Molecular Dynamics/Order Parameter eXtrapolation (MD/OPX) for Bionanosystem Simulations
Miao, Yinglong; Ortoleva, Peter J.
2009-01-01
A multiscale approach, Molecular Dynamics/Order Parameter eXtrapolation (MD/OPX), to the all-atom simulation of large bionanosystems is presented. The approach starts with the introduction of a set of order parameters (OPs) automatically generated with orthogonal polynomials to characterize the nanoscale features of bionanosystems. The OPs are shown to evolve slowly via Newton’s equations and the all-atom multiscale analysis (AMA) developed earlier1 demonstrates the existence of their stochas...
Multiscale Signal Analysis and Modeling
Zayed, Ahmed
2013-01-01
Multiscale Signal Analysis and Modeling presents recent advances in multiscale analysis and modeling using wavelets and other systems. This book also presents applications in digital signal processing using sampling theory and techniques from various function spaces, filter design, feature extraction and classification, signal and image representation/transmission, coding, nonparametric statistical signal processing, and statistical learning theory. This book also: Discusses recently developed signal modeling techniques, such as the multiscale method for complex time series modeling, multiscale positive density estimations, Bayesian Shrinkage Strategies, and algorithms for data adaptive statistics Introduces new sampling algorithms for multidimensional signal processing Provides comprehensive coverage of wavelets with presentations on waveform design and modeling, wavelet analysis of ECG signals and wavelet filters Reviews features extraction and classification algorithms for multiscale signal and image proce...
Multiscale analysis of neural spike trains.
Ramezan, Reza; Marriott, Paul; Chenouri, Shojaeddin
2014-01-30
This paper studies the multiscale analysis of neural spike trains, through both graphical and Poisson process approaches. We introduce the interspike interval plot, which simultaneously visualizes characteristics of neural spiking activity at different time scales. Using an inhomogeneous Poisson process framework, we discuss multiscale estimates of the intensity functions of spike trains. We also introduce the windowing effect for two multiscale methods. Using quasi-likelihood, we develop bootstrap confidence intervals for the multiscale intensity function. We provide a cross-validation scheme, to choose the tuning parameters, and study its unbiasedness. Studying the relationship between the spike rate and the stimulus signal, we observe that adjusting for the first spike latency is important in cross-validation. We show, through examples, that the correlation between spike trains and spike count variability can be multiscale phenomena. Furthermore, we address the modeling of the periodicity of the spike trains caused by a stimulus signal or by brain rhythms. Within the multiscale framework, we introduce intensity functions for spike trains with multiplicative and additive periodic components. Analyzing a dataset from the retinogeniculate synapse, we compare the fit of these models with the Bayesian adaptive regression splines method and discuss the limitations of the methodology. Computational efficiency, which is usually a challenge in the analysis of spike trains, is one of the highlights of these new models. In an example, we show that the reconstruction quality of a complex intensity function demonstrates the ability of the multiscale methodology to crack the neural code. PMID:23996238
Numerical Analysis of Multiscale Computations
Engquist, Björn; Tsai, Yen-Hsi R
2012-01-01
This book is a snapshot of current research in multiscale modeling, computations and applications. It covers fundamental mathematical theory, numerical algorithms as well as practical computational advice for analysing single and multiphysics models containing a variety of scales in time and space. Complex fluids, porous media flow and oscillatory dynamical systems are treated in some extra depth, as well as tools like analytical and numerical homogenization, and fast multipole method.
[Multiscale entropy analysis of electrocardiogram].
Wang, Jun; Ning, Xinbao; Li, Jin; Ma, Qianli; Xu, Yinlin; Bian, Chunhua
2007-10-01
Using the algorithm proposed by Costa M, et al., we studied the multiscale entropy (MSE) of electrocardiogram. The sample entropy (SampEn) of the healthy subjects was found to be higher than that of the subjects with coronary heart disease or myocardial infarction. The healthy subjects' complexity was found to be the highest. The SampEn of the subjects with coronary heart disease was noted to be only slightly higher than that of the subjects with myocardial infarction. These findings show that the complexity of the subjects with coronary heart disease or myocardial infarction is distinctly lower than the complexity of the healthy ones, and the subjects suffereing from coronary heart disease are liable to the onset of myocardial infarction. PMID:18027679
Multiscale analysis and computation for flows in heterogeneous media
Energy Technology Data Exchange (ETDEWEB)
Efendiev, Yalchin [Texas A & M Univ., College Station, TX (United States); Hou, T. Y. [California Inst. of Technology (CalTech), Pasadena, CA (United States); Durlofsky, L. J. [Stanford Univ., CA (United States); Tchelepi, H. [Stanford Univ., CA (United States)
2016-08-04
Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scale basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics. Below, we present a brief overview of each of these contributions.
Multiscale Entropy Analysis on Human Operating Behavior
Junshan Pan; Hanping Hu; Xiang Liu; Yong Hu
2015-01-01
By exploiting the statistical analysis method, human dynamics provides new insights to the research of human behavior. In this paper, we analyze the characteristics of the computer operating behavior through a modified multiscale entropy algorithm with both the interval time series and the number series of individuals’ operating behavior been investigated. We also discuss the activity of individuals’ behavior from the three groups denoted as the retiree group, the student group and the worker...
Time Series Analysis Using Composite Multiscale Entropy
Directory of Open Access Journals (Sweden)
Kung-Yen Lee
2013-03-01
Full Text Available Multiscale entropy (MSE was recently developed to evaluate the complexity of time series over different time scales. Although the MSE algorithm has been successfully applied in a number of different fields, it encounters a problem in that the statistical reliability of the sample entropy (SampEn of a coarse-grained series is reduced as a time scale factor is increased. Therefore, in this paper, the concept of a composite multiscale entropy (CMSE is introduced to overcome this difficulty. Simulation results on both white noise and 1/f noise show that the CMSE provides higher entropy reliablity than the MSE approach for large time scale factors. On real data analysis, both the MSE and CMSE are applied to extract features from fault bearing vibration signals. Experimental results demonstrate that the proposed CMSE-based feature extractor provides higher separability than the MSE-based feature extractor.
Multivariate multiscale entropy for brain consciousness analysis.
Ahmed, Mosabber Uddin; Li, Ling; Cao, Jianting; Mandic, Danilo P
2011-01-01
The recently introduced multiscale entropy (MSE) method accounts for long range correlations over multiple time scales and can therefore reveal the complexity of biological signals. The existing MSE algorithm deals with scalar time series whereas multivariate time series are common in experimental and biological systems. To that cause, in this paper the MSE method is extended to the multivariate case. This allows us to gain a greater insight into the complexity of the underlying signal generating system, producing multifaceted and more robust estimates than standard single channel MSE. Simulations on both synthetic data and brain consciousness analysis support the approach. PMID:22254434
Multiscale entropy analysis of electroseismic time series
L. Guzmán-Vargas; Ramírez-Rojas, A.; Angulo-Brown, F.
2008-01-01
In this work we use the multiscale entropy method to analyse the variability of geo-electric time series monitored in two sites located in Mexico. In our analysis we consider a period of time from January 1995 to December 1995. We systematically calculate the sample entropy of electroseismic time series. Important differences in the entropy profile for several time scales are observed in records from the same station. In particular, a complex behaviour is observed in the vicinity of a
Multiscale statistical analysis of coronal solar activity
Gamborino, Diana; Martinell, Julio J
2016-01-01
Multi-filter images from the solar corona are used to obtain temperature maps which are analyzed using techniques based on proper orthogonal decomposition (POD) in order to extract dynamical and structural information at various scales. Exploring active regions before and after a solar flare and comparing them with quiet regions we show that the multiscale behavior presents distinct statistical properties for each case that can be used to characterize the level of activity in a region. Information about the nature of heat transport is also be extracted from the analysis.
The multiscale analysis between stock market time series
Shi, Wenbin; Shang, Pengjian
2015-11-01
This paper is devoted to multiscale cross-correlation analysis on stock market time series, where multiscale DCCA cross-correlation coefficient as well as multiscale cross-sample entropy (MSCE) is applied. Multiscale DCCA cross-correlation coefficient is a realization of DCCA cross-correlation coefficient on multiple scales. The results of this method present a good scaling characterization. More significantly, this method is able to group stock markets by areas. Compared to multiscale DCCA cross-correlation coefficient, MSCE presents a more remarkable scaling characterization and the value of each log return of financial time series decreases with the increasing of scale factor. But the results of grouping is not as good as multiscale DCCA cross-correlation coefficient.
Landform Mapping Using Multiscale Topographic Analysis
Bliss, N. B.
2008-12-01
Many ecological and agricultural processes depend on topographic relationships. Topography strongly influences microclimate, the types and productivity of plants, biomass, evapotranspiration rates, carbon storage rates, and fire fuel accumulation. These factors in turn influence the water cycle, stream flow, water quality, and soil formation. Most previous topographic analysis methods have focused on the elevation of a given grid cell (pixel) and very localized measures of slope and aspect (e.g., computed from elevation in a 3x3 window). Some measures have moved beyond a strictly local relationship, such as the compound topographic index, which can be used as a soil wetness index. I introduce a new method of multiscale topographic analysis which can be applied to digital elevation model (DEM) data of any resolution. The method calculates slope and curvature (change of slope) of the land not only in relation to adjacent grid cells but also for much larger distances downstream. The algorithm uses a flow direction grid to create a synthetic stream network as a set of connected line segments (a vector dataset). The multiscale measures are stored on a node attribute table, where the nodes are the endpoints of line segments connecting the original DEM grid cells. A pointer is computed for directly accessing data for nodes at selected distances down the stream network. Baseline distances are selected by counting cells down the flow path by each power of two (1, 2, 4, 8, ... cells downstream). Slope and curvature measures are defined for each of these baselines and are queried to distinguish multiscale topographic characteristics. Several applications of these methods have been tested. A floodplain measure identifies areas that are relatively low on the landscape, even as elevation changes while moving from plains into hills or mountains (study area: South Dakota). The landscape may be partitioned to provide zones for ecological analysis, including selection of field
Multiscale entropy analysis of biological signals.
Costa, Madalena; Goldberger, Ary L; Peng, C-K
2005-02-01
Traditional approaches to measuring the complexity of biological signals fail to account for the multiple time scales inherent in such time series. These algorithms have yielded contradictory findings when applied to real-world datasets obtained in health and disease states. We describe in detail the basis and implementation of the multiscale entropy (MSE) method. We extend and elaborate previous findings showing its applicability to the fluctuations of the human heartbeat under physiologic and pathologic conditions. The method consistently indicates a loss of complexity with aging, with an erratic cardiac arrhythmia (atrial fibrillation), and with a life-threatening syndrome (congestive heart failure). Further, these different conditions have distinct MSE curve profiles, suggesting diagnostic uses. The results support a general "complexity-loss" theory of aging and disease. We also apply the method to the analysis of coding and noncoding DNA sequences and find that the latter have higher multiscale entropy, consistent with the emerging view that so-called "junk DNA" sequences contain important biological information. PMID:15783351
Multiscale entropy analysis of electroseismic time series
Directory of Open Access Journals (Sweden)
L. Guzmán-Vargas
2008-08-01
Full Text Available In this work we use the multiscale entropy method to analyse the variability of geo-electric time series monitored in two sites located in Mexico. In our analysis we consider a period of time from January 1995 to December 1995. We systematically calculate the sample entropy of electroseismic time series. Important differences in the entropy profile for several time scales are observed in records from the same station. In particular, a complex behaviour is observed in the vicinity of a M=7.4 EQ occurred on 14 September 1995. Besides, we also compare the changes in the entropy of the original data with their corresponding shuffled version.
Multiscale Entropy Analysis on Human Operating Behavior
Directory of Open Access Journals (Sweden)
Junshan Pan
2015-12-01
Full Text Available By exploiting the statistical analysis method, human dynamics provides new insights to the research of human behavior. In this paper, we analyze the characteristics of the computer operating behavior through a modified multiscale entropy algorithm with both the interval time series and the number series of individuals’ operating behavior been investigated. We also discuss the activity of individuals’ behavior from the three groups denoted as the retiree group, the student group and the worker group based on the nature of their jobs. We find that the operating behavior of the retiree group exhibits more complex dynamics than the other two groups and further present a reasonable explanation for this phenomenon. Our findings offer new insights for the further understanding of individual behavior at different time scales.
Development of multiscale analysis and some applications
Wang, Lipo
2014-11-01
For most complex systems the interaction of different scales is among the most interesting and challenging features. Typically different scale regimes have different physical properties. The commonly used analysis approaches such as structure function and Fourier analysis have their respective limitations, for instance the mixing of large and small scale information, i.e. the so-called infrared and ultraviolet effects. To make improvement in this regard, a new method, segment structure analysis (SSA), has been developed to study the multiscale statistics. Such method can detect the regime scaling based on the conditional extremal points, depicting the geometrical features directly in physical space. From standard test cases (e.g. fractal Brownian motion) to real turbulence data, results show that SSA can appropriately distinguish the different scale effects. A successful application is the scaling of the Lagrangian velocity structure function. This long-time controversial topic has been confirmed using the present method. In principle SSA can generally be applied to various problems.
Multiscale Analysis of RMS Envelope Dynamics
Fedorova, A N; Fedorova, Antonina N.; Zeitlin, Michael G.
2000-01-01
We present applications of variational -- wavelet approach to different forms of nonlinear (rational) rms envelope equations. We have the representation for beam bunch oscillations as a multiresolution (multiscales) expansion in the base of compactly supported wavelet bases.
Multiscale Analysis of Heart Rate Dynamics: Entropy and Time Irreversibility Measures
Costa, Madalena D.; Peng, Chung-Kang; Ary L Goldberger
2008-01-01
Cardiovascular signals are largely analyzed using traditional time and frequency domain measures. However, such measures fail to account for important properties related to multiscale organization and nonequilibrium dynamics. The complementary role of conventional signal analysis methods and emerging multiscale techniques, is, therefore, an important frontier area of investigation. The key finding of this presentation is that two recently developed multiscale computational tools— multiscale e...
Time Series Analysis Using Composite Multiscale Entropy
Kung-Yen Lee; Chun-Chieh Wang; Shiou-Gwo Lin; Chiu-Wen Wu; Shuen-De Wu
2013-01-01
Multiscale entropy (MSE) was recently developed to evaluate the complexity of time series over different time scales. Although the MSE algorithm has been successfully applied in a number of different fields, it encounters a problem in that the statistical reliability of the sample entropy (SampEn) of a coarse-grained series is reduced as a time scale factor is increased. Therefore, in this paper, the concept of a composite multiscale entropy (CMSE) is introduced to overcome this difficulty. S...
Multiscale Methods for Nuclear Reactor Analysis
Collins, Benjamin S.
The ability to accurately predict local pin powers in nuclear reactors is necessary to understand the mechanisms that cause fuel pin failure during steady state and transient operation. In the research presented here, methods are developed to improve the local solution using high order methods with boundary conditions from a low order global solution. Several different core configurations were tested to determine the improvement in the local pin powers compared to the standard techniques, that use diffusion theory and pin power reconstruction (PPR). Two different multiscale methods were developed and analyzed; the post-refinement multiscale method and the embedded multiscale method. The post-refinement multiscale methods use the global solution to determine boundary conditions for the local solution. The local solution is solved using either a fixed boundary source or an albedo boundary condition; this solution is "post-refinement" and thus has no impact on the global solution. The embedded multiscale method allows the local solver to change the global solution to provide an improved global and local solution. The post-refinement multiscale method is assessed using three core designs. When the local solution has more energy groups, the fixed source method has some difficulties near the interface: however the albedo method works well for all cases. In order to remedy the issue with boundary condition errors for the fixed source method, a buffer region is used to act as a filter, which decreases the sensitivity of the solution to the boundary condition. Both the albedo and fixed source methods benefit from the use of a buffer region. Unlike the post-refinement method, the embedded multiscale method alters the global solution. The ability to change the global solution allows for refinement in areas where the errors in the few group nodal diffusion are typically large. The embedded method is shown to improve the global solution when it is applied to a MOX/LEU assembly
Multiscale Analysis and Optimisation of Photosynthetic Solar Energy Systems
Ringsmuth, Andrew K
2014-01-01
This work asks how light harvesting in photosynthetic systems can be optimised for economically scalable, sustainable energy production. Hierarchy theory is introduced as a system-analysis and optimisation tool better able to handle multiscale, multiprocess complexities in photosynthetic energetics compared with standard linear-process analysis. Within this framework, new insights are given into relationships between composition, structure and energetics at the scale of the thylakoid membrane, and also into how components at different scales cooperate under functional objectives of the whole photosynthetic system. Combining these reductionistic and holistic analyses creates a platform for modelling multiscale-optimal, idealised photosynthetic systems in silico.
Humeau, Anne; Mahé, Guillaume; Chapeau-Blondeau, François; Rousseau, David; Abraham, Pierre
2011-10-01
Processes regulating the cardiovascular system (CVS) are numerous. Each possesses several temporal scales. Their interactions lead to interdependences across multiple scales. For the CVS analysis, different multiscale studies have been proposed, mostly performed on heart rate variability signals (HRV) reflecting the central CVS; only few were dedicated to data from the peripheral CVS, such as laser Doppler flowmetry (LDF) signals. Very recently, a study implemented the first computation of multiscale entropy for LDF signals. A nonmonotonic evolution of multiscale entropy with two distinctive scales was reported, leading to a markedly different behavior from the one of HRV. Our goal herein is to confirm these results and to go forward in the investigations on origins of this behavior. For this purpose, 12 LDF signals recorded simultaneously on the two forearms of six healthy subjects are processed. This is performed before and after application of physiological scales-based filters aiming at isolating previously found frequency bands linked to physiological activities. The results obtained with signals recorded simultaneously on two different sites of each subject show a probable central origin for the nonmonotonic behavior. The filtering results lead to the suggestion that origins of the distinctive scales could be dominated by the cardiac activity. PMID:21712149
Multiscale Analysis of Information Dynamics for Linear Multivariate Processes
Faes, Luca; Stramaglia, Sebastiano; Nollo, Giandomenico; Stramaglia, Sebastiano
2016-01-01
In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving average (MA) component, we describe how to represent the resulting VARMA process using state-space (SS) models and how to exploit the SS model parameters to compute analytical measures of information storage and information transfer for the original and rescaled processes. The framework is then used to quantify multiscale infor...
Multiscale analysis of structure development in expanded starch snacks
Sman, van der R.G.M.; Broeze, J.
2014-01-01
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 mo
Accelerated Multiscale Analysis on the Earth's Surface
Gutting, Martin
2014-05-01
By the use of an underlying Runge sphere harmonic scaling functions and wavelets can be constructed on regular surfaces such as the surface of the Earth. They allow a space-frequency decomposition of geopotentials on the surface. Moreover, due to their localizing properties regional modeling or the improvement of a global model is possible. The acceleration of the convolution by the fast multipole method is possible for certain types of harmonic scaling functions and wavelets. The main idea of the fast multipole algorithm consists of a hierarchical decomposition of the computational domain into cubes and a kernel approximation for the more distant points. The kernel evaluation is performed directly only for points in neighboring cubes on the finest level. The contributions of the other points are transferred into a set of coefficients. The kernel approximation is applied on the coarsest possible level using translations of these coefficients. This reduces the numerical effort of the convolution for a prescribed accuracy of the kernel approximation. Multiscale methods are known to possess a tree algorithm that allows the computation of the lower frequency scales from a starting scale that contains the highest frequency parts of the signal. The application of the fast multipole method can accelerate the computation of this starting point as well as the tree algorithm itself. The presentation includes applications to gravitational field modeling.
Lifetime statistics of quantum chaos studied by a multiscale analysis
Di Falco, A.
2012-04-30
In a series of pump and probe experiments, we study the lifetime statistics of a quantum chaotic resonator when the number of open channels is greater than one. Our design embeds a stadium billiard into a two dimensional photonic crystal realized on a silicon-on-insulator substrate. We calculate resonances through a multiscale procedure that combines energy landscape analysis and wavelet transforms. Experimental data is found to follow the universal predictions arising from random matrix theory with an excellent level of agreement.
Complexity of carbon market from multi-scale entropy analysis
Fan, Xinghua; Li, Shasha; Tian, Lixin
2016-06-01
Complexity of carbon market is the consequence of economic dynamics and extreme social political events in global carbon markets. The multi-scale entropy can measure the long-term structures in the daily price return time series. By using multi-scale entropy analysis, we explore the complexity of carbon market and mean reversion trend of daily price return. The logarithmic difference of data Dec16 from August 6, 2010 to May 22, 2015 is selected as the sample. The entropy is higher in small time scale, while lower in large. The dependence of the entropy on the time scale reveals the mean reversion of carbon prices return in the long run. A relatively great fluctuation over some short time period indicates that the complexity of carbon market evolves consistently with economic development track and the events of international climate conferences.
Multiscale analysis of heart rate variability in nonstationary environments
Directory of Open Access Journals (Sweden)
Jianbo eGao
2013-05-01
Full Text Available Heart rate variability (HRV is highly nonstationary, even if no perturbing influences can be identified during the recording of the data. The nonstationarity becomes more profound when HRV data are measured in intrinsically nonstationary environments, such as social stress. In general, HRV data measured in such situations are more difficult to analyze than those measured in constant environments. In this paper, we analyze HRV data measured during a social stress test using two multiscale approaches, the adaptive fractal analysis (AFA and scale-dependent Lyapunov exponent (SDLE, for the purpose of uncovering differences in HRV between chronic fatigue syndrome (CFS patients and their matched-controls. CFS is a debilitating, heterogeneous illness with no known biomarker. HRV has shown some promise recently as a non-invasive measure of subtle physiological disturbances and trauma that are otherwise difficult to assess. If the HRV in persons with CFS are significantly different from their healthy controls, then certain cardiac irregularities may constitute good candidate biomarkers for CFS. Our multiscale analyses show that there are notable differences in HRV between CFS and their matched controls before a social stress test, but these differences seem to diminish during the test. These analyses illustrate that the two employed multiscale approaches could be useful for the analysis of HRV measured in various environments, both stationary and nonstationary.
Engineering Complex Systems: Multiscale Analysis and Evolutionary Engineering
Bar-Yam, Yaneer
We describe an analytic approach, multiscale analysis, that can demonstrate the fundamental limitations of decomposition based engineering for the development of highly complex systems. The interdependence of components and communication between design teams limits any planning based process. Recognizing this limitation, we found that a new strategy for constructing many highly complex systems should be modeled after biological evolution, or market economies, where multiple design efforts compete in parallel for adoption through testing in actual use. Evolution is the only process that is known to create highly complex systems.
Multiscale recurrence analysis of spatio-temporal data
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.
Romeny, Bart M Haar
2008-01-01
Front-End Vision and Multi-Scale Image Analysis is a tutorial in multi-scale methods for computer vision and image processing. It builds on the cross fertilization between human visual perception and multi-scale computer vision (`scale-space') theory and applications. The multi-scale strategies recognized in the first stages of the human visual system are carefully examined, and taken as inspiration for the many geometric methods discussed. All chapters are written in Mathematica, a spectacular high-level language for symbolic and numerical manipulations. The book presents a new and effective
Adaptive multiscale entropy analysis of multivariate neural data.
Hu, Meng; Liang, Hualou
2012-01-01
Multiscale entropy (MSE) has been widely used to quantify a system's complexity by taking into account the multiple time scales inherent in physiologic time series. The method, however, is biased toward the coarse scale, i.e., low-frequency components due to the progressive smoothing operations. In addition, the algorithm for extracting the different scales is not well adapted to nonlinear/nonstationary signals. In this letter, we introduce adaptive multiscale entropy (AME) measures in which the scales are adaptively derived directly from the data by virtue of recently developed multivariate empirical mode decomposition. Depending on the consecutive removal of low-frequency or high-frequency components, our AME can be estimated at either coarse-to-fine or fine-to-coarse scales over which the sample entropy is performed. Computer simulations are performed to verify the effectiveness of AME for analysis of the highly nonstationary data. Local field potentials collected from the visual cortex of macaque monkey while performing a generalized flash suppression task are used as an example to demonstrate the usefulness of our AME approach to reveal the underlying dynamics in complex neural data. PMID:21788182
Bednarcyk, Brett A.; Arnold, Steven M.
2012-01-01
A framework for the multiscale design and analysis of composite materials and structures is presented. The ImMAC software suite, developed at NASA Glenn Research Center, embeds efficient, nonlinear micromechanics capabilities within higher scale structural analysis methods such as finite element analysis. The result is an integrated, multiscale tool that relates global loading to the constituent scale, captures nonlinearities at this scale, and homogenizes local nonlinearities to predict their effects at the structural scale. Example applications of the multiscale framework are presented for the stochastic progressive failure of a SiC/Ti composite tensile specimen and the effects of microstructural variations on the nonlinear response of woven polymer matrix composites.
Multiscale Asymptotic Analysis and Parallel Algorithm of Parabolic Equation in Composite Materials
Directory of Open Access Journals (Sweden)
Xin Wang
2014-01-01
Full Text Available An efficient parallel multiscale numerical algorithm is proposed for a parabolic equation with rapidly oscillating coefficients representing heat conduction in composite material with periodic configuration. Instead of following the classical multiscale asymptotic expansion method, the Fourier transform in time is first applied to obtain a set of complex-valued elliptic problems in frequency domain. The multiscale asymptotic analysis is presented and multiscale asymptotic solutions are obtained in frequency domain which can be solved in parallel essentially without data communications. The inverse Fourier transform will then recover the approximate solution in time domain. Convergence result is established. Finally, a novel parallel multiscale FEM algorithm is proposed and some numerical examples are reported.
Jiang, Lijian
2010-08-01
In this paper, we discuss a numerical multiscale approach for solving wave equations with heterogeneous coefficients. Our interest comes from geophysics applications and we assume that there is no scale separation with respect to spatial variables. To obtain the solution of these multiscale problems on a coarse grid, we compute global fields such that the solution smoothly depends on these fields. We present a Galerkin multiscale finite element method using the global information and provide a convergence analysis when applied to solve the wave equations. We investigate the relation between the smoothness of the global fields and convergence rates of the global Galerkin multiscale finite element method for the wave equations. Numerical examples demonstrate that the use of global information renders better accuracy for wave equations with heterogeneous coefficients than the local multiscale finite element method. © 2010 IMACS.
Lin, Yen-Hung; Huang, Hui-Chun; Chang, Yi-Chung; Lin, Chen; Lo, Men-Tzung; Liu, Li-Yu Daisy; Tsai, Pi-Ru; Chen, Yih-Sharng; Ko, Wen-Je; Ho, Yi-Lwun; Chen, Ming-Fong; Peng, Chung-Kang; Buchman, Timothy G.
2014-01-01
Introduction: Extracorporeal life support (ECLS) can temporarily support cardiopulmonary function, and is occasionally used in resuscitation. Multi-scale entropy (MSE) derived from heart rate variability (HRV) is a powerful tool in outcome prediction of patients with cardiovascular diseases. Multi-scale symbolic entropy analysis (MSsE), a new method derived from MSE, mitigates the effect of arrhythmia on analysis. The objective is to evaluate the prognostic value of MSsE in patients receiving...
Lin, Yen-Hung; Huang, Hui-Chun; Chang, Yi-Chung; Lin, Chen; Lo, Men-Tzung; Liu, Li-Yu Daisy; Tsai, Pi-Ru; Chen, Yih-Sharng; Ko, Wen-Je; Ho, Yi-Lwun; Chen, Ming-Fong; Peng, Chung-Kang; Buchman, Timothy G.
2014-01-01
Introduction Extracorporeal life support (ECLS) can temporarily support cardiopulmonary function, and is occasionally used in resuscitation. Multi-scale entropy (MSE) derived from heart rate variability (HRV) is a powerful tool in outcome prediction of patients with cardiovascular diseases. Multi-scale symbolic entropy analysis (MSsE), a new method derived from MSE, mitigates the effect of arrhythmia on analysis. The objective is to evaluate the prognostic value of MSsE in patients receiving ...
Multivariate Multi-Scale Permutation Entropy for Complexity Analysis of Alzheimer’s Disease EEG
Isabella Palamara; Giuseppe Morabito; Alessia Bramanti; Fabio La Foresta; Domenico Labate; Francesco Carlo Morabito
2012-01-01
An original multivariate multi-scale methodology for assessing the complexity of physiological signals is proposed. The technique is able to incorporate the simultaneous analysis of multi-channel data as a unique block within a multi-scale framework. The basic complexity measure is done by using Permutation Entropy, a methodology for time series processing based on ordinal analysis. Permutation Entropy is conceptually simple, structurally robust to noise and artifacts, computationally very fa...
Multiscale entropy analysis of different spontaneous motor unit discharge patterns.
Zhang, Xu; Chen, Xiang; Barkhaus, Paul E; Zhou, Ping
2013-03-01
This study explores a novel application of multiscale entropy (MSE) analysis for characterizing different patterns of spontaneous electromyogram (EMG) signals including sporadic, tonic and repetitive spontaneous motor unit discharges, and normal surface EMG baseline. Two algorithms for MSE analysis, namely, the standard MSE and the intrinsic mode entropy (IMEn) (based on the recently developed multivariate empirical mode decomposition method), were applied to different patterns of spontaneous EMG. Significant differences were observed in multiple scales of the standard MSE and IMEn analyses (p <; 0.001) for any two of the spontaneous EMG patterns, while such significance may not be observed from the single-scale entropy analysis. Compared to the standard MSE, the IMEn analysis facilitates usage of a relatively low scale number to discern entropy difference among various patterns of spontaneous EMG signals. The findings from this study contribute to our understanding of the nonlinear dynamic properties of different spontaneous EMG patterns, which may be related to spinal motoneuron or motor unit health. PMID:24235117
Multi-Scale Analysis Based Curve Feature Extraction in Reverse Engineering
Institute of Scientific and Technical Information of China (English)
YANG Hongjuan; ZHOU Yiqi; CHEN Chengjun; ZHAO Zhengxu
2006-01-01
A sectional curve feature extraction algorithm based on multi-scale analysis is proposed for reverse engineering. The algorithm consists of two parts: feature segmentation and feature classification. In the first part, curvature scale space is applied to multi-scale analysis and original feature detection. To obtain the primary and secondary curve primitives, feature fusion is realized by multi-scale feature detection information transmission. In the second part: projection height function is presented based on the area of quadrilateral, which improved criterions of sectional curve feature classification. Results of synthetic curves and practical scanned sectional curves are given to illustrate the efficiency of the proposed algorithm on feature extraction. The consistence between feature extraction based on multi-scale curvature analysis and curve primitives is verified.
Analysis of complex time series using refined composite multiscale entropy
Energy Technology Data Exchange (ETDEWEB)
Wu, Shuen-De; Wu, Chiu-Wen [Department of Mechatronic Technology, National Taiwan Normal University, Taipei 10610, Taiwan (China); Lin, Shiou-Gwo [Department of Communications, Navigation and Control Engineering, National Taiwan Ocean University, Keelung 20224, Taiwan (China); Lee, Kung-Yen [Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei 10617, Taiwan (China); Peng, Chung-Kang [College of Health Sciences and Technology, National Central University, Chung-Li 32001, Taiwan (China); Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center/Harvard Medical School, Boston (United States)
2014-04-01
Multiscale entropy (MSE) is an effective algorithm for measuring the complexity of a time series that has been applied in many fields successfully. However, MSE may yield an inaccurate estimation of entropy or induce undefined entropy because the coarse-graining procedure reduces the length of a time series considerably at large scales. Composite multiscale entropy (CMSE) was recently proposed to improve the accuracy of MSE, but it does not resolve undefined entropy. Here we propose a refined composite multiscale entropy (RCMSE) to improve CMSE. For short time series analyses, we demonstrate that RCMSE increases the accuracy of entropy estimation and reduces the probability of inducing undefined entropy.
Ontology-based analysis of multi-scale modeling of geographical features
Institute of Scientific and Technical Information of China (English)
WANG Yanhui; LI Xiaojuan; GONG Huili
2006-01-01
As multi-scale databases based on scale series of map data are built, conceptual models are needed to define proper multi-scale representation formulas and to extract model entities and the relationships among them. However, the results of multi-scale conceptual abstraction schema may differ, according to which cognition, abstraction and application views are utilized, which presents an obvious obstacle to the reuse and sharing of spatial data. To facilitate the design of unified, common and objective abstract schema views for multi-scale spatial databases, this paper proposes an ontology-based analysis method for the multi-scale modeling of geographical features. It includes a three-layer ontology model, which serves as the framework for common multi-scale abstraction schema; an explanation of formulary abstractions accompanied by definitions of entities and their relationships at the same scale, as well as different scales,which are meant to provide strong feasibility, expansibility and speciality functions; and a case in point involving multi-scale representations of road features, to verify the method's feasibility.
Multi-scale analysis of lung computed tomography images
Gori, I.; Bagagli, F.; Fantacci, M. E.; Martinez, A. Preite; Retico, A.; De Mitri, I.; Donadio, S.; Fulcheri, C.; Gargano, G; Magro, R.; Santoro, M; Stumbo, S
2009-01-01
A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on...
Dynamical glucometry: use of multiscale entropy analysis in diabetes.
Costa, Madalena D; Henriques, Teresa; Munshi, Medha N; Segal, Alissa R; Goldberger, Ary L
2014-09-01
Diabetes mellitus (DM) is one of the world's most prevalent medical conditions. Contemporary management focuses on lowering mean blood glucose values toward a normal range, but largely ignores the dynamics of glucose fluctuations. We probed analyte time series obtained from continuous glucose monitor (CGM) sensors. We show that the fluctuations in CGM values sampled every 5 min are not uncorrelated noise. Next, using multiscale entropy analysis, we quantified the complexity of the temporal structure of the CGM time series from a group of elderly subjects with type 2 DM and age-matched controls. We further probed the structure of these CGM time series using detrended fluctuation analysis. Our findings indicate that the dynamics of glucose fluctuations from control subjects are more complex than those of subjects with type 2 DM over time scales ranging from about 5 min to 5 h. These findings support consideration of a new framework, dynamical glucometry, to guide mechanistic research and to help assess and compare therapeutic interventions, which should enhance complexity of glucose fluctuations and not just lower mean and variance of blood glucose levels. PMID:25273219
Escudero, Javier; Acar, Evrim; Fernandez, Alberto; Bro, Rasmus
2015-01-01
Tensor factorisations have proven useful to model amplitude and spectral information of brain recordings. Here, we assess the usefulness of tensor factorisations in the multiway analysis of other brain signal features in the context of complexity measures recently proposed to inspect multiscale dynamics. We consider the “refined composite multiscale entropy” (rcMSE), which computes entropy “profiles” showing levels of physiological complexity over temporal scales for individual signals. We co...
Multi-scale analysis for random quantum systems with interaction
Chulaevsky, Victor
2014-01-01
The study of quantum disorder has generated considerable research activity in mathematics and physics over past 40 years. While single-particle models have been extensively studied at a rigorous mathematical level, little was known about systems of several interacting particles, let alone systems with positive spatial particle density. Creating a consistent theory of disorder in multi-particle quantum systems is an important and challenging problem that largely remains open. Multi-scale Analysis for Random Quantum Systems with Interaction presents the progress that had been recently achieved in this area. The main focus of the book is on a rigorous derivation of the multi-particle localization in a strong random external potential field. To make the presentation accessible to a wider audience, the authors restrict attention to a relatively simple tight-binding Anderson model on a cubic lattice Zd. This book includes the following cutting-edge features: * an introduction to the state-of-the-art single-...
Design and Analysis of a Multiscale Active Queue Management Scheme
Institute of Scientific and Technical Information of China (English)
Qi-Jin Ji; Yong-Qiang Dong
2006-01-01
Since Internet is dominated by TCP-based applications, active queue management (AQM) is considered as an effective way for congestion control. However, most AQM schemes suffer obvious performance degradation with dynamic traffic. Extensive measurements found that Internet traffic is extremely bursty and possibly self-similar. We propose in this paper a new AQM scheme called multiscale controller (MSC) based on the understanding of traffic burstiness in multiple time scale. Different from most of other AQM schemes, MSC combines rate-based and queue-based control in two time scales. While the rate-based dropping on burst level (large time scales) determines the packet drop aggressiveness and is responsible for low and stable queuing delay, good robustness and responsiveness, the queue-based modulation of the packet drop probability on packet level (small time scales) will bring low loss and high throughput. Stability analysis is performed based on a fluid-flow model of the TCP/MSC congestion control system and simulation results show that MSC outperforms many of the current AQM schemes.
Multiscale Analysis of the Predictability of Stock Returns
Directory of Open Access Journals (Sweden)
Paweł Fiedor
2015-06-01
Full Text Available Due to the strong complexity of financial markets, economics does not have a unified theory of price formation in financial markets. The most common assumption is the Efficient-Market Hypothesis, which has been attacked by a number of researchers, using different tools. There were varying degrees to which these tools complied with the formal definitions of efficiency and predictability. In our earlier work, we analysed the predictability of stock returns at two time scales using the entropy rate, which can be directly linked to the mathematical definition of predictability. Nonetheless, none of the above-mentioned studies allow any general understanding of how the financial markets work, beyond disproving the Efficient-Market Hypothesis. In our previous study, we proposed the Maximum Entropy Production Principle, which uses the entropy rate to create a general principle underlying the price formation processes. Both of these studies show that the predictability of price changes is higher at the transaction level intraday scale than the scale of daily returns, but ignore all scales in between. In this study we extend these ideas using the multiscale entropy analysis framework to enhance our understanding of the predictability of price formation processes at various time scales.
Magnetospheric Multiscale (MMS) Mission Commissioning Phase Orbit Determination Error Analysis
Chung, Lauren R.; Novak, Stefan; Long, Anne; Gramling, Cheryl
2009-01-01
The Magnetospheric MultiScale (MMS) mission commissioning phase starts in a 185 km altitude x 12 Earth radii (RE) injection orbit and lasts until the Phase 1 mission orbits and orientation to the Earth-Sun li ne are achieved. During a limited time period in the early part of co mmissioning, five maneuvers are performed to raise the perigee radius to 1.2 R E, with a maneuver every other apogee. The current baseline is for the Goddard Space Flight Center Flight Dynamics Facility to p rovide MMS orbit determination support during the early commissioning phase using all available two-way range and Doppler tracking from bo th the Deep Space Network and Space Network. This paper summarizes th e results from a linear covariance analysis to determine the type and amount of tracking data required to accurately estimate the spacecraf t state, plan each perigee raising maneuver, and support thruster cal ibration during this phase. The primary focus of this study is the na vigation accuracy required to plan the first and the final perigee ra ising maneuvers. Absolute and relative position and velocity error hi stories are generated for all cases and summarized in terms of the ma ximum root-sum-square consider and measurement noise error contributi ons over the definitive and predictive arcs and at discrete times inc luding the maneuver planning and execution times. Details of the meth odology, orbital characteristics, maneuver timeline, error models, and error sensitivities are provided.
Multiscale Analysis of the Gradient of Linear Polarisation
Robitaille, J -F
2015-01-01
We propose a new multiscale method to calculate the amplitude of the gradient of the linear polarisation vector using a wavelet-based formalism. We demonstrate this method using a field of the Canadian Galactic Plane Survey (CGPS) and show that the filamentary structure typically seen in gradients of linear polarisation maps depends strongly on the instrumental resolution. Our analysis reveals that different networks of filaments are present on different angular scales. The wavelet formalism allows us to calculate the power spectrum of the fluctuations seen in gradients of linear polarisation maps and to determine the scaling behaviour of this quantity. The power spectrum is found to follow a power law with gamma ~ 2.1. We identify a small drop in power between scales of 80 < l < 300 arcmin, which corresponds well to the overlap in the u-v plane between the Effelsberg 100-m telescope and the DRAO 26-m telescope data. We suggest that this drop is due to undersampling present in the 26-m telescope data. I...
Analysis of electroencephalograms in Alzheimer's disease patients with multiscale entropy.
Escudero, J; Abásolo, D; Hornero, R; Espino, P; López, M
2006-11-01
The aim of this study was to analyse the electroencephalogram (EEG) background activity of Alzheimer's disease (AD) patients using multiscale entropy (MSE). MSE is a recently developed method that quantifies the regularity of a signal on different time scales. These time scales are inspected by means of several coarse-grained sequences formed from the analysed signals. We recorded the EEGs from 19 scalp electrodes in 11 AD patients and 11 age-matched controls and estimated the MSE profile for each epoch of the EEG recordings. The shape of the MSE profiles reveals the EEG complexity, and it suggests that the EEG contains information in deeper scales than the smallest one. Moreover, the results showed that the EEG background activity is less complex in AD patients than control subjects. We found significant differences between both subject groups at electrodes F3, F7, Fp1, Fp2, T5, T6, P3, P4, O1 and O2 (p-value < 0.01, Student's t-test). These findings indicate that the EEG complexity analysis performed on deeper time scales by MSE may be a useful tool in order to increase our knowledge of AD. PMID:17028404
Multiscale Analysis of Spreading in a Large Communication Network
Kivelä, Mikko; Kaski, Kimmo; Kertész, János; Saramäki, Jari; Karsai, Márton
2011-01-01
In temporal networks, both the topology of the underlying network and the timings of interaction events can be crucial in determining how some dynamic process mediated by the network unfolds. We have explored the limiting case of the speed of spreading in the SI model, set up such that an event between an infectious and susceptible individual always transmits the infection. The speed of this process sets an upper bound for the speed of any dynamic process that is mediated through the interaction events of the network. With the help of temporal networks derived from large scale time-stamped data on mobile phone calls, we extend earlier results that point out the slowing-down effects of burstiness and temporal inhomogeneities. In such networks, links are not permanently active, but dynamic processes are mediated by recurrent events taking place on the links at specific points in time. We perform a multi-scale analysis and pinpoint the importance of the timings of event sequences on individual links, their corre...
Multi-scale analysis of lung computed tomography images
Gori, I; Fantacci, M E; Martinez, A Preite; Retico, A; De Mitri, I; Donadio, S; Fulcheri, C; Gargano, G; Magro, R; Santoro, M; Stumbo, S; 10.1088/1748-0221/2/09/P09007
2009-01-01
A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on a dataset of low-dose and thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.
Multi-scale analysis of lung computed tomography images
Gori, I; Fantacci, M E; Preite Martinez, A; Retico, A; De Mitri, I; Donadio, S; Fulcheri, C
2007-01-01
A computer-aided detection (CAD) system for the identification of lung internal nodules in low-dose multi-detector helical Computed Tomography (CT) images was developed in the framework of the MAGIC-5 project. The three modules of our lung CAD system, a segmentation algorithm for lung internal region identification, a multi-scale dot-enhancement filter for nodule candidate selection and a multi-scale neural technique for false positive finding reduction, are described. The results obtained on a dataset of low-dose and thin-slice CT scans are shown in terms of free response receiver operating characteristic (FROC) curves and discussed.
Directory of Open Access Journals (Sweden)
Zhang Xiao-Ping
2006-01-01
Full Text Available Video content analysis is essential for efficient and intelligent utilizations of vast multimedia databases over the Internet. In video sequences, object-based extraction techniques are important for content-based video processing in many applications. In this paper, a novel technique is developed to extract objects from video sequences based on spatiotemporal independent component analysis (stICA and multiscale analysis. The stICA is used to extract the preliminary source images containing moving objects in video sequences. The source image data obtained after stICA analysis are further processed using wavelet-based multiscale image segmentation and region detection techniques to improve the accuracy of the extracted object. An automated video object extraction system is developed based on these new techniques. Preliminary results demonstrate great potential for the new stICA and multiscale-segmentation-based object extraction system in content-based video processing applications.
The set of prime numbers: Multifractals and multiscale analysis
International Nuclear Information System (INIS)
In this work we show that the prime numbers can be seen as the sides or angles of a multifractal polygon based on a hexagon. This also means that primes follow a multiscale distribution and can be generated in a beautiful deterministic fashion.
Implementation of Grid-computing Framework for Simulation in Multi-scale Structural Analysis
Directory of Open Access Journals (Sweden)
Data Iranata
2010-05-01
Full Text Available A new grid-computing framework for simulation in multi-scale structural analysis is presented. Two levels of parallel processing will be involved in this framework: multiple local distributed computing environments connected by local network to form a grid-based cluster-to-cluster distributed computing environment. To successfully perform the simulation, a large-scale structural system task is decomposed into the simulations of a simplified global model and several detailed component models using various scales. These correlated multi-scale structural system tasks are distributed among clusters and connected together in a multi-level hierarchy and then coordinated over the internet. The software framework for supporting the multi-scale structural simulation approach is also presented. The program architecture design allows the integration of several multi-scale models as clients and servers under a single platform. To check its feasibility, a prototype software system has been designed and implemented to perform the proposed concept. The simulation results show that the software framework can increase the speedup performance of the structural analysis. Based on this result, the proposed grid-computing framework is suitable to perform the simulation of the multi-scale structural analysis.
A New Method for Pitch Tracking and Voicing Decision Based on Spectral Multi-Scale Analysis
Directory of Open Access Journals (Sweden)
Aicha Bouzid
2009-11-01
Full Text Available This paper proposes a new voicing detection and pitch estimation method that is particularly robust for noisy speech. This method is based on the spectral analysis of the speech multi-scale product. The multi-scale product (MP consists of making the product of wavelet transform coefficients. The wavelet used is the quadratic spline function. We argue that the spectral of Multi-scale Product Analysis is capable of revealing an estimate of a pitch-harmonic more accurately even in a heavy noisy scenario. We evaluate our approach on the Keele database. The experimental results show the robustness of our method for noisy speech, and the good performance for clean speech in comparison with state-of-the-art algorithms.
Analysis of electroencephalograms in Alzheimer's disease patients with multiscale entropy
Escudero, J; Abasolo, D; Hornero, R.; Espino, P; M. Lopez
2006-01-01
The aim of this study was to analyse the electroencephalogram ( EEG) background activity of Alzheimer's disease ( AD) patients using multiscale entropy (MSE). MSE is a recently developed method that quantifies the regularity of a signal on different time scales. These time scales are inspected by means of several coarse-grained sequences formed from the analysed signals. We recorded the EEGs from 19 scalp electrodes in 11 AD patients and 11 age-matched controls and estimated the MSE profile f...
Creep behavior multi-scale analysis of zirconium alloys
International Nuclear Information System (INIS)
Zirconium alloys are used in the nuclear industry as fuel cladding tubes in order to prevent radionuclide leaks into primary loop. They are also used to ensure an efficient heat transfer between nuclear fuel and primary water. Under operating conditions, these alloys are subjected to intense thermal-mechanical and neutronic solicitations. The mechanical wear of fuel rods is a key element in nuclear reactor safety. During this work, TEM investigations have been carried out by coworkers in order to quantify driving plasticity mechanisms in investigated stress and temperature range. The main result of this study is that the prismatic glide of screw dislocations remains the main plasticity mechanism. It is frequently associated with a cross slip mechanism on pyramidal planes. These experimental observations have been implemented into a multi-scale approach, thus providing a better description of the phenomenon. The results of a characterization campaign of the multiaxial creep behavior at 400 C of recrystallised Zircaloy-4 are used in this work and a micromechanical interpretation is proposed. The Elasto-Visco-Plastic (EVP) behavior is also characterized with relaxation tests between 280 C and 43 C. Analysis of experimental results indicates macroscopic effects of dynamic strain ageing. At the same time, Finite Element computations on polycrystalline aggregates were undertaken and a procedure for the statistical estimation of intra-phase mean mechanical fields is proposed. For a sufficient number of statistical realizations, it is shown that this estimator allows the precise determination of the analytical solution provided by the self consistent model within the framework of anisotropic elasticity. Thus, this procedure was applied to an EVP medium. It seems that rule allow a good description of numerical observations. However, EVP flow of quasi-elastic crystallographic phases remains difficult to describe. The aim of this PhD is to develop models of EVP behavior of
Energy Technology Data Exchange (ETDEWEB)
Donald Estep; Michael Holst; Simon Tavener
2010-02-08
This project was concerned with the accurate computational error estimation for numerical solutions of multiphysics, multiscale systems that couple different physical processes acting across a large range of scales relevant to the interests of the DOE. Multiscale, multiphysics models are characterized by intimate interactions between different physics across a wide range of scales. This poses significant computational challenges addressed by the proposal, including: (1) Accurate and efficient computation; (2) Complex stability; and (3) Linking different physics. The research in this project focused on Multiscale Operator Decomposition methods for solving multiphysics problems. The general approach is to decompose a multiphysics problem into components involving simpler physics over a relatively limited range of scales, and then to seek the solution of the entire system through some sort of iterative procedure involving solutions of the individual components. MOD is a very widely used technique for solving multiphysics, multiscale problems; it is heavily used throughout the DOE computational landscape. This project made a major advance in the analysis of the solution of multiscale, multiphysics problems.
Filter-based multiscale entropy analysis of complex physiological time series.
Xu, Yuesheng; Zhao, Liang
2013-08-01
Multiscale entropy (MSE) has been widely and successfully used in analyzing the complexity of physiological time series. We reinterpret the averaging process in MSE as filtering a time series by a filter of a piecewise constant type. From this viewpoint, we introduce filter-based multiscale entropy (FME), which filters a time series to generate multiple frequency components, and then we compute the blockwise entropy of the resulting components. By choosing filters adapted to the feature of a given time series, FME is able to better capture its multiscale information and to provide more flexibility for studying its complexity. Motivated by the heart rate turbulence theory, which suggests that the human heartbeat interval time series can be described in piecewise linear patterns, we propose piecewise linear filter multiscale entropy (PLFME) for the complexity analysis of the time series. Numerical results from PLFME are more robust to data of various lengths than those from MSE. The numerical performance of the adaptive piecewise constant filter multiscale entropy without prior information is comparable to that of PLFME, whose design takes prior information into account. PMID:24032873
Multiscale and cross entropy analysis of auroral and polar cap indices during geomagnetic storms
Gopinath, Sumesh; Prince, P. R.
2016-01-01
In order to improve general monoscale information entropy methods like permutation and sample entropy in characterizing the irregularity of complex magnetospheric system, it is necessary to extend these entropy metrics to a multiscale paradigm. We propose novel multiscale and cross entropy method for the analysis of magnetospheric proxies such as auroral and polar cap indices during geomagnetic disturbance times. Such modified entropy metrics are certainly advantageous in classifying subsystems such as individual contributions of auroral electrojets and field aligned currents to high latitude magnetic perturbations during magnetic storm and polar substorm periods. We show that the multiscale entropy/cross entropy of geomagnetic indices vary with scale factor. These variations can be attributed to changes in multiscale dynamical complexity of non-equilibrium states present in the magnetospheric system. These types of features arise due to imbalance in injection and dissipation rates of energy with variations in magnetospheric response to solar wind. We also show that the multiscale entropy values of time series decrease during geomagnetic storm times which reveals an increase in temporal correlations as the system gradually shifts to a more orderly state. Such variations in entropy values can be interpreted as the signature of dynamical phase transitions which arise at the periods of geomagnetic storms and substorms that confirms several previously found results regarding emergence of cooperative dynamics, self-organization and non-Markovian nature of magnetosphere during disturbed periods.
Multi-Scale Scratch Analysis in Qinghai-Tibet Plateau and its Geological Implications
Sun, Yanyun; Yang, Wencai; Yu, Changqing
2016-04-01
Multi-scale scratch analysis on a regional gravity field is a new data processing system for depicting three-dimensional density structures and tectonic features. It comprises four modules including the spectral analysis of potential fields, multi-scale wavelet analysis, density distribution inversion, and scratch analysis. The multi-scale scratch analysis method was applied to regional gravity data to extract information about the deformation belts in the Qinghai-Tibet Plateau, which can help reveal variations of the deformation belts and plane distribution features from the upper crust to the lower crust, provide evidence for the study of three-dimensional crustal structures, and define distribution of deformation belts and mass movement. Results show the variation of deformation belts from the upper crust to the lower crust. The deformation belts vary from dense and thin in the upper crust to coarse and thick in the lower crust, demonstrating that vertical distribution of deformation belts resembles a tree with a coarse and thick trunk in the lower part and dense and thin branches at the top. The dense and thin deformation areas in the upper crust correspond to crustal shortening areas, while the thick and continuous deformation belts in the lower crust indicate the structural framework of the plateau. Additionally, the lower crustal deformation belts recognized by the multi-scale scratch analysis coincide approximately with the crustal deformation belts recognized using single-scale scratch analysis. However, deformation belts recognized by the latter are somewhat rough while multi-scale scratch analysis can provide more detailed and accurate results.
Analysis of the Spatial Distribution of Galaxies by Multiscale Methods
Directory of Open Access Journals (Sweden)
E. Saar
2005-09-01
Full Text Available Galaxies are arranged in interconnected walls and filaments forming a cosmic web encompassing huge, nearly empty, regions between the structures. Many statistical methods have been proposed in the past in order to describe the galaxy distribution and discriminate the different cosmological models. We present in this paper multiscale geometric transforms sensitive to clusters, sheets, and walls: the 3D isotropic undecimated wavelet transform, the 3D ridgelet transform, and the 3D beamlet transform. We show that statistical properties of transform coefficients measure in a coherent and statistically reliable way, the degree of clustering, filamentarity, sheetedness, and voidedness of a data set.
The set of prime numbers: Multiscale analysis and numeric accelerators
International Nuclear Information System (INIS)
In this work, we show that the prime numbers follow a multiscale distribution. Indeed they can be classified thanks to tree structures, which are expressed in terms of two maximal subsets of N and using multilayer selection rules, acting on these sets of prime candidates. Consequently, the prime numbers follow a specific deterministic rules. Indeed, a numeric accelerator for generating primes can be realized in terms of the above mentioned specific rules. From the comparison with the Fibonacci numbers a beautiful harmony comes in terms of the Golden Mean which is relevant to high energy physics and E-Infinity theory too.
Multiscale entropy analysis of complex physiologic time series.
Costa, Madalena; Goldberger, Ary L; Peng, C-K
2002-08-01
There has been considerable interest in quantifying the complexity of physiologic time series, such as heart rate. However, traditional algorithms indicate higher complexity for certain pathologic processes associated with random outputs than for healthy dynamics exhibiting long-range correlations. This paradox may be due to the fact that conventional algorithms fail to account for the multiple time scales inherent in healthy physiologic dynamics. We introduce a method to calculate multiscale entropy (MSE) for complex time series. We find that MSE robustly separates healthy and pathologic groups and consistently yields higher values for simulated long-range correlated noise compared to uncorrelated noise. PMID:12190613
Strain analysis of nanowire interfaces in multiscale composites
Malakooti, Mohammad H.; Zhou, Zhi; Spears, John H.; Shankwitz, Timothy J.; Sodano, Henry A.
2016-04-01
Recently, the reinforcement-matrix interface of fiber reinforced polymers has been modified through grafting nanostructures - particularly carbon nanotubes and ZnO nanowires - on to the fiber surface. This type of interface engineering has made a great impact on the development of multiscale composites that have high stiffness, interfacial strength, toughness, and vibrational damping - qualities that are mutually exclusive to a degree in most raw materials. Although the efficacy of such nanostructured interfaces has been established, the reinforcement mechanisms of these multiscale composites have not been explored. Here, strain transfer across a nanowire interphase is studied in order to gain a heightened understanding of the working principles of physical interface modification and the formation of a functional gradient. This problem is studied using a functionally graded piezoelectric interface composed of vertically aligned lead zirconate titanate nanowires, as their piezoelectric properties can be utilized to precisely control the strain on one side of the interface. The displacement and strain across the nanowire interface is captured using digital image correlation. It is demonstrated that the material gradient created through nanowires cause a smooth strain transfer from reinforcement phase into matrix phase that eliminates the stress concentration between these phases, which have highly mismatched elasticity.
Timeline analysis and wavelet multiscale analysis of the AKARI All-Sky Survey at 90 micron
Wang, Lingyu; Yamamura, Issei; Shibai, Hiroshi; Savage, Rich; Oliver, Seb; Thomson, Matthew; Rahman, Nurur; Clements, Dave; Figueredo, Elysandra; Goto, Tomotsugu; Hasegawa, Sunao; Jeong, Woong-Seob; Matsuura, Shuji; Muller, Thomas G; Nakagawa, Takao; Pearson, Chris P; Serjeant, Stephen; Shirahata, Mai; White, Glenn J
2008-01-01
We present a careful analysis of the point source detection limit of the AKARI All-Sky Survey in the WIDE-S 90 $\\mu$m band near the North Ecliptic Pole (NEP). Timeline Analysis is used to detect IRAS sources and then a conversion factor is derived to transform the peak timeline signal to the interpolated 90 $\\mu$m flux of a source. Combined with a robust noise measurement, the point source flux detection limit at S/N $>5$ for a single detector row is $1.1\\pm0.1$ Jy which corresponds to a point source detection limit of the survey of $\\sim$0.4 Jy. Wavelet transform offers a multiscale representation of the Time Series Data (TSD). We calculate the continuous wavelet transform of the TSD and then search for significant wavelet coefficients considered as potential source detections. To discriminate real sources from spurious or moving objects, only sources with confirmation are selected. In our multiscale analysis, IRAS sources selected above $4\\sigma$ can be identified as the only real sources at the Point Sourc...
Quantitative Multiscale Analysis using Different Wavelets in 1D Voice Signal and 2D Image
Shakhakarmi, Niraj
2012-01-01
Mutiscale analysis represents multiresolution scrutiny of a signal to improve its signal quality. Multiresolution analysis of 1D voice signal and 2D image is conducted using DCT, FFT and different wavelets such as Haar, Deubachies, Morlet, Cauchy, Shannon, Biorthogonal, Symmlet and Coiflet deploying the cascaded filter banks based decomposition and reconstruction. The outstanding quantitative analysis of the specified wavelets is done to investigate the signal quality, mean square error, entropy and peak-to-peak SNR at multiscale stage-4 for both 1D voice signal and 2D image. In addition, the 2D image compression performance is significantly found 93.00% in DB-4, 93.68% in bior-4.4, 93.18% in Sym-4 and 92.20% in Coif-2 during the multiscale analysis.
Multiscale Topographical Analysis of Biogeochemically Reduced Hematite Surfaces
Rustad, J.; Rosso, K. M.; Dubuffet, F.; Yuen, D. A.
2001-12-01
Establishing the mechanisms and magnitudes of nano-mesoscale influences on interfacial chemical reactivity requires a multiscale description of the structure of the interfacial region. The identification of scaling relationships characterizing mineral surface structure in low-temperature environments is a first step in the construction structure-activity relationships that are potentially applicable over multiple length scales. Using wavelet image processing techniques and scaling relationships such as the evaluation of Hurst exponents and fractal dimension, we systematize and quantify mineral surface topography of a sample of hematite undergoing biochemically induced reductive dissolution. Image mosaicking methods commonly applied in remote sensing and medical imaging contexts are applied to AFM images to obtain large scale images for the evalution of scaling exponents. Gaussian wavelet methods are used to enhance and quantify structural features associated with the biogeochemically reduced surfaces.
Multiscale analysis of heavy metal contents in Spanish agricultural topsoils.
Rodríguez, José Antonio; Nanos, Nikos; Grau, José Manuel; Gil, Luis; López-Arias, Manuel
2008-01-01
This study characterized and mapped the spatial variability patterns of seven topsoil heavy metals (Cr, Ni, Pb, Cu, Zn, Hg and Cd) within the Ebro river basin (9.3 million ha) by Multivariate Factorial Kriging. The variograms and cross-variograms of heavy metal concentrations showed the presence of multiscale variation that was modeled using three variogram models with ranges of 20km (short-range), 100km (medium-range) and 225km (long-range). Our results indicate that the heavy metal concentration is influenced by bedrock composition and dynamics at all the spatial scales, while human activities have a notorious effect only at the short- and medium-range scale of variation. Sources of Cu, Pb and Zn (and secondary Cd) are associated with agricultural practices (at the short-range scale of variation), whereas Hg variation at the short- and medium-range scale of variation is related to atmospheric deposition. PMID:17904195
Framework for adaptive multiscale analysis of nonhomogeneous point processes.
Helgason, Hannes; Bartroff, Jay; Abry, Patrice
2011-01-01
We develop the methodology for hypothesis testing and model selection in nonhomogeneous Poisson processes, with an eye toward the application of modeling and variability detection in heart beat data. Modeling the process' non-constant rate function using templates of simple basis functions, we develop the generalized likelihood ratio statistic for a given template and a multiple testing scheme to model-select from a family of templates. A dynamic programming algorithm inspired by network flows is used to compute the maximum likelihood template in a multiscale manner. In a numerical example, the proposed procedure is nearly as powerful as the super-optimal procedures that know the true template size and true partition, respectively. Extensions to general history-dependent point processes is discussed.
Traffic time series analysis by using multiscale time irreversibility and entropy
Wang, Xuejiao; Shang, Pengjian; Fang, Jintang
2014-09-01
Traffic systems, especially urban traffic systems, are regulated by different kinds of interacting mechanisms which operate across multiple spatial and temporal scales. Traditional approaches fail to account for the multiple time scales inherent in time series, such as empirical probability distribution function and detrended fluctuation analysis, which have lead to different results. The role of multiscale analytical method in traffic time series is a frontier area of investigation. In this paper, our main purpose is to introduce a new method—multiscale time irreversibility, which is helpful to extract information from traffic time series we studied. In addition, to analyse the complexity of traffic volume time series of Beijing Ring 2, 3, 4 roads between workdays and weekends, which are from August 18, 2012 to October 26, 2012, we also compare the results by this new method and multiscale entropy method we have known well. The results show that the higher asymmetry index we get, the higher traffic congestion level will be, and accord with those which are obtained by multiscale entropy.
Directory of Open Access Journals (Sweden)
Madalena D. Costa
2015-03-01
Full Text Available We introduce a generalization of multiscale entropy (MSE analysis. The method is termed MSEn, where the subscript denotes the moment used to coarse-grain a time series. MSEμ, described previously, uses the mean value (first moment. Here, we focus on MSEσ2 , which uses the second moment, i.e., the variance. MSEσ2 quantifies the dynamics of the volatility (variance of a signal over multiple time scales. We use the method to analyze the structure of heartbeat time series. We find that the dynamics of the volatility of heartbeat time series obtained from healthy young subjects is highly complex. Furthermore, we find that the multiscale complexity of the volatility, not only the multiscale complexity of the mean heart rate, degrades with aging and pathology. The “bursty” behavior of the dynamics may be related to intermittency in energy and information flows, as part of multiscale cycles of activation and recovery. Generalized MSE may also be useful in quantifying the dynamical properties of other physiologic and of non-physiologic time series.
ANALYSIS/MODEL COVER SHEET, MULTISCALE THERMOHYDROLOGIC MODEL
International Nuclear Information System (INIS)
The purpose of the Multiscale Thermohydrologic Model (MSTHM) is to describe the thermohydrologic evolution of the near-field environment (NFE) and engineered barrier system (EBS) throughout the potential high-level nuclear waste repository at Yucca Mountain for a particular engineering design (CRWMS M andO 2000c). The process-level model will provide thermohydrologic (TH) information and data (such as in-drift temperature, relative humidity, liquid saturation, etc.) for use in other technical products. This data is provided throughout the entire repository area as a function of time. The MSTHM couples the Smeared-heat-source Drift-scale Thermal-conduction (SDT), Line-average-heat-source Drift-scale Thermohydrologic (LDTH), Discrete-heat-source Drift-scale Thermal-conduction (DDT), and Smeared-heat-source Mountain-scale Thermal-conduction (SMT) submodels such that the flow of water and water vapor through partially-saturated fractured rock is considered. The MSTHM accounts for 3-D drift-scale and mountain-scale heat flow, repository-scale variability of stratigraphy and infiltration flux, and waste package (WP)-to-WP variability in heat output from WPs. All submodels use the nonisothermal unsaturated-saturated flow and transport (NUFT) simulation code. The MSTHM is implemented in several data-processing steps. The four major steps are: (1) submodel input-file preparation, (2) execution of the four submodel families with the use of the NUFT code, (3) execution of the multiscale thermohydrologic abstraction code (MSTHAC), and (4) binning and post-processing (i.e., graphics preparation) of the output from MSTHAC. Section 6 describes the MSTHM in detail. The objectives of this Analyses and Model Report (AMR) are to investigate near field (NF) and EBS thermohydrologic environments throughout the repository area at various evolution periods, and to provide TH data that may be used in other process model reports
Applying Multiscale Entropy to the Complexity Analysis of Rainfall-Runoff Relationships
Chien-Ming Chou
2012-01-01
This paper presents a novel framework for the complexity analysis of rainfall, runoff, and runoff coefficient (RC) time series using multiscale entropy (MSE). The MSE analysis of RC time series was used to investigate changes in the complexity of rainfall-runoff processes due to human activities. Firstly, a coarse graining process was applied to a time series. The sample entropy was then computed for each coarse-grained time series, and plotted as a function of the scale factor. The proposed ...
Escudero, J; Abasolo, D; Hornero, R.; Espino, P; M. Lopez
2007-01-01
We appreciate the interest of Dr Tang in our article. Certainly, our previous results should be taken with caution due to the small database size. Nevertheless, it must be noted that this limitation was clearly recognized in our article. Furthermore, our hypothesis is completely justified from the current state of the art in the analysis of electroencephalogram (EEG) signals from Alzheimer's disease (AD) patients. We evaluated whether the multiscale entropy (MSE) analysis of the EEG backgroun...
Takahashi, Tetsuya; Cho, Raymond Y; Mizuno, Tomoyuki; Kikuchi, Mitsuru; Murata, Tetsuhito; Takahashi, Koichi; Wada, Yuji
2010-01-01
Multiscale entropy (MSE) analysis is a novel entropy-based approach for measuring dynamical complexity in physiological systems over a range of temporal scales. To evaluate this analytic approach as an aid to elucidating the pathophysiologic mechanisms in schizophrenia, we examined MSE in EEG activity in drug-naïve schizophrenia subjects pre- and post-treatment with antipsychotics in comparison with traditional EEG analysis. We recorded eyes-closed resting state EEG from frontal, temporal, pa...
Multi-Scale Entropy Analysis of Different Spontaneous Motor Unit Discharge Patterns
Zhang, Xu; Chen, Xiang; Barkhaus, Paul E.; Zhou, Ping
2013-01-01
This study explores a novel application of multi-scale entropy (MSE) analysis for characterizing different patterns of spontaneous electromyogram (EMG) signals including sporadic, tonic and repetitive spontaneous motor unit discharges, and normal surface EMG baseline. Two algorithms for MSE analysis, namely the standard MSE and the intrinsic mode entropy (IMEn) (based on the recently developed multivariate empirical mode decomposition (MEMD) method), were applied to different patterns of spon...
Wavelet-Based Multi-Scale Entropy Analysis of Complex Rainfall Time Series
Chien-Ming Chou
2011-01-01
This paper presents a novel framework to determine the number of resolution levels in the application of a wavelet transformation to a rainfall time series. The rainfall time series are decomposed using the à trous wavelet transform. Then, multi-scale entropy (MSE) analysis that helps to elucidate some hidden characteristics of the original rainfall time series is applied to the decomposed rainfall time series. The analysis shows that the Mann-Kendall (MK) rank correlation test of MSE curves ...
DEFF Research Database (Denmark)
Escudero, Javier; Evrim, Acar Ataman; Fernández, Alberto;
2015-01-01
Tensor factorisations have proven useful to model amplitude and spectral information of brain recordings. Here, we assess the usefulness of tensor factorisations in the multiway analysis of other brain signal features in the context of complexity measures recently proposed to inspect multiscale.......77. This confirms the suitability of tensor factorisations to represent electrophysiological brain data efficiently despite the unsupervised nature of these techniques. This article is part of a Special Issue entitled 'Neural data analysis'....
Multi-scale Analysis for Rosseland Equation with Small Periodic Oscillating Coefficients
Qiao-fu, Zhang
2012-01-01
Rosseland equation is one of the most popular models of the conduction-radiation coupled heat transfer in the thermal protection system. The well-posedness, the corresponding mathematical theory and the Multi-scale analysis method for the Rosseland-type equations with small periodic oscillating coefficients are concerned, which provides a theoretical basis for the Multi-scale computation of the conduction-radiation coupled heat transfer in an optically thick medium with a small periodic structure. The global well-posedness of the Rosseland-type (parabolic) equations is given in the first part. The corresponding solving algorithms and their convergence analysis are presented in the second part. In the third part we study the well-posedness and the second-order two-scale asymptotic expansion of the Rosseland-type (elliptic) equations with small periodic oscillating coefficients. The convergence analysis of the second-order two-scale asymptotic expansion is studied in the last part.
Chia-Hsuan Lee; Tien-Lung Sun
2015-01-01
The goal of this study was to investigate the parameters affecting exergame performance using multi-scale entropy analysis, with the aim of informing the design of exergames for personalized balance training. Test subjects’ center of pressure (COP) displacement data were recorded during exergame play to examine their balance ability at varying difficulty levels of a balance-based exergame; the results of a multi-scale entropy-based analysis were then compared to traditional COP indicators. F...
Multiscale analysis of heart rate, blood pressure and respiration time series
Angelini, L; Marinazzo, D; Nitti, L; Pellicoro, M; Pinna, G D; Stramaglia, S; Tupputi, S A
2005-01-01
We present the multiscale entropy analysis of short term physiological time series of simultaneously acquired samples of heart rate, blood pressure and lung volume, from healthy subjects and from subjects with Chronic Heart Failure. Evaluating the complexity of signals at the multiple time scales inherent in physiologic dynamics, we find that healthy subjects show more complex time series at large time scales; on the other hand, at fast time scales, which are more influenced by respiration, the pathologic dynamics of blood pressure is the most random. These results robustly separate healthy and pathologic groups. We also propose a multiscale approach to evaluate interactions between time series, by performing a multivariate autoregressive modelling of the coarse grained time series: this analysis provides several new quantitative indicators which are statistically correlated with the pathology.
Pak, Theodore R; Kasarskis, Andrew
2015-12-01
Recent reviews have examined the extent to which routine next-generation sequencing (NGS) on clinical specimens will improve the capabilities of clinical microbiology laboratories in the short term, but do not explore integrating NGS with clinical data from electronic medical records (EMRs), immune profiling data, and other rich datasets to create multiscale predictive models. This review introduces a range of "omics" and patient data sources relevant to managing infections and proposes 3 potentially disruptive applications for these data in the clinical workflow. The combined threats of healthcare-associated infections and multidrug-resistant organisms may be addressed by multiscale analysis of NGS and EMR data that is ideally updated and refined over time within each healthcare organization. Such data and analysis should form the cornerstone of future learning health systems for infectious disease.
Learning Multiscale Active Facial Patches for Expression Analysis.
Zhong, Lin; Liu, Qingshan; Yang, Peng; Huang, Junzhou; Metaxas, Dimitris N
2015-08-01
In this paper, we present a new idea to analyze facial expression by exploring some common and specific information among different expressions. Inspired by the observation that only a few facial parts are active in expression disclosure (e.g., around mouth, eye), we try to discover the common and specific patches which are important to discriminate all the expressions and only a particular expression, respectively. A two-stage multitask sparse learning (MTSL) framework is proposed to efficiently locate those discriminative patches. In the first stage MTSL, expression recognition tasks are combined to located common patches. Each of the tasks aims to find dominant patches for each expression. Secondly, two related tasks, facial expression recognition and face verification tasks, are coupled to learn specific facial patches for individual expression. The two-stage patch learning is performed on patches sampled by multiscale strategy. Extensive experiments validate the existence and significance of common and specific patches. Utilizing these learned patches, we achieve superior performances on expression recognition compared to the state-of-the-arts. PMID:25291808
Multiscale entropy analysis of biological signals: a fundamental bi-scaling law
Gao, Jianbo; Hu, Jing; Liu, Feiyan; Cao, Yinhe
2015-01-01
Since introduced in early 2000, multiscale entropy (MSE) has found many applications in biosignal analysis, and been extended to multivariate MSE. So far, however, no analytic results for MSE or multivariate MSE have been reported. This has severely limited our basic understanding of MSE. For example, it has not been studied whether MSE estimated using default parameter values and short data set is meaningful or not. Nor is it known whether MSE has any relation with other complexity measures,...
Low-carbon building assessment and multi-scale input-output analysis
Chen, G. Q.; Chen, H.; Chen, Z. M.; Zhang, Bo; Shao, L.; Guo, S.; Zhou, S. Y.; Jiang, M. M.
2011-01-01
Presented as a low-carbon building evaluation framework in this paper are detailed carbon emission account procedures for the life cycle of buildings in terms of nine stages as building construction, fitment, outdoor facility construction, transportation, operation, waste treatment, property management, demolition, and disposal for buildings, supported by integrated carbon intensity databases based on multi-scale input-output analysis, essential for low-carbon planning, procurement and supply chain design, and logistics management.
Lin, Aijing; Shang, Pengjian
2016-04-01
Considering the diverse application of multifractal techniques in natural scientific disciplines, this work underscores the versatility of multiscale multifractal detrended fluctuation analysis (MMA) method to investigate artificial and real-world data sets. The modified MMA method based on cumulative distribution function is proposed with the objective of quantifying the scaling exponent and multifractality of nonstationary time series. It is demonstrated that our approach can provide a more stable and faithful description of multifractal properties in comprehensive range rather than fixing the window length and slide length. Our analyzes based on CDF-MMA method reveal significant differences in the multifractal characteristics in the temporal dynamics between US and Chinese stock markets, suggesting that these two stock markets might be regulated by very different mechanism. The CDF-MMA method is important for evidencing the stable and fine structure of multiscale and multifractal scaling behaviors and can be useful to deepen and broaden our understanding of scaling exponents and multifractal characteristics.
Nanosystem Self-Assembly Pathways Discovered via All-Atom Multiscale Analysis
Pankavich, Stephen
2014-01-01
We consider the self-assembly of composite structures from a group of nanocomponents, each consisting of particles within an $N$-atom system. Self-assembly pathways and rates for nanocomposites are derived via a multiscale analysis of the classical Liouville equation. From a reduced statistical framework, rigorous stochastic equations for population levels of beginning, intermediate, and final aggregates are also derived. It is shown that the definition of an assembly type is a self-consistency criterion that must strike a balance between precision and the need for population levels to be slowly varying relative to the time scale of atomic motion. The deductive multiscale approach is complemented by a qualitative notion of multicomponent association and the ensemble of exact atomic-level configurations consistent with them. In processes such as viral self-assembly from proteins and RNA or DNA, there are many possible intermediates, so that it is usually difficult to predict the most efficient assembly pathway...
Multivariate multiscale entropy: a tool for complexity analysis of multichannel data.
Ahmed, Mosabber Uddin; Mandic, Danilo P
2011-12-01
This work generalizes the recently introduced univariate multiscale entropy (MSE) analysis to the multivariate case. This is achieved by introducing multivariate sample entropy (MSampEn) in a rigorous way, in order to account for both within- and cross-channel dependencies in multiple data channels, and by evaluating it over multiple temporal scales. The multivariate MSE (MMSE) method is shown to provide an assessment of the underlying dynamical richness of multichannel observations, and more degrees of freedom in the analysis than standard MSE. The benefits of the proposed approach are illustrated by simulations on complexity analysis of multivariate stochastic processes and on real-world multichannel physiological and environmental data. PMID:22304127
Jolivet, S.; Mezghani, S.; El Mansori, M.
2016-09-01
The replication of topography has been generally restricted to optimizing material processing technologies in terms of statistical and single-scale features such as roughness. By contrast, manufactured surface topography is highly complex, irregular, and multiscale. In this work, we have demonstrated the use of multiscale analysis on replicates of surface finish to assess the precise control of the finished replica. Five commercial resins used for surface replication were compared. The topography of five standard surfaces representative of common finishing processes were acquired both directly and by a replication technique. Then, they were characterized using the ISO 25178 standard and multiscale decomposition based on a continuous wavelet transform, to compare the roughness transfer quality at different scales. Additionally, atomic force microscope force modulation mode was used in order to compare the resins’ stiffness properties. The results showed that less stiff resins are able to replicate the surface finish along a larger wavelength band. The method was then tested for non-destructive quality control of automotive gear tooth surfaces.
Mood states modulate complexity in heartbeat dynamics: A multiscale entropy analysis
Valenza, G.; Nardelli, M.; Bertschy, G.; Lanata, A.; Scilingo, E. P.
2014-07-01
This paper demonstrates that heartbeat complex dynamics is modulated by different pathological mental states. Multiscale entropy analysis was performed on R-R interval series gathered from the electrocardiogram of eight bipolar patients who exhibited mood states among depression, hypomania, and euthymia, i.e., good affective balance. Three different methodologies for the choice of the sample entropy radius value were also compared. We show that the complexity level can be used as a marker of mental states being able to discriminate among the three pathological mood states, suggesting to use heartbeat complexity as a more objective clinical biomarker for mental disorders.
Costa, Madalena D.; Ary L Goldberger
2015-01-01
We introduce a generalization of multiscale entropy (MSE) analysis. The method is termed MSE n , where the subscript denotes the moment used to coarse-grain a time series. MSE μ , described previously, uses the mean value (first moment). Here, we focus on MSE σ 2 , which uses the second moment, i.e., the variance. MSE σ 2 quantifies the dynamics of the volatility (variance) of a signal over multiple time scales. We use the method to analyze the structure of heartbeat time series. We find that...
Multiscale entropy analysis of biological signals:a fundamental bi-scaling law
Jianbo eGao
2015-01-01
Multiscale entropy (MSE) analysis is an interesting method for analyzing biological signals.So far, however, few analytic results for MSE have been reported. This has severelylimited our basic understanding of MSE. To overcome this limitation, and more importantly,to guide more fruitful applications of MSE in various areas of life sciences, we derive, for timeseries with long memory, a fundamental bi-scaling law, one for the scale in the phase space,the other for the block size used for smoot...
Arnold, Steven M.; Bednarcyk, Brett A.; Hussain, Aquila; Katiyar, Vivek
2010-01-01
A unified framework is presented that enables coupled multiscale analysis of composite structures and associated graphical pre- and postprocessing within the Abaqus/CAE environment. The recently developed, free, Finite Element Analysis--Micromechanics Analysis Code (FEAMAC) software couples NASA's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with Abaqus/Standard and Abaqus/Explicit to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. The Graphical User Interfaces (FEAMAC-Pre and FEAMAC-Post), developed through collaboration between SIMULIA Erie and the NASA Glenn Research Center, enable users to employ a new FEAMAC module within Abaqus/CAE that provides access to the composite microscale. FEA IAC-Pre is used to define and store constituent material properties, set-up and store composite repeating unit cells, and assign composite materials as sections with all data being stored within the CAE database. Likewise FEAMAC-Post enables multiscale field quantity visualization (contour plots, X-Y plots), with point and click access to the microscale i.e., fiber and matrix fields).
Multi-Scale Distributed Sensitivity Analysis of Radiative Transfer Model
Neelam, M.; Mohanty, B.
2015-12-01
Amidst nature's great variability and complexity and Soil Moisture Active Passive (SMAP) mission aims to provide high resolution soil moisture products for earth sciences applications. One of the biggest challenges still faced by the remote sensing community are the uncertainties, heterogeneities and scaling exhibited by soil, land cover, topography, precipitation etc. At each spatial scale, there are different levels of uncertainties and heterogeneities. Also, each land surface variable derived from various satellite mission comes with their own error margins. As such, soil moisture retrieval accuracy is affected as radiative model sensitivity changes with space, time, and scale. In this paper, we explore the distributed sensitivity analysis of radiative model under different hydro-climates and spatial scales, 1.5 km, 3 km, 9km and 39km. This analysis is conducted in three different regions Iowa, U.S.A (SMEX02), Arizona, USA (SMEX04) and Winnipeg, Canada (SMAPVEX12). Distributed variables such as soil moisture, soil texture, vegetation and temperature are assumed to be uncertain and are conditionally simulated to obtain uncertain maps, whereas roughness data which is spatially limited are assumed a probability distribution. The relative contribution of the uncertain model inputs to the aggregated model output is also studied, using various aggregation techniques. We use global sensitivity analysis (GSA) to conduct this analysis across spatio-temporal scales. Keywords: Soil moisture, radiative transfer, remote sensing, sensitivity, SMEX02, SMAPVEX12.
Global Appearance Applied to Visual Map Building and Path Estimation Using Multiscale Analysis
Directory of Open Access Journals (Sweden)
Francisco Amorós
2014-01-01
Full Text Available In this work we present a topological map building and localization system for mobile robots based on global appearance of visual information. We include a comparison and analysis of global-appearance techniques applied to wide-angle scenes in retrieval tasks. Next, we define multiscale analysis, which permits improving the association between images and extracting topological distances. Then, a topological map-building algorithm is proposed. At first, the algorithm has information only of some isolated positions of the navigation area in the form of nodes. Each node is composed of a collection of images that covers the complete field of view from a certain position. The algorithm solves the node retrieval and estimates their spatial arrangement. With these aims, it uses the visual information captured along some routes that cover the navigation area. As a result, the algorithm builds a graph that reflects the distribution and adjacency relations between nodes (map. After the map building, we also propose a route path estimation system. This algorithm takes advantage of the multiscale analysis. The accuracy in the pose estimation is not reduced to the nodes locations but also to intermediate positions between them. The algorithms have been tested using two different databases captured in real indoor environments under dynamic conditions.
Escudero, Javier; Acar, Evrim; Fernández, Alberto; Bro, Rasmus
2015-10-01
Tensor factorisations have proven useful to model amplitude and spectral information of brain recordings. Here, we assess the usefulness of tensor factorisations in the multiway analysis of other brain signal features in the context of complexity measures recently proposed to inspect multiscale dynamics. We consider the "refined composite multiscale entropy" (rcMSE), which computes entropy "profiles" showing levels of physiological complexity over temporal scales for individual signals. We compute the rcMSE of resting-state magnetoencephalogram (MEG) recordings from 36 patients with Alzheimer's disease and 26 control subjects. Instead of traditional simple visual examinations, we organise the entropy profiles as a three-way tensor to inspect relationships across temporal and spatial scales and subjects with multiway data analysis techniques based on PARAFAC and PARAFAC2 factorisations. A PARAFAC2 model with two factors was appropriate to account for the interactions in the entropy tensor between temporal scales and MEG channels for all subjects. Moreover, the PARAFAC2 factors had information related to the subjects' diagnosis, achieving a cross-validated area under the ROC curve of 0.77. This confirms the suitability of tensor factorisations to represent electrophysiological brain data efficiently despite the unsupervised nature of these techniques. This article is part of a Special Issue entitled 'Neural data analysis'. PMID:25982737
A Multi-scale Approach to Urban Thermal Analysis
Gluch, Renne; Quattrochi, Dale A.
2005-01-01
An environmental consequence of urbanization is the urban heat island effect, a situation where urban areas are warmer than surrounding rural areas. The urban heat island phenomenon results from the replacement of natural landscapes with impervious surfaces such as concrete and asphalt and is linked to adverse economic and environmental impacts. In order to better understand the urban microclimate, a greater understanding of the urban thermal pattern (UTP), including an analysis of the thermal properties of individual land covers, is needed. This study examines the UTP by means of thermal land cover response for the Salt Lake City, Utah, study area at two scales: 1) the community level, and 2) the regional or valleywide level. Airborne ATLAS (Advanced Thermal Land Applications Sensor) data, a high spatial resolution (10-meter) dataset appropriate for an environment containing a concentration of diverse land covers, are used for both land cover and thermal analysis at the community level. The ATLAS data consist of 15 channels covering the visible, near-IR, mid-IR and thermal-IR wavelengths. At the regional level Landsat TM data are used for land cover analysis while the ATLAS channel 13 data are used for the thermal analysis. Results show that a heat island is evident at both the community and the valleywide level where there is an abundance of impervious surfaces. ATLAS data perform well in community level studies in terms of land cover and thermal exchanges, but other, more coarse-resolution data sets are more appropriate for large-area thermal studies. Thermal response per land cover is consistent at both levels, which suggests potential for urban climate modeling at multiple scales.
Multiscale Embedded Gene Co-expression Network Analysis
Song, Won-Min; Zhang, Bin
2015-01-01
Gene co-expression network analysis has been shown effective in identifying functional co-expressed gene modules associated with complex human diseases. However, existing techniques to construct co-expression networks require some critical prior information such as predefined number of clusters, numerical thresholds for defining co-expression/interaction, or do not naturally reproduce the hallmarks of complex systems such as the scale-free degree distribution of small-worldness. Previously, a...
Multiscale 3D shape analysis using spherical wavelets.
Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen R
2005-01-01
Shape priors attempt to represent biological variations within a population. When variations are global, Principal Component Analysis (PCA) can be used to learn major modes of variation, even from a limited training set. However, when significant local variations exist, PCA typically cannot represent such variations from a small training set. To address this issue, we present a novel algorithm that learns shape variations from data at multiple scales and locations using spherical wavelets and spectral graph partitioning. Our results show that when the training set is small, our algorithm significantly improves the approximation of shapes in a testing set over PCA, which tends to oversmooth data. PMID:16685992
Multi-scale model analysis and hindcast of the 2013 Colorado Flood
Gochis, David; Yu, Wei; Sampson, Kevin; Dugger, Aubrey; McCreight, James; Zhang, Yongxin; Ikeda, Kyoko
2015-04-01
While the generation of most flood and flash flood events is fundamentally linked to the occurrence of heavy rainfall, the physical mechanisms responsible for translating rainfall into floods are complex and manifold. These runoff generation processes evolve over many spatial and temporal scales during the course of flooding events. As such robust flood and flash flood prediction systems need to account for multitude of terrestrial processes occurring over a wide range of space and time scales. One such extreme multiscale flood event was the 2013 Colorado Flood in which over 400 mm of rainfall fell along the Rock Mountain mountain front region over the course of a few days. The flooding impacts from this heavy rainfall event included not only high, fast flows in steep mountain streams but also included large areas of inundation on the adjacent plains and numerous soil saturation excess impacts such as hillslope failures and groundwater intrusions into domestic structures. A multi-scale and multi-process evaluation of this flood event is performed using the community WRF-Hydro modeling system. We incorporate several operational quantitative precipitation estimate and quantitative precipitation forecast products in the analysis and document the skill of multiple configurations of WRF-Hydro physics options across a range of contributing area length scales. Emphasis is placed on assessing how well the different model configurations capture the multi-scale streamflow response from small headwater catchments out to the entire South Platte River basin whose total contributing area exceeds 25,000 sq km. In addition to streamflow we also present evaluations of event simulations and hindcasts of soil saturation fraction, groundwater levels and inundated areas as a means of assessing different runoff generation mechanisms. Finally, results from a U.S. national-scale, fully-coupled hydrometeorological hindcast of the 2013 Colorado flood event using the combined WRF atmospheric
Raischel, F.; Moreira, A.; Lind, P. G.
2014-10-01
We address and discuss recent trends in the analysis of big data sets, with the emphasis on studying multiscale phenomena. Applications of big data analysis in different scientific fields are described and two particular examples of multiscale phenomena are explored in more detail. The first one deals with wind power production at the scale of single wind turbines, the scale of entire wind farms and also at the scale of a whole country. Using open source data we show that the wind power production has an intermittent character at all those three scales, with implications for defining adequate strategies for stable energy production. The second example concerns the dynamics underlying human mobility, which presents different features at different scales. For that end, we analyze 12-month data of the Eduroam database within Portuguese universities, and find that, at the smallest scales, typically within a set of a few adjacent buildings, the characteristic exponents of average displacements are different from the ones found at the scale of one country or one continent.
Multiscale analysis of heart beat interval increment series and its clinical significance
Institute of Scientific and Technical Information of China (English)
HUANG XiaoLin; NING XinBao; WANG XinLong
2009-01-01
Analysis of multiscale entropy (MSE) and multiscale standard deviation (MSD) are performed for both the heart rate interval series and the interval increment series. For the interval series, it is found that, it is impractical to discriminate the diseases of atrial fibrillation (AF) and congestive heart failure (CHF) unambiguously from the healthy. A clear discrimination from the healthy, both young and old, however, can be made in the MSE analysis of the increment series where we find that both CHF and AF sufferers have significantly low MSE values in the whole range of time scales investigated, which reveals that there are common dynamic characteristics underlying these two different diseases. In addition, we propose the sample entropy (SE) corresponding to time scale factor 4 of increment series as a diag-nosis index of both AF and CHF, and the reference threshold is recommended. Further indication that this index can help discriminate sensitively the mild heart failure (cardiac function classes 1 and 2) from the healthy gives a clue to early clinic diagnosis of CHF.
Goïc, Gaëtan Le; Bigerelle, Maxence; Samper, Serge; Favrelière, Hugues; Pillet, Maurice
2016-01-01
This study investigates the correlations between the topography of different damaged rough surfaces and process conditions. Several surfaces are measured and compared to determine if they can be discriminated. The analysis is performed by using Gaussian Filtering, Wavelet Transform and a more recent approach named Discrete Modal Decomposition. Standardized 3D roughness parameters are computed for each multiscale method, filter (e.g., high-pass, low-pass and band-pass) and available scale. The relevance (i.e., the ability to discriminate surface topographies corresponding to different process conditions) is then investigated using a statistical analysis based on the MesRugTM expert system. The results indicate clear differences between the multiscale methods and show that the Wavelet approach is useful when characterizing localized surface defects while Gaussian Filtering is more appropriate for highly periodic morphological structures. For more complex topographies, this study also clearly shows that the Discrete Modal Decomposition exhibits compelling abilities that fall between those of the Gaussian and Wavelet approaches; this method is clearly more relevant than the Gaussian method in the case of localized defects and less relevant in the case of highly periodical structures and fractal surfaces (1 /fα spectrum). This can be explained by the modulated frequency/amplitude descriptors generated via the modal basis.
Multivariate Image Analysis in Gaussian Multi-Scale Space for Defect Detection
Institute of Scientific and Technical Information of China (English)
Dong-tai Liang; Wei-yan Deng; Xuan-yin Wang; Yang Zhang
2009-01-01
Inspired by the coarse-to-fine visual perception process of human vision system, a new approach based on Gaussian multi-scale space for defect detection of industrial products was proposed. By selecting different scale parameters of the Gaussian kernel, the multi-scale representation of the original image data could be obtained and used to constitute the multi-variate image, in which each channel could represent a perceptual observation of the original image from different scales. The Multivariate Image Analysis (MIA) techniques were used to extract defect features information. The MIA combined Principal Component Analysis (PCA) to obtain the principal component scores of the multivariate test image. The Q-statistic image, derived from the residuals after the extraction of the first principal component score and noise, could be used to efficiently reveal the surface defects with an appropriate threshold value decided by training images. Experimental results show that the proposed method performs better than the gray histogram-based method. It has less sensitivity to the inhomogeneous of illumination, and has more robustness and reliability of defect detection with lower pseudo reject rate.
Varghese, Julian
This research work has contributed in various ways to help develop a better understanding of textile composites and materials with complex microstructures in general. An instrumental part of this work was the development of an object-oriented framework that made it convenient to perform multiscale/multiphysics analyses of advanced materials with complex microstructures such as textile composites. In addition to the studies conducted in this work, this framework lays the groundwork for continued research of these materials. This framework enabled a detailed multiscale stress analysis of a woven DCB specimen that revealed the effect of the complex microstructure on the stress and strain energy release rate distribution along the crack front. In addition to implementing an oxidation model, the framework was also used to implement strategies that expedited the simulation of oxidation in textile composites so that it would take only a few hours. The simulation showed that the tow architecture played a significant role in the oxidation behavior in textile composites. Finally, a coupled diffusion/oxidation and damage progression analysis was implemented that was used to study the mechanical behavior of textile composites under mechanical loading as well as oxidation. A parametric study was performed to determine the effect of material properties and the number of plies in the laminate on its mechanical behavior. The analyses indicated a significant effect of the tow architecture and other parameters on the damage progression in the laminates.
Multiscale analysis of nonlinear systems using computational homology
Energy Technology Data Exchange (ETDEWEB)
Konstantin Mischaikow; Michael Schatz; William Kalies; Thomas Wanner
2010-05-24
This is a collaborative project between the principal investigators. However, as is to be expected, different PIs have greater focus on different aspects of the project. This report lists these major directions of research which were pursued during the funding period: (1) Computational Homology in Fluids - For the computational homology effort in thermal convection, the focus of the work during the first two years of the funding period included: (1) A clear demonstration that homology can sensitively detect the presence or absence of an important flow symmetry, (2) An investigation of homology as a probe for flow dynamics, and (3) The construction of a new convection apparatus for probing the effects of large-aspect-ratio. (2) Computational Homology in Cardiac Dynamics - We have initiated an effort to test the use of homology in characterizing data from both laboratory experiments and numerical simulations of arrhythmia in the heart. Recently, the use of high speed, high sensitivity digital imaging in conjunction with voltage sensitive fluorescent dyes has enabled researchers to visualize electrical activity on the surface of cardiac tissue, both in vitro and in vivo. (3) Magnetohydrodynamics - A new research direction is to use computational homology to analyze results of large scale simulations of 2D turbulence in the presence of magnetic fields. Such simulations are relevant to the dynamics of black hole accretion disks. The complex flow patterns from simulations exhibit strong qualitative changes as a function of magnetic field strength. Efforts to characterize the pattern changes using Fourier methods and wavelet analysis have been unsuccessful. (4) Granular Flow - two experts in the area of granular media are studying 2D model experiments of earthquake dynamics where the stress fields can be measured; these stress fields from complex patterns of 'force chains' that may be amenable to analysis using computational homology. (5) Microstructure
Multiscale analysis of nonlinear systems using computational homology
Energy Technology Data Exchange (ETDEWEB)
Konstantin Mischaikow, Rutgers University/Georgia Institute of Technology, Michael Schatz, Georgia Institute of Technology, William Kalies, Florida Atlantic University, Thomas Wanner,George Mason University
2010-05-19
This is a collaborative project between the principal investigators. However, as is to be expected, different PIs have greater focus on different aspects of the project. This report lists these major directions of research which were pursued during the funding period: (1) Computational Homology in Fluids - For the computational homology effort in thermal convection, the focus of the work during the first two years of the funding period included: (1) A clear demonstration that homology can sensitively detect the presence or absence of an important flow symmetry, (2) An investigation of homology as a probe for flow dynamics, and (3) The construction of a new convection apparatus for probing the effects of large-aspect-ratio. (2) Computational Homology in Cardiac Dynamics - We have initiated an effort to test the use of homology in characterizing data from both laboratory experiments and numerical simulations of arrhythmia in the heart. Recently, the use of high speed, high sensitivity digital imaging in conjunction with voltage sensitive fluorescent dyes has enabled researchers to visualize electrical activity on the surface of cardiac tissue, both in vitro and in vivo. (3) Magnetohydrodynamics - A new research direction is to use computational homology to analyze results of large scale simulations of 2D turbulence in the presence of magnetic fields. Such simulations are relevant to the dynamics of black hole accretion disks. The complex flow patterns from simulations exhibit strong qualitative changes as a function of magnetic field strength. Efforts to characterize the pattern changes using Fourier methods and wavelet analysis have been unsuccessful. (4) Granular Flow - two experts in the area of granular media are studying 2D model experiments of earthquake dynamics where the stress fields can be measured; these stress fields from complex patterns of 'force chains' that may be amenable to analysis using computational homology. (5) Microstructure
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
The multi-scale characteristics of wave significant height (Hs) in eastern China seas were revealed by multi-scale wavelet analysis. In order to understand the relation between wave and wind, the TOPEX/Poseidon measurements of Hs and wind speed were analyzed. The result showed that Hs and wind speed change in multi-scale at one-, two-month, half-, one- and two-year cycles. But in a larger time scale, the variations in Hs and wind speed are different. Hs has a five-year cycle similar to the cycle of ENSO variation, while the wind speed has no such cycle. In the time domain, the correlation between Hs and ENSO is unclear.
Multi-Scale Morphological Analysis of SDSS DR5 Survey using the Metric Space Technique
Wu, Yongfeng; Khalil, Andre
2008-01-01
Following novel development and adaptation of the Metric Space Technique (MST), a multi-scale morphological analysis of the Sloan Digital Sky Survey (SDSS) Data Release 5 (DR5) was performed. The technique was adapted to perform a space-scale morphological analysis by filtering the galaxy point distributions with a smoothing gaussian function, thus giving quantitative structural information on all size scales between 5 and 250 Mpc. The analysis was performed on a dozen slices of a volume of space containing many newly measured galaxies from the SDSS DR5 survey. Using the MST, observational data were compared to galaxy samples taken from N-body simulations with current best estimates of cosmological parameters and from random catalogs. By using the maximal ranking method among MST output functions we also develop a way to quantify the overall similarity of the observed samples with the simulated samples.
International Nuclear Information System (INIS)
Nature's functional surfaces are typically hierarchical multiscale structures. There are several techniques for producing such artificial structures on polymers but their mass production is not straightforward. We present here a simple and versatile method for manufacturing hierarchical multiscale polymer surface patterns. The microroughening technique permits the single-step production of multilevel three-dimensional surface architectures in a mechanically durable nickel mold. The molding technique is suitable for area-controlled fabrication of structures with various geometrical shapes on smooth and curved surfaces. The mold structures were transferred to polypropylene surfaces by means of injection molding. The fabricated surface structures were characterized by using a filtered power spectral density method which facilitated a quantitative study of the roughness distributions at different length scales of structure periodicities. Analysis showed that the microroughening technique is an appropriate tool for controlled production of surface roughness at a micro-nanometer scale. Roughness distribution values can be used for predicting surface structure-related properties such as wetting, and the distributions can also be simulated without an experimental preparation process. The work presents a suitable approach for mass production of hierarchical polymer surfaces at different length scales and provides a new route for designing surface structures with tunable wetting properties. (paper)
Multiscale Multiphysics-Based Modeling and Analysis on the Tool Wear in Micro Drilling
Niu, Zhichao; Cheng, Kai
2016-02-01
In micro-cutting processes, process variables including cutting force, cutting temperature and drill-workpiece interfacing conditions (lubrication and interaction, etc.) significantly affect the tool wear in a dynamic interactive in-process manner. The resultant tool life and cutting performance directly affect the component surface roughness, material removal rate and form accuracy control, etc. In this paper, a multiscale multiphysics oriented approach to modeling and analysis is presented particularly on tooling performance in micro drilling processes. The process optimization is also taken account based on establishing the intrinsic relationship between process parameters and cutting performance. The modeling and analysis are evaluated and validated through well-designed machining trials, and further supported by metrology measurements and simulations. The paper is concluded with a further discussion on the potential and application of the approach for broad micro manufacturing purposes.
Bornas, Xavier; Llabrés, Jordi; Noguera, Miquel; López, Ana M A; Gelabert, Joan Miquel; Vila, Irene
2006-10-01
In this study we explored the changes in the variability and complexity of the electrocardiogram (ECG) of flight phobics (N=61) and a matched non-phobic control group (N=58) when they performed a paced breathing task and were exposed to flight related stimuli. Lower complexity/entropy values were expected in phobics as compared to controls. The phobic system complexity as well as the heart rate variability (HRV) were expected to be reduced by the exposure to fearful stimuli. The multiscale entropy (MSE) analysis revealed lower entropy values in phobics during paced breathing and exposure, and a complexity loss was observed in phobics during exposure to threatening situations. The expected HRV decreases were not found in this study. The discussion is focused on the distinction between variability and complexity measures of the cardiac output, and on the usefulness of the MSE analysis in the field of anxiety disorders. PMID:16839658
Multi-scale dynamical analysis (MSDA) of sea level records versus PDO, AMO, and NAO indexes
Scafetta, Nicola
2013-01-01
Herein I propose a multi-scale dynamical analysis to facilitate the physical interpretation of tide gauge records. The technique uses graphical diagrams. It is applied to six secular-long tide gauge records representative of the world oceans: Sydney, Pacific coast of Australia; Fremantle, Indian Ocean coast of Australia; New York City, Atlantic coast of USA; Honolulu, U.S. state of Hawaii; San Diego, U.S. state of California; and Venice, Mediterranean Sea, Italy. For comparison, an equivalent analysis is applied to the Pacific Decadal Oscillation (PDO) index and to the Atlantic Multidecadal Oscillation (AMO) index. Finally, a global reconstruction of sea level and a reconstruction of the North Atlantic Oscillation (NAO) index are analyzed and compared: both sequences cover about three centuries from 1700 to 2000. The proposed methodology quickly highlights oscillations and teleconnections among the records at the decadal and multidecadal scales. At the secular time scales tide gauge records present relatively...
Sparse Image and Signal Processing: Wavelets and Related Geometric Multiscale Analysis
Starck, J-L.; Murtagh, Fionn; Fadili, J.
2010-01-01
This book presents the state of the art in sparse and multiscale image and signal processing, covering linear multiscale transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Recent concepts of sparsity and morphological diversity are described and exploited for various problems such as denoising, inverse problem regularization, sparse signal decomposition, blind source separation, and com...
Valenza, G; Wendt, H; Kiyono, K; Hayano, J; Watanabe, E; Yamamoto, Y; Abry, P; Barbieri, R
2015-08-01
Multiscale analysis of human heartbeat dynamics has been proved effective in characterizeing cardiovascular control physiology in health and disease. However, estimation of multiscale properties can be affected by the interpolation procedure used to preprocess the unevenly sampled R-R intervals derived from the ECG. To this extent, in this study we propose the estimation of wavelet coefficients and wavelet leaders on the output of inhomogeneous point process models of heartbeat dynamics. The RR interval series is modeled using probability density functions (pdfs) characterizing and predicting the time until the next heartbeat event occurs, as a linear function of the past history. Multiscale analysis is then applied to the pdfs' instantaneous first order moment. The proposed approach is tested on experimental data gathered from 57 congestive heart failure (CHF) patients by evaluating the recognition accuracy in predicting survivor and non-survivor patients, and by comparing performances from the informative point-process based interpolation and non-informative spline-based interpolation. Results demonstrate that multiscale analysis of point-process high-resolution representations achieves the highest prediction accuracy of 65.45%, proving our method as a promising tool to assess risk prediction in CHF patients. PMID:26736666
Takahashi, Tetsuya; Cho, Raymond Y.; Mizuno, Tomoyuki; Kikuchi, Mitsuru; Murata, Tetsuhito; Takahashi, Koichi; Wada, Yuji
2010-01-01
Multiscale entropy (MSE) analysis is a novel entropy-based approach for measuring dynamical complexity in physiological systems over a range of temporal scales. To evaluate this analytic approach as an aid to elucidating the pathophysiologic mechanisms in schizophrenia, we examined MSE in EEG activity in drug-naïve schizophrenia subjects pre- and post-treatment with antipsychotics in comparison with traditional EEG analysis. We recorded eyes-closed resting state EEG from frontal, temporal, parietal and occipital regions in drug-naïve 22 schizophrenia and 24 age-matched healthy control subjects. Fifteen patients were re-evaluated within 2–8 weeks after the initiation of antipsychotic treatment. For each participant, MSE was calculated on one continuous 60 second epoch for each experimental session. Schizophrenia subjects showed significantly higher complexity at higher time scales (lower frequencies), than that of healthy controls in fronto-centro-temporal, but not in parieto-occipital regions. Post-treatment, this higher complexity decreased to healthy control subject levels selectively in fronto-central regions, while the increased complexity in temporal sites remained higher. Comparative power analysis identified spectral slowing in frontal regions in pre-treatment schizophrenia subjects, consistent with previous findings, whereas no antipsychotic treatment effect was observed. In summary, multiscale entropy measures identified abnormal dynamical EEG signal complexity in anterior brain areas in schizophrenia that normalized selectively in fronto-central areas with antipsychotic treatment. These findings show that entropy-based analytic methods may serve as a novel approach for characterizing and understanding abnormal cortical dynamics in schizophrenia, and elucidating the therapeutic mechanisms of antipsychotics. PMID:20149880
Takahashi, Tetsuya; Cho, Raymond Y; Mizuno, Tomoyuki; Kikuchi, Mitsuru; Murata, Tetsuhito; Takahashi, Koichi; Wada, Yuji
2010-05-15
Multiscale entropy (MSE) analysis is a novel entropy-based approach for measuring dynamical complexity in physiological systems over a range of temporal scales. To evaluate this analytic approach as an aid to elucidating the pathophysiologic mechanisms in schizophrenia, we examined MSE in EEG activity in drug-naive schizophrenia subjects pre- and post-treatment with antipsychotics in comparison with traditional EEG analysis. We recorded eyes-closed resting-state EEG from frontal, temporal, parietal, and occipital regions in drug-naive 22 schizophrenia and 24 age-matched healthy control subjects. Fifteen patients were re-evaluated within 2-8 weeks after the initiation of antipsychotic treatment. For each participant, MSE was calculated on one continuous 60-s epoch for each experimental session. Schizophrenia subjects showed significantly higher complexity at higher time scales (lower frequencies) than did healthy controls in fronto-centro-temporal, but not in parieto-occipital regions. Post-treatment, this higher complexity decreased to healthy control subject levels selectively in fronto-central regions, while the increased complexity in temporal sites remained higher. Comparative power analysis identified spectral slowing in frontal regions in pre-treatment schizophrenia subjects, consistent with previous findings, whereas no antipsychotic treatment effect was observed. In summary, multiscale entropy measures identified abnormal dynamical EEG signal complexity in anterior brain areas in schizophrenia that normalized selectively in fronto-central areas with antipsychotic treatment. These findings show that entropy-based analytic methods may serve as a novel approach for characterizing and understanding abnormal cortical dynamics in schizophrenia and elucidating the therapeutic mechanisms of antipsychotics. PMID:20149880
A multiscale analysis of blast impact mitigation on the human head
Jenson, Daniel Bryan
The effectiveness of helmets in preventing shrapnel wounds and internal damage due to blast shock waves has been studied. Carbon nanotubes and similar nanostructures have also recently generated heightened interest due to their strength-to-weight ratio and other unique properties. Therefore, to understand and develop a helmet with improved protection, it is necessary to develop computational procedures that will enable the accurate modeling of traumatic head injuries as well as the precise measurement of the mechanical properties of nanostructures and how these characteristics behave when embedded as an advanced composite structure into a helmet. In this study, a multiscale simulation strategy is used to estimate the mechanical characteristics of advanced composite structures with embedded nanostructures. In most of the previous theoretical works, an analysis dedicated to improving the design of the helmet using composite structures was not included due to a lack of understanding of the interactions of the nanostructures with the matrix materials. In this work, the role of the helmet on the over pressurization and impulse experienced by the head during blast shock wave and blunt force trauma due to shrapnel impacts is studied. In addition, the properties of nanocomposite structures are estimated using molecular dynamics (MD) simulations and then scaled to the macroscopic level using continuum mechanic formulations. This modeling is further developed using Finite Element (FE) analysis to demonstrate the effectiveness of various types of nanostructures in energy absorption. An analysis is carried out on a model of an unprotected head to compare the results to those obtained when protected by a helmet containing different nanostructures. The developed multiscale model is used to improve the composition of helmets and the general understanding of the effects of blast shock wave and shrapnel impacts thereby leading to the mitigation and prevention of traumatic head
Directory of Open Access Journals (Sweden)
T. Lahousse
2011-10-01
Full Text Available We developed a multi-scale OBIA (object-based image analysis landslide detection technique to map shallow landslides in the Baichi watershed, Taiwan, after the 2004 Typhoon Aere event. Our semi-automated detection method selected multiple scales through landslide size statistics analysis for successive classification rounds. The detection performance achieved a modified success rate (MSR of 86.5% with the training dataset and 86% with the validation dataset. This performance level was due to the multi-scale aspect of our methodology, as the MSR for single scale classification was substantially lower, even after spectral difference segmentation, with a maximum of 74%. Our multi-scale technique was capable of detecting landslides of varying sizes, including very small landslides, up to 95 m^{2}. The method presented certain limitations: the thresholds we established for classification were specific to the study area, to the landslide type in the study area, and to the spectral characteristics of the satellite image. Because updating site-specific and image-specific classification thresholds is easy with OBIA software, our multi-scale technique is expected to be useful for mapping shallow landslides at watershed level.
Alzheimer's Disease Detection in Brain Magnetic Resonance Images Using Multiscale Fractal Analysis
International Nuclear Information System (INIS)
We present a new automated system for the detection of brain magnetic resonance images (MRI) affected by Alzheimer's disease (AD). The MRI is analyzed by means of multiscale analysis (MSA) to obtain its fractals at six different scales. The extracted fractals are used as features to differentiate healthy brain MRI from those of AD by a support vector machine (SVM) classifier. The result of classifying 93 brain MRIs consisting of 51 images of healthy brains and 42 of brains affected by AD, using leave-one-out cross-validation method, yielded 99.18% ± 0.01 classification accuracy, 100% sensitivity, and 98.20% ± 0.02 specificity. These results and a processing time of 5.64 seconds indicate that the proposed approach may be an efficient diagnostic aid for radiologists in the screening for AD
Three-band decomposition analysis in multiscale FSI models of abdominal aortic aneurysms
Nestola, Maria G. C.; Gizzi, Alessio; Cherubini, Christian; Filippi, Simonetta
2016-07-01
Computational modeling plays an important role in biology and medicine to assess the effects of hemodynamic alterations in the onset and development of vascular pathologies. Synthetic analytic indices are of primary importance for a reliable and effective a priori identification of the risk. In this scenario, we propose a multiscale fluid-structure interaction (FSI) modeling approach of hemodynamic flows, extending the recently introduced three-band decomposition (TBD) analysis for moving domains. A quantitative comparison is performed with respect to the most common hemodynamic risk indicators in a systematic manner. We demonstrate the reliability of the TBD methodology also for deformable domains by assuming a hyperelastic formulation of the arterial wall and a Newtonian approximation of the blood flow. Numerical simulations are performed for physiologic and pathologic axially symmetric geometry models with particular attention to abdominal aortic aneurysms (AAAs). Risk assessment, limitations and perspectives are finally discussed.
Multiscale entropy analysis of biological signals:a fundamental bi-scaling law
Directory of Open Access Journals (Sweden)
Jianbo eGao
2015-06-01
Full Text Available Multiscale entropy (MSE analysis is an interesting method for analyzing biological signals.So far, however, few analytic results for MSE have been reported. This has severelylimited our basic understanding of MSE. To overcome this limitation, and more importantly,to guide more fruitful applications of MSE in various areas of life sciences, we derive, for timeseries with long memory, a fundamental bi-scaling law, one for the scale in the phase space,the other for the block size used for smoothing. We illustrate the usefulness of the approach byexamining heart rate variability (HRV data for the purpose of distinguishing healthy subjectsfrom patients with congestive heart failure, a life-threatening condition.1
Wang, Wen-Jing; Cui, Ling-Li; Chen, Dao-Yun
2016-04-01
Monitoring of potential bearing faults in operation is of critical importance to safe operation of high speed trains. One of the major challenges is how to differentiate relevant signals to operational conditions of bearings from noises emitted from the surrounding environment. In this work, we report a procedure for analyzing acoustic emission signals collected from rolling bearings for diagnosis of bearing health conditions by examining their morphological pattern spectrum (MPS) through a multi-scale morphology analysis procedure. The results show that acoustic emission signals resulted from a given type of bearing faults share rather similar MPS curves. Further examinations in terms of sample entropy and Lempel-Ziv complexity of MPS curves suggest that these two parameters can be utilized to determine damage modes.
Lin, Aijing; Ma, Hui; Shang, Pengjian
2015-10-01
Here we propose the new method DH-MMA, based on multiscale multifractal detrended fluctuation analysis(MMA), to investigate the scaling properties in stock markets. It is demonstrated that our approach can provide a more stable and faithful description of the scaling properties in comprehensive range rather than fixing the window length and slide length. It allows the assessment of more universal and subtle scaling characteristics. We illustrate DH-MMA by selecting power-law artificial data sets and six stock markets from US and China. The US stocks exhibit very strong multifractality for positive values of q, however, the Chinese stocks show stronger multifractality for negative q than positive q. In general, the US stock markets show similar behaviors, but Chinese stock markets display distinguishing characteristics.
Etournay, Raphaël; Merkel, Matthias; Popović, Marko; Brandl, Holger; Dye, Natalie A; Aigouy, Benoît; Salbreux, Guillaume; Eaton, Suzanne; Jülicher, Frank
2016-01-01
Segmentation and tracking of cells in long-term time-lapse experiments has emerged as a powerful method to understand how tissue shape changes emerge from the complex choreography of constituent cells. However, methods to store and interrogate the large datasets produced by these experiments are not widely available. Furthermore, recently developed methods for relating tissue shape changes to cell dynamics have not yet been widely applied by biologists because of their technical complexity. We therefore developed a database format that stores cellular connectivity and geometry information of deforming epithelial tissues, and computational tools to interrogate it and perform multi-scale analysis of morphogenesis. We provide tutorials for this computational framework, called TissueMiner, and demonstrate its capabilities by comparing cell and tissue dynamics in vein and inter-vein subregions of the Drosophila pupal wing. These analyses reveal an unexpected role for convergent extension in shaping wing veins. PMID:27228153
Multi-Scale Entropy Analysis as a Method for Time-Series Analysis of Climate Data
Directory of Open Access Journals (Sweden)
Heiko Balzter
2015-03-01
Full Text Available Evidence is mounting that the temporal dynamics of the climate system are changing at the same time as the average global temperature is increasing due to multiple climate forcings. A large number of extreme weather events such as prolonged cold spells, heatwaves, droughts and floods have been recorded around the world in the past 10 years. Such changes in the temporal scaling behaviour of climate time-series data can be difficult to detect. While there are easy and direct ways of analysing climate data by calculating the means and variances for different levels of temporal aggregation, these methods can miss more subtle changes in their dynamics. This paper describes multi-scale entropy (MSE analysis as a tool to study climate time-series data and to identify temporal scales of variability and their change over time in climate time-series. MSE estimates the sample entropy of the time-series after coarse-graining at different temporal scales. An application of MSE to Central European, variance-adjusted, mean monthly air temperature anomalies (CRUTEM4v is provided. The results show that the temporal scales of the current climate (1960–2014 are different from the long-term average (1850–1960. For temporal scale factors longer than 12 months, the sample entropy increased markedly compared to the long-term record. Such an increase can be explained by systems theory with greater complexity in the regional temperature data. From 1961 the patterns of monthly air temperatures are less regular at time-scales greater than 12 months than in the earlier time period. This finding suggests that, at these inter-annual time scales, the temperature variability has become less predictable than in the past. It is possible that climate system feedbacks are expressed in altered temporal scales of the European temperature time-series data. A comparison with the variance and Shannon entropy shows that MSE analysis can provide additional information on the
Multiscale Static Analysis of Notched and Unnotched Laminates Using the Generalized Method of Cells
Naghipour Ghezeljeh, Paria; Arnold, Steven M.; Pineda, Evan J.; Stier, Bertram; Hansen, Lucas; Bednarcyk, Brett A.; Waas, Anthony M.
2016-01-01
The generalized method of cells (GMC) is demonstrated to be a viable micromechanics tool for predicting the deformation and failure response of laminated composites, with and without notches, subjected to tensile and compressive static loading. Given the axial [0], transverse [90], and shear [+45/-45] response of a carbon/epoxy (IM7/977-3) system, the unnotched and notched behavior of three multidirectional layups (Layup 1: [0,45,90,-45](sub 2S), Layup 2: [0,60,0](sub 3S), and Layup 3: [30,60,90,-30, -60](sub 2S)) are predicted under both tensile and compressive static loading. Matrix nonlinearity is modeled in two ways. The first assumes all nonlinearity is due to anisotropic progressive damage of the matrix only, which is modeled, using the multiaxial mixed-mode continuum damage model (MMCDM) within GMC. The second utilizes matrix plasticity coupled with brittle final failure based on the maximum principle strain criteria to account for matrix nonlinearity and failure within the Finite Element Analysis--Micromechanics Analysis Code (FEAMAC) software multiscale framework. Both MMCDM and plasticity models incorporate brittle strain- and stress-based failure criteria for the fiber. Upon satisfaction of these criteria, the fiber properties are immediately reduced to a nominal value. The constitutive response for each constituent (fiber and matrix) is characterized using a combination of vendor data and the axial, transverse, and shear responses of unnotched laminates. Then, the capability of the multiscale methodology is assessed by performing blind predictions of the mentioned notched and unnotched composite laminates response under tensile and compressive loading. Tabulated data along with the detailed results (i.e., stress-strain curves as well as damage evolution states at various ratios of strain to failure) for all laminates are presented.
Delineation of Urban Active Faults Using Multi-scale Gravity Analysis in Shenzhen, South China
Xu, C.; Liu, X.
2015-12-01
In fact, many cities in the world are established on the active faults. As the rapid urban development, thousands of large facilities, such as ultrahigh buildings, supersized bridges, railway, and so on, are built near or on the faults, which may change the balance of faults and induce urban earthquake. Therefore, it is significant to delineate effectively the faults for urban planning construction and social sustainable development. Due to dense buildings in urban area, the ordinary approaches to identify active faults, like geological survey, artificial seismic exploration and electromagnetic exploration, are not convenient to be carried out. Gravity, reflecting the mass distribution of the Earth's interior, provides a more efficient and convenient method to delineate urban faults. The present study is an attempt to propose a novel gravity method, multi-scale gravity analysis, for identifying urban active faults and determining their stability. Firstly, the gravity anomalies are decomposed by wavelet multi-scale analysis. Secondly, based on the decomposed gravity anomalies, the crust is layered and the multilayer horizontal tectonic stress is inverted. Lastly, the decomposed anomalies and the inverted horizontal tectonic stress are used to infer the distribution and stability of main active faults. For validating our method, a case study on active faults in Shenzhen City is processed. The results show that the distribution of decomposed gravity anomalies and multilayer horizontal tectonic stress are controlled significantly by the strike of the main faults and can be used to infer depths of the faults. The main faults in Shenzhen may range from 4km to 20km in the depth. Each layer of the crust is nearly equipressure since the horizontal tectonic stress has small amplitude. It indicates that the main faults in Shenzhen are relatively stable and have no serious impact on planning and construction of the city.
Bednarcyk, Brett A.; Arnold, Steven M.
2007-01-01
A framework is presented that enables coupled multiscale analysis of composite structures. The recently developed, free, Finite Element Analysis-Micromechanics Analysis Code (FEAMAC) software couples the Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) with ABAQUS to perform micromechanics based FEA such that the nonlinear composite material response at each integration point is modeled at each increment by MAC/GMC. As a result, the stochastic nature of fiber breakage in composites can be simulated through incorporation of an appropriate damage and failure model that operates within MAC/GMC on the level of the fiber. Results are presented for the progressive failure analysis of a titanium matrix composite tensile specimen that illustrate the power and utility of the framework and address the techniques needed to model the statistical nature of the problem properly. In particular, it is shown that incorporating fiber strength randomness on multiple scales improves the quality of the simulation by enabling failure at locations other than those associated with structural level stress risers.
San Liang, X.; Robinson, Allan R.
2007-12-01
A novel localized finite-amplitude hydrodynamic stability analysis is established in a unified treatment for the study of real oceanic and atmospheric processes, which are in general highly nonlinear, and intermittent in space and time. We first re-state the classical definition using the multi-scale energy and vorticity analysis (MS-EVA) developed in Liang and Robinson [Liang, X.S., Robinson, A.R., 2005. Localized multiscale energy and vorticity analysis. I. Fundamentals. Dyn. Atmos. Oceans 38, 195-230], and then manipulate certain global operators to achieve the temporal and spatial localization. The key of the spatial localization is transfer-transport separation, which is made precise with the concept of perfect transfer, while relaxation of marginalization leads to the localization of time. In doing so the information of transfer lost in the averages is retrieved and an easy-to-use instability metric is obtained. The resulting metric is field-like (Eulerian), conceptually generalizing the classical formalism, a bulk notion over the whole system. In this framework, an instability has a structure, which is of particular use for open flow processes. We check the structure of baroclinic instability with the benchmark Eady model solution, and the Iceland-Faeroe Frontal (IFF) intrusion, a highly localized and nonlinear process occurring frequently in the region between Iceland and Faeroe Islands. A clear isolated baroclinic instability is identified around the intrusion, which is further found to be characterized by the transition from a spatially growing mode to a temporally growing mode. We also check the consistency of the MS-EVA dynamics with the barotropic Kuo model. An observation is that a local perturbation burst does not necessarily imply an instability: the perturbation energy could be transported from other processes occurring elsewhere. We find that our analysis yields a Kuo theorem-consistent mean-eddy interaction, which is not seen in a conventional
Chung, Chen-Chih; Kang, Jiunn-Horng; Yuan, Rey-Yue; Wu, Dean; Chen, Chih-Chung; Chi, Nai-Fang; Chen, Po-Chih; Hu, Chaur-Jong
2013-07-01
Sleep disorders are frequently seen in patients with Parkinson disease (PD), including rapid eye movement (REM) behavior disorder and periodic limb movement disorder. However, knowledge about changes in non-REM sleep in patients with PD is limited. This study explored the characteristics of electroencephalography (EEG) during sleep in patients with PD and non-PD controls. We further conducted multiscale entropy (MSE) analysis to evaluate and compare the complexity of sleep EEG for the 2 groups. There were 9 patients with PD (Hoehn-Yahr stage 1 or 2) and 11 non-PD controls. All participants underwent standard whole-night polysomnography (PSG), which included 23 channels, 6 of which were for EEG. The raw data of the EEG were extracted and subjected to MSE analysis. Patients with PD had a longer sleep onset time and a higher spontaneous EEG arousal index. Sleep stage-specific increased MSE was observed in patients with PD during non-REM sleep. The difference was more marked and significant at higher time scale factors (TSFs). In conclusion, increased biosignal complexity, as revealed by MSE analysis, was found in patients with PD during non-REM sleep at high TSFs. This finding might reflect a compensatory mechanism for early defects in neuronal network control machinery in PD. PMID:23545244
SIMULATION OF CRACK DIAGNOSIS OF ROTOR BASED ON MULTI-SCALE SINGULAR-SPECTRUM ANALYSIS
Institute of Scientific and Technical Information of China (English)
LI Ruqiang; LIU Yuanfeng
2006-01-01
In the diagnosis of rotor crack based on wavelet analysis, it is a painful task to find out an adaptive mother wavelet as many of them can be chosen and the analytic results of different mother wavelets are yet not the same. For this limitation of wavelet analysis, a novel diagnostic approach of rotor crack based on multi-scale singular-spectrum analysis (MS-SSA) is proposed. Firstly, a Jeffcott model of a cracked rotor is developed and the forth-order Runge-Kutta method is used to solve the motion equations of this rotor to obtain its time response (signals). Secondly, a comparatively simple approach of MS-SSA is presented and the empirical orthogonal functions of different orders in various scales are regarded as analyzing functions. At last, the signals of the cracked rotor and an uncracked rotor are analyzed using the proposed approach of MS-SSA, and the simulative results are compared. The results show that, the data-adaptive analyzing functions can capture many features of signals and the rotor crack can be identified and diagnosed effectively by comparing the analytic results of signals of the cracked rotor with those of the uncracked rotor using the analyzing functions of different orders.
Medical image retrieval and analysis by Markov random fields and multi-scale fractal dimension
International Nuclear Information System (INIS)
Many Content-based Image Retrieval (CBIR) systems and image analysis tools employ color, shape and texture (in a combined fashion or not) as attributes, or signatures, to retrieve images from databases or to perform image analysis in general. Among these attributes, texture has turned out to be the most relevant, as it allows the identification of a larger number of images of a different nature. This paper introduces a novel signature which can be used for image analysis and retrieval. It combines texture with complexity extracted from objects within the images. The approach consists of a texture segmentation step, modeled as a Markov Random Field process, followed by the estimation of the complexity of each computed region. The complexity is given by a Multi-scale Fractal Dimension. Experiments have been conducted using an MRI database in both pattern recognition and image retrieval contexts. The results show the accuracy of the proposed method in comparison with other traditional texture descriptors and also indicate how the performance changes as the level of complexity is altered. (paper)
Medical image retrieval and analysis by Markov random fields and multi-scale fractal dimension
Backes, André Ricardo; Cavaleri Gerhardinger, Leandro; do Espírito Santo Batista Neto, João; Martinez Bruno, Odemir
2015-02-01
Many Content-based Image Retrieval (CBIR) systems and image analysis tools employ color, shape and texture (in a combined fashion or not) as attributes, or signatures, to retrieve images from databases or to perform image analysis in general. Among these attributes, texture has turned out to be the most relevant, as it allows the identification of a larger number of images of a different nature. This paper introduces a novel signature which can be used for image analysis and retrieval. It combines texture with complexity extracted from objects within the images. The approach consists of a texture segmentation step, modeled as a Markov Random Field process, followed by the estimation of the complexity of each computed region. The complexity is given by a Multi-scale Fractal Dimension. Experiments have been conducted using an MRI database in both pattern recognition and image retrieval contexts. The results show the accuracy of the proposed method in comparison with other traditional texture descriptors and also indicate how the performance changes as the level of complexity is altered.
ESMAEILLOU, Bardia; Fitoussi, Joseph; Meraghni, Fodil; TCHARKHTCHI, Abbas
2014-01-01
The objective of this work is to identify and to analyze the main micro-mechanisms which govern the fatigue behavior of a short glass fiber reinforced polyamide 66 composite through a multi-scale experimental analysis. Tension-tension fatigue tests have been performed at different applied maximum stress and have been analyzed at both microscopic and macroscopic scale. Together with the progressive stiffness reduction, the temperature rise due to self-heating during cyclic loading has been mea...
Antrett, Philipp
2011-01-01
This thesis describes a multidisciplinary, multiscale approach to the analysis of tight gas reservoirs. It focused initially on the facies architecture of a Permian tight gas field in the Southern Permian Basin (SPB), East Frisia, Northern Germany. To improve field development, 3D seismic data, wireline and core data were compared to a reservoir analogue in the Panamint Valley, California, United States. Depositional environments of the Permian Upper Rotliegend II included perennial saline la...
Multi codes and multi-scale analysis for void fraction prediction in hot channel for VVER-1000/V392
International Nuclear Information System (INIS)
Recently, an approach of multi codes and multi-scale analysis is widely applied to study core thermal hydraulic behavior such as void fraction prediction. Better results are achieved by using multi codes or coupling codes such as PARCS and RELAP5. The advantage of multi-scale analysis is zooming of the interested part in the simulated domain for detail investigation. Therefore, in this study, the multi codes between MCNP5, RELAP5, CTF and also the multi-scale analysis based RELAP5 and CTF are applied to investigate void fraction in hot channel of VVER-1000/V392 reactor. Since VVER-1000/V392 reactor is a typical advanced reactor that can be considered as the base to develop later VVER-1200 reactor, then understanding core behavior in transient conditions is necessary in order to investigate VVER technology. It is shown that the item of near wall boiling, Γw in RELAP5 proposed by Lahey mechanistic method may not give enough accuracy of void fraction prediction as smaller scale code as CTF. (author)
Saether, Erik; Hochhalter, Jacob D.; Glaessgen, Edward H.; Mishin, Yuri
2014-01-01
A multiscale modeling methodology is developed for structurally-graded material microstructures. Molecular dynamic (MD) simulations are performed at the nanoscale to determine fundamental failure mechanisms and quantify material constitutive parameters. These parameters are used to calibrate material processes at the mesoscale using discrete dislocation dynamics (DD). Different grain boundary interactions with dislocations are analyzed using DD to predict grain-size dependent stress-strain behavior. These relationships are mapped into crystal plasticity (CP) parameters to develop a computationally efficient finite element-based DD/CP model for continuum-level simulations and complete the multiscale analysis by predicting the behavior of macroscopic physical specimens. The present analysis is focused on simulating the behavior of a graded microstructure in which grain sizes are on the order of nanometers in the exterior region and transition to larger, multi-micron size in the interior domain. This microstructural configuration has been shown to offer improved mechanical properties over homogeneous coarse-grained materials by increasing yield stress while maintaining ductility. Various mesoscopic polycrystal models of structurally-graded microstructures are generated, analyzed and used as a benchmark for comparison between multiscale DD/CP model and DD predictions. A final series of simulations utilize the DD/CP analysis method exclusively to study macroscopic models that cannot be analyzed by MD or DD methods alone due to the model size.
Multi-scale analysis and characterization of the ITER pre-compression rings
Foussat, A.; Park, B.; Rajainmaki, H.
2014-01-01
The toroidal field (TF) system of ITER Tokamak composed of 18 "D" shaped Toroidal Field (TF) coils during an operating scenario experiences out-of-plane forces caused by the interaction between the 68kA operating TF current and the poloidal magnetic fields. In order to keep the induced static and cyclic stress range in the intercoil shear keys between coils cases within the ITER allowable limits [1], centripetal preload is introduced by means of S2 fiber-glass/epoxy composite pre-compression rings (PCRs). Those PCRs consist in two sets of three rings, each 5 m in diameter and 337 × 288 mm in cross-section, and are installed at the top and bottom regions to apply a total resultant preload of 70 MN per TF coil equivalent to about 400 MPa hoop stress. Recent developments of composites in the aerospace industry have accelerated the use of advanced composites as primary structural materials. The PCRs represent one of the most challenging composite applications of large dimensions and highly stressed structures operating at 4 K over a long term life. Efficient design of those pre-compression composite structures requires a detailed understanding of both the failure behavior of the structure and the fracture behavior of the material. Due to the inherent difficulties to carry out real scale testing campaign, there is a need to develop simulation tools to predict the multiple complex failure mechanisms in pre-compression rings. A framework contract was placed by ITER Organization with SENER Ingenieria y Sistemas SA to develop multi-scale models representative of the composite structure of the Pre-compression rings based on experimental material data. The predictive modeling based on ABAQUS FEM provides the opportunity both to understand better how PCR composites behave in operating conditions and to support the development of materials by the supplier with enhanced performance to withstand the machine design lifetime of 30,000 cycles. The multi-scale stress analysis has
Pineda, Evan J.; Waas, Anthony M.; Berdnarcyk, Brett A.; Arnold, Steven M.; Collier, Craig S.
2009-01-01
This preliminary report demonstrates the capabilities of the recently developed software implementation that links the Generalized Method of Cells to explicit finite element analysis by extending a previous development which tied the generalized method of cells to implicit finite elements. The multiscale framework, which uses explicit finite elements at the global-scale and the generalized method of cells at the microscale is detailed. This implementation is suitable for both dynamic mechanics problems and static problems exhibiting drastic and sudden changes in material properties, which often encounter convergence issues with commercial implicit solvers. Progressive failure analysis of stiffened and un-stiffened fiber-reinforced laminates subjected to normal blast pressure loads was performed and is used to demonstrate the capabilities of this framework. The focus of this report is to document the development of the software implementation; thus, no comparison between the results of the models and experimental data is drawn. However, the validity of the results are assessed qualitatively through the observation of failure paths, stress contours, and the distribution of system energies.
Baumert, Mathias; Javorka, Michal; Seeck, Andrea; Faber, Renaldo; Sanders, Prashanthan; Voss, Andreas
2012-03-01
Pregnancy leads to physiological changes in various parameters of the cardiovascular system. The aim of this study was to investigate longitudinal changes in the structure and complexity of heart rate variability (HRV) and QT interval variability during the second half of normal gestation. We analysed 30-min high-resolution ECGs recorded monthly in 32 pregnant women, starting from the 20th week of gestation. Heart rate and QT variability were quantified using multiscale entropy (MSE) and detrended fluctuation analyses (DFA). DFA of HRV showed significantly higher scaling exponents towards the end of gestation (p<0.0001). MSE analysis showed a significant decrease in sample entropy of HRV with progressing gestation on scales 1-4 (p<0.05). MSE analysis and DFA of QT interval time series revealed structures significantly different from those of HRV with no significant alteration during the second half of gestation. In conclusion, pregnancy is associated with increases in long-term correlations and regularity of HRV, but it does not affect QT variability. The structure of QT time series is significantly different from that of RR time series, despite its close physiological dependence. PMID:21530956
Liu, An-Bang; Wu, Hsien-Tsai; Liu, Chun-Wei; Liu, Cyuan-Cin; Tang, Chieh-Ju; Tsai, I-Ting; Sun, Cheuk-Kwan
2015-01-01
We applied multiscale entropy (MSE) to assess variation in crest time (CT), a parameter in arterial waveform analysis, in diagnosing patients with diabetes. Data on digital volume pulse were obtained from 93 individuals in three groups [Healthy young (Group 1, 20 40, n = 30), and diabetic (Group 3, n = 33) subjects]. Crest time, normalized crest time, crest time ratio (CTR), small- and large-scale MSE on CT [MSESS(CT) and MSELS(CT), respectively] were computed and correlated with anthropometric (i.e., body weight/height, waist circumference), hemodynamic (i.e., blood pressure), and biochemical parameters (i.e., serum triglyceride, high-density lipoprotein, fasting blood sugar, and glycosylated hemoglobin). The results demonstrated higher variability in CT in healthy subjects (Groups 1 and 2) compared with that in diabetic patients (Group 3) as reflected in significantly elevated MSESS(CT) and MSELS(CT) in the former (p < 0.003 and p < 0.001, respectively). MSELS(CT) also showed significant association with waist circumference and fasting blood sugar (i.e., two diagnostic criteria of metabolic syndrome) as well as glycosylated hemoglobin concentration. In conclusion, using MSE analysis for assessing CT variation successfully distinguished diabetic patients from healthy subjects. MSESS(CT) and MSELS(CT) therefore may serve as noninvasive tools for identifying subjects with diabetes and those at risk. PMID:25351478
Multiscale integral analysis of a HT leakage in a fusion nuclear power plant
Velarde, M.; Fradera, J.; Perlado, J. M.; Zamora, I.; Martínez-Saban, E.; Colomer, C.; Briani, P.
2016-05-01
The present work presents an example of the application of an integral methodology based on a multiscale analysis that covers the whole tritium cycle within a nuclear fusion power plant, from a micro scale, analyzing key components where tritium is leaked through permeation, to a macro scale, considering its atmospheric transport. A leakage from the Nuclear Power Plants, (NPP) primary to the secondary side of a heat exchanger (HEX) is considered for the present example. Both primary and secondary loop coolants are assumed to be He. Leakage is placed inside the HEX, leaking tritium in elementary tritium (HT) form to the secondary loop where it permeates through the piping structural material to the exterior. The Heating Ventilation and Air Conditioning (HVAC) system removes the leaked tritium towards the NPP exhaust. The HEX is modelled with system codes and coupled to Computational Fluid Dynamic (CFD) to account for tritium dispersion inside the nuclear power plants buildings and in site environment. Finally, tritium dispersion is calculated with an atmospheric transport code and a dosimetry analysis is carried out. Results show how the implemented methodology is capable of assessing the impact of tritium from the microscale to the atmospheric scale including the dosimetric aspect.
Directory of Open Access Journals (Sweden)
Johan Debayle
2011-05-01
Full Text Available An image analysis method has been developed in order to compute the velocity field of a granular medium (sand grains, mean diameter 600 μm submitted to different kinds of mechanical stresses. The differential method based on optical flow conservation consists in describing a dense motion field with vectors associated to each pixel. A multiscale, coarse-to-fine, analytical approach through tailor sized windows yields the best compromise between accuracy and robustness of the results, while enabling an acceptable computation time. The corresponding algorithmis presented and its validation discussed through different tests. The results of the validation tests of the proposed approach show that the method is satisfactory when attributing specific values to parameters in association with the size of the image analysis window. An application in the case of vibrated sand has been studied. An instrumented laboratory device provides sinusoidal vibrations and enables external optical observations of sand motion in 3D transparent boxes. At 50 Hz, by increasing the relative acceleration G, the onset and development of two convective rolls can be observed. An ultra fast camera records the grain avalanches, and several pairs of images are analysed by the proposed method. The vertical velocity profiles are deduced and allow to precisely quantify the dimensions of the fluidized region as a function of G.
Directory of Open Access Journals (Sweden)
Wen-Yao Pan
2015-01-01
Full Text Available Obstructive sleep apnea (OSA is an independent cardiovascular risk factor to which autonomic nervous dysfunction has been reported to be an important contributor. Ninety subjects recruited from the sleep center of a single medical center were divided into four groups: normal snoring subjects without OSA (apnea hypopnea index, AHI < 5, n = 11, mild OSA (5 ≤ AHI < 15, n = 10, moderate OSA (15 ≤ AHI < 30, n = 24, and severe OSA (AHI ≥ 30, n = 45. Demographic (i.e., age, gender, anthropometric (i.e., body mass index, neck circumference, and polysomnographic (PSG data were recorded and compared among the different groups. For each subject, R-R intervals (RRI from 10 segments of 10-minute electrocardiogram recordings during non-rapid eye movement sleep at stage N2 were acquired and analyzed for heart rate variability (HRV and sample entropy using multiscale entropy index (MEI that was divided into small scale (MEISS, scale 1–5 and large scale (MEILS, scale 6–10. Our results not only demonstrated that MEISS could successfully distinguish normal snoring subjects and those with mild OSA from those with moderate and severe disease, but also revealed good correlation between MEISS and AHI with Spearman correlation analysis (r = −0.684, p < 0.001. Therefore, using the two parameters of EEG and ECG, MEISS may serve as a simple preliminary screening tool for assessing the severity of OSA before proceeding to PSG analysis.
Rong, Libin; Perelson, Alan S
2013-09-01
Chronic hepatitis C virus (HCV) infection remains a world-wide public health problem. Therapy with interferon and ribavirin leads to viral elimination in less than 50% of treated patients. New treatment options aiming at a higher cure rate are focused on direct-acting antiviral agents (DAAs), which directly interfere with different steps in the HCV life cycle. In this paper, we describe and analyze a recently developed multiscale model that predicts HCV dynamics under therapy with DAAs. The model includes both intracellular viral RNA replication and extracellular viral infection. We calculate the steady states of the model and perform a detailed stability analysis. With certain assumptions we obtain analytical approximations of the viral load decline after treatment initiation. One approximation agrees well with the prediction of the model, and can conveniently be used to fit patient data and estimate parameter values. We also discuss other possible ways to incorporate intracellular viral dynamics into the multiscale model.
A Systemic Analysis of Multiscale Deep Convective Variability over the Tropical Pacific.
Tung, Wen-Wen; Moncrieff, Mitchell W.; Gao, Jian-Bo
2004-07-01
The multiscale tropical deep convective variability over the Pacific Ocean is examined with the 4-month high-resolution deep convection index (ITBB) derived from satellite imagery. With a systemic view, the complex phenomenon is described with succinct parameters known as generalized dimensions associated with the correlation structures embedded in the observed time series, with higher-order dimensions emphasizing extreme convective events. It is suggested that convective activities of lifetimes ranging from 1 h to 21 days have interdependence across scales that can be described by a series of power laws; hence, a spectrum of generalized dimensions, that is, the ITBB time series is multifractal. The spatiotemporal features of the ITBB time series is preliminarily examined by changing the spatial domain from 0.1° × 0.1° to 25° × 25°. The multifractal features are weakened with increasing strength of spatial averaging but cannot be eliminated. Furthermore, the ITBB data has the property of long-range dependency, implying that its autocorrelation function decays with a power law in contrast to the zero or exponentially decaying autocorrelation functions for white and commonly used red noise processes generated from autoregressive models. Physically, this means that intensified convection tends to be followed by another intensified event, and vice versa for weakened events or droughts. Such tendency is stronger with larger domain averaging, probably due to more complete inclusion of larger-scale variability that has more definite trends, such as the supercloud clusters associated with the Madden Julian oscillation (MJO). The evolution of cloud clusters within an MJO event is studied by following the MJO system across the analysis domain for 21 days. Convective activities along the front, center, and rear parts of the MJO event continuously intensify while approaching the date line, indicating multifractal features in the range of 1 h to about 5 10 days
Multi-scale Analysis of MEMS Sensors Subject to Drop Impacts
Directory of Open Access Journals (Sweden)
Sarah Zerbini
2007-09-01
Full Text Available The effect of accidental drops on MEMS sensors are examined within the frame-work of a multi-scale finite element approach. With specific reference to a polysilicon MEMSaccelerometer supported by a naked die, the analysis is decoupled into macro-scale (at dielength-scale and meso-scale (at MEMS length-scale simulations, accounting for the verysmall inertial contribution of the sensor to the overall dynamics of the device. Macro-scaleanalyses are adopted to get insights into the link between shock waves caused by the impactagainst a target surface and propagating inside the die, and the displacement/acceleration his-tories at the MEMS anchor points. Meso-scale analyses are adopted to detect the most stresseddetails of the sensor and to assess whether the impact can lead to possible localized failures.Numerical results show that the acceleration at sensor anchors cannot be considered an ob-jective indicator for drop severity. Instead, accurate analyses at sensor level are necessary toestablish how MEMS can fail because of drops.
Gierałtowski, J.; Żebrowski, J. J.; Baranowski, R.
2012-02-01
Human heart rate variability, in the form of time series of intervals between heart beats, shows complex, fractal properties. Recently, it was demonstrated many times that the fractal properties vary from point to point along the series, leading to multifractality. In this paper, we concentrate not only on the fact that the human heart rate has multifractal properties but also that these properties depend on the time scale in which the multifractality is measured. This time scale is related to the frequency band of the signal. We find that human heart rate variability appears to be far more complex than hitherto reported in the studies using a fixed time scale. We introduce a method called multiscale multifractal analysis (MMA), which allows us to extend the description of heart rate variability to include the dependence on the magnitude of the variability and time scale (or frequency band). MMA is relatively immune to additive noise and nonstationarity, including the nonstationarity due to inclusions into the time series of events of a different dynamics (e.g., arrhythmic events in sinus rhythm). The MMA method may provide new ways of measuring the nonlinearity of a signal, and it may help to develop new methods of medical diagnostics.
Directory of Open Access Journals (Sweden)
Brian J. Gow
2015-11-01
Full Text Available Multiscale entropy (MSE is a widely used metric for characterizing the nonlinear dynamics of physiological processes. Significant variability, however, exists in the methodological approaches to MSE which may ultimately impact results and their interpretations. Using publications focused on balance-related center of pressure (COP dynamics, we highlight sources of methodological heterogeneity that can impact study findings. Seventeen studies were systematically identified that employed MSE for characterizing COP displacement dynamics. We identified five key methodological procedures that varied significantly between studies: (1 data length; (2 frequencies of the COP dynamics analyzed; (3 sampling rate; (4 point matching tolerance and sequence length; and (5 filtering of displacement changes from drifts, fidgets, and shifts. We discuss strengths and limitations of the various approaches employed and supply flowcharts to assist in the decision making process regarding each of these procedures. Our guidelines are intended to more broadly inform the design and analysis of future studies employing MSE for continuous time series, such as COP.
Multiscale entropy analysis of biological signals: a fundamental bi-scaling law.
Gao, Jianbo; Hu, Jing; Liu, Feiyan; Cao, Yinhe
2015-01-01
Since introduced in early 2000, multiscale entropy (MSE) has found many applications in biosignal analysis, and been extended to multivariate MSE. So far, however, no analytic results for MSE or multivariate MSE have been reported. This has severely limited our basic understanding of MSE. For example, it has not been studied whether MSE estimated using default parameter values and short data set is meaningful or not. Nor is it known whether MSE has any relation with other complexity measures, such as the Hurst parameter, which characterizes the correlation structure of the data. To overcome this limitation, and more importantly, to guide more fruitful applications of MSE in various areas of life sciences, we derive a fundamental bi-scaling law for fractal time series, one for the scale in phase space, the other for the block size used for smoothing. We illustrate the usefulness of the approach by examining two types of physiological data. One is heart rate variability (HRV) data, for the purpose of distinguishing healthy subjects from patients with congestive heart failure, a life-threatening condition. The other is electroencephalogram (EEG) data, for the purpose of distinguishing epileptic seizure EEG from normal healthy EEG. PMID:26082711
Multiscale analysis of heat transfer in coated fuel particle compacts – Application to the HTTR
International Nuclear Information System (INIS)
Highlights: • Heat diffusion in heterogeneous materials is modeled using multiple-scales analysis. • High order expansion is performed, and enables the evaluation of macro- and micro-scale features. • Non-linear effects due to the temperature-dependent thermal conductivities are considered. • The accuracy is validated: weak scale separation and different micro-scale lattice are investigated. • Results are presented for fuel compacts at various operating temperatures and fuel EFPDs. - Abstract: Heat conduction in coated fuel particles compacts is modeled for a nuclear application. In order to take into account the multi-scale features of the heterogeneous material, the homogenization method is used to evaluate macro- as well as micro-scale temperature fluctuations. The method is validated against direct computations of the temperature field for simple configurations, and is shown to be robust with respect to the micro-scale lattice used in the homogenization procedure. Non-linear effects due to the temperature dependence of thermal conductivities are taken into account in the model
Applying Multiscale Entropy to the Complexity Analysis of Rainfall-Runoff Relationships
Directory of Open Access Journals (Sweden)
Chien-Ming Chou
2012-05-01
Full Text Available This paper presents a novel framework for the complexity analysis of rainfall, runoff, and runoff coefficient (RC time series using multiscale entropy (MSE. The MSE analysis of RC time series was used to investigate changes in the complexity of rainfall-runoff processes due to human activities. Firstly, a coarse graining process was applied to a time series. The sample entropy was then computed for each coarse-grained time series, and plotted as a function of the scale factor. The proposed method was tested in a case study of daily rainfall and runoff data for the upstream Wu–Tu watershed. Results show that the entropy measures of rainfall time series are higher than those of runoff time series at all scale factors. The entropy measures of the RC time series are between the entropy measures of the rainfall and runoff time series at various scale factors. Results also show that the entropy values of rainfall, runoff, and RC time series increase as scale factors increase. The changes in the complexity of RC time series indicate the changes of rainfall-runoff relations due to human activities and provide a reference for the selection of rainfall-runoff models that are capable of dealing with great complexity and take into account of obvious self-similarity can be suggested to the modeling of rainfall-runoff processes. Moreover, the robustness of the MSE results were tested to confirm that MSE analysis is consistent and the same results when removing 25% data, making this approach suitable for the complexity analysis of rainfall, runoff, and RC time series.
Bhattacharjee, Satyaki; Matouš, Karel
2016-05-01
A new manifold-based reduced order model for nonlinear problems in multiscale modeling of heterogeneous hyperelastic materials is presented. The model relies on a global geometric framework for nonlinear dimensionality reduction (Isomap), and the macroscopic loading parameters are linked to the reduced space using a Neural Network. The proposed model provides both homogenization and localization of the multiscale solution in the context of computational homogenization. To construct the manifold, we perform a number of large three-dimensional simulations of a statistically representative unit cell using a parallel finite strain finite element solver. The manifold-based reduced order model is verified using common principles from the machine-learning community. Both homogenization and localization of the multiscale solution are demonstrated on a large three-dimensional example and the local microscopic fields as well as the homogenized macroscopic potential are obtained with acceptable engineering accuracy.
Bayesian hierarchical multi-subject multiscale analysis of functional MRI data.
Sanyal, Nilotpal; Ferreira, Marco A R
2012-11-15
We develop a methodology for Bayesian hierarchical multi-subject multiscale analysis of functional Magnetic Resonance Imaging (fMRI) data. We begin by modeling the brain images temporally with a standard general linear model. After that, we transform the resulting estimated standardized regression coefficient maps through a discrete wavelet transformation to obtain a sparse representation in the wavelet space. Subsequently, we assign to the wavelet coefficients a prior that is a mixture of a point mass at zero and a Gaussian white noise. In this mixture prior for the wavelet coefficients, the mixture probabilities are related to the pattern of brain activity across different resolutions. To incorporate this information, we assume that the mixture probabilities for wavelet coefficients at the same location and level are common across subjects. Furthermore, we assign for the mixture probabilities a prior that depends on a few hyperparameters. We develop an empirical Bayes methodology to estimate the hyperparameters and, as these hyperparameters are shared by all subjects, we obtain precise estimated values. Then we carry out inference in the wavelet space and obtain smoothed images of the regression coefficients by applying the inverse wavelet transform to the posterior means of the wavelet coefficients. An application to computer simulated synthetic data has shown that, when compared to single-subject analysis, our multi-subject methodology performs better in terms of mean squared error. Finally, we illustrate the utility and flexibility of our multi-subject methodology with an application to an event-related fMRI dataset generated by Postle (2005) through a multi-subject fMRI study of working memory related brain activation. PMID:22951257
DEFF Research Database (Denmark)
Dai, Gaoming; Mishnaevsky, Leon, Jr.
2014-01-01
3D numerical simulations of fatigue damage of multiscale fiber reinforced polymer composites with secondary nanoclay reinforcement are carried out. Macro–micro FE models of the multiscale composites are generated automatically using Python based software. The effect of the nanoclay reinforcement...... (localized in the fiber/matrix interface (fiber sizing) and distributed throughout the matrix) on the crack path, damage mechanisms and fatigue behavior is investigated in numerical experiments. It was observed that the composites with secondary nanoreinforcement localized in the fiber sizing ensure higher...
Stability analysis of titanium alloy milling by multiscale entropy and Hurst exponent
Rusinek, Rafał; Borowiec, Marek
2015-10-01
This paper discusses the problem of stability in a milling process for titanium super-alloy Ti6242. The phenomenon of chatter vibration is analysed by the multiscale entropy method and Hurst exponent. Although this problem is often considered based on stability lobe diagrams, theoretical findings do not always agree with experimental results. First, a stability lobe diagram is created based on parameters determined by impact testing. Next, cutting forces are measured in an experiment where the axial cutting depth is gradually increased. Finally, the obtained experimental signals are investigated with respect to stability using the multiscale entropy method and Hurst exponent.
Chenxi, Li; Chen, Yanni; Li, Youjun; Wang, Jue; Liu, Tian
2016-06-01
The multiscale entropy (MSE) is a novel method for quantifying the intrinsic dynamical complexity of physiological systems over several scales. To evaluate this method as a promising way to explore the neural mechanisms in ADHD, we calculated the MSE in EEG activity during the designed task. EEG data were collected from 13 outpatient boys with a confirmed diagnosis of ADHD and 13 age- and gender-matched normal control children during their doing multi-source interference task (MSIT). We estimated the MSE by calculating the sample entropy values of delta, theta, alpha and beta frequency bands over twenty time scales using coarse-grained procedure. The results showed increased complexity of EEG data in delta and theta frequency bands and decreased complexity in alpha frequency bands in ADHD children. The findings of this study revealed aberrant neural connectivity of kids with ADHD during interference task. The results showed that MSE method may be a new index to identify and understand the neural mechanism of ADHD. PMID:26995277
Multiscale Entropy Analysis of the Portevin-Le Chatelier Effect in an Al-2.5%Mg Alloy
Sarkar, A.; Barat, P.; Mukherjee, P.
2006-01-01
The complexity of the Portevin-Le Chatelier effect in Al-2.5%Mg polycrystalline samples subjected to uniaxial tensile tests is quantified. Multiscale entropy analysis is carried out on the stress time series data observed during jerky flow to quantify the complexity of the distinct spatiotemporal dynamical regimes. It is shown that for the static type C band, the entropy is very low for all the scales compared to the hopping type B and the propagating type A bands. The results are interpreted...
Huo, Chengyu; Huang, Xiaolin; Zhuang, Jianjun; Hou, Fengzhen; Ni, Huangjing; Ning, Xinbao
2013-09-01
The Poincaré plot is one of the most important approaches in human cardiac rhythm analysis. However, further investigations are still needed to concentrate on techniques that can characterize the dispersion of the points displayed by a Poincaré plot. Based on a modified Poincaré plot, we provide a novel measurement named distribution entropy (DE) and propose a quadrantal multi-scale distribution entropy analysis (QMDE) for the quantitative descriptions of the scatter distribution patterns in various regions and temporal scales. We apply this method to the heartbeat interval series derived from healthy subjects and congestive heart failure (CHF) sufferers, respectively, and find that the discriminations between them are most significant in the first quadrant, which implies significant impacts on vagal regulation brought about by CHF. We also investigate the day-night differences of young healthy people, and it is shown that the results present a clearly circadian rhythm, especially in the first quadrant. In addition, the multi-scale analysis indicates that the results of healthy subjects and CHF sufferers fluctuate in different trends with variation of the scale factor. The same phenomenon also appears in circadian rhythm investigations of young healthy subjects, which implies that the cardiac dynamic system is affected differently in various temporal scales by physiological or pathological factors.
Multi-scale model analysis of boundary layer ozone over East Asia
Directory of Open Access Journals (Sweden)
M. Lin
2009-05-01
Full Text Available This study employs the regional Community Multiscale Air Quality (CMAQ model to examine seasonal and diurnal variations of boundary layer ozone (O_{3} over East Asia. We evaluate the response of model simulations of boundary layer O_{3} to the choice of chemical mechanisms, meteorological fields, boundary conditions, and model resolutions. Data obtained from surface stations, aircraft measurements, and satellites are used to advance understanding of O_{3} chemistry and mechanisms over East Asia and evaluate how well the model represents the observed features. Satellite measurements and model simulations of summertime rainfall are used to assess the impact of the Asian monsoon on O_{3} production. Our results suggest that summertime O_{3} over Central Eastern China is highly sensitive to cloud cover and monsoonal rainfall over this region. Thus, accurate simulation of the East Asia summer monsoon is critical to model analysis of atmospheric chemistry over China. Examination of hourly summertime O_{3} mixing ratios from sites in Japan confirms the important role of diurnal boundary layer fluctuations in controlling ground-level O_{3}. By comparing five different model configurations with observations at six sites, the specific mechanisms responsible for model behavior are identified and discussed. In particular, vertical mixing, urban chemistry, and dry deposition depending on boundary layer height strongly affect model ability to capture observed behavior. Central Eastern China appears to be the most sensitive region in our study to the choice of chemical mechanisms. Evaluation with TRACE-P aircraft measurements reveals that neither the CB4 nor the SAPRC99 mechanisms consistently capture observed behavior of key photochemical oxidants in springtime. However, our analysis finds that SAPRC99 performs somewhat better in simulating mixing ratios of H_{2}O_{2} (hydrogen peroxide
Gow, Brian J.; Chung-Kang Peng; Wayne, Peter M.; Andrew C Ahn
2015-01-01
Multiscale entropy (MSE) is a widely used metric for characterizing the nonlinear dynamics of physiological processes. Significant variability, however, exists in the methodological approaches to MSE which may ultimately impact results and their interpretations. Using publications focused on balance-related center of pressure (COP) dynamics, we highlight sources of methodological heterogeneity that can impact study findings. Seventeen studies were systematically identified that employed MSE f...
Performance Analysis of Multiscale Entropy for the Assessment of ECG Signal Quality
Zhang, Yatao; Wei, Shoushui; Long, Yutao; Liu, Chengyu
2015-01-01
This study explored the performance of multiscale entropy (MSE) for the assessment of mobile ECG signal quality, aiming to provide a reasonable application guideline. Firstly, the MSE for the typical noises, that is, high frequency (HF) noise, low frequency (LF) noise, and power-line (PL) noise, was analyzed. The sensitivity of MSE to the signal to noise ratio (SNR) of the synthetic artificial ECG plus different noises was further investigated. The results showed that the MSE values could ref...
Institute of Scientific and Technical Information of China (English)
Xavier Blanc; Claude Le Bris; Prédéric Legol
2007-01-01
In order to describe a solid which deforms smoothly in some region,but non smoothly in some other region,many multiscale methods have been recently proposed that aim at coupling an atonfistic model (discrete mechanics)with a macroscopic model(continuum mechanics).We provide here a theoretical basis for such a coupling in a one-dimensional setting,in the case of convex energy.
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.
Luo, Shihua; Guo, Fan; Lai, Dejian; Yan, Fang; Tang, Feilai
2015-09-01
Hurst exponent is an important measure of nonlinearity of dynamical time series. In this paper, using rescaled-range (R/S) analysis, multi-fractal detrended fluctuation analysis (MF-DFA) methods, the multiscale Hurst exponent (MHE) and the multiscale generalized Hurst exponent (MGHE) of coarse-grained silicon content ([Si]) time series in blast furnace (BF) hot metal were calculated. First, we collected these [Si] time series from No. 1 BF of Nanchang Iron and Steel Co. and No. 10 BF of Xinyu Iron and Steel Co. in Jiangxi Province, China. Then, we analyzed and compared the estimated Hurst exponents and the generalized Hurst exponent of these observed time series with some simulated time series. Our results show that the observed time series from these BFs have negative correlation with the Hurst exponent less than 0.5, the generalized Hurst exponent H(q) is a nonlinear function of q, and such negative correlation and local various structure persist in their moving averages of the observed time series up to lag 5 or 10.
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. PMID:27225948
Directory of Open Access Journals (Sweden)
Chia-Hsuan Lee
2015-11-01
Full Text Available The goal of this study was to investigate the parameters affecting exergame performance using multi-scale entropy analysis, with the aim of informing the design of exergames for personalized balance training. Test subjects’ center of pressure (COP displacement data were recorded during exergame play to examine their balance ability at varying difficulty levels of a balance-based exergame; the results of a multi-scale entropy-based analysis were then compared to traditional COP indicators. For games involving static posture frames, variation in posture frame travel time was found to significantly affect the complexity of both the anterior-posterior (MSE-AP and medio-lateral (MSE-ML components of balancing movements. However, in games involving dynamic posture frames, only MSE-AP was found to be sensitive to the variation of parameters, namely foot-lifting speed. Findings were comparable to the COP data published by Sun et al., indicating that the use of complexity data is a feasible means of distinguishing between different parameter sets and of understanding how human design considerations must be taken into account in exergame development. Not only can this method be used as another assessment index in the future, it can also be used in the optimization of parameters within the virtual environments of exergames.
Lin, Pei-Feng; Lo, Men-Tzung; Tsao, Jenho; Chang, Yi-Chung; Lin, Chen; Ho, Yi-Lwun
2014-01-01
The heart begins to beat before the brain is formed. Whether conventional hierarchical central commands sent by the brain to the heart alone explain all the interplay between these two organs should be reconsidered. Here, we demonstrate correlations between the signal complexity of brain and cardiac activity. Eighty-seven geriatric outpatients with healthy hearts and varied cognitive abilities each provided a 24-hour electrocardiography (ECG) and a 19-channel eye-closed routine electroencephalography (EEG). Multiscale entropy (MSE) analysis was applied to three epochs (resting-awake state, photic stimulation of fast frequencies (fast-PS), and photic stimulation of slow frequencies (slow-PS)) of EEG in the 1-58 Hz frequency range, and three RR interval (RRI) time series (awake-state, sleep and that concomitant with the EEG) for each subject. The low-to-high frequency power (LF/HF) ratio of RRI was calculated to represent sympatho-vagal balance. With statistics after Bonferroni corrections, we found that: (a) the summed MSE value on coarse scales of the awake RRI (scales 11-20, RRI-MSE-coarse) were inversely correlated with the summed MSE value on coarse scales of the resting-awake EEG (scales 6-20, EEG-MSE-coarse) at Fp2, C4, T6 and T4; (b) the awake RRI-MSE-coarse was inversely correlated with the fast-PS EEG-MSE-coarse at O1, O2 and C4; (c) the sleep RRI-MSE-coarse was inversely correlated with the slow-PS EEG-MSE-coarse at Fp2; (d) the RRI-MSE-coarse and LF/HF ratio of the awake RRI were correlated positively to each other; (e) the EEG-MSE-coarse at F8 was proportional to the cognitive test score; (f) the results conform to the cholinergic hypothesis which states that cognitive impairment causes reduction in vagal cardiac modulation; (g) fast-PS significantly lowered the EEG-MSE-coarse globally. Whether these heart-brain correlations could be fully explained by the central autonomic network is unknown and needs further exploration. PMID:24498375
Directory of Open Access Journals (Sweden)
Pei-Feng Lin
Full Text Available The heart begins to beat before the brain is formed. Whether conventional hierarchical central commands sent by the brain to the heart alone explain all the interplay between these two organs should be reconsidered. Here, we demonstrate correlations between the signal complexity of brain and cardiac activity. Eighty-seven geriatric outpatients with healthy hearts and varied cognitive abilities each provided a 24-hour electrocardiography (ECG and a 19-channel eye-closed routine electroencephalography (EEG. Multiscale entropy (MSE analysis was applied to three epochs (resting-awake state, photic stimulation of fast frequencies (fast-PS, and photic stimulation of slow frequencies (slow-PS of EEG in the 1-58 Hz frequency range, and three RR interval (RRI time series (awake-state, sleep and that concomitant with the EEG for each subject. The low-to-high frequency power (LF/HF ratio of RRI was calculated to represent sympatho-vagal balance. With statistics after Bonferroni corrections, we found that: (a the summed MSE value on coarse scales of the awake RRI (scales 11-20, RRI-MSE-coarse were inversely correlated with the summed MSE value on coarse scales of the resting-awake EEG (scales 6-20, EEG-MSE-coarse at Fp2, C4, T6 and T4; (b the awake RRI-MSE-coarse was inversely correlated with the fast-PS EEG-MSE-coarse at O1, O2 and C4; (c the sleep RRI-MSE-coarse was inversely correlated with the slow-PS EEG-MSE-coarse at Fp2; (d the RRI-MSE-coarse and LF/HF ratio of the awake RRI were correlated positively to each other; (e the EEG-MSE-coarse at F8 was proportional to the cognitive test score; (f the results conform to the cholinergic hypothesis which states that cognitive impairment causes reduction in vagal cardiac modulation; (g fast-PS significantly lowered the EEG-MSE-coarse globally. Whether these heart-brain correlations could be fully explained by the central autonomic network is unknown and needs further exploration.
International Nuclear Information System (INIS)
Despite the recognized importance of the multi-scale spatio-temporal organization of proteins, most computational tools can only access a limited spectrum of time and spatial scales, thereby ignoring the effects on protein behavior of the intricate coupling between the different scales. Starting from a physico-chemical atomistic network of interactions that encodes the structure of the protein, we introduce a methodology based on multi-scale graph partitioning that can uncover partitions and levels of organization of proteins that span the whole range of scales, revealing biological features occurring at different levels of organization and tracking their effect across scales. Additionally, we introduce a measure of robustness to quantify the relevance of the partitions through the generation of biochemically-motivated surrogate random graph models. We apply the method to four distinct conformations of myosin tail interacting protein, a protein from the molecular motor of the malaria parasite, and study properties that have been experimentally addressed such as the closing mechanism, the presence of conserved clusters, and the identification through computational mutational analysis of key residues for binding
Blood Flow Multiscale Phenomena
Agić, Ante; Mijović, Budimir; Nikolić, Tatjana
2007-01-01
The cardiovascular disease is one of most frequent cause deaths in modern society. The objective of this work is analyse the effect of dynamic vascular geometry (curvature, torsion,bifurcation) and pulsatile blood nature on secondary flow, wall shear stress and platelet deposition. The problem was examined as multi-scale physical phenomena using perturbation analysis and numerical modelling. The secondary flow determined as influence pulsatile pressure, vascular tube time-dependen...
Refined Multiscale Fuzzy Entropy based on Standard Deviation for Biomedical Signal Analysis
Azami, Hamed; Fernandez, Alberto; Escudero, Javier
2016-01-01
Multiscale entropy (MSE) has been a prevalent algorithm to quantify the complexity of fluctuations in the local mean value of biomedical time series. Recent developments in the field have tried to improve the MSE by reducing its variability in large scale factors. On the other hand, there has been recent interest in using other statistical moments than the mean, i.e. variance, in the coarse-graining step of the MSE. Building on these trends, here we introduce the so-called refined composite m...
An integrated multi-scale risk analysis procedure for pluvial flooding
Tader, Andreas; Mergili, Martin; Jäger, Stefan; Glade, Thomas; Neuhold, Clemens; Stiefelmeyer, Heinz
2016-04-01
Mitigation of or adaptation to the negative impacts of natural processes on society requires a better understanding of the spatio-temporal distribution not only of the processes themselves, but also of the elements at risk. Information on their values, exposures and vulnerabilities towards the expected impact magnitudes/intensities of the relevant processes is needed. GIS-supported methods are particularly useful for integrated spatio-temporal analyses of natural processes and their potential consequences. Hereby, pluvial floods are of particular concern for many parts of Austria. The overall aim of the present study is to calculate the hazards emanating from pluvial floods, to determine the exposure of given elements at risk, to determine their vulnerabilities towards given pluvial flood hazards and to analyze potential consequences in terms of monetary losses. The whole approach builds on data available on a national scale. We introduce an integrated, multi-scale risk analysis procedure with regard to pluvial flooding. Focusing on the risk to buildings, we firstly exemplify this procedure with a well-documented event in the city of Graz (Austria), in order to highlight the associated potentials and limitations. Secondly, we attempt to predict the possible consequences of pluvial flooding triggered by rainfall events with recurrence intervals of 30, 100 and 300 years. (i) We compute spatially distributed inundation depths using the software FloodArea. Infiltration capacity and surface roughness are estimated from the land cover units given by the official cadastre. Various assumptions are tested with regard to the inflow to the urban sewer system. (ii) Based on the inundation depths and the official building register, we employ a set of rules and functions to deduce the exposure, vulnerability and risk for each building. A risk indicator for each building, expressed as the expected damage associated to a given event, is derived by combining the building value and
Unsupervised DInSAR processing chain for multi-scale displacement analysis
Casu, Francesco; Manunta, Michele
2016-04-01
Earth Observation techniques can be very helpful for the estimation of several sources of ground deformation due to their characteristics of large spatial coverage, high resolution and cost effectiveness. In this scenario, Differential Synthetic Aperture Radar Interferometry (DInSAR) is one of the most effective methodologies for its capability to generate spatially dense deformation maps at both global and local spatial scale, with centimeter to millimeter accuracy. DInSAR exploits the phase difference (interferogram) between SAR image pairs relevant to acquisitions gathered at different times, but with the same illumination geometry and from sufficiently close flight tracks, whose separation is typically referred to as baseline. Among several, the SBAS algorithm is one of the most used DInSAR approaches and it is aimed at generating displacement time series at a multi-scale level by exploiting a set of small baseline interferograms. SBAS, and generally DInSAR, has taken benefit from the large availability of spaceborne SAR data collected along years by several satellite systems, with particular regard to the European ERS and ENVISAT sensors, which have acquired SAR images worldwide during approximately 20 years. Moreover, since 2014 the new generation of Copernicus Sentinel satellites has started to acquire data with a short revisit time (12 days) and a global coverage policy, thus flooding the scientific EO community with an unprecedent amount of data. To efficiently manage such amount of data, proper processing facilities (as those coming from the emerging Cloud Computing technologies) have to be used, as well as novel algorithms aimed at their efficient exploitation have to be developed. In this work we present a set of results achieved by exploiting a recently proposed implementation of the SBAS algorithm, namely Parallel-SBAS (P-SBAS), which allows us to effectively process, in an unsupervised way and in a limited time frame, a huge number of SAR images
Yanchuk, Serhiy; Giacomelli, Giovanni
2015-10-01
Dynamical systems with multiple, hierarchically long-delayed feedback are introduced and studied extending our previous work [Yanchuk and Giacomelli, Phys. Rev. Lett. 112, 174103 (2014)]. Focusing on the phenomenological model of a Stuart-Landau oscillator with two feedbacks, we show the multiscale properties of its dynamics and demonstrate them by means of a space-time representation. For sufficiently long delays, we derive a normal form describing the system close to the destabilization. The space and temporal variables, which are involved in the space-time representation, correspond to suitable time scales of the original system. The physical meaning of the results, together with the interpretation of the description at different scales, is presented and discussed. In particular, it is shown how this representation uncovers hidden multiscale patterns such as spirals or spatiotemporal chaos. The effect of the delay size and the features of the transition between small and large delays is also analyzed. Finally, we comment on the application of the method and on its extension to an arbitrary, but finite, number of delayed feedback terms. PMID:26565300
Multiscale in situ analysis of the role of dyskerin in lung cancer cells.
Fernandez-Garcia, Ignacio; Marcos, Tamara; Muñoz-Barrutia, Arrate; Serrano, Diego; Pio, Ruben; Montuenga, Luis M; Ortiz-de-Solorzano, Carlos
2013-02-01
Dyskerin is one of the three subunits of the telomerase ribonucleoprotein (RNP) complex. Very little is known about the role of dyskerin in the biology of the telomeres in cancer cells. In this study, we use a quantitative, multiscale 3D image-based in situ method and several molecular techniques to show that dyskerin is overexpressed in lung cancer cell lines. Furthermore, we show that dyskerin expression correlates with telomere length both at the cell population level--cells with higher dyskerin expression have short telomeres--and at the single cell level--the shortest telomeres of the cell are spatially associated with areas of concentration of dyskerin proteins. Using this in vitro model, we also show that exogenous increase in dyskerin expression confers resistance to telomere shortening caused by a telomerase inactivating drug. Finally, we show that resistance is achieved by the recovery of telomerase activity associated with dyskerin. In summary, using a novel multiscale image-based in situ method, we show that, in lung cancer cell lines, dyskerin responds to continuous telomere attrition by increasing the telomerase RNP activity, which in turn provides resistance to telomere shortening.
Raghib, M; Levin, S A; Kevrekidis, I G
2010-06-01
We propose a (time) multiscale method for the coarse-grained analysis of collective motion and decision-making in self-propelled particle models of swarms comprising a mixture of 'naïve' and 'informed' individuals. The method is based on projecting the particle configuration onto a single 'meta-particle' that consists of the elongation of the flock together with the mean group velocity and position. We find that the collective states can be associated with the transient and asymptotic transport properties of the random walk followed by the meta-particle, which we assume follows a continuous time random walk (CTRW). These properties can be accurately predicted at the macroscopic level by an advection-diffusion equation with memory (ADEM) whose parameters are obtained from a mean group velocity time series obtained from a single simulation run of the individual-based model.
Giampietro, Mario; Sorman, Alevgül H
2013-01-01
The vast majority of the countries of the world are now facing an imminent energy crisis, particularly the USA, China, India, Japan and EU countries, but also developing countries having to boost their economic growth precisely when more powerful economies will prevent them from using the limited supply of fossil energy. Despite this crisis, current protocols of energy accounting have been developed for dealing with fossil energy exclusively and are therefore not useful for the analysis of alternative energy sources. The first part of the book illustrates the weakness of existing analyses of energy problems: the science of energy was born and developed neglecting the issue of scale. The authors argue that it is necessary to adopt more complex protocols of accounting and analysis in order to generate robust energy scenarios and effective assessments of the quality of alternative energy sources. The second part of the book introduces the concept of energetic metabolism of modern societies and uses empirical res...
Hamano, H.; Nakayama, T.; Fujita, T.; Hori, H.; Tagami, H.
2009-12-01
It is necessary to reduce Greenhouse gases (GHG) emissions drastically to stabilize climate change, and Japan is also required to assess its long-term global warming policy. In achieving the low carbon society and sustainable cities, the numerical evaluation of environmental impacts of the application of different technologies and policies was preliminarily examined by utilizing integrative urban environmental model. This research aims to develop the multi-scale model for urban climate analysis and to evaluate the urban greening effects on energy consumption from household and business sectors. It developed the multi-scale model combined the process-based NIES integrated catchment-based eco-hydrology (NICE) model with the meso-scale meteorological model (Regional Atmospheric Modeling System : RAMS) and urban canopy model to estimate the urban climate mitigation effects by introduction of urban heat environmental mitigation technology and scenario. The numerical simulation conducted with the multi-scale level horizontally consisting regional scale (260×260km with 2km grid) and urban area scale (36×26km with 0.2km grid) against the objective area, Kawasaki city of Japan. The urban canopy model predicts the three dimensional atmospheric conditions including anthropogenic heat effect from household, business and factory sectors. Furthermore the tile method applied into the urban canopy model for the improvement of numerical accuracy and detailed land use information in each grid. The validation of this model was conducted by comparison with the observed air temperature of 29 points in entire Kawasaki area from 1st to 31th of August, 2006. From the quantitative validation of model performance, the coefficient of correlation was 0.72 and the root mean square error was 2.99C. The introduction of patch method into urban canopy model made it possible to calculate the each land use effect, and the accuracy of predicted results was improved against the land use area
Energy Technology Data Exchange (ETDEWEB)
Speck, D E
2008-04-28
The Multiscale Epidemiologic/Economic Simulation and Analysis (MESA) Decision Support System (DSS) is the product of investments that began in FY05 by the Department of Homeland Security (DHS) Science and Technology Directorate and continue today with joint funding by both DHS and the US Department of Agriculture (USDA). The DSS consists of a coupled epidemiologic/economic model, a standalone graphical user interface (GUI) that supports both model setup and post-analysis, and a Scenario Bank archive to store all content related to foreign animal disease (FAD) studies. The MESA epi model is an object-oriented, agent-based, stochastic, spatio-temporal simulator that parametrically models FAD outbreaks and response strategies from initial disease introduction to conclusion over local, regional, and national scales. Through its output database, the epi model couples to an economic model that calculates farm-level impacts from animal infections, responsive control strategies and loss of trade. The MESA architecture contains a variety of internal models that implement the major components of the epi simulation, including disease introduction, intra-herd spread, inter-herd spread (direct and indirect), detection, and various control strategies (movement restrictions, culling, vaccination) in a highly configurable and extensible fashion. MESA development was originally focused to support investigations into the economic and agricultural industry impacts associated with Foot-and-Mouth Disease (FMD outbreaks). However, it has been adapted to other FADs such has Highly Pathogenic Avian Influenza (HPAI), Classical Swine Fever (CSF) and Exotic Newcastle Disease (END). The MESA model is highly parameterized and employs an extensible architecture that permits straightforward addition of new component models (e.g., alternative disease spread approaches) when necessary. Since its inception, MESA has been developed with a requirement to enable simulation of the very large scale
Adjoint Based A Posteriori Analysis of Multiscale Mortar Discretizations with Multinumerics
Tavener, Simon
2013-01-01
In this paper we derive a posteriori error estimates for linear functionals of the solution to an elliptic problem discretized using a multiscale nonoverlapping domain decomposition method. The error estimates are based on the solution of an appropriately defined adjoint problem. We present a general framework that allows us to consider both primal and mixed formulations of the forward and adjoint problems within each subdomain. The primal subdomains are discretized using either an interior penalty discontinuous Galerkin method or a continuous Galerkin method with weakly imposed Dirichlet conditions. The mixed subdomains are discretized using Raviart- Thomas mixed finite elements. The a posteriori error estimate also accounts for the errors due to adjoint-inconsistent subdomain discretizations. The coupling between the subdomain discretizations is achieved via a mortar space. We show that the numerical discretization error can be broken down into subdomain and mortar components which may be used to drive adaptive refinement.Copyright © by SIAM.
Multi-scale analysis of the European airspace using network community detection.
Directory of Open Access Journals (Sweden)
Gérald Gurtner
Full Text Available We show that the European airspace can be represented as a multi-scale traffic network whose nodes are airports, sectors, or navigation points and links are defined and weighted according to the traffic of flights between the nodes. By using a unique database of the air traffic in the European airspace, we investigate the architecture of these networks with a special emphasis on their community structure. We propose that unsupervised network community detection algorithms can be used to monitor the current use of the airspace and improve it by guiding the design of new ones. Specifically, we compare the performance of several community detection algorithms, both with fixed and variable resolution, and also by using a null model which takes into account the spatial distance between nodes, and we discuss their ability to find communities that could be used to define new control units of the airspace.
Multi-scale analysis of the European airspace using network community detection
Gurtner, Gérald; Cipolla, Marco; Lillo, Fabrizio; Mantegna, Rosario Nunzio; Miccichè, Salvatore; Pozzi, Simone
2013-01-01
We show that the European airspace can be represented as a multi-scale traffic network whose nodes are airports, sectors, or navigation points and links are defined and weighted according to the traffic of flights between the nodes. By using a unique database of the air traffic in the European airspace, we investigate the architecture of these networks with a special emphasis on their community structure. We propose that unsupervised network community detection algorithms can be used to monitor the current use of the airspaces and improve it by guiding the design of new ones. Specifically, we compare the performance of three community detection algorithms, also by using a null model which takes into account the spatial distance between nodes, and we discuss their ability to find communities that could be used to define new control units of the airspace.
多尺度几何分析的图像去噪方法综述%Overview on image denoising based on multi-scale geometric analysis
Institute of Scientific and Technical Information of China (English)
李彦; 汪胜前; 邓承志
2011-01-01
Wavelet image denoising has become the most widely classical method in image denoising area, and the concomitant emergence of multi-scale denoising method makes it as a hot spot in the current method of image denoising.This paper gives a overall summary on the current status of image denoising and wavelet denoising, also gives a brief description of the multi-scale geometric analysis and its development.And further more,it takes the detailed analysis and summary of image denoising methods based on multi-scale transform.Based on the understanding of the wavelet transform denoising and multi-scale image denoising,it puts forward on some prospects in the multi-scale image denoising.%小波图像去噪已经成为图像去噪中应用最广泛的经典方法,而随之出现的多尺度变换去噪方法也已是当前图像去噪研究的一个热点.在对目前图像去噪的现状以及小波去噪总体概括的基础上,简要介绍了多尺度几何分析的产生和发展,进一步详细分析和总结了基于多尺度变换的图像去噪方法.基于对小波去噪以及多尺度变换图像去噪问题的理解,提出了对多尺度变换图像去噪方法的一些展望.
Borgdorff, J.; Bona-Casas, C.; Mamonski, M.; Kurowski, K.; Piontek, T.; Bosak, B.; Rycerz, K.; Ciepiela, E.; Gubala, T.; Harezlak, D.; Bubak, M.; Lorenz, E.; Hoekstra, A.G.
2012-01-01
Nature is observed at all scales; with multiscale modeling, scientists bring together several scales for a holistic analysis of a phenomenon. The models on these different scales may require significant but also heterogeneous computational resources, creating the need for distributed multiscale computing. A particularly demanding type of multiscale models, tightly coupled, brings with it a number of theoretical and practical issues. In this contribution, a tightly coupled model of in-stent re...
Morales-Navarrete, Hernán; Segovia-Miranda, Fabián; Klukowski, Piotr; Meyer, Kirstin; Nonaka, Hidenori; Marsico, Giovanni; Chernykh, Mikhail; Kalaidzidis, Alexander; Zerial, Marino; Kalaidzidis, Yannis
2015-01-01
A prerequisite for the systems biology analysis of tissues is an accurate digital three-dimensional reconstruction of tissue structure based on images of markers covering multiple scales. Here, we designed a flexible pipeline for the multi-scale reconstruction and quantitative morphological analysis of tissue architecture from microscopy images. Our pipeline includes newly developed algorithms that address specific challenges of thick dense tissue reconstruction. Our implementation allows for a flexible workflow, scalable to high-throughput analysis and applicable to various mammalian tissues. We applied it to the analysis of liver tissue and extracted quantitative parameters of sinusoids, bile canaliculi and cell shapes, recognizing different liver cell types with high accuracy. Using our platform, we uncovered an unexpected zonation pattern of hepatocytes with different size, nuclei and DNA content, thus revealing new features of liver tissue organization. The pipeline also proved effective to analyse lung and kidney tissue, demonstrating its generality and robustness. DOI: http://dx.doi.org/10.7554/eLife.11214.001 PMID:26673893
Multiscale Simulation Framework for Coupled Fluid Flow and Mechanical Deformation
Energy Technology Data Exchange (ETDEWEB)
Hou, Thomas [California Inst. of Technology (CalTech), Pasadena, CA (United States); Efendiev, Yalchin [Stanford Univ., CA (United States); Tchelepi, Hamdi [Texas A & M Univ., College Station, TX (United States); Durlofsky, Louis [Stanford Univ., CA (United States)
2016-05-24
Our work in this project is aimed at making fundamental advances in multiscale methods for flow and transport in highly heterogeneous porous media. The main thrust of this research is to develop a systematic multiscale analysis and efficient coarse-scale models that can capture global effects and extend existing multiscale approaches to problems with additional physics and uncertainties. A key emphasis is on problems without an apparent scale separation. Multiscale solution methods are currently under active investigation for the simulation of subsurface flow in heterogeneous formations. These procedures capture the effects of fine-scale permeability variations through the calculation of specialized coarse-scale basis functions. Most of the multiscale techniques presented to date employ localization approximations in the calculation of these basis functions. For some highly correlated (e.g., channelized) formations, however, global effects are important and these may need to be incorporated into the multiscale basis functions. Other challenging issues facing multiscale simulations are the extension of existing multiscale techniques to problems with additional physics, such as compressibility, capillary effects, etc. In our project, we explore the improvement of multiscale methods through the incorporation of additional (single-phase flow) information and the development of a general multiscale framework for flows in the presence of uncertainties, compressible flow and heterogeneous transport, and geomechanics. We have considered (1) adaptive local-global multiscale methods, (2) multiscale methods for the transport equation, (3) operator-based multiscale methods and solvers, (4) multiscale methods in the presence of uncertainties and applications, (5) multiscale finite element methods for high contrast porous media and their generalizations, and (6) multiscale methods for geomechanics.
Analysis of Fiber Clustering in Composite Materials Using High-Fidelity Multiscale Micromechanics
Bednarcyk, Brett A.; Aboudi, Jacob; Arnold, Steven M.
2015-01-01
A new multiscale micromechanical approach is developed for the prediction of the behavior of fiber reinforced composites in presence of fiber clustering. The developed method is based on a coupled two-scale implementation of the High-Fidelity Generalized Method of Cells theory, wherein both the local and global scales are represented using this micromechanical method. Concentration tensors and effective constitutive equations are established on both scales and linked to establish the required coupling, thus providing the local fields throughout the composite as well as the global properties and effective nonlinear response. Two nondimensional parameters, in conjunction with actual composite micrographs, are used to characterize the clustering of fibers in the composite. Based on the predicted local fields, initial yield and damage envelopes are generated for various clustering parameters for a polymer matrix composite with both carbon and glass fibers. Nonlinear epoxy matrix behavior is also considered, with results in the form of effective nonlinear response curves, with varying fiber clustering and for two sets of nonlinear matrix parameters.
Novel Materials & Multi-scale Analysis of the Superconducting State in Iron Based Superconductors
Sefat, Athena S.
2015-03-01
The understanding of the fundamental nature of a material's superconducting state is of crucial importance, if superconductors are to fulfill their promise for widespread use in energy-related needs. Our research applies multi-scale characterization techniques to study and probe the nuclear, electronic, and magnetic details of single crystals. The importance of such broad investigative work is demonstrated in our recent publication on praseodymium-doped BaFe2As2 for which non-uniform local distortions through isolated Pr atoms do not provide percolation path superconductivity. For CaFe2As2, it is found that large Fermi-surface reconstruction in the non-magnetic phase causes a non-superconducting ground state, while different crystalline domains with varying lattice parameters are identified. For Cu-doped BaFe2As2 it is found that orthorhombic distortion below Ts leads to magnetically ordered state of FeAs planes, hence no superconductivity. Studies of this nature can yield groundbreaking results by demonstrating that many parameters can compete in a bulk material and even be spatially and electronically non-homogenous on nanometers. This work was primarily supported by the U. S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Science and Engineering Division.
Multiscale Multiphysics Caprock Seal Analysis: A Case Study of the Farnsworth Unit, Texas, USA
Heath, J. E.; Dewers, T. A.; Mozley, P.
2015-12-01
Caprock sealing behavior depends on coupled processes that operate over a variety of length and time scales. Capillary sealing behavior depends on nanoscale pore throats and interfacial fluid properties. Larger-scale sedimentary architecture, fractures, and faults may govern properties of potential "seal-bypass" systems. We present the multiscale multiphysics investigation of sealing integrity of the caprock system that overlies the Morrow Sandstone reservoir, Farnsworth Unit, Texas. The Morrow Sandstone is the target injection unit for an on-going combined enhanced oil recovery-CO2 storage project by the Southwest Regional Partnership on Carbon Sequestration (SWP). Methods include small-to-large scale measurement techniques, including: focused ion beam-scanning electron microscopy; laser scanning confocal microscopy; electron and optical petrography; core examinations of sedimentary architecture and fractures; geomechanical testing; and a noble gas profile through sealing lithologies into the reservoir, as preserved from fresh core. The combined data set is used as part of a performance assessment methodology. The authors gratefully acknowledge the U.S. Department of Energy's (DOE) National Energy Technology Laboratory for sponsoring this project through the SWP under Award No. DE-FC26-05NT42591. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
MRI-Based Multiscale Model for Electromagnetic Analysis in the Human Head with Implanted DBS
Directory of Open Access Journals (Sweden)
Maria Ida Iacono
2013-01-01
Full Text Available Deep brain stimulation (DBS is an established procedure for the treatment of movement and affective disorders. Patients with DBS may benefit from magnetic resonance imaging (MRI to evaluate injuries or comorbidities. However, the MRI radio-frequency (RF energy may cause excessive tissue heating particularly near the electrode. This paper studies how the accuracy of numerical modeling of the RF field inside a DBS patient varies with spatial resolution and corresponding anatomical detail of the volume surrounding the electrodes. A multiscale model (MS was created by an atlas-based segmentation using a 1 mm3 head model (mRes refined in the basal ganglia by a 200 μm2 ex-vivo dataset. Four DBS electrodes targeting the left globus pallidus internus were modeled. Electromagnetic simulations at 128 MHz showed that the peak of the electric field of the MS doubled (18.7 kV/m versus 9.33 kV/m and shifted 6.4 mm compared to the mRes model. Additionally, the MS had a sixfold increase over the mRes model in peak-specific absorption rate (SAR of 43.9 kW/kg versus 7 kW/kg. The results suggest that submillimetric resolution and improved anatomical detail in the model may increase the accuracy of computed electric field and local SAR around the tip of the implant.
Wu, Hsien-Tsai; Hsu, Po-Chun; Lin, Cheng-Feng; Wang, Hou-Jun; Sun, Cheuk-Kwan; Liu, An-Bang; Lo, Men-Tzung; Tang, Chieh-Ju
2011-10-01
This study proposed a dynamic pulse wave velocity (PWV)-based biomedical parameter in assessing the degree of atherosclerosis for the aged and diabetic populations. Totally, 91 subjects were recruited from a single medical institution between July 2009 and October 2010. The subjects were divided into four groups: young healthy adults (Group 1, n = 22), healthy upper middle-aged adults (Group 2, n = 28), type 2 diabetics with satisfactory blood sugar control (Group 3, n = 21), and unsatisfactory blood sugar control (Group 4, n = 20). A self-developed six-channel electrocardiography (ECG)-PWV-based equipment was used to acquire 1000 successive recordings of PWV(foot) values within 30 min. The data, thus, obtained were analyzed with multiscale entropy (MSE). Large-scale MSE index (MEI(LS)) was chosen as the assessment parameter. Not only did MEI(LS) successfully differentiate between subjects in Groups 1 and 2, but it also showed a significant difference between Groups 3 and 4. Compared with the conventional parameter of PWV(foot) and MEI on R-R interval [i.e., MEI(RRI)] in evaluating the degree of atherosclerotic change, the dynamic parameter, MEI(LS) (PWV), could better reflect the impact of age and blood sugar control on the progression of atherosclerosis. PMID:21693413
Performance Analysis of Multiscale Entropy for the Assessment of ECG Signal Quality
Directory of Open Access Journals (Sweden)
Yatao Zhang
2015-01-01
Full Text Available This study explored the performance of multiscale entropy (MSE for the assessment of mobile ECG signal quality, aiming to provide a reasonable application guideline. Firstly, the MSE for the typical noises, that is, high frequency (HF noise, low frequency (LF noise, and power-line (PL noise, was analyzed. The sensitivity of MSE to the signal to noise ratio (SNR of the synthetic artificial ECG plus different noises was further investigated. The results showed that the MSE values could reflect content level of various noises contained in the ECG signals. For the synthetic ECG plus LF noise, the MSE was sensitive to SNR within higher range of scale factor. However, for the synthetic ECG plus HF noise, the MSE was sensitive to SNR within lower range of scale factor. Thus, a recommended scale factor range within 5 to 10 was given. Finally, the results were verified on the real ECG signals, which were derived from MIT-BIH Arrhythmia Database and Noise Stress Test Database. In all, MSE could effectively assess the noise level on the real ECG signals, and this study provided a valuable reference for applying MSE method to the practical signal quality assessment of mobile ECG.
Time-Varying, Multi-Scale Adaptive System Reliability Analysis of Lifeline Infrastructure Networks
Energy Technology Data Exchange (ETDEWEB)
Gearhart, Jared Lee [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Kurtz, Nolan Scot [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2014-09-01
The majority of current societal and economic needs world-wide are met by the existing networked, civil infrastructure. Because the cost of managing such infrastructure is high and increases with time, risk-informed decision making is essential for those with management responsibilities for these systems. To address such concerns, a methodology that accounts for new information, deterioration, component models, component importance, group importance, network reliability, hierarchical structure organization, and efficiency concerns has been developed. This methodology analyzes the use of new information through the lens of adaptive Importance Sampling for structural reliability problems. Deterioration, multi-scale bridge models, and time-variant component importance are investigated for a specific network. Furthermore, both bridge and pipeline networks are studied for group and component importance, as well as for hierarchical structures in the context of specific networks. Efficiency is the primary driver throughout this study. With this risk-informed approach, those responsible for management can address deteriorating infrastructure networks in an organized manner.
Multi-scale and multi-fractal analysis of pressure fluctuation in slurry bubble column bed reactor
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
The Daubechies second order wavelet was applied to decompose pressure fluctuation signals with the gas flux varying from 0.18 to 0.90 m3/h and the solid mass fraction from 0 to 20% and scales 1-9 detail signals and the 9th scale approximation signals. The pressure signals were studied by multi-scale and R/S analysis method. Hurst analysis method was applied to analyze multi-fractal characteristics of different scale signals. The results show that the characteristics of mono-fractal under scale 1 and scale 2, and bi-fractal under scale 3-9 are effective in deducing the hydrodynamics in slurry bubbling flow system. The measured pressure signals are decomposed to micro-scale signals, meso-scale signals and macro-scale signals. Micro-scale and macro-scale signals are of mono-fractal characteristics, and meso-scale signals are of bi-fractal characteristics. By analyzing energy distribution of different scale signals, it is shown that pressure fluctuations mainly reflects meso-scale interaction between the particles and the bubble.
Li, Rui; Wang, Jun
2016-01-01
A financial price model is developed based on the voter interacting system in this work. The Lempel-Ziv complexity is introduced to analyze the complex behaviors of the stock market. Some stock market stylized facts including fat tails, absence of autocorrelation and volatility clustering are investigated for the proposed price model firstly. Then the complexity of fluctuation behaviors of the real stock markets and the proposed price model are mainly explored by Lempel-Ziv complexity (LZC) analysis and multi-scale weighted-permutation entropy (MWPE) analysis. A series of LZC analyses of the returns and the absolute returns of daily closing prices and moving average prices are performed. Moreover, the complexity of the returns, the absolute returns and their corresponding intrinsic mode functions (IMFs) derived from the empirical mode decomposition (EMD) with MWPE is also investigated. The numerical empirical study shows similar statistical and complex behaviors between the proposed price model and the real stock markets, which exhibits that the proposed model is feasible to some extent.
J. Borgdorff; C. Bona-Casas; M. Mamonski; K. Kurowski; T. Piontek; B. Bosak; K. Rycerz; E. Ciepiela; T. Gubala; D. Harezlak; M. Bubak; E. Lorenz; A.G. Hoekstra
2012-01-01
Nature is observed at all scales; with multiscale modeling, scientists bring together several scales for a holistic analysis of a phenomenon. The models on these different scales may require significant but also heterogeneous computational resources, creating the need for distributed multiscale comp
Microstructural analysis of TRISO particles using multi-scale X-ray computed tomography
Energy Technology Data Exchange (ETDEWEB)
Lowe, T., E-mail: tristan.lowe@manchester.ac.uk [Manchester X-ray Imaging Facility, School of Materials, University of Manchester, M13 9PL (United Kingdom); Bradley, R.S. [Manchester X-ray Imaging Facility, School of Materials, University of Manchester, M13 9PL (United Kingdom); Yue, S. [Manchester X-ray Imaging Facility, School of Materials, University of Manchester, M13 9PL (United Kingdom); The Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot, Oxfordshire OX11 0FA (United Kingdom); Barii, K. [School of Mechanical Engineering, University of Manchester, M13 9PL (United Kingdom); Gelb, J. [Zeiss Xradia Inc., Pleasanton, CA (United States); Rohbeck, N. [Manchester X-ray Imaging Facility, School of Materials, University of Manchester, M13 9PL (United Kingdom); Turner, J. [School of Mechanical Engineering, University of Manchester, M13 9PL (United Kingdom); Withers, P.J. [Manchester X-ray Imaging Facility, School of Materials, University of Manchester, M13 9PL (United Kingdom); The Research Complex at Harwell, Rutherford Appleton Laboratory, Didcot, Oxfordshire OX11 0FA (United Kingdom)
2015-06-15
TRISO particles, a composite nuclear fuel built up by ceramic and graphitic layers, have outstanding high temperature resistance. TRISO fuel is the key technology for High Temperature Reactors (HTRs) and the Generation IV Very High Temperature Reactor (VHTR) variant. TRISO offers unparalleled containment of fission products and is extremely robust during accident conditions. An understanding of the thermal performance and mechanical properties of TRISO fuel requires a detailed knowledge of pore sizes, their distribution and interconnectivity. Here 50 nm, nano-, and 1 μm resolution, micro-computed tomography (CT), have been used to quantify non-destructively porosity of a surrogate TRISO particle at the 0.3–10 μm and 3–100 μm scales respectively. This indicates that pore distributions can reliably be measured down to a size approximately 3 times the pixel size which is consistent with the segmentation process. Direct comparison with Scanning Electron Microscopy (SEM) sections indicates that destructive sectioning can introduce significant levels of coarse damage, especially in the pyrolytic carbon layers. Further comparative work is required to identify means of minimizing such damage for SEM studies. Finally since it is non-destructive, multi-scale time-lapse X-ray CT opens the possibility of intermittently tracking the degradation of TRISO structure under thermal cycles or radiation conditions in order to validate models of degradation such as kernel movement. X-ray CT in-situ experimentation of TRISO particles under load and temperature could also be used to understand the internal changes that occur in the particles under accident conditions.
Bush Encroachment Mapping for Africa - Multi-Scale Analysis with Remote Sensing and GIS
Graw, V. A. M.; Oldenburg, C.; Dubovyk, O.
2015-12-01
Bush encroachment describes a global problem which is especially facing the savanna ecosystem in Africa. Livestock is directly affected by decreasing grasslands and inedible invasive species which defines the process of bush encroachment. For many small scale farmers in developing countries livestock represents a type of insurance in times of crop failure or drought. Among that bush encroachment is also a problem for crop production. Studies on the mapping of bush encroachment so far focus on small scales using high-resolution data and rarely provide information beyond the national level. Therefore a process chain was developed using a multi-scale approach to detect bush encroachment for whole Africa. The bush encroachment map is calibrated with ground truth data provided by experts in Southern, Eastern and Western Africa. By up-scaling location specific information on different levels of remote sensing imagery - 30m with Landsat images and 250m with MODIS data - a map is created showing potential and actual areas of bush encroachment on the African continent and thereby provides an innovative approach to map bush encroachment on the regional scale. A classification approach links location data based on GPS information from experts to the respective pixel in the remote sensing imagery. Supervised classification is used while actual bush encroachment information represents the training samples for the up-scaling. The classification technique is based on Random Forests and regression trees, a machine learning classification approach. Working on multiple scales and with the help of field data an innovative approach can be presented showing areas affected by bush encroachment on the African continent. This information can help to prevent further grassland decrease and identify those regions where land management strategies are of high importance to sustain livestock keeping and thereby also secure livelihoods in rural areas.
Microstructural analysis of TRISO particles using multi-scale X-ray computed tomography
Lowe, T.; Bradley, R. S.; Yue, S.; Barii, K.; Gelb, J.; Rohbeck, N.; Turner, J.; Withers, P. J.
2015-06-01
TRISO particles, a composite nuclear fuel built up by ceramic and graphitic layers, have outstanding high temperature resistance. TRISO fuel is the key technology for High Temperature Reactors (HTRs) and the Generation IV Very High Temperature Reactor (VHTR) variant. TRISO offers unparalleled containment of fission products and is extremely robust during accident conditions. An understanding of the thermal performance and mechanical properties of TRISO fuel requires a detailed knowledge of pore sizes, their distribution and interconnectivity. Here 50 nm, nano-, and 1 μm resolution, micro-computed tomography (CT), have been used to quantify non-destructively porosity of a surrogate TRISO particle at the 0.3-10 μm and 3-100 μm scales respectively. This indicates that pore distributions can reliably be measured down to a size approximately 3 times the pixel size which is consistent with the segmentation process. Direct comparison with Scanning Electron Microscopy (SEM) sections indicates that destructive sectioning can introduce significant levels of coarse damage, especially in the pyrolytic carbon layers. Further comparative work is required to identify means of minimizing such damage for SEM studies. Finally since it is non-destructive, multi-scale time-lapse X-ray CT opens the possibility of intermittently tracking the degradation of TRISO structure under thermal cycles or radiation conditions in order to validate models of degradation such as kernel movement. X-ray CT in-situ experimentation of TRISO particles under load and temperature could also be used to understand the internal changes that occur in the particles under accident conditions.
Bender, Jason D.
Understanding hypersonic aerodynamics is important for the design of next-generation aerospace vehicles for space exploration, national security, and other applications. Ground-level experimental studies of hypersonic flows are difficult and expensive; thus, computational science plays a crucial role in this field. Computational fluid dynamics (CFD) simulations of extremely high-speed flows require models of chemical and thermal nonequilibrium processes, such as dissociation of diatomic molecules and vibrational energy relaxation. Current models are outdated and inadequate for advanced applications. We describe a multiscale computational study of gas-phase thermochemical processes in hypersonic flows, starting at the atomic scale and building systematically up to the continuum scale. The project was part of a larger effort centered on collaborations between aerospace scientists and computational chemists. We discuss the construction of potential energy surfaces for the N4, N2O2, and O4 systems, focusing especially on the multi-dimensional fitting problem. A new local fitting method named L-IMLS-G2 is presented and compared with a global fitting method. Then, we describe the theory of the quasiclassical trajectory (QCT) approach for modeling molecular collisions. We explain how we implemented the approach in a new parallel code for high-performance computing platforms. Results from billions of QCT simulations of high-energy N2 + N2, N2 + N, and N2 + O2 collisions are reported and analyzed. Reaction rate constants are calculated and sets of reactive trajectories are characterized at both thermal equilibrium and nonequilibrium conditions. The data shed light on fundamental mechanisms of dissociation and exchange reactions -- and their coupling to internal energy transfer processes -- in thermal environments typical of hypersonic flows. We discuss how the outcomes of this investigation and other related studies lay a rigorous foundation for new macroscopic models for
Multiscale Analysis for Field-Effect Penetration through Two-Dimensional Materials.
Tian, Tian; Rice, Peter; Santos, Elton J G; Shih, Chih-Jen
2016-08-10
Gate-tunable two-dimensional (2D) materials-based quantum capacitors (QCs) and van der Waals heterostructures involve tuning transport or optoelectronic characteristics by the field effect. Recent studies have attributed the observed gate-tunable characteristics to the change of the Fermi level in the first 2D layer adjacent to the dielectrics, whereas the penetration of the field effect through the one-molecule-thick material is often ignored or oversimplified. Here, we present a multiscale theoretical approach that combines first-principles electronic structure calculations and the Poisson-Boltzmann equation methods to model penetration of the field effect through graphene in a metal-oxide-graphene-semiconductor (MOGS) QC, including quantifying the degree of "transparency" for graphene two-dimensional electron gas (2DEG) to an electric displacement field. We find that the space charge density in the semiconductor layer can be modulated by gating in a nonlinear manner, forming an accumulation or inversion layer at the semiconductor/graphene interface. The degree of transparency is determined by the combined effect of graphene quantum capacitance and the semiconductor capacitance, which allows us to predict the ranking for a variety of monolayer 2D materials according to their transparency to an electric displacement field as follows: graphene > silicene > germanene > WS2 > WTe2 > WSe2 > MoS2 > phosphorene > MoSe2 > MoTe2, when the majority carrier is electron. Our findings reveal a general picture of operation modes and design rules for the 2D-materials-based QCs. PMID:27409143
Bari, Vlasta; Valencia, Jose F; Vallverdu, Montserrat; Girardengo, Giulia; Bassani, Tito; Marchi, Andrea; Calvillo, Laura; Caminal, Pere; Cerutti, Sergio; Brink, Paul A; Crotti, Lia; Schwartz, Peter J; Porta, Alberto
2013-01-01
This study assesses complexity of cardiovascular control in patients affected by type-1 variant of long QT (LQT1) syndrome. Complexity was assessed by refined multiscale entropy of heart period (HP) and QT interval variabilities. HP was taken as the time distance between two consecutive R peaks (RR) and QT interval was approximated as the time distance between the R-peak and T-wave apex (RTa) and between R-peak and T-wave end (RTe). RR, RTa and RTe intervals were automatically extracted from 24h Holter recordings and the daytime period was analyzed (from 02:00 to 06:00 PM). Non mutation carrier (NMC) individuals (n=11), utilized as a control group, were taken from the same family line of the mutation carrier (MC) subjects (n=26). We found that, while NMC and MC groups were indistinguishable based on time domain and complexity analyses of RR dynamics, complexity analysis of RTa and RTe variabilities clearly separates the two populations and suggests an impairment in the cardiac control mechanisms acting on the ventricles. PMID:24110995
Xu, Chuang; Chen, Liang; Liu, Xi-kai
2016-04-01
Urban faults in Shenzhen are potential threat to the city security and sustainable development. To improve the knowledge of the Shenzhen fault zone, interpretation and inversion of gravity data were carried out. Bouguer gravity covering the whole Shenzhen city was calculated with a resolution of 1kmx1km. Wavelet multi-scale analysis (MSA) was applied to the Bouguer gravity data to obtain the multilayer residual anomalies corresponding to different depths. In addition, 2D gravity models were constructed along three profiles. The Bouguer gravity anomaly shows a NE-striking high-low-high pattern from northwest to southeast, strongly related to the main faults. According to the result of MSA, the correlation between gravity anomaly and faults is particularly significant from 4 to 12 km depth. The residual gravity with small amplitude in each layer indicates weak tectonic activity in the crust. In the upper layers, positive anomalies along most of faults reveal the upwelling of high-density materials during the past tectonic movements. The multilayer residual anomalies also implicate important information about the faults, such as the vertical extension and the dip direction. The maximum depth of the faults is about 20km. In general, NE-striking faults extend deeper than NW-striking Faults and have a larger dip angle. This study is supported by the National Natural Science Foundation of China (Grant No.41504015) and China Postdoctoral Science Foundation (Grant No.2015M572146).
Gago, Jorge; Martínez-Núñez, Lourdes; Landín, Mariana; Flexas, Jaume; Gallego, Pedro P.
2014-01-01
Background Plant acclimation is a highly complex process, which cannot be fully understood by analysis at any one specific level (i.e. subcellular, cellular or whole plant scale). Various soft-computing techniques, such as neural networks or fuzzy logic, were designed to analyze complex multivariate data sets and might be used to model large such multiscale data sets in plant biology. Methodology and Principal Findings In this study we assessed the effectiveness of applying neuro-fuzzy logic to modeling the effects of light intensities and sucrose content/concentration in the in vitro culture of kiwifruit on plant acclimation, by modeling multivariate data from 14 parameters at different biological scales of organization. The model provides insights through application of 14 sets of straightforward rules and indicates that plants with lower stomatal aperture areas and higher photoinhibition and photoprotective status score best for acclimation. The model suggests the best condition for obtaining higher quality acclimatized plantlets is the combination of 2.3% sucrose and photonflux of 122–130 µmol m−2 s−1. Conclusions Our results demonstrate that artificial intelligence models are not only successful in identifying complex non-linear interactions among variables, by integrating large-scale data sets from different levels of biological organization in a holistic plant systems-biology approach, but can also be used successfully for inferring new results without further experimental work. PMID:24465829
A Multi-scale Approach for CO2 Accounting and Risk Analysis in CO2 Enhanced Oil Recovery Sites
Dai, Z.; Viswanathan, H. S.; Middleton, R. S.; Pan, F.; Ampomah, W.; Yang, C.; Jia, W.; Lee, S. Y.; McPherson, B. J. O. L.; Grigg, R.; White, M. D.
2015-12-01
Using carbon dioxide in enhanced oil recovery (CO2-EOR) is a promising technology for emissions management because CO2-EOR can dramatically reduce carbon sequestration costs in the absence of greenhouse gas emissions policies that include incentives for carbon capture and storage. This study develops a multi-scale approach to perform CO2 accounting and risk analysis for understanding CO2 storage potential within an EOR environment at the Farnsworth Unit of the Anadarko Basin in northern Texas. A set of geostatistical-based Monte Carlo simulations of CO2-oil-water flow and transport in the Marrow formation are conducted for global sensitivity and statistical analysis of the major risk metrics: CO2 injection rate, CO2 first breakthrough time, CO2 production rate, cumulative net CO2 storage, cumulative oil and CH4 production, and water injection and production rates. A global sensitivity analysis indicates that reservoir permeability, porosity, and thickness are the major intrinsic reservoir parameters that control net CO2 injection/storage and oil/CH4 recovery rates. The well spacing (the distance between the injection and production wells) and the sequence of alternating CO2 and water injection are the major operational parameters for designing an effective five-spot CO2-EOR pattern. The response surface analysis shows that net CO2 injection rate increases with the increasing reservoir thickness, permeability, and porosity. The oil/CH4 production rates are positively correlated to reservoir permeability, porosity and thickness, but negatively correlated to the initial water saturation. The mean and confidence intervals are estimated for quantifying the uncertainty ranges of the risk metrics. The results from this study provide useful insights for understanding the CO2 storage potential and the corresponding risks of commercial-scale CO2-EOR fields.
Chen, Jin-Long; Chen, Pin-Fan; Wang, Hung-Ming
2014-07-15
Parameters of glucose dynamics recorded by the continuous glucose monitoring system (CGMS) could help in the control of glycemic fluctuations, which is important in diabetes management. Multiscale entropy (MSE) analysis has recently been developed to measure the complexity of physical and physiological time sequences. A reduced MSE complexity index indicates the increased repetition patterns of the time sequence, and, thus, a decreased complexity in this system. No study has investigated the MSE analysis of glucose dynamics in diabetes. This study was designed to compare the complexity of glucose dynamics between the diabetic patients (n = 17) and the control subjects (n = 13), who were matched for sex, age, and body mass index via MSE analysis using the CGMS data. Compared with the control subjects, the diabetic patients revealed a significant increase (P < 0.001) in the mean (diabetic patients 166.0 ± 10.4 vs. control subjects 93.3 ± 1.5 mg/dl), the standard deviation (51.7 ± 4.3 vs. 11.1 ± 0.5 mg/dl), and the mean amplitude of glycemic excursions (127.0 ± 9.2 vs. 27.7 ± 1.3 mg/dl) of the glucose levels; and a significant decrease (P < 0.001) in the MSE complexity index (5.09 ± 0.23 vs. 7.38 ± 0.28). In conclusion, the complexity of glucose dynamics is decreased in diabetes. This finding implies the reactivity of glucoregulation is impaired in the diabetic patients. Such impairment presenting as an increased regularity of glycemic fluctuating pattern could be detected by MSE analysis. Thus, the MSE complexity index could potentially be used as a biomarker in the monitoring of diabetes. PMID:24808497
Gao, Zhong-Ke; Yang, Yu-Xuan; Zhai, Lu-Sheng; Dang, Wei-Dong; Yu, Jia-Liang; Jin, Ning-De
2016-02-01
High water cut and low velocity vertical upward oil-water two-phase flow is a typical complex system with the features of multiscale, unstable and non-homogenous. We first measure local flow information by using distributed conductance sensor and then develop a multivariate multiscale complex network (MMCN) to reveal the dispersed oil-in-water local flow behavior. Specifically, we infer complex networks at different scales from multi-channel measurements for three typical vertical oil-in-water flow patterns. Then we characterize the generated multiscale complex networks in terms of network clustering measure. The results suggest that the clustering coefficient entropy from the MMCN not only allows indicating the oil-in-water flow pattern transition but also enables to probe the dynamical flow behavior governing the transitions of vertical oil-water two-phase flow.
Multiscale remote sensing analysis to monitor riparian and upland semiarid vegetation
Nguyen, Uyen
The health of natural vegetation communities is of concern due to observed changes in the climatic-hydrological regime and land cover changes particularly in arid and semiarid regions. Monitoring vegetation at multi temporal and spatial scales can be the most informative approach for detecting change and inferring causal agents of change and remediation strategies. Riparian communities are tightly linked to annual stream hydrology, ground water elevations and sediment transport. These processes are subject to varying magnitudes of disturbance overtime and are candidates for multi-scale monitoring. My first research objective focused on the response of vegetation in the Upper San Pedro River, Arizona, to reduced base flows and climate change. I addressed the correlation between riparian vegetation and hydro-climate variables during the last three decades in one of the remaining undammed rivers in the southwestern U.S. Its riparian forest is threatened by the diminishing base flows, attributed by different studies either to increases in evapotranspiration (ET) due to conversion of grasslands to mesquite shrublands in the adjacent uplands, or to increased regional groundwater pumping to serve growing populations in surrounding urban areas and or to some interactions of those causes. Landsat 5 imagery was acquired for pre- monsoon period, when riparian trees had leafed out but before the arrival of summer monsoon rains in July. The result has showed Normalized Difference Vegetation Index (NDVI) values from both Landsat and Moderate Resolution Imaging Spectrometer (MODIS) had significant decreases which positively correlated to river flows, which decreased over the study period, and negatively correlated with air temperatures, which have increased by about 1.4°C from 1904 to the present. The predictions from other studies that decreased river flows could negatively impact the riparian forest were supported by this study. The pre-monsoon Normalized Different Vegetation
Energy Technology Data Exchange (ETDEWEB)
Dombroski, M; Melius, C; Edmunds, T; Banks, L E; Bates, T; Wheeler, R
2008-09-24
This study uses the Multi-scale Epidemiologic Simulation and Analysis (MESA) system developed for foreign animal diseases to assess consequences of nationwide human infectious disease outbreaks. A literature review identified the state of the art in both small-scale regional models and large-scale nationwide models and characterized key aspects of a nationwide epidemiological model. The MESA system offers computational advantages over existing epidemiological models and enables a broader array of stochastic analyses of model runs to be conducted because of those computational advantages. However, it has only been demonstrated on foreign animal diseases. This paper applied the MESA modeling methodology to human epidemiology. The methodology divided 2000 US Census data at the census tract level into school-bound children, work-bound workers, elderly, and stay at home individuals. The model simulated mixing among these groups by incorporating schools, workplaces, households, and long-distance travel via airports. A baseline scenario with fixed input parameters was run for a nationwide influenza outbreak using relatively simple social distancing countermeasures. Analysis from the baseline scenario showed one of three possible results: (1) the outbreak burned itself out before it had a chance to spread regionally, (2) the outbreak spread regionally and lasted a relatively long time, although constrained geography enabled it to eventually be contained without affecting a disproportionately large number of people, or (3) the outbreak spread through air travel and lasted a long time with unconstrained geography, becoming a nationwide pandemic. These results are consistent with empirical influenza outbreak data. The results showed that simply scaling up a regional small-scale model is unlikely to account for all the complex variables and their interactions involved in a nationwide outbreak. There are several limitations of the methodology that should be explored in future
Paz-Ferreiro, Jorge; Marinho, Mara de A.; de Abreu, Cleide A.
2014-05-01
Mono- and multifractal analysis of soil nitrogen adsorption isotherms (NAI) have been proven to be useful, allowing a better characterization of soil surface properties and soil porous system. Multiscale analysis of nitrogen desorption isotherms (NDI), which was less frequently performed, can also provide very valuable information. The multifractal theory was used to analyse both soil adsorption and desorption isotherms from soils developed over contrasting parent material and with different texture. We sampled 32 soil horizons from 6 soil profiles in neighbouring sites from São Paulo State, Brazil. Three of the profiles, developed over sandstone, were sandy loam or loamy, whereas the other three profiles, developed over weathered sediments or basic parent material, were clayey textured. Soil specific surface area (SSA) varied, from about 3.0 to 46 m2 g-1. Surface parameters showed a strong correlation with clay content, but they were not correlated with cation exchange capacity (CEC). The scaling properties of both nitrogen adsorption and desorption isotherms from all the studied soil horizons could be fitted reasonably well with multifractal models. Multifractal parameters from NAIs and NDIs showed great differences. The singularity spectra, f(α) of the desorption isotherms had an asymmetrically long left part and its asymmetry was in general higher compared with adsorption isotherms. Moreover, adsorption isotherms behaved like more clustered measures, showing lower entropy dimension, D1, smaller correlation dimension, D2, and higher heterogeneity than desorption isotherms. Differences in multifractal behaviour of NAIs and NDIs had been proven to be mainly related to the characteristics of the hysteretic loop measured at high relative pressures. Several multifractal parameters extracted from NAIs and NDIs also distinguished between sandy-loam and loam soils and clayey soils. Multifractal parameters calculated from NAIs and NDIs provide new insight to assess
Energy Technology Data Exchange (ETDEWEB)
Wagner, Gregory John (Sandia National Laboratories, Livermore, CA); Collis, Samuel Scott; Templeton, Jeremy Alan (Sandia National Laboratories, Livermore, CA); Lehoucq, Richard B.; Parks, Michael L.; Jones, Reese E. (Sandia National Laboratories, Livermore, CA); Silling, Stewart Andrew; Scovazzi, Guglielmo; Bochev, Pavel B.
2007-10-01
This report is a collection of documents written as part of the Laboratory Directed Research and Development (LDRD) project A Mathematical Framework for Multiscale Science and Engineering: The Variational Multiscale Method and Interscale Transfer Operators. We present developments in two categories of multiscale mathematics and analysis. The first, continuum-to-continuum (CtC) multiscale, includes problems that allow application of the same continuum model at all scales with the primary barrier to simulation being computing resources. The second, atomistic-to-continuum (AtC) multiscale, represents applications where detailed physics at the atomistic or molecular level must be simulated to resolve the small scales, but the effect on and coupling to the continuum level is frequently unclear.
Multi-scale similarity entropy as a complexity descriptor to discriminate healthy to distress foetus
Girault, Jean Marc; Oudjemia, Souad; Voicu, Iulian
2013-01-01
International audience This paper deals with the discrimination between suffering foetuses and normal foetuses by means of a multi-scale similarity entropy. Sample entropy and similarity entropy are evaluated in multi-scale analysis on foetal heart rate signals. Without multi-scale analysis, our results show that only the similarity entropy differentiate suffering foetuses to normal foetuses. Furthermore with the multi-scale analysis, our results show that both the sample entropy and the s...
Multiscale remote sensing analysis to monitor riparian and upland semiarid vegetation
Nguyen, Uyen
The health of natural vegetation communities is of concern due to observed changes in the climatic-hydrological regime and land cover changes particularly in arid and semiarid regions. Monitoring vegetation at multi temporal and spatial scales can be the most informative approach for detecting change and inferring causal agents of change and remediation strategies. Riparian communities are tightly linked to annual stream hydrology, ground water elevations and sediment transport. These processes are subject to varying magnitudes of disturbance overtime and are candidates for multi-scale monitoring. My first research objective focused on the response of vegetation in the Upper San Pedro River, Arizona, to reduced base flows and climate change. I addressed the correlation between riparian vegetation and hydro-climate variables during the last three decades in one of the remaining undammed rivers in the southwestern U.S. Its riparian forest is threatened by the diminishing base flows, attributed by different studies either to increases in evapotranspiration (ET) due to conversion of grasslands to mesquite shrublands in the adjacent uplands, or to increased regional groundwater pumping to serve growing populations in surrounding urban areas and or to some interactions of those causes. Landsat 5 imagery was acquired for pre- monsoon period, when riparian trees had leafed out but before the arrival of summer monsoon rains in July. The result has showed Normalized Difference Vegetation Index (NDVI) values from both Landsat and Moderate Resolution Imaging Spectrometer (MODIS) had significant decreases which positively correlated to river flows, which decreased over the study period, and negatively correlated with air temperatures, which have increased by about 1.4°C from 1904 to the present. The predictions from other studies that decreased river flows could negatively impact the riparian forest were supported by this study. The pre-monsoon Normalized Different Vegetation
DEFF Research Database (Denmark)
Cash, Philip; Hicks, Ben; Culley, Steve
2015-01-01
This paper contributes to improving our understanding of design activity. Specifically the paper uses Activity Theory to enable a multi-scale analysis of the activity of three engineering designers over a period of one month. Correspondingly, this paper represents the first work that explicitly...... investigates design activity across different scales, referred to as macro-, meso- and microscales. In addition to establishing the range of activities and tasks that occur at, and constitute, each scale the underlying relationships between the scales of activity are discussed. Further, the paper elucidates...
Energy Technology Data Exchange (ETDEWEB)
Steed, Chad A [ORNL; Beaver, Justin M [ORNL; BogenII, Paul L. [Google Inc.; Drouhard, Margaret MEG G [ORNL; Pyle, Joshua M [ORNL
2015-01-01
In this paper, we introduce a new visual analytics system, called Matisse, that allows exploration of global trends in textual information streams with specific application to social media platforms. Despite the potential for real-time situational awareness using these services, interactive analysis of such semi-structured textual information is a challenge due to the high-throughput and high-velocity properties. Matisse addresses these challenges through the following contributions: (1) robust stream data management, (2) automated sen- timent/emotion analytics, (3) inferential temporal, geospatial, and term-frequency visualizations, and (4) a flexible drill-down interaction scheme that progresses from macroscale to microscale views. In addition to describing these contributions, our work-in-progress paper concludes with a practical case study focused on the analysis of Twitter 1% sample stream information captured during the week of the Boston Marathon bombings.
Analysis and Visualization of Multi-Scale Astrophysical Simulations using Python and NumPy
Energy Technology Data Exchange (ETDEWEB)
Turk, M.; /KIPAC, Menlo Park
2008-09-30
The study the origins of cosmic structure requires large-scale computer simulations beginning with well-constrained, observationally-determined, initial conditions. We use Adaptive Mesh Refinement to conduct multi-resolution simulations spanning twelve orders of magnitude in spatial dimensions and over twenty orders of magnitude in density. These simulations must be analyzed and visualized in a manner that is fast, accurate, and reproducible. I present 'yt,' a cross-platform analysis toolkit written in Python. 'yt' consists of a data-management layer for transporting and tracking simulation outputs, a plotting layer, a parallel analysis layer for handling mesh-based and particle-based data, as well as several interfaces. I demonstrate how the origins of cosmic structure--from the scale of clusters of galaxies down to the formation of individual stars--can be analyzed and visualized using a NumPy-based toolkit. Additionally, I discuss efforts to port this analysis code to other adaptive mesh refinement data formats, enabling direct comparison of data between research groups using different methods to simulate the same objects.
Multidisciplinary approach and multi-scale elemental analysis and separation chemistry
International Nuclear Information System (INIS)
The development of methods for the analysis of trace elements is an important component of my research activities either for a radiometric measure or mass spectrometric detection. Many studies raise the question of the chemical signature of a sample or a process: eruptive behavior of a volcano, indicator of pollution, ion exchange in vectors vesicles of active principles,... Each time, highly sensitive analytical procedures, accurate and multi-elementary as well as the development of specific protocols were needed. Neutron activation analysis has often been used as reference procedure and allowed to validate the chemical lixiviation and the measurement by ICP-MS. Analysis of radioactive samples requires skills in analysis of trace but also separation chemistry. Two separation methods occupy an important place in the separation chemistry of radionuclides: chromatography and liquid-liquid extraction. The study of extraction of Lanthanide (III) by the oxide octyl (phenyl)-n, N-diisobutyl-carbamoylmethyl phosphine (CMPO) and a calixarene-CMPO led to better understand and quantify the influence of operating conditions on their performance of extraction and selectivity. The high concentration of salts in aqueous solutions required to reason in terms of thermodynamic activities in relying on a comprehensive approach to quantification of deviations from ideality. In order to reduce the amount of waste generated and costs, alternatives to the hydrometallurgical extraction processes were considered using ionic liquids at low temperatures as alternative solvents in biphasic processes. Remaining in this logic of effluent reduction, miniaturization of the liquid-liquid extraction is also study so as to exploit the characteristics of microscopic scale (very large specific surface, short diffusion distances). The miniaturization of chromatographic separations carries the same ambitions of gain of volumes of wastes and reagents. The miniaturization of the separation Uranium
Multiscale Monitoring and Analysis of the Impacts of Rural Land Use Changes on Downstream Flooding
Geris, J.; Ewen, J.; O'Donnell, G.; O'Connell, P. E.
2010-12-01
Recent dramatic flood events in several parts of the world have reignited the debate on the role played by rural land use/management changes (RLUMC). Whereas the effects of RLUMC on runoff generation and flood risk at small scales are often clear, it is difficult to determine how these effects travel through the river network to affect flooding at larger scales downstream. The headwaters of the River Hodder catchment (260 km2) in Northwest England, United Kingdom, have recently undergone widespread RLUMC, including changes in stocking density, blocking of moorland drainage ditches, and woodland planting. An unusually dense nested monitoring network has been set-up so that the effects of RLUMC can be studied at increasing scales, from the process scale (~1 ha) to the meso scale (~100 km2). The stream gauges are nested up to 5 deep. In total there are 27 stream gauges, 7 rain gauges, and 1 weather station. The main effort in analysis has focussed on detecting signals from stocking density changes, by studying pre-change and post-change runoff and river network flows at increasing scales. The field data set available for the analysis is comprehensive but is relatively short (approximately 1 year pre-change and 1 year post-change). Given the natural variability of rainfall and hydrological response, working with such short records is an important challenge, especially as there is an almost universal lack of comprehensive, nested, long-term historical data sets worldwide that could be used to investigate the effects of RLUMC on flooding. An analysis of a commonly used statistical data analysis method (based on data based mechanistic modelling) showed that, for such short records, any change effects from RLUMC are apparently masked by natural variability. In addition, the effects of some types of RLUMC, including changes in stocking density, need several years to be fully established. Analysis methods have therefore been sought that are sensitive to changes in the
Czech, Christopher
The field of meta-materials engineering has largely expanded mechanical design possibilities over the last two decades; some notable design advances include the systematic engineering of negative Poisson's ratio materials and functionally graded materials, materials designed for optimal electronic and thermo-mechanical performances, and the design of materials under uncertainty. With these innovations, the systematic engineering of materials for design-specific uses is becoming more common in industrial and military uses. The motivation for this body of research is the design of the shear beam for a non-pneumatic wheel. Previously, a design optimization of a finite element model of the non-pneumatic wheel was completed, where a linear elastic material was simulated in the shear beam to reduce hysteretic energy losses. As part of the optimization, a set of optimal orthotropic material properties and other geometric properties were identified for the shear beam. Given that no such natural linear elastic material exists, a meta-material can be engineered that meets these properties using the aforementioned tools. However, manufacturing constraints prevent the use of standard homogenization analysis and optimization tools in the engineering of the shear beam due to limitations in the accuracy of the homogenization process for thin materials. In this research, the more general volume averaging analysis is shown to be an accurate tool for meta-material analysis for engineering thin-layered materials. Given an accurate analysis method, several optimization formulations are proposed, and optimality conditions are derived to determine the most mathematically feasible and numerically reliable formulation for topology optimization of a material design problem using a continuous material interpolation over the design domain. This formulation is implemented to engineer meta-materials for problems using the volume averaging analysis, which includes the use of variable linking
New methodologies for multi-scale time-variant reliability analysis of complex lifeline networks
Kurtz, Nolan Scot
The cost of maintaining existing civil infrastructure is enormous. Since the livelihood of the public depends on such infrastructure, its state must be managed appropriately using quantitative approaches. Practitioners must consider not only which components are most fragile to hazard, e.g. seismicity, storm surge, hurricane winds, etc., but also how they participate on a network level using network analysis. Focusing on particularly damaged components does not necessarily increase network functionality, which is most important to the people that depend on such infrastructure. Several network analyses, e.g. S-RDA, LP-bounds, and crude-MCS, and performance metrics, e.g. disconnection bounds and component importance, are available for such purposes. Since these networks are existing, the time state is also important. If networks are close to chloride sources, deterioration may be a major issue. Information from field inspections may also have large impacts on quantitative models. To address such issues, hazard risk analysis methodologies for deteriorating networks subjected to seismicity, i.e. earthquakes, have been created from analytics. A bridge component model has been constructed for these methodologies. The bridge fragilities, which were constructed from data, required a deeper level of analysis as these were relevant for specific structures. Furthermore, chloride-induced deterioration network effects were investigated. Depending on how mathematical models incorporate new information, many approaches are available, such as Bayesian model updating. To make such procedures more flexible, an adaptive importance sampling scheme was created for structural reliability problems. Additionally, such a method handles many kinds of system and component problems with singular or multiple important regions of the limit state function. These and previously developed analysis methodologies were found to be strongly sensitive to the network size. Special network topologies may
Koch, Steven E.; Golus, Robert E.
1988-01-01
This paper presents a statistical analysis of the characteristics of the wavelike activity that occurred over the north-central United States on July 11-12, 1981, using data from the Cooperative Convective Precipitation Experiment in Montana. In particular, two distinct wave episodes of about 8-h duration within a longer (33 h) period of wave activity were studied in detail. It is demonstrated that the observed phenomena display features consistent with those of mesoscale gravity waves. The principles of statistical methods used to detect and track mesoscale gravity waves are discussed together with their limitations.
Multiscale Computing with the Multiscale Modeling Library and Runtime Environment
Borgdorff J.; Mamonski M.; Bosak B.; Groen D.; Ben Belgacem M.; Kurowski K.; Hoekstra A.G.
2013-01-01
We introduce a software tool to simulate multiscale models: The Multiscale Coupling Library and Environment 2 (MUSCLE 2). MUSCLE 2 is a component-based modeling tool inspired by the multiscale modeling and simulation framework, with an easy-to-use API which supports Java, C++, C, and Fortran. We present MUSCLE 2's runtime features, such as its distributed computing capabilities, and its benefits to multiscale modelers. We also describe two multiscale models that use MUSCLE 2 to do distributed...
Evaluation of the landscape surrounding northern bobwhite nest sites: A multiscale analysis
White, C.G.; Schweitzer, Sara H.; Moore, C.T.; Parnell, I.B.; Lewis-Weis, L.A.
2005-01-01
Implementation of the Conservation Reserve Program (CRP) altered the interspersion and abundance of patches of different land-cover types in landscapes of the southeastern United States. Because northern bobwhites (Colinus virginianus) are experiencing significant population declines throughout most of their range, including the Southeast, it is critical to understand the impacts of landscape-scale changes in habitat on their reproductive rates. Our objective was to identify components of landscape structure important in predicting nest site selection by bobwhites at different spatial scales in the Upper Coastal Plain of Georgia. We used a Geographic Information System (GIS) and spatial analysis software to calculate metrics of landscape structure near bobwhite nest sites. Logistic regression was used to model the relationship of nest sites to structure within the surrounding landscape at 4 spatial scales. We found that patch density and open-canopy planted pine were consistently important predictor variables at multiple scales, and other variables were important at various scales. The density of different patch types could be increased by thinning rows of pines in large monotypic stands of closed-canopy planted pine stands. Thinning and creating openings in CRP pine plantations should provide increased nesting opportunities for bobwhites. We interpret the support for other variables in our analysis as an indication that various patch configuration lead to different combinations of landscape structure that provide an acceptable range of habitat conditions for bobwhites.
Multi-scale AM-FM motion analysis of ultrasound videos of carotid artery plaques
Murillo, Sergio; Murray, Victor; Loizou, C. P.; Pattichis, C. S.; Pattichis, Marios; Barriga, E. Simon
2012-03-01
An estimated 82 million American adults have one or more type of cardiovascular diseases (CVD). CVD is the leading cause of death (1 of every 3 deaths) in the United States. When considered separately from other CVDs, stroke ranks third among all causes of death behind diseases of the heart and cancer. Stroke accounts for 1 out of every 18 deaths and is the leading cause of serious long-term disability in the United States. Motion estimation of ultrasound videos (US) of carotid artery (CA) plaques provides important information regarding plaque deformation that should be considered for distinguishing between symptomatic and asymptomatic plaques. In this paper, we present the development of verifiable methods for the estimation of plaque motion. Our methodology is tested on a set of 34 (5 symptomatic and 29 asymptomatic) ultrasound videos of carotid artery plaques. Plaque and wall motion analysis provides information about plaque instability and is used in an attempt to differentiate between symptomatic and asymptomatic cases. The final goal for motion estimation and analysis is to identify pathological conditions that can be detected from motion changes due to changes in tissue stiffness.
Quan Liu; Yi-Feng Chen; Shou-Zen Fan; Maysam F. Abbod; Jiann-Shing Shieh
2015-01-01
In order to build a reliable index to monitor the depth of anesthesia (DOA), many algorithms have been proposed in recent years, one of which is sample entropy (SampEn), a commonly used and important tool to measure the regularity of data series. However, SampEn only estimates the complexity of signals on one time scale. In this study, a new approach is introduced using multiscale entropy (MSE) considering the structure information over different time scales. The entropy values over different...
Kang, Xiaoxu; Jia, Xiaofeng; Geocadin, Romergryko G.; Thakor, Nitish V.; Maybhate, Anil
2009-01-01
Neurological complications after cardiac arrest (CA) can be fatal. Although hypothermia has been shown to be beneficial, understanding the mechanism and establishing neurological outcomes remains challenging because effects of CA and hypothermia are not well characterized. This paper aims to analyze EEG (and the α-rhythms) using multiscale entropy (MSE) to demonstrate the ability of MSE in tracking changes due to hypothermia and compare MSE during early recovery with long-term neurological ex...
Georgopoulos, Panos G.; Isukapalli, Sastry S.
2009-01-01
A conceptual framework is presented for multiscale field/network/agent-based modeling to support human and ecological health risk assessments. This framework is based on the representation of environmental dynamics in terms of interacting networks, agents that move across different networks, fields representing spatiotemporal distributions of physical properties, rules governing constraints and interactions, and actors that make decisions affecting the state of the system. Different determini...
Directory of Open Access Journals (Sweden)
Yu-Ching Shih
2014-04-01
Full Text Available Micro-cantilever sensors are widely used to detect biomolecules, chemical gases, and ionic species. However, the theoretical descriptions and predictive modeling of these devices are not well developed, and lag behind advances in fabrication and applications. In this paper, we present a novel multiscale simulation framework for nanomechanical sensors. This framework, combining density functional theory (DFT calculations and finite element method (FEM analysis, is capable of analyzing molecular adsorption-induced deformation and stress fields in the sensors from the molecular scale to the device scale. Adsorption of alkanethiolate self-assembled monolayer (SAM on the Au(111 surface of the micro-cantilever sensor is studied in detail to demonstrate the applicability of this framework. DFT calculations are employed to investigate the molecular adsorption-induced surface stress upon the gold surface. The 3D shell elements with initial stresses obtained from the DFT calculations serve as SAM domains in the adsorption layer, while FEM is employed to analyze the deformation and stress of the sensor devices. We find that the micro-cantilever tip deflection has a linear relationship with the coverage of the SAM domains. With full coverage, the tip deflection decreases as the molecular chain length increases. The multiscale simulation framework provides a quantitative analysis of the displacement and stress fields, and can be used to predict the response of nanomechanical sensors subjected to complex molecular adsorption.
Intercomparison of the community multiscale air quality model and CALGRID using process analysis.
O'Neill, Susan M; Lamb, Brian K
2005-08-01
This study was designed to examine the similarities and differences between two advanced photochemical air quality modeling systems: EPA Models-3/CMAQ and CALGRID/CALMET. Both modeling systems were applied to an ozone episode that occurred along the I-5 urban corridor in western Washington and Oregon during July 11-14, 1996. Both models employed the same modeling domain and used the same detailed gridded emission inventory. The CMAQ model was run using both the CB-IV and RADM2 chemical mechanisms, while CALGRID was used with the SAPRC-97 chemical mechanism. Outputfrom the Mesoscale Meteorological Model (MM5) employed with observational nudging was used in both models. The two modeling systems, representing three chemical mechanisms and two sets of meteorological inputs, were evaluated in terms of statistical performance measures for both 1- and 8-h average observed ozone concentrations. The results showed that the different versions of the systems were more similar than different, and all versions performed well in the Portland region and downwind of Seattle but performed poorly in the more rural region north of Seattle. Improving the meteorological input into the CALGRID/CALMET system with planetary boundary layer (PBL) parameters from the Models-3/CMAQ meteorology preprocessor (MCIP) improved the performance of the CALGRID/CALMET system. The 8-h ensemble case was often the best performer of all the cases indicating that the models perform better over longer analysis periods. The 1-h ensemble case, derived from all runs, was not necessarily an improvement over the five individual cases, but the standard deviation about the mean provided a measure of overall modeling uncertainty. Process analysis was applied to examine the contribution of the individual processes to the species conservation equation. The process analysis results indicated that the two modeling systems arrive at similar solutions by very different means. Transport rates are faster and exhibit
A Multi-Scaler Recording System and its Application to Radiometric ''Off-Line'' Analysis
International Nuclear Information System (INIS)
In large complex reprocessing plants a great deal has been done over the past few years to provide in-line instrumentation for the contemporary analysis of process stream content and characteristics. However, these instruments have a qualitative rather than a quantitative part to play in the overall control of the plant. Quantitative information, which must be obtained for control and accounting purposes, demands and relies upon the efficient use of laboratory techniques and instrumentation for the precise analysis of representative samples taken from the process streams. These techniques, in particular those involving pulse counting systems, can be made automatic with modern instrumentation, such as will be described, in which the data is obtained in digital form in electronic stores (scalers). To support a large plant there will be many separate counting systems of this kind, independently controlled and therefore having no time correlation between them. The automatic recording system described in the paper provides a common data read-out facility for more than 50 independently operating counting systems, recording scaler data, together with associated sample and system identification and the absolute time occurrence of each read-out. The data can be recorded, in forms suitable for subsequent processing by a computer, on a variety of tape and card punches, serial and parallel printers or magnetic tape. In addition, the whole recording system, including the scalers in any one system, can be checked for correct operation on an automatic routine basis which does not interfere with the operation of other counting systems. It is concluded that the effective quantitative control of a plant rests on a rapid efficient sample analysis under laboratory conditions. It is probable that future developments of ''off-line'' facilities rather than on-line instrumentation will be possible and more worthwhile. The desirable characteristics of instrumentation for such a laboratory
Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine
2014-10-01
The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure
Wu, Guo Rong; Chen, Fuyong; Kang, Dezhi; Zhang, Xiangyang; Marinazzo, Daniele; Chen, Huafu
2011-11-01
Multivariate Granger causality is a well-established approach for inferring information flow in complex systems, and it is being increasingly applied to map brain connectivity. Traditional Granger causality is based on vector autoregressive (AR) or mixed autoregressive moving average (ARMA) model, which are potentially affected by errors in parameter estimation and may be contaminated by zero-lag correlation, notably when modeling neuroimaging data. To overcome this issue, we present here an extended canonical correlation approach to measure multivariate Granger causal interactions among time series. The procedure includes a reduced rank step for calculating canonical correlation analysis (CCA), and extends the definition of causality including instantaneous effects, thus avoiding the potential estimation problems of AR (or ARMA) models. We tested this approach on simulated data and confirmed its practical utility by exploring local network connectivity at different scales in the epileptic brain analyzing scalp and depth-EEG data during an interictal period. PMID:21788178
de Aranzabal, Itziar; Schmitz, María F; Pineda, Francisco D
2009-11-01
Tourism and landscape are interdependent concepts. Nature- and culture-based tourism are now quite well developed activities and can constitute an excellent way of exploiting the natural resources of certain areas, and should therefore be considered as key objectives in landscape planning and management in a growing number of countries. All of this calls for careful evaluation of the effects of tourism on the territory. This article focuses on an integrated spatial method for landscape analysis aimed at quantifying the relationship between preferences of visitors and landscape features. The spatial expression of the model relating types of leisure and recreational preferences to the potential capacity of the landscape to meet them involves a set of maps showing degrees of potential visitor satisfaction. The method constitutes a useful tool for the design of tourism planning and management strategies, with landscape conservation as a reference.
de Aranzabal, Itziar; Schmitz, María F; Pineda, Francisco D
2009-11-01
Tourism and landscape are interdependent concepts. Nature- and culture-based tourism are now quite well developed activities and can constitute an excellent way of exploiting the natural resources of certain areas, and should therefore be considered as key objectives in landscape planning and management in a growing number of countries. All of this calls for careful evaluation of the effects of tourism on the territory. This article focuses on an integrated spatial method for landscape analysis aimed at quantifying the relationship between preferences of visitors and landscape features. The spatial expression of the model relating types of leisure and recreational preferences to the potential capacity of the landscape to meet them involves a set of maps showing degrees of potential visitor satisfaction. The method constitutes a useful tool for the design of tourism planning and management strategies, with landscape conservation as a reference. PMID:19760454
Natoli, J. Y.; Wagner, F.; Ciapponi, A.; Capoulade, J.; Gallais, L.; Commandré, M.
2010-11-01
The mechanism of laser induced damage in optical materials under high power nanosecond laser irradiation is commonly attributed to the presence of precursor centers. Depending on material and laser source, the precursors could have different origins. Some of them are clearly extrinsic, such as impurities or structural defects linked to the fabrication conditions. In most cases the center size ranging from sub-micrometer to nanometer scale does not permit an easy detection by optical techniques before irradiation. Most often, only a post mortem observation of optics permits to proof the local origin of breakdown. Multi-scale analyzes by changing irradiation beam size have been performed to investigate the density, size and nature of laser damage precursors. Destructive methods such as raster scan, laser damage probability plot and morphology studies permit to deduce the precursor densities. Another experimental way to get information on nature of precursors is to use non destructive methods such as photoluminescence and absorption measurements. The destructive and non destructive multiscale studies are also motivated for practical reasons. Indeed LIDT studies of large optics as those used in LMJ or NIF projects are commonly performed on small samples and with table top lasers whose characteristics change from one to another. In these conditions, it is necessary to know exactly the influence of the different experimental parameters and overall the spot size effect on the final data. In this paper, we present recent developments in multiscale characterization and results obtained on optical coatings (surface case) and KDP crystal (bulk case).
Drought analysis using multi-scale standardized precipitation index in the Han River Basin, China
Institute of Scientific and Technical Information of China (English)
Yue-ping XU; Sheng-ji LIN; Yan HUANG; Qin-qing ZHANG; Qi-hua RAN
2011-01-01
Regional drought analysis provides useful information for sustainable water resources management. In this paper, a standardized precipitation index (SPI) at multiple time scales was used to investigate the spatial patterns and trends of drought in the Han River Basin, one of the largest tributaries of Yangtze River, China. It was found that, in terms of drought severity, the upper basin of the Hart River is the least, while the growing trend is the most conspicuous; a less conspicuous growing trend can be observed in the middle basin; and there is an insignificant decreasing trend in the lower basin. Meanwhile, the impact of drought on the Middle Route of the South-to-North Water Transfer Project was investigated, and it is suggested that water intake must be reduced in times of drought, particularly when successive or simultaneous droughts in the upper and middle basins of the Han River Basin occur. The results can provide substantial information for future water allocation schemes of the South-to-North Water Transfer Project.
Analysis of multi-scale systemic risk in Brazil's financial market
Directory of Open Access Journals (Sweden)
Adriana Bruscato Bortoluzzo
2014-06-01
Full Text Available This work analyzes whether the relationship between risk and returns predicted by the Capital Asset Pricing Model (CAPM is valid in the Brazilian stock market. The analysis is based on discrete wavelet decomposition on different time scales. This technique allows to analyze the relationship between different time horizons, since the short-term ones (2 to 4 days up to the long-term ones (64 to 128 days. The results indicate that there is a negative or null relationship between systemic risk and returns for Brazil from 2004 to 2007. As the average excess return of a market portfolio in relation to a risk-free asset during that period was positive, it would be expected this relationship to be positive. That is, higher systematic risk should result in higher excess returns, which did not occur. Therefore, during that period, appropriate compensation for systemic risk was not observed in the Brazilian market. The scales that proved to be most significant to the risk-return relation were the first three, which corresponded to short-term time horizons. When treating differently, year-by-year, and consequently separating positive and negative premiums, some relevance is found, during some years, in the risk/return relation predicted by the CAPM. However, this pattern did not persist throughout the years. Therefore, there is not any evidence strong enough confirming that the asset pricing follows the model.
Korres, W.; Reichenau, T. G.; Schneider, K.
2012-12-01
Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture, influencing the partitioning of solar energy into latent and sensible heat flux as well as the partitioning of precipitation into runoff and percolation. Numerous studies have shown that in addition to natural factors (rainfall, soil, topography etc.) agricultural management is one of the key drivers for spatio-temporal patterns of soil moisture in agricultural landscapes. Interactions between plant growth, soil hydrology and soil nitrogen transformation processes are modeled by using a dynamically coupled modeling approach. The process-based ecohydrological model components of the integrated decision support system DANUBIA are used to identify the important processes and feedbacks determining soil moisture patterns in agroecosystems. Integrative validation of plant growth and surface soil moisture dynamics serves as a basis for a spatially distributed modeling analysis of surface soil moisture patterns in the northern part of the Rur catchment (1100 sq km), Western Germany. An extensive three year dataset (2007-2009) of surface soil moisture-, plant- (LAI, organ specific biomass and N) and soil- (texture, N, C) measurements was collected. Plant measurements were carried out biweekly for winter wheat, maize, and sugar beet during the growing season. Soil moisture was measured with three FDR soil moisture stations. Meteorological data was measured with an eddy flux station. The results of the model validation showed a very good agreement between the modeled plant parameters (biomass, green LAI) and the measured parameters with values between 0.84 and 0.98 (Willmotts index of agreement). The modeled surface soil moisture (0 - 20 cm) showed also a very favorable agreement with the measurements for winter wheat and sugar beet with an RMSE between 1.68 and 3.45 Vol.-%. For maize, the RMSE was less favorable particularly in the 1.5 months prior to harvest. The modeled soil
The U.S. Shale Oil and Gas Resource - a Multi-Scale Analysis of Productivity
O'sullivan, F.
2014-12-01
Over the past decade, the large-scale production of natural gas, and more recently oil, from U.S. shale formations has had a transformative impact on the energy industry. The emergence of shale oil and gas as recoverable resources has altered perceptions regarding both the future abundance and cost of hydrocarbons, and has shifted the balance of global energy geopolitics. However, despite the excitement, shale is a resource in its nascency, and many challenges surrounding its exploitation remain. One of the most significant of these is the dramatic variation in resource productivity across multiple length scales, which is a feature of all of today's shale plays. This paper will describe the results of work that has looked to characterize the spatial and temporal variations in the productivity of the contemporary shale resource. Analysis will be presented that shows there is a strong stochastic element to observed shale well productivity in all the major plays. It will be shown that the nature of this stochasticity is consistent regardless of specific play being considered. A characterization of this stochasticity will be proposed. As a parallel to the discussion of productivity, the paper will also address the issue of "learning" in shale development. It will be shown that "creaming" trends are observable and that although "absolute" well productivity levels have increased, "specific" productivity levels (i.e. considering well and stimulation size) have actually falling markedly in many plays. The paper will also show that among individual operators' well ensembles, normalized well-to-well performance distributions are almost identical, and have remained consistent year-to-year. This result suggests little if any systematic learning regarding the effective management of well-to-well performance variability has taken place. The paper will conclude with an articulation of how the productivity characteristics of the shale resource are impacting on the resources
Semi-convection in the ocean and in stars: A multi-scale analysis
Directory of Open Access Journals (Sweden)
Friedrich Kupka
2015-04-01
Full Text Available Fluid stratified by gravitation can be subject to a number of instabilities which eventually lead to a flow that causes enhanced mixing and transport of heat. The special case where a destabilizing temperature gradient counteracts the action of a stabilizing gradient in molecular weight is of interest to astrophysics (inside stars and giant planets and geophysics (lakes, oceans as well as to some engineering applications. The detailed dynamics of such a system depend on the molecular diffusivities of heat, momentum, and solute as well as system parameters including the ratio of the two gradients to each other. Further important properties are the formation and merging of well-defined layers in the fluid which cannot be derived from linear stability analysis. Moreover, the physical processes operate on a vast range of length and time scales. This has made the case of semi-convection, where a mean temperature gradient destabilizes the stratification while at the same time the mean molecular gradient tends to stabilize it, a challenge to physical modelling and to numerical hydrodynamical simulation. During the MetStröm project the simulation codes ANTARES and MITgcm have been extended such that they can be used for the simulations of such flows. We present a comparison of effective diffusivities derived from direct numerical simulations. For both stars and the oceanic regimes, the Nusselt numbers (scaled diffusivities follow similar relationships. Semi-convection quickly becomes inefficient, because the formation of layers limits vertical mixing. In contrast to the complementary saltfingering, these layers tend to damp instabilities so that effective diffusivities of salinity (concentration are up to two orders of magnitudes smaller than in the former case.
An integrative multi-scale analysis of the dynamic DNA methylation landscape in aging.
Directory of Open Access Journals (Sweden)
Tian Yuan
2015-02-01
Full Text Available Recent studies have demonstrated that the DNA methylome changes with age. This epigenetic drift may have deep implications for cellular differentiation and disease development. However, it remains unclear how much of this drift is functional or caused by underlying changes in cell subtype composition. Moreover, no study has yet comprehensively explored epigenetic drift at different genomic length scales and in relation to regulatory elements. Here we conduct an in-depth analysis of epigenetic drift in blood tissue. We demonstrate that most of the age-associated drift is independent of the increase in the granulocyte to lymphocyte ratio that accompanies aging and that enrichment of age-hypermethylated CpG islands increases upon adjustment for cellular composition. We further find that drift has only a minimal impact on in-cis gene expression, acting primarily to stabilize pre-existing baseline expression levels. By studying epigenetic drift at different genomic length scales, we demonstrate the existence of mega-base scale age-associated hypomethylated blocks, covering approximately 14% of the human genome, and which exhibit preferential hypomethylation in age-matched cancer tissue. Importantly, we demonstrate the feasibility of integrating Illumina 450k DNA methylation with ENCODE data to identify transcription factors with key roles in cellular development and aging. Specifically, we identify REST and regulatory factors of the histone methyltransferase MLL complex, whose function may be disrupted in aging. In summary, most of the epigenetic drift seen in blood is independent of changes in blood cell type composition, and exhibits patterns at different genomic length scales reminiscent of those seen in cancer. Integration of Illumina 450k with appropriate ENCODE data may represent a fruitful approach to identify transcription factors with key roles in aging and disease.
Energy Technology Data Exchange (ETDEWEB)
Li, Dengwang [Shandong Normal University, Jinan, Shandong Province (China); Wang, Qinfen [Shandong Normal University, Jinan, Shandong (China); Li, H; Chen, J [Shandong Cancer Hospital and Institute, Jinan, Shandong (China)
2014-06-01
Purpose: The purpose of this research is studying tumor heterogeneity of the primary and lymphoma by using multi-scale texture analysis with PET-CT images, where the tumor heterogeneity is expressed by texture features. Methods: Datasets were collected from 12 lung cancer patients, and both of primary and lymphoma tumors were detected with all these patients. All patients underwent whole-body 18F-FDG PET/CT scan before treatment.The regions of interest (ROI) of primary and lymphoma tumor were contoured by experienced clinical doctors. Then the ROI of primary and lymphoma tumor is extracted automatically by using Matlab software. According to the geometry size of contour structure, the images of tumor are decomposed by multi-scale method.Wavelet transform was performed on ROI structures within images by L layers sampling, and then wavelet sub-bands which have the same size of the original image are obtained. The number of sub-bands is 3L+1.The gray level co-occurrence matrix (GLCM) is calculated within different sub-bands, thenenergy, inertia, correlation and gray in-homogeneity were extracted from GLCM.Finally, heterogeneity statistical analysis was studied for primary and lymphoma tumor using the texture features. Results: Energy, inertia, correlation and gray in-homogeneity are calculated with our experiments for heterogeneity statistical analysis.Energy for primary and lymphomatumor is equal with the same patient, while gray in-homogeneity and inertia of primaryare 2.59595±0.00855, 0.6439±0.0007 respectively. Gray in-homogeneity and inertia of lymphoma are 2.60115±0.00635, 0.64435±0.00055 respectively. The experiments showed that the volume of lymphoma is smaller than primary tumor, but thegray in-homogeneity and inertia were higher than primary tumor with the same patient, and the correlation with lymphoma tumors is zero, while the correlation with primary tumor isslightly strong. Conclusion: This studying showed that there were effective heterogeneity
Bari, V.; Valencia, Jose Fernando; Vallverdú Ferrer, Montserrat; Girardengo, G.; Bassani, T; A. Marchi; Calvillo, L; Caminal Magrans, Pere; Cerutti, Sergio; Brink, P. A.; Crotti, L.; Schwartz, P. J.; Porta, A.
2013-01-01
This study assesses complexity of cardiovascular control in patients affected by type-1 variant of long QT(LQT1) syndrome. Complexity was assessed by refined multiscale entropy of heart period (HP) and QT interval variabilities. HP was taken as the time distance between two consecutive R peaks (RR) and QT interval was approximated as the time distance between the R-peak and T-wave apex (RTa) and between R-peak and T-wave end (RTe). RR, RTa and RTe intervals were automatically extracted from 2...
Homogenization-based multi-scale damage theory
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
The research of modern mechanics reveals that the damage and failure of structures should be considered on different scales. The present paper is dedicated to establishing the multi-scale damage theory for the nonlinear structural analysis. Starting from the asymptotic expansion based homogenization theory, the multi-scale energy integration is proposed to bridge the gap between the micro and macro scales. By recalling the Helmholtz free energy based damage definition, the damage variable is represented by the multi-scale energy integration. Hence the damage evolution could be numerically simulated on the basis of the unit cell analysis rather than the experimental data identification. Finally the framework of the multi-scale damage theory is established by transforming the multi-scale damage evolution into the conventional continuum damage mechanics. The agree- ment between the simulated results and the benchmark results indicates the validity and effectiveness of the proposed theory.
Directory of Open Access Journals (Sweden)
Jiann-Shing Shieh
2012-11-01
Full Text Available Falls are unpredictable accidents and resulting injuries can be serious to the elderly. A preventative solution can be the use of vibration stimulus of white noise to improve the sense of balance. In this work, a pair of vibration shoes were developed and controlled by a touch-type switch which can generate mechanical vibration noise to stimulate the patient’s feet while wearing the shoes. In order to evaluate the balance stability and treatment effect of vibrating insoles in these shoes, multivariate multiscale entropy (MMSE algorithm is applied to calculate the relative complexity index of reconstructed center of pressure (COP signals in antero-posterior and medio-lateral directions by the multivariate empirical mode decomposition (MEMD. The results show that the balance stability of 61.5% elderly subjects is improved after wearing the developed shoes, which is more than 30.8% using multiscale entropy. In conclusion, MEMD-enhanced MMSE is able to distinguish the smaller differences between before and after the use of vibration shoes in both two directions, which is more powerful than the empirical mode decomposition (EMD-enhanced MSE in each individual direction.
Directory of Open Access Journals (Sweden)
Sandra R. Baptista
2008-12-01
Full Text Available Within the contexts of globalization and the Atlantic Forest ecoregion, I present a multiscale analysis of anthropogenic landscape dynamics in the Florianópolis city-region, Santa Catarina, southern Brazil. Drawing on field research conducted between 2000 and 2004 and a review of the literature, I examined Brazilian demographic and agricultural census data for the period of 1970 to 1995-1996. I hypothesized that economic restructuring, new institutional arrangements, and the valuation of environmental amenities and ecosystem services have contributed to forest recovery trends and thus a forest transition in the city-region. My results indicate that along with rapid urbanization, in-migration, socioeconomic polarization, and segregation, the city-region has experienced the contraction of private agricultural land area, expansion of protected areas, recovery of forests, and conversion of coastal plain ecosystems to built environments. Future analyses of forest transition dynamics should consider the spatial configurations of socioeconomic inequality in city-regions.
Differential geometry based multiscale models.
Wei, Guo-Wei
2010-08-01
Large chemical and biological systems such as fuel cells, ion channels, molecular motors, and viruses are of great importance to the scientific community and public health. Typically, these complex systems in conjunction with their aquatic environment pose a fabulous challenge to theoretical description, simulation, and prediction. In this work, we propose a differential geometry based multiscale paradigm to model complex macromolecular systems, and to put macroscopic and microscopic descriptions on an equal footing. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum mechanical description of the aquatic environment with the microscopic discrete atomistic description of the macromolecule. Multiscale free energy functionals, or multiscale action functionals are constructed as a unified framework to derive the governing equations for the dynamics of different scales and different descriptions. Two types of aqueous macromolecular complexes, ones that are near equilibrium and others that are far from equilibrium, are considered in our formulations. We show that generalized Navier-Stokes equations for the fluid dynamics, generalized Poisson equations or generalized Poisson-Boltzmann equations for electrostatic interactions, and Newton's equation for the molecular dynamics can be derived by the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows. Comparison is given to classical descriptions of the fluid and electrostatic interactions without geometric flow based micro-macro interfaces. The detailed balance of forces is emphasized in the present work. We further extend the proposed multiscale paradigm to micro-macro analysis of electrohydrodynamics, electrophoresis, fuel cells, and ion channels. We derive generalized Poisson-Nernst-Planck equations that are
Multiscale full waveform inversion
Fichtner, Andreas; Trampert, Jeannot; Cupillard, Paul; Saygin, Erdinc; Taymaz, Tuncay; Capdeville, Yann; Villaseñor, Antonio
2013-07-01
We develop and apply a full waveform inversion method that incorporates seismic data on a wide range of spatio-temporal scales, thereby constraining the details of both crustal and upper-mantle structure. This is intended to further our understanding of crust-mantle interactions that shape the nature of plate tectonics, and to be a step towards improved tomographic models of strongly scale-dependent earth properties, such as attenuation and anisotropy. The inversion for detailed regional earth structure consistently embedded within a large-scale model requires locally refined numerical meshes that allow us to (1) model regional wave propagation at high frequencies, and (2) capture the inferred fine-scale heterogeneities. The smallest local grid spacing sets the upper bound of the largest possible time step used to iteratively advance the seismic wave field. This limitation leads to extreme computational costs in the presence of fine-scale structure, and it inhibits the construction of full waveform tomographic models that describe earth structure on multiple scales. To reduce computational requirements to a feasible level, we design a multigrid approach based on the decomposition of a multiscale earth model with widely varying grid spacings into a family of single-scale models where the grid spacing is approximately uniform. Each of the single-scale models contains a tractable number of grid points, which ensures computational efficiency. The multi-to-single-scale decomposition is the foundation of iterative, gradient-based optimization schemes that simultaneously and consistently invert data on all scales for one multi-scale model. We demonstrate the applicability of our method in a full waveform inversion for Eurasia, with a special focus on Anatolia where coverage is particularly dense. Continental-scale structure is constrained by complete seismic waveforms in the 30-200 s period range. In addition to the well-known structural elements of the Eurasian mantle
Multiscale flat norm signatures for shapes and images
Energy Technology Data Exchange (ETDEWEB)
Sandine, Gary [Los Alamos National Laboratory; Morgan, Simon P [Los Alamos National Laboratory; Vixie, Kevin R [WASHINGTON STATE UNIV.; Clawson, Keth [WASHINGTON STATE UNIV.; Asaki, Thomas J [WASHINGTON STATE UNIV.; Price, Brandon [WALLA WALLA UNIV.
2009-01-01
In this paper we begin to explore the application of the multiscale flat norm introduced in Morgan and Vixie to shape and image analysis. In particular, we look at the use of the multiscale flat norm signature for the identification of shapes. After briefly reviewing the multiscale flat norm, the L{sup 1}TV functional and the relation between these two, we introduce multiscale signatures that naturally follow from the multiscale flat norm and its components. A numerical method based on the min-cut, max-flow graph-cut is briefly recalled. We suggest using L{sup 2} minimization, rather than the usual Crofton's formula based approximation, for choosing the required weights. The resulting weights have the dual benefits of being analytically computable and of giving more accurate approximations to the anisotropic TV energy. Finally, we demonstrate the usefulness of the signatures on simple shape classification tasks.
Multicomponent and multiscale systems theory, methods, and applications in engineering
Geiser, Juergen
2016-01-01
This book examines the latest research results from combined multi-component and multi-scale explorations. It provides theory, considers underlying numerical methods, and presents brilliant computational experimentation. Engineering computations featured in this monograph further offer particular interest to many researchers, engineers, and computational scientists working in frontier modeling and applications of multicomponent and multiscale problems. Professor Geiser gives specific attention to the aspects of decomposing and splitting delicate structures and controlling decomposition and the rationale behind many important applications of multi-component and multi-scale analysis. Multicomponent and Multiscale Systems: Theory, Methods, and Applications in Engineering also considers the question of why iterative methods can be powerful and more appropriate for well-balanced multiscale and multicomponent coupled nonlinear problems. The book is ideal for engineers and scientists working in theoretical and a...
Multiscale Computing with the Multiscale Modeling Library and Runtime Environment
J. Borgdorff; M. Mamonski; B. Bosak; D. Groen; M. Ben Belgacem; K. Kurowski; A.G. Hoekstra
2013-01-01
We introduce a software tool to simulate multiscale models: the Multiscale Coupling Library and Environment 2 (MUSCLE 2). MUSCLE 2 is a component-based modeling tool inspired by the multiscale modeling and simulation framework, with an easy-to-use API which supports Java, C++, C, and Fortran. We pre
Distributed infrastructure for multiscale computing
S.J. Zasada; M. Mamonski; D. Groen; J. Borgdorff; I. Saverchenko; T. Piontek; K. Kurowski; P.V. Coveney
2012-01-01
Today scientists and engineers are commonly faced with the challenge of modelling, predicting and controlling multiscale systems which cross scientific disciplines and where several processes acting at different scales coexist and interact. Such multidisciplinary multiscale models, when simulated in
de la Cruz, Roberto; Spill, Fabian; Alarcón, Tomás
2016-01-01
We propose a modelling framework to analyse the stochastic behaviour of heterogeneous, multi-scale cellular populations. We illustrate our methodology with a particular example in which we study a population with an oxygen-regulated proliferation rate. Our formulation is based on an age-dependent stochastic process. Cells within the population are characterised by their age. The age-dependent (oxygen-regulated) birth rate is given by a stochastic model of oxygen-dependent cell cycle progression. We then formulate an age-dependent birth-and-death process, which dictates the time evolution of the cell population. The population is under a feedback loop which controls its steady state size: cells consume oxygen which in turns fuels cell proliferation. We show that our stochastic model of cell cycle progression allows for heterogeneity within the cell population induced by stochastic effects. Such heterogeneous behaviour is reflected in variations in the proliferation rate. Within this set-up, we have established...
Multiscale Thermohydrologic Model
International Nuclear Information System (INIS)
The purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. Thus, the goal is to predict the range of possible thermal-hydrologic conditions across the repository; this is quite different from predicting a single expected thermal-hydrologic response. The MSTHM calculates the following thermal-hydrologic parameters: temperature, relative humidity, liquid-phase saturation, evaporation rate, air-mass fraction, gas-phase pressure, capillary pressure, and liquid- and gas-phase fluxes (Table 1-1). These thermal-hydrologic parameters are required to support ''Total System Performance Assessment (TSPA) Model/Analysis for the License Application'' (BSC 2004 [DIRS 168504]). The thermal-hydrologic parameters are determined as a function of position along each of the emplacement drifts and as a function of waste package type. These parameters are determined at various reference locations within the emplacement drifts, including the waste package and drip-shield surfaces and in the invert. The parameters are also determined at various defined locations in the adjoining host rock. The MSTHM uses data obtained from the data tracking numbers (DTNs) listed in Table 4.1-1. The majority of those DTNs were generated from the following analyses and model reports: (1) ''UZ Flow Model and Submodels'' (BSC 2004 [DIRS 169861]); (2) ''Development of Numerical Grids for UZ Flow and Transport Modeling'' (BSC 2004); (3) ''Calibrated Properties Model'' (BSC 2004 [DIRS 169857]); (4) ''Thermal Conductivity of the Potential Repository Horizon'' (BSC 2004 [DIRS 169854]); (5) ''Thermal Conductivity of the Non-Repository Lithostratigraphic Layers'' (BSC 2004 [DIRS 170033]); (6) ''Ventilation Model and Analysis Report'' (BSC 2004 [DIRS 169862]); (7) ''Heat Capacity
Peridynamic Multiscale Finite Element Methods
Energy Technology Data Exchange (ETDEWEB)
Costa, Timothy [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bond, Stephen D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Littlewood, David John [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Moore, Stan Gerald [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2015-12-01
art of local models with the flexibility and accuracy of the nonlocal peridynamic model. In the mixed locality method this coupling occurs across scales, so that the nonlocal model can be used to communicate material heterogeneity at scales inappropriate to local partial differential equation models. Additionally, the computational burden of the weak form of the peridynamic model is reduced dramatically by only requiring that the model be solved on local patches of the simulation domain which may be computed in parallel, taking advantage of the heterogeneous nature of next generation computing platforms. Addition- ally, we present a novel Galerkin framework, the 'Ambulant Galerkin Method', which represents a first step towards a unified mathematical analysis of local and nonlocal multiscale finite element methods, and whose future extension will allow the analysis of multiscale finite element methods that mix models across scales under certain assumptions of the consistency of those models.
Trunkvalterova, Z; Javorka, M; Tonhajzerova, I; Javorkova, J; Lazarova, Z; Javorka, K; Baumert, M
2008-07-01
Multiscale entropy (MSE) analysis provides information about complexity on various time scales. The aim of this study was to test whether MSE is able to detect autonomic dysregulation in young patients with diabetes mellitus (DM). We analyzed heart rate (HR) oscillations, systolic (SBP) and diastolic blood pressure (DBP) signals in 14 patients with DM type 1 and 14 age- and sex-matched healthy controls. SampEn values (scales 1-10) and linear measures were computed. HR: among the linear measures of heart rate variability significant differences between groups were only found for RMSSD (p = 0.043). MSE was significantly reduced on scales 2 and 3 in DM (p = 0.023 and 0.010, respectively). SBP and DBP: no significant differences were detected with linear measures. In contrast, MSE analysis revealed significantly lower SampEn values in DM on scale 3 (p = 0.039 for SBP; p = 0.015 for DBP). No significant correlations were found between MSE and linear measures. In conclusion, MSE analysis of HR, SBP and DBP oscillations is able to detect subtle abnormalities in cardiovascular control in young patients with DM and is independent of standard linear measures. PMID:18583725
International Nuclear Information System (INIS)
The atomistic finite element method (AFEM) is a multiscale technique where a sequential mode is used to transfer information between two length scales to model and simulate nanostructures at the continuum level. This method is used in this paper to investigate the nonlinear frequency response of a single-layered graphene sheet (SLGS) for impulse and harmonic excitation. The multi-body interatomic Tersoff–Brenner (TB) potential is used to represent the energy between two adjacent carbon atoms. Based on the TB potential, the equivalent geometric and elastic properties of carbon–carbon bonds are derived which are consistent with the material constitutive relations. These properties are used further to derive the nonlinear material model (stress–strain curve) of carbon–carbon bonds based on the force–deflection curve using the multi-body interatomic Tersoff–Brenner potential. A square SLGS is considered and its nonlinear vibration characteristics under an impulse and harmonic excitation for bridged, cantilever and clamped boundary conditions are investigated using the derived nonlinear material model (NMM). Before using the proposed nonlinear material model, the derived equivalent geometric and elastic properties of carbon–carbon bond are validated using molecular dynamics simulation results. The geometric (large deformation) and material nonlinearities are included in the nonlinear frequency response analysis. The investigated results of the nonlinear frequency response analysis are compared with those of the linear frequency response analysis, and the effect of the nonlinear behavior of carbon–carbon bonds on the frequency response of SLGS is studied. (paper)
Dynamic Filtering Method for GPS Based on Multi-Scale
Directory of Open Access Journals (Sweden)
Tingjun Li
2013-01-01
Full Text Available Aiming at GPS dynamic filtering method, this paper uses the method of multi-scale analysis, combines the “current” statistical model of automotive carrier with multi-scale signal transformation which is based on statistical characteristic, establishes the new algorithm of multi-scale data fusion for GPS dynamic filter combining with normal Kalman filter algorithm, at last achieves the optimal fusion estimated value of the target states based on global information at the finest scale. When the above algorithm is used to GPS dynamic filter, the simulated results show that the proposed algorithm can effectively increase estimated precision of target states compared with the conventional KF.
Multi-scale salient feature extraction on mesh models
Yang, Yongliang
2012-01-01
We present a new method of extracting multi-scale salient features on meshes. It is based on robust estimation of curvature on multiple scales. The coincidence between salient feature and the scale of interest can be established straightforwardly, where detailed feature appears on small scale and feature with more global shape information shows up on large scale. We demonstrate this multi-scale description of features accords with human perception and can be further used for several applications as feature classification and viewpoint selection. Experiments exhibit that our method as a multi-scale analysis tool is very helpful for studying 3D shapes. © 2012 Springer-Verlag.
Institute of Scientific and Technical Information of China (English)
HAN Jian; JIANG Nan
2008-01-01
Experimental measurement of hypersonic boundary layer stability and transition on a sharp cone with a half angle of 5° is carried out at free-coming stream Mach number 6 in a hypersonic wind tunnel.Mean and fluctuation surface-thermal-flux characteristics of the hypersonic boundary layer flow are measured by Pt-thin-film thermocouple temperature sensors installed at 28 stations on the cone surface along longitudinal direction.At hypersonic speeds,the dominant flow instabilities demonstrate that the growth rate of the second mode tends to exceed that of the low-frequency mode.Wavelet-based cross-spectrum technique is introduced to obtain the multi-scale cross-spectral characteristics of the fluctuating signals in the frequency range of the second mode.Nonlinear interactions both of the second mode disturbance and the first mode disturbance axe demonstrated to be dominant instabilities in the initial stage of laminar-turbulence transition for hypersonic shear flow.
Hellmich, Christian; Fritsch, Andreas; Dormieux, Luc
Biomimetics deals with the application of nature-made "design solutions" to the realm of engineering. In the quest to understand mechanical implications of structural hierarchies found in biological materials, multiscale mechanics may hold the key to understand "building plans" inherent to entire material classes, here bone and bone replacement materials. Analyzing a multitude of biophysical hierarchical and biomechanical experiments through homogenization theories for upscaling stiffness and strength properties reveals the following design principles: The elementary component "collagen" induces, right at the nanolevel, the mechanical anisotropy of bone materials, which is amplified by fibrillar collagen-based structures at the 100-nm scale, and by pores in the micrometer-to-millimeter regime. Hydroxyapatite minerals are poorly organized, and provide stiffness and strength in a quasi-brittle manner. Water layers between hydroxyapatite crystals govern the inelastic behavior of the nanocomposite, unless the "collagen reinforcement" breaks. Bone replacement materials should mimic these "microstructural mechanics" features as closely as possible if an imitation of the natural form of bone is desired (Gebeshuber et al., Adv Mater Res 74:265-268, 2009).
Directory of Open Access Journals (Sweden)
Quan Liu
2015-01-01
Full Text Available In order to build a reliable index to monitor the depth of anesthesia (DOA, many algorithms have been proposed in recent years, one of which is sample entropy (SampEn, a commonly used and important tool to measure the regularity of data series. However, SampEn only estimates the complexity of signals on one time scale. In this study, a new approach is introduced using multiscale entropy (MSE considering the structure information over different time scales. The entropy values over different time scales calculated through MSE are applied as the input data to train an artificial neural network (ANN model using bispectral index (BIS or expert assessment of conscious level (EACL as the target. To test the performance of the new index’s sensitivity to artifacts, we compared the results before and after filtration by multivariate empirical mode decomposition (MEMD. The new approach via ANN is utilized in real EEG signals collected from 26 patients before and after filtering by MEMD, respectively; the results show that is a higher correlation between index from the proposed approach and the gold standard compared with SampEn. Moreover, the proposed approach is more structurally robust to noise and artifacts which indicates that it can be used for monitoring the DOA more accurately.
Kang, Xiaoxu; Jia, Xiaofeng; Geocadin, Romergryko G; Thakor, Nitish V; Maybhate, Anil
2009-04-01
Neurological complications after cardiac arrest (CA) can be fatal. Although hypothermia has been shown to be beneficial, understanding the mechanism and establishing neurological outcomes remains challenging because effects of CA and hypothermia are not well characterized. This paper aims to analyze EEG (and the alpha-rhythms) using multiscale entropy (MSE) to demonstrate the ability of MSE in tracking changes due to hypothermia and compare MSE during early recovery with long-term neurological examinations. Ten Wistar rats, upon post-CA resuscitation, were randomly subjected to hypothermia (32 degrees C-34 degrees C, N = 5) or normothermia (36.5 degrees C-37.5 degrees C, N = 5). EEG was recorded and analyzed using MSE during seven recovery phases for each experiment: baseline, CA, and five early recovery phases (R1-R5). Postresuscitation neurological examination was performed at 6, 24, 48, and 72 h to obtain neurological deficit scores (NDSs). Results showed MSE to be a sensitive marker of changes in alpha-rhythms. Significant difference (p < 0.05) was found between the MSE for two groups during recovery, suggesting that MSE can successfully reflect temperature modulation. A comparison of short-term MSE and long-term NDS suggested that MSE could be used for predicting favorability of long-term outcome. These experiments point to the role of cortical rhythms in reporting early neurological response to ischemia and therapeutic hypothermia. PMID:19174339
Liu, Quan; Chen, Yi-Feng; Fan, Shou-Zen; Abbod, Maysam F; Shieh, Jiann-Shing
2015-01-01
In order to build a reliable index to monitor the depth of anesthesia (DOA), many algorithms have been proposed in recent years, one of which is sample entropy (SampEn), a commonly used and important tool to measure the regularity of data series. However, SampEn only estimates the complexity of signals on one time scale. In this study, a new approach is introduced using multiscale entropy (MSE) considering the structure information over different time scales. The entropy values over different time scales calculated through MSE are applied as the input data to train an artificial neural network (ANN) model using bispectral index (BIS) or expert assessment of conscious level (EACL) as the target. To test the performance of the new index's sensitivity to artifacts, we compared the results before and after filtration by multivariate empirical mode decomposition (MEMD). The new approach via ANN is utilized in real EEG signals collected from 26 patients before and after filtering by MEMD, respectively; the results show that is a higher correlation between index from the proposed approach and the gold standard compared with SampEn. Moreover, the proposed approach is more structurally robust to noise and artifacts which indicates that it can be used for monitoring the DOA more accurately. PMID:26491464
Institute of Scientific and Technical Information of China (English)
无
2010-01-01
The empirical mode decomposition method is used for analyzing the paleoclimate proxy δ18O from Greenland GISP2 ice core.The results show that millennium climate change trends in Greenland record the Medieval Warm Period (MWP) from 860AD-1350AD lasting for about 490 years,and the Little Ice Age (LIA) from 1350AD-1920AD lasting about 570 years.During these events,sub cooling-warming variations occurred.Its multi-scale oscillations changed with quasi-period of 3-year,6.5-year,12-year,24-year,49-year,96-year,213-year and 468-year,and are not only affected by ENSO but also by solar activity.The oscillation of intrinsic mode function IMF7,IMF8 and their tendency obviously appear in 1350AD which is considered as the key stage of transformation between MWP and LIA.The results give more detailed changes and their stages of millennium climate change in high latitude areas of the Northern Hemisphere.
Liu, Gang; Yan, Guozheng; Kuang, Shuai; Wang, Yongbing
2016-03-01
Wireless capsule endoscopy (WCE) has been a revolutionary technique to noninvasively inspect gastrointestinal (GI) tract diseases, especially small bowel tumor. However, it is a tedious task for physicians to examine captured images. To develop a computer-aid diagnosis tool for relieving the huge burden of physicians, the intestinal video data from 89 clinical patients with the indications of potential tumors was analyzed. Out of the 89 patients, 15(16.8%) were diagnosed with small bowel tumor. A novel set of textural features that integrate multi-scale curvelet and fractal technology were proposed to distinguish normal images from tumor images. The second order textural descriptors as well as higher order moments between different color channels were computed from images synthesized by the inverse curvelet transform of the selected scales. Then, a classification approach based on support vector machine (SVM) and genetic algorithm (GA) was further employed to select the optimal feature set and classify the real small bowel images. Extensive comparison experiments validate that the proposed automatic diagnosis scheme achieves a promising tumor classification performance of 97.8% sensitivity and 96.7% specificity in the selected images from our clinical data. PMID:26829705
Multi-scale Analysis of Chaotic Characteristics in a Gas-Solid Fluidized Bed%气固流化床中非线性特性的多尺度分析
Institute of Scientific and Technical Information of China (English)
甄玲; 王晓萍; 陈伯川; 黄海; 黄春艳
2002-01-01
Deterministic chaos theory offers useful quantitative tools to characterize the non-linear dynamic behavior of a fluidized bed and the developed complexity theory presents a new approach to evaluate finite sequences.In this paper, the non-linear, hydrodynamic behavior of the pressure fluctuation signals in a reactor was discussed by chaos parameters and complexity measures. Coherent results were achieved by our multi-scale analysis, which further exposed the behavior in a gas-solid two-phase system.
DEFF Research Database (Denmark)
Somchaipeng, Kerawit; Sporring, Jon; Johansen, Peter;
2007-01-01
We propose MultiScale Singularity Trees (MSSTs) as a structure to represent images, and we propose an algorithm for image comparison based on comparing MSSTs. The algorithm is tested on 3 public image databases and compared to 2 state-of-theart methods. We conclude that the computational complexi...
International Nuclear Information System (INIS)
analysis is here limited to the mesoscale, at which only aggregates with a characteristic size above 5 mm are meshed while the remaining inclusions together with the cement paste are considered to be a homogeneous matrix. Finally, the numerical analysis carries out the need to perform an experimental campaign that is consistent with a multi-scale approach of the THM behavior of concrete: an experimental campaign that allows to identify thermal, hygral and mechanical properties of each concrete constituent and that permit to assess evolution of fields during up-scaling. An experimental protocol is then elaborated for this purpose and some obtained results are presented and analyzed with regard to results obtained in the modeling part. (author)
Multiscale Thermohydrologic Model
Energy Technology Data Exchange (ETDEWEB)
T. Buscheck
2004-10-12
The purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. Thus, the goal is to predict the range of possible thermal-hydrologic conditions across the repository; this is quite different from predicting a single expected thermal-hydrologic response. The MSTHM calculates the following thermal-hydrologic parameters: temperature, relative humidity, liquid-phase saturation, evaporation rate, air-mass fraction, gas-phase pressure, capillary pressure, and liquid- and gas-phase fluxes (Table 1-1). These thermal-hydrologic parameters are required to support ''Total System Performance Assessment (TSPA) Model/Analysis for the License Application'' (BSC 2004 [DIRS 168504]). The thermal-hydrologic parameters are determined as a function of position along each of the emplacement drifts and as a function of waste package type. These parameters are determined at various reference locations within the emplacement drifts, including the waste package and drip-shield surfaces and in the invert. The parameters are also determined at various defined locations in the adjoining host rock. The MSTHM uses data obtained from the data tracking numbers (DTNs) listed in Table 4.1-1. The majority of those DTNs were generated from the following analyses and model reports: (1) ''UZ Flow Model and Submodels'' (BSC 2004 [DIRS 169861]); (2) ''Development of Numerical Grids for UZ Flow and Transport Modeling'' (BSC 2004); (3) ''Calibrated Properties Model'' (BSC 2004 [DIRS 169857]); (4) ''Thermal Conductivity of the Potential Repository Horizon'' (BSC 2004 [DIRS 169854]); (5) ''Thermal Conductivity of the Non-Repository Lithostratigraphic Layers
Towards distributed multiscale computing for the VPH
A.G. Hoekstra; P. Coveney
2010-01-01
Multiscale modeling is fundamental to the Virtual Physiological Human (VPH) initiative. Most detailed three-dimensional multiscale models lead to prohibitive computational demands. As a possible solution we present MAPPER, a computational science infrastructure for Distributed Multiscale Computing o
Directory of Open Access Journals (Sweden)
Jaime Resano-Mayor
Full Text Available Inter-individual diet variation within populations is likely to have important ecological and evolutionary implications. The diet-fitness relationships at the individual level and the emerging population processes are, however, poorly understood for most avian predators inhabiting complex terrestrial ecosystems. In this study, we use an isotopic approach to assess the trophic ecology of nestlings in a long-lived raptor, the Bonelli's eagle Aquila fasciata, and investigate whether nestling dietary breath and main prey consumption can affect the species' reproductive performance at two spatial scales: territories within populations and populations over a large geographic area. At the territory level, those breeding pairs whose nestlings consumed similar diets to the overall population (i.e. moderate consumption of preferred prey, but complemented by alternative prey categories or those disproportionally consuming preferred prey were more likely to fledge two chicks. An increase in the diet diversity, however, related negatively with productivity. The age and replacements of breeding pair members had also an influence on productivity, with more fledglings associated to adult pairs with few replacements, as expected in long-lived species. At the population level, mean productivity was higher in those population-years with lower dietary breadth and higher diet similarity among territories, which was related to an overall higher consumption of preferred prey. Thus, we revealed a correspondence in diet-fitness relationships at two spatial scales: territories and populations. We suggest that stable isotope analyses may be a powerful tool to monitor the diet of terrestrial avian predators on large spatio-temporal scales, which could serve to detect potential changes in the availability of those prey on which predators depend for breeding. We encourage ecologists and evolutionary and conservation biologists concerned with the multi-scale fitness
Generalized multiscale finite element methods: Oversampling strategies
Efendiev, Yalchin R.
2014-01-01
In this paper, we propose oversampling strategies in the generalized multiscale finite element method (GMsFEM) framework. The GMsFEM, which has been recently introduced in Efendiev et al. (2013b) [Generalized Multiscale Finite Element Methods, J. Comput. Phys., vol. 251, pp. 116-135, 2013], allows solving multiscale parameter-dependent problems at a reduced computational cost by constructing a reduced-order representation of the solution on a coarse grid. The main idea of the method consists of (1) the construction of snapshot space, (2) the construction of the offline space, and (3) construction of the online space (the latter for parameter-dependent problems). In Efendiev et al. (2013b) [Generalized Multiscale Finite Element Methods, J. Comput. Phys., vol. 251, pp. 116-135, 2013], it was shown that the GMsFEM provides a flexible tool to solve multiscale problems with a complex input space by generating appropriate snapshot, offline, and online spaces. In this paper, we develop oversampling techniques to be used in this context (see Hou and Wu (1997) where oversampling is introduced for multiscale finite element methods). It is known (see Hou and Wu (1997)) that the oversampling can improve the accuracy of multiscale methods. In particular, the oversampling technique uses larger regions (larger than the target coarse block) in constructing local basis functions. Our motivation stems from the analysis presented in this paper, which shows that when using oversampling techniques in the construction of the snapshot space and offline space, GMsFEM will converge independent of small scales and high contrast under certain assumptions. We consider the use of a multiple eigenvalue problems to improve the convergence and discuss their relation to single spectral problems that use oversampled regions. The oversampling procedures proposed in this paper differ from those in Hou and Wu (1997). In particular, the oversampling domains are partially used in constructing local
Wang, Chun-Hao; Tsai, Chia-Liang; Tseng, Philip; Yang, Albert C; Lo, Men-Tzung; Peng, Chung-Kang; Wang, Hsin-Yi; Muggleton, Neil G; Juan, Chi-Hung; Liang, Wei-Kuang
2014-10-29
Physical activity has been shown to benefit brain and cognition in late adulthood. However, this effect is still unexplored in terms of brain signal complexity, which reflects the level of neural adaptability and efficiency during cognitive processing that cannot be acquired via averaged neuroelectric signals. Here we employed multiscale entropy analysis (MSE) of electroencephalography (EEG), a new approach that conveys important information related to the temporal dynamics of brain signal complexity across multiple time scales, to reveal the association of physical activity with neural adaptability and efficiency in elderly adults. A between-subjects design that included 24 participants (aged 66.63±1.31years; female=12) with high physical activity and 24 age- and gender-matched low physical activity participants (aged 67.29±1.20years) was conducted to examine differences related to physical activity in performance and MSE of EEG signals during a visuo-spatial cognition task. We observed that physically active elderly adults had better accuracy on both visuo-spatial attention and working memory conditions relative to their sedentary counterparts. Additionally, these physically active elderly adults displayed greater MSE values at larger time scales at the Fz electrode in both attention and memory conditions. The results suggest that physical activity may be beneficial for adaptability of brain systems in tasks involving visuo-spatial information. MSE thus might be a promising approach to test the effects of the benefits of exercise on cognition. PMID:25463141
Loizou, C. P.; Murray, V.; Pattichis, M. S.; Pantziaris, M.; Nicolaides, A. N.; Pattichis, C. S.
2014-01-01
The intima-media thickness (IMT) of the common carotid artery (CCA) is widely used as an early indicator of cardiovascular disease (CVD). Typically, the IMT grows with age and this is used as a sign of increased risk of CVD. Beyond thickness, there is also clinical interest in identifying how the composition and texture of the intima-media complex (IMC) changed and how these textural changes grow into atherosclerotic plaques that can cause stroke. Clearly though texture analysis of ultrasound images can be greatly affected by speckle noise, our goal here is to develop effective despeckle noise methods that can recover image texture associated with increased rates of atherosclerosis disease. In this study, we perform a comparative evaluation of several despeckle filtering methods, on 100 ultrasound images of the CCA, based on the extracted multiscale Amplitude-Modulation Frequency-Modulation (AM-FM) texture features and visual image quality assessment by two clinical experts. Texture features were extracted from the automatically segmented IMC for three different age groups. The despeckle filters hybrid median and the homogeneous mask area filter showed the best performance by improving the class separation between the three age groups and also yielded significantly improved image quality. PMID:24734038
Das, Debanjan; Shiladitya, Kumar; Biswas, Karabi; Dutta, Pranab Kumar; Parekh, Aditya; Mandal, Mahitosh; Das, Soumen
2015-12-01
The paper presents a study to differentiate normal and cancerous cells using label-free bioimpedance signal measured by electric cell-substrate impedance sensing. The real-time-measured bioimpedance data of human breast cancer cells and human epithelial normal cells employs fluctuations of impedance value due to cellular micromotions resulting from dynamic structural rearrangement of membrane protrusions under nonagitated condition. Here, a wavelet-based multiscale quantitative analysis technique has been applied to analyze the fluctuations in bioimpedance. The study demonstrates a method to classify cancerous and normal cells from the signature of their impedance fluctuations. The fluctuations associated with cellular micromotion are quantified in terms of cellular energy, cellular power dissipation, and cellular moments. The cellular energy and power dissipation are found higher for cancerous cells associated with higher micromotions in cancer cells. The initial study suggests that proposed wavelet-based quantitative technique promises to be an effective method to analyze real-time bioimpedance signal for distinguishing cancer and normal cells.
Multi-Scale Validation of a Nanodiamond Drug Delivery System and Multi-Scale Engineering Education
Schwalbe, Michelle Kristin
2010-01-01
This dissertation has two primary concerns: (i) evaluating the uncertainty and prediction capabilities of a nanodiamond drug delivery model using Bayesian calibration and bias correction, and (ii) determining conceptual difficulties of multi-scale analysis from an engineering education perspective. A Bayesian uncertainty quantification scheme…
Multiscale Simulations Using Particles
DEFF Research Database (Denmark)
Walther, Jens Honore
We are developing particle methods as a general framework for large scale simulations of discrete and continuous systems in science and engineering. The specific application and research areas include: discrete element simulations of granular flow, smoothed particle hydrodynamics and particle...... vortex methods for problems in continuum fluid dynamics, dissipative particle dynamics for flow at the meso scale, and atomistic molecular dynamics simulations of nanofluidic systems. We employ multiscale techniques to breach the atomistic and continuum scales to study fundamental problems in fluid...
喷砂表面的多尺度分析与表征%Analysis and Characterization of Sandblasted Surfaces Using Multi-scale Analysis
Institute of Scientific and Technical Information of China (English)
王春水; 何声馨; 张二亮; 李大磊
2015-01-01
目的：对喷砂表面的复杂轮廓特征进行分析和表征,以选取能表征最佳工艺参数的三维粗糙度参数。方法以喷砂工作距离为变量对AISI 304 L不锈钢试样进行喷砂处理,对喷砂处理后试样的表面形貌开展多尺度分析,选取5个评价尺度,每个评价尺度下采用12个常用的三维粗糙度参数进行表面形貌表征；分析各个粗糙度参数对于评价尺度的变化规律,同时进一步考虑喷砂工作距离对喷砂表面形貌的影响,在适宜评价尺度下建立粗糙度参数和工艺参数之间的线性回归模型。结果大部分三维粗糙度参数(Sku)的最优评价尺度均为80μm,在该评价尺度下,Sku与喷砂工作距离之间存在线性关系,且其线性相关系数最大；随着喷砂工作距离的增加,Sku随之增大,试样表面形貌的峰谷数量也随之增大。结论本次喷砂工艺实验的最优评价尺度为80μm,最优表面形貌表征参数为Sku,与普遍使用的Sa和Sq相比, Sku包含更多三维形貌信息,能更好地刻画喷砂工作距离对表面形貌的影响。%ABSTRACT:Objective To analyze and characterize the complicated surface topography of sandblasted surface, so as to obtain the 3D roughness parameter which is optimal in describing the influence of sandblasting parameters on surface topography. Methods The multi-scale analysis was conducted on the sandblasted surfaces of AISI 304L steel specimens, which were sandblasted at differ-ent distances as the processing parameter. Each surface was characterized using 12 common 3D roughness parameters at 5 evalua-tion scales. The variation trend of each roughness parameter against the evaluation scale was analyzed, meanwhile, the influence of process parameter ( distance) on surface topography was considered, the linear regression model between the roughness parameters and the process parameter was established at an appropriate evaluation scale. Results The optimal evaluation scale
Multiscale Gaussian network model (mGNM) and multiscale anisotropic network model (mANM).
Xia, Kelin; Opron, Kristopher; Wei, Guo-Wei
2015-11-28
Gaussian network model (GNM) and anisotropic network model (ANM) are some of the most popular methods for the study of protein flexibility and related functions. In this work, we propose generalized GNM (gGNM) and ANM methods and show that the GNM Kirchhoff matrix can be built from the ideal low-pass filter, which is a special case of a wide class of correlation functions underpinning the linear scaling flexibility-rigidity index (FRI) method. Based on the mathematical structure of correlation functions, we propose a unified framework to construct generalized Kirchhoff matrices whose matrix inverse leads to gGNMs, whereas, the direct inverse of its diagonal elements gives rise to FRI method. With this connection, we further introduce two multiscale elastic network models, namely, multiscale GNM (mGNM) and multiscale ANM (mANM), which are able to incorporate different scales into the generalized Kirchhoff matrices or generalized Hessian matrices. We validate our new multiscale methods with extensive numerical experiments. We illustrate that gGNMs outperform the original GNM method in the B-factor prediction of a set of 364 proteins. We demonstrate that for a given correlation function, FRI and gGNM methods provide essentially identical B-factor predictions when the scale value in the correlation function is sufficiently large. More importantly, we reveal intrinsic multiscale behavior in protein structures. The proposed mGNM and mANM are able to capture this multiscale behavior and thus give rise to a significant improvement of more than 11% in B-factor predictions over the original GNM and ANM methods. We further demonstrate the benefits of our mGNM through the B-factor predictions of many proteins that fail the original GNM method. We show that the proposed mGNM can also be used to analyze protein domain separations. Finally, we showcase the ability of our mANM for the analysis of protein collective motions. PMID:26627949
Using Multiscale Product for ECG Characterization
Directory of Open Access Journals (Sweden)
Rym Besrour
2009-01-01
Full Text Available This paper introduces a new method for R wave's locations using the multiscale wavelet analysis, that is based on Mallat's and Hwang's approach for singularity detection via local maxima of the wavelet coefficients signals. Using a first derivative Gaussian function as prototype wavelet, we apply the pointwise product of the wavelet coefficients (PWCs over some successive scales, in order to enhance the peak amplitude of the modulus maxima line and to reduce noise. The R wave corresponds to two modulus maximum lines with opposite signs (min-max of multi-scale product. The proposed algorithm does not include regularity analysis but only amplitude-based criteria. We evaluated the algorithm on two manually annotated databases, such as MIT-BIH Arrhythmia and QT.
Multiscale Event Detection in Social Media
Dong, Xiaowen; Mavroeidis, Dimitrios; Calabrese, Francesco; Frossard, Pascal
2014-01-01
Event detection has been one of the most important research topics in social media analysis. Most of the traditional approaches detect events based on fixed temporal and spatial resolutions, while in reality events of different scales usually occur simultaneously, namely, they span different intervals in time and space. In this paper, we propose a novel approach towards multiscale event detection using social media data, which takes into account different temporal and spatial scales of events...
Multiscale Medical Image Fusion in Wavelet Domain
Rajiv Singh; Ashish Khare
2013-01-01
Wavelet transforms have emerged as a powerful tool in image fusion. However, the study and analysis of medical image fusion is still a challenging area of research. Therefore, in this paper, we propose a multiscale fusion of multimodal medical images in wavelet domain. Fusion of medical images has been performed at multiple scales varying from minimum to maximum level using maximum selection rule which provides more flexibility and choice to select the relevant fused images. The experimental ...
Multi-scale theory of rotating turbulence
Leprovost, Nicolas; Kim, Eun-Jin
2007-01-01
We consider turbulence induced by an arbitrary forcing and derive turbulence amplitude and turbulent transport coefficients, first by using a quasi-linear theory and then by using a multi-scale renormalisation analysis. With an isotropic forcing, the quasi-linear theory gives that the turbulent transport coefficients, both parallel and perpendicular to the rotation vector, have the asymptotic scaling $\\Omega^{-1}$ for rapid rotation (i.e. when the rotation rate $\\Omega$ is larger than the inv...
Maxwell, R. M.; Bearup, L. A.; Penn, C. A.; Jefferson, J.; Engdahl, N. B.
2014-12-01
Changing climate, including warmer temperatures and drought conditions, has intensified mountain pine beetle infestation in the Rocky Mountains of North America, resulting in tree death over the last decade that is unprecedented in recorded history. The subsequent perturbation to tree-scale water budget processes such as interception, transpiration, and evaporation often combine non-uniformly and produce variable catchment-scale responses. Potentially offsetting perturbations such as decreased transpiration with tree death and increased exposure and evaporation with needle fall can produce changes in peak streamflow and water yield that are undetectable above typical interannual variability. These combined perturbations, however, may change streamflow generating processes and water sources that impact water quality in important mountain headwater streams. To determine the potential impact of widespread land cover change on catchment contributions to streamflow, this study combines a chemical and isotopic separation analysis using paired watersheds and pre-infestation controls with a multi-scale modeling approach (from hillslope to headwaters systems) that determines changes in water stores and fluxes between canopy, land-surface, groundwater and streamflow. Field observations and chemical hydrograph separation analysis suggest that groundwater contributions to streamflow increase with recent insect infestation, as transpiration ceases to remove water from the subsurface but potentially increased ground evaporation removes water from the land and subsurface with relative uniformity. Comparing these field observations to hillslope models provides additional spatial and temporal controls on inherently challenging field heterogeneities as well as a way of testing the influence of natural properties such as precipitation and topography on perturbations to streamflow partitioning from insect infestation. At larger scales, watershed models demonstrate how other factors
Yang, Albert C; Huang, Chu-Chung; Yeh, Heng-Liang; Liu, Mu-En; Hong, Chen-Jee; Tu, Pei-Chi; Chen, Jin-Fan; Huang, Norden E; Peng, Chung-Kang; Lin, Ching-Po; Tsai, Shih-Jen
2013-02-01
The nonlinear properties of spontaneous fluctuations in blood oxygen level-dependent (BOLD) signals remain unexplored. We test the hypothesis that complexity of BOLD activity is reduced with aging and is correlated with cognitive performance in the elderly. A total of 99 normal older and 56 younger male subjects were included. Cognitive function was assessed using Cognitive Abilities Screening Instrument and Wechsler Digit Span Task. We employed a complexity measure, multiscale entropy (MSE) analysis, and investigated appropriate parameters for MSE calculation from relatively short BOLD signals. We then compared the complexity of BOLD signals between the younger and older groups, and examined the correlation between cognitive test scores and complexity of BOLD signals in various brain regions. Compared with the younger group, older subjects had the most significant reductions in MSE of BOLD signals in posterior cingulate gyrus and hippocampal cortex. For older subjects, MSE of BOLD signals from default mode network areas, including hippocampal cortex, cingulate cortex, superior and middle frontal gyrus, and middle temporal gyrus, were found to be positively correlated with major cognitive functions, such as attention, orientation, short-term memory, mental manipulation, and language. MSE from subcortical regions, such as amygdala and putamen, were found to be positively correlated with abstract thinking and list-generating fluency, respectively. Our findings confirmed the hypothesis that complexity of BOLD activity was correlated with aging and cognitive performance based on MSE analysis, and may provide insights on how dynamics of spontaneous brain activity relates to aging and cognitive function in specific brain regions. PMID:22683008
Turbulent photospheric drivers of multiscale solar corona
Uritsky, Vadim M.; Ofman, Leon; Davila, Joseph M.
2015-04-01
We investigate the collective dynamics of transient photospheric and coronal events detected using high-resolution solar magnetograms and coronal emission images. We focus on statistical, ensemble-averaged properties of the interacting solar regions [Uritsky et al., 2011, 2013, 2014; Uritsky and Davila, 2012], as opposed to case-oriented methodologies recruited in some previous studies. The behavior of solar events is studied in the three-dimensional space-time enabling accurate representation of the event evolution. By applying advanced data analysis methods including feature tracking algorithms, multiscale correlation analysis and scaling analysis techniques, we identify leading physical scenarios of the photosphere - corona coupling in quiet and active solar regions, and strive to identify new statistical precursors of coronal eruptions. We also discuss the possibility of modeling multiscale photosphere - corona interactions using idealized three-dimensional MHD models. The obtained results shed a new light on the origin of multiscale dissipation in the solar corona by enabling quantitative validation of several popular statistical physical scenarios, such as e.g. intermittent turbulence, self-organized criticality, and topological complexity.
Cipitria, A; Wagermaier, W; Zaslansky, P; Schell, H; Reichert, J C; Fratzl, P; Hutmacher, D W; Duda, G N
2015-09-01
Scaffold architecture guides bone formation. However, in critical-sized long bone defects additional BMP-mediated osteogenic stimulation is needed to form clinically relevant volumes of new bone. The hierarchical structure of bone determines its mechanical properties. Yet, the micro- and nanostructure of BMP-mediated fast-forming bone has not been compared with slower regenerating bone without BMP. We investigated the combined effects of scaffold architecture (physical cue) and BMP stimulation (biological cue) on bone regeneration. It was hypothesized that a structured scaffold directs tissue organization through structural guidance and load transfer, while BMP stimulation accelerates bone formation without altering the microstructure at different length scales. BMP-loaded medical grade polycaprolactone-tricalcium phosphate scaffolds were implanted in 30mm tibial defects in sheep. BMP-mediated bone formation after 3 and 12 months was compared with slower bone formation with a scaffold alone after 12 months. A multiscale analysis based on microcomputed tomography, histology, polarized light microscopy, backscattered electron microscopy, small angle X-ray scattering and nanoindentation was used to characterize bone volume, collagen fiber orientation, mineral particle thickness and orientation, and local mechanical properties. Despite different observed kinetics in bone formation, similar structural properties on a microscopic and sub-micron level seem to emerge in both BMP-treated and scaffold only groups. The guiding effect of the scaffold architecture is illustrated through structural differences in bone across different regions. In the vicinity of the scaffold increased tissue organization is observed at 3 months. Loading along the long bone axis transferred through the scaffold defines bone micro- and nanostructure after 12 months. PMID:26004222
Directory of Open Access Journals (Sweden)
Hsien-Tsai Wu
2015-12-01
Full Text Available To explore information hidden in the electromyographic (EMG signals of the urethral sphincter that may be of prognostic significance for patients with primary bladder neck obstruction (PBNO, 41 patients with voiding difficulty were divided into four groups: 1 patients with primary bladder neck obstruction (PBNO with successful (Group 1, n = 14 and 2 unsuccessful (Group 2, n = 8 surgical outcomes, 3 patients with detrusor overactivity (Group 3, n = 7, and 4 patients with detrusor-external sphincter dyssynergia (Group 4, n = 12. All patients underwent baseline urodynamic studies (preoperative for Group 1 and Group 2 for comparison. The results demonstrated that, despite no significant difference in urodynamic parameters between Group 1 and Group 2, the large-scale multiscale entropy (MSE of preoperative EMG (i.e., MSELS(EMG of Group 1 was significantly higher than that of Group 2 without notable difference between Group 1 and Group 3 (i.e., patients with normal sphincter function. Moreover, the MSELS(EMG and small-scale MSE of preoperative EMG (i.e., MSESS(EMG of Group 2 were notably higher than those of Group 4 (i.e., patients with abnormal sphincter function, while both MSELS(EMG and MSESS(EMG of Group 3 were notably higher than those of Group 2. In conclusion, using MSE analysis for assessing preoperative urethral sphincter EMG signals successfully distinguished between PBNO patients with subsequent successful surgery from those with surgical failure possibly due to subtle functional impairment of the urethral sphincter that cannot be detected by routine urodynamic studies. The results, therefore, highlight the potential clinical significance of this analytical tool in guiding urologists regarding their choice of medical versus surgical treatment for this patient population.
Ho, Yi-Lwun; Lin, Chen; Lin, Yen-Hung; Lo, Men-Tzung
2011-01-01
Aims The influences of nonstationarity and nonlinearity on heart rate time series can be mathematically qualified or quantified by multiscale entropy (MSE). The aim of this study is to investigate the prognostic value of parameters derived from MSE in the patients with systolic heart failure. Methods and Results Patients with systolic heart failure were enrolled in this study. One month after clinical condition being stable, 24-hour Holter electrocardiogram was recording. MSE as well as other standard parameters of heart rate variability (HRV) and detrended fluctuation analysis (DFA) were assessed. A total of 40 heart failure patients with a mea age of 56±16 years were enrolled and followed-up for 684±441 days. There were 25 patients receiving β-blockers treatment. During follow-up period, 6 patients died or received urgent heart transplantation. The short-term exponent of DFA and the slope of MSE between scale 1 to 5 were significantly different between patients with or without β-blockers (p = 0.014 and p = 0.028). Only the area under the MSE curve for scale 6 to 20 (Area6–20) showed the strongest predictive power between survival (n = 34) and mortality (n = 6) groups among all the parameters. The value of Area6–2021.2 served as a significant predictor of mortality or heart transplant (p = 0.0014). Conclusion The area under the MSE curve for scale 6 to 20 is not relevant to β-blockers and could further warrant independent risk stratification for the prognosis of CHF patients. PMID:21533258
Directory of Open Access Journals (Sweden)
Yi-Lwun Ho
Full Text Available AIMS: The influences of nonstationarity and nonlinearity on heart rate time series can be mathematically qualified or quantified by multiscale entropy (MSE. The aim of this study is to investigate the prognostic value of parameters derived from MSE in the patients with systolic heart failure. METHODS AND RESULTS: Patients with systolic heart failure were enrolled in this study. One month after clinical condition being stable, 24-hour Holter electrocardiogram was recording. MSE as well as other standard parameters of heart rate variability (HRV and detrended fluctuation analysis (DFA were assessed. A total of 40 heart failure patients with a mea age of 56±16 years were enrolled and followed-up for 684±441 days. There were 25 patients receiving β-blockers treatment. During follow-up period, 6 patients died or received urgent heart transplantation. The short-term exponent of DFA and the slope of MSE between scale 1 to 5 were significantly different between patients with or without β-blockers (p = 0.014 and p = 0.028. Only the area under the MSE curve for scale 6 to 20 (Area(6-20 showed the strongest predictive power between survival (n = 34 and mortality (n = 6 groups among all the parameters. The value of Area(6-2021.2 served as a significant predictor of mortality or heart transplant (p = 0.0014. CONCLUSION: The area under the MSE curve for scale 6 to 20 is not relevant to β-blockers and could further warrant independent risk stratification for the prognosis of CHF patients.
Strijker, G.
2013-01-01
Natural fractures occur over several orders of size magnitude. Accurately predicting the three-dimensional and multi-scale distribution of fractures in subsurface reservoirs is very difficult. Direct observations are limited to large-scale faults visible on seismic data and high-resolution, mostly s
MULTISCALE THERMOHYDROLOGIC MODEL
Energy Technology Data Exchange (ETDEWEB)
T. Buscheck
2005-07-07
The intended purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. The goal of the MSTHM is to predict a reasonable range of possible thermal-hydrologic conditions within the emplacement drift. To be reasonable, this range includes the influence of waste-package-to-waste-package heat output variability relevant to the license application design, as well as the influence of uncertainty and variability in the geologic and hydrologic conditions relevant to predicting the thermal-hydrologic response in emplacement drifts. This goal is quite different from the goal of a model to predict a single expected thermal-hydrologic response. As a result, the development and validation of the MSTHM and the associated analyses using this model are focused on the goal of predicting a reasonable range of thermal-hydrologic conditions resulting from parametric uncertainty and waste-package-to-waste-package heat-output variability. Thermal-hydrologic conditions within emplacement drifts depend primarily on thermal-hydrologic conditions in the host rock at the drift wall and on the temperature difference between the drift wall and the drip-shield and waste-package surfaces. Thus, the ability to predict a reasonable range of relevant in-drift MSTHM output parameters (e.g., temperature and relative humidity) is based on valid predictions of thermal-hydrologic processes in the host rock, as well as valid predictions of heat-transfer processes between the drift wall and the drip-shield and waste-package surfaces. Because the invert contains crushed gravel derived from the host rock, the invert is, in effect, an extension of the host rock, with thermal and hydrologic properties that have been modified by virtue of the crushing (and the resulting
MULTISCALE THERMOHYDROLOGIC MODEL
International Nuclear Information System (INIS)
The intended purpose of the multiscale thermohydrologic model (MSTHM) is to predict the possible range of thermal-hydrologic conditions, resulting from uncertainty and variability, in the repository emplacement drifts, including the invert, and in the adjoining host rock for the repository at Yucca Mountain. The goal of the MSTHM is to predict a reasonable range of possible thermal-hydrologic conditions within the emplacement drift. To be reasonable, this range includes the influence of waste-package-to-waste-package heat output variability relevant to the license application design, as well as the influence of uncertainty and variability in the geologic and hydrologic conditions relevant to predicting the thermal-hydrologic response in emplacement drifts. This goal is quite different from the goal of a model to predict a single expected thermal-hydrologic response. As a result, the development and validation of the MSTHM and the associated analyses using this model are focused on the goal of predicting a reasonable range of thermal-hydrologic conditions resulting from parametric uncertainty and waste-package-to-waste-package heat-output variability. Thermal-hydrologic conditions within emplacement drifts depend primarily on thermal-hydrologic conditions in the host rock at the drift wall and on the temperature difference between the drift wall and the drip-shield and waste-package surfaces. Thus, the ability to predict a reasonable range of relevant in-drift MSTHM output parameters (e.g., temperature and relative humidity) is based on valid predictions of thermal-hydrologic processes in the host rock, as well as valid predictions of heat-transfer processes between the drift wall and the drip-shield and waste-package surfaces. Because the invert contains crushed gravel derived from the host rock, the invert is, in effect, an extension of the host rock, with thermal and hydrologic properties that have been modified by virtue of the crushing (and the resulting
MULTISCALE PHENOMENA IN MATERIALS
Energy Technology Data Exchange (ETDEWEB)
A. BISHOP
2000-09-01
This project developed and supported a technology base in nonequilibrium phenomena underpinning fundamental issues in condensed matter and materials science, and applied this technology to selected problems. In this way the increasingly sophisticated synthesis and characterization available for classes of complex electronic and structural materials provided a testbed for nonlinear science, while nonlinear and nonequilibrium techniques helped advance our understanding of the scientific principles underlying the control of material microstructure, their evolution, fundamental to macroscopic functionalities. The project focused on overlapping areas of emerging thrusts and programs in the Los Alamos materials community for which nonlinear and nonequilibrium approaches will have decisive roles and where productive teamwork among elements of modeling, simulations, synthesis, characterization and applications could be anticipated--particularly multiscale and nonequilibrium phenomena, and complex matter in and between fields of soft, hard and biomimetic materials. Principal topics were: (i) Complex organic and inorganic electronic materials, including hard, soft and biomimetic materials, self-assembly processes and photophysics; (ii) Microstructure and evolution in multiscale and hierarchical materials, including dynamic fracture and friction, dislocation and large-scale deformation, metastability, and inhomogeneity; and (iii) Equilibrium and nonequilibrium phases and phase transformations, emphasizing competing interactions, frustration, landscapes, glassy and stochastic dynamics, and energy focusing.
International Nuclear Information System (INIS)
The simulation of complex thermal-hydraulic phenomena is a challenging task. On one hand Computational Fluid Dynamics (CFD) codes allow a fine resolution of 3D phenomena but have a computational cost which is still prohibitive for some applications. On the other hand, System Analysis codes are fast running but cannot account for 3D phenomena. The coupling of these two approaches provides a tool which combines their advantages. In the context of the European THINS Project (7th Framework Program) the Gesellschaft für Anlagen- und Reaktorsicherheit mbH (GRS) developed a coupling between ANSYS CFX and ATHLET. The validation of this coupled code is to be performed with the help of experimental data provided by KTH (Sweden), which has built the TALL-3D facility for this purpose. This facility investigates the transition from forced to natural circulation of the Lead-Bismuth Eutectic (LBE) in a pool connected to a 3-leg primary circuit with two heaters and a heat exchanger. TUM is responsible for the Uncertainty and Sensitivity Analysis (USA) of the coupled ATHLET-CFX simulations in the THINS Project. The influence of modeling uncertainty on the simulation results needs to be assessed because it can significantly impair their accuracy. USA is a powerful tool to assess the model output variability resulting from modeling uncertainty (Uncertainty Analysis) and to identify and rank the influential model input parameters (Sensitivity Analysis). TUM has developed a computational framework to propagate modeling uncertainty through coupled Systems Analysis – Computational Fluid Dynamics (CFD) codes. This framework is being applied to the simulation of the experiments performed on the TALL-3D facility. The uncertainty methodology used is based on the statistical sampling of the uncertain inputs and models used by the two codes, its propagation through coupled calculations, and the final processing of the output sample of variables of interest with non-parametric statistical
Papaioannou, Vasilios E; Chouvarda, Ioanna G; Maglaveras, Nikos K; Pneumatikos, Ioannis A
2012-01-01
Background Even though temperature is a continuous quantitative variable, its measurement has been considered a snapshot of a process, indicating whether a patient is febrile or afebrile. Recently, other diagnostic techniques have been proposed for the association between different properties of the temperature curve with severity of illness in the Intensive Care Unit (ICU), based on complexity analysis of continuously monitored body temperature. In this study, we tried to assess temperature ...
Valencia, Jose F.; Melia, Umberto Sergio Pio; Vallverdú Ferrer, Montserrat; Jospin, Mathieu; Erik W. Jensen; Porta, Alberto; Gambus, Pedro L.; Caminal Magrans, Pere
2014-01-01
The level of sedation in patients undergoing medical procedures evolves contin uously since the effect of the anesthetic and analgesic agents is counteracted by noxious stimuli. The monitors of depth of anesthesia, based on the analysis of the electroencephalogram (EEG), have been progressively introduced into the daily practice to provide additional information about the state of the patient. However, the quantification of analgesia still remains an open problem. The purpose of this...
Betzel, Richard F
2016-01-01
The network architecture of the human brain has become a feature of increasing interest to the neuroscientific community, largely because of its potential to illuminate human cognition, its variation over development and aging, and its alteration in disease or injury. Traditional tools and approaches to study this architecture have largely focused on single scales -- of topology, time, and space. Expanding beyond this narrow view, we focus this review on pertinent questions and novel methodological advances for the multi-scale brain. We separate our exposition into content related to multi-scale topological structure, multi-scale temporal structure, and multi-scale spatial structure. In each case, we recount empirical evidence for such structures, survey network-based methodological approaches to reveal these structures, and outline current frontiers and open questions. Although predominantly peppered with examples from human neuroimaging, we hope that this account will offer an accessible guide to any neuros...
Multiscale spacetimes from first principles
Calcagni, Gianluca
2016-01-01
We formulate a theorem for the general profile of the Hausdorff and the spectral dimension of multiscale geometries, assuming a smooth and slow change of spacetime dimensionality at large scales. Agreement with various scenarios of quantum gravity is found. In particular, we derive uniquely the multiscale measure with log oscillations of theories of multifractional geometry. Predictivity of this class of models and falsifiability of their abundant phenomenology are thus established.
Sensing and Multiscale Structure
Fletcher, John F A
2012-01-01
We introduce a method of estimating parameters associated with a fractal random scattering medium, which utilizes the multiscale properties of the scattered field. The example of ray-density fluctuations beyond a phase screen with fractal slope is considered. An exact solution to the forward problem, in the case of the Brownian fractal, leads to an expression for the volatility of the slope. This expression is invariant under a change of probability measure, a fact which gives rise to the corresponding result for a (stationary) Ornstein-Uhlenbeck slope. We demonstrate that our analytical results are consistent with numerical simulations. Finally, an application to the determination of sea ice thickness via sonar is discussed.
MULTISCALE THERMOHYDROLOGIC MODEL
Energy Technology Data Exchange (ETDEWEB)
T.A. Buscheck
2001-12-21
The purpose of the Multiscale Thermohydrologic Model (MSTHM) is to describe the thermohydrologic evolution of the near-field environment (NFE) and engineered barrier system (EBS) throughout the potential high-level nuclear waste repository at Yucca Mountain for a particular engineering design (CRWMS M&O 2000c). The process-level model will provide thermohydrologic (TH) information and data (such as in-drift temperature, relative humidity, liquid saturation, etc.) for use in other technical products. This data is provided throughout the entire repository area as a function of time. The MSTHM couples the Smeared-heat-source Drift-scale Thermal-conduction (SDT), Line-average-heat-source Drift-scale Thermohydrologic (LDTH), Discrete-heat-source Drift-scale Thermal-conduction (DDT), and Smeared-heat-source Mountain-scale Thermal-conduction (SMT) submodels such that the flow of water and water vapor through partially-saturated fractured rock is considered. The MSTHM accounts for 3-D drift-scale and mountain-scale heat flow, repository-scale variability of stratigraphy and infiltration flux, and waste package (WP)-to-WP variability in heat output from WPs. All submodels use the nonisothermal unsaturated-saturated flow and transport (NUFT) simulation code. The MSTHM is implemented in several data-processing steps. The four major steps are: (1) submodel input-file preparation, (2) execution of the four submodel families with the use of the NUFT code, (3) execution of the multiscale thermohydrologic abstraction code (MSTHAC), and (4) binning and post-processing (i.e., graphics preparation) of the output from MSTHAC. Section 6 describes the MSTHM in detail. The objectives of this Analyses and Model Report (AMR) are to investigate near field (NF) and EBS thermohydrologic environments throughout the repository area at various evolution periods, and to provide TH data that may be used in other process model reports.
Yi-Lwun Ho; Chen Lin; Yen-Hung Lin; Men-Tzung Lo
2011-01-01
AIMS: The influences of nonstationarity and nonlinearity on heart rate time series can be mathematically qualified or quantified by multiscale entropy (MSE). The aim of this study is to investigate the prognostic value of parameters derived from MSE in the patients with systolic heart failure. METHODS AND RESULTS: Patients with systolic heart failure were enrolled in this study. One month after clinical condition being stable, 24-hour Holter electrocardiogram was recording. MSE as well as oth...
Hsien-Tsai Wu; Chih-Yuan Lee; Cyuan-Cin Liu; An-Bang Liu
2013-01-01
Physiological signals often show complex fluctuation (CF) under the dual influence of temporal and spatial scales, and CF can be used to assess the health of physiologic systems in the human body. This study applied multiscale cross-approximate entropy (MC-ApEn) to quantify the complex fluctuation between R-R intervals series and photoplethysmography amplitude series. All subjects were then divided into the following two groups: healthy upper middle-aged subjects (Group 1, age range: 41–80 ye...
Ming-Shu Chen; Jiang, Bernard C.
2014-01-01
Falls are unpredictable accidents, and the resulting injuries can be serious in the elderly, particularly those with chronic diseases. Regular exercise is recommended to prevent and treat hypertension and other chronic diseases by reducing clinical blood pressure. The “complexity index” (CI), based on multiscale entropy (MSE) algorithm, has been applied in recent studies to show a person's adaptability to intrinsic and external perturbations and widely used measure of postural sway or stabili...
Directory of Open Access Journals (Sweden)
Ming-Shu Chen
2014-01-01
Full Text Available Falls are unpredictable accidents, and the resulting injuries can be serious in the elderly, particularly those with chronic diseases. Regular exercise is recommended to prevent and treat hypertension and other chronic diseases by reducing clinical blood pressure. The “complexity index” (CI, based on multiscale entropy (MSE algorithm, has been applied in recent studies to show a person’s adaptability to intrinsic and external perturbations and widely used measure of postural sway or stability. The multivariate multiscale entropy (MMSE was advanced algorithm used to calculate the complexity index (CI values of the center of pressure (COP data. In this study, we applied the MSE & MMSE to analyze gait function of 24 elderly, chronically ill patients (44% female; 56% male; mean age, 67.56±10.70 years with either cardiovascular disease, diabetes mellitus, or osteoporosis. After a 12-week training program, postural stability measurements showed significant improvements. Our results showed beneficial effects of resistance training, which can be used to improve postural stability in the elderly and indicated that MMSE algorithms to calculate CI of the COP data were superior to the multiscale entropy (MSE algorithm to identify the sense of balance in the elderly.
Chen, Ming-Shu; Jiang, Bernard C
2014-01-01
Falls are unpredictable accidents, and the resulting injuries can be serious in the elderly, particularly those with chronic diseases. Regular exercise is recommended to prevent and treat hypertension and other chronic diseases by reducing clinical blood pressure. The "complexity index" (CI), based on multiscale entropy (MSE) algorithm, has been applied in recent studies to show a person's adaptability to intrinsic and external perturbations and widely used measure of postural sway or stability. The multivariate multiscale entropy (MMSE) was advanced algorithm used to calculate the complexity index (CI) values of the center of pressure (COP) data. In this study, we applied the MSE & MMSE to analyze gait function of 24 elderly, chronically ill patients (44% female; 56% male; mean age, 67.56 ± 10.70 years) with either cardiovascular disease, diabetes mellitus, or osteoporosis. After a 12-week training program, postural stability measurements showed significant improvements. Our results showed beneficial effects of resistance training, which can be used to improve postural stability in the elderly and indicated that MMSE algorithms to calculate CI of the COP data were superior to the multiscale entropy (MSE) algorithm to identify the sense of balance in the elderly. PMID:25295070
Multiscale entropy to distinguish physiologic and synthetic RR time series.
Costa, M; Goldberger, A L; Peng, C-K
2002-01-01
We address the challenge of distinguishing physiologic interbeat interval time series from those generated by synthetic algorithms via a newly developed multiscale entropy method. Traditional measures of time series complexity only quantify the degree of regularity on a single time scale. However, many physiologic variables, such as heart rate, fluctuate in a very complex manner and present correlations over multiple time scales. We have proposed a new method to calculate multiscale entropy from complex signals. In order to distinguish between physiologic and synthetic time series, we first applied the method to a learning set of RR time series derived from healthy subjects. We empirically established selected criteria characterizing the entropy dependence on scale factor for these datasets. We then applied this algorithm to the CinC 2002 test datasets. Using only the multiscale entropy method, we correctly classified 48 of 50 (96%) time series. In combination with Fourier spectral analysis, we correctly classified all time series. PMID:14686448
Complexity multiscale asynchrony measure and behavior for interacting financial dynamics
Yang, Ge; Wang, Jun; Niu, Hongli
2016-08-01
A stochastic financial price process is proposed and investigated by the finite-range multitype contact dynamical system, in an attempt to study the nonlinear behaviors of real asset markets. The viruses spreading process in a finite-range multitype system is used to imitate the interacting behaviors of diverse investment attitudes in a financial market, and the empirical research on descriptive statistics and autocorrelation behaviors of return time series is performed for different values of propagation rates. Then the multiscale entropy analysis is adopted to study several different shuffled return series, including the original return series, the corresponding reversal series, the random shuffled series, the volatility shuffled series and the Zipf-type shuffled series. Furthermore, we propose and compare the multiscale cross-sample entropy and its modification algorithm called composite multiscale cross-sample entropy. We apply them to study the asynchrony of pairs of time series under different time scales.
The Magnetospheric Multiscale Magnetometers
Russell, C. T.; Anderson, B. J.; Baumjohann, W.; Bromund, K. R.; Dearborn, D.; Fischer, D.; Le, G.; Leinweber, H. K.; Leneman, D.; Magnes, W.; Means, J. D.; Moldwin, M. B.; Nakamura, R.; Pierce, D.; Plaschke, F.; Rowe, K. M.; Slavin, J. A.; Strangeway, R. J.; Torbert, R.; Hagen, C.; Jernej, I.; Valavanoglou, A.; Richter, I.
2016-03-01
The success of the Magnetospheric Multiscale mission depends on the accurate measurement of the magnetic field on all four spacecraft. To ensure this success, two independently designed and built fluxgate magnetometers were developed, avoiding single-point failures. The magnetometers were dubbed the digital fluxgate (DFG), which uses an ASIC implementation and was supplied by the Space Research Institute of the Austrian Academy of Sciences and the analogue magnetometer (AFG) with a more traditional circuit board design supplied by the University of California, Los Angeles. A stringent magnetic cleanliness program was executed under the supervision of the Johns Hopkins University's Applied Physics Laboratory. To achieve mission objectives, the calibration determined on the ground will be refined in space to ensure all eight magnetometers are precisely inter-calibrated. Near real-time data plays a key role in the transmission of high-resolution observations stored on board so rapid processing of the low-resolution data is required. This article describes these instruments, the magnetic cleanliness program, and the instrument pre-launch calibrations, the planned in-flight calibration program, and the information flow that provides the data on the rapid time scale needed for mission success.
Nonparametric sparsification of complex multiscale networks.
Directory of Open Access Journals (Sweden)
Nicholas J Foti
Full Text Available Many real-world networks tend to be very dense. Particular examples of interest arise in the construction of networks that represent pairwise similarities between objects. In these cases, the networks under consideration are weighted, generally with positive weights between any two nodes. Visualization and analysis of such networks, especially when the number of nodes is large, can pose significant challenges which are often met by reducing the edge set. Any effective "sparsification" must retain and reflect the important structure in the network. A common method is to simply apply a hard threshold, keeping only those edges whose weight exceeds some predetermined value. A more principled approach is to extract the multiscale "backbone" of a network by retaining statistically significant edges through hypothesis testing on a specific null model, or by appropriately transforming the original weight matrix before applying some sort of threshold. Unfortunately, approaches such as these can fail to capture multiscale structure in which there can be small but locally statistically significant similarity between nodes. In this paper, we introduce a new method for backbone extraction that does not rely on any particular null model, but instead uses the empirical distribution of similarity weight to determine and then retain statistically significant edges. We show that our method adapts to the heterogeneity of local edge weight distributions in several paradigmatic real world networks, and in doing so retains their multiscale structure with relatively insignificant additional computational costs. We anticipate that this simple approach will be of great use in the analysis of massive, highly connected weighted networks.
Multi-Scale Pattern Recognition for Image Classification and Segmentation
Li, Y.
2013-01-01
Scale is an important parameter of images. Different objects or image structures (e.g. edges and corners) can appear at different scales and each is meaningful only over a limited range of scales. Multi-scale analysis has been widely used in image processing and computer vision, serving as the basi
Multiscale coupling:challenges and opportunities
Institute of Scientific and Technical Information of China (English)
HE Guowei; XIA Mengfen; KE Fuju; BAI Yilong
2004-01-01
Multiscale coupling is ubiquitous in nature and attracts broad interests of scientists from mathematicians, physicists, machinists, chemists to biologists. However, much less attention has been paid to its intrinsic implication. In this paper, multiscale coupling is introduced by studying two typical examples in classic mechanics: fluid turbulence and solid failure. The nature of multiscale coupling in the two examples lies in their physical diversities and strong coupling over wide-range scales. The theories of dynamical system and statistical mechanics provide fundamental methods for the multiscale coupling problems. The diverse multiscale couplings call for unified approaches and might expedite new concepts, theories and disciplines.
Gwak, Yunki; Moon, Janghyuk; Cho, Maenghyo
2016-03-01
The electrochemical performance of Li-ion batteries strongly depends on the interaction between atomic scale and micro scale phenomena in high capacity electrode materials such as silicon and sulfur. Local thermodynamic interactions between host and guest species on atomic-scale significantly influence transfer kinetics and deformation kinematics on the micro-scale. We propose a multi-scale model to characterize the electrochemical and mechanical response of an amorphous silicon thin film during discharge/charge cycling. In the atomic-scale simulation, the stress-dependent energy barrier for the migration of lithium and the molar excess Gibbs free energy were calculated using density functional theory. These atomic-scale effects account for the nonlinear lithium diffusion behavior in the continuum simulation. In the continuum simulation, we considered the coupled diffusion and large deformation model on the cell-scale to determine the non-equilibrium cell potential as a function of the surface lithium concentration using Butler-Volmer kinetics. We clearly show that Li macroscopic kinetics is significantly affected by the stress induced by the volumetric strain associated with diffusion and the mixing formation energy of LixSi. Our simulation results demonstrate that the multi-scale model is consistent with experimental observations at different C-rates.
Multiscale Image Based Flow Visualization
Telea, Alexandru; Strzodka, Robert
2006-01-01
We present MIBFV, a method to produce real-time, multiscale animations of flow datasets. MIBFV extends the attractive features of the Image-Based Flow Visualization (IBFV) method, i.e. dense flow domain coverage with flow-aligned noise, real-time animation, implementation simplicity, and few (or no)
Generalized multiscale finite element methods for problems in perforated heterogeneous domains
Chung, Eric T.
2015-06-08
Complex processes in perforated domains occur in many real-world applications. These problems are typically characterized by physical processes in domains with multiple scales. Moreover, these problems are intrinsically multiscale and their discretizations can yield very large linear or nonlinear systems. In this paper, we investigate multiscale approaches that attempt to solve such problems on a coarse grid by constructing multiscale basis functions in each coarse grid, where the coarse grid can contain many perforations. In particular, we are interested in cases when there is no scale separation and the perforations can have different sizes. In this regard, we mention some earlier pioneering works, where the authors develop multiscale finite element methods. In our paper, we follow Generalized Multiscale Finite Element Method (GMsFEM) and develop a multiscale procedure where we identify multiscale basis functions in each coarse block using snapshot space and local spectral problems. We show that with a few basis functions in each coarse block, one can approximate the solution, where each coarse block can contain many small inclusions. We apply our general concept to (1) Laplace equation in perforated domains; (2) elasticity equation in perforated domains; and (3) Stokes equations in perforated domains. Numerical results are presented for these problems using two types of heterogeneous perforated domains. The analysis of the proposed methods will be presented elsewhere. © 2015 Taylor & Francis
Ding, Jiao; Jiang, Yuan; Liu, Qi; Hou, Zhaojiang; Liao, Jianyu; Fu, Lan; Peng, Qiuzhi
2016-05-01
Understanding the relationships between land use patterns and water quality in low-order streams is useful for effective landscape planning to protect downstream water quality. A clear understanding of these relationships remains elusive due to the heterogeneity of land use patterns and scale effects. To better assess land use influences, we developed empirical models relating land use patterns to the water quality of low-order streams at different geomorphic regions across multi-scales in the Dongjiang River basin using multivariate statistical analyses. The land use pattern was quantified in terms of the composition, configuration and hydrological distance of land use types at the reach buffer, riparian corridor and catchment scales. Water was sampled under summer base flow at 56 low-order catchments, which were classified into two homogenous geomorphic groups. The results indicated that the water quality of low-order streams was most strongly affected by the configuration metrics of land use. Poorer water quality was associated with higher patch densities of cropland, orchards and grassland in the mountain catchments, whereas it was associated with a higher value for the largest patch index of urban land use in the plain catchments. The overall water quality variation was explained better by catchment scale than by riparian- or reach-scale land use, whereas the spatial scale over which land use influenced water quality also varied across specific water parameters and the geomorphic basis. Our study suggests that watershed management should adopt better landscape planning and multi-scale measures to improve water quality. PMID:26878633
Analysis of Sleep EEG by Using Multi-Scale Entropy%睡眠EEG的多尺度信息熵分析
Institute of Scientific and Technical Information of China (English)
宦飞; 王志中; 郑崇勋
2001-01-01
Based on application of continuous wavelet transform, a new method for analyzing sleep EEG is presented.The wavelet transform coefficients of the EEG signals are computed by using Morlet's wavelet. The information content carried by the wavelet coefficients on any scale is measured with entropy. Analyzing sleep EEG, it may be observed that the change in the multi-scale entropy of the EEG signals in light sleep stage is different from that in deep sleep stage, and the change in the multiscale entropy of the EEG signals in REM sleep stage is similar to that in deep sleep. By this method, we can distinguish thecharacteristics of the EEG in light sleep stage and that in the REM sleep stage.%本文提出一种基于连续小波变换的睡眠EEG分析方法。该方法使用Morlet小波计算EEG信息的小波变换系数，通过计算EEG信号在多个尺度上小波系数的熵分析睡眠EEG。结果表明：浅睡阶段EEG信号的多尺度熵的变化模式与深睡阶段的多尺度熵的变化模式不同，REM睡眠期间EEG信号的多尺度熵的变化与深睡阶段类似，使用多尺度熵可以区分REM睡眠和浅睡时EEG之间的差别。
Randomized Oversampling for Generalized Multiscale Finite Element Methods
Calo, Victor M.
2016-03-23
In this paper, we develop efficient multiscale methods for flows in heterogeneous media. We use the generalized multiscale finite element (GMsFEM) framework. GMsFEM approximates the solution space locally using a few multiscale basis functions. This approximation selects an appropriate snapshot space and a local spectral decomposition, e.g., the use of oversampled regions, in order to achieve an efficient model reduction. However, the successful construction of snapshot spaces may be costly if too many local problems need to be solved in order to obtain these spaces. We use a moderate quantity of local solutions (or snapshot vectors) with random boundary conditions on oversampled regions with zero forcing to deliver an efficient methodology. Motivated by the randomized algorithm presented in [P. G. Martinsson, V. Rokhlin, and M. Tygert, A Randomized Algorithm for the approximation of Matrices, YALEU/DCS/TR-1361, Yale University, 2006], we consider a snapshot space which consists of harmonic extensions of random boundary conditions defined in a domain larger than the target region. Furthermore, we perform an eigenvalue decomposition in this small space. We study the application of randomized sampling for GMsFEM in conjunction with adaptivity, where local multiscale spaces are adaptively enriched. Convergence analysis is provided. We present representative numerical results to validate the method proposed.
基于多尺度几何分析的SAR图像融合%An SAR Image Fusion Method Based on Multiscale Geometrical Analysis
Institute of Scientific and Technical Information of China (English)
李志希; 孔令讲; 贾勇; 柯晓东; 赵中兴
2014-01-01
For through-wall-radar imaging,the image of building layout is conducive to implementing target localization and multi-path suppression.The current access to the building image is obtained by multi-channel and multi-view image fusion.In this paper,an image fusion method based on multiscale geometric analysis,namely wavelet transform(WT)is proposed to form a panorama image of building layout.The method is divided into two stages.The first stage refers to the multi-channel image fusion.The purpose of this stage is to enhance image details and improve image definition.Hence the fusion method of high frequency of the sub-images after WT is based on average gradient improvement.For the low frequency sub-image,average coefficient is adopted, then several single view images is obtained through inverse wavelet transform.The second stage refers to the multi-view image fusion.The purpose of this stage is to enhance the contrast of image.Given that the image contrast of high frequency of multi-view sub-images differs from one another,the fusion method of high frequency of the sub-image is based on image contrast improvement.For the low frequency sub-image,average coefficient is adopted.Then,the final image is obtained through inverse wavelet transform by the low frequency image and the high frequency images.Simulation results show that the proposed algorithm can enhance the peak signal to noise ratio(PSNR),leading to noticeable improvement in visual quality.%在穿墙雷达成像技术中，建筑布局成像对确定墙后人体目标的空间相对位置以及多径虚假目标的提取有重要意义。目前的建筑布局成像一般采用多通道多视角图像融合方法，对此提出一种基于多尺度分析，即基于小波分解下的多通道多视角图像融合算法。该算法分为两个阶段，第一阶段涉及到单视角下的多通道图像融合，该阶段的融合目的主要是为增强图像细节信息和提高图像清晰度。因此对其
Multi-scale roughness transfer in cold metal rolling
Plouraboué, Franck; Boehm, Matthieu
1999-01-01
We report on a comparative Atomic Force Microscope (AFM) multi-scale roughness analysis of cold rolled Al alloy and steel roll, in order to characterize the roughness transfer from the steel roll to the workpiece in cold strip rolling processes. More than three orders of length-scale magnitudes were investigated from 100 microns to 50 nanometers on both types of surfaces. The analysis reveals that both types of surfaces are anisotropic self-afﬁne surfaces. Transverse and longitudinal height p...
Multiscale Multifunctional Progressive Fracture of Composite Structures
Chamis, C. C.; Minnetyan, L.
2012-01-01
A new approach is described for evaluating fracture in composite structures. This approach is independent of classical fracture mechanics parameters like fracture toughness. It relies on computational simulation and is programmed in a stand-alone integrated computer code. It is multiscale, multifunctional because it includes composite mechanics for the composite behavior and finite element analysis for predicting the structural response. It contains seven modules; layered composite mechanics (micro, macro, laminate), finite element, updating scheme, local fracture, global fracture, stress based failure modes, and fracture progression. The computer code is called CODSTRAN (Composite Durability Structural ANalysis). It is used in the present paper to evaluate the global fracture of four composite shell problems and one composite built-up structure. Results show that the composite shells. Global fracture is enhanced when internal pressure is combined with shear loads. The old reference denotes that nothing has been added to this comprehensive report since then.
The Magnetospheric Multiscale Mission
Burch, James
Magnetospheric Multiscale (MMS), a NASA four-spacecraft mission scheduled for launch in November 2014, will investigate magnetic reconnection in the boundary regions of the Earth’s magnetosphere, particularly along its dayside boundary with the solar wind and the neutral sheet in the magnetic tail. Among the important questions about reconnection that will be addressed are the following: Under what conditions can magnetic-field energy be converted to plasma energy by the annihilation of magnetic field through reconnection? How does reconnection vary with time, and what factors influence its temporal behavior? What microscale processes are responsible for reconnection? What determines the rate of reconnection? In order to accomplish its goals the MMS spacecraft must probe both those regions in which the magnetic fields are very nearly antiparallel and regions where a significant guide field exists. From previous missions we know the approximate speeds with which reconnection layers move through space to be from tens to hundreds of km/s. For electron skin depths of 5 to 10 km, the full 3D electron population (10 eV to above 20 keV) has to be sampled at rates greater than 10/s. The MMS Fast-Plasma Instrument (FPI) will sample electrons at greater than 30/s. Because the ion skin depth is larger, FPI will make full ion measurements at rates of greater than 6/s. 3D E-field measurements will be made by MMS once every ms. MMS will use an Active Spacecraft Potential Control device (ASPOC), which emits indium ions to neutralize the photoelectron current and keep the spacecraft from charging to more than +4 V. Because ion dynamics in Hall reconnection depend sensitively on ion mass, MMS includes a new-generation Hot Plasma Composition Analyzer (HPCA) that corrects problems with high proton fluxes that have prevented accurate ion-composition measurements near the dayside magnetospheric boundary. Finally, Energetic Particle Detector (EPD) measurements of electrons and
A heterogeneous multiscale method for poroelasticity
Delgado, Paul M.
In this thesis, we develop and analyze a heterogeneous multiscale model for coupled fluid flow and solid deformation in porous media based on operator splitting and finite volume method. The splitting method results in two elliptic multiscale PDE's in the form of a reaction diffusion equation and a linear elasticity equation. We extend our previous multiscale method from 1D to higher dimensions and develop new approaches for the inclusion of mixed boundary conditions and source terms. We derive an error estimate for our multiscale method and analyze the stability of our splitting method. We also test the effectiveness of our method in the case of steady state linear poroelasticity.
Multiscale Modelling and Inverse Problems
Nolen, J; Stuart, A M
2010-01-01
The need to blend observational data and mathematical models arises in many applications and leads naturally to inverse problems. Parameters appearing in the model, such as constitutive tensors, initial conditions, boundary conditions, and forcing can be estimated on the basis of observed data. The resulting inverse problems are often ill-posed and some form of regularization is required. These notes discuss parameter estimation in situations where the unknown parameters vary across multiple scales. We illustrate the main ideas using a simple model for groundwater flow. We will highlight various approaches to regularization for inverse problems, including Tikhonov and Bayesian methods. We illustrate three ideas that arise when considering inverse problems in the multiscale context. The first idea is that the choice of space or set in which to seek the solution to the inverse problem is intimately related to whether a homogenized or full multiscale solution is required. This is a choice of regularization. The ...
Multi-scale MSDT inversion based on LAI spatial knowledge
Institute of Scientific and Technical Information of China (English)
ZHU XiaoHua; FENG XiaoMing; ZHAO YingShi
2012-01-01
Quantitative remote sensing inversion is ill-posed.The Moderate Resolution Imaging Spectroradiometer at 250 m resolution (MODIS_250m) contains two bands.To deal with this ill-posed inversion of MODIS_250m data,we propose a framework,the Multi-scale,Multi-stage,Sample-direction Dependent,Target-decisions (Multi-scale MSDT) inversion method,based on spatial knowledge.First,MODIS images (1 km,500 m,250 m) are used to extract multi-scale spatial knowledge.The inversion accuracy of MODIS_1km data is improved by reducing the impact of spatial heterogeneity.Then,coarse-scale inversion is taken as prior knowledge for the fine scale,again by inversion.The prior knowledge is updated after each inversion step.At each scale,MODIS_1km to MODIS_250m,the inversion is directed by the Uncertainty and Sensitivity Matrix (USM),and the most uncertain parameters are inversed by the most sensitive data.All remote sensing data are involved in the inversion,during which multi-scale spatial knowledge is introduced,to reduce the impact of spatial heterogeneity.The USM analysis is used to implement a reasonable allocation of limited remote sensing data in the model space.In the entire multi-scale inversion process,field data,spatial knowledge and multi-scale remote sensing data are all involved.As the multi-scale,multi-stage inversion is gradually refined,initial expectations of parameters become more reasonable and their uncertainty range is effectively reduced,so that the inversion becomes increasingly targeted.Finally,the method is tested by retrieving the Leaf Area Index (LAI) of the crop canopy in the Heihe River Basin.The results show that the proposed method is reliable.
Multiscale structure of sheet nacre.
Rousseau, Marthe; Lopez, Evelyne; Stempflé, Philippe; Brendlé, Marcel; Franke, Loïc; Guette, Alain; Naslain, Roger; Bourrat, Xavier
2005-01-01
This work was conducted on Pinctada maxima nacre (mother of pearl) in order to understand its multiscale ordering and the role of the organic matrix in its structure. Intermittent-contact atomic force microscopy with phase detection imaging reveals a nanostructure within the tablet. A continuous organic framework divides each tablet into nanograins. Their shape is supposed to be flat with a mean extension of 45 nm. TEM performed in the darkfield mode evidences that at least part of the intrac...
Multiscale expansions in discrete world
Indian Academy of Sciences (India)
Ömer Ünsal; Filiz Taşcan; Mehmet Naci Özer
2014-07-01
In this paper, we show the attainability of KdV equation from some types of nonlinear Schrödinger equation by using multiscale expansions discretely. The power of this manageable method is confirmed by applying it to two selected nonlinear Schrödinger evolution equations. This approach can also be applied to other nonlinear discrete evolution equations. All the computations have been made with Maple computer packet program.
Canonical transfer and multiscale energetics for primitive and quasi-geostrophic atmospheres
Liang, X San
2016-01-01
The past years have seen the success of a novel multiscale energetic formalism in a variety of ocean and engineering fluid applications. In a self-contained way, this study introduces it to the atmospheric dynamical diagnostics, with important theoretical updates. Multiscale energy equations are derived using a new analysis apparatus, namely, multiscale window transform, with respect to both the primitive equation and quasi-geostrophic models. A reconstruction of the "atomic" energy fluxes on the multiple scale windows allows for a natural and unique separation of the in-scale transports and cross-scale transfers from the intertwined nonlinear processes. The resulting energy transfers bear a Lie bracket form, reminiscent of the Poisson bracket in Hamiltonian mechanics, we hence would call them "canonical". A canonical transfer process is a mere redistribution of energy among scale windows, without generating or destroying energy as a whole. By classification, a multiscale energetic cycle comprises of availabl...
Mathematical and Numerical Analyses of Peridynamics for Multiscale Materials Modeling
Energy Technology Data Exchange (ETDEWEB)
Du, Qiang [Pennsylvania State Univ., State College, PA (United States)
2014-11-12
The rational design of materials, the development of accurate and efficient material simulation algorithms, and the determination of the response of materials to environments and loads occurring in practice all require an understanding of mechanics at disparate spatial and temporal scales. The project addresses mathematical and numerical analyses for material problems for which relevant scales range from those usually treated by molecular dynamics all the way up to those most often treated by classical elasticity. The prevalent approach towards developing a multiscale material model couples two or more well known models, e.g., molecular dynamics and classical elasticity, each of which is useful at a different scale, creating a multiscale multi-model. However, the challenges behind such a coupling are formidable and largely arise because the atomistic and continuum models employ nonlocal and local models of force, respectively. The project focuses on a multiscale analysis of the peridynamics materials model. Peridynamics can be used as a transition between molecular dynamics and classical elasticity so that the difficulties encountered when directly coupling those two models are mitigated. In addition, in some situations, peridynamics can be used all by itself as a material model that accurately and efficiently captures the behavior of materials over a wide range of spatial and temporal scales. Peridynamics is well suited to these purposes because it employs a nonlocal model of force, analogous to that of molecular dynamics; furthermore, at sufficiently large length scales and assuming smooth deformation, peridynamics can be approximated by classical elasticity. The project will extend the emerging mathematical and numerical analysis of peridynamics. One goal is to develop a peridynamics-enabled multiscale multi-model that potentially provides a new and more extensive mathematical basis for coupling classical elasticity and molecular dynamics, thus enabling next
International Nuclear Information System (INIS)
The NURESIM project, the numerical simulation platform, is developed in the frame of the NURISP European Collaborative Project (FP7), which includes 22 organizations from 14 European countries. NURESIM intends to be a reference platform providing high quality software tools, physical models, generic functions and assessment results. The NURESIM platform provides an accurate representation of the physical phenomena by promoting and incorporating the latest advances in core physics, two-phase thermal-hydraulics and fuel modelling. It includes multi-scale and multi-physics features, especially for coupling core physics and thermal-hydraulics models for reactor safety. Easy coupling of the different codes and solvers is provided through the use of a common data structure and generic functions (e.g., for interpolation between non-conforming meshes). More generally, the platform includes generic pre-processing, post-processing and supervision functions through the open-source SALOME software, in order to make the codes more user-friendly. The platform also provides the informatics environment for testing and comparing different codes. The contribution summarizes the achievements and ongoing developments of the simulation platform in core physics, thermal-hydraulics, multi-physics, uncertainties and code integration
Institute of Scientific and Technical Information of China (English)
Zhou Hongjian; Huang Shuling; Wang Yuanyuan; Wang Jing'ai; Jia Huicong
2006-01-01
Increasing populations are causing an increase in food demands, and the area of cultivated land expands every year. Inappropriate land transition from ecology to production results in the constant decline of the ecological security level and influences the regional sustainable development. Adjusting unreasonable land use mode and reconstructing natural land cover are important ways to maintain and improve the ecological environment. Also reclaiming farmland as areas for forests and grasslands (FRFG) is another way. Successful implementation of FRFG in China is the result of comprehensive effect of the multi-scales driving forces.This paper analyses the driving forces of FRFG in China on a national (country) -regional (province) - local(county) - household (farmer) level scale, and the results are: driving forces at the national scale include ecological and food security and the western development of China;at the regional scale, ecological and economic benefits become the main factors to influence the dimension of FRFG under the same policy. The driving forces can be divided into 6 types: industrial structure adjustment,water source protection, flood prevention, the Three-Gorge Project protection, reduction of the amount of sediment flowing into the Yellow River and wind erosion desertification prevention. The driving forces at the local scale can be divided into 12 types with developing leading industries, increasing farmers'income and improving agricultural production conditions as the main types; at the household scale, the national policy meeting farmers' demands and the optimization of individual interests are all driving forces.
Quantifying multiscale inefficiency in electricity markets
Energy Technology Data Exchange (ETDEWEB)
Uritskaya, Olga Y. [Department of Economics, University of Calgary, Calgary, Alberta T2N 1N4, and Department of Economics and Management, St. Petersburg Polytechnic University, St. Petersburg (Russian Federation); Serletis, Apostolos [Department of Economics, University of Calgary, Calgary, Alberta (Canada)
2008-11-15
One of the basic features of efficient markets is the absence of correlations between price increments over any time scale leading to random walk-type behavior of prices. In this paper, we propose a new approach for measuring deviations from the efficient market state based on an analysis of scale-dependent fractal exponent characterizing correlations at different time scales. The approach is applied to two electricity markets, Alberta and Mid Columbia (Mid-C), as well as to the AECO Alberta natural gas market (for purposes of providing a comparison between storable and non-storable commodities). We show that price fluctuations in all studied markets are not efficient, with electricity prices exhibiting complex multiscale correlated behavior not captured by monofractal methods used in previous studies. (author)
Multiscales and cascade in isotropic turbulence
Ran, Zheng
2010-01-01
The central problem of fully developed turbulence is the energy cascading process. It has revisited all attempts at a full physical understanding or mathematical formulation. The main reason for this failure are related to the large hierarchy of scales involved, the highly nonlinear character inherent in the Navier-Stokes equations, and the spatial intermittency of the dynamically active regions. Richardson has described the interplay between large and small scales and the phenomena so described are known as the Richardson cascade. This local interplay also forms the basis of a theory by Kolmogorov. In this letter, we use the explicit map method to analyze the nonlinear dynamical behavior for cascade in isotropic turbulence. This deductive scale analysis is shown to provide the first visual evidence of the celebrated Richardson cascade, and reveals in particular its multiscale character. The results also indicate that the energy cascading process has remarkable similarities with the deterministic construction...
Multi-scale modelling of elastic moduli of trabecular bone
Hamed, Elham; Jasiuk, Iwona; Yoo, Andrew; Lee, YikHan; Liszka, Tadeusz
2012-01-01
We model trabecular bone as a nanocomposite material with hierarchical structure and predict its elastic properties at different structural scales. The analysis involves a bottom-up multi-scale approach, starting with nanoscale (mineralized collagen fibril) and moving up the scales to sub-microscale (single lamella), microscale (single trabecula) and mesoscale (trabecular bone) levels. Continuum micromechanics methods, composite materials laminate theory and finite-element methods are used in...
The Multiscale Entropy Algorithm and Its Variants: A Review
Anne Humeau-Heurtier
2015-01-01
Multiscale entropy (MSE) analysis was introduced in the 2002 to evaluate the complexity of a time series by quantifying its entropy over a range of temporal scales. The algorithm has been successfully applied in different research fields. Since its introduction, a number of modifications and refinements have been proposed, some aimed at increasing the accuracy of the entropy estimates, others at exploring alternative coarse-graining procedures. In this review, we first describe the original M...
The Adaptive Multi-scale Simulation Infrastructure
Energy Technology Data Exchange (ETDEWEB)
Tobin, William R. [Rensselaer Polytechnic Inst., Troy, NY (United States)
2015-09-01
The Adaptive Multi-scale Simulation Infrastructure (AMSI) is a set of libraries and tools developed to support the development, implementation, and execution of general multimodel simulations. Using a minimal set of simulation meta-data AMSI allows for minimally intrusive work to adapt existent single-scale simulations for use in multi-scale simulations. Support for dynamic runtime operations such as single- and multi-scale adaptive properties is a key focus of AMSI. Particular focus has been spent on the development on scale-sensitive load balancing operations to allow single-scale simulations incorporated into a multi-scale simulation using AMSI to use standard load-balancing operations without affecting the integrity of the overall multi-scale simulation.
DMS: A Package for Multiscale Molecular Dynamics
Somogyi, Endre; Ortoleva, Peter J
2013-01-01
Advances in multiscale theory and computation provide a novel paradigm for simulating many-classical particle systems. The Deductive Multiscale Simulator (DMS) is a multiscale molecular dynamics (MD) program built on two of these advances, i.e., multiscale Langevin (ML) and multiscale factorization (MF). Both capture the coevolution of the the coarse-grained (CG) state and the microstate. This provides these methods with great efficiency over conventional MD. Neither involve the introduction of phenomenological governing equations for the CG state with attendant uncertainty in both their form of the governing equations and the data needed to calibrate them. The design and implementation of DMS as an open source computational platform is presented here. DMS is written in Python, uses Gromacs to achieve the microphase, and then advances the microstate via a CG-guided evolution. DMS uses MDAnalysis, a Python library for analyzing MD trajectories, to perform computations required to construct CG-related variables...
Multiscale empirical interpolation for solving nonlinear PDEs
Calo, Victor M.
2014-12-01
In this paper, we propose a multiscale empirical interpolation method for solving nonlinear multiscale partial differential equations. The proposed method combines empirical interpolation techniques and local multiscale methods, such as the Generalized Multiscale Finite Element Method (GMsFEM). To solve nonlinear equations, the GMsFEM is used to represent the solution on a coarse grid with multiscale basis functions computed offline. Computing the GMsFEM solution involves calculating the system residuals and Jacobians on the fine grid. We use empirical interpolation concepts to evaluate these residuals and Jacobians of the multiscale system with a computational cost which is proportional to the size of the coarse-scale problem rather than the fully-resolved fine scale one. The empirical interpolation method uses basis functions which are built by sampling the nonlinear function we want to approximate a limited number of times. The coefficients needed for this approximation are computed in the offline stage by inverting an inexpensive linear system. The proposed multiscale empirical interpolation techniques: (1) divide computing the nonlinear function into coarse regions; (2) evaluate contributions of nonlinear functions in each coarse region taking advantage of a reduced-order representation of the solution; and (3) introduce multiscale proper-orthogonal-decomposition techniques to find appropriate interpolation vectors. We demonstrate the effectiveness of the proposed methods on several nonlinear multiscale PDEs that are solved with Newton\\'s methods and fully-implicit time marching schemes. Our numerical results show that the proposed methods provide a robust framework for solving nonlinear multiscale PDEs on a coarse grid with bounded error and significant computational cost reduction.
Multiscale structure of meanders
Vermeulen, B.; Hoitink, A.J.F.; Zolezzi, G.; Abad, J.D.; Aalto, R.
2016-01-01
River meander planforms can be described based on wavelet analysis, but an objective method to identify the main characteristics of a meander planform over all spatial scales is yet to be found. Here we show how a set of simple metrics representing meander shape can be retrieved from a continuous
Implementing Multiscale Fluid Simulations using Multiscale Universal Interface
Tang, Yu-Hang; Kudo, Shuhei; Bian, Xin; Li, Zhen; Karniadakis, George; Crunch Team
2015-11-01
The power of multiscale fluid simulations lies in its ability to recover a hierarchical levels of details by choreographing multiple solvers, thus extending the length and time scale accessible given a fixed amount of computing power. However, practical difficulties frequently arise when stitching together solvers which were not designed to be coupled, and would often result in tedious and unsustainable coding effort. The Multiscale Universal Interface (MUI) aims to solve this problem by exposing a small set of generalized programming interfaces that can be dropped into existing solvers with minimal intrusion. Three deployment cases will be given for demonstrating real-world applications of MUI. In the first case we used MUI to implement simulations of polymer-grafted surface in flow using Smoothed Particle Hydrodynamics/Dissipative Particle Dynamics (SPH/DPD) and state variable coupling. In the second case we constructed coupled DPD/Finite Element Method (FEM) simulation of conjugate heat transfer in heterogeneous coolant. In the third case we built hybrid DPD/molecular dynamics (MD) simulations by blending the forces on atoms at interface regions. Supported by the DOE Collaboratory on Mathematics for Mesoscopic Modeling of Materials (CM4) and AFOSR FA9550-12-1-0463. Computer hours at ORNL allocated through INCITE BIP118 and DD102.
Multiscale hierarchical support vector clustering
Hansen, Michael Saas; Holm, David Alberg; Sjöstrand, Karl; Ley, Carsten Dan; Rowland, Ian John; Larsen, Rasmus
2008-03-01
Clustering is the preferred choice of method in many applications, and support vector clustering (SVC) has proven efficient for clustering noisy and high-dimensional data sets. A method for multiscale support vector clustering is demonstrated, using the recently emerged method for fast calculation of the entire regularization path of the support vector domain description. The method is illustrated on artificially generated examples, and applied for detecting blood vessels from high resolution time series of magnetic resonance imaging data. The obtained results are robust while the need for parameter estimation is reduced, compared to support vector clustering.
Survey of multiscale and multiphysics applications and communities
Groen D.; Zasada S.J.; Coveney P.V.
2014-01-01
Multiscale and multiphysics applications are now commonplace, and many researchers focus on combining existing models to construct combined multiscale models. Here we present a concise review of multiscale applications and their source communities. We investigate the prevalence of multiscale projects in the EU and the US, review a range of coupling toolkits they use to construct multiscale models and identify areas where collaboration between disciplines could be particularly beneficial. We c...
Scafetta, Nicola
2013-01-01
Herein we adopt a multi-scale dynamical spectral analysis technique to compare and study the dynamical evolution of the harmonic components of the overlapping ACRIMSAT/ACRIM3, SOHO/VIRGO and SORCE/TIM total solar irradiance (TSI) records during 2003.15 to 2013.16 in solar cycles 23 and 24. The three TSI time series present highly correlated patterns. Significant power spectral peaks are common to these records and are observed at the following periods: 0.070 year, 0.097 year, 0.20 year, 0.25 year, 0.30-0.34 year, 0.39 year. Less certain spectral peaks occur at about 0.55 year, 0.60-0.65 year and 0.7-0.9 year. Four main frequency periods at 24.8 days (0.068 year), 27.3 days (0.075 year), at 34-35 days (0.093-0.096 year) and 36-38 days (0.099-0.104 year) characterize the solar rotation cycle. The amplitude of these oscillations, in particular of those with periods larger than 0.5 year, appears to be modulated by the 11-year solar cycle. Similar harmonics have been found in other solar indices. The observed peri...
Multiscale ground aurora observations
Kozelov, Boris
Aurora is the most impressive phenomenon that initially motivates people's interest in the study of near-Earth space. Now auroral observations provide unique information about the processes occurring in the magnetosphere-ionosphere plasma: this is the only type of observations that gives detailed two-dimensional spatial distribution with sufficient temporal resolution. Fractal power-law distributions that are typical for aurora indicate the passing transients in near-Earth plasma. Spatio-temporal dynamics of active auroral forms on the night side is showing signs of turbulence and self-organized criticality at huge range of scales. Pulsing auroral forms are usually associated with the wave-particle interaction. The report describes the current state of the ground-based optical observations of aurorae at different scales and methods of analysis of their results.
Biomedical Engineering Bionanosystems Research at Louisiana Tech University
Energy Technology Data Exchange (ETDEWEB)
Palmer, James; Lvov, Yuri; Hegab, Hisham; Snow, Dale; Wilson, Chester; McDonald, John; Walker, Lynn; Pratt, Jon; Davis, Despina; Agarwal, Mangilal; DeCoster, Mark; Feng, June; Que, Long; O' Neal, Chad; Guilbeau, Eric; Zivanovic, Sandra; Dobbins, Tabbetha; Gold, Scott; Mainardi, Daniela; Gowda, Shathabish; Napper, Stan
2010-03-25
The nature of this project is to equip and support research in nanoengineered systems for biomedical, bioenvironmental, and bioenergy applications. Funds provided by the Department of Energy (DoE) under this Congressional Directive were used to support two ongoing research projects at Louisiana Tech University in biomedical, bioenvironmental, and bioenergy applications. Two major projects (Enzyme Immobilization for Large Scale Reactors to Reduce Cellulosic Ethanol Costs, and Nanocatalysts for Coal and Biomass Conversion to Diesel Fuel) and to fund three to five additional seed projects were funded using the project budget. The project funds also allowed the purchase and repair of sophisticated research equipment that will support continued research in these areas for many years to come. Project funds also supported faculty, graduate students, and undergraduate students, contributing to the development of a technically sophisticated work force in the region and the State. Descriptions of the technical accomplishments for each funded project are provided. Biofuels are an important part of the solution for sustainable transportation fuel and energy production for the future. Unfortunately, the country's appetite for fuel cannot be satisfied with traditional sugar crops such as sugar cane or corn. Emerging technologies are allowing cellulosic biomass (wood, grass, stalks, etc.) to also be converted into ethanol. Cellulosic ethanol does not compete with food production and it has the potential to decrease greenhouse gas (GHG) emissions by 86% versus current fossil fuels (current techniques for corn ethanol only reduce greenhouse gases by 19%). Because of these advantages, the federal government has made cellulosic ethanol a high priority. The Energy Independence and Security Act of 2007 (EISA) requires a minimum production of at least 16 billion gallons of cellulosic ethanol by 2022. Indeed, the Obama administration has signaled an ambitious commitment of achieving 2 billion gallons of cellulosic ethanol by 2013. Louisiana is well positioned to become a national contributor in cellulosic ethanol, with an excellent growing season, a strong pulp/paper industry, and one of the nation's first cellulosic ethanol demonstration plants. Dr. Palmer in Chemical Engineering at Louisiana Tech University is collaborating with Drs. Lvov and Snow in Chemistry and Dr. Hegab in Mechanical Engineering to capitalize on these advantages by applying nanotechnology to improve the cellulosic ethanol processes. In many of these processes, expensive enzymes are used to convert the cellulose to sugars. The nanotechnology processes developed at Louisiana Tech University can immobilize these enzymes and therefore significantly reduce the overall costs of the process. Estimates of savings range from approximately $32 million at each cellulosic ethanol plant, to $7.5 billion total if the 16 billion gallons of cellulosic ethanol is achieved. This process has the advantage of being easy to apply in a large-scale commercial environment and can immobilize a wide variety or mixture of enzymes for production. Two primary objectives with any immobilization technique are to demonstrate reusability and catalytic activity (both reuse of the immobilized enzyme and reuse of the polymer substrate). The scale-up of the layering-by-layering process has been a focus this past year as some interesting challenges in the surface chemistry have become evident. Catalytic activity of cellulase is highly dependent upon how the feed material is pretreated to enhance digestion. Therefore, efforts this year have been performed this year to characterize our process on a few of the more prevalent pretreatment methods.
Triad interactions in multi-scale ITG/TEM/ETG turbulence
Maeyama, Shinya; Watanabe, Tomohiko; Idomura, Yasuhiro; Nakata, Motoki; Ishizawa, Akihiro; Nunami, Masanori
2015-11-01
Most of turbulent transport studies assume scale separation between electron- and ion-scale turbulence. However, latest massively parallel simulations based on gyrokinetics reveal that multi-scale interactions between electron- and ion-scale turbulence can influence turbulent transport [S. Maeyama, Phys. Rev. Lett. 114, 255002 (2015)]. The physical mechanism is investigated by applying triad transfer analysis. It is revealed that short-wave-length ITG turbulent eddies stabilize electron-scale streamers. Additionally, it is found that electron-scale turbulence has a damping effect on zonal flows. As a result, turbulent transport spectrum obtained from the multi-scale turbulence simulation differs from the sum of ones obtained from single-scale simulations. We will discuss gyrokinetic triad transfer analysis and the applicability of its fluid approximation, and explain the physical mechanism of multi-scale interactions by means of triad transfer analysis.
Integrated Multiscale Latent Variable Regression and Application to Distillation Columns
Directory of Open Access Journals (Sweden)
Muddu Madakyaru
2013-01-01
Full Text Available Proper control of distillation columns requires estimating some key variables that are challenging to measure online (such as compositions, which are usually estimated using inferential models. Commonly used inferential models include latent variable regression (LVR techniques, such as principal component regression (PCR, partial least squares (PLS, and regularized canonical correlation analysis (RCCA. Unfortunately, measured practical data are usually contaminated with errors, which degrade the prediction abilities of inferential models. Therefore, noisy measurements need to be filtered to enhance the prediction accuracy of these models. Multiscale filtering has been shown to be a powerful feature extraction tool. In this work, the advantages of multiscale filtering are utilized to enhance the prediction accuracy of LVR models by developing an integrated multiscale LVR (IMSLVR modeling algorithm that integrates modeling and feature extraction. The idea behind the IMSLVR modeling algorithm is to filter the process data at different decomposition levels, model the filtered data from each level, and then select the LVR model that optimizes a model selection criterion. The performance of the developed IMSLVR algorithm is illustrated using three examples, one using synthetic data, one using simulated distillation column data, and one using experimental packed bed distillation column data. All examples clearly demonstrate the effectiveness of the IMSLVR algorithm over the conventional methods.
A Multiscale Enrichment Procedure for Nonlinear Monotone Operators
Efendiev, Yalchin R.
2014-03-11
In this paper, multiscale finite element methods (MsFEMs) and domain decomposition techniques are developed for a class of nonlinear elliptic problems with high-contrast coefficients. In the process, existing work on linear problems [Y. Efendiev, J. Galvis, R. Lazarov, S. Margenov and J. Ren, Robust two-level domain decomposition preconditioners for high-contrast anisotropic flows in multiscale media. Submitted.; Y. Efendiev, J. Galvis and X. Wu, J. Comput. Phys. 230 (2011) 937–955; J. Galvis and Y. Efendiev, SIAM Multiscale Model. Simul. 8 (2010) 1461–1483.] is extended to treat a class of nonlinear elliptic operators. The proposed method requires the solutions of (small dimension and local) nonlinear eigenvalue problems in order to systematically enrich the coarse solution space. Convergence of the method is shown to relate to the dimension of the coarse space (due to the enrichment procedure) as well as the coarse mesh size. In addition, it is shown that the coarse mesh spaces can be effectively used in two-level domain decomposition preconditioners. A number of numerical results are presented to complement the analysis.
Multi-scale interactions in Dictyostelium discoideum aggregation
Dixon, James A.; Kelty-Stephen, Damian G.
2012-12-01
Cellular aggregation is essential for a wide range of phenomena in developmental biology, and a crucial event in the life-cycle of Dictyostelium discoideum. The current manuscript presents an analysis of multi-scale interactions involved in D. discoideum aggregation and non-aggregation events. The multi-scale fractal dimensions of a sequence of microscope images were used to estimate changing structure at different spatial scales. Three regions showing aggregation and three showing non-aggregation were considered. The results showed that both aggregation and non-aggregation regions were strongly multi-fractal. Analyses of the over-time relationships among nine scales of the generalized dimension, D(q), were conducted using vector autoregression and vector error-correction models. Both types of regions showed evidence that across-scale interactions serve to maintain the equilibrium of the system. Aggregation and non-aggregation regions also showed different patterns of effects of individual scales on other scales. Specifically, aggregation regions showed greater effects of both the smallest and largest scales on the smaller scale structures. The results suggest that multi-scale interactions are responsible for maintaining and altering the cellular structures during aggregation.
Generalized multiscale finite element method for elasticity equations
Chung, Eric T.
2014-10-05
In this paper, we discuss the application of generalized multiscale finite element method (GMsFEM) to elasticity equation in heterogeneous media. We consider steady state elasticity equations though some of our applications are motivated by elastic wave propagation in subsurface where the subsurface properties can be highly heterogeneous and have high contrast. We present the construction of main ingredients for GMsFEM such as the snapshot space and offline spaces. The latter is constructed using local spectral decomposition in the snapshot space. The spectral decomposition is based on the analysis which is provided in the paper. We consider both continuous Galerkin and discontinuous Galerkin coupling of basis functions. Both approaches have their cons and pros. Continuous Galerkin methods allow avoiding penalty parameters though they involve partition of unity functions which can alter the properties of multiscale basis functions. On the other hand, discontinuous Galerkin techniques allow gluing multiscale basis functions without any modifications. Because basis functions are constructed independently from each other, this approach provides an advantage. We discuss the use of oversampling techniques that use snapshots in larger regions to construct the offline space. We provide numerical results to show that one can accurately approximate the solution using reduced number of degrees of freedom.
Moist multi-scale models for the hurricane embryo
Energy Technology Data Exchange (ETDEWEB)
Majda, Andrew J. [New York University; Xing, Yulong [ORNL; Mohammadian, Majid [University of Ottawa, Canada
2010-01-01
Determining the finite-amplitude preconditioned states in the hurricane embryo, which lead to tropical cyclogenesis, is a central issue in contemporary meteorology. In the embryo there is competition between different preconditioning mechanisms involving hydrodynamics and moist thermodynamics, which can lead to cyclogenesis. Here systematic asymptotic methods from applied mathematics are utilized to develop new simplified moist multi-scale models starting from the moist anelastic equations. Three interesting multi-scale models emerge in the analysis. The balanced mesoscale vortex (BMV) dynamics and the microscale balanced hot tower (BHT) dynamics involve simplified balanced equations without gravity waves for vertical vorticity amplification due to moist heat sources and incorporate nonlinear advective fluxes across scales. The BMV model is the central one for tropical cyclogenesis in the embryo. The moist mesoscale wave (MMW) dynamics involves simplified equations for mesoscale moisture fluctuations, as well as linear hydrostatic waves driven by heat sources from moisture and eddy flux divergences. A simplified cloud physics model for deep convection is introduced here and used to study moist axisymmetric plumes in the BHT model. A simple application in periodic geometry involving the effects of mesoscale vertical shear and moist microscale hot towers on vortex amplification is developed here to illustrate features of the coupled multi-scale models. These results illustrate the use of these models in isolating key mechanisms in the embryo in a simplified content.
Multiscale geometric modeling of macromolecules II: Lagrangian representation.
Feng, Xin; Xia, Kelin; Chen, Zhan; Tong, Yiying; Wei, Guo-Wei
2013-09-15
Geometric modeling of biomolecules plays an essential role in the conceptualization of biolmolecular structure, function, dynamics, and transport. Qualitatively, geometric modeling offers a basis for molecular visualization, which is crucial for the understanding of molecular structure and interactions. Quantitatively, geometric modeling bridges the gap between molecular information, such as that from X-ray, NMR, and cryo-electron microscopy, and theoretical/mathematical models, such as molecular dynamics, the Poisson-Boltzmann equation, and the Nernst-Planck equation. In this work, we present a family of variational multiscale geometric models for macromolecular systems. Our models are able to combine multiresolution geometric modeling with multiscale electrostatic modeling in a unified variational framework. We discuss a suite of techniques for molecular surface generation, molecular surface meshing, molecular volumetric meshing, and the estimation of Hadwiger's functionals. Emphasis is given to the multiresolution representations of biomolecules and the associated multiscale electrostatic analyses as well as multiresolution curvature characterizations. The resulting fine resolution representations of a biomolecular system enable the detailed analysis of solvent-solute interaction, and ion channel dynamics, whereas our coarse resolution representations highlight the compatibility of protein-ligand bindings and possibility of protein-protein interactions. PMID:23813599
Mixed Generalized Multiscale Finite Element Methods and Applications
Chung, Eric T.
2015-03-03
In this paper, we present a mixed generalized multiscale finite element method (GMsFEM) for solving flow in heterogeneous media. Our approach constructs multiscale basis functions following a GMsFEM framework and couples these basis functions using a mixed finite element method, which allows us to obtain a mass conservative velocity field. To construct multiscale basis functions for each coarse edge, we design a snapshot space that consists of fine-scale velocity fields supported in a union of two coarse regions that share the common interface. The snapshot vectors have zero Neumann boundary conditions on the outer boundaries, and we prescribe their values on the common interface. We describe several spectral decompositions in the snapshot space motivated by the analysis. In the paper, we also study oversampling approaches that enhance the accuracy of mixed GMsFEM. A main idea of oversampling techniques is to introduce a small dimensional snapshot space. We present numerical results for two-phase flow and transport, without updating basis functions in time. Our numerical results show that one can achieve good accuracy with a few basis functions per coarse edge if one selects appropriate offline spaces. © 2015 Society for Industrial and Applied Mathematics.
Final Technical Report "Multiscale Simulation Algorithms for Biochemical Systems"
Energy Technology Data Exchange (ETDEWEB)
Petzold, Linda R.
2012-10-25
Biochemical systems are inherently multiscale and stochastic. In microscopic systems formed by living cells, the small numbers of reactant molecules can result in dynamical behavior that is discrete and stochastic rather than continuous and deterministic. An analysis tool that respects these dynamical characteristics is the stochastic simulation algorithm (SSA, Gillespie, 1976), a numerical simulation procedure that is essentially exact for chemical systems that are spatially homogeneous or well stirred. Despite recent improvements, as a procedure that simulates every reaction event, the SSA is necessarily inefficient for most realistic problems. There are two main reasons for this, both arising from the multiscale nature of the underlying problem: (1) stiffness, i.e. the presence of multiple timescales, the fastest of which are stable; and (2) the need to include in the simulation both species that are present in relatively small quantities and should be modeled by a discrete stochastic process, and species that are present in larger quantities and are more efficiently modeled by a deterministic differential equation (or at some scale in between). This project has focused on the development of fast and adaptive algorithms, and the fun- damental theory upon which they must be based, for the multiscale simulation of biochemical systems. Areas addressed by this project include: (1) Theoretical and practical foundations for ac- celerated discrete stochastic simulation (tau-leaping); (2) Dealing with stiffness (fast reactions) in an efficient and well-justified manner in discrete stochastic simulation; (3) Development of adaptive multiscale algorithms for spatially homogeneous discrete stochastic simulation; (4) Development of high-performance SSA algorithms.
Generalization of mixed multiscale finite element methods with applications
Energy Technology Data Exchange (ETDEWEB)
Lee, C S [Texas A & M Univ., College Station, TX (United States)
2016-08-01
Many science and engineering problems exhibit scale disparity and high contrast. The small scale features cannot be omitted in the physical models because they can affect the macroscopic behavior of the problems. However, resolving all the scales in these problems can be prohibitively expensive. As a consequence, some types of model reduction techniques are required to design efficient solution algorithms. For practical purpose, we are interested in mixed finite element problems as they produce solutions with certain conservative properties. Existing multiscale methods for such problems include the mixed multiscale finite element methods. We show that for complicated problems, the mixed multiscale finite element methods may not be able to produce reliable approximations. This motivates the need of enrichment for coarse spaces. Two enrichment approaches are proposed, one is based on generalized multiscale finte element metthods (GMsFEM), while the other is based on spectral element-based algebraic multigrid (rAMGe). The former one, which is called mixed GMsFEM, is developed for both Darcy’s flow and linear elasticity. Application of the algorithm in two-phase flow simulations are demonstrated. For linear elasticity, the algorithm is subtly modified due to the symmetry requirement of the stress tensor. The latter enrichment approach is based on rAMGe. The algorithm differs from GMsFEM in that both of the velocity and pressure spaces are coarsened. Due the multigrid nature of the algorithm, recursive application is available, which results in an efficient multilevel construction of the coarse spaces. Stability, convergence analysis, and exhaustive numerical experiments are carried out to validate the proposed enrichment approaches. iii
Institute of Scientific and Technical Information of China (English)
支联合; 支羽光; 谭永杰
2011-01-01
Objective To discuss the impact of aliasing frequency on the performance of multiscale feature extraction (MFE) for fMRI data analysis. Methods Under the conditions of removing and not removing aliasing frequencies. MFE was employed to analyze the simulated and the auditory fMRI data. In addition, the results revealed by MFE were compared with those of the general linear model (GLM) implemented with SPM8 software. Results Whether removing aliasing frequencies or not, MFE showed the same specificity as that of GLM. However, in terms of the sensitivity, the performance of MFE without removing aliasing frequencies was better than that of MFE when removing aliasing frequencies, and the latter was better than that of GLM. Conclusion In case of correlation analysis employed, aliasing frequencies do not influence the specificity of MFE, while removing these frequencies will decrease its sensitivity.%目的 探讨混频对多尺度特征提取(MFE)方法分析fMRI数据的影响.方法 分别在去除和不去除混频条件下用MFE分析模拟数据及听觉fMRI试验数据,并与由SPM8软件运行的广义线性模型(GLM)方法的结果进行比较.结果 MFE在去除和不去除混频两种条件下的特异度均与GLM相同,但MFE不去除混频时的灵敏度优于去除混频时的灵敏度,后者又优于GLM.结论 在使用相关分析检测激活的条件下,混频不影响MFE的特异度,但去除混频降低其灵敏度.
Multiscale Modeling of Hall Thrusters Project
National Aeronautics and Space Administration — New multiscale modeling capability for analyzing advanced Hall thrusters is proposed. This technology offers NASA the ability to reduce development effort of new...
Collaborating for Multi-Scale Chemical Science
Energy Technology Data Exchange (ETDEWEB)
William H. Green
2006-07-14
Advanced model reduction methods were developed and integrated into the CMCS multiscale chemical science simulation software. The new technologies were used to simulate HCCI engines and burner flames with exceptional fidelity.
Multiscale Model Approach for Magnetization Dynamics Simulations
De Lucia, Andrea; Tretiakov, Oleg A; Kläui, Mathias
2016-01-01
Simulations of magnetization dynamics in a multiscale environment enable rapid evaluation of the Landau-Lifshitz-Gilbert equation in a mesoscopic sample with nanoscopic accuracy in areas where such accuracy is required. We have developed a multiscale magnetization dynamics simulation approach that can be applied to large systems with spin structures that vary locally on small length scales. To implement this, the conventional micromagnetic simulation framework has been expanded to include a multiscale solving routine. The software selectively simulates different regions of a ferromagnetic sample according to the spin structures located within in order to employ a suitable discretization and use either a micromagnetic or an atomistic model. To demonstrate the validity of the multiscale approach, we simulate the spin wave transmission across the regions simulated with the two different models and different discretizations. We find that the interface between the regions is fully transparent for spin waves with f...
Multiscale modelling in immunology: a review.
Cappuccio, Antonio; Tieri, Paolo; Castiglione, Filippo
2016-05-01
One of the greatest challenges in biomedicine is to get a unified view of observations made from the molecular up to the organism scale. Towards this goal, multiscale models have been highly instrumental in contexts such as the cardiovascular field, angiogenesis, neurosciences and tumour biology. More recently, such models are becoming an increasingly important resource to address immunological questions as well. Systematic mining of the literature in multiscale modelling led us to identify three main fields of immunological applications: host-virus interactions, inflammatory diseases and their treatment and development of multiscale simulation platforms for immunological research and for educational purposes. Here, we review the current developments in these directions, which illustrate that multiscale models can consistently integrate immunological data generated at several scales, and can be used to describe and optimize therapeutic treatments of complex immune diseases.
Multiscale Phenomena Related to Diabetic Foot
Agić, Ante; Nikolić, Tatjana; Mijović, Budimir
2011-01-01
Diabetes is a group of metabolic diseases causing a system disorder, i.e.; it cannot be explained or understood by phenomena on single material scale. The diabetic foot is studied as flexible multibody structure by nonlinear finite element method. The physical and geometrical multiscale heterogeneity is solved by multilevel finite element approach. The diabetic tissue is described by internal coordinate’s formalism, as complex multiscale process in tissue. The accompanying problem...
Multiscale modeling of pedestrian dynamics
Cristiani, Emiliano; Tosin, Andrea
2014-01-01
This book presents mathematical models and numerical simulations of crowd dynamics. The core topic is the development of a new multiscale paradigm, which bridges the microscopic and macroscopic scales taking the most from each of them for capturing the relevant clues of complexity of crowds. The background idea is indeed that most of the complex trends exhibited by crowds are due to an intrinsic interplay between individual and collective behaviors. The modeling approach promoted in this book pursues actively this intuition and profits from it for designing general mathematical structures susceptible of application also in fields different from the inspiring original one. The book considers also the two most traditional points of view: the microscopic one, in which pedestrians are tracked individually, and the macroscopic one, in which pedestrians are assimilated to a continuum. Selected existing models are critically analyzed. The work is addressed to researchers and graduate students.
Multiscale modelling of DNA mechanics
International Nuclear Information System (INIS)
Mechanical properties of DNA are important not only in a wide range of biological processes but also in the emerging field of DNA nanotechnology. We review some of the recent developments in modeling these properties, emphasizing the multiscale nature of the problem. Modern atomic resolution, explicit solvent molecular dynamics simulations have contributed to our understanding of DNA fine structure and conformational polymorphism. These simulations may serve as data sources to parameterize rigid base models which themselves have undergone major development. A consistent buildup of larger entities involving multiple rigid bases enables us to describe DNA at more global scales. Free energy methods to impose large strains on DNA, as well as bead models and other approaches, are also briefly discussed. (topical review)
Multiscale Modeling of Damage Processes in fcc Aluminum: From Atoms to Grains
Glaessgen, E. H.; Saether, E.; Yamakov, V.
2008-01-01
Molecular dynamics (MD) methods are opening new opportunities for simulating the fundamental processes of material behavior at the atomistic level. However, current analysis is limited to small domains and increasing the size of the MD domain quickly presents intractable computational demands. A preferred approach to surmount this computational limitation has been to combine continuum mechanics-based modeling procedures, such as the finite element method (FEM), with MD analyses thereby reducing the region of atomic scale refinement. Such multiscale modeling strategies can be divided into two broad classifications: concurrent multiscale methods that directly incorporate an atomistic domain within a continuum domain and sequential multiscale methods that extract an averaged response from the atomistic simulation for later use as a constitutive model in a continuum analysis.
On the optimal choice of wavelet function for multiscale honed surface characterization
Energy Technology Data Exchange (ETDEWEB)
Mezghani, S; Mansori, M El [Arts and Metiers ParisTech, LMPF, rue St Dominique - BP 508, 51006 Chalons-en-Champagne (France); Sabri, L [RENAULT S.A.S., Direction de la Mecanique/Direction de l' Ingenierie Process, Rueil Malmaison, Paris (France); Zahouani, H, E-mail: sabeur.mezghani@ensam.eu [Ecole Centrale de Lyon, LTDS UMR CNRS 5513, 36 avenue Guy de Collongue, 69131 Ecully Cedex (France)
2011-08-19
Multiscale surface topography characterization is mostly suited than standard approaches because it is more adapted to the multi-stage process generation. Wavelet transform represents a power tool to perform the multiscale decomposition of the surface topography in a wide range of wavelength. However, characterization results depend closely on the topography data acquisition instrument (resolution, height accuracy, sensitivity...) and also on the wavelet analysis method (discrete or continuous transform). In particular, the choice of wavelet function can have significant effect on the analysis results. In this paper, we present experimental work on a number of popular wavelets functions with the aim of finding wavelets that exhibit optimal description of honed surface features when continuous wavelet transform is used. We demonstrate that the regularity property of wavelet function has a significant influence on the characterization performances. This comparative study shows also that the Morlet wavelet is the more adapted wavelet basis function for multiscale characterization of honed surfaces using continuous wavelet transform.
An automated vessel segmentation of retinal images using multiscale vesselness
International Nuclear Information System (INIS)
The ocular fundus image can provide information on pathological changes caused by local ocular diseases and early signs of certain systemic diseases, such as diabetes and hypertension. Automated analysis and interpretation of fundus images has become a necessary and important diagnostic procedure in ophthalmology. The extraction of blood vessels from retinal images is an important and challenging task in medical analysis and diagnosis. In this paper, we introduce an implementation of the anisotropic diffusion which allows reducing the noise and better preserving small structures like vessels in 2D images. A vessel detection filter, based on a multi-scale vesselness function, is then applied to enhance vascular structures.
Multiscale coupling of molecular dynamics and peridynamics
Tong, Qi; Li, Shaofan
2016-10-01
We propose a multiscale computational model to couple molecular dynamics and peridynamics. The multiscale coupling model is based on a previously developed multiscale micromorphic molecular dynamics (MMMD) theory, which has three dynamics equations at three different scales, namely, microscale, mesoscale, and macroscale. In the proposed multiscale coupling approach, we divide the simulation domain into atomistic region and macroscale region. Molecular dynamics is used to simulate atom motions in atomistic region, and peridynamics is used to simulate macroscale material point motions in macroscale region, and both methods are nonlocal particle methods. A transition zone is introduced as a messenger to pass the information between the two regions or scales. We employ the "supercell" developed in the MMMD theory as the transition element, which is named as the adaptive multiscale element due to its ability of passing information from different scales, because the adaptive multiscale element can realize both top-down and bottom-up communications. We introduce the Cauchy-Born rule based stress evaluation into state-based peridynamics formulation to formulate atomistic-enriched constitutive relations. To mitigate the issue of wave reflection on the interface, a filter is constructed by switching on and off the MMMD dynamic equations at different scales. Benchmark tests of one-dimensional (1-D) and two-dimensional (2-D) wave propagations from atomistic region to macro region are presented. The mechanical wave can transit through the interface smoothly without spurious wave deflections, and the filtering process is proven to be efficient.
Distributed multiscale computing with MUSCLE 2, the Multiscale Coupling Library and Environment
J. Borgdorff; M. Mamonski; B. Bosak; K. Kurowski; M. Ben Belgacem; B. Chopard; D. Groen; P.V. Coveney; A.G. Hoekstra
2014-01-01
We present the Multiscale Coupling Library and Environment: MUSCLE 2. This multiscale component-based execution environment has a simple to use Java, C++, C, Python and Fortran API, compatible with MPI, OpenMP and threading codes. We demonstrate its local and distributed computing capabilities and c
Evaluation of Multi-Scale Full Waveform Inversion with Marine Vertical Cable Data
Institute of Scientific and Technical Information of China (English)
Aifei Bian; Zhihui Zou; Hua-Wei Zhou; Jin Zhang
2015-01-01
Seismic illumination plays an important role in subsurface imaging. A better image can be expected either through optimizing acquisition geometry or introducing more advanced seismic mi-gration and/or tomographic inversion methods involving illumination compensation. Vertical cable survey is a potential replacement of traditional marine seismic survey for its flexibility and data quality. Conventional vertical cable data processing requires separation of primaries and multiples before mi-gration. We proposed to use multi-scale full waveform inversion (FWI) to improve illumination cover-age of vertical cable survey. A deep water velocity model is built to test the capability of multi-scale FWI in detecting low velocity anomalies below seabed. Synthetic results show that multi-scale FWI is an effective model building tool in deep-water exploration. Geometry optimization through target ori-ented illumination analysis and multi-scale FWI may help to mitigate the risks of vertical cable survey. The combination of multi-scale FWI, low-frequency data and multi-vertical-cable acquisition system may provide both high resolution and high fidelity subsurface models.
Xu, Yonghong; Cui, Jie; Hong, Wenxue; Liang, Huijuan
2015-04-01
Traditional sample entropy fails to quantify inherent long-range dependencies among real data. Multiscale sample entropy (MSE) can detect intrinsic correlations in data, but it is usually used in univariate data. To generalize this method for multichannel data, we introduced multivariate multiscale entropy into multiscale signals as a reflection of the nonlinear dynamic correlation. But traditional multivariate multiscale entropy has a large quantity of computation and costs a large period of time and space for more channel system, so that it can not reflect the correlation between variables timely and accurately. In this paper, therefore, an improved multivariate multiscale entropy embeds on all variables at the same time, instead of embedding on a single variable as in the traditional methods, to solve the memory overflow while the number of channels rise, and it is more suitable for the actual multivariate signal analysis. The method was tested in simulation data and Bonn epilepsy dataset. The simulation results showed that the proposed method had a good performance to distinguish correlation data. Bonn epilepsy dataset experiment also showed that the method had a better classification accuracy among the five data set, especially with an accuracy of 100% for data collection of Z and S. PMID:26211236
Universal hierarchical symmetry for turbulence and general multi-scale fluctuation systems
Institute of Scientific and Technical Information of China (English)
Zhen-Su She; Zhi-Xiong Zhang
2009-01-01
Scaling is an important measure of multi-scale fluctuation systems. Turbulence as the most remarkable multi-scale system possesses scaling over a wide range of scales. She-Leveque (SL) hierarchical symmetry, since its publication in 1994, has received wide attention. A num-ber of experimental, numerical and theoretical work have been devoted to its verification, extension, and modification. Application to the understanding of magnetohydrodynamic turbulence, motions of cosmic baryon fluids, cosmological supersonic turbulence, natural image, spiral turbulent patterns, DNA anomalous composition, human heart vari-ability are just a few among the most successful examples. A number of modified scaling laws have been derived in the framework of the hierarchical symmetry, and the SL model parameters are found to reveal both the organizational order of the whole system and the properties of the most signif-icant fluctuation structures. A partial set of work related to these studies are reviewed. Particular emphasis is placed on the nature of the hierarchical symmetry. It is suggested that the SL hierarchical symmetry is a new form of the self-orga-nization principle for multi-scale fluctuation systems, and can be employed as a standard analysis tool in the general multi-scale methodology. It is further suggested that the SL hierarchical symmetry implies the existence of a turbulence ensemble. It is speculated that the search for defining the turbulence ensemble might open a new way for deriving sta-tistical closure equations for turbulence and other multi-scale fluctuation systems.
Wide Range Multiscale Entropy Changes through Development
Directory of Open Access Journals (Sweden)
Nicola R. Polizzotto
2015-12-01
Full Text Available How variability in the brain’s neurophysiologic signals evolves during development is important for a global, system-level understanding of brain maturation and its disturbance in neurodevelopmental disorders. In the current study, we use multiscale entropy (MSE, a measure that has been related to signal complexity, to investigate how this variability evolves during development across a broad range of temporal scales. We computed MSE, standard deviation (STD and standard spectral analyses on resting EEG from 188 healthy individuals aged 8–22 years old. We found age-related increases in entropy at lower scales (<~20 ms and decreases in entropy at higher scales (~60–80 ms. Decreases in the overall signal STD were anticorrelated with entropy, especially in the lower scales, where regression analyses showed substantial covariation of observed changes. Our findings document for the first time the scale dependency of developmental changes from childhood to early adulthood, challenging a parsimonious MSE-based account of brain maturation along a unidimensional, complexity measure. At the level of analysis permitted by electroencephalography (EEG, MSE could capture critical spatiotemporal variations in the role of noise in the brain. However, interpretations critically rely on defining how signal STD affects MSE properties.
N.S. Anders; A.C. Seijmonsbergen; W. Bouten
2009-01-01
Geomorphological maps are useful to a wide variety of applications, such as hazard risk analysis (Seijmonsbergen 1992), forest ecological research (Van Noord 1996) and geoconservation evaluation studies (Seijmonsbergen et al. in press). Traditional field-based geomorphological mapping strategies are
Fast multiscale directional filter bank-based speckle mitigation in gallstone ultrasound images.
Leavline, Epiphany Jebamalar; Sutha, Shunmugam; Singh, Danasingh Asir Antony Gnana
2014-02-01
Speckle noise is a multiplicative type of noise commonly seen in medical and remote sensing images. It gives a granular appearance that degrades the quality of the recorded images. These speckle noise components need to be mitigated before the image is used for further processing and analysis. This paper presents a novel approach for removing granular speckle noise in gray scale images. We used an efficient multiscale image representation scheme named fast multiscale directional filter bank (FMDFB) along with simple threshold methods such as Vishushrink for image processing. It is a perfect reconstruction framework that can be used for a wide range of image processing applications because of its directionality and reduced computational complexity. The FMDFB-based speckle mitigation is appealing over other traditional multiscale approaches such as wavelets and Contourlets. Our experimental results show that the despeckling performance of the proposed method outperforms the wavelet and Contourlet-based despeckling methods.
A multiscale products technique for denoising of DNA capillary electrophoresis signals
Gao, Qingwei; Lu, Yixiang; Sun, Dong; Zhang, Dexiang
2013-06-01
Since noise degrades the accuracy and precision of DNA capillary electrophoresis (CE) analysis, signal denoising is thus important to facilitate the postprocessing of CE data. In this paper, a new denoising algorithm based on dyadic wavelet transform using multiscale products is applied for the removal of the noise in the DNA CE signal. The adjacent scale wavelet coefficients are first multiplied to amplify the significant features of the CE signal while diluting noise. Then, noise is suppressed by applying a multiscale threshold to the multiscale products instead of directly to the wavelet coefficients. Finally, the noise-free CE signal is recovered from the thresholded coefficients by using inverse dyadic wavelet transform. We compare the performance of the proposed algorithm with other denoising methods applied to the synthetic CE and real CE signals. Experimental results show that the new scheme achieves better removal of noise while preserving the shape of peaks corresponding to the analytes in the sample.
Fast multiscale directional filter bank-based speckle mitigation in gallstone ultrasound images.
Leavline, Epiphany Jebamalar; Sutha, Shunmugam; Singh, Danasingh Asir Antony Gnana
2014-02-01
Speckle noise is a multiplicative type of noise commonly seen in medical and remote sensing images. It gives a granular appearance that degrades the quality of the recorded images. These speckle noise components need to be mitigated before the image is used for further processing and analysis. This paper presents a novel approach for removing granular speckle noise in gray scale images. We used an efficient multiscale image representation scheme named fast multiscale directional filter bank (FMDFB) along with simple threshold methods such as Vishushrink for image processing. It is a perfect reconstruction framework that can be used for a wide range of image processing applications because of its directionality and reduced computational complexity. The FMDFB-based speckle mitigation is appealing over other traditional multiscale approaches such as wavelets and Contourlets. Our experimental results show that the despeckling performance of the proposed method outperforms the wavelet and Contourlet-based despeckling methods. PMID:24562027
Biomimic design of multi-scale fabric with efficient heat transfer property
Directory of Open Access Journals (Sweden)
Fan Jie
2012-01-01
Full Text Available Wool fiber has a complex hierarchic structure. The multi-scale fibrils are assembled to form a tree-like channel net in wool fiber, providing an efficient heat transfer property. The optimal inner configuration of wool fiber can also be invited to biomimic design of textile fabrics to improve the thermal comfort of cloth. A heat transfer model of biomimic multi-scale fabric using the fractal derivative is established. Theoretical analysis indicates that the heat flux efficiency in the biomimic fabric can be 2 orders of magnitude comparing with that of the continuous medium.
Multiscale Design of Advanced Materials based on Hybrid Ab Initio and Quasicontinuum Methods
Energy Technology Data Exchange (ETDEWEB)
Luskin, Mitchell [University of Minnesota
2014-03-12
This project united researchers from mathematics, chemistry, computer science, and engineering for the development of new multiscale methods for the design of materials. Our approach was highly interdisciplinary, but it had two unifying themes: first, we utilized modern mathematical ideas about change-of-scale and state-of-the-art numerical analysis to develop computational methods and codes to solve real multiscale problems of DOE interest; and, second, we took very seriously the need for quantum mechanics-based atomistic forces, and based our methods on fast solvers of chemically accurate methods.
Multi-Scale Jacobi Method for Anderson Localization
Imbrie, John Z.
2015-11-01
A new KAM-style proof of Anderson localization is obtained. A sequence of local rotations is defined, such that off-diagonal matrix elements of the Hamiltonian are driven rapidly to zero. This leads to the first proof via multi-scale analysis of exponential decay of the eigenfunction correlator (this implies strong dynamical localization). The method has been used in recent work on many-body localization (Imbrie in On many-body localization for quantum spin chains, arXiv:1403.7837 URL"/> , 2014).
Moving in a crowd: human perception as a multiscale process
Colombi, Annachiara; Tosin, Andrea
2015-01-01
The strategic behavior of pedestrians is largely determined by how they perceive and consequently react to neighboring people. Such interpersonal interactions may be dictated by the emotional state of the individuals, the purpose of their trip, the local crowding, the quality of the environment to mention but a few common examples. This issue is addressed in this paper by a mathematical model which combines, in an evolutionary time- and space-dependent way, discrete and continuous effects of pedestrian interactions. Numerical simulations and qualitative analysis suggest that human perception, and its impact on crowd dynamics, can be effectively modeled as a multiscale process based on such a dual representation of groups of agents.
Multiscale mechanics of macromolecular materials with unfolding domains
De Tommasi, D.; Puglisi, G.; Saccomandi, G.
2015-05-01
We propose a general multiscale approach for the mechanical behavior of three-dimensional networks of macromolecules undergoing strain-induced unfolding. Starting from a (statistically based) energetic analysis of the macromolecule unfolding strategy, we obtain a three-dimensional continuum model with variable natural configuration and an energy function analytically deduced from the microscale material parameters. The comparison with the experiments shows the ability of the model to describe the complex behavior, with residual stretches and unfolding effects, observed in different biological materials.
The Multiscale Entropy Algorithm and Its Variants: A Review
Directory of Open Access Journals (Sweden)
Anne Humeau-Heurtier
2015-05-01
Full Text Available Multiscale entropy (MSE analysis was introduced in the 2002 to evaluate the complexity of a time series by quantifying its entropy over a range of temporal scales. The algorithm has been successfully applied in different research fields. Since its introduction, a number of modifications and refinements have been proposed, some aimed at increasing the accuracy of the entropy estimates, others at exploring alternative coarse-graining procedures. In this review, we first describe the original MSE algorithm. Then, we review algorithms that have been introduced to improve the estimation of MSE. We also report a recent generalization of the method to higher moments.
Multiscale simulation of erythrocyte membranes
Peng, Zhangli; Asaro, Robert J.; Zhu, Qiang
2010-03-01
To quantitatively predict the mechanical response and mechanically induced remodeling of red blood cells, we developed a multiscale method to correlate distributions of internal stress with overall cell deformation. This method consists of three models at different length scales: in the complete cell level the membrane is modeled as two distinct layers of continuum shells using finite element method (Level III), in which the skeleton-bilayer interactions are depicted as a slide in the lateral (i.e., in-plane) direction (caused by the mobility of the skeleton-bilayer pinning points) and a normal contact force; the constitutive laws of the inner layer (the protein skeleton) are obtained from a molecular-based model (Level II); the mechanical properties of the spectrin (Sp, a key component of the skeleton), including its folding/unfolding reactions, are obtained with a stress-strain model (Level I). Model verification is achieved through comparisons with existing numerical and experimental studies in terms of the resting shape of the cell as well as cell deformations induced by micropipettes and optical tweezers. Detailed distributions of the interaction force between the lipid bilayer and the skeleton that may cause their dissociation and lead to phenomena such as vesiculation are predicted. Specifically, our model predicts correlation between the occurrence of Sp unfolding and increase in the mechanical load upon individual skeleton-bilayer pinning points. Finally a simulation of the necking process after skeleton-bilayer dissociation, a precursor of vesiculation, is conducted.
Multi-scale Material Appearance
Wu, Hongzhi
Modeling and rendering the appearance of materials is important for a diverse range of applications of computer graphics - from automobile design to movies and cultural heritage. The appearance of materials varies considerably at different scales, posing significant challenges due to the sheer complexity of the data, as well the need to maintain inter-scale consistency constraints. This thesis presents a series of studies around the modeling, rendering and editing of multi-scale material appearance. To efficiently render material appearance at multiple scales, we develop an object-space precomputed adaptive sampling method, which precomputes a hierarchy of view-independent points that preserve multi-level appearance. To support bi-scale material appearance design, we propose a novel reflectance filtering algorithm, which rapidly computes the large-scale appearance from small-scale details, by exploiting the low-rank structures of Bidirectional Visible Normal Distribution Functions and pre-rotated Bidirectional Reflectance Distribution Functions in the matrix formulation of the rendering algorithm. This approach can guide the physical realization of appearance, as well as the modeling of real-world materials using very sparse measurements. Finally, we present a bi-scale-inspired high-quality general representation for material appearance described by Bidirectional Texture Functions. Our representation is at once compact, easily editable, and amenable to efficient rendering.
Multiscale modelling of evolving foams
Saye, R. I.; Sethian, J. A.
2016-06-01
We present a set of multi-scale interlinked algorithms to model the dynamics of evolving foams. These algorithms couple the key effects of macroscopic bubble rearrangement, thin film drainage, and membrane rupture. For each of the mechanisms, we construct consistent and accurate algorithms, and couple them together to work across the wide range of space and time scales that occur in foam dynamics. These algorithms include second order finite difference projection methods for computing incompressible fluid flow on the macroscale, second order finite element methods to solve thin film drainage equations in the lamellae and Plateau borders, multiphase Voronoi Implicit Interface Methods to track interconnected membrane boundaries and capture topological changes, and Lagrangian particle methods for conservative liquid redistribution during rearrangement and rupture. We derive a full set of numerical approximations that are coupled via interface jump conditions and flux boundary conditions, and show convergence for the individual mechanisms. We demonstrate our approach by computing a variety of foam dynamics, including coupled evolution of three-dimensional bubble clusters attached to an anchored membrane and collapse of a foam cluster.
SEGMENTATION USING MULTISCALE MORPHOLOGICAL RECONSTRUCTION
Directory of Open Access Journals (Sweden)
NANMOZHI.R
2013-04-01
Full Text Available Image segmentation is a crucial step in the field of image processing and pattern recognition. Segmentation allows the identification of structures in an image which can be utilized for further processing. This paper proposes a technique for object segmentation from its background. We utilized both region-based and object-based segmentation capabilities to handle the object segmentation for large-scale database images in a robust and principled manner. MultiScalE Graylevel mOrphological recoNstructions (SEGON is used for segmenting an image. SEGON roughly identifies the background and object regions in the image. To further refine the boundaries of the objects mean-shift segmentation technique is applied on the SEGON processed image. Accuracy of segmentation is evaluated by computing structural similarity index (SSIM, for the image segmented with and without using SEGON. Images collected from Corel, Caltech, PASCAL, UCID and CMU-PIE databases are utilized for this work. Experimental results showed that the proposed object segmentation method outperforms the state-of-the-art image segmentation techniques.
Multiscale Modeling of Hematologic Disorders
Energy Technology Data Exchange (ETDEWEB)
Fedosov, Dmitry A.; Pivkin, Igor; Pan, Wenxiao; Dao, Ming; Caswell, Bruce; Karniadakis, George E.
2012-01-28
Parasitic infectious diseases and other hereditary hematologic disorders are often associated with major changes in the shape and viscoelastic properties of red blood cells (RBCs). Such changes can disrupt blood flow and even brain perfusion, as in the case of cerebral malaria. Modeling of these hematologic disorders requires a seamless multiscale approach, where blood cells and blood flow in the entire arterial tree are represented accurately using physiologically consistent parameters. In this chapter, we present a computational methodology based on dissipative particle dynamics (DPD) which models RBCs as well as whole blood in health and disease. DPD is a Lagrangian method that can be derived from systematic coarse-graining of molecular dynamics but can scale efficiently up to small arteries and can also be used to model RBCs down to spectrin level. To this end, we present two complementary mathematical models for RBCs and describe a systematic procedure on extracting the relevant input parameters from optical tweezers and microfluidic experiments for single RBCs. We then use these validated RBC models to predict the behavior of whole healthy blood and compare with experimental results. The same procedure is applied to modeling malaria, and results for infected single RBCs and whole blood are presented.
MULTISCALE DISCRETIZATION OF SHAPE CONTOURS
Energy Technology Data Exchange (ETDEWEB)
Prasad, L.; Rao, R.
2000-09-01
We present an efficient multi-scale scheme to adaptively approximate the continuous (or densely sampled) contour of a planar shape at varying resolutions. The notion of shape is intimately related to the notion of contour, and the efficient representation of the contour of a shape is vital to a computational understanding of the shape. Any polygonal approximation of a planar smooth curve is equivalent to a piecewise constant approximation of the parameterized X and Y coordinate functions of a discrete point set obtained by densely sampling the curve. Using the Haar wavelet transform for the piecewise approximation yields a hierarchical scheme in which the size of the approximating point set is traded off against the morphological accuracy of the approximation. Our algorithm compresses the representation of the initial shape contour to a sparse sequence of points in the plane defining the vertices of the shape's polygonal approximation. Furthermore, it is possible to control the overall resolution of the approximation by a single, scale-independent parameter.
A Multiscale Bidirectional Coupling Framework
Energy Technology Data Exchange (ETDEWEB)
Kabilan, Senthil; Kuprat, Andrew P.; Hlastala, Michael P.; Corley, Richard A.; Einstein, Daniel R.
2011-12-01
The lung is geometrically articulated across multiple scales from the trachea to the alveoli. A major computational challenge is to tightly link ODEs that describe lower scales to 3D finite element or finite volume models of airway mechanics using iterative communication between scales. In this study, we developed a novel multiscale computational framework for bidirectionally coupling 3D CFD models and systems of lower order ODEs. To validate the coupling framework, a four and eight generation Weibel lung model was constructed. For the coupled CFD-ODE simulations, the lung models were truncated at different generations and a RL circuit represented the truncated portion. The flow characteristics from the coupled models were compared to untruncated full 3D CFD models at peak inhalation and peak exhalation. Results showed that at no time or simulation was the difference in mass flux and/or pressure at a given location between uncoupled and coupled models was greater than 2.43%. The flow characteristics at prime locations for the coupled models showed good agreement to uncoupled models. Remarkably, due to reuse of the Krylov subspace, the cost of the ODE coupling is not much greater than uncoupled full 3D-CFD computations with simple prescribed pressure values at the outlets.
Multiscale modelling of saliva secretion.
Sneyd, James; Crampin, Edmund; Yule, David
2014-11-01
We review a multiscale model of saliva secretion, describing in brief how the model is constructed and what we have so far learned from it. The model begins at the level of inositol trisphosphate receptors (IPR), and proceeds through the cellular level (with a model of acinar cell calcium dynamics) to the multicellular level (with a model of the acinus), finally to a model of a saliva production unit that includes an acinus and associated duct. The model at the level of the entire salivary gland is not yet completed. Particular results from the model so far include (i) the importance of modal behaviour of IPR, (ii) the relative unimportance of Ca(2+) oscillation frequency as a controller of saliva secretion, (iii) the need for the periodic Ca(2+) waves to be as fast as possible in order to maximise water transport, (iv) the presence of functional K(+) channels in the apical membrane increases saliva secretion, (v) the relative unimportance of acinar spatial structure for isotonic water transport, (vi) the prediction that duct cells are highly depolarised, (vii) the prediction that the secondary saliva takes at least 1mm (from the acinus) to reach ionic equilibrium. We end with a brief discussion of future directions for the model, both in construction and in the study of scientific questions.
International Nuclear Information System (INIS)
In the context of the FP7 European THINS Project, complex thermal-hydraulic phenomena relevant for the Generation IV of nuclear reactors are investigated. KTH (Sweden) built the TALL-3D facility to investigate the transition from forced to natural circulation of the Lead-Bismuth Eutectic (LBE) in a pool connected to a 3-leg primary circuit with two heaters and a heat exchanger. The simulation of such 3D phenomena is a challenging task. GRS (Germany) developed the coupling between the Computational Fluid Dynamics (CFD) code ANSYS CFX and the System Analysis code ATHLET. Such coupled codes combine the advantages of CFD, which allow a fine resolution of 3D phenomena, and of System Analysis codes, which are fast running. TUM (Germany) is responsible for the Uncertainty and Sensitivity Analysis of the coupled ATHLET-CFX model in the THINS Project. The influence of modeling uncertainty on simulation results needs to be assessed to characterize and to improve the model and, eventually, to assess its performance against experimental data. TUM has developed a computational framework capable of propagating model input uncertainty through coupled codes. This framework can also be used to apply different approaches for the assessment of the influence of the uncertain input parameters on the model output (Sensitivity Analysis). The work reported in this paper focuses on three methods for the assessment of the sensitivity of the results to the modeling uncertainty. The first method (Morris) allows for the computation of the Elementary Effects resulting from the input parameters. This method is widely used to perform Screening Analysis. The second method (Spearman's rank correlation) relies on regression-based non-parametric measures. This method is suitable if the relation between the input and the output variables is at least monotonic, with the advantage of a low computational cost. The last method (Sobol') computes so-called total effect indices which account for
Multiscale 3-D shape representation and segmentation using spherical wavelets.
Nain, Delphine; Haker, Steven; Bobick, Aaron; Tannenbaum, Allen
2007-04-01
This paper presents a novel multiscale shape representation and segmentation algorithm based on the spherical wavelet transform. This work is motivated by the need to compactly and accurately encode variations at multiple scales in the shape representation in order to drive the segmentation and shape analysis of deep brain structures, such as the caudate nucleus or the hippocampus. Our proposed shape representation can be optimized to compactly encode shape variations in a population at the needed scale and spatial locations, enabling the construction of more descriptive, nonglobal, nonuniform shape probability priors to be included in the segmentation and shape analysis framework. In particular, this representation addresses the shortcomings of techniques that learn a global shape prior at a single scale of analysis and cannot represent fine, local variations in a population of shapes in the presence of a limited dataset. Specifically, our technique defines a multiscale parametric model of surfaces belonging to the same population using a compact set of spherical wavelets targeted to that population. We further refine the shape representation by separating into groups wavelet coefficients that describe independent global and/or local biological variations in the population, using spectral graph partitioning. We then learn a prior probability distribution induced over each group to explicitly encode these variations at different scales and spatial locations. Based on this representation, we derive a parametric active surface evolution using the multiscale prior coefficients as parameters for our optimization procedure to naturally include the prior for segmentation. Additionally, the optimization method can be applied in a coarse-to-fine manner. We apply our algorithm to two different brain structures, the caudate nucleus and the hippocampus, of interest in the study of schizophrenia. We show: 1) a reconstruction task of a test set to validate the expressiveness of
Li, L.; Chen, C. H.; Huang, C; Huang, H Y; Zhang, G. F.; Wang, Y. J.; Wang, H. L.; Lou, S. R.; Qiao, L. P.; Zhou, M.; Chen, M H; Chen, Y. R.; D. G. Streets; Fu, J.S.; C. J. Jang
2012-01-01
A high O_{3} episode was detected in urban Shanghai, a typical city in the Yangtze River Delta (YRD) region in August 2010. The CMAQ integrated process rate method is applied to account for the contribution of different atmospheric processes during the high pollution episode. The analysis shows that the maximum concentration of ozone occurs due to transport phenomena, including vertical diffusion and horizontal advective transport. Gas-phase chemistry producing O
C. Montebello; S. Pommier; K. Demmou; Leroux, J.; J. Mériaux
2015-01-01
This paper describes a novel method to model the stress gradient effect in fretting-fatigue. The analysis of the mechanical fields in the proximity of the contact edges allows to extract nonlocal intensity factors that take into account the stress gradient evolution. For this purpose, the kinetic field around the contact ends is partitioned into a summation of multiple terms, each one expressed as the product between nonlocal intensity factors, Is, Ia, Ic, depending on the macrosc...
A multiscale soil loss evaluation index
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Exploring the relationships between land use and soil erosion at different scales is a frontier research field and a hot spot topic in contemporary physical geography. Based on the scale-pattern-process theory in landscape ecology and with consideration of such influential factors as land use, topography, soil and rainfall, this paper applies the scale transition method to establishing a soil loss evaluation index at different scales and puts forward a research path and methodology for multiscale soil loss evaluation indices. The multiscale soil loss evaluation index is applied to the evaluation of relationships between land use and soil erosion and the research of soil erosion evaluation at multiple scales. It provides a new method for optimizing the design of regional land use patterns and integrated multiscale research.
Generalized multiscale radial basis function networks.
Billings, Stephen A; Wei, Hua-Liang; Balikhin, Michael A
2007-12-01
A novel modelling framework is proposed for constructing parsimonious and flexible multiscale radial basis function networks (RBF). Unlike a conventional standard single scale RBF network, where all the basis functions have a common kernel width, the new network structure adopts multiscale Gaussian functions as the bases, where each selected centre has multiple kernel widths, to provide more flexible representations with better generalization properties for general nonlinear dynamical systems. As a direct extension of the traditional single scale Gaussian networks, the new multiscale network is easy to implement and is quick to learn using standard learning algorithms. A k-means clustering algorithm and an improved orthogonal least squares (OLS) algorithm are used to determine the unknown parameters in the network model including the centres and widths of the basis functions, and the weights between the basis functions. It is demonstrated that the new network can lead to a parsimonious model with much better generalization property compared with the traditional single width RBF networks.
Multiscale Bone Remodelling with Spatial P Systems
Cacciagrano, Diletta; Merelli, Emanuela; Tesei, Luca; 10.4204/EPTCS.40.6
2010-01-01
Many biological phenomena are inherently multiscale, i.e. they are characterized by interactions involving different spatial and temporal scales simultaneously. Though several approaches have been proposed to provide "multilayer" models, only Complex Automata, derived from Cellular Automata, naturally embed spatial information and realize multiscaling with well-established inter-scale integration schemas. Spatial P systems, a variant of P systems in which a more geometric concept of space has been added, have several characteristics in common with Cellular Automata. We propose such a formalism as a basis to rephrase the Complex Automata multiscaling approach and, in this perspective, provide a 2-scale Spatial P system describing bone remodelling. The proposed model not only results to be highly faithful and expressive in a multiscale scenario, but also highlights the need of a deep and formal expressiveness study involving Complex Automata, Spatial P systems and other promising multiscale approaches, such as ...
Multiscale modeling in biomechanics and mechanobiology
Hwang, Wonmuk; Kuhl, Ellen
2015-01-01
Presenting a state-of-the-art overview of theoretical and computational models that link characteristic biomechanical phenomena, this book provides guidelines and examples for creating multiscale models in representative systems and organisms. It develops the reader's understanding of and intuition for multiscale phenomena in biomechanics and mechanobiology, and introduces a mathematical framework and computational techniques paramount to creating predictive multiscale models. Biomechanics involves the study of the interactions of physical forces with biological systems at all scales – including molecular, cellular, tissue and organ scales. The emerging field of mechanobiology focuses on the way that cells produce and respond to mechanical forces – bridging the science of mechanics with the disciplines of genetics and molecular biology. Linking disparate spatial and temporal scales using computational techniques is emerging as a key concept in investigating some of the complex problems underlying these...
The center for multiscale plasma dynamics
Energy Technology Data Exchange (ETDEWEB)
Kevrekidis, Yannis G [Princeton Univ., Princeton, NJ (United States)
2015-01-20
This final report describes research performed in Princeton University, led by Professor Yannis G. Kevrekidis, over a period of six years (August 1, 2014 to July 31, 2010, including a one-year, no-cost extension) as part of the Center for Multiscale Plasma Dynamics led by the University of Maryland. The work resulted in the development and implementation of several multiscale algorithms based on the equation-free approach pioneered by the PI, including its applications in plasma dynamics problems. These algoriithms include coarse projective integration and coarse stability/bifurcation computations. In the later stages of the work, new links were made between this multiscale, coarse-graining approach and advances in data mining/machine learning algorithms.
应用多尺度化的基本尺度熵分析心率变异性%Multiscale base-scale entropy analysis of heart rate variability signal~
Institute of Scientific and Technical Information of China (English)
严碧歌; 赵婷婷
2011-01-01
Multiscale base- scale entropy is introduced in this paper. We use it to analyze heart rate variability series. The results show that multiscale base-scale entropy can identify patterns generated from healthy and pathologic states, and can distinguish daytime and nighttime heartbeat time series. We also calculate the multiscale base-scale entropy of surrogate signal （phase randomized data） , compare it with the entropy of atrial fibrillation signal, and find that the tends of two entropys are similar to each other, which indicates that atrial fibrillation reflects the linear characteristics of physiological signals. Multiscale base-scale entropy method has potential applications to studying a wide variety of other physiologic and physical time series data.%本文采用多尺度化的基本尺度熵方法，针对心率变异性信号进行了分析，研究发现多尺度化的基本尺度熵可以区分不同生理病理信号，包括健康人、充血性心力衰竭患者和房颤心律失常患者的心率变异性信号，以及健康人白天黑夜的心率变异性信号．通过对健康人代理数据的分析，发现房颤心律失常患者与代理数据的熵值趋势相似，研究结果表明房颤心律失常患者的心率变异性信号更多的是反映生理信号的线性特征，而对环境变化不能很好的进行自我调节．
X Wang; Zhang, Y.; Hu, Y.; Zhou, W.; Lu, K.; L. Zhong(Center for High Energy Physics, Tsinghua University, Beijing, China); Zeng, L; SHAO, M.; Hu, M.; Russell, A. G.
2010-01-01
In this study, the Community Multiscale Air Quality (CMAQ) modeling system is used to simulate the ozone (O_{3}) episodes during the Program of Regional Integrated Experiments of Air Quality over the Pearl River Delta, China, in October 2004 (PRIDE-PRD2004). The simulation suggests that O_{3} pollution is a regional phenomenon in the Pearl River Delta (PRD). Elevated O_{3} levels often occurred in the southwestern inland PRD, Pearl R...
Directory of Open Access Journals (Sweden)
Lina Zhong
2014-04-01
Full Text Available In this study, statistical data on the national economic and social development, including the year-end actual area of arable land, the crop yield per unit area and 10 factors, were obtained for the period between 1980 and 2010 and used to analyze the factors driving changes in the arable land of the Loess Plateau in northern Shaanxi, China. The following areas of arable land, which represent different spatial scales, were investigated: the Baota District, the city of Yan’an, and the Northern Shaanxi region. The scale effects of the factors driving the changes to the arable land were analyzed using a canonical correlation analysis and a principal component analysis. Because it was difficult to quantify the impact of the national government policies on the arable land changes, the contributions of the national government policies to the changes in arable land were analyzed qualitatively. The primary conclusions of the study were as follows: between 1980 and 2010, the arable land area decreased. The trends of the year-end actual arable land proportion of the total area in the northern Shaanxi region and Yan’an City were broadly consistent, whereas the proportion in the Baota District had no obvious similarity with the northern Shaanxi region and Yan’an City. Remarkably different factors were shown to influence the changes in the arable land at different scales. Environmental factors exerted a greater effect for smaller scale arable land areas (the Baota District. The effect of socio-economic development was a major driving factor for the changes in the arable land area at the city and regional scales. At smaller scales, population change, urbanization and socio-economic development affected the crop yield per unit area either directly or indirectly. Socio-economic development and the modernization of agricultural technology had a greater effect on the crop yield per unit area at the large-scales. Furthermore, the qualitative analysis
Directory of Open Access Journals (Sweden)
X. Wang
2010-05-01
Full Text Available In this study, the Community Multiscale Air Quality (CMAQ modeling system is used to simulate the ozone (O_{3} episodes during the Program of Regional Integrated Experiments of Air Quality over the Pearl River Delta, China, in October 2004 (PRIDE-PRD2004. The simulation suggests that O_{3} pollution is a regional phenomenon in the Pearl River Delta (PRD. Elevated O_{3} levels often occurred in the southwestern inland PRD, Pearl River estuary (PRE, and southern coastal areas during the 1-month field campaign. Three evolution patterns of simulated surface O_{3} are summarized based on different near-ground flow conditions. More than 75% of days featured interactions between weak synoptic forcing and local sea-land circulation. Integrated process rate (IPR analysis shows that photochemical production is a dominant contributor to O_{3} enhancement from 09:00 to 15:00 local standard time in the atmospheric boundary layer over most areas with elevated O_{3} occurrence in the mid-afternoon. The simulated ozone production efficiency is 2–8 O_{3} molecules per NO_{x} molecule oxidized in areas with high O_{3} chemical production. Precursors of O_{3} originating from different source regions in the central PRD are mixed during the course of transport to downwind rural areas during nighttime and early morning, where they then contribute to the daytime O_{3} photochemical production. The sea-land circulation plays an important role on the regional O_{3} formation and distribution over PRD. Sensitivity studies suggest that O_{3} formation is volatile-organic-compound-limited in the central inland PRD, PRE, and surrounding coastal areas with less chemical aging (NO_{x}/NO_{y}>0.6, but is NO_{x}-limited in the rural southwestern PRD with aged air (NO_{x}/NO_{y}<0.3.
Wang, Yulei; Liu, Jian
2016-01-01
In this paper, the secular full-orbit simulations of runaway electrons with synchrotron radiation in tokamak fields are carried out using a relativistic volume-preserving algorithm. Detailed phase-space behaviors of runaway electrons are investigated in different dynamical timescales spanning 11 orders. When looking into the small timescale, i.e., the characteristic timescale imposed by Lorentz force, the severely deformed helical trajectory of energetic runaway electron is witnessed. A qualitative analysis of the neoclassical scattering, a kind of collisionless pitch-angle scattering phenomena, is provided when considering the coupling between the rotation of momentum vector and the background magnetic field. In large timescale up to one second, it is found that the initial condition of runaway electrons in phase space globally influences the pitch-angle scattering, the momentum evolution, and the loss-gain ratio of runaway energy evidently. However, the initial value has little impact on the synchrotron ene...
Defect detection in industrial radiography: a multi-scale approach
International Nuclear Information System (INIS)
Radiography is used by Electricite de France for pipe inspection in nuclear power plant in order to detect defects. For several years, the RD Division of EDF has undertaken research to define image processing methods well adapted to radiographic images. The main issues raised by these images are their low contrast, their high level of noise, the presence of a trend and the variable size of the defects. A data base of digitized radiographs of pipes has been gathered and the statistical, topological and geometrical properties of all of these images have been analyzed. From this study, a global indicator of the presence of defects and local features, leading to a classification of images into areas with or without defects, have been extracted. The defect localisation problem has been considered in a multi-scale framework based on the creation of a family of images with increasing regularity and defined as a solution of a partial differential equation. From a choice of axioms, a set of equations may be deduced which define various multi-scale analyses. The survey of the properties of such analysed, when applied to images altered with different types of noise, has lead to the selection of the digitized radiographs best adapted multi-scale analysis. The segmentation process, uses the geodesic information attached to defects via connection cost concept. The final decision is based on a summary of the information extracted at several scales. A fuzzy logic approach has been proposed to solve this part. We then developed methods and tools for expertise guidance and validated them on a complete data base of images. Some global indicators have been extracted and a detection and localisation process has been achieved for large defects. (author). 117 refs., 73 figs
Computer-Aided Multiscale Modelling for Chemical Process Engineering
DEFF Research Database (Denmark)
Morales Rodriguez, Ricardo; Gani, Rafiqul
2007-01-01
Chemical processes are generally modeled through monoscale approaches, which, while not adequate, satisfy a useful role in product-process design. In this case, use of a multi-dimensional and multi-scale model-based approach has importance in product-process development. A computer-aided framework......T) for model translation, analysis and solution. The integration of ModDev, MoT and ICAS or any other external software or process simulator (using COM-Objects) permits the generation of different models and/or process configurations for purposes of simulation, design and analysis. Consequently, it is possible...... for model generation, analysis, solution and implementation is necessary for the development and application of the desired model-based approach for product-centric process design/analysis. This goal is achieved through the combination of a system for model development (ModDev), and a modelling tool (Mo...
Netzeband, Christian; Arlt, Tobias; Wippermann, Klaus; Lehnert, Werner; Manke, Ingo
2016-09-01
This study investigates the ageing effects on the microstructure of the anode catalyst layer of direct methanol fuel cells (DMFC) after complete methanol starvation. To this end the samples of two methanol-depleted membrane electrode assemblies (MEA) have been compared with a pristine reference sample. A three-dimensional characterization of the anode catalyst layer (ACL) structure on a nanometer scale has been conducted by focused ion beam (FIB)/scanning electron microscope (SEM) tomography. The FIB/SEM tomography allows for a detailed analysis of statistic parameters of micro-structured materials, such as porosity, tortuosity and pore size distributions. Furthermore, the SEM images displayed a high material contrast between the heavy catalyst metals (Pt/Ru) and the relatively light carbon support, which made it possible to map the catalyst distribution in the acquired FIB/SEM tomographies. Additional synchrotron X-ray tomographies have been conducted in order to obtain an overview of the structural changes of all the components of a section of the MEAs after methanol depletion.
Coppedè, Nicola
2016-03-18
Conducting polymers are materials displaying high electrical conductivity, easy of fabrication, flexibility and biocompatibility, for this, they are routinely employed in organic electronics, printed electronics, and bioelectronics. Organic electrochemical transistors (OECTs) are a second generation of organic thin transistors, in which the insulator layer is an electrolyte medium and the conductive polymer is electrochemically active. OECT devices have been demonstrated in chemical and biological sensing: while accurate in determining the size of individual ions in solution, similar devices break down if challenged with complex mixtures. Here, we combine a conductive PEODOT:PSS polymer with a super-hydrophobic scheme to obtain a family of advanced devices, in which the ability to manipulate a biological solution couples to a precise texture of the substrate (which incorporates five micro-electrodes in a line, and each is a site specific measurement point), and this permits to realize time and space resolved analysis of a solution. While the competition between convection and diffusion in a super-hydrophobic drop operates the separation of different species based on their size and charge, the described device delivers the ability to register a similar difference. In the following, we demonstrate the device in the sensing of a solution in which CTAB and adrenaline are separated with good sensitivity, selectivity and reliability.
Directory of Open Access Journals (Sweden)
C. Montebello
2015-07-01
Full Text Available This paper describes a novel method to model the stress gradient effect in fretting-fatigue. The analysis of the mechanical fields in the proximity of the contact edges allows to extract nonlocal intensity factors that take into account the stress gradient evolution. For this purpose, the kinetic field around the contact ends is partitioned into a summation of multiple terms, each one expressed as the product between nonlocal intensity factors, Is, Ia, Ic, depending on the macroscopic loads applied to the mechanical assembly, and spatial reference fields, ds, da, dc, depending on the local geometry of the part. This description is obtained through nonintrusive post-processing of FE computation and is conceived in order to be easily implementable in the industrial context. By using as input the macroscopic load, the procedure consists in computing a set of nonlocal stress intensity factors, which are an index of the severity of the stress field in the proximity of the contact edges. This description has two main advantages. First, the nonlocal stress intensity factors are independent from the geometry used. Secondly, the procedure is easily applicable to industrial scale FE model..
Interactive multiscale tensor reconstruction for multiresolution volume visualization.
Suter, Susanne K; Guitián, José A Iglesias; Marton, Fabio; Agus, Marco; Elsener, Andreas; Zollikofer, Christoph P E; Gopi, M; Gobbetti, Enrico; Pajarola, Renato
2011-12-01
Large scale and structurally complex volume datasets from high-resolution 3D imaging devices or computational simulations pose a number of technical challenges for interactive visual analysis. In this paper, we present the first integration of a multiscale volume representation based on tensor approximation within a GPU-accelerated out-of-core multiresolution rendering framework. Specific contributions include (a) a hierarchical brick-tensor decomposition approach for pre-processing large volume data, (b) a GPU accelerated tensor reconstruction implementation exploiting CUDA capabilities, and (c) an effective tensor-specific quantization strategy for reducing data transfer bandwidth and out-of-core memory footprint. Our multiscale representation allows for the extraction, analysis and display of structural features at variable spatial scales, while adaptive level-of-detail rendering methods make it possible to interactively explore large datasets within a constrained memory footprint. The quality and performance of our prototype system is evaluated on large structurally complex datasets, including gigabyte-sized micro-tomographic volumes.
Wattrus, N. J.; Binder, T.
2012-12-01
. Bottom classification based upon backscatter measurements from the collected multibeam sonar data using Quester Tangent's Multiview software does not appear to readily resolve the various classes of rocky substrate, for example it appears to have difficulty differentiating between areas dominated by boulder sized rocks from areas covered predominantly by cobble sized fragments. The extremely shallow nature of the reef areas utilized by the spawning fish (z_av fish in spawning condition. We describe the results of a study to investigate the application of terrain analysis for subdividing the reefs into regions based upon their texture and morphology. A variety of descriptors are evaluated as is the influence of scale on the analyses.
Directory of Open Access Journals (Sweden)
L. Li
2012-11-01
Full Text Available A high O_{3} episode was detected in urban Shanghai, a typical city in the Yangtze River Delta (YRD region in August 2010. The CMAQ integrated process rate method is applied to account for the contribution of different atmospheric processes during the high pollution episode. The analysis shows that the maximum concentration of ozone occurs due to transport phenomena, including vertical diffusion and horizontal advective transport. Gas-phase chemistry producing O_{3} mainly occurs at the height of 300–1500 m, causing a strong vertical O_{3} transport from upper levels to the surface layer. The gas-phase chemistry is an important sink for O_{3} in the surface layer, coupled with dry deposition. Cloud processes may contribute slightly to the increase of O_{3} due to convective clouds or to the decrease of O_{3} due to scavenging. The horizontal diffusion and heterogeneous chemistry contributions are negligible during the whole episode. Modeling results show that the O_{3} pollution characteristics among the different cities in the YRD region have both similarities and differences. During the buildup period, the O_{3} starts to appear in the city regions of the YRD and is then transported to the surrounding areas under the prevailing wind conditions. The O_{3} production from photochemical reaction in Shanghai and the surrounding area is most significant, due to the high emission intensity in the large city; this ozone is then transported out to sea by the westerly wind flow, and later diffuses to rural areas like Chongming island, Wuxi and even to Nanjing. The O_{3} concentrations start to decrease in the cities after sunset, due to titration of the NO emissions, but ozone can still be transported and maintain a significant concentration in rural areas and even regions outside the YRD region, where the NO emissions are very small.
Morante-Filho, José Carlos; Arroyo-Rodríguez, Víctor; Faria, Deborah
2016-01-01
Biodiversity maintenance in human-altered landscapes (HALs) depends on the species turnover among localities, but the patterns and determinants of β-diversity in HALs are poorly known. In fact, declines, increases and neutral shifts in β-diversity have all been documented, depending on the landscape, ecological group and spatial scale of analysis. We shed some light on this controversy by assessing the patterns and predictors of bird β-diversity across multiple spatial scales considering forest specialist and habitat generalist bird assemblages. We surveyed birds from 144 point counts in 36 different forest sites across two landscapes with different amount of forest cover in the Brazilian Atlantic forest. We analysed β-diversity among points, among sites and between landscapes with multiplicative diversity partitioning of Hill numbers. We tested whether β-diversity among points was related to within-site variations in vegetation structure, and whether β-diversity among sites was related to site location and/or to differences among sites in vegetation structure and landscape composition (i.e. per cent forest and pasture cover surrounding each site). β-diversity between landscapes was lower than among sites and among points in both bird assemblages. In forest specialist birds, the landscape with less forest cover showed the highest β-diversity among sites (bird differentiation among sites), but generalist birds showed the opposite pattern. At the local scale, however, the less forested landscape showed the lowest β-diversity among points (bird homogenization within sites), independently of the bird assemblage. β-diversity among points was weakly related to vegetation structure, but higher β-diversity values were recorded among sites that were more isolated from each other, and among sites with higher differences in landscape composition, particularly in the less forested landscape. Our findings indicate that patterns of bird β-diversity vary across scales
Directory of Open Access Journals (Sweden)
L. Li
2012-06-01
Full Text Available High ozone concentration has become an important issue in summer in most economically developed cities in Eastern China. In this paper, observations at an urban site within the Shanghai city are used to examine the typical high ozone episodes in August 2010, and the MM5-CMAQ modeling system is then applied to reproduce the typical high ozone episodes. In order to account for the contribution of different atmospheric processes during the high pollution episodes, the CMAQ integrated process rate (IPR is used to assess the different atmospheric dynamics in rural and urban sites of Shanghai, Nanjing and Hangzhou, which are typical cities of the Yangtze River Delta (YRD region. In order to study the contributions of the main atmospheric processes leading to ozone formation, vertical process analysis in layer 1 (0–40 m, layer 7 (350–500 m, layer 8 (500–900 m and layer 10 (1400–2000 m has been considered. The observations compare well with the results of the numerical model. IPR analysis shows that the maximum concentration of ozone occurs due to transport phenomena, including vertical diffusion and horizontal advective transport. The gas-phase chemistry producing O_{3} mainly occurs in the height of 300–1500 m, causing a strong vertical O_{3} transport from upper levels to the surface layer. The gas-phase chemistry is an important sink for O_{3} in the surface layer, coupled with dry deposition. The cloud processes, horizontal diffusion and heterogeneous chemistry contributions are negligible during the whole episode. In the urban Shanghai area, the average O_{3} production rates contributed by vertical diffusion and horizontal transport are 24.7 ppb h^{−1}, 3.6 ppb h^{−1}, accounting for 27.6% and 6.6% of net surface O_{3} change, respectively. The average contributions of chemistry, dry deposition and vertical advective transport to O_{3} production are −21.9, −4.3 and
EEMD-based multiscale ICA method for slewing bearing fault detection and diagnosis
Žvokelj, Matej; Zupan, Samo; Prebil, Ivan
2016-05-01
A novel multivariate and multiscale statistical process monitoring method is proposed with the aim of detecting incipient failures in large slewing bearings, where subjective influence plays a minor role. The proposed method integrates the strengths of the Independent Component Analysis (ICA) multivariate monitoring approach with the benefits of Ensemble Empirical Mode Decomposition (EEMD), which adaptively decomposes signals into different time scales and can thus cope with multiscale system dynamics. The method, which was named EEMD-based multiscale ICA (EEMD-MSICA), not only enables bearing fault detection but also offers a mechanism of multivariate signal denoising and, in combination with the Envelope Analysis (EA), a diagnostic tool. The multiscale nature of the proposed approach makes the method convenient to cope with data which emanate from bearings in complex real-world rotating machinery and frequently represent the cumulative effect of many underlying phenomena occupying different regions in the time-frequency plane. The efficiency of the proposed method was tested on simulated as well as real vibration and Acoustic Emission (AE) signals obtained through conducting an accelerated run-to-failure lifetime experiment on a purpose-built laboratory slewing bearing test stand. The ability to detect and locate the early-stage rolling-sliding contact fatigue failure of the bearing indicates that AE and vibration signals carry sufficient information on the bearing condition and that the developed EEMD-MSICA method is able to effectively extract it, thereby representing a reliable bearing fault detection and diagnosis strategy.
Fabrication of Modified MMT/Glass/Vinylester Multiscale Composites and Their Mechanical Properties
Directory of Open Access Journals (Sweden)
Garima Mittal
2015-01-01
Full Text Available Montmorillonite (MMT may become a preferred filler material for fiber-reinforced polymer (FRP composites due to its high aspect ratio, large surface area, and low charge density. In the present paper, MMT/glass/vinylester multiscale composites are prepared with untreated and surface-treated MMT clay particles with an MMT content of 1.0 wt%. Effects of surface treatment on mechanical properties of MMT/glass/vinylester multiscale composites are investigated through tensile and bending tests, which revealed enhanced mechanical properties in the case of surface-treated MMT. Thermal properties are studied through thermogravimetric analysis (TGA and dynamic mechanical analysis (DMA. X-Ray diffraction is performed to investigate the interaction between MMT and the matrix. Fourier Transform Infrared (FTIR is also performed for both untreated and surface-treated MMT. Furthermore, Field Emission-Scanning Electron Microscope (FE-SEM is conducted to investigate the path of fracture propagation within the composite surface, showing that the surface-treated MMT based multiscale composite has better interactions with the host matrix than the untreated MMT multiscale composites. These composites with enhanced mechanical strength can be used for various mechanical applications.
Energy Technology Data Exchange (ETDEWEB)
Rundle, John B.
2004-12-31
Physical Review Letters (Tiampo et al., in press), demonstrate that the Southern California system is ergodic in the same way that is seen in the models. These results will be discussed in more detail below. However, the point that needs to be emphasized is that it was the combination of model investigation via theory and simulation coupled with assimilation and classification of real data and applying the methods of statistical mechanics to real fault systems that led to both a successful forecasting algorithm and a deeper understanding of the nature of earthquake fault systems. This paper describes in some detail the results obtained in the previous funding period. We present these in three groups. (A) Investigation of statistical physics models and applications. (B) Earthquake fault systems and Greens functions for complex sources and (C) Space time patterns, data analysis and forecasting.
Multiscale optimization of saturated poroelastic actuators
DEFF Research Database (Denmark)
Andreasen, Casper Schousboe; Sigmund, Ole
A multiscale method for optimizing the material micro structure in a macroscopically heterogeneous saturated poroelastic media with respect to macro properties is presented. The method is based on topology optimization using the homogenization technique, here applied to the optimization of a bi......-morph saturated poroelastic actuator....
Multiscale Simulation of Protein Mediated Membrane Remodeling
Ayton, Gary S.; Voth, Gregory A.
2009-01-01
Proteins interacting with membranes can result in substantial membrane deformations and curvatures. This effect is known in its broadest terms as membrane remodeling. This review article will survey current multiscale simulation methodologies that have been employed to examine protein-mediated membrane remodeling.
Multiscale entropy (MSE and multicomponent complexity (MCC
Directory of Open Access Journals (Sweden)
M. Boorboor
2007-06-01
Full Text Available Multiscale entropy (MSE is a powerful method for determining the complexity of random time series. In this paper we, investigate the cardiac heart interbeat interval (RR time series by introducing a new method based on MSE, called multicomponent complexity (MCC and find clear difference between healthy samples and samples with Congestive heart failure (CHF disease.
Multiscale entropy (MSE) and multicomponent complexity (MCC)
M. Boorboor; Shahbazi, F.; Mirza, B.
2007-01-01
Multiscale entropy (MSE) is a powerful method for determining the complexity of random time series. In this paper we, investigate the cardiac heart interbeat interval (RR) time series by introducing a new method based on MSE, called multicomponent complexity (MCC) and find clear difference between healthy samples and samples with Congestive heart failure (CHF) disease.
Collaboratory for Multiscale Chemical Science (CMCS)
Energy Technology Data Exchange (ETDEWEB)
Allison, Thomas C [NIST
2012-07-03
This document provides details of the contributions made by NIST to the Collaboratory for Multiscale Chemical Science (CMCS) project. In particular, efforts related to the provision of data (and software in support of that data) relevant to the combustion pilot project are described.
Multiscale phenomenology of the cosmic web
Aragon-Calvo, Miguel A.; van de Weijgaert, Marinus; Jones, Bernard J. T.
2010-01-01
We analyse the structure and connectivity of the distinct morphologies that define the cosmic web. With the help of our multiscale morphology filter (MMF), we dissect the matter distribution of a cosmological Lambda cold dark matter N-body computer simulation into cluster, filaments and walls. The M
Multi-Scale Change Detection Research of Remotely Sensed Big Data in CyberGIS
Xing, J.; Sieber, R.
2015-12-01
Big remotely sensed data, the heterogeneity of satellite platforms and file formats along with increasing volumes and velocities, offers new types of analyses. This makes big remotely sensed data a good candidate for CyberGIS, the aim of which is to enable knowledge discovery of big data in the cloud. We apply CyberGIS to feature-based multi-scale land use/cover change (LUCC) detection. There have been attempts to do multi-scale LUCC. However, studies were done with small data and could not consider the mismatch between multi-scale analysis and computational scale. They have yet to consider the possibilities for scalar research across numerous temporal and spatial scales afforded by big data, especially if we want to advance beyond pixel-based analysis and also reduce preprocessing requirements. We create a geospatial cyberinfrastructure (GCI) to handle multi-spatio-temporal scale change detection. We first clarify different meanings of scale in CyberGIS and LUCC to derive a feature scope layer in the GCI based on Stommel modelling. Our analysis layer contains a multi-scale segmentation-based method based on normalized cut image segmentation and wavelet-based image scaling algorithms. Our computer resource utilization layer uses Wang and Armstrong's (2009) method for mainly for memory, I/O and CPU time. Our case is urban-rural change detection in the Greater Montreal Area (5 time periods, 2006-2012, 100 virtual machines), 36,000km2 and varying from 0.6m to 38m resolution. We present a ground truthed accuracy assessment of a change matrix that is composed of 6 feature classes at 12 different spatio-temporal scales, and the performance of the change detection GCI for multi-scale LUCC study. The GCI allows us to extract and coordinate different types of changes by varying spatio-temporal scales from the big imagery datasets.
Multiscale dictionaries, transforms, and learning in high-dimensions
Maggioni, Mauro; Gerber, Samuel
2013-09-01
Mapping images to a high-dimensional feature space, either by considering patches of images or other features, has lead to state-of-art results in signal processing tasks such as image denoising and imprinting, and in various machine learning and computer vision tasks on images. Understanding the geometry of the embedding of images into high-dimensional feature space is a challenging problem. Finding efficient representations and learning dictionaries for such embeddings is also problematic, often leading to expensive optimization algorithms. Many such algorithms scale poorly with the dimension of the feature space, for example with the size of patches of images if these are chosen as features. This is in contrast with the crucial needs of using a multi-scale approach in the analysis of images, as details at multiple scales are crucial in image understanding, as well as in many signal processing tasks. Here we exploit a recent dictionary learning algorithm based on Geometric Wavelets, and we extend it to perform multi-scale dictionary learning on image patches, with efficient algorithms for both the learning of the dictionary, and the computation of coefficients onto that dictionary. We also discuss how invariances in images may be introduced in the dictionary learning phase, by generalizing the construction of such dictionaries to non-Euclidean spaces.
Multiscale analysis of a sustained precipitation event
Knupp, Kevin R.; Williams, Steven F.
1987-01-01
Mesoscale data collected during both the satellite precipitation and cloud experiment and the microburst and severe thunderstorm program are analyzed in order to describe features associated with two distinct mesoscale precipitation events that occurred about 10 hours apart over the region of northern Alabama to central Tennessee in June 1986. Data sets used include mesobeta-scale rawinsonde data, surface mesonet data, RADAP data, and GOES images. The present mesoscale environment involved the merger of Hurricane Bonnie remnants with a preexisting midlatitude short-wave trough.
Multiscale thermomechanical analysis of multiphase materials
Yadegari Varnamkhasti, S.
2015-01-01
The thermomechanical simulation of materials with evolving, multiphase microstructures poses various modeling and numerical challenges. For example, the separate phases in a multiphase microstructure can interact with each other during thermal and/or mechanical loading, the effect of which is signif
The triple decomposition of a fluctuating velocity field in a multiscale flow
Energy Technology Data Exchange (ETDEWEB)
Baj, P.; Bruce, P. J. K.; Buxton, O. R. H. [Department of Aeronautics, Imperial College London, London SW7 2AZ (United Kingdom)
2015-07-15
A new method for the triple decomposition of a multiscale flow, which is based on the novel optimal mode decomposition (OMD) technique, is presented. OMD provides low order linear dynamics, which fits a given data set in an optimal way and is used to distinguish between a coherent (periodic) part of a flow and a stochastic fluctuation. The method needs no external phase indication since this information, separate for coherent structures associated with each length scale introduced into the flow, appears as the output. The proposed technique is compared against two traditional methods of the triple decomposition, i.e., bin averaging and proper orthogonal decomposition. This is done with particle image velocimetry data documenting the near wake of a multiscale bar array. It is shown that both traditional methods are unable to provide a reliable estimation for the coherent fluctuation while the proposed technique performs very well. The crucial result is that the coherence peaks are not observed within the spectral properties of the stochastic fluctuation derived with the proposed method; however, these properties remain unaltered at the residual frequencies. This proves the method’s capability of making a distinction between both types of fluctuations. The sensitivity to some prescribed parameters is checked revealing the technique’s robustness. Additionally, an example of the method application for analysis of a multiscale flow is given, i.e., the phase conditioned transverse integral length is investigated in the near wake region of the multiscale object array.
Expanded Mixed Multiscale Finite Element Methods and Their Applications for Flows in Porous Media
Jiang, L.
2012-01-01
We develop a family of expanded mixed multiscale finite element methods (MsFEMs) and their hybridizations for second-order elliptic equations. This formulation expands the standard mixed multiscale finite element formulation in the sense that four unknowns (hybrid formulation) are solved simultaneously: pressure, gradient of pressure, velocity, and Lagrange multipliers. We use multiscale basis functions for both the velocity and the gradient of pressure. In the expanded mixed MsFEM framework, we consider both separable and nonseparable spatial scales. Specifically, we analyze the methods in three categories: periodic separable scales, G-convergent separable scales, and a continuum of scales. When there is no scale separation, using some global information can significantly improve the accuracy of the expanded mixed MsFEMs. We present a rigorous convergence analysis of these methods that includes both conforming and nonconforming formulations. Numerical results are presented for various multiscale models of flow in porous media with shale barriers that illustrate the efficacy of the proposed family of expanded mixed MsFEMs. © 2012 Society for Industrial and Applied Mathematics.
Chakraborty, Saikat; Balakotaiah, Vemuri; Bidani, Akhil
2007-01-21
This paper presents a novel multiscale methodology for quantitative analysis of pulmonary gas exchange. The process of oxygen uptake in the lungs is a complex multiscale process, characterized by multiple time and length scales which are coupled nonlinearly through the processes of diffusion, convection and reaction, and the overall oxygen uptake is significantly influenced by the transport and reaction rate processes at the small-scales. Based on the separation of length scales, we characterize these disparate scales by three representative ones, namely micro (red blood cell), meso (capillary and alveolus) and macro (lung). We start with the fundamental convection-diffusion-reaction (CDR) equation that quantifies transport and reaction rates at each scale and apply spatial averaging techniques to reduce the dimensionality of these models. The resultant low-dimensional models embed each scale hierarchically within the other while retaining the important parameters of the small-scales in the averaged equations, and drastically reduce the computational efforts involved in solving them. We use our multiscale model for pulmonary gas exchange to quantify the oxygen uptake abnormalities in patients with hepatopulmonary syndrome (HPS), a disease which is characterized by coupled abnormalities in multiple length scales. Based on our multiscale modeling, we suggest a strategy to stratify patients with HPS into two categories--those who are oxygen-responsive and those who are oxygen non-responsive with intractable hypoxemia. PMID:16973178
Genetic divergence among cupuaçu accessions by multiscale bootstrap resampling
Directory of Open Access Journals (Sweden)
Vinicius Silva dos Santos
2015-06-01
Full Text Available This study aimed at investigating the genetic divergence of eighteen accessions of cupuaçu trees based on fruit morphometric traits and comparing usual methods of cluster analysis with the proposed multiscale bootstrap resampling methodology. The data were obtained from an experiment conducted in Tomé-Açu city (PA, Brazil, arranged in a completely randomized design with eighteen cupuaçu accessions and 10 repetitions, from 2004 to 2011. Genetic parameters were estimated by restricted maximum likelihood/best linear unbiased prediction (REML/BLUP methodology. The predicted breeding values were used in the study on genetic divergence through Unweighted Pair Cluster Method with Arithmetic Mean (UPGMA hierarchical clustering and Tocher’s optimization method based on standardized Euclidean distance. Clustering consistency and optimal number of clusters in the UPGMA method were verified by the cophenetic correlation coefficient (CCC and Mojena’s criterion, respectively, besides the multiscale bootstrap resampling technique. The use of the clustering UPGMA method in situations with and without multiscale bootstrap resulted in four and five clusters, respectively, while the Tocher’s method resulted in seven clusters. The multiscale bootstrap resampling technique proves to be efficient to assess the consistency of clustering in hierarchical methods and, consequently, the optimal number of clusters.
Urban climate multi-scale modelling in Bilbao (Spain): a review
Acero, Juan A.; Kupski, Sebastian; Arrizabalaga, Jon; Katzschner, Lutz
2015-01-01
Despite development of cities are including more sustainable aspects (e.g. reduction of energy consumption), urban climate still needs to be consolidated as an important variable in urban planning. In this sense, the analysis of urban climate requires a multiscale approach. This work presents a review of the results of the analysis of urban climate in Bilbao (Spain). In the meso-scale, an Urban Climate Map (UC-Map) is developed using a method based on GIS calculations, specific clima...
Multiscale modeling of polymer nanocomposites
Sheidaei, Azadeh
In recent years, polymer nano-composites (PNCs) have increasingly gained more attention due to their improved mechanical, barrier, thermal, optical, electrical and biodegradable properties in comparison with the conventional micro-composites or pristine polymer. With a modest addition of nanoparticles (usually less than 5wt. %), PNCs offer a wide range of improvements in moduli, strength, heat resistance, biodegradability, as well as decrease in gas permeability and flammability. Although PNCs offer enormous opportunities to design novel material systems, development of an effective numerical modeling approach to predict their properties based on their complex multi-phase and multiscale structure is still at an early stage. Developing a computational framework to predict the mechanical properties of PNC is the focus of this dissertation. A computational framework has been developed to predict mechanical properties of polymer nano-composites. In chapter 1, a microstructure inspired material model has been developed based on statistical technique and this technique has been used to reconstruct the microstructure of Halloysite nanotube (HNT) polypropylene composite. This technique also has been used to reconstruct exfoliated Graphene nanoplatelet (xGnP) polymer composite. The model was able to successfully predict the material behavior obtained from experiment. Chapter 2 is the summary of the experimental work to support the numerical work. First, different processing techniques to make the polymer nanocomposites have been reviewed. Among them, melt extrusion followed by injection molding was used to manufacture high density polyethylene (HDPE)---xGnP nanocomposties. Scanning electron microscopy (SEM) also was performed to determine particle size and distribution and to examine fracture surfaces. Particle size was measured from these images and has been used for calculating the probability density function for GNPs in chapter 1. A series of nanoindentation tests have
Chung, Eric
2015-12-11
In this paper, we develop a mass conservative multiscale method for coupled flow and transport in heterogeneous porous media. We consider a coupled system consisting of a convection-dominated transport equation and a flow equation. We construct a coarse grid solver based on the Generalized Multiscale Finite Element Method (GMsFEM) for a coupled system. In particular, multiscale basis functions are constructed based on some snapshot spaces for the pressure and the concentration equations and some local spectral decompositions in the snapshot spaces. The resulting approach uses a few multiscale basis functions in each coarse block (for both the pressure and the concentration) to solve the coupled system. We use the mixed framework, which allows mass conservation. Our main contributions are: (1) the development of a mass conservative GMsFEM for the coupled flow and transport; (2) the development of a robust multiscale method for convection-dominated transport problems by choosing appropriate test and trial spaces within Petrov-Galerkin mixed formulation. We present numerical results and consider several heterogeneous permeability fields. Our numerical results show that with only a few basis functions per coarse block, we can achieve a good approximation.
International Conference on Multiscale Methods and Partial Differential Equations.
Energy Technology Data Exchange (ETDEWEB)
Thomas Hou
2006-12-12
The International Conference on Multiscale Methods and Partial Differential Equations (ICMMPDE for short) was held at IPAM, UCLA on August 26-27, 2005. The conference brought together researchers, students and practitioners with interest in the theoretical, computational and practical aspects of multiscale problems and related partial differential equations. The conference provided a forum to exchange and stimulate new ideas from different disciplines, and to formulate new challenging multiscale problems that will have impact in applications.
Tracking magnetogram proper motions by multiscale regularization
Jones, Harrison P.
1995-01-01
Long uninterrupted sequences of solar magnetograms from the global oscillations network group (GONG) network and from the solar and heliospheric observatory (SOHO) satellite will provide the opportunity to study the proper motions of magnetic features. The possible use of multiscale regularization, a scale-recursive estimation technique which begins with a prior model of how state variables and their statistical properties propagate over scale. Short magnetogram sequences are analyzed with the multiscale regularization algorithm as applied to optical flow. This algorithm is found to be efficient, provides results for all the spatial scales spanned by the data and provides error estimates for the solutions. It is found that the algorithm is less sensitive to evolutionary changes than correlation tracking.
Quantum Mechanics Based Multiscale Modeling of Materials
Lu, Gang
2013-03-01
We present two quantum mechanics based multiscale approaches that can simulate extended defects in metals accurately and efficiently. The first approach (QCDFT) can treat multimillion atoms effectively via density functional theory (DFT). The method is an extension of the original quasicontinuum approach with DFT as its sole energetic formulation. The second method (QM/MM) has to do with quantum mechanics/molecular mechanics coupling based on the constrained density functional theory, which provides an exact framework for a self-consistent quantum mechanical embedding. Several important materials problems will be addressed using the multiscale modeling approaches, including hydrogen-assisted cracking in Al, magnetism-controlled dislocation properties in Fe and Si pipe diffusion along Al dislocation core. We acknowledge the support from the Office of Navel Research and the Army Research Office.
Multiscale Investigation of Chemical Interference in Proteins
Samiotakis, Antonios; Cheung, Margaret S
2010-01-01
We developed a multiscale approach (MultiSCAAL) that integrates the potential of mean force (PMF) obtained from all-atomistic molecular dynamics simulations with a knowledge-based energy function for coarse-grained molecular simulations in better exploring the energy landscape of a small protein under chemical interference such as chemical denaturation. An excessive amount of water molecules in all-atomistic molecular dynamics simulations often negatively impacts the sampling efficiency of some advanced sampling techniques such as the replica exchange method and it makes the investigation of chemical interferences on protein dynamics difficult. Thus, there is a need to develop an effective strategy that focuses on sampling structural changes in protein conformations rather than solvent molecule fluctuations. In this work, we address this issue by devising a multiscale simulation scheme (MultiSCAAL) that bridges the gap between all-atomistic molecular dynamics simulation and coarse-grained molecular simulation...
MULTI-SCALE GAUSSIAN PROCESSES MODEL
Institute of Scientific and Technical Information of China (English)
Zhou Yatong; Zhang Taiyi; Li Xiaohe
2006-01-01
A novel model named Multi-scale Gaussian Processes (MGP) is proposed. Motivated by the ideas of multi-scale representations in the wavelet theory, in the new model, a Gaussian process is represented at a scale by a linear basis that is composed of a scale function and its different translations. Finally the distribution of the targets of the given samples can be obtained at different scales. Compared with the standard Gaussian Processes (GP) model, the MGP model can control its complexity conveniently just by adjusting the scale parameter. So it can trade-off the generalization ability and the empirical risk rapidly. Experiments verify the feasibility of the MGP model, and exhibit that its performance is superior to the GP model if appropriate scales are chosen.
Zewail, R.; Elsafi, A.; Durdle, N.
2009-02-01
Medical experts often examine hundreds of spine x-rays to determine existence of diseases like osteoarthritis, osteoporoses, and osteophites. Accurate vertebrae segmentation plays a great role in the proper assessment of various vertebral abnormalities. Manual segmentation methods are both time consuming and non-reproducible, hence, developing efficient computer-assisted segmentation methods has been a long standing goal. Over the past decade, segmentation methods that utilize statistical models of shape and appearance have drawn much interest within the medical imaging community. However, despite being a promising approach, they are always faced with a number of challenges such as: poor image quality, and the ability to generalize well to unseen vertebral deformities. This paper presents a novel vertebral segmentation method using Contourlet-based salient point matching and a localized multi-scale shape prior. We employ a multi-scale directional analysis tool, namely contourlets, to build local appearance profiles at salient points of the vertebra's body. The contourlet-based local appearance model is used to detect the vertebral bodies in the test x-ray image. A novel localized multi-scale shape prior is used to drive the segmentation process. Within a best-basis selection framework, the proposed shape prior benefits from the multi-scale nature of wavelet packets, and the capability of ICA to capture hidden independent modes of variations. Experiments were conducted using a set of 100 digital x-ray images of lumbar spines. The contourlet-based appearance profiles and the localized multi-scale shape prior were constructed using a training subset of images, and then matched to unseen images. Promising results were obtained compared to related work in the literature with an average segmentation error of 1.1997 mm.
Generalized Multiscale Finite Element Methods for Wave Propagation in Heterogeneous Media
Chung, Eric T.
2014-11-13
Numerical modeling of wave propagation in heterogeneous media is important in many applications. Due to their complex nature, direct numerical simulations on the fine grid are prohibitively expensive. It is therefore important to develop efficient and accurate methods that allow the use of coarse grids. In this paper, we present a multiscale finite element method for wave propagation on a coarse grid. The proposed method is based on the generalized multiscale finite element method (GMsFEM) (see [Y. Efendiev, J. Galvis, and T. Hou, J. Comput. Phys., 251 (2012), pp. 116--135]). To construct multiscale basis functions, we start with two snapshot spaces in each coarse-grid block, where one represents the degrees of freedom on the boundary and the other represents the degrees of freedom in the interior. We use local spectral problems to identify important modes in each snapshot space. These local spectral problems are different from each other and their formulations are based on the analysis. To the best of knowledge, this is the first time that multiple snapshot spaces and multiple spectral problems are used and necessary for efficient computations. Using the dominant modes from local spectral problems, multiscale basis functions are constructed to represent the solution space locally within each coarse block. These multiscale basis functions are coupled via the symmetric interior penalty discontinuous Galerkin method which provides a block diagonal mass matrix and, consequently, results in fast computations in an explicit time discretization. Our methods\\' stability and spectral convergence are rigorously analyzed. Numerical examples are presented to show our methods\\' performance. We also test oversampling strategies. In particular, we discuss how the modes from different snapshot spaces can affect the proposed methods\\' accuracy.
Towards multiscale modeling of influenza infection
Murillo, Lisa N.; Murillo, Michael S.; Alan S Perelson
2013-01-01
Aided by recent advances in computational power, algorithms, and higher fidelity data, increasingly detailed theoretical models of infection with influenza A virus are being developed. We review single scale models as they describe influenza infection from intracellular to global scales, and, in particular, we consider those models that capture details specific to influenza and can be used to link different scales. We discuss the few multiscale models of influenza infection that have been dev...
Multiscale Decomposition for Vlasov-Poisson Equations
Fedorova, A N; Fedorova, Antonina N.; Zeitlin, Michael G.
2002-01-01
We consider the applications of a numerical-analytical approach based on multiscale variational wavelet technique to the systems with collective type behaviour described by some forms of Vlasov-Poisson/Maxwell equations. We calculate the exact fast convergent representations for solutions in high-localized wavelet-like bases functions, which correspond to underlying hidden (coherent) nonlinear eigenmodes. This helps to control stability/unstability scenario of evolution in parameter space on pure algebraical level.
Wide Range Multiscale Entropy Changes through Development
Nicola R. Polizzotto; Tetsuya Takahashi; Walker, Christopher P.; Cho, Raymond Y
2015-01-01
How variability in the brain’s neurophysiologic signals evolves during development is important for a global, system-level understanding of brain maturation and its disturbance in neurodevelopmental disorders. In the current study, we use multiscale entropy (MSE), a measure that has been related to signal complexity, to investigate how this variability evolves during development across a broad range of temporal scales. We computed MSE, standard deviation (STD) and standard spectral analyses o...
MUSCLE: MUltiscale Spherical-ColLapse Evolution
Neyrinck, Mark C.
2016-05-01
MUSCLE (MUltiscale Spherical ColLapse Evolution) produces low-redshift approximate N-body realizations accurate to few-Megaparsec scales. It applies a spherical-collapse prescription on multiple Gaussian-smoothed scales. It achieves higher accuracy than perturbative schemes (Zel'dovich and second-order Lagrangian perturbation theory - 2LPT), and by including the void-in-cloud process (voids in large-scale collapsing regions), solves problems with a single-scale spherical-collapse scheme.
Engineering Digestion: Multiscale Processes of Food Digestion
Bornhorst, GM; Gouseti, O; Wickham, MSJ; Bakalis, S.
2016-01-01
Food digestion is a complex, multiscale process that has recently become of interest to the food industry due to the developing links between food and health or disease. Food digestion can be studied by using either in vitro or in vivo models, each having certain advantages or disadvantages. The recent interest in food digestion has resulted in a large number of studies in this area, yet few have provided an in-depth, quantitative description of digestion processes. To provide a framework to ...
Multiscale sequentially-coupled arterial FSI technique
Tezduyar, Tayfun E.; Takizawa, Kenji; Moorman, Creighton; Wright, Samuel; Christopher, Jason
2009-10-01
Multiscale versions of the Sequentially-Coupled Arterial Fluid-Structure Interaction (SCAFSI) technique are presented. The SCAFSI technique was introduced as an approximate FSI approach in arterial fluid mechanics. It is based on the assumption that the arterial deformation during a cardiac cycle is driven mostly by the blood pressure. First we compute a “reference” arterial deformation as a function of time, driven only by the blood pressure profile of the cardiac cycle. Then we compute a sequence of updates involving mesh motion, fluid dynamics calculations, and recomputing the arterial deformation. The SCAFSI technique was developed and tested in conjunction with the stabilized space-time FSI (SSTFSI) technique. Beyond providing a computationally more economical alternative to the fully coupled arterial FSI approach, the SCAFSI technique brings additional flexibility, such as being able to carry out the computations in a spatially or temporally multiscale fashion. In the test computations reported here for the spatially multiscale versions of the SCAFSI technique, we focus on a patient-specific middle cerebral artery segment with aneurysm, where the arterial geometry is based on computed tomography images. The arterial structure is modeled with the continuum element made of hyperelastic (Fung) material.
Engineering Digestion: Multiscale Processes of Food Digestion.
Bornhorst, Gail M; Gouseti, Ourania; Wickham, Martin S J; Bakalis, Serafim
2016-03-01
Food digestion is a complex, multiscale process that has recently become of interest to the food industry due to the developing links between food and health or disease. Food digestion can be studied by using either in vitro or in vivo models, each having certain advantages or disadvantages. The recent interest in food digestion has resulted in a large number of studies in this area, yet few have provided an in-depth, quantitative description of digestion processes. To provide a framework to develop these quantitative comparisons, a summary is given here between digestion processes and parallel unit operations in the food and chemical industry. Characterization parameters and phenomena are suggested for each step of digestion. In addition to the quantitative characterization of digestion processes, the multiscale aspect of digestion must also be considered. In both food systems and the gastrointestinal tract, multiple length scales are involved in food breakdown, mixing, absorption. These different length scales influence digestion processes independently as well as through interrelated mechanisms. To facilitate optimized development of functional food products, a multiscale, engineering approach may be taken to describe food digestion processes. A framework for this approach is described in this review, as well as examples that demonstrate the importance of process characterization as well as the multiple, interrelated length scales in the digestion process. PMID:26799793
Multiscale computation from a chemical engineering perspective
Institute of Scientific and Technical Information of China (English)
Li Jinghai
2014-01-01
This-paper-mainly-discusses-the-multiscale-computation-from-a-chemical-engineering-perspective.-From-the-application-designer’s-perspective,we-propose-a-new-approach-to-investigate-and-develop-both-flexi-ble-and-efficient-computer-architectures.-Based-on-the-requirements-of-applications-within-one-category,we-first-induce-and-extract-some-inherent-computing-patterns-or-core-computing-kernels-from-the-applications.-Some-computing-models-and-innovative-computing-architectures-will-then-be-developed-for-these-patterns-or-kernels,as-well-as-the-software-mapping-techniques.-Finally-those-applications-which-can-share-and-utilize-those-computing-patterns-or-kernels-can-be-executed-very-efficiently-on-those-novel-computing-architectures.-We-think-that-the-proposed-approach-may-not-be-achievable-within-the-existing-technology.-However,we-believe-that-it-will-be-available-in-the-near-future.-Hence,we-will-describe-this-approach-from-the-following-four-as-pects:multiscale-environment-in-the-world,-mesoscale-as-a-key-scale,-energy-minimization-multiscale-(EMMS)paradigm-and-our-perspective.
Engineering Digestion: Multiscale Processes of Food Digestion.
Bornhorst, Gail M; Gouseti, Ourania; Wickham, Martin S J; Bakalis, Serafim
2016-03-01
Food digestion is a complex, multiscale process that has recently become of interest to the food industry due to the developing links between food and health or disease. Food digestion can be studied by using either in vitro or in vivo models, each having certain advantages or disadvantages. The recent interest in food digestion has resulted in a large number of studies in this area, yet few have provided an in-depth, quantitative description of digestion processes. To provide a framework to develop these quantitative comparisons, a summary is given here between digestion processes and parallel unit operations in the food and chemical industry. Characterization parameters and phenomena are suggested for each step of digestion. In addition to the quantitative characterization of digestion processes, the multiscale aspect of digestion must also be considered. In both food systems and the gastrointestinal tract, multiple length scales are involved in food breakdown, mixing, absorption. These different length scales influence digestion processes independently as well as through interrelated mechanisms. To facilitate optimized development of functional food products, a multiscale, engineering approach may be taken to describe food digestion processes. A framework for this approach is described in this review, as well as examples that demonstrate the importance of process characterization as well as the multiple, interrelated length scales in the digestion process.
Distributed multiscale computing with MUSCLE 2, the Multiscale Coupling Library and Environment
Borgdorff, J.; Mamonski, M.; Bosak, B.; Kurowski, K.; Ben Belgacem, M.; Chopard, B.; Groen, D; Coveney, P. V.; Hoekstra, A.G.
2014-01-01
We present the Multiscale Coupling Library and Environment: MUSCLE 2. This multiscale component-based execution environment has a simple to use Java, C++, C, Python and Fortran API, compatible with MPI, OpenMP and threading codes. We demonstrate its local and distributed computing capabilities and compare its performance to MUSCLE 1, file copy, MPI, MPWide, and GridFTP. The local throughput of MPI is about two times higher, so very tightly coupled code should use MPI as a single submodel of M...
A multispectral and multiscale view of the Sun
de Wit, T Dudok
2010-01-01
The emergence of a new discipline called space weather, which aims at understanding and predicting the impact of solar activity on the terrestrial environment and on technological systems, has led to a growing need for analysing solar images in real time. The rapidly growing volume of solar images, however, makes it increasingly impractical to process them for scientific purposes. This situation has prompted the development of novel processing techniques for doing feature recognition, image tracking, knowledge extraction, etc. Here we focus on two particular concepts and list some of their applications. The first one is Blind Source Separation (BSS), which has a great potential for condensing the information that is contained in multispectral images. The second one is multiscale (multiresolution, or wavelet) analysis, which is particularly well suited for capturing scale-invariant structures in solar images. This article provides a brief overview of existing and potential applications to solar images taken in...
Critical behavior of the contact process in a multiscale network
Ferreira, Silvio C; 10.1103/PhysRevE.76.036112
2011-01-01
Inspired by dengue and yellow fever epidemics, we investigated the contact process (CP) in a multiscale network constituted by one-dimensional chains connected through a Barab\\'asi-Albert scale-free network. In addition to the CP dynamics inside the chains, the exchange of individuals between connected chains (travels) occurs at a constant rate. A finite epidemic threshold and an epidemic mean lifetime diverging exponentially in the subcritical phase, concomitantly with a power law divergence of the outbreak's duration, were found. A generalized scaling function involving both regular and SF components was proposed for the quasistationary analysis and the associated critical exponents determined, demonstrating that the CP on this hybrid network and nonvanishing travel rates establishes a new universality class.
Multi-scale correlations in different future markets
Bartolozzi, M; Di Matteo, T; Aste, T
2007-01-01
In the present work we investigate the multiscale nature of the correlations for high frequency data (1 minute) 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.
Multi-scale correlations in different futures markets
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.
Arnold, Steven M.; Murthy, Pappu L.; Bednarcyk, Brett A.; Lawson, John W.; Monk, Joshua D.; Bauschlicher, Charles W., Jr.
2016-01-01
Next generation ablative thermal protection systems are expected to consist of 3D woven composite architectures. It is well known that composites can be tailored to achieve desired mechanical and thermal properties in various directions and thus can be made fit-for-purpose if the proper combination of constituent materials and microstructures can be realized. In the present work, the first, multiscale, atomistically-informed, computational analysis of mechanical and thermal properties of a present day - Carbon/Phenolic composite Thermal Protection System (TPS) material is conducted. Model results are compared to measured in-plane and out-of-plane mechanical and thermal properties to validate the computational approach. Results indicate that given sufficient microstructural fidelity, along with lowerscale, constituent properties derived from molecular dynamics simulations, accurate composite level (effective) thermo-elastic properties can be obtained. This suggests that next generation TPS properties can be accurately estimated via atomistically informed multiscale analysis.
Cho, Changsoon; Lee, Jung-Yong
2013-03-11
An efficient light trapping scheme is a key to enhancing the power conversion efficiency (PCE) of thin-film photovoltaic (PV) cells by compensating for the insufficient light absorption. To handle optical components from nano-scale to micro-scale seamlessly, a multi-scale optical simulation is carefully designed in this study and is used to qualitatively analyze the light trapping performances of a micro lens array (MLA), a V-shaped configuration, and the newly proposed scheme, which is termed a double parabolic trapper (DPT) according to both daily and annual movement of the sun. DPT has the potential to enhance the PCE significantly, from 5.9% to 8.9%, for PCDTBT:PC(70)BM-based polymer solar cells by perfectly trapping the incident light between two parabolic PV cells.
A Novel Spectral Approach to Multi-Scale Modeling
Landi, Giacomo
2011-12-01
In this work, we present a novel approach for predicting the elastic, thermo-elastic and plastic fields in three-dimensional (3-D) voxel-based microstructure datasets subjected to uniform periodic boundary conditions. Such localization relationships (linkages) lie at the core of all multi-scale modeling frameworks and can be efficiently formulated in a Discrete Fourier Transforms (DFT) -based knowledge system. This new formalism has its theoretical roots in the statistical continuum theories developed originally by Kroner [1]. However, in the approach described by Kroner, the terms in the series were established by selecting a reference medium and numerically evaluating a complex series of nested convolution integrals. This approach is largely hampered by the principal value problem, and exhibits high sensitivity to the properties of the selected reference medium. In the present work, the same series expressions have been recast into much more computationally efficient representations using DFTs. The spectral analysis transforms the complex integral relations into relatively simple algebraic expressions involving polynomials of structure parameters and morphology-independent influence coefficients. These coefficients need to be established only once for a given material system. The main advantage of the new DFT-based framework is that it allows easy calibration of Kroner's expansions to results from finite element methods, thereby overcoming all of the main obstacles associated with the principal value problem and the need to select a reference medium. This approach can be seen as an efficient procedure for data-mining the results from computationally expensive numerical models and establishing the underlying knowledge systems at a selected length scale in multi-scale modeling problems. The set of influence coefficients described above constitutes the underlying knowledge for a given deformation and can be easily stored and recalled as and when needed in a multi-scale
Institute of Scientific and Technical Information of China (English)
马学虎; 彭本利; 兰忠; 王爱丽; 王四芳; 张崇峰; 白涛
2011-01-01
Dropwise condensation heat transfer process possesses typical multi-scale characteristics,such as the droplet size distribution on condensation surface, time sequence during droplet growth process, the physicochemical properties of condensation surfaces, and interaction effects between droplets and condensing surface. Based on the dropwise condensation heat transfer model with liquid-solid interfacial effect, multi-scale phenomenon of droplet size distribution and its effect on dropwise condensation heat transfer are analyzed in this paper, in addition, an optimal contact angle is obtained from analyzing the relationship among droplet size, contact angle and average heat transfer characteristics.%滴状冷凝传热过程具有典型的多尺度特征,一方面体现于壁面上液滴尺寸分布的空间多尺度特征以及液滴生长过程的时间多尺度分布,另一方面体现于冷凝壁面物理化学特性以及液固相互作用特性的描述和量度上的多尺度特征.本文基于包含界面效应影响的滴状冷凝传热模型,分析了液滴尺寸分布的多尺度特征及其对滴状冷凝传热性能的影响,并通过分析液滴尺寸、接触角等因素与平均冷凝传热性能的关系,进行多尺度分析规划,得到冷凝壁面传热性能最佳时的接触角.
Multiscale models in the biomechanics of plant growth
Jensen, O.E. & Fozard, J.A.
2015-01-01
Plant growth occurs through the coordinated expansion of tightly adherent cells, driven by regulated softening of cell walls. It is an intrinsically multiscale process, with the integrated properties of multiple cell walls shaping the whole tissue. Multiscale models encode physical relationships to bring new understanding to plant physiology and development.
Multiscale molecular dynamics and the reverse mapping problem
B. Ensing; S.O. Nielsen
2010-01-01
Multiscale techniques are becoming increasingly important for molecular simulation as a result of interest in increasingly complex problems involving events occurring over multiple time and length scales. Here, inspired by the success of the multiscale quantum mechanics/molecular mechanics (QM/MM) m
Transitions of the Multi-Scale Singularity Trees
DEFF Research Database (Denmark)
Somchaipeng, Kerawit; Sporring, Jon; Kreiborg, Sven;
2005-01-01
Multi-Scale Singularity Trees(MSSTs) [10] are multi-scale image descriptors aimed at representing the deep structures of images. Changes in images are directly translated to changes in the deep structures; therefore transitions in MSSTs. Because MSSTs can be used to represent the deep structure o...
Addressing the Multi-scale lapsus of landscape
Schoorl, J.M.
2002-01-01
"Addressing the Multi-scale Lapsus of Landscape" with the sub-title "Multi-scale landscape process modelling to support sustainable land use: A case study for the Lower Guadalhorce valley South Spain" focuses on the role of landscape as the main driving factor behind many geo-environm
Ryoko eOkazaki; Tetsuya eTakahashi; Kanji eUeno; Koichi eTakahashi; Makoto eIshitobi; Mitsuru eKikuchi; Masato eHigashima; Yuji eWada
2015-01-01
Autism spectrum disorders (ASD) are heterogeneous neurodevelopmental disorders that are reportedly characterized by aberrant neural networks. Recently developed multiscale entropy analysis (MSE) can characterize the complexity inherent in electroencephalography (EEG) dynamics over multiple temporal scales in the dynamics of neural networks. We encountered an 18-year-old man with ASD whose refractory catatonic obsessive–compulsive symptoms were improved dramatically after electroconvulsive the...
A multiscale modeling technique for bridging molecular dynamics with finite element method
Energy Technology Data Exchange (ETDEWEB)
Lee, Yongchang, E-mail: yl83@buffalo.edu; Basaran, Cemal
2013-11-15
In computational mechanics, molecular dynamics (MD) and finite element (FE) analysis are well developed and most popular on nanoscale and macroscale analysis, respectively. MD can very well simulate the atomistic behavior, but cannot simulate macroscale length and time due to computational limits. FE can very well simulate continuum mechanics (CM) problems, but has the limitation of the lack of atomistic level degrees of freedom. Multiscale modeling is an expedient methodology with a potential to connect different levels of modeling such as quantum mechanics, molecular dynamics, and continuum mechanics. This study proposes a new multiscale modeling technique to couple MD with FE. The proposed method relies on weighted average momentum principle. A wave propagation example has been used to illustrate the challenges in coupling MD with FE and to verify the proposed technique. Furthermore, 2-Dimensional problem has also been used to demonstrate how this method would translate into real world applications. -- Highlights: •A weighted averaging momentum method is introduced for bridging molecular dynamics (MD) with finite element (FE) method. •The proposed method shows excellent coupling results in 1-D and 2-D examples. •The proposed method successfully reduces the spurious wave reflection at the border of MD and FE regions. •Big advantages of the proposed method are simplicity and inexpensive computational cost of multiscale analysis.
Efficient algorithms for multiscale modeling in porous media
Wheeler, Mary F.
2010-09-26
We describe multiscale mortar mixed finite element discretizations for second-order elliptic and nonlinear parabolic equations modeling Darcy flow in porous media. The continuity of flux is imposed via a mortar finite element space on a coarse grid scale, while the equations in the coarse elements (or subdomains) are discretized on a fine grid scale. We discuss the construction of multiscale mortar basis and extend this concept to nonlinear interface operators. We present a multiscale preconditioning strategy to minimize the computational cost associated with construction of the multiscale mortar basis. We also discuss the use of appropriate quadrature rules and approximation spaces to reduce the saddle point system to a cell-centered pressure scheme. In particular, we focus on multiscale mortar multipoint flux approximation method for general hexahedral grids and full tensor permeabilities. Numerical results are presented to verify the accuracy and efficiency of these approaches. © 2010 John Wiley & Sons, Ltd.
A Concurrent Multiscale Micromorphic Molecular Dynamics. Part I. Theoretical Formulation
Li, Shaofan
2014-01-01
Based on a novel concept of multiplicative multiscale decomposition, we have derived a multiscale micromorphic molecular dynamics (MMMD)to extent the (Andersen)-Parrinello-Rahman molecular dynamics to mesoscale and macroscale. The multiscale micromorphic molecular dynamics is a con-current three-scale particle dynamics that couples a fine scale molecular dynamics, a mesoscale particle dynamics of micromorphic medium, and a coarse scale nonlocal particle dynamics of nonlinear continuum. By choosing proper statistical closure conditions, we have shown that the original Andersen-Parrinello-Rahman molecular dynamics can be rigorously formulated and justified from first principle, and it is a special case of the proposed multiscale micromorphic molecular dynamics. The discovered mutiscale structure and the corresponding multiscale dynamics reveal a seamless transition channel from atomistic scale to continuum scale and the intrinsic coupling relation among them, and it can be used to solve finite size nanoscale sc...
Particle methods for multi-scale simulation of complex flows
Institute of Scientific and Technical Information of China (English)
GE Wei; MA Jingsen; ZHANG Jiayuan; TANG Dexiang; CHEN Feiguo; WANG Xiaowei; GUO Li; LI Jinghai
2005-01-01
The multi-scale structures of complex flows have been great challenges to both theoretical and engineering researches, and multi-scale modeling is the natural way in response. Particle methods (PMs) are ideal constitutors and powerful probes of multi-scale models, owing to their physical insight and computational simplicity. In this paper, the role of different PMs for multi-scale modeling of complex flows is critically reviewed and possible development of PMs in this background is prospected, with the emphasis on pseudo-particle modeling (PPM). The performances of some different PMs are compared in simulations and new development in the fundamentals and applications of PPM is also reported, demonstrating PPM as a unique PM for multi-scale modeling.
A Coupled Multiscale Model of Texture Evolution and Plastic Anisotropy
Gawad, J.; Van Bael, A.; Yerra, S. K.; Samaey, G.; Van Houtte, P.; Roose, D.
2010-06-01
In this paper we present a multiscale model of a plastic deformation process in which the anisotropy of plastic properties is related to the evolution of the crystallographic texture. The model spans several length scales from the macroscopic deformation of the workpiece to the microscale interactions between individual grains in a polycrystalline material. The macroscopic behaviour of the material is described by means of a Finite Element (FE) model. Plastic anisotropy is taken into account in a constitutive law, based on the concept of a plastic potential in strain rate space. The coefficients of a sixth-order Facet equation are determined using the Taylor theory, provided that the current crystallographic texture at a given FE integration point is known. Texture evolution in the FE integration points is predicted by an ALAMEL micromechanical model. Mutual interactions between coarse and fine scale are inherent in the physics of the deformation process. These dependencies are taken into account by full bidirectional coupling in the model. Therefore, the plastic deformation influences the crystallographic texture and the evolution of the texture induces anisotropy of the macroscopic deformation. The presented approach enables an adaptive texture and yield surface update scheme with respect to the local plastic deformation in the FE integration points. Additionally, the computational cost related to the updates of the constitutive law is reduced by application of parallel computing techniques. Suitability of on-demand computing for this computational problem is discussed. The parallelisation strategy addresses both distributed memory and shared memory architectures. The cup drawing process has been simulated using the multiscale model outlined above. The discussion of results includes the analysis of the planar anisotropy in the cup and the influence of complex deformation path on texture development. Evolution of texture at selected material points is assessed as
Digital marbling: a multiscale fluid model.
Acar, Rüyam; Boulanger, Pierre
2006-01-01
This paper presents a multiscale fluid model based on mesoscale dynamics and viscous fluid equations as a generic tool for digital marbling purposes. The model uses an averaging technique on the adaptation of a stochastic mesoscale model to obtain the effect of fluctuations at different levels. It allows various user controls to simulate complex flow behaviors as in traditional marbling techniques, as well as laminar and turbulent flows. Material transport is based on an improved advection solution to be able to match the highly detailed, sharp fluid interfaces in marbling patterns. In the transport model, two reaction models are introduced to create different effects and to simulate density fluctuations. PMID:16805267
Structure and multiscale mechanics of carbon nanomaterials
2016-01-01
This book aims at providing a broad overview on the relationship between structure and mechanical properties of carbon nanomaterials from world-leading scientists in the field. The main aim is to get an in-depth understanding of the broad range of mechanical properties of carbon materials based on their unique nanostructure and on defects of several types and at different length scales. Besides experimental work mainly based on the use of (in-situ) Raman and X-ray scattering and on nanoindentation, the book also covers some aspects of multiscale modeling of the mechanics of carbon nanomaterials.
Learning Entropy: Multiscale Measure for Incremental Learning
Ivo Bukovsky
2013-01-01
First, this paper recalls a recently introduced method of adaptive monitoring of dynamical systems and presents the most recent extension with a multiscale-enhanced approach. Then, it is shown that this concept of real-time data monitoring establishes a novel non-Shannon and non-probabilistic concept of novelty quantification, i.e., Entropy of Learning, or in short the Learning Entropy. This novel cognitive measure can be used for evaluation of each newly measured sample of data, or even of w...
Computational design and multiscale modeling of a nanoactuator using DNA actuation
International Nuclear Information System (INIS)
Developments in the field of nano-biodevices coupling nanostructures and biological components are of great interest in medical nanorobotics. As the fundamentals of bio/non-bio interaction processes are still poorly understood in the design of these devices, design tools and multiscale dynamics modeling approaches are necessary at the fabrication pre-project stage. This paper proposes a new concept of optimized carbon nanotube based servomotor design for drug delivery and biomolecular transport applications. The design of an encapsulated DNA-multi-walled carbon nanotube actuator is prototyped using multiscale modeling. The system is parametrized by using a quantum level approach and characterized by using a molecular dynamics simulation. Based on the analysis of the simulation results, a servo nanoactuator using ionic current feedback is simulated and analyzed for application as a drug delivery carrier.
Adaptive time splitting method for multi-scale evolutionary partial differential equations
Descombes, Stéphane; Dumont, Thierry; Louvet, Violaine; Massot, Marc
2011-01-01
This paper introduces an adaptive time splitting technique for the solution of stiff evolutionary PDEs that guarantees an effective error control of the simulation, independent of the fastest physical time scale for highly unsteady problems. The strategy considers a second order Strang method and another lower order embedded splitting scheme that takes into account potential loss of order due to the stiffness featured by time-space multi-scale phenomena. The scheme is then built upon a precise numerical analysis of the method and a complementary numerical procedure, conceived to overcome classical restrictions of adaptive time stepping schemes based on lower order embedded methods, whenever asymptotic estimates fail to predict the dynamics of the problem. The performance of the method in terms of control of integration errors is evaluated by numerical simulations of stiff propagating waves coming from nonlinear chemical dynamics models as well as highly multi-scale nanosecond repetitively pulsed gas discharge...
Directory of Open Access Journals (Sweden)
Liyun Su
2011-01-01
Full Text Available In order to suppress the interference of the strong fractional noise signal in discrete-time ultrawideband (UWB systems, this paper presents a new UWB multi-scale Kalman filter (KF algorithm for the interference suppression. This approach solves the problem of the narrowband interference (NBI as nonstationary fractional signal in UWB communication, which does not need to estimate any channel parameter. In this paper, the received sampled signal is transformed through multiscale wavelet to obtain a state transition equation and an observation equation based on the stationarity theory of wavelet coefficients in time domain. Then through the Kalman filter method, fractional signal of arbitrary scale is easily figured out. Finally, fractional noise interference is subtracted from the received signal. Performance analysis and computer simulations reveal that this algorithm is effective to reduce the strong fractional noise when the sampling rate is low.
Rolling Element Bearing Fault Diagnosis Based on Multiscale General Fractal Features
Directory of Open Access Journals (Sweden)
Weigang Wen
2015-01-01
Full Text Available Nonlinear characteristics are ubiquitous in the vibration signals produced by rolling element bearings. Fractal dimensions are effective tools to illustrate nonlinearity. This paper proposes a new approach based on Multiscale General Fractal Dimensions (MGFDs to realize fault diagnosis of rolling element bearings, which are robust to the effects of variation in operating conditions. The vibration signals of bearing are analyzed to extract the general fractal dimensions in multiscales, which are in turn utilized to construct a feature space to identify fault pattern. Finally, bearing faults are revealed by pattern recognition. Case studies are carried out to evaluate the validity and accuracy of the approach. It is verified that this approach is effective for fault diagnosis of rolling element bearings under various operating conditions via experiment and data analysis.
Multiscale Stochastic Simulation and Modeling
Energy Technology Data Exchange (ETDEWEB)
James Glimm; Xiaolin Li
2006-01-10
Acceleration driven instabilities of fluid mixing layers include the classical cases of Rayleigh-Taylor instability, driven by a steady acceleration and Richtmyer-Meshkov instability, driven by an impulsive acceleration. Our program starts with high resolution methods of numerical simulation of two (or more) distinct fluids, continues with analytic analysis of these solutions, and the derivation of averaged equations. A striking achievement has been the systematic agreement we obtained between simulation and experiment by using a high resolution numerical method and improved physical modeling, with surface tension. Our study is accompanies by analysis using stochastic modeling and averaged equations for the multiphase problem. We have quantified the error and uncertainty using statistical modeling methods.
Multiscale measurement error models for aggregated small area health data.
Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin
2016-08-01
Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates.
Multiscale measurement error models for aggregated small area health data.
Aregay, Mehreteab; Lawson, Andrew B; Faes, Christel; Kirby, Russell S; Carroll, Rachel; Watjou, Kevin
2016-08-01
Spatial data are often aggregated from a finer (smaller) to a coarser (larger) geographical level. The process of data aggregation induces a scaling effect which smoothes the variation in the data. To address the scaling problem, multiscale models that link the convolution models at different scale levels via the shared random effect have been proposed. One of the main goals in aggregated health data is to investigate the relationship between predictors and an outcome at different geographical levels. In this paper, we extend multiscale models to examine whether a predictor effect at a finer level hold true at a coarser level. To adjust for predictor uncertainty due to aggregation, we applied measurement error models in the framework of multiscale approach. To assess the benefit of using multiscale measurement error models, we compare the performance of multiscale models with and without measurement error in both real and simulated data. We found that ignoring the measurement error in multiscale models underestimates the regression coefficient, while it overestimates the variance of the spatially structured random effect. On the other hand, accounting for the measurement error in multiscale models provides a better model fit and unbiased parameter estimates. PMID:27566773
Identify Precipitation Pattern Using Multi-scale Sample Entropy
Liang, X.; Zhou, X.; Lin, J. S.; Xu, W.
2015-12-01
In an effort to seek new perspectives on identifying precipitation patterns associated with the precipitation time series, this study explored the potential use of the information metrics through Multi-scale Sample Entropy (MSE) analysis. The objectives were to develop MSE analysis in investigating if discernable changes in long term patterns could be identified when the information metrics in the data were studied in terms of how they change with scales. Scales, in the present context, are the intervals of days that sample entropy (SE) is sampled within a time series. For this study we looked into the characteristics of precipitation before and after 1980 for the regions upstream of Yangtze River in southwestern China, based on the daily rain-gauge data collected from 70 gauges since 1951. The results suggest three main patterns of SE with scale, they are: significant decrease, relatively flat and significant increase. These three patterns correspond, respectively, to the downstream, midstream and upstream of the upper Yangtze River region. By the nature of entropy, a significant decrease in SE implies more regularity with scale, which could mean a longer continuous drought or a more evenly distributed continuous precipitation. In this case, our analysis shows that it is attributed to the longer continuous drought. For the case of significant SE increase, it was found to be tied to an increase in the rain frequency. These results appear to show that the MSE analysis could indeed be useful for long term precipitation study.
A Multiscale Model for Virus Capsid Dynamics
Directory of Open Access Journals (Sweden)
Changjun Chen
2010-01-01
Full Text Available Viruses are infectious agents that can cause epidemics and pandemics. The understanding of virus formation, evolution, stability, and interaction with host cells is of great importance to the scientific community and public health. Typically, a virus complex in association with its aquatic environment poses a fabulous challenge to theoretical description and prediction. In this work, we propose a differential geometry-based multiscale paradigm to model complex biomolecule systems. In our approach, the differential geometry theory of surfaces and geometric measure theory are employed as a natural means to couple the macroscopic continuum domain of the fluid mechanical description of the aquatic environment from the microscopic discrete domain of the atomistic description of the biomolecule. A multiscale action functional is constructed as a unified framework to derive the governing equations for the dynamics of different scales. We show that the classical Navier-Stokes equation for the fluid dynamics and Newton's equation for the molecular dynamics can be derived from the least action principle. These equations are coupled through the continuum-discrete interface whose dynamics is governed by potential driven geometric flows.
Institute for Multiscale Modeling of Biological Interactions
Energy Technology Data Exchange (ETDEWEB)
Paulaitis, Michael E; Garcia-Moreno, Bertrand; Lenhoff, Abraham
2009-12-26
The Institute for Multiscale Modeling of Biological Interactions (IMMBI) has two primary goals: Foster interdisciplinary collaborations among faculty and their research laboratories that will lead to novel applications of multiscale simulation and modeling methods in the biological sciences and engineering; and Building on the unique biophysical/biology-based engineering foundations of the participating faculty, train scientists and engineers to apply computational methods that collectively span multiple time and length scales of biological organization. The success of IMMBI will be defined by the following: Size and quality of the applicant pool for pre-doctoral and post-doctoral fellows; Academic performance; Quality of the pre-doctoral and post-doctoral research; Impact of the research broadly and to the DOE (ASCR program) mission; Distinction of the next career step for pre-doctoral and post-doctoral fellows; and Faculty collaborations that result from IMMBI activities. Specific details about accomplishments during the three years of DOE support for IMMBI have been documented in Annual Progress Reports (April 2005, June 2006, and March 2007) and a Report for a National Academy of Sciences Review (October 2005) that were submitted to DOE on the dates indicated. An overview of these accomplishments is provided.
Multiscale Modeling of Phase Transformations in Steels
Militzer, M.; Hoyt, J. J.; Provatas, N.; Rottler, J.; Sinclair, C. W.; Zurob, H. S.
2014-05-01
Multiscale modeling tools have great potential to aid the development of new steels and processing routes. Currently, industrial process models are at least in part based on empirical material parameters to describe microstructure evolution and the resulting material properties. Modeling across different length and time scales is a promising approach to develop next-generation process models with enhanced predictive capabilities for the role of alloying elements. The status and challenges of this multiscale modeling approach are discussed for microstructure evolution in advanced low-carbon steels. First-principle simulations of solute segregation to a grain boundary and an austenite-ferrite interface in iron confirm trends of important alloying elements (e.g., Nb, Mo, and Mn) on grain growth, recrystallization, and phase transformation in steels. In particular, the linkage among atomistic simulations, phase-field modeling, and classic diffusion models is illustrated for the effects of solute drag on the austenite-to-ferrite transformation as observed in dedicated experimental studies for iron model alloys and commercial steels.
Multi-scale gravity and cosmology
Calcagni, Gianluca
2013-12-01
The gravitational dynamics and cosmological implications of three classes of recently introduced multi-scale spacetimes (with, respectively, ordinary, weighted and q-derivatives) are discussed. These spacetimes are non-Riemannian: the metric structure is accompanied by an independent measure-differential structure with the characteristics of a multi-fractal, namely, different dimensionality at different scales and, at ultra-short distances, a discrete symmetry known as discrete scale invariance. Under this minimal paradigm, five general features arise: (a) the big-bang singularity can be replaced by a finite bounce, (b) the cosmological constant problem is reinterpreted, since accelerating phases can be mimicked by the change of geometry with the time scale, without invoking a slowly rolling scalar field, (c) the discreteness of geometry at Planckian scales can leave an observable imprint of logarithmic oscillations in cosmological spectra and (d) give rise to an alternative mechanism to inflation or (e) to a fully analytic model of cyclic mild inflation, where near scale invariance of the perturbation spectrum can be produced without strong acceleration. Various properties of the models and exact dynamical solutions are discussed. In particular, the multi-scale geometry with weighted derivatives is shown to be a Weyl integrable spacetime.
Concurrent multiscale modeling of amorphous materials
Tan, Vincent
2013-03-01
An approach to multiscale modeling of amorphous materials is presented whereby atomistic scale domains coexist with continuum-like domains. The atomistic domains faithfully predict severe deformation while the continuum domains allow the computation to scale up the size of the model without incurring excessive computational costs associated with fully atomistic models and without the introduction of spurious forces across the boundary of atomistic and continuum-like domains. The material domain is firstly constructed as a tessellation of Amorphous Cells (AC). For regions of small deformation, the number of degrees of freedom is then reduced by computing the displacements of only the vertices of the ACs instead of the atoms within. This is achieved by determining, a priori, the atomistic displacements within such Pseudo Amorphous Cells associated with orthogonal deformation modes of the cell. Simulations of nanoscale polymer tribology using full molecular mechanics computation and our multiscale approach give almost identical prediction of indentation force and the strain contours of the polymer. We further demonstrate the capability of performing adaptive simulations during which domains that were discretized into cells revert to full atomistic domains when their strain attain a predetermined threshold. The authors would like to acknowledge the financial support given to this study by the Agency of Science, Technology and Research (ASTAR), Singapore (SERC Grant No. 092 137 0013).
Bayesian Integration of multiscale environmental data
Energy Technology Data Exchange (ETDEWEB)
2016-08-22
The software is designed for efficiently integrating large-size of multi-scale environmental data using the Bayesian framework. Suppose we need to estimate the spatial distribution of variable X with high spatial resolution. The available data include (1) direct measurements Z of the unknowns with high resolution in a subset of the spatial domain (small spatial coverage), (2) measurements C of the unknowns at the median scale, and (3) measurements A of the unknowns at the coarsest scale but with large spatial coverage. The goal is to estimate the unknowns at the fine grids by conditioning to all the available data. We first consider all the unknowns as random variables and estimate conditional probability distribution of those variables by conditioning to the limited high-resolution observations (Z). We then treat the estimated probability distribution as the prior distribution. Within the Bayesian framework, we combine the median and large-scale measurements (C and A) through likelihood functions. Since we assume that all the relevant multivariate distributions are Gaussian, the resulting posterior distribution is a multivariate Gaussian distribution. The developed software provides numerical solutions of the posterior probability distribution. The software can be extended in several different ways to solve more general multi-scale data integration problems.
Algebraic Multiscale Solver for Elastic Geomechanical Deformation
Castelletto, N.; Hajibeygi, H.; Tchelepi, H.
2015-12-01
Predicting the geomechanical response of geological formations to thermal, pressure, and mechanical loading is important in many engineering applications. The mathematical formulation that describes deformation of a reservoir coupled with flow and transport entails heterogeneous coefficients with a wide range of length scales. Such detailed heterogeneous descriptions of reservoir properties impose severe computational challenges for the study of realistic-scale (km) reservoirs. To deal with these challenges, we developed an Algebraic Multiscale Solver for ELastic geomechanical deformation (EL-AMS). Constructed on finite element fine-scale system, EL-AMS imposes a coarse-scale grid, which is a non-overlapping decomposition of the domain. Then, local (coarse) basis functions for the displacement vector are introduced. These basis functions honor the elastic properties of the local domains subject to the imposed local boundary conditions. The basis form the Restriction and Prolongation operators. These operators allow for the construction of accurate coarse-scale systems for the displacement. While the multiscale system is efficient for resolving low-frequency errors, coupling it with a fine-scale smoother, e.g., ILU(0), leads to an efficient iterative solver. Numerical results for several test cases illustrate that EL-AMS is quite efficient and applicable to simulate elastic deformation of large-scale heterogeneous reservoirs.
Residual-driven online generalized multiscale finite element methods
Chung, Eric T.
2015-09-08
The construction of local reduced-order models via multiscale basis functions has been an area of active research. In this paper, we propose online multiscale basis functions which are constructed using the offline space and the current residual. Online multiscale basis functions are constructed adaptively in some selected regions based on our error indicators. We derive an error estimator which shows that one needs to have an offline space with certain properties to guarantee that additional online multiscale basis function will decrease the error. This error decrease is independent of physical parameters, such as the contrast and multiple scales in the problem. The offline spaces are constructed using Generalized Multiscale Finite Element Methods (GMsFEM). We show that if one chooses a sufficient number of offline basis functions, one can guarantee that additional online multiscale basis functions will reduce the error independent of contrast. We note that the construction of online basis functions is motivated by the fact that the offline space construction does not take into account distant effects. Using the residual information, we can incorporate the distant information provided the offline approximation satisfies certain properties. In the paper, theoretical and numerical results are presented. Our numerical results show that if the offline space is sufficiently large (in terms of the dimension) such that the coarse space contains all multiscale spectral basis functions that correspond to small eigenvalues, then the error reduction by adding online multiscale basis function is independent of the contrast. We discuss various ways computing online multiscale basis functions which include a use of small dimensional offline spaces.
Improvement and Extension of Shape Evaluation Criteria in Multi-Scale Image Segmentation
Sakamoto, M.; Honda, Y.; Kondo, A.
2016-06-01
From the last decade, the multi-scale image segmentation is getting a particular interest and practically being used for object-based image analysis. In this study, we have addressed the issues on multi-scale image segmentation, especially, in improving the performances for validity of merging and variety of derived region's shape. Firstly, we have introduced constraints on the application of spectral criterion which could suppress excessive merging between dissimilar regions. Secondly, we have extended the evaluation for smoothness criterion by modifying the definition on the extent of the object, which was brought for controlling the shape's diversity. Thirdly, we have developed new shape criterion called aspect ratio. This criterion helps to improve the reproducibility on the shape of object to be matched to the actual objectives of interest. This criterion provides constraint on the aspect ratio in the bounding box of object by keeping properties controlled with conventional shape criteria. These improvements and extensions lead to more accurate, flexible, and diverse segmentation results according to the shape characteristics of the target of interest. Furthermore, we also investigated a technique for quantitative and automatic parameterization in multi-scale image segmentation. This approach is achieved by comparing segmentation result with training area specified in advance by considering the maximization of the average area in derived objects or satisfying the evaluation index called F-measure. Thus, it has been possible to automate the parameterization that suited the objectives especially in the view point of shape's reproducibility.
Control of Thermo-Acoustics Instabilities: The Multi-Scale Extended Kalman Approach
Le, Dzu K.; DeLaat, John C.; Chang, Clarence T.
2003-01-01
"Multi-Scale Extended Kalman" (MSEK) is a novel model-based control approach recently found to be effective for suppressing combustion instabilities in gas turbines. A control law formulated in this approach for fuel modulation demonstrated steady suppression of a high-frequency combustion instability (less than 500Hz) in a liquid-fuel combustion test rig under engine-realistic conditions. To make-up for severe transport-delays on control effect, the MSEK controller combines a wavelet -like Multi-Scale analysis and an Extended Kalman Observer to predict the thermo-acoustic states of combustion pressure perturbations. The commanded fuel modulation is composed of a damper action based on the predicted states, and a tones suppression action based on the Multi-Scale estimation of thermal excitations and other transient disturbances. The controller performs automatic adjustments of the gain and phase of these actions to minimize the Time-Scale Averaged Variances of the pressures inside the combustion zone and upstream of the injector. The successful demonstration of Active Combustion Control with this MSEK controller completed an important NASA milestone for the current research in advanced combustion technologies.
Developing a multiscale, multi-resolution agent-based brain tumor model by graphics processing units
Directory of Open Access Journals (Sweden)
Zhang Le
2011-12-01
Full Text Available Abstract Multiscale agent-based modeling (MABM has been widely used to simulate Glioblastoma Multiforme (GBM and its progression. At the intracellular level, the MABM approach employs a system of ordinary differential equations to describe quantitatively specific intracellular molecular pathways that determine phenotypic switches among cells (e.g. from migration to proliferation and vice versa. At the intercellular level, MABM describes cell-cell interactions by a discrete module. At the tissue level, partial differential equations are employed to model the diffusion of chemoattractants, which are the input factors of the intracellular molecular pathway. Moreover, multiscale analysis makes it possible to explore the molecules that play important roles in determining the cellular phenotypic switches that in turn drive the whole GBM expansion. However, owing to limited computational resources, MABM is currently a theoretical biological model that uses relatively coarse grids to simulate a few cancer cells in a small slice of brain cancer tissue. In order to improve this theoretical model to simulate and predict actual GBM cancer progression in real time, a graphics processing unit (GPU-based parallel computing algorithm was developed and combined with the multi-resolution design to speed up the MABM. The simulated results demonstrated that the GPU-based, multi-resolution and multiscale approach can accelerate the previous MABM around 30-fold with relatively fine grids in a large extracellular matrix. Therefore, the new model has great potential for simulating and predicting real-time GBM progression, if real experimental data are incorporated.
Multiscale Enaction Model (MEM): the case of complexity and “context-sensitivity” in vision
Laurent, Éric
2014-01-01
I review the data on human visual perception that reveal the critical role played by non-visual contextual factors influencing visual activity. The global perspective that progressively emerges reveals that vision is sensitive to multiple couplings with other systems whose nature and levels of abstraction in science are highly variable. Contrary to some views where vision is immersed in modular hard-wired modules, rather independent from higher-level or other non-cognitive processes, converging data gathered in this article suggest that visual perception can be theorized in the larger context of biological, physical, and social systems with which it is coupled, and through which it is enacted. Therefore, any attempt to model complexity and multiscale couplings, or to develop a complex synthesis in the fields of mind, brain, and behavior, shall involve a systematic empirical study of both connectedness between systems or subsystems, and the embodied, multiscale and flexible teleology of subsystems. The conceptual model (Multiscale Enaction Model [MEM]) that is introduced in this paper finally relates empirical evidence gathered from psychology to biocomputational data concerning the human brain. Both psychological and biocomputational descriptions of MEM are proposed in order to help fill in the gap between scales of scientific analysis and to provide an account for both the autopoiesis-driven search for information, and emerging perception. PMID:25566115