Theis, Fabian; Geisel, Theo

2012-02-01

Although human musical performances represent one of the most valuable achievements of mankind, the best musicians perform imperfectly. Musical rhythms are not entirely accurate and thus inevitably deviate from the ideal beat pattern. Nevertheless, computer generated perfect beat patterns are frequently devalued by listeners due to a perceived lack of human touch. Professional audio editing software therefore offers a humanizing feature which artificially generates rhythmic fluctuations. However, the built-in humanizing units are essentially random number generators producing only simple uncorrelated fluctuations. Here, for the first time, we establish long-range fluctuations as an inevitable natural companion of both simple and complex human rhythmic performances [1]. Moreover, we demonstrate that listeners strongly prefer long-range correlated fluctuations in musical rhythms. Thus, the favorable fluctuation type for humanizing interbeat intervals coincides with the one generically inherent in human musical performances. [1] HH et al., PLoS ONE,6,e26457 (2011)

Superdiffusive transport and energy localization in disordered granular crystals

DOE PAGES

Martinez, Alejandro J.; Kevrekidis, Panagiotis G.; Porter, Mason A.

2016-02-12

We study the spreading of initially localized excitations in one-dimensional disordered granular crystals. We thereby investigate localization phenomena in strongly nonlinear systems, which we demonstrate to be fundamentally different from localization in linear and weakly nonlinear systems. We conduct a thorough comparison of wave dynamics in chains with three different types of disorder: an uncorrelated (Anderson-like) disorder and two types of correlated disorders (which are produced by random dimer arrangements), and for two families of initial conditions: displacement perturbations and velocity perturbations. We find for strongly precompressed (i.e., weakly nonlinear) chains that the dynamics strongly depends on the initial condition.more » Furthermore, for displacement perturbations, the long-time asymptotic behavior of the second moment m ~2 has oscillations that depend on the type of disorder, with a complex trend that is markedly different from a power law and which is particularly evident for an Anderson-like disorder.« less

Thermal machines beyond the weak coupling regime

NASA Astrophysics Data System (ADS)

Gallego, R.; Riera, A.; Eisert, J.

2014-12-01

How much work can be extracted from a heat bath using a thermal machine? The study of this question has a very long history in statistical physics in the weak-coupling limit, when applied to macroscopic systems. However, the assumption that thermal heat baths remain uncorrelated with associated physical systems is less reasonable on the nano-scale and in the quantum setting. In this work, we establish a framework of work extraction in the presence of quantum correlations. We show in a mathematically rigorous and quantitative fashion that quantum correlations and entanglement emerge as limitations to work extraction compared to what would be allowed by the second law of thermodynamics. At the heart of the approach are operations that capture the naturally non-equilibrium dynamics encountered when putting physical systems into contact with each other. We discuss various limits that relate to known results and put our work into the context of approaches to finite-time quantum thermodynamics.

Multiple Indicator Stationary Time Series Models.

ERIC Educational Resources Information Center

Sivo, Stephen A.

2001-01-01

Discusses the propriety and practical advantages of specifying multivariate time series models in the context of structural equation modeling for time series and longitudinal panel data. For time series data, the multiple indicator model specification improves on classical time series analysis. For panel data, the multiple indicator model…

Efficient Algorithms for Segmentation of Item-Set Time Series

NASA Astrophysics Data System (ADS)

Chundi, Parvathi; Rosenkrantz, Daniel J.

We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.

How to test for partially predictable chaos.

PubMed

Wernecke, Hendrik; Sándor, Bulcsú; Gros, Claudius

2017-04-24

For a chaotic system pairs of initially close-by trajectories become eventually fully uncorrelated on the attracting set. This process of decorrelation can split into an initial exponential decrease and a subsequent diffusive process on the chaotic attractor causing the final loss of predictability. Both processes can be either of the same or of very different time scales. In the latter case the two trajectories linger within a finite but small distance (with respect to the overall extent of the attractor) for exceedingly long times and remain partially predictable. Standard tests for chaos widely use inter-orbital correlations as an indicator. However, testing partially predictable chaos yields mostly ambiguous results, as this type of chaos is characterized by attractors of fractally broadened braids. For a resolution we introduce a novel 0-1 indicator for chaos based on the cross-distance scaling of pairs of initially close trajectories. This test robustly discriminates chaos, including partially predictable chaos, from laminar flow. Additionally using the finite time cross-correlation of pairs of initially close trajectories, we are able to identify laminar flow as well as strong and partially predictable chaos in a 0-1 manner solely from the properties of pairs of trajectories.

Real-time vehicle noise cancellation techniques for gunshot acoustics

NASA Astrophysics Data System (ADS)

Ramos, Antonio L. L.; Holm, Sverre; Gudvangen, Sigmund; Otterlei, Ragnvald

2012-06-01

Acoustical sniper positioning systems rely on the detection and direction-of-arrival (DOA) estimation of the shockwave and the muzzle blast in order to provide an estimate of a potential snipers location. Field tests have shown that detecting and estimating the DOA of the muzzle blast is a rather difficult task in the presence of background noise sources, e.g., vehicle noise, especially in long range detection and absorbing terrains. In our previous work presented in the 2011 edition of this conference we highlight the importance of improving the SNR of the gunshot signals prior to the detection and recognition stages, aiming at lowering the false alarm and miss-detection rates and, thereby, increasing the reliability of the system. This paper reports on real-time noise cancellation techniques, like Spectral Subtraction and Adaptive Filtering, applied to gunshot signals. Our model assumes the background noise as being short-time stationary and uncorrelated to the impulsive gunshot signals. In practice, relatively long periods without signal occur and can be used to estimate the noise spectrum and its first and second order statistics as required in the spectral subtraction and adaptive filtering techniques, respectively. The results presented in this work are supported with extensive simulations based on real data.

Context-Dependent Duration Signals in the Primate Prefrontal Cortex

PubMed Central

Genovesio, Aldo; Seitz, Lucia K.; Tsujimoto, Satoshi; Wise, Steven P.

2016-01-01

The activity of some prefrontal (PF) cortex neurons distinguishes short from long time intervals. Here, we examined whether this property reflected a general timing mechanism or one dependent on behavioral context. In one task, monkeys discriminated the relative duration of 2 stimuli; in the other, they discriminated the relative distance of 2 stimuli from a fixed reference point. Both tasks had a pre-cue period (interval 1) and a delay period (interval 2) with no discriminant stimulus. Interval 1 elapsed before the presentation of the first discriminant stimulus, and interval 2 began after that stimulus. Both intervals had durations of either 400 or 800 ms. Most PF neurons distinguished short from long durations in one task or interval, but not in the others. When neurons did signal something about duration for both intervals, they did so in an uncorrelated or weakly correlated manner. These results demonstrate a high degree of context dependency in PF time processing. The PF, therefore, does not appear to signal durations abstractedly, as would be expected of a general temporal encoder, but instead does so in a highly context-dependent manner, both within and between tasks. PMID:26209845

A novel weight determination method for time series data aggregation

NASA Astrophysics Data System (ADS)

Xu, Paiheng; Zhang, Rong; Deng, Yong

2017-09-01

Aggregation in time series is of great importance in time series smoothing, predicting and other time series analysis process, which makes it crucial to address the weights in times series correctly and reasonably. In this paper, a novel method to obtain the weights in time series is proposed, in which we adopt induced ordered weighted aggregation (IOWA) operator and visibility graph averaging (VGA) operator and linearly combine the weights separately generated by the two operator. The IOWA operator is introduced to the weight determination of time series, through which the time decay factor is taken into consideration. The VGA operator is able to generate weights with respect to the degree distribution in the visibility graph constructed from the corresponding time series, which reflects the relative importance of vertices in time series. The proposed method is applied to two practical datasets to illustrate its merits. The aggregation of Construction Cost Index (CCI) demonstrates the ability of proposed method to smooth time series, while the aggregation of The Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX) illustrate how proposed method maintain the variation tendency of original data.

Association mining of dependency between time series

NASA Astrophysics Data System (ADS)

Hafez, Alaaeldin

2001-03-01

Time series analysis is considered as a crucial component of strategic control over a broad variety of disciplines in business, science and engineering. Time series data is a sequence of observations collected over intervals of time. Each time series describes a phenomenon as a function of time. Analysis on time series data includes discovering trends (or patterns) in a time series sequence. In the last few years, data mining has emerged and been recognized as a new technology for data analysis. Data Mining is the process of discovering potentially valuable patterns, associations, trends, sequences and dependencies in data. Data mining techniques can discover information that many traditional business analysis and statistical techniques fail to deliver. In this paper, we adapt and innovate data mining techniques to analyze time series data. By using data mining techniques, maximal frequent patterns are discovered and used in predicting future sequences or trends, where trends describe the behavior of a sequence. In order to include different types of time series (e.g. irregular and non- systematic), we consider past frequent patterns of the same time sequences (local patterns) and of other dependent time sequences (global patterns). We use the word 'dependent' instead of the word 'similar' for emphasis on real life time series where two time series sequences could be completely different (in values, shapes, etc.), but they still react to the same conditions in a dependent way. In this paper, we propose the Dependence Mining Technique that could be used in predicting time series sequences. The proposed technique consists of three phases: (a) for all time series sequences, generate their trend sequences, (b) discover maximal frequent trend patterns, generate pattern vectors (to keep information of frequent trend patterns), use trend pattern vectors to predict future time series sequences.

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.

Statistical process control of cocrystallization processes: A comparison between OPLS and PLS.

PubMed

Silva, Ana F T; Sarraguça, Mafalda Cruz; Ribeiro, Paulo R; Santos, Adenilson O; De Beer, Thomas; Lopes, João Almeida

2017-03-30

Orthogonal partial least squares regression (OPLS) is being increasingly adopted as an alternative to partial least squares (PLS) regression due to the better generalization that can be achieved. Particularly in multivariate batch statistical process control (BSPC), the use of OPLS for estimating nominal trajectories is advantageous. In OPLS, the nominal process trajectories are expected to be captured in a single predictive principal component while uncorrelated variations are filtered out to orthogonal principal components. In theory, OPLS will yield a better estimation of the Hotelling's T 2 statistic and corresponding control limits thus lowering the number of false positives and false negatives when assessing the process disturbances. Although OPLS advantages have been demonstrated in the context of regression, its use on BSPC was seldom reported. This study proposes an OPLS-based approach for BSPC of a cocrystallization process between hydrochlorothiazide and p-aminobenzoic acid monitored on-line with near infrared spectroscopy and compares the fault detection performance with the same approach based on PLS. A series of cocrystallization batches with imposed disturbances were used to test the ability to detect abnormal situations by OPLS and PLS-based BSPC methods. Results demonstrated that OPLS was generally superior in terms of sensibility and specificity in most situations. In some abnormal batches, it was found that the imposed disturbances were only detected with OPLS. Copyright © 2017 Elsevier B.V. All rights reserved.

Pliocene-Quaternary tectonic evolution of the Gulf of Gökova, southwest Turkey

NASA Astrophysics Data System (ADS)

Tur, Hüseyin; Yaltırak, Cenk; Elitez, İrem; Sarıkavak, Kerim Tuncer

2015-01-01

Evolution of the east-west-trending Gökova Graben structure is related to the north-south extension of the Aegean segment of the Aegean-Anatolian Microplate. The Pliocene-Quaternary successions surrounding the onland portion of the Gökova Graben as well as coeval successions within the marine portion of the graben are cut by at least three families of faults that strike northwest-southeast, east-west and east-northeast-west-southwest. These orientations are inconsistent with a simple north-south extensional regime. Interpretation of seismic reflection profiles, multibeam bathymetry and GPS vectors indicates that the Gökova Graben developed as a lazy-S-shaped graben in the back-arc setting north of the Hellenic Arc. A counterclockwise rotation of the Aegean segment of the Aegean-Anatolian Microplate is the suggested mechanism for this geometry, as subduction zone rolled back occurred during the Pliocene-Quaternary. The Gulf of Gökova is the youngest of a series of basins that developed within this large back-arc system, including the Nisyros, Karpathos, and Kamilonisi basins, collectively named to as the Gökova-Nisyros-Karpathos Graben. It is proposed that this graben experienced a scissor-like opening initiating from the west during the Pliocene and progressing eastward during the Quaternary. Faults that are seemingly un-correlated onland and in the marine areas become remarkably aligned when the Marmaris-Rhodes Block is progressively rotated by 6° counterclockwise relative to the Muğla Block using a pole position located within the Gulf of Gökova. The scissor-like opening of the westernmost regions of the Gökova Graben likely occurred during the late Pliocene, whereas the central and eastern portions of the graben developed during the early-middle Pleistocene and late Pleistocene-Holocene, respectively. The onset of the opening of the westernmost segment of the Gökova-Nisyros-Karpathos Graben occurred at a time earlier than the late Pliocene.

Seasonal Variability of Saturn's Atmosphere

NASA Technical Reports Server (NTRS)

Yanamandra-Fisher, Padma A.; Simon, Amy; Delcroix, Marc; Orton, Glenn S.; Trinh, Shirley

2012-01-01

The seasonal variability of Saturn's clouds and weather layer, currently displaying a variety of phenomena (convective storms, planetary waves, giant storms and lightning-induced events, etc.) is not yet fully understood. Variations of Saturn's radiance at 5.2 microns, a spectral region dominated by thermal emission in an atmospheric window containing weak gaseous absorption, contain a strong axisymmetric component as well as large discrete features at low and mid-latitudes that are several degrees colder than the planetary average and uncorrelated with features at shorter wavelengths that are dominated by reflected sunlight (Yanamandra-Fisher et al., 2001. Icarus, Vol. 150). The characterization of several fundamental atmospheric properties and processes, however, remains incomplete, namely: How do seasons affect (a) the global distribution of gaseous constituents and aerosols; and (b) temperatures and the stability against convection and large scale-atmospheric transport? Do 5-micron clouds have counterparts at other altitude levels? What changes occur during the emergence of Great White Storms? Data acquired at the NASA/IRTF and NAOJ/Subaru from 1995 - 2011; since 2004, high-resolution multi-spectral and high-spatial imaging data acquired by the NASA/ESA Cassini mission, represents half a Saturnian year or two seasons. With the addition of detailed multi-spectral data sets acquired by amateur observers, we study these dramatic phenomena to better understand the timeline of the evolution of these events. Seasonal (or temporal) trends in the observables such as albedo of the clouds, thermal fields of the atmosphere as function of altitude, development of clouds, hazes and global abundances of various hydrocarbons in the atmosphere can now be modeled. We will present results of our ongoing investigation for the search and characterization of periodicities over half a Saturnian year, based on a non-biased a priori approach and time series techniques (such as Principal Component Analysis, PCA and Lomb-Scargle periodograms, LSP).

Antarctic Circumpolar Current Transport Variability during 2003-05 from GRACE

NASA Technical Reports Server (NTRS)

Zlotnicki, Victor; Wahr, John; Fukumori, Ichiro; Song, Yuhe T.

2006-01-01

Gravity Recovery and Climate Experiment (GRACE) gravity data spanning January 2003 - November 2005 are used as proxies for ocean bottom pressure (BP) averaged over 1 month, spherical Gaussian caps 500 km in radius, and along paths bracketing the Antarctic Circumpolar Current's various fronts. The GRACE BP signals are compared with those derived from the Estimating the Circulation and Climate of the Ocean (ECCO) ocean modeling-assimilation system, and to a non-Boussinesq version of the Regional Ocean Model System (ROMS). The discrepancy found between GRACE and the models is 1.7 cm(sub H2O) (1 cm(sub H2O) similar to 1 hPa), slightly lower than the 1.9 cm(sub H2O) estimated by the authors independently from propagation of GRACE errors. The northern signals are weak and uncorrelated among basins. The southern signals are strong, with a common seasonality. The seasonal cycle GRACE data observed in the Pacific and Indian Ocean sectors of the ACC are consistent, with annual and semiannual amplitudes of 3.6 and 0.6 cm(sub H2O) (1.1 and 0.6 cm(sub H2O) with ECCO), the average over the full southern path peaks (stronger ACC) in the southern winter, on days of year 197 and 97 for the annual and semiannual components, respectively; the Atlantic Ocean annual peak is 20 days earlier. An approximate conversion factor of 3.1 Sv ( Sv equivalent to 10(exp 6) m(exp 3) s(exp -1)) of barotropic transport variability per cm(sub H2O) of BP change is estimated. Wind stress data time series from the Quick Scatterometer (QuikSCAT), averaged monthly, zonally, and over the latitude band 40 de - 65 deg S, are also constructed and subsampled at the same months as with the GRACE data. The annual and semiannual harmonics of the wind stress peak on days 198 and 82, respectively. A decreasing trend over the 3 yr is observed in the three data types.

Antarctic Circumpolar Current Transport Variability during 2003-05 from GRACE

NASA Technical Reports Server (NTRS)

Zlotnicki, Victor; Wahr, John; Fukumori, Ichiro; Song, Yuhe T.

2007-01-01

Gravity Recovery and Climate Experiment (GRACE) gravity data spanning January 2003-November 2005 are used as proxies for ocean bottom pressure (BP) averaged over 1 month, spherical Gaussian caps 500 km in radius, and along paths bracketing the Antarctic Circumpolar Current's various fronts. The GRACE BP signals are compared with those derived from the Estimating the Circulation and Climate of the Ocean (ECCO) ocean modeling-assimilation system, and to a non-Boussinesq version of the Regional Ocean Model System (ROMS). The discrepancy found between GRACE and the models is 1.7 cmH2O (1 cmH2O approx. 1 hPa), slightly lower than the 1.9 cmH2O estimated by the authors independently from propagation of GRACE errors. The northern signals are weak and uncorrelated among basins. The southern signals are strong, with a common seasonality. The seasonal cycle GRACE data observed in the Pacific and Indian Ocean sectors of the ACC are consistent, with annual and semiannual amplitudes of 3.6 and 0.6 cmH2O (1.1 and 0.6 cmH2O with ECCO), the average over the full southern path peaks (stronger ACC) in the southern winter, on days of year 197 and 97 for the annual and semiannual components, respectively; the Atlantic Ocean annual peak is 20 days earlier. An approximate conversion factor of 3.1 Sv (Sv equiv 10(exp 6)cu m/s) of barotropic transport variability per cmH2O of BP change is estimated. Wind stress data time series from the Quick Scatterometer (QuikSCAT), averaged monthly, zonally, and over the latitude band 40(deg)- 65(deg)S, are also constructed and subsampled at the same months as with the GRACE data. The annual and semiannual harmonics of the wind stress peak on days 198 and 82, respectively. A decreasing trend over the 3 yr is observed in the three data types.

The effect of the East Atlantic pattern on the precipitation δ18O-NAO relationship in Europe

NASA Astrophysics Data System (ADS)

Comas-Bru, L.; McDermott, F.; Werner, M.

2016-10-01

The North Atlantic Oscillation (NAO) is known to influence precipitation δ18O (δ18Op) through its control on air temperature and on the trajectory of the westerly winds that carry moisture onto Europe during boreal winters. Hence, paleoclimate studies seeking to reconstruct the NAO can exploit the δ18O signal that is commonly preserved in natural archives such as stalagmites, ice cores, tree rings and lake sediments. However, such reconstructions should consider the uncertainties that arise from non-stationarities in the δ18Op-NAO relationship. Here, new insights into the causes of these temporal non-stationarities are presented for the European region using both observations (GNIP database) and the output of an isotope-enabled general circulation model (ECHAM5-wiso). The results show that, although the East Atlantic (EA) pattern is generally uncorrelated to δ18Op during the instrumental period, its polarity affects the δ18Op-NAO relationship. Non-stationarities in this relationship result from spatial shifts of the δ18Op-NAO correlated areas as a consequence of different NAO/EA combinations. These shifts are consistent with those reported previously for NAO-winter climate variables and the resulting non-stationarities mean that δ18O-based NAO reconstructions could be compromised if the balance of positive and negative NAO/EA states differs substantially in a calibration period compared with the period of interest in the past. The same approach has been followed to assess the relationships between δ18Op and both winter total precipitation and winter mean surface air temperature, with similar results. Crucially, this study also identifies regions within Europe where temporal changes in the NAO, air temperature and precipitation can be more robustly reconstructed using δ18O time series from natural archives, irrespective of concomitant changes in the EA.

Updating Landsat time series of surface-reflectance composites and forest change products with new observations

NASA Astrophysics Data System (ADS)

Hermosilla, Txomin; Wulder, Michael A.; White, Joanne C.; Coops, Nicholas C.; Hobart, Geordie W.

2017-12-01

The use of time series satellite data allows for the temporally dense, systematic, transparent, and synoptic capture of land dynamics over time. Subsequent to the opening of the Landsat archive, several time series approaches for characterizing landscape change have been developed, often representing a particular analytical time window. The information richness and widespread utility of these time series data have created a need to maintain the currency of time series information via the addition of new data, as it becomes available. When an existing time series is temporally extended, it is critical that previously generated change information remains consistent, thereby not altering reported change statistics or science outcomes based on that change information. In this research, we investigate the impacts and implications of adding additional years to an existing 29-year annual Landsat time series for forest change. To do so, we undertook a spatially explicit comparison of the 29 overlapping years of a time series representing 1984-2012, with a time series representing 1984-2016. Surface reflectance values, and presence, year, and type of change were compared. We found that the addition of years to extend the time series had minimal effect on the annual surface reflectance composites, with slight band-specific differences (r ≥ 0.1) in the final years of the original time series being updated. The area of stand replacing disturbances and determination of change year are virtually unchanged for the overlapping period between the two time-series products. Over the overlapping temporal period (1984-2012), the total area of change differs by 0.53%, equating to an annual difference in change area of 0.019%. Overall, the spatial and temporal agreement of the changes detected by both time series was 96%. Further, our findings suggest that the entire pre-existing historic time series does not need to be re-processed during the update process. Critically, given the time series change detection and update approach followed here, science outcomes or reports representing one temporal epoch can be considered stable and will not be altered when a time series is updated with newly available data.

Highly comparative time-series analysis: the empirical structure of time series and their methods.

PubMed

Fulcher, Ben D; Little, Max A; Jones, Nick S

2013-06-06

The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated time series, and over 9000 time-series analysis algorithms are analysed in this work. We introduce reduced representations of both time series, in terms of their properties measured by diverse scientific methods, and of time-series analysis methods, in terms of their behaviour on empirical time series, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for time-series classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine time series, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in time-series analysis for applications across the scientific disciplines.

Highly comparative time-series analysis: the empirical structure of time series and their methods

PubMed Central

Fulcher, Ben D.; Little, Max A.; Jones, Nick S.

2013-01-01

The process of collecting and organizing sets of observations represents a common theme throughout the history of science. However, despite the ubiquity of scientists measuring, recording and analysing the dynamics of different processes, an extensive organization of scientific time-series data and analysis methods has never been performed. Addressing this, annotated collections of over 35 000 real-world and model-generated time series, and over 9000 time-series analysis algorithms are analysed in this work. We introduce reduced representations of both time series, in terms of their properties measured by diverse scientific methods, and of time-series analysis methods, in terms of their behaviour on empirical time series, and use them to organize these interdisciplinary resources. This new approach to comparing across diverse scientific data and methods allows us to organize time-series datasets automatically according to their properties, retrieve alternatives to particular analysis methods developed in other scientific disciplines and automate the selection of useful methods for time-series classification and regression tasks. The broad scientific utility of these tools is demonstrated on datasets of electroencephalograms, self-affine time series, heartbeat intervals, speech signals and others, in each case contributing novel analysis techniques to the existing literature. Highly comparative techniques that compare across an interdisciplinary literature can thus be used to guide more focused research in time-series analysis for applications across the scientific disciplines. PMID:23554344

Molecular binoculars: how to spatially resolve environmental fluctuations by following two or more single-molecule spectral trails at a time.

PubMed

Lubchenko, Vassiliy; Silbey, Robert J

2013-10-24

We propose a novel type of spectral diffusion experiment that enables one to decouple spatial characteristics of the environmental fluctuations, such as their concentration, from the interaction with the chromophore. Traditional hole broadening experiments do not allow for such decoupling in the common case when the chromophore-environment interaction is scale invariant. Here we propose to simultaneously follow the spectral trails of a small number of nearby chromophores--two or more--which thereby sense a highly overlapping set of the fluctuations. To this end, we estimate the combined probability distribution for the frequencies of a set of chromophores contained within the same sample. The present setup introduces a new length scale, i.e., the interchromophore distance, which breaks the aforementioned scale invariance and enables one to determine independently the concentration of the environmental fluctuations and their coupling to the chromophores, by monitoring the time after which spectral diffusion of distinct chromophores becomes uncorrelated. We illustrate these results with structural excitations in low temperature glasses.

Measurement time and statistics for a noise thermometer with a synthetic-noise reference

NASA Astrophysics Data System (ADS)

White, D. R.; Benz, S. P.; Labenski, J. R.; Nam, S. W.; Qu, J. F.; Rogalla, H.; Tew, W. L.

2008-08-01

This paper describes methods for reducing the statistical uncertainty in measurements made by noise thermometers using digital cross-correlators and, in particular, for thermometers using pseudo-random noise for the reference signal. First, a discrete-frequency expression for the correlation bandwidth for conventional noise thermometers is derived. It is shown how an alternative frequency-domain computation can be used to eliminate the spectral response of the correlator and increase the correlation bandwidth. The corresponding expressions for the uncertainty in the measurement of pseudo-random noise in the presence of uncorrelated thermal noise are then derived. The measurement uncertainty in this case is less than that for true thermal-noise measurements. For pseudo-random sources generating a frequency comb, an additional small reduction in uncertainty is possible, but at the cost of increasing the thermometer's sensitivity to non-linearity errors. A procedure is described for allocating integration times to further reduce the total uncertainty in temperature measurements. Finally, an important systematic error arising from the calculation of ratios of statistical variables is described.

A Framework and Algorithms for Multivariate Time Series Analytics (MTSA): Learning, Monitoring, and Recommendation

ERIC Educational Resources Information Center

Ngan, Chun-Kit

2013-01-01

Making decisions over multivariate time series is an important topic which has gained significant interest in the past decade. A time series is a sequence of data points which are measured and ordered over uniform time intervals. A multivariate time series is a set of multiple, related time series in a particular domain in which domain experts…

A Review of Subsequence Time Series Clustering

PubMed Central

Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies. PMID:25140332

A review of subsequence time series clustering.

PubMed

Zolhavarieh, Seyedjamal; Aghabozorgi, Saeed; Teh, Ying Wah

2014-01-01

Clustering of subsequence time series remains an open issue in time series clustering. Subsequence time series clustering is used in different fields, such as e-commerce, outlier detection, speech recognition, biological systems, DNA recognition, and text mining. One of the useful fields in the domain of subsequence time series clustering is pattern recognition. To improve this field, a sequence of time series data is used. This paper reviews some definitions and backgrounds related to subsequence time series clustering. The categorization of the literature reviews is divided into three groups: preproof, interproof, and postproof period. Moreover, various state-of-the-art approaches in performing subsequence time series clustering are discussed under each of the following categories. The strengths and weaknesses of the employed methods are evaluated as potential issues for future studies.

Multiscale structure of time series revealed by the monotony spectrum.

PubMed

Vamoş, Călin

2017-03-01

Observation of complex systems produces time series with specific dynamics at different time scales. The majority of the existing numerical methods for multiscale analysis first decompose the time series into several simpler components and the multiscale structure is given by the properties of their components. We present a numerical method which describes the multiscale structure of arbitrary time series without decomposing them. It is based on the monotony spectrum defined as the variation of the mean amplitude of the monotonic segments with respect to the mean local time scale during successive averagings of the time series, the local time scales being the durations of the monotonic segments. The maxima of the monotony spectrum indicate the time scales which dominate the variations of the time series. We show that the monotony spectrum can correctly analyze a diversity of artificial time series and can discriminate the existence of deterministic variations at large time scales from the random fluctuations. As an application we analyze the multifractal structure of some hydrological time series.

Many behavioral tendencies associated with right-leaning (conservative) political ideologies are malleable and unrelated to negativity.

PubMed

Olivola, Christopher Y; Sussman, Abigail B

2014-06-01

Recent research has identified several judgment and decision making tendencies associated with right-leaning political ideologies that are difficult (if not impossible) to explain in terms of stable, negative affective appraisals because they (1) are uncorrelated with the negativity of the stimuli being considered, (2) do not reflect divergent affective evaluations, and (3) can be eliminated by superficial manipulations and interventions.

Lifted Turbulent Jet Flames

DTIC Science & Technology

1993-04-14

flame length L simultaneously with h, and measuring the visible radiation I simultaneously with h. L(t) was found to be nearly uncorrelated with h(t...variation of 7i/2 /76 with ýh. These experiments included measuring the flame length L simultaneously with h, and measuring the visible radiation I...Measurements of Liftoff Height and Flame Length ... 66 4.5 Simultaneous Measurements of Liftoff Height and Radiation ....... 71 4.6 D scussion

Uncorrelated Encounter Model of the National Airspace System, Version 2.0

DTIC Science & Technology

2013-08-19

can exist to certify avoidance systems for operational use. Evaluations typically include flight tests, operational impact studies, and simulation of...appropriate for large-scale air traffic impact studies— for example, examination of sector loading or conflict rates. The focus here includes two types of...between two IFR aircraft in oceanic airspace. The reason for this is that one cannot observe encounters of sufficient fidelity in the available data

Optical communication noise rejection using corelated photons

NASA Technical Reports Server (NTRS)

Jackson, D.; Hockney, G. M.; Dowling, J. P.

2002-01-01

This paper describes a completely new way to perform noise rejection using photons correlated through quantum entanglement to improve an optical communications link in the presence of uncorrelated noise. In particular, a detailed analysis is made of the case where a classical link would be saturated by an intense background, such as when a satellite is in front of the sun, and identifies where the quantum correlating system has superior performance.

Technical Report for the Period 1 October 1987 - 30 September 1989

DTIC Science & Technology

1990-03-01

low pass filter results. -dt dt specifies the sampling rate in seconds. -gin specifies .w file (binary waveform data) input. - gout specifies .w file...waves arriving at moderate incidence angles, * high signal-to-noise ratio (SNR). The following assumptions are made, for simplicity* * additive...spatially uncorrelated noise, * simple signal model, free of refraction and scattering effects. This study is limited to the case of a plane incident P

Motivation for HPV Vaccination Among Young Adult Men: Validation of TTM Decisional Balance and Self-Efficacy Constructs.

PubMed

Fernandez, Anne C; Amoyal, Nicole R; Paiva, Andrea L; Prochaska, James O

2016-01-01

In the United States, 36% of human papillomavirus (HPV)-related cancers occur among men. HPV vaccination can substantially reduce the risk of HPV infection; however, the vast majority of men are unvaccinated. This study developed and validated transtheoretical model-based measures for HPV vaccination in young adult men. Cross-sectional measurement development. Online survey of young adult men. Three hundred twenty-nine mostly college-attending men, ages 18 to 26. Stage of change, decisional balance (pros/cons), and self-efficacy. The sample was randomly split into halves for exploratory principal components analysis (PCA), followed by confirmatory factor analyses (CFA) to test measurement models. Multivariate analyses examined relationships between scales. For decisional balance, PCA revealed two uncorrelated five-item factors (pros α = .78; cons α = .83). For the self-efficacy scale, PCA revealed a single-factor solution (α = .83). CFA confirmed that the two-factor uncorrelated model for decisional balance and a single-factor model for self-efficacy. Follow-up analyses of variance supported the theoretically predicted relationships between stage of change, pros, and self-efficacy. This study resulted in reliable and valid measures of pros and self-efficacy for HPV vaccination that can be used in future clinical research.

Resonance interatomic energy in a Schwarzschild spacetime

NASA Astrophysics Data System (ADS)

Zhou, Wenting; Yu, Hongwei

2017-08-01

We study, in the Schwarzschild spacetime, the resonance interatomic energy (RIE) of two static identical atoms with an interatomic separation L along the radial direction and correlated by a symmetric/antisymmetric entangled state. The atoms are assumed to be coupled to massless scalar fields in the Boulware, Unruh, and Hartle-Hawking vacua, and approximate analytical results are obtained both at infinity and near the horizon. Our results show that at infinity, the RIE approaches that in a flat spacetime, while, near the horizon, they can deviate dramatically from each other. Besides, different from other atomic radiative properties such as the Lamb shift of a single atom or the interatomic energy between two uncorrelated atoms, which can be obviously affected by the thermal character of quantum fields, the RIE of two atoms in a symmetric/antisymmetric entangled state in the Boulware, Unruh, and Hartle-Hawking vacua are exactly the same as a result of the fact that the RIE of two such atoms depends only on the atomic self-reaction, i.e., it does not feel the vacuum fluctuations. This suggests that the RIE of two static atoms in a symmetric/antisymmetric entangled state outside a black hole is oblivious to the Hawking radiation, in contrast to those uncorrelated atoms.

Measurement of the top quark mass using single top quark events in proton-proton collisions at [Formula: see text] TeV.

PubMed

Sirunyan, A M; Tumasyan, A; Adam, W; Asilar, E; Bergauer, T; Brandstetter, J; Brondolin, E; Dragicevic, M; Erö, J; Flechl, M; Friedl, M; Frühwirth, R; Ghete, V M; Hartl, C; Hörmann, N; Hrubec, J; Jeitler, M; König, A; Krätschmer, I; Liko, D; Matsushita, T; Mikulec, I; Rabady, D; Rad, N; Rahbaran, B; Rohringer, H; Schieck, J; Strauss, J; Waltenberger, W; Wulz, C-E; Dvornikov, O; Makarenko, V; Mossolov, V; Gonzalez, J Suarez; Zykunov, V; Shumeiko, N; Alderweireldt, S; De Wolf, E A; Janssen, X; Lauwers, J; Van De Klundert, M; Van Haevermaet, H; Van Mechelen, P; Van Remortel, N; Van Spilbeeck, A; Abu Zeid, S; Blekman, F; D'Hondt, J; Daci, N; De Bruyn, I; Deroover, K; Lowette, S; Moortgat, S; Moreels, L; Olbrechts, A; Python, Q; Skovpen, K; Tavernier, S; Van Doninck, W; Van Mulders, P; Van Parijs, I; Brun, H; Clerbaux, B; De Lentdecker, G; Delannoy, H; Fasanella, G; Favart, L; Goldouzian, R; Grebenyuk, A; Karapostoli, G; Lenzi, T; Léonard, A; Luetic, J; Maerschalk, T; Marinov, A; Randle-Conde, A; Seva, T; Vander Velde, C; Vanlaer, P; Vannerom, D; Yonamine, R; Zenoni, F; Zhang, F; Cimmino, A; Cornelis, T; Dobur, D; Fagot, A; Gul, M; Khvastunov, I; Poyraz, D; Salva, S; Schöfbeck, R; Tytgat, M; Van Driessche, W; Yazgan, E; Zaganidis, N; Bakhshiansohi, H; Beluffi, C; Bondu, O; Brochet, S; Bruno, G; Caudron, A; De Visscher, S; Delaere, C; Delcourt, M; Francois, B; Giammanco, A; Jafari, A; Komm, M; Krintiras, G; Lemaitre, V; Magitteri, A; Mertens, A; Musich, M; Piotrzkowski, K; Quertenmont, L; Selvaggi, M; Marono, M Vidal; Wertz, S; Beliy, N; Aldá Júnior, W L; Alves, F L; Alves, G A; Brito, L; Hensel, C; Moraes, A; Pol, M E; Rebello Teles, P; Belchior Batista Das Chagas, E; Carvalho, W; Chinellato, J; Custódio, A; Da Costa, E M; Da Silveira, G G; De Jesus Damiao, D; De Oliveira Martins, C; Fonseca De Souza, S; Huertas Guativa, L M; Malbouisson, H; Matos Figueiredo, D; Mora Herrera, C; Mundim, L; Nogima, H; Prado Da Silva, W L; Santoro, A; Sznajder, A; Tonelli Manganote, E J; Torres Da Silva De Araujo, F; Vilela Pereira, A; Ahuja, S; Bernardes, C A; Dogra, S; Fernandez Perez Tomei, T R; Gregores, E M; Mercadante, P G; Moon, C S; Novaes, S F; Padula, Sandra S; Romero Abad, D; Ruiz Vargas, J C; Aleksandrov, A; Hadjiiska, R; Iaydjiev, P; Rodozov, M; Stoykova, S; Sultanov, G; Vutova, M; Dimitrov, A; Glushkov, I; Litov, L; Pavlov, B; Petkov, P; Fang, W; Ahmad, M; Bian, J G; Chen, G M; Chen, H S; Chen, M; Chen, Y; Cheng, T; Jiang, C H; Leggat, D; Liu, Z; Romeo, F; Ruan, M; Shaheen, S M; Spiezia, A; Tao, J; Wang, C; Wang, Z; Zhang, H; Zhao, J; Ban, Y; Chen, G; Li, Q; Liu, S; Mao, Y; Qian, S J; Wang, D; Xu, Z; Avila, C; Cabrera, A; Chaparro Sierra, L F; Florez, C; Gomez, J P; González Hernández, C F; Ruiz Alvarez, J D; Sanabria, J C; Godinovic, N; Lelas, D; Puljak, I; Ribeiro Cipriano, P M; Sculac, T; Antunovic, Z; Kovac, M; Brigljevic, V; Ferencek, D; Kadija, K; Mesic, B; Susa, T; Attikis, A; Mavromanolakis, G; Mousa, J; Nicolaou, C; Ptochos, F; Razis, P A; Rykaczewski, H; Tsiakkouri, D; Finger, M; Finger, M; Carrera Jarrin, E; El-Khateeb, E; Elgammal, S; Mohamed, A; Kadastik, M; Perrini, L; Raidal, M; Tiko, A; Veelken, C; Eerola, P; Pekkanen, J; Voutilainen, M; Härkönen, J; Järvinen, T; Karimäki, V; Kinnunen, R; Lampén, T; Lassila-Perini, K; Lehti, S; Lindén, T; Luukka, P; Tuominiemi, J; Tuovinen, E; Wendland, L; Talvitie, J; Tuuva, T; Besancon, M; Couderc, F; Dejardin, M; Denegri, D; Fabbro, B; Faure, J L; Favaro, C; Ferri, F; Ganjour, S; Ghosh, S; Givernaud, A; Gras, P; Hamel de Monchenault, G; Jarry, P; Kucher, I; Locci, E; Machet, M; Malcles, J; Rander, J; Rosowsky, A; Titov, M; Abdulsalam, A; Antropov, I; Baffioni, S; Beaudette, F; Busson, P; Cadamuro, L; Chapon, E; Charlot, C; Davignon, O; Granier de Cassagnac, R; Jo, M; Lisniak, S; Miné, P; Nguyen, M; Ochando, C; Ortona, G; Paganini, P; Pigard, P; Regnard, S; Salerno, R; Sirois, Y; Stahl Leiton, A G; Strebler, T; Yilmaz, Y; Zabi, A; Zghiche, A; Agram, J-L; Andrea, J; Aubin, A; Bloch, D; Brom, J-M; Buttignol, M; Chabert, E C; Chanon, N; Collard, C; Conte, E; Coubez, X; Fontaine, J-C; Gelé, D; Goerlach, U; Le Bihan, A-C; Van Hove, P; Gadrat, S; Beauceron, S; Bernet, C; Boudoul, G; Carrillo Montoya, C A; Chierici, R; Contardo, D; Courbon, B; Depasse, P; Mamouni, H El; Fay, J; Gascon, S; Gouzevitch, M; Grenier, G; Ille, B; Lagarde, F; Laktineh, I B; Lethuillier, M; Mirabito, L; Pequegnot, A L; Perries, S; Popov, A; Sabes, D; Sordini, V; Vander Donckt, M; Verdier, P; Viret, S; Khvedelidze, A; Tsamalaidze, Z; Autermann, C; Beranek, S; Feld, L; Kiesel, M K; Klein, K; Lipinski, M; Preuten, M; Schomakers, C; Schulz, J; Verlage, T; Albert, A; Brodski, M; Dietz-Laursonn, E; Duchardt, D; Endres, M; Erdmann, M; Erdweg, S; Esch, T; Fischer, R; Güth, A; Hamer, M; Hebbeker, T; Heidemann, C; Hoepfner, K; Knutzen, S; Merschmeyer, M; Meyer, A; Millet, P; Mukherjee, S; Olschewski, M; Padeken, K; Pook, T; Radziej, M; Reithler, H; Rieger, M; Scheuch, F; Sonnenschein, L; Teyssier, D; Thüer, S; Cherepanov, V; Flügge, G; Kargoll, B; Kress, T; Künsken, A; Lingemann, J; Müller, T; Nehrkorn, A; Nowack, A; Pistone, C; Pooth, O; Stahl, A; Aldaya Martin, M; Arndt, T; Asawatangtrakuldee, C; Beernaert, K; Behnke, O; Behrens, U; Bin Anuar, A A; Borras, K; Campbell, A; Connor, P; Contreras-Campana, C; Costanza, F; Diez Pardos, C; Dolinska, G; Eckerlin, G; Eckstein, D; Eichhorn, T; Eren, E; Gallo, E; Garay Garcia, J; Geiser, A; Gizhko, A; Grados Luyando, J M; Grohsjean, A; Gunnellini, P; Harb, A; Hauk, J; Hempel, M; Jung, H; Kalogeropoulos, A; Karacheban, O; Kasemann, M; Keaveney, J; Kleinwort, C; Korol, I; Krücker, D; Lange, W; Lelek, A; Lenz, T; Leonard, J; Lipka, K; Lobanov, A; Lohmann, W; Mankel, R; Melzer-Pellmann, I-A; Meyer, A B; Mittag, G; Mnich, J; Mussgiller, A; Pitzl, D; Placakyte, R; Raspereza, A; Roland, B; Sahin, M Ö; Saxena, P; Schoerner-Sadenius, T; Spannagel, S; Stefaniuk, N; Van Onsem, G P; Walsh, R; Wissing, C; Blobel, V; Centis Vignali, M; Draeger, A R; Dreyer, T; Garutti, E; Gonzalez, D; Haller, J; Hoffmann, M; Junkes, A; Klanner, R; Kogler, R; Kovalchuk, N; Lapsien, T; Marchesini, I; Marconi, D; Meyer, M; Niedziela, M; Nowatschin, D; Pantaleo, F; Peiffer, T; Perieanu, A; Scharf, C; Schleper, P; Schmidt, A; Schumann, S; Schwandt, J; Stadie, H; Steinbrück, G; Stober, F M; Stöver, M; Tholen, H; Troendle, D; Usai, E; Vanelderen, L; Vanhoefer, A; Vormwald, B; Akbiyik, M; Barth, C; Baur, S; Baus, C; Berger, J; Butz, E; Caspart, R; Chwalek, T; Colombo, F; De Boer, W; Dierlamm, A; Fink, S; Freund, B; Friese, R; Giffels, M; Gilbert, A; Goldenzweig, P; Haitz, D; Hartmann, F; Heindl, S M; Husemann, U; Katkov, I; Kudella, S; Mildner, H; Mozer, M U; Müller, Th; Plagge, M; Quast, G; Rabbertz, K; Röcker, S; Roscher, F; Schröder, M; Shvetsov, I; Sieber, G; Simonis, H J; Ulrich, R; Wayand, S; Weber, M; Weiler, T; Williamson, S; Wöhrmann, C; Wolf, R; Anagnostou, G; Daskalakis, G; Geralis, T; Giakoumopoulou, V A; Kyriakis, A; Loukas, D; Topsis-Giotis, I; Kesisoglou, S; Panagiotou, A; Saoulidou, N; Tziaferi, E; Evangelou, I; Flouris, G; Foudas, C; Kokkas, P; Loukas, N; Manthos, N; Papadopoulos, I; Paradas, E; Filipovic, N; Pasztor, G; Bencze, G; Hajdu, C; Horvath, D; Sikler, F; Veszpremi, V; Vesztergombi, G; Zsigmond, A J; Beni, N; Czellar, S; Karancsi, J; Makovec, A; Molnar, J; Szillasi, Z; Bartók, M; Raics, P; Trocsanyi, Z L; Ujvari, B; Komaragiri, J R; Bahinipati, S; Bhowmik, S; Choudhury, S; Mal, P; Mandal, K; Nayak, A; Sahoo, D K; Sahoo, N; Swain, S K; Bansal, S; Beri, S B; Bhatnagar, V; Chawla, R; Bhawandeep, U; Kalsi, A K; Kaur, A; Kaur, M; Kumar, R; Kumari, P; Mehta, A; Mittal, M; Singh, J B; Walia, G; Ashok Kumar; Bhardwaj, A; Choudhary, B C; Garg, R B; Keshri, S; Malhotra, S; Naimuddin, M; Ranjan, K; Sharma, R; Sharma, V; Bhattacharya, R; Bhattacharya, S; Chatterjee, K; Dey, S; Dutt, S; Dutta, S; Ghosh, S; Majumdar, N; Modak, A; Mondal, K; Mukhopadhyay, S; Nandan, S; Purohit, A; Roy, A; Roy, D; Roy Chowdhury, S; Sarkar, S; Sharan, M; Thakur, S; Behera, P K; Chudasama, R; Dutta, D; Jha, V; Kumar, V; Mohanty, A K; Netrakanti, P K; Pant, L M; Shukla, P; Topkar, A; Aziz, T; Dugad, S; Kole, G; Mahakud, B; Mitra, S; Mohanty, G B; Parida, B; Sur, N; Sutar, B; Banerjee, S; Dewanjee, R K; Ganguly, S; Guchait, M; Jain, Sa; Kumar, S; Maity, M; Majumder, G; Mazumdar, K; Sarkar, T; Wickramage, N; Chauhan, S; Dube, S; Hegde, V; Kapoor, A; Kothekar, K; Pandey, S; Rane, A; Sharma, S; Chenarani, S; Eskandari Tadavani, E; Etesami, S M; Khakzad, M; Mohammadi Najafabadi, M; Naseri, M; Paktinat Mehdiabadi, S; Rezaei Hosseinabadi, F; Safarzadeh, B; Zeinali, M; Felcini, M; Grunewald, M; Abbrescia, M; Calabria, C; Caputo, C; Colaleo, A; Creanza, D; Cristella, L; De Filippis, N; De Palma, M; Fiore, L; Iaselli, G; Maggi, G; Maggi, M; Miniello, G; My, S; Nuzzo, S; Pompili, A; Pugliese, G; Radogna, R; Ranieri, A; Selvaggi, G; Sharma, A; Silvestris, L; Venditti, R; Verwilligen, P; Abbiendi, G; Battilana, C; Bonacorsi, D; Braibant-Giacomelli, S; Brigliadori, L; Campanini, R; Capiluppi, P; Castro, A; Cavallo, F R; Chhibra, S S; Codispoti, G; Cuffiani, M; Dallavalle, G M; Fabbri, F; Fanfani, A; Fasanella, D; Giacomelli, P; Grandi, C; Guiducci, L; Marcellini, S; Masetti, G; Montanari, A; Navarria, F L; Perrotta, A; Rossi, A M; Rovelli, T; Siroli, G P; Tosi, N; Albergo, S; Costa, S; Di Mattia, A; Giordano, F; Potenza, R; Tricomi, A; Tuve, C; Barbagli, G; Ciulli, V; Civinini, C; D'Alessandro, R; Focardi, E; Lenzi, P; Meschini, M; Paoletti, S; Russo, L; Sguazzoni, G; Strom, D; Viliani, L; Benussi, L; Bianco, S; Fabbri, F; Piccolo, D; Primavera, F; Calvelli, V; Ferro, F; Monge, M R; Robutti, E; Tosi, S; Brianza, L; Brivio, F; Ciriolo, V; Dinardo, M E; Fiorendi, S; Gennai, S; Ghezzi, A; Govoni, P; Malberti, M; Malvezzi, S; Manzoni, R A; Menasce, D; Moroni, L; Paganoni, M; Pedrini, D; Pigazzini, S; Ragazzi, S; Tabarelli de Fatis, T; Buontempo, S; Cavallo, N; De Nardo, G; Di Guida, S; Esposito, M; Fabozzi, F; Fienga, F; Iorio, A O M; Lanza, G; Lista, L; Meola, S; Paolucci, P; Sciacca, C; Thyssen, F; Azzi, P; Bacchetta, N; Benato, L; Bisello, D; Boletti, A; Carlin, R; Carvalho Antunes De Oliveira, A; Checchia, P; Dall'Osso, M; De Castro Manzano, P; Dorigo, T; Dosselli, U; Gasparini, F; Gasparini, U; Gozzelino, A; Lacaprara, S; Margoni, M; Meneguzzo, A T; Pazzini, J; Pozzobon, N; Ronchese, P; Simonetto, F; Torassa, E; Zanetti, M; Zotto, P; Zumerle, G; Braghieri, A; Fallavollita, F; Magnani, A; Montagna, P; Ratti, S P; Re, V; Riccardi, C; Salvini, P; Vai, I; Vitulo, P; Alunni Solestizi, L; Bilei, G M; Ciangottini, D; Fanò, L; Lariccia, P; Leonardi, R; Mantovani, G; Menichelli, M; Saha, A; Santocchia, A; Androsov, K; Azzurri, P; Bagliesi, G; Bernardini, J; Boccali, T; Castaldi, R; Ciocci, M A; Dell'Orso, R; Donato, S; Fedi, G; Giassi, A; Grippo, M T; Ligabue, F; Lomtadze, T; Martini, L; Messineo, A; Palla, F; Rizzi, A; Savoy-Navarro, A; Spagnolo, P; Tenchini, R; Tonelli, G; Venturi, A; Verdini, P G; Barone, L; Cavallari, F; Cipriani, M; Del Re, D; Diemoz, M; Gelli, S; Longo, E; Margaroli, F; Marzocchi, B; Meridiani, P; Organtini, G; Paramatti, R; Preiato, F; Rahatlou, S; Rovelli, C; Santanastasio, F; Amapane, N; Arcidiacono, R; Argiro, S; Arneodo, M; Bartosik, N; Bellan, R; Biino, C; Cartiglia, N; Cenna, F; Costa, M; Covarelli, R; Degano, A; Demaria, N; Finco, L; Kiani, B; Mariotti, C; Maselli, S; Migliore, E; Monaco, V; Monteil, E; Monteno, M; Obertino, M M; Pacher, L; Pastrone, N; Pelliccioni, M; Pinna Angioni, G L; Ravera, F; Romero, A; Ruspa, M; Sacchi, R; Shchelina, K; Sola, V; Solano, A; Staiano, A; Traczyk, P; Belforte, S; Casarsa, M; Cossutti, F; Della Ricca, G; Zanetti, A; Kim, D H; Kim, G N; Kim, M S; Lee, S; Lee, S W; Oh, Y D; Sekmen, S; Son, D C; Yang, Y C; Lee, A; Kim, H; Brochero Cifuentes, J A; Kim, T J; Cho, S; Choi, S; Go, Y; Gyun, D; Ha, S; Hong, B; Jo, Y; Kim, Y; Lee, K; Lee, K S; Lee, S; Lim, J; Park, S K; Roh, Y; Almond, J; Kim, J; Lee, H; Oh, S B; Radburn-Smith, B C; Seo, S H; Yang, U K; Yoo, H D; Yu, G B; Choi, M; Kim, H; Kim, J H; Lee, J S H; Park, I C; Ryu, G; Ryu, M S; Choi, Y; Goh, J; Hwang, C; Lee, J; Yu, I; Dudenas, V; Juodagalvis, A; Vaitkus, J; Ahmed, I; Ibrahim, Z A; Md Ali, M A B; Mohamad Idris, F; Wan Abdullah, W A T; Yusli, M N; Zolkapli, Z; Castilla-Valdez, H; De La Cruz-Burelo, E; Heredia-De La Cruz, I; Hernandez-Almada, A; Lopez-Fernandez, R; Magaña Villalba, R; Mejia Guisao, J; Sanchez-Hernandez, A; Carrillo Moreno, S; Oropeza Barrera, C; Vazquez Valencia, F; Carpinteyro, S; Pedraza, I; Salazar Ibarguen, H A; Uribe Estrada, C; Morelos Pineda, A; Krofcheck, D; Butler, P H; Ahmad, A; Ahmad, M; Hassan, Q; Hoorani, H R; Khan, W A; Saddique, A; Shah, M A; Shoaib, M; Waqas, M; Bialkowska, H; Bluj, M; Boimska, B; Frueboes, T; Górski, M; Kazana, M; Nawrocki, K; Romanowska-Rybinska, K; Szleper, M; Zalewski, P; Bunkowski, K; Byszuk, A; Doroba, K; Kalinowski, A; Konecki, M; Krolikowski, J; Misiura, M; Olszewski, M; Walczak, M; Bargassa, P; Beirão Da Cruz E Silva, C; Calpas, B; Di Francesco, A; Faccioli, P; Ferreira Parracho, P G; Gallinaro, M; Hollar, J; Leonardo, N; Lloret Iglesias, L; Nemallapudi, M V; Rodrigues Antunes, J; Seixas, J; Toldaiev, O; Vadruccio, D; Varela, J; Afanasiev, S; Bunin, P; Gavrilenko, M; Golutvin, I; Gorbunov, I; Kamenev, A; Karjavin, V; Lanev, A; Malakhov, A; Matveev, V; Palichik, V; Perelygin, V; Shmatov, S; Shulha, S; Skatchkov, N; Smirnov, V; Voytishin, N; Zarubin, A; Chtchipounov, L; Golovtsov, V; Ivanov, Y; Kim, V; Kuznetsova, E; Murzin, V; Oreshkin, V; Sulimov, V; Vorobyev, A; Andreev, Yu; Dermenev, A; Gninenko, S; Golubev, N; Karneyeu, A; Kirsanov, M; Krasnikov, N; Pashenkov, A; Tlisov, D; Toropin, A; Epshteyn, V; Gavrilov, V; Lychkovskaya, N; Popov, V; Pozdnyakov, I; Safronov, G; Spiridonov, A; Toms, M; Vlasov, E; Zhokin, A; Aushev, T; Bylinkin, A; Danilov, M; Popova, E; Rusinov, V; Andreev, V; Azarkin, M; Dremin, I; Kirakosyan, M; Leonidov, A; Terkulov, A; Baskakov, A; Belyaev, A; Boos, E; Bunichev, V; Dubinin, M; Dudko, L; Klyukhin, V; Kodolova, O; Korneeva, N; Lokhtin, I; Miagkov, I; Obraztsov, S; Perfilov, M; Savrin, V; Volkov, P; Blinov, V; Skovpen, Y; Shtol, D; Azhgirey, I; Bayshev, I; Bitioukov, S; Elumakhov, D; Kachanov, V; Kalinin, A; Konstantinov, D; Krychkine, V; Petrov, V; Ryutin, R; Sobol, A; Troshin, S; Tyurin, N; Uzunian, A; Volkov, A; Adzic, P; Cirkovic, P; Devetak, D; Dordevic, M; Milosevic, J; Rekovic, V; Alcaraz Maestre, J; Barrio Luna, M; Calvo, E; Cerrada, M; Chamizo Llatas, M; Colino, N; De La Cruz, B; Delgado Peris, A; Escalante Del Valle, A; Fernandez Bedoya, C; Fernández Ramos, J P; Flix, J; Fouz, M C; Garcia-Abia, P; Gonzalez Lopez, O; Goy Lopez, S; Hernandez, J M; Josa, M I; Navarro De Martino, E; Pérez-Calero Yzquierdo, A; Puerta Pelayo, J; Quintario Olmeda, A; Redondo, I; Romero, L; Soares, M S; de Trocóniz, J F; Missiroli, M; Moran, D; Cuevas, J; Fernandez Menendez, J; Gonzalez Caballero, I; González Fernández, J R; Palencia Cortezon, E; Sanchez Cruz, S; Suárez Andrés, I; Vischia, P; Vizan Garcia, J M; Cabrillo, I J; Calderon, A; Curras, E; Fernandez, M; Garcia-Ferrero, J; Gomez, G; Lopez Virto, A; Marco, J; Martinez Rivero, C; Matorras, F; Piedra Gomez, J; Rodrigo, T; Ruiz-Jimeno, A; Scodellaro, L; Trevisani, N; Vila, I; Vilar Cortabitarte, R; Abbaneo, D; Auffray, E; Auzinger, G; Baillon, P; Ball, A H; Barney, D; Bloch, P; Bocci, A; Botta, C; Camporesi, T; Castello, R; Cepeda, M; Cerminara, G; Chen, Y; d'Enterria, D; Dabrowski, A; Daponte, V; David, A; De Gruttola, M; De Roeck, A; Di Marco, E; Dobson, M; Dorney, B; du Pree, T; Duggan, D; Dünser, M; Dupont, N; Elliott-Peisert, A; Everaerts, P; Fartoukh, S; Franzoni, G; Fulcher, J; Funk, W; Gigi, D; Gill, K; Girone, M; Glege, F; Gulhan, D; Gundacker, S; Guthoff, M; Harris, P; Hegeman, J; Innocente, V; Janot, P; Kieseler, J; Kirschenmann, H; Knünz, V; Kornmayer, A; Kortelainen, M J; Kousouris, K; Krammer, M; Lange, C; Lecoq, P; Lourenço, C; Lucchini, M T; Malgeri, L; Mannelli, M; Martelli, A; Meijers, F; Merlin, J A; Mersi, S; Meschi, E; Milenovic, P; Moortgat, F; Morovic, S; Mulders, M; Neugebauer, H; Orfanelli, S; Orsini, L; Pape, L; Perez, E; Peruzzi, M; Petrilli, A; Petrucciani, G; Pfeiffer, A; Pierini, M; Racz, A; Reis, T; Rolandi, G; Rovere, M; Sakulin, H; Sauvan, J B; Schäfer, C; Schwick, C; Seidel, M; Sharma, A; Silva, P; Sphicas, P; Steggemann, J; Stoye, M; Takahashi, Y; Tosi, M; Treille, D; Triossi, A; Tsirou, A; Veckalns, V; Veres, G I; Verweij, M; Wardle, N; Wöhri, H K; Zagozdzinska, A; Zeuner, W D; Bertl, W; Deiters, K; Erdmann, W; Horisberger, R; Ingram, Q; Kaestli, H C; Kotlinski, D; Langenegger, U; Rohe, T; Wiederkehr, S A; Bachmair, F; Bäni, L; Bianchini, L; Casal, B; Dissertori, G; Dittmar, M; Donegà, M; Grab, C; Heidegger, C; Hits, D; Hoss, J; Kasieczka, G; Lustermann, W; Mangano, B; Marionneau, M; Martinez Ruiz Del Arbol, P; Masciovecchio, M; Meinhard, M T; Meister, D; Micheli, F; Musella, P; Nessi-Tedaldi, F; Pandolfi, F; Pata, J; Pauss, F; Perrin, G; Perrozzi, L; Quittnat, M; Rossini, M; Schönenberger, M; Starodumov, A; Tavolaro, V R; Theofilatos, K; Wallny, R; Aarrestad, T K; Amsler, C; Caminada, L; Canelli, M F; De Cosa, A; Galloni, C; Hinzmann, A; Hreus, T; Kilminster, B; Ngadiuba, J; Pinna, D; Rauco, G; Robmann, P; Salerno, D; Seitz, C; Yang, Y; Zucchetta, A; Candelise, V; Doan, T H; Jain, Sh; Khurana, R; Konyushikhin, M; Kuo, C M; Lin, W; Pozdnyakov, A; Yu, S S; Kumar, Arun; Chang, P; Chang, Y H; Chao, Y; Chen, K F; Chen, P H; Fiori, F; Hou, W-S; Hsiung, Y; Liu, Y F; Lu, R-S; Miñano Moya, M; Paganis, E; Psallidas, A; Tsai, J F; Asavapibhop, B; Singh, G; Srimanobhas, N; Suwonjandee, N; Adiguzel, A; Damarseckin, S; Demiroglu, Z S; Dozen, C; Eskut, E; Girgis, S; Gokbulut, G; Guler, Y; Hos, I; Kangal, E E; Kara, O; Kayis Topaksu, A; Kiminsu, U; Oglakci, M; Onengut, G; Ozdemir, K; Ozturk, S; Polatoz, A; Tali, B; Turkcapar, S; Zorbakir, I S; Zorbilmez, C; Bilin, B; Bilmis, S; Isildak, B; Karapinar, G; Yalvac, M; Zeyrek, M; Gülmez, E; Kaya, M; Kaya, O; Yetkin, E A; Yetkin, T; Cakir, A; Cankocak, K; Sen, S; Grynyov, B; Levchuk, L; Sorokin, P; Aggleton, R; Ball, F; Beck, L; Brooke, J J; Burns, D; Clement, E; Cussans, D; Flacher, H; Goldstein, J; Grimes, M; Heath, G P; Heath, H F; Jacob, J; Kreczko, L; Lucas, C; Newbold, D M; Paramesvaran, S; Poll, A; Sakuma, T; Seif El Nasr-Storey, S; Smith, D; Smith, V J; Bell, K W; Belyaev, A; Brew, C; Brown, R M; Calligaris, L; Cieri, D; Cockerill, D J A; Coughlan, J A; Harder, K; Harper, S; Olaiya, E; Petyt, D; Shepherd-Themistocleous, C H; Thea, A; Tomalin, I R; Williams, T; Baber, M; Bainbridge, R; Buchmuller, O; Bundock, A; Burton, D; Casasso, S; Citron, M; Colling, D; Corpe, L; Dauncey, P; Davies, G; De Wit, A; Della Negra, M; Di Maria, R; Dunne, P; Elwood, A; Futyan, D; Haddad, Y; Hall, G; Iles, G; James, T; Lane, R; Laner, C; Lucas, R; Lyons, L; Magnan, A-M; Malik, S; Mastrolorenzo, L; Nash, J; Nikitenko, A; Pela, J; Penning, B; Pesaresi, M; Raymond, D M; Richards, A; Rose, A; Scott, E; Seez, C; Summers, S; Tapper, A; Uchida, K; Vazquez Acosta, M; Virdee, T; Wright, J; Zenz, S C; Cole, J E; Hobson, P R; Khan, A; Kyberd, P; Reid, I D; Symonds, P; Teodorescu, L; Turner, M; Borzou, A; Call, K; Dittmann, J; Hatakeyama, K; Liu, H; Pastika, N; Bartek, R; Dominguez, A; Buccilli, A; Cooper, S I; Henderson, C; Rumerio, P; West, C; Arcaro, D; Avetisyan, A; Bose, T; Gastler, D; Rankin, D; Richardson, C; Rohlf, J; Sulak, L; Zou, D; Benelli, G; Cutts, D; Garabedian, A; Hakala, J; Heintz, U; Hogan, J M; Jesus, O; Kwok, K H M; Laird, E; Landsberg, G; Mao, Z; Narain, M; Piperov, S; Sagir, S; Spencer, E; Syarif, R; Breedon, R; Burns, D; Calderon De La Barca Sanchez, M; Chauhan, S; Chertok, M; Conway, J; Conway, R; Cox, P T; Erbacher, R; Flores, C; Funk, G; Gardner, M; Ko, W; Lander, R; Mclean, C; Mulhearn, M; Pellett, D; Pilot, J; Shalhout, S; Shi, M; Smith, J; Squires, M; Stolp, D; Tos, K; Tripathi, M; Bachtis, M; Bravo, C; Cousins, R; Dasgupta, A; Florent, A; Hauser, J; Ignatenko, M; Mccoll, N; Saltzberg, D; Schnaible, C; Valuev, V; Weber, M; Bouvier, E; Burt, K; Clare, R; Ellison, J; Gary, J W; Ghiasi Shirazi, S M A; Hanson, G; Heilman, J; Jandir, P; Kennedy, E; Lacroix, F; Long, O R; Olmedo Negrete, M; Paneva, M I; Shrinivas, A; Si, W; Wei, H; Wimpenny, S; Yates, B R; Branson, J G; Cerati, G B; Cittolin, S; Derdzinski, M; Gerosa, R; Holzner, A; Klein, D; Krutelyov, V; Letts, J; Macneill, I; Olivito, D; Padhi, S; Pieri, M; Sani, M; Sharma, V; Simon, S; Tadel, M; Vartak, A; Wasserbaech, S; Welke, C; Wood, J; Würthwein, F; Yagil, A; Zevi Della Porta, G; Amin, N; Bhandari, R; Bradmiller-Feld, J; Campagnari, C; Dishaw, A; Dutta, V; Franco Sevilla, M; George, C; Golf, F; Gouskos, L; Gran, J; Heller, R; Incandela, J; Mullin, S D; Ovcharova, A; Qu, H; Richman, J; Stuart, D; Suarez, I; Yoo, J; Anderson, D; Bendavid, J; Bornheim, A; Bunn, J; Duarte, J; Lawhorn, J M; Mott, A; Newman, H B; Pena, C; Spiropulu, M; Vlimant, J R; Xie, S; Zhu, R Y; Andrews, M B; Ferguson, T; Paulini, M; Russ, J; Sun, M; Vogel, H; Vorobiev, I; Weinberg, M; Cumalat, J P; Ford, W T; Jensen, F; Johnson, A; Krohn, M; Leontsinis, S; Mulholland, T; Stenson, K; Wagner, S R; Alexander, J; Chaves, J; Chu, J; Dittmer, S; Mcdermott, K; Mirman, N; Nicolas Kaufman, G; Patterson, J R; Rinkevicius, A; Ryd, A; Skinnari, L; Soffi, L; Tan, S M; Tao, Z; Thom, J; Tucker, J; Wittich, P; Zientek, M; Winn, D; Abdullin, S; Albrow, M; Apollinari, G; Apresyan, A; Banerjee, S; Bauerdick, L A T; Beretvas, A; Berryhill, J; Bhat, P C; Bolla, G; Burkett, K; Butler, J N; Cheung, H W K; Chlebana, F; Cihangir, S; Cremonesi, M; Elvira, V D; Fisk, I; Freeman, J; Gottschalk, E; Gray, L; Green, D; Grünendahl, S; Gutsche, O; Hare, D; Harris, R M; Hasegawa, S; Hirschauer, J; Hu, Z; Jayatilaka, B; Jindariani, S; Johnson, M; Joshi, U; Klima, B; Kreis, B; Lammel, S; Linacre, J; Lincoln, D; Lipton, R; Liu, M; Liu, T; Lopes De Sá, R; Lykken, J; Maeshima, K; Magini, N; Marraffino, J M; Maruyama, S; Mason, D; McBride, P; Merkel, P; Mrenna, S; Nahn, S; O'Dell, V; Pedro, K; Prokofyev, O; Rakness, G; Ristori, L; Sexton-Kennedy, E; Soha, A; Spalding, W J; Spiegel, L; Stoynev, S; Strait, J; Strobbe, N; Taylor, L; Tkaczyk, S; Tran, N V; Uplegger, L; Vaandering, E W; Vernieri, C; Verzocchi, M; Vidal, R; Wang, M; Weber, H A; Whitbeck, A; Wu, Y; Acosta, D; Avery, P; Bortignon, P; Bourilkov, D; Brinkerhoff, A; Carnes, A; Carver, M; Curry, D; Das, S; Field, R D; Furic, I K; Konigsberg, J; Korytov, A; Low, J F; Ma, P; Matchev, K; Mei, H; Mitselmakher, G; Rank, D; Shchutska, L; Sperka, D; Thomas, L; Wang, J; Wang, S; Yelton, J; Linn, S; Markowitz, P; Martinez, G; Rodriguez, J L; Ackert, A; Adams, T; Askew, A; Bein, S; Hagopian, S; Hagopian, V; Johnson, K F; Kolberg, T; Prosper, H; Santra, A; Yohay, R; Baarmand, M M; Bhopatkar, V; Colafranceschi, S; Hohlmann, M; Noonan, D; Roy, T; Yumiceva, F; Adams, M R; Apanasevich, L; Berry, D; Betts, R R; Bucinskaite, I; Cavanaugh, R; Evdokimov, O; Gauthier, L; Gerber, C E; Hofman, D J; Jung, K; Sandoval Gonzalez, I D; Varelas, N; Wang, H; Wu, Z; Zakaria, M; Zhang, J; Bilki, B; Clarida, W; Dilsiz, K; Durgut, S; Gandrajula, R P; Haytmyradov, M; Khristenko, V; Merlo, J-P; Mermerkaya, H; Mestvirishvili, A; Moeller, A; Nachtman, J; Ogul, H; Onel, Y; Ozok, F; Penzo, A; Snyder, C; Tiras, E; Wetzel, J; Yi, K; Blumenfeld, B; Cocoros, A; Eminizer, N; Fehling, D; Feng, L; Gritsan, A V; Maksimovic, P; Roskes, J; Sarica, U; Swartz, M; Xiao, M; You, C; Al-Bataineh, A; Baringer, P; Bean, A; Boren, S; Bowen, J; Castle, J; Forthomme, L; Kenny, R P; Khalil, S; Kropivnitskaya, A; Majumder, D; Mcbrayer, W; Murray, M; Sanders, S; Stringer, R; Tapia Takaki, J D; Wang, Q; Ivanov, A; Kaadze, K; Maravin, Y; Mohammadi, A; Saini, L K; Skhirtladze, N; Toda, S; Rebassoo, F; Wright, D; Anelli, C; Baden, A; Baron, O; Belloni, A; Calvert, B; Eno, S C; Ferraioli, C; Gomez, J A; Hadley, N J; Jabeen, S; Jeng, G Y; Kellogg, R G; Kunkle, J; Mignerey, A C; Ricci-Tam, F; Shin, Y H; Skuja, A; Tonjes, M B; Tonwar, S C; Abercrombie, D; Allen, B; Apyan, A; Azzolini, V; Barbieri, R; Baty, A; Bi, R; Bierwagen, K; Brandt, S; Busza, W; Cali, I A; D'Alfonso, M; Demiragli, Z; Gomez Ceballos, G; Goncharov, M; Hsu, D; Iiyama, Y; Innocenti, G M; Klute, M; Kovalskyi, D; Krajczar, K; Lai, Y S; Lee, Y-J; Levin, A; Luckey, P D; Maier, B; Marini, A C; Mcginn, C; Mironov, C; Narayanan, S; Niu, X; Paus, C; Roland, C; Roland, G; Salfeld-Nebgen, J; Stephans, G S F; Tatar, K; Velicanu, D; Wang, J; Wang, T W; Wyslouch, B; Benvenuti, A C; Chatterjee, R M; Evans, A; Hansen, P; Kalafut, S; Kao, S C; Kubota, Y; Lesko, Z; Mans, J; Nourbakhsh, S; Ruckstuhl, N; Rusack, R; Tambe, N; Turkewitz, J; Acosta, J G; Oliveros, S; Avdeeva, E; Bloom, K; Claes, D R; Fangmeier, C; Gonzalez Suarez, R; Kamalieddin, R; Kravchenko, I; Malta Rodrigues, A; Monroy, J; Siado, J E; Snow, G R; Stieger, B; Alyari, M; Dolen, J; Godshalk, A; Harrington, C; Iashvili, I; Kaisen, J; Nguyen, D; Parker, A; Rappoccio, S; Roozbahani, B; Alverson, G; Barberis, E; Hortiangtham, A; Massironi, A; Morse, D M; Nash, D; Orimoto, T; Teixeira De Lima, R; Trocino, D; Wang, R-J; Wood, D; Bhattacharya, S; Charaf, O; Hahn, K A; Kumar, A; Mucia, N; Odell, N; Pollack, B; Schmitt, M H; Sung, K; Trovato, M; Velasco, M; Dev, N; Hildreth, M; Hurtado Anampa, K; Jessop, C; Karmgard, D J; Kellams, N; Lannon, K; Marinelli, N; Meng, F; Mueller, C; Musienko, Y; Planer, M; Reinsvold, A; Ruchti, R; Rupprecht, N; Smith, G; Taroni, S; Wayne, M; Wolf, M; Woodard, A; Alimena, J; Antonelli, L; Bylsma, B; Durkin, L S; Flowers, S; Francis, B; Hart, A; Hill, C; Hughes, R; Ji, W; Liu, B; Luo, W; Puigh, D; Winer, B L; Wulsin, H W; Cooperstein, S; Driga, O; Elmer, P; Hardenbrook, J; Hebda, P; Lange, D; Luo, J; Marlow, D; Medvedeva, T; Mei, K; Ojalvo, I; Olsen, J; Palmer, C; Piroué, P; Stickland, D; Svyatkovskiy, A; Tully, C; Malik, S; Barker, A; Barnes, V E; Folgueras, S; Gutay, L; Jha, M K; Jones, M; Jung, A W; Khatiwada, A; Miller, D H; Neumeister, N; Schulte, J F; Shi, X; Sun, J; Wang, F; Xie, W; Parashar, N; Stupak, J; Adair, A; Akgun, B; Chen, Z; Ecklund, K M; Geurts, F J M; Guilbaud, M; Li, W; Michlin, B; Northup, M; Padley, B P; Roberts, J; Rorie, J; Tu, Z; Zabel, J; Betchart, B; Bodek, A; de Barbaro, P; Demina, R; Duh, Y T; Ferbel, T; Galanti, M; Garcia-Bellido, A; Han, J; Hindrichs, O; Khukhunaishvili, A; Lo, K H; Tan, P; Verzetti, M; Agapitos, A; Chou, J P; Gershtein, Y; Gómez Espinosa, T A; Halkiadakis, E; Heindl, M; Hughes, E; Kaplan, S; Kunnawalkam Elayavalli, R; Kyriacou, S; Lath, A; Nash, K; Osherson, M; Saka, H; Salur, S; Schnetzer, S; Sheffield, D; Somalwar, S; Stone, R; Thomas, S; Thomassen, P; Walker, M; Delannoy, A G; Foerster, M; Heideman, J; Riley, G; Rose, K; Spanier, S; Thapa, K; Bouhali, O; Celik, A; Dalchenko, M; De Mattia, M; Delgado, A; Dildick, S; Eusebi, R; Gilmore, J; Huang, T; Juska, E; Kamon, T; Mueller, R; Pakhotin, Y; Patel, R; Perloff, A; Perniè, L; Rathjens, D; Safonov, A; Tatarinov, A; Ulmer, K A; Akchurin, N; Cowden, C; Damgov, J; De Guio, F; Dragoiu, C; Dudero, P R; Faulkner, J; Gurpinar, E; Kunori, S; Lamichhane, K; Lee, S W; Libeiro, T; Peltola, T; Undleeb, S; Volobouev, I; Wang, Z; Greene, S; Gurrola, A; Janjam, R; Johns, W; Maguire, C; Melo, A; Ni, H; Sheldon, P; Tuo, S; Velkovska, J; Xu, Q; Arenton, M W; Barria, P; Cox, B; Goodell, J; Hirosky, R; Ledovskoy, A; Li, H; Neu, C; Sinthuprasith, T; Sun, X; Wang, Y; Wolfe, E; Xia, F; Clarke, C; Harr, R; Karchin, P E; Sturdy, J; Belknap, D A; Buchanan, J; Caillol, C; Dasu, S; Dodd, L; Duric, S; Gomber, B; Grothe, M; Herndon, M; Hervé, A; Klabbers, P; Lanaro, A; Levine, A; Long, K; Loveless, R; Perry, T; Pierro, G A; Polese, G; Ruggles, T; Savin, A; Smith, N; Smith, W H; Taylor, D; Woods, N

2017-01-01

A measurement of the top quark mass is reported in events containing a single top quark produced via the electroweak t channel. The analysis is performed using data from proton-proton collisions collected with the CMS detector at the LHC at a centre-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 19.7 fb[Formula: see text]. Top quark candidates are reconstructed from their decay to a [Formula: see text] boson and a b quark, with the [Formula: see text] boson decaying leptonically to a muon and a neutrino. The final state signature and kinematic properties of single top quark events in the t channel are used to enhance the purity of the sample, suppressing the contribution from top quark pair production. A fit to the invariant mass distribution of reconstructed top quark candidates yields a value of the top quark mass of [Formula: see text]. This result is in agreement with the current world average, and represents the first measurement of the top quark mass in event topologies not dominated by top quark pair production, therefore contributing to future averages with partially uncorrelated systematic uncertainties and a largely uncorrelated statistical uncertainty.

Martingales, detrending data, and the efficient market hypothesis

NASA Astrophysics Data System (ADS)

McCauley, Joseph L.; Bassler, Kevin E.; Gunaratne, Gemunu H.

2008-01-01

We discuss martingales, detrending data, and the efficient market hypothesis (EMH) for stochastic processes x( t) with arbitrary diffusion coefficients D( x, t). Beginning with x-independent drift coefficients R( t) we show that martingale stochastic processes generate uncorrelated, generally non-stationary increments. Generally, a test for a martingale is therefore a test for uncorrelated increments. A detrended process with an x-dependent drift coefficient is generally not a martingale, and so we extend our analysis to include the class of ( x, t)-dependent drift coefficients of interest in finance. We explain why martingales look Markovian at the level of both simple averages and 2-point correlations. And while a Markovian market has no memory to exploit and presumably cannot be beaten systematically, it has never been shown that martingale memory cannot be exploited in 3-point or higher correlations to beat the market. We generalize our Markov scaling solutions presented earlier, and also generalize the martingale formulation of the EMH to include ( x, t)-dependent drift in log returns. We also use the analysis of this paper to correct a misstatement of the ‘fair game’ condition in terms of serial correlations in Fama's paper on the EMH. We end with a discussion of Levy's characterization of Brownian motion and prove that an arbitrary martingale is topologically inequivalent to a Wiener process.

Empirical investigation into depth-resolution of Magnetotelluric data

NASA Astrophysics Data System (ADS)

Piana Agostinetti, N.; Ogaya, X.

2017-12-01

We investigate the depth-resolution of MT data comparing reconstructed 1D resistivity profiles with measured resistivity and lithostratigraphy from borehole data. Inversion of MT data has been widely used to reconstruct the 1D fine-layered resistivity structure beneath an isolated Magnetotelluric (MT) station. Uncorrelated noise is generally assumed to be associated to MT data. However, wrong assumptions on error statistics have been proved to strongly bias the results obtained in geophysical inversions. In particular the number of resolved layers at depth strongly depends on error statistics. In this study, we applied a trans-dimensional McMC algorithm for reconstructing the 1D resistivity profile near-by the location of a 1500 m-deep borehole, using MT data. We resolve the MT inverse problem imposing different models for the error statistics associated to the MT data. Following a Hierachical Bayes' approach, we also inverted for the hyper-parameters associated to each error statistics model. Preliminary results indicate that assuming un-correlated noise leads to a number of resolved layers larger than expected from the retrieved lithostratigraphy. Moreover, comparing the inversion of synthetic resistivity data obtained from the "true" resistivity stratification measured along the borehole shows that a consistent number of resistivity layers can be obtained using a Gaussian model for the error statistics, with substantial correlation length.

Neuronal synchrony and the relation between the blood-oxygen-level dependent response and the local field potential

PubMed Central

Nguyen, Mai; Winawer, Jonathan

2017-01-01

The most widespread measures of human brain activity are the blood-oxygen-level dependent (BOLD) signal and surface field potential. Prior studies report a variety of relationships between these signals. To develop an understanding of how to interpret these signals and the relationship between them, we developed a model of (a) neuronal population responses and (b) transformations from neuronal responses into the functional magnetic resonance imaging (fMRI) BOLD signal and electrocorticographic (ECoG) field potential. Rather than seeking a transformation between the two measures directly, this approach interprets each measure with respect to the underlying neuronal population responses. This model accounts for the relationship between BOLD and ECoG data from human visual cortex in V1, V2, and V3, with the model predictions and data matching in three ways: across stimuli, the BOLD amplitude and ECoG broadband power were positively correlated, the BOLD amplitude and alpha power (8–13 Hz) were negatively correlated, and the BOLD amplitude and narrowband gamma power (30–80 Hz) were uncorrelated. The two measures provide complementary information about human brain activity, and we infer that features of the field potential that are uncorrelated with BOLD arise largely from changes in synchrony, rather than level, of neuronal activity. PMID:28742093

A three-dimensional refractive index model for simulation of optical wave propagation in atmospheric turbulence

NASA Astrophysics Data System (ADS)

Paramonov, P. V.; Vorontsov, A. M.; Kunitsyn, V. E.

2015-10-01

Numerical modeling of optical wave propagation in atmospheric turbulence is traditionally performed with using the so-called "split"-operator method, when the influence of the propagation medium's refractive index inhomogeneities is accounted for only within a system of infinitely narrow layers (phase screens) where phase is distorted. Commonly, under certain assumptions, such phase screens are considered as mutually statistically uncorrelated. However, in several important applications including laser target tracking, remote sensing, and atmospheric imaging, accurate optical field propagation modeling assumes upper limitations on interscreen spacing. The latter situation can be observed, for instance, in the presence of large-scale turbulent inhomogeneities or in deep turbulence conditions, where interscreen distances become comparable with turbulence outer scale and, hence, corresponding phase screens cannot be statistically uncorrelated. In this paper, we discuss correlated phase screens. The statistical characteristics of screens are calculated based on a representation of turbulent fluctuations of three-dimensional (3D) refractive index random field as a set of sequentially correlated 3D layers displaced in the wave propagation direction. The statistical characteristics of refractive index fluctuations are described in terms of the von Karman power spectrum density. In the representation of these 3D layers by corresponding phase screens, the geometrical optics approximation is used.

Coherency of seismic noise, Green functions and site effects

NASA Astrophysics Data System (ADS)

Prieto, G. A.; Beroza, G. C.

2007-12-01

The newly rediscovered methodology of cross correlating seismic noise (or seismic coda) to retrieve the Green function takes advantage of the coherency of the signals across a set of stations. Only coherent signals are expected to emerge after stacking over a long enough time. Cross-correlation has a significant disadvantage for this purpose, in that the Green function recovered is convolved with the source-time function of the noise source. For seismic waves, this can mean that the microseism peak dominates the signal. We show how the use of the transfer function between sensors provides a better resolved Green function (after inverse Fourier transform), because the deconvolution process removes the effect of the noise source-time function. In addition, we compute the coherence of the seismic noise as a function of frequency and distance, providing information about the effective frequency band over which Green function retrieval is possible. The coherence may also be used in resolution analysis for time reversal as a constraint on the de-coherence length (the distance between sensors over which the signals become uncorrelated). We use the information from the transfer function and the coherence to examine wave propagation effects (attenuation and site effects) for closely spaced stations compared to a reference station.

The spike trains of inhibited pacemaker neurons seen through the magnifying glass of nonlinear analyses.

PubMed

Segundo, J P; Sugihara, G; Dixon, P; Stiber, M; Bersier, L F

1998-12-01

This communication describes the new information that may be obtained by applying nonlinear analytical techniques to neurobiological time-series. Specifically, we consider the sequence of interspike intervals Ti (the "timing") of trains recorded from synaptically inhibited crayfish pacemaker neurons. As reported earlier, different postsynaptic spike train forms (sets of timings with shared properties) are generated by varying the average rate and/or pattern (implying interval dispersions and sequences) of presynaptic spike trains. When the presynaptic train is Poisson (independent exponentially distributed intervals), the form is "Poisson-driven" (unperturbed and lengthened intervals succeed each other irregularly). When presynaptic trains are pacemaker (intervals practically equal), forms are either "p:q locked" (intervals repeat periodically), "intermittent" (mostly almost locked but disrupted irregularly), "phase walk throughs" (intermittencies with briefer regular portions), or "messy" (difficult to predict or describe succinctly). Messy trains are either "erratic" (some intervals natural and others lengthened irregularly) or "stammerings" (intervals are integral multiples of presynaptic intervals). The individual spike train forms were analysed using attractor reconstruction methods based on the lagged coordinates provided by successive intervals from the time-series Ti. Numerous models were evaluated in terms of their predictive performance by a trial-and-error procedure: the most successful model was taken as best reflecting the true nature of the system's attractor. Each form was characterized in terms of its dimensionality, nonlinearity and predictability. (1) The dimensionality of the underlying dynamical attractor was estimated by the minimum number of variables (coordinates Ti) required to model acceptably the system's dynamics, i.e. by the system's degrees of freedom. Each model tested was based on a different number of Ti; the smallest number whose predictions were judged successful provided the best integer approximation of the attractor's true dimension (not necessarily an integer). Dimensionalities from three to five provided acceptable fits. (2) The degree of nonlinearity was estimated by: (i) comparing the correlations between experimental results and data from linear and nonlinear models, and (ii) tuning model nonlinearity via a distance-weighting function and identifying the either local or global neighborhood size. Lockings were compatible with linear models and stammerings were marginal; nonlinear models were best for Poisson-driven, intermittent and erratic forms. (3) Finally, prediction accuracy was plotted against increasingly long sequences of intervals forecast: the accuracies for Poisson-driven, locked and stammering forms were invariant, revealing irregularities due to uncorrelated noise, but those of intermittent and messy erratic forms decayed rapidly, indicating an underlying deterministic process. The excellent reconstructions possible for messy erratic and for some intermittent forms are especially significant because of their relatively low dimensionality (around 4), high degree of nonlinearity and prediction decay with time. This is characteristic of chaotic systems, and provides evidence that nonlinear couplings between relatively few variables are the major source of the apparent complexity seen in these cases. This demonstration of different dimensions, degrees of nonlinearity and predictabilities provides rigorous support for the categorization of different synaptically driven discharge forms proposed earlier on the basis of more heuristic criteria. This has significant implications. (1) It demonstrates that heterogeneous postsynaptic forms can indeed be induced by manipulating a few presynaptic variables. (2) Each presynaptic timing induces a form with characteristic dimensionality, thus breaking up the preparation into subsystems such that the physical variables in each operate as one

76 FR 6646 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing of Proposed Rule...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-02-07

... Series, adjusted option series and any options series until the time to expiration for such series is... time to expiration for such series is less than nine months be treated differently. Specifically, under... series until the time to expiration for such series is less than nine months. Accordingly, the...

Complexity quantification of cardiac variability time series using improved sample entropy (I-SampEn).

PubMed

Marwaha, Puneeta; Sunkaria, Ramesh Kumar

2016-09-01

The sample entropy (SampEn) has been widely used to quantify the complexity of RR-interval time series. It is a fact that higher complexity, and hence, entropy is associated with the RR-interval time series of healthy subjects. But, SampEn suffers from the disadvantage that it assigns higher entropy to the randomized surrogate time series as well as to certain pathological time series, which is a misleading observation. This wrong estimation of the complexity of a time series may be due to the fact that the existing SampEn technique updates the threshold value as a function of long-term standard deviation (SD) of a time series. However, time series of certain pathologies exhibits substantial variability in beat-to-beat fluctuations. So the SD of the first order difference (short term SD) of the time series should be considered while updating threshold value, to account for period-to-period variations inherited in a time series. In the present work, improved sample entropy (I-SampEn), a new methodology has been proposed in which threshold value is updated by considering the period-to-period variations of a time series. The I-SampEn technique results in assigning higher entropy value to age-matched healthy subjects than patients suffering atrial fibrillation (AF) and diabetes mellitus (DM). Our results are in agreement with the theory of reduction in complexity of RR-interval time series in patients suffering from chronic cardiovascular and non-cardiovascular diseases.

Development and application of a modified dynamic time warping algorithm (DTW-S) to analyses of primate brain expression time series

PubMed Central

2011-01-01

Background Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Results Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S) algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR) and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. Conclusions The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html. PMID:21851598

Development and application of a modified dynamic time warping algorithm (DTW-S) to analyses of primate brain expression time series.

PubMed

Yuan, Yuan; Chen, Yi-Ping Phoebe; Ni, Shengyu; Xu, Augix Guohua; Tang, Lin; Vingron, Martin; Somel, Mehmet; Khaitovich, Philipp

2011-08-18

Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S) algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR) and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html.

Measuring Complexity and Predictability of Time Series with Flexible Multiscale Entropy for Sensor Networks

PubMed Central

Zhou, Renjie; Yang, Chen; Wan, Jian; Zhang, Wei; Guan, Bo; Xiong, Naixue

2017-01-01

Measurement of time series complexity and predictability is sometimes the cornerstone for proposing solutions to topology and congestion control problems in sensor networks. As a method of measuring time series complexity and predictability, multiscale entropy (MSE) has been widely applied in many fields. However, sample entropy, which is the fundamental component of MSE, measures the similarity of two subsequences of a time series with either zero or one, but without in-between values, which causes sudden changes of entropy values even if the time series embraces small changes. This problem becomes especially severe when the length of time series is getting short. For solving such the problem, we propose flexible multiscale entropy (FMSE), which introduces a novel similarity function measuring the similarity of two subsequences with full-range values from zero to one, and thus increases the reliability and stability of measuring time series complexity. The proposed method is evaluated on both synthetic and real time series, including white noise, 1/f noise and real vibration signals. The evaluation results demonstrate that FMSE has a significant improvement in reliability and stability of measuring complexity of time series, especially when the length of time series is short, compared to MSE and composite multiscale entropy (CMSE). The proposed method FMSE is capable of improving the performance of time series analysis based topology and traffic congestion control techniques. PMID:28383496

Measuring Complexity and Predictability of Time Series with Flexible Multiscale Entropy for Sensor Networks.

PubMed

Zhou, Renjie; Yang, Chen; Wan, Jian; Zhang, Wei; Guan, Bo; Xiong, Naixue

2017-04-06

Measurement of time series complexity and predictability is sometimes the cornerstone for proposing solutions to topology and congestion control problems in sensor networks. As a method of measuring time series complexity and predictability, multiscale entropy (MSE) has been widely applied in many fields. However, sample entropy, which is the fundamental component of MSE, measures the similarity of two subsequences of a time series with either zero or one, but without in-between values, which causes sudden changes of entropy values even if the time series embraces small changes. This problem becomes especially severe when the length of time series is getting short. For solving such the problem, we propose flexible multiscale entropy (FMSE), which introduces a novel similarity function measuring the similarity of two subsequences with full-range values from zero to one, and thus increases the reliability and stability of measuring time series complexity. The proposed method is evaluated on both synthetic and real time series, including white noise, 1/f noise and real vibration signals. The evaluation results demonstrate that FMSE has a significant improvement in reliability and stability of measuring complexity of time series, especially when the length of time series is short, compared to MSE and composite multiscale entropy (CMSE). The proposed method FMSE is capable of improving the performance of time series analysis based topology and traffic congestion control techniques.

Empirical method to measure stochasticity and multifractality in nonlinear time series

NASA Astrophysics Data System (ADS)

Lin, Chih-Hao; Chang, Chia-Seng; Li, Sai-Ping

2013-12-01

An empirical algorithm is used here to study the stochastic and multifractal nature of nonlinear time series. A parameter can be defined to quantitatively measure the deviation of the time series from a Wiener process so that the stochasticity of different time series can be compared. The local volatility of the time series under study can be constructed using this algorithm, and the multifractal structure of the time series can be analyzed by using this local volatility. As an example, we employ this method to analyze financial time series from different stock markets. The result shows that while developed markets evolve very much like an Ito process, the emergent markets are far from efficient. Differences about the multifractal structures and leverage effects between developed and emergent markets are discussed. The algorithm used here can be applied in a similar fashion to study time series of other complex systems.

Multiscale Poincaré plots for visualizing the structure of heartbeat time series.

PubMed

Henriques, Teresa S; Mariani, Sara; Burykin, Anton; Rodrigues, Filipa; Silva, Tiago F; Goldberger, Ary L

2016-02-09

Poincaré delay maps are widely used in the analysis of cardiac interbeat interval (RR) dynamics. To facilitate visualization of the structure of these time series, we introduce multiscale Poincaré (MSP) plots. Starting with the original RR time series, the method employs a coarse-graining procedure to create a family of time series, each of which represents the system's dynamics in a different time scale. Next, the Poincaré plots are constructed for the original and the coarse-grained time series. Finally, as an optional adjunct, color can be added to each point to represent its normalized frequency. We illustrate the MSP method on simulated Gaussian white and 1/f noise time series. The MSP plots of 1/f noise time series reveal relative conservation of the phase space area over multiple time scales, while those of white noise show a marked reduction in area. We also show how MSP plots can be used to illustrate the loss of complexity when heartbeat time series from healthy subjects are compared with those from patients with chronic (congestive) heart failure syndrome or with atrial fibrillation. This generalized multiscale approach to Poincaré plots may be useful in visualizing other types of time series.

Degree-Pruning Dynamic Programming Approaches to Central Time Series Minimizing Dynamic Time Warping Distance.

PubMed

Sun, Tao; Liu, Hongbo; Yu, Hong; Chen, C L Philip

2016-06-28

The central time series crystallizes the common patterns of the set it represents. In this paper, we propose a global constrained degree-pruning dynamic programming (g(dp)²) approach to obtain the central time series through minimizing dynamic time warping (DTW) distance between two time series. The DTW matching path theory with global constraints is proved theoretically for our degree-pruning strategy, which is helpful to reduce the time complexity and computational cost. Our approach can achieve the optimal solution between two time series. An approximate method to the central time series of multiple time series [called as m_g(dp)²] is presented based on DTW barycenter averaging and our g(dp)² approach by considering hierarchically merging strategy. As illustrated by the experimental results, our approaches provide better within-group sum of squares and robustness than other relevant algorithms.

From Networks to Time Series

NASA Astrophysics Data System (ADS)

Shimada, Yutaka; Ikeguchi, Tohru; Shigehara, Takaomi

2012-10-01

In this Letter, we propose a framework to transform a complex network to a time series. The transformation from complex networks to time series is realized by the classical multidimensional scaling. Applying the transformation method to a model proposed by Watts and Strogatz [Nature (London) 393, 440 (1998)], we show that ring lattices are transformed to periodic time series, small-world networks to noisy periodic time series, and random networks to random time series. We also show that these relationships are analytically held by using the circulant-matrix theory and the perturbation theory of linear operators. The results are generalized to several high-dimensional lattices.

76 FR 14111 - Self-Regulatory Organizations; The NASDAQ Stock Market LLC; Notice of Filing and Immediate...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-15

... Options Series, adjusted option series and any options series until the time to expiration for such series... time to expiration for such series is less than nine months be treated differently. Specifically, under... until the time to expiration for such series is less than nine months. Accordingly, the requirement to...

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance

PubMed Central

Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy. PMID:29795600

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance.

PubMed

Liu, Yongli; Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy.

A Microlensing Analysis of the Central Engine in the Lensed Quasar WFI J2033-4723

NASA Astrophysics Data System (ADS)

Hyer, Gregory Edward; Morgan, Christopher; Bonvin, Vivien; Courbin, Fredric; Kochanek, Christopher; Falco, Emilio

2018-01-01

We report a detection of uncorrelated variability in 12 season optical light curves of the gravitationally lensed quasar WFI J2033-4723 from the 1.3m SMARTS telescope at CTIO and the 1.5m EULER telescope in La Silla. We analyzed this variability using the Monte Carlo technique of Kochanek (2004) to yield the first measurement of the size of this quasar’s accretion disk.

Seismic Data from Roosevelt Hot Springs, Utah FORGE Study Area

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

Miller, John

This set of data contains raw and processed 2D and 3D seismic data from the Utah FORGE study area near Roosevelt Hot Springs. The zipped archives numbered from 1-100 to 1001-1122 contain 3D seismic uncorrelated shot gatherers SEG-Y files. The zipped archives numbered from 1-100C to 1001-1122C contain 3D seismic correlated shot gatherers SEG-Y files. Other data have intuitive names.

Single-shot speckle reduction in numerical reconstruction of digitally recorded holograms.

PubMed

Hincapie, Diego; Herrera-Ramírez, Jorge; Garcia-Sucerquia, Jorge

2015-04-15

A single-shot method to reduce the speckle noise in the numerical reconstructions of electronically recorded holograms is presented. A recorded hologram with the dimensions N×M is split into S=T×T sub-holograms. The uncorrelated superposition of the individually reconstructed sub-holograms leads to an image with the speckle noise reduced proportionally to the 1/S law. The experimental results are presented to support the proposed methodology.

The Correlation of Active and Passive Microwave Outputs for the Skylab S-193 Sensor

NASA Technical Reports Server (NTRS)

Krishen, K.

1976-01-01

This paper presents the results of the correlation analysis of the Skylab S-193 13.9 GHz Radiometer/Scatterometer data. Computer analysis of the S-193 data shows more than 50 percent of the radiometer and scatterometer data are uncorrelated. The correlation coefficients computed for the data gathered over various ground scenes indicates the desirability of using both active and passive sensors for the determination of various Earth phenomena.

Linear Space-Variant Image Restoration of Photon-Limited Images

DTIC Science & Technology

1978-03-01

levels of performance of the wavefront seisor. The parameter ^ represents the residual rms wavefront error ^measurement noise plus ♦ttting error...known to be optimum only when the signal and noise are uncorrelated stationary random processes «nd when the noise statistics are gaussian. In the...regime of photon-Iimited imaging, the noise is non-gaussian and signaI-dependent, and it is therefore reasonable to assume that tome form of linear

Visibility Graph Based Time Series Analysis.

PubMed

Stephen, Mutua; Gu, Changgui; Yang, Huijie

2015-01-01

Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it's microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq) and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks.

Multichannel biomedical time series clustering via hierarchical probabilistic latent semantic analysis.

PubMed

Wang, Jin; Sun, Xiangping; Nahavandi, Saeid; Kouzani, Abbas; Wu, Yuchuan; She, Mary

2014-11-01

Biomedical time series clustering that automatically groups a collection of time series according to their internal similarity is of importance for medical record management and inspection such as bio-signals archiving and retrieval. In this paper, a novel framework that automatically groups a set of unlabelled multichannel biomedical time series according to their internal structural similarity is proposed. Specifically, we treat a multichannel biomedical time series as a document and extract local segments from the time series as words. We extend a topic model, i.e., the Hierarchical probabilistic Latent Semantic Analysis (H-pLSA), which was originally developed for visual motion analysis to cluster a set of unlabelled multichannel time series. The H-pLSA models each channel of the multichannel time series using a local pLSA in the first layer. The topics learned in the local pLSA are then fed to a global pLSA in the second layer to discover the categories of multichannel time series. Experiments on a dataset extracted from multichannel Electrocardiography (ECG) signals demonstrate that the proposed method performs better than previous state-of-the-art approaches and is relatively robust to the variations of parameters including length of local segments and dictionary size. Although the experimental evaluation used the multichannel ECG signals in a biometric scenario, the proposed algorithm is a universal framework for multichannel biomedical time series clustering according to their structural similarity, which has many applications in biomedical time series management. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Novel non-parametric models to estimate evolutionary rates and divergence times from heterochronous sequence data.

PubMed

Fourment, Mathieu; Holmes, Edward C

2014-07-24

Early methods for estimating divergence times from gene sequence data relied on the assumption of a molecular clock. More sophisticated methods were created to model rate variation and used auto-correlation of rates, local clocks, or the so called "uncorrelated relaxed clock" where substitution rates are assumed to be drawn from a parametric distribution. In the case of Bayesian inference methods the impact of the prior on branching times is not clearly understood, and if the amount of data is limited the posterior could be strongly influenced by the prior. We develop a maximum likelihood method--Physher--that uses local or discrete clocks to estimate evolutionary rates and divergence times from heterochronous sequence data. Using two empirical data sets we show that our discrete clock estimates are similar to those obtained by other methods, and that Physher outperformed some methods in the estimation of the root age of an influenza virus data set. A simulation analysis suggests that Physher can outperform a Bayesian method when the real topology contains two long branches below the root node, even when evolution is strongly clock-like. These results suggest it is advisable to use a variety of methods to estimate evolutionary rates and divergence times from heterochronous sequence data. Physher and the associated data sets used here are available online at http://code.google.com/p/physher/.

Analysis of Nonstationary Time Series for Biological Rhythms Research.

PubMed

Leise, Tanya L

2017-06-01

This article is part of a Journal of Biological Rhythms series exploring analysis and statistics topics relevant to researchers in biological rhythms and sleep research. The goal is to provide an overview of the most common issues that arise in the analysis and interpretation of data in these fields. In this article on time series analysis for biological rhythms, we describe some methods for assessing the rhythmic properties of time series, including tests of whether a time series is indeed rhythmic. Because biological rhythms can exhibit significant fluctuations in their period, phase, and amplitude, their analysis may require methods appropriate for nonstationary time series, such as wavelet transforms, which can measure how these rhythmic parameters change over time. We illustrate these methods using simulated and real time series.

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Time Series Remote Sensing in Monitoring the Spatio-Temporal Dynamics of Plant Invasions: A Study of Invasive Saltcedar (Tamarix Spp.)

NASA Astrophysics Data System (ADS)

Diao, Chunyuan

In today's big data era, the increasing availability of satellite and airborne platforms at various spatial and temporal scales creates unprecedented opportunities to understand the complex and dynamic systems (e.g., plant invasion). Time series remote sensing is becoming more and more important to monitor the earth system dynamics and interactions. To date, most of the time series remote sensing studies have been conducted with the images acquired at coarse spatial scale, due to their relatively high temporal resolution. The construction of time series at fine spatial scale, however, is limited to few or discrete images acquired within or across years. The objective of this research is to advance the time series remote sensing at fine spatial scale, particularly to shift from discrete time series remote sensing to continuous time series remote sensing. The objective will be achieved through the following aims: 1) Advance intra-annual time series remote sensing under the pure-pixel assumption; 2) Advance intra-annual time series remote sensing under the mixed-pixel assumption; 3) Advance inter-annual time series remote sensing in monitoring the land surface dynamics; and 4) Advance the species distribution model with time series remote sensing. Taking invasive saltcedar as an example, four methods (i.e., phenological time series remote sensing model, temporal partial unmixing method, multiyear spectral angle clustering model, and time series remote sensing-based spatially explicit species distribution model) were developed to achieve the objectives. Results indicated that the phenological time series remote sensing model could effectively map saltcedar distributions through characterizing the seasonal phenological dynamics of plant species throughout the year. The proposed temporal partial unmixing method, compared to conventional unmixing methods, could more accurately estimate saltcedar abundance within a pixel by exploiting the adequate temporal signatures of saltcedar. The multiyear spectral angle clustering model could guide the selection of the most representative remotely sensed image for repetitive saltcedar mapping over space and time. Through incorporating spatial autocorrelation, the species distribution model developed in the study could identify the suitable habitats of saltcedar at a fine spatial scale and locate appropriate areas at high risk of saltcedar infestation. Among 10 environmental variables, the distance to the river and the phenological attributes summarized by the time series remote sensing were regarded as the most important. These methods developed in the study provide new perspectives on how the continuous time series can be leveraged under various conditions to investigate the plant invasion dynamics.

A hybrid approach EMD-HW for short-term forecasting of daily stock market time series data

NASA Astrophysics Data System (ADS)

Awajan, Ahmad Mohd; Ismail, Mohd Tahir

2017-08-01

Recently, forecasting time series has attracted considerable attention in the field of analyzing financial time series data, specifically within the stock market index. Moreover, stock market forecasting is a challenging area of financial time-series forecasting. In this study, a hybrid methodology between Empirical Mode Decomposition with the Holt-Winter method (EMD-HW) is used to improve forecasting performances in financial time series. The strength of this EMD-HW lies in its ability to forecast non-stationary and non-linear time series without a need to use any transformation method. Moreover, EMD-HW has a relatively high accuracy and offers a new forecasting method in time series. The daily stock market time series data of 11 countries is applied to show the forecasting performance of the proposed EMD-HW. Based on the three forecast accuracy measures, the results indicate that EMD-HW forecasting performance is superior to traditional Holt-Winter forecasting method.

hctsa: A Computational Framework for Automated Time-Series Phenotyping Using Massive Feature Extraction.

PubMed

Fulcher, Ben D; Jones, Nick S

2017-11-22

Phenotype measurements frequently take the form of time series, but we currently lack a systematic method for relating these complex data streams to scientifically meaningful outcomes, such as relating the movement dynamics of organisms to their genotype or measurements of brain dynamics of a patient to their disease diagnosis. Previous work addressed this problem by comparing implementations of thousands of diverse scientific time-series analysis methods in an approach termed highly comparative time-series analysis. Here, we introduce hctsa, a software tool for applying this methodological approach to data. hctsa includes an architecture for computing over 7,700 time-series features and a suite of analysis and visualization algorithms to automatically select useful and interpretable time-series features for a given application. Using exemplar applications to high-throughput phenotyping experiments, we show how hctsa allows researchers to leverage decades of time-series research to quantify and understand informative structure in time-series data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Time series momentum and contrarian effects in the Chinese stock market

NASA Astrophysics Data System (ADS)

Shi, Huai-Long; Zhou, Wei-Xing

2017-10-01

This paper concentrates on the time series momentum or contrarian effects in the Chinese stock market. We evaluate the performance of the time series momentum strategy applied to major stock indices in mainland China and explore the relation between the performance of time series momentum strategies and some firm-specific characteristics. Our findings indicate that there is a time series momentum effect in the short run and a contrarian effect in the long run in the Chinese stock market. The performances of the time series momentum and contrarian strategies are highly dependent on the look-back and holding periods and firm-specific characteristics.

A Multitaper, Causal Decomposition for Stochastic, Multivariate Time Series: Application to High-Frequency Calcium Imaging Data.

PubMed

Sornborger, Andrew T; Lauderdale, James D

2016-11-01

Neural data analysis has increasingly incorporated causal information to study circuit connectivity. Dimensional reduction forms the basis of most analyses of large multivariate time series. Here, we present a new, multitaper-based decomposition for stochastic, multivariate time series that acts on the covariance of the time series at all lags, C ( τ ), as opposed to standard methods that decompose the time series, X ( t ), using only information at zero-lag. In both simulated and neural imaging examples, we demonstrate that methods that neglect the full causal structure may be discarding important dynamical information in a time series.

Graphical Data Analysis on the Circle: Wrap-Around Time Series Plots for (Interrupted) Time Series Designs.

PubMed

Rodgers, Joseph Lee; Beasley, William Howard; Schuelke, Matthew

2014-01-01

Many data structures, particularly time series data, are naturally seasonal, cyclical, or otherwise circular. Past graphical methods for time series have focused on linear plots. In this article, we move graphical analysis onto the circle. We focus on 2 particular methods, one old and one new. Rose diagrams are circular histograms and can be produced in several different forms using the RRose software system. In addition, we propose, develop, illustrate, and provide software support for a new circular graphical method, called Wrap-Around Time Series Plots (WATS Plots), which is a graphical method useful to support time series analyses in general but in particular in relation to interrupted time series designs. We illustrate the use of WATS Plots with an interrupted time series design evaluating the effect of the Oklahoma City bombing on birthrates in Oklahoma County during the 10 years surrounding the bombing of the Murrah Building in Oklahoma City. We compare WATS Plots with linear time series representations and overlay them with smoothing and error bands. Each method is shown to have advantages in relation to the other; in our example, the WATS Plots more clearly show the existence and effect size of the fertility differential.

Nonlinear parametric model for Granger causality of time series

NASA Astrophysics Data System (ADS)

Marinazzo, Daniele; Pellicoro, Mario; Stramaglia, Sebastiano

2006-06-01

The notion of Granger causality between two time series examines if the prediction of one series could be improved by incorporating information of the other. In particular, if the prediction error of the first time series is reduced by including measurements from the second time series, then the second time series is said to have a causal influence on the first one. We propose a radial basis function approach to nonlinear Granger causality. The proposed model is not constrained to be additive in variables from the two time series and can approximate any function of these variables, still being suitable to evaluate causality. Usefulness of this measure of causality is shown in two applications. In the first application, a physiological one, we consider time series of heart rate and blood pressure in congestive heart failure patients and patients affected by sepsis: we find that sepsis patients, unlike congestive heart failure patients, show symmetric causal relationships between the two time series. In the second application, we consider the feedback loop in a model of excitatory and inhibitory neurons: we find that in this system causality measures the combined influence of couplings and membrane time constants.

Multivariate time series clustering on geophysical data recorded at Mt. Etna from 1996 to 2003

NASA Astrophysics Data System (ADS)

Di Salvo, Roberto; Montalto, Placido; Nunnari, Giuseppe; Neri, Marco; Puglisi, Giuseppe

2013-02-01

Time series clustering is an important task in data analysis issues in order to extract implicit, previously unknown, and potentially useful information from a large collection of data. Finding useful similar trends in multivariate time series represents a challenge in several areas including geophysics environment research. While traditional time series analysis methods deal only with univariate time series, multivariate time series analysis is a more suitable approach in the field of research where different kinds of data are available. Moreover, the conventional time series clustering techniques do not provide desired results for geophysical datasets due to the huge amount of data whose sampling rate is different according to the nature of signal. In this paper, a novel approach concerning geophysical multivariate time series clustering is proposed using dynamic time series segmentation and Self Organizing Maps techniques. This method allows finding coupling among trends of different geophysical data recorded from monitoring networks at Mt. Etna spanning from 1996 to 2003, when the transition from summit eruptions to flank eruptions occurred. This information can be used to carry out a more careful evaluation of the state of volcano and to define potential hazard assessment at Mt. Etna.

An Energy-Based Similarity Measure for Time Series

NASA Astrophysics Data System (ADS)

Boudraa, Abdel-Ouahab; Cexus, Jean-Christophe; Groussat, Mathieu; Brunagel, Pierre

2007-12-01

A new similarity measure, called SimilB, for time series analysis, based on the cross-[InlineEquation not available: see fulltext.]-energy operator (2004), is introduced. [InlineEquation not available: see fulltext.] is a nonlinear measure which quantifies the interaction between two time series. Compared to Euclidean distance (ED) or the Pearson correlation coefficient (CC), SimilB includes the temporal information and relative changes of the time series using the first and second derivatives of the time series. SimilB is well suited for both nonstationary and stationary time series and particularly those presenting discontinuities. Some new properties of [InlineEquation not available: see fulltext.] are presented. Particularly, we show that [InlineEquation not available: see fulltext.] as similarity measure is robust to both scale and time shift. SimilB is illustrated with synthetic time series and an artificial dataset and compared to the CC and the ED measures.

A hybrid algorithm for clustering of time series data based on affinity search technique.

PubMed

Aghabozorgi, Saeed; Ying Wah, Teh; Herawan, Tutut; Jalab, Hamid A; Shaygan, Mohammad Amin; Jalali, Alireza

2014-01-01

Time series clustering is an important solution to various problems in numerous fields of research, including business, medical science, and finance. However, conventional clustering algorithms are not practical for time series data because they are essentially designed for static data. This impracticality results in poor clustering accuracy in several systems. In this paper, a new hybrid clustering algorithm is proposed based on the similarity in shape of time series data. Time series data are first grouped as subclusters based on similarity in time. The subclusters are then merged using the k-Medoids algorithm based on similarity in shape. This model has two contributions: (1) it is more accurate than other conventional and hybrid approaches and (2) it determines the similarity in shape among time series data with a low complexity. To evaluate the accuracy of the proposed model, the model is tested extensively using syntactic and real-world time series datasets.

A Hybrid Algorithm for Clustering of Time Series Data Based on Affinity Search Technique

PubMed Central

Aghabozorgi, Saeed; Ying Wah, Teh; Herawan, Tutut; Jalab, Hamid A.; Shaygan, Mohammad Amin; Jalali, Alireza

2014-01-01

Time series clustering is an important solution to various problems in numerous fields of research, including business, medical science, and finance. However, conventional clustering algorithms are not practical for time series data because they are essentially designed for static data. This impracticality results in poor clustering accuracy in several systems. In this paper, a new hybrid clustering algorithm is proposed based on the similarity in shape of time series data. Time series data are first grouped as subclusters based on similarity in time. The subclusters are then merged using the k-Medoids algorithm based on similarity in shape. This model has two contributions: (1) it is more accurate than other conventional and hybrid approaches and (2) it determines the similarity in shape among time series data with a low complexity. To evaluate the accuracy of the proposed model, the model is tested extensively using syntactic and real-world time series datasets. PMID:24982966

Macroscale water fluxes 3. Effects of land processes on variability of monthly river discharge

USGS Publications Warehouse

Milly, P.C.D.; Wetherald, R.T.

2002-01-01

A salient characteristic of river discharge is its temporal variability. The time series of flow at a point on a river can be viewed as the superposition of a smooth seasonal cycle and an irregular, random variation. Viewing the random component in the spectral domain facilitates both its characterization and an interpretation of its major physical controls from a global perspective. The power spectral density functions of monthly flow anomalies of many large rivers worldwide are typified by a "red noise" process: the density is higher at low frequencies (e.g., <1 y-1) than at high frequencies, indicating disproportionate (relative to uncorrelated "white noise") contribution of low frequencies to variability of monthly flow. For many high-latitude and arid-region rivers, however, the power is relatively evenly distributed across the frequency spectrum. The power spectrum of monthly flow can be interpreted as the product of the power spectrum of monthly basin total precipitation (which is typically white or slightly red) and several filters that have physical significance. The filters are associated with (1) the conversion of total precipitation (sum of rainfall and snowfall) to effective rainfall (liquid flux to the ground surface from above), (2) the conversion of effective rainfall to soil water excess (runoff), and (3) the conversion of soil water excess to river discharge. Inferences about the roles of each filter can be made through an analysis of observations, complemented by information from a global model of the ocean-atmosphere-land system. The first filter causes a snowmelt-related amplification of high-frequency variability in those basins that receive substantial snowfall. The second filter causes a relatively constant reduction in variability across all frequencies and can be predicted well by means of a semiempirical water balance relation. The third filter, associated with groundwater and surface water storage in the river basin, causes a strong reduction in high-frequency variability of many basins. The strength of this reduction can be quantified by an average residence time of water in storage, which is typically on the order of 20-50 days. The residence time is demonstrably influenced by freezing conditions in the basin, fractional cover of the basin by lakes, and runoff ratio (ratio of mean runoff to mean precipitation). Large lake areas enhance storage and can greatly increase total residence times (100 to several hundred days). Freezing conditions appear to cause bypassing of subsurface storage, thus reducing residence times (0-30 days). Small runoff ratios tend to be associated with arid regions, where the water table is deep, and consequently, most of the runoff is produced by processes that bypass the saturated zone, leading to relatively small residence times for such basins (0-40 days).

Clustering Financial Time Series by Network Community Analysis

NASA Astrophysics Data System (ADS)

Piccardi, Carlo; Calatroni, Lisa; Bertoni, Fabio

In this paper, we describe a method for clustering financial time series which is based on community analysis, a recently developed approach for partitioning the nodes of a network (graph). A network with N nodes is associated to the set of N time series. The weight of the link (i, j), which quantifies the similarity between the two corresponding time series, is defined according to a metric based on symbolic time series analysis, which has recently proved effective in the context of financial time series. Then, searching for network communities allows one to identify groups of nodes (and then time series) with strong similarity. A quantitative assessment of the significance of the obtained partition is also provided. The method is applied to two distinct case-studies concerning the US and Italy Stock Exchange, respectively. In the US case, the stability of the partitions over time is also thoroughly investigated. The results favorably compare with those obtained with the standard tools typically used for clustering financial time series, such as the minimal spanning tree and the hierarchical tree.

Solving large-scale PDE-constrained Bayesian inverse problems with Riemann manifold Hamiltonian Monte Carlo

NASA Astrophysics Data System (ADS)

Bui-Thanh, T.; Girolami, M.

2014-11-01

We consider the Riemann manifold Hamiltonian Monte Carlo (RMHMC) method for solving statistical inverse problems governed by partial differential equations (PDEs). The Bayesian framework is employed to cast the inverse problem into the task of statistical inference whose solution is the posterior distribution in infinite dimensional parameter space conditional upon observation data and Gaussian prior measure. We discretize both the likelihood and the prior using the H1-conforming finite element method together with a matrix transfer technique. The power of the RMHMC method is that it exploits the geometric structure induced by the PDE constraints of the underlying inverse problem. Consequently, each RMHMC posterior sample is almost uncorrelated/independent from the others providing statistically efficient Markov chain simulation. However this statistical efficiency comes at a computational cost. This motivates us to consider computationally more efficient strategies for RMHMC. At the heart of our construction is the fact that for Gaussian error structures the Fisher information matrix coincides with the Gauss-Newton Hessian. We exploit this fact in considering a computationally simplified RMHMC method combining state-of-the-art adjoint techniques and the superiority of the RMHMC method. Specifically, we first form the Gauss-Newton Hessian at the maximum a posteriori point and then use it as a fixed constant metric tensor throughout RMHMC simulation. This eliminates the need for the computationally costly differential geometric Christoffel symbols, which in turn greatly reduces computational effort at a corresponding loss of sampling efficiency. We further reduce the cost of forming the Fisher information matrix by using a low rank approximation via a randomized singular value decomposition technique. This is efficient since a small number of Hessian-vector products are required. The Hessian-vector product in turn requires only two extra PDE solves using the adjoint technique. Various numerical results up to 1025 parameters are presented to demonstrate the ability of the RMHMC method in exploring the geometric structure of the problem to propose (almost) uncorrelated/independent samples that are far away from each other, and yet the acceptance rate is almost unity. The results also suggest that for the PDE models considered the proposed fixed metric RMHMC can attain almost as high a quality performance as the original RMHMC, i.e. generating (almost) uncorrelated/independent samples, while being two orders of magnitude less computationally expensive.

A perturbative approach for enhancing the performance of time series forecasting.

PubMed

de Mattos Neto, Paulo S G; Ferreira, Tiago A E; Lima, Aranildo R; Vasconcelos, Germano C; Cavalcanti, George D C

2017-04-01

This paper proposes a method to perform time series prediction based on perturbation theory. The approach is based on continuously adjusting an initial forecasting model to asymptotically approximate a desired time series model. First, a predictive model generates an initial forecasting for a time series. Second, a residual time series is calculated as the difference between the original time series and the initial forecasting. If that residual series is not white noise, then it can be used to improve the accuracy of the initial model and a new predictive model is adjusted using residual series. The whole process is repeated until convergence or the residual series becomes white noise. The output of the method is then given by summing up the outputs of all trained predictive models in a perturbative sense. To test the method, an experimental investigation was conducted on six real world time series. A comparison was made with six other methods experimented and ten other results found in the literature. Results show that not only the performance of the initial model is significantly improved but also the proposed method outperforms the other results previously published. Copyright © 2017 Elsevier Ltd. All rights reserved.

Visibility Graph Based Time Series Analysis

PubMed Central

Stephen, Mutua; Gu, Changgui; Yang, Huijie

2015-01-01

Network based time series analysis has made considerable achievements in the recent years. By mapping mono/multivariate time series into networks, one can investigate both it’s microscopic and macroscopic behaviors. However, most proposed approaches lead to the construction of static networks consequently providing limited information on evolutionary behaviors. In the present paper we propose a method called visibility graph based time series analysis, in which series segments are mapped to visibility graphs as being descriptions of the corresponding states and the successively occurring states are linked. This procedure converts a time series to a temporal network and at the same time a network of networks. Findings from empirical records for stock markets in USA (S&P500 and Nasdaq) and artificial series generated by means of fractional Gaussian motions show that the method can provide us rich information benefiting short-term and long-term predictions. Theoretically, we propose a method to investigate time series from the viewpoint of network of networks. PMID:26571115

Quantifying memory in complex physiological time-series.

PubMed

Shirazi, Amir H; Raoufy, Mohammad R; Ebadi, Haleh; De Rui, Michele; Schiff, Sami; Mazloom, Roham; Hajizadeh, Sohrab; Gharibzadeh, Shahriar; Dehpour, Ahmad R; Amodio, Piero; Jafari, G Reza; Montagnese, Sara; Mani, Ali R

2013-01-01

In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of "memory length" was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on inverse statistical analysis and provides empiric evidence that rare fluctuations in cardio-respiratory time-series are 'forgotten' quickly in healthy subjects while the memory for such events is significantly prolonged in pathological conditions such as asthma (respiratory time-series) and liver cirrhosis (heart-beat time-series). The memory length was significantly higher in patients with uncontrolled asthma compared to healthy volunteers. Likewise, it was significantly higher in patients with decompensated cirrhosis compared to those with compensated cirrhosis and healthy volunteers. We also observed that the cardio-respiratory system has simple low order dynamics and short memory around its average, and high order dynamics around rare fluctuations.

Quantifying Memory in Complex Physiological Time-Series

PubMed Central

Shirazi, Amir H.; Raoufy, Mohammad R.; Ebadi, Haleh; De Rui, Michele; Schiff, Sami; Mazloom, Roham; Hajizadeh, Sohrab; Gharibzadeh, Shahriar; Dehpour, Ahmad R.; Amodio, Piero; Jafari, G. Reza; Montagnese, Sara; Mani, Ali R.

2013-01-01

In a time-series, memory is a statistical feature that lasts for a period of time and distinguishes the time-series from a random, or memory-less, process. In the present study, the concept of “memory length” was used to define the time period, or scale over which rare events within a physiological time-series do not appear randomly. The method is based on inverse statistical analysis and provides empiric evidence that rare fluctuations in cardio-respiratory time-series are ‘forgotten’ quickly in healthy subjects while the memory for such events is significantly prolonged in pathological conditions such as asthma (respiratory time-series) and liver cirrhosis (heart-beat time-series). The memory length was significantly higher in patients with uncontrolled asthma compared to healthy volunteers. Likewise, it was significantly higher in patients with decompensated cirrhosis compared to those with compensated cirrhosis and healthy volunteers. We also observed that the cardio-respiratory system has simple low order dynamics and short memory around its average, and high order dynamics around rare fluctuations. PMID:24039811

Scale-dependent intrinsic entropies of complex time series.

PubMed

Yeh, Jia-Rong; Peng, Chung-Kang; Huang, Norden E

2016-04-13

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal's complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease. © 2016 The Author(s).

A non linear analysis of human gait time series based on multifractal analysis and cross correlations

NASA Astrophysics Data System (ADS)

Muñoz-Diosdado, A.

2005-01-01

We analyzed databases with gait time series of adults and persons with Parkinson, Huntington and amyotrophic lateral sclerosis (ALS) diseases. We obtained the staircase graphs of accumulated events that can be bounded by a straight line whose slope can be used to distinguish between gait time series from healthy and ill persons. The global Hurst exponent of these series do not show tendencies, we intend that this is because some gait time series have monofractal behavior and others have multifractal behavior so they cannot be characterized with a single Hurst exponent. We calculated the multifractal spectra, obtained the spectra width and found that the spectra of the healthy young persons are almost monofractal. The spectra of ill persons are wider than the spectra of healthy persons. In opposition to the interbeat time series where the pathology implies loss of multifractality, in the gait time series the multifractal behavior emerges with the pathology. Data were collected from healthy and ill subjects as they walked in a roughly circular path and they have sensors in both feet, so we have one time series for the left foot and other for the right foot. First, we analyzed these time series separately, and then we compared both results, with direct comparison and with a cross correlation analysis. We tried to find differences in both time series that can be used as indicators of equilibrium problems.

Transverse momentum correlations of quarks in recursive jet models

NASA Astrophysics Data System (ADS)

Artru, X.; Belghobsi, Z.; Redouane-Salah, E.

2016-08-01

In the symmetric string fragmentation recipe adopted by PYTHIA for jet simulations, the transverse momenta of successive quarks are uncorrelated. This is a simplification but has no theoretical basis. Transverse momentum correlations are naturally expected, for instance, in a covariant multiperipheral model of quark hadronization. We propose a simple recipe of string fragmentation which leads to such correlations. The definition of the jet axis and its relation with the primordial transverse momentum of the quark is also discussed.

Low Frequency Acoustic Detection Research in Support of Human Detection Range Prediction

DTIC Science & Technology

1979-10-01

beat at narrow separations and hence made estimates of bandwidth difficult. In addition, Zwicker’s and Green’s data show large discrepancies, the...already known that this spurious low frequency noise can profoundly influence psychoacoustic results. For some years a binaural phenomenon known as the...tend to be uncorrelated in the two ears) and thus preserved the binaural advantage for the low frequency signals. Green et al. (Reference 21) used a

Investigating Traffic Avoidance Maneuver Preferences of Unmanned Aircraft Operators

DTIC Science & Technology

2016-06-13

aircraft in the NAS under instrument flight rules ( IFR ), in radio communications with ATC, and with a traffic display highlighting traffic within 80...Lincoln Laboratory developed uncorrelated encounter model [13] for evaluation of a preliminary pilot model. The UAS was assumed to be on an IFR ...Vol. 59, No. 1, Human Factors and Ergonomics Society, Santa Monica, CA, 2015, pp. 45-49. [10] Rorie, R. C., Fern, L., and Shively R. J., “The impact

Multiple-Array Detection, Association and Location of Infrasound and Seismo-Acoustic Event-Utilization of Ground Truth Information (Postprint)

DTIC Science & Technology

2012-05-07

AFRL-RV-PS- AFRL-RV-PS- TP-2012-0017 TP-2012-0017 MULTIPLE-ARRAY DETECTION, ASSOCIATION AND LOCATION OF INFRASOUND AND SEISMO-ACOUSTIC...ASSOCIATION AND LOCATION OF 5a. CONTRACT NUMBER FA8718-08-C-0008 INFRASOUND AND SEISMO-ACOUSTIC EVENT – UTILIZATION OF GROUND-TRUTH... infrasound signals from both correlated and uncorrelated noise. Approaches to this problem are implementation of the F-detector, which employs the F

The examination of headache activity using time-series research designs.

PubMed

Houle, Timothy T; Remble, Thomas A; Houle, Thomas A

2005-05-01

The majority of research conducted on headache has utilized cross-sectional designs which preclude the examination of dynamic factors and principally rely on group-level effects. The present article describes the application of an individual-oriented process model using time-series analytical techniques. The blending of a time-series approach with an interactive process model allows consideration of the relationships of intra-individual dynamic processes, while not precluding the researcher to examine inter-individual differences. The authors explore the nature of time-series data and present two necessary assumptions underlying the time-series approach. The concept of shock and its contribution to headache activity is also presented. The time-series approach is not without its problems and two such problems are specifically reported: autocorrelation and the distribution of daily observations. The article concludes with the presentation of several analytical techniques suited to examine the time-series interactive process model.

Data mining of molecular dynamics data reveals Li diffusion characteristics in garnet Li7La3Zr2O12

PubMed Central

Chen, Chi; Lu, Ziheng; Ciucci, Francesco

2017-01-01

Understanding Li diffusion in solid conductors is essential for the next generation Li batteries. Here we show that density-based clustering of the trajectories computed using molecular dynamics simulations helps elucidate the Li diffusion mechanism within the Li7La3Zr2O12 (LLZO) crystal lattice. This unsupervised learning method recognizes lattice sites, is able to give the site type, and can identify Li hopping events. Results show that, while the cubic LLZO has a much higher hopping rate compared to its tetragonal counterpart, most of the Li hops in the cubic LLZO do not contribute to the diffusivity due to the dominance of back-and-forth type jumps. The hopping analysis and local Li configuration statistics give evidence that Li diffusivity in cubic LLZO is limited by the low vacancy concentration. The hopping statistics also shows uncorrelated Poisson-like diffusion for Li in the cubic LLZO, and correlated diffusion for Li in the tetragonal LLZO in the temporal scale. Further analysis of the spatio-temporal correlation using site-to-site mutual information confirms the weak site dependence of Li diffusion in the cubic LLZO as the origin for the uncorrelated diffusion. This work puts forward a perspective on combining machine learning and information theory to interpret results of molecular dynamics simulations. PMID:28094317

Perception-action dissociation generalizes to the size-inertia illusion.

PubMed

Platkiewicz, Jonathan; Hayward, Vincent

2014-04-01

Two objects of similar visual aspects and of equal mass, but of different sizes, generally do not elicit the same percept of heaviness in humans. The larger object is consistently felt to be lighter than the smaller, an effect known as the "size-weight illusion." When asked to repeatedly lift the two objects, the grip forces were observed to adapt rapidly to the true object weight while the size-weight illusion persisted, a phenomenon interpreted as a dissociation between perception and action. We investigated whether the same phenomenon can be observed if the mass of an object is available to participants through inertial rather than gravitational cues and if the number and statistics of the stimuli is such that participants cannot remember each individual stimulus. We compared the responses of 10 participants in 2 experimental conditions, where they manipulated 33 objects having uncorrelated masses and sizes, supported by a frictionless, air-bearing slide that could be oriented vertically or horizontally. We also analyzed the participants' anticipatory motor behavior by measuring the grip force before motion onset. We found that the perceptual illusory effect was quantitatively the same in the two conditions and observed that both visual size and haptic mass had a negligible effect on the anticipatory gripping control of the participants in the gravitational and inertial conditions, despite the enormous differences in the mechanics of the two conditions and the large set of uncorrelated stimuli.

Optimizing weak lensing mass estimates for cluster profile uncertainty

DOE PAGES

Gruen, D.; Bernstein, G. M.; Lam, T. Y.; ...

2011-09-11

Weak lensing measurements of cluster masses are necessary for calibrating mass-observable relations (MORs) to investigate the growth of structure and the properties of dark energy. However, the measured cluster shear signal varies at fixed mass M 200m due to inherent ellipticity of background galaxies, intervening structures along the line of sight, and variations in the cluster structure due to scatter in concentrations, asphericity and substructure. We use N-body simulated halos to derive and evaluate a weak lensing circular aperture mass measurement M ap that minimizes the mass estimate variance <(M ap - M 200m) 2> in the presence of allmore » these forms of variability. Depending on halo mass and observational conditions, the resulting mass estimator improves on M ap filters optimized for circular NFW-profile clusters in the presence of uncorrelated large scale structure (LSS) about as much as the latter improve on an estimator that only minimizes the influence of shape noise. Optimizing for uncorrelated LSS while ignoring the variation of internal cluster structure puts too much weight on the profile near the cores of halos, and under some circumstances can even be worse than not accounting for LSS at all. As a result, we discuss the impact of variability in cluster structure and correlated structures on the design and performance of weak lensing surveys intended to calibrate cluster MORs.« less

Measurement of the top quark mass using single top quark events in proton-proton collisions at $$\\sqrt{s}= 8$$ TeV

DOE PAGES

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; ...

2017-05-29

In this study, a measurement of the top quark mass is reported in events containing a single top quark produced via the electroweak t channel. The analysis is performed using data from proton-proton collisions collected with the CMS detector at the LHC at a centre-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 19.7 fb –1. Top quark candidates are reconstructed from their decay to a W boson and a b quark, with the W boson decaying leptonically to a muon and a neutrino. The final state signature and kinematic properties of single top quark events in themore » t channel are used to enhance the purity of the sample, suppressing the contribution from top quark pair production. A fit to the invariant mass distribution of reconstructed top quark candidates yields a value of the top quark mass of 172.95 ± 0.77(stat) +0.97 –0.93(syst)GeV. This result is in agreement with the current world average, and represents the first measurement of the top quark mass in event topologies not dominated by top quark pair production, therefore contributing to future averages with partially uncorrelated systematic uncertainties and a largely uncorrelated statistical uncertainty.« less

Data mining of molecular dynamics data reveals Li diffusion characteristics in garnet Li7La3Zr2O12

NASA Astrophysics Data System (ADS)

Chen, Chi; Lu, Ziheng; Ciucci, Francesco

2017-01-01

Understanding Li diffusion in solid conductors is essential for the next generation Li batteries. Here we show that density-based clustering of the trajectories computed using molecular dynamics simulations helps elucidate the Li diffusion mechanism within the Li7La3Zr2O12 (LLZO) crystal lattice. This unsupervised learning method recognizes lattice sites, is able to give the site type, and can identify Li hopping events. Results show that, while the cubic LLZO has a much higher hopping rate compared to its tetragonal counterpart, most of the Li hops in the cubic LLZO do not contribute to the diffusivity due to the dominance of back-and-forth type jumps. The hopping analysis and local Li configuration statistics give evidence that Li diffusivity in cubic LLZO is limited by the low vacancy concentration. The hopping statistics also shows uncorrelated Poisson-like diffusion for Li in the cubic LLZO, and correlated diffusion for Li in the tetragonal LLZO in the temporal scale. Further analysis of the spatio-temporal correlation using site-to-site mutual information confirms the weak site dependence of Li diffusion in the cubic LLZO as the origin for the uncorrelated diffusion. This work puts forward a perspective on combining machine learning and information theory to interpret results of molecular dynamics simulations.

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.

Improving estimates of ecosystem metabolism by reducing effects of tidal advection on dissolved oxygen time series

EPA Science Inventory

In aquatic systems, time series of dissolved oxygen (DO) have been used to compute estimates of ecosystem metabolism. Central to this open-water method is the assumption that the DO time series is a Lagrangian specification of the flow field. However, most DO time series are coll...

76 FR 28897 - Magnuson-Stevens Act Provisions; Fisheries Off West Coast States; Pacific Coast Groundfish...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-19

... time series became closer (while depletion at the end of the time series became more divergent); (4) the agreement in the recruitment time series was much improved; (5) recruitment deviations in log space showed much closer agreement; and (6) the fishing intensity time series showed much closer...

75 FR 4570 - Government-Owned Inventions; Availability for Licensing

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-28

... applications. Signal-to-Noise Enhancement in Imaging Applications Using a Time-Series of Images Description of... applications that use a time-series of images. In one embodiment of the invention, a time-series of images is... Imaging Applications Using a Time-Series of Images'' (HHS Reference No. E-292- 2009/0-US-01). Related...

Do missing data influence the accuracy of divergence-time estimation with BEAST?

PubMed

Zheng, Yuchi; Wiens, John J

2015-04-01

Time-calibrated phylogenies have become essential to evolutionary biology. A recurrent and unresolved question for dating analyses is whether genes with missing data cells should be included or excluded. This issue is particularly unclear for the most widely used dating method, the uncorrelated lognormal approach implemented in BEAST. Here, we test the robustness of this method to missing data. We compare divergence-time estimates from a nearly complete dataset (20 nuclear genes for 32 species of squamate reptiles) to those from subsampled matrices, including those with 5 or 2 complete loci only and those with 5 or 8 incomplete loci added. In general, missing data had little impact on estimated dates (mean error of ∼5Myr per node or less, given an overall age of ∼220Myr in squamates), even when 80% of sampled genes had 75% missing data. Mean errors were somewhat higher when all genes were 75% incomplete (∼17Myr). However, errors increased dramatically when only 2 of 9 fossil calibration points were included (∼40Myr), regardless of missing data. Overall, missing data (and even numbers of genes sampled) may have only minor impacts on the accuracy of divergence dating with BEAST, relative to the dramatic effects of fossil calibrations. Copyright © 2015 Elsevier Inc. All rights reserved.

Phylogeny, time divergence, and historical biogeography of the South American Liolaemus alticolor-bibronii group (Iguania: Liolaemidae)

PubMed Central

2018-01-01

The genus Liolaemus comprises more than 260 species and can be divided in two subgenera: Eulaemus and Liolaemus sensu stricto. In this paper, we present a phylogenetic analysis, divergence times, and ancestral distribution ranges of the Liolaemus alticolor-bibronii group (Liolaemus sensu stricto subgenus). We inferred a total evidence phylogeny combining molecular (Cytb and 12S genes) and morphological characters using Maximum Parsimony and Bayesian Inference. Divergence times were calculated using Bayesian MCMC with an uncorrelated lognormal distributed relaxed clock, calibrated with a fossil record. Ancestral ranges were estimated using the Dispersal-Extinction-Cladogenesis (DEC-Lagrange). Effects of some a priori parameters of DEC were also tested. Distribution ranged from central Perú to southern Argentina, including areas at sea level up to the high Andes. The L. alticolor-bibronii group was recovered as monophyletic, formed by two clades: L. walkeri and L. gracilis, the latter can be split in two groups. Additionally, many species candidates were recognized. We estimate that the L. alticolor-bibronii group diversified 14.5 Myr ago, during the Middle Miocene. Our results suggest that the ancestor of the Liolaemus alticolor-bibronii group was distributed in a wide area including Patagonia and Puna highlands. The speciation pattern follows the South-North Diversification Hypothesis, following the Andean uplift. PMID:29479502

78 FR 15385 - Self-Regulatory Organizations; NASDAQ OMX BX, Inc.; Notice of Filing of Proposed Rule Change To...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-11

... Series, any adjusted option series, and any option series until the time to expiration for such series is... existing requirement may at times discourage liquidity in particular options series because a market maker... the option is subject to the Price/Time execution algorithm, the Directed Market Maker shall receive...

A novel water quality data analysis framework based on time-series data mining.

PubMed

Deng, Weihui; Wang, Guoyin

2017-07-01

The rapid development of time-series data mining provides an emerging method for water resource management research. In this paper, based on the time-series data mining methodology, we propose a novel and general analysis framework for water quality time-series data. It consists of two parts: implementation components and common tasks of time-series data mining in water quality data. In the first part, we propose to granulate the time series into several two-dimensional normal clouds and calculate the similarities in the granulated level. On the basis of the similarity matrix, the similarity search, anomaly detection, and pattern discovery tasks in the water quality time-series instance dataset can be easily implemented in the second part. We present a case study of this analysis framework on weekly Dissolve Oxygen time-series data collected from five monitoring stations on the upper reaches of Yangtze River, China. It discovered the relationship of water quality in the mainstream and tributary as well as the main changing patterns of DO. The experimental results show that the proposed analysis framework is a feasible and efficient method to mine the hidden and valuable knowledge from water quality historical time-series data. Copyright © 2017 Elsevier Ltd. All rights reserved.

Climate Prediction Center - Stratosphere: Polar Stratosphere and Ozone

Science.gov Websites

depletion processes can occur. In addition, the latitudinal-time cross sections shows the thermal evolution UV Daily Dosage Estimate South Polar Vertical Ozone Profile Time Series of Size of S.H. Polar Vortex Time Series of Size of S.H. PSC Temperature Time Series of Size of N.H. Polar Vortex Time Series of

Using forbidden ordinal patterns to detect determinism in irregularly sampled time series.

PubMed

Kulp, C W; Chobot, J M; Niskala, B J; Needhammer, C J

2016-02-01

It is known that when symbolizing a time series into ordinal patterns using the Bandt-Pompe (BP) methodology, there will be ordinal patterns called forbidden patterns that do not occur in a deterministic series. The existence of forbidden patterns can be used to identify deterministic dynamics. In this paper, the ability to use forbidden patterns to detect determinism in irregularly sampled time series is tested on data generated from a continuous model system. The study is done in three parts. First, the effects of sampling time on the number of forbidden patterns are studied on regularly sampled time series. The next two parts focus on two types of irregular-sampling, missing data and timing jitter. It is shown that forbidden patterns can be used to detect determinism in irregularly sampled time series for low degrees of sampling irregularity (as defined in the paper). In addition, comments are made about the appropriateness of using the BP methodology to symbolize irregularly sampled time series.

Sensor-Generated Time Series Events: A Definition Language

PubMed Central

Anguera, Aurea; Lara, Juan A.; Lizcano, David; Martínez, Maria Aurora; Pazos, Juan

2012-01-01

There are now a great many domains where information is recorded by sensors over a limited time period or on a permanent basis. This data flow leads to sequences of data known as time series. In many domains, like seismography or medicine, time series analysis focuses on particular regions of interest, known as events, whereas the remainder of the time series contains hardly any useful information. In these domains, there is a need for mechanisms to identify and locate such events. In this paper, we propose an events definition language that is general enough to be used to easily and naturally define events in time series recorded by sensors in any domain. The proposed language has been applied to the definition of time series events generated within the branch of medicine dealing with balance-related functions in human beings. A device, called posturograph, is used to study balance-related functions. The platform has four sensors that record the pressure intensity being exerted on the platform, generating four interrelated time series. As opposed to the existing ad hoc proposals, the results confirm that the proposed language is valid, that is generally applicable and accurate, for identifying the events contained in the time series.

Homogenising time series: Beliefs, dogmas and facts

NASA Astrophysics Data System (ADS)

Domonkos, P.

2010-09-01

For obtaining reliable information about climate change and climate variability the use of high quality data series is essentially important, and one basic tool of quality improvements is the statistical homogenisation of observed time series. In the recent decades large number of homogenisation methods has been developed, but the real effects of their application on time series are still not known entirely. The ongoing COST HOME project (COST ES0601) is devoted to reveal the real impacts of homogenisation methods more detailed and with higher confidence than earlier. As part of the COST activity, a benchmark dataset was built whose characteristics approach well the characteristics of real networks of observed time series. This dataset offers much better opportunity than ever to test the wide variety of homogenisation methods, and analyse the real effects of selected theoretical recommendations. The author believes that several old theoretical rules have to be re-evaluated. Some examples of the hot questions, a) Statistically detected change-points can be accepted only with the confirmation of metadata information? b) Do semi-hierarchic algorithms for detecting multiple change-points in time series function effectively in practise? c) Is it good to limit the spatial comparison of candidate series with up to five other series in the neighbourhood? Empirical results - those from the COST benchmark, and other experiments too - show that real observed time series usually include several inhomogeneities of different sizes. Small inhomogeneities seem like part of the climatic variability, thus the pure application of classic theory that change-points of observed time series can be found and corrected one-by-one is impossible. However, after homogenisation the linear trends, seasonal changes and long-term fluctuations of time series are usually much closer to the reality, than in raw time series. The developers and users of homogenisation methods have to bear in mind that the eventual purpose of homogenisation is not to find change-points, but to have the observed time series with statistical properties those characterise well the climate change and climate variability.

The storage time, age, and erosion hazard of laterally accreted sediment on the floodplain of a simulated meandering river

USGS Publications Warehouse

Bradley, D. Nathan; Tucker, Gregory E.

2013-01-01

A sediment particle traversing the fluvial system may spend the majority of the total transit time at rest, stored in various sedimentary deposits. Floodplains are among the most important of these deposits, with the potential to store large amounts of sediment for long periods of time. The virtual velocity of a sediment grain depends strongly on the amount of time spent in storage, but little is known about sediment storage times. Measurements of floodplain vegetation age have suggested that storage times are exponentially distributed, a case that arises when all the sediment on a floodplain is equally vulnerable to erosion in a given interval. This assumption has been incorporated into sediment routing models, despite some evidence that younger sediment is more likely to be eroded from floodplains than older sediment. We investigate the relationship between sediment age and erosion, which we term the “erosion hazard,” with a model of a meandering river that constructs its floodplain by lateral accretion. We find that the erosion hazard decreases with sediment age, leading to a storage time distribution that is not exponential. We propose an alternate model that requires that channel motion is approximately diffusive and results in a heavy tailed distribution of storage time. The model applies to timescales over which the direction of channel motion is uncorrelated. We speculate that the lower end of this range of time is set by the meander cutoff timescale and the upper end is set by processes that limit the width of the meander belt.

Causal Inference and the Comparative Interrupted Time Series Design: Findings from Within-Study Comparisons

ERIC Educational Resources Information Center

St. Clair, Travis; Hallberg, Kelly; Cook, Thomas D.

2014-01-01

Researchers are increasingly using comparative interrupted time series (CITS) designs to estimate the effects of programs and policies when randomized controlled trials are not feasible. In a simple interrupted time series design, researchers compare the pre-treatment values of a treatment group time series to post-treatment values in order to…

Time Series Model Identification and Prediction Variance Horizon.

DTIC Science & Technology

1980-06-01

stationary time series Y(t). -6- In terms of p(v), the definition of the three time series memory types is: No Memory Short Memory Long Memory X IP (v)I 0 0...X lp(v)l < - I IP (v) = v=1 v=l v=l Within short memory time series there are three types whose classification in terms of correlation functions is...1974) "Some Recent Advances in Time Series Modeling", TEEE Transactions on Automatic ControZ, VoZ . AC-19, No. 6, December, 723-730. Parzen, E. (1976) "An

Extending nonlinear analysis to short ecological time series.

PubMed

Hsieh, Chih-hao; Anderson, Christian; Sugihara, George

2008-01-01

Nonlinearity is important and ubiquitous in ecology. Though detectable in principle, nonlinear behavior is often difficult to characterize, analyze, and incorporate mechanistically into models of ecosystem function. One obvious reason is that quantitative nonlinear analysis tools are data intensive (require long time series), and time series in ecology are generally short. Here we demonstrate a useful method that circumvents data limitation and reduces sampling error by combining ecologically similar multispecies time series into one long time series. With this technique, individual ecological time series containing as few as 20 data points can be mined for such important information as (1) significantly improved forecast ability, (2) the presence and location of nonlinearity, and (3) the effective dimensionality (the number of relevant variables) of an ecological system.

Dynamic behavior of the interaction between epidemics and cascades on heterogeneous networks

NASA Astrophysics Data System (ADS)

Jiang, Lurong; Jin, Xinyu; Xia, Yongxiang; Ouyang, Bo; Wu, Duanpo

2014-12-01

Epidemic spreading and cascading failure are two important dynamical processes on complex networks. They have been investigated separately for a long time. But in the real world, these two dynamics sometimes may interact with each other. In this paper, we explore a model combined with the SIR epidemic spreading model and a local load sharing cascading failure model. There exists a critical value of the tolerance parameter for which the epidemic with high infection probability can spread out and infect a fraction of the network in this model. When the tolerance parameter is smaller than the critical value, the cascading failure cuts off the abundance of paths and blocks the spreading of the epidemic locally. While the tolerance parameter is larger than the critical value, the epidemic spreads out and infects a fraction of the network. A method for estimating the critical value is proposed. In simulations, we verify the effectiveness of this method in the uncorrelated configuration model (UCM) scale-free networks.

Initial correlations in open-systems dynamics: The Jaynes-Cummings model

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

Smirne, Andrea; Vacchini, Bassano; INFN, Sezione di Milano, Via Celoria 16, I-20133 Milano

2010-12-15

Employing the trace distance as a measure for the distinguishability of quantum states, we study the influence of initial correlations on the dynamics of open systems. We concentrate on the Jaynes-Cummings model for which the knowledge of the exact joint dynamics of system and reservoir allows the treatment of initial states with arbitrary correlations. As a measure for the correlations in the initial state we consider the trace distance between the system-environment state and the product of its marginal states. In particular, we examine the correlations contained in the thermal equilibrium state for the total system, analyze their dependence onmore » the temperature and on the coupling strength, and demonstrate their connection to the entanglement properties of the eigenstates of the Hamiltonian. A detailed study of the time dependence of the distinguishability of the open system states evolving from the thermal equilibrium state and its corresponding uncorrelated product state shows that the open system dynamically uncovers typical features of the initial correlations.« less

Potential Explosion Hazard of Carbonaceous Nanoparticles: Screening of Allotropes

PubMed Central

Turkevich, Leonid A.; Fernback, Joseph; Dastidar, Ashok G.; Osterberg, Paul

2016-01-01

There is a concern that engineered carbon nanoparticles, when manufactured on an industrial scale, will pose an explosion hazard. Explosion testing has been performed on 20 codes of carbonaceous powders. These include several different codes of SWCNTs (single-walled carbon nanotubes), MWCNTs (multi-walled carbon nanotubes) and CNFs (carbon nanofibers), graphene, diamond, fullerene, as well as several different control carbon blacks and graphites. Explosion screening was performed in a 20 L explosion chamber (ASTM E1226 protocol), at a concentration of 500 g/m3, using a 5 kJ ignition source. Time traces of overpressure were recorded. Samples typically exhibited overpressures of 5–7 bar, and deflagration index KSt = V1/3 (dP/dt)max ~ 10 – 80 bar-m/s, which places these materials in European Dust Explosion Class St-1. There is minimal variation between these different materials. The explosive characteristics of these carbonaceous powders are uncorrelated with primary particle size (BET specific surface area). PMID:27468178

Development and Validation of the Single Item Narcissism Scale (SINS)

PubMed Central

Konrath, Sara; Meier, Brian P.; Bushman, Brad J.

2014-01-01

Main Objectives The narcissistic personality is characterized by grandiosity, entitlement, and low empathy. This paper describes the development and validation of the Single Item Narcissism Scale (SINS). Although the use of longer instruments is superior in most circumstances, we recommend the SINS in some circumstances (e.g. under serious time constraints, online studies). Methods In 11 independent studies (total N = 2,250), we demonstrate the SINS' psychometric properties. Results The SINS is significantly correlated with longer narcissism scales, but uncorrelated with self-esteem. It also has high test-retest reliability. We validate the SINS in a variety of samples (e.g., undergraduates, nationally representative adults), intrapersonal correlates (e.g., positive affect, depression), and interpersonal correlates (e.g., aggression, relationship quality, prosocial behavior). The SINS taps into the more fragile and less desirable components of narcissism. Significance The SINS can be a useful tool for researchers, especially when it is important to measure narcissism with constraints preventing the use of longer measures. PMID:25093508

Asymmetric noise sensitivity of pulse trains in an excitable microlaser with delayed optical feedback

NASA Astrophysics Data System (ADS)

Terrien, Soizic; Krauskopf, Bernd; Broderick, Neil G. R.; Andréoli, Louis; Selmi, Foued; Braive, Rémy; Beaudoin, Grégoire; Sagnes, Isabelle; Barbay, Sylvain

2017-10-01

A semiconductor micropillar laser with delayed optical feedback is considered. In the excitable regime, we show that a single optical perturbation can trigger a train of pulses that is sustained for a finite duration. The distribution of the pulse train duration exhibits an exponential behavior characteristic of a noise-induced process driven by uncorrelated white noise present in the system. The comparison of experimental observations with theoretical and numerical analysis of a minimal model yields excellent agreement. Importantly, the random switch-off process takes place between two attractors of different nature: an equilibrium and a periodic orbit. Our analysis shows that there is a small time window during which the pulsations are very sensitive to noise, and this explains the observed strong bias toward switch-off. These results raise the possibility of all optical control of the pulse train duration that may have an impact for practical applications in photonics and may also apply to the dynamics of other noise-driven excitable systems with delayed feedback.

A public study of the lifetime distribution of soap films

NASA Astrophysics Data System (ADS)

Tobin, S. T.; Meagher, A. J.; Bulfin, B.; Möbius, M.; Hutzler, S.

2011-08-01

We present data for the lifetime distribution of soap films made from commercial dish-washing solution and contained in sealed cylinders. Data for over 2500 films were gathered during a 2-month exhibition on the science and art of bubbles and foams in Dublin's Science Gallery. Visitors to the gallery were invited to create 10-20 parallel soap films in acrylic tubes which were sealed with cork stoppers. Individual film bursts occurred at random and were uncorrelated. The total number of remaining films in the tubes was recorded every day. Visitors could monitor the status of their soap film tube and the daily updated histogram of the lifetime of all films. The histogram of the bubble lifetimes is well described by a Weibull distribution, which indicates that the failure rate is not constant and increases over time. Unsealed cylinders show drastically reduced film lifetimes. This experiment illustrates the difference between the unpredictability of the lifetime of individual films and the existence of a well-defined lifetime distribution for the ensemble.

Disentangling prototypicality and social desirability: the case of the KNOWI task.

PubMed

Turan, Bulent

2011-01-01

The prototype of indicators of a relationship partner who can be trusted to be responsive at times of stress is one kind of social knowledge structure. The Knowledge of Indicators (KNOWI) Task assesses individual differences in knowledge about these prototypic indicators. In constructing the KNOWI, an iterative procedure was used in an attempt to identify those indicators for which ratings of prototypicality are not influenced by social desirability. Study 1 demonstrated that the correlation between ratings of prototypicality and social desirability is indeed eliminated for the final set of indicators retained in the KNOWI. Study 2 tested the prototype matching hypothesis: Comparing an actual partner to the prototype might shape global judgments about that partner's responsiveness. Because in Study 2 only those indicators that are uncorrelated with social desirability were used, this result cannot be explained by social desirability. These results support the construct validity of the indicators used in the KNOWI Task, which seems to be a precise assessment tool not influenced by social desirability.

Power-law decay exponents: A dynamical criterion for predicting thermalization

NASA Astrophysics Data System (ADS)

Távora, Marco; Torres-Herrera, E. J.; Santos, Lea F.

2017-01-01

From the analysis of the relaxation process of isolated lattice many-body quantum systems quenched far from equilibrium, we deduce a criterion for predicting when they are certain to thermalize. It is based on the algebraic behavior ∝t-γ of the survival probability at long times. We show that the value of the power-law exponent γ depends on the shape and filling of the weighted energy distribution of the initial state. Two scenarios are explored in detail: γ ≥2 and γ <1 . Exponents γ ≥2 imply that the energy distribution of the initial state is ergodically filled and the eigenstates are uncorrelated, so thermalization is guaranteed to happen. In this case, the power-law behavior is caused by bounds in the energy spectrum. Decays with γ <1 emerge when the energy eigenstates are correlated and signal lack of ergodicity. They are typical of systems undergoing localization due to strong onsite disorder and are found also in clean integrable systems.

A coarsening model for self-organization of tropical convection

NASA Astrophysics Data System (ADS)

Craig, G. C.; Mack, J. M.

2013-08-01

If the influence of humidity on cumulus convection causes moist regions of the tropical troposphere to become moister and dry regions to become drier, and if horizontal mixing of moisture is not rapid enough to overcome this tendency, then the atmosphere will tend to separate into increasingly large moist and dry regions through a process of coarsening. We present a simple model for the moisture budget of the free troposphere, including subsidence drying, convective moistening, and horizontal mixing, and a constraint on total precipitation representing radiative-convective equilibrium. When initialized with a spatially uncorrelated moisture distribution, the model shows self-organization of precipitation with two main stages: A coarsening stage where the correlation length grows proportional to time to the power 1/2 and a droplet stage where precipitation is confined to a decreasing number of circular moist regions. A potential function is introduced to characterize the tendency for self-organization, which could be a useful diagnostic for analyzing cloud-resolving model simulations.

Triple galaxies and a hidden mass problem

NASA Technical Reports Server (NTRS)

Karachentsev, I. D.; Karachentseva, V. E.; Lebedev, V. S.

1990-01-01

The authors consider a homogeneous sample of 84 triple systems of galaxies with components brighter than m = 15.7, located in the northern sky and satisfying an isolation criterion with respect to neighboring galaxies in projection. The distributions of basic dynamical parameters for triplets have median values as follows: radial velocity dispersion 133 km/s, mean harmonic radius 63 kpc, absolute magnitude of galaxies M sub B equals -20.38, crossing time tau = 0.04 H(sup minus 1). For different ways of estimation the median mass-to-luminosity ratio is (20 - 30). A comparison of the last value with the ones for single and binary galaxies shows the presence of a virial mass excess for triplets by a factor 4. The mass-to-luminosity ratio is practically uncorrelated with linear size of triplets or with morphological types of their components. We note that a significant part of the virial excess may be explained by the presence of nonisolated triple configurations in the sample, which are produced by debris of more populous groups of galaxies.

Measurement and subtraction of Schumann resonances at gravitational-wave interferometers

NASA Astrophysics Data System (ADS)

Coughlin, Michael W.; Cirone, Alessio; Meyers, Patrick; Atsuta, Sho; Boschi, Valerio; Chincarini, Andrea; Christensen, Nelson L.; De Rosa, Rosario; Effler, Anamaria; Fiori, Irene; Gołkowski, Mark; Guidry, Melissa; Harms, Jan; Hayama, Kazuhiro; Kataoka, Yuu; Kubisz, Jerzy; Kulak, Andrzej; Laxen, Michael; Matas, Andrew; Mlynarczyk, Janusz; Ogawa, Tsutomu; Paoletti, Federico; Salvador, Jacobo; Schofield, Robert; Somiya, Kentaro; Thrane, Eric

2018-05-01

Correlated magnetic noise from Schumann resonances threatens to contaminate the observation of a stochastic gravitational-wave background in interferometric detectors. In previous work, we reported on the first effort to eliminate global correlated noise from the Schumann resonances using Wiener filtering, demonstrating as much as a factor of two reduction in the coherence between magnetometers on different continents. In this work, we present results from dedicated magnetometer measurements at the Virgo and KAGRA sites, which are the first results for subtraction using data from gravitational-wave detector sites. We compare these measurements to a growing network of permanent magnetometer stations, including at the LIGO sites. We show the effect of mutual magnetometer attraction, arguing that magnetometers should be placed at least one meter from one another. In addition, for the first time, we show how dedicated measurements by magnetometers near to the interferometers can reduce coherence to a level consistent with uncorrelated noise, making a potential detection of a stochastic gravitational-wave background possible.

Membrane Potential Dynamics of CA1 Pyramidal Neurons During Hippocampal Ripples in Awake Mice

PubMed Central

Hulse, Brad K.; Moreaux, Laurent C.; Lubenov, Evgueniy V.; Siapas, Athanassios G.

2016-01-01

Ripples are high-frequency oscillations associated with population bursts in area CA1 of the hippocampus that play a prominent role in theories of memory consolidation. While spiking during ripples has been extensively studied, our understanding of the subthreshold behavior of hippocampal neurons during these events remains incomplete. Here, we combine in vivo whole-cell and multisite extracellular recordings to characterize the membrane potential dynamics of identified CA1 pyramidal neurons during ripples. We find that the subthreshold depolarization during ripples is uncorrelated with the net excitatory input to CA1, while the post-ripple hyperpolarization varies proportionately. This clarifies the circuit mechanism keeping most neurons silent during ripples. On a finer time scale, the phase delay between intracellular and extracellular ripple oscillations varies systematically with membrane potential. Such smoothly varying delays are inconsistent with models of intracellular ripple generation involving perisomatic inhibition alone. Instead, they suggest that ripple-frequency excitation leading inhibition shapes intracellular ripple oscillations. PMID:26889811

Microlensing of Relativistic Knots in the Quasar HE 1104-1805 AB

NASA Astrophysics Data System (ADS)

Schechter, Paul L.; Udalski, A.; Szymański, M.; Kubiak, M.; Pietrzyński, G.; Soszyński, I.; Woźniak, P.; Żebruń, K.; Szewczyk, O.; Wyrzykowski, Ł.

2003-02-01

We present 3 years of photometry of the ``Double Hamburger'' lensed quasar, HE 1104-1805 AB, obtained on 102 separate nights using the Optical Gravitational Lensing Experiment 1.3 m telescope. Both the A and B images show variations, but with substantial differences in the light curves at all time delays. At the 310 day delay reported by Wisotzki and collaborators, the difference light curve has an rms amplitude of 0.060 mag. The structure functions for the A and B images are quite different, with image A more than twice as variable as image B (a factor of 4 in structure function) on timescales of less than a month. Adopting microlensing as a working hypothesis for the uncorrelated variability, the short timescale argues for the relativistic motion of one or more components of the source. We argue that the small amplitude of the fluctuations is due to the finite size of the source with respect to the microlenses.

Way-Scaling to Reduce Power of Cache with Delay Variation

NASA Astrophysics Data System (ADS)

Goudarzi, Maziar; Matsumura, Tadayuki; Ishihara, Tohru

The share of leakage in cache power consumption increases with technology scaling. Choosing a higher threshold voltage (Vth) and/or gate-oxide thickness (Tox) for cache transistors improves leakage, but impacts cell delay. We show that due to uncorrelated random within-die delay variation, only some (not all) of cells actually violate the cache delay after the above change. We propose to add a spare cache way to replace delay-violating cache-lines separately in each cache-set. By SPICE and gate-level simulations in a commercial 90nm process, we show that choosing higher Vth, Tox and adding one spare way to a 4-way 16KB cache reduces leakage power by 42%, which depending on the share of leakage in total cache power, gives up to 22.59% and 41.37% reduction of total energy respectively in L1 instruction- and L2 unified-cache with a negligible delay penalty, but without sacrificing cache capacity or timing-yield.

Status of Cycle 23 Forecasts

NASA Technical Reports Server (NTRS)

Hathaway, D. H.

2000-01-01

A number of techniques for predicting solar activity on a solar cycle time scale are identified, described, and tested with historical data. Some techniques, e.g,, regression and curve-fitting, work well as solar activity approaches maximum and provide a month- by-month description of future activity, while others, e.g., geomagnetic precursors, work well near solar minimum but provide an estimate only of the amplitude of the cycle. A synthesis of different techniques is shown to provide a more accurate and useful forecast of solar cycle activity levels. A combination of two uncorrelated geomagnetic precursor techniques provides the most accurate prediction for the amplitude of a solar activity cycle at a time well before activity minimum. This precursor method gave a smoothed sunspot number maximum of 154+21 for cycle 23. A mathematical function dependent upon the time of cycle initiation and the cycle amplitude then describes the level of solar activity for the complete cycle. As the time of cycle maximum approaches a better estimate of the cycle activity is obtained by including the fit between recent activity levels and this function. This Combined Solar Cycle Activity Forecast now gives a smoothed sunspot maximum of 140+20 for cycle 23. The success of the geomagnetic precursors in predicting future solar activity suggests that solar magnetic phenomena at latitudes above the sunspot activity belts are linked to solar activity, which occurs many years later in the lower latitudes.

Characterization of Fissile Assemblies Using Low-Efficiency Detection Systems

DOE PAGES

Chapline, George F.; Verbeke, Jerome M.

2017-02-02

Here, we have investigated the possibility that the amount, chemical form, multiplication, and shape of the fissile material in an assembly can be passively assayed using scintillator detection systems by only measuring the fast neutron pulse height distribution and distribution of time intervals Δt between fast neutrons. We have previously demonstrated that the alpha-ratio can be obtained from the observed pulse height distribution for fast neutrons. In this paper we report that we report that when the distribution of time intervals is plotted as a function of logΔt, the position of the correlated neutron peak is nearly independent of detectormore » efficiency and determines the internal relaxation rate for fast neutrons. If this information is combined with knowledge of the alpha-ratio, then the position of the minimum between the correlated and uncorrelated peaks can be used to rapidly estimate the mass, multiplication, and shape of fissile material. This method does not require a priori knowledge of either the efficiency for neutron detection or the alpha-ratio. Although our method neglects 3-neutron correlations, we have used previously obtained experimental data for metallic and oxide forms of Pu to demonstrate that our method yields good estimates for multiplications as large as 2, and that the only constraint on detector efficiency/observation time is that a peak in the interval time distribution due to correlated neutrons is visible.« less

A Double-difference Earthquake location algorithm: Method and application to the Northern Hayward Fault, California

USGS Publications Warehouse

Waldhauser, F.; Ellsworth, W.L.

2000-01-01

We have developed an efficient method to determine high-resolution hypocenter locations over large distances. The location method incorporates ordinary absolute travel-time measurements and/or cross-correlation P-and S-wave differential travel-time measurements. Residuals between observed and theoretical travel-time differences (or double-differences) are minimized for pairs of earthquakes at each station while linking together all observed event-station pairs. A least-squares solution is found by iteratively adjusting the vector difference between hypocentral pairs. The double-difference algorithm minimizes errors due to unmodeled velocity structure without the use of station corrections. Because catalog and cross-correlation data are combined into one system of equations, interevent distances within multiplets are determined to the accuracy of the cross-correlation data, while the relative locations between multiplets and uncorrelated events are simultaneously determined to the accuracy of the absolute travel-time data. Statistical resampling methods are used to estimate data accuracy and location errors. Uncertainties in double-difference locations are improved by more than an order of magnitude compared to catalog locations. The algorithm is tested, and its performance is demonstrated on two clusters of earthquakes located on the northern Hayward fault, California. There it colapses the diffuse catalog locations into sharp images of seismicity and reveals horizontal lineations of hypocenter that define the narrow regions on the fault where stress is released by brittle failure.

Insect-damaged fossil leaves record food web response to ancient climate change and extinction.

PubMed

Wilf, P

2008-01-01

Plants and herbivorous insects have dominated terrestrial ecosystems for over 300 million years. Uniquely in the fossil record, foliage with well-preserved insect damage offers abundant and diverse information both about producers and about ecological and sometimes taxonomic groups of consumers. These data are ideally suited to investigate food web response to environmental perturbations, and they represent an invaluable deep-time complement to neoecological studies of global change. Correlations between feeding diversity and temperature, between herbivory and leaf traits that are modulated by climate, and between insect diversity and plant diversity can all be investigated in deep time. To illustrate, I emphasize recent work on the time interval from the latest Cretaceous through the middle Eocene (67-47 million years ago (Ma)), including two significant events that affected life: the end-Cretaceous mass extinction (65.5 Ma) and its ensuing recovery; and globally warming temperatures across the Paleocene-Eocene boundary (55.8 Ma). Climatic effects predicted from neoecology generally hold true in these deep-time settings. Rising temperature is associated with increased herbivory in multiple studies, a result with major predictive importance for current global warming. Diverse floras are usually associated with diverse insect damage; however, recovery from the end-Cretaceous extinction reveals uncorrelated plant and insect diversity as food webs rebuilt chaotically from a drastically simplified state. Calibration studies from living forests are needed to improve interpretation of the fossil data.

Conventional and advanced time series estimation: application to the Australian and New Zealand Intensive Care Society (ANZICS) adult patient database, 1993-2006.

PubMed

Moran, John L; Solomon, Patricia J

2011-02-01

Time series analysis has seen limited application in the biomedical Literature. The utility of conventional and advanced time series estimators was explored for intensive care unit (ICU) outcome series. Monthly mean time series, 1993-2006, for hospital mortality, severity-of-illness score (APACHE III), ventilation fraction and patient type (medical and surgical), were generated from the Australia and New Zealand Intensive Care Society adult patient database. Analyses encompassed geographical seasonal mortality patterns, series structural time changes, mortality series volatility using autoregressive moving average and Generalized Autoregressive Conditional Heteroscedasticity models in which predicted variances are updated adaptively, and bivariate and multivariate (vector error correction models) cointegrating relationships between series. The mortality series exhibited marked seasonality, declining mortality trend and substantial autocorrelation beyond 24 lags. Mortality increased in winter months (July-August); the medical series featured annual cycling, whereas the surgical demonstrated long and short (3-4 months) cycling. Series structural breaks were apparent in January 1995 and December 2002. The covariance stationary first-differenced mortality series was consistent with a seasonal autoregressive moving average process; the observed conditional-variance volatility (1993-1995) and residual Autoregressive Conditional Heteroscedasticity effects entailed a Generalized Autoregressive Conditional Heteroscedasticity model, preferred by information criterion and mean model forecast performance. Bivariate cointegration, indicating long-term equilibrium relationships, was established between mortality and severity-of-illness scores at the database level and for categories of ICUs. Multivariate cointegration was demonstrated for {log APACHE III score, log ICU length of stay, ICU mortality and ventilation fraction}. A system approach to understanding series time-dependence may be established using conventional and advanced econometric time series estimators. © 2010 Blackwell Publishing Ltd.

Early Events in Insulin Fibrillization Studied by Time-Lapse Atomic Force Microscopy

PubMed Central

Podestà, Alessandro; Tiana, Guido; Milani, Paolo; Manno, Mauro

2006-01-01

The importance of understanding the mechanism of protein aggregation into insoluble amyloid fibrils lies not only in its medical consequences, but also in its more basic properties of self-organization. The discovery that a large number of uncorrelated proteins can form, under proper conditions, structurally similar fibrils has suggested that the underlying mechanism is a general feature of polypeptide chains. In this work, we address the early events preceding amyloid fibril formation in solutions of zinc-free human insulin incubated at low pH and high temperature. Here, we show by time-lapse atomic force microscopy that a steady-state distribution of protein oligomers with a quasiexponential tail is reached within a few minutes after heating. This metastable phase lasts for a few hours, until fibrillar aggregates are observable. Although for such complex systems different aggregation mechanisms can occur simultaneously, our results indicate that the prefibrillar phase is mainly controlled by a simple coagulation-evaporation kinetic mechanism, in which concentration acts as a critical parameter. These experimental facts, along with the kinetic model used, suggest a critical role for thermal concentration fluctuations in the process of fibril nucleation. PMID:16239333

A threshold model of investor psychology

NASA Astrophysics Data System (ADS)

Cross, Rod; Grinfeld, Michael; Lamba, Harbir; Seaman, Tim

2005-08-01

We introduce a class of agent-based market models founded upon simple descriptions of investor psychology. Agents are subject to various psychological tensions induced by market conditions and endowed with a minimal ‘personality’. This personality consists of a threshold level for each of the tensions being modeled, and the agent reacts whenever a tension threshold is reached. This paper considers an elementary model including just two such tensions. The first is ‘cowardice’, which is the stress caused by remaining in a minority position with respect to overall market sentiment and leads to herding-type behavior. The second is ‘inaction’, which is the increasing desire to act or re-evaluate one's investment position. There is no inductive learning by agents and they are only coupled via the global market price and overall market sentiment. Even incorporating just these two psychological tensions, important stylized facts of real market data, including fat-tails, excess kurtosis, uncorrelated price returns and clustered volatility over the timescale of a few days are reproduced. By then introducing an additional parameter that amplifies the effect of externally generated market noise during times of extreme market sentiment, long-time volatility correlations can also be recovered.

Measurements of n-p correlations in the reaction of relativistic neon with uranium

NASA Technical Reports Server (NTRS)

Frankel, K.; Schimmerling, W.; Rasmussen, J. O.; Crowe, K. M.; Bistirlich, J.; Bowman, H.; Hashimoto, O.; Murphy, D. L.; Ridout, J.; Sullivan, J. P.;

Modeling Pilot Pulse Control

NASA Technical Reports Server (NTRS)

Bachelder, Edward; Hess, Ronald; Godfroy-Cooper, Martine; Aponso, Bimal

2017-01-01

In this study, behavioral models are developed that closely reproduced pulsive control response of two pilots from the experimental pool using markedly different control techniques (styles) while conducting a tracking task. An intriguing find was that the pilots appeared to: 1) produce a continuous, internally-generated stick signal that they integrated in time; 2) integrate the actual stick position; and 3) compare the two integrations to issue and cease pulse commands. This suggests that the pilots utilized kinesthetic feedback in order to perceive and integrate stick position, supporting the hypothesis that pilots can access and employ the proprioceptive inner feedback loop proposed by Hess' pilot Structural Model. The Pulse Models used in conjunction with the pilot Structural Model closely recreated the pilot data both in the frequency and time domains during closed-loop simulation. This indicates that for the range of tasks and control styles encountered, the models captured the fundamental mechanisms governing pulsive and control processes. The pilot Pulse Models give important insight for the amount of remnant (stick output uncorrelated with the forcing function) that arises from nonlinear pilot technique, and for the remaining remnant arising from different sources unrelated to tracking control (i.e. neuromuscular tremor, reallocation of cognitive resources, etc.).

Observing behavior in a computer game.

PubMed Central

Case, D A; Ploog, B O; Fantino, E

1990-01-01

Contingencies studied in lever-pressing procedures were incorporated into a popular computer game, "Star Trek," played by college students. One putative reinforcer, the opportunity to destroy Klingon invaders, was scheduled independently of responding according to a variable-time schedule that alternated unpredictably with equal periods of Klingon unavailability (mixed variable time, extinction schedule of reinforcement). Two commands ("observing responses") each produced stimuli that were either correlated or uncorrelated with the two components. In several variations of the basic game, an S-, or bad news, was not as reinforcing as an S+, or good news. In addition, in other conditions for the same subjects observing responses were not maintained better by bad news than by an uninformative stimulus. In both choices, more observing tended to be maintained by an S- for response-independent Klingons when its information could be (and was) used to advantage with respect to other types of reinforcement in the situation (Parts 1 and 2) than when the information could not be so used (Part 3). The findings favor the conditioned reinforcement hypothesis of observing behavior over the uncertainty-reduction hypothesis. This extends research to a more natural setting and to multialternative concurrent schedules of events of seemingly intrinsic value. PMID:2103581

The physics of mental acts: coherence and creativity

NASA Astrophysics Data System (ADS)

Tito Arecchi, F.

2009-06-01

Coherence is a long range order absent at thermal equilibrium, where a system is the superposition of many uncorrelated components. To build non-trivial correlations, the system must enter a nonlinear dynamical regime. The nonlinearity leads to a multiplicity of equilibrium states, the number of which increases exponentially with the number of partners; we call complexity such a situation. Complete exploration of complexity would require a very large amount of time. On the contrary, in cognitive tasks, one reaches a decision within a few hundred milliseconds. Neuron synchronization lasting around 301 msec is the indicator of a conscious perception (Gestalt); however, the loss of information in the chaotic spike train of a single neuron takes a few msec, thus a conscious perception implies a control of chaos, whereby the information stored in a brain area survives for a time sufficient to elicit an action. Control of chaos is achieved by the interaction of a bottom-up stimulus with a top-down control (induced by the semantic memory). We call creativity this optimal control of neuronal chaos; it goes beyond the Bayesian inference, which is the way a computer operates, thus it represent a non-algorithmic step.

Reward Draws the Eye, Uncertainty Holds the Eye: Associative Learning Modulates Distractor Interference in Visual Search

PubMed Central

Koenig, Stephan; Kadel, Hanna; Uengoer, Metin; Schubö, Anna; Lachnit, Harald

2017-01-01

Stimuli in our sensory environment differ with respect to their physical salience but moreover may acquire motivational salience by association with reward. If we repeatedly observed that reward is available in the context of a particular cue but absent in the context of another cue the former typically attracts more attention than the latter. However, we also may encounter cues uncorrelated with reward. A cue with 50% reward contingency may induce an average reward expectancy but at the same time induces high reward uncertainty. In the current experiment we examined how both values, reward expectancy and uncertainty, affected overt attention. Two different colors were established as predictive cues for low reward and high reward respectively. A third color was followed by high reward on 50% of the trials and thus induced uncertainty. Colors then were introduced as distractors during search for a shape target, and we examined the relative potential of the color distractors to capture and hold the first fixation. We observed that capture frequency corresponded to reward expectancy while capture duration corresponded to uncertainty. The results may suggest that within trial reward expectancy is represented at an earlier time window than uncertainty. PMID:28744206

Sea change: Charting the course for biogeochemical ocean time-series research in a new millennium

NASA Astrophysics Data System (ADS)

Church, Matthew J.; Lomas, Michael W.; Muller-Karger, Frank

2013-09-01

Ocean time-series provide vital information needed for assessing ecosystem change. This paper summarizes the historical context, major program objectives, and future research priorities for three contemporary ocean time-series programs: The Hawaii Ocean Time-series (HOT), the Bermuda Atlantic Time-series Study (BATS), and the CARIACO Ocean Time-Series. These three programs operate in physically and biogeochemically distinct regions of the world's oceans, with HOT and BATS located in the open-ocean waters of the subtropical North Pacific and North Atlantic, respectively, and CARIACO situated in the anoxic Cariaco Basin of the tropical Atlantic. All three programs sustain near-monthly shipboard occupations of their field sampling sites, with HOT and BATS beginning in 1988, and CARIACO initiated in 1996. The resulting data provide some of the only multi-disciplinary, decadal-scale determinations of time-varying ecosystem change in the global ocean. Facilitated by a scoping workshop (September 2010) sponsored by the Ocean Carbon Biogeochemistry (OCB) program, leaders of these time-series programs sought community input on existing program strengths and for future research directions. Themes that emerged from these discussions included: 1. Shipboard time-series programs are key to informing our understanding of the connectivity between changes in ocean-climate and biogeochemistry 2. The scientific and logistical support provided by shipboard time-series programs forms the backbone for numerous research and education programs. Future studies should be encouraged that seek mechanistic understanding of ecological interactions underlying the biogeochemical dynamics at these sites. 3. Detecting time-varying trends in ocean properties and processes requires consistent, high-quality measurements. Time-series must carefully document analytical procedures and, where possible, trace the accuracy of analyses to certified standards and internal reference materials. 4. Leveraged implementation, testing, and validation of autonomous and remote observing technologies at time-series sites provide new insights into spatiotemporal variability underlying ecosystem changes. 5. The value of existing time-series data for formulating and validating ecosystem models should be promoted. In summary, the scientific underpinnings of ocean time-series programs remain as strong and important today as when these programs were initiated. The emerging data inform our knowledge of the ocean's biogeochemistry and ecology, and improve our predictive capacity about planetary change.

Characterization of time series via Rényi complexity-entropy curves

NASA Astrophysics Data System (ADS)

Jauregui, M.; Zunino, L.; Lenzi, E. K.; Mendes, R. S.; Ribeiro, H. V.

2018-05-01

One of the most useful tools for distinguishing between chaotic and stochastic time series is the so-called complexity-entropy causality plane. This diagram involves two complexity measures: the Shannon entropy and the statistical complexity. Recently, this idea has been generalized by considering the Tsallis monoparametric generalization of the Shannon entropy, yielding complexity-entropy curves. These curves have proven to enhance the discrimination among different time series related to stochastic and chaotic processes of numerical and experimental nature. Here we further explore these complexity-entropy curves in the context of the Rényi entropy, which is another monoparametric generalization of the Shannon entropy. By combining the Rényi entropy with the proper generalization of the statistical complexity, we associate a parametric curve (the Rényi complexity-entropy curve) with a given time series. We explore this approach in a series of numerical and experimental applications, demonstrating the usefulness of this new technique for time series analysis. We show that the Rényi complexity-entropy curves enable the differentiation among time series of chaotic, stochastic, and periodic nature. In particular, time series of stochastic nature are associated with curves displaying positive curvature in a neighborhood of their initial points, whereas curves related to chaotic phenomena have a negative curvature; finally, periodic time series are represented by vertical straight lines.

Long-term memory and volatility clustering in high-frequency price changes

NASA Astrophysics Data System (ADS)

oh, Gabjin; Kim, Seunghwan; Eom, Cheoljun

2008-02-01

We studied the long-term memory in diverse stock market indices and foreign exchange rates using Detrended Fluctuation Analysis (DFA). For all high-frequency market data studied, no significant long-term memory property was detected in the return series, while a strong long-term memory property was found in the volatility time series. The possible causes of the long-term memory property were investigated using the return data filtered by the AR(1) model, reflecting the short-term memory property, the GARCH(1,1) model, reflecting the volatility clustering property, and the FIGARCH model, reflecting the long-term memory property of the volatility time series. The memory effect in the AR(1) filtered return and volatility time series remained unchanged, while the long-term memory property diminished significantly in the volatility series of the GARCH(1,1) filtered data. Notably, there is no long-term memory property, when we eliminate the long-term memory property of volatility by the FIGARCH model. For all data used, although the Hurst exponents of the volatility time series changed considerably over time, those of the time series with the volatility clustering effect removed diminish significantly. Our results imply that the long-term memory property of the volatility time series can be attributed to the volatility clustering observed in the financial time series.

Modeling seasonal variation of hip fracture in Montreal, Canada.

PubMed

Modarres, Reza; Ouarda, Taha B M J; Vanasse, Alain; Orzanco, Maria Gabriela; Gosselin, Pierre

2012-04-01

The investigation of the association of the climate variables with hip fracture incidences is important in social health issues. This study examined and modeled the seasonal variation of monthly population based hip fracture rate (HFr) time series. The seasonal ARIMA time series modeling approach is used to model monthly HFr incidences time series of female and male patients of the ages 40-74 and 75+ of Montreal, Québec province, Canada, in the period of 1993-2004. The correlation coefficients between meteorological variables such as temperature, snow depth, rainfall depth and day length and HFr are significant. The nonparametric Mann-Kendall test for trend assessment and the nonparametric Levene's test and Wilcoxon's test for checking the difference of HFr before and after change point are also used. The seasonality in HFr indicated sharp difference between winter and summer time. The trend assessment showed decreasing trends in HFr of female and male groups. The nonparametric test also indicated a significant change of the mean HFr. A seasonal ARIMA model was applied for HFr time series without trend and a time trend ARIMA model (TT-ARIMA) was developed and fitted to HFr time series with a significant trend. The multi criteria evaluation showed the adequacy of SARIMA and TT-ARIMA models for modeling seasonal hip fracture time series with and without significant trend. In the time series analysis of HFr of the Montreal region, the effects of the seasonal variation of climate variables on hip fracture are clear. The Seasonal ARIMA model is useful for modeling HFr time series without trend. However, for time series with significant trend, the TT-ARIMA model should be applied for modeling HFr time series. Copyright © 2011 Elsevier Inc. All rights reserved.

Smoothing of climate time series revisited

NASA Astrophysics Data System (ADS)

Mann, Michael E.

2008-08-01

We present an easily implemented method for smoothing climate time series, generalizing upon an approach previously described by Mann (2004). The method adaptively weights the three lowest order time series boundary constraints to optimize the fit with the raw time series. We apply the method to the instrumental global mean temperature series from 1850-2007 and to various surrogate global mean temperature series from 1850-2100 derived from the CMIP3 multimodel intercomparison project. These applications demonstrate that the adaptive method systematically out-performs certain widely used default smoothing methods, and is more likely to yield accurate assessments of long-term warming trends.

Forecasting and analyzing high O3 time series in educational area through an improved chaotic approach

NASA Astrophysics Data System (ADS)

Hamid, Nor Zila Abd; Adenan, Nur Hamiza; Noorani, Mohd Salmi Md

2017-08-01

Forecasting and analyzing the ozone (O3) concentration time series is important because the pollutant is harmful to health. This study is a pilot study for forecasting and analyzing the O3 time series in one of Malaysian educational area namely Shah Alam using chaotic approach. Through this approach, the observed hourly scalar time series is reconstructed into a multi-dimensional phase space, which is then used to forecast the future time series through the local linear approximation method. The main purpose is to forecast the high O3 concentrations. The original method performed poorly but the improved method addressed the weakness thereby enabling the high concentrations to be successfully forecast. The correlation coefficient between the observed and forecasted time series through the improved method is 0.9159 and both the mean absolute error and root mean squared error are low. Thus, the improved method is advantageous. The time series analysis by means of the phase space plot and Cao method identified the presence of low-dimensional chaotic dynamics in the observed O3 time series. Results showed that at least seven factors affect the studied O3 time series, which is consistent with the listed factors from the diurnal variations investigation and the sensitivity analysis from past studies. In conclusion, chaotic approach has been successfully forecast and analyzes the O3 time series in educational area of Shah Alam. These findings are expected to help stakeholders such as Ministry of Education and Department of Environment in having a better air pollution management.

Transformation-cost time-series method for analyzing irregularly sampled data

NASA Astrophysics Data System (ADS)

Ozken, Ibrahim; Eroglu, Deniz; Stemler, Thomas; Marwan, Norbert; Bagci, G. Baris; Kurths, Jürgen

2015-06-01

Irregular sampling of data sets is one of the challenges often encountered in time-series analysis, since traditional methods cannot be applied and the frequently used interpolation approach can corrupt the data and bias the subsequence analysis. Here we present the TrAnsformation-Cost Time-Series (TACTS) method, which allows us to analyze irregularly sampled data sets without degenerating the quality of the data set. Instead of using interpolation we consider time-series segments and determine how close they are to each other by determining the cost needed to transform one segment into the following one. Using a limited set of operations—with associated costs—to transform the time series segments, we determine a new time series, that is our transformation-cost time series. This cost time series is regularly sampled and can be analyzed using standard methods. While our main interest is the analysis of paleoclimate data, we develop our method using numerical examples like the logistic map and the Rössler oscillator. The numerical data allows us to test the stability of our method against noise and for different irregular samplings. In addition we provide guidance on how to choose the associated costs based on the time series at hand. The usefulness of the TACTS method is demonstrated using speleothem data from the Secret Cave in Borneo that is a good proxy for paleoclimatic variability in the monsoon activity around the maritime continent.

Transformation-cost time-series method for analyzing irregularly sampled data.

PubMed

Ozken, Ibrahim; Eroglu, Deniz; Stemler, Thomas; Marwan, Norbert; Bagci, G Baris; Kurths, Jürgen

2015-06-01

Irregular sampling of data sets is one of the challenges often encountered in time-series analysis, since traditional methods cannot be applied and the frequently used interpolation approach can corrupt the data and bias the subsequence analysis. Here we present the TrAnsformation-Cost Time-Series (TACTS) method, which allows us to analyze irregularly sampled data sets without degenerating the quality of the data set. Instead of using interpolation we consider time-series segments and determine how close they are to each other by determining the cost needed to transform one segment into the following one. Using a limited set of operations-with associated costs-to transform the time series segments, we determine a new time series, that is our transformation-cost time series. This cost time series is regularly sampled and can be analyzed using standard methods. While our main interest is the analysis of paleoclimate data, we develop our method using numerical examples like the logistic map and the Rössler oscillator. The numerical data allows us to test the stability of our method against noise and for different irregular samplings. In addition we provide guidance on how to choose the associated costs based on the time series at hand. The usefulness of the TACTS method is demonstrated using speleothem data from the Secret Cave in Borneo that is a good proxy for paleoclimatic variability in the monsoon activity around the maritime continent.

a Method of Time-Series Change Detection Using Full Polsar Images from Different Sensors

NASA Astrophysics Data System (ADS)

Liu, W.; Yang, J.; Zhao, J.; Shi, H.; Yang, L.

2018-04-01

Most of the existing change detection methods using full polarimetric synthetic aperture radar (PolSAR) are limited to detecting change between two points in time. In this paper, a novel method was proposed to detect the change based on time-series data from different sensors. Firstly, the overall difference image of a time-series PolSAR was calculated by ominous statistic test. Secondly, difference images between any two images in different times ware acquired by Rj statistic test. Generalized Gaussian mixture model (GGMM) was used to obtain time-series change detection maps in the last step for the proposed method. To verify the effectiveness of the proposed method, we carried out the experiment of change detection by using the time-series PolSAR images acquired by Radarsat-2 and Gaofen-3 over the city of Wuhan, in China. Results show that the proposed method can detect the time-series change from different sensors.

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.

Network structure of multivariate time series.

PubMed

Lacasa, Lucas; Nicosia, Vincenzo; Latora, Vito

2015-10-21

Our understanding of a variety of phenomena in physics, biology and economics crucially depends on the analysis of multivariate time series. While a wide range tools and techniques for time series analysis already exist, the increasing availability of massive data structures calls for new approaches for multidimensional signal processing. We present here a non-parametric method to analyse multivariate time series, based on the mapping of a multidimensional time series into a multilayer network, which allows to extract information on a high dimensional dynamical system through the analysis of the structure of the associated multiplex network. The method is simple to implement, general, scalable, does not require ad hoc phase space partitioning, and is thus suitable for the analysis of large, heterogeneous and non-stationary time series. We show that simple structural descriptors of the associated multiplex networks allow to extract and quantify nontrivial properties of coupled chaotic maps, including the transition between different dynamical phases and the onset of various types of synchronization. As a concrete example we then study financial time series, showing that a multiplex network analysis can efficiently discriminate crises from periods of financial stability, where standard methods based on time-series symbolization often fail.

Homogenising time series: beliefs, dogmas and facts

NASA Astrophysics Data System (ADS)

Domonkos, P.

2011-06-01

In the recent decades various homogenisation methods have been developed, but the real effects of their application on time series are still not known sufficiently. The ongoing COST action HOME (COST ES0601) is devoted to reveal the real impacts of homogenisation methods more detailed and with higher confidence than earlier. As a part of the COST activity, a benchmark dataset was built whose characteristics approach well the characteristics of real networks of observed time series. This dataset offers much better opportunity than ever before to test the wide variety of homogenisation methods, and analyse the real effects of selected theoretical recommendations. Empirical results show that real observed time series usually include several inhomogeneities of different sizes. Small inhomogeneities often have similar statistical characteristics than natural changes caused by climatic variability, thus the pure application of the classic theory that change-points of observed time series can be found and corrected one-by-one is impossible. However, after homogenisation the linear trends, seasonal changes and long-term fluctuations of time series are usually much closer to the reality than in raw time series. Some problems around detecting multiple structures of inhomogeneities, as well as that of time series comparisons within homogenisation procedures are discussed briefly in the study.

The Timeseries Toolbox - A Web Application to Enable Accessible, Reproducible Time Series Analysis

NASA Astrophysics Data System (ADS)

Veatch, W.; Friedman, D.; Baker, B.; Mueller, C.

2017-12-01

The vast majority of data analyzed by climate researchers are repeated observations of physical process or time series data. This data lends itself of a common set of statistical techniques and models designed to determine trends and variability (e.g., seasonality) of these repeated observations. Often, these same techniques and models can be applied to a wide variety of different time series data. The Timeseries Toolbox is a web application designed to standardize and streamline these common approaches to time series analysis and modeling with particular attention to hydrologic time series used in climate preparedness and resilience planning and design by the U. S. Army Corps of Engineers. The application performs much of the pre-processing of time series data necessary for more complex techniques (e.g. interpolation, aggregation). With this tool, users can upload any dataset that conforms to a standard template and immediately begin applying these techniques to analyze their time series data.

Fuzzy time-series based on Fibonacci sequence for stock price forecasting

NASA Astrophysics Data System (ADS)

Chen, Tai-Liang; Cheng, Ching-Hsue; Jong Teoh, Hia

2007-07-01

Time-series models have been utilized to make reasonably accurate predictions in the areas of stock price movements, academic enrollments, weather, etc. For promoting the forecasting performance of fuzzy time-series models, this paper proposes a new model, which incorporates the concept of the Fibonacci sequence, the framework of Song and Chissom's model and the weighted method of Yu's model. This paper employs a 5-year period TSMC (Taiwan Semiconductor Manufacturing Company) stock price data and a 13-year period of TAIEX (Taiwan Stock Exchange Capitalization Weighted Stock Index) stock index data as experimental datasets. By comparing our forecasting performances with Chen's (Forecasting enrollments based on fuzzy time-series. Fuzzy Sets Syst. 81 (1996) 311-319), Yu's (Weighted fuzzy time-series models for TAIEX forecasting. Physica A 349 (2004) 609-624) and Huarng's (The application of neural networks to forecast fuzzy time series. Physica A 336 (2006) 481-491) models, we conclude that the proposed model surpasses in accuracy these conventional fuzzy time-series models.

Multivariate Time Series Decomposition into Oscillation Components.

PubMed

Matsuda, Takeru; Komaki, Fumiyasu

2017-08-01

Many time series are considered to be a superposition of several oscillation components. We have proposed a method for decomposing univariate time series into oscillation components and estimating their phases (Matsuda & Komaki, 2017 ). In this study, we extend that method to multivariate time series. We assume that several oscillators underlie the given multivariate time series and that each variable corresponds to a superposition of the projections of the oscillators. Thus, the oscillators superpose on each variable with amplitude and phase modulation. Based on this idea, we develop gaussian linear state-space models and use them to decompose the given multivariate time series. The model parameters are estimated from data using the empirical Bayes method, and the number of oscillators is determined using the Akaike information criterion. Therefore, the proposed method extracts underlying oscillators in a data-driven manner and enables investigation of phase dynamics in a given multivariate time series. Numerical results show the effectiveness of the proposed method. From monthly mean north-south sunspot number data, the proposed method reveals an interesting phase relationship.

Time-series modeling of long-term weight self-monitoring data.

PubMed

Helander, Elina; Pavel, Misha; Jimison, Holly; Korhonen, Ilkka

2015-08-01

Long-term self-monitoring of weight is beneficial for weight maintenance, especially after weight loss. Connected weight scales accumulate time series information over long term and hence enable time series analysis of the data. The analysis can reveal individual patterns, provide more sensitive detection of significant weight trends, and enable more accurate and timely prediction of weight outcomes. However, long term self-weighing data has several challenges which complicate the analysis. Especially, irregular sampling, missing data, and existence of periodic (e.g. diurnal and weekly) patterns are common. In this study, we apply time series modeling approach on daily weight time series from two individuals and describe information that can be extracted from this kind of data. We study the properties of weight time series data, missing data and its link to individuals behavior, periodic patterns and weight series segmentation. Being able to understand behavior through weight data and give relevant feedback is desired to lead to positive intervention on health behaviors.

FALSE DETERMINATIONS OF CHAOS IN SHORT NOISY TIME SERIES. (R828745)

EPA Science Inventory

A method (NEMG) proposed in 1992 for diagnosing chaos in noisy time series with 50 or fewer observations entails fitting the time series with an empirical function which predicts an observation in the series from previous observations, and then estimating the rate of divergenc...

New Results in Magnitude and Sign Correlations in Heartbeat Fluctuations for Healthy Persons and Congestive Heart Failure (CHF) Patients

NASA Astrophysics Data System (ADS)

Diosdado, A. Muñoz; Cruz, H. Reyes; Hernández, D. Bueno; Coyt, G. Gálvez; González, J. Arellanes

2008-08-01

Heartbeat fluctuations exhibit temporal structure with fractal and nonlinear features that reflect changes in the neuroautonomic control. In this work we have used the detrended fluctuation analysis (DFA) to analyze heartbeat (RR) intervals of 54 healthy subjects and 40 patients with congestive heart failure during 24 hours; we separate time series for sleep and wake phases. We observe long-range correlations in time series of healthy persons and CHF patients. However, the correlations for CHF patients are weaker than the correlations for healthy persons; this fact has been reported by Ashkenazy et al. [1] but with a smaller group of subjects. In time series of CHF patients there is a crossover, it means that the correlations for high and low frequencies are different, but in time series of healthy persons there are not crossovers even if they are sleeping. These crossovers are more pronounced for CHF patients in the sleep phase. We decompose the heartbeat interval time series into magnitude and sign series, we know that these kinds of signals can exhibit different time organization for the magnitude and sign and the magnitude series relates to nonlinear properties of the original time series, while the sign series relates to the linear properties. Magnitude series are long-range correlated, while the sign series are anticorrelated. Newly, the correlations for healthy persons are different that the correlations for CHF patients both for magnitude and sign time series. In the paper of Ashkenazy et al. they proposed the empirical relation: αsign≈1/2(αoriginal+αmagnitude) for the short-range regime (high frequencies), however, we have found a different relation that in our calculations is valid for short and long-range regime: αsign≈1/4(αoriginal+αmagnitude).

An evaluation of the accuracy of modeled and computed streamflow time-series data for the Ohio River at Hannibal Lock and Dam and at a location upstream from Sardis, Ohio

USGS Publications Warehouse

Koltun, G.F.

2015-01-01

Streamflow hydrographs were plotted for modeled/computed time series for the Ohio River near the USGS Sardis gage and the Ohio River at the Hannibal Lock and Dam. In general, the time series at these two locations compared well. Some notable differences include the exclusive presence of short periods of negative streamflows in the USGS 15-minute time-series data for the gage on the Ohio River above Sardis, Ohio, and the occurrence of several peak streamflows in the USACE gate/hydropower time series for the Hannibal Lock and Dam that were appreciably larger than corresponding peaks in the other time series, including those modeled/computed for the downstream Sardis gage

Using wavelet-feedforward neural networks to improve air pollution forecasting in urban environments.

PubMed

Dunea, Daniel; Pohoata, Alin; Iordache, Stefania

2015-07-01

The paper presents the screening of various feedforward neural networks (FANN) and wavelet-feedforward neural networks (WFANN) applied to time series of ground-level ozone (O3), nitrogen dioxide (NO2), and particulate matter (PM10 and PM2.5 fractions) recorded at four monitoring stations located in various urban areas of Romania, to identify common configurations with optimal generalization performance. Two distinct model runs were performed as follows: data processing using hourly-recorded time series of airborne pollutants during cold months (O3, NO2, and PM10), when residential heating increases the local emissions, and data processing using 24-h daily averaged concentrations (PM2.5) recorded between 2009 and 2012. Dataset variability was assessed using statistical analysis. Time series were passed through various FANNs. Each time series was decomposed in four time-scale components using three-level wavelets, which have been passed also through FANN, and recomposed into a single time series. The agreement between observed and modelled output was evaluated based on the statistical significance (r coefficient and correlation between errors and data). Daubechies db3 wavelet-Rprop FANN (6-4-1) utilization gave positive results for O3 time series optimizing the exclusive use of the FANN for hourly-recorded time series. NO2 was difficult to model due to time series specificity, but wavelet integration improved FANN performances. Daubechies db3 wavelet did not improve the FANN outputs for PM10 time series. Both models (FANN/WFANN) overestimated PM2.5 forecasted values in the last quarter of time series. A potential improvement of the forecasted values could be the integration of a smoothing algorithm to adjust the PM2.5 model outputs.

A novel encoding Lempel-Ziv complexity algorithm for quantifying the irregularity of physiological time series.

PubMed

Zhang, Yatao; Wei, Shoushui; Liu, Hai; Zhao, Lina; Liu, Chengyu

2016-09-01

The Lempel-Ziv (LZ) complexity and its variants have been extensively used to analyze the irregularity of physiological time series. To date, these measures cannot explicitly discern between the irregularity and the chaotic characteristics of physiological time series. Our study compared the performance of an encoding LZ (ELZ) complexity algorithm, a novel variant of the LZ complexity algorithm, with those of the classic LZ (CLZ) and multistate LZ (MLZ) complexity algorithms. Simulation experiments on Gaussian noise, logistic chaotic, and periodic time series showed that only the ELZ algorithm monotonically declined with the reduction in irregularity in time series, whereas the CLZ and MLZ approaches yielded overlapped values for chaotic time series and time series mixed with Gaussian noise, demonstrating the accuracy of the proposed ELZ algorithm in capturing the irregularity, rather than the complexity, of physiological time series. In addition, the effect of sequence length on the ELZ algorithm was more stable compared with those on CLZ and MLZ, especially when the sequence length was longer than 300. A sensitivity analysis for all three LZ algorithms revealed that both the MLZ and the ELZ algorithms could respond to the change in time sequences, whereas the CLZ approach could not. Cardiac interbeat (RR) interval time series from the MIT-BIH database were also evaluated, and the results showed that the ELZ algorithm could accurately measure the inherent irregularity of the RR interval time series, as indicated by lower LZ values yielded from a congestive heart failure group versus those yielded from a normal sinus rhythm group (p < 0.01). Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Colored noise and a stochastic fractional model for correlated inputs and adaptation in neuronal firing.

PubMed

Pirozzi, Enrica

2018-04-01

High variability in the neuronal response to stimulations and the adaptation phenomenon cannot be explained by the standard stochastic leaky integrate-and-fire model. The main reason is that the uncorrelated inputs involved in the model are not realistic. There exists some form of dependency between the inputs, and it can be interpreted as memory effects. In order to include these physiological features in the standard model, we reconsider it with time-dependent coefficients and correlated inputs. Due to its hard mathematical tractability, we perform simulations of it for a wide investigation of its output. A Gauss-Markov process is constructed for approximating its non-Markovian dynamics. The first passage time probability density of such a process can be numerically evaluated, and it can be used to fit the histograms of simulated firing times. Some estimates of the moments of firing times are also provided. The effect of the correlation time of the inputs on firing densities and on firing rates is shown. An exponential probability density of the first firing time is estimated for low values of input current and high values of correlation time. For comparison, a simulation-based investigation is also carried out for a fractional stochastic model that allows to preserve the memory of the time evolution of the neuronal membrane potential. In this case, the memory parameter that affects the firing activity is the fractional derivative order. In both models an adaptation level of spike frequency is attained, even if along different modalities. Comparisons and discussion of the obtained results are provided.