Field-aligned currents' scale analysis performed with the Swarm constellation

NASA Astrophysics Data System (ADS)

Lühr, Hermann; Park, Jaeheung; Gjerloev, Jesper W.; Rauberg, Jan; Michaelis, Ingo; Merayo, Jose M. G.; Brauer, Peter

2015-01-01

We present a statistical study of the temporal- and spatial-scale characteristics of different field-aligned current (FAC) types derived with the Swarm satellite formation. We divide FACs into two classes: small-scale, up to some 10 km, which are carried predominantly by kinetic Alfvén waves, and large-scale FACs with sizes of more than 150 km. For determining temporal variability we consider measurements at the same point, the orbital crossovers near the poles, but at different times. From correlation analysis we obtain a persistent period of small-scale FACs of order 10 s, while large-scale FACs can be regarded stationary for more than 60 s. For the first time we investigate the longitudinal scales. Large-scale FACs are different on dayside and nightside. On the nightside the longitudinal extension is on average 4 times the latitudinal width, while on the dayside, particularly in the cusp region, latitudinal and longitudinal scales are comparable.

Scale and time dependence of serial correlations in word-length time series of written texts

NASA Astrophysics Data System (ADS)

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

2014-11-01

This work considered the quantitative analysis of large written texts. To this end, the text was converted into a time series by taking the sequence of word lengths. The detrended fluctuation analysis (DFA) was used for characterizing long-range serial correlations of the time series. To this end, the DFA was implemented within a rolling window framework for estimating the variations of correlations, quantified in terms of the scaling exponent, strength along the text. Also, a filtering derivative was used to compute the dependence of the scaling exponent relative to the scale. The analysis was applied to three famous English-written literary narrations; namely, Alice in Wonderland (by Lewis Carrol), Dracula (by Bram Stoker) and Sense and Sensibility (by Jane Austen). The results showed that high correlations appear for scales of about 50-200 words, suggesting that at these scales the text contains the stronger coherence. The scaling exponent was not constant along the text, showing important variations with apparent cyclical behavior. An interesting coincidence between the scaling exponent variations and changes in narrative units (e.g., chapters) was found. This suggests that the scaling exponent obtained from the DFA is able to detect changes in narration structure as expressed by the usage of words of different lengths.

Multi-Spatiotemporal Patterns of Residential Burglary Crimes in Chicago: 2006-2016

NASA Astrophysics Data System (ADS)

Luo, J.

2017-10-01

This research attempts to explore the patterns of burglary crimes at multi-spatiotemporal scales in Chicago between 2006 and 2016. Two spatial scales are investigated that are census block and police beat area. At each spatial scale, three temporal scales are integrated to make spatiotemporal slices: hourly scale with two-hour time step from 12:00am to the end of the day; daily scale with one-day step from Sunday to Saturday within a week; monthly scale with one-month step from January to December. A total of six types of spatiotemporal slices will be created as the base for the analysis. Burglary crimes are spatiotemporally aggregated to spatiotemporal slices based on where and when they occurred. For each type of spatiotemporal slices with burglary occurrences integrated, spatiotemporal neighborhood will be defined and managed in a spatiotemporal matrix. Hot-spot analysis will identify spatiotemporal clusters of each type of spatiotemporal slices. Spatiotemporal trend analysis is conducted to indicate how the clusters shift in space and time. The analysis results will provide helpful information for better target policing and crime prevention policy such as police patrol scheduling regarding times and places covered.

Modes and emergent time scales of embayed beach dynamics

NASA Astrophysics Data System (ADS)

Ratliff, Katherine M.; Murray, A. Brad

2014-10-01

In this study, we use a simple numerical model (the Coastline Evolution Model) to explore alongshore transport-driven shoreline dynamics within generalized embayed beaches (neglecting cross-shore effects). Using principal component analysis (PCA), we identify two primary orthogonal modes of shoreline behavior that describe shoreline variation about its unchanging mean position: the rotation mode, which has been previously identified and describes changes in the mean shoreline orientation, and a newly identified breathing mode, which represents changes in shoreline curvature. Wavelet analysis of the PCA mode time series reveals characteristic time scales of these modes (typically years to decades) that emerge within even a statistically constant white-noise wave climate (without changes in external forcing), suggesting that these time scales can arise from internal system dynamics. The time scales of both modes increase linearly with shoreface depth, suggesting that the embayed beach sediment transport dynamics exhibit a diffusive scaling.

Influence of the Time Scale on the Construction of Financial Networks

PubMed Central

Emmert-Streib, Frank; Dehmer, Matthias

2010-01-01

Background In this paper we investigate the definition and formation of financial networks. Specifically, we study the influence of the time scale on their construction. Methodology/Principal Findings For our analysis we use correlation-based networks obtained from the daily closing prices of stock market data. More precisely, we use the stocks that currently comprise the Dow Jones Industrial Average (DJIA) and estimate financial networks where nodes correspond to stocks and edges correspond to none vanishing correlation coefficients. That means only if a correlation coefficient is statistically significant different from zero, we include an edge in the network. This construction procedure results in unweighted, undirected networks. By separating the time series of stock prices in non-overlapping intervals, we obtain one network per interval. The length of these intervals corresponds to the time scale of the data, whose influence on the construction of the networks will be studied in this paper. Conclusions/Significance Numerical analysis of four different measures in dependence on the time scale for the construction of networks allows us to gain insights about the intrinsic time scale of the stock market with respect to a meaningful graph-theoretical analysis. PMID:20949124

Scale-Limited Lagrange Stability and Finite-Time Synchronization for Memristive Recurrent Neural Networks on Time Scales.

PubMed

Xiao, Qiang; Zeng, Zhigang

2017-10-01

The existed results of Lagrange stability and finite-time synchronization for memristive recurrent neural networks (MRNNs) are scale-free on time evolvement, and some restrictions appear naturally. In this paper, two novel scale-limited comparison principles are established by means of inequality techniques and induction principle on time scales. Then the results concerning Lagrange stability and global finite-time synchronization of MRNNs on time scales are obtained. Scaled-limited Lagrange stability criteria are derived, in detail, via nonsmooth analysis and theory of time scales. Moreover, novel criteria for achieving the global finite-time synchronization are acquired. In addition, the derived method can also be used to study global finite-time stabilization. The proposed results extend or improve the existed ones in the literatures. Two numerical examples are chosen to show the effectiveness of the obtained results.

Understanding Business Interests in International Large-Scale Student Assessments: A Media Analysis of "The Economist," "Financial Times," and "Wall Street Journal"

ERIC Educational Resources Information Center

Steiner-Khamsi, Gita; Appleton, Margaret; Vellani, Shezleen

2018-01-01

The media analysis is situated in the larger body of studies that explore the varied reasons why different policy actors advocate for international large-scale student assessments (ILSAs) and adds to the research on the fast advance of the global education industry. The analysis of "The Economist," "Financial Times," and…

Statistical Analysis of Small-Scale Magnetic Flux Emergence Patterns: A Useful Subsurface Diagnostic?

NASA Astrophysics Data System (ADS)

Lamb, Derek A.

2016-10-01

While sunspots follow a well-defined pattern of emergence in space and time, small-scale flux emergence is assumed to occur randomly at all times in the quiet Sun. HMI's full-disk coverage, high cadence, spatial resolution, and duty cycle allow us to probe that basic assumption. Some case studies of emergence suggest that temporal clustering on spatial scales of 50-150 Mm may occur. If clustering is present, it could serve as a diagnostic of large-scale subsurface magnetic field structures. We present the results of a manual survey of small-scale flux emergence events over a short time period, and a statistical analysis addressing the question of whether these events show spatio-temporal behavior that is anything other than random.

Multiple-time scales analysis of physiological time series under neural control

NASA Technical Reports Server (NTRS)

Peng, C. K.; Hausdorff, J. M.; Havlin, S.; Mietus, J. E.; Stanley, H. E.; Goldberger, A. L.

1998-01-01

We discuss multiple-time scale properties of neurophysiological control mechanisms, using heart rate and gait regulation as model systems. We find that scaling exponents can be used as prognostic indicators. Furthermore, detection of more subtle degradation of scaling properties may provide a novel early warning system in subjects with a variety of pathologies including those at high risk of sudden death.

Detectability of Granger causality for subsampled continuous-time neurophysiological processes.

PubMed

Barnett, Lionel; Seth, Anil K

2017-01-01

Granger causality is well established within the neurosciences for inference of directed functional connectivity from neurophysiological data. These data usually consist of time series which subsample a continuous-time biophysiological process. While it is well known that subsampling can lead to imputation of spurious causal connections where none exist, less is known about the effects of subsampling on the ability to reliably detect causal connections which do exist. We present a theoretical analysis of the effects of subsampling on Granger-causal inference. Neurophysiological processes typically feature signal propagation delays on multiple time scales; accordingly, we base our analysis on a distributed-lag, continuous-time stochastic model, and consider Granger causality in continuous time at finite prediction horizons. Via exact analytical solutions, we identify relationships among sampling frequency, underlying causal time scales and detectability of causalities. We reveal complex interactions between the time scale(s) of neural signal propagation and sampling frequency. We demonstrate that detectability decays exponentially as the sample time interval increases beyond causal delay times, identify detectability "black spots" and "sweet spots", and show that downsampling may potentially improve detectability. We also demonstrate that the invariance of Granger causality under causal, invertible filtering fails at finite prediction horizons, with particular implications for inference of Granger causality from fMRI data. Our analysis emphasises that sampling rates for causal analysis of neurophysiological time series should be informed by domain-specific time scales, and that state-space modelling should be preferred to purely autoregressive modelling. On the basis of a very general model that captures the structure of neurophysiological processes, we are able to help identify confounds, and offer practical insights, for successful detection of causal connectivity from neurophysiological recordings. Copyright © 2016 Elsevier B.V. All rights reserved.

Multiscale entropy-based methods for heart rate variability complexity analysis

NASA Astrophysics Data System (ADS)

Silva, Luiz Eduardo Virgilio; Cabella, Brenno Caetano Troca; Neves, Ubiraci Pereira da Costa; Murta Junior, Luiz Otavio

2015-03-01

Physiologic complexity is an important concept to characterize time series from biological systems, which associated to multiscale analysis can contribute to comprehension of many complex phenomena. Although multiscale entropy has been applied to physiological time series, it measures irregularity as function of scale. In this study we purpose and evaluate a set of three complexity metrics as function of time scales. Complexity metrics are derived from nonadditive entropy supported by generation of surrogate data, i.e. SDiffqmax, qmax and qzero. In order to access accuracy of proposed complexity metrics, receiver operating characteristic (ROC) curves were built and area under the curves was computed for three physiological situations. Heart rate variability (HRV) time series in normal sinus rhythm, atrial fibrillation, and congestive heart failure data set were analyzed. Results show that proposed metric for complexity is accurate and robust when compared to classic entropic irregularity metrics. Furthermore, SDiffqmax is the most accurate for lower scales, whereas qmax and qzero are the most accurate when higher time scales are considered. Multiscale complexity analysis described here showed potential to assess complex physiological time series and deserves further investigation in wide context.

Detecting and characterizing high-frequency oscillations in epilepsy: a case study of big data analysis

NASA Astrophysics Data System (ADS)

Huang, Liang; Ni, Xuan; Ditto, William L.; Spano, Mark; Carney, Paul R.; Lai, Ying-Cheng

2017-01-01

We develop a framework to uncover and analyse dynamical anomalies from massive, nonlinear and non-stationary time series data. The framework consists of three steps: preprocessing of massive datasets to eliminate erroneous data segments, application of the empirical mode decomposition and Hilbert transform paradigm to obtain the fundamental components embedded in the time series at distinct time scales, and statistical/scaling analysis of the components. As a case study, we apply our framework to detecting and characterizing high-frequency oscillations (HFOs) from a big database of rat electroencephalogram recordings. We find a striking phenomenon: HFOs exhibit on-off intermittency that can be quantified by algebraic scaling laws. Our framework can be generalized to big data-related problems in other fields such as large-scale sensor data and seismic data analysis.

Data series embedding and scale invariant statistics.

PubMed

Michieli, I; Medved, B; Ristov, S

2010-06-01

Data sequences acquired from bio-systems such as human gait data, heart rate interbeat data, or DNA sequences exhibit complex dynamics that is frequently described by a long-memory or power-law decay of autocorrelation function. One way of characterizing that dynamics is through scale invariant statistics or "fractal-like" behavior. For quantifying scale invariant parameters of physiological signals several methods have been proposed. Among them the most common are detrended fluctuation analysis, sample mean variance analyses, power spectral density analysis, R/S analysis, and recently in the realm of the multifractal approach, wavelet analysis. In this paper it is demonstrated that embedding the time series data in the high-dimensional pseudo-phase space reveals scale invariant statistics in the simple fashion. The procedure is applied on different stride interval data sets from human gait measurements time series (Physio-Bank data library). Results show that introduced mapping adequately separates long-memory from random behavior. Smaller gait data sets were analyzed and scale-free trends for limited scale intervals were successfully detected. The method was verified on artificially produced time series with known scaling behavior and with the varying content of noise. The possibility for the method to falsely detect long-range dependence in the artificially generated short range dependence series was investigated. (c) 2009 Elsevier B.V. All rights reserved.

Characterizing the performance of ecosystem models across time scales: A spectral analysis of the North American Carbon Program site-level synthesis

Treesearch

Michael C. Dietze; Rodrigo Vargas; Andrew D. Richardson; Paul C. Stoy; Alan G. Barr; Ryan S. Anderson; M. Altaf Arain; Ian T. Baker; T. Andrew Black; Jing M. Chen; Philippe Ciais; Lawrence B. Flanagan; Christopher M. Gough; Robert F. Grant; David Hollinger; R. Cesar Izaurralde; Christopher J. Kucharik; Peter Lafleur; Shugang Liu; Erandathie Lokupitiya; Yiqi Luo; J. William Munger; Changhui Peng; Benjamin Poulter; David T. Price; Daniel M. Ricciuto; William J. Riley; Alok Kumar Sahoo; Kevin Schaefer; Andrew E. Suyker; Hanqin Tian; Christina Tonitto; Hans Verbeeck; Shashi B. Verma; Weifeng Wang; Ensheng Weng

2011-01-01

Ecosystem models are important tools for diagnosing the carbon cycle and projecting its behavior across space and time. Despite the fact that ecosystems respond to drivers at multiple time scales, most assessments of model performance do not discriminate different time scales. Spectral methods, such as wavelet analyses, present an alternative approach that enables the...

Spatio-temporal hierarchy in the dynamics of a minimalist protein model

NASA Astrophysics Data System (ADS)

Matsunaga, Yasuhiro; Baba, Akinori; Li, Chun-Biu; Straub, John E.; Toda, Mikito; Komatsuzaki, Tamiki; Berry, R. Stephen

2013-12-01

A method for time series analysis of molecular dynamics simulation of a protein is presented. In this approach, wavelet analysis and principal component analysis are combined to decompose the spatio-temporal protein dynamics into contributions from a hierarchy of different time and space scales. Unlike the conventional Fourier-based approaches, the time-localized wavelet basis captures the vibrational energy transfers among the collective motions of proteins. As an illustrative vehicle, we have applied our method to a coarse-grained minimalist protein model. During the folding and unfolding transitions of the protein, vibrational energy transfers between the fast and slow time scales were observed among the large-amplitude collective coordinates while the other small-amplitude motions are regarded as thermal noise. Analysis employing a Gaussian-based measure revealed that the time scales of the energy redistribution in the subspace spanned by such large-amplitude collective coordinates are slow compared to the other small-amplitude coordinates. Future prospects of the method are discussed in detail.

A model of return intervals between earthquake events

NASA Astrophysics Data System (ADS)

Zhou, Yu; Chechkin, Aleksei; Sokolov, Igor M.; Kantz, Holger

2016-06-01

Application of the diffusion entropy analysis and the standard deviation analysis to the time sequence of the southern California earthquake events from 1976 to 2002 uncovered scaling behavior typical for anomalous diffusion. However, the origin of such behavior is still under debate. Some studies attribute the scaling behavior to the correlations in the return intervals, or waiting times, between aftershocks or mainshocks. To elucidate a nature of the scaling, we applied specific reshulffling techniques to eliminate correlations between different types of events and then examined how it affects the scaling behavior. We demonstrate that the origin of the scaling behavior observed is the interplay between mainshock waiting time distribution and the structure of clusters of aftershocks, but not correlations in waiting times between the mainshocks and aftershocks themselves. Our findings are corroborated by numerical simulations of a simple model showing a very similar behavior. The mainshocks are modeled by a renewal process with a power-law waiting time distribution between events, and aftershocks follow a nonhomogeneous Poisson process with the rate governed by Omori's law.

Multiscaling for systems with a broad continuum of characteristic lengths and times: Structural transitions in nanocomposites.

PubMed

Pankavich, S; Ortoleva, P

2010-06-01

The multiscale approach to N-body systems is generalized to address the broad continuum of long time and length scales associated with collective behaviors. A technique is developed based on the concept of an uncountable set of time variables and of order parameters (OPs) specifying major features of the system. We adopt this perspective as a natural extension of the commonly used discrete set of time scales and OPs which is practical when only a few, widely separated scales exist. The existence of a gap in the spectrum of time scales for such a system (under quasiequilibrium conditions) is used to introduce a continuous scaling and perform a multiscale analysis of the Liouville equation. A functional-differential Smoluchowski equation is derived for the stochastic dynamics of the continuum of Fourier component OPs. A continuum of spatially nonlocal Langevin equations for the OPs is also derived. The theory is demonstrated via the analysis of structural transitions in a composite material, as occurs for viral capsids and molecular circuits.

Multi-scale variability and long-range memory in indoor Radon concentrations from Coimbra, Portugal

NASA Astrophysics Data System (ADS)

Donner, Reik V.; Potirakis, Stelios; Barbosa, Susana

2014-05-01

The presence or absence of long-range correlations in the variations of indoor Radon concentrations has recently attracted considerable interest. As a radioactive gas naturally emitted from the ground in certain geological settings, understanding environmental factors controlling Radon concentrations and their dynamics is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we re-analyze two high-resolution records of indoor Radon concentrations from Coimbra, Portugal, each of which spans several months of continuous measurements. In order to evaluate the presence of long-range correlations and fractal scaling, we utilize a multiplicity of complementary methods, including power spectral analysis, ARFIMA modeling, classical and multi-fractal detrended fluctuation analysis, and two different estimators of the signals' fractal dimensions. Power spectra and fluctuation functions reveal some complex behavior with qualitatively different properties on different time-scales: white noise in the high-frequency part, indications of some long-range correlated process dominating time scales of several hours to days, and pronounced low-frequency variability associated with tidal and/or meteorological forcing. In order to further decompose these different scales of variability, we apply two different approaches. On the one hand, applying multi-resolution analysis based on the discrete wavelet transform allows separately studying contributions on different time scales and characterize their specific correlation and scaling properties. On the other hand, singular system analysis (SSA) provides a reconstruction of the essential modes of variability. Specifically, by considering only the first leading SSA modes, we achieve an efficient de-noising of our environmental signals, highlighting the low-frequency variations together with some distinct scaling on sub-daily time-scales resembling the properties of a long-range correlated process.

Comparison of detrending methods for fluctuation analysis in hydrology

NASA Astrophysics Data System (ADS)

Zhang, Qiang; Zhou, Yu; Singh, Vijay P.; Chen, Yongqin David

2011-03-01

SummaryTrends within a hydrologic time series can significantly influence the scaling results of fluctuation analysis, such as rescaled range (RS) analysis and (multifractal) detrended fluctuation analysis (MF-DFA). Therefore, removal of trends is important in the study of scaling properties of the time series. In this study, three detrending methods, including adaptive detrending algorithm (ADA), Fourier-based method, and average removing technique, were evaluated by analyzing numerically generated series and observed streamflow series with obvious relative regular periodic trend. Results indicated that: (1) the Fourier-based detrending method and ADA were similar in detrending practices, and given proper parameters, these two methods can produce similarly satisfactory results; (2) detrended series by Fourier-based detrending method and ADA lose the fluctuation information at larger time scales, and the location of crossover points is heavily impacted by the chosen parameters of these two methods; and (3) the average removing method has an advantage over the other two methods, i.e., the fluctuation information at larger time scales is kept well-an indication of relatively reliable performance in detrending. In addition, the average removing method performed reasonably well in detrending a time series with regular periods or trends. In this sense, the average removing method should be preferred in the study of scaling properties of the hydrometeorolgical series with relative regular periodic trend using MF-DFA.

Solving the puzzle of discrepant quasar variability on monthly time-scales implied by SDSS and CRTS data sets

NASA Astrophysics Data System (ADS)

Suberlak, Krzysztof; Ivezić, Željko; MacLeod, Chelsea L.; Graham, Matthew; Sesar, Branimir

2017-12-01

We present an improved photometric error analysis for the 7 100 CRTS (Catalina Real-Time Transient Survey) optical light curves for quasars from the SDSS (Sloan Digital Sky Survey) Stripe 82 catalogue. The SDSS imaging survey has provided a time-resolved photometric data set, which greatly improved our understanding of the quasar optical continuum variability: Data for monthly and longer time-scales are consistent with a damped random walk (DRW). Recently, newer data obtained by CRTS provided puzzling evidence for enhanced variability, compared to SDSS results, on monthly time-scales. Quantitatively, SDSS results predict about 0.06 mag root-mean-square (rms) variability for monthly time-scales, while CRTS data show about a factor of 2 larger rms, for spectroscopically confirmed SDSS quasars. Our analysis has successfully resolved this discrepancy as due to slightly underestimated photometric uncertainties from the CRTS image processing pipelines. As a result, the correction for observational noise is too small and the implied quasar variability is too large. The CRTS photometric error correction factors, derived from detailed analysis of non-variable SDSS standard stars that were re-observed by CRTS, are about 20-30 per cent, and result in reconciling quasar variability behaviour implied by the CRTS data with earlier SDSS results. An additional analysis based on independent light curve data for the same objects obtained by the Palomar Transient Factory provides further support for this conclusion. In summary, the quasar variability constraints on weekly and monthly time-scales from SDSS, CRTS and PTF surveys are mutually compatible, as well as consistent with DRW model.

AQMEII3 evaluation of regional NA/EU simulations and analysis of scale, boundary conditions and emissions error-dependence

EPA Science Inventory

Through the comparison of several regional-scale chemistry transport modelling systems that simulate meteorology and air quality over the European and American continents, this study aims at i) apportioning the error to the responsible processes using time-scale analysis, ii) hel...

Broadband Structural Dynamics: Understanding the Impulse-Response of Structures Across Multiple Length and Time Scales

DTIC Science & Technology

2010-08-18

Spectral domain response calculated • Time domain response obtained through inverse transform Approach 4: WASABI Wavelet Analysis of Structural Anomalies...differences at unity scale! Time Function Transform Apply Spectral Domain Transfer Function Time Function Inverse Transform Transform Transform  mtP

Self-similarity of waiting times in fracture systems

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

Niccolini, G.; Bosia, F.; Carpinteri, A.

2009-08-15

Experimental and numerical results are presented for a fracture experiment carried out on a fiber-reinforced element under flexural loading, and a statistical analysis is performed for acoustic emission waiting-time distributions. By an optimization procedure, a recently proposed scaling law describing these distributions for different event magnitude scales is confirmed by both experimental and numerical data, thus reinforcing the idea that fracture of heterogeneous materials has scaling properties similar to those found for earthquakes. Analysis of the different scaling parameters obtained for experimental and numerical data leads us to formulate the hypothesis that the type of scaling function obtained depends onmore » the level of correlation among fracture events in the system.« less

Estimation of surface heat and moisture fluxes over a prairie grassland. II - Two-dimensional time filtering and site variability

NASA Technical Reports Server (NTRS)

Crosson, William L.; Smith, Eric A.

1992-01-01

The behavior of in situ measurements of surface fluxes obtained during FIFE 1987 is examined by using correlative and spectral techniques in order to assess the significance of fluctuations on various time scales, from subdiurnal up to synoptic, intraseasonal, and annual scales. The objectives of this analysis are: (1) to determine which temporal scales have a significant impact on areal averaged fluxes and (2) to design a procedure for filtering an extended flux time series that preserves the basic diurnal features and longer time scales while removing high frequency noise that cannot be attributed to site-induced variation. These objectives are accomplished through the use of a two-dimensional cross-time Fourier transform, which serves to separate processes inherently related to diurnal and subdiurnal variability from those which impact flux variations on the longer time scales. A filtering procedure is desirable before the measurements are utilized as input with an experimental biosphere model, to insure that model based intercomparisons at multiple sites are uncontaminated by input variance not related to true site behavior. Analysis of the spectral decomposition indicates that subdiurnal time scales having periods shorter than 6 hours have little site-to-site consistency and therefore little impact on areal integrated fluxes.

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).

Shoreline Position Dynamics: Measurement and Analysis

NASA Astrophysics Data System (ADS)

Barton, C. C.; Rigling, B.; Hunter, N.; Tebbens, S. F.

2012-12-01

The dynamics of sandy shoreline position is a fundamental property of complex beach face processes and is characterized by the power scaling exponent. Spectral analysis was performed on the temporal position of four sandy shorelines extracted from four shore perpendicular profiles each resurveyed approximately seven times per year over twenty-seven years at the Field Research Facility (FRF) by the U.S. Army Corps of Engineers, located at Kitty Hawk, NC. The four shorelines we studied are mean-higher-high-water (MHHW), mean-high-water (MHW), and mean-low-water (MLW) and mean-lower-low-water (MLLW) with elevations of 0.75m, 0.65m, -0.33m, and -0.37m respectively, relative to the NGVD29 geodetic datum. Spectral analysis used to quantify scaling exponents requires data evenly spaced in time. Our previous studies of shoreline dynamics used the Lomb Periodogram method for spectral analysis, which we now show does not return the correct scaling exponent for unevenly spaced data. New to this study is the use of slotted resampling and a linear predictor to construct an evenly spaced data set from an unevenly spaced data set which has been shown with synthetic data to return correct values of the scaling exponents. A periodogram linear regression (PLR) estimate is used to determine the scaling exponent β of the constructed evenly spaced time series. This study shows that sandy shoreline position exhibits nonlinear self-affine dynamics through time. The times series of each of the four shorelines has scaling exponents ranging as follows: MHHW, β = 1.3-2.2; MHW, β = 1.3-2.1; MLW, β = 1.2-1.6; and MLLW, β = 1.2-1.6. Time series with β greater than 1 are non-stationary (mean and standard deviation are not constant through time) and are increasingly internally correlated with increasing β. The range of scaling exponents of the MLW and MLLW shorelines, near β = 1.5, is indicative of a diffusion process. The range of scaling exponents for the MHW and MHHW shorelines indicates spatially variable dynamics higher on the beach face.

Generalization of Turbulent Pair Dispersion to Large Initial Separations

NASA Astrophysics Data System (ADS)

Shnapp, Ron; Liberzon, Alex; International Collaboration for Turbulence Research

2018-06-01

We present a generalization of turbulent pair dispersion to large initial separations (η

Rasch Analysis of the Geriatric Depression Scale--Short Form

ERIC Educational Resources Information Center

Chiang, Karl S.; Green, Kathy E.; Cox, Enid O.

2009-01-01

Purpose: The purpose of this study was to examine scale dimensionality, reliability, invariance, targeting, continuity, cutoff scores, and diagnostic use of the Geriatric Depression Scale-Short Form (GDS-SF) over time with a sample of 177 English-speaking U.S. elders. Design and Methods: An item response theory, Rasch analysis, was conducted with…

Study of the human postural control system during quiet standing using detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Teresa Blázquez, M.; Anguiano, Marta; de Saavedra, Fernando Arias; Lallena, Antonio M.; Carpena, Pedro

2009-05-01

The detrended fluctuation analysis is used to study the behavior of different time series obtained from the trajectory of the center of pressure, the output of the activity of the human postural control system. The results suggest that these trajectories present two different regimes in their scaling properties: persistent (for high frequencies, short-range time scale) to antipersistent (for low frequencies, long-range time scale) behaviors. The similitude between the results obtained for the measurements, done with both eyes open and eyes closed, indicate either that the visual system may be disregarded by the postural control system while maintaining the quiet standing, or that the control mechanisms associated with each type of information (visual, vestibular and somatosensory) cannot be disentangled with the type of analysis performed here.

Scalable Parameter Estimation for Genome-Scale Biochemical Reaction Networks

PubMed Central

Kaltenbacher, Barbara; Hasenauer, Jan

2017-01-01

Mechanistic mathematical modeling of biochemical reaction networks using ordinary differential equation (ODE) models has improved our understanding of small- and medium-scale biological processes. While the same should in principle hold for large- and genome-scale processes, the computational methods for the analysis of ODE models which describe hundreds or thousands of biochemical species and reactions are missing so far. While individual simulations are feasible, the inference of the model parameters from experimental data is computationally too intensive. In this manuscript, we evaluate adjoint sensitivity analysis for parameter estimation in large scale biochemical reaction networks. We present the approach for time-discrete measurement and compare it to state-of-the-art methods used in systems and computational biology. Our comparison reveals a significantly improved computational efficiency and a superior scalability of adjoint sensitivity analysis. The computational complexity is effectively independent of the number of parameters, enabling the analysis of large- and genome-scale models. Our study of a comprehensive kinetic model of ErbB signaling shows that parameter estimation using adjoint sensitivity analysis requires a fraction of the computation time of established methods. The proposed method will facilitate mechanistic modeling of genome-scale cellular processes, as required in the age of omics. PMID:28114351

Adolescent Time Attitude Scale: Adaptation into Turkish

ERIC Educational Resources Information Center

Çelik, Eyüp; Sahranç, Ümit; Kaya, Mehmet; Turan, Mehmet Emin

2017-01-01

This research is aimed at examining the validity and reliability of the Turkish version of the Time Attitude Scale. Data was collected from 433 adolescents; 206 males and 227 females participated in the study. Confirmatory factor analysis performed to discover the structural validity of the scale. The internal consistency method was used for…

Endogenous and exogenous dynamics in the fluctuations of capital fluxes. An empirical analysis of the Chinese stock market

NASA Astrophysics Data System (ADS)

Jiang, Z.-Q.; Guo, L.; Zhou, W.-X.

2007-06-01

A phenomenological investigation of the endogenous and exogenous dynamics in the fluctuations of capital fluxes is carried out on the Chinese stock market using mean-variance analysis, fluctuation analysis, and their generalizations to higher orders. Non-universal dynamics have been found not only in the scaling exponent α, which is different from the universal values 1/2 and 1, but also in the distributions of the ratio η= σexo / σendo of individual stocks. Both the scaling exponent α of fluctuations and the Hurst exponent Hi increase in logarithmic form with the time scale Δt and the mean traded value per minute , respectively. We find that the scaling exponent αendo of the endogenous fluctuations is independent of the time scale. Multiscaling and multifractal features are observed in the data as well. However, the inhomogeneous impact model is not verified.

Deviations from uniform power law scaling in nonstationary time series

NASA Technical Reports Server (NTRS)

Viswanathan, G. M.; Peng, C. K.; Stanley, H. E.; Goldberger, A. L.

1997-01-01

A classic problem in physics is the analysis of highly nonstationary time series that typically exhibit long-range correlations. Here we test the hypothesis that the scaling properties of the dynamics of healthy physiological systems are more stable than those of pathological systems by studying beat-to-beat fluctuations in the human heart rate. We develop techniques based on the Fano factor and Allan factor functions, as well as on detrended fluctuation analysis, for quantifying deviations from uniform power-law scaling in nonstationary time series. By analyzing extremely long data sets of up to N = 10(5) beats for 11 healthy subjects, we find that the fluctuations in the heart rate scale approximately uniformly over several temporal orders of magnitude. By contrast, we find that in data sets of comparable length for 14 subjects with heart disease, the fluctuations grow erratically, indicating a loss of scaling stability.

Timing of Formal Phase Safety Reviews for Large-Scale Integrated Hazard Analysis

NASA Technical Reports Server (NTRS)

Massie, Michael J.; Morris, A. Terry

2010-01-01

Integrated hazard analysis (IHA) is a process used to identify and control unacceptable risk. As such, it does not occur in a vacuum. IHA approaches must be tailored to fit the system being analyzed. Physical, resource, organizational and temporal constraints on large-scale integrated systems impose additional direct or derived requirements on the IHA. The timing and interaction between engineering and safety organizations can provide either benefits or hindrances to the overall end product. The traditional approach for formal phase safety review timing and content, which generally works well for small- to moderate-scale systems, does not work well for very large-scale integrated systems. This paper proposes a modified approach to timing and content of formal phase safety reviews for IHA. Details of the tailoring process for IHA will describe how to avoid temporary disconnects in major milestone reviews and how to maintain a cohesive end-to-end integration story particularly for systems where the integrator inherently has little to no insight into lower level systems. The proposal has the advantage of allowing the hazard analysis development process to occur as technical data normally matures.

Flow topologies and turbulence scales in a jet-in-cross-flow

DOE PAGES

Oefelein, Joseph C.; Ruiz, Anthony M.; Lacaze, Guilhem

2015-04-03

This study presents a detailed analysis of the flow topologies and turbulence scales in the jet-in-cross-flow experiment of [Su and Mungal JFM 2004]. The analysis is performed using the Large Eddy Simulation (LES) technique with a highly resolved grid and time-step and well controlled boundary conditions. This enables quantitative agreement with the first and second moments of turbulence statistics measured in the experiment. LES is used to perform the analysis since experimental measurements of time-resolved 3D fields are still in their infancy and because sampling periods are generally limited with direct numerical simulation. A major focal point is the comprehensivemore » characterization of the turbulence scales and their evolution. Time-resolved probes are used with long sampling periods to obtain maps of the integral scales, Taylor microscales, and turbulent kinetic energy spectra. Scalar-fluctuation scales are also quantified. In the near-field, coherent structures are clearly identified, both in physical and spectral space. Along the jet centerline, turbulence scales grow according to a classical one-third power law. However, the derived maps of turbulence scales reveal strong inhomogeneities in the flow. From the modeling perspective, these insights are useful to design optimized grids and improve numerical predictions in similar configurations.« less

Establishing a direct connection between detrended fluctuation analysis and Fourier analysis

NASA Astrophysics Data System (ADS)

Kiyono, Ken

2015-10-01

To understand methodological features of the detrended fluctuation analysis (DFA) using a higher-order polynomial fitting, we establish the direct connection between DFA and Fourier analysis. Based on an exact calculation of the single-frequency response of the DFA, the following facts are shown analytically: (1) in the analysis of stochastic processes exhibiting a power-law scaling of the power spectral density (PSD), S (f ) ˜f-β , a higher-order detrending in the DFA has no adverse effect in the estimation of the DFA scaling exponent α , which satisfies the scaling relation α =(β +1 )/2 ; (2) the upper limit of the scaling exponents detectable by the DFA depends on the order of polynomial fit used in the DFA, and is bounded by m +1 , where m is the order of the polynomial fit; (3) the relation between the time scale in the DFA and the corresponding frequency in the PSD are distorted depending on both the order of the DFA and the frequency dependence of the PSD. We can improve the scale distortion by introducing the corrected time scale in the DFA corresponding to the inverse of the frequency scale in the PSD. In addition, our analytical approach makes it possible to characterize variants of the DFA using different types of detrending. As an application, properties of the detrending moving average algorithm are discussed.

Development of multiscale complexity and multifractality of fetal heart rate variability.

PubMed

Gierałtowski, Jan; Hoyer, Dirk; Tetschke, Florian; Nowack, Samuel; Schneider, Uwe; Zebrowski, Jan

2013-11-01

During fetal development a complex system grows and coordination over multiple time scales is formed towards an integrated behavior of the organism. Since essential cardiovascular and associated coordination is mediated by the autonomic nervous system (ANS) and the ANS activity is reflected in recordable heart rate patterns, multiscale heart rate analysis is a tool predestined for the diagnosis of prenatal maturation. The analyses over multiple time scales requires sufficiently long data sets while the recordings of fetal heart rate as well as the behavioral states studied are themselves short. Care must be taken that the analysis methods used are appropriate for short data lengths. We investigated multiscale entropy and multifractal scaling exponents from 30 minute recordings of 27 normal fetuses, aged between 23 and 38 weeks of gestational age (WGA) during the quiet state. In multiscale entropy, we found complexity lower than that of non-correlated white noise over all 20 coarse graining time scales investigated. Significant maturation age related complexity increase was strongest expressed at scale 2, both using sample entropy and generalized mutual information as complexity estimates. Multiscale multifractal analysis (MMA) in which the Hurst surface h(q,s) is calculated, where q is the multifractal parameter and s is the scale, was applied to the fetal heart rate data. MMA is a method derived from detrended fluctuation analysis (DFA). We modified the base algorithm of MMA to be applicable for short time series analysis using overlapping data windows and a reduction of the scale range. We looked for such q and s for which the Hurst exponent h(q,s) is most correlated with gestational age. We used this value of the Hurst exponent to predict the gestational age based only on fetal heart rate variability properties. Comparison with the true age of the fetus gave satisfying results (error 2.17±3.29 weeks; p<0.001; R(2)=0.52). In addition, we found that the normally used DFA scale range is non-optimal for fetal age evaluation. We conclude that 30 min recordings are appropriate and sufficient for assessing fetal age by multiscale entropy and multiscale multifractal analysis. The predominant prognostic role of scale 2 heart beats for MSE and scale 39 heart beats (at q=-0.7) for MMA cannot be explored neither by single scale complexity measures nor by standard detrended fluctuation analysis. Copyright © 2013 Elsevier B.V. All rights reserved.

Aerosol Index Dynamics over Athens and Beijing

NASA Astrophysics Data System (ADS)

Christodoulakis, J.; Varotsos, C.; Tzanis, C.; Xue, Y.

2014-11-01

We present the analysis of monthly mean Aerosol Index (AI) values, over Athens, Greece, and Beijing, China, for the period 1979-2012. The aim of the analysis is the identification of time scaling in the AI time series, by using a data analysis technique that would not be affected by the non-stationarity of the data. The appropriate technique satisfying this criterion is the Detrended Fluctuation Analysis (DF A). For the deseasonalization of time series classic Wiener method was applied filtering out the seasonal - 3 months, semiannual - 6 months and annual - 12 months periods. The data analysis for both Athens and Beijing revealed that the exponents α for both time periods are greater than 0.5 indicating that persistence of the correlations in the fluctuations of the deseasonalized AI values exists for time scales between about 4 months and 3.5 years (for the period 1979-1993) or 4 years (for the period 1996-2012).

Aerosol Index Dynamics over Athens and Beijing

NASA Astrophysics Data System (ADS)

Christodoulakis, J.; Varotsos, C.; Tzanis, C.; Xue, Y.

2014-11-01

We present the analysis of monthly mean Aerosol Index (AI) values, over Athens, Greece, and Beijing, China, for the period 1979- 2012. The aim of the analysis is the identification of time scaling in the AI time series, by using a data analysis technique that would not be affected by the non-stationarity of the data. The appropriate technique satisfying this criterion is the Detrended Fluctuation Analysis (DFA). For the deseasonalization of time series classic Wiener method was applied filtering out the seasonal - 3 months, semiannual - 6 months and annual - 12 months periods. The data analysis for both Athens and Beijing revealed that the exponents α for both time periods are greater than 0.5 indicating that persistence of the correlations in the fluctuations of the deseasonalized AI values exists for time scales between about 4 months and 3.5 years (for the period 1979-1993) or 4 years (for the period 1996-2012).

Demonstration of Wavelet Techniques in the Spectral Analysis of Bypass Transition Data

NASA Technical Reports Server (NTRS)

Lewalle, Jacques; Ashpis, David E.; Sohn, Ki-Hyeon

1997-01-01

A number of wavelet-based techniques for the analysis of experimental data are developed and illustrated. A multiscale analysis based on the Mexican hat wavelet is demonstrated as a tool for acquiring physical and quantitative information not obtainable by standard signal analysis methods. Experimental data for the analysis came from simultaneous hot-wire velocity traces in a bypass transition of the boundary layer on a heated flat plate. A pair of traces (two components of velocity) at one location was excerpted. A number of ensemble and conditional statistics related to dominant time scales for energy and momentum transport were calculated. The analysis revealed a lack of energy-dominant time scales inside turbulent spots but identified transport-dominant scales inside spots that account for the largest part of the Reynolds stress. Momentum transport was much more intermittent than were energetic fluctuations. This work is the first step in a continuing study of the spatial evolution of these scale-related statistics, the goal being to apply the multiscale analysis results to improve the modeling of transitional and turbulent industrial flows.

Real Time Text Analysis

NASA Astrophysics Data System (ADS)

Senthilkumar, K.; Ruchika Mehra Vijayan, E.

2017-11-01

This paper aims to illustrate real time analysis of large scale data. For practical implementation we are performing sentiment analysis on live Twitter feeds for each individual tweet. To analyze sentiments we will train our data model on sentiWordNet, a polarity assigned wordNet sample by Princeton University. Our main objective will be to efficiency analyze large scale data on the fly using distributed computation. Apache Spark and Apache Hadoop eco system is used as distributed computation platform with Java as development language

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.

How High Frequency Trading Affects a Market Index

PubMed Central

Kenett, Dror Y.; Ben-Jacob, Eshel; Stanley, H. Eugene; gur-Gershgoren, Gitit

2013-01-01

The relationship between a market index and its constituent stocks is complicated. While an index is a weighted average of its constituent stocks, when the investigated time scale is one day or longer the index has been found to have a stronger effect on the stocks than vice versa. We explore how this interaction changes in short time scales using high frequency data. Using a correlation-based analysis approach, we find that in short time scales stocks have a stronger influence on the index. These findings have implications for high frequency trading and suggest that the price of an index should be published on shorter time scales, as close as possible to those of the actual transaction time scale. PMID:23817553

Trend Switching Processes in Financial Markets

NASA Astrophysics Data System (ADS)

Preis, Tobias; Stanley, H. Eugene

For an intriguing variety of switching processes in nature, the underlying complex system abruptly changes at a specific point from one state to another in a highly discontinuous fashion. Financial market fluctuations are characterized by many abrupt switchings creating increasing trends ("bubble formation") and decreasing trends ("bubble collapse"), on time scales ranging from macroscopic bubbles persisting for hundreds of days to microscopic bubbles persisting only for very short time scales. Our analysis is based on a German DAX Future data base containing 13,991,275 transactions recorded with a time resolution of 10- 2 s. For a parallel analysis, we use a data base of all S&P500 stocks providing 2,592,531 daily closing prices. We ask whether these ubiquitous switching processes have quantifiable features independent of the time horizon studied. We find striking scale-free behavior of the volatility after each switching occurs. We interpret our findings as being consistent with time-dependent collective behavior of financial market participants. We test the possible universality of our result by performing a parallel analysis of fluctuations in transaction volume and time intervals between trades. We show that these financial market switching processes have features similar to those present in phase transitions. We find that the well-known catastrophic bubbles that occur on large time scales - such as the most recent financial crisis - are no outliers but in fact single dramatic representatives caused by the formation of upward and downward trends on time scales varying over nine orders of magnitude from the very large down to the very small.

Scaling analysis of bilateral hand tremor movements in essential tremor patients.

PubMed

Blesic, S; Maric, J; Dragasevic, N; Milanovic, S; Kostic, V; Ljubisavljevic, Milos

2011-08-01

Recent evidence suggests that the dynamic-scaling behavior of the time-series of signals extracted from separate peaks of tremor spectra may reveal existence of multiple independent sources of tremor. Here, we have studied dynamic characteristics of the time-series of hand tremor movements in essential tremor (ET) patients using the detrended fluctuation analysis method. Hand accelerometry was recorded with (500 g) and without weight loading under postural conditions in 25 ET patients and 20 normal subjects. The time-series comprising peak-to-peak (PtP) intervals were extracted from regions around the first three main frequency components of power spectra (PwS) of the recorded tremors. The data were compared between the load and no-load condition on dominant (related to tremor severity) and non-dominant tremor side and with the normal (physiological) oscillations in healthy subjects. Our analysis shows that, in ET, the dynamic characteristics of the main frequency component of recorded tremors exhibit scaling behavior. Furthermore, they show that the two main components of ET tremor frequency spectra, otherwise indistinguishable without load, become significantly different after inertial loading and that they differ between the tremor sides (related to tremor severity). These results show that scaling, a time-domain analysis, helps revealing tremor features previously not revealed by frequency-domain analysis and suggest that distinct oscillatory central circuits may generate the tremor in ET patients.

A longitudinal evaluation of the Center for Epidemiologic Studies-Depression scale (CES-D) in a Rheumatoid Arthritis Population using Rasch Analysis

PubMed Central

Covic, Tanya; Pallant, Julie F; Conaghan, Philip G; Tennant, Alan

2007-01-01

Background The aim of this study was to test the internal validity of the total Center for Epidemiologic Studies-Depression (CES-D) scale using Rasch analysis in a rheumatoid arthritis (RA) population. Methods CES-D was administered to 157 patients with RA over three time points within a 12 month period. Rasch analysis was applied using RUMM2020 software to assess the overall fit of the model, the response scale used, individual item fit, differential item functioning (DIF) and person separation. Results Pooled data across three time points was shown to fit the Rasch model with removal of seven items from the original 20-item CES-D scale. It was necessary to rescore the response format from four to three categories in order to improve the scale's fit. Two items demonstrated some DIF for age and gender but were retained within the 13-item CES-D scale. A new cut point for depression score of 9 was found to correspond to the original cut point score of 16 in the full CES-D scale. Conclusion This Rasch analysis of the CES-D in a longstanding RA cohort resulted in the construction of a modified 13-item scale with good internal validity. Further validation of the modified scale is recommended particularly in relation to the new cut point for depression. PMID:17629902

Exploring the Links in Monthly to Decadal Variability of the Atmospheric Water Balance Over the Wettest Regions in ERA-20C

NASA Astrophysics Data System (ADS)

Nogueira, M.

2017-10-01

Monthly-to-decadal variability of the regional precipitation over Intertropical Convergence Zone and north-Atlantic and north-Pacific storm tracks was investigated using ERA-20C reanalysis. Satellite-based precipitation (P) and evaporation (E) climatological patterns were well reproduced by ERA-20C. Regional P and E monthly time series displayed 20% differences, but these decreased rapidly with time scale ( 10% at yearly time scales). Spectral analysis showed good scale-by-scale statistical agreement between ERA-20C and observations. Using ERA-Interim showed no improvement despite the much wider range of information assimilated (including satellites). Remarkably high Detrended Cross-Correlation Analysis coefficients (ρDCCA > 0.7 and often ρDCCA > 0.9) revealed tight links between the nonperiodic variability of P, moisture divergence (DIV), and pressure velocity (ω) at monthly-to-decadal time scales over all the wet regions. In contrast, ρDCCA was essentially nonsignificant between nonperiodic P and E or sea surface temperature (SST). Thus, the nonperiodic monthly-to-decadal variability of precipitation in these regions is almost fully controlled by dynamics and not by local E or SST (suggested by Clausius-Clapeyron relation). Analysis of regional nonperiodic standard deviations and power spectra (and respective spectral exponents, β) provided further robustness to this conclusion. Finally, clear transitions in β for P, DIV, and ω between tropical and storm track regions were found. The latter is dominated by transient storms, with energy accumulation at synoptic scales and β < 0.1 at monthly-to-decadal time scales, implying that variability and information creation decrease rapidly with time scale. Larger β values (0.2 to 0.4) were found in the tropics, implying longer-range autocorrelations and slower decreasing variability and information creation with time scale, consistent with the important forcing from internal modes of variability (e.g., El Niño-Southern Oscillation).

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.

A novel way to detect correlations on multi-time scales, with temporal evolution and for multi-variables

NASA Astrophysics Data System (ADS)

Yuan, Naiming; Xoplaki, Elena; Zhu, Congwen; Luterbacher, Juerg

2016-06-01

In this paper, two new methods, Temporal evolution of Detrended Cross-Correlation Analysis (TDCCA) and Temporal evolution of Detrended Partial-Cross-Correlation Analysis (TDPCCA), are proposed by generalizing DCCA and DPCCA. Applying TDCCA/TDPCCA, it is possible to study correlations on multi-time scales and over different periods. To illustrate their properties, we used two climatological examples: i) Global Sea Level (GSL) versus North Atlantic Oscillation (NAO); and ii) Summer Rainfall over Yangtze River (SRYR) versus previous winter Pacific Decadal Oscillation (PDO). We find significant correlations between GSL and NAO on time scales of 60 to 140 years, but the correlations are non-significant between 1865-1875. As for SRYR and PDO, significant correlations are found on time scales of 30 to 35 years, but the correlations are more pronounced during the recent 30 years. By combining TDCCA/TDPCCA and DCCA/DPCCA, we proposed a new correlation-detection system, which compared to traditional methods, can objectively show how two time series are related (on which time scale, during which time period). These are important not only for diagnosis of complex system, but also for better designs of prediction models. Therefore, the new methods offer new opportunities for applications in natural sciences, such as ecology, economy, sociology and other research fields.

Multidimensional scaling analysis of financial time series based on modified cross-sample entropy methods

NASA Astrophysics Data System (ADS)

He, Jiayi; Shang, Pengjian; Xiong, Hui

2018-06-01

Stocks, as the concrete manifestation of financial time series with plenty of potential information, are often used in the study of financial time series. In this paper, we utilize the stock data to recognize their patterns through out the dissimilarity matrix based on modified cross-sample entropy, then three-dimensional perceptual maps of the results are provided through multidimensional scaling method. Two modified multidimensional scaling methods are proposed in this paper, that is, multidimensional scaling based on Kronecker-delta cross-sample entropy (MDS-KCSE) and multidimensional scaling based on permutation cross-sample entropy (MDS-PCSE). These two methods use Kronecker-delta based cross-sample entropy and permutation based cross-sample entropy to replace the distance or dissimilarity measurement in classical multidimensional scaling (MDS). Multidimensional scaling based on Chebyshev distance (MDSC) is employed to provide a reference for comparisons. Our analysis reveals a clear clustering both in synthetic data and 18 indices from diverse stock markets. It implies that time series generated by the same model are easier to have similar irregularity than others, and the difference in the stock index, which is caused by the country or region and the different financial policies, can reflect the irregularity in the data. In the synthetic data experiments, not only the time series generated by different models can be distinguished, the one generated under different parameters of the same model can also be detected. In the financial data experiment, the stock indices are clearly divided into five groups. Through analysis, we find that they correspond to five regions, respectively, that is, Europe, North America, South America, Asian-Pacific (with the exception of mainland China), mainland China and Russia. The results also demonstrate that MDS-KCSE and MDS-PCSE provide more effective divisions in experiments than MDSC.

Slow dynamics in protein fluctuations revealed by time-structure based independent component analysis: The case of domain motions

NASA Astrophysics Data System (ADS)

Naritomi, Yusuke; Fuchigami, Sotaro

2011-02-01

Protein dynamics on a long time scale was investigated using all-atom molecular dynamics (MD) simulation and time-structure based independent component analysis (tICA). We selected the lysine-, arginine-, ornithine-binding protein (LAO) as a target protein and focused on its domain motions in the open state. A MD simulation of the LAO in explicit water was performed for 600 ns, in which slow and large-amplitude domain motions of the LAO were observed. After extracting domain motions by rigid-body domain analysis, the tICA was applied to the obtained rigid-body trajectory, yielding slow modes of the LAO's domain motions in order of decreasing time scale. The slowest mode detected by the tICA represented not a closure motion described by a largest-amplitude mode determined by the principal component analysis but a twist motion with a time scale of tens of nanoseconds. The slow dynamics of the LAO were well described by only the slowest mode and were characterized by transitions between two basins. The results show that tICA is promising for describing and analyzing slow dynamics of proteins.

Slow dynamics in protein fluctuations revealed by time-structure based independent component analysis: the case of domain motions.

PubMed

Naritomi, Yusuke; Fuchigami, Sotaro

2011-02-14

Protein dynamics on a long time scale was investigated using all-atom molecular dynamics (MD) simulation and time-structure based independent component analysis (tICA). We selected the lysine-, arginine-, ornithine-binding protein (LAO) as a target protein and focused on its domain motions in the open state. A MD simulation of the LAO in explicit water was performed for 600 ns, in which slow and large-amplitude domain motions of the LAO were observed. After extracting domain motions by rigid-body domain analysis, the tICA was applied to the obtained rigid-body trajectory, yielding slow modes of the LAO's domain motions in order of decreasing time scale. The slowest mode detected by the tICA represented not a closure motion described by a largest-amplitude mode determined by the principal component analysis but a twist motion with a time scale of tens of nanoseconds. The slow dynamics of the LAO were well described by only the slowest mode and were characterized by transitions between two basins. The results show that tICA is promising for describing and analyzing slow dynamics of proteins.

Ultra-Long Time Dynamics of Contaminant Plume Mixing Induced by Transient Forcing Factors in Geologic Formations

NASA Astrophysics Data System (ADS)

Rajabi, F.; Battiato, I.

2016-12-01

Long term predictions of the impact of anthropogenic stressors on the environment is essential to reduce the risks associated with processes such as CO2 sequestration and nuclear waste storage in the subsurface. On the other hand, transient forcing factors (e.g. time-varying injection or pumping rate) with evolving heterogeneity of time scales spanning from days to years can influence transport phenomena at the pore scale. A comprehensive spatio-temporal prediction of reactive transport in porous media under time-dependent forcing factors for thousands of years requires the formulation of continuum scale models for time-averages. Yet, as every macroscopic model, time-averaged models can loose predictivity and accuracy when certain conditions are violated. This is true whenever lack of temporal and spatial scale separation occurs and it makes the continuum scale equation a poor assumption for the processes at the pore scale. In this work, we consider mass transport of a dissolved species undergoing a heterogeneous reaction and subject to time-varying boundary conditions in a periodic porous medium. By means of homogenization method and asymptotic expansion technique, we derive a macro-time continuum-scale equation as well as expressions for its effective properties. Our analysis demonstrates that the dynamics at the macro-scale is strongly influenced by the interplay between signal frequency at the boundary and transport processes at the pore level. In addition, we provide the conditions under which the space-time averaged equations accurately describe pore-scale processes. To validate our theoretical predictions, we consider a thin fracture with reacting walls and transient boundary conditions at the inlet. Our analysis shows a good agreement between numerical simulations and theoretical predictions. Furthermore, our numerical experiments show that mixing patterns of the contaminant plumes at the pore level strongly depend on the signal frequency.

The sensitivity of the atmospheric branch of the global water cycle to temperature fluctuations at synoptic to decadal time-scales in different satellite- and model-based products

NASA Astrophysics Data System (ADS)

Nogueira, Miguel

2018-02-01

Spectral analysis of global-mean precipitation, P, evaporation, E, precipitable water, W, and surface temperature, Ts, revealed significant variability from sub-daily to multi-decadal time-scales, superposed on high-amplitude diurnal and yearly peaks. Two distinct regimes emerged from a transition in the spectral exponents, β. The weather regime covering time-scales < 10 days with β ≥ 1; and the macroweather regime extending from a few months to a few decades with 0 <β <1. Additionally, the spectra showed a generally good statistical agreement amongst several different model- and satellite-based datasets. Detrended cross-correlation analysis (DCCA) revealed three important results which are robust across all datasets: (1) Clausius-Clapeyron (C-C) relationship is the dominant mechanism of W non-periodic variability at multi-year time-scales; (2) C-C is not the dominant control of W, P or E non-periodic variability at time-scales below about 6 months, where the weather regime is approached and other mechanisms become important; (3) C-C is not a dominant control for P or E over land throughout the entire time-scale range considered. Furthermore, it is suggested that the atmosphere and oceans start to act as a single coupled system at time-scales > 1-2 years, while at time-scales < 6 months they are not the dominant drivers of each other. For global-ocean and full-globe averages, ρDCCA showed large spread of the C-C importance for P and E variability amongst different datasets at multi-year time-scales, ranging from negligible (< 0.3) to high ( 0.6-0.8) values. Hence, state-of-the-art climate datasets have significant uncertainties in the representation of macroweather precipitation and evaporation variability and its governing mechanisms.

SRM Internal Flow Tests and Computational Fluid Dynamic Analysis. Volume 2; CFD RSRM Full-Scale Analyses

NASA Technical Reports Server (NTRS)

2001-01-01

This document presents the full-scale analyses of the CFD RSRM. The RSRM model was developed with a 20 second burn time. The following are presented as part of the full-scale analyses: (1) RSRM embedded inclusion analysis; (2) RSRM igniter nozzle design analysis; (3) Nozzle Joint 4 erosion anomaly; (4) RSRM full motor port slag accumulation analysis; (5) RSRM motor analysis of two-phase flow in the aft segment/submerged nozzle region; (6) Completion of 3-D Analysis of the hot air nozzle manifold; (7) Bates Motor distributed combustion test case; and (8) Three Dimensional Polysulfide Bump Analysis.

Statistical physics approaches to financial fluctuations

NASA Astrophysics Data System (ADS)

Wang, Fengzhong

2009-12-01

Complex systems attract many researchers from various scientific fields. Financial markets are one of these widely studied complex systems. Statistical physics, which was originally developed to study large systems, provides novel ideas and powerful methods to analyze financial markets. The study of financial fluctuations characterizes market behavior, and helps to better understand the underlying market mechanism. Our study focuses on volatility, a fundamental quantity to characterize financial fluctuations. We examine equity data of the entire U.S. stock market during 2001 and 2002. To analyze the volatility time series, we develop a new approach, called return interval analysis, which examines the time intervals between two successive volatilities exceeding a given value threshold. We find that the return interval distribution displays scaling over a wide range of thresholds. This scaling is valid for a range of time windows, from one minute up to one day. Moreover, our results are similar for commodities, interest rates, currencies, and for stocks of different countries. Further analysis shows some systematic deviations from a scaling law, which we can attribute to nonlinear correlations in the volatility time series. We also find a memory effect in return intervals for different time scales, which is related to the long-term correlations in the volatility. To further characterize the mechanism of price movement, we simulate the volatility time series using two different models, fractionally integrated generalized autoregressive conditional heteroscedasticity (FIGARCH) and fractional Brownian motion (fBm), and test these models with the return interval analysis. We find that both models can mimic time memory but only fBm shows scaling in the return interval distribution. In addition, we examine the volatility of daily opening to closing and of closing to opening. We find that each volatility distribution has a power law tail. Using the detrended fluctuation analysis (DFA) method, we show long-term auto-correlations in these volatility time series. We also analyze return, the actual price changes of stocks, and find that the returns over the two sessions are often anti-correlated.

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales.

PubMed

Rueckl, Martin; Lenzi, Stephen C; Moreno-Velasquez, Laura; Parthier, Daniel; Schmitz, Dietmar; Ruediger, Sten; Johenning, Friedrich W

2017-01-01

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca 2+ -imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca 2+ imaging datasets, particularly when these have been acquired at different spatial scales.

SamuROI, a Python-Based Software Tool for Visualization and Analysis of Dynamic Time Series Imaging at Multiple Spatial Scales

PubMed Central

Rueckl, Martin; Lenzi, Stephen C.; Moreno-Velasquez, Laura; Parthier, Daniel; Schmitz, Dietmar; Ruediger, Sten; Johenning, Friedrich W.

2017-01-01

The measurement of activity in vivo and in vitro has shifted from electrical to optical methods. While the indicators for imaging activity have improved significantly over the last decade, tools for analysing optical data have not kept pace. Most available analysis tools are limited in their flexibility and applicability to datasets obtained at different spatial scales. Here, we present SamuROI (Structured analysis of multiple user-defined ROIs), an open source Python-based analysis environment for imaging data. SamuROI simplifies exploratory analysis and visualization of image series of fluorescence changes in complex structures over time and is readily applicable at different spatial scales. In this paper, we show the utility of SamuROI in Ca2+-imaging based applications at three spatial scales: the micro-scale (i.e., sub-cellular compartments including cell bodies, dendrites and spines); the meso-scale, (i.e., whole cell and population imaging with single-cell resolution); and the macro-scale (i.e., imaging of changes in bulk fluorescence in large brain areas, without cellular resolution). The software described here provides a graphical user interface for intuitive data exploration and region of interest (ROI) management that can be used interactively within Jupyter Notebook: a publicly available interactive Python platform that allows simple integration of our software with existing tools for automated ROI generation and post-processing, as well as custom analysis pipelines. SamuROI software, source code and installation instructions are publicly available on GitHub and documentation is available online. SamuROI reduces the energy barrier for manual exploration and semi-automated analysis of spatially complex Ca2+ imaging datasets, particularly when these have been acquired at different spatial scales. PMID:28706482

Decoding the spatial signatures of multi-scale climate variability - a climate network perspective

NASA Astrophysics Data System (ADS)

Donner, R. V.; Jajcay, N.; Wiedermann, M.; Ekhtiari, N.; Palus, M.

2017-12-01

During the last years, the application of complex networks as a versatile tool for analyzing complex spatio-temporal data has gained increasing interest. Establishing this approach as a new paradigm in climatology has already provided valuable insights into key spatio-temporal climate variability patterns across scales, including novel perspectives on the dynamics of the El Nino Southern Oscillation or the emergence of extreme precipitation patterns in monsoonal regions. In this work, we report first attempts to employ network analysis for disentangling multi-scale climate variability. Specifically, we introduce the concept of scale-specific climate networks, which comprises a sequence of networks representing the statistical association structure between variations at distinct time scales. For this purpose, we consider global surface air temperature reanalysis data and subject the corresponding time series at each grid point to a complex-valued continuous wavelet transform. From this time-scale decomposition, we obtain three types of signals per grid point and scale - amplitude, phase and reconstructed signal, the statistical similarity of which is then represented by three complex networks associated with each scale. We provide a detailed analysis of the resulting connectivity patterns reflecting the spatial organization of climate variability at each chosen time-scale. Global network characteristics like transitivity or network entropy are shown to provide a new view on the (global average) relevance of different time scales in climate dynamics. Beyond expected trends originating from the increasing smoothness of fluctuations at longer scales, network-based statistics reveal different degrees of fragmentation of spatial co-variability patterns at different scales and zonal shifts among the key players of climate variability from tropically to extra-tropically dominated patterns when moving from inter-annual to decadal scales and beyond. The obtained results demonstrate the potential usefulness of systematically exploiting scale-specific climate networks, whose general patterns are in line with existing climatological knowledge, but provide vast opportunities for further quantifications at local, regional and global scales that are yet to be explored.

Automatic Real Time Ionogram Scaler with True Height Analysis - Artist

DTIC Science & Technology

1983-07-01

scaled. The corresponding autoscaled values were compared with the manual scaled h’F, h’F2, fminF, foE, foEs, h’E and hlEs. The ARTIST program...I ... , ·~ J .,\\; j~~·n! I:\\’~ .. IC HT:/\\L rritw!E I ONOGI\\AM SCALER ’:!"[’!’if T:\\!_1!: H~:IGHT ANALYSIS - ARTIST P...S. TYPE OF REPORT & PERiCO COVERED Scientific Report No. 7 AUTOMATIC REAL TIME IONOGRAM SCALER WITH TRUE HEIGHT ANALYSIS - ARTIST 6. PERFORMING O𔃾G

Analysis of DNA Sequences by an Optical Time-Integrating Correlator: Proposal

DTIC Science & Technology

1991-11-01

OF THE PROBLEM AND CURRENT TECHNOLOGY 2 3.0 TIME-INTEGRATING CORRELATOR 2 4.0 REPRESENTATIONS OF THE DNA BASES 8 5.0 DNA ANALYSIS STRATEGY 8 6.0... DNA bases where each base is represented by a 7-bits long pseudorandom sequence. 9 Figure 5: The flow of data in a DNA analysis system based on an...logarithmic scale and a linear scale. 15 x LIST OF TABLES PAGE Table 1: Short representations of the DNA bases where each base is represented by 7-bits

Inhomogeneous scaling behaviors in Malaysian foreign currency exchange rates

NASA Astrophysics Data System (ADS)

Muniandy, S. V.; Lim, S. C.; Murugan, R.

2001-12-01

In this paper, we investigate the fractal scaling behaviors of foreign currency exchange rates with respect to Malaysian currency, Ringgit Malaysia. These time series are examined piecewise before and after the currency control imposed in 1st September 1998 using the monofractal model based on fractional Brownian motion. The global Hurst exponents are determined using the R/ S analysis, the detrended fluctuation analysis and the method of second moment using the correlation coefficients. The limitation of these monofractal analyses is discussed. The usual multifractal analysis reveals that there exists a wide range of Hurst exponents in each of the time series. A new method of modelling the multifractal time series based on multifractional Brownian motion with time-varying Hurst exponents is studied.

A General Procedure to Assess the Internal Structure of a Noncognitive Measure--The Student360 Insight Program (S360) Time Management Scale. Research Report. ETS RR-11-42

ERIC Educational Resources Information Center

Ling, Guangming; Rijmen, Frank

2011-01-01

The factorial structure of the Time Management (TM) scale of the Student 360: Insight Program (S360) was evaluated based on a national sample. A general procedure with a variety of methods was introduced and implemented, including the computation of descriptive statistics, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA).…

Identifying the scale-dependent motifs in atmospheric surface layer by ordinal pattern analysis

NASA Astrophysics Data System (ADS)

Li, Qinglei; Fu, Zuntao

2018-07-01

Ramp-like structures in various atmospheric surface layer time series have been long studied, but the presence of motifs with the finer scale embedded within larger scale ramp-like structures has largely been overlooked in the reported literature. Here a novel, objective and well-adapted methodology, the ordinal pattern analysis, is adopted to study the finer-scaled motifs in atmospheric boundary-layer (ABL) time series. The studies show that the motifs represented by different ordinal patterns take clustering properties and 6 dominated motifs out of the whole 24 motifs account for about 45% of the time series under particular scales, which indicates the higher contribution of motifs with the finer scale to the series. Further studies indicate that motif statistics are similar for both stable conditions and unstable conditions at larger scales, but large discrepancies are found at smaller scales, and the frequencies of motifs "1234" and/or "4321" are a bit higher under stable conditions than unstable conditions. Under stable conditions, there are great changes for the occurrence frequencies of motifs "1234" and "4321", where the occurrence frequencies of motif "1234" decrease from nearly 24% to 4.5% with the scale factor increasing, and the occurrence frequencies of motif "4321" change nonlinearly with the scale increasing. These great differences of dominated motifs change with scale can be taken as an indicator to quantify the flow structure changes under different stability conditions, and motif entropy can be defined just by only 6 dominated motifs to quantify this time-scale independent property of the motifs. All these results suggest that the defined scale of motifs with the finer scale should be carefully taken into consideration in the interpretation of turbulence coherent structures.

Allan deviation analysis of financial return series

NASA Astrophysics Data System (ADS)

Hernández-Pérez, R.

2012-05-01

We perform a scaling analysis for the return series of different financial assets applying the Allan deviation (ADEV), which is used in the time and frequency metrology to characterize quantitatively the stability of frequency standards since it has demonstrated to be a robust quantity to analyze fluctuations of non-stationary time series for different observation intervals. The data used are opening price daily series for assets from different markets during a time span of around ten years. We found that the ADEV results for the return series at short scales resemble those expected for an uncorrelated series, consistent with the efficient market hypothesis. On the other hand, the ADEV results for absolute return series for short scales (first one or two decades) decrease following approximately a scaling relation up to a point that is different for almost each asset, after which the ADEV deviates from scaling, which suggests that the presence of clustering, long-range dependence and non-stationarity signatures in the series drive the results for large observation intervals.

Analysis of passive scalar advection in parallel shear flows: Sorting of modes at intermediate time scales

NASA Astrophysics Data System (ADS)

Camassa, Roberto; McLaughlin, Richard M.; Viotti, Claudio

2010-11-01

The time evolution of a passive scalar advected by parallel shear flows is studied for a class of rapidly varying initial data. Such situations are of practical importance in a wide range of applications from microfluidics to geophysics. In these contexts, it is well-known that the long-time evolution of the tracer concentration is governed by Taylor's asymptotic theory of dispersion. In contrast, we focus here on the evolution of the tracer at intermediate time scales. We show how intermediate regimes can be identified before Taylor's, and in particular, how the Taylor regime can be delayed indefinitely by properly manufactured initial data. A complete characterization of the sorting of these time scales and their associated spatial structures is presented. These analytical predictions are compared with highly resolved numerical simulations. Specifically, this comparison is carried out for the case of periodic variations in the streamwise direction on the short scale with envelope modulations on the long scales, and show how this structure can lead to "anomalously" diffusive transients in the evolution of the scalar onto the ultimate regime governed by Taylor dispersion. Mathematically, the occurrence of these transients can be viewed as a competition in the asymptotic dominance between large Péclet (Pe) numbers and the long/short scale aspect ratios (LVel/LTracer≡k), two independent nondimensional parameters of the problem. We provide analytical predictions of the associated time scales by a modal analysis of the eigenvalue problem arising in the separation of variables of the governing advection-diffusion equation. The anomalous time scale in the asymptotic limit of large k Pe is derived for the short scale periodic structure of the scalar's initial data, for both exactly solvable cases and in general with WKBJ analysis. In particular, the exactly solvable sawtooth flow is especially important in that it provides a short cut to the exact solution to the eigenvalue problem for the physically relevant vanishing Neumann boundary conditions in linear-shear channel flow. We show that the life of the corresponding modes at large Pe for this case is shorter than the ones arising from shear free zones in the fluid's interior. A WKBJ study of the latter modes provides a longer intermediate time evolution. This part of the analysis is technical, as the corresponding spectrum is dominated by asymptotically coalescing turning points in the limit of large Pe numbers. When large scale initial data components are present, the transient regime of the WKBJ (anomalous) modes evolves into one governed by Taylor dispersion. This is studied by a regular perturbation expansion of the spectrum in the small wavenumber regimes.

Multiscale analysis of the intensity fluctuation in a time series of dynamic speckle patterns.

PubMed

Federico, Alejandro; Kaufmann, Guillermo H

2007-04-10

We propose the application of a method based on the discrete wavelet transform to detect, identify, and measure scaling behavior in dynamic speckle. The multiscale phenomena presented by a sample and displayed by its speckle activity are analyzed by processing the time series of dynamic speckle patterns. The scaling analysis is applied to the temporal fluctuation of the speckle intensity and also to the two derived data sets generated by its magnitude and sign. The application of the method is illustrated by analyzing paint-drying processes and bruising in apples. The results are discussed taking into account the different time organizations obtained for the scaling behavior of the magnitude and the sign of the intensity fluctuation.

Characterizing the human postural control system using detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Teresa Blázquez, M.; Anguiano, Marta; de Saavedra, Fernando Arias; Lallena, Antonio M.; Carpena, Pedro

2010-01-01

Detrended fluctuation analysis is used to study the behaviour of the time series of the position of the center of pressure, output from the activity of a human postural control system. The results suggest that these trajectories present a crossover in their scaling properties from persistent (for high frequencies, short-range time scale) to anti-persistent (for low frequencies, long-range time scale) behaviours. The values of the scaling exponent found for the persistent parts of the trajectories are very similar for all the cases analysed. The similarity of the results obtained for the measurements done with both eyes open and both eyes closed indicate either that the visual system may be disregarded by the postural control system, while maintaining quiet standing, or that the control mechanisms associated with each type of information (visual, vestibular and somatosensory) cannot be disentangled with this technique.

Multiscale analysis of structure development in expanded starch snacks

NASA Astrophysics Data System (ADS)

van der Sman, R. G. M.; Broeze, J.

2014-11-01

In this paper we perform a multiscale analysis of the food structuring process of the expansion of starchy snack foods like keropok, which obtains a solid foam structure. In particular, we want to investigate the validity of the hypothesis of Kokini and coworkers, that expansion is optimal at the moisture content, where the glass transition and the boiling line intersect. In our analysis we make use of several tools, (1) time scale analysis from the field of physical transport phenomena, (2) the scale separation map (SSM) developed within a multiscale simulation framework of complex automata, (3) the supplemented state diagram (SSD), depicting phase transition and glass transition lines, and (4) a multiscale simulation model for the bubble expansion. Results of the time scale analysis are plotted in the SSD, and give insight into the dominant physical processes involved in expansion. Furthermore, the results of the time scale analysis are used to construct the SSM, which has aided us in the construction of the multiscale simulation model. Simulation results are plotted in the SSD. This clearly shows that the hypothesis of Kokini is qualitatively true, but has to be refined. Our results show that bubble expansion is optimal for moisture content, where the boiling line for gas pressure of 4 bars intersects the isoviscosity line of the critical viscosity 106 Pa.s, which runs parallel to the glass transition line.

Atmospheric Diabatic Heating in Different Weather States and the General Circulation

NASA Technical Reports Server (NTRS)

Rossow, William B.; Zhang, Yuanchong; Tselioudis, George

2016-01-01

Analysis of multiple global satellite products identifies distinctive weather states of the atmosphere from the mesoscale pattern of cloud properties and quantifies the associated diabatic heating/cooling by radiative flux divergence, precipitation, and surface sensible heat flux. The results show that the forcing for the atmospheric general circulation is a very dynamic process, varying strongly at weather space-time scales, comprising relatively infrequent, strong heating events by ''stormy'' weather and more nearly continuous, weak cooling by ''fair'' weather. Such behavior undercuts the value of analyses of time-averaged energy exchanges in observations or numerical models. It is proposed that an analysis of the joint time-related variations of the global weather states and the general circulation on weather space-time scales might be used to establish useful ''feedback like'' relationships between cloud processes and the large-scale circulation.

Scaling properties of Polish rain series

NASA Astrophysics Data System (ADS)

Licznar, P.

2009-04-01

Scaling properties as well as multifractal nature of precipitation time series have not been studied for local Polish conditions until recently due to lack of long series of high-resolution data. The first Polish study of precipitation time series scaling phenomena was made on the base of pluviograph data from the Wroclaw University of Environmental and Life Sciences meteorological station located at the south-western part of the country. The 38 annual rainfall records from years 1962-2004 were converted into digital format and transformed into a standard format of 5-minute time series. The scaling properties and multifractal character of this material were studied by means of several different techniques: power spectral density analysis, functional box-counting, probability distribution/multiple scaling and trace moment methods. The result proved the general scaling character of time series at the range of time scales ranging form 5 minutes up to at least 24 hours. At the same time some characteristic breaks at scaling behavior were recognized. It is believed that the breaks were artificial and arising from the pluviograph rain gauge measuring precision limitations. Especially strong limitations at the precision of low-intensity precipitations recording by pluviograph rain gauge were found to be the main reason for artificial break at energy spectra, as was reported by other authors before. The analysis of co-dimension and moments scaling functions showed the signs of the first-order multifractal phase transition. Such behavior is typical for dressed multifractal processes that are observed by spatial or temporal averaging on scales larger than the inner-scale of those processes. The fractal dimension of rainfall process support derived from codimension and moments scaling functions geometry analysis was found to be 0.45. The same fractal dimension estimated by means of the functional box-counting method was equal to 0.58. At the final part of the study implementation of double trace moment method allowed for estimation of local universal multifractal rainfall parameters (α=0.69; C1=0.34; H=-0.01). The research proved the fractal character of rainfall process support and multifractal character of the rainfall intensity values variability among analyzed time series. It is believed that scaling of local Wroclaw's rainfalls for timescales at the range from 24 hours up to 5 minutes opens the door for future research concerning for example random cascades implementation for daily precipitation totals disaggregation for smaller time intervals. The results of such a random cascades functioning in a form of 5 minute artificial rainfall scenarios could be of great practical usability for needs of urban hydrology, and design and hydrodynamic modeling of storm water and combined sewage conveyance systems.

Prediction of Time Response of Electrowetting

NASA Astrophysics Data System (ADS)

Lee, Seung Jun; Hong, Jiwoo; Kang, Kwan Hyoung

2009-11-01

It is very important to predict the time response of electrowetting-based devices, such as liquid lenses, reflective displays, and optical switches. We investigated the time response of electrowetting, based on an analytical and a numerical method, to find out characteristic scales and a scaling law for the switching time. For this, spreading process of a sessile droplet was analyzed based on the domain perturbation method. First, we considered the case of weakly viscous fluids. The analytical result for the spreading process was compared with experimental results, which showed very good agreement in overall time response. It was shown that the overall dynamics is governed by P2 shape mode. We derived characteristic scales combining the droplet volume, density, and surface tension. The overall dynamic process was scaled quite well by the scales. A scaling law was derived from the analytical solution and was verified experimentally. We also suggest a scaling law for highly viscous liquids, based on results of numerical analysis for the electrowetting-actuated spreading process.

The multiple time scales of sleep dynamics as a challenge for modelling the sleeping brain.

PubMed

Olbrich, Eckehard; Claussen, Jens Christian; Achermann, Peter

2011-10-13

A particular property of the sleeping brain is that it exhibits dynamics on very different time scales ranging from the typical sleep oscillations such as sleep spindles and slow waves that can be observed in electroencephalogram (EEG) segments of several seconds duration over the transitions between the different sleep stages on a time scale of minutes to the dynamical processes involved in sleep regulation with typical time constants in the range of hours. There is an increasing body of work on mathematical and computational models addressing these different dynamics, however, usually considering only processes on a single time scale. In this paper, we review and present a new analysis of the dynamics of human sleep EEG at the different time scales and relate the findings to recent modelling efforts pointing out both the achievements and remaining challenges.

Multiscale entropy analysis of heart rate variability in heart failure, hypertensive, and sinoaortic-denervated rats: classical and refined approaches.

PubMed

Silva, Luiz Eduardo Virgilio; Lataro, Renata Maria; Castania, Jaci Airton; da Silva, Carlos Alberto Aguiar; Valencia, Jose Fernando; Murta, Luiz Otavio; Salgado, Helio Cesar; Fazan, Rubens; Porta, Alberto

2016-07-01

The analysis of heart rate variability (HRV) by nonlinear methods has been gaining increasing interest due to their ability to quantify the complexity of cardiovascular regulation. In this study, multiscale entropy (MSE) and refined MSE (RMSE) were applied to track the complexity of HRV as a function of time scale in three pathological conscious animal models: rats with heart failure (HF), spontaneously hypertensive rats (SHR), and rats with sinoaortic denervation (SAD). Results showed that HF did not change HRV complexity, although there was a tendency to decrease the entropy in HF animals. On the other hand, SHR group was characterized by reduced complexity at long time scales, whereas SAD animals exhibited a smaller short- and long-term irregularity. We propose that short time scales (1 to 4), accounting for fast oscillations, are more related to vagal and respiratory control, whereas long time scales (5 to 20), accounting for slow oscillations, are more related to sympathetic control. The increased sympathetic modulation is probably the main reason for the lower entropy observed at high scales for both SHR and SAD groups, acting as a negative factor for the cardiovascular complexity. This study highlights the contribution of the multiscale complexity analysis of HRV for understanding the physiological mechanisms involved in cardiovascular regulation. Copyright © 2016 the American Physiological Society.

Time-Frequency Analysis of Beach Bacteria Variations and its Implication for Recreational Water Quality Modeling

EPA Science Inventory

This paper explores the potential of time-frequency wavelet analysis in resolving beach bacteria concentration and possible explanatory variables across multiple time scales with temporal information still preserved. The wavelet scalograms of E. coli concentrations and the explan...

Rotational relaxation time as unifying time scale for polymer and fiber drag reduction

NASA Astrophysics Data System (ADS)

Boelens, A. M. P.; Muthukumar, M.

2016-05-01

Using hybrid direct numerical simulation plus Langevin dynamics, a comparison is performed between polymer and fiber stress tensors in turbulent flow. The stress tensors are found to be similar, suggesting a common drag reducing mechanism in the onset regime for both flexible polymers and rigid fibers. Since fibers do not have an elastic backbone, this must be a viscous effect. Analysis of the viscosity tensor reveals that all terms are negligible, except the off-diagonal shear viscosity associated with rotation. Based on this analysis, we identify the rotational orientation time as the unifying time scale setting a new time criterion for drag reduction by both flexible polymers and rigid fibers.

Rotational relaxation time as unifying time scale for polymer and fiber drag reduction.

PubMed

Boelens, A M P; Muthukumar, M

2016-05-01

Using hybrid direct numerical simulation plus Langevin dynamics, a comparison is performed between polymer and fiber stress tensors in turbulent flow. The stress tensors are found to be similar, suggesting a common drag reducing mechanism in the onset regime for both flexible polymers and rigid fibers. Since fibers do not have an elastic backbone, this must be a viscous effect. Analysis of the viscosity tensor reveals that all terms are negligible, except the off-diagonal shear viscosity associated with rotation. Based on this analysis, we identify the rotational orientation time as the unifying time scale setting a new time criterion for drag reduction by both flexible polymers and rigid fibers.

Statistical analysis of hydrological response in urbanising catchments based on adaptive sampling using inter-amount times

NASA Astrophysics Data System (ADS)

ten Veldhuis, Marie-Claire; Schleiss, Marc

2017-04-01

In this study, we introduced an alternative approach for analysis of hydrological flow time series, using an adaptive sampling framework based on inter-amount times (IATs). The main difference with conventional flow time series is the rate at which low and high flows are sampled: the unit of analysis for IATs is a fixed flow amount, instead of a fixed time window. We analysed statistical distributions of flows and IATs across a wide range of sampling scales to investigate sensitivity of statistical properties such as quantiles, variance, skewness, scaling parameters and flashiness indicators to the sampling scale. We did this based on streamflow time series for 17 (semi)urbanised basins in North Carolina, US, ranging from 13 km2 to 238 km2 in size. Results showed that adaptive sampling of flow time series based on inter-amounts leads to a more balanced representation of low flow and peak flow values in the statistical distribution. While conventional sampling gives a lot of weight to low flows, as these are most ubiquitous in flow time series, IAT sampling gives relatively more weight to high flow values, when given flow amounts are accumulated in shorter time. As a consequence, IAT sampling gives more information about the tail of the distribution associated with high flows, while conventional sampling gives relatively more information about low flow periods. We will present results of statistical analyses across a range of subdaily to seasonal scales and will highlight some interesting insights that can be derived from IAT statistics with respect to basin flashiness and impact urbanisation on hydrological response.

Spectral analysis of temporal non-stationary rainfall-runoff processes

NASA Astrophysics Data System (ADS)

Chang, Ching-Min; Yeh, Hund-Der

2018-04-01

This study treats the catchment as a block box system with considering the rainfall input and runoff output being a stochastic process. The temporal rainfall-runoff relationship at the catchment scale is described by a convolution integral on a continuous time scale. Using the Fourier-Stieltjes representation approach, a frequency domain solution to the convolution integral is developed to the spectral analysis of runoff processes generated by temporal non-stationary rainfall events. It is shown that the characteristic time scale of rainfall process increases the runoff discharge variability, while the catchment mean travel time constant plays the role in reducing the variability of runoff discharge. Similar to the behavior of groundwater aquifers, catchments act as a low-pass filter in the frequency domain for the rainfall input signal.

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.

A propagating freshwater mode in the Arctic Ocean with multidecadal time scale

NASA Astrophysics Data System (ADS)

Schmith, Torben; Malskær Olsen, Steffen; Margrethe Ringgaard, Ida

2017-04-01

We apply Principal Oscillatory Pattern analysis to the Arctic Ocean fresh water content as simulated in a 500 year long control run with constant preindustrial forcing with the EC-Earth global climate model. Two modes emerge from this analysis. One mode is a standing mode with decadal time scale describing accumulation and release of fresh water in the Beaufort Gyre, known in the literature as the Beaufort Gyre flywheel. In addition, we identify a propagating mode with a time scale around 80 years, propagating along the rim of the Canadian Basin. This mode has maximum variability of the fresh water content in the Transpolar Drift and represents the bulk of the total variability of the fresh water content in the Arctic Ocean and also projects on the fresh water through the Fram Strait. Therefore, potentially, it can introduce a multidecadal variability to the Atlantic meridional overturning circulation. We will discuss the physical origin of this propagating mode. This include planetary-scale internal Rossby waves with multidecadal time scale, due to the slow variation of the Coriolis parameter at these high latitudes, as well as topographic steering of these Rossby waves.

Scaling behavior of online human activity

NASA Astrophysics Data System (ADS)

Zhao, Zhi-Dan; Cai, Shi-Min; Huang, Junming; Fu, Yan; Zhou, Tao

2012-11-01

The rapid development of the Internet technology enables humans to explore the web and record the traces of online activities. From the analysis of these large-scale data sets (i.e., traces), we can get insights about the dynamic behavior of human activity. In this letter, the scaling behavior and complexity of human activity in the e-commerce, such as music, books, and movies rating, are comprehensively investigated by using the detrended fluctuation analysis technique and the multiscale entropy method. Firstly, the interevent time series of rating behaviors of these three types of media show similar scaling properties with exponents ranging from 0.53 to 0.58, which implies that the collective behaviors of rating media follow a process embodying self-similarity and long-range correlation. Meanwhile, by dividing the users into three groups based on their activities (i.e., rating per unit time), we find that the scaling exponents of the interevent time series in the three groups are different. Hence, these results suggest that a stronger long-range correlations exist in these collective behaviors. Furthermore, their information complexities vary in the three groups. To explain the differences of the collective behaviors restricted to the three groups, we study the dynamic behavior of human activity at the individual level, and find that the dynamic behaviors of a few users have extremely small scaling exponents associated with long-range anticorrelations. By comparing the interevent time distributions of four representative users, we can find that the bimodal distributions may bring forth the extraordinary scaling behaviors. These results of the analysis of the online human activity in the e-commerce may not only provide insight into its dynamic behaviors but may also be applied to acquire potential economic interest.

Minimum entropy density method for the time series analysis

NASA Astrophysics Data System (ADS)

Lee, Jeong Won; Park, Joongwoo Brian; Jo, Hang-Hyun; Yang, Jae-Suk; Moon, Hie-Tae

2009-01-01

The entropy density is an intuitive and powerful concept to study the complicated nonlinear processes derived from physical systems. We develop the minimum entropy density method (MEDM) to detect the structure scale of a given time series, which is defined as the scale in which the uncertainty is minimized, hence the pattern is revealed most. The MEDM is applied to the financial time series of Standard and Poor’s 500 index from February 1983 to April 2006. Then the temporal behavior of structure scale is obtained and analyzed in relation to the information delivery time and efficient market hypothesis.

Cycles, scaling and crossover phenomenon in length of the day (LOD) time series

NASA Astrophysics Data System (ADS)

Telesca, Luciano

2007-06-01

The dynamics of the temporal fluctuations of the length of the day (LOD) time series from January 1, 1962 to November 2, 2006 were investigated. The power spectrum of the whole time series has revealed annual, semi-annual, decadal and daily oscillatory behaviors, correlated with oceanic-atmospheric processes and interactions. The scaling behavior was analyzed by using the detrended fluctuation analysis (DFA), which has revealed two different scaling regimes, separated by a crossover timescale at approximately 23 days. Flicker-noise process can describe the dynamics of the LOD time regime involving intermediate and long timescales, while Brownian dynamics characterizes the LOD time series for small timescales.

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.

Most suitable mother wavelet for the analysis of fractal properties of stride interval time series via the average wavelet coefficient

PubMed Central

Zhang, Zhenwei; VanSwearingen, Jessie; Brach, Jennifer S.; Perera, Subashan

2016-01-01

Human gait is a complex interaction of many nonlinear systems and stride intervals exhibit self-similarity over long time scales that can be modeled as a fractal process. The scaling exponent represents the fractal degree and can be interpreted as a biomarker of relative diseases. The previous study showed that the average wavelet method provides the most accurate results to estimate this scaling exponent when applied to stride interval time series. The purpose of this paper is to determine the most suitable mother wavelet for the average wavelet method. This paper presents a comparative numerical analysis of sixteen mother wavelets using simulated and real fractal signals. Simulated fractal signals were generated under varying signal lengths and scaling exponents that indicate a range of physiologically conceivable fractal signals. The five candidates were chosen due to their good performance on the mean square error test for both short and long signals. Next, we comparatively analyzed these five mother wavelets for physiologically relevant stride time series lengths. Our analysis showed that the symlet 2 mother wavelet provides a low mean square error and low variance for long time intervals and relatively low errors for short signal lengths. It can be considered as the most suitable mother function without the burden of considering the signal length. PMID:27960102

The TRMM Multi-Satellite Precipitation Analysis (TMPA)

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Bolvin, David T.; Nelkin, Eric J.

2008-01-01

The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) is intended to provide a "best" estimate of quasi-global precipitation from the wide variety of modern satellite-borne precipitation-related sensors. Estimates are provided at relatively fine scales (0.25degx0.25deg, 3-hourly) in both real and post-real time to accommodate a wide range of researchers. However, the errors inherent in the finest scale estimates are large. The most successful use of the TMPA data is when the analysis takes advantage of the fine-scale data to create time/space averages appropriate to the user s application. We review the conceptual basis for the TMPA, summarize the processing sequence, and focus on two new activities. First, a recent upgrade to the real-time version incorporates several additional satellite data sources and employs monthly climatological adjustments to approximate the bias characteristics of the research quality post-real-time product. Second, an upgrade of the research quality post-real-time TMPA from Version 6 to Version 7 (in beta test at press time) is designed to provide a variety of improvements that increase the list of input data sets and correct several issues. Future enhancements for the TMPA will include improved error estimation, extension to higher latitudes, and a shift to a Lagrangian time interpolation scheme.

The TRMM Multi-Satellite Precipitation Analysis (TMPA)

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Bolvin, David T.; Nelkin, Eric J.

2010-01-01

The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) is intended to provide a "best" estimate of quasi-global precipitation from the wide variety of modern satellite-borne precipitation-related sensors. Estimates are provided at relatively fine scales (0.25 deg x 0.25 deg. 3-h) in both real and post-real time to accommodate a wide range of researchers. However, the errors inherent in the finest scale estimates are large. The most successful use of the TMPA data is when the analysis takes advantage of the fine-scale data to create time/space averages appropriate to the user fs application. We review the conceptual basis for the TMPA, summarize the processing sequence, and focus on two new activities. First, a recent upgrade for the real-time version incorporates several additional satellite data sources and employs monthly climatological adjustments to approximate the bias characteristics of the research quality post-real-time product. Second, an upgrade for the research quality post-real-time TMPA from Versions 6 to 7 (in beta test at press time) is designed to provide a variety of improvements that increase the list of input data sets and correct several issues. Future enhancements for the TMPA will include improved error estimation, extension to higher latitudes, and a shift to a Lagrangian time interpolation scheme.

The Relationship of Dynamical Heterogeneity to the Adam-Gibbs and Random First-Order Transition Theories of Glass Formation

NASA Astrophysics Data System (ADS)

Starr, Francis; Douglas, Jack; Sastry, Srikanth

2013-03-01

We examine measures of dynamical heterogeneity for a bead-spring polymer melt and test how these scales compare with the scales hypothesized by the Adam and Gibbs (AG) and random first-order transition (RFOT) theories. We show that the time scale of the high-mobility clusters and strings is associated with a diffusive time scale, while the low-mobility particles' time scale relates to a structural relaxation time. The difference of the characteristic times naturally explains the decoupling of diffusion and structural relaxation time scales. We examine the appropriateness of identifying the size scales of mobile particle clusters or strings with the size of cooperatively rearranging regions (CRR) in the AG and RFOT theories. We find that the string size appears to be the most consistent measure of CRR for both the AG and RFOT models. Identifying strings or clusters with the``mosaic'' length of the RFOT model relaxes the conventional assumption that the``entropic droplet'' are compact. We also confirm the validity of the entropy formulation of the AG theory, constraining the exponent values of the RFOT theory. This constraint, together with the analysis of size scales, enables us to estimate the characteristic exponents of RFOT.

High-resolution time-frequency representation of EEG data using multi-scale wavelets

NASA Astrophysics Data System (ADS)

Li, Yang; Cui, Wei-Gang; Luo, Mei-Lin; Li, Ke; Wang, Lina

2017-09-01

An efficient time-varying autoregressive (TVAR) modelling scheme that expands the time-varying parameters onto the multi-scale wavelet basis functions is presented for modelling nonstationary signals and with applications to time-frequency analysis (TFA) of electroencephalogram (EEG) signals. In the new parametric modelling framework, the time-dependent parameters of the TVAR model are locally represented by using a novel multi-scale wavelet decomposition scheme, which can allow the capability to capture the smooth trends as well as track the abrupt changes of time-varying parameters simultaneously. A forward orthogonal least square (FOLS) algorithm aided by mutual information criteria are then applied for sparse model term selection and parameter estimation. Two simulation examples illustrate that the performance of the proposed multi-scale wavelet basis functions outperforms the only single-scale wavelet basis functions or Kalman filter algorithm for many nonstationary processes. Furthermore, an application of the proposed method to a real EEG signal demonstrates the new approach can provide highly time-dependent spectral resolution capability.

Multiple time scale analysis of pressure oscillations in solid rocket motors

NASA Astrophysics Data System (ADS)

Ahmed, Waqas; Maqsood, Adnan; Riaz, Rizwan

2018-03-01

In this study, acoustic pressure oscillations for single and coupled longitudinal acoustic modes in Solid Rocket Motor (SRM) are investigated using Multiple Time Scales (MTS) method. Two independent time scales are introduced. The oscillations occur on fast time scale whereas the amplitude and phase changes on slow time scale. Hopf bifurcation is employed to investigate the properties of the solution. The supercritical bifurcation phenomenon is observed for linearly unstable system. The amplitude of the oscillations result from equal energy gain and loss rates of longitudinal acoustic modes. The effect of linear instability and frequency of longitudinal modes on amplitude and phase of oscillations are determined for both single and coupled modes. For both cases, the maximum amplitude of oscillations decreases with the frequency of acoustic mode and linear instability of SRM. The comparison of analytical MTS results and numerical simulations demonstrate an excellent agreement.

Analysis of Thermal and Reaction Times for Hydrogen Reduction of Lunar Regolith

NASA Technical Reports Server (NTRS)

Hegde, U.; Balasubramaniam, R.; Gokoglu, S.

2008-01-01

System analysis of oxygen production by hydrogen reduction of lunar regolith has shown the importance of the relative time scales for regolith heating and chemical reaction to overall performance. These values determine the sizing and power requirements of the system and also impact the number and operational phasing of reaction chambers. In this paper, a Nusselt number correlation analysis is performed to determine the heat transfer rates and regolith heat up times in a fluidized bed reactor heated by a central heating element (e.g., a resistively heated rod, or a solar concentrator heat pipe). A coupled chemical and transport model has also been developed for the chemical reduction of regolith by a continuous flow of hydrogen. The regolith conversion occurs on the surfaces of and within the regolith particles. Several important quantities are identified as a result of the above analyses. Reactor scale parameters include the void fraction (i.e., the fraction of the reactor volume not occupied by the regolith particles) and the residence time of hydrogen in the reactor. Particle scale quantities include the particle Reynolds number, the Archimedes number, and the time needed for hydrogen to diffuse into the pores of the regolith particles. The analysis is used to determine the heat up and reaction times and its application to NASA s oxygen production system modeling tool is noted.

Analysis of Thermal and Reaction Times for Hydrogen Reduction of Lunar Regolith

NASA Technical Reports Server (NTRS)

Hegde, U.; Balasubramaniam, R.; Gokoglu, S.

2009-01-01

System analysis of oxygen production by hydrogen reduction of lunar regolith has shown the importance of the relative time scales for regolith heating and chemical reaction to overall performance. These values determine the sizing and power requirements of the system and also impact the number and operational phasing of reaction chambers. In this paper, a Nusselt number correlation analysis is performed to determine the heat transfer rates and regolith heat up times in a fluidized bed reactor heated by a central heating element (e.g., a resistively heated rod, or a solar concentrator heat pipe). A coupled chemical and transport model has also been developed for the chemical reduction of regolith by a continuous flow of hydrogen. The regolith conversion occurs on the surfaces of and within the regolith particles. Several important quantities are identified as a result of the above analyses. Reactor scale parameters include the void fraction (i.e., the fraction of the reactor volume not occupied by the regolith particles) and the residence time of hydrogen in the reactor. Particle scale quantities include the particle Reynolds number, the Archimedes number, and the time needed for hydrogen to diffuse into the pores of the regolith particles. The analysis is used to determine the heat up and reaction times and its application to NASA s oxygen production system modeling tool is noted.

Revisiting the investor sentiment-stock returns relationship: A multi-scale perspective using wavelets

NASA Astrophysics Data System (ADS)

Lao, Jiashun; Nie, He; Jiang, Yonghong

2018-06-01

This paper employs SBW proposed by Baker and Wurgler (2006) to investigate the nonlinear asymmetric Granger causality between investor sentiment and stock returns for US economy while considering different time-scales. The wavelet method is utilized to decompose time series of investor sentiment and stock returns at different time-scales to focus on the local analysis of different time horizons of investors. The linear and nonlinear asymmetric Granger methods are employed to examine the Granger causal relationship on similar time-scales. We find evidence of strong bilateral linear and nonlinear asymmetric Granger causality between longer-term investor sentiment and stock returns. Furthermore, we observe the positive nonlinear causal relationship from stock returns to investor sentiment and the negative nonlinear causal relationship from investor sentiment to stock returns.

Kepler light-curve analysis of the blazar W2R 1926+42

NASA Astrophysics Data System (ADS)

Mohan, P.; Gupta, Alok C.; Bachev, Rumen; Strigachev, Anton

2016-02-01

We study the long term Kepler light curve of the blazar W2R 1926+42 (˜1.6 yr) which indicates a variety of variability properties during different intervals of observation. The normalized excess variance, Fvar ranges from 1.8 per cent in the quiescent phase and 43.3 per cent in the outburst phase. We find no significant deviation from linearity in the Fvar-flux relation. Time series analysis is conducted using the Fourier power spectrum and the wavelet analysis methods to study the power spectral density (PSD) shape, infer characteristic time-scales and statistically significant quasi-periodic oscillations (QPOs). A bending power law with an associated time-scale of T_B = 6.2^{+6.4}_{-3.1} hours is inferred in the PSD analysis. We obtain a black hole mass of M• = (1.5-5.9) × 107 M⊙ for the first time using Fvar and the bend time-scale for this source. From a mean outburst lifetime of days, we infer a distance from the jet base r ≤ 1.75 pc indicating that the outburst originates due to a shock. A possible QPO peaked at 9.1 d and lasting 3.4 cycles is inferred from the wavelet analysis. Assuming that the QPO is a true feature, r = (152-378)GM•/c2 and supported by the other timing analysis products such as a weighted mean PSD slope of -1.5 ± 0.2 from the PSD analysis, we argue that the observed variability and the weak and short duration QPO could be due to jet based processes including orbital features in a relativistic helical jet and others such as shocks and turbulence.

Real-time fMRI processing with physiological noise correction - Comparison with off-line analysis.

PubMed

Misaki, Masaya; Barzigar, Nafise; Zotev, Vadim; Phillips, Raquel; Cheng, Samuel; Bodurka, Jerzy

2015-12-30

While applications of real-time functional magnetic resonance imaging (rtfMRI) are growing rapidly, there are still limitations in real-time data processing compared to off-line analysis. We developed a proof-of-concept real-time fMRI processing (rtfMRIp) system utilizing a personal computer (PC) with a dedicated graphic processing unit (GPU) to demonstrate that it is now possible to perform intensive whole-brain fMRI data processing in real-time. The rtfMRIp performs slice-timing correction, motion correction, spatial smoothing, signal scaling, and general linear model (GLM) analysis with multiple noise regressors including physiological noise modeled with cardiac (RETROICOR) and respiration volume per time (RVT). The whole-brain data analysis with more than 100,000voxels and more than 250volumes is completed in less than 300ms, much faster than the time required to acquire the fMRI volume. Real-time processing implementation cannot be identical to off-line analysis when time-course information is used, such as in slice-timing correction, signal scaling, and GLM. We verified that reduced slice-timing correction for real-time analysis had comparable output with off-line analysis. The real-time GLM analysis, however, showed over-fitting when the number of sampled volumes was small. Our system implemented real-time RETROICOR and RVT physiological noise corrections for the first time and it is capable of processing these steps on all available data at a given time, without need for recursive algorithms. Comprehensive data processing in rtfMRI is possible with a PC, while the number of samples should be considered in real-time GLM. Copyright © 2015 Elsevier B.V. All rights reserved.

Multi-time scale analysis of the spatial representativeness of in situ soil moisture data within satellite footprints

USDA-ARS?s Scientific Manuscript database

We conduct a novel comprehensive investigation that seeks to prove the connection between spatial and time scales in surface soil moisture (SM) within the satellite footprint (~50 km). Modeled and measured point series at Yanco and Little Washita in situ networks are first decomposed into anomalies ...

Structure of Student Time Management Scale (STMS)

ERIC Educational Resources Information Center

Balamurugan, M.

2013-01-01

With the aim of constructing a Student Time Management Scale (STMS), the initial version was administered and data were collected from 523 standard eleventh students. (Mean age = 15.64). The data obtained were subjected to Reliability and Factor analysis using PASW Statistical software version 18. From 42 items 14 were dropped, resulting in the…

Falcon: Visual analysis of large, irregularly sampled, and multivariate time series data in additive manufacturing

DOE PAGES

Steed, Chad A.; Halsey, William; Dehoff, Ryan; ...

2017-02-16

Flexible visual analysis of long, high-resolution, and irregularly sampled time series data from multiple sensor streams is a challenge in several domains. In the field of additive manufacturing, this capability is critical for realizing the full potential of large-scale 3D printers. Here, we propose a visual analytics approach that helps additive manufacturing researchers acquire a deep understanding of patterns in log and imagery data collected by 3D printers. Our specific goals include discovering patterns related to defects and system performance issues, optimizing build configurations to avoid defects, and increasing production efficiency. We introduce Falcon, a new visual analytics system thatmore » allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations, all with adjustable scale options. To illustrate the effectiveness of Falcon at providing thorough and efficient knowledge discovery, we present a practical case study involving experts in additive manufacturing and data from a large-scale 3D printer. The techniques described are applicable to the analysis of any quantitative time series, though the focus of this paper is on additive manufacturing.« less

Falcon: Visual analysis of large, irregularly sampled, and multivariate time series data in additive manufacturing

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

Steed, Chad A.; Halsey, William; Dehoff, Ryan

Flexible visual analysis of long, high-resolution, and irregularly sampled time series data from multiple sensor streams is a challenge in several domains. In the field of additive manufacturing, this capability is critical for realizing the full potential of large-scale 3D printers. Here, we propose a visual analytics approach that helps additive manufacturing researchers acquire a deep understanding of patterns in log and imagery data collected by 3D printers. Our specific goals include discovering patterns related to defects and system performance issues, optimizing build configurations to avoid defects, and increasing production efficiency. We introduce Falcon, a new visual analytics system thatmore » allows users to interactively explore large, time-oriented data sets from multiple linked perspectives. Falcon provides overviews, detailed views, and unique segmented time series visualizations, all with adjustable scale options. To illustrate the effectiveness of Falcon at providing thorough and efficient knowledge discovery, we present a practical case study involving experts in additive manufacturing and data from a large-scale 3D printer. The techniques described are applicable to the analysis of any quantitative time series, though the focus of this paper is on additive manufacturing.« less

The study on the parallel processing based time series correlation analysis of RBC membrane flickering in quantitative phase imaging

NASA Astrophysics Data System (ADS)

Lee, Minsuk; Won, Youngjae; Park, Byungjun; Lee, Seungrag

2017-02-01

Not only static characteristics but also dynamic characteristics of the red blood cell (RBC) contains useful information for the blood diagnosis. Quantitative phase imaging (QPI) can capture sample images with subnanometer scale depth resolution and millisecond scale temporal resolution. Various researches have been used QPI for the RBC diagnosis, and recently many researches has been developed to decrease the process time of RBC information extraction using QPI by the parallel computing algorithm, however previous studies are interested in the static parameters such as morphology of the cells or simple dynamic parameters such as root mean square (RMS) of the membrane fluctuations. Previously, we presented a practical blood test method using the time series correlation analysis of RBC membrane flickering with QPI. However, this method has shown that there is a limit to the clinical application because of the long computation time. In this study, we present an accelerated time series correlation analysis of RBC membrane flickering using the parallel computing algorithm. This method showed consistent fractal scaling exponent results of the surrounding medium and the normal RBC with our previous research.

An Analysis of Moisture Fluxes into the Gulf of California

NASA Technical Reports Server (NTRS)

Wu, Man-Li C.; Schubert, Siegfried D.; Suarez, Max J.; Huang, Norden E.

2009-01-01

This study examines the nature of episodes of enhanced warm-season moisture flux into the Gulf of California. Both spatial structure and primary time scales of the fluxes are examined using the 40-yr ECMWF Re-Analysis data for the period 1980-2001. The analysis approach consists of a compositing technique that is keyed on the low-level moisture fluxes into the Gulf of California. The results show that the fluxes have a rich spectrum of temporal variability, with periods of enhanced transport over the gulf linked to African easterly waves on subweekly (3-8 day) time scales, the Madden-Julian oscillation (MJO) at intraseasonal time scales (20-90 day), and intermediate (10-15 day) time-scale disturbances that appear to originate primarily in the Caribbean Sea-western Atlantic Ocean. In the case of the MJO, enhanced low-level westerlies and large-scale rising motion provide an environment that favors large-scale cyclonic development near the west coast of Central America that, over the course of about 2 weeks, expands northward along the coast eventually reaching the mouth of the Gulf of California where it acts to enhance the southerly moisture flux in that region. On a larger scale, the development includes a northward shift in the eastern Pacific ITCZ, enhanced precipitation over much of Mexico and the southwestern United States, and enhanced southerly/southeasterly fluxes from the Gulf of Mexico into Mexico and the southwestern and central United States. In the case of the easterly waves, the systems that reach Mexico appear to redevelop/reorganize on the Pacific coast and then move rapidly to the northwest to contribute to the moisture flux into the Gulf of California. The most intense fluxes into the gulf on these time scales appear to be synchronized with a midlatitude short-wave trough over the U.S. West Coast and enhanced low-level southerly fluxes over the U.S. Great Plains. The intermediate (10-15 day) time-scale systems have zonal wavelengths roughly twice that of the easterly waves, and their initiation appears to be linked to an extratropical U.S. East Coast ridge and associated northeasterly winds that extend well into the Caribbean Sea during their development phase. The short (3-8 day) and, to a lesser extent, the intermediate (10-15 day) time-scale fluxes tend to be enhanced when the convectively active phase of the MJO is situated over the Americas.

Scaling and design analyses of a scaled-down, high-temperature test facility for experimental investigation of the initial stages of a VHTR air-ingress accident

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

Arcilesi, David J.; Ham, Tae Kyu; Kim, In Hun

2015-07-01

A critical event in the safety analysis of the very high-temperature gas-cooled reactor (VHTR) is an air-ingress accident. This accident is initiated, in its worst case scenario, by a double-ended guillotine break of the coaxial cross vessel, which leads to a rapid reactor vessel depressurization. In a VHTR, the reactor vessel is located within a reactor cavity that is filled with air during normal operating conditions. Following the vessel depressurization, the dominant mode of ingress of an air–helium mixture into the reactor vessel will either be molecular diffusion or density-driven stratified flow. The mode of ingress is hypothesized to dependmore » largely on the break conditions of the cross vessel. Since the time scales of these two ingress phenomena differ by orders of magnitude, it is imperative to understand under which conditions each of these mechanisms will dominate in the air ingress process. Computer models have been developed to analyze this type of accident scenario. There are, however, limited experimental data available to understand the phenomenology of the air-ingress accident and to validate these models. Therefore, there is a need to design and construct a scaled-down experimental test facility to simulate the air-ingress accident scenarios and to collect experimental data. The current paper focuses on the analyses performed for the design and operation of a 1/8th geometric scale (by height and diameter), high-temperature test facility. A geometric scaling analysis for the VHTR, a time scale analysis of the air-ingress phenomenon, a transient depressurization analysis of the reactor vessel, a hydraulic similarity analysis of the test facility, a heat transfer characterization of the hot plenum, a power scaling analysis for the reactor system, and a design analysis of the containment vessel are discussed.« less

SIGN SINGULARITY AND FLARES IN SOLAR ACTIVE REGION NOAA 11158

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

Sorriso-Valvo, L.; De Vita, G.; Kazachenko, M. D.

Solar Active Region NOAA 11158 has hosted a number of strong flares, including one X2.2 event. The complexity of current density and current helicity are studied through cancellation analysis of their sign-singular measure, which features power-law scaling. Spectral analysis is also performed, revealing the presence of two separate scaling ranges with different spectral index. The time evolution of parameters is discussed. Sudden changes of the cancellation exponents at the time of large flares and the presence of correlation with Extreme-Ultra-Violet and X-ray flux suggest that eruption of large flares can be linked to the small-scale properties of the current structures.

Ultrastructure and morphogenesis of the wing scales in Heliconius erato phyllis (Lepidoptera: Nymphalidae): what silvery/brownish surfaces can tell us about the development of color patterning?

PubMed

Aymone, A C B; Valente, V L S; de Araújo, A M

2013-09-01

Usually the literature on Heliconius show three types of scales, classified based on the correlation between color and ultrastructure: type I - white and yellow, type II - black, and type III - orange and red. The ultrastructure of the scales located at the silvery/brownish surfaces of males/females is for the first time described in this paper. Besides, we describe the ontogeny of pigmentation, the scale morphogenesis and the maturation timing of scales fated to different colors in Heliconius erato phyllis. The silvery/brownish surfaces showed ultrastructurally similar scales to the type I, II and III. The ontogeny of pigmentation follows the sequence red, black, silvery/brownish and yellow. The maturation of yellow-fated scales, however, occurred simultaneously with the red-fated scales, before the pigmentation becomes visible. In spite of the scales at the silvery/brownish surfaces being ultrastructurally similar to the yellow, red and black scales, they mature after them; this suggests that the maturation timing does not show a relationship with the scale ultrastructure, with the deposition timing of the yellow pigment. The analysis of H. erato phyllis scale morphogenesis, as well as the scales ultrastructure and maturation timing, provided new findings into the developmental architecture of color pattern in Heliconius. Copyright © 2013 Elsevier Ltd. All rights reserved.

Understanding the effect of vector dynamics in epidemic models using center manifold analysis

NASA Astrophysics Data System (ADS)

Rocha, Filipe; Aguiar, Maíra; Souza, Max; Stollenwerk, Nico

2012-09-01

In vector borne diseases the human hosts' epidemiology often acts on a much slower time scales than the one of the mosquitos which transmit the disease as a vector from human to human, due to their vastly different life cycles. We investigate in a model with susceptible (S), infected (I) and recovered (R) humans and susceptible (U) and infected (V) mosquitoes in how far the fast time scale of the mosquito epidemiology can be slaved by the slower human epidemiology, so that for the understanding of human disease data mainly the dynamics of the human time scale is essential and only slightly perturbed by the mosquito dynamics. This analysis of the SIRUV model is qualitatively in agreement with a previously investigated simpler SISUV model, hence a feature of vector-borne diseases in general.

Detrended Partial-Cross-Correlation Analysis: A New Method for Analyzing Correlations in Complex System

PubMed Central

Yuan, Naiming; Fu, Zuntao; Zhang, Huan; Piao, Lin; Xoplaki, Elena; Luterbacher, Juerg

2015-01-01

In this paper, a new method, detrended partial-cross-correlation analysis (DPCCA), is proposed. Based on detrended cross-correlation analysis (DCCA), this method is improved by including partial-correlation technique, which can be applied to quantify the relations of two non-stationary signals (with influences of other signals removed) on different time scales. We illustrate the advantages of this method by performing two numerical tests. Test I shows the advantages of DPCCA in handling non-stationary signals, while Test II reveals the “intrinsic” relations between two considered time series with potential influences of other unconsidered signals removed. To further show the utility of DPCCA in natural complex systems, we provide new evidence on the winter-time Pacific Decadal Oscillation (PDO) and the winter-time Nino3 Sea Surface Temperature Anomaly (Nino3-SSTA) affecting the Summer Rainfall over the middle-lower reaches of the Yangtze River (SRYR). By applying DPCCA, better significant correlations between SRYR and Nino3-SSTA on time scales of 6 ~ 8 years are found over the period 1951 ~ 2012, while significant correlations between SRYR and PDO on time scales of 35 years arise. With these physically explainable results, we have confidence that DPCCA is an useful method in addressing complex systems. PMID:25634341

Using multi-scale entropy and principal component analysis to monitor gears degradation via the motor current signature analysis

NASA Astrophysics Data System (ADS)

Aouabdi, Salim; Taibi, Mahmoud; Bouras, Slimane; Boutasseta, Nadir

2017-06-01

This paper describes an approach for identifying localized gear tooth defects, such as pitting, using phase currents measured from an induction machine driving the gearbox. A new tool of anomaly detection based on multi-scale entropy (MSE) algorithm SampEn which allows correlations in signals to be identified over multiple time scales. The motor current signature analysis (MCSA) in conjunction with principal component analysis (PCA) and the comparison of observed values with those predicted from a model built using nominally healthy data. The Simulation results show that the proposed method is able to detect gear tooth pitting in current signals.

The combined use of dynamic factor analysis and wavelet analysis to evaluate latent factors controlling complex groundwater level fluctuations in a riverside alluvial aquifer

NASA Astrophysics Data System (ADS)

Oh, Yun-Yeong; Yun, Seong-Taek; Yu, Soonyoung; Hamm, Se-Yeong

2017-12-01

To identify and quantitatively evaluate complex latent factors controlling groundwater level (GWL) fluctuations in a riverside alluvial aquifer influenced by barrage construction, we developed the combined use of dynamic factor analysis (DFA) and wavelet analysis (WA). Time series data of GWL, river water level and precipitation were collected for 3 years (July 2012 to June 2015) from an alluvial aquifer underneath an agricultural area of the Nakdong river basin, South Korea. Based on the wavelet coefficients of the final approximation, the GWL data was clustered into three groups (WCG1 to WCG3). Two dynamic factors (DFs) were then extracted using DFA for each group; thus, six major factors were extracted. Next, the time-frequency variability of the extracted DFs was examined using multiresolution cross-correlation analysis (MRCCA) with the following steps: 1) major driving forces and their scales in GWL fluctuations were identified by comparing maximum correlation coefficients (rmax) between DFs and the GWL time series and 2) the results were supplemented using the wavelet transformed coherence (WTC) analysis between DFs and the hydrological time series. Finally, relative contributions of six major DFs to the GWL fluctuations could be quantitatively assessed by calculating the effective dynamic efficiency (Def). The characteristics and relevant process of the identified six DFs are: 1) WCG1DF4,1 as an indicative of seasonal agricultural pumping (scales = 64-128 days; rmax = 0.68-0.89; Def ≤ 23.1%); 2) WCG1DF4,4 representing the cycle of regional groundwater recharge (scales = 64-128 days; rmax = 0.98-1.00; Def ≤ 11.1%); 3) WCG2DF4,1 indicating the complex interaction between the episodes of precipitation and direct runoff (scales = 2-8 days; rmax = 0.82-0.91; Def ≤ 35.3%) and seasonal GW-RW interaction (scales = 64-128 days; rmax = 0.76-0.91; Def ≤ 14.2%); 4) WCG2DF4,4 reflecting the complex effects of seasonal pervasive pumping and the local recharge cycle (scales = 64-128 days; rmax = 0.86-0.94; Def ≤ 16.4%); 5) WCG3DF4,2 as the result of temporal pumping (scales = 2-8 days; rmax = 0.98-0.99; Def ≤ 7.7%); and 6) WCG3DF4,4 indicating the local recharge cycle (scales = 64-128 days; rmax = 0.76-0.91; Def ≤ 34.2 %). This study shows that major driving forces controlling GWL time series data in a complex hydrological setting can be identified and quantitatively evaluated by the combined use of DFA and WA and applying MRCCA and WTC.

Hydrometeorological variability on a large french catchment and its relation to large-scale circulation across temporal scales

NASA Astrophysics Data System (ADS)

Massei, Nicolas; Dieppois, Bastien; Fritier, Nicolas; Laignel, Benoit; Debret, Maxime; Lavers, David; Hannah, David

2015-04-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating large-scale/local-scale correlation, enmpirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the large-scale/local-scale links were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach which integrated discrete wavelet multiresolution analysis for reconstructing local hydrometeorological processes (predictand : precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector) on a monthly time-step. This approach basically consisted in 1- decomposing both signals (SLP field and precipitation or streamflow) using discrete wavelet multiresolution analysis and synthesis, 2- generating one statistical downscaling model per time-scale, 3- summing up all scale-dependent models in order to obtain a final reconstruction of the predictand. The results obtained revealed a significant improvement of the reconstructions for both precipitation and streamflow when using the multiresolution ESD model instead of basic ESD ; in addition, the scale-dependent spatial patterns associated to the model matched quite well those obtained from scale-dependent composite analysis. In particular, the multiresolution ESD model handled very well the significant changes in variance through time observed in either prepciptation or streamflow. For instance, the post-1980 period, which had been characterized by particularly high amplitudes in interannual-to-interdecadal variability associated with flood and extremely low-flow/drought periods (e.g., winter 2001, summer 2003), could not be reconstructed without integrating wavelet multiresolution analysis into the model. Further investigations would be required to address the issue of the stationarity of the large-scale/local-scale relationships and to test the capability of the multiresolution ESD model for interannual-to-interdecadal forecasting. In terms of methodological approach, further investigations may concern a fully comprehensive sensitivity analysis of the modeling to the parameter of the multiresolution approach (different families of scaling and wavelet functions used, number of coefficients/degree of smoothness, etc.).

Towards a High-resolution Time Scale for the Early Devonian

NASA Astrophysics Data System (ADS)

Dekkers, M. J.; da Silva, A. C.

2017-12-01

High-resolution time scales are crucial to understand Earth's history in detail. The construction of a robust geological time scale, however, inevitably becomes increasingly harder further back in time. Uncertainties associated with anchor radiometric ages increase in size, not speaking of the mere presence of suitable datable strata. However, durations of stages can be tightly constrained by making use of cyclic expressions in sediments, an approach that revolutionized the Cenozoic time scale. When precisely determined durations are stitched together, ultimately, a very precise time scale is the result. For the Mesozoic and Paleozoic an astronomical solution as a tuning target is not available but the dominant periods of eccentricity, obliquity and precession are reasonably well constrained for the entire Phanerozoic which enables their detection by means of spectral analysis. Eccentricity is time-invariant and is used as the prime building block. Here we focus on the Early Devonian, on its lowermost three stages: the Lochkovian, Pragian and Emsian. The uncertainties on the Devonian stage boundaries are currently in the order of several millions of years. The preservation of climatic cycles in diagenetically or even anchimetamorphically affected successions, however, is essential. The fit of spectral peak ratios with those calculated for orbital cycles, is classically used as a strong argument for a preserved climatic signal. Here we use primarily the low field magnetic susceptibility (MS) as proxy parameter, supported by gamma-ray spectrometry to test for consistency. Continuous Wavelet Transform, Evolutive Harmonic Analysis, Multitaper Method, and Average Spectral Misfit are used to reach an optimal astronomical interpretation. We report on classic Early Devonian sections from the Czech Republic: the Pozar-CS (Lochkovian and Pragian), Pod Barrandovem (Pragian and Lower Emsian), and Zlichov (Middle-Upper Emsian). Also a Middle-Upper Emsian section from the US (Road 199 section, Kingston, New York) will be targeted. Strata display Milankovitch cycles to a varying visible degree but spectral analysis of MS with supporting magnetic property tests enables to constrain durations up to an order of magnitude more precise than in the current (2012) Geological Time Scale.

Stationary Wavelet-based Two-directional Two-dimensional Principal Component Analysis for EMG Signal Classification

NASA Astrophysics Data System (ADS)

Ji, Yi; Sun, Shanlin; Xie, Hong-Bo

2017-06-01

Discrete wavelet transform (WT) followed by principal component analysis (PCA) has been a powerful approach for the analysis of biomedical signals. Wavelet coefficients at various scales and channels were usually transformed into a one-dimensional array, causing issues such as the curse of dimensionality dilemma and small sample size problem. In addition, lack of time-shift invariance of WT coefficients can be modeled as noise and degrades the classifier performance. In this study, we present a stationary wavelet-based two-directional two-dimensional principal component analysis (SW2D2PCA) method for the efficient and effective extraction of essential feature information from signals. Time-invariant multi-scale matrices are constructed in the first step. The two-directional two-dimensional principal component analysis then operates on the multi-scale matrices to reduce the dimension, rather than vectors in conventional PCA. Results are presented from an experiment to classify eight hand motions using 4-channel electromyographic (EMG) signals recorded in healthy subjects and amputees, which illustrates the efficiency and effectiveness of the proposed method for biomedical signal analysis.

Scale-dependent behavior of the foredune: Implications for barrier island response to storms and sea-level rise

NASA Astrophysics Data System (ADS)

Houser, Chris; Wernette, Phil; Weymer, Bradley A.

2018-02-01

The impact of storm surge on a barrier island tends to be considered from a single cross-shore dimension, dependent on the relative elevations of the storm surge and dune crest. However, the foredune is rarely uniform and can exhibit considerable variation in height and width at a range of length scales. In this study, LiDAR data from barrier islands in Texas and Florida are used to explore how shoreline position and dune morphology vary alongshore, and to determine how this variability is altered or reinforced by storms and post-storm recovery. Wavelet analysis reveals that a power law can approximate historical shoreline change across all scales, but that storm-scale shoreline change ( 10 years) and dune height exhibit similar scale-dependent variations at swash and surf zone scales (< 1000 m). The in-phase nature of the relationship between dune height and storm-scale shoreline change indicates that areas of greater storm-scale shoreline retreat are associated with areas of smaller dunes. It is argued that the decoupling of storm-scale and historical shoreline change at swash and surf zone scales is also associated with the alongshore redistribution of sediment and the tendency of shorelines to evolve to a more diffusive (or straight) pattern with time. The wavelet analysis of the data for post-storm dune recovery is also characterized by red noise at the smallest scales characteristic of diffusive systems, suggesting that it is possible that small-scale variations in dune height can be repaired through alongshore recovery and expansion if there is sufficient time between storms. However, the time required for dune recovery exceeds the time between storms capable of eroding and overwashing the dune. Correlation between historical shoreline retreat and the variance of the dune at swash and surf zone scales suggests that the persistence of the dune is an important control on transgression through island migration or shoreline retreat with relative sea-level rise.

Nonlinear Image Denoising Methodologies

DTIC Science & Technology

2002-05-01

53 5.3 A Multiscale Approach to Scale-Space Analysis . . . . . . . . . . . . . . . . 53 5.4...etc. In this thesis, Our approach to denoising is first based on a controlled nonlinear stochastic random walk to achieve a scale space analysis ( as in... stochastic treatment or interpretation of the diffusion. In addition, unless a specific stopping time is known to be adequate, the resulting evolution

Identifying the time scale of synchronous movement: a study on tropical snakes.

PubMed

Lindström, Tom; Phillips, Benjamin L; Brown, Gregory P; Shine, Richard

2015-01-01

Individual movement is critical to organismal fitness and also influences broader population processes such as demographic stochasticity and gene flow. Climatic change and habitat fragmentation render the drivers of individual movement especially critical to understand. Rates of movement of free-ranging animals through the landscape are influenced both by intrinsic attributes of an organism (e.g., size, body condition, age), and by external forces (e.g., weather, predation risk). Statistical modelling can clarify the relative importance of those processes, because externally-imposed pressures should generate synchronous displacements among individuals within a population, whereas intrinsic factors should generate consistency through time within each individual. External and intrinsic factors may vary in importance at different time scales. In this study we focused on daily displacement of an ambush-foraging snake from tropical Australia (the Northern Death Adder Acanthophis praelongus), based on a radiotelemetric study. We used a mixture of spectral representation and Bayesian inference to study synchrony in snake displacement by phase shift analysis. We further studied autocorrelation in fluctuations of displacement distances as "one over f noise". Displacement distances were positively autocorrelated with all considered noise colour parameters estimated as >0. We show how the methodology can reveal time scales of particular interest for synchrony and found that for the analysed data, synchrony was only present at time scales above approximately three weeks. We conclude that the spectral representation combined with Bayesian inference is a promising approach for analysis of movement data. Applying the framework to telemetry data of A. praelongus, we were able to identify a cut-off time scale above which we found support for synchrony, thus revealing a time scale where global external drivers have a larger impact on the movement behaviour. Our results suggest that for the considered study period, movement at shorter time scales was primarily driven by factors at the individual level; daily fluctuations in weather conditions had little effect on snake movement.

Detecting transitions in protein dynamics using a recurrence quantification analysis based bootstrap method.

PubMed

Karain, Wael I

2017-11-28

Proteins undergo conformational transitions over different time scales. These transitions are closely intertwined with the protein's function. Numerous standard techniques such as principal component analysis are used to detect these transitions in molecular dynamics simulations. In this work, we add a new method that has the ability to detect transitions in dynamics based on the recurrences in the dynamical system. It combines bootstrapping and recurrence quantification analysis. We start from the assumption that a protein has a "baseline" recurrence structure over a given period of time. Any statistically significant deviation from this recurrence structure, as inferred from complexity measures provided by recurrence quantification analysis, is considered a transition in the dynamics of the protein. We apply this technique to a 132 ns long molecular dynamics simulation of the β-Lactamase Inhibitory Protein BLIP. We are able to detect conformational transitions in the nanosecond range in the recurrence dynamics of the BLIP protein during the simulation. The results compare favorably to those extracted using the principal component analysis technique. The recurrence quantification analysis based bootstrap technique is able to detect transitions between different dynamics states for a protein over different time scales. It is not limited to linear dynamics regimes, and can be generalized to any time scale. It also has the potential to be used to cluster frames in molecular dynamics trajectories according to the nature of their recurrence dynamics. One shortcoming for this method is the need to have large enough time windows to insure good statistical quality for the recurrence complexity measures needed to detect the transitions.

Projection-Based Reduced Order Modeling for Spacecraft Thermal Analysis

NASA Technical Reports Server (NTRS)

Qian, Jing; Wang, Yi; Song, Hongjun; Pant, Kapil; Peabody, Hume; Ku, Jentung; Butler, Charles D.

2015-01-01

This paper presents a mathematically rigorous, subspace projection-based reduced order modeling (ROM) methodology and an integrated framework to automatically generate reduced order models for spacecraft thermal analysis. Two key steps in the reduced order modeling procedure are described: (1) the acquisition of a full-scale spacecraft model in the ordinary differential equation (ODE) and differential algebraic equation (DAE) form to resolve its dynamic thermal behavior; and (2) the ROM to markedly reduce the dimension of the full-scale model. Specifically, proper orthogonal decomposition (POD) in conjunction with discrete empirical interpolation method (DEIM) and trajectory piece-wise linear (TPWL) methods are developed to address the strong nonlinear thermal effects due to coupled conductive and radiative heat transfer in the spacecraft environment. Case studies using NASA-relevant satellite models are undertaken to verify the capability and to assess the computational performance of the ROM technique in terms of speed-up and error relative to the full-scale model. ROM exhibits excellent agreement in spatiotemporal thermal profiles (<0.5% relative error in pertinent time scales) along with salient computational acceleration (up to two orders of magnitude speed-up) over the full-scale analysis. These findings establish the feasibility of ROM to perform rational and computationally affordable thermal analysis, develop reliable thermal control strategies for spacecraft, and greatly reduce the development cycle times and costs.

A Comprehensive Analysis of Multiscale Field-Aligned Currents: Characteristics, Controlling Parameters, and Relationships

NASA Astrophysics Data System (ADS)

McGranaghan, Ryan M.; Mannucci, Anthony J.; Forsyth, Colin

2017-12-01

We explore the characteristics, controlling parameters, and relationships of multiscale field-aligned currents (FACs) using a rigorous, comprehensive, and cross-platform analysis. Our unique approach combines FAC data from the Swarm satellites and the Advanced Magnetosphere and Planetary Electrodynamics Response Experiment (AMPERE) to create a database of small-scale (˜10-150 km, <1° latitudinal width), mesoscale (˜150-250 km, 1-2° latitudinal width), and large-scale (>250 km) FACs. We examine these data for the repeatable behavior of FACs across scales (i.e., the characteristics), the dependence on the interplanetary magnetic field orientation, and the degree to which each scale "departs" from nominal large-scale specification. We retrieve new information by utilizing magnetic latitude and local time dependence, correlation analyses, and quantification of the departure of smaller from larger scales. We find that (1) FACs characteristics and dependence on controlling parameters do not map between scales in a straight forward manner, (2) relationships between FAC scales exhibit local time dependence, and (3) the dayside high-latitude region is characterized by remarkably distinct FAC behavior when analyzed at different scales, and the locations of distinction correspond to "anomalous" ionosphere-thermosphere behavior. Comparing with nominal large-scale FACs, we find that differences are characterized by a horseshoe shape, maximizing across dayside local times, and that difference magnitudes increase when smaller-scale observed FACs are considered. We suggest that both new physics and increased resolution of models are required to address the multiscale complexities. We include a summary table of our findings to provide a quick reference for differences between multiscale FACs.

Multidisciplinary and biodanza intervention for the management of fibromyalgia.

PubMed

Carbonell-Baeza, Ana; Ruiz, Jonatan R; Aparicio, Virginia A; Martins-Pereira, Clelia M; Gatto-Cardia, M Claudia; Martinez, Jose M; Ortega, Francisco B; Delgado-Fernandez, Manuel

2012-01-01

To evaluate and compare the effectiveness of a 16-week multidisciplinary (exercise plus psychological therapy) and biodanza intervention in women with fibromyalgia. Thirty-eight women with fibromyalgia were distributed to a 16-week multidisciplinary (3-times/week) intervention (n=21) or Biodanza (1-time/week) intervention (n=17). We assessed tender point, body composition, physical fitness and psychological outcomes (Fibromyalgia Impact Questionnaire, the Short-Form Health Survey 36 questionnaire (SF-36), the Hospital Anxiety and Depression Scale, Vanderbilt Pain Management Inventory (VPMI), Rosenberg Self-Esteem Scale and General Self-Efficacy Scale). We observed a significant group*time interaction effect for the scales of SF-36 physical role (P=0.038) and social functioning (P=0.030) and for the passive coping scale in VPMI (P=0.043). Post hoc analysis revealed a significant improvement on social functioning (P=0.030) in the multidisciplinary group whereas it did not change in the Biodanza group. Post hoc analysis revealed a reduction in the use of passive coping (positive) (P less than 0.001) in the multidisciplinary group. There was no significant interaction or time effect in body composition and physical fitness. 16 weeks of multidisciplinary intervention induced greater benefits than a Biodanza intervention for social functioning and the use of passive coping strategies in women with fibromyalgia.

Method for Hot Real-Time Analysis of Pyrolysis Vapors at Pilot Scale

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

Pomeroy, Marc D

Pyrolysis oils contain more than 400 compounds, up to 60% of which do not re-volatilize for subsequent chemical analysis. Vapor chemical composition is also complicated as additional condensation reactions occur during quenching and collection of the product. Due to the complexity of the pyrolysis oil, and a desire to catalytically upgrade the vapor composition before condensation, online real-time analytical techniques such as Molecular Beam Mass Spectrometry (MBMS) are of great use. However, in order to properly sample hot pyrolysis vapors at the pilot scale, many challenges must be overcome.

Time-oriented hierarchical method for computation of principal components using subspace learning algorithm.

PubMed

Jankovic, Marko; Ogawa, Hidemitsu

2004-10-01

Principal Component Analysis (PCA) and Principal Subspace Analysis (PSA) are classic techniques in statistical data analysis, feature extraction and data compression. Given a set of multivariate measurements, PCA and PSA provide a smaller set of "basis vectors" with less redundancy, and a subspace spanned by them, respectively. Artificial neurons and neural networks have been shown to perform PSA and PCA when gradient ascent (descent) learning rules are used, which is related to the constrained maximization (minimization) of statistical objective functions. Due to their low complexity, such algorithms and their implementation in neural networks are potentially useful in cases of tracking slow changes of correlations in the input data or in updating eigenvectors with new samples. In this paper we propose PCA learning algorithm that is fully homogeneous with respect to neurons. The algorithm is obtained by modification of one of the most famous PSA learning algorithms--Subspace Learning Algorithm (SLA). Modification of the algorithm is based on Time-Oriented Hierarchical Method (TOHM). The method uses two distinct time scales. On a faster time scale PSA algorithm is responsible for the "behavior" of all output neurons. On a slower scale, output neurons will compete for fulfillment of their "own interests". On this scale, basis vectors in the principal subspace are rotated toward the principal eigenvectors. At the end of the paper it will be briefly analyzed how (or why) time-oriented hierarchical method can be used for transformation of any of the existing neural network PSA method, into PCA method.

Evaluation of Hydrologic and Meteorological Impacts on Dengue Fever Incidences in Southern Taiwan using Time- Frequency Method

NASA Astrophysics Data System (ADS)

Tsai, Christina; Yeh, Ting-Gu

2017-04-01

Extreme weather events are occurring more frequently as a result of climate change. Recently dengue fever has become a serious issue in southern Taiwan. It may have characteristic temporal scales that can be identified. Some researchers have hypothesized that dengue fever incidences are related to climate change. This study applies time-frequency analysis to time series data concerning dengue fever and hydrologic and meteorological variables. Results of three time-frequency analytical methods - the Hilbert Huang transform (HHT), the Wavelet Transform (WT) and the Short Time Fourier Transform (STFT) are compared and discussed. A more effective time-frequency analysis method will be identified to analyze relevant time series data. The most influential time scales of hydrologic and meteorological variables that are associated with dengue fever are determined. Finally, the linkage between hydrologic/meteorological factors and dengue fever incidences can be established.

Scale/Analytical Analyses of Freezing and Convective Melting with Internal Heat Generation

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

Ali S. Siahpush; John Crepeau; Piyush Sabharwall

2013-07-01

Using a scale/analytical analysis approach, we model phase change (melting) for pure materials which generate constant internal heat generation for small Stefan numbers (approximately one). The analysis considers conduction in the solid phase and natural convection, driven by internal heat generation, in the liquid regime. The model is applied for a constant surface temperature boundary condition where the melting temperature is greater than the surface temperature in a cylindrical geometry. The analysis also consider constant heat flux (in a cylindrical geometry).We show the time scales in which conduction and convection heat transfer dominate.

Asymptotic Analysis of Time-Dependent Neutron Transport Coupled with Isotopic Depletion and Radioactive Decay

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

Brantley, P S

2006-09-27

We describe an asymptotic analysis of the coupled nonlinear system of equations describing time-dependent three-dimensional monoenergetic neutron transport and isotopic depletion and radioactive decay. The classic asymptotic diffusion scaling of Larsen and Keller [1], along with a consistent small scaling of the terms describing the radioactive decay of isotopes, is applied to this coupled nonlinear system of equations in a medium of specified initial isotopic composition. The analysis demonstrates that to leading order the neutron transport equation limits to the standard time-dependent neutron diffusion equation with macroscopic cross sections whose number densities are determined by the standard system of ordinarymore » differential equations, the so-called Bateman equations, describing the temporal evolution of the nuclide number densities.« less

F-15 inlet/engine test techniques and distortion methodologies studies. Volume 2: Time variant data quality analysis plots

NASA Technical Reports Server (NTRS)

Stevens, C. H.; Spong, E. D.; Hammock, M. S.

1978-01-01

Time variant data quality analysis plots were used to determine if peak distortion data taken from a subscale inlet model can be used to predict peak distortion levels for a full scale flight test vehicle.

Doubly stochastic Poisson process models for precipitation at fine time-scales

NASA Astrophysics Data System (ADS)

Ramesh, Nadarajah I.; Onof, Christian; Xie, Dichao

2012-09-01

This paper considers a class of stochastic point process models, based on doubly stochastic Poisson processes, in the modelling of rainfall. We examine the application of this class of models, a neglected alternative to the widely-known Poisson cluster models, in the analysis of fine time-scale rainfall intensity. These models are mainly used to analyse tipping-bucket raingauge data from a single site but an extension to multiple sites is illustrated which reveals the potential of this class of models to study the temporal and spatial variability of precipitation at fine time-scales.

Scaling effects in the impact response of graphite-epoxy composite beams

NASA Technical Reports Server (NTRS)

Jackson, Karen E.; Fasanella, Edwin L.

1989-01-01

In support of crashworthiness studies on composite airframes and substructure, an experimental and analytical study was conducted to characterize size effects in the large deflection response of scale model graphite-epoxy beams subjected to impact. Scale model beams of 1/2, 2/3, 3/4, 5/6, and full scale were constructed of four different laminate stacking sequences including unidirectional, angle ply, cross ply, and quasi-isotropic. The beam specimens were subjected to eccentric axial impact loads which were scaled to provide homologous beam responses. Comparisons of the load and strain time histories between the scale model beams and the prototype should verify the scale law and demonstrate the use of scale model testing for determining impact behavior of composite structures. The nonlinear structural analysis finite element program DYCAST (DYnamic Crash Analysis of STructures) was used to model the beam response. DYCAST analysis predictions of beam strain response are compared to experimental data and the results are presented.

Exploring the History of Time in an Integrated System: the Ramifications for Water

NASA Astrophysics Data System (ADS)

Green, M. B.; Adams, L. E.; Allen, T. L.; Arrigo, J. S.; Bain, D. J.; Bray, E. N.; Duncan, J. M.; Hermans, C. M.; Pastore, C.; Schlosser, C. A.; Vorosmarty, C. J.; Witherell, B. B.; Wollheim, W. M.; Wreschnig, A. J.

2009-12-01

Characteristic time scales are useful and simple descriptors of geophysical and socio-economic system dynamics. Focusing on the integrative nature of the hydrologic cycle, new insights into system couplings can be gained by compiling characteristic time scales of important processes driving these systems. There are many examples of changing characteristic time scales. Human life expectancy has increased over the recent history of medical advancement. The transport time of goods has decreased with the progression from horse to rail to car to plane. The transport time of information changed with the progression from letter to telegraph to telephone to networked computing. Soil residence time (pedogenesis to estuary deposition) has been influenced by changing agricultural technology, urbanization, and forest practices. Surface water residence times have varied as beaver dams have disappeared and been replaced with modern reservoirs, flood control works, and channelization. These dynamics raise the question of how these types of time scales interact with each other to form integrated Earth system dynamics? Here we explore the coupling of geophysical and socio-economic systems in the northeast United States over the 1600 to 2010 period by examining characteristic time scales. This visualization of many time scales serves as an exploratory analysis, producing new hypotheses about how the integrated system dynamics have evolved over the last 400 years. Specifically, exponential population growth and the evolving strategies to maintain that population appears as fundamental to many of the time scales.

The effect of orthostatic stress on multiscale entropy of heart rate and blood pressure.

PubMed

Turianikova, Zuzana; Javorka, Kamil; Baumert, Mathias; Calkovska, Andrea; Javorka, Michal

2011-09-01

Cardiovascular control acts over multiple time scales, which introduces a significant amount of complexity to heart rate and blood pressure time series. Multiscale entropy (MSE) analysis has been developed to quantify the complexity of a time series over multiple time scales. In previous studies, MSE analyses identified impaired cardiovascular control and increased cardiovascular risk in various pathological conditions. Despite the increasing acceptance of the MSE technique in clinical research, information underpinning the involvement of the autonomic nervous system in the MSE of heart rate and blood pressure is lacking. The objective of this study is to investigate the effect of orthostatic challenge on the MSE of heart rate and blood pressure variability (HRV, BPV) and the correlation between MSE (complexity measures) and traditional linear (time and frequency domain) measures. MSE analysis of HRV and BPV was performed in 28 healthy young subjects on 1000 consecutive heart beats in the supine and standing positions. Sample entropy values were assessed on scales of 1-10. We found that MSE of heart rate and blood pressure signals is sensitive to changes in autonomic balance caused by postural change from the supine to the standing position. The effect of orthostatic challenge on heart rate and blood pressure complexity depended on the time scale under investigation. Entropy values did not correlate with the mean values of heart rate and blood pressure and showed only weak correlations with linear HRV and BPV measures. In conclusion, the MSE analysis of heart rate and blood pressure provides a sensitive tool to detect changes in autonomic balance as induced by postural change.

Long-range persistence in the global mean surface temperature and the global warming "time bomb"

NASA Astrophysics Data System (ADS)

Rypdal, M.; Rypdal, K.

2012-04-01

Detrended Fluctuation Analysis (DFA) and Maximum Likelihood Estimations (MLE) based on instrumental data over the last 160 years indicate that there is Long-Range Persistence (LRP) in Global Mean Surface Temperature (GMST) on time scales of months to decades. The persistence is much higher in sea surface temperature than in land temperatures. Power spectral analysis of multi-model, multi-ensemble runs of global climate models indicate further that this persistence may extend to centennial and maybe even millennial time-scales. We also support these conclusions by wavelet variogram analysis, DFA, and MLE of Northern hemisphere mean surface temperature reconstructions over the last two millennia. These analyses indicate that the GMST is a strongly persistent noise with Hurst exponent H>0.9 on time scales from decades up to at least 500 years. We show that such LRP can be very important for long-term climate prediction and for the establishment of a "time bomb" in the climate system due to a growing energy imbalance caused by the slow relaxation to radiative equilibrium under rising anthropogenic forcing. We do this by the construction of a multi-parameter dynamic-stochastic model for the GMST response to deterministic and stochastic forcing, where LRP is represented by a power-law response function. Reconstructed data for total forcing and GMST over the last millennium are used with this model to estimate trend coefficients and Hurst exponent for the GMST on multi-century time scale by means of MLE. Ensembles of solutions generated from the stochastic model also allow us to estimate confidence intervals for these estimates.

Future time perspective: opportunities and limitations are differentially associated with subjective well-being and hair cortisol concentration.

PubMed

Kozik, Pavel; Hoppmann, Christiane A; Gerstorf, Denis

2015-01-01

Future time perspective has been associated with subjective well-being, though depending on the line of research considered either an open-ended future time perspective or a limited future time perspective has been associated with high well-being. Most of this research however has conceptualized future time perspective as a one-dimensional construct, whereas recent evidence has demonstrated that there are likely at least two different underlying dimensions, a focus on opportunities and a focus on limitations. This project first seeks to replicate the two-dimensional structure of the Future Time Perspective Scale, and then examines the associations these dimensions may have with different measures of subjective well-being and a biological index of chronic stress. To test if the two dimensions of the Future Time Perspective Scale, a focus on opportunities and a focus on limitations, differentially associate with two measures of subjective well-being and a biological indicator of chronic stress, namely hair cortisol. Sixty-six community-dwelling participants with a mean age of 72 years (SD = 5.83) completed the Future Time Perspective Scale, Center for Epidemiologic Studies Depression Scale, and Philadelphia Geriatric Center Morale Scale. Participants also provided a 3-cm-long hair strand to index cortisol accumulation over the past 3 months. Following the results of a factor analysis, a mediation model was created for each dimension of the Future Time Perspective Scale, and significance testing was done through a bootstrapping approach to harness maximal statistical power. Factor analysis results replicated the two-dimensional structure of the Future Time Perspective Scale. Both dimensions were then found to have unique associations with well-being. Specifically, a high focus on opportunities was associated with fewer depressive symptoms and higher morale, whereas a low focus on limitations was associated with reduced hair cortisol, though this association was mediated by subjective well-being. RESULTS replicate and extend previous research by pointing to the multi-dimensional nature of the Future Time Perspective Scale. While an open future time perspective was overall beneficial for well-being, the exact association each dimension had with well-being differed depending on whether subjective measures of well-being or biological indices of chronic stress were considered. © 2014 S. Karger AG, Basel.

Memory and long-range correlations in chess games

NASA Astrophysics Data System (ADS)

Schaigorodsky, Ana L.; Perotti, Juan I.; Billoni, Orlando V.

2014-01-01

In this paper we report the existence of long-range memory in the opening moves of a chronologically ordered set of chess games using an extensive chess database. We used two mapping rules to build discrete time series and analyzed them using two methods for detecting long-range correlations; rescaled range analysis and detrended fluctuation analysis. We found that long-range memory is related to the level of the players. When the database is filtered according to player levels we found differences in the persistence of the different subsets. For high level players, correlations are stronger at long time scales; whereas in intermediate and low level players they reach the maximum value at shorter time scales. This can be interpreted as a signature of the different strategies used by players with different levels of expertise. These results are robust against the assignation rules and the method employed in the analysis of the time series.

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids.

PubMed

Dahlberg, Jerry; Tkacik, Peter T; Mullany, Brigid; Fleischhauer, Eric; Shahinian, Hossein; Azimi, Farzad; Navare, Jayesh; Owen, Spencer; Bisel, Tucker; Martin, Tony; Sholar, Jodie; Keanini, Russell G

2017-12-04

An analog, macroscopic method for studying molecular-scale hydrodynamic processes in dense gases and liquids is described. The technique applies a standard fluid dynamic diagnostic, particle image velocimetry (PIV), to measure: i) velocities of individual particles (grains), extant on short, grain-collision time-scales, ii) velocities of systems of particles, on both short collision-time- and long, continuum-flow-time-scales, iii) collective hydrodynamic modes known to exist in dense molecular fluids, and iv) short- and long-time-scale velocity autocorrelation functions, central to understanding particle-scale dynamics in strongly interacting, dense fluid systems. The basic system is composed of an imaging system, light source, vibrational sensors, vibrational system with a known media, and PIV and analysis software. Required experimental measurements and an outline of the theoretical tools needed when using the analog technique to study molecular-scale hydrodynamic processes are highlighted. The proposed technique provides a relatively straightforward alternative to photonic and neutron beam scattering methods traditionally used in molecular hydrodynamic studies.

Slow speed—fast motion: time-lapse recordings in physics education

NASA Astrophysics Data System (ADS)

Vollmer, Michael; Möllmann, Klaus-Peter

2018-05-01

Video analysis with a 30 Hz frame rate is the standard tool in physics education. The development of affordable high-speed-cameras has extended the capabilities of the tool for much smaller time scales to the 1 ms range, using frame rates of typically up to 1000 frames s-1, allowing us to study transient physics phenomena happening too fast for the naked eye. Here we want to extend the range of phenomena which may be studied by video analysis in the opposite direction by focusing on much longer time scales ranging from minutes, hours to many days or even months. We discuss this time-lapse method, needed equipment and give a few hints of how to produce respective recordings for two specific experiments.

Metrology with Weak Value Amplification and Related Topics

DTIC Science & Technology

2013-10-12

sensitivity depend crucially on the relative time scales involved, which include: 4 +- PBS PC HWP SBC Piezo Pulsed Laser Split Detector 50:50 FIG. 1. Simple...reasons why this may be impossible or inadvisable given a laboratory set-up. There may be a minimum quiet time between laser pulses, for example, or...measurements is a full 100 ms, our filtering limits the laser noise to time scales of about 30 ms. For analysis, we take this as our integration time in

Statistical analysis of hydrological response in urbanising catchments based on adaptive sampling using inter-amount times

NASA Astrophysics Data System (ADS)

ten Veldhuis, Marie-Claire; Schleiss, Marc

2017-04-01

Urban catchments are typically characterised by a more flashy nature of the hydrological response compared to natural catchments. Predicting flow changes associated with urbanisation is not straightforward, as they are influenced by interactions between impervious cover, basin size, drainage connectivity and stormwater management infrastructure. In this study, we present an alternative approach to statistical analysis of hydrological response variability and basin flashiness, based on the distribution of inter-amount times. We analyse inter-amount time distributions of high-resolution streamflow time series for 17 (semi-)urbanised basins in North Carolina, USA, ranging from 13 to 238 km2 in size. We show that in the inter-amount-time framework, sampling frequency is tuned to the local variability of the flow pattern, resulting in a different representation and weighting of high and low flow periods in the statistical distribution. This leads to important differences in the way the distribution quantiles, mean, coefficient of variation and skewness vary across scales and results in lower mean intermittency and improved scaling. Moreover, we show that inter-amount-time distributions can be used to detect regulation effects on flow patterns, identify critical sampling scales and characterise flashiness of hydrological response. The possibility to use both the classical approach and the inter-amount-time framework to identify minimum observable scales and analyse flow data opens up interesting areas for future research.

Time-space and cognition-space transformations for transportation network analysis based on multidimensional scaling and self-organizing map

NASA Astrophysics Data System (ADS)

Hong, Zixuan; Bian, Fuling

2008-10-01

Geographic space, time space and cognition space are three fundamental and interrelated spaces in geographic information systems for transportation. However, the cognition space and its relationships to the time space and geographic space are often neglected. This paper studies the relationships of these three spaces in urban transportation system from a new perspective and proposes a novel MDS-SOM transformation method which takes the advantages of the techniques of multidimensional scaling (MDS) and self-organizing map (SOM). The MDS-SOM transformation framework includes three kinds of mapping: the geographic-time transformation, the cognition-time transformation and the time-cognition transformation. The transformations in our research provide a better understanding of the interactions of these three spaces and beneficial knowledge is discovered to help the transportation analysis and decision supports.

Efficiency and cross-correlation in equity market during global financial crisis: Evidence from China

NASA Astrophysics Data System (ADS)

Ma, Pengcheng; Li, Daye; Li, Shuo

2016-02-01

Using one minute high-frequency data of the Shanghai Composite Index (SHCI) and the Shenzhen Composite Index (SZCI) (2007-2008), we employ the detrended fluctuation analysis (DFA) and the detrended cross correlation analysis (DCCA) with rolling window approach to observe the evolution of market efficiency and cross-correlation in pre-crisis and crisis period. Considering the fat-tail distribution of return time series, statistical test based on shuffling method is conducted to verify the null hypothesis of no long-term dependence. Our empirical research displays three main findings. First Shanghai equity market efficiency deteriorated while Shenzhen equity market efficiency improved with the advent of financial crisis. Second the highly positive dependence between SHCI and SZCI varies with time scale. Third financial crisis saw a significant increase of dependence between SHCI and SZCI at shorter time scales but a lack of significant change at longer time scales, providing evidence of contagion and absence of interdependence during crisis.

Divided-evolution-based pulse scheme for quantifying exchange processes in proteins: powerful complement to relaxation dispersion experiments.

PubMed

Bouvignies, Guillaume; Hansen, D Flemming; Vallurupalli, Pramodh; Kay, Lewis E

2011-02-16

A method for quantifying millisecond time scale exchange in proteins is presented based on scaling the rate of chemical exchange using a 2D (15)N, (1)H(N) experiment in which (15)N dwell times are separated by short spin-echo pulse trains. Unlike the popular Carr-Purcell-Meiboom-Gill (CPMG) experiment where the effects of a radio frequency field on measured transverse relaxation rates are quantified, the new approach measures peak positions in spectra that shift as the effective exchange time regime is varied. The utility of the method is established through an analysis of data recorded on an exchanging protein-ligand system for which the exchange parameters have been accurately determined using alternative approaches. Computations establish that a combined analysis of CPMG and peak shift profiles extends the time scale that can be studied to include exchanging systems with highly skewed populations and exchange rates as slow as 20 s(-1).

Time Correlations and the Frequency Spectrum of Sound Radiated by Turbulent Flows

NASA Technical Reports Server (NTRS)

Rubinstein, Robert; Zhou, Ye

1997-01-01

Theories of turbulent time correlations are applied to compute frequency spectra of sound radiated by isotropic turbulence and by turbulent shear flows. The hypothesis that Eulerian time correlations are dominated by the sweeping action of the most energetic scales implies that the frequency spectrum of the sound radiated by isotropic turbulence scales as omega(exp 4) for low frequencies and as omega(exp -3/4) for high frequencies. The sweeping hypothesis is applied to an approximate theory of jet noise. The high frequency noise again scales as omega(exp -3/4), but the low frequency spectrum scales as omega(exp 2). In comparison, a classical theory of jet noise based on dimensional analysis gives omega(exp -2) and omega(exp 2) scaling for these frequency ranges. It is shown that the omega(exp -2) scaling is obtained by simplifying the description of turbulent time correlations. An approximate theory of the effect of shear on turbulent time correlations is developed and applied to the frequency spectrum of sound radiated by shear turbulence. The predicted steepening of the shear dominated spectrum appears to be consistent with jet noise measurements.

Characterization of large-scale fluctuations and short-term variability of Seine river daily streamflow (France) over the period 1950-2008 by empirical mode decomposition and the Hilbert-Huang transform

NASA Astrophysics Data System (ADS)

Massei, N.; Fournier, M.

2010-12-01

Daily Seine river flow from 1950 to 2008 was analyzed using Hilbert-Huang Tranform (HHT). For the last ten years, this method which combines the so-called Empirical Mode Decomposition (EMD) multiresolution analysis and the Hilbert transform has proven its efficiency for the analysis of transient oscillatory signals, although the mathematical definition of the EMD is not totally established yet. HHT also provides an interesting alternative to other time-frequency or time-scale analysis of non-stationary signals, the most famous of which being wavelet-based approaches. In this application of HHT to the analysis of the hydrological variability of the Seine river, we seek to characterize the interannual patterns of daily flow, differenciate them from the short-term dynamics and eventually interpret them in the context of regional climate regime fluctuations. In this aim, HHT is also applied to the North-Atlantic Oscillation (NAO) through the annual winter-months NAO index time series. For both hydrological and climatic signals, dominant variability scales are extracted and their temporal variations analyzed by determination of the intantaneous frequency of each component. When compared to previous ones obtained from continuous wavelet transform (CWT) on the same data, HHT results highlighted the same scales and somewhat the same internal components for each signal. However, HHT allowed the identification and extraction of much more similar features during the 1950-2008 period (e.g., around 7-yr, between NAO and Seine flow than what was obtained from CWT, which comes to say that variability scales in flow likely to originate from climatic regime fluctuations were much properly identified in river flow. In addition, a more accurate determination of singularities in the natural processes analyzed were authorized by HHT compared to CWT, in which case the time-frequency resolution partly depends on the basic properties of the filter (i.e., the reference wavelet chosen initially). Compared to CWT or even to discrete wavelet multiresolution analysis, HHT is auto-adaptive, non-parametric, allows an orthogonal decomposition of the signal analyzed and provides a more accurate estimation of changing variability scales across time for highly transient signals.

Seeking a fingerprint: analysis of point processes in actigraphy recording

NASA Astrophysics Data System (ADS)

Gudowska-Nowak, Ewa; Ochab, Jeremi K.; Oleś, Katarzyna; Beldzik, Ewa; Chialvo, Dante R.; Domagalik, Aleksandra; Fąfrowicz, Magdalena; Marek, Tadeusz; Nowak, Maciej A.; Ogińska, Halszka; Szwed, Jerzy; Tyburczyk, Jacek

2016-05-01

Motor activity of humans displays complex temporal fluctuations which can be characterised by scale-invariant statistics, thus demonstrating that structure and fluctuations of such kinetics remain similar over a broad range of time scales. Previous studies on humans regularly deprived of sleep or suffering from sleep disorders predicted a change in the invariant scale parameters with respect to those for healthy subjects. In this study we investigate the signal patterns from actigraphy recordings by means of characteristic measures of fractional point processes. We analyse spontaneous locomotor activity of healthy individuals recorded during a week of regular sleep and a week of chronic partial sleep deprivation. Behavioural symptoms of lack of sleep can be evaluated by analysing statistics of duration times during active and resting states, and alteration of behavioural organisation can be assessed by analysis of power laws detected in the event count distribution, distribution of waiting times between consecutive movements and detrended fluctuation analysis of recorded time series. We claim that among different measures characterising complexity of the actigraphy recordings and their variations implied by chronic sleep distress, the exponents characterising slopes of survival functions in resting states are the most effective biomarkers distinguishing between healthy and sleep-deprived groups.

Sensitivity of the breastfeeding motivational measurement scale: a known group analysis of first time mothers.

PubMed

Stockdale, Janine; Sinclair, Marlene; Kernohan, George; McCrum-Gardner, Evie; Keller, John

2013-01-01

Breastfeeding has immense public health value for mothers, babies, and society. But there is an undesirably large gap between the number of new mothers who undertake and persist in breastfeeding compared to what would be a preferred level of accomplishment. This gap is a reflection of the many obstacles, both physical and psychological, that confront new mothers. Previous research has illuminated many of these concerns, but research on this problem is limited in part by the unavailability of a research instrument that can measure the key differences between first-time mothers and experienced mothers, with regard to the challenges they face when breastfeeding and the instructional advice they require. An instrument was designed to measure motivational complexity associated with sustained breast feeding behaviour; the Breastfeeding Motivational Measurement Scale. It contains 51 self-report items (7 point Likert scale) that cluster into four categories related to perceived value of breast-feeding, confidence to succeed, factors that influence success or failure, and strength of intentions, or goal. However, this scale has not been validated in terms of its sensitivity to profile the motivation of new mothers and experienced mothers. This issue was investigated by having 202 breastfeeding mothers (100 first time mothers) fill out the scale. The analysis reported in this paper is a three factor solution consisting of value, midwife support, and expectancies for success that explained the characteristics of first time mothers as a known group. These results support the validity of the BMM scale as a diagnostic tool for research on first time mothers who are learning to breastfeed. Further research studies are required to further test the validity of the scale in additional subgroups.

Time Correlations of Lightning Flash Sequences in Thunderstorms Revealed by Fractal Analysis

NASA Astrophysics Data System (ADS)

Gou, Xueqiang; Chen, Mingli; Zhang, Guangshu

2018-01-01

By using the data of lightning detection and ranging system at the Kennedy Space Center, the temporal fractal and correlation of interevent time series of lightning flash sequences in thunderstorms have been investigated with Allan factor (AF), Fano factor (FF), and detrended fluctuation analysis (DFA) methods. AF, FF, and DFA methods are powerful tools to detect the time-scaling structures and correlations in point processes. Totally 40 thunderstorms with distinguishing features of a single-cell storm and apparent increase and decrease in the total flash rate were selected for the analysis. It is found that the time-scaling exponents for AF (αAF) and FF (αFF) analyses are 1.62 and 0.95 in average, respectively, indicating a strong time correlation of the lightning flash sequences. DFA analysis shows that there is a crossover phenomenon—a crossover timescale (τc) ranging from 54 to 195 s with an average of 114 s. The occurrence of a lightning flash in a thunderstorm behaves randomly at timescales <τc but shows strong time correlation at scales >τc. Physically, these may imply that the establishment of an extensive strong electric field necessary for the occurrence of a lightning flash needs a timescale >τc, which behaves strongly time correlated. But the initiation of a lightning flash within a well-established extensive strong electric field may involve the heterogeneities of the electric field at a timescale <τc, which behave randomly.

The TRMM Multi-satellite Precipitation Analysis (TMPA): Quasi-Global Precipitation Estimates at Fine Scales

NASA Technical Reports Server (NTRS)

Huffman, George J.; Adler, Robert F.; Bolvin, David T.; Gu, Guojun; Nelkin, Eric J.; Bowman, Kenneth P.; Stocker, Erich; Wolff, David B.

2006-01-01

The TRMM Multi-satellite Precipitation Analysis (TMPA) provides a calibration-based sequential scheme for combining multiple precipitation estimates from satellites, as well as gauge analyses where feasible, at fine scales (0.25 degrees x 0.25 degrees and 3-hourly). It is available both after and in real time, based on calibration by the TRMM Combined Instrument and TRMM Microwave Imager precipitation products, respectively. Only the after-real-time product incorporates gauge data at the present. The data set covers the latitude band 50 degrees N-S for the period 1998 to the delayed present. Early validation results are as follows: The TMPA provides reasonable performance at monthly scales, although it is shown to have precipitation rate dependent low bias due to lack of sensitivity to low precipitation rates in one of the input products (based on AMSU-B). At finer scales the TMPA is successful at approximately reproducing the surface-observation-based histogram of precipitation, as well as reasonably detecting large daily events. The TMPA, however, has lower skill in correctly specifying moderate and light event amounts on short time intervals, in common with other fine-scale estimators. Examples are provided of a flood event and diurnal cycle determination.

Time-frequency analysis of electric motors

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

Bentley, C.L.; Dunn, M.E.; Mattingly, J.K.

1995-12-31

Physical signals such as the current of an electric motor become nonstationary as a consequence of degraded operation and broken parts. In this instance, their power spectral densities become time dependent, and time-frequency analysis techniques become the appropriate tools for signal analysis. The first among these techniques, generally called the short-time Fourier transform (STFT) method, is the Gabor transform 2 (GT) of a signal S(t), which decomposes the signal into time-local frequency modes: where the window function, {Phi}(t-{tau}), is a normalized Gaussian. Alternatively, one can decompose the signal into its multi-resolution representation at different levels of magnification. This representation ismore » achieved by the continuous wavelet transform (CWT) where the function g(t) is a kernel of zero average belonging to a family of scaled and shifted wavelet kernels. The CWT can be interpreted as the action of a microscope that locates the signal by the shift parameter b and adjusts its magnification by changing the scale parameter a. The Fourier-transformed CWT, W,{sub g}(a, {omega}), acts as a filter that places the high-frequency content of a signal into the lower end of the scale spectrum and vice versa for the low frequencies. Signals from a motor in three different states were analyzed.« less

Chaotic dynamics of Comet 1P/Halley: Lyapunov exponent and survival time expectancy

NASA Astrophysics Data System (ADS)

Muñoz-Gutiérrez, M. A.; Reyes-Ruiz, M.; Pichardo, B.

2015-03-01

The orbital elements of Comet Halley are known to a very high precision, suggesting that the calculation of its future dynamical evolution is straightforward. In this paper we seek to characterize the chaotic nature of the present day orbit of Comet Halley and to quantify the time-scale over which its motion can be predicted confidently. In addition, we attempt to determine the time-scale over which its present day orbit will remain stable. Numerical simulations of the dynamics of test particles in orbits similar to that of Comet Halley are carried out with the MERCURY 6.2 code. On the basis of these we construct survival time maps to assess the absolute stability of Halley's orbit, frequency analysis maps to study the variability of the orbit, and we calculate the Lyapunov exponent for the orbit for variations in initial conditions at the level of the present day uncertainties in our knowledge of its orbital parameters. On the basis of our calculations of the Lyapunov exponent for Comet Halley, the chaotic nature of its motion is demonstrated. The e-folding time-scale for the divergence of initially very similar orbits is approximately 70 yr. The sensitivity of the dynamics on initial conditions is also evident in the self-similarity character of the survival time and frequency analysis maps in the vicinity of Halley's orbit, which indicates that, on average, it is unstable on a time-scale of hundreds of thousands of years. The chaotic nature of Halley's present day orbit implies that a precise determination of its motion, at the level of the present-day observational uncertainty, is difficult to predict on a time-scale of approximately 100 yr. Furthermore, we also find that the ejection of Halley from the Solar system or its collision with another body could occur on a time-scale as short as 10 000 yr.

Cross-sectional fluctuation scaling in the high-frequency illiquidity of Chinese stocks

NASA Astrophysics Data System (ADS)

Cai, Qing; Gao, Xing-Lu; Zhou, Wei-Xing; Stanley, H. Eugene

2018-03-01

Taylor's law of temporal and ensemble fluctuation scaling has been ubiquitously observed in diverse complex systems including financial markets. Stock illiquidity is an important nonadditive financial quantity, which is found to comply with Taylor's temporal fluctuation scaling law. In this paper, we perform the cross-sectional analysis of the 1 min high-frequency illiquidity time series of Chinese stocks and unveil the presence of Taylor's law of ensemble fluctuation scaling. The estimated daily Taylor scaling exponent fluctuates around 1.442. We find that Taylor's scaling exponents of stock illiquidity do not relate to the ensemble mean and ensemble variety of returns. Our analysis uncovers a new scaling law of financial markets and might stimulate further investigations for a better understanding of financial markets' dynamics.

Confirmatory Factor Analysis of the Scales for Diagnosing Attention Deficit Hyperactivity Disorder (SCALES)

ERIC Educational Resources Information Center

Ryser, Gail R.; Campbell, Hilary L.; Miller, Brian K.

2010-01-01

The diagnostic criteria for attention deficit hyperactivity disorder have evolved over time with current versions of the "Diagnostic and Statistical Manual", (4th edition), text revision, ("DSM-IV-TR") suggesting that two constellations of symptoms may be present alone or in combination. The SCALES instrument for diagnosing attention deficit…

EVALUATING THE PERFORMANCE OF REGIONAL-SCALE PHOTOCHEMICAL MODELING SYSTEMS: PART I--METEOROLOGICAL PREDICTIONS. (R825260)

EPA Science Inventory

In this study, the concept of scale analysis is applied to evaluate two state-of-science meteorological models, namely MM5 and RAMS3b, currently being used to drive regional-scale air quality models. To this end, seasonal time series of observations and predictions for temperatur...

Memory and betweenness preference in temporal networks induced from time series

NASA Astrophysics Data System (ADS)

Weng, Tongfeng; Zhang, Jie; Small, Michael; Zheng, Rui; Hui, Pan

2017-02-01

We construct temporal networks from time series via unfolding the temporal information into an additional topological dimension of the networks. Thus, we are able to introduce memory entropy analysis to unravel the memory effect within the considered signal. We find distinct patterns in the entropy growth rate of the aggregate network at different memory scales for time series with different dynamics ranging from white noise, 1/f noise, autoregressive process, periodic to chaotic dynamics. Interestingly, for a chaotic time series, an exponential scaling emerges in the memory entropy analysis. We demonstrate that the memory exponent can successfully characterize bifurcation phenomenon, and differentiate the human cardiac system in healthy and pathological states. Moreover, we show that the betweenness preference analysis of these temporal networks can further characterize dynamical systems and separate distinct electrocardiogram recordings. Our work explores the memory effect and betweenness preference in temporal networks constructed from time series data, providing a new perspective to understand the underlying dynamical systems.

Multiscale multifractal detrended cross-correlation analysis of financial time series

NASA Astrophysics Data System (ADS)

Shi, Wenbin; Shang, Pengjian; Wang, Jing; Lin, Aijing

2014-06-01

In this paper, we introduce a method called multiscale multifractal detrended cross-correlation analysis (MM-DCCA). The method allows us to extend the description of the cross-correlation properties between two time series. MM-DCCA may provide new ways of measuring the nonlinearity of two signals, and it helps to present much richer information than multifractal detrended cross-correlation analysis (MF-DCCA) by sweeping all the range of scale at which the multifractal structures of complex system are discussed. Moreover, to illustrate the advantages of this approach we make use of the MM-DCCA to analyze the cross-correlation properties between financial time series. We show that this new method can be adapted to investigate stock markets under investigation. It can provide a more faithful and more interpretable description of the dynamic mechanism between financial time series than traditional MF-DCCA. We also propose to reduce the scale ranges to analyze short time series, and some inherent properties which remain hidden when a wide range is used may exhibit perfectly in this way.

Non-stationary dynamics in the bouncing ball: A wavelet perspective

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

Behera, Abhinna K., E-mail: abhinna@iiserkol.ac.in; Panigrahi, Prasanta K., E-mail: pprasanta@iiserkol.ac.in; Sekar Iyengar, A. N., E-mail: ansekar.iyengar@saha.ac.in

2014-12-01

The non-stationary dynamics of a bouncing ball, comprising both periodic as well as chaotic behavior, is studied through wavelet transform. The multi-scale characterization of the time series displays clear signatures of self-similarity, complex scaling behavior, and periodicity. Self-similar behavior is quantified by the generalized Hurst exponent, obtained through both wavelet based multi-fractal detrended fluctuation analysis and Fourier methods. The scale dependent variable window size of the wavelets aptly captures both the transients and non-stationary periodic behavior, including the phase synchronization of different modes. The optimal time-frequency localization of the continuous Morlet wavelet is found to delineate the scales corresponding tomore » neutral turbulence, viscous dissipation regions, and different time varying periodic modulations.« less

Wavelet Analysis of Turbulent Spots and Other Coherent Structures in Unsteady Transition

NASA Technical Reports Server (NTRS)

Lewalle, Jacques

1998-01-01

This is a secondary analysis of a portion of the Halstead data. The hot-film traces from an embedded stage of a low pressure turbine have been extensively analyzed by Halstead et al. In this project, wavelet analysis is used to develop the quantitative characterization of individual coherent structures in terms of size, amplitude, phase, convection speed, etc., as well as phase-averaged time scales. The purposes of the study are (1) to extract information about turbulent time scales for comparison with unsteady model results (e.g. k/epsilon). Phase-averaged maps of dominant time scales will be presented; and (2) to evaluate any differences between wake-induced and natural spots that might affect model performance. Preliminary results, subject to verification with data at higher frequency resolution, indicate that spot properties are independent of their phase relative to the wake footprints: therefore requirements for the physical content of models are kept relatively simple. Incidentally, we also observed that spot substructures can be traced over several stations; further study will examine their possible impact.

Examining the Interplay of Processes Across Multiple Time-Scales: Illustration With the Intraindividual Study of Affect, Health, and Interpersonal Behavior (iSAHIB).

PubMed

Ram, Nilam; Conroy, David E; Pincus, Aaron L; Lorek, Amy; Rebar, Amanda; Roche, Michael J; Coccia, Michael; Morack, Jennifer; Feldman, Josh; Gerstorf, Denis

Human development is characterized by the complex interplay of processes that manifest at multiple levels of analysis and time-scales. We introduce the Intraindividual Study of Affect, Health and Interpersonal Behavior (iSAHIB) as a model for how multiple time-scale study designs facilitate more precise articulation of developmental theory. Combining age heterogeneity, longitudinal panel, daily diary, and experience sampling protocols, the study made use of smartphone and web-based technologies to obtain intensive longitudinal data from 150 persons age 18-89 years as they completed three 21-day measurement bursts ( t = 426 bursts, t = 8,557 days) wherein they provided reports on their social interactions ( t = 64,112) as they went about their daily lives. We illustrate how multiple time-scales of data can be used to articulate bioecological models of development and the interplay among more 'distal' processes that manifest at 'slower' time-scales (e.g., age-related differences and burst-to-burst changes in mental health) and more 'proximal' processes that manifest at 'faster' time-scales (e.g., changes in context that progress in accordance with the weekly calendar and family influence processes).

Age-related alterations in the fractal scaling of cardiac interbeat interval dynamics

NASA Technical Reports Server (NTRS)

Iyengar, N.; Peng, C. K.; Morin, R.; Goldberger, A. L.; Lipsitz, L. A.

1996-01-01

We postulated that aging is associated with disruption in the fractallike long-range correlations that characterize healthy sinus rhythm cardiac interval dynamics. Ten young (21-34 yr) and 10 elderly (68-81 yr) rigorously screened healthy subjects underwent 120 min of continuous supine resting electrocardiographic recording. We analyzed the interbeat interval time series using standard time and frequency domain statistics and using a fractal measure, detrended fluctuation analysis, to quantify long-range correlation properties. In healthy young subjects, interbeat intervals demonstrated fractal scaling, with scaling exponents (alpha) from the fluctuation analysis close to a value of 1.0. In the group of healthy elderly subjects, the interbeat interval time series had two scaling regions. Over the short range, interbeat interval fluctuations resembled a random walk process (Brownian noise, alpha = 1.5), whereas over the longer range they resembled white noise (alpha = 0.5). Short (alpha s)- and long-range (alpha 1) scaling exponents were significantly different in the elderly subjects compared with young (alpha s = 1.12 +/- 0.19 vs. 0.90 +/- 0.14, respectively, P = 0.009; alpha 1 = 0.75 +/- 0.17 vs. 0.99 +/- 0.10, respectively, P = 0.002). The crossover behavior from one scaling region to another could be modeled as a first-order autoregressive process, which closely fit the data from four elderly subjects. This implies that a single characteristic time scale may be dominating heartbeat control in these subjects. The age-related loss of fractal organization in heartbeat dynamics may reflect the degradation of integrated physiological regulatory systems and may impair an individual's ability to adapt to stress.

A primer on the study of transitory dynamics in ecological series using the scale-dependent correlation analysis.

PubMed

Rodríguez-Arias, Miquel Angel; Rodó, Xavier

2004-03-01

Here we describe a practical, step-by-step primer to scale-dependent correlation (SDC) analysis. The analysis of transitory processes is an important but often neglected topic in ecological studies because only a few statistical techniques appear to detect temporary features accurately enough. We introduce here the SDC analysis, a statistical and graphical method to study transitory processes at any temporal or spatial scale. SDC analysis, thanks to the combination of conventional procedures and simple well-known statistical techniques, becomes an improved time-domain analogue of wavelet analysis. We use several simple synthetic series to describe the method, a more complex example, full of transitory features, to compare SDC and wavelet analysis, and finally we analyze some selected ecological series to illustrate the methodology. The SDC analysis of time series of copepod abundances in the North Sea indicates that ENSO primarily is the main climatic driver of short-term changes in population dynamics. SDC also uncovers some long-term, unexpected features in the population. Similarly, the SDC analysis of Nicholson's blowflies data locates where the proposed models fail and provides new insights about the mechanism that drives the apparent vanishing of the population cycle during the second half of the series.

Multiscaling properties of coastal waters particle size distribution from LISST in situ measurements

NASA Astrophysics Data System (ADS)

Pannimpullath Remanan, R.; Schmitt, F. G.; Loisel, H.; Mériaux, X.

2013-12-01

An eulerian high frequency sampling of particle size distribution (PSD) is performed during 5 tidal cycles (65 hours) in a coastal environment of the eastern English Channel at 1 Hz. The particle data are recorded using a LISST-100x type C (Laser In Situ Scattering and Transmissometry, Sequoia Scientific), recording volume concentrations of particles having diameters ranging from 2.5 to 500 mu in 32 size classes in logarithmic scale. This enables the estimation at each time step (every second) of the probability density function of particle sizes. At every time step, the pdf of PSD is hyperbolic. We can thus estimate PSD slope time series. Power spectral analysis shows that the mean diameter of the suspended particles is scaling at high frequencies (from 1s to 1000s). The scaling properties of particle sizes is studied by computing the moment function, from the pdf of the size distribution. Moment functions at many different time scales (from 1s to 1000 s) are computed and their scaling properties considered. The Shannon entropy at each time scale is also estimated and is related to other parameters. The multiscaling properties of the turbidity (coefficient cp computed from the LISST) are also consider on the same time scales, using Empirical Mode Decomposition.

Characteristic variations of sea surface temperature with multiple time scales in the North Pacific

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

Tanimoto, Youichi; Hanawa, Kimio; Toba, Yoshiaki

1993-06-01

It is unclear whether the recent increases in global temperatures are really due to the increase of greenhouse gases or are a manifestation of natural variability. Temporal evolution and spectral structure of sea surface temperature (SST) anomalies in the North Pacific over the last 37 years are investigated on the three characteristic time scales: shorter than 24 months (HF), 24-60 months (ES), and longer than 60 months (DC). The leading empirical-orthogonal function (EOF) for the DC time scale is characterized by a zonally elongated monopole centered at around 40[degrees]N, 180[degrees]. The leading EOF for the HF time scale is somewhatmore » similar to that for the DC time scale, although there are two centers of action with the same polarity at the mid and western Pacific. The leading EOF for the ES time scale, however, exhibits a different pattern whose center of action at the mid Pacific is located farther southeastward. In the time evolution of the SST anomalies associated with the leading EOF of the DC time scale, several anomaly periods can be identified that last five years or longer. The transition from a persistent period to another with the opposite polarity is generally very brief, except for the one that lasts throughout the late 1960s. The EOF analysis was repeated separately on these persistent anomaly periods and the long transition period. The spatial structure of the leading EOF of the SST variability with the ES time scale is found to be sensitive to the polarity of the decadal anomaly. These results are suggestive of the possible influence of the decadal SST variability upon the spatial structure of the variability with shorter time scales. 31 refs., 8 figs.« less

Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2017-06-06

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our systemmore » detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.« less

Scale-specific effects: A report on multiscale analysis of acupunctured EEG in entropy and power

NASA Astrophysics Data System (ADS)

Song, Zhenxi; Deng, Bin; Wei, Xile; Cai, Lihui; Yu, Haitao; Wang, Jiang; Wang, Ruofan; Chen, Yingyuan

2018-02-01

Investigating acupuncture effects contributes to improving clinical application and understanding neuronal dynamics under external stimulation. In this report, we recorded electroencephalography (EEG) signals evoked by acupuncture at ST36 acupoint with three stimulus frequencies of 50, 100 and 200 times per minutes, and selected non-acupuncture EEGs as the control group. Multiscale analyses were introduced to investigate the possible acupuncture effects on complexity and power in multiscale level. Using multiscale weighted-permutation entropy, we found the significant effects on increased complexity degree in EEG signals induced by acupuncture. The comparison of three stimulation manipulations showed that 100 times/min generated most obvious effects, and affected most cortical regions. By estimating average power spectral density, we found decreased power induced by acupuncture. The joint distribution of entropy and power indicated an inverse correlation, and this relationship was weakened by acupuncture effects, especially under the manipulation of 100 times/min frequency. Above findings are more evident and stable in large scales than small scales, which suggests that multiscale analysis allows evaluating significant effects in specific scale and enables to probe the inherent characteristics underlying physiological signals.

A comparative analysis of spectral exponent estimation techniques for 1/fβ processes with applications to the analysis of stride interval time series

PubMed Central

Schaefer, Alexander; Brach, Jennifer S.; Perera, Subashan; Sejdić, Ervin

2013-01-01

Background The time evolution and complex interactions of many nonlinear systems, such as in the human body, result in fractal types of parameter outcomes that exhibit self similarity over long time scales by a power law in the frequency spectrum S(f) = 1/fβ. The scaling exponent β is thus often interpreted as a “biomarker” of relative health and decline. New Method This paper presents a thorough comparative numerical analysis of fractal characterization techniques with specific consideration given to experimentally measured gait stride interval time series. The ideal fractal signals generated in the numerical analysis are constrained under varying lengths and biases indicative of a range of physiologically conceivable fractal signals. This analysis is to complement previous investigations of fractal characteristics in healthy and pathological gait stride interval time series, with which this study is compared. Results The results of our analysis showed that the averaged wavelet coefficient method consistently yielded the most accurate results. Comparison with Existing Methods: Class dependent methods proved to be unsuitable for physiological time series. Detrended fluctuation analysis as most prevailing method in the literature exhibited large estimation variances. Conclusions The comparative numerical analysis and experimental applications provide a thorough basis for determining an appropriate and robust method for measuring and comparing a physiologically meaningful biomarker, the spectral index β. In consideration of the constraints of application, we note the significant drawbacks of detrended fluctuation analysis and conclude that the averaged wavelet coefficient method can provide reasonable consistency and accuracy for characterizing these fractal time series. PMID:24200509

A comparative analysis of spectral exponent estimation techniques for 1/f(β) processes with applications to the analysis of stride interval time series.

PubMed

Schaefer, Alexander; Brach, Jennifer S; Perera, Subashan; Sejdić, Ervin

2014-01-30

The time evolution and complex interactions of many nonlinear systems, such as in the human body, result in fractal types of parameter outcomes that exhibit self similarity over long time scales by a power law in the frequency spectrum S(f)=1/f(β). The scaling exponent β is thus often interpreted as a "biomarker" of relative health and decline. This paper presents a thorough comparative numerical analysis of fractal characterization techniques with specific consideration given to experimentally measured gait stride interval time series. The ideal fractal signals generated in the numerical analysis are constrained under varying lengths and biases indicative of a range of physiologically conceivable fractal signals. This analysis is to complement previous investigations of fractal characteristics in healthy and pathological gait stride interval time series, with which this study is compared. The results of our analysis showed that the averaged wavelet coefficient method consistently yielded the most accurate results. Class dependent methods proved to be unsuitable for physiological time series. Detrended fluctuation analysis as most prevailing method in the literature exhibited large estimation variances. The comparative numerical analysis and experimental applications provide a thorough basis for determining an appropriate and robust method for measuring and comparing a physiologically meaningful biomarker, the spectral index β. In consideration of the constraints of application, we note the significant drawbacks of detrended fluctuation analysis and conclude that the averaged wavelet coefficient method can provide reasonable consistency and accuracy for characterizing these fractal time series. Copyright © 2013 Elsevier B.V. All rights reserved.

Statistical geometric affinity in human brain electric activity

NASA Astrophysics Data System (ADS)

Chornet-Lurbe, A.; Oteo, J. A.; Ros, J.

2007-05-01

The representation of the human electroencephalogram (EEG) records by neurophysiologists demands standardized time-amplitude scales for their correct conventional interpretation. In a suite of graphical experiments involving scaling affine transformations we have been able to convert electroencephalogram samples corresponding to any particular sleep phase and relaxed wakefulness into each other. We propound a statistical explanation for that finding in terms of data collapse. As a sequel, we determine characteristic time and amplitude scales and outline a possible physical interpretation. An analysis for characteristic times based on lacunarity is also carried out as well as a study of the synchrony between left and right EEG channels.

Characteristic time scales in the American dollar-Mexican peso exchange currency market

NASA Astrophysics Data System (ADS)

Alvarez-Ramirez, Jose

2002-06-01

Daily fluctuations of the American dollar-Mexican peso exchange currency market are studied using multifractal analysis methods. It is found evidence of multiaffinity of daily fluctuations in the sense that the qth-order (roughness) Hurst exponent Hq varies with changes in q. It is also found that there exist several characteristic time scales ranging from week to year. Accordingly, the market exhibits persistence in the sense that instabilities introduced by market events acting around the characteristic time scales (mainly, quarter and year) would propagate through the future market activity. Some implications of our results on the regulation of the dollar-mexpeso market activity are discussed.

Fractal scaling analysis of groundwater dynamics in confined aquifers

NASA Astrophysics Data System (ADS)

Tu, Tongbi; Ercan, Ali; Kavvas, M. Levent

2017-10-01

Groundwater closely interacts with surface water and even climate systems in most hydroclimatic settings. Fractal scaling analysis of groundwater dynamics is of significance in modeling hydrological processes by considering potential temporal long-range dependence and scaling crossovers in the groundwater level fluctuations. In this study, it is demonstrated that the groundwater level fluctuations in confined aquifer wells with long observations exhibit site-specific fractal scaling behavior. Detrended fluctuation analysis (DFA) was utilized to quantify the monofractality, and multifractal detrended fluctuation analysis (MF-DFA) and multiscale multifractal analysis (MMA) were employed to examine the multifractal behavior. The DFA results indicated that fractals exist in groundwater level time series, and it was shown that the estimated Hurst exponent is closely dependent on the length and specific time interval of the time series. The MF-DFA and MMA analyses showed that different levels of multifractality exist, which may be partially due to a broad probability density distribution with infinite moments. Furthermore, it is demonstrated that the underlying distribution of groundwater level fluctuations exhibits either non-Gaussian characteristics, which may be fitted by the Lévy stable distribution, or Gaussian characteristics depending on the site characteristics. However, fractional Brownian motion (fBm), which has been identified as an appropriate model to characterize groundwater level fluctuation, is Gaussian with finite moments. Therefore, fBm may be inadequate for the description of physical processes with infinite moments, such as the groundwater level fluctuations in this study. It is concluded that there is a need for generalized governing equations of groundwater flow processes that can model both the long-memory behavior and the Brownian finite-memory behavior.

Real-time powder diffraction studies of energy materials under non-equilibrium conditions

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

Peterson, Vanessa K.; Auckett, Josie E.; Pang, Wei-Kong

Energy materials form the central part of energy devices. An essential part of their function is the ability to reversibly host charge or energy carriers, and analysis of their phase composition and structure in real time under non-equilibrium conditions is mandatory for a full understanding of their atomic-scale functional mechanism. Real-time powder diffraction is increasingly being applied for this purpose, forming a critical step in the strategic chemical engineering of materials with improved behaviour. This topical review gives examples of real-time analysis using powder diffraction of rechargeable battery electrodes and porous sorbent materials used for the separation and storage ofmore » energy-relevant gases to demonstrate advances in the insights which can be gained into their atomic-scale function.« less

Real-time powder diffraction studies of energy materials under non-equilibrium conditions

PubMed Central

Peterson, Vanessa K.; Auckett, Josie E.; Pang, Wei-Kong

2017-01-01

Energy materials form the central part of energy devices. An essential part of their function is the ability to reversibly host charge or energy carriers, and analysis of their phase composition and structure in real time under non-equilibrium conditions is mandatory for a full understanding of their atomic-scale functional mechanism. Real-time powder diffraction is increasingly being applied for this purpose, forming a critical step in the strategic chemical engineering of materials with improved behaviour. This topical review gives examples of real-time analysis using powder diffraction of rechargeable battery electrodes and porous sorbent materials used for the separation and storage of energy-relevant gases to demonstrate advances in the insights which can be gained into their atomic-scale function. PMID:28989711

Nonlinear Time Series Analysis in the Absence of Strong Harmonics

NASA Astrophysics Data System (ADS)

Stine, Peter; Jevtic, N.

2010-05-01

Nonlinear time series analysis has successfully been used for noise reduction and for identifying long term periodicities in variable star light curves. It was thought that good noise reduction could be obtained when a strong fundamental and second harmonic are present. We show that, quite unexpectedly, this methodology for noise reduction can be efficient for data with very noisy power spectra without a strong fundamental and second harmonic. Not only can one obtain almost two orders of magnitude noise reduction of the white noise tail, insight can also be gained into the short time scale of organized behavior. Thus, we are able to obtain an estimate of this short time scale, which is on the order of 1.5 hours in the case of a variable white dwarf.

Assessing Stress in Cancer Patients: A Second-Order Factor Analysis Model for the Perceived Stress Scale

ERIC Educational Resources Information Center

Golden-Kreutz, Deanna M.; Browne, Michael W.; Frierson, Georita M.; Andersen, Barbara L.

2004-01-01

Using the Perceived Stress Scale (PSS), perceptions of global stress were assessed in 111women following breast cancer surgery and at 12 and 24 months later. This is the first study to factor analyze the PSS. The PSS data were factor analyzed each time using exploratory factor analysis with oblique direct quartimin rotation. Goodness-of-fit…

A statistical forecast model using the time-scale decomposition technique to predict rainfall during flood period over the middle and lower reaches of the Yangtze River Valley

NASA Astrophysics Data System (ADS)

Hu, Yijia; Zhong, Zhong; Zhu, Yimin; Ha, Yao

2018-04-01

In this paper, a statistical forecast model using the time-scale decomposition method is established to do the seasonal prediction of the rainfall during flood period (FPR) over the middle and lower reaches of the Yangtze River Valley (MLYRV). This method decomposites the rainfall over the MLYRV into three time-scale components, namely, the interannual component with the period less than 8 years, the interdecadal component with the period from 8 to 30 years, and the interdecadal component with the period larger than 30 years. Then, the predictors are selected for the three time-scale components of FPR through the correlation analysis. At last, a statistical forecast model is established using the multiple linear regression technique to predict the three time-scale components of the FPR, respectively. The results show that this forecast model can capture the interannual and interdecadal variation of FPR. The hindcast of FPR during 14 years from 2001 to 2014 shows that the FPR can be predicted successfully in 11 out of the 14 years. This forecast model performs better than the model using traditional scheme without time-scale decomposition. Therefore, the statistical forecast model using the time-scale decomposition technique has good skills and application value in the operational prediction of FPR over the MLYRV.

Multiscale adaptive analysis of circadian rhythms and intradaily variability: Application to actigraphy time series in acute insomnia subjects

PubMed Central

Rivera, Ana Leonor; Toledo-Roy, Juan C.; Ellis, Jason; Angelova, Maia

2017-01-01

Circadian rhythms become less dominant and less regular with chronic-degenerative disease, such that to accurately assess these pathological conditions it is important to quantify not only periodic characteristics but also more irregular aspects of the corresponding time series. Novel data-adaptive techniques, such as singular spectrum analysis (SSA), allow for the decomposition of experimental time series, in a model-free way, into a trend, quasiperiodic components and noise fluctuations. We compared SSA with the traditional techniques of cosinor analysis and intradaily variability using 1-week continuous actigraphy data in young adults with acute insomnia and healthy age-matched controls. The findings suggest a small but significant delay in circadian components in the subjects with acute insomnia, i.e. a larger acrophase, and alterations in the day-to-day variability of acrophase and amplitude. The power of the ultradian components follows a fractal 1/f power law for controls, whereas for those with acute insomnia this power law breaks down because of an increased variability at the 90min time scale, reminiscent of Kleitman’s basic rest-activity (BRAC) cycles. This suggests that for healthy sleepers attention and activity can be sustained at whatever time scale required by circumstances, whereas for those with acute insomnia this capacity may be impaired and these individuals need to rest or switch activities in order to stay focused. Traditional methods of circadian rhythm analysis are unable to detect the more subtle effects of day-to-day variability and ultradian rhythm fragmentation at the specific 90min time scale. PMID:28753669

EVALUATING THE PERFORMANCE OF REGIONAL-SCALE PHOTOCHEMICAL MODELING SYSTEMS: PART II--OZONE PREDICTIONS. (R825260)

EPA Science Inventory

In this paper, the concept of scale analysis is applied to evaluate ozone predictions from two regional-scale air quality models. To this end, seasonal time series of observations and predictions from the RAMS3b/UAM-V and MM5/MAQSIP (SMRAQ) modeling systems for ozone were spectra...

Psychometric Properties of the Fatigue Severity Scale in Polio Survivors

ERIC Educational Resources Information Center

Burger, Helena; Franchignoni, Franco; Puzic, Natasa; Giordano, Andrea

2010-01-01

The objective of this study was to evaluate by means of classical test theory and Rasch analysis the scaling characteristics and psychometric properties of the Fatigue Severity Scale (FSS) in polio survivors. A questionnaire, consisting of five general questions (sex, age, age at time of acute polio, sequelae of polio, and new symptoms), the FSS,…

How large a dataset should be in order to estimate scaling exponents and other statistics correctly in studies of solar wind turbulence

NASA Astrophysics Data System (ADS)

Rowlands, G.; Kiyani, K. H.; Chapman, S. C.; Watkins, N. W.

2009-12-01

Quantitative analysis of solar wind fluctuations are often performed in the context of intermittent turbulence and center around methods to quantify statistical scaling, such as power spectra and structure functions which assume a stationary process. The solar wind exhibits large scale secular changes and so the question arises as to whether the timeseries of the fluctuations is non-stationary. One approach is to seek a local stationarity by parsing the time interval over which statistical analysis is performed. Hence, natural systems such as the solar wind unavoidably provide observations over restricted intervals. Consequently, due to a reduction of sample size leading to poorer estimates, a stationary stochastic process (time series) can yield anomalous time variation in the scaling exponents, suggestive of nonstationarity. The variance in the estimates of scaling exponents computed from an interval of N observations is known for finite variance processes to vary as ~1/N as N becomes large for certain statistical estimators; however, the convergence to this behavior will depend on the details of the process, and may be slow. We study the variation in the scaling of second-order moments of the time-series increments with N for a variety of synthetic and “real world” time series, and we find that in particular for heavy tailed processes, for realizable N, one is far from this ~1/N limiting behavior. We propose a semiempirical estimate for the minimum N needed to make a meaningful estimate of the scaling exponents for model stochastic processes and compare these with some “real world” time series from the solar wind. With fewer datapoints the stationary timeseries becomes indistinguishable from a nonstationary process and we illustrate this with nonstationary synthetic datasets. Reference article: K. H. Kiyani, S. C. Chapman and N. W. Watkins, Phys. Rev. E 79, 036109 (2009).

Multiscale Information Transfer in Functional Corticomuscular Coupling Estimation Following Stroke: A Pilot Study

PubMed Central

Chen, Xiaoling; Xie, Ping; Zhang, Yuanyuan; Chen, Yuling; Yang, Fangmei; Zhang, Litai; Li, Xiaoli

2018-01-01

Recently, functional corticomuscular coupling (FCMC) between the cortex and the contralateral muscle has been used to evaluate motor function after stroke. As we know, the motor-control system is a closed-loop system that is regulated by complex self-regulating and interactive mechanisms which operate in multiple spatial and temporal scales. Multiscale analysis can represent the inherent complexity. However, previous studies in FCMC for stroke patients mainly focused on the coupling strength in single-time scale, without considering the changes of the inherently directional and multiscale properties in sensorimotor systems. In this paper, a multiscale-causal model, named multiscale transfer entropy, was used to quantify the functional connection between electroencephalogram over the scalp and electromyogram from the flexor digitorum superficialis (FDS) recorded simultaneously during steady-state grip task in eight stroke patients and eight healthy controls. Our results showed that healthy controls exhibited higher coupling when the scale reached up to about 12, and the FCMC in descending direction was stronger at certain scales (1, 7, 12, and 14) than that in ascending direction. Further analysis showed these multi-time scale characteristics mainly focused on the beta1 band at scale 11 and beta2 band at scale 9, 11, 13, and 15. Compared to controls, the multiscale properties of the FCMC for stroke were changed, the strengths in both directions were reduced, and the gaps between the descending and ascending directions were disappeared over all scales. Further analysis in specific bands showed that the reduced FCMC mainly focused on the alpha2 at higher scale, beta1 and beta2 across almost the entire scales. This study about multi-scale confirms that the FCMC between the brain and muscles is capable of complex and directional characteristics, and these characteristics in functional connection for stroke are destroyed by the structural lesion in the brain that might disrupt coordination, feedback, and information transmission in efferent control and afferent feedback. The study demonstrates for the first time the multiscale and directional characteristics of the FCMC for stroke patients, and provides a preliminary observation for application in clinical assessment following stroke. PMID:29765351

Visual search of cyclic spatio-temporal events

NASA Astrophysics Data System (ADS)

Gautier, Jacques; Davoine, Paule-Annick; Cunty, Claire

2018-05-01

The analysis of spatio-temporal events, and especially of relationships between their different dimensions (space-time-thematic attributes), can be done with geovisualization interfaces. But few geovisualization tools integrate the cyclic dimension of spatio-temporal event series (natural events or social events). Time Coil and Time Wave diagrams represent both the linear time and the cyclic time. By introducing a cyclic temporal scale, these diagrams may highlight the cyclic characteristics of spatio-temporal events. However, the settable cyclic temporal scales are limited to usual durations like days or months. Because of that, these diagrams cannot be used to visualize cyclic events, which reappear with an unusual period, and don't allow to make a visual search of cyclic events. Also, they don't give the possibility to identify the relationships between the cyclic behavior of the events and their spatial features, and more especially to identify localised cyclic events. The lack of possibilities to represent the cyclic time, outside of the temporal diagram of multi-view geovisualization interfaces, limits the analysis of relationships between the cyclic reappearance of events and their other dimensions. In this paper, we propose a method and a geovisualization tool, based on the extension of Time Coil and Time Wave, to provide a visual search of cyclic events, by allowing to set any possible duration to the diagram's cyclic temporal scale. We also propose a symbology approach to push the representation of the cyclic time into the map, in order to improve the analysis of relationships between space and the cyclic behavior of events.

Periodicity and Multi-scale Analysis of Runoff and Sediment Load in the Wulanghe River, Jinsha River

NASA Astrophysics Data System (ADS)

Chen, Yiming

2018-01-01

Based on the annual runoff and sediment data (1959-2014 ) of Zongguantian hydrological station, time-frequency wavelet transform characteristics and their periodic rules of high and low flow alternating change were analyzed in multi-time scales by the Morlet continue wavelet transformation (CWT). It is concluded that the primary periods of runoff and sediment load time series of the high and low annual flow in the different time scales were 12-year, 3-year and 26-year, 18-year, 13-year, 5-year, respectively, and predicted that the major variant trend of the two time series would been gradually decreasing and been in the high flow period around 8-year (from 2014 to 2022) and 10-year (from 2014 to 2020).

Energy and time determine scaling in biological and computer designs

PubMed Central

Bezerra, George; Edwards, Benjamin; Brown, James; Forrest, Stephanie

2016-01-01

Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy–time minimization principle may govern the design of many complex systems that process energy, materials and information. This article is part of the themed issue ‘The major synthetic evolutionary transitions’. PMID:27431524

Energy and time determine scaling in biological and computer designs.

PubMed

Moses, Melanie; Bezerra, George; Edwards, Benjamin; Brown, James; Forrest, Stephanie

2016-08-19

Metabolic rate in animals and power consumption in computers are analogous quantities that scale similarly with size. We analyse vascular systems of mammals and on-chip networks of microprocessors, where natural selection and human engineering, respectively, have produced systems that minimize both energy dissipation and delivery times. Using a simple network model that simultaneously minimizes energy and time, our analysis explains empirically observed trends in the scaling of metabolic rate in mammals and power consumption and performance in microprocessors across several orders of magnitude in size. Just as the evolutionary transitions from unicellular to multicellular animals in biology are associated with shifts in metabolic scaling, our model suggests that the scaling of power and performance will change as computer designs transition to decentralized multi-core and distributed cyber-physical systems. More generally, a single energy-time minimization principle may govern the design of many complex systems that process energy, materials and information.This article is part of the themed issue 'The major synthetic evolutionary transitions'. © 2016 The Author(s).

Exometabolome analysis reveals hypoxia at the up-scaling of a Saccharomyces cerevisiae high-cell density fed-batch biopharmaceutical process

PubMed Central

2014-01-01

Background Scale-up to industrial production level of a fermentation process occurs after optimization at small scale, a critical transition for successful technology transfer and commercialization of a product of interest. At the large scale a number of important bioprocess engineering problems arise that should be taken into account to match the values obtained at the small scale and achieve the highest productivity and quality possible. However, the changes of the host strain’s physiological and metabolic behavior in response to the scale transition are still not clear. Results Heterogeneity in substrate and oxygen distribution is an inherent factor at industrial scale (10,000 L) which affects the success of process up-scaling. To counteract these detrimental effects, changes in dissolved oxygen and pressure set points and addition of diluents were applied to 10,000 L scale to enable a successful process scale-up. A comprehensive semi-quantitative and time-dependent analysis of the exometabolome was performed to understand the impact of the scale-up on the metabolic/physiological behavior of the host microorganism. Intermediates from central carbon catabolism and mevalonate/ergosterol synthesis pathways were found to accumulate in both the 10 L and 10,000 L scale cultures in a time-dependent manner. Moreover, excreted metabolites analysis revealed that hypoxic conditions prevailed at the 10,000 L scale. The specific product yield increased at the 10,000 L scale, in spite of metabolic stress and catabolic-anabolic uncoupling unveiled by the decrease in biomass yield on consumed oxygen. Conclusions An optimized S. cerevisiae fermentation process was successfully scaled-up to an industrial scale bioreactor. The oxygen uptake rate (OUR) and overall growth profiles were matched between scales. The major remaining differences between scales were wet cell weight and culture apparent viscosity. The metabolic and physiological behavior of the host microorganism at the 10,000 L scale was investigated with exometabolomics, indicating that reduced oxygen availability affected oxidative phosphorylation cascading into down- and up-stream pathways producing overflow metabolism. Our study revealed striking metabolic and physiological changes in response to hypoxia exerted by industrial bioprocess up-scaling. PMID:24593159

Finite-Time and -Size Scalings in the Evaluation of Large Deviation Functions. Numerical Analysis in Continuous Time

NASA Astrophysics Data System (ADS)

Guevara Hidalgo, Esteban; Nemoto, Takahiro; Lecomte, Vivien

Rare trajectories of stochastic systems are important to understand because of their potential impact. However, their properties are by definition difficult to sample directly. Population dynamics provide a numerical tool allowing their study, by means of simulating a large number of copies of the system, which are subjected to a selection rule that favors the rare trajectories of interest. However, such algorithms are plagued by finite simulation time- and finite population size- effects that can render their use delicate. Using the continuous-time cloning algorithm, we analyze the finite-time and finite-size scalings of estimators of the large deviation functions associated to the distribution of the rare trajectories. We use these scalings in order to propose a numerical approach which allows to extract the infinite-time and infinite-size limit of these estimators.

Estimating time-dependent connectivity in marine systems

USGS Publications Warehouse

Defne, Zafer; Ganju, Neil K.; Aretxabaleta, Alfredo

2016-01-01

Hydrodynamic connectivity describes the sources and destinations of water parcels within a domain over a given time. When combined with biological models, it can be a powerful concept to explain the patterns of constituent dispersal within marine ecosystems. However, providing connectivity metrics for a given domain is a three-dimensional problem: two dimensions in space to define the sources and destinations and a time dimension to evaluate connectivity at varying temporal scales. If the time scale of interest is not predefined, then a general approach is required to describe connectivity over different time scales. For this purpose, we have introduced the concept of a “retention clock” that highlights the change in connectivity through time. Using the example of connectivity between protected areas within Barnegat Bay, New Jersey, we show that a retention clock matrix is an informative tool for multitemporal analysis of connectivity.

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.

The efficiency of parameter estimation of latent path analysis using summated rating scale (SRS) and method of successive interval (MSI) for transformation of score to scale

NASA Astrophysics Data System (ADS)

Solimun, Fernandes, Adji Achmad Rinaldo; Arisoesilaningsih, Endang

2017-12-01

Research in various fields generally investigates systems and involves latent variables. One method to analyze the model representing the system is path analysis. The data of latent variables measured using questionnaires by applying attitude scale model yields data in the form of score, before analyzed should be transformation so that it becomes data of scale. Path coefficient, is parameter estimator, calculated from scale data using method of successive interval (MSI) and summated rating scale (SRS). In this research will be identifying which data transformation method is better. Path coefficients have smaller varieties are said to be more efficient. The transformation method that produces scaled data and used in path analysis capable of producing path coefficients (parameter estimators) with smaller varieties is said to be better. The result of analysis using real data shows that on the influence of Attitude variable to Intention Entrepreneurship, has relative efficiency (ER) = 1, where it shows that the result of analysis using data transformation of MSI and SRS as efficient. On the other hand, for simulation data, at high correlation between items (0.7-0.9), MSI method is more efficient 1.3 times better than SRS method.

Defining Tsunami Magnitude as Measure of Potential Impact

NASA Astrophysics Data System (ADS)

Titov, V. V.; Tang, L.

2016-12-01

The goal of tsunami forecast, as a system for predicting potential impact of a tsunami at coastlines, requires quick estimate of a tsunami magnitude. This goal has been recognized since the beginning of tsunami research. The work of Kajiura, Soloviev, Abe, Murty, and many others discussed several scales for tsunami magnitude based on estimates of tsunami energy. However, difficulties of estimating tsunami energy based on available tsunami measurements at coastal sea-level stations has carried significant uncertainties and has been virtually impossible in real time, before tsunami impacts coastlines. The slow process of tsunami magnitude estimates, including collection of vast amount of available coastal sea-level data from affected coastlines, made it impractical to use any tsunami magnitude scales in tsunami warning operations. Uncertainties of estimates made tsunami magnitudes difficult to use as universal scale for tsunami analysis. Historically, the earthquake magnitude has been used as a proxy of tsunami impact estimates, since real-time seismic data is available of real-time processing and ample amount of seismic data is available for an elaborate post event analysis. This measure of tsunami impact carries significant uncertainties in quantitative tsunami impact estimates, since the relation between the earthquake and generated tsunami energy varies from case to case. In this work, we argue that current tsunami measurement capabilities and real-time modeling tools allow for establishing robust tsunami magnitude that will be useful for tsunami warning as a quick estimate for tsunami impact and for post-event analysis as a universal scale for tsunamis inter-comparison. We present a method for estimating the tsunami magnitude based on tsunami energy and present application of the magnitude analysis for several historical events for inter-comparison with existing methods.

Pattern analysis of total item score and item response of the Kessler Screening Scale for Psychological Distress (K6) in a nationally representative sample of US adults

PubMed Central

Kawasaki, Yohei; Ide, Kazuki; Akutagawa, Maiko; Yamada, Hiroshi; Yutaka, Ono; Furukawa, Toshiaki A.

2017-01-01

Background Several recent studies have shown that total scores on depressive symptom measures in a general population approximate an exponential pattern except for the lower end of the distribution. Furthermore, we confirmed that the exponential pattern is present for the individual item responses on the Center for Epidemiologic Studies Depression Scale (CES-D). To confirm the reproducibility of such findings, we investigated the total score distribution and item responses of the Kessler Screening Scale for Psychological Distress (K6) in a nationally representative study. Methods Data were drawn from the National Survey of Midlife Development in the United States (MIDUS), which comprises four subsamples: (1) a national random digit dialing (RDD) sample, (2) oversamples from five metropolitan areas, (3) siblings of individuals from the RDD sample, and (4) a national RDD sample of twin pairs. K6 items are scored using a 5-point scale: “none of the time,” “a little of the time,” “some of the time,” “most of the time,” and “all of the time.” The pattern of total score distribution and item responses were analyzed using graphical analysis and exponential regression model. Results The total score distributions of the four subsamples exhibited an exponential pattern with similar rate parameters. The item responses of the K6 approximated a linear pattern from “a little of the time” to “all of the time” on log-normal scales, while “none of the time” response was not related to this exponential pattern. Discussion The total score distribution and item responses of the K6 showed exponential patterns, consistent with other depressive symptom scales. PMID:28289560

Quantifying the scale- and process- dependent reorganization of landscape under climatic change: inferences from an experimental landscape

NASA Astrophysics Data System (ADS)

Singh, A.; Tejedor, A.; Grimaud, J. L.; Zaliapin, I. V.; Foufoula-Georgiou, E.

2016-12-01

Knowledge of the dynamics of evolving landscapes in terms of their geomorphic and topologic re-organization in response to changing climatic or tectonic forcing is of scientific and practical interest. Although several studies have addressed the large-scale response (e.g., change in mean relief), studies on the smaller-scale drainage pattern re-organization and quantification of landscape vulnerability to the timing, magnitude, and frequency of changing forcing are lacking. The reason is the absence of data for such an analysis. To that goal, a series of controlled laboratory experiments were conducted at the St. Anthony Falls laboratory of the University of Minnesota to study the effect of changing precipitation patterns on landscape evolution at the short and long-time scales. High resolution digital elevation (DEM) both in space and time were measured for a range of rainfall patterns and uplift rates. Results from our study show a distinct signature of the precipitation increase on the probabilistic and geometrical structure of landscape features, evident in widening and deepening of channels and valleys, change in drainage patterns within sub-basins and change in the space-time structure of erosional and depositional events. A spatially explicit analysis of the locus of these erosional and depositional events suggests a regime shift, during the onset of the transient state, from supply-limited to transport-limited fluvial channels. We document a characteristic scale-dependent signature of erosion at steady state (which we term the "E50-area curve") and show that during reorganization, its evolving shape reflects process and scales of geomorphic change. Finally, we document changes in the longitudinal river profiles, in response to increased precipitation rate, with the formation of abrupt gradient (knickpoints) that migrate upstream as time proceeds.

Parameter Uncertainty Analysis Using Monte Carlo Simulations for a Regional-Scale Groundwater Model

NASA Astrophysics Data System (ADS)

Zhang, Y.; Pohlmann, K.

2016-12-01

Regional-scale grid-based groundwater models for flow and transport often contain multiple types of parameters that can intensify the challenge of parameter uncertainty analysis. We propose a Monte Carlo approach to systematically quantify the influence of various types of model parameters on groundwater flux and contaminant travel times. The Monte Carlo simulations were conducted based on the steady-state conversion of the original transient model, which was then combined with the PEST sensitivity analysis tool SENSAN and particle tracking software MODPATH. Results identified hydrogeologic units whose hydraulic conductivity can significantly affect groundwater flux, and thirteen out of 173 model parameters that can cause large variation in travel times for contaminant particles originating from given source zones.

Position space analysis of the AdS (in)stability problem

NASA Astrophysics Data System (ADS)

Dimitrakopoulos, Fotios V.; Freivogel, Ben; Lippert, Matthew; Yang, I.-Sheng

2015-08-01

We investigate whether arbitrarily small perturbations in global AdS space are generically unstable and collapse into black holes on the time scale set by gravitational interactions. We argue that current evidence, combined with our analysis, strongly suggests that a set of nonzero measure in the space of initial conditions does not collapse on this time scale. We perform an analysis in position space to study this puzzle, and our formalism allows us to directly study the vanishing-amplitude limit. We show that gravitational self-interaction leads to tidal deformations which are equally likely to focus or defocus energy, and we sketch the phase diagram accordingly. We also clarify the connection between gravitational evolution in global AdS and holographic thermalization.

AQMEII3: the EU and NA regional scale program of the ...

EPA Pesticide Factsheets

The presentation builds on the work presented last year at the 14th CMAS meeting and it is applied to the work performed in the context of the AQMEII-HTAP collaboration. The analysis is conducted within the framework of the third phase of AQMEII (Air Quality Model Evaluation International Initiative) and encompasses the gauging of model performance through measurement-to-model comparison, error decomposition and time series analysis of the models biases. Through the comparison of several regional-scale chemistry transport modelling systems applied to simulate meteorology and air quality over two continental areas, this study aims at i) apportioning the error to the responsible processes through time-scale analysis, and ii) help detecting causes of models error, and iii) identify the processes and scales most urgently requiring dedicated investigations. The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overall sense of model strengths and deficiencies, while the apportioning of the error into its constituent parts (bias, variance and covariance) can help assess the nature and quality of the error. Each of the error components is analysed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intra-day) using the error apportionment technique devised in the previous phases of AQMEII. The National Exposure Research Laboratory (NERL) Computational Exposur

Synchronous dynamics of zooplankton competitors prevail in temperate lake ecosystems.

PubMed

Vasseur, David A; Fox, Jeremy W; Gonzalez, Andrew; Adrian, Rita; Beisner, Beatrix E; Helmus, Matthew R; Johnson, Catherine; Kratina, Pavel; Kremer, Colin; de Mazancourt, Claire; Miller, Elizabeth; Nelson, William A; Paterson, Michael; Rusak, James A; Shurin, Jonathan B; Steiner, Christopher F

2014-08-07

Although competing species are expected to exhibit compensatory dynamics (negative temporal covariation), empirical work has demonstrated that competitive communities often exhibit synchronous dynamics (positive temporal covariation). This has led to the suggestion that environmental forcing dominates species dynamics; however, synchronous and compensatory dynamics may appear at different length scales and/or at different times, making it challenging to identify their relative importance. We compiled 58 long-term datasets of zooplankton abundance in north-temperate and sub-tropical lakes and used wavelet analysis to quantify general patterns in the times and scales at which synchronous/compensatory dynamics dominated zooplankton communities in different regions and across the entire dataset. Synchronous dynamics were far more prevalent at all scales and times and were ubiquitous at the annual scale. Although we found compensatory dynamics in approximately 14% of all combinations of time period/scale/lake, there were no consistent scales or time periods during which compensatory dynamics were apparent across different regions. Our results suggest that the processes driving compensatory dynamics may be local in their extent, while those generating synchronous dynamics operate at much larger scales. This highlights an important gap in our understanding of the interaction between environmental and biotic forces that structure communities. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Characterization of the Spatio-temporal Evolution of the Energy of Recent Tsunamis in Chile and its Connection with the Seismic Source and Geomorphological Conditions

NASA Astrophysics Data System (ADS)

Quiroz, M.; Cienfuegos, R.

2017-12-01

At present, there is good knowledge acquired by the scientific community on characterizing the evolution of tsunami energy at ocean and shelf scales. For instance, the investigations of Rabinovich (2013) and Yamazaki (2011), represent some important advances in this subject. In the present paper we rather focus on tsunami energy evolution, and ultimately its decay, in coastal areas because characteristic time scales of this process has implications for early warning, evacuation initiation, and cancelling. We address the tsunami energy evolution analysis at three different spatial scales, a global scale at the ocean basin level, in particular the Pacific Ocean basin, a regional scale comprising processes that occur at the continental shelf level, and finally a local scale comprising coastal areas or bays. These scales were selected following the motivation to understand how the response is associated with tsunami, and how the energy evolves until it is completely dissipated. Through signal processing methods, such as discrete and wavelets analysis, we analyze time series of recent tsunamigenic events in the main Chilean coastal cities. Based on this analysis, we propose a conceptual model based on the influence of geomorphological variables on the evolution and decay of tsunami energy. This model acts as a filter from the seismic source to the observed response in coastal zones. Finally, we hope to conclude with practical tools that will establish patterns of behavior and scaling of energy evolution through interconnections from seismic source variables and the geomorphological component to understand the response and predict behavior for a given site.

[Development of a New Scale for Gauging Smartphone Dependence].

PubMed

Toda, Masahiro; Nishio, Nobuhiro; Takeshita, Tatsuya

2015-01-01

We designed a scale to gauge smartphone dependence and assessed its reliability and validity. A prototype self-rating smartphone-dependence scale was tested on 133 medical students who use smartphones more frequently than other devices to access web pages. Each response was scored on a Likert scale (0, 1, 2, 3), with higher scores indicating greater dependence. To select items for the final scale, exploratory factor analysis was conducted. On the basis of factor analysis results, we designed the Wakayama Smartphone-Dependence Scale (WSDS) comprising 21 items with 3 subscales: immersion in Internet communication; using a smartphone for extended periods of time and neglecting social obligations and other tasks; using a smartphone while doing something else and neglect of etiquette. Our analysis confirmed the validity of the different elements of the WSDS: the reliability coefficient (Cronbach's alpha) values of all subscales and total WSDS were from 0.79 to 0.83 and 0.88, respectively. These findings suggest that the WSDS is a useful tool for rating smartphone dependence.

Nonlinear zero-sum differential game analysis by singular perturbation methods

NASA Technical Reports Server (NTRS)

Sinar, J.; Farber, N.

1982-01-01

A class of nonlinear, zero-sum differential games, exhibiting time-scale separation properties, can be analyzed by singular-perturbation techniques. The merits of such an analysis, leading to an approximate game solution, as well as the 'well-posedness' of the formulation, are discussed. This approach is shown to be attractive for investigating pursuit-evasion problems; the original multidimensional differential game is decomposed to a 'simple pursuit' (free-stream) game and two independent (boundary-layer) optimal-control problems. Using multiple time-scale boundary-layer models results in a pair of uniformly valid zero-order composite feedback strategies. The dependence of suboptimal strategies on relative geometry and own-state measurements is demonstrated by a three dimensional, constant-speed example. For game analysis with realistic vehicle dynamics, the technique of forced singular perturbations and a variable modeling approach is proposed. Accuracy of the analysis is evaluated by comparison with the numerical solution of a time-optimal, variable-speed 'game of two cars' in the horizontal plane.

Computational singular perturbation analysis of stochastic chemical systems with stiffness

NASA Astrophysics Data System (ADS)

Wang, Lijin; Han, Xiaoying; Cao, Yanzhao; Najm, Habib N.

2017-04-01

Computational singular perturbation (CSP) is a useful method for analysis, reduction, and time integration of stiff ordinary differential equation systems. It has found dominant utility, in particular, in chemical reaction systems with a large range of time scales at continuum and deterministic level. On the other hand, CSP is not directly applicable to chemical reaction systems at micro or meso-scale, where stochasticity plays an non-negligible role and thus has to be taken into account. In this work we develop a novel stochastic computational singular perturbation (SCSP) analysis and time integration framework, and associated algorithm, that can be used to not only construct accurately and efficiently the numerical solutions to stiff stochastic chemical reaction systems, but also analyze the dynamics of the reduced stochastic reaction systems. The algorithm is illustrated by an application to a benchmark stochastic differential equation model, and numerical experiments are carried out to demonstrate the effectiveness of the construction.

Operational Consequences of Literacy Gap.

DTIC Science & Technology

1980-05-01

Comprehension Scores on the Safety and Sanitation Content 37 11. Statistics on Experimental Groups’ Performance by Sex and Content 37 12. Analysis of...Variance of Experimental Groups by Sex and Content 38 13. Mean Comprehension Scores Broken Down by Content, Subject RGL and Reading Time 39 14. Analysis...ratings along a scale of difficulty which parallels the school grade scale. Burkett (1975) and Klare (1963; 1974-1975) provide summaries of the extensive

A Comparison of Change in the 0–10 Numeric Rating Scale to a Pain Relief Scale and Global Medication Performance Scale in a Short-term Clinical Trial of Breakthrough Pain Intensity

PubMed Central

Farrar, John T.; Polomano, Rosemary C.; Berlin, Jesse A.; Strom, Brian L.

2010-01-01

Background Pain intensity is commonly reported using a 0–10 numeric rating scale in breakthrough pain clinical trials. Analysis of the change on the Pain Intensity Numerical Rating Scale as a proportion as most consistently correlated with clinically important differences reported on the Patient Global Impression of Change. The analysis of data using a different global outcome measures and the pain relief scale will extend our understanding of these measures. Use of the pain relief scale is also explored in this study Methods Data came from the open titration phase of a multiple crossover, randomized, double-blind clinical trial comparing oral transmucosal fentanyl citrate to immediate-release oral morphine sulfate for treatment of cancer-related breakthrough pain. Raw and percent changes in the pain intensity scores on 1,307 from 134 oral transmucosal fentanyl citrate-naive patients were compared to the clinically relevant secondary outcomes of the pain relief verbal response scale and the global medication performance. The changes in raw and percent change were assessed over time and compared to the ordinal pain relief verbal response scale and global medication performance scales. Results The p-value of the interaction between the raw pain intensity difference was significant but not for the percent pain intensity difference score over 4 15 minute time periods (p = 0.034 and p = 0.26 respectively), in comparison with the ordinal pain relief verbal response scale (p = 0.0048 and p = 0.36 respectively), and global medication performance categories (p = 0.048 and p = 0.45 respectively). Conclusion The change in pain intensity in breakthrough pain was more consistent over time and when compared to both the pain relief verbal response scale and global medication performance scale when the percent change is used rather than raw pain intensity difference. PMID:20463579

Application of Wavelet Filters in an Evaluation of ...

EPA Pesticide Factsheets

Air quality model evaluation can be enhanced with time-scale specific comparisons of outputs and observations. For example, high-frequency (hours to one day) time scale information in observed ozone is not well captured by deterministic models and its incorporation into model performance metrics lead one to devote resources to stochastic variations in model outputs. In this analysis, observations are compared with model outputs at seasonal, weekly, diurnal and intra-day time scales. Filters provide frequency specific information that can be used to compare the strength (amplitude) and timing (phase) of observations and model estimates. The National Exposure Research Laboratory′s (NERL′s) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA′s mission to protect human health and the environment. AMAD′s research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the Nation′s air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollu

Effect of facet joint injection versus systemic steroids in low back pain: a randomized controlled trial.

PubMed

Ribeiro, Luiza Helena; Furtado, Rita Nely Vilar; Konai, Monique Sayuri; Andreo, Ana Beatriz; Rosenfeld, Andre; Natour, Jamil

2013-11-01

Randomized clinical trial. To compare the effectiveness of facet joint injection versus systemic steroid in patients with a diagnosis of facet joint syndrome. The term facet joint syndrome has been used to define back pain originating from the facet joints. Treatment is mainly conservative, although interventions, including intra-articular injections and medial branch nerve blocks are used to manage facet-mediated pain. Several studies have evaluated the effectiveness of these interventions. Results of facet joint injection, however, are conflicting. Sixty subjects with a diagnosis of facet joint syndrome were enrolled in the study. They were randomized into experimental and control groups. The experimental group was administered with intra-articular injection of 6 lumbar facet joints with triamcinolone hexacetonide; the control group was administered with triamcinolone acetonide intramuscular injection of 6 lumbar paravertebral points. Visits were taken at baseline and at 1, 4, 12, and 24 weeks after interventions. Outcome measures were used: pain visual analogue scale, pain visual analogue scale during extension of the spine, Likert scale, improvement percentage scale, Roland-Morris, 36-Item Short Form Health Survey, and accountability of medications taken.Homogeneity was tested using the Student t, Pearson χ, and Mann-Whitney tests. Analysis of variance was used to analyze differences in the groups over time and the Student t test to analyze differences between groups at each time evaluation. The groups were similar at baseline. Comparisons between the groups showed, in analysis of variance analysis, an improvement in the experimental group regarding diclofenac intake and quality of life, in the "role physical" profile, assessed by 36-Item Short Form Health Survey.In the analysis at each time point, an improvement in the experimental group was also found in the Roland-Morris questionnaire, in the improvement percentage scale and in the response to treatment, assessed by the Likert scale. Both treatments were effective, with a slight superiority of the intra-articular injection of steroids over intramuscular injection.

Comparative analysis of time-scaling properties about water pH in Poyang Lake Inlet and Outlet on the basis of fractal methods.

PubMed

Shi, K; Liu, C Q; Huang, Z W; Zhang, B; Su, Y

2010-01-01

Detrended fluctuation analysis (DFA) and multifractal methods are applied to the time-scaling properties analysis of water pH series in Poyang Lake Inlet and Outlet in China. The results show that these pH series are characterised by long-term memory and multifractal scaling, and these characteristics have obvious differences between the Lake Inlet and Outlet. The comparison results suggest that monofractal and multifractal parameters can be quantitative dynamical indexes reflecting the capability of anti-acidification of Poyang Lake. Furthermore, we investigated the frequency-size distribution of pH series in Poyang Lake Inlet and Outlet. Our findings suggest that water pH is an example of a self-organised criticality (SOC) process. The results show that it is different SOC behaviours that result in the differences of power-law relations between pH series in Poyang Lake Inlet and Outlet. This work can be helpful to improvement of modelling of lake water quality.

Anomalous scaling of stochastic processes and the Moses effect

NASA Astrophysics Data System (ADS)

Chen, Lijian; Bassler, Kevin E.; McCauley, Joseph L.; Gunaratne, Gemunu H.

2017-04-01

The state of a stochastic process evolving over a time t is typically assumed to lie on a normal distribution whose width scales like t1/2. However, processes in which the probability distribution is not normal and the scaling exponent differs from 1/2 are known. The search for possible origins of such "anomalous" scaling and approaches to quantify them are the motivations for the work reported here. In processes with stationary increments, where the stochastic process is time-independent, autocorrelations between increments and infinite variance of increments can cause anomalous scaling. These sources have been referred to as the Joseph effect and the Noah effect, respectively. If the increments are nonstationary, then scaling of increments with t can also lead to anomalous scaling, a mechanism we refer to as the Moses effect. Scaling exponents quantifying the three effects are defined and related to the Hurst exponent that characterizes the overall scaling of the stochastic process. Methods of time series analysis that enable accurate independent measurement of each exponent are presented. Simple stochastic processes are used to illustrate each effect. Intraday financial time series data are analyzed, revealing that their anomalous scaling is due only to the Moses effect. In the context of financial market data, we reiterate that the Joseph exponent, not the Hurst exponent, is the appropriate measure to test the efficient market hypothesis.

Anomalous scaling of stochastic processes and the Moses effect.

PubMed

Chen, Lijian; Bassler, Kevin E; McCauley, Joseph L; Gunaratne, Gemunu H

2017-04-01

The state of a stochastic process evolving over a time t is typically assumed to lie on a normal distribution whose width scales like t^{1/2}. However, processes in which the probability distribution is not normal and the scaling exponent differs from 1/2 are known. The search for possible origins of such "anomalous" scaling and approaches to quantify them are the motivations for the work reported here. In processes with stationary increments, where the stochastic process is time-independent, autocorrelations between increments and infinite variance of increments can cause anomalous scaling. These sources have been referred to as the Joseph effect and the Noah effect, respectively. If the increments are nonstationary, then scaling of increments with t can also lead to anomalous scaling, a mechanism we refer to as the Moses effect. Scaling exponents quantifying the three effects are defined and related to the Hurst exponent that characterizes the overall scaling of the stochastic process. Methods of time series analysis that enable accurate independent measurement of each exponent are presented. Simple stochastic processes are used to illustrate each effect. Intraday financial time series data are analyzed, revealing that their anomalous scaling is due only to the Moses effect. In the context of financial market data, we reiterate that the Joseph exponent, not the Hurst exponent, is the appropriate measure to test the efficient market hypothesis.

Shock-induced thermal wave propagation and response analysis of a viscoelastic thin plate under transient heating loads

NASA Astrophysics Data System (ADS)

Li, Chenlin; Guo, Huili; Tian, Xiaogeng

2018-04-01

This paper is devoted to the thermal shock analysis for viscoelastic materials under transient heating loads. The governing coupled equations with time-delay parameter and nonlocal scale parameter are derived based on the generalized thermo-viscoelasticity theory. The problem of a thin plate composed of viscoelastic material, subjected to a sudden temperature rise at the boundary plane, is solved by employing Laplace transformation techniques. The transient responses, i.e. temperature, displacement, stresses, heat flux as well as strain, are obtained and discussed. The effects of time-delay and nonlocal scale parameter on the transient responses are analyzed and discussed. It can be observed that: the propagation of thermal wave is dynamically smoothed and changed with the variation of time-delay; while the displacement, strain, and stress can be rapidly reduced by nonlocal scale parameter, which can be viewed as an important indicator for predicting the stiffness softening behavior for viscoelastic materials.

Continuous wavelet transform based time-scale and multifractal analysis of the nonlinear oscillations in a hollow cathode glow discharge plasma

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

Nurujjaman, Md.; Narayanan, Ramesh; Iyengar, A. N. Sekar

2009-10-15

Continuous wavelet transform (CWT) based time-scale and multifractal analyses have been carried out on the anode glow related nonlinear floating potential fluctuations in a hollow cathode glow discharge plasma. CWT has been used to obtain the contour and ridge plots. Scale shift (or inversely frequency shift), which is a typical nonlinear behavior, has been detected from the undulating contours. From the ridge plots, we have identified the presence of nonlinearity and degree of chaoticity. Using the wavelet transform modulus maxima technique we have obtained the multifractal spectrum for the fluctuations at different discharge voltages and the spectrum was observed tomore » become a monofractal for periodic signals. These multifractal spectra were also used to estimate different quantities such as the correlation and fractal dimension, degree of multifractality, and complexity parameters. These estimations have been found to be consistent with the nonlinear time series analysis.« less

Linear static structural and vibration analysis on high-performance computers

NASA Technical Reports Server (NTRS)

Baddourah, M. A.; Storaasli, O. O.; Bostic, S. W.

1993-01-01

Parallel computers offer the oppurtunity to significantly reduce the computation time necessary to analyze large-scale aerospace structures. This paper presents algorithms developed for and implemented on massively-parallel computers hereafter referred to as Scalable High-Performance Computers (SHPC), for the most computationally intensive tasks involved in structural analysis, namely, generation and assembly of system matrices, solution of systems of equations and calculation of the eigenvalues and eigenvectors. Results on SHPC are presented for large-scale structural problems (i.e. models for High-Speed Civil Transport). The goal of this research is to develop a new, efficient technique which extends structural analysis to SHPC and makes large-scale structural analyses tractable.

Influence of non steady gravity on natural convection during micro-gravity solidification of semiconductors. I - Time scale analysis. II - Implications for crystal growth experiments

NASA Technical Reports Server (NTRS)

Griffin, P. R.; Motakef, S.

1989-01-01

Consideration is given to the influence of temporal variations in the magnitude of gravity on natural convection during unidirectional solidification of semiconductors. It is shown that the response time to step changes in g at low Rayleigh numbers is controlled by the momentum diffusive time scale. At higher Rayleigh numbers, the response time to increases in g is reduced because of inertial effects. The degree of perturbation of flow fields by transients in the gravitational acceleration on the Space Shuttle and the Space Station is determined. The analysis is used to derive the requirements for crystal growth experiments conducted on low duration low-g vehicles. Also, the effectiveness of sounding rockets and KC-135 aircraft for microgravity experiments is examined.

[Validity and reliability of Pediatric Quality of Life Inventory Version 4.0 Generic Core Scales in Chinese children and adolescents].

PubMed

Chen, Yu-Ming; He, Li-Ping; Mai, Jin-Cheng; Hao, Yuan-Tao; Xiong, Li-Hua; Chen, Wei-Qing; Wu, Jiang-Nan

2008-06-01

To evaluate the reliability and validity of parent proxy-report scales of Pediatric Quality of Life Inventory Version 4.0 (PedsQL 4.0) Generic Core Scales, the Chinese Version. 3493 school students aged 6-18 years were recruited using multistage cluster sampling method. Health-related quality of life was assessed using the above-mentioned PedsQL 4.0 scales. The internal consistency was assessed, using Cronbach's a coefficient, while its validity was tested through correlation analysis, t-test and exploratory factor analysis. The internal consistency reliability for Total Scale Score (Cronbach's alpha = 0.90), Physical Health Summary Score (alpha= 0.81), and Psychosocial Health Summary Score (alpha= 0.89) were excellent. Six major factors were extracted by factor analysis which basically matched the designed structure of the original version accounting for nearly 66% of the variance. The total Scale Score significantly decreased by 3.5 to 13.3 (P < 0.05) in children and adolescents who had diseases including cold, skin hypersensitiveness, food allergy, courbature or arthralgia, breathlessness with a frequency of 6 times or more per year or had asthma as compared to those with lower frequency (< or = 5 times/y) of the diseases or without asthma. We found moderate to high correlations between items and the subscales. Correlation coefficients ranged between 0.45 to 0.84 (P < 0.01). The reliability and validity of the parent proxy-report scales of PedsQL 4.0 Generic Core Scales of the Chinese Version were as good as the original version. Our findings suggested that the scales could be applied to evaluate the health-related quality of life in childhood children in similar Chinese regions to Guangzhou.

Variability of suspended-sediment concentration at tidal to annual time scales in San Francisco Bay, USA

USGS Publications Warehouse

Schoellhamer, D.H.

2002-01-01

Singular spectrum analysis for time series with missing data (SSAM) was used to reconstruct components of a 6-yr time series of suspended-sediment concentration (SSC) from San Francisco Bay. Data were collected every 15 min and the time series contained missing values that primarily were due to sensor fouling. SSAM was applied in a sequential manner to calculate reconstructed components with time scales of variability that ranged from tidal to annual. Physical processes that controlled SSC and their contribution to the total variance of SSC were (1) diurnal, semidiurnal, and other higher frequency tidal constituents (24%), (2) semimonthly tidal cycles (21%), (3) monthly tidal cycles (19%), (4) semiannual tidal cycles (12%), and (5) annual pulses of sediment caused by freshwater inflow, deposition, and subsequent wind-wave resuspension (13%). Of the total variance 89% was explained and subtidal variability (65%) was greater than tidal variability (24%). Processes at subtidal time scales accounted for more variance of SSC than processes at tidal time scales because sediment accumulated in the water column and the supply of easily erodible bed sediment increased during periods of increased subtidal energy. This large range of time scales that each contained significant variability of SSC and associated contaminants can confound design of sampling programs and interpretation of resulting data.

Development of a Comprehensive Assessment of Food Parenting Practices: The Home Self-Administered Tool for Environmental Assessment of Activity and Diet Family Food Practices Survey.

PubMed

Vaughn, Amber E; Dearth-Wesley, Tracy; Tabak, Rachel G; Bryant, Maria; Ward, Dianne S

2017-02-01

Parents' food parenting practices influence children's dietary intake and risk for obesity and chronic disease. Understanding the influence and interactions between parents' practices and children's behavior is limited by a lack of development and psychometric testing and/or limited scope of current measures. The Home Self-Administered Tool for Environmental Assessment of Activity and Diet (HomeSTEAD) was created to address this gap. This article describes development and psychometric testing of the HomeSTEAD family food practices survey. Between August 2010 and May 2011, a convenience sample of 129 parents of children aged 3 to 12 years were recruited from central North Carolina and completed the self-administered HomeSTEAD survey on three occasions during a 12- to 18-day window. Demographic characteristics and child diet were assessed at Time 1. Child height and weight were measured during the in-home observations (following Time 1 survey). Exploratory factor analysis with Time 1 data was used to identify potential scales. Scales with more than three items were examined for scale reduction. Following this, mean scores were calculated at each time point. Construct validity was assessed by examining Spearman rank correlations between mean scores (Time 1) and children's diet (fruits and vegetables, sugar-sweetened beverages, snacks, sweets) and body mass index (BMI) z scores. Repeated measures analysis of variance was used to examine differences in mean scores between time points, and single-measure intraclass correlations were calculated to examine test-retest reliability between time points. Exploratory factor analysis identified 24 factors and retained 124 items; however, scale reduction narrowed items to 86. The final instrument captures five coercive control practices (16 items), seven autonomy support practices (24 items), and 12 structure practices (46 items). All scales demonstrated good internal reliability (α>.62), 18 factors demonstrated construct validity (significant association with child diet, P<0.05), and 22 demonstrated good reliability (intraclass correlation coefficient>0.61). The HomeSTEAD family food practices survey provides a brief, yet comprehensive and psychometrically sound assessment of food parenting practices. Copyright © 2017 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Versatile synchronized real-time MEG hardware controller for large-scale fast data acquisition.

PubMed

Sun, Limin; Han, Menglai; Pratt, Kevin; Paulson, Douglas; Dinh, Christoph; Esch, Lorenz; Okada, Yoshio; Hämäläinen, Matti

2017-05-01

Versatile controllers for accurate, fast, and real-time synchronized acquisition of large-scale data are useful in many areas of science, engineering, and technology. Here, we describe the development of a controller software based on a technique called queued state machine for controlling the data acquisition (DAQ) hardware, continuously acquiring a large amount of data synchronized across a large number of channels (>400) at a fast rate (up to 20 kHz/channel) in real time, and interfacing with applications for real-time data analysis and display of electrophysiological data. This DAQ controller was developed specifically for a 384-channel pediatric whole-head magnetoencephalography (MEG) system, but its architecture is useful for wide applications. This controller running in a LabVIEW environment interfaces with microprocessors in the MEG sensor electronics to control their real-time operation. It also interfaces with a real-time MEG analysis software via transmission control protocol/internet protocol, to control the synchronous acquisition and transfer of the data in real time from >400 channels to acquisition and analysis workstations. The successful implementation of this controller for an MEG system with a large number of channels demonstrates the feasibility of employing the present architecture in several other applications.

Versatile synchronized real-time MEG hardware controller for large-scale fast data acquisition

NASA Astrophysics Data System (ADS)

Sun, Limin; Han, Menglai; Pratt, Kevin; Paulson, Douglas; Dinh, Christoph; Esch, Lorenz; Okada, Yoshio; Hämäläinen, Matti

2017-05-01

Versatile controllers for accurate, fast, and real-time synchronized acquisition of large-scale data are useful in many areas of science, engineering, and technology. Here, we describe the development of a controller software based on a technique called queued state machine for controlling the data acquisition (DAQ) hardware, continuously acquiring a large amount of data synchronized across a large number of channels (>400) at a fast rate (up to 20 kHz/channel) in real time, and interfacing with applications for real-time data analysis and display of electrophysiological data. This DAQ controller was developed specifically for a 384-channel pediatric whole-head magnetoencephalography (MEG) system, but its architecture is useful for wide applications. This controller running in a LabVIEW environment interfaces with microprocessors in the MEG sensor electronics to control their real-time operation. It also interfaces with a real-time MEG analysis software via transmission control protocol/internet protocol, to control the synchronous acquisition and transfer of the data in real time from >400 channels to acquisition and analysis workstations. The successful implementation of this controller for an MEG system with a large number of channels demonstrates the feasibility of employing the present architecture in several other applications.

[Multiple time scales analysis of spatial differentiation characteristics of non-point source nitrogen loss within watershed].

PubMed

Liu, Mei-bing; Chen, Xing-wei; Chen, Ying

2015-07-01

Identification of the critical source areas of non-point source pollution is an important means to control the non-point source pollution within the watershed. In order to further reveal the impact of multiple time scales on the spatial differentiation characteristics of non-point source nitrogen loss, a SWAT model of Shanmei Reservoir watershed was developed. Based on the simulation of total nitrogen (TN) loss intensity of all 38 subbasins, spatial distribution characteristics of nitrogen loss and critical source areas were analyzed at three time scales of yearly average, monthly average and rainstorms flood process, respectively. Furthermore, multiple linear correlation analysis was conducted to analyze the contribution of natural environment and anthropogenic disturbance on nitrogen loss. The results showed that there were significant spatial differences of TN loss in Shanmei Reservoir watershed at different time scales, and the spatial differentiation degree of nitrogen loss was in the order of monthly average > yearly average > rainstorms flood process. TN loss load mainly came from upland Taoxi subbasin, which was identified as the critical source area. At different time scales, land use types (such as farmland and forest) were always the dominant factor affecting the spatial distribution of nitrogen loss, while the effect of precipitation and runoff on the nitrogen loss was only taken in no fertilization month and several processes of storm flood at no fertilization date. This was mainly due to the significant spatial variation of land use and fertilization, as well as the low spatial variability of precipitation and runoff.

A novel approach to the dynamical complexity of the Earth's magnetosphere at geomagnetic storm time-scales based on recurrences

NASA Astrophysics Data System (ADS)

Donner, Reik; Balasis, Georgios; Stolbova, Veronika; Wiedermann, Marc; Georgiou, Marina; Kurths, Jürgen

2016-04-01

Magnetic storms are the most prominent global manifestations of out-of-equilibrium magnetospheric dynamics. Investigating the dynamical complexity exhibited by geomagnetic observables can provide valuable insights into relevant physical processes as well as temporal scales associated with this phenomenon. In this work, we introduce several innovative data analysis techniques enabling a quantitative analysis of the Dst index non-stationary behavior. Using recurrence quantification analysis (RQA) and recurrence network analysis (RNA), we obtain a variety of complexity measures serving as markers of quiet- and storm-time magnetospheric dynamics. We additionally apply these techniques to the main driver of Dst index variations, the V BSouth coupling function and interplanetary medium parameters Bz and Pdyn in order to discriminate internal processes from the magnetosphere's response directly induced by the external forcing by the solar wind. The derived recurrence-based measures allow us to improve the accuracy with which magnetospheric storms can be classified based on ground-based observations. The new methodology presented here could be of significant interest for the space weather research community working on time series analysis for magnetic storm forecasts.

Scaling analysis and model estimation of solar corona index

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Multifractality and heteroscedastic dynamics: An application to time series analysis

NASA Astrophysics Data System (ADS)

Nascimento, C. M.; Júnior, H. B. N.; Jennings, H. D.; Serva, M.; Gleria, Iram; Viswanathan, G. M.

2008-01-01

An increasingly important problem in physics concerns scale invariance symmetry in diverse complex systems, often characterized by heteroscedastic dynamics. We investigate the nature of the relationship between the heteroscedastic and fractal aspects of the dynamics of complex systems, by analyzing the sensitivity to heteroscedasticity of the scaling properties of weakly nonstationary time series. By using multifractal detrended fluctuation analysis, we study the singularity spectra of currency exchange rate fluctuations, after partially or completely eliminating n-point correlations via data shuffling techniques. We conclude that heteroscedasticity can significantly increase multifractality and interpret these findings in the context of self-organizing and adaptive complex systems.

Factors Influencing the Sahelian Paradox at the Local Watershed Scale: Causal Inference Insights

NASA Astrophysics Data System (ADS)

Van Gordon, M.; Groenke, A.; Larsen, L.

2017-12-01

While the existence of paradoxical rainfall-runoff and rainfall-groundwater correlations are well established in the West African Sahel, the hydrologic mechanisms involved are poorly understood. In pursuit of mechanistic explanations, we perform a causal inference analysis on hydrologic variables in three watersheds in Benin and Niger. Using an ensemble of techniques, we compute the strength of relationships between observational soil moisture, runoff, precipitation, and temperature data at seasonal and event timescales. Performing analysis over a range of time lags allows dominant time scales to emerge from the relationships between variables. By determining the time scales of hydrologic connectivity over vertical and lateral space, we show differences in the importance of overland and subsurface flow over the course of the rainy season and between watersheds. While previous work on the paradoxical hydrologic behavior in the Sahel focuses on surface processes and infiltration, our results point toward the importance of subsurface flow to rainfall-runoff relationships in these watersheds. The hypotheses generated from our ensemble approach suggest that subsequent explorations of mechanistic hydrologic processes in the region include subsurface flow. Further, this work highlights how an ensemble approach to causal analysis can reveal nuanced relationships between variables even in poorly understood hydrologic systems.

A space-time multiscale modelling of Earth's gravity field variations

NASA Astrophysics Data System (ADS)

Wang, Shuo; Panet, Isabelle; Ramillien, Guillaume; Guilloux, Frédéric

2017-04-01

The mass distribution within the Earth varies over a wide range of spatial and temporal scales, generating variations in the Earth's gravity field in space and time. These variations are monitored by satellites as the GRACE mission, with a 400 km spatial resolution and 10 days to 1 month temporal resolution. They are expressed in the form of gravity field models, often with a fixed spatial or temporal resolution. The analysis of these models allows us to study the mass transfers within the Earth system. Here, we have developed space-time multi-scale models of the gravity field, in order to optimize the estimation of gravity signals resulting from local processes at different spatial and temporal scales, and to adapt the time resolution of the model to its spatial resolution according to the satellites sampling. For that, we first build a 4D wavelet family combining spatial Poisson wavelets with temporal Haar wavelets. Then, we set-up a regularized inversion of inter-satellites gravity potential differences in a bayesian framework, to estimate the model parameters. To build the prior, we develop a spectral analysis, localized in time and space, of geophysical models of mass transport and associated gravity variations. Finally, we test our approach to the reconstruction of space-time variations of the gravity field due to hydrology. We first consider a global distribution of observations along the orbit, from a simplified synthetic hydrology signal comprising only annual variations at large spatial scales. Then, we consider a regional distribution of observations in Africa, and a larger number of spatial and temporal scales. We test the influence of an imperfect prior and discuss our results.

Multifractal analysis of geophysical time series in the urban lake of Créteil (France).

NASA Astrophysics Data System (ADS)

Mezemate, Yacine; Tchiguirinskaia, Ioulia; Bonhomme, Celine; Schertzer, Daniel; Lemaire, Bruno Jacques; Vinçon leite, Brigitte; Lovejoy, Shaun

2013-04-01

Urban water bodies take part in the environmental quality of the cities. They regulate heat, contribute to the beauty of landscape and give some space for leisure activities (aquatic sports, swimming). As they are often artificial they are only a few meters deep. It confers them some specific properties. Indeed, they are particularly sensitive to global environmental changes, including climate change, eutrophication and contamination by micro-pollutants due to the urbanization of the watershed. Monitoring their quality has become a major challenge for urban areas. The need for a tool for predicting short-term proliferation of potentially toxic phytoplankton therefore arises. In lakes, the behavior of biological and physical (temperature) fields is mainly driven by the turbulence regime in the water. Turbulence is highly non linear, nonstationary and intermittent. This is why statistical tools are needed to characterize the evolution of the fields. The knowledge of the probability distribution of all the statistical moments of a given field is necessary to fully characterize it. This possibility is offered by the multifractal analysis based on the assumption of scale invariance. To investigate the effect of space-time variability of temperature, chlorophyll and dissolved oxygen on the cyanobacteria proliferation in the urban lake of Creteil (France), a spectral analysis is first performed on each time series (or on subsamples) to have an overall estimate of their scaling behaviors. Then a multifractal analysis (Trace Moment, Double Trace Moment) estimates the statistical moments of different orders. This analysis is adapted to the specific properties of the studied time series, i. e. the presence of large scale gradients. The nonlinear behavior of the scaling functions K(q) confirms that the investigated aquatic time series are indeed multifractal and highly intermittent .The knowledge of the universal multifractal parameters is the key to calculate the different statistical moments and thus make some predictions on the fields. As a conclusion, the relationships between the fields will be highlighted with a discussion on the cross predictability of the different fields. This draws a prospective for the use of this kind of time series analysis in the field of limnology. The authors acknowledge the financial support from the R2DS-PLUMMME and Climate-KIC BlueGreenDream projects.

The Application of Structured Job Analysis Information Based on the Position Analysis Questionnaire (PAQ).

DTIC Science & Technology

Position Analysis Questionnaire ( PAQ ). This job analysis instrument consists of 187 job elements organized into six divisions. In the analysis of a job...with the PAQ the relevance of the individual elements to the job are rated using any of several rating scales such as importance, or time.

Data Streaming for Metabolomics: Accelerating Data Processing and Analysis from Days to Minutes

PubMed Central

2016-01-01

The speed and throughput of analytical platforms has been a driving force in recent years in the “omics” technologies and while great strides have been accomplished in both chromatography and mass spectrometry, data analysis times have not benefited at the same pace. Even though personal computers have become more powerful, data transfer times still represent a bottleneck in data processing because of the increasingly complex data files and studies with a greater number of samples. To meet the demand of analyzing hundreds to thousands of samples within a given experiment, we have developed a data streaming platform, XCMS Stream, which capitalizes on the acquisition time to compress and stream recently acquired data files to data processing servers, mimicking just-in-time production strategies from the manufacturing industry. The utility of this XCMS Online-based technology is demonstrated here in the analysis of T cell metabolism and other large-scale metabolomic studies. A large scale example on a 1000 sample data set demonstrated a 10 000-fold time savings, reducing data analysis time from days to minutes. Further, XCMS Stream has the capability to increase the efficiency of downstream biochemical dependent data acquisition (BDDA) analysis by initiating data conversion and data processing on subsets of data acquired, expanding its application beyond data transfer to smart preliminary data decision-making prior to full acquisition. PMID:27983788

Data streaming for metabolomics: Accelerating data processing and analysis from days to minutes

DOE PAGES

Montenegro-Burke, J. Rafael; Aisporna, Aries E.; Benton, H. Paul; ...

2016-12-16

The speed and throughput of analytical platforms has been a driving force in recent years in the “omics” technologies and while great strides have been accomplished in both chromatography and mass spectrometry, data analysis times have not benefited at the same pace. Even though personal computers have become more powerful, data transfer times still represent a bottleneck in data processing because of the increasingly complex data files and studies with a greater number of samples. To meet the demand of analyzing hundreds to thousands of samples within a given experiment, we have developed a data streaming platform, XCMS Stream, whichmore » capitalizes on the acquisition time to compress and stream recently acquired data files to data processing servers, mimicking just-in-time production strategies from the manufacturing industry. The utility of this XCMS Online-based technology is demonstrated here in the analysis of T cell metabolism and other large-scale metabolomic studies. A large scale example on a 1000 sample data set demonstrated a 10 000-fold time savings, reducing data analysis time from days to minutes. Here, XCMS Stream has the capability to increase the efficiency of downstream biochemical dependent data acquisition (BDDA) analysis by initiating data conversion and data processing on subsets of data acquired, expanding its application beyond data transfer to smart preliminary data decision-making prior to full acquisition.« less

Data Streaming for Metabolomics: Accelerating Data Processing and Analysis from Days to Minutes.

PubMed

Montenegro-Burke, J Rafael; Aisporna, Aries E; Benton, H Paul; Rinehart, Duane; Fang, Mingliang; Huan, Tao; Warth, Benedikt; Forsberg, Erica; Abe, Brian T; Ivanisevic, Julijana; Wolan, Dennis W; Teyton, Luc; Lairson, Luke; Siuzdak, Gary

2017-01-17

The speed and throughput of analytical platforms has been a driving force in recent years in the "omics" technologies and while great strides have been accomplished in both chromatography and mass spectrometry, data analysis times have not benefited at the same pace. Even though personal computers have become more powerful, data transfer times still represent a bottleneck in data processing because of the increasingly complex data files and studies with a greater number of samples. To meet the demand of analyzing hundreds to thousands of samples within a given experiment, we have developed a data streaming platform, XCMS Stream, which capitalizes on the acquisition time to compress and stream recently acquired data files to data processing servers, mimicking just-in-time production strategies from the manufacturing industry. The utility of this XCMS Online-based technology is demonstrated here in the analysis of T cell metabolism and other large-scale metabolomic studies. A large scale example on a 1000 sample data set demonstrated a 10 000-fold time savings, reducing data analysis time from days to minutes. Further, XCMS Stream has the capability to increase the efficiency of downstream biochemical dependent data acquisition (BDDA) analysis by initiating data conversion and data processing on subsets of data acquired, expanding its application beyond data transfer to smart preliminary data decision-making prior to full acquisition.

ClinicAl Evaluation of Dental Restorative Materials

DTIC Science & Technology

1989-01-01

use of an Atuarial Life Table Survival Analysis procedure. The median survival time for anterior composites was 13.5 years, as compared to 12.1 years...dental materials. For the first time in clinical biomaterials research, we used a statistical approach of Survival Analysis which utilized the... analysis has been established to assure uniformity in usage. This scale is now in use by clinical investigators throughout the country. Its use at the

Hilbert-Huang spectral analysis for characterizing the intrinsic time-scales of variability in decennial time-series of surface solar radiation

NASA Astrophysics Data System (ADS)

Bengulescu, Marc; Blanc, Philippe; Wald, Lucien

2016-04-01

An analysis of the variability of the surface solar irradiance (SSI) at different local time-scales is presented in this study. Since geophysical signals, such as long-term measurements of the SSI, are often produced by the non-linear interaction of deterministic physical processes that may also be under the influence of non-stationary external forcings, the Hilbert-Huang transform (HHT), an adaptive, noise-assisted, data-driven technique, is employed to extract locally - in time and in space - the embedded intrinsic scales at which a signal oscillates. The transform consists of two distinct steps. First, by means of the Empirical Mode Decomposition (EMD), the time-series is "de-constructed" into a finite number - often small - of zero-mean components that have distinct temporal scales of variability, termed hereinafter the Intrinsic Mode Functions (IMFs). The signal model of the components is an amplitude modulation - frequency modulation (AM - FM) one, and can also be thought of as an extension of a Fourier series having both time varying amplitude and frequency. Following the decomposition, Hilbert spectral analysis is then employed on the IMFs, yielding a time-frequency-energy representation that portrays changes in the spectral contents of the original data, with respect to time. As measurements of surface solar irradiance may possibly be contaminated by the manifestation of different type of stochastic processes (i.e. noise), the identification of real, physical processes from this background of random fluctuations is of interest. To this end, an adaptive background noise null hypothesis is assumed, based on the robust statistical properties of the EMD when applied to time-series of different classes of noise (e.g. white, red or fractional Gaussian). Since the algorithm acts as an efficient constant-Q dyadic, "wavelet-like", filter bank, the different noise inputs are decomposed into components having the same spectral shape, but that are translated to the next lower octave in the spectral domain. Thus, when the sampling step is increased, the spectral shape of IMFs cannot remain at its original position, due to the new lower Nyquist frequency, and is instead pushed toward the lower scaled frequency. Based on these features, the identification of potential signals within the data should become possible without any prior knowledge of the background noises. When applying the above outlined procedure to decennial time-series of surface solar irradiance, only the component that has an annual time-scale of variability is shown to have statistical properties that diverge from those of noise. Nevertheless, the noise-like components are not completely devoid of information, as it is found that their AM components have a non-null rank correlation coefficient with the annual mode, i.e. the background noise intensity seems to be modulated by the seasonal cycle. The findings have possible implications on the modelling and forecast of the surface solar irradiance, by discriminating its deterministic from its quasi-stochastic constituents, at distinct local time-scales.

Fractal Dimension Analysis of Transient Visual Evoked Potentials: Optimisation and Applications.

PubMed

Boon, Mei Ying; Henry, Bruce Ian; Chu, Byoung Sun; Basahi, Nour; Suttle, Catherine May; Luu, Chi; Leung, Harry; Hing, Stephen

2016-01-01

The visual evoked potential (VEP) provides a time series signal response to an external visual stimulus at the location of the visual cortex. The major VEP signal components, peak latency and amplitude, may be affected by disease processes. Additionally, the VEP contains fine detailed and non-periodic structure, of presently unclear relevance to normal function, which may be quantified using the fractal dimension. The purpose of this study is to provide a systematic investigation of the key parameters in the measurement of the fractal dimension of VEPs, to develop an optimal analysis protocol for application. VEP time series were mathematically transformed using delay time, τ, and embedding dimension, m, parameters. The fractal dimension of the transformed data was obtained from a scaling analysis based on straight line fits to the numbers of pairs of points with separation less than r versus log(r) in the transformed space. Optimal τ, m, and scaling analysis were obtained by comparing the consistency of results using different sampling frequencies. The optimised method was then piloted on samples of normal and abnormal VEPs. Consistent fractal dimension estimates were obtained using τ = 4 ms, designating the fractal dimension = D2 of the time series based on embedding dimension m = 7 (for 3606 Hz and 5000 Hz), m = 6 (for 1803 Hz) and m = 5 (for 1000Hz), and estimating D2 for each embedding dimension as the steepest slope of the linear scaling region in the plot of log(C(r)) vs log(r) provided the scaling region occurred within the middle third of the plot. Piloting revealed that fractal dimensions were higher from the sampled abnormal than normal achromatic VEPs in adults (p = 0.02). Variances of fractal dimension were higher from the abnormal than normal chromatic VEPs in children (p = 0.01). A useful analysis protocol to assess the fractal dimension of transformed VEPs has been developed.

A Matter of Time: Faster Percolator Analysis via Efficient SVM Learning for Large-Scale Proteomics.

PubMed

Halloran, John T; Rocke, David M

2018-05-04

Percolator is an important tool for greatly improving the results of a database search and subsequent downstream analysis. Using support vector machines (SVMs), Percolator recalibrates peptide-spectrum matches based on the learned decision boundary between targets and decoys. To improve analysis time for large-scale data sets, we update Percolator's SVM learning engine through software and algorithmic optimizations rather than heuristic approaches that necessitate the careful study of their impact on learned parameters across different search settings and data sets. We show that by optimizing Percolator's original learning algorithm, l 2 -SVM-MFN, large-scale SVM learning requires nearly only a third of the original runtime. Furthermore, we show that by employing the widely used Trust Region Newton (TRON) algorithm instead of l 2 -SVM-MFN, large-scale Percolator SVM learning is reduced to nearly only a fifth of the original runtime. Importantly, these speedups only affect the speed at which Percolator converges to a global solution and do not alter recalibration performance. The upgraded versions of both l 2 -SVM-MFN and TRON are optimized within the Percolator codebase for multithreaded and single-thread use and are available under Apache license at bitbucket.org/jthalloran/percolator_upgrade .

Diffuse-charge dynamics of ionic liquids in electrochemical systems.

PubMed

Zhao, Hui

2011-11-01

We employ a continuum theory of solvent-free ionic liquids accounting for both short-range electrostatic correlations and steric effects (finite ion size) [Bazant et al., Phys. Rev. Lett. 106, 046102 (2011)] to study the response of a model microelectrochemical cell to a step voltage. The model problem consists of a 1-1 symmetric ionic liquid between two parallel blocking electrodes, neglecting any transverse transport phenomena. Matched asymptotic expansions in the limit of thin double layers are applied to analyze the resulting one-dimensional equations and study the overall charge-time relation in the weakly nonlinear regime. One important conclusion is that our simple scaling analysis suggests that the length scale √(λ*(D)l*(c)) accurately characterizes the double-layer structure of ionic liquids with strong electrostatic correlations where l*(c) is the electrostatic correlation length (in contrast, the Debye screening length λ*(D) is the primary double-layer length for electrolytes) and the response time of λ(D)(*3/2)L*/(D*l(c)(1/2)) (not λ*(D)L*/D* that is the primary charging time of electrolytes) is the correct charging time scale of ionic liquids with strong electrostatic correlations where D* is the diffusivity and L* is the separation length of the cell. With these two new scales, data of both electric potential versus distance from the electrode and the total diffuse charge versus time collapse onto each individual master curve in the presence of strong electrostatic correlations. In addition, the dependance of the total diffuse charge on steric effects, short-range correlations, and driving voltages is thoroughly examined. The results from the asymptotic analysis are compared favorably with those from full numerical simulations. Finally, the absorption of excess salt by the double layer creates a depletion region outside the double layer. Such salt depletion may bring a correction to the leading order terms and break down the weakly nonlinear analysis. A criterion which justifies the weakly nonlinear analysis is verified with numerical simulations.

DEVELOPMENT AND PEER REVIEW OF TIME-TO-EFFECT MODELS FOR THE ANALYSIS OF NEUROTOXICITY AND OTHER TIME DEPENDENT DATA

EPA Science Inventory

Neurobehavioral studies pose unique challenges for dose-response modeling, including small sample size and relatively large intra-subject variation, repeated measurements over time, multiple endpoints with both continuous and ordinal scales, and time dependence of risk characteri...

Retrieving pace in vegetation growth using precipitation and soil moisture

NASA Astrophysics Data System (ADS)

Sohoulande Djebou, D. C.; Singh, V. P.

2013-12-01

The complexity of interactions between the biophysical components of the watershed increases the challenge of understanding water budget. Hence, the perspicacity of the continuum soil-vegetation-atmosphere's functionality still remains crucial for science. This study targeted the Texas Gulf watershed and evaluated the behavior of vegetation covers by coupling precipitation and soil moisture patterns. Growing season's Normalized Differential Vegetation Index NDVI for deciduous forest and grassland were used over a 23 year period as well as precipitation and soil moisture data. The role of time scales on vegetation dynamics analysis was appraised using both entropy rescaling and correlation analysis. This resulted in that soil moisture at 5 cm and 25cm are potentially more efficient to use for vegetation dynamics monitoring at finer time scale compared to precipitation. Albeit soil moisture at 5 cm and 25 cm series are highly correlated (R2>0.64), it appeared that 5 cm soil moisture series can better explain the variability of vegetation growth. A logarithmic transformation of soil moisture and precipitation data increased correlation with NDVI for the different time scales considered. Based on a monthly time scale we came out with a relationship between vegetation index and the couple soil moisture and precipitation [NDVI=a*Log(% soil moisture)+b*Log(Precipitation)+c] with R2>0.25 for each vegetation type. Further, we proposed to assess vegetation green-up using logistic regression model and transinformation entropy using the couple soil moisture and precipitation as independent variables and vegetation growth metrics (NDVI, NDVI ratio, NDVI slope) as the dependent variable. The study is still ongoing and the results will surely contribute to the knowledge in large scale vegetation monitoring. Keywords: Precipitation, soil moisture, vegetation growth, entropy Time scale, Logarithmic transformation and correlation between soil moisture and NDVI, precipitation and NDVI. The analysis is performed by combining both scenes 7 and 8 data. Schematic illustration of the two dimension transinformation entropy approach. T(P,SM;VI) stand for the transinformation contained in the couple soil moisture (SM)/precipitation (P) and explaining vegetation growth (VI).

Wavelet analysis and scaling properties of time series

NASA Astrophysics Data System (ADS)

Manimaran, P.; Panigrahi, Prasanta K.; Parikh, Jitendra C.

2005-10-01

We propose a wavelet based method for the characterization of the scaling behavior of nonstationary time series. It makes use of the built-in ability of the wavelets for capturing the trends in a data set, in variable window sizes. Discrete wavelets from the Daubechies family are used to illustrate the efficacy of this procedure. After studying binomial multifractal time series with the present and earlier approaches of detrending for comparison, we analyze the time series of averaged spin density in the 2D Ising model at the critical temperature, along with several experimental data sets possessing multifractal behavior.

Spatial and Temporal Characteristics of Insulator Contaminations Revealed by Daily Observations of Equivalent Salt Deposit Density

PubMed Central

Ruan, Ling; Han, Ge; Zhu, Zhongmin; Zhang, Miao; Gong, Wei

2015-01-01

The accurate estimation of deposits adhering on insulators is of great significance to prevent pollution flashovers which cause huge costs worldwide. Researchers have developed sensors using different technologies to monitor insulator contamination on a fine time scale. However, there is lack of analysis of these data to reveal spatial and temporal characteristics of insulator contamination, and as a result the scheduling of periodical maintenance of power facilities is highly dependent on personal experience. Owing to the deployment of novel sensors, daily Equivalent Salt Deposit Density (ESDD) observations of over two years were collected and analyzed for the first time. Results from 16 sites distributed in four regions of Hubei demonstrated that spatial heterogeneity can be seen at both the fine and coarse geographical scales, suggesting that current polluted area maps are necessary but are not sufficient conditions to guide the maintenance of power facilities. Both the local emission and the regional air pollution condition exert evident influences on deposit accumulation. A relationship between ESDD and PM10 was revealed by using regression analysis, proving that air pollution exerts influence on pollution accumulations on insulators. Moreover, the seasonality of ESDD was discovered for the first time by means of time series analysis, which could help engineers select appropriate times to clean the contamination. Besides, the trend component shows that the ESDD increases in a negative exponential fashion with the accumulation date (ESDD = a − b × exp(−time)) at a long time scale in real environments. PMID:25643058

Fast time- and frequency-domain finite-element methods for electromagnetic analysis

NASA Astrophysics Data System (ADS)

Lee, Woochan

Fast electromagnetic analysis in time and frequency domain is of critical importance to the design of integrated circuits (IC) and other advanced engineering products and systems. Many IC structures constitute a very large scale problem in modeling and simulation, the size of which also continuously grows with the advancement of the processing technology. This results in numerical problems beyond the reach of existing most powerful computational resources. Different from many other engineering problems, the structure of most ICs is special in the sense that its geometry is of Manhattan type and its dielectrics are layered. Hence, it is important to develop structure-aware algorithms that take advantage of the structure specialties to speed up the computation. In addition, among existing time-domain methods, explicit methods can avoid solving a matrix equation. However, their time step is traditionally restricted by the space step for ensuring the stability of a time-domain simulation. Therefore, making explicit time-domain methods unconditionally stable is important to accelerate the computation. In addition to time-domain methods, frequency-domain methods have suffered from an indefinite system that makes an iterative solution difficult to converge fast. The first contribution of this work is a fast time-domain finite-element algorithm for the analysis and design of very large-scale on-chip circuits. The structure specialty of on-chip circuits such as Manhattan geometry and layered permittivity is preserved in the proposed algorithm. As a result, the large-scale matrix solution encountered in the 3-D circuit analysis is turned into a simple scaling of the solution of a small 1-D matrix, which can be obtained in linear (optimal) complexity with negligible cost. Furthermore, the time step size is not sacrificed, and the total number of time steps to be simulated is also significantly reduced, thus achieving a total cost reduction in CPU time. The second contribution is a new method for making an explicit time-domain finite-element method (TDFEM) unconditionally stable for general electromagnetic analysis. In this method, for a given time step, we find the unstable modes that are the root cause of instability, and deduct them directly from the system matrix resulting from a TDFEM based analysis. As a result, an explicit TDFEM simulation is made stable for an arbitrarily large time step irrespective of the space step. The third contribution is a new method for full-wave applications from low to very high frequencies in a TDFEM based on matrix exponential. In this method, we directly deduct the eigenmodes having large eigenvalues from the system matrix, thus achieving a significantly increased time step in the matrix exponential based TDFEM. The fourth contribution is a new method for transforming the indefinite system matrix of a frequency-domain FEM to a symmetric positive definite one. We deduct non-positive definite component directly from the system matrix resulting from a frequency-domain FEM-based analysis. The resulting new representation of the finite-element operator ensures an iterative solution to converge in a small number of iterations. We then add back the non-positive definite component to synthesize the original solution with negligible cost.

The RATIO method for time-resolved Laue crystallography

PubMed Central

Coppens, Philip; Pitak, Mateusz; Gembicky, Milan; Messerschmidt, Marc; Scheins, Stephan; Benedict, Jason; Adachi, Shin-ichi; Sato, Tokushi; Nozawa, Shunsuke; Ichiyanagi, Kohei; Chollet, Matthieu; Koshihara, Shin-ya

2009-01-01

A RATIO method for analysis of intensity changes in time-resolved pump–probe Laue diffraction experiments is described. The method eliminates the need for scaling the data with a wavelength curve representing the spectral distribution of the source and removes the effect of possible anisotropic absorption. It does not require relative scaling of series of frames and removes errors due to all but very short term fluctuations in the synchrotron beam. PMID:19240334

Models of inertial range spectra of interplanetary magnetohydrodynamic turbulence

NASA Technical Reports Server (NTRS)

Zhou, YE; Matthaeus, William H.

1990-01-01

A framework based on turbulence theory is presented to develop approximations for the local turbulence effects that are required in transport models. An approach based on Kolmogoroff-style dimensional analysis is presented as well as one based on a wave-number diffusion picture. Particular attention is given to the case of MHD turbulence with arbitrary cross helicity and with arbitrary ratios of the Alfven time scale and the nonlinear time scale.

Dosage-based parameters for characterization of puff dispersion results.

PubMed

Berbekar, Eva; Harms, Frank; Leitl, Bernd

2015-01-01

A set of parameters is introduced to characterize the dispersion of puff releases based on the measured dosage. These parameters are the dosage, peak concentration, arrival time, peak time, leaving time, ascent time, descent time and duration. Dimensionless numbers for the scaling of the parameters are derived from dimensional analysis. The dimensionless numbers are tested and confirmed based on a statistically representative wind tunnel dataset. The measurements were carried out in a 1:300 scale model of the Central Business District in Oklahoma City. Additionally, the effect of the release duration on the puff parameters is investigated. Copyright © 2014 Elsevier B.V. All rights reserved.

A wavelet analysis of scaling laws and long-memory in stock market volatility

NASA Astrophysics Data System (ADS)

Vuorenmaa, Tommi A.

2005-05-01

This paper studies the time-varying behavior of scaling laws and long-memory. This is motivated by the earlier finding that in the FX markets a single scaling factor might not always be sufficient across all relevant timescales: a different region may exist for intradaily time-scales and for larger time-scales. In specific, this paper investigates (i) if different scaling regions appear in stock market as well, (ii) if the scaling factor systematically differs from the Brownian, (iii) if the scaling factor is constant in time, and (iv) if the behavior can be explained by the heterogenuity of the players in the market and/or by intraday volatility periodicity. Wavelet method is used because it delivers a multiresolution decomposition and has excellent local adaptiviness properties. As a consequence, a wavelet-based OLS method allows for consistent estimation of long-memory. Thus issues (i)-(iv) shed light on the magnitude and behavior of a long-memory parameter, as well. The data are the 5-minute volatility series of Nokia Oyj at the Helsinki Stock Exchange around the burst of the IT-bubble. Period one represents the era of "irrational exuberance" and another the time after it. The results show that different scaling regions (i.e. multiscaling) may appear in the stock markets and not only in the FX markets, the scaling factor and the long-memory parameter are systematically different from the Brownian and they do not have to be constant in time, and that the behavior can be explained for a significant part by an intraday volatility periodicity called the New York effect. This effect was magnified by the frenzy trading of short-term speculators in the bubble period. The found stronger long-memory is also attributable to irrational exuberance.

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.

Research on the fractal structure in the Chinese stock market

NASA Astrophysics Data System (ADS)

Zhuang, Xin-tian; Huang, Xiao-yuan; Sha, Yan-li

2004-02-01

Applying fractal theory, this paper probes and discusses self-similarity and scale invariance of the Chinese stock market. It analyses three kinds of scale indexes, i.e., autocorrelation index, Hurst index and the scale index on the basis of detrended fluctuation analysis (DFA) algorithm and promotes DFA into a recursive algorithm. Using the three kinds of scale indexes, we conduct empirical research on the Chinese Shanghai and Shenzhen stock markets. The results indicate that the rate of returns of the two stock markets does not obey the normal distribution. A correlation exists between the stock price indexes over time scales. The stock price indexes exhibit fractal time series. It indicates that the policy guide hidden at the back influences the characteristic of the Chinese stock market.

The Revised Child Anxiety and Depression Scale-Short Version: Scale Reduction via Exploratory Bifactor Modeling of the Broad Anxiety Factor

ERIC Educational Resources Information Center

Ebesutani, Chad; Reise, Steven P.; Chorpita, Bruce F.; Ale, Chelsea; Regan, Jennifer; Young, John; Higa-McMillan, Charmaine; Weisz, John R.

2012-01-01

Using a school-based (N = 1,060) and clinic-referred (N = 303) youth sample, the authors developed a 25-item shortened version of the Revised Child Anxiety and Depression Scale (RCADS) using Schmid-Leiman exploratory bifactor analysis to reduce client burden and administration time and thus improve the transportability characteristics of this…

A spatial length scale analysis of turbulent temperature and velocity fluctuations within and above an orchard canopy

USGS Publications Warehouse

Wang, Y.S.; Miller, D.R.; Anderson, D.E.; Cionco, R.M.; Lin, J.D.

1992-01-01

Turbulent flow within and above an almond orchard was measured with three-dimensional wind sensors and fine-wire thermocouple sensors arranged in a horizontal array. The data showed organized turbulent structures as indicated by coherent asymmetric ramp patterns in the time series traces across the sensor array. Space-time correlation analysis indicated that velocity and temperature fluctuations were significantly correlated over a transverse distance more than 4m. Integral length scales of velocity and temperature fluctuations were substantially greater in unstable conditions than those in stable conditions. The coherence spectral analysis indicated that Davenport's geometric similarity hypothesis was satisfied in the lower frequency region. From the geometric similarity hypothesis, the spatial extents of large ramp structures were also estimated with the coherence functions.

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.

Anticipating flash-floods: Multi-scale aspects of the social response

NASA Astrophysics Data System (ADS)

Lutoff, Céline; Creutin, Jean-Dominique; Ruin, Isabelle; Borga, Marco

2016-10-01

This paper aims at exploring the anticipation phase before a flash flood, corresponding to the time between the first climatic signs and the peak-flow. We focus the analysis on people's behaviors observing how they use this period to organize themselves for facing the event. The analysis is made through the definition of three specific scales: the timeliness scale, an analytical scale of anticipatory actions and the scale of human response network. Using a cross-scale and cross level analysis enables to define different phases in the anticipation period where different kind of environmental precursors are mobilized by the actors in order to make sense of the situation and adapt. Three main points deserve attention at the end: firstly, the concepts of timeliness, anticipatory actions and crisis network scales enable to understand differently what happens both physically and socially during an extreme event; secondly, analyzing the precursors shows that each level of crisis network uses different kinds of signs for estimating the situation, organizing and reacting; thirdly, there is a potential for improvement in observation on both social and physical processes at different scales, for verifying the theory of the anticipatory phases.

Analysis of the 2H-evaporator scale samples (HTF-17-56, -57)

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

Hay, M.; Coleman, C.; Diprete, D.

Savannah River National Laboratory analyzed scale samples from both the wall and cone sections of the 242-16H Evaporator prior to chemical cleaning. The samples were analyzed for uranium and plutonium isotopes required for a Nuclear Criticality Safety Assessment of the scale removal process. The analysis of the scale samples found the material to contain crystalline nitrated cancrinite and clarkeite. Samples from both the wall and cone contain depleted uranium. Uranium concentrations of 16.8 wt% 4.76 wt% were measured in the wall and cone samples, respectively. The ratio of plutonium isotopes in both samples is ~85% Pu-239 and ~15% Pu-238 bymore » mass and shows approximately the same 3.5 times higher concentration in the wall sample versus the cone sample as observed in the uranium concentrations. The mercury concentrations measured in the scale samples were higher than previously reported values. The wall sample contains 19.4 wt% mercury and the cone scale sample 11.4 wt% mercury. The results from the current scales samples show reasonable agreement with previous 242-16H Evaporator scale sample analysis; however, the uranium concentration in the current wall sample is substantially higher than previous measurements.« less

Spatiotemporal analysis of land use and land cover change in the Brazilian Amazon

PubMed Central

Li, Guiying; Moran, Emilio; Hetrick, Scott

2013-01-01

This paper provides a comparative analysis of land use and land cover (LULC) changes among three study areas with different biophysical environments in the Brazilian Amazon at multiple scales, from per-pixel, polygon, census sector, to study area. Landsat images acquired in the years of 1990/1991, 1999/2000, and 2008/2010 were used to examine LULC change trajectories with the post-classification comparison approach. A classification system composed of six classes – forest, savanna, other-vegetation (secondary succession and plantations), agro-pasture, impervious surface, and water, was designed for this study. A hierarchical-based classification method was used to classify Landsat images into thematic maps. This research shows different spatiotemporal change patterns, composition and rates among the three study areas and indicates the importance of analyzing LULC change at multiple scales. The LULC change analysis over time for entire study areas provides an overall picture of change trends, but detailed change trajectories and their spatial distributions can be better examined at a per-pixel scale. The LULC change at the polygon scale provides the information of the changes in patch sizes over time, while the LULC change at census sector scale gives new insights on how human-induced activities (e.g., urban expansion, roads, and land use history) affect LULC change patterns and rates. This research indicates the necessity to implement change detection at multiple scales for better understanding the mechanisms of LULC change patterns and rates. PMID:24127130

The error and bias of supplementing a short, arid climate, rainfall record with regional vs. global frequency analysis

NASA Astrophysics Data System (ADS)

Endreny, Theodore A.; Pashiardis, Stelios

2007-02-01

SummaryRobust and accurate estimates of rainfall frequencies are difficult to make with short, and arid-climate, rainfall records, however new regional and global methods were used to supplement such a constrained 15-34 yr record in Cyprus. The impact of supplementing rainfall frequency analysis with the regional and global approaches was measured with relative bias and root mean square error (RMSE) values. Analysis considered 42 stations with 8 time intervals (5-360 min) in four regions delineated by proximity to sea and elevation. Regional statistical algorithms found the sites passed discordancy tests of coefficient of variation, skewness and kurtosis, while heterogeneity tests revealed the regions were homogeneous to mildly heterogeneous. Rainfall depths were simulated in the regional analysis method 500 times, and then goodness of fit tests identified the best candidate distribution as the general extreme value (GEV) Type II. In the regional analysis, the method of L-moments was used to estimate location, shape, and scale parameters. In the global based analysis, the distribution was a priori prescribed as GEV Type II, a shape parameter was a priori set to 0.15, and a time interval term was constructed to use one set of parameters for all time intervals. Relative RMSE values were approximately equal at 10% for the regional and global method when regions were compared, but when time intervals were compared the global method RMSE had a parabolic-shaped time interval trend. Relative bias values were also approximately equal for both methods when regions were compared, but again a parabolic-shaped time interval trend was found for the global method. The global method relative RMSE and bias trended with time interval, which may be caused by fitting a single scale value for all time intervals.

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

DOE PAGES

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.; ...

2015-08-07

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

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

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

Equilibrium and out-of-equilibrium mechanics of living mammalian cytoplasm

NASA Astrophysics Data System (ADS)

Gupta, Satish Kumar; Guo, Ming

2017-10-01

Living cells are intrinsically non-equilibrium systems. They are driven out of equilibrium by the activity of the molecular motors and other enzymatic processes. This activity along with the ever present thermal agitation results in intracellular fluctuations inside the cytoplasm. In analogy to Brownian motion, the material property of the cytoplasm also influences the characteristics of these fluctuations. In this paper, through a combination of experimentation and theoretical analysis, we show that intracellular fluctuations are indeed due to non-thermal forces at relatively long time-scales, however, are dominated solely by thermal forces at relatively short time-scales. Thus, the cytoplasm of living mammalian cells behaves as an equilibrium material at short time-scales. The mean square displacement of these intracellular fluctuations scales inversely with the cytoplasmic shear modulus in this short time-scale equilibrium regime, and is inversely proportional to the square of the cytoplasmic shear modulus in the long time-scale out-of-equilibrium regime. Furthermore, we deploy passive microrheology based on these fluctuations to extract the mechanical property of the cytoplasm at the high-frequency regime. We show that the cytoplasm of living mammalian cells is a weak elastic gel in this regime; this is in an excellent agreement with an independent micromechanical measurement using optical tweezers.

Impact of the time scale of model sensitivity response on coupled model parameter estimation

NASA Astrophysics Data System (ADS)

Liu, Chang; Zhang, Shaoqing; Li, Shan; Liu, Zhengyu

2017-11-01

That a model has sensitivity responses to parameter uncertainties is a key concept in implementing model parameter estimation using filtering theory and methodology. Depending on the nature of associated physics and characteristic variability of the fluid in a coupled system, the response time scales of a model to parameters can be different, from hourly to decadal. Unlike state estimation, where the update frequency is usually linked with observational frequency, the update frequency for parameter estimation must be associated with the time scale of the model sensitivity response to the parameter being estimated. Here, with a simple coupled model, the impact of model sensitivity response time scales on coupled model parameter estimation is studied. The model includes characteristic synoptic to decadal scales by coupling a long-term varying deep ocean with a slow-varying upper ocean forced by a chaotic atmosphere. Results show that, using the update frequency determined by the model sensitivity response time scale, both the reliability and quality of parameter estimation can be improved significantly, and thus the estimated parameters make the model more consistent with the observation. These simple model results provide a guideline for when real observations are used to optimize the parameters in a coupled general circulation model for improving climate analysis and prediction initialization.

Multifractal cross-correlation effects in two-variable time series of complex network vertex observables

NASA Astrophysics Data System (ADS)

OświÈ©cimka, Paweł; Livi, Lorenzo; DroŻdŻ, Stanisław

2016-10-01

We investigate the scaling of the cross-correlations calculated for two-variable time series containing vertex properties in the context of complex networks. Time series of such observables are obtained by means of stationary, unbiased random walks. We consider three vertex properties that provide, respectively, short-, medium-, and long-range information regarding the topological role of vertices in a given network. In order to reveal the relation between these quantities, we applied the multifractal cross-correlation analysis technique, which provides information about the nonlinear effects in coupling of time series. We show that the considered network models are characterized by unique multifractal properties of the cross-correlation. In particular, it is possible to distinguish between Erdös-Rényi, Barabási-Albert, and Watts-Strogatz networks on the basis of fractal cross-correlation. Moreover, the analysis of protein contact networks reveals characteristics shared with both scale-free and small-world models.

Mouse Activity across Time Scales: Fractal Scenarios

PubMed Central

Lima, G. Z. dos Santos; Lobão-Soares, B.; do Nascimento, G. C.; França, Arthur S. C.; Muratori, L.; Ribeiro, S.; Corso, G.

2014-01-01

In this work we devise a classification of mouse activity patterns based on accelerometer data using Detrended Fluctuation Analysis. We use two characteristic mouse behavioural states as benchmarks in this study: waking in free activity and slow-wave sleep (SWS). In both situations we find roughly the same pattern: for short time intervals we observe high correlation in activity - a typical 1/f complex pattern - while for large time intervals there is anti-correlation. High correlation of short intervals ( to : waking state and to : SWS) is related to highly coordinated muscle activity. In the waking state we associate high correlation both to muscle activity and to mouse stereotyped movements (grooming, waking, etc.). On the other side, the observed anti-correlation over large time scales ( to : waking state and to : SWS) during SWS appears related to a feedback autonomic response. The transition from correlated regime at short scales to an anti-correlated regime at large scales during SWS is given by the respiratory cycle interval, while during the waking state this transition occurs at the time scale corresponding to the duration of the stereotyped mouse movements. Furthermore, we find that the waking state is characterized by longer time scales than SWS and by a softer transition from correlation to anti-correlation. Moreover, this soft transition in the waking state encompass a behavioural time scale window that gives rise to a multifractal pattern. We believe that the observed multifractality in mouse activity is formed by the integration of several stereotyped movements each one with a characteristic time correlation. Finally, we compare scaling properties of body acceleration fluctuation time series during sleep and wake periods for healthy mice. Interestingly, differences between sleep and wake in the scaling exponents are comparable to previous works regarding human heartbeat. Complementarily, the nature of these sleep-wake dynamics could lead to a better understanding of neuroautonomic regulation mechanisms. PMID:25275515

Ultrascalable Techniques Applied to the Global Intelligence Community Information Awareness Common Operating Picture (IA COP)

DTIC Science & Technology

2005-11-01

more random. Autonomous systems can exchange entropy statistics for packet streams with no confidentiality concerns, potentially enabling timely and... analysis began with simulation results, which were validated by analysis of actual data from an Autonomous System (AS). A scale-free network is one...traffic—for example, time series of flux at given nodes and mean path length Outputs the time series from any node queried Calculates

Multi-time-scale hydroclimate dynamics of a regional watershed and links to large-scale atmospheric circulation: Application to the Seine river catchment, France

NASA Astrophysics Data System (ADS)

Massei, N.; Dieppois, B.; Hannah, D. M.; Lavers, D. A.; Fossa, M.; Laignel, B.; Debret, M.

2017-03-01

In the present context of global changes, considerable efforts have been deployed by the hydrological scientific community to improve our understanding of the impacts of climate fluctuations on water resources. Both observational and modeling studies have been extensively employed to characterize hydrological changes and trends, assess the impact of climate variability or provide future scenarios of water resources. In the aim of a better understanding of hydrological changes, it is of crucial importance to determine how and to what extent trends and long-term oscillations detectable in hydrological variables are linked to global climate oscillations. In this work, we develop an approach associating correlation between large and local scales, empirical statistical downscaling and wavelet multiresolution decomposition of monthly precipitation and streamflow over the Seine river watershed, and the North Atlantic sea level pressure (SLP) in order to gain additional insights on the atmospheric patterns associated with the regional hydrology. We hypothesized that: (i) atmospheric patterns may change according to the different temporal wavelengths defining the variability of the signals; and (ii) definition of those hydrological/circulation relationships for each temporal wavelength may improve the determination of large-scale predictors of local variations. The results showed that the links between large and local scales were not necessarily constant according to time-scale (i.e. for the different frequencies characterizing the signals), resulting in changing spatial patterns across scales. This was then taken into account by developing an empirical statistical downscaling (ESD) modeling approach, which integrated discrete wavelet multiresolution analysis for reconstructing monthly regional hydrometeorological processes (predictand: precipitation and streamflow on the Seine river catchment) based on a large-scale predictor (SLP over the Euro-Atlantic sector). This approach basically consisted in three steps: 1 - decomposing large-scale climate and hydrological signals (SLP field, precipitation or streamflow) using discrete wavelet multiresolution analysis, 2 - generating a statistical downscaling model per time-scale, 3 - summing up all scale-dependent models in order to obtain a final reconstruction of the predictand. The results obtained revealed a significant improvement of the reconstructions for both precipitation and streamflow when using the multiresolution ESD model instead of basic ESD. In particular, the multiresolution ESD model handled very well the significant changes in variance through time observed in either precipitation or streamflow. For instance, the post-1980 period, which had been characterized by particularly high amplitudes in interannual-to-interdecadal variability associated with alternating flood and extremely low-flow/drought periods (e.g., winter/spring 2001, summer 2003), could not be reconstructed without integrating wavelet multiresolution analysis into the model. In accordance with previous studies, the wavelet components detected in SLP, precipitation and streamflow on interannual to interdecadal time-scales could be interpreted in terms of influence of the Gulf-Stream oceanic front on atmospheric circulation.

Field scale spatiotemporal analysis of surface soil moisture for evaluating point-scale in situ networks

USDA-ARS?s Scientific Manuscript database

Soil moisture is an intrinsic state variable that varies considerably in space and time. From a hydrologic viewpoint, soil moisture controls runoff, infiltration, storage and drainage. Soil moisture determines the partitioning of the incoming radiation between latent and sensible heat fluxes. Althou...

Evaluation and error apportionment of an ensemble of atmospheric chemistry transport modeling systems: multivariable temporal and spatial breakdown

EPA Science Inventory

Through the comparison of several regional-scale chemistry transport modelling systems that simulate meteorology and air quality over the European and American continents, this study aims at i) apportioning the error to the responsible processes using time-scale analysis, ii) hel...

Exclusively Visual Analysis of Classroom Group Interactions

ERIC Educational Resources Information Center

Tucker, Laura; Scherr, Rachel E.; Zickler, Todd; Mazur, Eric

2016-01-01

Large-scale audiovisual data that measure group learning are time consuming to collect and analyze. As an initial step towards scaling qualitative classroom observation, we qualitatively coded classroom video using an established coding scheme with and without its audio cues. We find that interrater reliability is as high when using visual data…

A High-Resolution Record of Holocene Climate Variability from a Western Canadian Coastal Inlet

NASA Astrophysics Data System (ADS)

Dallimore, A.; Thomson, R. E.; Enkin, R. J.; Kulikov, E. A.; Bertram, M. A.; Wright, C. A.; Southon, J. R.; Barrie, J. V.; Baker, J.; Pienitz, R.; Calvert, S. E.; Chang, A. S.; Pedersen, T. F.

2004-12-01

Conditions within the Pacific Ocean have a major effect on the climate of northwestern North America. High resolution records of present and past northeast Pacific climate are revealed in our multi-disciplinary study of annually laminated marine sediments from anoxic coastal inlets of British Columbia. Past climate conditions for the entire Holocene are recorded in the sediment record contained in a 40 meter, annually laminated marine sediment core taken in Effingham Inlet, on the west coast of Vancouver Island, British Columbia, from the French ship the Marion Dufresne, as part of the international IMAGES program. By combining our eight year continuous instrument record of modern coastal ocean dynamics and climate with high-resolution analysis of depositional processes, we have been able to develop proxy measurements of past climatic and oceanographic changes on annual to millennial time scales. Results indicate that regional climate has oscillated on a variety of time scales throughout the Holocene. At times, climatic change has been dramatically rapid. We are also developing digital methods for statistical time-series analyses of physical sediment properties through the Holocene in order to obtain a more objective quantitative approach for detecting cyclicity in our data. Results of the time series analysis of lamination thickness reveals statistically significant spectral peaks of climate scale variability at established decadal to century time scales. These in turn may be related to solar cycles and quasi-cyclical ocean processes such as the Pacific Decadal Oscillation. However, the annually laminated time series are periodically interrupted by massive mud intervals which are related to bottom currents and at times paleo-seismic events, illustrating the need for a full understanding of modern oceanographic and sedimentation processes, so an accurate proxy record of past climate can be established.

Characterization of the infrared/X-ray subsecond variability for the black hole transient GX 339-4

NASA Astrophysics Data System (ADS)

Vincentelli, F. M.; Casella, P.; Maccarone, T. J.; Uttley, P.; Gandhi, P.; Belloni, T.; De Marco, B.; Russell, D. M.; Stella, L.; O'Brien, K.

2018-07-01

We present a detailed analysis of the X-ray/IR fast variability of the Black-Hole Transient GX 339-4 during its low/hard state in 2008 August. Thanks to simultaneous high time resolution observations made with the VLT and RXTE, we performed the first characterization of the subsecond variability in the near-infrared band - and of its correlation with the X-rays - for a low-mass X-ray binary, using both time- and frequency-domain techniques. We found a power-law correlation between the X-ray and infrared fluxes when measured on time-scales of 16 s, with a marginally variable slope, steeper than the one found on time-scales of days at similar flux levels. We suggest the variable slope - if confirmed - could be due to the infrared flux being a non-constant combination of both optically thin and optically thick synchrotron emission from the jet, as a result of a variable self-absorption break. From cross spectral analysis, we found an approximately constant infrared time lag of ≈0.1 s, and a very high coherence of ˜90 per cent on time-scales of tens of seconds, slowly decreasing towards higher frequencies. Finally, we report on the first detection of a linear rms-flux relation in the emission from a low-mass X-ray binary jet, on time-scales where little correlation is found between the X-rays and the jet emission itself. This suggests that either the inflow variations and jet IR emission are coupled by a non-linear or time-variable transform, or that the IR rms-flux relation is not transferred from the inflow to the jet, but is an intrinsic property of emission processes in the jet.

Analysis and Prediction of Sea Ice Evolution using Koopman Mode Decomposition Techniques

DTIC Science & Technology

Koopman Mode Analysis was newly applied to southern hemisphere sea ice concentration data. The resulting Koopman modes from analysis of both the...southern and northern hemisphere sea ice concentration data shows geographical regions where sea ice coverage has decreased over multiyear time scales.

Power Grid Data Analysis with R and Hadoop

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

Hafen, Ryan P.; Gibson, Tara D.; Kleese van Dam, Kerstin

This book chapter presents an approach to analysis of large-scale time-series sensor information based on our experience with power grid data. We use the R-Hadoop Integrated Programming Environment (RHIPE) to analyze a 2TB data set and present code and results for this analysis.

Benefit-Cost Analysis of Foot-and-Mouth Disease Vaccination at the Farm-Level in South Vietnam.

PubMed

Truong, Dinh Bao; Goutard, Flavie Luce; Bertagnoli, Stéphane; Delabouglise, Alexis; Grosbois, Vladimir; Peyre, Marisa

2018-01-01

This study aimed to analyze the financial impact of foot-and-mouth disease (FMD) outbreaks in cattle at the farm-level and the benefit-cost ratio (BCR) of biannual vaccination strategy to prevent and eradicate FMD for cattle in South Vietnam. Production data were collected from 49 small-scale dairy farms, 15 large-scale dairy farms, and 249 beef farms of Long An and Tay Ninh province using a questionaire. Financial data of FMD impacts were collected using participatory tools in 37 villages of Long An province. The net present value, i.e., the difference between the benefits (additional revenue and saved costs) and costs (additional costs and revenue foregone), of FMD vaccination in large-scale dairy farms was 2.8 times higher than in small-scale dairy farms and 20 times higher than in beef farms. The BCR of FMD vaccination over 1 year in large-scale dairy farms, small-scale dairy farms, and beef farms were 11.6 [95% confidence interval (95% CI) 6.42-16.45], 9.93 (95% CI 3.45-16.47), and 3.02 (95% CI 0.76-7.19), respectively. The sensitivity analysis showed that varying the vaccination cost had more effect on the BCR of cattle vaccination than varying the market price. This benefit-cost analysis of biannual vaccination strategy showed that investment in FMD prevention can be financially profitable, and therefore sustainable, for dairy farmers. For beef cattle, it is less certain that vaccination is profitable. Additional benefit-cost analysis study of vaccination strategies at the national-level would be required to evaluate and adapt the national strategy to achieve eradication of this disease in Vietnam.

Multi-Scale Modeling of Liquid Phase Sintering Affected by Gravity: Preliminary Analysis

NASA Technical Reports Server (NTRS)

Olevsky, Eugene; German, Randall M.

2012-01-01

A multi-scale simulation concept taking into account impact of gravity on liquid phase sintering is described. The gravity influence can be included at both the micro- and macro-scales. At the micro-scale, the diffusion mass-transport is directionally modified in the framework of kinetic Monte-Carlo simulations to include the impact of gravity. The micro-scale simulations can provide the values of the constitutive parameters for macroscopic sintering simulations. At the macro-scale, we are attempting to embed a continuum model of sintering into a finite-element framework that includes the gravity forces and substrate friction. If successful, the finite elements analysis will enable predictions relevant to space-based processing, including size and shape and property predictions. Model experiments are underway to support the models via extraction of viscosity moduli versus composition, particle size, heating rate, temperature and time.

An analysis of neural receptive field plasticity by point process adaptive filtering

PubMed Central

Brown, Emery N.; Nguyen, David P.; Frank, Loren M.; Wilson, Matthew A.; Solo, Victor

2001-01-01

Neural receptive fields are plastic: with experience, neurons in many brain regions change their spiking responses to relevant stimuli. Analysis of receptive field plasticity from experimental measurements is crucial for understanding how neural systems adapt their representations of relevant biological information. Current analysis methods using histogram estimates of spike rate functions in nonoverlapping temporal windows do not track the evolution of receptive field plasticity on a fine time scale. Adaptive signal processing is an established engineering paradigm for estimating time-varying system parameters from experimental measurements. We present an adaptive filter algorithm for tracking neural receptive field plasticity based on point process models of spike train activity. We derive an instantaneous steepest descent algorithm by using as the criterion function the instantaneous log likelihood of a point process spike train model. We apply the point process adaptive filter algorithm in a study of spatial (place) receptive field properties of simulated and actual spike train data from rat CA1 hippocampal neurons. A stability analysis of the algorithm is sketched in the Appendix. The adaptive algorithm can update the place field parameter estimates on a millisecond time scale. It reliably tracked the migration, changes in scale, and changes in maximum firing rate characteristic of hippocampal place fields in a rat running on a linear track. Point process adaptive filtering offers an analytic method for studying the dynamics of neural receptive fields. PMID:11593043

Detrended Fluctuation Analysis: A Scale-Free View on Neuronal Oscillations

PubMed Central

Hardstone, Richard; Poil, Simon-Shlomo; Schiavone, Giuseppina; Jansen, Rick; Nikulin, Vadim V.; Mansvelder, Huibert D.; Linkenkaer-Hansen, Klaus

2012-01-01

Recent years of research have shown that the complex temporal structure of ongoing oscillations is scale-free and characterized by long-range temporal correlations. Detrended fluctuation analysis (DFA) has proven particularly useful, revealing that genetic variation, normal development, or disease can lead to differences in the scale-free amplitude modulation of oscillations. Furthermore, amplitude dynamics is remarkably independent of the time-averaged oscillation power, indicating that the DFA provides unique insights into the functional organization of neuronal systems. To facilitate understanding and encourage wider use of scaling analysis of neuronal oscillations, we provide a pedagogical explanation of the DFA algorithm and its underlying theory. Practical advice on applying DFA to oscillations is supported by MATLAB scripts from the Neurophysiological Biomarker Toolbox (NBT) and links to the NBT tutorial website http://www.nbtwiki.net/. Finally, we provide a brief overview of insights derived from the application of DFA to ongoing oscillations in health and disease, and discuss the putative relevance of criticality for understanding the mechanism underlying scale-free modulation of oscillations. PMID:23226132

The Contribution of Human Factors in Military System Development: Methodological Considerations

DTIC Science & Technology

1980-07-01

Risk/Uncertainty Analysis - Project Scoring - Utility Scales - Relevance Tree Techniques (Reverse Factor Analysis) 2. Computer Simulation Simulation...effectiveness of mathematical models for R&D project selection. Management Science, April 1973, 18. 6-43 .1~ *.-. Souder, W.E. h scoring methodology for...per some interval PROFICIENCY test scores (written) RADIATION radiation effects aircrew performance on radiation environments REACTION TIME 1) (time

Surface electromyography analysis of blepharoptosis correction by transconjunctival incisions.

PubMed

Tu, Lung-Chen; Wu, Ming-Chya; Chu, Hsueh-Liang; Chiang, Yi-Pin; Kuo, Chih-Lin; Li, Hsing-Yuan; Chang, Chia-Ching

2016-06-01

Upper eyelid movement depends on the antagonistic actions of orbicularis oculi muscle and levator aponeurosis. Blepharoptosis is an abnormal drooping of upper eyelid margin with the eye in primary position of gaze. Transconjunctival incisions for upper eyelid ptosis correction have been a well-developed technique. Conventional prognosis however depends on clinical observations and lacks of quantitatively analysis for the eyelid muscle controlling. This study examines the possibility of using the assessments of temporal correlation in surface electromyography (SEMG) as a quantitative description for the change of muscle controlling after operation. Eyelid SEMG was measured from patients with blepharoptosis preoperatively and postoperatively, as well as, for comparative study, from young and aged normal subjects. The data were analyzed using the detrended fluctuation analysis method. The results show that the temporal correlation of the SEMG signals can be characterized by two indices associated with the correlation properties in short and long time scales demarcated at 3ms, corresponding to the time scale of neural response. Aging causes degradation of the correlation properties at both time scales, and patient group likely possess more serious correlation degradation in long-time regime which was improved moderately by the ptosis corrections. We propose that the temporal correlation in SEMG signals may be regarded as an indicator for evaluating the performance of eyelid muscle controlling in postoperative recovery. Copyright © 2016 Elsevier Ltd. All rights reserved.

A multi-scale model for geared transmission aero-thermodynamics

NASA Astrophysics Data System (ADS)

McIntyre, Sean M.

A multi-scale, multi-physics computational tool for the simulation of high-per- formance gearbox aero-thermodynamics was developed and applied to equilibrium and pathological loss-of-lubrication performance simulation. The physical processes at play in these systems include multiphase compressible ow of the air and lubricant within the gearbox, meshing kinematics and tribology, as well as heat transfer by conduction, and free and forced convection. These physics are coupled across their representative space and time scales in the computational framework developed in this dissertation. These scales span eight orders of magnitude, from the thermal response of the full gearbox O(100 m; 10 2 s), through effects at the tooth passage time scale O(10-2 m; 10-4 s), down to tribological effects on the meshing gear teeth O(10-6 m; 10-6 s). Direct numerical simulation of these coupled physics and scales is intractable. Accordingly, a scale-segregated simulation strategy was developed by partitioning and treating the contributing physical mechanisms as sub-problems, each with associated space and time scales, and appropriate coupling mechanisms. These are: (1) the long time scale thermal response of the system, (2) the multiphase (air, droplets, and film) aerodynamic flow and convective heat transfer within the gearbox, (3) the high-frequency, time-periodic thermal effects of gear tooth heating while in mesh and its subsequent cooling through the rest of rotation, (4) meshing effects including tribology and contact mechanics. The overarching goal of this dissertation was to develop software and analysis procedures for gearbox loss-of-lubrication performance. To accommodate these four physical effects and their coupling, each is treated in the CFD code as a sub problem. These physics modules are coupled algorithmically. Specifically, the high- frequency conduction analysis derives its local heat transfer coefficient and near-wall air temperature boundary conditions from a quasi-steady cyclic-symmetric simulation of the internal flow. This high-frequency conduction solution is coupled directly with a model for the meshing friction, developed by a collaborator, which was adapted for use in a finite-volume CFD code. The local surface heat flux on solid surfaces is calculated by time-averaging the heat flux in the high-frequency analysis. This serves as a fixed-flux boundary condition in the long time scale conduction module. The temperature distribution from this long time scale heat transfer calculation serves as a boundary condition for the internal convection simulation, and as the initial condition for the high-frequency heat transfer module. Using this multi-scale model, simulations were performed for equilibrium and loss-of-lubrication operation of the NASA Glenn Research Center test stand. Results were compared with experimental measurements. In addition to the multi-scale model itself, several other specific contributions were made. Eulerian models for droplets and wall-films were developed and im- plemented in the CFD code. A novel approach to retaining liquid film on the solid surfaces, and strategies for its mass exchange with droplets, were developed and verified. Models for interfacial transfer between droplets and wall-film were implemented, and include the effects of droplet deposition, splashing, bouncing, as well as film breakup. These models were validated against airfoil data. To mitigate the observed slow convergence of CFD simulations of the enclosed aerodynamic flows within gearboxes, Fourier stability analysis was applied to the SIMPLE-C fractional-step algorithm. From this, recommendations to accelerate the convergence rate through enhanced pressure-velocity coupling were made. These were shown to be effective. A fast-running finite-volume reduced-order-model of the gearbox aero-thermo- dynamics was developed, and coupled with the tribology model to investigate the sensitivity of loss-of-lubrication predictions to various model and physical param- eters. This sensitivity study was instrumental in guiding efforts toward improving the accuracy of the multi-scale model without undue increase in computational cost. In addition, the reduced-order model is now used extensively by a collaborator in tribology model development and testing. Experimental measurements of high-speed gear windage in partially and fully- shrouded configurations were performed to supplement the paucity of available validation data. This measurement program provided measurements of windage loss for a gear of design-relevant size and operating speed, as well as guidance for increasing the accuracy of future measurements.

Electrochemical Ionization and Analyte Charging in the Array of Micromachined UltraSonic Electrospray (AMUSE) Ion Source

PubMed Central

Forbes, Thomas P.; Degertekin, F. Levent; Fedorov, Andrei G.

2010-01-01

Electrochemistry and ion transport in a planar array of mechanically-driven, droplet-based ion sources are investigated using an approximate time scale analysis and in-depth computational simulations. The ion source is modeled as a controlled-current electrolytic cell, in which the piezoelectric transducer electrode, which mechanically drives the charged droplet generation using ultrasonic atomization, also acts as the oxidizing/corroding anode (positive mode). The interplay between advective and diffusive ion transport of electrochemically generated ions is analyzed as a function of the transducer duty cycle and electrode location. A time scale analysis of the relative importance of advective vs. diffusive ion transport provides valuable insight into optimality, from the ionization prospective, of alternative design and operation modes of the ion source operation. A computational model based on the solution of time-averaged, quasi-steady advection-diffusion equations for electroactive species transport is used to substantiate the conclusions of the time scale analysis. The results show that electrochemical ion generation at the piezoelectric transducer electrodes located at the back-side of the ion source reservoir results in poor ionization efficiency due to insufficient time for the charged analyte to diffuse away from the electrode surface to the ejection location, especially at near 100% duty cycle operation. Reducing the duty cycle of droplet/analyte ejection increases the analyte residence time and, in turn, improves ionization efficiency, but at an expense of the reduced device throughput. For applications where this is undesirable, i.e., multiplexed and disposable device configurations, an alternative electrode location is incorporated. By moving the charging electrode to the nozzle surface, the diffusion length scale is greatly reduced, drastically improving ionization efficiency. The ionization efficiency of all operating conditions considered is expressed as a function of the dimensionless Peclet number, which defines the relative effect of advection as compared to diffusion. This analysis is general enough to elucidate an important role of electrochemistry in ionization efficiency of any arrayed ion sources, be they mechanically-driven or electrosprays, and is vital for determining optimal design and operation conditions. PMID:20607111

An Analysis of Model Scale Data Transformation to Full Scale Flight Using Chevron Nozzles

NASA Technical Reports Server (NTRS)

Brown, Clifford; Bridges, James

2003-01-01

Ground-based model scale aeroacoustic data is frequently used to predict the results of flight tests while saving time and money. The value of a model scale test is therefore dependent on how well the data can be transformed to the full scale conditions. In the spring of 2000, a model scale test was conducted to prove the value of chevron nozzles as a noise reduction device for turbojet applications. The chevron nozzle reduced noise by 2 EPNdB at an engine pressure ratio of 2.3 compared to that of the standard conic nozzle. This result led to a full scale flyover test in the spring of 2001 to verify these results. The flyover test confirmed the 2 EPNdB reduction predicted by the model scale test one year earlier. However, further analysis of the data revealed that the spectra and directivity, both on an OASPL and PNL basis, do not agree in either shape or absolute level. This paper explores these differences in an effort to improve the data transformation from model scale to full scale.

The science of visual analysis at extreme scale

NASA Astrophysics Data System (ADS)

Nowell, Lucy T.

2011-01-01

Driven by market forces and spanning the full spectrum of computational devices, computer architectures are changing in ways that present tremendous opportunities and challenges for data analysis and visual analytic technologies. Leadership-class high performance computing system will have as many as a million cores by 2020 and support 10 billion-way concurrency, while laptop computers are expected to have as many as 1,000 cores by 2015. At the same time, data of all types are increasing exponentially and automated analytic methods are essential for all disciplines. Many existing analytic technologies do not scale to make full use of current platforms and fewer still are likely to scale to the systems that will be operational by the end of this decade. Furthermore, on the new architectures and for data at extreme scales, validating the accuracy and effectiveness of analytic methods, including visual analysis, will be increasingly important.

Backpropagation and ordered derivatives in the time scales calculus.

PubMed

Seiffertt, John; Wunsch, Donald C

2010-08-01

Backpropagation is the most widely used neural network learning technique. It is based on the mathematical notion of an ordered derivative. In this paper, we present a formulation of ordered derivatives and the backpropagation training algorithm using the important emerging area of mathematics known as the time scales calculus. This calculus, with its potential for application to a wide variety of inter-disciplinary problems, is becoming a key area of mathematics. It is capable of unifying continuous and discrete analysis within one coherent theoretical framework. Using this calculus, we present here a generalization of backpropagation which is appropriate for cases beyond the specifically continuous or discrete. We develop a new multivariate chain rule of this calculus, define ordered derivatives on time scales, prove a key theorem about them, and derive the backpropagation weight update equations for a feedforward multilayer neural network architecture. By drawing together the time scales calculus and the area of neural network learning, we present the first connection of two major fields of research.

Liquidity crises on different time scales

NASA Astrophysics Data System (ADS)

Corradi, Francesco; Zaccaria, Andrea; Pietronero, Luciano

2015-12-01

We present an empirical analysis of the microstructure of financial markets and, in particular, of the static and dynamic properties of liquidity. We find that on relatively large time scales (15 min) large price fluctuations are connected to the failure of the subtle mechanism of compensation between the flows of market and limit orders: in other words, the missed revelation of the latent order book breaks the dynamical equilibrium between the flows, triggering the large price jumps. On smaller time scales (30 s), instead, the static depletion of the limit order book is an indicator of an intrinsic fragility of the system, which is related to a strongly nonlinear enhancement of the response. In order to quantify this phenomenon we introduce a measure of the liquidity imbalance present in the book and we show that it is correlated to both the sign and the magnitude of the next price movement. These findings provide a quantitative definition of the effective liquidity, which proves to be strongly dependent on the considered time scales.

Liquidity crises on different time scales.

PubMed

Corradi, Francesco; Zaccaria, Andrea; Pietronero, Luciano

2015-12-01

We present an empirical analysis of the microstructure of financial markets and, in particular, of the static and dynamic properties of liquidity. We find that on relatively large time scales (15 min) large price fluctuations are connected to the failure of the subtle mechanism of compensation between the flows of market and limit orders: in other words, the missed revelation of the latent order book breaks the dynamical equilibrium between the flows, triggering the large price jumps. On smaller time scales (30 s), instead, the static depletion of the limit order book is an indicator of an intrinsic fragility of the system, which is related to a strongly nonlinear enhancement of the response. In order to quantify this phenomenon we introduce a measure of the liquidity imbalance present in the book and we show that it is correlated to both the sign and the magnitude of the next price movement. These findings provide a quantitative definition of the effective liquidity, which proves to be strongly dependent on the considered time scales.

Choice with frequently changing food rates and food ratios.

PubMed

Baum, William M; Davison, Michael

2014-03-01

In studies of operant choice, when one schedule of a concurrent pair is varied while the other is held constant, the constancy of the constant schedule may exert discriminative control over performance. In our earlier experiments, schedules varied reciprocally across components within sessions, so that while food ratio varied food rate remained constant. In the present experiment, we held one variable-interval (VI) schedule constant while varying the concurrent VI schedule within sessions. We studied five conditions, each with a different constant left VI schedule. On the right key, seven different VI schedules were presented in seven different unsignaled components. We analyzed performances at several different time scales. At the longest time scale, across conditions, behavior ratios varied with food ratios as would be expected from the generalized matching law. At shorter time scales, effects due to holding the left VI constant became more and more apparent, the shorter the time scale. In choice relations across components, preference for the left key leveled off as the right key became leaner. Interfood choice approximated strict matching for the varied right key, whereas interfood choice hardly varied at all for the constant left key. At the shortest time scale, visit patterns differed for the left and right keys. Much evidence indicated the development of a fix-and-sample pattern. In sum, the procedural difference made a large difference to performance, except for choice at the longest time scale and the fix-and-sample pattern at the shortest time scale. © Society for the Experimental Analysis of Behavior.

Causality and correlations between BSE and NYSE indexes: A Janus faced relationship

NASA Astrophysics Data System (ADS)

Neeraj; Panigrahi, Prasanta K.

2017-09-01

We study the multi-scale temporal correlations and causality connections between the New York Stock Exchange (NYSE) and Bombay Stock Exchange (BSE) monthly average closing price indexes for a period of 300 months, encompassing the time period of the liberalisation of the Indian economy and its gradual global exposure. In multi-scale analysis; clearly identifiable 1, 2 and 3 year non-stationary periodic modulations in NYSE and BSE have been observed, with NYSE commensurating changes in BSE at 3 years scale. Interestingly, at one year time scale, the two exchanges are phase locked only during the turbulent times, while at the scale of three year, in-phase nature is observed for a much longer time frame. The two year time period, having characteristics of both one and three year variations, acts as the transition regime. The normalised NYSE's stock value is found to Granger cause those of BSE, with a time lag of 9 months. Surprisingly, observed Granger causality of high frequency variations reveals BSE behaviour getting reflected in the NYSE index fluctuations, after a smaller time lag. This Janus faced relationship, shows that smaller stock exchanges may provide a natural setting for simulating market fluctuations of much bigger exchanges. This possibly arises due to the fact that high frequency fluctuations form an universal part of the financial time series, and are expected to exhibit similar characteristics in open market economies.

Continent-scale global change attribution in European birds - combining annual and decadal time scales.

PubMed

Jørgensen, Peter Søgaard; Böhning-Gaese, Katrin; Thorup, Kasper; Tøttrup, Anders P; Chylarecki, Przemysław; Jiguet, Frédéric; Lehikoinen, Aleksi; Noble, David G; Reif, Jiri; Schmid, Hans; van Turnhout, Chris; Burfield, Ian J; Foppen, Ruud; Voříšek, Petr; van Strien, Arco; Gregory, Richard D; Rahbek, Carsten

2016-02-01

Species attributes are commonly used to infer impacts of environmental change on multiyear species trends, e.g. decadal changes in population size. However, by themselves attributes are of limited value in global change attribution since they do not measure the changing environment. A broader foundation for attributing species responses to global change may be achieved by complementing an attributes-based approach by one estimating the relationship between repeated measures of organismal and environmental changes over short time scales. To assess the benefit of this multiscale perspective, we investigate the recent impact of multiple environmental changes on European farmland birds, here focusing on climate change and land use change. We analyze more than 800 time series from 18 countries spanning the past two decades. Analysis of long-term population growth rates documents simultaneous responses that can be attributed to both climate change and land-use change, including long-term increases in populations of hot-dwelling species and declines in long-distance migrants and farmland specialists. In contrast, analysis of annual growth rates yield novel insights into the potential mechanisms driving long-term climate induced change. In particular, we find that birds are affected by winter, spring, and summer conditions depending on the distinct breeding phenology that corresponds to their migratory strategy. Birds in general benefit from higher temperatures or higher primary productivity early on or in the peak of the breeding season with the largest effect sizes observed in cooler parts of species' climatic ranges. Our results document the potential of combining time scales and integrating both species attributes and environmental variables for global change attribution. We suggest such an approach will be of general use when high-resolution time series are available in large-scale biodiversity surveys. © 2015 John Wiley & Sons Ltd.

Scaling Analysis of Tide Gauge Data from the Atlantic, Gulf of Mexico, and Pacific Coasts of the United States

NASA Astrophysics Data System (ADS)

Barton, C. C.; Smigelski, J. R.; Tebbens, S. F.

2008-12-01

Most coastal regions are subject to inundation due to many periodic and non-periodic inputs including for example: diurnal and semi diurnal tides, storms, tsunamis, and global sea level change. Tide guage data provide a frequently sampled long term record of fluctuations in water level. A power-spectral-density analysis of tidal gauge data is used to quantify persistence (degree of internal correlation over various time intervals) in terms of the scaling exponent β and to identify temporal changes in persistence. The stations are located at different proximity to the open ocean, including bays, harbors, and channels. The datasets are from the NOAA CO-OPS Verified Hourly Station Datum. The length of the data sets ranges from 3 years to 101 years. The hourly data sets are decimated to one record every four hours. All data sets analyzed show three distinct regions of persistence with two inflection points at approximately one day and five days. For times less than one day, the scaling exponent ranges between 0 < β < 2.6. For the time interval 1 to 5 days, the scaling exponent ranges between 1.1 < β < 2.1. For times greater than 5 days, the scaling exponent ranges between 0.4 < β < 0.9. Persistence generally decreases as period increases but is stable between the inflection points. At Duck, NC, long term persistence in the tide gauge signal is 0.6 as compared to 0.9 for the biweekly shoreline position signal over twenty years, suggesting a strong correlation between the two and the possibility of using tide gauge data to quantify nearby shoreline mobility over similar time intervals.

A behavioral-level HDL description of SFQ logic circuits for quantitative performance analysis of large-scale SFQ digital systems

NASA Astrophysics Data System (ADS)

Matsuzaki, F.; Yoshikawa, N.; Tanaka, M.; Fujimaki, A.; Takai, Y.

2003-10-01

Recently many single flux quantum (SFQ) logic circuits containing several thousands of Josephson junctions have been designed successfully by using digital domain simulation based on the hard ware description language (HDL). In the present HDL-based design of SFQ circuits, a structure-level HDL description has been used, where circuits are made up of basic gate cells. However, in order to analyze large-scale SFQ digital systems, such as a microprocessor, more higher-level circuit abstraction is necessary to reduce the circuit simulation time. In this paper we have investigated the way to describe functionality of the large-scale SFQ digital circuits by a behavior-level HDL description. In this method, the functionality and the timing of the circuit block is defined directly by describing their behavior by the HDL. Using this method, we can dramatically reduce the simulation time of large-scale SFQ digital circuits.

On the transition towards slow manifold in shallow-water and 3D Euler equations in a rotating frame

NASA Technical Reports Server (NTRS)

Mahalov, A.

1994-01-01

The long-time, asymptotic state of rotating homogeneous shallow-water equations is investigated. Our analysis is based on long-time averaged rotating shallow-water equations describing interactions of large-scale, horizontal, two-dimensional motions with surface inertial-gravity waves field for a shallow, uniformly rotating fluid layer. These equations are obtained in two steps: first by introducing a Poincare/Kelvin linear propagator directly into classical shallow-water equations, then by averaging. The averaged equations describe interaction of wave fields with large-scale motions on time scales long compared to the time scale 1/f(sub o) introduced by rotation (f(sub o)/2-angular velocity of background rotation). The present analysis is similar to the one presented by Waleffe (1991) for 3D Euler equations in a rotating frame. However, since three-wave interactions in rotating shallow-water equations are forbidden, the final equations describing the asymptotic state are simplified considerably. Special emphasis is given to a new conservation law found in the asymptotic state and decoupling of the dynamics of the divergence free part of the velocity field. The possible rising of a decoupled dynamics in the asymptotic state is also investigated for homogeneous turbulence subjected to a background rotation. In our analysis we use long-time expansion, where the velocity field is decomposed into the 'slow manifold' part (the manifold which is unaffected by the linear 'rapid' effects of rotation or the inertial waves) and a formal 3D disturbance. We derive the physical space version of the long-time averaged equations and consider an invariant, basis-free derivation. This formulation can be used to generalize Waleffe's (1991) helical decomposition to viscous inhomogeneous flows (e.g. problems in cylindrical geometry with no-slip boundary conditions on the cylinder surface and homogeneous in the vertical direction).

Time tracking and interaction of energy-eddies at different scales

NASA Astrophysics Data System (ADS)

Cardesa, Jose I.; Vela-Martin, Alberto; Jimenez, Javier

2016-11-01

We study the energy cascade through coherent structures obtained in time-resolved simulations of incompressible, statistically steady isotropic turbulence. The structures are defined as geometrically connected regions of the flow with high kinetic energy. We compute the latter by band-pass filtering the velocity field around a scale r. We analyse the dynamics of structures extracted with different r, which are a proxy for eddies containing energy at those r. We find that the size of these "energy-eddies" scales with r, while their lifetime scales with the local eddy-turnover r 2 / 3ɛ - 1 / 3 , where ɛ is the energy dissipation averaged over all space and time. Furthermore, a statistical analysis over the lives of the eddies shows a slight predominance of the splitting over the merging process. When we isolate the eddies which do not interact with other eddies of the same scale, we observe a parent-child dependence by which, on average, structures are born at scale r during the decaying part of the life of a structure at scale r' > r . The energy-eddy at r' lives in the same region of space as that at r. Finally, we investigate how interactions between eddies at the same scale are echoed across other scales. Funded by the ERC project Coturb.

Quantifying distinct associations on different temporal scales: comparison of DCCA and Pearson methods

NASA Astrophysics Data System (ADS)

Piao, Lin; Fu, Zuntao

2016-11-01

Cross-correlation between pairs of variables takes multi-time scale characteristic, and it can be totally different on different time scales (changing from positive correlation to negative one), e.g., the associations between mean air temperature and relative humidity over regions to the east of Taihang mountain in China. Therefore, how to correctly unveil these correlations on different time scales is really of great importance since we actually do not know if the correlation varies with scales in advance. Here, we compare two methods, i.e. Detrended Cross-Correlation Analysis (DCCA for short) and Pearson correlation, in quantifying scale-dependent correlations directly to raw observed records and artificially generated sequences with known cross-correlation features. Studies show that 1) DCCA related methods can indeed quantify scale-dependent correlations, but not Pearson method; 2) the correlation features from DCCA related methods are robust to contaminated noises, however, the results from Pearson method are sensitive to noise; 3) the scale-dependent correlation results from DCCA related methods are robust to the amplitude ratio between slow and fast components, while Pearson method may be sensitive to the amplitude ratio. All these features indicate that DCCA related methods take some advantages in correctly quantifying scale-dependent correlations, which results from different physical processes.

Quantifying distinct associations on different temporal scales: comparison of DCCA and Pearson methods.

PubMed

Piao, Lin; Fu, Zuntao

2016-11-09

Cross-correlation between pairs of variables takes multi-time scale characteristic, and it can be totally different on different time scales (changing from positive correlation to negative one), e.g., the associations between mean air temperature and relative humidity over regions to the east of Taihang mountain in China. Therefore, how to correctly unveil these correlations on different time scales is really of great importance since we actually do not know if the correlation varies with scales in advance. Here, we compare two methods, i.e. Detrended Cross-Correlation Analysis (DCCA for short) and Pearson correlation, in quantifying scale-dependent correlations directly to raw observed records and artificially generated sequences with known cross-correlation features. Studies show that 1) DCCA related methods can indeed quantify scale-dependent correlations, but not Pearson method; 2) the correlation features from DCCA related methods are robust to contaminated noises, however, the results from Pearson method are sensitive to noise; 3) the scale-dependent correlation results from DCCA related methods are robust to the amplitude ratio between slow and fast components, while Pearson method may be sensitive to the amplitude ratio. All these features indicate that DCCA related methods take some advantages in correctly quantifying scale-dependent correlations, which results from different physical processes.

Factorial invariance and stability of the Effort-Reward Imbalance Scales: a longitudinal analysis of two samples with different time lags.

PubMed

de Jonge, Jan; van der Linden, Sjaak; Schaufeli, Wilmar; Peter, Richard; Siegrist, Johannes

2008-01-01

Key measures of Siegrist's (1996) Effort-Reward Imbalance (ERI) Model (i.e., efforts, rewards, and overcommitment) were psychometrically tested. To study change in organizational interventions, knowledge about the type of change underlying the instruments used is needed. Next to assessing baseline factorial validity and reliability, the factorial stability over time - known as alpha-beta-gamma change - of the ERI scales was examined. Psychometrics were tested among 383 and 267 healthcare workers from two Dutch panel surveys with different time lags. Baseline results favored a five-factor model (i.e., efforts, esteem rewards, financial/career-related aspects, job security, and overcommitment) over and above a three-factor solution (i.e., efforts, composite rewards, and overcommitment). Considering changes as a whole, particularly the factor loadings of the three ERI scales were not equal over time. Findings suggest in general that moderate changes in the ERI factor structure did not affect the interpretation of mean changes over time. Occupational health researchers utilizing the ERI scales can feel confident that self-reported changes are more likely to be due to factors other than structural change of the ERI scales over time, which has important implications for evaluating job stress and health interventions.

Scaling properties of foreign exchange volatility

NASA Astrophysics Data System (ADS)

Gençay, Ramazan; Selçuk, Faruk; Whitcher, Brandon

2001-01-01

In this paper, we investigate the scaling properties of foreign exchange volatility. Our methodology is based on a wavelet multi-scaling approach which decomposes the variance of a time series and the covariance between two time series on a scale by scale basis through the application of a discrete wavelet transformation. It is shown that foreign exchange rate volatilities follow different scaling laws at different horizons. Particularly, there is a smaller degree of persistence in intra-day volatility as compared to volatility at one day and higher scales. Therefore, a common practice in the risk management industry to convert risk measures calculated at shorter horizons into longer horizons through a global scaling parameter may not be appropriate. This paper also demonstrates that correlation between the foreign exchange volatilities is the lowest at the intra-day scales but exhibits a gradual increase up to a daily scale. The correlation coefficient stabilizes at scales one day and higher. Therefore, the benefit of currency diversification is the greatest at the intra-day scales and diminishes gradually at higher scales (lower frequencies). The wavelet cross-correlation analysis also indicates that the association between two volatilities is stronger at lower frequencies.

Bi-scale analysis of multitemporal land cover fractions for wetland vegetation mapping

NASA Astrophysics Data System (ADS)

Michishita, Ryo; Jiang, Zhiben; Gong, Peng; Xu, Bing

2012-08-01

Land cover fractions (LCFs) derived through spectral mixture analysis are useful in understanding sub-pixel information. However, few studies have been conducted on the analysis of time-series LCFs. Although multi-scale comparisons of spectral index, hard classification, and land surface temperature images have received attention, rarely have these approaches been applied to LCFs. This study compared the LCFs derived through Multiple Endmember Spectral Mixture Analysis (MESMA) using the time-series Landsat Thematic Mapper (TM) and Terra Moderate Resolution Imaging Spectroradiometer (MODIS) data acquired in the Poyang Lake area, China between 2004 and 2005. Specifically, we aimed to: (1) propose an approach for optimal endmember (EM) selection in time-series MESMA; (2) understand the trends in time-series LCFs derived from the TM and MODIS data; and (3) examine the trends in the correlation between the bi-scale LCFs derived from the time-series TM and MODIS data. Our results indicated: (1) the EM spectra chosen according to the proposed hierarchical three-step approach (overall, seasonal, and individual) accurately modeled the both the TM and MODIS images; (2) green vegetation (GV) and NPV/soil/impervious surface (N/S/I) classes followed sine curve trends in the overall area, while the two water classes displayed the water level change pattern in the areas primarily covered with wetland vegetation; and (3) GV, N/S/I, and bright water classes indicated a moderately high agreement between the TM and MODIS LCFs in the whole area (adjusted R2 ⩾ 0.6). However, low levels of correlations were found in the areas primarily dominated by wetland vegetation for all land cover classes.

Influence of Sub-Daily Variation on Multi-Fractal Detrended Fluctuation Analysis of Wind Speed Time Series

PubMed Central

Li, Weinan; Kong, Yanjun; Cong, Xiangyu

2016-01-01

Using multi-fractal detrended fluctuation analysis (MF-DFA), the scaling features of wind speed time series (WSTS) could be explored. In this paper, we discuss the influence of sub-daily variation, which is a natural feature of wind, in MF-DFA of WSTS. First, the choice of the lower bound of the segment length, a significant parameter of MF-DFA, was studied. The results of expanding the lower bound into sub-daily scope shows that an abrupt declination and discrepancy of scaling exponents is caused by the inability to keep the whole diel process of wind in one single segment. Additionally, the specific value, which is effected by the sub-daily feature of local meteo-climatic, might be different. Second, the intra-day temporal order of wind was shuffled to determine the impact of diel variation on scaling exponents of MF-DFA. The results illustrate that disregarding diel variation leads to errors in scaling. We propose that during the MF-DFA of WSTS, the segment length should be longer than 1 day and the diel variation of wind should be maintained to avoid abnormal phenomena and discrepancy in scaling exponents. PMID:26741491

Image Analysis for Facility Siting: a Comparison of Lowand High-altitude Image Interpretability for Land Use/land Cover Mapping

NASA Technical Reports Server (NTRS)

Borella, H. M.; Estes, J. E.; Ezra, C. E.; Scepan, J.; Tinney, L. R.

1982-01-01

For two test sites in Pennsylvania the interpretability of commercially acquired low-altitude and existing high-altitude aerial photography are documented in terms of time, costs, and accuracy for Anderson Level II land use/land cover mapping. Information extracted from the imagery is to be used in the evaluation process for siting energy facilities. Land use/land cover maps were drawn at 1:24,000 scale using commercially flown color infrared photography obtained from the United States Geological Surveys' EROS Data Center. Detailed accuracy assessment of the maps generated by manual image analysis was accomplished employing a stratified unaligned adequate class representation. Both 'area-weighted' and 'by-class' accuracies were documented and field-verified. A discrepancy map was also drawn to illustrate differences in classifications between the two map scales. Results show that the 1:24,000 scale map set was more accurate (99% to 94% area-weighted) than the 1:62,500 scale set, especially when sampled by class (96% to 66%). The 1:24,000 scale maps were also more time-consuming and costly to produce, due mainly to higher image acquisition costs.

A randomised controlled cross-over trial of aerobic training versus Qigong in advanced Parkinson's disease.

PubMed

Burini, D; Farabollini, B; Iacucci, S; Rimatori, C; Riccardi, G; Capecci, M; Provinciali, L; Ceravolo, M G

2006-09-01

To investigate the effects of an aerobic training in subjects with Parkinson's disease (PD) as compared to a medical Chinese exercise (Qigong). randomized controlled trial with a cross over design. PD out-patients referred to a Neurorehabilitation facility for the management of motor disability. 26 PD patients in Hoehn and Yahr stage II to III under stable medication were randomly allocated to either Group AT1+QG2 (receiving 20 aerobic training sessions followed by 20 ''Qigong'' group sessions with 2 month interval between the interventions), or Group QG1+AT2 (performing the same treatments with an inverted sequence). clinical effects of treatment were sought through the Unified Parkinson's Disease Rating Scale (UPDRS), Brown's Disability Scale (B'DS), six-Minute Walking Test (6MWT), Borg scale for breathlessness, Beck Depression Inventory (BDI) and Parkinson's Disease Questionnaire-39 items (PDQ-39). A spirometry test and maximum cardiopulmonary exercise test (CPET) were also performed to determine the pulmonary function, the metabolic and cardio-respiratory requests at rest and under exercise. All measures were taken immediately before and at the completion of each treatment phase. The statistical analysis focusing on the evolution of motor disability and quality of life revealed a significant interaction effect between group and time for the 6MWT (time x group effect: F: 5.4 P=0.002) and the Borg scale (time x group effect: F: 4.2 P=0.009). Post hoc analysis showed a significant increase in 6MWT and a larger decrease in Borg score after aerobic training within each subgroup, whereas no significant changes were observed during Qigong. No significant changes over time were detected through the analysis of UPDRS, B'DS, BDI and PDQ-39 scores. The analysis of cardiorespiratory parameters showed significant interaction effects between group and time for the Double Productpeak (time x group effect: F: 7.7 P=0.0003), the VO(2peak) (time x group effect: F: 4.8 P=0.007), and the VO(2)/kg ratio (time x group effect: F: 4.3 P=0.009), owing to their decrease after aerobic training to an extent that was never observed after Qigong treatment. Aerobic training exerts a significant impact on the ability of moderately disabled PD patients to cope with exercise, although it does not improve their self-sufficiency and quality of life.

Multiscale recurrence analysis of spatio-temporal data

NASA Astrophysics Data System (ADS)

Riedl, M.; Marwan, N.; Kurths, J.

2015-12-01

The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.

Multiscale recurrence analysis of spatio-temporal data.

PubMed

Riedl, M; Marwan, N; Kurths, J

2015-12-01

The description and analysis of spatio-temporal dynamics is a crucial task in many scientific disciplines. In this work, we propose a method which uses the mapogram as a similarity measure between spatially distributed data instances at different time points. The resulting similarity values of the pairwise comparison are used to construct a recurrence plot in order to benefit from established tools of recurrence quantification analysis and recurrence network analysis. In contrast to other recurrence tools for this purpose, the mapogram approach allows the specific focus on different spatial scales that can be used in a multi-scale analysis of spatio-temporal dynamics. We illustrate this approach by application on mixed dynamics, such as traveling parallel wave fronts with additive noise, as well as more complicate examples, pseudo-random numbers and coupled map lattices with a semi-logistic mapping rule. Especially the complicate examples show the usefulness of the multi-scale consideration in order to take spatial pattern of different scales and with different rhythms into account. So, this mapogram approach promises new insights in problems of climatology, ecology, or medicine.

Long-term, high-frequency water quality monitoring in an agricultural catchment: insights from spectral analysis

NASA Astrophysics Data System (ADS)

Aubert, Alice; Kirchner, James; Faucheux, Mikael; Merot, Philippe; Gascuel-Odoux, Chantal

2013-04-01

The choice of sampling frequency is a key issue in the design and operation of environmental observatories. The choice of sampling frequency creates a spectral window (or temporal filter) that highlights some timescales and processes, and de-emphasizes others (1). New online measurement technologies can monitor surface water quality almost continuously, allowing the creation of very rich time series. The question of how best to analyze such detailed temporal datasets is an important issue in environmental monitoring. In the present work, we studied water quality data from the AgrHys long-term hydrological observatory (located at Kervidy-Naizin, Western France) sampled at daily and 20-minute time scales. Manual sampling has provided 12 years of daily measurements of nitrate, dissolved organic carbon (DOC), chloride and sulfate (2), and 3 years of daily measurements of about 30 other solutes. In addition, a UV-spectrometry probe (Spectrolyser) provides one year of 20-minute measurements for nitrate and DOC. Spectral analysis of the daily water quality time series reveals that our intensively farmed catchment exhibits universal 1/f scaling (power spectrum slope of -1) for a large number of solutes, confirming and extending the earlier discovery of universal 1/f scaling in the relatively pristine Plynlimon catchment (3). 1/f time series confound conventional methods for assessing the statistical significance of trends. Indeed, conventional methods assume that there is a clear separation of scales between the signal (the trend line) and the noise (the scatter around the line). This is not true for 1/f noise, since it overestimates the occurrence of significant trends. Our results raise the possibility that 1/f scaling is widespread in water quality time series, thus posing fundamental challenges to water quality trend analysis. Power spectra of the 20-minute nitrate and DOC time series show 1/f scaling at frequencies below 1/day, consistent with the longer-term daily measurements. At higher frequencies, however, the spectra steepen to a slope of -2, indicating that at sub-daily time scales the concentration time series become relatively smooth. However, at time scales shorter than 2-3 hours, the spectra flatten to a slope near zero (white noise), reflecting analytical noise in the measurement probe. This result demonstrates that measuring water quality dynamics at high frequencies also requires high measurement precision, because as measurements are taken closer and closer together in time, the real-world differences that must be measured between adjacent measurements become smaller and smaller. Our results highlight the importance of quantifying the spectral properties of analytical noise in environmental measurements, to identify frequency ranges where measurements could be dominated by analytical noise instead of real-world signals. 1. Kirchner, J.W., Feng, X., Neal, C., Robson, A.J., 2004. The fine structure of water-quality dynamics: the (high-frequency) wave of the future. Hydrological Processes, 18(7): 1353-1359 2. Aubert, A.H. et al., 2012. The chemical signature of a livestock farming catchment: synthesis from a high-frequency multi-element long term monitoring. HESSD, 9(8): 9715 - 9741 3. Kirchner, J.W. and Neal, C., 2013. Universal fractal scaling in water quality dynamics across the periodic table. Manuscript in review.

Application of Open Source Technologies for Oceanographic Data Analysis

NASA Astrophysics Data System (ADS)

Huang, T.; Gangl, M.; Quach, N. T.; Wilson, B. D.; Chang, G.; Armstrong, E. M.; Chin, T. M.; Greguska, F.

2015-12-01

NEXUS is a data-intensive analysis solution developed with a new approach for handling science data that enables large-scale data analysis by leveraging open source technologies such as Apache Cassandra, Apache Spark, Apache Solr, and Webification. NEXUS has been selected to provide on-the-fly time-series and histogram generation for the Soil Moisture Active Passive (SMAP) mission for Level 2 and Level 3 Active, Passive, and Active Passive products. It also provides an on-the-fly data subsetting capability. NEXUS is designed to scale horizontally, enabling it to handle massive amounts of data in parallel. It takes a new approach on managing time and geo-referenced array data by dividing data artifacts into chunks and stores them in an industry-standard, horizontally scaled NoSQL database. This approach enables the development of scalable data analysis services that can infuse and leverage the elastic computing infrastructure of the Cloud. It is equipped with a high-performance geospatial and indexed data search solution, coupled with a high-performance data Webification solution free from file I/O bottlenecks, as well as a high-performance, in-memory data analysis engine. In this talk, we will focus on the recently funded AIST 2014 project by using NEXUS as the core for oceanographic anomaly detection service and web portal. We call it, OceanXtremes

Effects of forcing time scale on the simulated turbulent flows and turbulent collision statistics of inertial particles

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

Rosa, B., E-mail: bogdan.rosa@imgw.pl; Parishani, H.; Department of Earth System Science, University of California, Irvine, California 92697-3100

2015-01-15

In this paper, we study systematically the effects of forcing time scale in the large-scale stochastic forcing scheme of Eswaran and Pope [“An examination of forcing in direct numerical simulations of turbulence,” Comput. Fluids 16, 257 (1988)] on the simulated flow structures and statistics of forced turbulence. Using direct numerical simulations, we find that the forcing time scale affects the flow dissipation rate and flow Reynolds number. Other flow statistics can be predicted using the altered flow dissipation rate and flow Reynolds number, except when the forcing time scale is made unrealistically large to yield a Taylor microscale flow Reynoldsmore » number of 30 and less. We then study the effects of forcing time scale on the kinematic collision statistics of inertial particles. We show that the radial distribution function and the radial relative velocity may depend on the forcing time scale when it becomes comparable to the eddy turnover time. This dependence, however, can be largely explained in terms of altered flow Reynolds number and the changing range of flow length scales present in the turbulent flow. We argue that removing this dependence is important when studying the Reynolds number dependence of the turbulent collision statistics. The results are also compared to those based on a deterministic forcing scheme to better understand the role of large-scale forcing, relative to that of the small-scale turbulence, on turbulent collision of inertial particles. To further elucidate the correlation between the altered flow structures and dynamics of inertial particles, a conditional analysis has been performed, showing that the regions of higher collision rate of inertial particles are well correlated with the regions of lower vorticity. Regions of higher concentration of pairs at contact are found to be highly correlated with the region of high energy dissipation rate.« less

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.

Choice of time-scale in Cox's model analysis of epidemiologic cohort data: a simulation study.

PubMed

Thiébaut, Anne C M; Bénichou, Jacques

2004-12-30

Cox's regression model is widely used for assessing associations between potential risk factors and disease occurrence in epidemiologic cohort studies. Although age is often a strong determinant of disease risk, authors have frequently used time-on-study instead of age as the time-scale, as for clinical trials. Unless the baseline hazard is an exponential function of age, this approach can yield different estimates of relative hazards than using age as the time-scale, even when age is adjusted for. We performed a simulation study in order to investigate the existence and magnitude of bias for different degrees of association between age and the covariate of interest. Age to disease onset was generated from exponential, Weibull or piecewise Weibull distributions, and both fixed and time-dependent dichotomous covariates were considered. We observed no bias upon using age as the time-scale. Upon using time-on-study, we verified the absence of bias for exponentially distributed age to disease onset. For non-exponential distributions, we found that bias could occur even when the covariate of interest was independent from age. It could be severe in case of substantial association with age, especially with time-dependent covariates. These findings were illustrated on data from a cohort of 84,329 French women followed prospectively for breast cancer occurrence. In view of our results, we strongly recommend not using time-on-study as the time-scale for analysing epidemiologic cohort data. 2004 John Wiley & Sons, Ltd.

A rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures

NASA Astrophysics Data System (ADS)

Kossieris, Panagiotis; Makropoulos, Christos; Onof, Christian; Koutsoyiannis, Demetris

2018-01-01

Many hydrological applications, such as flood studies, require the use of long rainfall data at fine time scales varying from daily down to 1 min time step. However, in the real world there is limited availability of data at sub-hourly scales. To cope with this issue, stochastic disaggregation techniques are typically employed to produce possible, statistically consistent, rainfall events that aggregate up to the field data collected at coarser scales. A methodology for the stochastic disaggregation of rainfall at fine time scales was recently introduced, combining the Bartlett-Lewis process to generate rainfall events along with adjusting procedures to modify the lower-level variables (i.e., hourly) so as to be consistent with the higher-level one (i.e., daily). In the present paper, we extend the aforementioned scheme, initially designed and tested for the disaggregation of daily rainfall into hourly depths, for any sub-hourly time scale. In addition, we take advantage of the recent developments in Poisson-cluster processes incorporating in the methodology a Bartlett-Lewis model variant that introduces dependence between cell intensity and duration in order to capture the variability of rainfall at sub-hourly time scales. The disaggregation scheme is implemented in an R package, named HyetosMinute, to support disaggregation from daily down to 1-min time scale. The applicability of the methodology was assessed on a 5-min rainfall records collected in Bochum, Germany, comparing the performance of the above mentioned model variant against the original Bartlett-Lewis process (non-random with 5 parameters). The analysis shows that the disaggregation process reproduces adequately the most important statistical characteristics of rainfall at wide range of time scales, while the introduction of the model with dependent intensity-duration results in a better performance in terms of skewness, rainfall extremes and dry proportions.

Near-Surface Flow Fields Deduced Using Correlation Tracking and Time-Distance Analysis

NASA Technical Reports Server (NTRS)

DeRosa, Marc; Duvall, T. L., Jr.; Toomre, Juri

1999-01-01

Near-photospheric flow fields on the Sun are deduced using two independent methods applied to the same time series of velocity images observed by SOI-MDI on SOHO. Differences in travel times between f modes entering and leaving each pixel measured using time-distance helioseismology are used to determine sites of supergranular outflows. Alternatively, correlation tracking analysis of mesogranular scales of motion applied to the same time series is used to deduce the near-surface flow field. These two approaches provide the means to assess the patterns and evolution of horizontal flows on supergranular scales even near disk center, which is not feasible with direct line-of-sight Doppler measurements. We find that the locations of the supergranular outflows seen in flow fields generated from correlation tracking coincide well with the locations of the outflows determined from the time-distance analysis, with a mean correlation coefficient after smoothing of bar-r(sub s) = 0.840. Near-surface velocity field measurements can used to study the evolution of the supergranular network, as merging and splitting events are observed to occur in these images. The data consist of one 2048-minute time series of high-resolution (0.6" pixels) line-of-sight velocity images taken by MDI on 1997 January 16-18 at a cadence of one minute.

Simulation and scaling analysis of a spherical particle-laden blast wave

NASA Astrophysics Data System (ADS)

Ling, Y.; Balachandar, S.

2018-02-01

A spherical particle-laden blast wave, generated by a sudden release of a sphere of compressed gas-particle mixture, is investigated by numerical simulation. The present problem is a multiphase extension of the classic finite-source spherical blast-wave problem. The gas-particle flow can be fully determined by the initial radius of the spherical mixture and the properties of gas and particles. In many applications, the key dimensionless parameters, such as the initial pressure and density ratios between the compressed gas and the ambient air, can vary over a wide range. Parametric studies are thus performed to investigate the effects of these parameters on the characteristic time and spatial scales of the particle-laden blast wave, such as the maximum radius the contact discontinuity can reach and the time when the particle front crosses the contact discontinuity. A scaling analysis is conducted to establish a scaling relation between the characteristic scales and the controlling parameters. A length scale that incorporates the initial pressure ratio is proposed, which is able to approximately collapse the simulation results for the gas flow for a wide range of initial pressure ratios. This indicates that an approximate similarity solution for a spherical blast wave exists, which is independent of the initial pressure ratio. The approximate scaling is also valid for the particle front if the particles are small and closely follow the surrounding gas.

Simulation and scaling analysis of a spherical particle-laden blast wave

NASA Astrophysics Data System (ADS)

Ling, Y.; Balachandar, S.

2018-05-01

A spherical particle-laden blast wave, generated by a sudden release of a sphere of compressed gas-particle mixture, is investigated by numerical simulation. The present problem is a multiphase extension of the classic finite-source spherical blast-wave problem. The gas-particle flow can be fully determined by the initial radius of the spherical mixture and the properties of gas and particles. In many applications, the key dimensionless parameters, such as the initial pressure and density ratios between the compressed gas and the ambient air, can vary over a wide range. Parametric studies are thus performed to investigate the effects of these parameters on the characteristic time and spatial scales of the particle-laden blast wave, such as the maximum radius the contact discontinuity can reach and the time when the particle front crosses the contact discontinuity. A scaling analysis is conducted to establish a scaling relation between the characteristic scales and the controlling parameters. A length scale that incorporates the initial pressure ratio is proposed, which is able to approximately collapse the simulation results for the gas flow for a wide range of initial pressure ratios. This indicates that an approximate similarity solution for a spherical blast wave exists, which is independent of the initial pressure ratio. The approximate scaling is also valid for the particle front if the particles are small and closely follow the surrounding gas.

Computational singular perturbation analysis of stochastic chemical systems with stiffness

DOE PAGES

Wang, Lijin; Han, Xiaoying; Cao, Yanzhao; ...

2017-01-25

Computational singular perturbation (CSP) is a useful method for analysis, reduction, and time integration of stiff ordinary differential equation systems. It has found dominant utility, in particular, in chemical reaction systems with a large range of time scales at continuum and deterministic level. On the other hand, CSP is not directly applicable to chemical reaction systems at micro or meso-scale, where stochasticity plays an non-negligible role and thus has to be taken into account. In this work we develop a novel stochastic computational singular perturbation (SCSP) analysis and time integration framework, and associated algorithm, that can be used to notmore » only construct accurately and efficiently the numerical solutions to stiff stochastic chemical reaction systems, but also analyze the dynamics of the reduced stochastic reaction systems. Furthermore, the algorithm is illustrated by an application to a benchmark stochastic differential equation model, and numerical experiments are carried out to demonstrate the effectiveness of the construction.« less

WarpIV: In situ visualization and analysis of ion accelerator simulations

DOE PAGES

Rubel, Oliver; Loring, Burlen; Vay, Jean -Luc; ...

2016-05-09

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analyticsmore » to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.« less

Forecasting of magnitude and duration of currency crises based on the analysis of distortions of fractal scaling in exchange rate fluctuations

NASA Astrophysics Data System (ADS)

Uritskaya, Olga Y.

2005-05-01

Results of fractal stability analysis of daily exchange rate fluctuations of more than 30 floating currencies for a 10-year period are presented. It is shown for the first time that small- and large-scale dynamical instabilities of national monetary systems correlate with deviations of the detrended fluctuation analysis (DFA) exponent from the value 1.5 predicted by the efficient market hypothesis. The observed dependence is used for classification of long-term stability of floating exchange rates as well as for revealing various forms of distortion of stable currency dynamics prior to large-scale crises. A normal range of DFA exponents consistent with crisis-free long-term exchange rate fluctuations is determined, and several typical scenarios of unstable currency dynamics with DFA exponents fluctuating beyond the normal range are identified. It is shown that monetary crashes are usually preceded by prolonged periods of abnormal (decreased or increased) DFA exponent, with the after-crash exponent tending to the value 1.5 indicating a more reliable exchange rate dynamics. Statistically significant regression relations (R=0.99, p<0.01) between duration and magnitude of currency crises and the degree of distortion of monofractal patterns of exchange rate dynamics are found. It is demonstrated that the parameters of these relations characterizing small- and large-scale crises are nearly equal, which implies a common instability mechanism underlying these events. The obtained dependences have been used as a basic ingredient of a forecasting technique which provided correct in-sample predictions of monetary crisis magnitude and duration over various time scales. The developed technique can be recommended for real-time monitoring of dynamical stability of floating exchange rate systems and creating advanced early-warning-system models for currency crisis prevention.

A novel scale for measuring mixed states in bipolar disorder.

PubMed

Cavanagh, Jonathan; Schwannauer, Matthias; Power, Mick; Goodwin, Guy M

2009-01-01

Conventional descriptions of bipolar disorder tend to treat the mixed state as something of an afterthought. There is no scale that specifically measures the phenomena of the mixed state. This study aimed to test a novel scale for mixed state in a clinical and community population of bipolar patients. The scale included clinically relevant symptoms of both mania and depression in a bivariate scale. Recovered respondents were asked to recall their last manic episode. The scale allowed endorsement of one or more of the manic and depressive symptoms. Internal consistency analyses were carried out using Cronbach alpha. Factor analysis was carried out using a standard Principal Components Analysis followed by Varimax Rotation. A confirmatory factor analytic method was used to validate the scale structure in a representative clinical sample. The reliability analysis gave a Cronbach alpha value of 0.950, with a range of corrected-item-total-scale correlations from 0.546 (weight change) to 0.830 (mood). The factor analysis revealed a two-factor solution for the manic and depressed items which accounted for 61.2% of the variance in the data. Factor 1 represented physical activity, verbal activity, thought processes and mood. Factor 2 represented eating habits, weight change, passage of time and pain sensitivity. This novel scale appears to capture the key features of mixed states. The two-factor solution fits well with previous models of bipolar disorder and concurs with the view that mixed states may be more than the sum of their parts.

Some dynamical aspects of interacting quintessence model

NASA Astrophysics Data System (ADS)

Choudhury, Binayak S.; Mondal, Himadri Shekhar; Chatterjee, Devosmita

2018-04-01

In this paper, we consider a particular form of coupling, namely B=σ (\\dot{ρ _m}-\\dot{ρ _φ }) in spatially flat (k=0) Friedmann-Lemaitre-Robertson-Walker (FLRW) space-time. We perform phase-space analysis for this interacting quintessence (dark energy) and dark matter model for different numerical values of parameters. We also show the phase-space analysis for the `best-fit Universe' or concordance model. In our analysis, we observe the existence of late-time scaling attractors.

Dimension reduction and multiscaling law through source extraction

NASA Astrophysics Data System (ADS)

Capobianco, Enrico

2003-04-01

Through the empirical analysis of financial return generating processes one may find features that are common to other research fields, such as internet data from network traffic, physiological studies about human heart beat, speech and sleep recorded time series, geophysics signals, just to mention well-known cases of study. In particular, long range dependence, intermittency, heteroscedasticity are clearly appearing, and consequently power laws and multi-scaling behavior result typical signatures of either the spectral or the time correlation diagnostics. We study these features and the dynamics underlying financial volatility, which can respectively be detected and inferred from high frequency realizations of stock index returns, and show that they vary according to the resolution levels used for both the analysis and the synthesis of the available information. Discovering whether the volatility dynamics are subject to changes in scaling regimes requires the consideration of a model embedding scale-dependent information packets, thus accounting for possible heterogeneous activity occurring in financial markets. Independent component analysis result to be an important tool for reducing the dimension of the problem and calibrating greedy approximation techniques aimed to learn the structure of the underlying volatility.

[Effect of occupational stress on mental health].

PubMed

Yu, Shan-fa; Zhang, Rui; Ma, Liang-qing; Gu, Gui-zhen; Yang, Yan; Li, Kui-rong

2003-02-01

To study the effect of job psychological demands and job control on mental health and their interaction. 93 male freight train dispatchers were evaluated by using revised Job Demand-Control Scale and 7 strain scales. Stepwise regression analysis, Univariate ANOVA, Kruskal-Wallis H and Modian methods were used in statistic analysis. Kruskal-Wallis H and Modian methods analysis revealed the difference in mental health scores among groups of decision latitude (mean rank 55.57, 47.95, 48.42, 33.50, P < 0.05), the differences in scores of mental health (37.45, 40.01, 58.35), job satisfaction (53.18, 46.91, 32.43), daily life strains (33.00, 44.96, 56.12) and depression (36.45, 42.25, 53.61) among groups of job time demands (P < 0.05) were all statistically significant. ANOVA showed that job time demands and decision latitude had interaction effects on physical complains (R(2) = 0.24), state-anxiety (R(2) = 0.26), and daytime fatigue (R(2) = 0.28) (P < 0.05). Regression analysis revealed a significant job time demands and job decision latitude interaction effect as well as significant main effects of the some independent variables on different job strains (R(2) > 0.05). Job time demands and job decision latitude have direct and interactive effects on psychosomatic health, the more time demands, the more psychological strains, the effect of job time demands is greater than that of job decision latitude.

Monitoring forest dynamics with multi-scale and time series imagery.

PubMed

Huang, Chunbo; Zhou, Zhixiang; Wang, Di; Dian, Yuanyong

2016-05-01

To learn the forest dynamics and evaluate the ecosystem services of forest effectively, a timely acquisition of spatial and quantitative information of forestland is very necessary. Here, a new method was proposed for mapping forest cover changes by combining multi-scale satellite remote-sensing imagery with time series data. Using time series Normalized Difference Vegetation Index products derived from the Moderate Resolution Imaging Spectroradiometer images (MODIS-NDVI) and Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images as data source, a hierarchy stepwise analysis from coarse scale to fine scale was developed for detecting the forest change area. At the coarse scale, MODIS-NDVI data with 1-km resolution were used to detect the changes in land cover types and a land cover change map was constructed using NDVI values at vegetation growing seasons. At the fine scale, based on the results at the coarse scale, Landsat TM/ETM+ data with 30-m resolution were used to precisely detect the forest change location and forest change trend by analyzing time series forest vegetation indices (IFZ). The method was tested using the data for Hubei Province, China. The MODIS-NDVI data from 2001 to 2012 were used to detect the land cover changes, and the overall accuracy was 94.02 % at the coarse scale. At the fine scale, the available TM/ETM+ images at vegetation growing seasons between 2001 and 2012 were used to locate and verify forest changes in the Three Gorges Reservoir Area, and the overall accuracy was 94.53 %. The accuracy of the two layer hierarchical monitoring results indicated that the multi-scale monitoring method is feasible and reliable.

Spatiotemporal Drought Analysis and Drought Indices Comparison in India

NASA Astrophysics Data System (ADS)

Janardhanan, A.

2017-12-01

Droughts and floods are an ever-occurring phenomenon that has been wreaking havoc on humans since the start of time. As droughts are on a very large scale, studying them within a regional context can minimize confounding factors such as climate change. Droughts and floods are extremely erratic and very difficult to predict and therefore necessitate modeling through advanced statistics. The SPI (Standard Precipitation Index) and the SPEI (Standard Precipitation Evapotranspiration Index) are two ways to temporally model drought and flood patterns across each metrological sub basin in India over a variety of different time scales. SPI only accounts for precipitation values, while the SPEI accounts for both precipitation and temperature and is commonly regarded as a more reliable drought index. Using monthly rainfall and temperature data from 1871-2016, these two indices were calculated. The results depict the drought and flood severity index, length of drought, and average SPI or SPEI value for each meteorological sub region in India. A Wilcox Ranksum test was then conducted to determine whether these two indices differed over the long term for drought analysis. The drought return periods were analyzed to determine if the population mean differed between the SPI and SPEI values. Our analysis found no statistical difference between SPI and SPEI with regards to long-term drought analysis. This indicates that temperature is not needed when modeling drought on a long-term time scale and that SPI is just as effective as SPEI, which has the potential to save a lot of time and resources on calculating drought indices.

Novel Flood Detection and Analysis Method Using Recurrence Property

NASA Astrophysics Data System (ADS)

Wendi, Dadiyorto; Merz, Bruno; Marwan, Norbert

2016-04-01

Temporal changes in flood hazard are known to be difficult to detect and attribute due to multiple drivers that include processes that are non-stationary and highly variable. These drivers, such as human-induced climate change, natural climate variability, implementation of flood defence, river training, or land use change, could impact variably on space-time scales and influence or mask each other. Flood time series may show complex behavior that vary at a range of time scales and may cluster in time. This study focuses on the application of recurrence based data analysis techniques (recurrence plot) for understanding and quantifying spatio-temporal changes in flood hazard in Germany. The recurrence plot is known as an effective tool to visualize the dynamics of phase space trajectories i.e. constructed from a time series by using an embedding dimension and a time delay, and it is known to be effective in analyzing non-stationary and non-linear time series. The emphasis will be on the identification of characteristic recurrence properties that could associate typical dynamic behavior to certain flood situations.

Cross-correlations and influence in world gold markets

NASA Astrophysics Data System (ADS)

Lin, Min; Wang, Gang-Jin; Xie, Chi; Stanley, H. Eugene

2018-01-01

Using the detrended cross-correlation analysis (DCCA) coefficient and the detrended partial cross-correlation analysis (DPCCA) coefficient, we investigate cross-correlations and net cross-correlations among five major world gold markets (London, New York, Shanghai, Tokyo, and Mumbai) at different time scales. We propose multiscale influence measures for examining the influence of individual markets on other markets and on the entire system. We find (i) that the cross-correlations, net cross-correlations, and net influences among the five gold markets vary across time scales, (ii) that the cross-market correlation between London and New York at each time scale is intense and inherent, meaning that the influence of other gold markets on the London-New York market is negligible, (iii) that the remaining cross-market correlations (i.e., those other than London-New York) are greatly affected by other gold markets, and (iv) that the London gold market significantly affects the other four gold markets and dominates the world-wide gold market. Our multiscale findings give market participants and market regulators new information on cross-market linkages in the world-wide gold market.

Scaling Behavior in Mitochondrial Redox Fluctuations

PubMed Central

Ramanujan, V. Krishnan; Biener, Gabriel; Herman, Brian A.

2006-01-01

Scale-invariant long-range correlations have been reported in fluctuations of time-series signals originating from diverse processes such as heart beat dynamics, earthquakes, and stock market data. The common denominator of these apparently different processes is a highly nonlinear dynamics with competing forces and distinct feedback species. We report for the first time an experimental evidence for scaling behavior in NAD(P)H signal fluctuations in isolated mitochondria and intact cells isolated from the liver of a young (5-month-old) mouse. Time-series data were collected by two-photon imaging of mitochondrial NAD(P)H fluorescence and signal fluctuations were quantitatively analyzed for statistical correlations by detrended fluctuation analysis and spectral power analysis. Redox [NAD(P)H / NAD(P)+] fluctuations in isolated mitochondria and intact liver cells were found to display nonrandom, long-range correlations. These correlations are interpreted as arising due to the regulatory dynamics operative in Krebs' cycle enzyme network and electron transport chain in the mitochondria. This finding may provide a novel basis for understanding similar regulatory networks that govern the nonequilibrium properties of living cells. PMID:16565066

Complex Dynamics of Equatorial Scintillation

NASA Astrophysics Data System (ADS)

Piersanti, Mirko; Materassi, Massimo; Forte, Biagio; Cicone, Antonio

2017-04-01

Radio power scintillation, namely highly irregular fluctuations of the power of trans-ionospheric GNSS signals, is the effect of ionospheric plasma turbulence. The scintillation patterns on radio signals crossing the medium inherit the ionospheric turbulence characteristics of inter-scale coupling, local randomness and large time variability. On this basis, the remote sensing of local features of the turbulent plasma is feasible by studying radio scintillation induced by the ionosphere. The distinctive character of intermittent turbulent media depends on the fluctuations on the space- and time-scale statistical properties of the medium. Hence, assessing how the signal fluctuation properties vary under different Helio-Geophysical conditions will help to understand the corresponding dynamics of the turbulent medium crossed by the signal. Data analysis tools, provided by complex system science, appear to be best fitting to study the response of a turbulent medium, as the Earth's equatorial ionosphere, to the non-linear forcing exerted by the Solar Wind (SW). In particular we used the Adaptive Local Iterative Filtering, the Wavelet analysis and the Information theory data analysis tool. We have analysed the radio scintillation and ionospheric fluctuation data at low latitude focusing on the time and space multi-scale variability and on the causal relationship between forcing factors from the SW environment and the ionospheric response.

Investigation of aquifer-estuary interaction using wavelet analysis of fiber-optic temperature data

USGS Publications Warehouse

Henderson, R.D.; Day-Lewis, Frederick D.; Harvey, Charles F.

2009-01-01

Fiber-optic distributed temperature sensing (FODTS) provides sub-minute temporal and meter-scale spatial resolution over kilometer-long cables. Compared to conventional thermistor or thermocouple-based technologies, which measure temperature at discrete (and commonly sparse) locations, FODTS offers nearly continuous spatial coverage, thus providing hydrologic information at spatiotemporal scales previously impossible. Large and information-rich FODTS datasets, however, pose challenges for data exploration and analysis. To date, FODTS analyses have focused on time-series variance as the means to discriminate between hydrologic phenomena. Here, we demonstrate the continuous wavelet transform (CWT) and cross-wavelet transform (XWT) to analyze FODTS in the context of related hydrologic time series. We apply the CWT and XWT to data from Waquoit Bay, Massachusetts to identify the location and timing of tidal pumping of submarine groundwater.

Scale-free avalanche dynamics in the stock market

NASA Astrophysics Data System (ADS)

Bartolozzi, M.; Leinweber, D. B.; Thomas, A. W.

2006-10-01

Self-organized criticality (SOC) has been claimed to play an important role in many natural and social systems. In the present work we empirically investigate the relevance of this theory to stock-market dynamics. Avalanches in stock-market indices are identified using a multi-scale wavelet-filtering analysis designed to remove Gaussian noise from the index. Here, new methods are developed to identify the optimal filtering parameters which maximize the noise removal. The filtered time series is reconstructed and compared with the original time series. A statistical analysis of both high-frequency Nasdaq E-mini Futures and daily Dow Jones data is performed. The results of this new analysis confirm earlier results revealing a robust power-law behaviour in the probability distribution function of the sizes, duration and laminar times between avalanches. This power-law behaviour holds the potential to be established as a stylized fact of stock market indices in general. While the memory process, implied by the power-law distribution of the laminar times, is not consistent with classical models for SOC, we note that a power-law distribution of the laminar times cannot be used to rule out self-organized critical behaviour.

Scaling laws and dynamics of bubble coalescence

NASA Astrophysics Data System (ADS)

Anthony, Christopher R.; Kamat, Pritish M.; Thete, Sumeet S.; Munro, James P.; Lister, John R.; Harris, Michael T.; Basaran, Osman A.

2017-08-01

The coalescence of bubbles and drops plays a central role in nature and industry. During coalescence, two bubbles or drops touch and merge into one as the neck connecting them grows from microscopic to macroscopic scales. The hydrodynamic singularity that arises when two bubbles or drops have just touched and the flows that ensue have been studied thoroughly when two drops coalesce in a dynamically passive outer fluid. In this paper, the coalescence of two identical and initially spherical bubbles, which are idealized as voids that are surrounded by an incompressible Newtonian liquid, is analyzed by numerical simulation. This problem has recently been studied (a) experimentally using high-speed imaging and (b) by asymptotic analysis in which the dynamics is analyzed by determining the growth of a hole in the thin liquid sheet separating the two bubbles. In the latter, advantage is taken of the fact that the flow in the thin sheet of nonconstant thickness is governed by a set of one-dimensional, radial extensional flow equations. While these studies agree on the power law scaling of the variation of the minimum neck radius with time, they disagree with respect to the numerical value of the prefactors in the scaling laws. In order to reconcile these differences and also provide insights into the dynamics that are difficult to probe by either of the aforementioned approaches, simulations are used to access both earlier times than has been possible in the experiments and also later times when asymptotic analysis is no longer applicable. Early times and extremely small length scales are attained in the new simulations through the use of a truncated domain approach. Furthermore, it is shown by direct numerical simulations in which the flow within the bubbles is also determined along with the flow exterior to them that idealizing the bubbles as passive voids has virtually no effect on the scaling laws relating minimum neck radius and time.

Evaluation and error apportionment of an ensemble of ...

EPA Pesticide Factsheets

Through the comparison of several regional-scale chemistry transport modelling systems that simulate meteorology and air quality over the European and American continents, this study aims at i) apportioning the error to the responsible processes using time-scale analysis, ii) helping to detect causes of models error, and iii) identifying the processes and scales most urgently requiring dedicated investigations. The analysis is conducted within the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) and tackles model performance gauging through measurement-to-model comparison, error decomposition and time series analysis of the models biases for several fields (ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature). The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overall sense of model strengths and deficiencies, while apportioning the error to its constituent parts (bias, variance and covariance) can help to assess the nature and quality of the error. Each of the error components is analysed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intra-day) using the error apportionment technique devised in the former phases of AQMEII.The application of the error apportionment method to the AQMEII Phase 3 simulations provides several key insights. In addition to reaffirming the strong impact

Evaluating the assumption of power-law late time scaling of breakthrough curves in highly heterogeneous media

NASA Astrophysics Data System (ADS)

Pedretti, Daniele

2017-04-01

Power-law (PL) distributions are widely adopted to define the late-time scaling of solute breakthrough curves (BTCs) during transport experiments in highly heterogeneous media. However, from a statistical perspective, distinguishing between a PL distribution and another tailed distribution is difficult, particularly when a qualitative assessment based on visual analysis of double-logarithmic plotting is used. This presentation aims to discuss the results from a recent analysis where a suite of statistical tools was applied to evaluate rigorously the scaling of BTCs from experiments that generate tailed distributions typically described as PL at late time. To this end, a set of BTCs from numerical simulations in highly heterogeneous media were generated using a transition probability approach (T-PROGS) coupled to a finite different numerical solver of the flow equation (MODFLOW) and a random walk particle tracking approach for Lagrangian transport (RW3D). The T-PROGS fields assumed randomly distributed hydraulic heterogeneities with long correlation scales creating solute channeling and anomalous transport. For simplicity, transport was simulated as purely advective. This combination of tools generates strongly non-symmetric BTCs visually resembling PL distributions at late time when plotted in double log scales. Unlike other combination of modeling parameters and boundary conditions (e.g. matrix diffusion in fractures), at late time no direct link exists between the mathematical functions describing scaling of these curves and physical parameters controlling transport. The results suggest that the statistical tests fail to describe the majority of curves as PL distributed. Moreover, they suggest that PL or lognormal distributions have the same likelihood to represent parametrically the shape of the tails. It is noticeable that forcing a model to reproduce the tail as PL functions results in a distribution of PL slopes comprised between 1.2 and 4, which are the typical values observed during field experiments. We conclude that care must be taken when defining a BTC late time distribution as a power law function. Even though the estimated scaling factors are found to fall in traditional ranges, the actual distribution controlling the scaling of concentration may different from a power-law function, with direct consequences for instance for the selection of effective parameters in upscaling modeling solutions.

Introduction and application of the multiscale coefficient of variation analysis.

PubMed

Abney, Drew H; Kello, Christopher T; Balasubramaniam, Ramesh

2017-10-01

Quantifying how patterns of behavior relate across multiple levels of measurement typically requires long time series for reliable parameter estimation. We describe a novel analysis that estimates patterns of variability across multiple scales of analysis suitable for time series of short duration. The multiscale coefficient of variation (MSCV) measures the distance between local coefficient of variation estimates within particular time windows and the overall coefficient of variation across all time samples. We first describe the MSCV analysis and provide an example analytical protocol with corresponding MATLAB implementation and code. Next, we present a simulation study testing the new analysis using time series generated by ARFIMA models that span white noise, short-term and long-term correlations. The MSCV analysis was observed to be sensitive to specific parameters of ARFIMA models varying in the type of temporal structure and time series length. We then apply the MSCV analysis to short time series of speech phrases and musical themes to show commonalities in multiscale structure. The simulation and application studies provide evidence that the MSCV analysis can discriminate between time series varying in multiscale structure and length.

The Theory of Intelligence and Its Measurement

ERIC Educational Resources Information Center

Jensen, A. R.

2011-01-01

Mental chronometry (MC) studies cognitive processes measured by time. It provides an absolute, ratio scale. The limitations of instrumentation and statistical analysis caused the early studies in MC to be eclipsed by the "paper-and-pencil" psychometric tests started by Binet. However, they use an age-normed, rather than a ratio scale, which…

Economies of Scale and Scope in Australian Higher Education

ERIC Educational Resources Information Center

Worthington, A. C.; Higgs, H.

2011-01-01

This paper estimates economies of scale and scope for 36 Australian universities using a multiple-input, multiple-output cost function over the period 1998-2006. The three inputs included in the analysis are full-time equivalent academic and non-academic staff and physical capital. The five outputs are undergraduate, postgraduate and PhD…

Wind gusts and plant aeroelasticity effects on the aerodynamics of pollen shedding: a hypothetical turbulence-initiated wind-pollination mechanism.

PubMed

Urzay, Javier; Llewellyn Smith, Stefan G; Thompson, Elinor; Glover, Beverley J

2009-08-21

Plant reproduction depends on pollen dispersal. For anemophilous (wind-pollinated) species, such as grasses and many trees, shedding pollen from the anther must be accomplished by physical mechanisms. The unknown nature of this process has led to its description as the 'paradox of pollen liberation'. A simple scaling analysis, supported by experimental measurements on typical wind-pollinated plant species, is used to estimate the suitability of previous resolutions of this paradox based on wind-gust aerodynamic models of fungal-spore liberation. According to this scaling analysis, the steady Stokes drag force is found to be large enough to liberate anemophilous pollen grains, and unsteady boundary-layer forces produced by wind gusts are found to be mostly ineffective since the ratio of the characteristic viscous time scale to the inertial time scale of acceleration of the wind stream is a small parameter for typical anemophilous species. A hypothetical model of a stochastic aeroelastic mechanism, initiated by the atmospheric turbulence typical of the micrometeorological conditions in the vicinity of the plant, is proposed to contribute to wind pollination.

A Reduced Order Model for Whole-Chip Thermal Analysis of Microfluidic Lab-on-a-Chip Systems

PubMed Central

Wang, Yi; Song, Hongjun; Pant, Kapil

2013-01-01

This paper presents a Krylov subspace projection-based Reduced Order Model (ROM) for whole microfluidic chip thermal analysis, including conjugate heat transfer. Two key steps in the reduced order modeling procedure are described in detail, including (1) the acquisition of a 3D full-scale computational model in the state-space form to capture the dynamic thermal behavior of the entire microfluidic chip; and (2) the model order reduction using the Block Arnoldi algorithm to markedly lower the dimension of the full-scale model. Case studies using practically relevant thermal microfluidic chip are undertaken to establish the capability and to evaluate the computational performance of the reduced order modeling technique. The ROM is compared against the full-scale model and exhibits good agreement in spatiotemporal thermal profiles (<0.5% relative error in pertinent time scales) and over three orders-of-magnitude acceleration in computational speed. The salient model reusability and real-time simulation capability renders it amenable for operational optimization and in-line thermal control and management of microfluidic systems and devices. PMID:24443647

Statistical analysis of an inter-laboratory comparison of small-scale safety and thermal testing of RDX

DOE PAGES

Brown, Geoffrey W.; Sandstrom, Mary M.; Preston, Daniel N.; ...

2014-11-17

In this study, the Integrated Data Collection Analysis (IDCA) program has conducted a proficiency test for small-scale safety and thermal (SSST) testing of homemade explosives (HMEs). Described here are statistical analyses of the results from this test for impact, friction, electrostatic discharge, and differential scanning calorimetry analysis of the RDX Class 5 Type II standard. The material was tested as a well-characterized standard several times during the proficiency test to assess differences among participants and the range of results that may arise for well-behaved explosive materials.

Measurement of New Observables from the pi+pi- Electroproduction off the Proton

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

Trivedi, Arjun

Knowledge of the Universe as constructed by human beings, in order to tackle its complexity, can be thought to be organized at varying scales at which it is observed. Implicit in such an approach is the idea of a smooth evolution of knowledge between scales and, therefore, access to how Nature constructs the visible Universe beginning from its most fundamental constituents. New and, in a sense, fundamental phenomena may typically be emergent as the scale of observation changes. The study of the Strong Interaction, which is responsible for the construction of the bulk of the visible matter in the Universemore » (98% by mass), in this sense, is a labor of exploring evolutions and unifying aspects of its knowledge found at varying scales ranging from interaction of quarks and gluons as represented by the theory of Quantum Chromodynamics (QCD) at small space-time scale to emerging dressed quark and even meson-baryon degrees of freedom mostly described by effective models as the space-time scale increases. A direct effort to study the Strong Interaction over this scale forms the basis of an international collaborative effort often referred to as the N* program. The core work of this thesis is an experimental analysis prompted by the need to measure experimental observables that are of particular interest to the theory-experiment epistemological framework of this collaboration. While the core of this thesis, therefore, discusses the nature of the experimental analysis and presents its results which will serve as input to the N* program's epistemological framework, the particular nature of this framework in the context of not only the Strong Interaction, but also that of the physical science and human knowledge in general will be used to motivate and introduce the experimental analysis and its related observables.« less

Measurement of new observables from the pi+pi - electroproduction off the proton

NASA Astrophysics Data System (ADS)

Trivedi, Arjun

Knowledge of the Universe as constructed by human beings, in order to tackle its complexity, can be thought to be organized at varying scales at which it is observed. Implicit in such an approach is the idea of a smooth evolution of knowledge between scales and, therefore, access to how Nature constructs the visible Universe beginning from its most fundamental constituents. New and, in a sense, fundamental phenomena may typically be emergent as the scale of observation changes. The study of the Strong Interaction, which is responsible for the construction of the bulk of the visible matter in the Universe (98% by mass), in this sense, is a labor of exploring evolutions and unifying aspects of its knowledge found at varying scales ranging from interaction of quarks and gluons as represented by the theory of Quantum Chromodynamics (QCD) at small space-time scale to emerging dressed quark and even mesonbaryon degrees of freedom mostly described by effective models as the space-time scale increases. A direct effort to study the Strong Interaction over this scale forms the basis of an international collaborative effort often referred to as the N* program. The core work of this thesis is an experimental analysis prompted by the need to measure experimental observables that are of particular interest to the theory-experiment epistemological framework of this collaboration. While the core of this thesis, therefore, discusses the nature of the experimental analysis and presents its results which will serve as input to the N* program's epistemological framework, the particular nature of this framework in the context of not only the Strong Interaction, but also that of the physical science and human knowledge in general will be used to motivate and introduce the experimental analysis and its related observables.

Time-Lapse Videos for Physics Education: Specific Examples

ERIC Educational Resources Information Center

Vollmer, Michael; Möllmann, Klaus-Peter

2018-01-01

There are many physics experiments with long time scales such that they are usually neither shown in the physics class room nor in student labs. However, they can be easily recorded with time-lapse cameras and the respective time-lapse videos allow qualitative and/or quantitative analysis of the underlying physics. Here, we present some examples…

Leisure-time physical activity and psychological well-being in university students.

PubMed

Molina-García, J; Castillo, I; Queralt, A

2011-10-01

An analysis of psychological well-being (self-esteem and subjective vitality) of 639 Spanish university students was performed, while accounting for the amount of leisure-time physical activity. The Spanish versions of the Rosenberg Self-Esteem Scale and Subjective Vitality Scale were employed. Participants were divided into four groups (Low, Moderate, High, and Very high) depending on estimation of energy expenditure in leisure-time physical activity. Men and women having higher physical activity rated higher mean subjective vitality; however, differences in self-esteem were observed only in men, specifically between Very high and the other physical activity groups.

Father for the first time - development and validation of a questionnaire to assess fathers’ experiences of first childbirth (FTFQ)

PubMed Central

2012-01-01

Background A father’s experience of the birth of his first child is important not only for his birth-giving partner but also for the father himself, his relationship with the mother and the newborn. No validated questionnaire assessing first-time fathers' experiences during childbirth is currently available. Hence, the aim of this study was to develop and validate an instrument to assess first-time fathers’ experiences of childbirth. Method Domains and items were initially derived from interviews with first-time fathers, and supplemented by a literature search and a focus group interview with midwives. The comprehensibility, comprehension and relevance of the items were evaluated by four paternity research experts and a preliminary questionnaire was pilot tested in eight first-time fathers. A revised questionnaire was completed by 200 first-time fathers (response rate = 81%) Exploratory factor analysis using principal component analysis with varimax rotation was performed and multitrait scaling analysis was used to test scaling assumptions. External validity was assessed by means of known-groups analysis. Results Factor analysis yielded four factors comprising 22 items and accounting 48% of the variance. The domains found were Worry, Information, Emotional support and Acceptance. Multitrait analysis confirmed the convergent and discriminant validity of the domains; however, Cronbach’s alpha did not meet conventional reliability standards in two domains. The questionnaire was sensitive to differences between groups of fathers hypothesized to differ on important socio demographic or clinical variables. Conclusions The questionnaire adequately measures important dimensions of first-time fathers’ childbirth experience and may be used to assess aspects of fathers’ experiences during childbirth. To obtain the FTFQ and permission for its use, please contact the corresponding author. PMID:22594834

Father for the first time--development and validation of a questionnaire to assess fathers' experiences of first childbirth (FTFQ).

PubMed

Premberg, Åsa; Taft, Charles; Hellström, Anna-Lena; Berg, Marie

2012-05-17

A father's experience of the birth of his first child is important not only for his birth-giving partner but also for the father himself, his relationship with the mother and the newborn. No validated questionnaire assessing first-time fathers' experiences during childbirth is currently available. Hence, the aim of this study was to develop and validate an instrument to assess first-time fathers' experiences of childbirth. Domains and items were initially derived from interviews with first-time fathers, and supplemented by a literature search and a focus group interview with midwives. The comprehensibility, comprehension and relevance of the items were evaluated by four paternity research experts and a preliminary questionnaire was pilot tested in eight first-time fathers. A revised questionnaire was completed by 200 first-time fathers (response rate = 81%) Exploratory factor analysis using principal component analysis with varimax rotation was performed and multitrait scaling analysis was used to test scaling assumptions. External validity was assessed by means of known-groups analysis. Factor analysis yielded four factors comprising 22 items and accounting 48% of the variance. The domains found were Worry, Information, Emotional support and Acceptance. Multitrait analysis confirmed the convergent and discriminant validity of the domains; however, Cronbach's alpha did not meet conventional reliability standards in two domains. The questionnaire was sensitive to differences between groups of fathers hypothesized to differ on important socio demographic or clinical variables. The questionnaire adequately measures important dimensions of first-time fathers' childbirth experience and may be used to assess aspects of fathers' experiences during childbirth. To obtain the FTFQ and permission for its use, please contact the corresponding author.

The firefighter coping self-efficacy scale: measure development and validation.

PubMed

Lambert, Jessica E; Benight, Charles C; Harrison, Erica; Cieslak, Roman

2012-01-01

The authors evaluated the psychometric properties of the Firefighter Coping Self-Efficacy (FFCSE) Scale, a new measure developed to assess firefighters' perceived competence in managing stressful and traumatic experiences encountered on the job. Two samples of firefighters completed the FFCSE Scale at two different time points. Exploratory factor analysis yielded a unidimensional structure, which was further supported with confirmatory factor analysis using a second sample. Internal consistency of the measure was excellent. Analysis of cross-sectional data indicated FFCSE was positively associated with measures of psychological well-being and social support, and negatively associated with work-related stress and psychological distress. FFCSE also uniquely contributed to the variance in psychological distress, over and above variables previously shown to be associated with distress among this population. Implications and suggestions for future research are discussed.

Nonlinearities of heart rate variability in animal models of impaired cardiac control: contribution of different time scales.

PubMed

Silva, Luiz Eduardo Virgilio; Lataro, Renata Maria; Castania, Jaci Airton; Silva, Carlos Alberto Aguiar; Salgado, Helio Cesar; Fazan, Rubens; Porta, Alberto

2017-08-01

Heart rate variability (HRV) has been extensively explored by traditional linear approaches (e.g., spectral analysis); however, several studies have pointed to the presence of nonlinear features in HRV, suggesting that linear tools might fail to account for the complexity of the HRV dynamics. Even though the prevalent notion is that HRV is nonlinear, the actual presence of nonlinear features is rarely verified. In this study, the presence of nonlinear dynamics was checked as a function of time scales in three experimental models of rats with different impairment of the cardiac control: namely, rats with heart failure (HF), spontaneously hypertensive rats (SHRs), and sinoaortic denervated (SAD) rats. Multiscale entropy (MSE) and refined MSE (RMSE) were chosen as the discriminating statistic for the surrogate test utilized to detect nonlinearity. Nonlinear dynamics is less present in HF animals at both short and long time scales compared with controls. A similar finding was found in SHR only at short time scales. SAD increased the presence of nonlinear dynamics exclusively at short time scales. Those findings suggest that a working baroreflex contributes to linearize HRV and to reduce the likelihood to observe nonlinear components of the cardiac control at short time scales. In addition, an increased sympathetic modulation seems to be a source of nonlinear dynamics at long time scales. Testing nonlinear dynamics as a function of the time scales can provide a characterization of the cardiac control complementary to more traditional markers in time, frequency, and information domains. NEW & NOTEWORTHY Although heart rate variability (HRV) dynamics is widely assumed to be nonlinear, nonlinearity tests are rarely used to check this hypothesis. By adopting multiscale entropy (MSE) and refined MSE (RMSE) as the discriminating statistic for the nonlinearity test, we show that nonlinear dynamics varies with time scale and the type of cardiac dysfunction. Moreover, as complexity metrics and nonlinearities provide complementary information, we strongly recommend using the test for nonlinearity as an additional index to characterize HRV. Copyright © 2017 the American Physiological Society.

Areal and time distributions of volcanic formations on Mars

NASA Technical Reports Server (NTRS)

Katterfeld, G. N.; Vityaz, V. I.

1987-01-01

The analysis of igneous rock distribution has been fulfilled on the basis of the geomorphological map of Mars at scale 1:5,000,000, according to data obtained from interpretation of 1:2,000,000 scale pictures of Mariner 9, Mars 4, Mars 5, Viking 1 and 2. Areological areas are listed as having been distinguished as the stratigraphic basis for a martian time scale. The area of volcanic eruptions and the number of eruptive centers are calculated on 10 x 10 deg cells and for each areological eras. The largest area of eruptive happening at different times is related with Tharsis tectonic uplift. The study of distribution of igneous rock area and volcanic centers number on 10 deg sectors and zones revealed the concentration belts of volcanic formations.

The sensitivity to land use and climate variations in the whitewater river basin, kansas, USA: Closing the water budget using groundwater models

NASA Astrophysics Data System (ADS)

Beeson, P.; Duffy, C.; Springer, E.

2003-04-01

A water budget was developed using groundwater models to assess the impact of land use and climate variability on the Whitewater River Basin located in southeastern Kansas within the ARM-SGP as part of the DOE Water Cycle Pilot Study. The Whitewater River Basin has an area of 1,100 km2, an elevation range of 380 - 470 m above mean sea level, and an average annual precipitation of 858 mm. Time series and geospatial analysis are used to identify significant spatial structure and dominant temporal modes in the watershed runoff and groundwater response. Space-time analyses confirmed the hydrogeologic conceptual model developed from the hydrostratigraphic information provided by existing geologic studies and over 2,000 wells located in the area. The groundwater-surface water interactions are identified by time series analysis of stream discharge, precipitation, temperature, and water levels in wells. Singular spectrum analysis suggests a two layer leaky perched system with strong influences of daily, monthly, seasonal, and interannual oscillations. The geospatial analysis identifies the important length scales and the time series analysis the corresponding time scales, which must be incorporated in the model. The fine scale layering, which creates the perched leaky top layer, was represented by using an anisotropy ratio. This ratio was determined from select well data to be 100 (Kh/Kv), by calculating the vertical conductivity from harmonic mean and horizontal conductivity from arithmetic mean. MODFLOW is used to assess the importance of groundwater when attempting to close the water budget. The R-squared value between MODFLOW predicted and observed head values for the watershed was 0.85 indicating a good fit. Mean recharge was estimated to be approximately 17 percent of total annual precipitation. The approach presented here is an initial attempt to examine the importance of groundwater in the water budget of a relatively small river basin.

Development and psychometric properties of the Inner Strength Scale.

PubMed

Lundman, Berit; Viglund, Kerstin; Aléx, Lena; Jonsén, Elisabeth; Norberg, Astrid; Fischer, Regina Santamäki; Strandberg, Gunilla; Nygren, Björn

2011-10-01

Four dimensions of inner strength were previously identified in a meta-theoretical analysis: firmness, creativity, connectedness, and flexibility. The aim of this study was to develop an Inner Strength Scale (ISS) based on those four dimensions and to evaluate its psychometric properties. An initial version of ISS was distributed for validation purpose with the Rosenberg Self-Esteem Scale, the resilience scale, and the sense of Coherence Scale. A convenience sample of 391 adults, aged 19-90 years participated. Principal component analysis (PCA) and confirmatory factor analysis (CFA) were used in the process of exploring, evaluating, and reducing the 63-item ISS to the 20-item ISS. Cronbach's alpha and test-retest were used to measure reliability. CFA showed satisfactory goodness-of-fit for the 20-item ISS. The analysis supported a fourfactor solution explaining 51% of the variance. Cronbach's alpha on the 20-item ISS was 0.86, and the test-retest showed stability over time (r=0.79). The ISS was found to be a valid and reliable instrument for capturing a multifaceted understanding of inner strength. Further tests of psychometric properties of the ISS will be performed in forthcoming studies. Copyright © 2011 Elsevier Ltd. All rights reserved.

Changes in the Hurst exponent of heartbeat intervals during physical activity

NASA Astrophysics Data System (ADS)

Martinis, M.; Knežević, A.; Krstačić, G.; Vargović, E.

2004-07-01

The fractal scaling properties of the heartbeat time series are studied in different controlled ergometric regimes using both the improved Hurst rescaled range (R/S) analysis and the detrended fluctuation analysis (DFA). The long-time “memory effect” quantified by the value of the Hurst exponent H>0.5 is found to increase during progressive physical activity in healthy subjects, in contrast to those having stable angina pectoris, where it decreases. The results are also supported by the detrended fluctuation analysis. We argue that this finding may be used as a useful new diagnostic parameter for short heartbeat time series.

Identifying Changes of Complex Flood Dynamics with Recurrence Analysis

NASA Astrophysics Data System (ADS)

Wendi, D.; Merz, B.; Marwan, N.

2016-12-01

Temporal changes in flood hazard system are known to be difficult to detect and attribute due to multiple drivers that include complex processes that are non-stationary and highly variable. These drivers, such as human-induced climate change, natural climate variability, implementation of flood defense, river training, or land use change, could impact variably on space-time scales and influence or mask each other. Flood time series may show complex behavior that vary at a range of time scales and may cluster in time. Moreover hydrological time series (i.e. discharge) are often subject to measurement errors, such as rating curve error especially in the case of extremes where observation are actually derived through extrapolation. This study focuses on the application of recurrence based data analysis techniques (recurrence plot) for understanding and quantifying spatio-temporal changes in flood hazard in Germany. The recurrence plot is known as an effective tool to visualize the dynamics of phase space trajectories i.e. constructed from a time series by using an embedding dimension and a time delay, and it is known to be effective in analyzing non-stationary and non-linear time series. Sensitivity of the common measurement errors and noise on recurrence analysis will also be analyzed and evaluated against conventional methods. The emphasis will be on the identification of characteristic recurrence properties that could associate typical dynamic to certain flood events.

Gyrokinetic theory for particle and energy transport in fusion plasmas

NASA Astrophysics Data System (ADS)

Falessi, Matteo Valerio; Zonca, Fulvio

2018-03-01

A set of equations is derived describing the macroscopic transport of particles and energy in a thermonuclear plasma on the energy confinement time. The equations thus derived allow studying collisional and turbulent transport self-consistently, retaining the effect of magnetic field geometry without postulating any scale separation between the reference state and fluctuations. Previously, assuming scale separation, transport equations have been derived from kinetic equations by means of multiple-scale perturbation analysis and spatio-temporal averaging. In this work, the evolution equations for the moments of the distribution function are obtained following the standard approach; meanwhile, gyrokinetic theory has been used to explicitly express the fluctuation induced fluxes. In this way, equations for the transport of particles and energy up to the transport time scale can be derived using standard first order gyrokinetics.

Underlying dynamics of typical fluctuations of an emerging market price index: The Heston model from minutes to months

NASA Astrophysics Data System (ADS)

Vicente, Renato; de Toledo, Charles M.; Leite, Vitor B. P.; Caticha, Nestor

2006-02-01

We investigate the Heston model with stochastic volatility and exponential tails as a model for the typical price fluctuations of the Brazilian São Paulo Stock Exchange Index (IBOVESPA). Raw prices are first corrected for inflation and a period spanning 15 years characterized by memoryless returns is chosen for the analysis. Model parameters are estimated by observing volatility scaling and correlation properties. We show that the Heston model with at least two time scales for the volatility mean reverting dynamics satisfactorily describes price fluctuations ranging from time scales larger than 20 min to 160 days. At time scales shorter than 20 min we observe autocorrelated returns and power law tails incompatible with the Heston model. Despite major regulatory changes, hyperinflation and currency crises experienced by the Brazilian market in the period studied, the general success of the description provided may be regarded as an evidence for a general underlying dynamics of price fluctuations at intermediate mesoeconomic time scales well approximated by the Heston model. We also notice that the connection between the Heston model and Ehrenfest urn models could be exploited for bringing new insights into the microeconomic market mechanics.

Effective pore-scale dispersion upscaling with a correlated continuous time random walk approach

NASA Astrophysics Data System (ADS)

Le Borgne, T.; Bolster, D.; Dentz, M.; de Anna, P.; Tartakovsky, A.

2011-12-01

We investigate the upscaling of dispersion from a pore-scale analysis of Lagrangian velocities. A key challenge in the upscaling procedure is to relate the temporal evolution of spreading to the pore-scale velocity field properties. We test the hypothesis that one can represent Lagrangian velocities at the pore scale as a Markov process in space. The resulting effective transport model is a continuous time random walk (CTRW) characterized by a correlated random time increment, here denoted as correlated CTRW. We consider a simplified sinusoidal wavy channel model as well as a more complex heterogeneous pore space. For both systems, the predictions of the correlated CTRW model, with parameters defined from the velocity field properties (both distribution and correlation), are found to be in good agreement with results from direct pore-scale simulations over preasymptotic and asymptotic times. In this framework, the nontrivial dependence of dispersion on the pore boundary fluctuations is shown to be related to the competition between distribution and correlation effects. In particular, explicit inclusion of spatial velocity correlation in the effective CTRW model is found to be important to represent incomplete mixing in the pore throats.

Equation-free multiscale computation: algorithms and applications.

PubMed

Kevrekidis, Ioannis G; Samaey, Giovanni

2009-01-01

In traditional physicochemical modeling, one derives evolution equations at the (macroscopic, coarse) scale of interest; these are used to perform a variety of tasks (simulation, bifurcation analysis, optimization) using an arsenal of analytical and numerical techniques. For many complex systems, however, although one observes evolution at a macroscopic scale of interest, accurate models are only given at a more detailed (fine-scale, microscopic) level of description (e.g., lattice Boltzmann, kinetic Monte Carlo, molecular dynamics). Here, we review a framework for computer-aided multiscale analysis, which enables macroscopic computational tasks (over extended spatiotemporal scales) using only appropriately initialized microscopic simulation on short time and length scales. The methodology bypasses the derivation of macroscopic evolution equations when these equations conceptually exist but are not available in closed form-hence the term equation-free. We selectively discuss basic algorithms and underlying principles and illustrate the approach through representative applications. We also discuss potential difficulties and outline areas for future research.

A validation of the construct and reliability of an emotional intelligence scale applied to nursing students1

PubMed Central

Espinoza-Venegas, Maritza; Sanhueza-Alvarado, Olivia; Ramírez-Elizondo, Noé; Sáez-Carrillo, Katia

2015-01-01

OBJECTIVE: The current study aimed to validate the construct and reliability of an emotional intelligence scale. METHOD: The Trait Meta-Mood Scale-24 was applied to 349 nursing students. The process included content validation, which involved expert reviews, pilot testing, measurements of reliability using Cronbach's alpha, and factor analysis to corroborate the validity of the theoretical model's construct. RESULTS: Adequate Cronbach coefficients were obtained for all three dimensions, and factor analysis confirmed the scale's dimensions (perception, comprehension, and regulation). CONCLUSION: The Trait Meta-Mood Scale is a reliable and valid tool to measure the emotional intelligence of nursing students. Its use allows for accurate determinations of individuals' abilities to interpret and manage emotions. At the same time, this new construct is of potential importance for measurements in nursing leadership; educational, organizational, and personal improvements; and the establishment of effective relationships with patients. PMID:25806642

Possible signatures of dissipation from time-series analysis techniques using a turbulent laboratory magnetohydrodynamic plasma

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

Schaffner, D. A.; Brown, M. R.; Rock, A. B.

The frequency spectrum of magnetic fluctuations as measured on the Swarthmore Spheromak Experiment is broadband and exhibits a nearly Kolmogorov 5/3 scaling. It features a steepening region which is indicative of dissipation of magnetic fluctuation energy similar to that observed in fluid and magnetohydrodynamic turbulence systems. Two non-spectrum based time-series analysis techniques are implemented on this data set in order to seek other possible signatures of turbulent dissipation beyond just the steepening of fluctuation spectra. Presented here are results for the flatness, permutation entropy, and statistical complexity, each of which exhibits a particular character at spectral steepening scales which canmore » then be compared to the behavior of the frequency spectrum.« less

Speech transformations based on a sinusoidal representation

NASA Astrophysics Data System (ADS)

Quatieri, T. E.; McAulay, R. J.

1986-05-01

A new speech analysis/synthesis technique is presented which provides the basis for a general class of speech transformation including time-scale modification, frequency scaling, and pitch modification. These modifications can be performed with a time-varying change, permitting continuous adjustment of a speaker's fundamental frequency and rate of articulation. The method is based on a sinusoidal representation of the speech production mechanism that has been shown to produce synthetic speech that preserves the waveform shape and is essentially perceptually indistinguishable from the original. Although the analysis/synthesis system originally was designed for single-speaker signals, it is equally capable of recovering and modifying nonspeech signals such as music; multiple speakers, marine biologic sounds, and speakers in the presence of interferences such as noise and musical backgrounds.

Evidence of Hierarchy in the Complex Fractured System of Geropotamos (Crete, Greece), as Extracted from Transient Electromagnetic Responses

NASA Astrophysics Data System (ADS)

Vallianatos, Filippos; Kouli, Maria; Kalisperi, Despina

2018-03-01

The essential goals of this paper are to test the transient electromagnetic (TEM) response in a fractured geological complex medium and to better understand the physics introduced by associating a roughness parameter β to the geological formation. An anomalous fractional diffusion approach is incorporated to describe the electromagnetic induction in rough multi-scaled geological structures. The multi-scaling characteristics of Geropotamos basin in Crete are revealed through the analysis of transient step-off response of an EM loop antenna. The semi-empirical parameters derived from late-time TEM measurements are correlated with the multi-scale heterogeneities of the medium. Certain interesting properties of the late-time slope γ(β) and the power law of near surface resistivity distribution, as extracted from TEM inversion for different depth, are presented. The analysis of the parameter γ(β) which scales the induced voltage in the loop in the late stage of the electromagnetic response leads to a different view of the EM geophysical data interpretation. We show that it is strongly correlated with areas of high fracture density within the geological formations of the Geropotamos area. For that reason, it is proposed as a local multi-scaling empirical index. The results of this paper suggest that anomalous diffusion could be a viable physical mechanism for the fractal transport of charge carriers, explaining observed late-time TEM responses across a variety of natural geological settings.

Determining the multi-scale hedge ratios of stock index futures using the lower partial moments method

NASA Astrophysics Data System (ADS)

Dai, Jun; Zhou, Haigang; Zhao, Shaoquan

2017-01-01

This paper considers a multi-scale future hedge strategy that minimizes lower partial moments (LPM). To do this, wavelet analysis is adopted to decompose time series data into different components. Next, different parametric estimation methods with known distributions are applied to calculate the LPM of hedged portfolios, which is the key to determining multi-scale hedge ratios over different time scales. Then these parametric methods are compared with the prevailing nonparametric kernel metric method. Empirical results indicate that in the China Securities Index 300 (CSI 300) index futures and spot markets, hedge ratios and hedge efficiency estimated by the nonparametric kernel metric method are inferior to those estimated by parametric hedging model based on the features of sequence distributions. In addition, if minimum-LPM is selected as a hedge target, the hedging periods, degree of risk aversion, and target returns can affect the multi-scale hedge ratios and hedge efficiency, respectively.

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

Rubel, Oliver; Loring, Burlen; Vay, Jean -Luc

The generation of short pulses of ion beams through the interaction of an intense laser with a plasma sheath offers the possibility of compact and cheaper ion sources for many applications--from fast ignition and radiography of dense targets to hadron therapy and injection into conventional accelerators. To enable the efficient analysis of large-scale, high-fidelity particle accelerator simulations using the Warp simulation suite, the authors introduce the Warp In situ Visualization Toolkit (WarpIV). WarpIV integrates state-of-the-art in situ visualization and analysis using VisIt with Warp, supports management and control of complex in situ visualization and analysis workflows, and implements integrated analyticsmore » to facilitate query- and feature-based data analytics and efficient large-scale data analysis. WarpIV enables for the first time distributed parallel, in situ visualization of the full simulation data using high-performance compute resources as the data is being generated by Warp. The authors describe the application of WarpIV to study and compare large 2D and 3D ion accelerator simulations, demonstrating significant differences in the acceleration process in 2D and 3D simulations. WarpIV is available to the public via https://bitbucket.org/berkeleylab/warpiv. The Warp In situ Visualization Toolkit (WarpIV) supports large-scale, parallel, in situ visualization and analysis and facilitates query- and feature-based analytics, enabling for the first time high-performance analysis of large-scale, high-fidelity particle accelerator simulations while the data is being generated by the Warp simulation suite. Furthermore, this supplemental material https://extras.computer.org/extra/mcg2016030022s1.pdf provides more details regarding the memory profiling and optimization and the Yee grid recentering optimization results discussed in the main article.« less

Longitudinal multigroup invariance analysis of the satisfaction with food-related life scale in university students.

PubMed

Schnettler, Berta; Miranda, Horacio; Miranda-Zapata, Edgardo; Salinas-Oñate, Natalia; Grunert, Klaus G; Lobos, Germán; Sepúlveda, José; Orellana, Ligia; Hueche, Clementina; Bonilla, Héctor

2017-06-01

This study examined longitudinal measurement invariance in the Satisfaction with Food-related Life (SWFL) scale using follow-up data from university students. We examined this measure of the SWFL in different groups of students, separated by various characteristics. Through non-probabilistic longitudinal sampling, 114 university students (65.8% female, mean age: 22.5) completed the SWFL questionnaire three times, over intervals of approximately one year. Confirmatory factor analysis was used to examine longitudinal measurement invariance. Two types of analysis were conducted: first, a longitudinal invariance by time, and second, a multigroup longitudinal invariance by sex, age, socio-economic status and place of residence during the study period. Results showed that the 3-item version of the SWFL exhibited strong longitudinal invariance (equal factor loadings and equal indicator intercepts). Longitudinal multigroup invariance analysis also showed that the 3-item version of the SWFL displays strong invariance by socio-economic status and place of residence during the study period over time. Nevertheless, it was only possible to demonstrate equivalence of the longitudinal factor structure among students of both sexes, and among those older and younger than 22 years. Generally, these findings suggest that the SWFL scale has satisfactory psychometric properties for longitudinal measurement invariance in university students with similar characteristics as the students that participated in this research. It is also possible to suggest that satisfaction with food-related life is associated with sex and age. Copyright © 2017 Elsevier Ltd. All rights reserved.

Scaling phenomena in fatigue and fracture

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

Barenblatt, G.I.

2004-12-01

The general classification of scaling laws will be presented and the basic concepts of modern similarity analysis--intermediate asymptotics, complete and incomplete similarity--will be introduced and discussed. The examples of scaling laws corresponding to complete similarity will be given. The Paris scaling law in fatigue will be discussed as an instructive example of incomplete similarity. It will be emphasized that in the Paris law the powers are not the material constants. Therefore, the evaluation of the life-time of structures using the data obtained from standard fatigue tests requires some precautions.

Measuring the impact of multiple sclerosis: Enhancing the measurement performance of the Multiple Sclerosis Impact Scale (MSIS-29) using Rasch Measurement Theory (RMT)

PubMed Central

Cleanthous, Sophie; Kinter, Elizabeth; Marquis, Patrick; Petrillo, Jennifer; You, Xiaojun; Wakeford, Craig; Sabatella, Guido

2017-01-01

Background Study objectives were to evaluate the Multiple Sclerosis Impact Scale (MSIS-29) and explore an optimized scoring structure based on empirical post-hoc analyses of data from the Phase III ADVANCE clinical trial. Methods ADVANCE MSIS-29 data from six time-points were analyzed in a sample of patients with relapsing–remitting multiple sclerosis (RRMS). Rasch Measurement Theory (RMT) analysis was undertaken to examine three broad areas: sample-to-scale targeting, measurement scale properties, and sample measurement validity. Interpretation of results led to an alternative MSIS-29 scoring structure, further evaluated alongside responsiveness of the original and revised scales at Week 48. Results RMT analysis provided mixed evidence for Physical and Psychological Impact scales that were sub-optimally targeted at the lower functioning end of the scales. Their conceptual basis could also stand to improve based on item fit results. The revised MSIS-29 rescored scales improved but did not resolve the measurement scale properties and targeting of the MSIS-29. In two out of three revised scales, responsiveness analysis indicated strengthened ability to detect change. Conclusion The revised MSIS-29 provides an initial evidence-based improved patient-reported outcome (PRO) instrument for evaluating the impact of MS. Revised scoring improves conceptual clarity and interpretation of scores by refining scale structure to include Symptoms, Psychological Impact, and General Limitations. Clinical trial ADVANCE (ClinicalTrials.gov identifier NCT00906399). PMID:29104758

Planetary-Scale Geospatial Data Analysis Techniques in Google's Earth Engine Platform (Invited)

NASA Astrophysics Data System (ADS)

Hancher, M.

2013-12-01

Geoscientists have more and more access to new tools for large-scale computing. With any tool, some tasks are easy and other tasks hard. It is natural to look to new computing platforms to increase the scale and efficiency of existing techniques, but there is a more exiting opportunity to discover and develop a new vocabulary of fundamental analysis idioms that are made easy and effective by these new tools. Google's Earth Engine platform is a cloud computing environment for earth data analysis that combines a public data catalog with a large-scale computational facility optimized for parallel processing of geospatial data. The data catalog includes a nearly complete archive of scenes from Landsat 4, 5, 7, and 8 that have been processed by the USGS, as well as a wide variety of other remotely-sensed and ancillary data products. Earth Engine supports a just-in-time computation model that enables real-time preview during algorithm development and debugging as well as during experimental data analysis and open-ended data exploration. Data processing operations are performed in parallel across many computers in Google's datacenters. The platform automatically handles many traditionally-onerous data management tasks, such as data format conversion, reprojection, resampling, and associating image metadata with pixel data. Early applications of Earth Engine have included the development of Google's global cloud-free fifteen-meter base map and global multi-decadal time-lapse animations, as well as numerous large and small experimental analyses by scientists from a range of academic, government, and non-governmental institutions, working in a wide variety of application areas including forestry, agriculture, urban mapping, and species habitat modeling. Patterns in the successes and failures of these early efforts have begun to emerge, sketching the outlines of a new set of simple and effective approaches to geospatial data analysis.

Forecasts, warnings and social response to flash floods: Is temporality a major problem? The case of the September 2005 flash flood in the Gard region (France)

NASA Astrophysics Data System (ADS)

Lutoff, C.; Anquetin, S.; Ruin, I.; Chassande, M.

2009-09-01

Flash floods are complex phenomena. The atmospheric and hydrological generating mechanisms of the phenomenon are not completely understood, leading to highly uncertain forecasts of and warnings for these events. On the other hand warning and crisis response to such violent and fast events is not a straightforward process. In both the social and physical aspect of the problem, space and time scales involved either in hydrometeorology, human behavior and social organizations sciences are of crucial importance. Forecasters, emergency managers, mayors, school superintendents, school transportation managers, first responders and road users, all have different time and space frameworks that they use to take emergency decision for themselves, their group or community. The integration of space and time scales of both the phenomenon and human activities is therefore a necessity to better deal with questions as forecasting lead-time and warning efficiency. The aim of this oral presentation is to focus on the spatio-temporal aspects of flash floods to improve our understanding of the event dynamic compared to the different scales of the social response. The authors propose a framework of analysis to compare the temporality of: i) the forecasts (from Méteo-France and from EFAS (Thielen et al., 2008)), ii) the meteorological and hydrological parameters, iii) the social response at different scales. The September 2005 event is particularly interesting for such analysis. The rainfall episode lasted nearly a week with two distinct phases separated by low intensity precipitations. Therefore the Méteo-France vigilance bulletin where somehow disconnected from the local flood’s impacts. Our analysis focuses on the timings of different types of local response, including the delicate issue of school transportation, in regard to the forecasts and the actual dynamic of the event.

Space-time analysis of snow cover change in the Romanian Carpathians (2001-2016)

NASA Astrophysics Data System (ADS)

Micu, Dana; Cosmin Sandric, Ionut

2017-04-01

Snow cover is recognized as an essential climate variable, highly sensitive to the ongoing climate warming, which plays an important role in regulating mountain ecosystems. Evidence from the existing weather stations located above 800 m over the last 50 years points out that the climate of the Romanian Carpathians is visibly changing, showing an ongoing and consistent warming process. Quantifying and attributing the changes in snow cover on various spatial and temporal scales have a great environmental and socio-economic importance for this mountain region. The study is revealing the inter-seasonal changes in the timing and distribution of snow cover across the Romanian Carpathians, by combining gridded snow data (CARPATCLIM dataset, 1961-2010) and remote sensing data (2001-2016) in specific space-time assessment at regional scale. The geostatistical approach applied in this study, based on a GIS hotspot analysis, takes advantage of all the dimensions in the datasets, in order to understand the space-time trends in this climate variable at monthly time-scale. The MODIS AQUA and TERRA images available from 2001 to 2016 have been processed using ArcGIS for Desktop and Python programming language. All the images were masked out with the Carpathians boundary. Only the pixels with snow have been retained for analysis. The regional trends in snow cover distribution and timing have been analysed using Space-Time cube with ArcGIS for Desktop, according with Esri documentation using the Mann-Kendall trend test on every location with data as an independent bin time-series test. The study aimed also to assess the location of emerging hotspots of snow cover change in Carpathians. These hotspots have been calculated using Getis-Ord Gi* statistic for each bin using Hot Spot Analysis implemented in ArcGIS for Desktop. On regional scale, snow cover appear highly sensitive to the decreasing trends in air temperatures and land surface temperatures, combined with the decrease in seasonal precipitation, especially at lower elevations in all the three divisions of the Romanian Carpathians (generally below 1,700-1,800 m). The space-time patterns of snow cover change are dominated by a significant decreasing trend of snow days and earlier spring snow melt. The key findings of this study provides robust indication of a decreasing snow trends across the Carpathian Mountain region and could provide valuable spatial and temporal snow information for other related research fields as well as for an effective environmental monitoring in the mountain ecosystems of the Carpathian region

Information transfer across the scales of climate data variability

NASA Astrophysics Data System (ADS)

Palus, Milan; Jajcay, Nikola; Hartman, David; Hlinka, Jaroslav

2015-04-01

Multitude of scales characteristic of the climate system variability requires innovative approaches in analysis of instrumental time series. We present a methodology which starts with a wavelet decomposition of a multi-scale signal into quasi-oscillatory modes of a limited band-with, described using their instantaneous phases and amplitudes. Then their statistical associations are tested in order to search for interactions across time scales. In particular, an information-theoretic formulation of the generalized, nonlinear Granger causality is applied together with surrogate data testing methods [1]. The method [2] uncovers causal influence (in the Granger sense) and information transfer from large-scale modes of climate variability with characteristic time scales from years to almost a decade to regional temperature variability on short time scales. In analyses of daily mean surface air temperature from various European locations an information transfer from larger to smaller scales has been observed as the influence of the phase of slow oscillatory phenomena with periods around 7-8 years on amplitudes of the variability characterized by smaller temporal scales from a few months to annual and quasi-biennial scales [3]. In sea surface temperature data from the tropical Pacific area an influence of quasi-oscillatory phenomena with periods around 4-6 years on the variability on and near the annual scale has been observed. This study is supported by the Ministry of Education, Youth and Sports of the Czech Republic within the Program KONTAKT II, Project No. LH14001. [1] M. Palus, M. Vejmelka, Phys. Rev. E 75, 056211 (2007) [2] M. Palus, Entropy 16(10), 5263-5289 (2014) [3] M. Palus, Phys. Rev. Lett. 112, 078702 (2014)

Scaling and design of landslide and debris-flow experiments

USGS Publications Warehouse

Iverson, Richard M.

2015-01-01

Scaling plays a crucial role in designing experiments aimed at understanding the behavior of landslides, debris flows, and other geomorphic phenomena involving grain-fluid mixtures. Scaling can be addressed by using dimensional analysis or – more rigorously – by normalizing differential equations that describe the evolving dynamics of the system. Both of these approaches show that, relative to full-scale natural events, miniaturized landslides and debris flows exhibit disproportionately large effects of viscous shear resistance and cohesion as well as disproportionately small effects of excess pore-fluid pressure that is generated by debris dilation or contraction. This behavioral divergence grows in proportion to H3, where H is the thickness of a moving mass. Therefore, to maximize geomorphological relevance, experiments with wet landslides and debris flows must be conducted at the largest feasible scales. Another important consideration is that, unlike stream flows, landslides and debris flows accelerate from statically balanced initial states. Thus, no characteristic macroscopic velocity exists to guide experiment scaling and design. On the other hand, macroscopic gravity-driven motion of landslides and debris flows evolves over a characteristic time scale (L/g)1/2, where g is the magnitude of gravitational acceleration and L is the characteristic length of the moving mass. Grain-scale stress generation within the mass occurs on a shorter time scale, H/(gL)1/2, which is inversely proportional to the depth-averaged material shear rate. A separation of these two time scales exists if the criterion H/L < < 1 is satisfied, as is commonly the case. This time scale separation indicates that steady-state experiments can be used to study some details of landslide and debris-flow behavior but cannot be used to study macroscopic landslide or debris-flow dynamics.

Applying the Pseudo-Panel Approach to International Large-Scale Assessments: A Methodology for Analyzing Subpopulation Trend Data

ERIC Educational Resources Information Center

Hooper, Martin

2017-01-01

TIMSS and PIRLS assess representative samples of students at regular intervals, measuring trends in student achievement and student contexts for learning. Because individual students are not tracked over time, analysis of international large-scale assessment data is usually conducted cross-sectionally. Gustafsson (2007) proposed examining the data…

Comparative Analysis of the Relative Validity for Subjective Time Rating Scales. Final Report.

ERIC Educational Resources Information Center

Carpenter, James B.; And Others

Since the accuracy and validity of occupational data may vary according to the rating scale format employed, the first phase of the research described in the report employed hypothetical job descriptions from which accurate criterion data could be generated. The second phase of the research required developing an occupational survey instrument…

Slow dynamics of a protein backbone in molecular dynamics simulation revealed by time-structure based independent component analysis

NASA Astrophysics Data System (ADS)

Naritomi, Yusuke; Fuchigami, Sotaro

2013-12-01

We recently proposed the method of time-structure based independent component analysis (tICA) to examine the slow dynamics involved in conformational fluctuations of a protein as estimated by molecular dynamics (MD) simulation [Y. Naritomi and S. Fuchigami, J. Chem. Phys. 134, 065101 (2011)]. Our previous study focused on domain motions of the protein and examined its dynamics by using rigid-body domain analysis and tICA. However, the protein changes its conformation not only through domain motions but also by various types of motions involving its backbone and side chains. Some of these motions might occur on a slow time scale: we hypothesize that if so, we could effectively detect and characterize them using tICA. In the present study, we investigated slow dynamics of the protein backbone using MD simulation and tICA. The selected target protein was lysine-, arginine-, ornithine-binding protein (LAO), which comprises two domains and undergoes large domain motions. MD simulation of LAO in explicit water was performed for 1 μs, and the obtained trajectory of Cα atoms in the backbone was analyzed by tICA. This analysis successfully provided us with slow modes for LAO that represented either domain motions or local movements of the backbone. Further analysis elucidated the atomic details of the suggested local motions and confirmed that these motions truly occurred on the expected slow time scale.

Long-term forecasting of internet backbone traffic.

PubMed

Papagiannaki, Konstantina; Taft, Nina; Zhang, Zhi-Li; Diot, Christophe

2005-09-01

We introduce a methodology to predict when and where link additions/upgrades have to take place in an Internet protocol (IP) backbone network. Using simple network management protocol (SNMP) statistics, collected continuously since 1999, we compute aggregate demand between any two adjacent points of presence (PoPs) and look at its evolution at time scales larger than 1 h. We show that IP backbone traffic exhibits visible long term trends, strong periodicities, and variability at multiple time scales. Our methodology relies on the wavelet multiresolution analysis (MRA) and linear time series models. Using wavelet MRA, we smooth the collected measurements until we identify the overall long-term trend. The fluctuations around the obtained trend are further analyzed at multiple time scales. We show that the largest amount of variability in the original signal is due to its fluctuations at the 12-h time scale. We model inter-PoP aggregate demand as a multiple linear regression model, consisting of the two identified components. We show that this model accounts for 98% of the total energy in the original signal, while explaining 90% of its variance. Weekly approximations of those components can be accurately modeled with low-order autoregressive integrated moving average (ARIMA) models. We show that forecasting the long term trend and the fluctuations of the traffic at the 12-h time scale yields accurate estimates for at least 6 months in the future.

Principal regression analysis and the index leverage effect

NASA Astrophysics Data System (ADS)

Reigneron, Pierre-Alain; Allez, Romain; Bouchaud, Jean-Philippe

2011-09-01

We revisit the index leverage effect, that can be decomposed into a volatility effect and a correlation effect. We investigate the latter using a matrix regression analysis, that we call ‘Principal Regression Analysis' (PRA) and for which we provide some analytical (using Random Matrix Theory) and numerical benchmarks. We find that downward index trends increase the average correlation between stocks (as measured by the most negative eigenvalue of the conditional correlation matrix), and makes the market mode more uniform. Upward trends, on the other hand, also increase the average correlation between stocks but rotates the corresponding market mode away from uniformity. There are two time scales associated to these effects, a short one on the order of a month (20 trading days), and a longer time scale on the order of a year. We also find indications of a leverage effect for sectorial correlations as well, which reveals itself in the second and third mode of the PRA.

5nsec Dead time multichannel scaling system for Mössbauer spectrometer

NASA Astrophysics Data System (ADS)

Verrastro, C.; Trombetta, G.; Pita, A.; Saragovi, C.; Duhalde, S.

1991-11-01

A PC programmable and fast multichannel scaling module has been designed to use a commercial Mössbauer spectrometer. This module is based on a 10 single chip 8 bits microcomputer (MC6805) and on a 35 fast ALU, which allows a high performance and low cost system. The module can operate in a stand-alone mode. Data analysis are performed in real time display, on XT/AT IBM PC or compatibles. The channels are ranged between 256 and 4096, the maximum number of counts is 232-1 per channel, the dwell time is 3 μsec and the dead time between channels is 5 nsec. A friendly software display the real time spectrum and offers menues with different options at each state.

IRIS COLOUR CLASSIFICATION SCALES – THEN AND NOW

PubMed Central

Grigore, Mariana; Avram, Alina

2015-01-01

Eye colour is one of the most obvious phenotypic traits of an individual. Since the first documented classification scale developed in 1843, there have been numerous attempts to classify the iris colour. In the past centuries, iris colour classification scales has had various colour categories and mostly relied on comparison of an individual’s eye with painted glass eyes. Once photography techniques were refined, standard iris photographs replaced painted eyes, but this did not solve the problem of painted/ printed colour variability in time. Early clinical scales were easy to use, but lacked objectivity and were not standardised or statistically tested for reproducibility. The era of automated iris colour classification systems came with the technological development. Spectrophotometry, digital analysis of high-resolution iris images, hyper spectral analysis of the human real iris and the dedicated iris colour analysis software, all accomplished an objective, accurate iris colour classification, but are quite expensive and limited in use to research environment. Iris colour classification systems evolved continuously due to their use in a wide range of studies, especially in the fields of anthropology, epidemiology and genetics. Despite the wide range of the existing scales, up until present there has been no generally accepted iris colour classification scale. PMID:27373112

IRIS COLOUR CLASSIFICATION SCALES--THEN AND NOW.

PubMed

Grigore, Mariana; Avram, Alina

2015-01-01

Eye colour is one of the most obvious phenotypic traits of an individual. Since the first documented classification scale developed in 1843, there have been numerous attempts to classify the iris colour. In the past centuries, iris colour classification scales has had various colour categories and mostly relied on comparison of an individual's eye with painted glass eyes. Once photography techniques were refined, standard iris photographs replaced painted eyes, but this did not solve the problem of painted/ printed colour variability in time. Early clinical scales were easy to use, but lacked objectivity and were not standardised or statistically tested for reproducibility. The era of automated iris colour classification systems came with the technological development. Spectrophotometry, digital analysis of high-resolution iris images, hyper spectral analysis of the human real iris and the dedicated iris colour analysis software, all accomplished an objective, accurate iris colour classification, but are quite expensive and limited in use to research environment. Iris colour classification systems evolved continuously due to their use in a wide range of studies, especially in the fields of anthropology, epidemiology and genetics. Despite the wide range of the existing scales, up until present there has been no generally accepted iris colour classification scale.

Factors Affecting the Inter-annual to Centennial Time Scale Variability of All Indian Summer Monsoon Rainfall

NASA Astrophysics Data System (ADS)

Malik, Abdul; Brönnimann, Stefan

2016-04-01

The All Indian Summer Monsoon Rainfall (AISMR) is highly important for the livelihood of more than 1 billion people living in the Indian sub-continent. The agriculture of this region is heavily dependent on seasonal (JJAS) monsoon rainfall. An early start or a slight delay of monsoon, or an early withdrawal or prolonged monsoon season may upset the farmer's agricultural plans, can cause significant reduction in crop yield, and hence economic loss. Understanding of AISMR is also vital because it is a part of global atmospheric circulation system. Several studies show that AISMR is influenced by internal climate forcings (ICFs) viz. ENSO, AMO, PDO etc. as well as external climate forcings (ECFs) viz. Greenhouse Gases, volcanic eruptions, and Total Solar Irradiance (TSI). We investigate the influence of ICFs and ECFs on AISMR using recently developed statistical technique called De-trended Partial-Cross-Correlation Analysis (DPCCA). DPCCA can analyse a complex system of several interlinked variables. Often, climatic variables, being cross correlated, are simultaneously tele-connected with several other variables and it is not easy to isolate their intrinsic relationship. In the presence of non-stationarities and background signals the calculated correlation coefficients can be overestimated and erroneous. DPCCA method removes the non-stationarities and partials out the influence of background signals from the variables being cross correlated and thus give a robust estimate of correlation. We have performed the analysis using NOAA Reconstructed SSTs and homogenised instrumental AISMR data set from 1854-1999. By employing the DPCCA method we find that there is a statistically insignificant negative intrinsic relation (by excluding the influence of ICFs, and ECFs except TSI) between AISMR and TSI on decadal to centennial time scale. The ICFs considerably modulate the relation between AISMR and solar activity between 50-80 year time scales and transform this relationship to statistically significant positive. We conclude that the positive relation between AISMR and solar activity, as found by other authors, is due to the combined effect of AMO, PDO and multi-decadal ENSO variability on AISMR. The solar activity influences the ICFs and this influence is then transmitted to AISMR. Further, we find that there is statistically positive intrinsic relation between AISMR and AMO from 26 to 100 year time scales which is modulated by ICFs (PDO, ENSO) and ECFs. PDO, ENSO, and solar activity weaken this intrinsic relationship whereas the combined effect of ECFc (solar activity, volcanic eruptions, CO2, & tropospheric aerosol optical depth) results in strengthening of this relationship from 70 to 100 year time scales. There is a negative intrinsic relation between AISMR and PDO which is not statistically significant at any time scale. However this relationship becomes statistically significant only in the presence of combined effect of North Atlantic SSTs and ENSO (4-39 year time scale) and individual effect of TSI (3-26 year time scale) on AISMR. We also find that there is statistical significant negative relationship between AISMR and ENSO on inter-annual to centennial time scale and the strength of this relationship is modulated by solar activity from 3 to 40 year time scale.

An operational global-scale ocean thermal analysis system

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

Clancy, R. M.; Pollak, K.D.; Phoebus, P.A.

1990-04-01

The Optimum Thermal Interpolation System (OTIS) is an ocean thermal analysis system designed for operational use at FNOC. It is based on the optimum interpolation of the assimilation technique and functions in an analysis-prediction-analysis data assimilation cycle with the TOPS mixed-layer model. OTIS provides a rigorous framework for combining real-time data, climatology, and predictions from numerical ocean prediction models to produce a large-scale synoptic representation of ocean thermal structure. The techniques and assumptions used in OTIS are documented and results of operational tests of global scale OTIS at FNOC are presented. The tests involved comparisons of OTIS against an existingmore » operational ocean thermal structure model and were conducted during February, March, and April 1988. Qualitative comparison of the two products suggests that OTIS gives a more realistic representation of subsurface anomalies and horizontal gradients and that it also gives a more accurate analysis of the thermal structure, with improvements largest below the mixed layer. 37 refs.« less

Multiscale wavelet representations for mammographic feature analysis

NASA Astrophysics Data System (ADS)

Laine, Andrew F.; Song, Shuwu

1992-12-01

This paper introduces a novel approach for accomplishing mammographic feature analysis through multiresolution representations. We show that efficient (nonredundant) representations may be identified from digital mammography and used to enhance specific mammographic features within a continuum of scale space. The multiresolution decomposition of wavelet transforms provides a natural hierarchy in which to embed an interactive paradigm for accomplishing scale space feature analysis. Choosing wavelets (or analyzing functions) that are simultaneously localized in both space and frequency, results in a powerful methodology for image analysis. Multiresolution and orientation selectivity, known biological mechanisms in primate vision, are ingrained in wavelet representations and inspire the techniques presented in this paper. Our approach includes local analysis of complete multiscale representations. Mammograms are reconstructed from wavelet coefficients, enhanced by linear, exponential and constant weight functions localized in scale space. By improving the visualization of breast pathology we can improve the changes of early detection of breast cancers (improve quality) while requiring less time to evaluate mammograms for most patients (lower costs).

Large-scale kinetic energy spectra from Eulerian analysis of EOLE wind data

NASA Technical Reports Server (NTRS)

Desbois, M.

1975-01-01

A data set of 56,000 winds determined from the horizontal displacements of EOLE balloons at the 200 mb level in the Southern Hemisphere during the period October 1971-February 1972 is utilized for the computation of planetary- and synoptic-scale kinetic energy space spectra. However, the random distribution of measurements in space and time presents some problems for the spectral analysis. Two different approaches are used, i.e., a harmonic analysis of daily wind values at equi-distant points obtained by space-time interpolation of the data, and a correlation method using the direct measurements. Both methods give similar results for small wavenumbers, but the second is more accurate for higher wavenumbers (k above or equal to 10). The spectra show a maximum at wavenumbers 5 and 6 due to baroclinic instability and then decrease for high wavenumbers up to wavenumber 35 (which is the limit of the analysis), according to the inverse power law k to the negative p, with p close to 3.

Quantifying the Metrics That Characterize Safety Culture of Three Engineered Systems

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

Tucker, Julie; Ernesti, Mary; Tokuhiro, Akira

2002-07-01

With potential energy shortages and increasing electricity demand, the nuclear energy option is being reconsidered in the United States. Public opinion will have a considerable voice in policy decisions that will 'road-map' the future of nuclear energy in this country. This report is an extension of the last author's work on the 'safety culture' associated with three engineered systems (automobiles, commercial airplanes, and nuclear power plants) in Japan and the United States. Safety culture, in brief is defined as a specifically developed culture based on societal and individual interpretations of the balance of real, perceived, and imagined risks versus themore » benefits drawn from utilizing a given engineered systems. The method of analysis is a modified scale analysis, with two fundamental Eigen-metrics, time- (t) and number-scales (N) that describe both engineered systems and human factors. The scale analysis approach is appropriate because human perception of risk, perception of benefit and level of (technological) acceptance are inherently subjective, therefore 'fuzzy' and rarely quantifiable in exact magnitude. Perception of risk, expressed in terms of the psychometric factors 'dread risk' and 'unknown risk', contains both time- and number-scale elements. Various engineering system accidents with fatalities, reported by mass media are characterized by t and N, and are presented in this work using the scale analysis method. We contend that level of acceptance infers a perception of benefit at least two orders larger magnitude than perception of risk. The 'amplification' influence of mass media is also deduced as being 100- to 1000-fold the actual number of fatalities/serious injuries in a nuclear-related accident. (authors)« less

The ability of clinical balance measures to identify falls risk in multiple sclerosis: a systematic review and meta-analysis.

PubMed

Quinn, Gillian; Comber, Laura; Galvin, Rose; Coote, Susan

2018-05-01

To determine the ability of clinical measures of balance to distinguish fallers from non-fallers and to determine their predictive validity in identifying those at risk of falls. AMED, CINAHL, Medline, Scopus, PubMed Central and Google Scholar. First search: July 2015. Final search: October 2017. Inclusion criteria were studies of adults with a definite multiple sclerosis diagnosis, a clinical balance assessment and method of falls recording. Data were extracted independently by two reviewers. Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 scale and the modified Newcastle-Ottawa Quality Assessment Scale. Statistical analysis was conducted for the cross-sectional studies using Review Manager 5. The mean difference with 95% confidence interval in balance outcomes between fallers and non-fallers was used as the mode of analysis. We included 33 studies (19 cross-sectional, 5 randomised controlled trials, 9 prospective) with a total of 3901 participants, of which 1917 (49%) were classified as fallers. The balance measures most commonly reported were the Berg Balance Scale, Timed Up and Go and Falls Efficacy Scale International. Meta-analysis demonstrated fallers perform significantly worse than non-fallers on all measures analysed except the Timed Up and Go Cognitive ( p < 0.05), but discriminative ability of the measures is commonly not reported. Of those reported, the Activities-specific Balance Confidence Scale had the highest area under the receiver operating characteristic curve value (0.92), but without reporting corresponding measures of clinical utility. Clinical measures of balance differ significantly between fallers and non-fallers but have poor predictive ability for falls risk in people with multiple sclerosis.

Return Intervals Approach to Financial Fluctuations

NASA Astrophysics Data System (ADS)

Wang, Fengzhong; Yamasaki, Kazuko; Havlin, Shlomo; Stanley, H. Eugene

Financial fluctuations play a key role for financial markets studies. A new approach focusing on properties of return intervals can help to get better understanding of the fluctuations. A return interval is defined as the time between two successive volatilities above a given threshold. We review recent studies and analyze the 1000 most traded stocks in the US stock markets. We find that the distribution of the return intervals has a well approximated scaling over a wide range of thresholds. The scaling is also valid for various time windows from one minute up to one trading day. Moreover, these results are universal for stocks of different countries, commodities, interest rates as well as currencies. Further analysis shows some systematic deviations from a scaling law, which are due to the nonlinear correlations in the volatility sequence. We also examine the memory in return intervals for different time scales, which are related to the long-term correlations in the volatility. Furthermore, we test two popular models, FIGARCH and fractional Brownian motion (fBm). Both models can catch the memory effect but only fBm shows a good scaling in the return interval distribution.

Affective stress responses during leisure time: Validity evaluation of a modified version of the Stress-Energy Questionnaire.

PubMed

Hadžibajramović, Emina; Ahlborg, Gunnar; Håkansson, Carita; Lundgren-Nilsson, Åsa; Grimby-Ekman, Anna

2015-12-01

Psychosocial stress at work is one of the most important factors behind increasing sick-leave rates. In addition to work stressors, it is important to account for non-work-related stressors when assessing stress responses. In this study, a modified version of the Stress-Energy Questionnaire (SEQ), the SEQ during leisure time (SEQ-LT) was introduced for assessing the affective stress response during leisure time. The aim of this study was to investigate the internal construct validity of the SEQ-LT. A second aim was to define the cut-off points for the scales, which could indicate high and low levels of leisure-time stress and energy, respectively. Internal construct validity of the SEQ-LT was evaluated using a Rasch analysis. We examined the unidimensionality and other psychometric properties of the scale by the fit to the Rasch model. A criterion-based approach was used for classification into high and low stress/energy levels. The psychometric properties of the stress and energy scales of the SEQ-LT were satisfactory, having accommodated for local dependency. The cut-off point for low stress was proposed to be in the interval between 2.45 and 3.02 on the Rasch metric score; while for high stress, it was between 3.65 and 3.90. The suggested cut-off points for the low and high energy levels were values between 1.73-1.97 and 2.66-3.08, respectively. The stress and energy scale of the SEQ-LT satisfied the measurement criteria defined by the Rasch analysis and it provided a useful tool for non-work-related assessment of stress responses. We provide guidelines on how to interpret the scale values. © 2015 the Nordic Societies of Public Health.

Effects of large-scale wind driven turbulence on sound propagation

NASA Technical Reports Server (NTRS)

Noble, John M.; Bass, Henry E.; Raspet, Richard

1990-01-01

Acoustic measurements made in the atmosphere have shown significant fluctuations in amplitude and phase resulting from the interaction with time varying meteorological conditions. The observed variations appear to have short term and long term (1 to 5 minutes) variations at least in the phase of the acoustic signal. One possible way to account for this long term variation is the use of a large scale wind driven turbulence model. From a Fourier analysis of the phase variations, the outer scales for the large scale turbulence is 200 meters and greater, which corresponds to turbulence in the energy-containing subrange. The large scale turbulence is assumed to be elongated longitudinal vortex pairs roughly aligned with the mean wind. Due to the size of the vortex pair compared to the scale of the present experiment, the effect of the vortex pair on the acoustic field can be modeled as the sound speed of the atmosphere varying with time. The model provides results with the same trends and variations in phase observed experimentally.

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

Rapid climate fluctuations over the past millennium: evidence from a lacustrine record of Basomtso Lake, southeastern Tibetan Plateau

PubMed Central

Li, Kai; Liu, Xingqi; Herzschuh, Ulrike; Wang, Yongbo

2016-01-01

Abrupt climate changes and fluctuations over short time scales are superimposed on long-term climate changes. Understanding rapid climate fluctuations at the decadal time scale over the past millennium will enhance our understanding of patterns of climate variability and aid in forecasting climate changes in the future. In this study, climate changes on the southeastern Tibetan Plateau over the past millennium were determined from a 4.82-m-long sediment core from Basomtso Lake. At the centennial time scale, the Medieval Climate Anomaly (MCA), Little Ice Age (LIA) and Current Warm Period (CWP) are distinct in the Basomtso region. Rapid climate fluctuations inferred from five episodes with higher sediment input and likely warmer conditions, as well as seven episodes with lower sediment input and likely colder conditions, were well preserved in our record. These episodes with higher and lower sediment input are characterized by abrupt climate changes and short time durations. Spectral analysis indicates that the climate variations at the centennial scale on the southeastern Tibetan Plateau are influenced by solar activity during the past millennium. PMID:27091591

Reduced linear noise approximation for biochemical reaction networks with time-scale separation: The stochastic tQSSA+

NASA Astrophysics Data System (ADS)

Herath, Narmada; Del Vecchio, Domitilla

2018-03-01

Biochemical reaction networks often involve reactions that take place on different time scales, giving rise to "slow" and "fast" system variables. This property is widely used in the analysis of systems to obtain dynamical models with reduced dimensions. In this paper, we consider stochastic dynamics of biochemical reaction networks modeled using the Linear Noise Approximation (LNA). Under time-scale separation conditions, we obtain a reduced-order LNA that approximates both the slow and fast variables in the system. We mathematically prove that the first and second moments of this reduced-order model converge to those of the full system as the time-scale separation becomes large. These mathematical results, in particular, provide a rigorous justification to the accuracy of LNA models derived using the stochastic total quasi-steady state approximation (tQSSA). Since, in contrast to the stochastic tQSSA, our reduced-order model also provides approximations for the fast variable stochastic properties, we term our method the "stochastic tQSSA+". Finally, we demonstrate the application of our approach on two biochemical network motifs found in gene-regulatory and signal transduction networks.

Extended principle component analysis - a useful tool to understand processes governing water quality at catchment scales

NASA Astrophysics Data System (ADS)

Selle, B.; Schwientek, M.

2012-04-01

Water quality of ground and surface waters in catchments is typically driven by many complex and interacting processes. While small scale processes are often studied in great detail, their relevance and interplay at catchment scales remain often poorly understood. For many catchments, extensive monitoring data on water quality have been collected for different purposes. These heterogeneous data sets contain valuable information on catchment scale processes but are rarely analysed using integrated methods. Principle component analysis (PCA) has previously been applied to this kind of data sets. However, a detailed analysis of scores, which are an important result of a PCA, is often missing. Mathematically, PCA expresses measured variables on water quality, e.g. nitrate concentrations, as linear combination of independent, not directly observable key processes. These computed key processes are represented by principle components. Their scores are interpretable as process intensities which vary in space and time. Subsequently, scores can be correlated with other key variables and catchment characteristics, such as water travel times and land use that were not considered in PCA. This detailed analysis of scores represents an extension of the commonly applied PCA which could considerably improve the understanding of processes governing water quality at catchment scales. In this study, we investigated the 170 km2 Ammer catchment in SW Germany which is characterised by an above average proportion of agricultural (71%) and urban (17%) areas. The Ammer River is mainly fed by karstic springs. For PCA, we separately analysed concentrations from (a) surface waters of the Ammer River and its tributaries, (b) spring waters from the main aquifers and (c) deep groundwater from production wells. This analysis was extended by a detailed analysis of scores. We analysed measured concentrations on major ions and selected organic micropollutants. Additionally, redox-sensitive variables and environmental tracers indicating groundwater age were analysed for deep groundwater from production wells. For deep groundwater, we found that microbial turnover was stronger influenced by local availability of energy sources than by travel times of groundwater to the wells. Groundwater quality primarily reflected the input of pollutants determined by landuse, e.g. agrochemicals. We concluded that for water quality in the Ammer catchment, conservative mixing of waters with different origin is more important than reactive transport processes along the flow path.

Effects of reward context on feedback processing as indexed by time-frequency analysis.

PubMed

Watts, Adreanna T M; Bernat, Edward M

2018-05-11

The role of reward context has been investigated as an important factor in feedback processing. Previous work has demonstrated that the amplitude of the feedback negativity (FN) depends on the value of the outcome relative to the range of possible outcomes in a given context, not the objective value of the outcome. However, some research has shown that the FN does not scale with loss magnitude in loss-only contexts, suggesting that some contexts do not show a pattern of context dependence. Methodologically, time-frequency decomposition techniques have proven useful for isolating time-domain ERP activity as separable processes indexed in delta (< 3 Hz) and theta (3-7 Hz). Thus, the current study assessed the role of context in a modified gambling feedback task using time-frequency analysis to better isolate the underlying processes. Results revealed that theta was more context dependent and reflected a binary evaluation of bad versus good outcomes in the gain and even contexts. Delta was more context independent: good outcomes scaled linearly with reward magnitude and good-bad differences scaled with context valence. Our findings reveal that theta and delta are differentially sensitive to context and that context valence may play a critical role in determining how the brain processes feedback. © 2018 Society for Psychophysiological Research.

Item response theory analysis of the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised in the Pooled Resource Open-Access ALS Clinical Trials Database.

PubMed

Bacci, Elizabeth D; Staniewska, Dorota; Coyne, Karin S; Boyer, Stacey; White, Leigh Ann; Zach, Neta; Cedarbaum, Jesse M

2016-01-01

Our objective was to examine dimensionality and item-level performance of the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) across time using classical and modern test theory approaches. Confirmatory factor analysis (CFA) and Item Response Theory (IRT) analyses were conducted using data from patients with amyotrophic lateral sclerosis (ALS) Pooled Resources Open-Access ALS Clinical Trials (PRO-ACT) database with complete ALSFRS-R data (n = 888) at three time-points (Time 0, Time 1 (6-months), Time 2 (1-year)). Results demonstrated that in this population of 888 patients, mean age was 54.6 years, 64.4% were male, and 93.7% were Caucasian. The CFA supported a 4* individual-domain structure (bulbar, gross motor, fine motor, and respiratory domains). IRT analysis within each domain revealed misfitting items and overlapping item response category thresholds at all time-points, particularly in the gross motor and respiratory domain items. Results indicate that many of the items of the ALSFRS-R may sub-optimally distinguish among varying levels of disability assessed by each domain, particularly in patients with less severe disability. Measure performance improved across time as patient disability severity increased. In conclusion, modifications to select ALSFRS-R items may improve the instrument's specificity to disability level and sensitivity to treatment effects.

Scalewise invariant analysis of the anisotropic Reynolds stress tensor for atmospheric surface layer and canopy sublayer turbulent flows

NASA Astrophysics Data System (ADS)

Brugger, Peter; Katul, Gabriel G.; De Roo, Frederik; Kröniger, Konstantin; Rotenberg, Eyal; Rohatyn, Shani; Mauder, Matthias

2018-05-01

Anisotropy in the turbulent stress tensor, which forms the basis of invariant analysis, is conducted using velocity time series measurements collected in the canopy sublayer (CSL) and the atmospheric surface layer (ASL). The goal is to assess how thermal stratification and surface roughness conditions simultaneously distort the scalewise relaxation towards isotropic state from large to small scales when referenced to homogeneous turbulence. To achieve this goal, conventional invariant analysis is extended to allow scalewise information about relaxation to isotropy in physical (instead of Fourier) space to be incorporated. The proposed analysis shows that the CSL is more isotropic than its ASL counterpart at large, intermediate, and small (or inertial) scales irrespective of the thermal stratification. Moreover, the small (or inertial) scale anisotropy is more prevalent in the ASL when compared to the CSL, a finding that cannot be fully explained by the intensity of the mean velocity gradient acting on all scales. Implications to the validity of scalewise Rotta and Lumley models for return to isotropy as well as advantages to using barycentric instead of anisotropy invariant maps for such scalewise analysis are discussed.

Wagering the future: Cognitive distortions, impulsivity, delay discounting, and time perspective in adolescent gambling.

PubMed

Cosenza, Marina; Nigro, Giovanna

2015-12-01

This study investigated the relationship of cognitive distortions, self-reported impulsivity, delay discounting, and time perspective to gambling severity in Italian adolescents. One thousand and thirty high school students were administered the South Oaks Gambling Screen Revised for Adolescents (SOGS-RA), the Gambling Related Cognitions Scale (GRCS), the Barratt Impulsiveness Scale (BIS-11), the Monetary Choice Questionnaire (MCQ), and the Consideration of Future Consequences Scale (CFC-14). A factor analysis, used to evaluate common factors assessed by the different measures, revealed a three-factor structure of Cognitive distortions, Impulsive present orientation, and Delay discounting. The results of regression analysis using factor scores showed that males scored higher than females on the SOGS-RA and that gambling severity correlated positively with high scores on the three factors. These results indicate that cognitive distortions associated with gambling are a powerful predictor of gambling severity, and that adolescent gamblers are impaired in their abilities to think about the future. Copyright © 2015. Published by Elsevier Ltd.

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

DOE PAGES

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.; ...

2016-10-20

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.« less

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

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

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.« less

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

PubMed Central

Sippel, Sebastian; Mahecha, Miguel D.; Hauhs, Michael; Bodesheim, Paul; Kaminski, Thomas; Gans, Fabian; Rosso, Osvaldo A.

2016-01-01

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observed and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. We demonstrate here that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics. PMID:27764187

The influence of coping styles on long-term employment in multiple sclerosis: A prospective study.

PubMed

Grytten, Nina; Skår, Anne Br; Aarseth, Jan Harald; Assmus, Jorg; Farbu, Elisabeth; Lode, Kirsten; Nyland, Harald I; Smedal, Tori; Myhr, Kjell Morten

2017-06-01

The aim was to investigate predictive values of coping styles, clinical and demographic factors on time to unemployment in patients diagnosed with multiple sclerosis (MS) during 1998-2002 in Norway. All patients ( N = 108) diagnosed with MS 1998-2002 in Hordaland and Rogaland counties, Western Norway, were invited to participate in the long-term follow-up study in 2002. Baseline recordings included disability scoring (Expanded Disability Status Scale (EDSS)), fatigue (Fatigue Severity Scale (FSS)), depression (Beck Depression Inventory (BDI)), and questionnaire assessing coping (the Dispositional Coping Styles Scale (COPE)). Logistic regression analysis was used to identify factors associated with unemployed at baseline, and Cox regression analysis to identify factors at baseline associated with time to unemployment during follow-up. In all, 41 (44%) were employed at baseline. After 13 years follow-up in 2015, mean disease duration of 22 years, 16 (17%) were still employed. Median time from baseline to unemployment was 6 years (±5). Older age at diagnosis, female gender, and depression were associated with patients being unemployed at baseline. Female gender, long disease duration, and denial as avoidant coping strategy at baseline predicted shorter time to unemployment. Avoidant coping style, female gender, and longer disease duration were associated with shorter time to unemployment. These factors should be considered when advising patients on MS and future employment.

Scaled boundary finite element simulation and modeling of the mechanical behavior of cracked nanographene sheets

NASA Astrophysics Data System (ADS)

Honarmand, M.; Moradi, M.

2018-06-01

In this paper, by using scaled boundary finite element method (SBFM), a perfect nanographene sheet or cracked ones were simulated for the first time. In this analysis, the atomic carbon bonds were modeled by simple bar elements with circular cross-sections. Despite of molecular dynamics (MD), the results obtained from SBFM analysis are quite acceptable for zero degree cracks. For all angles except zero, Griffith criterion can be applied for the relation between critical stress and crack length. Finally, despite the simplifications used in nanographene analysis, obtained results can simulate the mechanical behavior with high accuracy compared with experimental and MD ones.

Inferring changes in water cycle dynamics of intensively managed landscapes via the theory of time-variant travel time distributions

NASA Astrophysics Data System (ADS)

Danesh-Yazdi, Mohammad; Foufoula-Georgiou, Efi; Karwan, Diana L.; Botter, Gianluca

2016-10-01

Climatic trends and anthropogenic changes in land cover and land use are impacting the hydrology and water quality of streams at the field, watershed, and regional scales in complex ways. In poorly drained agricultural landscapes, subsurface drainage systems have been successful in increasing crop productivity by removing excess soil moisture. However, their hydroecological consequences are still debated in view of the observed increased concentrations of nitrate, phosphorus, and pesticides in many streams, as well as altered runoff volumes and timing. In this study, we employ the recently developed theory of time-variant travel time distributions within the StorAge Selection function framework to quantify changes in water cycle dynamics resulting from the combined climate and land use changes. Our results from analysis of a subbasin in the Minnesota River Basin indicate a significant decrease in the mean travel time of water in the shallow subsurface layer during the growing season under current conditions compared to the pre-1970s conditions. We also find highly damped year-to-year fluctuations in the mean travel time, which we attribute to the "homogenization" of the hydrologic response due to artificial drainage. The dependence of the mean travel time on the spatial heterogeneity of some soil characteristics as well as on the basin scale is further explored via numerical experiments. Simulations indicate that the mean travel time is independent of scale for spatial scales larger than approximately 200 km2, suggesting that hydrologic data from larger basins may be used to infer the average of smaller-scale-driven changes in water cycle dynamics.

Atomistic details of protein dynamics and the role of hydration water

DOE PAGES

Khodadadi, Sheila; Sokolov, Alexei P.

2016-05-04

The importance of protein dynamics for their biological activity is nowwell recognized. Different experimental and computational techniques have been employed to study protein dynamics, hierarchy of different processes and the coupling between protein and hydration water dynamics. But, understanding the atomistic details of protein dynamics and the role of hydration water remains rather limited. Based on overview of neutron scattering, molecular dynamic simulations, NMR and dielectric spectroscopy results we present a general picture of protein dynamics covering time scales from faster than ps to microseconds and the influence of hydration water on different relaxation processes. Internal protein dynamics spread overmore » a wide time range fromfaster than picosecond to longer than microseconds. We suggest that the structural relaxation in hydrated proteins appears on the microsecond time scale, while faster processes present mostly motion of side groups and some domains. Hydration water plays a crucial role in protein dynamics on all time scales. It controls the coupled protein-hydration water relaxation on 10 100 ps time scale. Our process defines the friction for slower protein dynamics. Analysis suggests that changes in amount of hydration water affect not only general friction, but also influence significantly the protein's energy landscape.« less

Testing our scenario of a failed wind for TW Hya

NASA Astrophysics Data System (ADS)

Guenther, Hans

2017-08-01

Young, accreting low-mass stars show strong, broad and asymmetric FUV emission lines. When multiple observations of the same wavelength region exist, we often see that the flux and profile of these lines change strongly between the observations. Observationally, this is poorly characterized, and theoretically, neither the lines profiles nor their variability can be explained. In 2011 we tried to remedy this situation by monitoring the classical Tauri star TW Hya for 10 orbits with HST/COS. At the time, the literature suggested that the variability could be due to a hot stellar wind and thus we distributed the observations over one month, which would have been the appropriate time scale. As it turns out, this assumption appears to have been wrong. The data we received clearly shows that no hot wind is present and that all variability happens on much shorter time scales. In this proposal, we show that we have done a thorough analysis of the existing data and we have a model to explain it. Now, we ask for additional monitoring of TW Hya to cover the time scale of a few hours - as we now know this is the relevant time scale to understand the variability.

Time-dependent vibrational spectral analysis of first principles trajectory of methylamine with wavelet transform.

PubMed

Biswas, Sohag; Mallik, Bhabani S

2017-04-12

The fluctuation dynamics of amine stretching frequencies, hydrogen bonds, dangling N-D bonds, and the orientation profile of the amine group of methylamine (MA) were investigated under ambient conditions by means of dispersion-corrected density functional theory-based first principles molecular dynamics (FPMD) simulations. Along with the dynamical properties, various equilibrium properties such as radial distribution function, spatial distribution function, combined radial and angular distribution functions and hydrogen bonding were also calculated. The instantaneous stretching frequencies of amine groups were obtained by wavelet transform of the trajectory obtained from FPMD simulations. The frequency-structure correlation reveals that the amine stretching frequency is weakly correlated with the nearest nitrogen-deuterium distance. The frequency-frequency correlation function has a short time scale of around 110 fs and a longer time scale of about 1.15 ps. It was found that the short time scale originates from the underdamped motion of intact hydrogen bonds of MA pairs. However, the long time scale of the vibrational spectral diffusion of N-D modes is determined by the overall dynamics of hydrogen bonds as well as the dangling ND groups and the inertial rotation of the amine group of the molecule.

Atomistic details of protein dynamics and the role of hydration water

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

Khodadadi, Sheila; Sokolov, Alexei P.

The importance of protein dynamics for their biological activity is nowwell recognized. Different experimental and computational techniques have been employed to study protein dynamics, hierarchy of different processes and the coupling between protein and hydration water dynamics. But, understanding the atomistic details of protein dynamics and the role of hydration water remains rather limited. Based on overview of neutron scattering, molecular dynamic simulations, NMR and dielectric spectroscopy results we present a general picture of protein dynamics covering time scales from faster than ps to microseconds and the influence of hydration water on different relaxation processes. Internal protein dynamics spread overmore » a wide time range fromfaster than picosecond to longer than microseconds. We suggest that the structural relaxation in hydrated proteins appears on the microsecond time scale, while faster processes present mostly motion of side groups and some domains. Hydration water plays a crucial role in protein dynamics on all time scales. It controls the coupled protein-hydration water relaxation on 10 100 ps time scale. Our process defines the friction for slower protein dynamics. Analysis suggests that changes in amount of hydration water affect not only general friction, but also influence significantly the protein's energy landscape.« less

Nudging and predictability in regional climate modelling: investigation in a nested quasi-geostrophic model

NASA Astrophysics Data System (ADS)

Omrani, Hiba; Drobinski, Philippe; Dubos, Thomas

2010-05-01

In this work, we consider the effect of indiscriminate and spectral nudging on the large and small scales of an idealized model simulation. The model is a two layer quasi-geostrophic model on the beta-plane driven at its boundaries by the « global » version with periodic boundary condition. This setup mimics the configuration used for regional climate modelling. The effect of large-scale nudging is studied by using the "perfect model" approach. Two sets of experiments are performed: (1) the effect of nudging is investigated with a « global » high resolution two layer quasi-geostrophic model driven by a low resolution two layer quasi-geostrophic model. (2) similar simulations are conducted with the two layer quasi-geostrophic Limited Area Model (LAM) where the size of the LAM domain comes into play in addition to the first set of simulations. The study shows that the indiscriminate nudging time that minimizes the error at both the large and small scales is reached for a nudging time close to the predictability time, for spectral nudging, the optimum nudging time should tend to zero since the best large scale dynamics is supposed to be given by the driving large-scale fields are generally given at much lower frequency than the model time step(e,g, 6-hourly analysis) with a basic interpolation between the fields, the optimum nudging time differs from zero, however remaining smaller than the predictability time.

Anomalous diffusion of a probe in a bath of active granular chains

NASA Astrophysics Data System (ADS)

Jerez, Michael Jade Y.; Confesor, Mark Nolan P.; Carpio-Bernido, M. Victoria; Bernido, Christopher C.

2017-08-01

We investigate the dynamics of a passive probe particle in a bath of active granular chains (AGC). The bath and the probe are enclosed in an experimental compartment with a sinusoidal boundary to prevent AGC congestion along the boundary while connected to an electrodynamic shaker. Single AGC trajectory analysis reveals a persistent type of motion compared to a purely Brownian motion as seen in its mean squared displacement (MSD). It was found that at small concentration, Φ ≤ 0.44, the MSD exhibits two dynamical regimes characterized by two different scaling exponents. For small time scales, the dynamics is superdiffusive (1.32-1.63) with the MSD scaling exponent increasing monotonically with increasing AGC concentration. On the other hand, at long time, we recover the Brownian dynamics regime, MSD = DΔt, where the mobility D ∝ Φ. We quantify the probe dynamics at short time scale by modeling it as a fractional Brownian motion. The analytical form of the MSD agrees with experimental results.

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

Naughton, M.J.; Bourke, W.; Browning, G.L.

The convergence of spectral model numerical solutions of the global shallow-water equations is examined as a function of the time step and the spectral truncation. The contributions to the errors due to the spatial and temporal discretizations are separately identified and compared. Numerical convergence experiments are performed with the inviscid equations from smooth (Rossby-Haurwitz wave) and observed (R45 atmospheric analysis) initial conditions, and also with the diffusive shallow-water equations. Results are compared with the forced inviscid shallow-water equations case studied by Browning et al. Reduction of the time discretization error by the removal of fast waves from the solution usingmore » initialization is shown. The effects of forcing and diffusion on the convergence are discussed. Time truncation errors are found to dominate when a feature is large scale and well resolved; spatial truncation errors dominate for small-scale features and also for large scale after the small scales have affected them. Possible implications of these results for global atmospheric modeling are discussed. 31 refs., 14 figs., 4 tabs.« less

Quantification of scaling exponent with Crossover type phenomena for different types of forcing in DC glow discharge plasma

NASA Astrophysics Data System (ADS)

Saha, Debajyoti; Shaw, Pankaj Kumar; Ghosh, Sabuj; Janaki, M. S.; Sekar Iyengar, A. N.

2018-01-01

We have carried out a detailed study of scaling region using detrended fractal analysis test by applying different forcing likewise noise, sinusoidal, square on the floating potential fluctuations acquired under different pressures in a DC glow discharge plasma. The transition in the dynamics is observed through recurrence plot techniques which is an efficient method to observe the critical regime transitions in dynamics. The complexity of the nonlinear fluctuation has been revealed with the help of recurrence quantification analysis which is a suitable tool for investigating recurrence, an ubiquitous feature providing a deep insight into the dynamics of real dynamical system. An informal test for stationarity which checks for the compatibility of nonlinear approximations to the dynamics made in different segments in a time series has been proposed. In case of sinusoidal, noise, square forcing applied on fluctuation acquired at P = 0.12 mbar only one dominant scaling region is observed whereas the forcing applied on fluctuation (P = 0.04 mbar) two prominent scaling regions have been explored reliably using different forcing amplitudes indicating the signature of crossover phenomena. Furthermore a persistence long range behavior has been observed in one of these scaling regions. A comprehensive study of the quantification of scaling exponents has been carried out with the increase in amplitude and frequency of sinusoidal, square type of forcings. The scalings exponent is envisaged to be the roughness of the time series. The method provides a single quantitative idea of the scaling exponent to quantify the correlation properties of a signal.

Time Hierarchies and Model Reduction in Canonical Non-linear Models

PubMed Central

Löwe, Hannes; Kremling, Andreas; Marin-Sanguino, Alberto

2016-01-01

The time-scale hierarchies of a very general class of models in differential equations is analyzed. Classical methods for model reduction and time-scale analysis have been adapted to this formalism and a complementary method is proposed. A unified theoretical treatment shows how the structure of the system can be much better understood by inspection of two sets of singular values: one related to the stoichiometric structure of the system and another to its kinetics. The methods are exemplified first through a toy model, then a large synthetic network and finally with numeric simulations of three classical benchmark models of real biological systems. PMID:27708665

High-speed peak matching algorithm for retention time alignment of gas chromatographic data for chemometric analysis

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

Johnson, Kevin J.; Wright, Bob W.; Jarman, Kristin H.

2003-05-09

A rapid retention time alignment algorithm was developed as a preprocessing utility to be used prior to chemometric analysis of large datasets of diesel fuel gas chromatographic profiles. Retention time variation from chromatogram-to-chromatogram has been a significant impediment against the use of chemometric techniques in the analysis of chromatographic data due to the inability of current multivariate techniques to correctly model information that shifts from variable to variable within a dataset. The algorithm developed is shown to increase the efficacy of pattern recognition methods applied to a set of diesel fuel chromatograms by retaining chemical selectivity while reducing chromatogram-to-chromatogram retentionmore » time variations and to do so on a time scale that makes analysis of large sets of chromatographic data practical.« less

Climate impact of beef: an analysis considering multiple time scales and production methods without use of global warming potentials

NASA Astrophysics Data System (ADS)

Pierrehumbert, R. T.; Eshel, G.

2015-08-01

An analysis of the climate impact of various forms of beef production is carried out, with a particular eye to the comparison between systems relying primarily on grasses grown in pasture (‘grass-fed’ or ‘pastured’ beef) and systems involving substantial use of manufactured feed requiring significant external inputs in the form of synthetic fertilizer and mechanized agriculture (‘feedlot’ beef). The climate impact is evaluated without employing metrics such as {{CO}}2{{e}} or global warming potentials. The analysis evaluates the impact at all time scales out to 1000 years. It is concluded that certain forms of pastured beef production have substantially lower climate impact than feedlot systems. However, pastured systems that require significant synthetic fertilization, inputs from supplemental feed, or deforestation to create pasture, have substantially greater climate impact at all time scales than the feedlot and dairy-associated systems analyzed. Even the best pastured system analyzed has enough climate impact to justify efforts to limit future growth of beef production, which in any event would be necessary if climate and other ecological concerns were met by a transition to primarily pasture-based systems. Alternate mitigation options are discussed, but barring unforseen technological breakthroughs worldwide consumption at current North American per capita rates appears incompatible with a 2 °C warming target.

Predicting Educational Outcomes and Psychological Well-Being in Adolescents Using Time Attitude Profiles

ERIC Educational Resources Information Center

Andretta, James R.; Worrell, Frank C.; Mello, Zena R.

2014-01-01

Using cluster analysis of Adolescent Time Attitude Scale (ATAS) scores in a sample of 300 adolescents ("M" age = 16 years; "SD" = 1.25; 60% male; 41% European American; 25.3% Asian American; 11% African American; 10.3% Latino), the authors identified five time attitude profiles based on positive and negative attitudes toward…

Large-Scale Atmospheric Teleconnection Patterns Associated with the Interannual Variability of Heatwaves in East Asia and Its Decadal Changes

NASA Astrophysics Data System (ADS)

Choi, N.; Lee, M. I.; Lim, Y. K.; Kim, K. M.

2017-12-01

Heatwave is an extreme hot weather event which accompanies fatal damage to human health. The heatwave has a strong relationship with the large-scale atmospheric teleconnection patterns. In this study, we examine the spatial pattern of heatwave in East Asia by using the EOF analysis and the relationship between heatwave frequency and large-scale atmospheric teleconnection patterns. We also separate the time scale of heatwave frequency as the time scale longer than a decade and the interannual time scale. The long-term variation of heatwave frequency in East Asia shows a linkage with the sea surface temperature (SST) variability over the North Atlantic with a decadal time scale (a.k.a. the Atlantic Multidecadal Oscillation; AMO). On the other hands, the interannual variation of heatwave frequency is linked with the two dominant spatial patterns associated with the large-scale teleconnection patterns mimicking the Scandinavian teleconnection (SCAND-like) pattern and the circumglobal teleconnection (CGT-like) pattern, respectively. It is highlighted that the interannual variation of heatwave frequency in East Asia shows a remarkable change after mid-1990s. While the heatwave frequency was mainly associated with the CGT-like pattern before mid-1990s, the SCAND-like pattern becomes the most dominant one after mid-1990s, making the CGT-like pattern as the second. This study implies that the large-scale atmospheric teleconnection patterns play a key role in developing heatwave events in East Asia. This study further discusses possible mechanisms for the decadal change in the linkage between heatwave frequency and the large-scale teleconnection patterns in East Asia such as early melting of snow cover and/or weakening of East Asian jet stream due to global warming.

Lifetime evaluation of large format CMOS mixed signal infrared devices

NASA Astrophysics Data System (ADS)

Linder, A.; Glines, Eddie

2015-09-01

New large scale foundry processes continue to produce reliable products. These new large scale devices continue to use industry best practice to screen for failure mechanisms and validate their long lifetime. The Failure-in-Time analysis in conjunction with foundry qualification information can be used to evaluate large format device lifetimes. This analysis is a helpful tool when zero failure life tests are typical. The reliability of the device is estimated by applying the failure rate to the use conditions. JEDEC publications continue to be the industry accepted methods.

Scaling behaviors of precipitation over China

NASA Astrophysics Data System (ADS)

Jiang, Lei; Li, Nana; Zhao, Xia

2017-04-01

Scaling behaviors in the precipitation time series derived from 1951 to 2009 over China are investigated by detrended fluctuation analysis (DFA) method. The results show that there exists long-term memory for the precipitation time series in some stations, where the values of the scaling exponent α are less than 0.62, implying weak persistence characteristics. The values of scaling exponent in other stations indicate random behaviors. In addition, the scaling exponent α in precipitation records varies from station to station over China. A numerical test is made to verify the significance in DFA exponents by shuffling the data records many times. We think it is significant when the values of scaling exponent before shuffled precipitation records are larger than the interval threshold for 95 % confidence level after shuffling precipitation records many times. By comparison, the daily precipitation records exhibit weak positively long-range correlation in a power law fashion mainly at the stations taking on zonal distributions in south China, upper and middle reaches of the Yellow River, northern part of northeast China. This may be related to the subtropical high. Furthermore, the values of scaling exponent which cannot pass the significance test do not show a clear distribution pattern. It seems that the stations are mainly distributed in coastal areas, southwest China, and southern part of north China. In fact, many complicated factors may affect the scaling behaviors of precipitation such as the system of the east and south Asian monsoon, the interaction between sea and land, and the big landform of the Tibetan Plateau. These results may provide a better prerequisite to long-term predictor of precipitation time series for different regions over China.

A FAST BAYESIAN METHOD FOR UPDATING AND FORECASTING HOURLY OZONE LEVELS

EPA Science Inventory

A Bayesian hierarchical space-time model is proposed by combining information from real-time ambient AIRNow air monitoring data, and output from a computer simulation model known as the Community Multi-scale Air Quality (Eta-CMAQ) forecast model. A model validation analysis shows...

Effects of Helicity on Lagrangian and Eulerian Time Correlations in Turbulence

NASA Technical Reports Server (NTRS)

Rubinstein, Robert; Zhou, Ye

1998-01-01

Taylor series expansions of turbulent time correlation functions are applied to show that helicity influences Eulerian time correlations more strongly than Lagrangian time correlations: to second order in time, the helicity effect on Lagrangian time correlations vanishes, but the helicity effect on Eulerian time correlations is nonzero. Fourier analysis shows that the helicity effect on Eulerian time correlations is confined to the largest inertial range scales. Some implications for sound radiation by swirling flows are discussed.

Sign and magnitude scaling properties of heart rate variability in patients with end-stage renal failure: Are these properties useful to identify pathophysiological adaptations?

NASA Astrophysics Data System (ADS)

Lerma, Claudia; Echeverría, Juan C.; Infante, Oscar; Pérez-Grovas, Héctor; González-Gómez, Hortensia

2017-09-01

The scaling properties of heart rate variability data are reliable dynamical features to predict mortality and for the assessment of cardiovascular risk. The aim of this manuscript was to determine if the scaling properties, as provided by the sign and magnitude analysis, can be used to differentiate between pathological changes and those adaptations basically introduced by modifications of the mean heart rate in distinct manoeuvres (active standing or hemodialysis treatment, HD), as well as clinical conditions (end stage renal disease, ESRD). We found that in response to active standing, the short-term scaling index (α1) increased in healthy subjects and in ESRD patients only after HD. The sign short-term scaling exponent (α1sign) increased in healthy subjects and ESRD patients, showing a less anticorrelated behavior in active standing. Both α1 and α1sign did show covariance with the mean heart rate in healthy subjects, while in ESRD patients, this covariance was observed only after HD. A reliable estimation of the magnitude short-term scaling exponent (α1magn) required the analysis of time series with a large number of samples (>3000 data points). This exponent was similar for both groups and conditions and did not show covariance with the mean heart rate. A surrogate analysis confirmed the presence of multifractal properties (α1magn > 0.5) in the time series of healthy subjects and ESDR patients. In conclusion, α1 and α1sign provided insights into the physiological adaptations during active standing, which revealed a transitory impairment before HD in ESRD patients. The presence of multifractal properties indicated that a reduced short-term variability does not necessarily imply a declined regulatory complexity in these patients.

Sign and magnitude scaling properties of heart rate variability in patients with end-stage renal failure: Are these properties useful to identify pathophysiological adaptations?

PubMed

Lerma, Claudia; Echeverría, Juan C; Infante, Oscar; Pérez-Grovas, Héctor; González-Gómez, Hortensia

2017-09-01

The scaling properties of heart rate variability data are reliable dynamical features to predict mortality and for the assessment of cardiovascular risk. The aim of this manuscript was to determine if the scaling properties, as provided by the sign and magnitude analysis, can be used to differentiate between pathological changes and those adaptations basically introduced by modifications of the mean heart rate in distinct manoeuvres (active standing or hemodialysis treatment, HD), as well as clinical conditions (end stage renal disease, ESRD). We found that in response to active standing, the short-term scaling index (α 1 ) increased in healthy subjects and in ESRD patients only after HD. The sign short-term scaling exponent (α 1sign ) increased in healthy subjects and ESRD patients, showing a less anticorrelated behavior in active standing. Both α 1 and α 1sign did show covariance with the mean heart rate in healthy subjects, while in ESRD patients, this covariance was observed only after HD. A reliable estimation of the magnitude short-term scaling exponent (α 1magn ) required the analysis of time series with a large number of samples (>3000 data points). This exponent was similar for both groups and conditions and did not show covariance with the mean heart rate. A surrogate analysis confirmed the presence of multifractal properties (α 1magn  > 0.5) in the time series of healthy subjects and ESDR patients. In conclusion, α 1 and α 1sign provided insights into the physiological adaptations during active standing, which revealed a transitory impairment before HD in ESRD patients. The presence of multifractal properties indicated that a reduced short-term variability does not necessarily imply a declined regulatory complexity in these patients.

IR temperatures of Mauna Loa caldera obtained with multispectral thermal imager

NASA Astrophysics Data System (ADS)

Pendergast, Malcolm M.; O'Steen, Byron L.; Kurzeja, Robert J.

2002-01-01

A survey of surface temperatures of the Mauna Loa caldera during 7/14/00 and 7/15/00 was made by SRTC in conjunction with a MTI satellite image collection. The general variation of surface temperature appears quite predictable responding to solar heating. The analysis of detailed times series of temperature indicates systematic variations in temperature of 5 C corresponding to time scales of 3-5 minutes and space scales of 10-20 m. The average temperature patterns are consistent with those predicted by the Regional Atmospheric Modeling System (RAMS).

The Dissipation Rate Transport Equation and Subgrid-Scale Models in Rotating Turbulence

NASA Technical Reports Server (NTRS)

Rubinstein, Robert; Ye, Zhou

1997-01-01

The dissipation rate transport equation remains the most uncertain part of turbulence modeling. The difficulties arc increased when external agencies like rotation prevent straightforward dimensional analysis from determining the correct form of the modelled equation. In this work, the dissipation rate transport equation and subgrid scale models for rotating turbulence are derived from an analytical statistical theory of rotating turbulence. In the strong rotation limit, the theory predicts a turbulent steady state in which the inertial range energy spectrum scales as k(sup -2) and the turbulent time scale is the inverse rotation rate. This scaling has been derived previously by heuristic arguments.

AQMEII3 evaluation of regional NA/EU simulations and ...

EPA Pesticide Factsheets

Through the comparison of several regional-scale chemistry transport modelling systems that simulate meteorology and air quality over the European and American continents, this study aims at i) apportioning the error to the responsible processes using time-scale analysis, ii) helping to detect causes of models error, and iii) identifying the processes and scales most urgently requiring dedicated investigations. The analysis is conducted within the framework of the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) and tackles model performance gauging through measurement-to-model comparison, error decomposition and time series analysis of the models biases for several fields (ozone, CO, SO2, NO, NO2, PM10, PM2.5, wind speed, and temperature). The operational metrics (magnitude of the error, sign of the bias, associativity) provide an overall sense of model strengths and deficiencies, while apportioning the error to its constituent parts (bias, variance and covariance) can help to assess the nature and quality of the error. Each of the error components is analysed independently and apportioned to specific processes based on the corresponding timescale (long scale, synoptic, diurnal, and intra-day) using the error apportionment technique devised in the former phases of AQMEII. The application of the error apportionment method to the AQMEII Phase 3 simulations provides several key insights. In addition to reaffirming the strong impac

paraGSEA: a scalable approach for large-scale gene expression profiling

PubMed Central

Peng, Shaoliang; Yang, Shunyun

2017-01-01

Abstract More studies have been conducted using gene expression similarity to identify functional connections among genes, diseases and drugs. Gene Set Enrichment Analysis (GSEA) is a powerful analytical method for interpreting gene expression data. However, due to its enormous computational overhead in the estimation of significance level step and multiple hypothesis testing step, the computation scalability and efficiency are poor on large-scale datasets. We proposed paraGSEA for efficient large-scale transcriptome data analysis. By optimization, the overall time complexity of paraGSEA is reduced from O(mn) to O(m+n), where m is the length of the gene sets and n is the length of the gene expression profiles, which contributes more than 100-fold increase in performance compared with other popular GSEA implementations such as GSEA-P, SAM-GS and GSEA2. By further parallelization, a near-linear speed-up is gained on both workstations and clusters in an efficient manner with high scalability and performance on large-scale datasets. The analysis time of whole LINCS phase I dataset (GSE92742) was reduced to nearly half hour on a 1000 node cluster on Tianhe-2, or within 120 hours on a 96-core workstation. The source code of paraGSEA is licensed under the GPLv3 and available at http://github.com/ysycloud/paraGSEA. PMID:28973463

Breaking common ground: Scalar perceptions and the effects on energy extraction in Pavillion, Wyoming

NASA Astrophysics Data System (ADS)

Watts, Kaitlyn

Conflicts over natural resources are increasing throughout the world. Researchers have taken the geographic concept of scale and applied it as a tool for analyzing environmental conflict and determining the correct jurisdictional arena for regulation. My research takes this social construction of scale and applies it to a case study of energy extraction in Pavillion, Wyoming. The case study focuses on the conflict that developed over hydraulic fracturing and water contamination at a time when the use of hydraulic fracturing increased nationwide. Through the use of personal interviews and document analysis I determine the ways that stakeholders use scale in the conflict to influence the strategies that they use to persuade policy decisions. This provides an example of how scale can be used as an effective tool of policy analysis and environmental conflict resolution

Fast response of electron-scale turbulence to auxiliary heating cessation in National Spherical Torus Experiment

DOE PAGES

Ren, Y.; Wang, W. X.; LeBlanc, B. P.; ...

2015-11-03

In this letter, we report the first observation of the fast response of electron-scale turbulence to auxiliary heating cessation in National Spherical Torus eXperiment [Ono et al., Nucl. Fusion 40, 557 (2000)]. The observation was made in a set of RF-heated L-mode plasmas with toroidal magnetic field of 0.55 T and plasma current of 300 kA. It is observed that electron-scale turbulence spectral power (measured with a high-k collective microwave scattering system) decreases significantly following fast cessation of RF heating that occurs in less than 200 μs. The large drop in the turbulence spectral power has a short time delaymore » of about 1–2 ms relative to the RF cessation and happens on a time scale of 0.5–1 ms, much smaller than the energy confinement time of about 10 ms. Power balance analysis shows a factor of about 2 decrease in electron thermal diffusivity after the sudden drop of turbulence spectral power. Measured small changes in equilibrium profiles across the RF cessation are unlikely able to explain this sudden reduction in the measured turbulence and decrease in electron thermal transport, supported by local linear stability analysis and both local and global nonlinear gyrokinetic simulations. Furthermore, the observations imply that nonlocal flux-driven mechanism may be important for the observed turbulence and electron thermal transport.« less

“Skill of Generalized Additive Model to Detect PM2.5 Health ...

EPA Pesticide Factsheets

Summary. Measures of health outcomes are collinear with meteorology and air quality, making analysis of connections between human health and air quality difficult. The purpose of this analysis was to determine time scales and periods shared by the variables of interest (and by implication scales and periods that are not shared). Hospital admissions, meteorology (temperature and relative humidity), and air quality (PM2.5 and daily maximum ozone) for New York City during the period 2000-2006 were decomposed into temporal scales ranging from 2 days to greater than two years using a complex wavelet transform. Health effects were modeled as functions of the wavelet components of meteorology and air quality using the generalized additive model (GAM) framework. This simulation study showed that GAM is extremely successful at extracting and estimating a health effect embedded in a dataset. It also shows that, if the objective in mind is to estimate the health signal but not to fully explain this signal, a simple GAM model with a single confounder (calendar time) whose smooth representation includes a sufficient number of constraints is as good as a more complex model.Introduction. In the context of wavelet regression, confounding occurs when two or more independent variables interact with the dependent variable at the same frequency. Confounding also acts on a variety of time scales, changing the PM2.5 coefficient (magnitude and sign) and its significance ac

Nonlinear analysis of pupillary dynamics.

PubMed

Onorati, Francesco; Mainardi, Luca Tommaso; Sirca, Fabiola; Russo, Vincenzo; Barbieri, Riccardo

2016-02-01

Pupil size reflects autonomic response to different environmental and behavioral stimuli, and its dynamics have been linked to other autonomic correlates such as cardiac and respiratory rhythms. The aim of this study is to assess the nonlinear characteristics of pupil size of 25 normal subjects who participated in a psychophysiological experimental protocol with four experimental conditions, namely “baseline”, “anger”, “joy”, and “sadness”. Nonlinear measures, such as sample entropy, correlation dimension, and largest Lyapunov exponent, were computed on reconstructed signals of spontaneous fluctuations of pupil dilation. Nonparametric statistical tests were performed on surrogate data to verify that the nonlinear measures are an intrinsic characteristic of the signals. We then developed and applied a piecewise linear regression model to detrended fluctuation analysis (DFA). Two joinpoints and three scaling intervals were identified: slope α0, at slow time scales, represents a persistent nonstationary long-range correlation, whereas α1 and α2, at middle and fast time scales, respectively, represent long-range power-law correlations, similarly to DFA applied to heart rate variability signals. Of the computed complexity measures, α0 showed statistically significant differences among experimental conditions (p<0.001). Our results suggest that (a) pupil size at constant light condition is characterized by nonlinear dynamics, (b) three well-defined and distinct long-memory processes exist at different time scales, and (c) autonomic stimulation is partially reflected in nonlinear dynamics. (c) autonomic stimulation is partially reflected in nonlinear dynamics.

Tsunamis generated by subaerial mass flows

USGS Publications Warehouse

Walder, S.J.; Watts, P.; Sorensen, O.E.; Janssen, K.

2003-01-01

Tsunamis generated in lakes and reservoirs by subaerial mass flows pose distinctive problems for hazards assessment because the domain of interest is commonly the "near field," beyond the zone of complex splashing but close enough to the source that wave propagation effects are not predominant. Scaling analysis of the equations governing water wave propagation shows that near-field wave amplitude and wavelength should depend on certain measures of mass flow dynamics and volume. The scaling analysis motivates a successful collapse (in dimensionless space) of data from two distinct sets of experiments with solid block "wave makers." To first order, wave amplitude/water depth is a simple function of the ratio of dimensionless wave maker travel time to dimensionless wave maker volume per unit width. Wave amplitude data from previous laboratory investigations with both rigid and deformable wave makers follow the same trend in dimensionless parameter space as our own data. The characteristic wavelength/water depth for all our experiments is simply proportional to dimensionless wave maker travel time, which is itself given approximately by a simple function of wave maker length/water depth. Wave maker shape and rigidity do not otherwise influence wave features. Application of the amplitude scaling relation to several historical events yields "predicted" near-field wave amplitudes in reasonable agreement with measurements and observations. Together, the scaling relations for near-field amplitude, wavelength, and submerged travel time provide key inputs necessary for computational wave propagation and hazards assessment.

A Constructive Mean-Field Analysis of Multi-Population Neural Networks with Random Synaptic Weights and Stochastic Inputs

PubMed Central

Faugeras, Olivier; Touboul, Jonathan; Cessac, Bruno

2008-01-01

We deal with the problem of bridging the gap between two scales in neuronal modeling. At the first (microscopic) scale, neurons are considered individually and their behavior described by stochastic differential equations that govern the time variations of their membrane potentials. They are coupled by synaptic connections acting on their resulting activity, a nonlinear function of their membrane potential. At the second (mesoscopic) scale, interacting populations of neurons are described individually by similar equations. The equations describing the dynamical and the stationary mean-field behaviors are considered as functional equations on a set of stochastic processes. Using this new point of view allows us to prove that these equations are well-posed on any finite time interval and to provide a constructive method for effectively computing their unique solution. This method is proved to converge to the unique solution and we characterize its complexity and convergence rate. We also provide partial results for the stationary problem on infinite time intervals. These results shed some new light on such neural mass models as the one of Jansen and Rit (1995): their dynamics appears as a coarse approximation of the much richer dynamics that emerges from our analysis. Our numerical experiments confirm that the framework we propose and the numerical methods we derive from it provide a new and powerful tool for the exploration of neural behaviors at different scales. PMID:19255631

Implementation of a flow-dependent background error correlation length scale formulation in the NEMOVAR OSTIA system

NASA Astrophysics Data System (ADS)

Fiedler, Emma; Mao, Chongyuan; Good, Simon; Waters, Jennifer; Martin, Matthew

2017-04-01

OSTIA is the Met Office's Operational Sea Surface Temperature (SST) and Ice Analysis system, which produces L4 (globally complete, gridded) analyses on a daily basis. Work is currently being undertaken to replace the original OI (Optimal Interpolation) data assimilation scheme with NEMOVAR, a 3D-Var data assimilation method developed for use with the NEMO ocean model. A dual background error correlation length scale formulation is used for SST in OSTIA, as implemented in NEMOVAR. Short and long length scales are combined according to the ratio of the decomposition of the background error variances into short and long spatial correlations. The pre-defined background error variances vary spatially and seasonally, but not on shorter time-scales. If the derived length scales applied to the daily analysis are too long, SST features may be smoothed out. Therefore a flow-dependent component to determining the effective length scale has also been developed. The total horizontal gradient of the background SST field is used to identify regions where the length scale should be shortened. These methods together have led to an improvement in the resolution of SST features compared to the previous OI analysis system, without the introduction of spurious noise. This presentation will show validation results for feature resolution in OSTIA using the OI scheme, the dual length scale NEMOVAR scheme, and the flow-dependent implementation.

Rayleigh-Taylor mixing in supernova experiments

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

Swisher, N. C.; Abarzhi, S. I., E-mail: snezhana.abarzhi@gmail.com; Kuranz, C. C.

We report a scrupulous analysis of data in supernova experiments that are conducted at high power laser facilities in order to study core-collapse supernova SN1987A. Parameters of the experimental system are properly scaled to investigate the interaction of a blast-wave with helium-hydrogen interface, and the induced Rayleigh-Taylor instability and Rayleigh-Taylor mixing of the denser and lighter fluids with time-dependent acceleration. We analyze all available experimental images of the Rayleigh-Taylor flow in supernova experiments and measure delicate features of the interfacial dynamics. A new scaling is identified for calibration of experimental data to enable their accurate analysis and comparisons. By properlymore » accounting for the imprint of the experimental conditions, the data set size and statistics are substantially increased. New theoretical solutions are reported to describe asymptotic dynamics of Rayleigh-Taylor flow with time-dependent acceleration by applying theoretical analysis that considers symmetries and momentum transport. Good qualitative and quantitative agreement is achieved of the experimental data with the theory and simulations. Our study indicates that in supernova experiments Rayleigh-Taylor flow is in the mixing regime, the interface amplitude contributes substantially to the characteristic length scale for energy dissipation; Rayleigh-Taylor mixing keeps order.« less

Fractal Signals & Space-Time Cartoons

NASA Astrophysics Data System (ADS)

Oetama, H. C. Jakob; Maksoed, W. H.

2016-03-01

In ``Theory of Scale Relativity'', 1991- L. Nottale states whereas ``scale relativity is a geometrical & fractal space-time theory''. It took in comparisons to ``a unified, wavelet based framework for efficiently synthetizing, analyzing ∖7 processing several broad classes of fractal signals''-Gregory W. Wornell:``Signal Processing with Fractals'', 1995. Furthers, in Fig 1.1. a simple waveform from statistically scale-invariant random process [ibid.,h 3 ]. Accompanying RLE Technical Report 566 ``Synthesis, Analysis & Processing of Fractal Signals'' as well as from Wornell, Oct 1991 herewith intended to deducts =a Δt + (1 - β Δ t) ...in Petersen, et.al: ``Scale invariant properties of public debt growth'',2010 h. 38006p2 to [1/{1- (2 α (λ) /3 π) ln (λ/r)}depicts in Laurent Nottale,1991, h 24. Acknowledgment devotes to theLates HE. Mr. BrigadierGeneral-TNI[rtd].Prof. Ir. HANDOJO.

Rumination and Loneliness Independently Predict Six-Month Later Depression Symptoms among Chinese Elderly in Nursing Homes.

PubMed

Gan, Pei; Xie, Yan; Duan, Wenjie; Deng, Qing; Yu, Xiuli

2015-01-01

Previous studies conducted in Western countries independently demonstrated that loneliness and rumination are remarkable risk factors of depression among the elderly in both community and nursing homes. However, knowledge on the relationship between these three constructs among the elderly in Eastern countries is scarce. The current study aims to determine the relationship between loneliness, rumination, and depression among Chinese elderly in nursing homes. A total of 71 elderly participants with an average age of 82.49 years completed this six-month longitudinal study. Physical reports indicated that none of the participants were clinically depressed before the study. At Time 1, their loneliness and rumination were measured using UCLA-8 Loneliness Scale and Ruminative Responses Scale. Six months later, the participants completed the Center for Epidemiologic Studies Depression Scale to assess depressive symptoms (Time 2). Multiple regression analysis revealed that both loneliness and rumination at Time 1 were the predictors of depression symptoms at Time 2 among the Chinese elderly in nursing homes. However, in the mediation analysis using PROCESS, the indirect effect between loneliness at Time 1 and depression symptoms at Time 2 was insignificant. Results suggest that previous loneliness and rumination thinking are predictors of future depression symptoms among the Chinese elderly in nursing homes. However, the insignificant mediation further suggests that the differences between loneliness and rumination should be explored in future studies. Findings have important implications for mental health professionals in nursing homes in China.

Rumination and Loneliness Independently Predict Six-Month Later Depression Symptoms among Chinese Elderly in Nursing Homes

PubMed Central

Gan, Pei; Xie, Yan; Duan, Wenjie; Deng, Qing; Yu, Xiuli

2015-01-01

Background Previous studies conducted in Western countries independently demonstrated that loneliness and rumination are remarkable risk factors of depression among the elderly in both community and nursing homes. However, knowledge on the relationship between these three constructs among the elderly in Eastern countries is scarce. The current study aims to determine the relationship between loneliness, rumination, and depression among Chinese elderly in nursing homes. Methods A total of 71 elderly participants with an average age of 82.49 years completed this six-month longitudinal study. Physical reports indicated that none of the participants were clinically depressed before the study. At Time 1, their loneliness and rumination were measured using UCLA-8 Loneliness Scale and Ruminative Responses Scale. Six months later, the participants completed the Center for Epidemiologic Studies Depression Scale to assess depressive symptoms (Time 2). Results Multiple regression analysis revealed that both loneliness and rumination at Time 1 were the predictors of depression symptoms at Time 2 among the Chinese elderly in nursing homes. However, in the mediation analysis using PROCESS, the indirect effect between loneliness at Time 1 and depression symptoms at Time 2 was insignificant. Conclusions Results suggest that previous loneliness and rumination thinking are predictors of future depression symptoms among the Chinese elderly in nursing homes. However, the insignificant mediation further suggests that the differences between loneliness and rumination should be explored in future studies. Findings have important implications for mental health professionals in nursing homes in China. PMID:26334298

Voice-onset time and buzz-onset time identification: A ROC analysis

NASA Astrophysics Data System (ADS)

Lopez-Bascuas, Luis E.; Rosner, Burton S.; Garcia-Albea, Jose E.

2004-05-01

Previous studies have employed signal detection theory to analyze data from speech and nonspeech experiments. Typically, signal distributions were assumed to be Gaussian. Schouten and van Hessen [J. Acoust. Soc. Am. 104, 2980-2990 (1998)] explicitly tested this assumption for an intensity continuum and a speech continuum. They measured response distributions directly and, assuming an interval scale, concluded that the Gaussian assumption held for both continua. However, Pastore and Macmillan [J. Acoust. Soc. Am. 111, 2432 (2002)] applied ROC analysis to Schouten and van Hessen's data, assuming only an ordinal scale. Their ROC curves suppported the Gaussian assumption for the nonspeech signals only. Previously, Lopez-Bascuas [Proc. Audit. Bas. Speech Percept., 158-161 (1997)] found evidence with a rating scale procedure that the Gaussian model was inadequate for a voice-onset time continuum but not for a noise-buzz continuum. Both continua contained ten stimuli with asynchronies ranging from -35 ms to +55 ms. ROC curves (double-probability plots) are now reported for each pair of adjacent stimuli on the two continua. Both speech and nonspeech ROCs often appeared nonlinear, indicating non-Gaussian signal distributions under the usual zero-variance assumption for response criteria.

Climate change and social vicissitudes in China over the past two millennia

NASA Astrophysics Data System (ADS)

Yin, Jun; Su, Yun; Fang, Xiuqi

2016-09-01

The relation between climate change and historical rhythms has long been discussed. However, this type of study still faces the lack of high-resolution data concerning long-term socio-economic processes. In this study, we collected 1586 items of direct and proffered evidence from 29 Chinese history books. We used semantic analysis to reconstruct a quantitative series of the social vicissitudes of the past 2000 yr with a 10-yr resolution to express the phase transition of the social vicissitudes of the dynasties in China. Our reconstruction demonstrates that social vicissitudes have clear cyclical features on multiple time scales. Analysis of the association of social rise and fall with climate change indicates that temperature displayed more significant effects on social vicissitudes in the long term, while precipitation displayed more significant effects on the social vicissitudes in the short term. There are great overlaps between social and climatic variables around the predominant or periodic bands. Social rise mostly occurred in the centennial-scale warm periods, whereas social decline mostly occurred in the centennial-scale cold periods. Under warm-wet conditions, social rise occurred over 57% of the time; under cold-dry conditions, the social decline occurred over 66% of the time.

Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics

DOE PAGES

Bordbar, Aarash; Yurkovich, James T.; Paglia, Giuseppe; ...

2017-04-07

In this study, the increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed “unsteady-state flux balance analysis” (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBAmore » predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through 13C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.« less

3-Dimensional Root Cause Diagnosis via Co-analysis

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

Zheng, Ziming; Lan, Zhiling; Yu, Li

2012-01-01

With the growth of system size and complexity, reliability has become a major concern for large-scale systems. Upon the occurrence of failure, system administrators typically trace the events in Reliability, Availability, and Serviceability (RAS) logs for root cause diagnosis. However, RAS log only contains limited diagnosis information. Moreover, the manual processing is time-consuming, error-prone, and not scalable. To address the problem, in this paper we present an automated root cause diagnosis mechanism for large-scale HPC systems. Our mechanism examines multiple logs to provide a 3-D fine-grained root cause analysis. Here, 3-D means that our analysis will pinpoint the failure layer,more » the time, and the location of the event that causes the problem. We evaluate our mechanism by means of real logs collected from a production IBM Blue Gene/P system at Oak Ridge National Laboratory. It successfully identifies failure layer information for 219 failures during 23-month period. Furthermore, it effectively identifies the triggering events with time and location information, even when the triggering events occur hundreds of hours before the resulting failures.« less

Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics

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

Bordbar, Aarash; Yurkovich, James T.; Paglia, Giuseppe

In this study, the increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed “unsteady-state flux balance analysis” (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBAmore » predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through 13C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.« less

Using the Advanced Progressive Matrices (Set I) to Assess Fluid Ability in a Short Time Frame: An Item Response Theory-Based Analysis

ERIC Educational Resources Information Center

Chiesi, Francesca; Ciancaleoni, Matteo; Galli, Silvia; Primi, Caterina

2012-01-01

This article is aimed at evaluating the possibility that Set I of the Advanced Progressive Matrices (APM-Set I) can be employed to assess fluid ability in a short time frame. The APM-Set I was administered to a sample of 1,389 primary and secondary school students. Confirmatory factor analysis attested to the unidimensionality of the scale. Item…

Time-resolved scanning electron microscopy with polarization analysis

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

Frömter, Robert, E-mail: rfroemte@physik.uni-hamburg.de; Oepen, Hans Peter; The Hamburg Centre for Ultrafast Imaging, Luruper Chaussee 149, 22761 Hamburg

2016-04-04

We demonstrate the feasibility of investigating periodically driven magnetization dynamics in a scanning electron microscope with polarization analysis based on spin-polarized low-energy electron diffraction. With the present setup, analyzing the time structure of the scattering events, we obtain a temporal resolution of 700 ps, which is demonstrated by means of imaging the field-driven 100 MHz gyration of the vortex in a soft-magnetic FeCoSiB square. Owing to the efficient intrinsic timing scheme, high-quality movies, giving two components of the magnetization simultaneously, can be recorded on the time scale of hours.

Multi-Scale Morphological Analysis of Conductance Signals in Vertical Upward Gas-Liquid Two-Phase Flow

NASA Astrophysics Data System (ADS)

Lian, Enyang; Ren, Yingyu; Han, Yunfeng; Liu, Weixin; Jin, Ningde; Zhao, Junying

2016-11-01

The multi-scale analysis is an important method for detecting nonlinear systems. In this study, we carry out experiments and measure the fluctuation signals from a rotating electric field conductance sensor with eight electrodes. We first use a recurrence plot to recognise flow patterns in vertical upward gas-liquid two-phase pipe flow from measured signals. Then we apply a multi-scale morphological analysis based on the first-order difference scatter plot to investigate the signals captured from the vertical upward gas-liquid two-phase flow loop test. We find that the invariant scaling exponent extracted from the multi-scale first-order difference scatter plot with the bisector of the second-fourth quadrant as the reference line is sensitive to the inhomogeneous distribution characteristics of the flow structure, and the variation trend of the exponent is helpful to understand the process of breakup and coalescence of the gas phase. In addition, we explore the dynamic mechanism influencing the inhomogeneous distribution of the gas phase in terms of adaptive optimal kernel time-frequency representation. The research indicates that the system energy is a factor influencing the distribution of the gas phase and the multi-scale morphological analysis based on the first-order difference scatter plot is an effective method for indicating the inhomogeneous distribution of the gas phase in gas-liquid two-phase flow.

Possibilities of LA-ICP-MS technique for the spatial elemental analysis of the recent fish scales: Line scan vs. depth profiling

NASA Astrophysics Data System (ADS)

Holá, Markéta; Kalvoda, Jiří; Nováková, Hana; Škoda, Radek; Kanický, Viktor

2011-01-01

LA-ICP-MS and solution based ICP-MS in combination with electron microprobe are presented as a method for the determination of the elemental spatial distribution in fish scales which represent an example of a heterogeneous layered bone structure. Two different LA-ICP-MS techniques were tested on recent common carp ( Cyprinus carpio) scales: A line scan through the whole fish scale perpendicular to the growth rings. The ablation crater of 55 μm width and 50 μm depth allowed analysis of the elemental distribution in the external layer. Suitable ablation conditions providing a deeper ablation crater gave average values from the external HAP layer and the collagen basal plate. Depth profiling using spot analysis was tested in fish scales for the first time. Spot analysis allows information to be obtained about the depth profile of the elements at the selected position on the sample. The combination of all mentioned laser ablation techniques provides complete information about the elemental distribution in the fish scale samples. The results were compared with the solution based ICP-MS and EMP analyses. The fact that the results of depth profiling are in a good agreement both with EMP and PIXE results and, with the assumed ways of incorporation of the studied elements in the HAP structure, suggests a very good potential for this method.

Towards understanding temporal and spatial dynamics of seagrass landscapes using time-series remote sensing

NASA Astrophysics Data System (ADS)

Lyons, Mitchell B.; Roelfsema, Chris M.; Phinn, Stuart R.

2013-03-01

The spatial and temporal dynamics of seagrasses have been well studied at the leaf to patch scales, however, the link to large spatial extent landscape and population dynamics is still unresolved in seagrass ecology. Traditional remote sensing approaches have lacked the temporal resolution and consistency to appropriately address this issue. This study uses two high temporal resolution time-series of thematic seagrass cover maps to examine the spatial and temporal dynamics of seagrass at both an inter- and intra-annual time scales, one of the first globally to do so at this scale. Previous work by the authors developed an object-based approach to map seagrass cover level distribution from a long term archive of Landsat TM and ETM+ images on the Eastern Banks (≈200 km2), Moreton Bay, Australia. In this work a range of trend and time-series analysis methods are demonstrated for a time-series of 23 annual maps from 1988 to 2010 and a time-series of 16 monthly maps during 2008-2010. Significant new insight was presented regarding the inter- and intra-annual dynamics of seagrass persistence over time, seagrass cover level variability, seagrass cover level trajectory, and change in area of seagrass and cover levels over time. Overall we found that there was no significant decline in total seagrass area on the Eastern Banks, but there was a significant decline in seagrass cover level condition. A case study of two smaller communities within the Eastern Banks that experienced a decline in both overall seagrass area and condition are examined in detail, highlighting possible differences in environmental and process drivers. We demonstrate how trend and time-series analysis enabled seagrass distribution to be appropriately assessed in context of its spatial and temporal history and provides the ability to not only quantify change, but also describe the type of change. We also demonstrate the potential use of time-series analysis products to investigate seagrass growth and decline as well as the processes that drive it. This study demonstrates clear benefits over traditional seagrass mapping and monitoring approaches, and provides a proof of concept for the use of trend and time-series analysis of remotely sensed seagrass products to benefit current endeavours in seagrass ecology.

Time-lapse videos for physics education: specific examples

NASA Astrophysics Data System (ADS)

Vollmer, Michael; Möllmann, Klaus-Peter

2018-05-01

There are many physics experiments with long time scales such that they are usually neither shown in the physics class room nor in student labs. However, they can be easily recorded with time-lapse cameras and the respective time-lapse videos allow qualitative and/or quantitative analysis of the underlying physics. Here, we present some examples from thermal physics (melting, evaporation, cooling) as well as diffusion processes

Fade Analysis of ORCA DATA Beam at NTTR and Pax River

DTIC Science & Technology

2010-08-01

bit-error-rate (BER) of the data beam on the downlink path. 15 Start Time-PST (Duration) Range Scin Index 1 Rx=5.1cm... Scin Index 2 Rx=13.7cm Scin Index 3 Rx=27.2cm Path Ave Cn2 (m-2/3) Path Ave Inner Scale Path Ave Outer Scale Flight 2 May 16

PARVMEC: An Efficient, Scalable Implementation of the Variational Moments Equilibrium Code

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

Seal, Sudip K; Hirshman, Steven Paul; Wingen, Andreas

The ability to sustain magnetically confined plasma in a state of stable equilibrium is crucial for optimal and cost-effective operations of fusion devices like tokamaks and stellarators. The Variational Moments Equilibrium Code (VMEC) is the de-facto serial application used by fusion scientists to compute magnetohydrodynamics (MHD) equilibria and study the physics of three dimensional plasmas in confined configurations. Modern fusion energy experiments have larger system scales with more interactive experimental workflows, both demanding faster analysis turnaround times on computational workloads that are stressing the capabilities of sequential VMEC. In this paper, we present PARVMEC, an efficient, parallel version of itsmore » sequential counterpart, capable of scaling to thousands of processors on distributed memory machines. PARVMEC is a non-linear code, with multiple numerical physics modules, each with its own computational complexity. A detailed speedup analysis supported by scaling results on 1,024 cores of a Cray XC30 supercomputer is presented. Depending on the mode of PARVMEC execution, speedup improvements of one to two orders of magnitude are reported. PARVMEC equips fusion scientists for the first time with a state-of-theart capability for rapid, high fidelity analyses of magnetically confined plasmas at unprecedented scales.« less

Is the pain visual analogue scale linear and responsive to change? An exploration using Rasch analysis.

PubMed

Kersten, Paula; White, Peter J; Tennant, Alan

2014-01-01

Pain visual analogue scales (VAS) are commonly used in clinical trials and are often treated as an interval level scale without evidence that this is appropriate. This paper examines the internal construct validity and responsiveness of the pain VAS using Rasch analysis. Patients (n = 221, mean age 67, 58% female) with chronic stable joint pain (hip 40% or knee 60%) of mechanical origin waiting for joint replacement were included. Pain was scored on seven daily VASs. Rasch analysis was used to examine fit to the Rasch model. Responsiveness (Standardized Response Means, SRM) was examined on the raw ordinal data and the interval data generated from the Rasch analysis. Baseline pain VAS scores fitted the Rasch model, although 15 aberrant cases impacted on unidimensionality. There was some local dependency between items but this did not significantly affect the person estimates of pain. Daily pain (item difficulty) was stable, suggesting that single measures can be used. Overall, the SRMs derived from ordinal data overestimated the true responsiveness by 59%. Changes over time at the lower and higher end of the scale were represented by large jumps in interval equivalent data points; in the middle of the scale the reverse was seen. The pain VAS is a valid tool for measuring pain at one point in time. However, the pain VAS does not behave linearly and SRMs vary along the trait of pain. Consequently, Minimum Clinically Important Differences using raw data, or change scores in general, are invalid as these will either under- or overestimate true change; raw pain VAS data should not be used as a primary outcome measure or to inform parametric-based Randomised Controlled Trial power calculations in research studies; and Rasch analysis should be used to convert ordinal data to interval data prior to data interpretation.

Temporal scaling of the growth dependent optical properties of microalgae

NASA Astrophysics Data System (ADS)

Zhao, J. M.; Ma, C. Y.; Liu, L. H.

2018-07-01

The optical properties of microalgae are basic parameters for analyzing light field distribution in photobioreactors (PBRs). With the growth of microalgae cell, their optical properties will vary with growth time due to accumulation of pigment and lipid, cell division and metabolism. In this work, we report a temporal scaling behavior of the growth dependent optical properties of microalgae cell suspensions with both experimental and theoretical evidence presented. A new concept, the temporal scaling function (TSF), defined as the ratio of absorption or scattering cross-sections at growth phase to that at stationary phase, is introduced to characterize the temporal scaling behavior. The temporal evolution and temporal scaling characteristics of the absorption and scattering cross-sections of three example microalgae species, Chlorella vulgaris, Chlorella pyrenoidosa, and Chlorella protothecoides, were experimentally studied at spectral range 380-850 nm. It is shown that the TSFs of the absorption and scattering cross-sections for different microalgae species are approximately constant at different wavelength, which confirms theoretical predictions very well. With the aid of the temporal scaling relation, the optical properties at any growth time can be calculated based on those measured at stationary phase, hence opens a new way to determine the time-dependent optical properties of microalgae. The findings of this work will help the understanding of time dependent optical properties of microalgae and facilitate their applications in light field analysis in PBRs design.

Evidence for the Maintenance of Slowly Varying Equatorial Currents by Intraseasonal Variability

NASA Astrophysics Data System (ADS)

Greatbatch, Richard J.; Claus, Martin; Brandt, Peter; Matthießen, Jan-Dirk; Tuchen, Franz Philip; Ascani, François; Dengler, Marcus; Toole, John; Roth, Christina; Farrar, J. Thomas

2018-02-01

Recent evidence from mooring data in the equatorial Atlantic reveals that semiannual and longer time scale ocean current variability is close to being resonant with equatorial basin modes. Here we show that intraseasonal variability, with time scales of tens of days, provides the energy to maintain these resonant basin modes against dissipation. The mechanism is analogous to that by which storm systems in the atmosphere act to maintain the atmospheric jet stream. We demonstrate the mechanism using an idealized model setup that exhibits equatorial deep jets. The results are supported by direct analysis of available mooring data from the equatorial Atlantic Ocean covering a depth range of several thousand meters. The analysis of the mooring data suggests that the same mechanism also helps maintain the seasonal variability.

Recurrence plot analysis of nonstationary data: the understanding of curved patterns.

PubMed

Facchini, A; Kantz, H; Tiezzi, E

2005-08-01

Recurrence plots of the calls of the Nomascus concolor (Western black crested gibbon) and Hylobates lar (White-handed gibbon) show characteristic circular, curved, and hyperbolic patterns superimposed to the main temporal scale of the signal. It is shown that these patterns are related to particular nonstationarities in the signal. Some of them can be reproduced by artificial signals like frequency modulated sinusoids and sinusoids with time divergent frequency. These modulations are too faint to be resolved by conventional time-frequency analysis with similar precision. Therefore, recurrence plots act as a magnifying glass for the detection of multiple temporal scales in slightly modulated signals. The detected phenomena in these acoustic signals can be explained in the biomechanical context by taking in account the role of the muscles controlling the vocal folds.

Genome-scale estimate of the metabolic turnover of E. Coli from the energy balance analysis

NASA Astrophysics Data System (ADS)

De Martino, D.

2016-02-01

In this article the notion of metabolic turnover is revisited in the light of recent results of out-of-equilibrium thermodynamics. By means of Monte Carlo methods we perform an exact sampling of the enzymatic fluxes in a genome scale metabolic network of E. Coli in stationary growth conditions from which we infer the metabolites turnover times. However the latter are inferred from net fluxes, and we argue that this approximation is not valid for enzymes working nearby thermodynamic equilibrium. We recalculate turnover times from total fluxes by performing an energy balance analysis of the network and recurring to the fluctuation theorem. We find in many cases values one of order of magnitude lower, implying a faster picture of intermediate metabolism.

Effect of spatial averaging on multifractal properties of meteorological time series

NASA Astrophysics Data System (ADS)

Hoffmann, Holger; Baranowski, Piotr; Krzyszczak, Jaromir; Zubik, Monika

2016-04-01

Introduction The process-based models for large-scale simulations require input of agro-meteorological quantities that are often in the form of time series of coarse spatial resolution. Therefore, the knowledge about their scaling properties is fundamental for transferring locally measured fluctuations to larger scales and vice-versa. However, the scaling analysis of these quantities is complicated due to the presence of localized trends and non-stationarities. Here we assess how spatially aggregating meteorological data to coarser resolutions affects the data's temporal scaling properties. While it is known that spatial aggregation may affect spatial data properties (Hoffmann et al., 2015), it is unknown how it affects temporal data properties. Therefore, the objective of this study was to characterize the aggregation effect (AE) with regard to both temporal and spatial input data properties considering scaling properties (i.e. statistical self-similarity) of the chosen agro-meteorological time series through multifractal detrended fluctuation analysis (MFDFA). Materials and Methods Time series coming from years 1982-2011 were spatially averaged from 1 to 10, 25, 50 and 100 km resolution to assess the impact of spatial aggregation. Daily minimum, mean and maximum air temperature (2 m), precipitation, global radiation, wind speed and relative humidity (Zhao et al., 2015) were used. To reveal the multifractal structure of the time series, we used the procedure described in Baranowski et al. (2015). The diversity of the studied multifractals was evaluated by the parameters of time series spectra. In order to analyse differences in multifractal properties to 1 km resolution grids, data of coarser resolutions was disaggregated to 1 km. Results and Conclusions Analysing the spatial averaging on multifractal properties we observed that spatial patterns of the multifractal spectrum (MS) of all meteorological variables differed from 1 km grids and MS-parameters were biased by -29.1 % (precipitation; width of MS) up to >4 % (min. Temperature, Radiation; asymmetry of MS). Also, the spatial variability of MS parameters was strongly affected at the highest aggregation (100 km). Obtained results confirm that spatial data aggregation may strongly affect temporal scaling properties. This should be taken into account when upscaling for large-scale studies. Acknowledgements The study was conducted within FACCE MACSUR. Please see Baranowski et al. (2015) for details on funding. References Baranowski, P., Krzyszczak, J., Sławiński, C. et al. (2015). Climate Research 65, 39-52. Hoffman, H., G. Zhao, L.G.J. Van Bussel et al. (2015). Climate Research 65, 53-69. Zhao, G., Siebert, S., Rezaei E. et al. (2015). Agricultural and Forest Meteorology 200, 156-171.

Intrinsic vs. spurious long-range memory in high-frequency records of environmental radioactivity - Critical re-assessment and application to indoor 222Rn concentrations from Coimbra, Portugal

NASA Astrophysics Data System (ADS)

Donner, Reik V.; Potirakis, Stelios M.; Barbosa, Susana M.; Matos, Jose A. O.

2015-04-01

The presence or absence of long-range correlations in environmental radioactivity fluctuations has recently attracted considerable interest. Among a multiplicity of practically relevant applications, identifying and disentangling the environmental factors controlling the variable concentrations of the radioactive noble gas Radon is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we present a critical re-assessment of a multiplicity of complementary methods that have been previously applied for evaluating the presence of long-range correlations and fractal scaling in environmental Radon variations with a particular focus on the specific properties of the underlying time series. As an illustrative case study, we subsequently re-analyze two high-frequency records of indoor Radon concentrations from Coimbra, Portugal, each of which spans several months of continuous measurements at a high temporal resolution of five minutes. Our results reveal that at the study site, Radon concentrations exhibit complex multi-scale dynamics with qualitatively different properties at different time-scales: (i) essentially white noise in the high-frequency part (up to time-scales of about one hour), (ii) spurious indications of a non-stationary, apparently long-range correlated process (at time scales between hours and one day) arising from marked periodic components probably related to tidal frequencies, and (iii) low-frequency variability indicating a true long-range dependent process, which might be dominated by a response to meteorological drivers. In the presence of such multi-scale variability, common estimators of long-range memory in time series are necessarily prone to fail if applied to the raw data without previous separation of time-scales with qualitatively different dynamics. We emphasize that similar properties can be found in other types of geophysical time series (for example, tide gauge records), calling for a careful application of time series analysis tools when studying such data.

HiQuant: Rapid Postquantification Analysis of Large-Scale MS-Generated Proteomics Data.

PubMed

Bryan, Kenneth; Jarboui, Mohamed-Ali; Raso, Cinzia; Bernal-Llinares, Manuel; McCann, Brendan; Rauch, Jens; Boldt, Karsten; Lynn, David J

2016-06-03

Recent advances in mass-spectrometry-based proteomics are now facilitating ambitious large-scale investigations of the spatial and temporal dynamics of the proteome; however, the increasing size and complexity of these data sets is overwhelming current downstream computational methods, specifically those that support the postquantification analysis pipeline. Here we present HiQuant, a novel application that enables the design and execution of a postquantification workflow, including common data-processing steps, such as assay normalization and grouping, and experimental replicate quality control and statistical analysis. HiQuant also enables the interpretation of results generated from large-scale data sets by supporting interactive heatmap analysis and also the direct export to Cytoscape and Gephi, two leading network analysis platforms. HiQuant may be run via a user-friendly graphical interface and also supports complete one-touch automation via a command-line mode. We evaluate HiQuant's performance by analyzing a large-scale, complex interactome mapping data set and demonstrate a 200-fold improvement in the execution time over current methods. We also demonstrate HiQuant's general utility by analyzing proteome-wide quantification data generated from both a large-scale public tyrosine kinase siRNA knock-down study and an in-house investigation into the temporal dynamics of the KSR1 and KSR2 interactomes. Download HiQuant, sample data sets, and supporting documentation at http://hiquant.primesdb.eu .

Analysis of cyclical behavior in time series of stock market returns

NASA Astrophysics Data System (ADS)

Stratimirović, Djordje; Sarvan, Darko; Miljković, Vladimir; Blesić, Suzana

2018-01-01

In this paper we have analyzed scaling properties and cyclical behavior of the three types of stock market indexes (SMI) time series: data belonging to stock markets of developed economies, emerging economies, and of the underdeveloped or transitional economies. We have used two techniques of data analysis to obtain and verify our findings: the wavelet transform (WT) spectral analysis to identify cycles in the SMI returns data, and the time-dependent detrended moving average (tdDMA) analysis to investigate local behavior around market cycles and trends. We found cyclical behavior in all SMI data sets that we have analyzed. Moreover, the positions and the boundaries of cyclical intervals that we found seam to be common for all markets in our dataset. We list and illustrate the presence of nine such periods in our SMI data. We report on the possibilities to differentiate between the level of growth of the analyzed markets by way of statistical analysis of the properties of wavelet spectra that characterize particular peak behaviors. Our results show that measures like the relative WT energy content and the relative WT amplitude of the peaks in the small scales region could be used to partially differentiate between market economies. Finally, we propose a way to quantify the level of development of a stock market based on estimation of local complexity of market's SMI series. From the local scaling exponents calculated for our nine peak regions we have defined what we named the Development Index, which proved, at least in the case of our dataset, to be suitable to rank the SMI series that we have analyzed in three distinct groups.

Robust control of combustion instabilities

NASA Astrophysics Data System (ADS)

Hong, Boe-Shong

Several interactive dynamical subsystems, each of which has its own time-scale and physical significance, are decomposed to build a feedback-controlled combustion- fluid robust dynamics. On the fast-time scale, the phenomenon of combustion instability is corresponding to the internal feedback of two subsystems: acoustic dynamics and flame dynamics, which are parametrically dependent on the slow-time-scale mean-flow dynamics controlled for global performance by a mean-flow controller. This dissertation constructs such a control system, through modeling, analysis and synthesis, to deal with model uncertainties, environmental noises and time- varying mean-flow operation. Conservation law is decomposed as fast-time acoustic dynamics and slow-time mean-flow dynamics, served for synthesizing LPV (linear parameter varying)- L2-gain robust control law, in which a robust observer is embedded for estimating and controlling the internal status, while achieving trade- offs among robustness, performances and operation. The robust controller is formulated as two LPV-type Linear Matrix Inequalities (LMIs), whose numerical solver is developed by finite-element method. Some important issues related to physical understanding and engineering application are discussed in simulated results of the control system.

NASA GEOS-3/TRMM Re-analysis: Capturing Observed Tropical Rainfall Variability in Global Analysis for Climate Research

NASA Technical Reports Server (NTRS)

Hou, Arthur Y.

2004-01-01

Understanding climate variability over a wide range of space-time scales requires a comprehensive description of the earth system. Global analyses produced by a fixed assimilation system (i.e., re-analyses) - as their quality continues to improve - have the potential of providing a vital tool for meeting this challenge. But at the present time, the usefulness of re-analyses is limited by uncertainties in such basic fields as clouds, precipitation, and evaporation - especially in the tropics, where observations are relatively sparse. Analyses of the tropics have long been shown to be sensitive to. the treatment of cloud precipitation processes, which remains a major source of uncertainty in current models. Yet, for many climate studies it is crucial that analyses can accurately reproduce the observed rainfall intensity and variability since a small error of 1 mm/d in surface rain translates into an error of approx. 30 W/sq m in energy (latent heat) flux. Currently, discrepancies between the observed and analyzed monthly-mean rain rates averaged to 100 km x 100 km resolution can exceed 4 mm/d (or 120 W/sq m ), compared to uncertainties in surface radiative fluxes of approx. 10-20 W/sq m . Improving precipitation in analyses would reduce a major source of uncertainty in the global energy budget. Uncertainties in tropical precipitation have also been a major impediment in understanding how the tropics interact with other regions, including the remote response to El Nino/Southern Oscillation (ENSO) variability on interannual time scales, the influence of Madden-Julian Oscillation (MJO) and monsoons on intraseasonal time scales. A global analysis that can replicate the observed precipitation variability together with physically consistent estimates of other atmospheric variables provides the key to breaking this roadblock. NASA Goddard Space Flight Center has been exploring the use of satellite-based microwave rainfall measurements in improving global analyses and has recently produced a multi-year, 1 x 1 TRMM re-analysis , which assimilates 6-hourly TMI and SSM/I surface rain rates over tropical oceans using a ID variational continuous assimilation (VCA) procedure in the GEOS-3 global data assimilation system. The analysis period extends from 1 November 1997 through 3 1 December 2002. The goal is to produce a multi-year global analysis that is dynamically consistent with available tropical precipitation observations for the community to assess its utility in climate applications and identify areas for further improvements. A distinct feature of the GEOS-3RRMh4 re-analysis is that its precipitation analysis is not derived from a short-term forecast (as done in most operational systems) but is given by a time- continuous model integration constrained by precipitation observations within a 6-h analysis window, while the wind, temperature, and pressure fields are allowed to directly respond to the improved precipitation and associated latent heating structures within the same analysis window. In this talk, I will assess the impact VCA precipitation assimilation on analyses of climate signals ranging from a few weeks to interannual time scales and compare results against other operational and reanalysis products.

Galactic outflows, star formation histories, and time-scales in starburst dwarf galaxies from STARBIRDS

NASA Astrophysics Data System (ADS)

McQuinn, Kristen B. W.; Skillman, Evan D.; Heilman, Taryn N.; Mitchell, Noah P.; Kelley, Tyler

2018-07-01

Winds are predicted to be ubiquitous in low-mass, actively star-forming galaxies. Observationally, winds have been detected in relatively few local dwarf galaxies, with even fewer constraints placed on their time-scales. Here, we compare galactic outflows traced by diffuse, soft X-ray emission from Chandra Space Telescope archival observations to the star formation histories derived from Hubble Space Telescope imaging of the resolved stellar populations in six starburst dwarfs. We constrain the longevity of a wind to have an upper limit of 25 Myr based on galaxies whose starburst activity has already declined, although a larger sample is needed to confirm this result. We find an average 16 per cent efficiency for converting the mechanical energy of stellar feedback to thermal, soft X-ray emission on the 25 Myr time-scale, somewhat higher than simulations predict. The outflows have likely been sustained for time-scales comparable to the duration of the starbursts (i.e. 100s Myr), after taking into account the time for the development and cessation of the wind. The wind time-scales imply that material is driven to larger distances in the circumgalactic medium than estimated by assuming short, 5-10 Myr starburst durations, and that less material is recycled back to the host galaxy on short time-scales. In the detected outflows, the expelled hot gas shows various morphologies that are not consistent with a simple biconical outflow structure. The sample and analysis are part of a larger program, the STARBurst IRregular Dwarf Survey (STARBIRDS), aimed at understanding the life cycle and impact of starburst activity in low-mass systems.

Nonadiabatic dynamics of electron transfer in solution: Explicit and implicit solvent treatments that include multiple relaxation time scales

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

Schwerdtfeger, Christine A.; Soudackov, Alexander V.; Hammes-Schiffer, Sharon, E-mail: shs3@illinois.edu

2014-01-21

The development of efficient theoretical methods for describing electron transfer (ET) reactions in condensed phases is important for a variety of chemical and biological applications. Previously, dynamical dielectric continuum theory was used to derive Langevin equations for a single collective solvent coordinate describing ET in a polar solvent. In this theory, the parameters are directly related to the physical properties of the system and can be determined from experimental data or explicit molecular dynamics simulations. Herein, we combine these Langevin equations with surface hopping nonadiabatic dynamics methods to calculate the rate constants for thermal ET reactions in polar solvents formore » a wide range of electronic couplings and reaction free energies. Comparison of explicit and implicit solvent calculations illustrates that the mapping from explicit to implicit solvent models is valid even for solvents exhibiting complex relaxation behavior with multiple relaxation time scales and a short-time inertial response. The rate constants calculated for implicit solvent models with a single solvent relaxation time scale corresponding to water, acetonitrile, and methanol agree well with analytical theories in the Golden rule and solvent-controlled regimes, as well as in the intermediate regime. The implicit solvent models with two relaxation time scales are in qualitative agreement with the analytical theories but quantitatively overestimate the rate constants compared to these theories. Analysis of these simulations elucidates the importance of multiple relaxation time scales and the inertial component of the solvent response, as well as potential shortcomings of the analytical theories based on single time scale solvent relaxation models. This implicit solvent approach will enable the simulation of a wide range of ET reactions via the stochastic dynamics of a single collective solvent coordinate with parameters that are relevant to experimentally accessible systems.« less

Multi-scale Slip Inversion Based on Simultaneous Spatial and Temporal Domain Wavelet Transform

NASA Astrophysics Data System (ADS)

Liu, W.; Yao, H.; Yang, H. Y.

2017-12-01

Finite fault inversion is a widely used method to study earthquake rupture processes. Some previous studies have proposed different methods to implement finite fault inversion, including time-domain, frequency-domain, and wavelet-domain methods. Many previous studies have found that different frequency bands show different characteristics of the seismic rupture (e.g., Wang and Mori, 2011; Yao et al., 2011, 2013; Uchide et al., 2013; Yin et al., 2017). Generally, lower frequency waveforms correspond to larger-scale rupture characteristics while higher frequency data are representative of smaller-scale ones. Therefore, multi-scale analysis can help us understand the earthquake rupture process thoroughly from larger scale to smaller scale. By the use of wavelet transform, the wavelet-domain methods can analyze both the time and frequency information of signals in different scales. Traditional wavelet-domain methods (e.g., Ji et al., 2002) implement finite fault inversion with both lower and higher frequency signals together to recover larger-scale and smaller-scale characteristics of the rupture process simultaneously. Here we propose an alternative strategy with a two-step procedure, i.e., firstly constraining the larger-scale characteristics with lower frequency signals, and then resolving the smaller-scale ones with higher frequency signals. We have designed some synthetic tests to testify our strategy and compare it with the traditional one. We also have applied our strategy to study the 2015 Gorkha Nepal earthquake using tele-seismic waveforms. Both the traditional method and our two-step strategy only analyze the data in different temporal scales (i.e., different frequency bands), while the spatial distribution of model parameters also shows multi-scale characteristics. A more sophisticated strategy is to transfer the slip model into different spatial scales, and then analyze the smooth slip distribution (larger scales) with lower frequency data firstly and more detailed slip distribution (smaller scales) with higher frequency data subsequently. We are now implementing the slip inversion using both spatial and temporal domain wavelets. This multi-scale analysis can help us better understand frequency-dependent rupture characteristics of large earthquakes.

Decoupling processes and scales of shoreline morphodynamics

USGS Publications Warehouse

Hapke, Cheryl J.; Plant, Nathaniel G.; Henderson, Rachel E.; Schwab, William C.; Nelson, Timothy R.

2016-01-01

Behavior of coastal systems on time scales ranging from single storm events to years and decades is controlled by both small-scale sediment transport processes and large-scale geologic, oceanographic, and morphologic processes. Improved understanding of coastal behavior at multiple time scales is required for refining models that predict potential erosion hazards and for coastal management planning and decision-making. Here we investigate the primary controls on shoreline response along a geologically-variable barrier island on time scales resolving extreme storms and decadal variations over a period of nearly one century. An empirical orthogonal function analysis is applied to a time series of shoreline positions at Fire Island, NY to identify patterns of shoreline variance along the length of the island. We establish that there are separable patterns of shoreline behavior that represent response to oceanographic forcing as well as patterns that are not explained by this forcing. The dominant shoreline behavior occurs over large length scales in the form of alternating episodes of shoreline retreat and advance, presumably in response to storms cycles. Two secondary responses include long-term response that is correlated to known geologic variations of the island and the other reflects geomorphic patterns with medium length scale. Our study also includes the response to Hurricane Sandy and a period of post-storm recovery. It was expected that the impacts from Hurricane Sandy would disrupt long-term trends and spatial patterns. We found that the response to Sandy at Fire Island is not notable or distinguishable from several other large storms of the prior decade.

Towards the 1 mm/y stability of the radial orbit error at regional scales

NASA Astrophysics Data System (ADS)

Couhert, Alexandre; Cerri, Luca; Legeais, Jean-François; Ablain, Michael; Zelensky, Nikita P.; Haines, Bruce J.; Lemoine, Frank G.; Bertiger, William I.; Desai, Shailen D.; Otten, Michiel

2015-01-01

An estimated orbit error budget for the Jason-1 and Jason-2 GDR-D solutions is constructed, using several measures of orbit error. The focus is on the long-term stability of the orbit time series for mean sea level applications on a regional scale. We discuss various issues related to the assessment of radial orbit error trends; in particular this study reviews orbit errors dependent on the tracking technique, with an aim to monitoring the long-term stability of all available tracking systems operating on Jason-1 and Jason-2 (GPS, DORIS, SLR). The reference frame accuracy and its effect on Jason orbit is assessed. We also examine the impact of analysis method on the inference of Geographically Correlated Errors as well as the significance of estimated radial orbit error trends versus the time span of the analysis. Thus a long-term error budget of the 10-year Jason-1 and Envisat GDR-D orbit time series is provided for two time scales: interannual and decadal. As the temporal variations of the geopotential remain one of the primary limitations in the Precision Orbit Determination modeling, the overall accuracy of the Jason-1 and Jason-2 GDR-D solutions is evaluated through comparison with external orbits based on different time-variable gravity models. This contribution is limited to an East-West “order-1” pattern at the 2 mm/y level (secular) and 4 mm level (seasonal), over the Jason-2 lifetime. The possibility of achieving sub-mm/y radial orbit stability over interannual and decadal periods at regional scales and the challenge of evaluating such an improvement using in situ independent data is discussed.

Scale-up of industrial biodiesel production to 40 m(3) using a liquid lipase formulation.

PubMed

Price, Jason; Nordblad, Mathias; Martel, Hannah H; Chrabas, Brent; Wang, Huali; Nielsen, Per Munk; Woodley, John M

2016-08-01

In this work, we demonstrate the scale-up from an 80 L fed-batch scale to 40 m(3) along with the design of a 4 m(3) continuous process for enzymatic biodiesel production catalyzed by NS-40116 (a liquid formulation of a modified Thermomyces lanuginosus lipase). Based on the analysis of actual pilot plant data for the transesterification of used cooking oil and brown grease, we propose a method applying first order integral analysis to fed-batch data based on either the bound glycerol or free fatty acid content in the oil. This method greatly simplifies the modeling process and gives an indication of the effect of mixing at the various scales (80 L to 40 m(3) ) along with the prediction of the residence time needed to reach a desired conversion in a CSTR. Suitable process metrics reflecting commercial performance such as the reaction time, enzyme efficiency, and reactor productivity were evaluated for both the fed-batch and CSTR cases. Given similar operating conditions, the CSTR operation on average, has a reaction time which is 1.3 times greater than the fed-batch operation. We also showed how the process metrics can be used to quickly estimate the selling price of the enzyme. Assuming a biodiesel selling price of 0.6 USD/kg and a one-time use of the enzyme (0.1% (w/woil ) enzyme dosage); the enzyme can then be sold for 30 USD/kg which ensures that that the enzyme cost is not more than 5% of the biodiesel revenue. Biotechnol. Bioeng. 2016;113: 1719-1728. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A Randomized Controlled Trial of Home-Based Exercise for Cancer-Related Fatigue in Women during and after Chemotherapy with or without Radiation Therapy

PubMed Central

Dodd, Marylin J.; Cho, Maria H.; Miaskowski, Christine; Painter, Patricia L.; Paul, Steven M.; Cooper, Bruce A.; Duda, John; Krasnoff, Joanne; Bank, Kayee A.

2010-01-01

Background Few studies have evaluated an individualized home-based exercise prescription during and after cancer treatment. Objective The purpose was to evaluate the effectiveness of a home-based exercise training intervention, the PRO-SELF FATIGUE CONTROL PROGRAM on the management of cancer related fatigue. Interventions/Methods Participants (N=119) were randomized into one of three groups: Group 1 (EE) received the exercise prescription throughout the study; Group 2 (CE) received their exercise prescription after completing cancer treatment; Group 3 (CC) received usual care. Patients completed the Piper Fatigue Scale, General Sleep Disturbance Scale, Center for Epidemiological Studies-Depression scale, and Worst Pain Intensity Scale. Results All groups reported mild fatigue levels, sleep disturbance and mild pain, but not depression. Using multilevel regression analysis significant linear and quadratic trends were found for change in fatigue and pain (i.e., scores increased, then decreased over time). No group differences were found in the changing scores over time. A significant quadratic effect for the trajectory of sleep disturbance was found, but no group differences were detected over time. No significant time or group effects were found for depression. Conclusions Our home-based exercise intervention had no effect on fatigue or related symptoms associated with cancer treatment. The optimal timing of exercise remains to be determined. Implications for practice Clinicians need to be aware that some physical activity is better than none, and there is no harm in exercise as tolerated during cancer treatment. Further analysis is needed to examine the adherence to exercise. More frequent assessments of fatigue, sleep disturbance, depression, and pain may capture the effect of exercise. PMID:20467301

Towards the 1 mm/y Stability of the Radial Orbit Error at Regional Scales

NASA Technical Reports Server (NTRS)

Couhert, Alexandre; Cerri, Luca; Legeais, Jean-Francois; Ablain, Michael; Zelensky, Nikita P.; Haines, Bruce J.; Lemoine, Frank G.; Bertiger, William I.; Desai, Shailen D.; Otten, Michiel

2015-01-01

An estimated orbit error budget for the Jason-1 and Jason-2 GDR-D solutions is constructed, using several measures of orbit error. The focus is on the long-term stability of the orbit time series for mean sea level applications on a regional scale. We discuss various issues related to the assessment of radial orbit error trends; in particular this study reviews orbit errors dependent on the tracking technique, with an aim to monitoring the long-term stability of all available tracking systems operating on Jason-1 and Jason-2 (GPS, DORIS, SLR). The reference frame accuracy and its effect on Jason orbit is assessed. We also examine the impact of analysis method on the inference of Geographically Correlated Errors as well as the significance of estimated radial orbit error trends versus the time span of the analysis. Thus a long-term error budget of the 10-year Jason-1 and Envisat GDR-D orbit time series is provided for two time scales: interannual and decadal. As the temporal variations of the geopotential remain one of the primary limitations in the Precision Orbit Determination modeling, the overall accuracy of the Jason-1 and Jason-2 GDR-D solutions is evaluated through comparison with external orbits based on different time-variable gravity models. This contribution is limited to an East-West "order-1" pattern at the 2 mm/y level (secular) and 4 mm level (seasonal), over the Jason-2 lifetime. The possibility of achieving sub-mm/y radial orbit stability over interannual and decadal periods at regional scales and the challenge of evaluating such an improvement using in situ independent data is discussed.

Towards the 1 mm/y Stability of the Radial Orbit Error at Regional Scales

NASA Technical Reports Server (NTRS)

Couhert, Alexandre; Cerri, Luca; Legeais, Jean-Francois; Ablain, Michael; Zelensky, Nikita P.; Haines, Bruce J.; Lemoine, Frank G.; Bertiger, William I.; Desai, Shailen D.; Otten, Michiel

2014-01-01

An estimated orbit error budget for the Jason-1 and Jason-2 GDR-D solutions is constructed, using several measures of orbit error. The focus is on the long-term stability of the orbit time series for mean sea level applications on a regional scale. We discuss various issues related to the assessment of radial orbit error trends; in particular this study reviews orbit errors dependent on the tracking technique, with an aim to monitoring the long-term stability of all available tracking systems operating on Jason-1 and Jason-2 (GPS, DORIS,SLR). The reference frame accuracy and its effect on Jason orbit is assessed. We also examine the impact of analysis method on the inference of Geographically Correlated Errors as well as the significance of estimated radial orbit error trends versus the time span of the analysis. Thus a long-term error budget of the 10-year Jason-1 and Envisat GDR-D orbit time series is provided for two time scales: interannual and decadal. As the temporal variations of the geopotential remain one of the primary limitations in the Precision Orbit Determination modeling, the overall accuracy of the Jason-1 and Jason-2 GDR-D solutions is evaluated through comparison with external orbits based on different time-variable gravity models. This contribution is limited to an East-West "order-1" pattern at the 2 mm/y level (secular) and 4 mm level (seasonal), over the Jason-2 lifetime. The possibility of achieving sub-mm/y radial orbit stability over interannual and decadal periods at regional scales and the challenge of evaluating such an improvement using in situ independent data is discussed.

Fixation of competing strategies when interacting agents differ in the time scale of strategy updating

NASA Astrophysics Data System (ADS)

Zhang, Jianlei; Weissing, Franz J.; Cao, Ming

2016-09-01

A commonly used assumption in evolutionary game theory is that natural selection acts on individuals in the same time scale; e.g., players use the same frequency to update their strategies. Variation in learning rates within populations suggests that evolutionary game theory may not necessarily be restricted to uniform time scales associated with the game interaction and strategy adaption evolution. In this study, we remove this restricting assumption by dividing the population into fast and slow groups according to the players' strategy updating frequencies and investigate how different strategy compositions of one group influence the evolutionary outcome of the other's fixation probabilities of strategies within its own group. Analytical analysis and numerical calculations are performed to study the evolutionary dynamics of strategies in typical classes of two-player games (prisoner's dilemma game, snowdrift game, and stag-hunt game). The introduction of the heterogeneity in strategy-update time scales leads to substantial changes in the evolution dynamics of strategies. We provide an approximation formula for the fixation probability of mutant types in finite populations and study the outcome of strategy evolution under the weak selection. We find that although heterogeneity in time scales makes the collective evolutionary dynamics more complicated, the possible long-run evolutionary outcome can be effectively predicted under technical assumptions when knowing the population composition and payoff parameters.

Open shop scheduling problem to minimize total weighted completion time

NASA Astrophysics Data System (ADS)

Bai, Danyu; Zhang, Zhihai; Zhang, Qiang; Tang, Mengqian

2017-01-01

A given number of jobs in an open shop scheduling environment must each be processed for given amounts of time on each of a given set of machines in an arbitrary sequence. This study aims to achieve a schedule that minimizes total weighted completion time. Owing to the strong NP-hardness of the problem, the weighted shortest processing time block (WSPTB) heuristic is presented to obtain approximate solutions for large-scale problems. Performance analysis proves the asymptotic optimality of the WSPTB heuristic in the sense of probability limits. The largest weight block rule is provided to seek optimal schedules in polynomial time for a special case. A hybrid discrete differential evolution algorithm is designed to obtain high-quality solutions for moderate-scale problems. Simulation experiments demonstrate the effectiveness of the proposed algorithms.

Investigating precipitation changes of anthropic origin: data and methodological issues

NASA Astrophysics Data System (ADS)

de Lima, Isabel; Lovejoy, Shaun

2017-04-01

There is much concern about the social, environmental and economic impacts of climate change that could result directly from changes in temperature and precipitation. For temperature, the situation is better understood; but despite the many studies that have been already dedicated to precipitation, change in this process - that could be associated to the transition to the Anthropocene - has not yet been convincingly proven. A large fraction of those studies have been exploring temporal (linear) trends in local precipitation, sometimes using records over only a few decades; other fewer studies have been dedicated to investigating global precipitation change. Overall, precipitation change of anthropic origin has showed to be difficult to establish with high statistical significance and, moreover, different data and products have displayed important discrepancies; this is valid even for global precipitation. We argue that the inadequate resolution and length of the data commonly used, as well as methodological issues, are among the main factors limiting the ability to identify the signature of change in precipitation. We propose several ways in which one can hope to improve the situation - or at least - clarify the difficulties. From the point of view of statistical analysis, the problem is one of detecting a low frequency anthropogenic signal in the presence of "noise" - the natural variability (the latter includes both internal dynamics and responses to volcanic, solar or other natural forcings). A consequence is that as one moves to longer and longer time scales, fluctuations are increasingly averaged and at some point, the anthropogenic signal will stand out above the natural variability noise. This approach can be systematized using scaling fluctuation analysis to characterizing different precipitation scaling regimes: weather, macroweather, climate - from higher to lower frequencies; in the anthropocene, the macroweather regime covers the range of time scales from about a month to ≈30 years. We illustrate this using local gauge data and three qualitatively different global scale precipitation products (from gauges, reanalyses and a satellite and gauge hybrid) that allow to investigate precipitation from monthly to centennial scales and in space from planetary down to 5°x5° scales. By systematically characterizing precipitation variability across wide ranges of time and space scales, we show that the anthropogenic signal only exceeded the natural variability at time scales larger than ≈20 years, so that the disagreement in the trends can be traced to these low frequencies.

Detecting climate-change responses of plants and soil organic matter using isotopomers

NASA Astrophysics Data System (ADS)

Schleucher, Jürgen; Ehlers, Ina; Segura, Javier; Haei, Mahsa; Augusti, Angela; Köhler, Iris; Zuidema, Pieter; Nilsson, Mats; Öquist, Mats

2015-04-01

Responses of vegetation and soils to environmental changes will strongly influence future climate, and responses on century time scales are most important for feedbacks on the carbon cycle, climate models, prediction of crop productivity, and for adaptation to climate change. That plants respond to increasing CO2 on century time scales has been proven by changes in stomatal index, but very little is known beyond this. In soil, the complexity of soil organic matter (SOM) has hampered a sufficient understanding of the temperature sensitivity of SOM turnover. Here we present new stable isotope methodology that allows detecting shifts in metabolism on long time scales, and elucidating SOM turnover on the molecular level. Compound-specific isotope analysis measures isotope ratios of defined metabolites, but as average of the entire molecule. Here we demonstrate how much more detailed information can be obtained from analyses of intramolecular distributions of stable isotopes, so-called isotopomer abundances. As key tool, we use nuclear magnetic resonance (NMR) spectroscopy, which allows detecting isotope abundance with intramolecular resolution and without risk for isotope fractionation during analysis. Enzyme isotope fractionations create non-random isotopomer patterns in biochemical metabolites. At natural isotope abundance, these patterns continuously store metabolic information. We present a strategy how these patterns can be used as to extract signals on plant physiology, climate variables, and their interactions. Applied in retrospective analyses to herbarium samples and tree-ring series, we detect century-time-scale metabolic changes in response to increasing atmospheric CO2, with no evidence for acclimatory reactions by the plants. In trees, the increase in photosynthesis expected from increasing CO2 ("CO2 fertilization) was diminished by increasing temperatures, which resolves the discrepancy between expected increases in photosynthesis and commonly observed lack of biomass increases. Isotopomer patterns are a rich source of metabolic information, which can be retrieved from archives of plant material covering centuries and millennia, the time scales relevant for climate change. Boreal soils contain a huge carbon pool that may be particularly vulnerable to climate change. Biological activity persists in soils under frozen conditions, but it is largely unknown what controls it, and whether it differs from unfrozen conditions. In an incubation experiment, we traced the metabolism of 13C-labeled cellulose by soil microorganisms. NMR analysis revealed that the 13C label was converted both to respired CO2 and to phospholipid fatty acids, indicating that the polymeric substrate cellulose entered both catabolic and anabolic pathways. Both applications demonstrate a fundamental advantage of isotopomer analysis, namely that their abundances directly reflect biochemical processes. This allows obtaining metabolic information on millennial time scales, thus bridging between plant-physiology and paleo sciences. It may also be key to characterizing SOM with sufficient resolution to understand current biogeochemical fluxes involving SOM and to identify molecular components and organisms that are key for SOM turnover.

Time-Series Analysis of Embodied Interaction: Movement Variability and Complexity Matching As Dyadic Properties

PubMed Central

Zapata-Fonseca, Leonardo; Dotov, Dobromir; Fossion, Ruben; Froese, Tom

2016-01-01

There is a growing consensus that a fuller understanding of social cognition depends on more systematic studies of real-time social interaction. Such studies require methods that can deal with the complex dynamics taking place at multiple interdependent temporal and spatial scales, spanning sub-personal, personal, and dyadic levels of analysis. We demonstrate the value of adopting an extended multi-scale approach by re-analyzing movement time-series generated in a study of embodied dyadic interaction in a minimal virtual reality environment (a perceptual crossing experiment). Reduced movement variability revealed an interdependence between social awareness and social coordination that cannot be accounted for by either subjective or objective factors alone: it picks out interactions in which subjective and objective conditions are convergent (i.e., elevated coordination is perceived as clearly social, and impaired coordination is perceived as socially ambiguous). This finding is consistent with the claim that interpersonal interaction can be partially constitutive of direct social perception. Clustering statistics (Allan Factor) of salient events revealed fractal scaling. Complexity matching defined as the similarity between these scaling laws was significantly more pronounced in pairs of participants as compared to surrogate dyads. This further highlights the multi-scale and distributed character of social interaction and extends previous complexity matching results from dyadic conversation to non-verbal social interaction dynamics. Trials with successful joint interaction were also associated with an increase in local coordination. Consequently, a local coordination pattern emerges on the background of complex dyadic interactions in the PCE task and makes joint successful performance possible. PMID:28018274

Grand Minima and Equatorward Propagation in a Cycling Stellar Convective Dynamo

NASA Astrophysics Data System (ADS)

Augustson, Kyle C.; Brun, Allan Sacha; Miesch, Mark; Toomre, Juri

2015-08-01

The 3-D magnetohydrodynamic (MHD) Anelastic Spherical Harmonic (ASH) code, using slope-limited diffusion, is employed to capture convective and dynamo processes achieved in a global-scale stellar convection simulation for a model solar-mass star rotating at three times the solar rate. The dynamo generated magnetic fields possesses many time scales, with a prominent polarity cycle occurring roughly every 6.2 years. The magnetic field forms large-scale toroidal wreaths, whose formation is tied to the low Rossby number of the convection in this simulation. The polarity reversals are linked to the weakened differential rotation and a resistive collapse of the large-scale magnetic field. An equatorial migration of the magnetic field is seen, which is due to the strong modulation of the differential rotation rather than a dynamo wave. A poleward migration of magnetic flux from the equator eventually leads to the reversal of the polarity of the high-latitude magnetic field. This simulation also enters an interval with reduced magnetic energy at low latitudes lasting roughly 16 years (about 2.5 polarity cycles), during which the polarity cycles are disrupted and after which the dynamo recovers its regular polarity cycles. An analysis of this grand minimum reveals that it likely arises through the interplay of symmetric and antisymmetric dynamo families. This intermittent dynamo state potentially results from the simulations relatively low magnetic Prandtl number. A mean-field-based analysis of this dynamo simulation demonstrates that it is of the α-Ω type. The time scales that appear to be relevant to the magnetic polarity reversal are also identified.

Interactive Exploration and Analysis of Large-Scale Simulations Using Topology-Based Data Segmentation.

PubMed

Bremer, Peer-Timo; Weber, Gunther; Tierny, Julien; Pascucci, Valerio; Day, Marcus S; Bell, John B

2011-09-01

Large-scale simulations are increasingly being used to study complex scientific and engineering phenomena. As a result, advanced visualization and data analysis are also becoming an integral part of the scientific process. Often, a key step in extracting insight from these large simulations involves the definition, extraction, and evaluation of features in the space and time coordinates of the solution. However, in many applications, these features involve a range of parameters and decisions that will affect the quality and direction of the analysis. Examples include particular level sets of a specific scalar field, or local inequalities between derived quantities. A critical step in the analysis is to understand how these arbitrary parameters/decisions impact the statistical properties of the features, since such a characterization will help to evaluate the conclusions of the analysis as a whole. We present a new topological framework that in a single-pass extracts and encodes entire families of possible features definitions as well as their statistical properties. For each time step we construct a hierarchical merge tree a highly compact, yet flexible feature representation. While this data structure is more than two orders of magnitude smaller than the raw simulation data it allows us to extract a set of features for any given parameter selection in a postprocessing step. Furthermore, we augment the trees with additional attributes making it possible to gather a large number of useful global, local, as well as conditional statistic that would otherwise be extremely difficult to compile. We also use this representation to create tracking graphs that describe the temporal evolution of the features over time. Our system provides a linked-view interface to explore the time-evolution of the graph interactively alongside the segmentation, thus making it possible to perform extensive data analysis in a very efficient manner. We demonstrate our framework by extracting and analyzing burning cells from a large-scale turbulent combustion simulation. In particular, we show how the statistical analysis enabled by our techniques provides new insight into the combustion process.

(Multi)fractality of Earthquakes by use of Wavelet Analysis

NASA Astrophysics Data System (ADS)

Enescu, B.; Ito, K.; Struzik, Z. R.

2002-12-01

The fractal character of earthquakes' occurrence, in time, space or energy, has by now been established beyond doubt and is in agreement with modern models of seismicity. Moreover, the cascade-like generation process of earthquakes -with one "main" shock followed by many aftershocks, having their own aftershocks- may well be described through multifractal analysis, well suited for dealing with such multiplicative processes. The (multi)fractal character of seismicity has been analysed so far by using traditional techniques, like the box-counting and correlation function algorithms. This work introduces a new approach for characterising the multifractal patterns of seismicity. The use of wavelet analysis, in particular of the wavelet transform modulus maxima, to multifractal analysis was pioneered by Arneodo et al. (1991, 1995) and applied successfully in diverse fields, such as the study of turbulence, the DNA sequences or the heart rate dynamics. The wavelets act like a microscope, revealing details about the analysed data at different times and scales. We introduce and perform such an analysis on the occurrence time of earthquakes and show its advantages. In particular, we analyse shallow seismicity, characterised by a high aftershock "productivity", as well as intermediate and deep seismic activity, known for its scarcity of aftershocks. We examine as well declustered (aftershocks removed) versions of seismic catalogues. Our preliminary results show some degree of multifractality for the undeclustered, shallow seismicity. On the other hand, at large scales, we detect a monofractal scaling behaviour, clearly put in evidence for the declustered, shallow seismic activity. Moreover, some of the declustered sequences show a long-range dependent (LRD) behaviour, characterised by a Hurst exponent, H > 0.5, in contrast with the memory-less, Poissonian model. We demonstrate that the LRD is a genuine characteristic and is not an effect of the time series probability distribution function. One of the most attractive features of wavelet analysis is its ability to determine a local Hurst exponent. We show that this feature together with the possibility of extending the analysis to spatial patterns may constitute a valuable approach to search for anomalous (precursory?) patterns of seismic activity.

Evolution of scaling emergence in large-scale spatial epidemic spreading.

PubMed

Wang, Lin; Li, Xiang; Zhang, Yi-Qing; Zhang, Yan; Zhang, Kan

2011-01-01

Zipf's law and Heaps' law are two representatives of the scaling concepts, which play a significant role in the study of complexity science. The coexistence of the Zipf's law and the Heaps' law motivates different understandings on the dependence between these two scalings, which has still hardly been clarified. In this article, we observe an evolution process of the scalings: the Zipf's law and the Heaps' law are naturally shaped to coexist at the initial time, while the crossover comes with the emergence of their inconsistency at the larger time before reaching a stable state, where the Heaps' law still exists with the disappearance of strict Zipf's law. Such findings are illustrated with a scenario of large-scale spatial epidemic spreading, and the empirical results of pandemic disease support a universal analysis of the relation between the two laws regardless of the biological details of disease. Employing the United States domestic air transportation and demographic data to construct a metapopulation model for simulating the pandemic spread at the U.S. country level, we uncover that the broad heterogeneity of the infrastructure plays a key role in the evolution of scaling emergence. The analyses of large-scale spatial epidemic spreading help understand the temporal evolution of scalings, indicating the coexistence of the Zipf's law and the Heaps' law depends on the collective dynamics of epidemic processes, and the heterogeneity of epidemic spread indicates the significance of performing targeted containment strategies at the early time of a pandemic disease.

Effect of noise in principal component analysis with an application to ozone pollution

NASA Astrophysics Data System (ADS)

Tsakiri, Katerina G.

This thesis analyzes the effect of independent noise in principal components of k normally distributed random variables defined by a covariance matrix. We prove that the principal components as well as the canonical variate pairs determined from joint distribution of original sample affected by noise can be essentially different in comparison with those determined from the original sample. However when the differences between the eigenvalues of the original covariance matrix are sufficiently large compared to the level of the noise, the effect of noise in principal components and canonical variate pairs proved to be negligible. The theoretical results are supported by simulation study and examples. Moreover, we compare our results about the eigenvalues and eigenvectors in the two dimensional case with other models examined before. This theory can be applied in any field for the decomposition of the components in multivariate analysis. One application is the detection and prediction of the main atmospheric factor of ozone concentrations on the example of Albany, New York. Using daily ozone, solar radiation, temperature, wind speed and precipitation data, we determine the main atmospheric factor for the explanation and prediction of ozone concentrations. A methodology is described for the decomposition of the time series of ozone and other atmospheric variables into the global term component which describes the long term trend and the seasonal variations, and the synoptic scale component which describes the short term variations. By using the Canonical Correlation Analysis, we show that solar radiation is the only main factor between the atmospheric variables considered here for the explanation and prediction of the global and synoptic scale component of ozone. The global term components are modeled by a linear regression model, while the synoptic scale components by a vector autoregressive model and the Kalman filter. The coefficient of determination, R2, for the prediction of the synoptic scale ozone component was found to be the highest when we consider the synoptic scale component of the time series for solar radiation and temperature. KEY WORDS: multivariate analysis; principal component; canonical variate pairs; eigenvalue; eigenvector; ozone; solar radiation; spectral decomposition; Kalman filter; time series prediction

A rapid local singularity analysis algorithm with applications

NASA Astrophysics Data System (ADS)

Chen, Zhijun; Cheng, Qiuming; Agterberg, Frits

2015-04-01

The local singularity model developed by Cheng is fast gaining popularity in characterizing mineralization and detecting anomalies of geochemical, geophysical and remote sensing data. However in one of the conventional algorithms involving the moving average values with different scales is time-consuming especially while analyzing a large dataset. Summed area table (SAT), also called as integral image, is a fast algorithm used within the Viola-Jones object detection framework in computer vision area. Historically, the principle of SAT is well-known in the study of multi-dimensional probability distribution functions, namely in computing 2D (or ND) probabilities (area under the probability distribution) from the respective cumulative distribution functions. We introduce SAT and it's variation Rotated Summed Area Table in the isotropic, anisotropic or directional local singularity mapping in this study. Once computed using SAT, any one of the rectangular sum can be computed at any scale or location in constant time. The area for any rectangular region in the image can be computed by using only 4 array accesses in constant time independently of the size of the region; effectively reducing the time complexity from O(n) to O(1). New programs using Python, Julia, matlab and C++ are implemented respectively to satisfy different applications, especially to the big data analysis. Several large geochemical and remote sensing datasets are tested. A wide variety of scale changes (linear spacing or log spacing) for non-iterative or iterative approach are adopted to calculate the singularity index values and compare the results. The results indicate that the local singularity analysis with SAT is more robust and superior to traditional approach in identifying anomalies.

How Do Novice and Expert Learners Represent, Understand, and Discuss Geologic Time?

NASA Astrophysics Data System (ADS)

Layow, Erica Amanda

This dissertation examined the representations novice and expert learners constructed for the geologic timescale. Learners engaged in a three-part activity. The purpose was to compare novice learners' representations to those of expert learners. This provided insight into the similarities and differences between their strategies for event ordering, assigning values and scale to the geologic timescale model, as well as their language and practices to complete the model. With a qualitative approach to data analysis informed by an expert-novice theoretical framework grounded in phenomenography, learner responses comprised the data analyzed. These data highlighted learners' metacognitive thoughts that might not otherwise be shared through lectures or laboratory activities. Learners' responses were analyzed using a discourse framework that positioned learners as knowers. Novice and expert learners both excelled at ordering and discussing events before the Phanerozoic, but were challenged with events during the Phanerozoic. Novice learners had difficulty assigning values to events and establishing a scale for their models. Expert learners expressed difficulty with determining a scale because of the size of the model, yet eventually used anchor points and unitized the model to establish a scale. Despite challenges constructing their models, novice learners spoke confidently using claims and few hedging phrases indicating their confidence in statements made. Experts used more hedges than novices, however the hedging comments were made about more complex conceptions. Using both phenomenographic and discourse analysis approaches for analysis foregrounded learners' discussions of how they perceived geologic time and their ways of knowing and doing. This research is intended to enhance the geoscience community's understanding of the ways novice and expert learners think and discuss conceptions of geologic time, including the events and values of time, and the strategies used to determine accuracy of scale. This knowledge will provide a base from which to support geoscience curriculum development at the university level, specifically to design activities that will not only engage and express learners' metacognitive scientific practices, but to encourage their construction of scientific identities and membership in the geoscience community.

Multi-scale correlations in different futures markets

NASA Astrophysics Data System (ADS)

Bartolozzi, M.; Mellen, C.; di Matteo, T.; Aste, T.

2007-07-01

In the present work we investigate the multiscale nature of the correlations for high frequency data (1 min) in different futures markets over a period of two years, starting on the 1st of January 2003 and ending on the 31st of December 2004. In particular, by using the concept of local Hurst exponent, we point out how the behaviour of this parameter, usually considered as a benchmark for persistency/antipersistency recognition in time series, is largely time-scale dependent in the market context. These findings are a direct consequence of the intrinsic complexity of a system where trading strategies are scale-adaptive. Moreover, our analysis points out different regimes in the dynamical behaviour of the market indices under consideration.

Cooperation without culture? The null effect of generalized trust on intentional homicide: a cross-national panel analysis, 1995-2009.

PubMed

Robbins, Blaine

2013-01-01

Sociologists, political scientists, and economists all suggest that culture plays a pivotal role in the development of large-scale cooperation. In this study, I used generalized trust as a measure of culture to explore if and how culture impacts intentional homicide, my operationalization of cooperation. I compiled multiple cross-national data sets and used pooled time-series linear regression, single-equation instrumental-variables linear regression, and fixed- and random-effects estimation techniques on an unbalanced panel of 118 countries and 232 observations spread over a 15-year time period. Results suggest that culture and large-scale cooperation form a tenuous relationship, while economic factors such as development, inequality, and geopolitics appear to drive large-scale cooperation.

Scaling in non-stationary time series. (II). Teen birth phenomenon

NASA Astrophysics Data System (ADS)

Ignaccolo, M.; Allegrini, P.; Grigolini, P.; Hamilton, P.; West, B. J.

2004-05-01

This paper is devoted to the problem of statistical mechanics raised by the analysis of an issue of sociological interest: the teen birth phenomenon. It is expected that these data are characterized by correlated fluctuations, reflecting the cooperative properties of the process. However, the assessment of the anomalous scaling generated by these correlations is made difficult, and ambiguous as well, by the non-stationary nature of the data that shows a clear dependence on seasonal periodicity (periodic component) and an average changing slowly in time (slow component) as well. We use the detrending techniques described in the companion paper [The earlier companion paper], to safely remove all the biases and to derive the genuine scaling of the teen birth phenomenon.

Multiscale multifractal time irreversibility analysis of stock markets

NASA Astrophysics Data System (ADS)

Jiang, Chenguang; Shang, Pengjian; Shi, Wenbin

2016-11-01

Time irreversibility is one of the most important properties of nonstationary time series. Complex time series often demonstrate even multiscale time irreversibility, such that not only the original but also coarse-grained time series are asymmetric over a wide range of scales. We study the multiscale time irreversibility of time series. In this paper, we develop a method called multiscale multifractal time irreversibility analysis (MMRA), which allows us to extend the description of time irreversibility to include the dependence on the segment size and statistical moments. We test the effectiveness of MMRA in detecting multifractality and time irreversibility of time series generated from delayed Henon map and binomial multifractal model. Then we employ our method to the time irreversibility analysis of stock markets in different regions. We find that the emerging market has higher multifractality degree and time irreversibility compared with developed markets. In this sense, the MMRA method may provide new angles in assessing the evolution stage of stock markets.

Global, Persistent, Real-time Multi-sensor Automated Satellite Image Analysis and Crop Forecasting in Commercial Cloud

NASA Astrophysics Data System (ADS)

Brumby, S. P.; Warren, M. S.; Keisler, R.; Chartrand, R.; Skillman, S.; Franco, E.; Kontgis, C.; Moody, D.; Kelton, T.; Mathis, M.

2016-12-01

Cloud computing, combined with recent advances in machine learning for computer vision, is enabling understanding of the world at a scale and at a level of space and time granularity never before feasible. Multi-decadal Earth remote sensing datasets at the petabyte scale (8×10^15 bits) are now available in commercial cloud, and new satellite constellations will generate daily global coverage at a few meters per pixel. Public and commercial satellite observations now provide a wide range of sensor modalities, from traditional visible/infrared to dual-polarity synthetic aperture radar (SAR). This provides the opportunity to build a continuously updated map of the world supporting the academic community and decision-makers in government, finanace and industry. We report on work demonstrating country-scale agricultural forecasting, and global-scale land cover/land, use mapping using a range of public and commercial satellite imagery. We describe processing over a petabyte of compressed raw data from 2.8 quadrillion pixels (2.8 petapixels) acquired by the US Landsat and MODIS programs over the past 40 years. Using commodity cloud computing resources, we convert the imagery to a calibrated, georeferenced, multiresolution tiled format suited for machine-learning analysis. We believe ours is the first application to process, in less than a day, on generally available resources, over a petabyte of scientific image data. We report on work combining this imagery with time-series SAR collected by ESA Sentinel 1. We report on work using this reprocessed dataset for experiments demonstrating country-scale food production monitoring, an indicator for famine early warning. We apply remote sensing science and machine learning algorithms to detect and classify agricultural crops and then estimate crop yields and detect threats to food security (e.g., flooding, drought). The software platform and analysis methodology also support monitoring water resources, forests and other general indicators of environmental health, and can detect growth and changes in cities that are displacing historical agricultural zones.

Spatial and temporal analysis of drought variability at several time scales in Syria during 1961-2012

NASA Astrophysics Data System (ADS)

Mathbout, Shifa; Lopez-Bustins, Joan A.; Martin-Vide, Javier; Bech, Joan; Rodrigo, Fernando S.

2018-02-01

This paper analyses the observed spatiotemporal characteristics of drought phenomenon in Syria using the Standardised Precipitation Index (SPI) and the Standardised Precipitation Evapotranspiration Index (SPEI). Temporal variability of drought is calculated for various time scales (3, 6, 9, 12, and 24 months) for 20 weather stations over the 1961-2012 period. The spatial patterns of drought were identified by applying a Principal Component Analysis (PCA) to the SPI and SPEI values at different time scales. The results revealed three heterogeneous and spatially well-defined regions with different temporal evolution of droughts: 1) Northeastern (inland desert); 2) Southern (mountainous landscape); 3) Northwestern (Mediterranean coast). The evolutionary characteristics of drought during 1961-2012 were analysed including spatial and temporal variability of SPI and SPEI, the frequency distribution, and the drought duration. The results of the non-parametric Mann-Kendall test applied to the SPI and SPEI series indicate prevailing significant negative trends (drought) at all stations. Both drought indices have been correlated both on spatial and temporal scales and they are highly comparable, especially, over a 12 and 24 month accumulation period. We concluded that the temporal and spatial characteristics of the SPI and SPEI can be used for developing a drought intensity - areal extent - and frequency curve that assesses the variability of regional droughts in Syria. The analysis of both indices suggests that all three regions had a severe drought in the 1990s, which had never been observed before in the country. Furthermore, the 2007-2010 drought was the driest period in the instrumental record, happening just before the onset of the recent conflict in Syria.

Empirical Investigation of Critical Transitions in Paleoclimate

NASA Astrophysics Data System (ADS)

Loskutov, E. M.; Mukhin, D.; Gavrilov, A.; Feigin, A.

2016-12-01

In this work we apply a new empirical method for the analysis of complex spatially distributed systems to the analysis of paleoclimate data. The method consists of two general parts: (i) revealing the optimal phase-space variables and (ii) construction the empirical prognostic model by observed time series. The method of phase space variables construction based on the data decomposition into nonlinear dynamical modes which was successfully applied to global SST field and allowed clearly separate time scales and reveal climate shift in the observed data interval [1]. The second part, the Bayesian approach to optimal evolution operator reconstruction by time series is based on representation of evolution operator in the form of nonlinear stochastic function represented by artificial neural networks [2,3]. In this work we are focused on the investigation of critical transitions - the abrupt changes in climate dynamics - in match longer time scale process. It is well known that there were number of critical transitions on different time scales in the past. In this work, we demonstrate the first results of applying our empirical methods to analysis of paleoclimate variability. In particular, we discuss the possibility of detecting, identifying and prediction such critical transitions by means of nonlinear empirical modeling using the paleoclimate record time series. The study is supported by Government of Russian Federation (agreement #14.Z50.31.0033 with the Institute of Applied Physics of RAS). 1. Mukhin, D., Gavrilov, A., Feigin, A., Loskutov, E., & Kurths, J. (2015). Principal nonlinear dynamical modes of climate variability. Scientific Reports, 5, 15510. http://doi.org/10.1038/srep155102. Ya. I. Molkov, D. N. Mukhin, E. M. Loskutov, A.M. Feigin, (2012) : Random dynamical models from time series. Phys. Rev. E, Vol. 85, n.3.3. Mukhin, D., Kondrashov, D., Loskutov, E., Gavrilov, A., Feigin, A., & Ghil, M. (2015). Predicting Critical Transitions in ENSO models. Part II: Spatially Dependent Models. Journal of Climate, 28(5), 1962-1976. http://doi.org/10.1175/JCLI-D-14-00240.1

TWO-STAGE FRAGMENTATION FOR CLUSTER FORMATION: ANALYTICAL MODEL AND OBSERVATIONAL CONSIDERATIONS

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

Bailey, Nicole D.; Basu, Shantanu, E-mail: nwityk@uwo.ca, E-mail: basu@uwo.ca

2012-12-10

Linear analysis of the formation of protostellar cores in planar magnetic interstellar clouds shows that molecular clouds exhibit a preferred length scale for collapse that depends on the mass-to-flux ratio and neutral-ion collision time within the cloud. We extend this linear analysis to the context of clustered star formation. By combining the results of the linear analysis with a realistic ionization profile for the cloud, we find that a molecular cloud may evolve through two fragmentation events in the evolution toward the formation of stars. Our model suggests that the initial fragmentation into clumps occurs for a transcritical cloud onmore » parsec scales while the second fragmentation can occur for transcritical and supercritical cores on subparsec scales. Comparison of our results with several star-forming regions (Perseus, Taurus, Pipe Nebula) shows support for a two-stage fragmentation model.« less

Nonlinear filtering properties of detrended fluctuation analysis

NASA Astrophysics Data System (ADS)

Kiyono, Ken; Tsujimoto, Yutaka

2016-11-01

Detrended fluctuation analysis (DFA) has been widely used for quantifying long-range correlation and fractal scaling behavior. In DFA, to avoid spurious detection of scaling behavior caused by a nonstationary trend embedded in the analyzed time series, a detrending procedure using piecewise least-squares fitting has been applied. However, it has been pointed out that the nonlinear filtering properties involved with detrending may induce instabilities in the scaling exponent estimation. To understand this issue, we investigate the adverse effects of the DFA detrending procedure on the statistical estimation. We show that the detrending procedure using piecewise least-squares fitting results in the nonuniformly weighted estimation of the root-mean-square deviation and that this property could induce an increase in the estimation error. In addition, for comparison purposes, we investigate the performance of a centered detrending moving average analysis with a linear detrending filter and sliding window DFA and show that these methods have better performance than the standard DFA.

Statistical properties of edge plasma turbulence in the Large Helical Device

NASA Astrophysics Data System (ADS)

Dewhurst, J. M.; Hnat, B.; Ohno, N.; Dendy, R. O.; Masuzaki, S.; Morisaki, T.; Komori, A.

2008-09-01

Ion saturation current (Isat) measurements made by three tips of a Langmuir probe array in the Large Helical Device are analysed for two plasma discharges. Absolute moment analysis is used to quantify properties on different temporal scales of the measured signals, which are bursty and intermittent. Strong coherent modes in some datasets are found to distort this analysis and are consequently removed from the time series by applying bandstop filters. Absolute moment analysis of the filtered data reveals two regions of power-law scaling, with the temporal scale τ ≈ 40 µs separating the two regimes. A comparison is made with similar results from the Mega-Amp Spherical Tokamak. The probability density function is studied and a monotonic relationship between connection length and skewness is found. Conditional averaging is used to characterize the average temporal shape of the largest intermittent bursts.

Multiscale analysis of the correlation of processing parameters on viscidity of composites fabricated by automated fiber placement

NASA Astrophysics Data System (ADS)

Han, Zhenyu; Sun, Shouzheng; Fu, Yunzhong; Fu, Hongya

2017-10-01

Viscidity is an important physical indicator for assessing fluidity of resin that is beneficial to contact resin with the fibers effectively and reduce manufacturing defects during automated fiber placement (AFP) process. However, the effect of processing parameters on viscidity evolution is rarely studied during AFP process. In this paper, viscidities under different scales are analyzed based on multi-scale analysis method. Firstly, viscous dissipation energy (VDE) within meso-unit under different processing parameters is assessed by using finite element method (FEM). According to multi-scale energy transfer model, meso-unit energy is used as the boundary condition for microscopic analysis. Furthermore, molecular structure of micro-system is built by molecular dynamics (MD) method. And viscosity curves are then obtained by integrating stress autocorrelation function (SACF) with time. Finally, the correlation characteristics of processing parameters to viscosity are revealed by using gray relational analysis method (GRAM). A group of processing parameters is found out to achieve the stability of viscosity and better fluidity of resin.

Large-Scale Aerosol Modeling and Analysis

DTIC Science & Technology

2008-09-30

novel method of simultaneous real- time measurements of ice-nucleating particle concentrations and size- resolved chemical composition of individual...is to develop a practical predictive capability for visibility and weather effects of aerosol particles for the entire globe for timely use in...prediction follows that used in numerical weather prediction, namely real- time assessment for initialization of first-principles models. The Naval

Hardware accelerator design for tracking in smart camera

NASA Astrophysics Data System (ADS)

Singh, Sanjay; Dunga, Srinivasa Murali; Saini, Ravi; Mandal, A. S.; Shekhar, Chandra; Vohra, Anil

2011-10-01

Smart Cameras are important components in video analysis. For video analysis, smart cameras needs to detect interesting moving objects, track such objects from frame to frame, and perform analysis of object track in real time. Therefore, the use of real-time tracking is prominent in smart cameras. The software implementation of tracking algorithm on a general purpose processor (like PowerPC) could achieve low frame rate far from real-time requirements. This paper presents the SIMD approach based hardware accelerator designed for real-time tracking of objects in a scene. The system is designed and simulated using VHDL and implemented on Xilinx XUP Virtex-IIPro FPGA. Resulted frame rate is 30 frames per second for 250x200 resolution video in gray scale.

Variability of rainfall over Lake Kariba catchment area in the Zambezi river basin, Zimbabwe

NASA Astrophysics Data System (ADS)

Muchuru, Shepherd; Botai, Joel O.; Botai, Christina M.; Landman, Willem A.; Adeola, Abiodun M.

2016-04-01

In this study, average monthly and annual rainfall totals recorded for the period 1970 to 2010 from a network of 13 stations across the Lake Kariba catchment area of the Zambezi river basin were analyzed in order to characterize the spatial-temporal variability of rainfall across the catchment area. In the analysis, the data were subjected to intervention and homogeneity analysis using the Cumulative Summation (CUSUM) technique and step change analysis using rank-sum test. Furthermore, rainfall variability was characterized by trend analysis using the non-parametric Mann-Kendall statistic. Additionally, the rainfall series were decomposed and the spectral characteristics derived using Cross Wavelet Transform (CWT) and Wavelet Coherence (WC) analysis. The advantage of using the wavelet-based parameters is that they vary in time and can therefore be used to quantitatively detect time-scale-dependent correlations and phase shifts between rainfall time series at various localized time-frequency scales. The annual and seasonal rainfall series were homogeneous and demonstrated no apparent significant shifts. According to the inhomogeneity classification, the rainfall series recorded across the Lake Kariba catchment area belonged to category A (useful) and B (doubtful), i.e., there were zero to one and two absolute tests rejecting the null hypothesis (at 5 % significance level), respectively. Lastly, the long-term variability of the rainfall series across the Lake Kariba catchment area exhibited non-significant positive and negative trends with coherent oscillatory modes that are constantly locked in phase in the Morlet wavelet space.

Mustiscaling Analysis applied to field Water Content through Distributed Fiber Optic Temperature sensing measurements

NASA Astrophysics Data System (ADS)

Benitez Buelga, Javier; Rodriguez-Sinobas, Leonor; Sanchez, Raul; Gil, Maria; Tarquis, Ana M.

2014-05-01

Soils can be seen as the result of spatial variation operating over several scales. This observation points to 'variability' as a key soil attribute that should be studied. Soil variability has often been considered to be composed of 'functional' (explained) variations plus random fluctuations or noise. However, the distinction between these two components is scale dependent because increasing the scale of observation almost always reveals structure in the noise. Geostatistical methods and, more recently, multifractal/wavelet techniques have been used to characterize scaling and heterogeneity of soil properties among others coming from complexity science. Multifractal formalism, first proposed by Mandelbrot (1982), is suitable for variables with self-similar distribution on a spatial domain (Kravchenko et al., 2002). Multifractal analysis can provide insight into spatial variability of crop or soil parameters (Vereecken et al., 2007). This technique has been used to characterize the scaling property of a variable measured along a transect as a mass distribution of a statistical measure on a spatial domain of the studied field (Zeleke and Si, 2004). To do this, it divides the transect into a number of self-similar segments. It identifies the differences among the subsets by using a wide range of statistical moments. Wavelets were developed in the 1980s for signal processing, and later introduced to soil science by Lark and Webster (1999). The wavelet transform decomposes a series; whether this be a time series (Whitcher, 1998; Percival and Walden, 2000), or as in our case a series of measurements made along a transect; into components (wavelet coefficients) which describe local variation in the series at different scale (or frequency) intervals, giving up only some resolution in space (Lark et al., 2003, 2004). Wavelet coefficients can be used to estimate scale specific components of variation and correlation. This allows us to see which scales contribute most to signal variation, or to see at which scales signals are most correlated. This can give us an insight into the dominant processes An alternative to both of the above methods has been described recently. Relative entropy and increments in relative entropy has been applied in soil images (Bird et al., 2006) and in soil transect data (Tarquis et al., 2008) to study scale effects localized in scale and provide the information that is complementary to the information about scale dependencies found across a range of scales. We will use them in this work to describe the spatial scaling properties of a set of field water content data measured in an extension of a corn field, in a plot of 500 m2 and an spatial resolution of 25 cm. These measurements are based on an optics cable (BruggSteal) buried on a ziz-zag deployment at 30cm depth. References Bird, N., M.C. Díaz, A. Saa, and A.M. Tarquis. 2006. A review of fractal and multifractal analysis of soil pore-scale images. J. Hydrol. 322:211-219. Kravchenko, A.N., R. Omonode, G.A. Bollero, and D.G. Bullock. 2002. Quantitative mapping of soil drainage classes using topographical data and soil electrical conductivity. Soil Sci. Soc. Am. J. 66:235-243. Lark, R.M., A.E. Milne, T.M. Addiscott, K.W.T. Goulding, C.P. Webster, and S. O'Flaherty. 2004. Scale- and location-dependent correlation of nitrous oxide emissions with soil properties: An analysis using wavelets. Eur. J. Soil Sci. 55:611-627. Lark, R.M., S.R. Kaffka, and D.L. Corwin. 2003. Multiresolution analysis of data on electrical conductivity of soil using wavelets. J. Hydrol. 272:276-290. Lark, R. M. and Webster, R. 1999. Analysis and elucidation of soil variation using wavelets. European J. of Soil Science, 50(2): 185-206. Mandelbrot, B.B. 1982. The fractal geometry of nature. W.H. Freeman, New York. Percival, D.B., and A.T. Walden. 2000. Wavelet methods for time series analysis. Cambridge Univ. Press, Cambridge, UK. Tarquis, A.M., N.R. Bird, A.P. Whitmore, M.C. Cartagena, and Y. Pachepsky. 2008. Multiscale analysis of soil transect data. Vadose Zone J. 7: 563-569. Vereecken, H., R. Kasteel, J. Vanderborght, and T. Harter. 2007. Upscaling hydraulic properties and soil water flow processes in heterogeneous soils: A review. Vadose Zone J. 6:1-28. Whitcher, B.J. 1998. Assessing nonstationary time series using wavelets. Ph.D. diss. Univ. of Washington, Seattle (Diss. Abstr. 9907961). Zeleke, T.B., and B.C. Si. 2004. Scaling properties of topographic indices and crop yield: Multifractal and joint multifractal approaches. Agron J., 96:1082-1090.