NASA Astrophysics Data System (ADS)
Qian, Xi-Yuan; Liu, Ya-Min; Jiang, Zhi-Qiang; Podobnik, Boris; Zhou, Wei-Xing; Stanley, H. Eugene
2015-06-01
When common factors strongly influence two power-law cross-correlated time series recorded in complex natural or social systems, using detrended cross-correlation analysis (DCCA) without considering these common factors will bias the results. We use detrended partial cross-correlation analysis (DPXA) to uncover the intrinsic power-law cross correlations between two simultaneously recorded time series in the presence of nonstationarity after removing the effects of other time series acting as common forces. The DPXA method is a generalization of the detrended cross-correlation analysis that takes into account partial correlation analysis. We demonstrate the method by using bivariate fractional Brownian motions contaminated with a fractional Brownian motion. We find that the DPXA is able to recover the analytical cross Hurst indices, and thus the multiscale DPXA coefficients are a viable alternative to the conventional cross-correlation coefficient. We demonstrate the advantage of the DPXA coefficients over the DCCA coefficients by analyzing contaminated bivariate fractional Brownian motions. We calculate the DPXA coefficients and use them to extract the intrinsic cross correlation between crude oil and gold futures by taking into consideration the impact of the U.S. dollar index. We develop the multifractal DPXA (MF-DPXA) method in order to generalize the DPXA method and investigate multifractal time series. We analyze multifractal binomial measures masked with strong white noises and find that the MF-DPXA method quantifies the hidden multifractal nature while the multifractal DCCA method fails.
NASA Astrophysics Data System (ADS)
Xie, Wen-Jie; Jiang, Zhi-Qiang; Gu, Gao-Feng; Xiong, Xiong; Zhou, Wei-Xing
2015-10-01
Many complex systems generate multifractal time series which are long-range cross-correlated. Numerous methods have been proposed to characterize the multifractal nature of these long-range cross correlations. However, several important issues about these methods are not well understood and most methods consider only one moment order. We study the joint multifractal analysis based on partition function with two moment orders, which was initially invented to investigate fluid fields, and derive analytically several important properties. We apply the method numerically to binomial measures with multifractal cross correlations and bivariate fractional Brownian motions without multifractal cross correlations. For binomial multifractal measures, the explicit expressions of mass function, singularity strength and multifractal spectrum of the cross correlations are derived, which agree excellently with the numerical results. We also apply the method to stock market indexes and unveil intriguing multifractality in the cross correlations of index volatilities.
Multiscale Detrended Cross-Correlation Analysis of STOCK Markets
NASA Astrophysics Data System (ADS)
Yin, Yi; Shang, Pengjian
2014-06-01
In this paper, we employ the detrended cross-correlation analysis (DCCA) to investigate the cross-correlations between different stock markets. We report the results of cross-correlated behaviors in US, Chinese and European stock markets in period 1997-2012 by using DCCA method. The DCCA shows the cross-correlated behaviors of intra-regional and inter-regional stock markets in the short and long term which display the similarities and differences of cross-correlated behaviors simply and roughly and the persistence of cross-correlated behaviors of fluctuations. Then, because of the limitation and inapplicability of DCCA method, we propose multiscale detrended cross-correlation analysis (MSDCCA) method to avoid "a priori" selecting the ranges of scales over which two coefficients of the classical DCCA method are identified, and employ MSDCCA to reanalyze these cross-correlations to exhibit some important details such as the existence and position of minimum, maximum and bimodal distribution which are lost if the scale structure is described by two coefficients only and essential differences and similarities in the scale structures of cross-correlation of intra-regional and inter-regional markets. More statistical characteristics of cross-correlation obtained by MSDCCA method help us to understand how two different stock markets influence each other and to analyze the influence from thus two inter-regional markets on the cross-correlation in detail, thus we get a richer and more detailed knowledge of the complex evolutions of dynamics of the cross-correlations between stock markets. The application of MSDCCA is important to promote our understanding of the internal mechanisms and structures of financial markets and helps to forecast the stock indices based on our current results demonstrated the cross-correlations between stock indices. We also discuss the MSDCCA methods of secant rolling window with different sizes and, lastly, provide some relevant implications and issue.
Multifractal Cross Wavelet Analysis
NASA Astrophysics Data System (ADS)
Jiang, Zhi-Qiang; Gao, Xing-Lu; Zhou, Wei-Xing; Stanley, H. Eugene
Complex systems are composed of mutually interacting components and the output values of these components usually exhibit long-range cross-correlations. Using wavelet analysis, we propose a method of characterizing the joint multifractal nature of these long-range cross correlations, a method we call multifractal cross wavelet analysis (MFXWT). We assess the performance of the MFXWT method by performing extensive numerical experiments on the dual binomial measures with multifractal cross correlations and the bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. For binomial multifractal measures, we find the empirical joint multifractality of MFXWT to be in approximate agreement with the theoretical formula. For bFBMs, MFXWT may provide spurious multifractality because of the wide spanning range of the multifractal spectrum. We also apply the MFXWT method to stock market indices, and in pairs of index returns and volatilities we find an intriguing joint multifractal behavior. The tests on surrogate series also reveal that the cross correlation behavior, particularly the cross correlation with zero lag, is the main origin of cross multifractality.
Multifractal detrended cross-correlation analysis for two nonstationary signals.
Zhou, Wei-Xing
2008-06-01
We propose a method called multifractal detrended cross-correlation analysis to investigate the multifractal behaviors in the power-law cross-correlations between two time series or higher-dimensional quantities recorded simultaneously, which can be applied to diverse complex systems such as turbulence, finance, ecology, physiology, geophysics, and so on. The method is validated with cross-correlated one- and two-dimensional binomial measures and multifractal random walks. As an example, we illustrate the method by analyzing two financial time series.
Scaling analysis of stock markets
NASA Astrophysics Data System (ADS)
Bu, Luping; Shang, Pengjian
2014-06-01
In this paper, we apply the detrended fluctuation analysis (DFA), local scaling detrended fluctuation analysis (LSDFA), and detrended cross-correlation analysis (DCCA) to investigate correlations of several stock markets. DFA method is for the detection of long-range correlations used in time series. LSDFA method is to show more local properties by using local scale exponents. DCCA method is a developed method to quantify the cross-correlation of two non-stationary time series. We report the results of auto-correlation and cross-correlation behaviors in three western countries and three Chinese stock markets in periods 2004-2006 (before the global financial crisis), 2007-2009 (during the global financial crisis), and 2010-2012 (after the global financial crisis) by using DFA, LSDFA, and DCCA method. The findings are that correlations of stocks are influenced by the economic systems of different countries and the financial crisis. The results indicate that there are stronger auto-correlations in Chinese stocks than western stocks in any period and stronger auto-correlations after the global financial crisis for every stock except Shen Cheng; The LSDFA shows more comprehensive and detailed features than traditional DFA method and the integration of China and the world in economy after the global financial crisis; When it turns to cross-correlations, it shows different properties for six stock markets, while for three Chinese stocks, it reaches the weakest cross-correlations during the global financial crisis.
A New Methodology of Spatial Cross-Correlation Analysis
Chen, Yanguang
2015-01-01
Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120
A new methodology of spatial cross-correlation analysis.
Chen, Yanguang
2015-01-01
Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran's index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.
The cross-correlation analysis of multi property of stock markets based on MM-DFA
NASA Astrophysics Data System (ADS)
Yang, Yujun; Li, Jianping; Yang, Yimei
2017-09-01
In this paper, we propose a new method called DH-MXA based on distribution histograms of Hurst surface and multiscale multifractal detrended fluctuation analysis. The method allows us to investigate the cross-correlation characteristics among multiple properties of different stock time series. It may provide a new way of measuring the nonlinearity of several signals. It also can provide a more stable and faithful description of cross-correlation of multiple properties of stocks. The DH-MXA helps us to present much richer information than multifractal detrented cross-correlation analysis and allows us to assess many universal and subtle cross-correlation characteristics of stock markets. We show DH-MXA by selecting four artificial data sets and five properties of four stock time series from different countries. The results show that our proposed method can be adapted to investigate the cross-correlation of stock markets. In general, the American stock markets are more mature and less volatile than the Chinese stock markets.
Joint multifractal analysis based on wavelet leaders
NASA Astrophysics Data System (ADS)
Jiang, Zhi-Qiang; Yang, Yan-Hong; Wang, Gang-Jin; Zhou, Wei-Xing
2017-12-01
Mutually interacting components form complex systems and these components usually have long-range cross-correlated outputs. Using wavelet leaders, we propose a method for characterizing the joint multifractal nature of these long-range cross correlations; we call this method joint multifractal analysis based on wavelet leaders (MF-X-WL). We test the validity of the MF-X-WL method by performing extensive numerical experiments on dual binomial measures with multifractal cross correlations and bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. Both experiments indicate that MF-X-WL is capable of detecting cross correlations in synthetic data with acceptable estimating errors. We also apply the MF-X-WL method to pairs of series from financial markets (returns and volatilities) and online worlds (online numbers of different genders and different societies) and determine intriguing joint multifractal behavior.
(abstract) Cross with Your Spectra? Cross-Correlate Instead!
NASA Technical Reports Server (NTRS)
Beer, Reinhard
1994-01-01
The use of cross-correlation for certain types of spectral analysis is discussed. Under certain circumstances, the use of cross-correlation between a real spectrum and either a model or another spectrum can provide a very powerful tool for spectral analysis. The method (and its limitations) will be described with concrete examples using ATMOS data.
Multifractal detrended cross-correlation analysis in the MENA area
NASA Astrophysics Data System (ADS)
El Alaoui, Marwane; Benbachir, Saâd
2013-12-01
In this paper, we investigated multifractal cross-correlations qualitatively and quantitatively using a cross-correlation test and the Multifractal detrended cross-correlation analysis method (MF-DCCA) for markets in the MENA area. We used cross-correlation coefficients to measure the level of this correlation. The analysis concerns four stock market indices of Morocco, Tunisia, Egypt and Jordan. The countries chosen are signatory of the Agadir agreement concerning the establishment of a free trade area comprising Arab Mediterranean countries. We computed the bivariate generalized Hurst exponent, Rényi exponent and spectrum of singularity for each pair of indices to measure quantitatively the cross-correlations. By analyzing the results, we found the existence of multifractal cross-correlations between all of these markets. We compared the spectrum width of these indices; we also found which pair of indices has a strong multifractal cross-correlation.
NASA Astrophysics Data System (ADS)
Wang, Fang; Liao, Gui-ping; Li, Jian-hui; Zou, Rui-biao; Shi, Wen
2013-03-01
A novel method, which we called the analogous multifractal cross-correlation analysis, is proposed in this paper to study the multifractal behavior in the power-law cross-correlation between price and load in California electricity market. In addition, a statistic ρAMF -XA, which we call the analogous multifractal cross-correlation coefficient, is defined to test whether the cross-correlation between two given signals is genuine or not. Our analysis finds that both the price and load time series in California electricity market express multifractal nature. While, as indicated by the ρAMF -XA statistical test, there is a huge difference in the cross-correlation behavior between the years 1999 and 2000 in California electricity markets.
Wang, Fang; Liao, Gui-ping; Li, Jian-hui; Zou, Rui-biao; Shi, Wen
2013-03-01
A novel method, which we called the analogous multifractal cross-correlation analysis, is proposed in this paper to study the multifractal behavior in the power-law cross-correlation between price and load in California electricity market. In addition, a statistic ρAMF-XA, which we call the analogous multifractal cross-correlation coefficient, is defined to test whether the cross-correlation between two given signals is genuine or not. Our analysis finds that both the price and load time series in California electricity market express multifractal nature. While, as indicated by the ρAMF-XA statistical test, there is a huge difference in the cross-correlation behavior between the years 1999 and 2000 in California electricity markets.
Multiscale multifractal detrended cross-correlation analysis of financial time series
NASA Astrophysics Data System (ADS)
Shi, Wenbin; Shang, Pengjian; Wang, Jing; Lin, Aijing
2014-06-01
In this paper, we introduce a method called multiscale multifractal detrended cross-correlation analysis (MM-DCCA). The method allows us to extend the description of the cross-correlation properties between two time series. MM-DCCA may provide new ways of measuring the nonlinearity of two signals, and it helps to present much richer information than multifractal detrended cross-correlation analysis (MF-DCCA) by sweeping all the range of scale at which the multifractal structures of complex system are discussed. Moreover, to illustrate the advantages of this approach we make use of the MM-DCCA to analyze the cross-correlation properties between financial time series. We show that this new method can be adapted to investigate stock markets under investigation. It can provide a more faithful and more interpretable description of the dynamic mechanism between financial time series than traditional MF-DCCA. We also propose to reduce the scale ranges to analyze short time series, and some inherent properties which remain hidden when a wide range is used may exhibit perfectly in this way.
NASA Astrophysics Data System (ADS)
Cao, Guangxi; Han, Yan; Chen, Yuemeng; Yang, Chunxia
2014-05-01
Based on the daily price data of Shanghai and London gold spot markets, we applied detrended cross-correlation analysis (DCCA) and detrended moving average cross-correlation analysis (DMCA) methods to quantify power-law cross-correlation between domestic and international gold markets. Results show that the cross-correlations between the Chinese domestic and international gold spot markets are multifractal. Furthermore, forward DMCA and backward DMCA seems to outperform DCCA and centered DMCA for short-range gold series, which confirms the comparison results of short-range artificial data in L. Y. He and S. P. Chen [Physica A 390 (2011) 3806-3814]. Finally, we analyzed the local multifractal characteristics of the cross-correlation between Chinese domestic and international gold markets. We show that multifractal characteristics of the cross-correlation between the Chinese domestic and international gold markets are time-varying and that multifractal characteristics were strengthened by the financial crisis in 2007-2008.
Price-volume multifractal analysis of the Moroccan stock market
NASA Astrophysics Data System (ADS)
El Alaoui, Marwane
2017-11-01
In this paper, we analyzed price-volume multifractal cross-correlations of Moroccan Stock Exchange. We chose the period from January 1st 2000 to January 20th 2017 to investigate the multifractal behavior of price change and volume change series. Then, we used multifractal detrended cross-correlations analysis method (MF-DCCA) and multifractal detrended fluctuation analysis (MF-DFA) to analyze the series. We computed bivariate generalized Hurst exponent, Rényi exponent and spectrum of singularity for each pair of indices to measure quantitatively cross-correlations. Furthermore, we used detrended cross-correlations coefficient (DCCA) and cross-correlation test (Q(m)) to analyze cross-correlation quantitatively and qualitatively. By analyzing results, we found existence of price-volume multifractal cross-correlations. The spectrum width has a strong multifractal cross-correlation. We remarked that volume change series is anti-persistent when we analyzed the generalized Hurst exponent for all moments q. The cross-correlation test showed the presence of a significant cross-correlation. However, DCCA coefficient had a small positive value, which means that the level of correlation is not very significant. Finally, we analyzed sources of multifractality and their degree of contribution in the series.
NASA Astrophysics Data System (ADS)
Manimaran, P.; Narayana, A. C.
2018-07-01
In this paper, we study the multifractal characteristics and cross-correlation behaviour of Air Pollution Index (API) time series data through multifractal detrended cross-correlation analysis method. We analyse the daily API records of nine air pollutants of the university of Hyderabad campus for a period of three years (2013-2016). The cross-correlation behaviour has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, it is found that the cross-correlation analysis shows anti-correlation behaviour for all possible 36 bivariate time series. We also observe the existence of multifractal nature in all the bivariate time series in which many of them show strong multifractal behaviour. In particular, the hazardous particulate matter PM2.5 and inhalable particulate matter PM10 shows anti-correlated behaviour with all air pollutants.
NASA Astrophysics Data System (ADS)
Xie, Chi; Zhou, Yingying; Wang, Gangjin; Yan, Xinguo
We use the multifractal detrended cross-correlation analysis (MF-DCCA) method to explore the multifractal behavior of the cross-correlation between exchange rates of onshore RMB (CNY) and offshore RMB (CNH) against US dollar (USD). The empirical data are daily prices of CNY/USD and CNH/USD from May 1, 2012 to February 29, 2016. The results demonstrate that: (i) the cross-correlation between CNY/USD and CNH/USD is persistent and its fluctuation is smaller when the order of fluctuation function is negative than that when the order is positive; (ii) the multifractal behavior of the cross-correlation between CNY/USD and CNH/USD is significant during the sample period; (iii) the dynamic Hurst exponents obtained by the rolling windows analysis show that the cross-correlation is stable when the global economic situation is good and volatile in bad situation; and (iv) the non-normal distribution of original data has a greater effect on the multifractality of the cross-correlation between CNY/USD and CNH/USD than the temporary correlation.
NASA Astrophysics Data System (ADS)
Wang, Gang-Jin; Xie, Chi; Chen, Shou; Yang, Jiao-Jiao; Yang, Ming-Yan
2013-09-01
In this study, we first build two empirical cross-correlation matrices in the US stock market by two different methods, namely the Pearson’s correlation coefficient and the detrended cross-correlation coefficient (DCCA coefficient). Then, combining the two matrices with the method of random matrix theory (RMT), we mainly investigate the statistical properties of cross-correlations in the US stock market. We choose the daily closing prices of 462 constituent stocks of S&P 500 index as the research objects and select the sample data from January 3, 2005 to August 31, 2012. In the empirical analysis, we examine the statistical properties of cross-correlation coefficients, the distribution of eigenvalues, the distribution of eigenvector components, and the inverse participation ratio. From the two methods, we find some new results of the cross-correlations in the US stock market in our study, which are different from the conclusions reached by previous studies. The empirical cross-correlation matrices constructed by the DCCA coefficient show several interesting properties at different time scales in the US stock market, which are useful to the risk management and optimal portfolio selection, especially to the diversity of the asset portfolio. It will be an interesting and meaningful work to find the theoretical eigenvalue distribution of a completely random matrix R for the DCCA coefficient because it does not obey the Marčenko-Pastur distribution.
NASA Astrophysics Data System (ADS)
Ruan, Qingsong; Zhang, Shuhua; Lv, Dayong; Lu, Xinsheng
2018-02-01
Based on the implementation of Shanghai-Hong Kong Stock Connect in China, this paper examines the effects of financial liberalization on stock market comovement using both multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DCCA) methods. Results based on MF-DFA confirm the multifractality of Shanghai and Hong Kong stock markets, and the market efficiency of Shanghai stock market increased after the implementation of this connect program. Besides, analysis based on MF-DCCA has verified the existence of persistent cross-correlation between Shanghai and Hong Kong stock markets, and the cross-correlation gets stronger after the launch of this liberalization program. Finally, we find that fat-tail distribution is the main source of multifractality in the cross-correlations before the stock connect program, while long-range correlation contributes to the multifractality after this program.
Atmospheric pollution measurement by optical cross correlation methods - A concept
NASA Technical Reports Server (NTRS)
Fisher, M. J.; Krause, F. R.
1971-01-01
Method combines standard spectroscopy with statistical cross correlation analysis of two narrow light beams for remote sensing to detect foreign matter of given particulate size and consistency. Method is applicable in studies of generation and motion of clouds, nuclear debris, ozone, and radiation belts.
NASA Astrophysics Data System (ADS)
Dong, Keqiang; Zhang, Hong; Gao, You
2017-01-01
Identifying the mutual interaction in aero-engine gas path system is a crucial problem that facilitates the understanding of emerging structures in complex system. By employing the multiscale multifractal detrended cross-correlation analysis method to aero-engine gas path system, the cross-correlation characteristics between gas path system parameters are established. Further, we apply multiscale multifractal detrended cross-correlation distance matrix and minimum spanning tree to investigate the mutual interactions of gas path variables. The results can infer that the low-spool rotor speed (N1) and engine pressure ratio (EPR) are main gas path parameters. The application of proposed method contributes to promote our understanding of the internal mechanisms and structures of aero-engine dynamics.
Analog computation of auto and cross-correlation functions
NASA Technical Reports Server (NTRS)
1974-01-01
For analysis of the data obtained from the cross beam systems it was deemed desirable to compute the auto- and cross-correlation functions by both digital and analog methods to provide a cross-check of the analysis methods and an indication as to which of the two methods would be most suitable for routine use in the analysis of such data. It is the purpose of this appendix to provide a concise description of the equipment and procedures used for the electronic analog analysis of the cross beam data. A block diagram showing the signal processing and computation set-up used for most of the analog data analysis is provided. The data obtained at the field test sites were recorded on magnetic tape using wide-band FM recording techniques. The data as recorded were band-pass filtered by electronic signal processing in the data acquisition systems.
Oczeretko, Edward; Swiatecka, Jolanta; Kitlas, Agnieszka; Laudanski, Tadeusz; Pierzynski, Piotr
2006-01-01
In physiological research, we often study multivariate data sets, containing two or more simultaneously recorded time series. The aim of this paper is to present the cross-correlation and the wavelet cross-correlation methods to assess synchronization between contractions in different topographic regions of the uterus. From a medical point of view, it is important to identify time delays between contractions, which may be of potential diagnostic significance in various pathologies. The cross-correlation was computed in a moving window with a width corresponding to approximately two or three contractions. As a result, the running cross-correlation function was obtained. The propagation% parameter assessed from this function allows quantitative description of synchronization in bivariate time series. In general, the uterine contraction signals are very complicated. Wavelet transforms provide insight into the structure of the time series at various frequencies (scales). To show the changes of the propagation% parameter along scales, a wavelet running cross-correlation was used. At first, the continuous wavelet transforms as the uterine contraction signals were received and afterwards, a running cross-correlation analysis was conducted for each pair of transformed time series. The findings show that running functions are very useful in the analysis of uterine contractions.
NASA Astrophysics Data System (ADS)
Fan, Xiaoqian; Yuan, Ying; Zhuang, Xintian; Jin, Xiu
2017-03-01
Taking Baidu Index as a proxy for abnormal investor attention (AIA), the long memory property in the AIA of Shanghai Stock Exchange (SSE) 50 Index component stocks was empirically investigated using detrended fluctuation analysis (DFA) method. The results show that abnormal investor attention is power-law correlated with Hurst exponents between 0.64 and 0.98. Furthermore, the cross-correlations between abnormal investor attention and trading volume, volatility respectively are studied using detrended cross-correlation analysis (DCCA) and the DCCA cross-correlation coefficient (ρDCCA). The results suggest that there are positive correlations between AIA and trading volume, volatility respectively. In addition, the correlations for trading volume are in general higher than the ones for volatility. By carrying on rescaled range analysis (R/S) and rolling windows analysis, we find that the results mentioned above are effective and significant.
NASA Astrophysics Data System (ADS)
Pal, Mayukha; Madhusudana Rao, P.; Manimaran, P.
2014-12-01
We apply the recently developed multifractal detrended cross-correlation analysis method to investigate the cross-correlation behavior and fractal nature between two non-stationary time series. We analyze the daily return price of gold, West Texas Intermediate and Brent crude oil, foreign exchange rate data, over a period of 18 years. The cross correlation has been measured from the Hurst scaling exponents and the singularity spectrum quantitatively. From the results, the existence of multifractal cross-correlation between all of these time series is found. We also found that the cross correlation between gold and oil prices possess uncorrelated behavior and the remaining bivariate time series possess persistent behavior. It was observed for five bivariate series that the cross-correlation exponents are less than the calculated average generalized Hurst exponents (GHE) for q<0 and greater than GHE when q>0 and for one bivariate series the cross-correlation exponent is greater than GHE for all q values.
Modified cross sample entropy and surrogate data analysis method for financial time series
NASA Astrophysics Data System (ADS)
Yin, Yi; Shang, Pengjian
2015-09-01
For researching multiscale behaviors from the angle of entropy, we propose a modified cross sample entropy (MCSE) and combine surrogate data analysis with it in order to compute entropy differences between original dynamics and surrogate series (MCSDiff). MCSDiff is applied to simulated signals to show accuracy and then employed to US and Chinese stock markets. We illustrate the presence of multiscale behavior in the MCSDiff results and reveal that there are synchrony containing in the original financial time series and they have some intrinsic relations, which are destroyed by surrogate data analysis. Furthermore, the multifractal behaviors of cross-correlations between these financial time series are investigated by multifractal detrended cross-correlation analysis (MF-DCCA) method, since multifractal analysis is a multiscale analysis. We explore the multifractal properties of cross-correlation between these US and Chinese markets and show the distinctiveness of NQCI and HSI among the markets in their own region. It can be concluded that the weaker cross-correlation between US markets gives the evidence for the better inner mechanism in the US stock markets than that of Chinese stock markets. To study the multiscale features and properties of financial time series can provide valuable information for understanding the inner mechanism of financial markets.
Cross-correlations between Renminbi and four major currencies in the Renminbi currency basket
NASA Astrophysics Data System (ADS)
Wang, Gang-Jin; Xie, Chi
2013-03-01
We investigate the cross-correlations between Renminbi (CNY) and four major currencies (USD, EUR, JPY, and KRW) in the Renminbi currency basket, i.e., the cross-correlations of CNY-USD, CNY-EUR, CNY-JPY, and CNY-KRW. Qualitatively, using a statistical test in analogy to the Ljung-Box test, we find that cross-correlations significantly exist in CNY-USD, CNY-EUR, CNY-JPY, and CNY-KRW. Quantitatively, employing the detrended cross-correlation analysis (DCCA) method, we find that the cross-correlations of CNY-USD, CNY-EUR, CNY-JPY, and CNY-KRW are weakly persistent. We use the DCCA cross-correlation coefficient ρ to quantify the level of cross-correlations and find the currency weight in the Renminbi currency basket is arranged in the order of USD>EUR>JPY >KRW. Using the method of rolling windows, which can capture the time-varying cross-correlation scaling exponents, we find that: (i) CNY and USD are positively cross-correlated over time, but the cross-correlations of CNY-USD are anti-persistent during the US sub-prime crisis and the European debt crisis. (ii) The cross-correlation scaling exponents of CNY-EUR have the cyclical fluctuation with a nearly two-year cycle. (iii) CNY-JPY has long-term negative cross-correlations, during the European debt crisis, but CNY and KRW are positively cross-correlated.
Yuan, Naiming; Fu, Zuntao; Zhang, Huan; Piao, Lin; Xoplaki, Elena; Luterbacher, Juerg
2015-01-01
In this paper, a new method, detrended partial-cross-correlation analysis (DPCCA), is proposed. Based on detrended cross-correlation analysis (DCCA), this method is improved by including partial-correlation technique, which can be applied to quantify the relations of two non-stationary signals (with influences of other signals removed) on different time scales. We illustrate the advantages of this method by performing two numerical tests. Test I shows the advantages of DPCCA in handling non-stationary signals, while Test II reveals the “intrinsic” relations between two considered time series with potential influences of other unconsidered signals removed. To further show the utility of DPCCA in natural complex systems, we provide new evidence on the winter-time Pacific Decadal Oscillation (PDO) and the winter-time Nino3 Sea Surface Temperature Anomaly (Nino3-SSTA) affecting the Summer Rainfall over the middle-lower reaches of the Yangtze River (SRYR). By applying DPCCA, better significant correlations between SRYR and Nino3-SSTA on time scales of 6 ~ 8 years are found over the period 1951 ~ 2012, while significant correlations between SRYR and PDO on time scales of 35 years arise. With these physically explainable results, we have confidence that DPCCA is an useful method in addressing complex systems. PMID:25634341
NASA Astrophysics Data System (ADS)
Kim, Kyungsik; Lee, Dong-In
2013-04-01
There is considerable interest in cross-correlations in collective modes of real data from atmospheric geophysics, seismology, finance, physiology, genomics, and nanodevices. If two systems interact mutually, that interaction gives rise to collective modes. This phenomenon is able to be analyzed using the cross-correlation of traditional methods, random matrix theory, and the detrended cross-correlation analysis method. The detrended cross-correlation analysis method was used in the past to analyze several models such as autoregressive fractionally integrated moving average processes, stock prices and their trading volumes, and taxi accidents. Particulate matter is composed of the organic and inorganic mixtures such as the natural sea salt, soil particle, vehicles exhaust, construction dust, and soot. The PM10 is known as the particle with the aerodynamic diameter (less than 10 microns) that is able to enter the human respiratory system. The PM10 concentration has an effect on the climate change by causing an unbalance of the global radiative equilibrium through the direct effect that blocks the stoma of plants and cuts off the solar radiation, different from the indirect effect that changes the optical property of clouds, cloudiness, and lifetime of clouds. Various factors contribute to the degree of the PM10 concentration. Notable among these are the land-use types, surface vegetation coverage, as well as meteorological factors. In this study, we analyze and simulate cross-correlations in time scales between the PM10 concentration and the meteorological factor (among temperature, wind speed and humidity) using the detrended cross-correlation analysis method through the removal of specific trends at eight cities in the Korean peninsula. We divide time series data into Asian dust events and non-Asian dust events to analyze the change of meteorological factors on the fluctuation of PM10 the concentration during Asian dust events. In particular, our result is compared to analytic findings from references published in all nations. ----------------------------------------------------------------- This work was supported by Center for the ASER (CATER 2012-6110) and by the NRFK through a grant provided by the KMEST(No.K1663000201107900).
NASA Astrophysics Data System (ADS)
Hoshor, Cory; Young, Stephan; Rogers, Brent; Currie, James; Oakes, Thomas; Scott, Paul; Miller, William; Caruso, Anthony
2014-03-01
A novel application of the Pearson Cross-Correlation to neutron spectral discernment in a moderating type neutron spectrometer is introduced. This cross-correlation analysis will be applied to spectral response data collected through both MCNP simulation and empirical measurement by the volumetrically sensitive spectrometer for comparison in 1, 2, and 3 spatial dimensions. The spectroscopic analysis methods discussed will be demonstrated to discern various common spectral and monoenergetic neutron sources.
NASA Astrophysics Data System (ADS)
Cao, Guangxi; Zhang, Minjia; Li, Qingchen
2017-04-01
This study focuses on multifractal detrended cross-correlation analysis of the different volatility intervals of Mainland China, US, and Hong Kong stock markets. A volatility-constrained multifractal detrended cross-correlation analysis (VC-MF-DCCA) method is proposed to study the volatility conductivity of Mainland China, US, and Hong Kong stock markets. Empirical results indicate that fluctuation may be related to important activities in real markets. The Hang Seng Index (HSI) stock market is more influential than the Shanghai Composite Index (SCI) stock market. Furthermore, the SCI stock market is more influential than the Dow Jones Industrial Average stock market. The conductivity between the HSI and SCI stock markets is the strongest. HSI was the most influential market in the large fluctuation interval of 1991 to 2014. The autoregressive fractionally integrated moving average method is used to verify the validity of VC-MF-DCCA. Results show that VC-MF-DCCA is effective.
Cross-correlation of point series using a new method
NASA Technical Reports Server (NTRS)
Strothers, Richard B.
1994-01-01
Traditional methods of cross-correlation of two time series do not apply to point time series. Here, a new method, devised specifically for point series, utilizes a correlation measure that is based in the rms difference (or, alternatively, the median absolute difference) between nearest neightbors in overlapped segments of the two series. Error estimates for the observed locations of the points, as well as a systematic shift of one series with respect to the other to accommodate a constant, but unknown, lead or lag, are easily incorporated into the analysis using Monte Carlo techniques. A methodological restriction adopted here is that one series be treated as a template series against which the other, called the target series, is cross-correlated. To estimate a significance level for the correlation measure, the adopted alternative (null) hypothesis is that the target series arises from a homogeneous Poisson process. The new method is applied to cross-correlating the times of the greatest geomagnetic storms with the times of maximum in the undecennial solar activity cycle.
NASA Astrophysics Data System (ADS)
Piao, Lin; Fu, Zuntao
2016-11-01
Cross-correlation between pairs of variables takes multi-time scale characteristic, and it can be totally different on different time scales (changing from positive correlation to negative one), e.g., the associations between mean air temperature and relative humidity over regions to the east of Taihang mountain in China. Therefore, how to correctly unveil these correlations on different time scales is really of great importance since we actually do not know if the correlation varies with scales in advance. Here, we compare two methods, i.e. Detrended Cross-Correlation Analysis (DCCA for short) and Pearson correlation, in quantifying scale-dependent correlations directly to raw observed records and artificially generated sequences with known cross-correlation features. Studies show that 1) DCCA related methods can indeed quantify scale-dependent correlations, but not Pearson method; 2) the correlation features from DCCA related methods are robust to contaminated noises, however, the results from Pearson method are sensitive to noise; 3) the scale-dependent correlation results from DCCA related methods are robust to the amplitude ratio between slow and fast components, while Pearson method may be sensitive to the amplitude ratio. All these features indicate that DCCA related methods take some advantages in correctly quantifying scale-dependent correlations, which results from different physical processes.
Piao, Lin; Fu, Zuntao
2016-11-09
Cross-correlation between pairs of variables takes multi-time scale characteristic, and it can be totally different on different time scales (changing from positive correlation to negative one), e.g., the associations between mean air temperature and relative humidity over regions to the east of Taihang mountain in China. Therefore, how to correctly unveil these correlations on different time scales is really of great importance since we actually do not know if the correlation varies with scales in advance. Here, we compare two methods, i.e. Detrended Cross-Correlation Analysis (DCCA for short) and Pearson correlation, in quantifying scale-dependent correlations directly to raw observed records and artificially generated sequences with known cross-correlation features. Studies show that 1) DCCA related methods can indeed quantify scale-dependent correlations, but not Pearson method; 2) the correlation features from DCCA related methods are robust to contaminated noises, however, the results from Pearson method are sensitive to noise; 3) the scale-dependent correlation results from DCCA related methods are robust to the amplitude ratio between slow and fast components, while Pearson method may be sensitive to the amplitude ratio. All these features indicate that DCCA related methods take some advantages in correctly quantifying scale-dependent correlations, which results from different physical processes.
Nonlinear Analysis on Cross-Correlation of Financial Time Series by Continuum Percolation System
NASA Astrophysics Data System (ADS)
Niu, Hongli; Wang, Jun
We establish a financial price process by continuum percolation system, in which we attribute price fluctuations to the investors’ attitudes towards the financial market, and consider the clusters in continuum percolation as the investors share the same investment opinion. We investigate the cross-correlations in two return time series, and analyze the multifractal behaviors in this relationship. Further, we study the corresponding behaviors for the real stock indexes of SSE and HSI as well as the liquid stocks pair of SPD and PAB by comparison. To quantify the multifractality in cross-correlation relationship, we employ multifractal detrended cross-correlation analysis method to perform an empirical research for the simulation data and the real markets data.
A generalization of random matrix theory and its application to statistical physics.
Wang, Duan; Zhang, Xin; Horvatic, Davor; Podobnik, Boris; Eugene Stanley, H
2017-02-01
To study the statistical structure of crosscorrelations in empirical data, we generalize random matrix theory and propose a new method of cross-correlation analysis, known as autoregressive random matrix theory (ARRMT). ARRMT takes into account the influence of auto-correlations in the study of cross-correlations in multiple time series. We first analytically and numerically determine how auto-correlations affect the eigenvalue distribution of the correlation matrix. Then we introduce ARRMT with a detailed procedure of how to implement the method. Finally, we illustrate the method using two examples taken from inflation rates for air pressure data for 95 US cities.
A study of correlations between crude oil spot and futures markets: A rolling sample test
NASA Astrophysics Data System (ADS)
Liu, Li; Wan, Jieqiu
2011-10-01
In this article, we investigate the asymmetries of exceedance correlations and cross-correlations between West Texas Intermediate (WTI) spot and futures markets. First, employing the test statistic proposed by Hong et al. [Asymmetries in stock returns: statistical tests and economic evaluation, Review of Financial Studies 20 (2007) 1547-1581], we find that the exceedance correlations were overall symmetric. However, the results from rolling windows show that some occasional events could induce the significant asymmetries of the exceedance correlations. Second, employing the test statistic proposed by Podobnik et al. [Quantifying cross-correlations using local and global detrending approaches, European Physics Journal B 71 (2009) 243-250], we find that the cross-correlations were significant even for large lagged orders. Using the detrended cross-correlation analysis proposed by Podobnik and Stanley [Detrended cross-correlation analysis: a new method for analyzing two nonstationary time series, Physics Review Letters 100 (2008) 084102], we find that the cross-correlations were weakly persistent and were stronger between spot and futures contract with larger maturity. Our results from rolling sample test also show the apparent effects of the exogenous events. Additionally, we have some relevant discussions on the obtained evidence.
Extreme values in the Chinese and American stock markets based on detrended fluctuation analysis
NASA Astrophysics Data System (ADS)
Cao, Guangxi; Zhang, Minjia
2015-10-01
This paper focuses on the comparative analysis of extreme values in the Chinese and American stock markets based on the detrended fluctuation analysis (DFA) algorithm using the daily data of Shanghai composite index and Dow Jones Industrial Average. The empirical results indicate that the multifractal detrended fluctuation analysis (MF-DFA) method is more objective than the traditional percentile method. The range of extreme value of Dow Jones Industrial Average is smaller than that of Shanghai composite index, and the extreme value of Dow Jones Industrial Average is more time clustering. The extreme value of the Chinese or American stock markets is concentrated in 2008, which is consistent with the financial crisis in 2008. Moreover, we investigate whether extreme events affect the cross-correlation between the Chinese and American stock markets using multifractal detrended cross-correlation analysis algorithm. The results show that extreme events have nothing to do with the cross-correlation between the Chinese and American stock markets.
Sarrigiannis, Ptolemaios G; Zhao, Yifan; Wei, Hua-Liang; Billings, Stephen A; Fotheringham, Jayne; Hadjivassiliou, Marios
2014-01-01
To introduce a new method of quantitative EEG analysis in the time domain, the error reduction ratio (ERR)-causality test. To compare performance against cross-correlation and coherence with phase measures. A simulation example was used as a gold standard to assess the performance of ERR-causality, against cross-correlation and coherence. The methods were then applied to real EEG data. Analysis of both simulated and real EEG data demonstrates that ERR-causality successfully detects dynamically evolving changes between two signals, with very high time resolution, dependent on the sampling rate of the data. Our method can properly detect both linear and non-linear effects, encountered during analysis of focal and generalised seizures. We introduce a new quantitative EEG method of analysis. It detects real time levels of synchronisation in the linear and non-linear domains. It computes directionality of information flow with corresponding time lags. This novel dynamic real time EEG signal analysis unveils hidden neural network interactions with a very high time resolution. These interactions cannot be adequately resolved by the traditional methods of coherence and cross-correlation, which provide limited results in the presence of non-linear effects and lack fidelity for changes appearing over small periods of time. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
Non-stationarity and cross-correlation effects in the MHD solar activity
NASA Astrophysics Data System (ADS)
Demin, S. A.; Nefedyev, Y. A.; Andreev, A. O.; Demina, N. Y.; Timashev, S. F.
2018-01-01
The analysis of turbulent processes in sunspots and pores which are self-organizing long-lived magnetic structures is a complicated and not yet solved problem. The present work focuses on studying such magneto-hydrodynamic (MHD) formations on the basis of flicker-noise spectroscopy using a new method of multi-parametric analysis. The non-stationarity and cross-correlation effects taking place in solar activity dynamics are considered. The calculated maximum values of non-stationarity factor may become precursors of significant restructuring in solar magnetic activity. The introduced cross-correlation functions enable us to judge synchronization effects between the signals of various solar activity indicators registered simultaneously.
NASA Astrophysics Data System (ADS)
Sun, Xuelian; Liu, Zixian
2016-02-01
In this paper, a new estimator of correlation matrix is proposed, which is composed of the detrended cross-correlation coefficients (DCCA coefficients), to improve portfolio optimization. In contrast to Pearson's correlation coefficients (PCC), DCCA coefficients acquired by the detrended cross-correlation analysis (DCCA) method can describe the nonlinear correlation between assets, and can be decomposed in different time scales. These properties of DCCA make it possible to improve the investment effect and more valuable to investigate the scale behaviors of portfolios. The minimum variance portfolio (MVP) model and the Mean-Variance (MV) model are used to evaluate the effectiveness of this improvement. Stability analysis shows the effect of two kinds of correlation matrices on the estimation error of portfolio weights. The observed scale behaviors are significant to risk management and could be used to optimize the portfolio selection.
NASA Technical Reports Server (NTRS)
Kim, Sang-Wook
1987-01-01
Various experimental, analytical, and numerical analysis methods for flow-solid interaction of a nest of cylinders subjected to cross flows are reviewed. A nest of cylinders subjected to cross flows can be found in numerous engineering applications including the Space Shuttle Maine Engine-Main Injector Assembly (SSME-MIA) and nuclear reactor heat exchangers. Despite its extreme importance in engineering applications, understanding of the flow-solid interaction process is quite limited and design of the tube banks are mostly dependent on experiments and/or experimental correlation equations. For future development of major numerical analysis methods for the flow-solid interaction of a nest of cylinders subjected to cross flow, various turbulence models, nonlinear structural dynamics, and existing laminar flow-solid interaction analysis methods are included.
NASA Astrophysics Data System (ADS)
Yang, Liansheng; Zhu, Yingming; Wang, Yudong; Wang, Yiqi
2016-11-01
Based on the daily price data of spot prices of West Texas Intermediate (WTI) crude oil and ten CSI300 sector indices in China, we apply multifractal detrended cross-correlation analysis (MF-DCCA) method to investigate the cross-correlations between crude oil and Chinese sector stock markets. We find that the strength of multifractality between WTI crude oil and energy sector stock market is the highest, followed by the strength of multifractality between WTI crude oil and financial sector market, which reflects a close connection between energy and financial market. Then we do vector autoregression (VAR) analysis to capture the interdependencies among the multiple time series. By comparing the strength of multifractality for original data and residual errors of VAR model, we get a conclusion that vector auto-regression (VAR) model could not be used to describe the dynamics of the cross-correlations between WTI crude oil and the ten sector stock markets.
NASA Astrophysics Data System (ADS)
Zhou, Yu; Chen, Shi
2016-02-01
In this paper, we investigate the high-frequency cross-correlation relationship between Chinese treasury futures contracts and treasury ETF. We analyze the logarithmic return of these two price series, from which we can conclude that both return series are not normally distributed and the futures markets have greater volatility. We find significant cross-correlation between these two series. We further confirm the relationship using the DCCA coefficient and the DMCA coefficient. We quantify the long-range cross-correlation with DCCA method, and we further show that the relationship is multifractal. An arbitrage algorithm based on DFA regression with stable return is proposed in the last part.
NASA Astrophysics Data System (ADS)
Delignières, Didier; Marmelat, Vivien
2014-01-01
In this paper, we analyze empirical data, accounting for coordination processes between complex systems (bimanual coordination, interpersonal coordination, and synchronization with a fractal metronome), by using a recently proposed method: detrended cross-correlation analysis (DCCA). This work is motivated by the strong anticipation hypothesis, which supposes that coordination between complex systems is not achieved on the basis of local adaptations (i.e., correction, predictions), but results from a more global matching of complexity properties. Indeed, recent experiments have evidenced a very close correlation between the scaling properties of the series produced by two coordinated systems, despite a quite weak local synchronization. We hypothesized that strong anticipation should result in the presence of long-range cross-correlations between the series produced by the two systems. Results allow a detailed analysis of the effects of coordination on the fluctuations of the series produced by the two systems. In the long term, series tend to present similar scaling properties, with clear evidence of long-range cross-correlation. Short-term results strongly depend on the nature of the task. Simulation studies allow disentangling the respective effects of noise and short-term coupling processes on DCCA results, and suggest that the matching of long-term fluctuations could be the result of short-term coupling processes.
He, Hong-di; Qiao, Zhong-Xia; Pan, Wei; Lu, Wei-Zhen
2017-07-01
In rural area, due to the reduction of NOx and CO emitted from vehicle exhausts, the ozone photochemical reaction exhibits relatively weak effect and ozone formation presents different pattern with its precursors in contrast to urban situation. Hence, in this study, we apply detrended cross-correlation analysis to investigate the multifractal properties between ozone and its precursors in a rural area in Hong Kong. The observed databases of ozone, NO 2 , NOx and CO levels during 2005-2014 are obtained from a rural monitoring station in Hong Kong. Based on the collected database, the cross-correlation analysis is carried out firstly to examine the cross-correlation patterns and the results indicate that close interactive relations exist between them. Then the detrended cross-correlation analysis is performed for further analysis. The multifractal characters occur between ozone and its precursors. The long-term cross-correlations behaviors in winter are verified to be stronger than that in other seasons. Additionally, the method is extended on daily averaged data to explore the multifractal property on various time scales. The long-term cross-correlation behavior of ozone vs NO 2 and NOx on daily basis becomes weaker while that of ozone vs CO becomes stronger. The multifractal properties for all pairs in summer are found to be the strongest among the whole year. These findings successfully illustrate that the multifractal analysis is a useful tool for describing the temporal scaling behaviors of ozone trends in different time series in rural areas. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Radhakrishnan, Srinivasan; Duvvuru, Arjun; Sultornsanee, Sivarit; Kamarthi, Sagar
2016-02-01
The cross correlation coefficient has been widely applied in financial time series analysis, in specific, for understanding chaotic behaviour in terms of stock price and index movements during crisis periods. To better understand time series correlation dynamics, the cross correlation matrices are represented as networks, in which a node stands for an individual time series and a link indicates cross correlation between a pair of nodes. These networks are converted into simpler trees using different schemes. In this context, Minimum Spanning Trees (MST) are the most favoured tree structures because of their ability to preserve all the nodes and thereby retain essential information imbued in the network. Although cross correlations underlying MSTs capture essential information, they do not faithfully capture dynamic behaviour embedded in the time series data of financial systems because cross correlation is a reliable measure only if the relationship between the time series is linear. To address the issue, this work investigates a new measure called phase synchronization (PS) for establishing correlations among different time series which relate to one another, linearly or nonlinearly. In this approach the strength of a link between a pair of time series (nodes) is determined by the level of phase synchronization between them. We compare the performance of phase synchronization based MST with cross correlation based MST along selected network measures across temporal frame that includes economically good and crisis periods. We observe agreement in the directionality of the results across these two methods. They show similar trends, upward or downward, when comparing selected network measures. Though both the methods give similar trends, the phase synchronization based MST is a more reliable representation of the dynamic behaviour of financial systems than the cross correlation based MST because of the former's ability to quantify nonlinear relationships among time series or relations among phase shifted time series.
Atmospheric turbulence profiling with SLODAR using multiple adaptive optics wavefront sensors.
Wang, Lianqi; Schöck, Matthias; Chanan, Gary
2008-04-10
The slope detection and ranging (SLODAR) method recovers atmospheric turbulence profiles from time averaged spatial cross correlations of wavefront slopes measured by Shack-Hartmann wavefront sensors. The Palomar multiple guide star unit (MGSU) was set up to test tomographic multiple guide star adaptive optics and provided an ideal test bed for SLODAR turbulence altitude profiling. We present the data reduction methods and SLODAR results from MGSU observations made in 2006. Wind profiling is also performed using delayed wavefront cross correlations along with SLODAR analysis. The wind profiling analysis is shown to improve the height resolution of the SLODAR method and in addition gives the wind velocities of the turbulent layers.
Multi-ball and one-ball geolocation and location verification
NASA Astrophysics Data System (ADS)
Nelson, D. J.; Townsend, J. L.
2017-05-01
We present analysis methods that may be used to geolocate emitters using one or more moving receivers. While some of the methods we present may apply to a broader class of signals, our primary interest is locating and tracking ships from short pulsed transmissions, such as the maritime Automatic Identification System (AIS.) The AIS signal is difficult to process and track since the pulse duration is only 25 milliseconds, and the pulses may only be transmitted every six to ten seconds. Several fundamental problems are addressed, including demodulation of AIS/GMSK signals, verification of the emitter location, accurate frequency and delay estimation and identification of pulse trains from the same emitter. In particular, we present several new correlation methods, including cross-cross correlation that greatly improves correlation accuracy over conventional methods and cross- TDOA and cross-FDOA functions that make it possible to estimate time and frequency delay without the need of computing a two dimensional cross-ambiguity surface. By isolating pulses from the same emitter and accurately tracking the received signal frequency, we are able to accurately estimate the emitter location from the received Doppler characteristics.
Multifractal detrending moving-average cross-correlation analysis
NASA Astrophysics Data System (ADS)
Jiang, Zhi-Qiang; Zhou, Wei-Xing
2011-07-01
There are a number of situations in which several signals are simultaneously recorded in complex systems, which exhibit long-term power-law cross correlations. The multifractal detrended cross-correlation analysis (MFDCCA) approaches can be used to quantify such cross correlations, such as the MFDCCA based on the detrended fluctuation analysis (MFXDFA) method. We develop in this work a class of MFDCCA algorithms based on the detrending moving-average analysis, called MFXDMA. The performances of the proposed MFXDMA algorithms are compared with the MFXDFA method by extensive numerical experiments on pairs of time series generated from bivariate fractional Brownian motions, two-component autoregressive fractionally integrated moving-average processes, and binomial measures, which have theoretical expressions of the multifractal nature. In all cases, the scaling exponents hxy extracted from the MFXDMA and MFXDFA algorithms are very close to the theoretical values. For bivariate fractional Brownian motions, the scaling exponent of the cross correlation is independent of the cross-correlation coefficient between two time series, and the MFXDFA and centered MFXDMA algorithms have comparative performances, which outperform the forward and backward MFXDMA algorithms. For two-component autoregressive fractionally integrated moving-average processes, we also find that the MFXDFA and centered MFXDMA algorithms have comparative performances, while the forward and backward MFXDMA algorithms perform slightly worse. For binomial measures, the forward MFXDMA algorithm exhibits the best performance, the centered MFXDMA algorithms performs worst, and the backward MFXDMA algorithm outperforms the MFXDFA algorithm when the moment order q<0 and underperforms when q>0. We apply these algorithms to the return time series of two stock market indexes and to their volatilities. For the returns, the centered MFXDMA algorithm gives the best estimates of hxy(q) since its hxy(2) is closest to 0.5, as expected, and the MFXDFA algorithm has the second best performance. For the volatilities, the forward and backward MFXDMA algorithms give similar results, while the centered MFXDMA and the MFXDFA algorithms fail to extract rational multifractal nature.
Bringing the cross-correlation method up to date
NASA Technical Reports Server (NTRS)
Statler, Thomas
1995-01-01
The cross-correlation (XC) method of Tonry & Davis (1979, AJ, 84, 1511) is generalized to arbitrary parametrized line profiles. In the new algorithm the correlation function itself, rather than the observed galaxy spectrum, is fitted by the model line profile: this removes much of the complication in the error analysis caused by template mismatch. Like the Fourier correlation quotient (FCQ) method of Bender (1990, A&A, 229, 441), the inferred line profiles are, up to a normalization constant, independent of template mismatch as long as there are no blended lines. The standard reduced chi(exp 2) is a good measure of the fit of the inferred velocity distribution, largely decoupled from the fit of the spectral template. The updated XC method performs as well as other recently developed methods, with the added virtue of conceptual simplicity.
High lateral resolution exploration using surface waves from noise records
NASA Astrophysics Data System (ADS)
Chávez-García, Francisco José Yokoi, Toshiaki
2016-04-01
Determination of the shear-wave velocity structure at shallow depths is a constant necessity in engineering or environmental projects. Given the sensitivity of Rayleigh waves to shear-wave velocity, subsoil structure exploration using surface waves is frequently used. Methods such as the spectral analysis of surface waves (SASW) or multi-channel analysis of surface waves (MASW) determine phase velocity dispersion from surface waves generated by an active source recorded on a line of geophones. Using MASW, it is important that the receiver array be as long as possible to increase the precision at low frequencies. However, this implies that possible lateral variations are discarded. Hayashi and Suzuki (2004) proposed a different way of stacking shot gathers to increase lateral resolution. They combined strategies used in MASW with the common mid-point (CMP) summation currently used in reflection seismology. In their common mid-point with cross-correlation method (CMPCC), they cross-correlate traces sharing CMP locations before determining phase velocity dispersion. Another recent approach to subsoil structure exploration is based on seismic interferometry. It has been shown that cross-correlation of a diffuse field, such as seismic noise, allows the estimation of the Green's Function between two receivers. Thus, a virtual-source seismic section may be constructed from the cross-correlation of seismic noise records obtained in a line of receivers. In this paper, we use the seismic interferometry method to process seismic noise records obtained in seismic refraction lines of 24 geophones, and analyse the results using CMPCC to increase the lateral resolution of the results. Cross-correlation of the noise records allows reconstructing seismic sections with virtual sources at each receiver location. The Rayleigh wave component of the Green's Functions is obtained with a high signal-to-noise ratio. Using CMPCC analysis of the virtual-source seismic lines, we are able to identify lateral variations of phase velocity inside the seismic line, and increase the lateral resolution compared with results of conventional analysis.
Optical correlation techniques in fluid dynamics
NASA Astrophysics Data System (ADS)
Schätzel, K.; Schulz-Dubois, E. O.; Vehrenkamp, R.
1981-04-01
Three flow measurement techniques make use of fast digital correlators. The most widely spread is photon correlation velocimetry using crossed laser beams, and detecting Doppler shifted light scattered by small particles in the flow. Depending on the processing of the photon correlation output, this technique yields mean velocity, turbulence level, and even the detailed probability distribution of one velocity component. An improved data processing scheme is demonstrated on laminar vortex flow in a curved channel. In the second method, rate correlation based upon threshold crossings of a high pass filtered laser Doppler signal can be used to obtain velocity correlation functions. The most powerful set-up developed in our laboratory uses a phase locked loop type tracker and a multibit correlator to analyze time-dependent Taylor vortex flow. With two optical systems and trackers, cross-correlation functions reveal phase relations between different vortices. The last method makes use of refractive index fluctuations (eg in two phase flows) instead of scattering particles. Interferometry with bidirectional counting, and digital correlation and probability analysis, constitutes a new quantitative technique related to classical Schlieren methods. Measurements on a mixing flow of heated and cold air contribute new ideas to the theory of turbulent random phase screens.
NASA Astrophysics Data System (ADS)
Dutta, Srimonti; Ghosh, Dipak; Chatterjee, Sucharita
2016-12-01
The manuscript studies autocorrelation and cross correlation of SENSEX fluctuations and Forex Exchange Rate in respect to Indian scenario. Multifractal detrended fluctuation analysis (MFDFA) and multifractal detrended cross correlation analysis (MFDXA) were employed to study the correlation between the two series. It was observed that the two series are strongly cross correlated. The change of degree of cross correlation with time was studied and the results are interpreted qualitatively.
NASA Astrophysics Data System (ADS)
Dong, Keqiang; Fan, Jie; Gao, You
2015-12-01
Identifying the mutual interaction is a crucial problem that facilitates the understanding of emerging structures in complex system. We here focus on aero-engine dynamic as an example of complex system. By applying the detrended cross-correlation analysis (DCCA) coefficient method to aero-engine gas path system, we find that the low-spool rotor speed (N1) and high-spool rotor speed (N2) fluctuation series exhibit cross-correlation characteristic. Further, we employ detrended cross-correlation coefficient matrix and rooted tree to investigate the mutual interactions of other gas path variables. The results can infer that the exhaust gas temperature (EGT), N1, N2, fuel flow (WF) and engine pressure ratio (EPR) are main gas path parameters.
Frequency domain analysis of errors in cross-correlations of ambient seismic noise
NASA Astrophysics Data System (ADS)
Liu, Xin; Ben-Zion, Yehuda; Zigone, Dimitri
2016-12-01
We analyse random errors (variances) in cross-correlations of ambient seismic noise in the frequency domain, which differ from previous time domain methods. Extending previous theoretical results on ensemble averaged cross-spectrum, we estimate confidence interval of stacked cross-spectrum of finite amount of data at each frequency using non-overlapping windows with fixed length. The extended theory also connects amplitude and phase variances with the variance of each complex spectrum value. Analysis of synthetic stationary ambient noise is used to estimate the confidence interval of stacked cross-spectrum obtained with different length of noise data corresponding to different number of evenly spaced windows of the same duration. This method allows estimating Signal/Noise Ratio (SNR) of noise cross-correlation in the frequency domain, without specifying filter bandwidth or signal/noise windows that are needed for time domain SNR estimations. Based on synthetic ambient noise data, we also compare the probability distributions, causal part amplitude and SNR of stacked cross-spectrum function using one-bit normalization or pre-whitening with those obtained without these pre-processing steps. Natural continuous noise records contain both ambient noise and small earthquakes that are inseparable from the noise with the existing pre-processing steps. Using probability distributions of random cross-spectrum values based on the theoretical results provides an effective way to exclude such small earthquakes, and additional data segments (outliers) contaminated by signals of different statistics (e.g. rain, cultural noise), from continuous noise waveforms. This technique is applied to constrain values and uncertainties of amplitude and phase velocity of stacked noise cross-spectrum at different frequencies, using data from southern California at both regional scale (˜35 km) and dense linear array (˜20 m) across the plate-boundary faults. A block bootstrap resampling method is used to account for temporal correlation of noise cross-spectrum at low frequencies (0.05-0.2 Hz) near the ocean microseismic peaks.
Weighted network analysis of high-frequency cross-correlation measures
NASA Astrophysics Data System (ADS)
Iori, Giulia; Precup, Ovidiu V.
2007-03-01
In this paper we implement a Fourier method to estimate high-frequency correlation matrices from small data sets. The Fourier estimates are shown to be considerably less noisy than the standard Pearson correlation measures and thus capable of detecting subtle changes in correlation matrices with just a month of data. The evolution of correlation at different time scales is analyzed from the full correlation matrix and its minimum spanning tree representation. The analysis is performed by implementing measures from the theory of random weighted networks.
Testing alternative ground water models using cross-validation and other methods
Foglia, L.; Mehl, S.W.; Hill, M.C.; Perona, P.; Burlando, P.
2007-01-01
Many methods can be used to test alternative ground water models. Of concern in this work are methods able to (1) rank alternative models (also called model discrimination) and (2) identify observations important to parameter estimates and predictions (equivalent to the purpose served by some types of sensitivity analysis). Some of the measures investigated are computationally efficient; others are computationally demanding. The latter are generally needed to account for model nonlinearity. The efficient model discrimination methods investigated include the information criteria: the corrected Akaike information criterion, Bayesian information criterion, and generalized cross-validation. The efficient sensitivity analysis measures used are dimensionless scaled sensitivity (DSS), composite scaled sensitivity, and parameter correlation coefficient (PCC); the other statistics are DFBETAS, Cook's D, and observation-prediction statistic. Acronyms are explained in the introduction. Cross-validation (CV) is a computationally intensive nonlinear method that is used for both model discrimination and sensitivity analysis. The methods are tested using up to five alternative parsimoniously constructed models of the ground water system of the Maggia Valley in southern Switzerland. The alternative models differ in their representation of hydraulic conductivity. A new method for graphically representing CV and sensitivity analysis results for complex models is presented and used to evaluate the utility of the efficient statistics. The results indicate that for model selection, the information criteria produce similar results at much smaller computational cost than CV. For identifying important observations, the only obviously inferior linear measure is DSS; the poor performance was expected because DSS does not include the effects of parameter correlation and PCC reveals large parameter correlations. ?? 2007 National Ground Water Association.
Quantifying the range of cross-correlated fluctuations using a q- L dependent AHXA coefficient
NASA Astrophysics Data System (ADS)
Wang, Fang; Wang, Lin; Chen, Yuming
2018-03-01
Recently, based on analogous height cross-correlation analysis (AHXA), a cross-correlation coefficient ρ×(L) has been proposed to quantify the levels of cross-correlation on different temporal scales for bivariate series. A limitation of this coefficient is that it cannot capture the full information of cross-correlations on amplitude of fluctuations. In fact, it only detects the cross-correlation at a specific order fluctuation, which might neglect some important information inherited from other order fluctuations. To overcome this disadvantage, in this work, based on the scaling of the qth order covariance and time delay L, we define a two-parameter dependent cross-correlation coefficient ρq(L) to detect and quantify the range and level of cross-correlations. This new version of ρq(L) coefficient leads to the formation of a ρq(L) surface, which not only is able to quantify the level of cross-correlations, but also allows us to identify the range of fluctuation amplitudes that are correlated in two given signals. Applications to the classical ARFIMA models and the binomial multifractal series illustrate the feasibility of this new coefficient ρq(L) . In addition, a statistical test is proposed to quantify the existence of cross-correlations between two given series. Applying our method to the real life empirical data from the 1999-2000 California electricity market, we find that the California power crisis in 2000 destroys the cross-correlation between the price and the load series but does not affect the correlation of the load series during and before the crisis.
The Identification and Tracking of Uterine Contractions Using Template Based Cross-Correlation.
McDonald, Sarah C; Brooker, Graham; Phipps, Hala; Hyett, Jon
2017-09-01
The purpose of this paper is to outline a novel method of using template based cross-correlation to identify and track uterine contractions during labour. A purpose built six-channel Electromyography (EMG) device was used to collect data from consenting women during labour and birth. A range of templates were constructed for the purpose of identifying and tracking uterine activity when cross-correlated with the EMG signal. Peak finding techniques were applied on the cross-correlated result to simplify and automate the identification and tracking of contractions. The EMG data showed a unique pattern when a woman was contracting with key features of the contraction signal remaining consistent and identifiable across subjects. Contraction profiles across subjects were automatically identified using template based cross-correlation. Synthetic templates from a rectangular function with a duration of between 5 and 10 s performed best at identifying and tracking uterine activity across subjects. The successful application of this technique provides opportunity for both simple and accurate real-time analysis of contraction data while enabling investigations into the application of techniques such as machine learning which could enable automated learning from contraction data as part of real-time monitoring and post analysis.
Multifractal detrended cross-correlation analysis on NO, NO2 and O3 concentrations at traffic sites
NASA Astrophysics Data System (ADS)
Xu, Weijia; Liu, Chunqiong; Shi, Kai; Liu, Yonghong
2018-07-01
NOX plays the important role for O3 production in atmospheric photochemical processes. In this paper, the cross-correlations between NO (NO2) and O3 at three traffic sites in Hong Kong are investigated, using the multifractal detrended cross-correlation analysis (MFDCCA). The results show that the cross-correlations between NO (NO2) and O3 have multifractal nature and long term persistent power-law decaying behavior. The sources of multifractality are discussed based on the shuffling and phase randomization procedure. The chi square test is applied to identify the contributions degree of NO and NO2 to multifractality due to its own long term correlations respectively. And the temporal evolutions of the local contributions degree of NO and NO2 to multifractality are investigated by the sliding windows method. The differences between them are explained by the self-organized criticality mechanism of air pollution, combined with global solar radiation. MFDCCA provides a helpful approach for understanding the quantitative relationship between the O3 and its precursors.
NASA Astrophysics Data System (ADS)
Yuan, Naiming; Xoplaki, Elena; Zhu, Congwen; Luterbacher, Juerg
2016-06-01
In this paper, two new methods, Temporal evolution of Detrended Cross-Correlation Analysis (TDCCA) and Temporal evolution of Detrended Partial-Cross-Correlation Analysis (TDPCCA), are proposed by generalizing DCCA and DPCCA. Applying TDCCA/TDPCCA, it is possible to study correlations on multi-time scales and over different periods. To illustrate their properties, we used two climatological examples: i) Global Sea Level (GSL) versus North Atlantic Oscillation (NAO); and ii) Summer Rainfall over Yangtze River (SRYR) versus previous winter Pacific Decadal Oscillation (PDO). We find significant correlations between GSL and NAO on time scales of 60 to 140 years, but the correlations are non-significant between 1865-1875. As for SRYR and PDO, significant correlations are found on time scales of 30 to 35 years, but the correlations are more pronounced during the recent 30 years. By combining TDCCA/TDPCCA and DCCA/DPCCA, we proposed a new correlation-detection system, which compared to traditional methods, can objectively show how two time series are related (on which time scale, during which time period). These are important not only for diagnosis of complex system, but also for better designs of prediction models. Therefore, the new methods offer new opportunities for applications in natural sciences, such as ecology, economy, sociology and other research fields.
Wear Detection of Drill Bit by Image-based Technique
NASA Astrophysics Data System (ADS)
Sukeri, Maziyah; Zulhilmi Paiz Ismadi, Mohd; Rahim Othman, Abdul; Kamaruddin, Shahrul
2018-03-01
Image processing for computer vision function plays an essential aspect in the manufacturing industries for the tool condition monitoring. This study proposes a dependable direct measurement method to measure the tool wear using image-based analysis. Segmentation and thresholding technique were used as the means to filter and convert the colour image to binary datasets. Then, the edge detection method was applied to characterize the edge of the drill bit. By using cross-correlation method, the edges of original and worn drill bits were correlated to each other. Cross-correlation graphs were able to detect the difference of the worn edge despite small difference between the graphs. Future development will focus on quantifying the worn profile as well as enhancing the sensitivity of the technique.
NASA Astrophysics Data System (ADS)
Constantoudis, Vassilios; Papavieros, George; Lorusso, Gian; Rutigliani, Vito; Van Roey, Frieda; Gogolides, Evangelos
2018-03-01
The aim of this paper is to investigate the role of etch transfer in two challenges of LER metrology raised by recent evolutions in lithography: the effects of SEM noise and the cross-line and edge correlations. The first comes from the ongoing scaling down of linewidths, which dictates SEM imaging with less scanning frames to reduce specimen damage and hence with more noise. During the last decade, it has been shown that image noise can be an important budget of the measured LER while systematically affects and alter the PSD curve of LER at high frequencies. A recent method for unbiased LER measurement is based on the systematic Fourier or correlation analysis to decompose the effects of noise from true LER (Fourier-Correlation filtering method). The success of the method depends on the PSD and HHCF curve. Previous experimental and model works have revealed that etch transfer affects the PSD of LER reducing its high frequency values. In this work, we estimate the noise contribution to the biased LER through PSD flat floor at high frequencies and relate it with the differences between the PSDs of lithography and etched LER. Based on this comparison, we propose an improvement of the PSD/HHCF-based method for noise-free LER measurement to include the missed high frequency real LER. The second issue is related with the increased density of lithographic patterns and the special characteristics of DSA and MP lithography patterns exhibits. In a previous work, we presented an enlarged LER characterization methodology for such patterns, which includes updated versions of the old metrics along with new metrics defined and developed to capture cross-edge and cross-line correlations. The fundamental concept has been the Line Center Roughness (LCR), the edge c-factor and the line c-factor correlation function and length quantifying the line fluctuations and the extent of cross-edge and cross-line correlations. In this work, we focus on the role of etch steps on cross-edge and line correlation metrics in SAQP data. We find that the spacer etch steps reduce edge correlations while etch steps with pattern transfer increase these. Furthermore, the density doubling and quadrupling increase edge correlations as well as cross-line correlations.
NASA Astrophysics Data System (ADS)
Wang, Duan; Podobnik, Boris; Horvatić, Davor; Stanley, H. Eugene
2011-04-01
We propose a modified time lag random matrix theory in order to study time-lag cross correlations in multiple time series. We apply the method to 48 world indices, one for each of 48 different countries. We find long-range power-law cross correlations in the absolute values of returns that quantify risk, and find that they decay much more slowly than cross correlations between the returns. The magnitude of the cross correlations constitutes “bad news” for international investment managers who may believe that risk is reduced by diversifying across countries. We find that when a market shock is transmitted around the world, the risk decays very slowly. We explain these time-lag cross correlations by introducing a global factor model (GFM) in which all index returns fluctuate in response to a single global factor. For each pair of individual time series of returns, the cross correlations between returns (or magnitudes) can be modeled with the autocorrelations of the global factor returns (or magnitudes). We estimate the global factor using principal component analysis, which minimizes the variance of the residuals after removing the global trend. Using random matrix theory, a significant fraction of the world index cross correlations can be explained by the global factor, which supports the utility of the GFM. We demonstrate applications of the GFM in forecasting risks at the world level, and in finding uncorrelated individual indices. We find ten indices that are practically uncorrelated with the global factor and with the remainder of the world indices, which is relevant information for world managers in reducing their portfolio risk. Finally, we argue that this general method can be applied to a wide range of phenomena in which time series are measured, ranging from seismology and physiology to atmospheric geophysics.
Wang, Duan; Podobnik, Boris; Horvatić, Davor; Stanley, H Eugene
2011-04-01
We propose a modified time lag random matrix theory in order to study time-lag cross correlations in multiple time series. We apply the method to 48 world indices, one for each of 48 different countries. We find long-range power-law cross correlations in the absolute values of returns that quantify risk, and find that they decay much more slowly than cross correlations between the returns. The magnitude of the cross correlations constitutes "bad news" for international investment managers who may believe that risk is reduced by diversifying across countries. We find that when a market shock is transmitted around the world, the risk decays very slowly. We explain these time-lag cross correlations by introducing a global factor model (GFM) in which all index returns fluctuate in response to a single global factor. For each pair of individual time series of returns, the cross correlations between returns (or magnitudes) can be modeled with the autocorrelations of the global factor returns (or magnitudes). We estimate the global factor using principal component analysis, which minimizes the variance of the residuals after removing the global trend. Using random matrix theory, a significant fraction of the world index cross correlations can be explained by the global factor, which supports the utility of the GFM. We demonstrate applications of the GFM in forecasting risks at the world level, and in finding uncorrelated individual indices. We find ten indices that are practically uncorrelated with the global factor and with the remainder of the world indices, which is relevant information for world managers in reducing their portfolio risk. Finally, we argue that this general method can be applied to a wide range of phenomena in which time series are measured, ranging from seismology and physiology to atmospheric geophysics.
Damage detection of structures with detrended fluctuation and detrended cross-correlation analyses
NASA Astrophysics Data System (ADS)
Lin, Tzu-Kang; Fajri, Haikal
2017-03-01
Recently, fractal analysis has shown its potential for damage detection and assessment in fields such as biomedical and mechanical engineering. For its practicability in interpreting irregular, complex, and disordered phenomena, a structural health monitoring (SHM) system based on detrended fluctuation analysis (DFA) and detrended cross-correlation analysis (DCCA) is proposed. First, damage conditions can be swiftly detected by evaluating ambient vibration signals measured from a structure through DFA. Damage locations can then be determined by analyzing the cross correlation of signals of different floors by applying DCCA. A damage index is also proposed based on multi-scale DCCA curves to improve the damage location accuracy. To verify the performance of the proposed SHM system, a four-story numerical model was used to simulate various damage conditions with different noise levels. Furthermore, an experimental verification was conducted on a seven-story benchmark structure to assess the potential damage. The results revealed that the DFA method could detect the damage conditions satisfactorily, and damage locations can be identified through the DCCA method with an accuracy of 75%. Moreover, damage locations can be correctly assessed by the damage index method with an improved accuracy of 87.5%. The proposed SHM system has promising application in practical implementations.
Long-term correlations and cross-correlations in IBovespa and constituent companies
NASA Astrophysics Data System (ADS)
de Lima, Neílson F.; Fernandes, Leonardo H. S.; Jale, Jader S.; de Mattos Neto, Paulo S. G.; Stošić, Tatijana; Stošić, Borko; Ferreira, Tiago A. E.
2018-02-01
We study auto-correlations and cross-correlations of IBovespa index and its constituent companies. We use Detrended Fluctuation Analysis (DFA) to quantify auto-correlations and Detrended Cross-Correlation Analysis (DCCA) to quantify cross-correlations in absolute returns of daily closing prices of IBovespa and the individual companies. We find persistent long-term correlations and cross-correlations which are weaker than those found for USA market. Our results indicate that market indices of developing markets exhibit weaker coupling with its constituents than for mature developed markets.
Detrended cross-correlation analysis on RMB exchange rate and Hang Seng China Enterprises Index
NASA Astrophysics Data System (ADS)
Ruan, Qingsong; Yang, Bingchan; Ma, Guofeng
2017-02-01
In this paper, we investigate the cross-correlations between the Hang Seng China Enterprises Index and RMB exchange markets on the basis of a cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). MF-DCCA has, at best, serious limitations for most of the signals describing complex natural processes and often indicates multifractal cross-correlations when there are none. In order to prevent these false multifractal cross-correlations, we apply MFCCA to verify the cross-correlations. Qualitatively, we find that the return series of the Hang Seng China Enterprises Index and RMB exchange markets were, overall, significantly cross-correlated based on the statistical analysis. Quantitatively, we find that the cross-correlations between the stock index and RMB exchange markets were strongly multifractal, and the multifractal degree of the onshore RMB exchange markets was somewhat larger than the offshore RMB exchange markets. Moreover, we use the absolute return series to investigate and confirm the fact of multifractality. The results from the rolling windows show that the short-term cross-correlations between volatility series remain high.
The effects of common risk factors on stock returns: A detrended cross-correlation analysis
NASA Astrophysics Data System (ADS)
Ruan, Qingsong; Yang, Bingchan
2017-10-01
In this paper, we investigate the cross-correlations between Fama and French three factors and the return of American industries on the basis of cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). Qualitatively, we find that the return series of Fama and French three factors and American industries were overall significantly cross-correlated based on the analysis of a statistic. Quantitatively, we find that the cross-correlations between three factors and the return of American industries were strongly multifractal, and applying MF-DCCA we also investigate the cross-correlation of industry returns and residuals. We find that there exists multifractality of industry returns and residuals. The result of correlation coefficients we can verify that there exist other factors which influence the industry returns except Fama three factors.
Taghva, Alexander; Song, Dong; Hampson, Robert E.; Deadwyler, Sam A.; Berger, Theodore W.
2013-01-01
BACKGROUND Identification of functional dependence among neurons is a necessary component in both the rational design of neural prostheses as well as in the characterization of network physiology. The objective of this article is to provide a tutorial for neurosurgeons regarding information theory, specifically time-delayed mutual information, and to compare time-delayed mutual information, an information theoretic quantity based on statistical dependence, with cross-correlation, a commonly used metric for this task in a preliminary analysis of rat hippocampal neurons. METHODS Spike trains were recorded from rats performing delayed nonmatch-to-sample task using an array of electrodes surgically implanted into the hippocampus of each hemisphere of the brain. In addition, spike train simulations of positively correlated neurons, negatively correlated neurons, and neurons correlated by nonlinear functions were generated. These were evaluated by time-delayed mutual information (MI) and cross-correlation. RESULTS Application of time-delayed MI to experimental data indicated the optimal bin size for information capture in the CA3-CA1 system was 40 ms, which may provide some insight into the spatiotemporal nature of encoding in the rat hippocampus. On simulated data, time-delayed MI showed peak values at appropriate time lags in positively correlated, negatively correlated, and complexly correlated data. Cross-correlation showed peak and troughs with positively correlated and negatively correlated data, but failed to capture some higher order correlations. CONCLUSIONS Comparison of time-delayed MI to cross-correlation in identification of functionally dependent neurons indicates that the methods are not equivalent. Time-delayed MI appeared to capture some interactions between CA3-CA1 neurons at physiologically plausible time delays missed by cross-correlation. It should be considered as a method for identification of functional dependence between neurons and may be useful in the development of neural prosthetics. PMID:22120279
NASA Astrophysics Data System (ADS)
Huerta, F. V.; Granados, I.; Aguirre, J.; Carrera, R. Á.
2017-12-01
Nowadays, in hydrocarbon industry, there is a need to optimize and reduce exploration costs in the different types of reservoirs, motivating the community specialized in the search and development of alternative exploration geophysical methods. This study show the reflection response obtained from a shale gas / oil deposit through the method of seismic interferometry of ambient vibrations in combination with Wavelet analysis and conventional seismic reflection techniques (CMP & NMO). The method is to generate seismic responses from virtual sources through the process of cross-correlation of records of Ambient Seismic Vibrations (ASV), collected in different receivers. The seismic response obtained is interpreted as the response that would be measured in one of the receivers considering a virtual source in the other. The acquisition of ASV records was performed in northern of Mexico through semi-rectangular arrays of multi-component geophones with instrumental response of 10 Hz. The in-line distance between geophones was 40 m while in cross-line was 280 m, the sampling used during the data collection was 2 ms and the total duration of the records was 6 hours. The results show the reflection response of two lines in the in-line direction and two in the cross-line direction for which the continuity of coherent events have been identified and interpreted as reflectors. There is certainty that the events identified correspond to reflections because the time-frequency analysis performed with the Wavelet Transform has allowed to identify the frequency band in which there are body waves. On the other hand, the CMP and NMO techniques have allowed to emphasize and correct the reflection response obtained during the correlation processes in the frequency band of interest. The results of the processing and analysis of ASV records through the seismic interferometry method have allowed us to see interesting results in light of the cross-correlation process in combination with the Wavelet analysis and conventional seismic reflection techniques. Therefore it was possible to recover the seismic response on each analyzed source-receiver pair, allowing us to obtain the reflection response of each analyzed seismic line.
Cross-correlations between RMB exchange rate and international commodity markets
NASA Astrophysics Data System (ADS)
Lu, Xinsheng; Li, Jianfeng; Zhou, Ying; Qian, Yubo
2017-11-01
This paper employs multifractal detrended analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DCCA) to study cross-correlation behaviors between China's RMB exchange rate market and four international commodity markets, using a comprehensive set of data covering the period from 22 July 2005 to 15 March 2016. Our empirical results from MF-DFA indicate that the RMB exchange rate is the most inefficient among the 4 selected markets. The results from quantitative analysis have testified the existence of cross-correlations and the result from MF-DCCA have further confirmed a strong multifractal behavior between RMB exchange rate and international commodity markets. We also demonstrate that the recent financial crisis has significant impact on the cross-correlated behavior. Through the rolling window analysis, we find that the RMB exchange rates and international commodity prices are anti-persistent cross-correlated. The main sources of multifractality in the cross-correlations are long-range correlations between RMB exchange rate and the aggregate commodity, energy and metals index.
Self spectrum window method in wigner-ville distribution.
Liu, Zhongguo; Liu, Changchun; Liu, Boqiang; Lv, Yangsheng; Lei, Yinsheng; Yu, Mengsun
2005-01-01
Wigner-Ville distribution (WVD) is an important type of time-frequency analysis in biomedical signal processing. The cross-term interference in WVD has a disadvantageous influence on its application. In this research, the Self Spectrum Window (SSW) method was put forward to suppress the cross-term interference, based on the fact that the cross-term and auto-WVD- terms in integral kernel function are orthogonal. With the Self Spectrum Window (SSW) algorithm, a real auto-WVD function was used as a template to cross-correlate with the integral kernel function, and the Short Time Fourier Transform (STFT) spectrum of the signal was used as window function to process the WVD in time-frequency plane. The SSW method was confirmed by computer simulation with good analysis results. Satisfactory time- frequency distribution was obtained.
NASA Astrophysics Data System (ADS)
Cristescu, Constantin P.; Stan, Cristina; Scarlat, Eugen I.; Minea, Teofil; Cristescu, Cristina M.
2012-04-01
We present a novel method for the parameter oriented analysis of mutual correlation between independent time series or between equivalent structures such as ordered data sets. The proposed method is based on the sliding window technique, defines a new type of correlation measure and can be applied to time series from all domains of science and technology, experimental or simulated. A specific parameter that can characterize the time series is computed for each window and a cross correlation analysis is carried out on the set of values obtained for the time series under investigation. We apply this method to the study of some currency daily exchange rates from the point of view of the Hurst exponent and the intermittency parameter. Interesting correlation relationships are revealed and a tentative crisis prediction is presented.
Decomposition of Proteins into Dynamic Units from Atomic Cross-Correlation Functions.
Calligari, Paolo; Gerolin, Marco; Abergel, Daniel; Polimeno, Antonino
2017-01-10
In this article, we present a clustering method of atoms in proteins based on the analysis of the correlation times of interatomic distance correlation functions computed from MD simulations. The goal is to provide a coarse-grained description of the protein in terms of fewer elements that can be treated as dynamically independent subunits. Importantly, this domain decomposition method does not take into account structural properties of the protein. Instead, the clustering of protein residues in terms of networks of dynamically correlated domains is defined on the basis of the effective correlation times of the pair distance correlation functions. For these properties, our method stands as a complementary analysis to the customary protein decomposition in terms of quasi-rigid, structure-based domains. Results obtained for a prototypal protein structure illustrate the approach proposed.
NASA Astrophysics Data System (ADS)
Ceffa, Nicolo G.; Cesana, Ilaria; Collini, Maddalena; D'Alfonso, Laura; Carra, Silvia; Cotelli, Franco; Sironi, Laura; Chirico, Giuseppe
2017-10-01
Ramification of blood circulation is relevant in a number of physiological and pathological conditions. The oxygen exchange occurs largely in the capillary bed, and the cancer progression is closely linked to the angiogenesis around the tumor mass. Optical microscopy has made impressive improvements in in vivo imaging and dynamic studies based on correlation analysis of time stacks of images. Here, we develop and test advanced methods that allow mapping the flow fields in branched vessel networks at the resolution of 10 to 20 μm. The methods, based on the application of spatiotemporal image correlation spectroscopy and its extension to cross-correlation analysis, are applied here to the case of early stage embryos of zebrafish.
ERIC Educational Resources Information Center
Sussman, Joshua; Beaujean, A. Alexander; Worrell, Frank C.; Watson, Stevie
2013-01-01
Item response models (IRMs) were used to analyze Cross Racial Identity Scale (CRIS) scores. Rasch analysis scores were compared with classical test theory (CTT) scores. The partial credit model demonstrated a high goodness of fit and correlations between Rasch and CTT scores ranged from 0.91 to 0.99. CRIS scores are supported by both methods.…
Tracking Image Correlation: Combining Single-Particle Tracking and Image Correlation
Dupont, A.; Stirnnagel, K.; Lindemann, D.; Lamb, D.C.
2013-01-01
The interactions and coordination of biomolecules are crucial for most cellular functions. The observation of protein interactions in live cells may provide a better understanding of the underlying mechanisms. After fluorescent labeling of the interacting partners and live-cell microscopy, the colocalization is generally analyzed by quantitative global methods. Recent studies have addressed questions regarding the individual colocalization of moving biomolecules, usually by using single-particle tracking (SPT) and comparing the fluorescent intensities in both color channels. Here, we introduce a new method that combines SPT and correlation methods to obtain a dynamical 3D colocalization analysis along single trajectories of dual-colored particles. After 3D tracking, the colocalization is computed at each particle’s position via the local 3D image cross correlation of the two detection channels. For every particle analyzed, the output consists of the 3D trajectory, the time-resolved 3D colocalization information, and the fluorescence intensity in both channels. In addition, the cross-correlation analysis shows the 3D relative movement of the two fluorescent labels with an accuracy of 30 nm. We apply this method to the tracking of viral fusion events in live cells and demonstrate its capacity to obtain the time-resolved colocalization status of single particles in dense and noisy environments. PMID:23746509
Digital processing of array seismic recordings
Ryall, Alan; Birtill, John
1962-01-01
This technical letter contains a brief review of the operations which are involved in digital processing of array seismic recordings by the methods of velocity filtering, summation, cross-multiplication and integration, and by combinations of these operations (the "UK Method" and multiple correlation). Examples are presented of analyses by the several techniques on array recordings which were obtained by the U.S. Geological Survey during chemical and nuclear explosions in the western United States. Seismograms are synthesized using actual noise and Pn-signal recordings, such that the signal-to-noise ratio, onset time and velocity of the signal are predetermined for the synthetic record. These records are then analyzed by summation, cross-multiplication, multiple correlation and the UK technique, and the results are compared. For all of the examples presented, analysis by the non-linear techniques of multiple correlation and cross-multiplication of the traces on an array recording are preferred to analyses by the linear operations involved in summation and the UK Method.
Cross-correlations between crude oil and exchange markets for selected oil rich economies
NASA Astrophysics Data System (ADS)
Li, Jianfeng; Lu, Xinsheng; Zhou, Ying
2016-07-01
Using multifractal detrended cross-correlation analysis (MF-DCCA), this paper studies the cross-correlation behavior between crude oil market and five selected exchange rate markets. The dataset covers the period of January 1,1996-December 31,2014, and contains 4,633 observations for each of the series, including daily closing prices of crude oil, Australian Dollars, Canadian Dollars, Mexican Pesos, Russian Rubles, and South African Rand. Our empirical results obtained from cross-correlation statistic and cross-correlation coefficient have confirmed the existence of cross-correlations, and the MF-DCCA results have demonstrated a strong multifractality between cross-correlated crude oil market and exchange rate markets in both short term and long term. Using rolling window analysis, we have also found the persistent cross-correlations between the exchange rates and crude oil returns, and the cross-correlation scaling exponents exhibit volatility during some time periods due to its sensitivity to sudden events.
Numerical determination of lateral loss coefficients for subchannel analysis in nuclear fuel bundles
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sin Kim; Goon-Cherl Park
1995-09-01
An accurate prediction of cross-flow based on detailed knowledge of the velocity field in subchannels of a nuclear fuel assembly is of importance in nuclear fuel performance analysis. In this study, the low-Reynolds number {kappa}-{epsilon} turbulence model has been adopted in two adjacent subchannels with cross-flow. The secondary flow is estimated accurately by the anisotropic algebraic Reynolds stress model. This model was numerically calculated by the finite element method and has been verified successfully through comparison with existing experimental data. Finally, with the numerical analysis of the velocity field in such subchannel domain, an analytical correlation of the lateral lossmore » coefficient is obtained to predict the cross-flow rate in subchannel analysis codes. The correlation is expressed as a function of the ratio of the lateral flow velocity to the donor subchannel axial velocity, recipient channel Reynolds number and pitch-to-diameter.« less
NASA Astrophysics Data System (ADS)
Zhuang, Xiaoyang; Wei, Yu; Ma, Feng
2015-07-01
In this paper, the multifractality and efficiency degrees of ten important Chinese sectoral indices are evaluated using the methods of MF-DFA and generalized Hurst exponents. The study also scrutinizes the dynamics of the efficiency of Chinese sectoral stock market by the rolling window approach. The overall empirical findings revealed that all the sectoral indices of Chinese stock market exist different degrees of multifractality. The results of different efficiency measures have agreed on that the 300 Materials index is the least efficient index. However, they have a slight diffidence on the most efficient one. The 300 Information Technology, 300 Telecommunication Services and 300 Health Care indices are comparatively efficient. We also investigate the cross-correlations between the ten sectoral indices and WTI crude oil price based on Multifractal Detrended Cross-correlation Analysis. At last, some relevant discussions and implications of the empirical results are presented.
NASA Astrophysics Data System (ADS)
Li, Zuhe; Fan, Yangyu; Liu, Weihua; Yu, Zeqi; Wang, Fengqin
2017-01-01
We aim to apply sparse autoencoder-based unsupervised feature learning to emotional semantic analysis for textile images. To tackle the problem of limited training data, we present a cross-domain feature learning scheme for emotional textile image classification using convolutional autoencoders. We further propose a correlation-analysis-based feature selection method for the weights learned by sparse autoencoders to reduce the number of features extracted from large size images. First, we randomly collect image patches on an unlabeled image dataset in the source domain and learn local features with a sparse autoencoder. We then conduct feature selection according to the correlation between different weight vectors corresponding to the autoencoder's hidden units. We finally adopt a convolutional neural network including a pooling layer to obtain global feature activations of textile images in the target domain and send these global feature vectors into logistic regression models for emotional image classification. The cross-domain unsupervised feature learning method achieves 65% to 78% average accuracy in the cross-validation experiments corresponding to eight emotional categories and performs better than conventional methods. Feature selection can reduce the computational cost of global feature extraction by about 50% while improving classification performance.
Nauleau, Pierre; Apostolakis, Iason; McGarry, Matthew; Konofagou, Elisa
2018-05-29
The stiffness of the arteries is known to be an indicator of the progression of various cardiovascular diseases. Clinically, the pulse wave velocity (PWV) is used as a surrogate for arterial stiffness. Pulse wave imaging (PWI) is a non-invasive, ultrasound-based imaging technique capable of mapping the motion of the vessel walls, allowing the local assessment of arterial properties. Conventionally, a distinctive feature of the displacement wave (e.g. the 50% upstroke) is tracked across the map to estimate the PWV. However, the presence of reflections, such as those generated at the carotid bifurcation, can bias the PWV estimation. In this paper, we propose a two-step cross-correlation based method to characterize arteries using the information available in the PWI spatio-temporal map. First, the area under the cross-correlation curve is proposed as an index for locating the regions of different properties. Second, a local peak of the cross-correlation function is tracked to obtain a less biased estimate of the PWV. Three series of experiments were conducted in phantoms to evaluate the capabilities of the proposed method compared with the conventional method. In the ideal case of a homogeneous phantom, the two methods performed similarly and correctly estimated the PWV. In the presence of reflections, the proposed method provided a more accurate estimate than conventional processing: e.g. for the soft phantom, biases of -0.27 and -0.71 m · s -1 were observed. In a third series of experiments, the correlation-based method was able to locate two regions of different properties with an error smaller than 1 mm. It also provided more accurate PWV estimates than conventional processing (biases: -0.12 versus -0.26 m · s -1 ). Finally, the in vivo feasibility of the proposed method was demonstrated in eleven healthy subjects. The results indicate that the correlation-based method might be less precise in vivo but more accurate than the conventional method.
Pickering, Ethan M; Hossain, Mohammad A; Mousseau, Jack P; Swanson, Rachel A; French, Roger H; Abramson, Alexis R
2017-01-01
Current approaches to building efficiency diagnoses include conventional energy audit techniques that can be expensive and time consuming. In contrast, virtual energy audits of readily available 15-minute-interval building electricity consumption are being explored to provide quick, inexpensive, and useful insights into building operation characteristics. A cross sectional analysis of six buildings in two different climate zones provides methods for data cleaning, population-based building comparisons, and relationships (correlations) of weather and electricity consumption. Data cleaning methods have been developed to categorize and appropriately filter or correct anomalous data including outliers, missing data, and erroneous values (resulting in < 0.5% anomalies). The utility of a cross-sectional analysis of a sample set of building's electricity consumption is found through comparisons of baseload, daily consumption variance, and energy use intensity. Correlations of weather and electricity consumption 15-minute interval datasets show important relationships for the heating and cooling seasons using computed correlations of a Time-Specific-Averaged-Ordered Variable (exterior temperature) and corresponding averaged variables (electricity consumption)(TSAOV method). The TSAOV method is unique as it introduces time of day as a third variable while also minimizing randomness in both correlated variables through averaging. This study found that many of the pair-wise linear correlation analyses lacked strong relationships, prompting the development of the new TSAOV method to uncover the causal relationship between electricity and weather. We conclude that a combination of varied HVAC system operations, building thermal mass, plug load use, and building set point temperatures are likely responsible for the poor correlations in the prior studies, while the correlation of time-specific-averaged-ordered temperature and corresponding averaged variables method developed herein adequately accounts for these issues and enables discovery of strong linear pair-wise correlation R values. TSAOV correlations lay the foundation for a new approach to building studies, that mitigates plug load interferences and identifies more accurate insights into weather-energy relationship for all building types. Over all six buildings analyzed the TSAOV method reported very significant average correlations per building of 0.94 to 0.82 in magnitude. Our rigorous statistics-based methods applied to 15-minute-interval electricity data further enables virtual energy audits of buildings to quickly and inexpensively inform energy savings measures.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pickering, Ethan M.; Hossain, Mohammad A.; Mousseau, Jack P.
Current approaches to building efficiency diagnoses include conventional energy audit techniques that can be expensive and time consuming. In contrast, virtual energy audits of readily available 15-minute-interval building electricity consumption are being explored to provide quick, inexpensive, and useful insights into building operation characteristics. A cross sectional analysis of six buildings in two different climate zones provides methods for data cleaning, population-based building comparisons, and relationships (correlations) of weather and electricity consumption. Data cleaning methods have been developed to categorize and appropriately filter or correct anomalous data including outliers, missing data, and erroneous values (resulting in < 0.5% anomalies). Themore » utility of a cross-sectional analysis of a sample set of building's electricity consumption is found through comparisons of baseload, daily consumption variance, and energy use intensity. Correlations of weather and electricity consumption 15-minute interval datasets show important relationships for the heating and cooling seasons using computed correlations of a Time-Specific-Averaged- Ordered Variable (exterior temperature) and corresponding averaged variables (electricity consumption)(TSAOV method). The TSAOV method is unique as it introduces time of day as a third variable while also minimizing randomness in both correlated variables through averaging. This study found that many of the pair-wise linear correlation analyses lacked strong relationships, prompting the development of the new TSAOV method to uncover the causal relationship between electricity and weather. We conclude that a combination of varied HVAC system operations, building thermal mass, plug load use, and building set point temperatures are likely responsible for the poor correlations in the prior studies, while the correlation of time-specific-averaged-ordered temperature and corresponding averaged variables method developed herein adequately accounts for these issues and enables discovery of strong linear pair-wise correlation R values. TSAOV correlations lay the foundation for a new approach to building studies, that mitigates plug load interferences and identifies more accurate insights into weather-energy relationship for all building types. Over all six buildings analyzed the TSAOV method reported very significant average correlations per building of 0.94 to 0.82 in magnitude. Our rigorous statistics-based methods applied to 15- minute-interval electricity data further enables virtual energy audits of buildings to quickly and inexpensively inform energy savings measures.« less
Pickering, Ethan M.; Hossain, Mohammad A.; Mousseau, Jack P.; ...
2017-10-31
Current approaches to building efficiency diagnoses include conventional energy audit techniques that can be expensive and time consuming. In contrast, virtual energy audits of readily available 15-minute-interval building electricity consumption are being explored to provide quick, inexpensive, and useful insights into building operation characteristics. A cross sectional analysis of six buildings in two different climate zones provides methods for data cleaning, population-based building comparisons, and relationships (correlations) of weather and electricity consumption. Data cleaning methods have been developed to categorize and appropriately filter or correct anomalous data including outliers, missing data, and erroneous values (resulting in < 0.5% anomalies). Themore » utility of a cross-sectional analysis of a sample set of building's electricity consumption is found through comparisons of baseload, daily consumption variance, and energy use intensity. Correlations of weather and electricity consumption 15-minute interval datasets show important relationships for the heating and cooling seasons using computed correlations of a Time-Specific-Averaged- Ordered Variable (exterior temperature) and corresponding averaged variables (electricity consumption)(TSAOV method). The TSAOV method is unique as it introduces time of day as a third variable while also minimizing randomness in both correlated variables through averaging. This study found that many of the pair-wise linear correlation analyses lacked strong relationships, prompting the development of the new TSAOV method to uncover the causal relationship between electricity and weather. We conclude that a combination of varied HVAC system operations, building thermal mass, plug load use, and building set point temperatures are likely responsible for the poor correlations in the prior studies, while the correlation of time-specific-averaged-ordered temperature and corresponding averaged variables method developed herein adequately accounts for these issues and enables discovery of strong linear pair-wise correlation R values. TSAOV correlations lay the foundation for a new approach to building studies, that mitigates plug load interferences and identifies more accurate insights into weather-energy relationship for all building types. Over all six buildings analyzed the TSAOV method reported very significant average correlations per building of 0.94 to 0.82 in magnitude. Our rigorous statistics-based methods applied to 15- minute-interval electricity data further enables virtual energy audits of buildings to quickly and inexpensively inform energy savings measures.« less
Hossain, Mohammad A.; Mousseau, Jack P.; Swanson, Rachel A.; French, Roger H.; Abramson, Alexis R.
2017-01-01
Current approaches to building efficiency diagnoses include conventional energy audit techniques that can be expensive and time consuming. In contrast, virtual energy audits of readily available 15-minute-interval building electricity consumption are being explored to provide quick, inexpensive, and useful insights into building operation characteristics. A cross sectional analysis of six buildings in two different climate zones provides methods for data cleaning, population-based building comparisons, and relationships (correlations) of weather and electricity consumption. Data cleaning methods have been developed to categorize and appropriately filter or correct anomalous data including outliers, missing data, and erroneous values (resulting in < 0.5% anomalies). The utility of a cross-sectional analysis of a sample set of building’s electricity consumption is found through comparisons of baseload, daily consumption variance, and energy use intensity. Correlations of weather and electricity consumption 15-minute interval datasets show important relationships for the heating and cooling seasons using computed correlations of a Time-Specific-Averaged-Ordered Variable (exterior temperature) and corresponding averaged variables (electricity consumption)(TSAOV method). The TSAOV method is unique as it introduces time of day as a third variable while also minimizing randomness in both correlated variables through averaging. This study found that many of the pair-wise linear correlation analyses lacked strong relationships, prompting the development of the new TSAOV method to uncover the causal relationship between electricity and weather. We conclude that a combination of varied HVAC system operations, building thermal mass, plug load use, and building set point temperatures are likely responsible for the poor correlations in the prior studies, while the correlation of time-specific-averaged-ordered temperature and corresponding averaged variables method developed herein adequately accounts for these issues and enables discovery of strong linear pair-wise correlation R values. TSAOV correlations lay the foundation for a new approach to building studies, that mitigates plug load interferences and identifies more accurate insights into weather-energy relationship for all building types. Over all six buildings analyzed the TSAOV method reported very significant average correlations per building of 0.94 to 0.82 in magnitude. Our rigorous statistics-based methods applied to 15-minute-interval electricity data further enables virtual energy audits of buildings to quickly and inexpensively inform energy savings measures. PMID:29088269
Frequency-phase analysis of resting-state functional MRI
Goelman, Gadi; Dan, Rotem; Růžička, Filip; Bezdicek, Ondrej; Růžička, Evžen; Roth, Jan; Vymazal, Josef; Jech, Robert
2017-01-01
We describe an analysis method that characterizes the correlation between coupled time-series functions by their frequencies and phases. It provides a unified framework for simultaneous assessment of frequency and latency of a coupled time-series. The analysis is demonstrated on resting-state functional MRI data of 34 healthy subjects. Interactions between fMRI time-series are represented by cross-correlation (with time-lag) functions. A general linear model is used on the cross-correlation functions to obtain the frequencies and phase-differences of the original time-series. We define symmetric, antisymmetric and asymmetric cross-correlation functions that correspond respectively to in-phase, 90° out-of-phase and any phase difference between a pair of time-series, where the last two were never introduced before. Seed maps of the motor system were calculated to demonstrate the strength and capabilities of the analysis. Unique types of functional connections, their dominant frequencies and phase-differences have been identified. The relation between phase-differences and time-delays is shown. The phase-differences are speculated to inform transfer-time and/or to reflect a difference in the hemodynamic response between regions that are modulated by neurotransmitters concentration. The analysis can be used with any coupled functions in many disciplines including electrophysiology, EEG or MEG in neuroscience. PMID:28272522
NASA Astrophysics Data System (ADS)
Huang, D.; Wang, G.
2014-12-01
Stochastic simulation of spatially distributed ground-motion time histories is important for performance-based earthquake design of geographically distributed systems. In this study, we develop a novel technique to stochastically simulate regionalized ground-motion time histories using wavelet packet analysis. First, a transient acceleration time history is characterized by wavelet-packet parameters proposed by Yamamoto and Baker (2013). The wavelet-packet parameters fully characterize ground-motion time histories in terms of energy content, time- frequency-domain characteristics and time-frequency nonstationarity. This study further investigates the spatial cross-correlations of wavelet-packet parameters based on geostatistical analysis of 1500 regionalized ground motion data from eight well-recorded earthquakes in California, Mexico, Japan and Taiwan. The linear model of coregionalization (LMC) is used to develop a permissible spatial cross-correlation model for each parameter group. The geostatistical analysis of ground-motion data from different regions reveals significant dependence of the LMC structure on regional site conditions, which can be characterized by the correlation range of Vs30 in each region. In general, the spatial correlation and cross-correlation of wavelet-packet parameters are stronger if the site condition is more homogeneous. Using the regional-specific spatial cross-correlation model and cokriging technique, wavelet packet parameters at unmeasured locations can be best estimated, and regionalized ground-motion time histories can be synthesized. Case studies and blind tests demonstrated that the simulated ground motions generally agree well with the actual recorded data, if the influence of regional-site conditions is considered. The developed method has great potential to be used in computational-based seismic analysis and loss estimation in a regional scale.
Bilenko, Natalia Y; Gallant, Jack L
2016-01-01
In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI) experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model.
Bilenko, Natalia Y.; Gallant, Jack L.
2016-01-01
In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI) experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model. PMID:27920675
NASA Astrophysics Data System (ADS)
Lee, Taesam
2018-05-01
Multisite stochastic simulations of daily precipitation have been widely employed in hydrologic analyses for climate change assessment and agricultural model inputs. Recently, a copula model with a gamma marginal distribution has become one of the common approaches for simulating precipitation at multiple sites. Here, we tested the correlation structure of the copula modeling. The results indicate that there is a significant underestimation of the correlation in the simulated data compared to the observed data. Therefore, we proposed an indirect method for estimating the cross-correlations when simulating precipitation at multiple stations. We used the full relationship between the correlation of the observed data and the normally transformed data. Although this indirect method offers certain improvements in preserving the cross-correlations between sites in the original domain, the method was not reliable in application. Therefore, we further improved a simulation-based method (SBM) that was developed to model the multisite precipitation occurrence. The SBM preserved well the cross-correlations of the original domain. The SBM method provides around 0.2 better cross-correlation than the direct method and around 0.1 degree better than the indirect method. The three models were applied to the stations in the Nakdong River basin, and the SBM was the best alternative for reproducing the historical cross-correlation. The direct method significantly underestimates the correlations among the observed data, and the indirect method appeared to be unreliable.
Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding
Tajima, Satohiro; Yanagawa, Toru; Fujii, Naotaka; Toyoizumi, Taro
2015-01-01
Brain-wide interactions generating complex neural dynamics are considered crucial for emergent cognitive functions. However, the irreducible nature of nonlinear and high-dimensional dynamical interactions challenges conventional reductionist approaches. We introduce a model-free method, based on embedding theorems in nonlinear state-space reconstruction, that permits a simultaneous characterization of complexity in local dynamics, directed interactions between brain areas, and how the complexity is produced by the interactions. We demonstrate this method in large-scale electrophysiological recordings from awake and anesthetized monkeys. The cross-embedding method captures structured interaction underlying cortex-wide dynamics that may be missed by conventional correlation-based analysis, demonstrating a critical role of time-series analysis in characterizing brain state. The method reveals a consciousness-related hierarchy of cortical areas, where dynamical complexity increases along with cross-area information flow. These findings demonstrate the advantages of the cross-embedding method in deciphering large-scale and heterogeneous neuronal systems, suggesting a crucial contribution by sensory-frontoparietal interactions to the emergence of complex brain dynamics during consciousness. PMID:26584045
NASA Astrophysics Data System (ADS)
Ghosh, Dipak; Dutta, Srimonti; Chakraborty, Sayantan
2015-09-01
This paper reports a study on the cross-correlation between the electric bid price and SENSEX using Multifractal Detrended Cross-correlation Analysis (MF-DXA). MF-DXA is a very rigorous and robust technique for assessment of cross-correction between two non-linear time series. The study reveals power law cross-correlation between Market Clearing Price (MCP) and SENSEX which suggests that a change in the value of one can create a subjective change in the value of the other.
Cross-correlations and influence in world gold markets
NASA Astrophysics Data System (ADS)
Lin, Min; Wang, Gang-Jin; Xie, Chi; Stanley, H. Eugene
2018-01-01
Using the detrended cross-correlation analysis (DCCA) coefficient and the detrended partial cross-correlation analysis (DPCCA) coefficient, we investigate cross-correlations and net cross-correlations among five major world gold markets (London, New York, Shanghai, Tokyo, and Mumbai) at different time scales. We propose multiscale influence measures for examining the influence of individual markets on other markets and on the entire system. We find (i) that the cross-correlations, net cross-correlations, and net influences among the five gold markets vary across time scales, (ii) that the cross-market correlation between London and New York at each time scale is intense and inherent, meaning that the influence of other gold markets on the London-New York market is negligible, (iii) that the remaining cross-market correlations (i.e., those other than London-New York) are greatly affected by other gold markets, and (iv) that the London gold market significantly affects the other four gold markets and dominates the world-wide gold market. Our multiscale findings give market participants and market regulators new information on cross-market linkages in the world-wide gold market.
Two-dimensional correlation spectroscopy — Biannual survey 2007-2009
NASA Astrophysics Data System (ADS)
Noda, Isao
2010-06-01
The publication activities in the field of 2D correlation spectroscopy are surveyed with the emphasis on papers published during the last two years. Pertinent review articles and conference proceedings are discussed first, followed by the examination of noteworthy developments in the theory and applications of 2D correlation spectroscopy. Specific topics of interest include Pareto scaling, analysis of randomly sampled spectra, 2D analysis of data obtained under multiple perturbations, evolution of 2D spectra along additional variables, comparison and quantitative analysis of multiple 2D spectra, orthogonal sample design to eliminate interfering cross peaks, quadrature orthogonal signal correction and other data transformation techniques, data pretreatment methods, moving window analysis, extension of kernel and global phase angle analysis, covariance and correlation coefficient mapping, variant forms of sample-sample correlation, and different display methods. Various static and dynamic perturbation methods used in 2D correlation spectroscopy, e.g., temperature, composition, chemical reactions, H/D exchange, physical phenomena like sorption, diffusion and phase transitions, optical and biological processes, are reviewed. Analytical probes used in 2D correlation spectroscopy include IR, Raman, NIR, NMR, X-ray, mass spectrometry, chromatography, and others. Application areas of 2D correlation spectroscopy are diverse, encompassing synthetic and natural polymers, liquid crystals, proteins and peptides, biomaterials, pharmaceuticals, food and agricultural products, solutions, colloids, surfaces, and the like.
Searches for correlation between UHECR events and high-energy gamma-ray Fermi-LAT data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Álvarez, Ezequiel; Cuoco, Alessandro; Mirabal, Nestor
The astrophysical sources responsible for ultra high-energy cosmic rays (UHECRs) continue to be one of the most intriguing mysteries in astrophysics. We present a comprehensive search for correlations between high-energy (∼> 1 GeV) gamma-ray events from the Fermi Large Area Telescope (LAT) and UHECRs (∼> 60 EeV) detected by the Telescope Array and the Pierre Auger Observatory. We perform two separate searches. First, we conduct a standard cross-correlation analysis between the arrival directions of 148 UHECRs and 360 gamma-ray sources in the Second Catalog of Hard Fermi-LAT sources (2FHL). Second, we search for a possible correlation between UHECR directions andmore » unresolved Fermi -LAT gamma-ray emission. For the latter, we use three different methods: a stacking technique with both a model-dependent and model-independent background estimate, and a cross-correlation function analysis. We also test for statistically significant excesses in gamma rays from signal regions centered on Cen A and the Telescope Array hotspot. No significant correlation is found in any of the analyses performed, except a weak (∼< 2σ) hint of signal with the correlation function method on scales ∼ 1°. Upper limits on the flux of possible power-law gamma-ray sources of UHECRs are derived.« less
Searches for correlation between UHECR events and high-energy gamma-ray Fermi-LAT data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Álvarez, Ezequiel; Cuoco, Alessandro; Mirabal, Nestor
The astrophysical sources responsible for ultra high-energy cosmic rays (UHECRs) continue to be one of the most intriguing mysteries in astrophysics. Here, we present a comprehensive search for correlations between high-energy (≳ 1 GeV) gamma-ray events from the Fermi Large Area Telescope (LAT) and UHECRs (≳ 60 EeV) detected by the Telescope Array and the Pierre Auger Observatory. We perform two separate searches. First, we conduct a standard cross-correlation analysis between the arrival directions of 148 UHECRs and 360 gamma-ray sources in the Second Catalog of Hard Fermi-LAT sources (2FHL). Second, we search for a possible correlation between UHECR directionsmore » and unresolved Fermi-LAT gamma-ray emission. For the latter, we use three different methods: a stacking technique with both a model-dependent and model-independent background estimate, and a cross-correlation function analysis. We also test for statistically significant excesses in gamma rays from signal regions centered on Cen A and the Telescope Array hotspot. There was no significant correlation is found in any of the analyses performed, except a weak (≲ 2σ) hint of signal with the correlation function method on scales ~ 1°. Upper limits on the flux of possible power-law gamma-ray sources of UHECRs are derived.« less
Searches for correlation between UHECR events and high-energy gamma-ray Fermi-LAT data
Álvarez, Ezequiel; Cuoco, Alessandro; Mirabal, Nestor; ...
2016-12-13
The astrophysical sources responsible for ultra high-energy cosmic rays (UHECRs) continue to be one of the most intriguing mysteries in astrophysics. Here, we present a comprehensive search for correlations between high-energy (≳ 1 GeV) gamma-ray events from the Fermi Large Area Telescope (LAT) and UHECRs (≳ 60 EeV) detected by the Telescope Array and the Pierre Auger Observatory. We perform two separate searches. First, we conduct a standard cross-correlation analysis between the arrival directions of 148 UHECRs and 360 gamma-ray sources in the Second Catalog of Hard Fermi-LAT sources (2FHL). Second, we search for a possible correlation between UHECR directionsmore » and unresolved Fermi-LAT gamma-ray emission. For the latter, we use three different methods: a stacking technique with both a model-dependent and model-independent background estimate, and a cross-correlation function analysis. We also test for statistically significant excesses in gamma rays from signal regions centered on Cen A and the Telescope Array hotspot. There was no significant correlation is found in any of the analyses performed, except a weak (≲ 2σ) hint of signal with the correlation function method on scales ~ 1°. Upper limits on the flux of possible power-law gamma-ray sources of UHECRs are derived.« less
NASA Technical Reports Server (NTRS)
Ni, Jianjun (David)
2012-01-01
This presentation discusses an analysis approach to evaluate the interuser interference for Direct-Sequence Spread-Spectrum (DSSS) Systems for Space Network (SN) Users. Part I of this analysis shows that the correlation property of pseudo noise (PN) sequences is the critical factor which determines the interuser interference performance of the DSSS system. For non-standard DSSS systems in which PN sequence s period is much larger than one data symbol duration, it is the partial-period cross-correlation that determines the system performance. This study reveals through an example that a well-designed PN sequence set (e.g. Gold Sequence, in which the cross-correlation for a whole-period is well controlled) may have non-controlled partial-period cross-correlation which could cause severe interuser interference for a DSSS system. Since the analytical derivation of performance metric (bit error rate or signal-to-noise ratio) based on partial-period cross-correlation is prohibitive, the performance degradation due to partial-period cross-correlation will be evaluated using simulation in Part II of this analysis in the future.
Taghva, Alexander; Song, Dong; Hampson, Robert E; Deadwyler, Sam A; Berger, Theodore W
2012-12-01
Identification of functional dependence among neurons is a necessary component in both the rational design of neural prostheses as well as in the characterization of network physiology. The objective of this article is to provide a tutorial for neurosurgeons regarding information theory, specifically time-delayed mutual information, and to compare time-delayed mutual information, an information theoretic quantity based on statistical dependence, with cross-correlation, a commonly used metric for this task in a preliminary analysis of rat hippocampal neurons. Spike trains were recorded from rats performing delayed nonmatch-to-sample task using an array of electrodes surgically implanted into the hippocampus of each hemisphere of the brain. In addition, spike train simulations of positively correlated neurons, negatively correlated neurons, and neurons correlated by nonlinear functions were generated. These were evaluated by time-delayed mutual information (MI) and cross-correlation. Application of time-delayed MI to experimental data indicated the optimal bin size for information capture in the CA3-CA1 system was 40 ms, which may provide some insight into the spatiotemporal nature of encoding in the rat hippocampus. On simulated data, time-delayed MI showed peak values at appropriate time lags in positively correlated, negatively correlated, and complexly correlated data. Cross-correlation showed peak and troughs with positively correlated and negatively correlated data, but failed to capture some higher order correlations. Comparison of time-delayed MI to cross-correlation in identification of functionally dependent neurons indicates that the methods are not equivalent. Time-delayed MI appeared to capture some interactions between CA3-CA1 neurons at physiologically plausible time delays missed by cross-correlation. It should be considered as a method for identification of functional dependence between neurons and may be useful in the development of neural prosthetics. Copyright © 2012 Elsevier Inc. All rights reserved.
Techniques for measurement of thoracoabdominal asynchrony
NASA Technical Reports Server (NTRS)
Prisk, G. Kim; Hammer, J.; Newth, Christopher J L.
2002-01-01
Respiratory motion measured by respiratory inductance plethysmography often deviates from the sinusoidal pattern assumed in the traditional Lissajous figure (loop) analysis used to determine thoraco-abdominal asynchrony, or phase angle phi. We investigated six different time-domain methods of measuring phi, using simulated data with sinusoidal and triangular waveforms, phase shifts of 0-135 degrees, and 10% noise. The techniques were then used on data from 11 lightly anesthetized rhesus monkeys (Macaca mulatta; 7.6 +/- 0.8 kg; 5.7 +/- 0.5 years old), instrumented with a respiratory inductive plethysmograph, and subjected to increasing levels of inspiratory resistive loading ranging from 5-1,000 cmH(2)O. L(-1). sec(-1).The best results were obtained from cross-correlation and maximum linear correlation, with errors less than approximately 5 degrees from the actual phase angle in the simulated data. The worst performance was produced by the loop analysis, which in some cases was in error by more than 30 degrees. Compared to correlation, other analysis techniques performed at an intermediate level. Maximum linear correlation and cross-correlation produced similar results on the data collected from monkeys (SD of the difference, 4.1 degrees ) but all other techniques had a high SD of the difference compared to the correlation techniques.We conclude that phase angles are best measured using cross-correlation or maximum linear correlation, techniques that are independent of waveform shape, and robust in the presence of noise. Copyright 2002 Wiley-Liss, Inc.
Hanson, Jeffery A; Yang, Haw
2008-11-06
The statistical properties of the cross correlation between two time series has been studied. An analytical expression for the cross correlation function's variance has been derived. On the basis of these results, a statistically robust method has been proposed to detect the existence and determine the direction of cross correlation between two time series. The proposed method has been characterized by computer simulations. Applications to single-molecule fluorescence spectroscopy are discussed. The results may also find immediate applications in fluorescence correlation spectroscopy (FCS) and its variants.
Robust Statistical Detection of Power-Law Cross-Correlation.
Blythe, Duncan A J; Nikulin, Vadim V; Müller, Klaus-Robert
2016-06-02
We show that widely used approaches in statistical physics incorrectly indicate the existence of power-law cross-correlations between financial stock market fluctuations measured over several years and the neuronal activity of the human brain lasting for only a few minutes. While such cross-correlations are nonsensical, no current methodology allows them to be reliably discarded, leaving researchers at greater risk when the spurious nature of cross-correlations is not clear from the unrelated origin of the time series and rather requires careful statistical estimation. Here we propose a theory and method (PLCC-test) which allows us to rigorously and robustly test for power-law cross-correlations, correctly detecting genuine and discarding spurious cross-correlations, thus establishing meaningful relationships between processes in complex physical systems. Our method reveals for the first time the presence of power-law cross-correlations between amplitudes of the alpha and beta frequency ranges of the human electroencephalogram.
Robust Statistical Detection of Power-Law Cross-Correlation
Blythe, Duncan A. J.; Nikulin, Vadim V.; Müller, Klaus-Robert
2016-01-01
We show that widely used approaches in statistical physics incorrectly indicate the existence of power-law cross-correlations between financial stock market fluctuations measured over several years and the neuronal activity of the human brain lasting for only a few minutes. While such cross-correlations are nonsensical, no current methodology allows them to be reliably discarded, leaving researchers at greater risk when the spurious nature of cross-correlations is not clear from the unrelated origin of the time series and rather requires careful statistical estimation. Here we propose a theory and method (PLCC-test) which allows us to rigorously and robustly test for power-law cross-correlations, correctly detecting genuine and discarding spurious cross-correlations, thus establishing meaningful relationships between processes in complex physical systems. Our method reveals for the first time the presence of power-law cross-correlations between amplitudes of the alpha and beta frequency ranges of the human electroencephalogram. PMID:27250630
Ahmed, Towfiq; Haraldsen, Jason T; Rehr, John J; Di Ventra, Massimiliano; Schuller, Ivan; Balatsky, Alexander V
2014-03-28
Nanopore-based sequencing has demonstrated a significant potential for the development of fast, accurate, and cost-efficient fingerprinting techniques for next generation molecular detection and sequencing. We propose a specific multilayered graphene-based nanopore device architecture for the recognition of single biomolecules. Molecular detection and analysis can be accomplished through the detection of transverse currents as the molecule or DNA base translocates through the nanopore. To increase the overall signal-to-noise ratio and the accuracy, we implement a new 'multi-point cross-correlation' technique for identification of DNA bases or other molecules on the single molecular level. We demonstrate that the cross-correlations between each nanopore will greatly enhance the transverse current signal for each molecule. We implement first-principles transport calculations for DNA bases surveyed across a multilayered graphene nanopore system to illustrate the advantages of the proposed geometry. A time-series analysis of the cross-correlation functions illustrates the potential of this method for enhancing the signal-to-noise ratio. This work constitutes a significant step forward in facilitating fingerprinting of single biomolecules using solid state technology.
Autocorrelation and cross-correlation in time series of homicide and attempted homicide
NASA Astrophysics Data System (ADS)
Machado Filho, A.; da Silva, M. F.; Zebende, G. F.
2014-04-01
We propose in this paper to establish the relationship between homicides and attempted homicides by a non-stationary time-series analysis. This analysis will be carried out by Detrended Fluctuation Analysis (DFA), Detrended Cross-Correlation Analysis (DCCA), and DCCA cross-correlation coefficient, ρ(n). Through this analysis we can identify a positive cross-correlation between homicides and attempted homicides. At the same time, looked at from the point of view of autocorrelation (DFA), this analysis can be more informative depending on time scale. For short scale (days), we cannot identify auto-correlations, on the scale of weeks DFA presents anti-persistent behavior, and for long time scales (n>90 days) DFA presents a persistent behavior. Finally, the application of this new type of statistical analysis proved to be efficient and, in this sense, this paper can contribute to a more accurate descriptive statistics of crime.
Cross correlation analysis of medium energy gamma rays for the Northern Hemisphere
NASA Technical Reports Server (NTRS)
Long, J.; Zanrosso, E.; Zych, A. D.; White, R. S.
1982-01-01
In the cross correlation method the observed gamma rays are compared with the expected telescope response for a discrete celestial source. The background consists of the atmospheric flux with its maximum near the horizon, the cosmic diffuse flux, and neutron induced gamma rays in the telescope. In sharp contrast to the background, a celestial source produces an asymmetric azimuthal response which varies predictably in time as the source moves through the telescope's aperture. This contrast serves as the basis of the cross correlation technique. Continuous data of 47.5 hr were obtained during a balloon flight from Palestine, TX from 0930 UT on September 30, 1978 to 2300 UT on October 1, 1978. The Crab Nebula-Anticenter region was observed on two consecutive days. A number of other medium energy source candidates also crossed the field-of-view. The obtained results are discussed.
NASA Astrophysics Data System (ADS)
Ma, Pengcheng; Li, Daye; Li, Shuo
2016-02-01
Using one minute high-frequency data of the Shanghai Composite Index (SHCI) and the Shenzhen Composite Index (SZCI) (2007-2008), we employ the detrended fluctuation analysis (DFA) and the detrended cross correlation analysis (DCCA) with rolling window approach to observe the evolution of market efficiency and cross-correlation in pre-crisis and crisis period. Considering the fat-tail distribution of return time series, statistical test based on shuffling method is conducted to verify the null hypothesis of no long-term dependence. Our empirical research displays three main findings. First Shanghai equity market efficiency deteriorated while Shenzhen equity market efficiency improved with the advent of financial crisis. Second the highly positive dependence between SHCI and SZCI varies with time scale. Third financial crisis saw a significant increase of dependence between SHCI and SZCI at shorter time scales but a lack of significant change at longer time scales, providing evidence of contagion and absence of interdependence during crisis.
Lamb, D C; Müller, B K; Bräuchle, C
2005-10-01
Fluorescence correlation spectroscopy (FCS) and fluorescence cross-correlation spectroscopy (FCCS) are methods that extract information about a sample from the influence of thermodynamic equilibrium fluctuations on the fluorescence intensity. This method allows dynamic information to be obtained from steady state equilibrium measurements and its popularity has dramatically increased in the last 10 years due to the development of high sensitivity detectors and its combination with confocal microscopy. Using time-correlated single-photon counting (TCSPC) detection and pulsed excitation, information over the duration of the excited state can be extracted and incorporated in the analysis. In this short review, we discuss new methodologies that have recently emerged which incorporated fluorescence lifetime information or TCSPC data in the FCS and FCCS analysis. Time-gated FCS discriminates between which photons are to be incorporated in the analysis dependent upon their arrival time after excitation. This allows for accurate FCS measurements in the presence of fluorescent background, determination of sample homogeneity, and the ability to distinguish between static and dynamic heterogeneities. A similar method, time-resolved FCS can be used to resolve the individual correlation functions from multiple fluorophores through the different fluorescence lifetimes. Pulsed interleaved excitation (PIE) encodes the excitation source into the TCSPC data. PIE can be used to perform dual-channel FCCS with a single detector and allows elimination of spectral cross-talk with dual-channel detection. For samples that undergo fluorescence resonance energy transfer (FRET), quantitative FCCS measurements can be performed in spite of the FRET and the static FRET efficiency can be determined.
Boker, Steven M; Xu, Minquan; Rotondo, Jennifer L; King, Kadijah
2002-09-01
Cross-correlation and most other longitudinal analyses assume that the association between 2 variables is stationary. Thus, a sample of occasions of measurement is expected to be representative of the association between variables regardless of the time of onset or number of occasions in the sample. The authors propose a method to analyze the association between 2 variables when the assumption of stationarity may not be warranted. The method results in estimates of both the strength of peak association and the time lag when the peak association occurred for a range of starting values of elapsed time from the beginning of an experiment.
Coherence Analysis of the Solar Wind Between l1 and the Lunar Orbit
NASA Astrophysics Data System (ADS)
Crane, S. O.; Fuqua, H.; Poppe, A. R.; Harada, Y.; Fatemi, S.; Delory, G. T.
2016-12-01
A cross correlation analysis of the lunar and solar wind interaction was performed to understand coherence length scales. This is mandatory for conducting tests in electromagnetic sounding of the moon with two measurement probes. Signal processing and data analysis methods encompass the study of the lunar electromagnetic plasma environment with properties of the solar wind at key positions outside of Earth's magnetosphere. Variations in solar activity detected by ACE, WIND, Kaguya and Lunar Prospector can be informative regarding how well correlated the magnetic properties of the solar wind are between the 1st Lagrange point (ACE & WIND orbits) and the lunar orbit (Kaguya & Lunar Prospector investigations). The analysis objective is to use cross correlation to understand the solar wind coherence between these positions. This requires mastering concrete analysis tools to filter and use data that yields high (>0.80) or intermediate (0.70-0.80) coherence values, while demonstrating an analysis of up to one month of data, and archiving poor (<0.50) cross correlation coefficients for effects of orbit position and downstream distance. We also consider the impact of high energy events such as Coronal Mass Ejections, Solar Flares, and shocks that may be recorded by `ACE's List of Disturbances and Transients' to the effect that, at the current level of analysis, various expected coefficients between 0.55 and 0.85 have been generated for up to 3 months of data, 2008-02-01 through 2008-05-03.
Game, Madhuri D.; Gabhane, K. B.; Sakarkar, D. M.
2010-01-01
A simple, accurate and precise spectrophotometric method has been developed for simultaneous estimation of clopidogrel bisulphate and aspirin by employing first order derivative zero crossing method. The first order derivative absorption at 232.5 nm (zero cross point of aspirin) was used for clopidogrel bisulphate and 211.3 nm (zero cross point of clopidogrel bisulphate) for aspirin.Both the drugs obeyed linearity in the concentration range of 5.0 μg/ml to 25.0 μg/ml (correlation coefficient r2<1). No interference was found between both determined constituents and those of matrix. The method was validated statistically and recovery studies were carried out to confirm the accuracy of the method. PMID:21969765
NASA Astrophysics Data System (ADS)
Nauleau, Pierre; Apostolakis, Iason; McGarry, Matthew; Konofagou, Elisa
2018-06-01
The stiffness of the arteries is known to be an indicator of the progression of various cardiovascular diseases. Clinically, the pulse wave velocity (PWV) is used as a surrogate for arterial stiffness. Pulse wave imaging (PWI) is a non-invasive, ultrasound-based imaging technique capable of mapping the motion of the vessel walls, allowing the local assessment of arterial properties. Conventionally, a distinctive feature of the displacement wave (e.g. the 50% upstroke) is tracked across the map to estimate the PWV. However, the presence of reflections, such as those generated at the carotid bifurcation, can bias the PWV estimation. In this paper, we propose a two-step cross-correlation based method to characterize arteries using the information available in the PWI spatio-temporal map. First, the area under the cross-correlation curve is proposed as an index for locating the regions of different properties. Second, a local peak of the cross-correlation function is tracked to obtain a less biased estimate of the PWV. Three series of experiments were conducted in phantoms to evaluate the capabilities of the proposed method compared with the conventional method. In the ideal case of a homogeneous phantom, the two methods performed similarly and correctly estimated the PWV. In the presence of reflections, the proposed method provided a more accurate estimate than conventional processing: e.g. for the soft phantom, biases of ‑0.27 and ‑0.71 m · s–1 were observed. In a third series of experiments, the correlation-based method was able to locate two regions of different properties with an error smaller than 1 mm. It also provided more accurate PWV estimates than conventional processing (biases: ‑0.12 versus ‑0.26 m · s–1). Finally, the in vivo feasibility of the proposed method was demonstrated in eleven healthy subjects. The results indicate that the correlation-based method might be less precise in vivo but more accurate than the conventional method.
NASA Technical Reports Server (NTRS)
Chambers, Jeffrey A.
1994-01-01
Finite element analysis is regularly used during the engineering cycle of mechanical systems to predict the response to static, thermal, and dynamic loads. The finite element model (FEM) used to represent the system is often correlated with physical test results to determine the validity of analytical results provided. Results from dynamic testing provide one means for performing this correlation. One of the most common methods of measuring accuracy is by classical modal testing, whereby vibratory mode shapes are compared to mode shapes provided by finite element analysis. The degree of correlation between the test and analytical mode shapes can be shown mathematically using the cross orthogonality check. A great deal of time and effort can be exhausted in generating the set of test acquired mode shapes needed for the cross orthogonality check. In most situations response data from vibration tests are digitally processed to generate the mode shapes from a combination of modal parameters, forcing functions, and recorded response data. An alternate method is proposed in which the same correlation of analytical and test acquired mode shapes can be achieved without conducting the modal survey. Instead a procedure is detailed in which a minimum of test information, specifically the acceleration response data from a random vibration test, is used to generate a set of equivalent local accelerations to be applied to the reduced analytical model at discrete points corresponding to the test measurement locations. The static solution of the analytical model then produces a set of deformations that once normalized can be used to represent the test acquired mode shapes in the cross orthogonality relation. The method proposed has been shown to provide accurate results for both a simple analytical model as well as a complex space flight structure.
Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations
NASA Astrophysics Data System (ADS)
Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław
2015-11-01
The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.
NASA Astrophysics Data System (ADS)
Max-Moerbeck, W.; Richards, J. L.; Hovatta, T.; Pavlidou, V.; Pearson, T. J.; Readhead, A. C. S.
2014-11-01
We present a practical implementation of a Monte Carlo method to estimate the significance of cross-correlations in unevenly sampled time series of data, whose statistical properties are modelled with a simple power-law power spectral density. This implementation builds on published methods; we introduce a number of improvements in the normalization of the cross-correlation function estimate and a bootstrap method for estimating the significance of the cross-correlations. A closely related matter is the estimation of a model for the light curves, which is critical for the significance estimates. We present a graphical and quantitative demonstration that uses simulations to show how common it is to get high cross-correlations for unrelated light curves with steep power spectral densities. This demonstration highlights the dangers of interpreting them as signs of a physical connection. We show that by using interpolation and the Hanning sampling window function we are able to reduce the effects of red-noise leakage and to recover steep simple power-law power spectral densities. We also introduce the use of a Neyman construction for the estimation of the errors in the power-law index of the power spectral density. This method provides a consistent way to estimate the significance of cross-correlations in unevenly sampled time series of data.
Ocean wavenumber estimation from wave-resolving time series imagery
Plant, N.G.; Holland, K.T.; Haller, M.C.
2008-01-01
We review several approaches that have been used to estimate ocean surface gravity wavenumbers from wave-resolving remotely sensed image sequences. Two fundamentally different approaches that utilize these data exist. A power spectral density approach identifies wavenumbers where image intensity variance is maximized. Alternatively, a cross-spectral correlation approach identifies wavenumbers where intensity coherence is maximized. We develop a solution to the latter approach based on a tomographic analysis that utilizes a nonlinear inverse method. The solution is tolerant to noise and other forms of sampling deficiency and can be applied to arbitrary sampling patterns, as well as to full-frame imagery. The solution includes error predictions that can be used for data retrieval quality control and for evaluating sample designs. A quantitative analysis of the intrinsic resolution of the method indicates that the cross-spectral correlation fitting improves resolution by a factor of about ten times as compared to the power spectral density fitting approach. The resolution analysis also provides a rule of thumb for nearshore bathymetry retrievals-short-scale cross-shore patterns may be resolved if they are about ten times longer than the average water depth over the pattern. This guidance can be applied to sample design to constrain both the sensor array (image resolution) and the analysis array (tomographic resolution). ?? 2008 IEEE.
Structure of a financial cross-correlation matrix under attack
NASA Astrophysics Data System (ADS)
Lim, Gyuchang; Kim, SooYong; Kim, Junghwan; Kim, Pyungsoo; Kang, Yoonjong; Park, Sanghoon; Park, Inho; Park, Sang-Bum; Kim, Kyungsik
2009-09-01
We investigate the structure of a perturbed stock market in terms of correlation matrices. For the purpose of perturbing a stock market, two distinct methods are used, namely local and global perturbation. The former involves replacing a correlation coefficient of the cross-correlation matrix with one calculated from two Gaussian-distributed time series while the latter reconstructs the cross-correlation matrix just after replacing the original return series with Gaussian-distributed time series. Concerning the local case, it is a technical study only and there is no attempt to model reality. The term ‘global’ means the overall effect of the replacement on other untouched returns. Through statistical analyses such as random matrix theory (RMT), network theory, and the correlation coefficient distributions, we show that the global structure of a stock market is vulnerable to perturbation. However, apart from in the analysis of inverse participation ratios (IPRs), the vulnerability becomes dull under a small-scale perturbation. This means that these analysis tools are inappropriate for monitoring the whole stock market due to the low sensitivity of a stock market to a small-scale perturbation. In contrast, when going down to the structure of business sectors, we confirm that correlation-based business sectors are regrouped in terms of IPRs. This result gives a clue about monitoring the effect of hidden intentions, which are revealed via portfolios taken mostly by large investors.
NASA Astrophysics Data System (ADS)
Hsiao, Y. R.; Tsai, C.
2017-12-01
As the WHO Air Quality Guideline indicates, ambient air pollution exposes world populations under threat of fatal symptoms (e.g. heart disease, lung cancer, asthma etc.), raising concerns of air pollution sources and relative factors. This study presents a novel approach to investigating the multiscale variations of PM2.5 in southern Taiwan over the past decade, with four meteorological influencing factors (Temperature, relative humidity, precipitation and wind speed),based on Noise-assisted Multivariate Empirical Mode Decomposition(NAMEMD) algorithm, Hilbert Spectral Analysis(HSA) and Time-dependent Intrinsic Correlation(TDIC) method. NAMEMD algorithm is a fully data-driven approach designed for nonlinear and nonstationary multivariate signals, and is performed to decompose multivariate signals into a collection of channels of Intrinsic Mode Functions (IMFs). TDIC method is an EMD-based method using a set of sliding window sizes to quantify localized correlation coefficients for multiscale signals. With the alignment property and quasi-dyadic filter bank of NAMEMD algorithm, one is able to produce same number of IMFs for all variables and estimates the cross correlation in a more accurate way. The performance of spectral representation of NAMEMD-HSA method is compared with Complementary Empirical Mode Decomposition/ Hilbert Spectral Analysis (CEEMD-HSA) and Wavelet Analysis. The nature of NAMAMD-based TDICC analysis is then compared with CEEMD-based TDIC analysis and the traditional correlation analysis.
Kim, Hugh I.; Kim, Hyungjun; Pang, Eric S.; Ryu, Ernest K.; Beegle, Luther W.; Loo, Joseph A.; Goddard, William A.; Kanik, Isik
2009-01-01
A number of phosphatidylcholine (PC) cations spanning a mass range of 400 to 1000 Da are investigated using electrospray ionization mass spectrometry coupled with traveling wave ion mobility spectrometry (TWIMS). A high correlation between mass and mobility is demonstrated with saturated phosphatidylcholine cations in N2. A significant deviation from this mass-mobility correlation line is observed for the unsaturated PC cation. We found that the double bond in the acyl chain causes a 5% reduction in drift time. The drift time is reduced at a rate of ~1% for each additional double bond. Theoretical collision cross sections of PC cations exhibit good agreement with experimentally evaluated values. Collision cross sections are determined using the recently derived relationship between mobility and drift time in TWIMS stacked ring ion guide (SRIG) and compared to estimate collision cross-sections using empiric calibration method. Computational analysis was performed using the modified trajectory (TJ) method with nonspherical N2 molecules as the drift gas. The difference between estimated collision cross-sections and theoretical collision cross-sections of PC cations is related to the sensitivity of the PC cation collision cross-sections to the details of the ion-neutral interactions. The origin of the observed correlation and deviation between mass and mobility of PC cations is discussed in terms of the structural rigidity of these molecules using molecular dynamic simulations. PMID:19764704
A New Method to Measure Crack Extension in Nuclear Graphite Based on Digital Image Correlation
Lai, Shigang; Shi, Li; Fok, Alex; ...
2017-01-01
Graphite components, used as moderators, reflectors, and core-support structures in a High-Temperature Gas-Cooled Reactor, play an important role in the safety of the reactor. Specifically, they provide channels for the fuel elements, control rods, and coolant flow. Fracture is the main failure mode for graphite, and breaching of the above channels by crack extension will seriously threaten the safety of a reactor. In this paper, a new method based on digital image correlation (DIC) is introduced for measuring crack extension in brittle materials. Cross-correlation of the displacements measured by DIC with a step function was employed to identify the advancingmore » crack tip in a graphite beam specimen under three-point bending. The load-crack extension curve, which is required for analyzing the R-curve and tension softening behaviors, was obtained for this material. Furthermore, a sensitivity analysis of the threshold value employed for the cross-correlation parameter in the crack identification process was conducted. Finally, the results were verified using the finite element method.« less
A New Method to Measure Crack Extension in Nuclear Graphite Based on Digital Image Correlation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lai, Shigang; Shi, Li; Fok, Alex
Graphite components, used as moderators, reflectors, and core-support structures in a High-Temperature Gas-Cooled Reactor, play an important role in the safety of the reactor. Specifically, they provide channels for the fuel elements, control rods, and coolant flow. Fracture is the main failure mode for graphite, and breaching of the above channels by crack extension will seriously threaten the safety of a reactor. In this paper, a new method based on digital image correlation (DIC) is introduced for measuring crack extension in brittle materials. Cross-correlation of the displacements measured by DIC with a step function was employed to identify the advancingmore » crack tip in a graphite beam specimen under three-point bending. The load-crack extension curve, which is required for analyzing the R-curve and tension softening behaviors, was obtained for this material. Furthermore, a sensitivity analysis of the threshold value employed for the cross-correlation parameter in the crack identification process was conducted. Finally, the results were verified using the finite element method.« less
Liu, Xuan; Ramella-Roman, Jessica C.; Huang, Yong; Guo, Yuan; Kang, Jin U.
2013-01-01
In this study, we proposed a generic speckle simulation for optical coherence tomography (OCT) signal, by convolving the point spread function (PSF) of the OCT system with the numerically synthesized random sample field. We validated our model and used the simulation method to study the statistical properties of cross-correlation coefficients (XCC) between Ascans which have been recently applied in transverse motion analysis by our group. The results of simulation show that over sampling is essential for accurate motion tracking; exponential decay of OCT signal leads to an under estimate of motion which can be corrected; lateral heterogeneity of sample leads to an over estimate of motion for a few pixels corresponding to the structural boundary. PMID:23456001
Coupling detrended fluctuation analysis for analyzing coupled nonstationary signals.
Hedayatifar, L; Vahabi, M; Jafari, G R
2011-08-01
When many variables are coupled to each other, a single case study could not give us thorough and precise information. When these time series are stationary, different methods of random matrix analysis and complex networks can be used. But, in nonstationary cases, the multifractal-detrended-cross-correlation-analysis (MF-DXA) method was introduced for just two coupled time series. In this article, we have extended the MF-DXA to the method of coupling detrended fluctuation analysis (CDFA) for the case when more than two series are correlated to each other. Here, we have calculated the multifractal properties of the coupled time series, and by comparing CDFA results of the original series with those of the shuffled and surrogate series, we can estimate the source of multifractality and the extent to which our series are coupled to each other. We illustrate the method by selected examples from air pollution and foreign exchange rates.
Coupling detrended fluctuation analysis for analyzing coupled nonstationary signals
NASA Astrophysics Data System (ADS)
Hedayatifar, L.; Vahabi, M.; Jafari, G. R.
2011-08-01
When many variables are coupled to each other, a single case study could not give us thorough and precise information. When these time series are stationary, different methods of random matrix analysis and complex networks can be used. But, in nonstationary cases, the multifractal-detrended-cross-correlation-analysis (MF-DXA) method was introduced for just two coupled time series. In this article, we have extended the MF-DXA to the method of coupling detrended fluctuation analysis (CDFA) for the case when more than two series are correlated to each other. Here, we have calculated the multifractal properties of the coupled time series, and by comparing CDFA results of the original series with those of the shuffled and surrogate series, we can estimate the source of multifractality and the extent to which our series are coupled to each other. We illustrate the method by selected examples from air pollution and foreign exchange rates.
Ozdemir, Filiz Ciledag; Pehlivan, Erkan; Melekoglu, Rauf
2017-01-01
To investigate the pelvic floor muscle strength of the women andevaluateits possible correlation with sexual dysfunction. In this cross-sectional type study, stratified clusters were used for the sampling method. Index of Female Sexual Function (IFSF) worksheetwere used for questions on sexual function. The pelvic floor muscle strength of subjects was assessed byperineometer. The chi-squared test, logistic regression and Pearson's correlation analysis were used for the statistical analysis. Four hundred thirty primiparous women, mean age 38.5 participated in this study. The average pelvic floor muscle strength value was found 31.4±9.6 cm H 2 O and the average Index of Female Sexual Function (IFSF) score was found 26.5±6.9. Parity (odds ratio OR=5.546) and age 40 or higher (OR=3.484) were found correlated with pelvic floor muscle weakness (p<0.05). The factors directly correlated with sexual dysfunction were found being overweight (OR=2.105) and age 40 or higher (OR=2.451) (p<0.05). Pearson's correlation analysis showed that there was a statistically significantlinear correlation between the muscular strength of the pelvic floor and sexual function (p=0.001). The results suggested subjects with decreased pelvic floor muscle strength value had higher frequency of sexual dysfunction.
NASA Astrophysics Data System (ADS)
Buttgereit, R.; Roths, T.; Honerkamp, J.; Aberle, L. B.
2001-10-01
Dynamic light scattering experiments have become a powerful tool in order to investigate the dynamical properties of complex fluids. In many applications in both soft matter research and industry so-called ``real world'' systems are subject of great interest. Here, the dilution of the investigated system often cannot be changed without getting measurement artifacts, so that one often has to deal with highly concentrated and turbid media. The investigation of such systems requires techniques that suppress the influence of multiple scattering, e.g., cross correlation techniques. However, measurements at turbid as well as highly diluted media lead to data with low signal-to-noise ratio, which complicates data analysis and leads to unreliable results. In this article a multiangle regularization method is discussed, which copes with the difficulties arising from such samples and enhances enormously the quality of the estimated solution. In order to demonstrate the efficiency of this multiangle regularization method we applied it to cross correlation functions measured at highly turbid samples.
NASA Astrophysics Data System (ADS)
Chen, Zhi; Hu, Kun; Stanley, H. Eugene; Novak, Vera; Ivanov, Plamen Ch.
2006-03-01
We investigate the relationship between the blood flow velocities (BFV) in the middle cerebral arteries and beat-to-beat blood pressure (BP) recorded from a finger in healthy and post-stroke subjects during the quasisteady state after perturbation for four different physiologic conditions: supine rest, head-up tilt, hyperventilation, and CO2 rebreathing in upright position. To evaluate whether instantaneous BP changes in the steady state are coupled with instantaneous changes in the BFV, we compare dynamical patterns in the instantaneous phases of these signals, obtained from the Hilbert transform, as a function of time. We find that in post-stroke subjects the instantaneous phase increments of BP and BFV exhibit well-pronounced patterns that remain stable in time for all four physiologic conditions, while in healthy subjects these patterns are different, less pronounced, and more variable. We propose an approach based on the cross-correlation of the instantaneous phase increments to quantify the coupling between BP and BFV signals. We find that the maximum correlation strength is different for the two groups and for the different conditions. For healthy subjects the amplitude of the cross-correlation between the instantaneous phase increments of BP and BFV is small and attenuates within 3-5 heartbeats. In contrast, for post-stroke subjects, this amplitude is significantly larger and cross-correlations persist up to 20 heartbeats. Further, we show that the instantaneous phase increments of BP and BFV are cross-correlated even within a single heartbeat cycle. We compare the results of our approach with three complementary methods: direct BP-BFV cross-correlation, transfer function analysis, and phase synchronization analysis. Our findings provide insight into the mechanism of cerebral vascular control in healthy subjects, suggesting that this control mechanism may involve rapid adjustments (within a heartbeat) of the cerebral vessels, so that BFV remains steady in response to changes in peripheral BP.
Chen, Zhi; Hu, Kun; Stanley, H Eugene; Novak, Vera; Ivanov, Plamen Ch
2006-03-01
We investigate the relationship between the blood flow velocities (BFV) in the middle cerebral arteries and beat-to-beat blood pressure (BP) recorded from a finger in healthy and post-stroke subjects during the quasisteady state after perturbation for four different physiologic conditions: supine rest, head-up tilt, hyperventilation, and CO2 rebreathing in upright position. To evaluate whether instantaneous BP changes in the steady state are coupled with instantaneous changes in the BFV, we compare dynamical patterns in the instantaneous phases of these signals, obtained from the Hilbert transform, as a function of time. We find that in post-stroke subjects the instantaneous phase increments of BP and BFV exhibit well-pronounced patterns that remain stable in time for all four physiologic conditions, while in healthy subjects these patterns are different, less pronounced, and more variable. We propose an approach based on the cross-correlation of the instantaneous phase increments to quantify the coupling between BP and BFV signals. We find that the maximum correlation strength is different for the two groups and for the different conditions. For healthy subjects the amplitude of the cross-correlation between the instantaneous phase increments of BP and BFV is small and attenuates within 3-5 heartbeats. In contrast, for post-stroke subjects, this amplitude is significantly larger and cross-correlations persist up to 20 heartbeats. Further, we show that the instantaneous phase increments of BP and BFV are cross-correlated even within a single heartbeat cycle. We compare the results of our approach with three complementary methods: direct BP-BFV cross-correlation, transfer function analysis, and phase synchronization analysis. Our findings provide insight into the mechanism of cerebral vascular control in healthy subjects, suggesting that this control mechanism may involve rapid adjustments (within a heartbeat) of the cerebral vessels, so that BFV remains steady in response to changes in peripheral BP.
NASA Astrophysics Data System (ADS)
Sanjaya, Kadek Heri; Sya'bana, Yukhi Mustaqim Kusuma
2017-01-01
Research on eco-friendly vehicle development in Indonesia has largely neglected ergonomic study, despite the fact that traffic accidents have resulted in greater economic cost than fuel subsidy. We have performed a biomechanical experiment on human locomotion earlier. In this article, we describe the importance of implementing the biomechanical measurement methods in transportation ergonomic study. The instruments such as electromyogram (EMG), load cell, pressure sensor, and motion analysis methods as well as cross-correlation function analysis were explained, then the possibility of their application in driving behavior study is described. We describe the potentials and challenges of the biomechanical methods concerning the future vehicle development. The methods provide greater advantages in objective and accurate measurement not only in human task performance but also its correlation with vehicle performance.
Biffi, E; Menegon, A; Regalia, G; Maida, S; Ferrigno, G; Pedrocchi, A
2011-08-15
Modern drug discovery for Central Nervous System pathologies has recently focused its attention to in vitro neuronal networks as models for the study of neuronal activities. Micro Electrode Arrays (MEAs), a widely recognized tool for pharmacological investigations, enable the simultaneous study of the spiking activity of discrete regions of a neuronal culture, providing an insight into the dynamics of networks. Taking advantage of MEAs features and making the most of the cross-correlation analysis to assess internal parameters of a neuronal system, we provide an efficient method for the evaluation of comprehensive neuronal network activity. We developed an intra network burst correlation algorithm, we evaluated its sensitivity and we explored its potential use in pharmacological studies. Our results demonstrate the high sensitivity of this algorithm and the efficacy of this methodology in pharmacological dose-response studies, with the advantage of analyzing the effect of drugs on the comprehensive correlative properties of integrated neuronal networks. Copyright © 2011 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Ferrera, Elisabetta; Giammanco, Salvatore; Cannata, Andrea; Montalto, Placido
2013-04-01
From November 2009 to April 2011 soil radon activity was continuously monitored using a Barasol® probe located on the upper NE flank of Mt. Etna volcano, close either to the Piano Provenzana fault or to the NE-Rift. Seismic and volcanological data have been analyzed together with radon data. We also analyzed air and soil temperature, barometric pressure, snow and rain fall data. In order to find possible correlations among the above parameters, and hence to reveal possible anomalies in the radon time-series, we used different statistical methods: i) multivariate linear regression; ii) cross-correlation; iii) coherence analysis through wavelet transform. Multivariate regression indicated a modest influence on soil radon from environmental parameters (R2 = 0.31). When using 100-days time windows, the R2 values showed wide variations in time, reaching their maxima (~0.63-0.66) during summer. Cross-correlation analysis over 100-days moving averages showed that, similar to multivariate linear regression analysis, the summer period is characterised by the best correlation between radon data and environmental parameters. Lastly, the wavelet coherence analysis allowed a multi-resolution coherence analysis of the time series acquired. This approach allows to study the relations among different signals either in time or frequency domain. It confirmed the results of the previous methods, but also allowed to recognize correlations between radon and environmental parameters at different observation scales (e.g., radon activity changed during strong precipitations, but also during anomalous variations of soil temperature uncorrelated with seasonal fluctuations). Our work suggests that in order to make an accurate analysis of the relations among distinct signals it is necessary to use different techniques that give complementary analytical information. In particular, the wavelet analysis showed to be very effective in discriminating radon changes due to environmental influences from those correlated with impending seismic or volcanic events.
NASA Astrophysics Data System (ADS)
Cao, Guangxi; Han, Yan; Cui, Weijun; Guo, Yu
2014-11-01
The cross-correlation between the China Securities Index 300 (CSI 300) index futures and the spot markets based on high-frequency data is discussed in this paper. We empirically analyze the cross-correlation by using the multifractal detrended cross-correlation analysis (MF-DCCA), and investigate further the characteristics of asymmetry, frequency difference, and transmission direction of the cross-correlation. The results indicate that the cross-correlation between the two markets is significant and multifractal. Meanwhile, weak asymmetries exist in the cross-correlation, and higher data frequency results in a lower multifractality degree of the cross-correlation. The causal relationship between the two markets is bidirectional, but the CSI 300 index futures market has greater impact on the spot market.
New methods for engineering site characterization using reflection and surface wave seismic survey
NASA Astrophysics Data System (ADS)
Chaiprakaikeow, Susit
This study presents two new seismic testing methods for engineering application, a new shallow seismic reflection method and Time Filtered Analysis of Surface Waves (TFASW). Both methods are described in this dissertation. The new shallow seismic reflection was developed to measure reflection at a single point using two to four receivers, assuming homogeneous, horizontal layering. It uses one or more shakers driven by a swept sine function as a source, and the cross-correlation technique to identify wave arrivals. The phase difference between the source forcing function and the ground motion due to the dynamic response of the shaker-ground interface was corrected by using a reference geophone. Attenuated high frequency energy was also recovered using the whitening in frequency domain. The new shallow seismic reflection testing was performed at the crest of Porcupine Dam in Paradise, Utah. The testing used two horizontal Vibroseis sources and four receivers for spacings between 6 and 300 ft. Unfortunately, the results showed no clear evidence of the reflectors despite correction of the magnitude and phase of the signals. However, an improvement in the shape of the cross-correlations was noticed after the corrections. The results showed distinct primary lobes in the corrected cross-correlated signals up to 150 ft offset. More consistent maximum peaks were observed in the corrected waveforms. TFASW is a new surface (Rayleigh) wave method to determine the shear wave velocity profile at a site. It is a time domain method as opposed to the Spectral Analysis of Surface Waves (SASW) method, which is a frequency domain method. This method uses digital filtering to optimize bandwidth used to determine the dispersion curve. Results from testings at three different sites in Utah indicated good agreement with the dispersion curves measured using both TFASW and SASW methods. The advantage of TFASW method is that the dispersion curves had less scatter at long wavelengths as a result from wider bandwidth used in those tests.
Bortnik, A T; Iakupova, L P
1991-01-01
Cross-correlation analysis of interdependence of the background spike activity was carried out for pairs of adjacent neurons simultaneously recorded in the incubated slices of the neocortex of guinea-pig. Statistical correlation of spike discharges was detected in 16 out of 26 recorded pairs of the neurons. Significant correlation was observed mainly in the range of +/- 100 ms from the null point. Cross-correlation had symmetric or asymmetric maxima up to 150 ms long and negative shifts up to 200 ms long. More complex positive-negative types of cross-correlations were also obtained. The data were compared to those known from other authors for the intact brain. The contribution of intrinsic intracortical interactions and extrinsic afferent influences in these correlations of activity is discussed.
Analysis/forecast experiments with a flow-dependent correlation function using FGGE data
NASA Technical Reports Server (NTRS)
Baker, W. E.; Bloom, S. C.; Carus, H.; Nestler, M. S.
1986-01-01
The use of a flow-dependent correlation function to improve the accuracy of an optimum interpolation (OI) scheme is examined. The development of the correlation function for the OI analysis scheme used for numerical weather prediction is described. The scheme uses a multivariate surface analysis over the oceans to model the pressure-wind error cross-correlation and it has the ability to use an error correlation function that is flow- and geographically-dependent. A series of four-day data assimilation experiments, conducted from January 5-9, 1979, were used to investigate the effect of the different features of the OI scheme (error correlation) on forecast skill for the barotropic lows and highs. The skill of the OI was compared with that of a successive correlation method (SCM) of analysis. It is observed that the largest difference in the correlation statistics occurred in barotropic and baroclinic lows and highs. The comparison reveals that the OI forecasts were more accurate than the SCM forecasts.
1992-04-10
and passive tracer concentrations, and their cross correlations have generally been used to estimate the magnitude of dispersive atmospheric transport...of gravity waves and turbulence. . 10 III. METHODS .......... ........................ 12 A. Data .......... ........................ 12 B. Analysis ...unstable, i.e., strange. For waves or even limit cycle motion about fixed attractors, self-similarity does not occur. Pertinent to time series analysis , this
NASA Astrophysics Data System (ADS)
Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Bartlett, J. G.; Bartolo, N.; Battaner, E.; Benabed, K.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Burigana, C.; Butler, R. C.; Calabrese, E.; Catalano, A.; Chamballu, A.; Chiang, H. C.; Christensen, P. R.; Churazov, E.; Clements, D. L.; Colombo, L. P. L.; Combet, C.; Comis, B.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Dickinson, C.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Finelli, F.; Flores-Cacho, I.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Galeotta, S.; Galli, S.; Ganga, K.; Génova-Santos, R. T.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Harrison, D. L.; Helou, G.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Keihänen, E.; Keskitalo, R.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Langer, M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leonardi, R.; Levrier, F.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maffei, B.; Maggio, G.; Maino, D.; Mak, D. S. Y.; Mandolesi, N.; Mangilli, A.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; Melchiorri, A.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Munshi, D.; Murphy, J. A.; Nati, F.; Natoli, P.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Partridge, B.; Pasian, F.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Ponthieu, N.; Pratt, G. W.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Savini, G.; Scott, D.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Tucci, M.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; Welikala, N.; Yvon, D.; Zacchei, A.; Zonca, A.
2016-09-01
We use Planck data to detect the cross-correlation between the thermal Sunyaev-Zeldovich (tSZ) effect and the infrared emission from the galaxies that make up the the cosmic infrared background (CIB). We first perform a stacking analysis towards Planck-confirmed galaxy clusters. We detect infrared emission produced by dusty galaxies inside these clusters and demonstrate that the infrared emission is about 50% more extended than the tSZ effect. Modelling the emission with a Navarro-Frenk-White profile, we find that the radial profile concentration parameter is c500 = 1.00+0.18-0.15 . This indicates that infrared galaxies in the outskirts of clusters have higher infrared flux than cluster-core galaxies. We also study the cross-correlation between tSZ and CIB anisotropies, following three alternative approaches based on power spectrum analyses: (I) using a catalogue of confirmed clusters detected in Planck data; (II) using an all-sky tSZ map built from Planck frequency maps; and (III) using cross-spectra between Planck frequency maps. With the three different methods, we detect the tSZ-CIB cross-power spectrum at significance levels of (I) 6σ; (II) 3σ; and (III) 4σ. We model the tSZ-CIB cross-correlation signature and compare predictions with the measurements. The amplitude of the cross-correlation relative to the fiducial model is AtSZ-CIB = 1.2 ± 0.3. This result is consistent with predictions for the tSZ-CIB cross-correlation assuming the best-fit cosmological model from Planck 2015 results along with the tSZ and CIB scaling relations.
Velghe, Katherine; Gregory-Eaves, Irene
2013-01-01
Biodiversity losses over the next century are predicted to result in alterations of ecosystem functions that are on par with other major drivers of global change. Given the seriousness of this issue, there is a need to effectively monitor global biodiversity. Because performing biodiversity censuses of all taxonomic groups is prohibitively costly, indicator groups have been studied to estimate the biodiversity of different taxonomic groups. Quantifying cross-taxon congruence is a method of evaluating the assumption that the diversity of one taxonomic group can be used to predict the diversity of another. To improve the predictive ability of cross-taxon congruence in aquatic ecosystems, we evaluated whether body size, measured as the ratio of average body length between organismal groups, is a significant predictor of their cross-taxon biodiversity congruence. To test this hypothesis, we searched the published literature and screened for studies that used species richness correlations as their metric of cross-taxon congruence. We extracted 96 correlation coefficients from 16 studies, which encompassed 784 inland water bodies. With these correlation coefficients, we conducted a categorical meta-analysis, grouping data based on the body size ratio of organisms. Our results showed that cross-taxon congruence is variable among sites and between different groups (r values ranging between −0.53 to 0.88). In addition, our quantitative meta-analysis demonstrated that organisms most similar in body size showed stronger species richness correlations than organisms which differed increasingly in size (radj 2 = 0.94, p = 0.02). We propose that future studies applying biodiversity indicators in aquatic ecosystems consider functional traits such as body size, so as to increase their success at predicting the biodiversity of taxonomic groups where cost-effective conservation tools are needed. PMID:23468903
NASA Astrophysics Data System (ADS)
Schmitz, R.; Yordanov, S.; Butt, H. J.; Koynov, K.; Dünweg, B.
2011-12-01
Total internal reflection fluorescence cross-correlation spectroscopy (TIR-FCCS) has recently [S. Yordanov , Optics ExpressOPEXFF1094-408710.1364/OE.17.021149 17, 21149 (2009)] been established as an experimental method to probe hydrodynamic flows near surfaces, on length scales of tens of nanometers. Its main advantage is that fluorescence occurs only for tracer particles close to the surface, thus resulting in high sensitivity. However, the measured correlation functions provide only rather indirect information about the flow parameters of interest, such as the shear rate and the slip length. In the present paper, we show how to combine detailed and fairly realistic theoretical modeling of the phenomena by Brownian dynamics simulations with accurate measurements of the correlation functions, in order to establish a quantitative method to retrieve the flow properties from the experiments. First, Brownian dynamics is used to sample highly accurate correlation functions for a fixed set of model parameters. Second, these parameters are varied systematically by means of an importance-sampling Monte Carlo procedure in order to fit the experiments. This provides the optimum parameter values together with their statistical error bars. The approach is well suited for massively parallel computers, which allows us to do the data analysis within moderate computing times. The method is applied to flow near a hydrophilic surface, where the slip length is observed to be smaller than 10nm, and, within the limitations of the experiments and the model, indistinguishable from zero.
Cervical vertebral maturation as a biologic indicator of skeletal maturity.
Santiago, Rodrigo César; de Miranda Costa, Luiz Felipe; Vitral, Robert Willer Farinazzo; Fraga, Marcelo Reis; Bolognese, Ana Maria; Maia, Lucianne Cople
2012-11-01
To identify and review the literature regarding the reliability of cervical vertebrae maturation (CVM) staging to predict the pubertal spurt. The selection criteria included cross-sectional and longitudinal descriptive studies in humans that evaluated qualitatively or quantitatively the accuracy and reproducibility of the CVM method on lateral cephalometric radiographs, as well as the correlation with a standard method established by hand-wrist radiographs. The searches retrieved 343 unique citations. Twenty-three studies met the inclusion criteria. Six articles had moderate to high scores, while 17 of 23 had low scores. Analysis also showed a moderate to high statistically significant correlation between CVM and hand-wrist maturation methods. There was a moderate to high reproducibility of the CVM method, and only one specific study investigated the accuracy of the CVM index in detecting peak pubertal growth. This systematic review has shown that the studies on CVM method for radiographic assessment of skeletal maturation stages suffer from serious methodological failures. Better-designed studies with adequate accuracy, reproducibility, and correlation analysis, including studies with appropriate sensitivity-specificity analysis, should be performed.
Cross-correlations between crude oil and agricultural commodity markets
NASA Astrophysics Data System (ADS)
Liu, Li
2014-02-01
In this paper, we investigate cross-correlations between crude oil and agricultural commodity markets. Based on a popular statistical test proposed by Podobnik et al. (2009), we find that the linear return cross-correlations are significant at larger lag lengths and the volatility cross-correlations are highly significant at all of the lag lengths under consideration. Using a detrended cross-correlation analysis (DCCA), we find that the return cross-correlations are persistent for corn and soybean and anti-persistent for oat and soybean. The volatility cross-correlations are strongly persistent. Using a nonlinear cross-correlation measure, our results show that cross-correlations are relatively weak but they are significant for smaller time scales. For larger time scales, the cross-correlations are not significant. The reason may be that information transmission from crude oil market to agriculture markets can complete within a certain period of time. Finally, based on multifractal extension of DCCA, we find that the cross-correlations are multifractal and high oil prices partly contribute to food crisis during the period of 2006-mid-2008.
Detecting coupled collective motions in protein by independent subspace analysis
NASA Astrophysics Data System (ADS)
Sakuraba, Shun; Joti, Yasumasa; Kitao, Akio
2010-11-01
Protein dynamics evolves in a high-dimensional space, comprising aharmonic, strongly correlated motional modes. Such correlation often plays an important role in analyzing protein function. In order to identify significantly correlated collective motions, here we employ independent subspace analysis based on the subspace joint approximate diagonalization of eigenmatrices algorithm for the analysis of molecular dynamics (MD) simulation trajectories. From the 100 ns MD simulation of T4 lysozyme, we extract several independent subspaces in each of which collective modes are significantly correlated, and identify the other modes as independent. This method successfully detects the modes along which long-tailed non-Gaussian probability distributions are obtained. Based on the time cross-correlation analysis, we identified a series of events among domain motions and more localized motions in the protein, indicating the connection between the functionally relevant phenomena which have been independently revealed by experiments.
Analysis of cross-correlations between financial markets after the 2008 crisis
NASA Astrophysics Data System (ADS)
Sensoy, A.; Yuksel, S.; Erturk, M.
2013-10-01
We analyze the cross-correlation matrix C of the index returns of the main financial markets after the 2008 crisis using methods of random matrix theory. We test the eigenvalues of C for universal properties of random matrices and find that the majority of the cross-correlation coefficients arise from randomness. We show that the eigenvector of the largest deviating eigenvalue of C represents a global market itself. We reveal that high volatility of financial markets is observed at the same times with high correlations between them which lowers the risk diversification potential even if one constructs a widely internationally diversified portfolio of stocks. We identify and compare the connection and cluster structure of markets before and after the crisis using minimal spanning and ultrametric hierarchical trees. We find that after the crisis, the co-movement degree of the markets increases. We also highlight the key financial markets of pre and post crisis using main centrality measures and analyze the changes. We repeat the study using rank correlation and compare the differences. Further implications are discussed.
Linearized spectrum correlation analysis for line emission measurements
NASA Astrophysics Data System (ADS)
Nishizawa, T.; Nornberg, M. D.; Den Hartog, D. J.; Sarff, J. S.
2017-08-01
A new spectral analysis method, Linearized Spectrum Correlation Analysis (LSCA), for charge exchange and passive ion Doppler spectroscopy is introduced to provide a means of measuring fast spectral line shape changes associated with ion-scale micro-instabilities. This analysis method is designed to resolve the fluctuations in the emission line shape from a stationary ion-scale wave. The method linearizes the fluctuations around a time-averaged line shape (e.g., Gaussian) and subdivides the spectral output channels into two sets to reduce contributions from uncorrelated fluctuations without averaging over the fast time dynamics. In principle, small fluctuations in the parameters used for a line shape model can be measured by evaluating the cross spectrum between different channel groupings to isolate a particular fluctuating quantity. High-frequency ion velocity measurements (100-200 kHz) were made by using this method. We also conducted simulations to compare LSCA with a moment analysis technique under a low photon count condition. Both experimental and synthetic measurements demonstrate the effectiveness of LSCA.
Correlation analysis of respiratory signals by using parallel coordinate plots.
Saatci, Esra
2018-01-01
The understanding of the bonds and the relationships between the respiratory signals, i.e. the airflow, the mouth pressure, the relative temperature and the relative humidity during breathing may provide the improvement on the measurement methods of respiratory mechanics and sensor designs or the exploration of the several possible applications in the analysis of respiratory disorders. Therefore, the main objective of this study was to propose a new combination of methods in order to determine the relationship between respiratory signals as a multidimensional data. In order to reveal the coupling between the processes two very different methods were used: the well-known statistical correlation analysis (i.e. Pearson's correlation and cross-correlation coefficient) and parallel coordinate plots (PCPs). Curve bundling with the number intersections for the correlation analysis, Least Mean Square Time Delay Estimator (LMS-TDE) for the point delay detection and visual metrics for the recognition of the visual structures were proposed and utilized in PCP. The number of intersections was increased when the correlation coefficient changed from high positive to high negative correlation between the respiratory signals, especially if whole breath was processed. LMS-TDE coefficients plotted in PCP indicated well-matched point delay results to the findings in the correlation analysis. Visual inspection of PCB by visual metrics showed range, dispersions, entropy comparisons and linear and sinusoidal-like relationships between the respiratory signals. It is demonstrated that the basic correlation analysis together with the parallel coordinate plots perceptually motivates the visual metrics in the display and thus can be considered as an aid to the user analysis by providing meaningful views of the data. Copyright © 2017 Elsevier B.V. All rights reserved.
Smith, Justin S; Lafage, Virginie; Ryan, Devon J; Shaffrey, Christopher I; Schwab, Frank J; Patel, Alpesh A; Brodke, Darrel S; Arnold, Paul M; Riew, K Daniel; Traynelis, Vincent C; Radcliff, Kris; Vaccaro, Alexander R; Fehlings, Michael G; Ames, Christopher P
2013-10-15
Post hoc analysis of prospectively collected data. Development of methods to determine in vivo spinal cord dimensions and application to correlate preoperative alignment, myelopathy, and health-related quality-of-life scores in patients with cervical spondylotic myelopathy (CSM). CSM is the leading cause of spinal cord dysfunction. The association between cervical alignment, sagittal balance, and myelopathy has not been well characterized. This was a post hoc analysis of the prospective, multicenter AOSpine North America CSM study. Inclusion criteria for this study required preoperative cervical magnetic resonance imaging (MRI) and neutral sagittal cervical radiography. Techniques for MRI assessment of spinal cord dimensions were developed. Correlations between imaging and health-related quality-of-life scores were assessed. Fifty-six patients met inclusion criteria (mean age = 55.4 yr). The modified Japanese Orthopedic Association (mJOA) scores correlated with C2-C7 sagittal vertical axis (SVA) (r = -0.282, P = 0.035). Spinal cord volume correlated with cord length (r = 0.472, P < 0.001) and cord average cross-sectional area (r = 0.957, P < 0.001). For all patients, no correlations were found between MRI measurements of spinal cord length, volume, mean cross-sectional area or surface area, and outcomes. For patients with cervical lordosis, mJOA scores correlated positively with cord volume (r = 0.366, P = 0.022), external cord area (r = 0.399, P = 0.012), and mean cross-sectional cord area (r = 0.345, P = 0.031). In contrast, for patients with cervical kyphosis, mJOA scores correlated negatively with cord volume (r = -0.496, P = 0.043) and mean cross-sectional cord area (r = -0.535, P = 0.027). This study is the first to correlate cervical sagittal balance (C2-C7 SVA) to myelopathy severity. We found a moderate negative correlation in kyphotic patients of cord volume and cross-sectional area to mJOA scores. The opposite (positive correlation) was found for lordotic patients, suggesting a relationship of cord volume to myelopathy that differs on the basis of sagittal alignment. It is interesting to note that sagittal balance but not kyphosis is tied to myelopathy score. Future work will correlate alignment changes to cord morphology changes and myelopathy outcomes. SUMMARY STATEMENTS: This is the first study to correlate sagittal balance (C2-C7 SVA) to myelopathy severity. We found a moderate negative correlation in kyphotic patients of cord volume and cross-sectional area to mJOA scores. The opposite (positive correlation) was found for lordotic patients, suggesting a relationship of cord volume to myelopathy that differs on the basis of sagittal alignment.
NASA Astrophysics Data System (ADS)
Yang, Zhen; Zhang, Min; Liao, Yanbiao; Lai, Shurong; Tian, Qian; Li, Qisheng; Zhang, Yi; Zhuang, Zhi
2009-11-01
An extrinsic Fabry-Perot interferometric (EFPI) optical fiber hydrogen sensor based on palladium silver (Pd-Ag) film is designed for hydrogen leakage detection. A modified cross correlation signal processing method for an optical fiber EFPI hydrogen sensor is presented. As the applying of a special correlating factor which advises the effect on the fringe visibility of the gap length and wavelength, the cross correlation method has a high accuracy which is insensitive to light source power drift or changes in attenuation in the fiber, and the segment search method is employed to reduce computation and demodulating speed is fast. The Fabry-Perot gap length resolution of better than 0.2nm is achieved in a certain concentration of hydrogen.
Multifractal cross-correlations between crude oil and tanker freight rate
NASA Astrophysics Data System (ADS)
Chen, Feier; Miao, Yuqi; Tian, Kang; Ding, Xiaoxu; Li, Tingyi
2017-05-01
Analysis of crude oil price and tanker freight rate volatility attract more attention as the mechanism is not only the basis of industrialization but also a vital role in economics, especially after the year 2008 when financial crisis notably blew the maritime transportation. In this paper, we studied the cross-correlations between the West Texas International crude oil (WTI) and Baltic Exchange Dirty Tanker Index (BDTI) employing the Multifractal Detrended Cross-Correlation Analysis (MF-DCCA). Empirical results show that the degree of short-term cross-correlation is higher than that in the long term and that the strength of multifractality after financial crisis is larger than that before. Moreover, the components of multifractal spectrum are quantified with the finite-size effect taken into consideration and an improved method in terms of constructing the surrogated time series provided. Numerical results show that the multifractality is generated mostly from the nonlinear and the fat-tailed probability distribution (PDF) part. Also, it is apparent that the PDF part changes a lot after the financial crisis. The research is contributory to risk management by providing various instructions for participants in shipping markets. Our main contribution is that we investigated both the multifractal features and the origin of multifractality and provided confirming evidence of multifractality through numerical results while applying quantitative analysis based on MF-DCCA; furthermore, the research is contributory to risk management since it provides instructions in both economic market and stock market simultaneously. However, constructing the surrogated series in order to obtain consistence seems less convincing which requires further discussion and attempts.
Baker, Jannah; White, Nicole; Mengersen, Kerrie
2014-11-20
Spatial analysis is increasingly important for identifying modifiable geographic risk factors for disease. However, spatial health data from surveys are often incomplete, ranging from missing data for only a few variables, to missing data for many variables. For spatial analyses of health outcomes, selection of an appropriate imputation method is critical in order to produce the most accurate inferences. We present a cross-validation approach to select between three imputation methods for health survey data with correlated lifestyle covariates, using as a case study, type II diabetes mellitus (DM II) risk across 71 Queensland Local Government Areas (LGAs). We compare the accuracy of mean imputation to imputation using multivariate normal and conditional autoregressive prior distributions. Choice of imputation method depends upon the application and is not necessarily the most complex method. Mean imputation was selected as the most accurate method in this application. Selecting an appropriate imputation method for health survey data, after accounting for spatial correlation and correlation between covariates, allows more complete analysis of geographic risk factors for disease with more confidence in the results to inform public policy decision-making.
Wang, Fang; Wang, Lin; Chen, Yuming
2017-08-31
In order to investigate the time-dependent cross-correlations of fine particulate (PM2.5) series among neighboring cities in Northern China, in this paper, we propose a new cross-correlation coefficient, the time-lagged q-L dependent height crosscorrelation coefficient (denoted by p q (τ, L)), which incorporates the time-lag factor and the fluctuation amplitude information into the analogous height cross-correlation analysis coefficient. Numerical tests are performed to illustrate that the newly proposed coefficient ρ q (τ, L) can be used to detect cross-correlations between two series with time lags and to identify different range of fluctuations at which two series possess cross-correlations. Applying the new coefficient to analyze the time-dependent cross-correlations of PM2.5 series between Beijing and the three neighboring cities of Tianjin, Zhangjiakou, and Baoding, we find that time lags between the PM2.5 series with larger fluctuations are longer than those between PM2.5 series withsmaller fluctuations. Our analysis also shows that cross-correlations between the PM2.5 series of two neighboring cities are significant and the time lags between two PM2.5 series of neighboring cities are significantly non-zero. These findings providenew scientific support on the view that air pollution in neighboring cities can affect one another not simultaneously but with a time lag.
NASA Astrophysics Data System (ADS)
Giammanco, S.; Ferrera, E.; Cannata, A.; Montalto, P.; Neri, M.
2013-12-01
From November 2009 to April 2011 soil radon activity was continuously monitored using a Barasol probe located on the upper NE flank of Mt. Etna volcano (Italy), close both to the Piano Provenzana fault and to the NE-Rift. Seismic, volcanological and radon data were analysed together with data on environmental parameters, such as air and soil temperature, barometric pressure, snow and rain fall. In order to find possible correlations among the above parameters, and hence to reveal possible anomalous trends in the radon time-series, we used different statistical methods: i) multivariate linear regression; ii) cross-correlation; iii) coherence analysis through wavelet transform. Multivariate regression indicated a modest influence on soil radon from environmental parameters (R2 = 0.31). When using 100-day time windows, the R2 values showed wide variations in time, reaching their maxima (~0.63-0.66) during summer. Cross-correlation analysis over 100-day moving averages showed that, similar to multivariate linear regression analysis, the summer period was characterised by the best correlation between radon data and environmental parameters. Lastly, the wavelet coherence analysis allowed a multi-resolution coherence analysis of the time series acquired. This approach allowed to study the relations among different signals either in the time or in the frequency domain. It confirmed the results of the previous methods, but also allowed to recognize correlations between radon and environmental parameters at different observation scales (e.g., radon activity changed during strong precipitations, but also during anomalous variations of soil temperature uncorrelated with seasonal fluctuations). Using the above analysis, two periods were recognized when radon variations were significantly correlated with marked soil temperature changes and also with local seismic or volcanic activity. This allowed to produce two different physical models of soil gas transport that explain the observed anomalies. Our work suggests that in order to make an accurate analysis of the relations among different signals it is necessary to use different techniques that give complementary analytical information. In particular, the wavelet analysis showed to be the most effective in discriminating radon changes due to environmental influences from those correlated with impending seismic or volcanic events.
NASA Astrophysics Data System (ADS)
Mensi, Walid; Hamdi, Atef; Shahzad, Syed Jawad Hussain; Shafiullah, Muhammad; Al-Yahyaee, Khamis Hamed
2018-07-01
This paper analyzes the dynamic efficiency and interdependence of Islamic and conventional banks of Saudi Arabia. This analysis applies the Multifractal Detrended Fluctuation Analysis (MF-DFA) and Multifractal Detrended Cross-Correlation Analysis (MF-DXA) approaches. The MF-DFA results show strong multifractality in the daily returns of Saudi banks. Moreover, all eight banks studied exhibit persistence correlation, which demonstrates inefficiency. The rolling window results show significant change in the inefficiency levels over the time. The cross-correlation analysis between bank-pairs exhibits long term interdependence between most of them. These findings indicate that the banking sector in Saudi Arabia suffers from inefficiency and exhibits long term memory.
The use of dwell time cross-correlation functions to study single-ion channel gating kinetics.
Ball, F G; Kerry, C J; Ramsey, R L; Sansom, M S; Usherwood, P N
1988-01-01
The derivation of cross-correlation functions from single-channel dwell (open and closed) times is described. Simulation of single-channel data for simple gating models, alongside theoretical treatment, is used to demonstrate the relationship of cross-correlation functions to underlying gating mechanisms. It is shown that time irreversibility of gating kinetics may be revealed in cross-correlation functions. Application of cross-correlation function analysis to data derived from the locust muscle glutamate receptor-channel provides evidence for multiple gateway states and time reversibility of gating. A model for the gating of this channel is used to show the effect of omission of brief channel events on cross-correlation functions. PMID:2462924
Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment
Camacho Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis
2018-01-01
This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks. PMID:29762505
Features of Cross-Correlation Analysis in a Data-Driven Approach for Structural Damage Assessment.
Camacho Navarro, Jhonatan; Ruiz, Magda; Villamizar, Rodolfo; Mujica, Luis; Quiroga, Jabid
2018-05-15
This work discusses the advantage of using cross-correlation analysis in a data-driven approach based on principal component analysis (PCA) and piezodiagnostics to obtain successful diagnosis of events in structural health monitoring (SHM). In this sense, the identification of noisy data and outliers, as well as the management of data cleansing stages can be facilitated through the implementation of a preprocessing stage based on cross-correlation functions. Additionally, this work evidences an improvement in damage detection when the cross-correlation is included as part of the whole damage assessment approach. The proposed methodology is validated by processing data measurements from piezoelectric devices (PZT), which are used in a piezodiagnostics approach based on PCA and baseline modeling. Thus, the influence of cross-correlation analysis used in the preprocessing stage is evaluated for damage detection by means of statistical plots and self-organizing maps. Three laboratory specimens were used as test structures in order to demonstrate the validity of the methodology: (i) a carbon steel pipe section with leak and mass damage types, (ii) an aircraft wing specimen, and (iii) a blade of a commercial aircraft turbine, where damages are specified as mass-added. As the main concluding remark, the suitability of cross-correlation features combined with a PCA-based piezodiagnostic approach in order to achieve a more robust damage assessment algorithm is verified for SHM tasks.
NASA Astrophysics Data System (ADS)
Ausloos, Marcel; Vandewalle, Nicolas; Ivanova, Kristinka
Specialized topics on financial data analysis from a numerical and physical point of view are discussed when pertaining to the analysis of coherent and random sequences in financial fluctuations within (i) the extended detrended fluctuation analysis method, (ii) multi-affine analysis technique, (iii) mobile average intersection rules and distributions, (iv) sandpile avalanches models for crash prediction, (v) the (m,k)-Zipf method and (vi) the i-variability diagram technique for sorting out short range correlations. The most baffling result that needs further thought from mathematicians and physicists is recalled: the crossing of two mobile averages is an original method for measuring the "signal" roughness exponent, but why it is so is not understood up to now.
Morelli, Maria Sole; Giannoni, Alberto; Passino, Claudio; Landini, Luigi; Emdin, Michele; Vanello, Nicola
2016-01-01
Electroencephalographic (EEG) irreducible artifacts are common and the removal of corrupted segments from the analysis may be required. The present study aims at exploring the effects of different EEG Missing Data Segment (MDS) distributions on cross-correlation analysis, involving EEG and physiological signals. The reliability of cross-correlation analysis both at single subject and at group level as a function of missing data statistics was evaluated using dedicated simulations. Moreover, a Bayesian-based approach for combining the single subject results at group level by considering each subject’s reliability was introduced. Starting from the above considerations, the cross-correlation function between EEG Global Field Power (GFP) in delta band and end-tidal CO2 (PETCO2) during rest and voluntary breath-hold was evaluated in six healthy subjects. The analysis of simulated data results at single subject level revealed a worsening of precision and accuracy in the cross-correlation analysis in the presence of MDS. At the group level, a large improvement in the results’ reliability with respect to single subject analysis was observed. The proposed Bayesian approach showed a slight improvement with respect to simple average results. Real data results were discussed in light of the simulated data tests and of the current physiological findings. PMID:27809243
Ade, P. A. R.; Aghanim, N.; Arnaud, M.; ...
2016-09-20
In this paper, we use Planck data to detect the cross-correlation between the thermal Sunyaev-Zeldovich (tSZ) effect and the infrared emission from the galaxies that make up the the cosmic infrared background (CIB). We first perform a stacking analysis towards Planck-confirmed galaxy clusters. We detect infrared emission produced by dusty galaxies inside these clusters and demonstrate that the infrared emission is about 50% more extended than the tSZ effect. Modelling the emission with a Navarro-Frenk-White profile, we find that the radial profile concentration parameter is c 500 = 1.00 +0.18 -0.15 . This indicates that infrared galaxies in the outskirtsmore » of clusters have higher infrared flux than cluster-core galaxies. We also study the cross-correlation between tSZ and CIB anisotropies, following three alternative approaches based on power spectrum analyses: (i) using a catalogue of confirmed clusters detected in Planck data; (ii) using an all-sky tSZ map built from Planck frequency maps; and (iii) using cross-spectra between Planck frequency maps. With the three different methods, we detect the tSZ-CIB cross-power spectrum at significance levels of (i) 6σ; (ii) 3σ; and (iii) 4σ. We model the tSZ-CIB cross-correlation signature and compare predictions with the measurements. The amplitude of the cross-correlation relative to the fiducial model is A tSZ-CIB = 1.2 ± 0.3. Finally, this result is consistent with predictions for the tSZ-CIB cross-correlation assuming the best-fit cosmological model from Planck 2015 results along with the tSZ and CIB scaling relations.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ade, P. A. R.; Aghanim, N.; Arnaud, M.
In this paper, we use Planck data to detect the cross-correlation between the thermal Sunyaev-Zeldovich (tSZ) effect and the infrared emission from the galaxies that make up the the cosmic infrared background (CIB). We first perform a stacking analysis towards Planck-confirmed galaxy clusters. We detect infrared emission produced by dusty galaxies inside these clusters and demonstrate that the infrared emission is about 50% more extended than the tSZ effect. Modelling the emission with a Navarro-Frenk-White profile, we find that the radial profile concentration parameter is c 500 = 1.00 +0.18 -0.15 . This indicates that infrared galaxies in the outskirtsmore » of clusters have higher infrared flux than cluster-core galaxies. We also study the cross-correlation between tSZ and CIB anisotropies, following three alternative approaches based on power spectrum analyses: (i) using a catalogue of confirmed clusters detected in Planck data; (ii) using an all-sky tSZ map built from Planck frequency maps; and (iii) using cross-spectra between Planck frequency maps. With the three different methods, we detect the tSZ-CIB cross-power spectrum at significance levels of (i) 6σ; (ii) 3σ; and (iii) 4σ. We model the tSZ-CIB cross-correlation signature and compare predictions with the measurements. The amplitude of the cross-correlation relative to the fiducial model is A tSZ-CIB = 1.2 ± 0.3. Finally, this result is consistent with predictions for the tSZ-CIB cross-correlation assuming the best-fit cosmological model from Planck 2015 results along with the tSZ and CIB scaling relations.« less
NASA Astrophysics Data System (ADS)
OświÈ©cimka, Paweł; Livi, Lorenzo; DroŻdŻ, Stanisław
2016-10-01
We investigate the scaling of the cross-correlations calculated for two-variable time series containing vertex properties in the context of complex networks. Time series of such observables are obtained by means of stationary, unbiased random walks. We consider three vertex properties that provide, respectively, short-, medium-, and long-range information regarding the topological role of vertices in a given network. In order to reveal the relation between these quantities, we applied the multifractal cross-correlation analysis technique, which provides information about the nonlinear effects in coupling of time series. We show that the considered network models are characterized by unique multifractal properties of the cross-correlation. In particular, it is possible to distinguish between Erdös-Rényi, Barabási-Albert, and Watts-Strogatz networks on the basis of fractal cross-correlation. Moreover, the analysis of protein contact networks reveals characteristics shared with both scale-free and small-world models.
Detrended Cross Correlation Analysis: a new way to figure out the underlying cause of global warming
NASA Astrophysics Data System (ADS)
Hazra, S.; Bera, S. K.
2016-12-01
Analysing non-stationary time series is a challenging task in earth science, seismology, solar physics, climate, biology, finance etc. Most of the cases external noise like oscillation, high frequency noise, low frequency noise in different scales lead to erroneous result. Many statistical methods are proposed to find the correlation between two non-stationary time series. N. Scafetta and B. J. West, Phys. Rev. Lett. 90, 248701 (2003), reported a strong relationship between solar flare intermittency (SFI) and global temperature anomalies (GTA) using diffusion entropy analysis. It has been recently shown that detrended cross correlation analysis (DCCA) is better technique to remove the effects of any unwanted signal as well as local and periodic trend. Thus DCCA technique is more suitable to find the correlation between two non-stationary time series. By this technique, correlation coefficient at different scale can be estimated. Motivated by this here we have applied a new DCCA technique to find the relationship between SFI and GTA. We have also applied this technique to find the relationship between GTA and carbon di-oxide density, GTA and methane density on earth atmosphere. In future we will try to find the relationship between GTA and aerosols present in earth atmosphere, water vapour density on earth atmosphere, ozone depletion etc. This analysis will help us for better understanding about the reason behind global warming
Erasing the Milky Way: new cleaning technique applied to GBT intensity mapping data
NASA Astrophysics Data System (ADS)
Wolz, L.; Blake, C.; Abdalla, F. B.; Anderson, C. J.; Chang, T.-C.; Li, Y.-C.; Masui, K. W.; Switzer, E.; Pen, U.-L.; Voytek, T. C.; Yadav, J.
2017-02-01
We present the first application of a new foreground removal pipeline to the current leading H I intensity mapping data set, obtained by the Green Bank Telescope (GBT). We study the 15- and 1-h-field data of the GBT observations previously presented in Mausui et al. and Switzer et al., covering about 41 deg2 at 0.6 < z < 1.0, for which cross-correlations may be measured with the galaxy distribution of the WiggleZ Dark Energy Survey. In the presented pipeline, we subtract the Galactic foreground continuum and the point-source contamination using an independent component analysis technique (FASTICA), and develop a Fourier-based optimal estimator to compute the temperature power spectrum of the intensity maps and cross-correlation with the galaxy survey data. We show that FASTICA is a reliable tool to subtract diffuse and point-source emission through the non-Gaussian nature of their probability distributions. The temperature power spectra of the intensity maps are dominated by instrumental noise on small scales which FASTICA, as a conservative subtraction technique of non-Gaussian signals, cannot mitigate. However, we determine similar GBT-WiggleZ cross-correlation measurements to those obtained by the singular value decomposition (SVD) method, and confirm that foreground subtraction with FASTICA is robust against 21 cm signal loss, as seen by the converged amplitude of these cross-correlation measurements. We conclude that SVD and FASTICA are complementary methods to investigate the foregrounds and noise systematics present in intensity mapping data sets.
NASA Astrophysics Data System (ADS)
Charonko, John J.; Vlachos, Pavlos P.
2013-06-01
Numerous studies have established firmly that particle image velocimetry (PIV) is a robust method for non-invasive, quantitative measurements of fluid velocity, and that when carefully conducted, typical measurements can accurately detect displacements in digital images with a resolution well below a single pixel (in some cases well below a hundredth of a pixel). However, to date, these estimates have only been able to provide guidance on the expected error for an average measurement under specific image quality and flow conditions. This paper demonstrates a new method for estimating the uncertainty bounds to within a given confidence interval for a specific, individual measurement. Here, cross-correlation peak ratio, the ratio of primary to secondary peak height, is shown to correlate strongly with the range of observed error values for a given measurement, regardless of flow condition or image quality. This relationship is significantly stronger for phase-only generalized cross-correlation PIV processing, while the standard correlation approach showed weaker performance. Using an analytical model of the relationship derived from synthetic data sets, the uncertainty bounds at a 95% confidence interval are then computed for several artificial and experimental flow fields, and the resulting errors are shown to match closely to the predicted uncertainties. While this method stops short of being able to predict the true error for a given measurement, knowledge of the uncertainty level for a PIV experiment should provide great benefits when applying the results of PIV analysis to engineering design studies and computational fluid dynamics validation efforts. Moreover, this approach is exceptionally simple to implement and requires negligible additional computational cost.
NASA Astrophysics Data System (ADS)
Pouyandeh, Sima; Iubini, Stefano; Jurinovich, Sandro; Omar, Yasser; Mennucci, Benedetta; Piazza, Francesco
2017-12-01
In this paper, we work out a parameterization of environmental noise within the Haken-Strobl-Reinenker (HSR) model for the PE545 light-harvesting complex, based on atomic-level quantum mechanics/molecular mechanics (QM/MM) simulations. We use this approach to investigate the role of various auto- and cross-correlations in the HSR noise tensor, confirming that site-energy autocorrelations (pure dephasing) terms dominate the noise-induced exciton mobility enhancement, followed by site energy-coupling cross-correlations for specific triplets of pigments. Interestingly, several cross-correlations of the latter kind, together with coupling-coupling cross-correlations, display clear low-frequency signatures in their spectral densities in the 30-70 cm-1 region. These slow components lie at the limits of validity of the HSR approach, which requires that environmental fluctuations be faster than typical exciton transfer time scales. We show that a simple coarse-grained elastic-network-model (ENM) analysis of the PE545 protein naturally spotlights collective normal modes in this frequency range that represent specific concerted motions of the subnetwork of cysteines covalenty linked to the pigments. This analysis strongly suggests that protein scaffolds in light-harvesting complexes are able to express specific collective, low-frequency normal modes providing a fold-rooted blueprint of exciton transport pathways. We speculate that ENM-based mixed quantum classical methods, such as Ehrenfest dynamics, might be promising tools to disentangle the fundamental designing principles of these dynamical processes in natural and artificial light-harvesting structures.
NASA Astrophysics Data System (ADS)
Noda, Isao
2018-05-01
Two-trace two-dimensional (2T2D) correlation spectroscopy, where a pair of spectra are compared as 2D maps by a form of cross correlation analysis, is introduced. In 2T2D, spectral intensity changes of bands arising from the same origin, which cannot change independently of each other, are synchronized. Meanwhile, those arising from different sources may and often do change asynchronously. By taking advantage of this property, one can distinguish and classify a number of contributing bands present in the original pair of spectra in a systematic manner. Highly overlapped neighboring bands originating from different sources can also be identified by the presence of asynchronous cross peaks, thus enhancing the apparent spectral resolution. Computational procedure to obtain 2T2D correlation spectra and their interpretation method, as well as an illustrative description of the basic concept in the vector phase space, are provided. 2T2D spectra may also be viewed as individual building blocks of the generalized 2D correlation spectra derived from a series of more than two spectral data. Some promising application potentials of 2T2D correlation and integration with established advanced 2D correlation techniques are discussed.
Multiscale multifractal DCCA and complexity behaviors of return intervals for Potts price model
NASA Astrophysics Data System (ADS)
Wang, Jie; Wang, Jun; Stanley, H. Eugene
2018-02-01
To investigate the characteristics of extreme events in financial markets and the corresponding return intervals among these events, we use a Potts dynamic system to construct a random financial time series model of the attitudes of market traders. We use multiscale multifractal detrended cross-correlation analysis (MM-DCCA) and Lempel-Ziv complexity (LZC) perform numerical research of the return intervals for two significant China's stock market indices and for the proposed model. The new MM-DCCA method is based on the Hurst surface and provides more interpretable cross-correlations of the dynamic mechanism between different return interval series. We scale the LZC method with different exponents to illustrate the complexity of return intervals in different scales. Empirical studies indicate that the proposed return intervals from the Potts system and the real stock market indices hold similar statistical properties.
Bairy, Santhosh Kumar; Suneel Kumar, B V S; Bhalla, Joseph Uday Tej; Pramod, A B; Ravikumar, Muttineni
2009-04-01
c-Src kinase play an important role in cell growth and differentiation and its inhibitors can be useful for the treatment of various diseases, including cancer, osteoporosis, and metastatic bone disease. Three dimensional quantitative structure-activity relationship (3D-QSAR) studies were carried out on quinazolin derivatives inhibiting c-Src kinase. Molecular field analysis (MFA) models with four different alignment techniques, namely, GLIDE, GOLD, LIGANDFIT and Least squares based methods were developed. glide based MFA model showed better results (Leave one out cross validation correlation coefficient r(2)(cv) = 0.923 and non-cross validation correlation coefficient r(2)= 0.958) when compared with other models. These results help us to understand the nature of descriptors required for activity of these compounds and thereby provide guidelines to design novel and potent c-Src kinase inhibitors.
Tajika, Tsuyoshi; Kobayashi, Tsutomu; Yamamoto, Atsushi; Kaneko, Tetsuya; Takagishi, Kenji
2013-11-01
First, we investigated the accuracy of carpal tunnel syndrome diagnosis by comparing the cross-sectional area of the median nerve measured at the level of proximal inlet of the carpal tunnel with that measured at the level of the distal radioulnar joint on sonography. Second, we evaluated the correlation between sonographic and neurophysiologic findings and clinical findings assessed by the Carpal Tunnel Syndrome Instrument of the Japanese Society for Surgery of the Hand (JSSH). Fifty wrists in 34 patients and 81 wrists in 45 healthy volunteers were examined. The proximal cross-sectional area and the difference (Δ) between the proximal and distal cross-sectional areas were calculated for each wrist. Nerve conduction velocity tests were performed for all patients with carpal tunnel syndrome. The proximal, distal, and Δ cross-sectional areas were compared for the two groups. We examined the correlation between the proximal, distal, and Δ areas, nerve conduction velocity findings, and JSSH scores in the patients. The diagnosis of carpal tunnel syndrome determined by the Δ cross-sectional area was more accurate than the diagnosis determined by the proximal area on receiver operating characteristic curve analysis (P = .006). Statistically significant correlations were found between proximal area, Δ area, and nerve conduction velocity findings (proximal, r = 0.45; P = .0013; Δ, r = 0.44; P = .001). The proximal and distal areas were positively correlated with the JSSH symptom severity score (proximal, r= 0.39; P= .005; distal, r = 0.35; P = .014). The cross-sectional area method using sonography has excellent performance for diagnosing carpal tunnel syndrome. It was useful for measuring the proximal and distal cross-sectional areas to evaluated the symptom severity and for calculating the Δ cross-sectional area to assess motor nerve damage in patients with carpal tunnel syndrome.
Gíslason, Magnús; Sigurðsson, Sigurður; Guðnason, Vilmundur; Harris, Tamara; Carraro, Ugo; Gargiulo, Paolo
2018-01-01
Sarcopenic muscular degeneration has been consistently identified as an independent risk factor for mortality in aging populations. Recent investigations have realized the quantitative potential of computed tomography (CT) image analysis to describe skeletal muscle volume and composition; however, the optimum approach to assessing these data remains debated. Current literature reports average Hounsfield unit (HU) values and/or segmented soft tissue cross-sectional areas to investigate muscle quality. However, standardized methods for CT analyses and their utility as a comorbidity index remain undefined, and no existing studies compare these methods to the assessment of entire radiodensitometric distributions. The primary aim of this study was to present a comparison of nonlinear trimodal regression analysis (NTRA) parameters of entire radiodensitometric muscle distributions against extant CT metrics and their correlation with lower extremity function (LEF) biometrics (normal/fast gait speed, timed up-and-go, and isometric leg strength) and biochemical and nutritional parameters, such as total solubilized cholesterol (SCHOL) and body mass index (BMI). Data were obtained from 3,162 subjects, aged 66–96 years, from the population-based AGES-Reykjavik Study. 1-D k-means clustering was employed to discretize each biometric and comorbidity dataset into twelve subpopulations, in accordance with Sturges’ Formula for Class Selection. Dataset linear regressions were performed against eleven NTRA distribution parameters and standard CT analyses (fat/muscle cross-sectional area and average HU value). Parameters from NTRA and CT standards were analogously assembled by age and sex. Analysis of specific NTRA parameters with standard CT results showed linear correlation coefficients greater than 0.85, but multiple regression analysis of correlative NTRA parameters yielded a correlation coefficient of 0.99 (P<0.005). These results highlight the specificities of each muscle quality metric to LEF biometrics, SCHOL, and BMI, and particularly highlight the value of the connective tissue regime in this regard. PMID:29513690
Edmunds, Kyle; Gíslason, Magnús; Sigurðsson, Sigurður; Guðnason, Vilmundur; Harris, Tamara; Carraro, Ugo; Gargiulo, Paolo
2018-01-01
Sarcopenic muscular degeneration has been consistently identified as an independent risk factor for mortality in aging populations. Recent investigations have realized the quantitative potential of computed tomography (CT) image analysis to describe skeletal muscle volume and composition; however, the optimum approach to assessing these data remains debated. Current literature reports average Hounsfield unit (HU) values and/or segmented soft tissue cross-sectional areas to investigate muscle quality. However, standardized methods for CT analyses and their utility as a comorbidity index remain undefined, and no existing studies compare these methods to the assessment of entire radiodensitometric distributions. The primary aim of this study was to present a comparison of nonlinear trimodal regression analysis (NTRA) parameters of entire radiodensitometric muscle distributions against extant CT metrics and their correlation with lower extremity function (LEF) biometrics (normal/fast gait speed, timed up-and-go, and isometric leg strength) and biochemical and nutritional parameters, such as total solubilized cholesterol (SCHOL) and body mass index (BMI). Data were obtained from 3,162 subjects, aged 66-96 years, from the population-based AGES-Reykjavik Study. 1-D k-means clustering was employed to discretize each biometric and comorbidity dataset into twelve subpopulations, in accordance with Sturges' Formula for Class Selection. Dataset linear regressions were performed against eleven NTRA distribution parameters and standard CT analyses (fat/muscle cross-sectional area and average HU value). Parameters from NTRA and CT standards were analogously assembled by age and sex. Analysis of specific NTRA parameters with standard CT results showed linear correlation coefficients greater than 0.85, but multiple regression analysis of correlative NTRA parameters yielded a correlation coefficient of 0.99 (P<0.005). These results highlight the specificities of each muscle quality metric to LEF biometrics, SCHOL, and BMI, and particularly highlight the value of the connective tissue regime in this regard.
The behaviour of share returns of football clubs: An econophysics approach
NASA Astrophysics Data System (ADS)
Ferreira, Paulo; Loures, Luís; Nunes, José Rato; Dionísio, Andreia
2017-04-01
Football is a sport that moves thousands of people and millions of euros. Since 1983, several clubs entered the stock markets with shares, and now twenty two clubs are listed in the Stoxx Football Index. In this study, we analyse the behaviour of the return rates of such shares, with Detrended Fluctuation Analysis and Detrended Cross-Correlation Analysis (and its correlation coefficient). With Detrended Fluctuation Analysis, we are able to observe that the shares of several clubs are far from the behaviour of a random walk, which is expected by the theory. Using Detrended Cross-Correlation Analysis, we calculate the cross correlations of clubs' returns with national indexes and then with the Stoxx Football Index. Although almost all of them are positive, they do not seem to be strong.
Application of ultrasonic signature analysis for fatigue detection in complex structures
NASA Technical Reports Server (NTRS)
Zuckerwar, A. J.
1974-01-01
Ultrasonic signature analysis shows promise of being a singularly well-suited method for detecting fatigue in structures as complex as aircraft. The method employs instrumentation centered about a Fourier analyzer system, which features analog-to-digital conversion, digital data processing, and digital display of cross-correlation functions and cross-spectra. These features are essential to the analysis of ultrasonic signatures according to the procedure described here. In order to establish the feasibility of the method, the initial experiments were confined to simple plates with simulated and fatigue-induced defects respectively. In the first test the signature proved sensitive to the size of a small hole drilled into the plate. In the second test, performed on a series of fatigue-loaded plates, the signature proved capable of indicating both the initial appearance and subsequent growth of a fatigue crack. In view of these encouraging results it is concluded that the method has reached a sufficiently advanced stage of development to warrant application to small-scale structures or even actual aircraft.
Cross-correlations between agricultural commodity futures markets in the US and China
NASA Astrophysics Data System (ADS)
Li, Zhihui; Lu, Xinsheng
2012-08-01
This paper examines the cross-correlation properties of agricultural futures markets between the US and China using a cross-correlation statistic test and multifractal detrended cross-correlation analysis (MF-DCCA). The results show that the cross-correlations between the two geographically distant markets for four pairs of important agricultural commodities futures are significantly multifractal. By introducing the concept of a “crossover”, we find that the multifractality of cross-correlations between the two markets is not long lasting. The cross-correlations in the short term are more strongly multifractal, but they are weakly so in the long term. Moreover, cross-correlations of small fluctuations are persistent and those of large fluctuations are anti-persistent in the short term while cross-correlations of all kinds of fluctuations for soy bean and soy meal futures are persistent and for corn and wheat futures are anti-persistent in the long term. We also find that cross-correlation exponents are less than the averaged generalized Hurst exponent when q<0 and more than the averaged generalized Hurst exponent when q>0 in the short term, while in the long term they are almost the same.
Price-volume multifractal analysis and its application in Chinese stock markets
NASA Astrophysics Data System (ADS)
Yuan, Ying; Zhuang, Xin-tian; Liu, Zhi-ying
2012-06-01
An empirical research on Chinese stock markets is conducted using statistical tools. First, the multifractality of stock price return series, ri(ri=ln(Pt+1)-ln(Pt)) and trading volume variation series, vi(vi=ln(Vt+1)-ln(Vt)) is confirmed using multifractal detrended fluctuation analysis. Furthermore, a multifractal detrended cross-correlation analysis between stock price return and trading volume variation in Chinese stock markets is also conducted. It is shown that the cross relationship between them is also found to be multifractal. Second, the cross-correlation between stock price Pi and trading volume Vi is empirically studied using cross-correlation function and detrended cross-correlation analysis. It is found that both Shanghai stock market and Shenzhen stock market show pronounced long-range cross-correlations between stock price and trading volume. Third, a composite index R based on price and trading volume is introduced. Compared with stock price return series ri and trading volume variation series vi, R variation series not only remain the characteristics of original series but also demonstrate the relative correlation between stock price and trading volume. Finally, we analyze the multifractal characteristics of R variation series before and after three financial events in China (namely, Price Limits, Reform of Non-tradable Shares and financial crisis in 2008) in the whole period of sample to study the changes of stock market fluctuation and financial risk. It is found that the empirical results verified the validity of R.
NASA Astrophysics Data System (ADS)
Ryabinin, Gennadiy; Gavrilov, Valeriy; Polyakov, Yuriy; Timashev, Serge
2012-06-01
We propose a new type of earthquake precursor based on the analysis of correlation dynamics between geophysical signals of different nature. The precursor is found using a two-parameter cross-correlation function introduced within the framework of flicker-noise spectroscopy, a general statistical physics approach to the analysis of time series. We consider an example of cross-correlation analysis for water salinity time series, an integral characteristic of the chemical composition of groundwater, and geoacoustic emissions recorded at the G-1 borehole on the Kamchatka peninsula in the time frame from 2001 to 2003, which is characterized by a sequence of three groups of significant seismic events. We found that cross-correlation precursors took place 27, 31, and 35 days ahead of the strongest earthquakes for each group of seismic events, respectively. At the same time, precursory anomalies in the signals themselves were observed only in the geoacoustic emissions for one group of earthquakes.
Zhou, Yunyi; Tao, Chenyang; Lu, Wenlian; Feng, Jianfeng
2018-04-20
Functional connectivity is among the most important tools to study brain. The correlation coefficient, between time series of different brain areas, is the most popular method to quantify functional connectivity. Correlation coefficient in practical use assumes the data to be temporally independent. However, the time series data of brain can manifest significant temporal auto-correlation. A widely applicable method is proposed for correcting temporal auto-correlation. We considered two types of time series models: (1) auto-regressive-moving-average model, (2) nonlinear dynamical system model with noisy fluctuations, and derived their respective asymptotic distributions of correlation coefficient. These two types of models are most commonly used in neuroscience studies. We show the respective asymptotic distributions share a unified expression. We have verified the validity of our method, and shown our method exhibited sufficient statistical power for detecting true correlation on numerical experiments. Employing our method on real dataset yields more robust functional network and higher classification accuracy than conventional methods. Our method robustly controls the type I error while maintaining sufficient statistical power for detecting true correlation in numerical experiments, where existing methods measuring association (linear and nonlinear) fail. In this work, we proposed a widely applicable approach for correcting the effect of temporal auto-correlation on functional connectivity. Empirical results favor the use of our method in functional network analysis. Copyright © 2018. Published by Elsevier B.V.
Cross Correlation versus Normalized Mutual Information on Image Registration
NASA Technical Reports Server (NTRS)
Tan, Bin; Tilton, James C.; Lin, Guoqing
2016-01-01
This is the first study to quantitatively assess and compare cross correlation and normalized mutual information methods used to register images in subpixel scale. The study shows that the normalized mutual information method is less sensitive to unaligned edges due to the spectral response differences than is cross correlation. This characteristic makes the normalized image resolution a better candidate for band to band registration. Improved band-to-band registration in the data from satellite-borne instruments will result in improved retrievals of key science measurements such as cloud properties, vegetation, snow and fire.
Radioisotope measurements of the liquid-gas flow in the horizontal pipeline using phase method
NASA Astrophysics Data System (ADS)
Hanus, Robert; Zych, Marcin; Jaszczur, Marek; Petryka, Leszek; Świsulski, Dariusz
2018-06-01
The paper presents application of the gamma-absorption method to a two-phase liquid-gas flow investigation in a horizontal pipeline. The water-air mixture was examined by a set of two Am-241 radioactive sources and two NaI(Tl) scintillation probes. For analysis of the electrical signals obtained from detectors the cross-spectral density function (CSDF) was applied. Results of the gas phase average velocity measurements for CSDF were compared with results obtained by application of the classical cross-correlation function (CCF). It was found that the combined uncertainties of the gas-phase velocity in the presented experiments did not exceed 1.6% for CSDF method and 5.5% for CCF.
NASA Astrophysics Data System (ADS)
Schroer, M. A.; Gutt, C.; Grübel, G.
2014-07-01
Recently the analysis of scattering patterns by angular cross-correlation analysis (CCA) was introduced to reveal the orientational order in disordered samples with special focus to future applications on x-ray free-electron laser facilities. We apply this CCA approach to ultra-small-angle light-scattering data obtained from two-dimensional monolayers of microspheres. The films were studied in addition by optical microscopy. This combined approach allows to calculate the cross-correlations of the scattering patterns, characterized by the orientational correlation function Ψl(q), as well as to obtain the real-space structure of the monolayers. We show that CCA is sensitive to the orientational order of monolayers formed by the microspheres which are not directly visible from the scattering patterns. By mixing microspheres of different radii the sizes of ordered monolayer domains is reduced. For these samples it is shown that Ψl(q) quantitatively describes the degree of hexagonal order of the two-dimensional films. The experimental CCA results are compared with calculations based on the microscopy images. Both techniques show qualitatively similar features. Differences can be attributed to the wave-front distortion of the laser beam in the experiment. This effect is discussed by investigating the effect of different wave fronts on the cross-correlation analysis results. The so-determined characteristics of the cross-correlation analysis will be also relevant for future x-ray-based studies.
Wang, Fang
2016-06-01
In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρDXA, contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.
NASA Astrophysics Data System (ADS)
Dong, Keqiang; Gao, You; Jing, Liming
2015-02-01
The presence of cross-correlation in complex systems has long been noted and studied in a broad range of physical applications. We here focus on an aero-engine system as an example of a complex system. By applying the detrended cross-correlation (DCCA) coefficient method to aero-engine time series, we investigate the effects of the data length and the time scale on the detrended cross-correlation coefficients ρ DCCA ( T, s). We then show, for a twin-engine aircraft, that the engine fuel flow time series derived from the left engine and the right engine exhibit much stronger cross-correlations than the engine exhaust-gas temperature series derived from the left engine and the right engine do.
Monitoring volcanic activity using correlation patterns between infrasound and ground motion
NASA Astrophysics Data System (ADS)
Ichihara, M.; Takeo, M.; Yokoo, A.; Oikawa, J.; Ohminato, T.
2012-02-01
This paper presents a simple method to distinguish infrasonic signals from wind noise using a cross-correlation function of signals from a microphone and a collocated seismometer. The method makes use of a particular feature of the cross-correlation function of vertical ground motion generated by infrasound, and the infrasound itself. Contribution of wind noise to the correlation function is effectively suppressed by separating the microphone and the seismometer by several meters because the correlation length of wind noise is much shorter than wavelengths of infrasound. The method is applied to data from two recent eruptions of Asama and Shinmoe-dake volcanoes, Japan, and demonstrates that the method effectively detects not only the main eruptions, but also minor activity generating weak infrasound hardly visible in the wave traces. In addition, the correlation function gives more information about volcanic activity than infrasound alone, because it reflects both features of incident infrasonic and seismic waves. Therefore, a graphical presentation of temporal variation in the cross-correlation function enables one to see qualitative changes of eruptive activity at a glance. This method is particularly useful when available sensors are limited, and will extend the utility of a single microphone and seismometer in monitoring volcanic activity.
NASA Astrophysics Data System (ADS)
Corciulo, M.; Roux, P.; Campillo, M.; Dubucq, D.
2010-12-01
Passive imaging from noise cross-correlation is a consolidated analysis applied at continental and regional scale whereas its use at local scale for seismic exploration purposes is still uncertain. The development of passive imaging by cross-correlation analysis is based on the extraction of the Green’s function from seismic noise data. In a completely random field in time and space, the cross-correlation permits to retrieve the complete Green’s function whatever the complexity of the medium. At the exploration scale and at frequency above 2 Hz, the noise sources are not ideally distributed around the stations which strongly affect the extraction of the direct arrivals from the noise cross-correlation process. In order to overcome this problem, the coda waves extracted from noise correlation could be useful. Coda waves describe long and scattered paths sampling the medium in different ways such that they become sensitive to weak velocity variations without being dependent on the noise source distribution. Indeed, scatters in the medium behave as a set of secondary noise sources which randomize the spatial distribution of noise sources contributing to the coda waves in the correlation process. We developed a new technique to measure weak velocity changes based on the computation of the local phase variations (instantaneous phase variation or IPV) of the cross-correlated signals. This newly-developed technique takes advantage from the doublet and stretching techniques classically used to monitor weak velocity variation from coda waves. We apply IPV to data acquired in Northern America (Canada) on a 1-km side square seismic network laid out by 397 stations. Data used to study temporal variations are cross-correlated signals computed on 10-minutes ambient noise in the frequency band 2-5 Hz. As the data set was acquired over five days, about 660 files are processed to perform a complete temporal analysis for each stations pair. The IPV permits to estimate the phase shift all over the signal length without any assumption on the medium velocity. The instantaneous phase is computed using the Hilbert transform of the signal. For each stations pair, we measure the phase difference between successive correlation functions calculated for 10 minutes of ambient noise. We then fit the instantaneous phase shift using a first-order polynomial function. The measure of the velocity variation corresponds to the slope of this fit. Compared to other techniques, the advantage of IPV is a very fast procedure which efficiently provides the measure of velocity variation on large data sets. Both experimental results and numerical tests on synthetic signals will be presented to assess the reliability of the IPV technique, with comparison to the doublet and stretching methods.
Hebert, Benedict; Costantino, Santiago; Wiseman, Paul W
2005-05-01
We introduce a new extension of image correlation spectroscopy (ICS) and image cross-correlation spectroscopy (ICCS) that relies on complete analysis of both the temporal and spatial correlation lags for intensity fluctuations from a laser-scanning microscopy image series. This new approach allows measurement of both diffusion coefficients and velocity vectors (magnitude and direction) for fluorescently labeled membrane proteins in living cells through monitoring of the time evolution of the full space-time correlation function. By using filtering in Fourier space to remove frequencies associated with immobile components, we are able to measure the protein transport even in the presence of a large fraction (>90%) of immobile species. We present the background theory, computer simulations, and analysis of measurements on fluorescent microspheres to demonstrate proof of principle, capabilities, and limitations of the method. We demonstrate mapping of flow vectors for mixed samples containing fluorescent microspheres with different emission wavelengths using space time image cross-correlation. We also present results from two-photon laser-scanning microscopy studies of alpha-actinin/enhanced green fluorescent protein fusion constructs at the basal membrane of living CHO cells. Using space-time image correlation spectroscopy (STICS), we are able to measure protein fluxes with magnitudes of mum/min from retracting lamellar regions and protrusions for adherent cells. We also demonstrate the measurement of correlated directed flows (magnitudes of mum/min) and diffusion of interacting alpha5 integrin/enhanced cyan fluorescent protein and alpha-actinin/enhanced yellow fluorescent protein within living CHO cells. The STICS method permits us to generate complete transport maps of proteins within subregions of the basal membrane even if the protein concentration is too high to perform single particle tracking measurements.
NASA Astrophysics Data System (ADS)
Pérez-Ràfols, Ignasi; Font-Ribera, Andreu; Miralda-Escudé, Jordi; Blomqvist, Michael; Bird, Simeon; Busca, Nicolás; du Mas des Bourboux, Hélion; Mas-Ribas, Lluís; Noterdaeme, Pasquier; Petitjean, Patrick; Rich, James; Schneider, Donald P.
2018-01-01
We present a measurement of the damped Ly α absorber (DLA) mean bias from the cross-correlation of DLAs and the Ly α forest, updating earlier results of Font-Ribera et al. (2012) with the final Baryon Oscillations Spectroscopic Survey data release and an improved method to address continuum fitting corrections. Our cross-correlation is well fitted by linear theory with the standard ΛCDM model, with a DLA bias of bDLA = 1.99 ± 0.11; a more conservative analysis, which removes DLA in the Ly β forest and uses only the cross-correlation at r > 10 h-1 Mpc, yields bDLA = 2.00 ± 0.19. This assumes the cosmological model from Planck Collaboration (2016) and the Ly α forest bias factors of Bautista et al. (2017) and includes only statistical errors obtained from bootstrap analysis. The main systematic errors arise from possible impurities and selection effects in the DLA catalogue and from uncertainties in the determination of the Ly α forest bias factors and a correction for effects of high column density absorbers. We find no dependence of the DLA bias on column density or redshift. The measured bias value corresponds to a host halo mass ∼4 × 1011 h-1 M⊙ if all DLAs were hosted in haloes of a similar mass. In a realistic model where host haloes over a broad mass range have a DLA cross-section Σ (M_h) ∝ M_h^{α } down to Mh > Mmin = 108.5 h-1 M⊙, we find that α > 1 is required to have bDLA > 1.7, implying a steeper relation or higher value of Mmin than is generally predicted in numerical simulations of galaxy formation.
ERIC Educational Resources Information Center
Melby-Lervag, Monica; Lervag, Arne
2011-01-01
We present a meta-analysis of cross-linguistic transfer of oral language (vocabulary and listening comprehension), phonology (decoding and phonological awareness) and reading comprehension. Our findings show a small meta-correlation between first (L1) and second (L2) oral language and a moderate to large correlation between L1 and L2 phonological…
Rodrigues, Marcelo F; Michel-Crosato, Edgard; Cardoso, Jefferson R; Traebert, Jefferson
2009-06-01
Cross-cultural translation and psychometric testing. To translate and cross-culturally adapt the Quebec Back Pain Disability Scale (QDS) to Brazilian Portuguese and to examine its validity and reliability. Current literature shows the need to adopt reliable and internationally standardized methods for the analysis of low back pain. To our knowledge, this specific questionnaire has not been translated and validated for Portuguese-speaking patients. The translation and cross-cultural adaptation of the QDS were developed in agreement with internationally recommended methodology, and the resulting product was evaluated in this study with 54 consecutive patients. Internal consistency was obtained through Cronbach's alpha; reliability was estimated through the intraclass correlation coefficient and the Bland and Altman agreement (d = mean difference). Validity was determined by correlating the scores of the Brazil-QDS with the Brazilian version of the Roland-Morris Questionnaire and Visual Analogue Pain Scale by means of the Spearman rank correlation coefficient. The internal consistency obtained was excellent (Cronbach's alpha = 0.97). Intraobserver and interobserver reliability were considered strong (ICC = 0.93-d = 0.68 and 0.96-d = 0.57, respectively). The correlation with Brazilian Roland-Morris Questionnaire and with the Visual Analogue Scale was high (r = 0.857; r = 0.758, respectively). The data showed that the process of translation and cross-cultural adaptation were successful and that the adapted instrument demonstrated excellent psychometric properties.
Huang, Wenzhu; Zhen, Tengkun; Zhang, Wentao; Zhang, Fusheng; Li, Fang
2015-01-01
Static strain can be detected by measuring a cross-correlation of reflection spectra from two fiber Bragg gratings (FBGs). However, the static-strain measurement resolution is limited by the dominant Gaussian noise source when using this traditional method. This paper presents a novel static-strain demodulation algorithm for FBG-based Fabry-Perot interferometers (FBG-FPs). The Hilbert transform is proposed for changing the Gaussian distribution of the two FBG-FPs’ reflection spectra, and a cross third-order cumulant is used to use the results of the Hilbert transform and get a group of noise-vanished signals which can be used to accurately calculate the wavelength difference of the two FBG-FPs. The benefit by these processes is that Gaussian noise in the spectra can be suppressed completely in theory and a higher resolution can be reached. In order to verify the precision and flexibility of this algorithm, a detailed theory model and a simulation analysis are given, and an experiment is implemented. As a result, a static-strain resolution of 0.9 nε under laboratory environment condition is achieved, showing a higher resolution than the traditional cross-correlation method. PMID:25923938
Huang, Wenzhu; Zhen, Tengkun; Zhang, Wentao; Zhang, Fusheng; Li, Fang
2015-04-27
Static strain can be detected by measuring a cross-correlation of reflection spectra from two fiber Bragg gratings (FBGs). However, the static-strain measurement resolution is limited by the dominant Gaussian noise source when using this traditional method. This paper presents a novel static-strain demodulation algorithm for FBG-based Fabry-Perot interferometers (FBG-FPs). The Hilbert transform is proposed for changing the Gaussian distribution of the two FBG-FPs' reflection spectra, and a cross third-order cumulant is used to use the results of the Hilbert transform and get a group of noise-vanished signals which can be used to accurately calculate the wavelength difference of the two FBG-FPs. The benefit by these processes is that Gaussian noise in the spectra can be suppressed completely in theory and a higher resolution can be reached. In order to verify the precision and flexibility of this algorithm, a detailed theory model and a simulation analysis are given, and an experiment is implemented. As a result, a static-strain resolution of 0.9 nε under laboratory environment condition is achieved, showing a higher resolution than the traditional cross-correlation method.
Long-range correlation and market segmentation in bond market
NASA Astrophysics Data System (ADS)
Wang, Zhongxing; Yan, Yan; Chen, Xiaosong
2017-09-01
This paper investigates the long-range auto-correlations and cross-correlations in bond market. Based on Detrended Moving Average (DMA) method, empirical results present a clear evidence of long-range persistence that exists in one year scale. The degree of long-range correlation related to maturities has an upward tendency with a peak in short term. These findings confirm the expectations of fractal market hypothesis (FMH). Furthermore, we have developed a method based on a complex network to study the long-range cross-correlation structure and applied it to our data, and found a clear pattern of market segmentation in the long run. We also detected the nature of long-range correlation in the sub-period 2007-2012 and 2011-2016. The result from our research shows that long-range auto-correlations are decreasing in the recent years while long-range cross-correlations are strengthening.
Mackeen, Mukram; Almond, Andrew; Cumpstey, Ian; Enis, Seth C; Kupce, Eriks; Butters, Terry D; Fairbanks, Antony J; Dwek, Raymond A; Wormald, Mark R
2006-06-07
The experimental determination of oligosaccharide conformations has traditionally used cross-linkage 1H-1H NOE/ROEs. As relatively few NOEs are observed, to provide sufficient conformational constraints this method relies on: accurate quantification of NOE intensities (positive constraints); analysis of absent NOEs (negative constraints); and hence calculation of inter-proton distances using the two-spin approximation. We have compared the results obtained by using 1H 2D NOESY, ROESY and T-ROESY experiments at 500 and 700 MHz to determine the conformation of the terminal Glc alpha1-2Glc alpha linkage in a dodecasaccharide and a related tetrasaccharide. For the tetrasaccharide, the NOESY and ROESY spectra produced the same qualitative pattern of linkage cross-peaks but the quantitative pattern, the relative peak intensities, was different. For the dodecasaccharide, the NOESY and ROESY spectra at 500 MHz produced a different qualitative pattern of linkage cross-peaks, with fewer peaks in the NOESY spectrum. At 700 MHz, the NOESY and ROESY spectra of the dodecasaccharide produced the same qualitative pattern of peaks, but again the relative peak intensities were different. These differences are due to very significant differences in the local correlation times for different proton pairs across this glycosidic linkage. The local correlation time for each proton pair was measured using the ratio of the NOESY and T-ROESY cross-relaxation rates, leaving the NOESY and ROESY as independent data sets for calculating the inter-proton distances. The inter-proton distances calculated including the effects of differences in local correlation times give much more consistent results.
A method to determine agro-climatic zones based on correlation and cluster analyses
NASA Astrophysics Data System (ADS)
Borges Valeriano, Taynara Tuany; de Souza Rolim, Glauco; de Oliveira Aparecido, Lucas Eduardo
2017-12-01
Determining agro-climatic zones (ACZs) is traditionally made by cross-comparing meteorological elements such as air temperature, rainfall, and water deficit (DEF). This study proposes a new method based on correlations between monthly DEFs during the crop cycle and annual yield and performs a multivariate cluster analysis on these correlations. This `correlation method' was applied to all municipalities in the state of São Paulo to determine ACZs for coffee plantations. A traditional ACZ method for coffee, which is based on temperature and DEF ranges (Evangelista et al.; RBEAA, 6:445-452, 2002), was applied to the study area to compare against the correlation method. The traditional ACZ classified the "Alta Mogina," "Média Mogiana," and "Garça and Marília" regions as traditional coffee regions that were either suitable or even restricted for coffee plantations. These traditional regions have produced coffee since 1800 and should not be classified as restricted. The correlation method classified those areas as high-producing regions and expanded them into other areas. The proposed method is innovative, because it is more detailed than common ACZ methods. Each developmental crop phase was analyzed based on correlations between the monthly DEF and yield, improving the importance of crop physiology in relation to climate.
Pneumatic testing in 45-degree-inclined boreholes in ash-flow tuff near Superior, Arizona
LeCain, G.D.
1995-01-01
Matrix permeability values determined by single-hole pneumatic testing in nonfractured ash-flow tuff ranged from 5.1 to 20.3 * 1046 m2 (meters squared), depending on the gas-injection rate and analysis method used. Results from the single-hole tests showed several significant correlations between permeability and injection rate and between permeability and test order. Fracture permeability values determined by cross-hole pneumatic testing in fractured ash-flow tuff ranged from 0.81 to 3.49 * 1044 m2, depending on injection rate and analysis method used. Results from the cross-hole tests monitor intervals showed no significant correlation between permeability and injection rate; however, results from the injection interval showed a significant correlation between injection rate and permeability. Porosity estimates from the 'cross-hole testing range from 0.8 to 2.0 percent. The maximum temperature change associated with the pneumatic testing was 1.2'(2 measured in the injection interval during cross-hole testing. The maximum temperature change in the guard and monitor intervals was O.Ip C. The maximum error introduced into the permeability values due to temperature fluctuations is approximately 4 percent. Data from temperature monitoring in the borehole indicated a positive correlation between the temperature decrease in the injection interval during recovery testing and the gas-injection rate. The thermocouple psychrometers indicated that water vapor was condensing in the boreholes during testing. The psychrometers in the guard and monitor intervals detected the drier injected gas as an increase in the dry bulb reading. The relative humidity in the test intervals was always higher than the upper measurement limit of the psychrometers. Although the installation of the packer system may have altered the water balance of the borehole, the gas-injection testing resulted in minimal or no changes in the borehole relative humidity.
Vivas, M; Silveira, S F; Viana, A P; Amaral, A T; Cardoso, D L; Pereira, M G
2014-07-02
Diallel crossing methods provide information regarding the performance of genitors between themselves and their hybrid combinations. However, with a large number of parents, the number of hybrid combinations that can be obtained and evaluated become limited. One option regarding the number of parents involved is the adoption of circulant diallels. However, information is lacking regarding diallel analysis using mixed models. This study aimed to evaluate the efficacy of the method of linear mixed models to estimate, for variable resistance to foliar fungal diseases, components of general and specific combining ability in a circulant table with different s values. Subsequently, 50 diallels were simulated for each s value, and the correlations and estimates of the combining abilities of the different diallel combinations were analyzed. The circulant diallel method using mixed modeling was effective in the classification of genitors regarding their combining abilities relative to the complete diallels. The numbers of crosses in which each genitor(s) will compose the circulant diallel and the estimated heritability affect the combining ability estimates. With three crosses per parent, it is possible to obtain good concordance (correlation above 0.8) between the combining ability estimates.
NASA Astrophysics Data System (ADS)
Zhang, Qiong; Peng, Cong; Lu, Yiming; Wang, Hao; Zhu, Kaiguang
2018-04-01
A novel technique is developed to level airborne geophysical data using principal component analysis based on flight line difference. In the paper, flight line difference is introduced to enhance the features of levelling error for airborne electromagnetic (AEM) data and improve the correlation between pseudo tie lines. Thus we conduct levelling to the flight line difference data instead of to the original AEM data directly. Pseudo tie lines are selected distributively cross profile direction, avoiding the anomalous regions. Since the levelling errors of selective pseudo tie lines show high correlations, principal component analysis is applied to extract the local levelling errors by low-order principal components reconstruction. Furthermore, we can obtain the levelling errors of original AEM data through inverse difference after spatial interpolation. This levelling method does not need to fly tie lines and design the levelling fitting function. The effectiveness of this method is demonstrated by the levelling results of survey data, comparing with the results from tie-line levelling and flight-line correlation levelling.
Spatial fluorescence cross-correlation spectroscopy between core and ring pinholes
NASA Astrophysics Data System (ADS)
Blancquaert, Yoann; Delon, Antoine; Derouard, Jacques; Jaffiol, Rodolphe
2006-04-01
Fluorescence Correlation Spectroscopy (FCS) is an attractive method to measure molecular concentration, mobility parameters and chemical kinetics. However its ability to descriminate different diffusing species needs to be improved. Recently, we have proposed a simplified spatial Fluorescence cross Correlation Spectroscopy (sFCCS) method, allowing, with only one focused laser beam to obtain two confocal volumes spatially shifted. Now, we present a new sFCCS optical geometry where the two pinholes, a ring and core, are encapsulated one in the other. In this approach all physical and chemical processes that occur in a single volume, like singlet-triplet dynamics and photobleaching, can be eliminated; moreover, this new optical geometry optimises the collection of fluorescence. The first cross Correlation curves for Rhodamine 6G (Rh6G) in Ethanol are presented, in addition to the effect of the size of fluorescent particules (nano-beads, diameters : 20, 100 and 200 nm). The relative simplicity of the method leads us to propose sFCCS as an appropriate method for the determination of diffusion parameters of fluorophores in solution or cells. Nevertheless, progresses in the ingeniering of the optical Molecular Detection Efficiency volumes are highly desirable, in order to improve the descrimination between the cross correlated volumes.
THE DiskMass SURVEY. III. STELLAR KINEMATICS VIA CROSS-CORRELATION
DOE Office of Scientific and Technical Information (OSTI.GOV)
Westfall, Kyle B.; Bershady, Matthew A.; Verheijen, Marc A. W., E-mail: westfall@astro.rug.nl, E-mail: mab@astro.wisc.edu, E-mail: verheyen@astro.rug.nl
2011-03-15
We describe a new cross-correlation (CC) approach used by our survey to derive stellar kinematics from galaxy-continuum spectroscopy. This approach adopts the formal error analysis derived by Statler, but properly handles spectral masks. Thus, we address the primary concerns regarding application of the CC method to censored data, while maintaining its primary advantage by consolidating kinematic and template-mismatch information toward different regions of the CC function. We identify a systematic error in the nominal CC method of approximately 10% in velocity dispersion incurred by a mistreatment of detector-censored data, which is eliminated by our new method. We derive our approachmore » from first principles, and we use Monte Carlo simulations to demonstrate its efficacy. An identical set of Monte Carlo simulations performed using the well-established penalized-pixel-fitting code of Cappellari and Emsellem compares favorably with the results from our newly implemented software. Finally, we provide a practical demonstration of this software by extracting stellar kinematics from SparsePak spectra of UGC 6918.« less
Analysis of radiometric signal in sedimentating suspension flow in open channel
NASA Astrophysics Data System (ADS)
Zych, Marcin; Hanus, Robert; Petryka, Leszek; Świsulski, Dariusz; Doktor, Marek; Mastej, Wojciech
2015-05-01
The article discusses issues related to the estimation of the sedimentating solid particles average flow velocity in an open channel using radiometric methods. Due to the composition of the compound, which formed water and diatomite, received data have a very weak signal to noise ratio. In the process analysis the known determining of the solid phase transportation time delay the classical cross-correlation function is the most reliable method. The use of advanced frequency analysis based on mutual spectral density function and wavelet transform of recorded signals allows a reduction of the noise contribution.
Jain, Meena; Tandon, Shourya; Sharma, Ankur; Jain, Vishal; Rani Yadav, Nisha
2018-01-01
Background: An appropriate scale to assess the dental anxiety of Hindi speaking population is lacking. This study, therefore, aims to evaluate the psychometric properties of Hindi version of one of the oldest dental anxiety scale, Corah’s Dental Anxiety Scale (CDAS) in Hindi speaking Indian adults. Methods: A total of 348 subjects from the outpatient department of a dental hospital in India participated in this cross-sectional study. The scale was cross-culturally adapted by forward and backward translation, committee review and pretesting method. The construct validity of the translated scale was explored with exploratory factor analysis. The correlation of the Hindi version of CDAS with visual analogue scale (VAS) was used to measure the convergent validity. Reliability was assessed through calculations of Cronbach’s alpha and intra class correlation 48 forms were completed for test-retest. Results: Prevalence of dental anxiety in the sample within the age range of 18-80 years was 85.63% [95% CI: 0.815-0.891]. The response rate was 100 %. Kaiser-Meyer-Olkin (KMO) test value was 0.776. After factor analysis, a single factor (dental anxiety) was obtained with 4 items.The single factor model explained 61% variance. Pearson correlation coefficient between CDASand VAS was 0.494. Test-retest showed the Cronbach’s alpha value of 0.814. The test-retest intraclass correlation coefficient of the total CDAS score was 0.881 [95% CI: 0.318-0.554]. Conclusion: Hindi version of CDAS is a valid and reliable scale to assess dental anxiety in Hindi speaking population. Convergent validity is well recognized but discriminant validity is limited and requires further study. PMID:29744307
Jain, Meena; Tandon, Shourya; Sharma, Ankur; Jain, Vishal; Rani Yadav, Nisha
2018-01-01
Background: An appropriate scale to assess the dental anxiety of Hindi speaking population is lacking. This study, therefore, aims to evaluate the psychometric properties of Hindi version of one of the oldest dental anxiety scale, Corah's Dental Anxiety Scale (CDAS) in Hindi speaking Indian adults. Methods: A total of 348 subjects from the outpatient department of a dental hospital in India participated in this cross-sectional study. The scale was cross-culturally adapted by forward and backward translation, committee review and pretesting method. The construct validity of the translated scale was explored with exploratory factor analysis. The correlation of the Hindi version of CDAS with visual analogue scale (VAS) was used to measure the convergent validity. Reliability was assessed through calculations of Cronbach's alpha and intra class correlation 48 forms were completed for test-retest. Results: Prevalence of dental anxiety in the sample within the age range of 18-80 years was 85.63% [95% CI: 0.815-0.891]. The response rate was 100 %. Kaiser-Meyer-Olkin (KMO) test value was 0.776. After factor analysis, a single factor (dental anxiety) was obtained with 4 items.The single factor model explained 61% variance. Pearson correlation coefficient between CDASand VAS was 0.494. Test-retest showed the Cronbach's alpha value of 0.814. The test-retest intraclass correlation coefficient of the total CDAS score was 0.881 [95% CI: 0.318-0.554]. Conclusion: Hindi version of CDAS is a valid and reliable scale to assess dental anxiety in Hindi speaking population. Convergent validity is well recognized but discriminant validity is limited and requires further study.
Macro elemental analysis of food samples by nuclear analytical technique
NASA Astrophysics Data System (ADS)
Syahfitri, W. Y. N.; Kurniawati, S.; Adventini, N.; Damastuti, E.; Lestiani, D. D.
2017-06-01
Energy-dispersive X-ray fluorescence (EDXRF) spectrometry is a non-destructive, rapid, multi elemental, accurate, and environment friendly analysis compared with other detection methods. Thus, EDXRF spectrometry is applicable for food inspection. The macro elements calcium and potassium constitute important nutrients required by the human body for optimal physiological functions. Therefore, the determination of Ca and K content in various foods needs to be done. The aim of this work is to demonstrate the applicability of EDXRF for food analysis. The analytical performance of non-destructive EDXRF was compared with other analytical techniques; neutron activation analysis and atomic absorption spectrometry. Comparison of methods performed as cross checking results of the analysis and to overcome the limitations of the three methods. Analysis results showed that Ca found in food using EDXRF and AAS were not significantly different with p-value 0.9687, whereas p-value of K between EDXRF and NAA is 0.6575. The correlation between those results was also examined. The Pearson correlations for Ca and K were 0.9871 and 0.9558, respectively. Method validation using SRM NIST 1548a Typical Diet was also applied. The results showed good agreement between methods; therefore EDXRF method can be used as an alternative method for the determination of Ca and K in food samples.
Kundi, Harun; Gok, Murat; Kiziltunc, Emrullah; Topcuoglu, Canan; Cetin, Mustafa; Cicekcioglu, Hulya; Ugurlu, Burcu; Ulusoy, Feridun Vasfi
2017-07-01
The aim of this study was to investigate the relationship between endocan levels with the presence of slow coronary flow (SCF). In this cross-sectional study, a total of 88 patients, who admitted to our hospital, were included in this study. Of these, 53 patients with SCF and 35 patients with normal coronary flow were included in the final analysis. Coronary flow rates of all patients were determined by the Timi Frame Count (TFC) method. In correlation analysis, endocan levels revealed a significantly positive correlation with high sensitive C-reactive protein and corrected TFC. In multivariate logistic regression analysis, the endocan levels were found as independently associated with the presence of SCF. Finally, using a cutoff level of 2.3, endocan level predicted the presence of SCF with a sensitivity of 77.2% and specificity of 75.2%. In conclusion, our study showed that higher endocan levels were significantly and independently related to the presence of SCF.
Pre-processing ambient noise cross-correlations with equalizing the covariance matrix eigenspectrum
NASA Astrophysics Data System (ADS)
Seydoux, Léonard; de Rosny, Julien; Shapiro, Nikolai M.
2017-09-01
Passive imaging techniques from ambient seismic noise requires a nearly isotropic distribution of the noise sources in order to ensure reliable traveltime measurements between seismic stations. However, real ambient seismic noise often partially fulfils this condition. It is generated in preferential areas (in deep ocean or near continental shores), and some highly coherent pulse-like signals may be present in the data such as those generated by earthquakes. Several pre-processing techniques have been developed in order to attenuate the directional and deterministic behaviour of this real ambient noise. Most of them are applied to individual seismograms before cross-correlation computation. The most widely used techniques are the spectral whitening and temporal smoothing of the individual seismic traces. We here propose an additional pre-processing to be used together with the classical ones, which is based on the spatial analysis of the seismic wavefield. We compute the cross-spectra between all available stations pairs in spectral domain, leading to the data covariance matrix. We apply a one-bit normalization to the covariance matrix eigenspectrum before extracting the cross-correlations in the time domain. The efficiency of the method is shown with several numerical tests. We apply the method to the data collected by the USArray, when the M8.8 Maule earthquake occurred on 2010 February 27. The method shows a clear improvement compared with the classical equalization to attenuate the highly energetic and coherent waves incoming from the earthquake, and allows to perform reliable traveltime measurement even in the presence of the earthquake.
Erasing the Milky Way: New Cleaning Technique Applied to GBT Intensity Mapping Data
NASA Technical Reports Server (NTRS)
Wolz, L.; Blake, C.; Abdalla, F. B.; Anderson, C. J.; Chang, T.-C.; Li, Y.-C.; Masi, K.W.; Switzer, E.; Pen, U.-L.; Voytek, T. C.;
2016-01-01
We present the first application of a new foreground removal pipeline to the current leading HI intensity mapping dataset, obtained by the Green Bank Telescope (GBT). We study the 15- and 1-h field data of the GBT observations previously presented in Masui et al. (2013) and Switzer et al. (2013), covering about 41 square degrees at 0.6 less than z is less than 1.0, for which cross-correlations may be measured with the galaxy distribution of the WiggleZ Dark Energy Survey. In the presented pipeline, we subtract the Galactic foreground continuum and the point source contamination using an independent component analysis technique (fastica), and develop a Fourier-based optimal estimator to compute the temperature power spectrum of the intensity maps and cross-correlation with the galaxy survey data. We show that fastica is a reliable tool to subtract diffuse and point-source emission through the non-Gaussian nature of their probability distributions. The temperature power spectra of the intensity maps is dominated by instrumental noise on small scales which fastica, as a conservative sub-traction technique of non-Gaussian signals, can not mitigate. However, we determine similar GBT-WiggleZ cross-correlation measurements to those obtained by the Singular Value Decomposition (SVD) method, and confirm that foreground subtraction with fastica is robust against 21cm signal loss, as seen by the converged amplitude of these cross-correlation measurements. We conclude that SVD and fastica are complementary methods to investigate the foregrounds and noise systematics present in intensity mapping datasets.
NASA Astrophysics Data System (ADS)
Gao, Yan; Liu, Yuyou; Ma, Yifan; Cheng, Xiaobin; Yang, Jun
2018-11-01
One major challenge currently facing pipeline networks across the world is the improvement of leak detection technologies in urban environments. There is an imperative to locate accurately leaks in buried water pipes to avoid serious environmental, social and economic consequences. Much attention has been paid to time delay estimation (TDE) in determining the position of a leak by utilising cross-correlation, which has been proven to be effective with varying degrees of success over the past half century. Previous research in published literature has demonstrated the effectiveness of the pre-whitening process for accentuating the peak in the cross-correlation associated with the time delay. This paper is concerned with the implementation of the differentiation process for TDE, with particular focus on the problem of determining a leak in pipelines by means of pipe pressure measurements. Rather than the pre-whitening operation, the proposed cross-correlation via the differentiation process, termed here DIF, changes the characteristics of the pipe system so that the pipe effectively acts as a band-pass filter. This method has the potential to eliminate some ambiguity caused by the interference at low frequencies and to allow more high frequency information to pass. Given an appropriate differentiation order, a more pronounced and reliable peak is obtained in the cross-correlation result. The use of differentiation process may provide a viable cross-correlation method suited to water leak detection. Its performance in relation to leak detection is further compared to the basic cross-correlation and pre-whitening methods for TDE in detecting a leak from actual PVC water pipes. Experimental results are presented to show an additional property of the DIF compensating for the resonance effects that may exist in cross-spectral density measurements, and hence better performance for TDE.
Ulloa, Alvaro; Jingyu Liu; Vergara, Victor; Jiayu Chen; Calhoun, Vince; Pattichis, Marios
2014-01-01
In the biomedical field, current technology allows for the collection of multiple data modalities from the same subject. In consequence, there is an increasing interest for methods to analyze multi-modal data sets. Methods based on independent component analysis have proven to be effective in jointly analyzing multiple modalities, including brain imaging and genetic data. This paper describes a new algorithm, three-way parallel independent component analysis (3pICA), for jointly identifying genomic loci associated with brain function and structure. The proposed algorithm relies on the use of multi-objective optimization methods to identify correlations among the modalities and maximally independent sources within modality. We test the robustness of the proposed approach by varying the effect size, cross-modality correlation, noise level, and dimensionality of the data. Simulation results suggest that 3p-ICA is robust to data with SNR levels from 0 to 10 dB and effect-sizes from 0 to 3, while presenting its best performance with high cross-modality correlations, and more than one subject per 1,000 variables. In an experimental study with 112 human subjects, the method identified links between a genetic component (pointing to brain function and mental disorder associated genes, including PPP3CC, KCNQ5, and CYP7B1), a functional component related to signal decreases in the default mode network during the task, and a brain structure component indicating increases of gray matter in brain regions of the default mode region. Although such findings need further replication, the simulation and in-vivo results validate the three-way parallel ICA algorithm presented here as a useful tool in biomedical data decomposition applications.
Parallel image logical operations using cross correlation
NASA Technical Reports Server (NTRS)
Strong, J. P., III
1972-01-01
Methods are presented for counting areas in an image in a parallel manner using noncoherent optical techniques. The techniques presented include the Levialdi algorithm for counting, optical techniques for binary operations, and cross-correlation.
Zhang, Mingjing; Wen, Ming; Zhang, Zhi-Min; Lu, Hongmei; Liang, Yizeng; Zhan, Dejian
2015-03-01
Retention time shift is one of the most challenging problems during the preprocessing of massive chromatographic datasets. Here, an improved version of the moving window fast Fourier transform cross-correlation algorithm is presented to perform nonlinear and robust alignment of chromatograms by analyzing the shifts matrix generated by moving window procedure. The shifts matrix in retention time can be estimated by fast Fourier transform cross-correlation with a moving window procedure. The refined shift of each scan point can be obtained by calculating the mode of corresponding column of the shifts matrix. This version is simple, but more effective and robust than the previously published moving window fast Fourier transform cross-correlation method. It can handle nonlinear retention time shift robustly if proper window size has been selected. The window size is the only one parameter needed to adjust and optimize. The properties of the proposed method are investigated by comparison with the previous moving window fast Fourier transform cross-correlation and recursive alignment by fast Fourier transform using chromatographic datasets. The pattern recognition results of a gas chromatography mass spectrometry dataset of metabolic syndrome can be improved significantly after preprocessing by this method. Furthermore, the proposed method is available as an open source package at https://github.com/zmzhang/MWFFT2. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Exploring the Dynamics of Cell Processes through Simulations of Fluorescence Microscopy Experiments
Angiolini, Juan; Plachta, Nicolas; Mocskos, Esteban; Levi, Valeria
2015-01-01
Fluorescence correlation spectroscopy (FCS) methods are powerful tools for unveiling the dynamical organization of cells. For simple cases, such as molecules passively moving in a homogeneous media, FCS analysis yields analytical functions that can be fitted to the experimental data to recover the phenomenological rate parameters. Unfortunately, many dynamical processes in cells do not follow these simple models, and in many instances it is not possible to obtain an analytical function through a theoretical analysis of a more complex model. In such cases, experimental analysis can be combined with Monte Carlo simulations to aid in interpretation of the data. In response to this need, we developed a method called FERNET (Fluorescence Emission Recipes and Numerical routines Toolkit) based on Monte Carlo simulations and the MCell-Blender platform, which was designed to treat the reaction-diffusion problem under realistic scenarios. This method enables us to set complex geometries of the simulation space, distribute molecules among different compartments, and define interspecies reactions with selected kinetic constants, diffusion coefficients, and species brightness. We apply this method to simulate single- and multiple-point FCS, photon-counting histogram analysis, raster image correlation spectroscopy, and two-color fluorescence cross-correlation spectroscopy. We believe that this new program could be very useful for predicting and understanding the output of fluorescence microscopy experiments. PMID:26039162
Soneson, Charlotte; Lilljebjörn, Henrik; Fioretos, Thoas; Fontes, Magnus
2010-04-15
With the rapid development of new genetic measurement methods, several types of genetic alterations can be quantified in a high-throughput manner. While the initial focus has been on investigating each data set separately, there is an increasing interest in studying the correlation structure between two or more data sets. Multivariate methods based on Canonical Correlation Analysis (CCA) have been proposed for integrating paired genetic data sets. The high dimensionality of microarray data imposes computational difficulties, which have been addressed for instance by studying the covariance structure of the data, or by reducing the number of variables prior to applying the CCA. In this work, we propose a new method for analyzing high-dimensional paired genetic data sets, which mainly emphasizes the correlation structure and still permits efficient application to very large data sets. The method is implemented by translating a regularized CCA to its dual form, where the computational complexity depends mainly on the number of samples instead of the number of variables. The optimal regularization parameters are chosen by cross-validation. We apply the regularized dual CCA, as well as a classical CCA preceded by a dimension-reducing Principal Components Analysis (PCA), to a paired data set of gene expression changes and copy number alterations in leukemia. Using the correlation-maximizing methods, regularized dual CCA and PCA+CCA, we show that without pre-selection of known disease-relevant genes, and without using information about clinical class membership, an exploratory analysis singles out two patient groups, corresponding to well-known leukemia subtypes. Furthermore, the variables showing the highest relevance to the extracted features agree with previous biological knowledge concerning copy number alterations and gene expression changes in these subtypes. Finally, the correlation-maximizing methods are shown to yield results which are more biologically interpretable than those resulting from a covariance-maximizing method, and provide different insight compared to when each variable set is studied separately using PCA. We conclude that regularized dual CCA as well as PCA+CCA are useful methods for exploratory analysis of paired genetic data sets, and can be efficiently implemented also when the number of variables is very large.
Na, Sung Dae; Wei, Qun; Seong, Ki Woong; Cho, Jin Ho; Kim, Myoung Nam
2018-01-01
The conventional methods of speech enhancement, noise reduction, and voice activity detection are based on the suppression of noise or non-speech components of the target air-conduction signals. However, air-conduced speech is hard to differentiate from babble or white noise signals. To overcome this problem, the proposed algorithm uses the bone-conduction speech signals and soft thresholding based on the Shannon entropy principle and cross-correlation of air- and bone-conduction signals. A new algorithm for speech detection and noise reduction is proposed, which makes use of the Shannon entropy principle and cross-correlation with the bone-conduction speech signals to threshold the wavelet packet coefficients of the noisy speech. The proposed method can be get efficient result by objective quality measure that are PESQ, RMSE, Correlation, SNR. Each threshold is generated by the entropy and cross-correlation approaches in the decomposed bands using the wavelet packet decomposition. As a result, the noise is reduced by the proposed method using the MATLAB simulation. To verify the method feasibility, we compared the air- and bone-conduction speech signals and their spectra by the proposed method. As a result, high performance of the proposed method is confirmed, which makes it quite instrumental to future applications in communication devices, noisy environment, construction, and military operations.
Dean, Roger T; Dunsmuir, William T M
2016-06-01
Many articles on perception, performance, psychophysiology, and neuroscience seek to relate pairs of time series through assessments of their cross-correlations. Most such series are individually autocorrelated: they do not comprise independent values. Given this situation, an unfounded reliance is often placed on cross-correlation as an indicator of relationships (e.g., referent vs. response, leading vs. following). Such cross-correlations can indicate spurious relationships, because of autocorrelation. Given these dangers, we here simulated how and why such spurious conclusions can arise, to provide an approach to resolving them. We show that when multiple pairs of series are aggregated in several different ways for a cross-correlation analysis, problems remain. Finally, even a genuine cross-correlation function does not answer key motivating questions, such as whether there are likely causal relationships between the series. Thus, we illustrate how to obtain a transfer function describing such relationships, informed by any genuine cross-correlations. We illustrate the confounds and the meaningful transfer functions by two concrete examples, one each in perception and performance, together with key elements of the R software code needed. The approach involves autocorrelation functions, the establishment of stationarity, prewhitening, the determination of cross-correlation functions, the assessment of Granger causality, and autoregressive model development. Autocorrelation also limits the interpretability of other measures of possible relationships between pairs of time series, such as mutual information. We emphasize that further complexity may be required as the appropriate analysis is pursued fully, and that causal intervention experiments will likely also be needed.
NASA Astrophysics Data System (ADS)
Wang, Fang
2016-06-01
In order to detect and quantify asymmetry of two time series, a novel cross-correlation coefficient is proposed based on recent asymmetric detrended cross-correlation analysis (A-DXA), which we called A-DXA coefficient. The A-DXA coefficient, as an important extension of DXA coefficient ρ D X A , contains two directional asymmetric cross-correlated indexes, describing upwards and downwards asymmetric cross-correlations, respectively. By using the information of directional covariance function of two time series and directional variance function of each series itself instead of power-law between the covariance function and time scale, the proposed A-DXA coefficient can well detect asymmetry between the two series no matter whether the cross-correlation is significant or not. By means of the proposed A-DXA coefficient conducted over the asymmetry for California electricity market, we found that the asymmetry between the prices and loads is not significant for daily average data in 1999 yr market (before electricity crisis) but extremely significant for those in 2000 yr market (during the crisis). To further uncover the difference of asymmetry between the years 1999 and 2000, a modified H statistic (MH) and ΔMH statistic are proposed. One of the present contributions is that the high MH values calculated for hourly data exist in majority months in 2000 market. Another important conclusion is that the cross-correlation with downwards dominates over the whole 1999 yr in contrast to the cross-correlation with upwards dominates over the 2000 yr.
Delay differential analysis of time series.
Lainscsek, Claudia; Sejnowski, Terrence J
2015-03-01
Nonlinear dynamical system analysis based on embedding theory has been used for modeling and prediction, but it also has applications to signal detection and classification of time series. An embedding creates a multidimensional geometrical object from a single time series. Traditionally either delay or derivative embeddings have been used. The delay embedding is composed of delayed versions of the signal, and the derivative embedding is composed of successive derivatives of the signal. The delay embedding has been extended to nonuniform embeddings to take multiple timescales into account. Both embeddings provide information on the underlying dynamical system without having direct access to all the system variables. Delay differential analysis is based on functional embeddings, a combination of the derivative embedding with nonuniform delay embeddings. Small delay differential equation (DDE) models that best represent relevant dynamic features of time series data are selected from a pool of candidate models for detection or classification. We show that the properties of DDEs support spectral analysis in the time domain where nonlinear correlation functions are used to detect frequencies, frequency and phase couplings, and bispectra. These can be efficiently computed with short time windows and are robust to noise. For frequency analysis, this framework is a multivariate extension of discrete Fourier transform (DFT), and for higher-order spectra, it is a linear and multivariate alternative to multidimensional fast Fourier transform of multidimensional correlations. This method can be applied to short or sparse time series and can be extended to cross-trial and cross-channel spectra if multiple short data segments of the same experiment are available. Together, this time-domain toolbox provides higher temporal resolution, increased frequency and phase coupling information, and it allows an easy and straightforward implementation of higher-order spectra across time compared with frequency-based methods such as the DFT and cross-spectral analysis.
Almaqrami, Bushra-Sufyan; Alhammadi, Maged-Sultan
2018-01-01
Background The objective of this study was to analyse three dimensionally the reliability and correlation of angular and linear measurements in assessment of anteroposterior skeletal discrepancy. Material and Methods In this retrospective cross sectional study, a sample of 213 subjects were three-dimensionally analysed from cone-beam computed tomography scans. The sample was divided according to three dimensional measurement of anteroposterior relation (ANB angle) into three groups (skeletal Class I, Class II and Class III). The anterior-posterior cephalometric indicators were measured on volumetric images using Anatomage software (InVivo5.2). These measurements included three angular and seven linear measurements. Cross tabulations were performed to correlate the ANB angle with each method. Intra-class Correlation Coefficient (ICC) test was applied for the difference between the two reliability measurements. P value of < 0.05 was considered significant. Results There was a statistically significant (P<0.05) agreement between all methods used with variability in assessment of different anteroposterior relations. The highest correlation was between ANB and DSOJ (0.913), strong correlation with AB/FH, AB/SN/, MM bisector, AB/PP, Wits appraisal (0.896, 0.890, 0.878, 0.867,and 0.858, respectively), moderate with AD/SN and Beta angle (0.787 and 0.760), and weak correlation with corrected ANB angle (0.550). Conclusions Conjunctive usage of ANB angle with DSOJ, AB/FH, AB/SN/, MM bisector, AB/PP and Wits appraisal in 3D cephalometric analysis provide a more reliable and valid indicator of the skeletal anteroposterior relationship. Clinical relevance: Most of orthodontic literature depends on single method (ANB) with its drawbacks in assessment of skeletal discrepancy which is a cardinal factors for proper treatment planning, this study assessed three dimensionally the degree of correlation between all available methods to make clinical judgement more accurate based on more than one method of assessment. Key words:Anteroposterior relationships, ANB angle, Three-dimension, CBCT. PMID:29750096
Wu, Mingwei; Li, Yan; Fu, Xinmei; Wang, Jinghui; Zhang, Shuwei; Yang, Ling
2014-09-01
Melanin concentrating hormone receptor 1 (MCHR1), a crucial regulator of energy homeostasis involved in the control of feeding and energy metabolism, is a promising target for treatment of obesity. In the present work, the up-to-date largest set of 181 quinoline/quinazoline derivatives as MCHR1 antagonists was subjected to both ligand- and receptor-based three-dimensional quantitative structure-activity (3D-QSAR) analysis applying comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The optimal predictable CoMSIA model exhibited significant validity with the cross-validated correlation coefficient (Q²) = 0.509, non-cross-validated correlation coefficient (R²(ncv)) = 0.841 and the predicted correlation coefficient (R²(pred)) = 0.745. In addition, docking studies and molecular dynamics (MD) simulations were carried out for further elucidation of the binding modes of MCHR1 antagonists. MD simulations in both water and lipid bilayer systems were performed. We hope that the obtained models and information may help to provide an insight into the interaction mechanism of MCHR1 antagonists and facilitate the design and optimization of novel antagonists as anti-obesity agents.
Particle Dark Matter Searches Outside the Local Group.
Regis, Marco; Xia, Jun-Qing; Cuoco, Alessandro; Branchini, Enzo; Fornengo, Nicolao; Viel, Matteo
2015-06-19
If dark matter (DM) is composed by particles which are nongravitationally coupled to ordinary matter, their annihilations or decays in cosmic structures can result in detectable radiation. We show that the most powerful technique to detect a particle DM signal outside the Local Group is to study the angular cross-correlation of nongravitational signals with low-redshift gravitational probes. This method allows us to enhance the signal to noise from the regions of the Universe where the DM-induced emission is preferentially generated. We demonstrate the power of this approach by focusing on GeV-TeV DM and on the recent cross-correlation analysis between the 2MASS galaxy catalogue and the Fermi-LAT γ-ray maps. We show that this technique is more sensitive than other extragalactic γ-ray probes, such as the energy spectrum and angular autocorrelation of the extragalactic background, and emission from clusters of galaxies. Intriguingly, we find that the measured cross-correlation can be well fitted by a DM component, with a thermal annihilation cross section and mass between 10 and 100 GeV, depending on the small-scale DM properties and γ-ray production mechanism. This solicits further data collection and dedicated analyses.
Particle Dark Matter Searches Outside the Local Group
NASA Astrophysics Data System (ADS)
Regis, Marco; Xia, Jun-Qing; Cuoco, Alessandro; Branchini, Enzo; Fornengo, Nicolao; Viel, Matteo
2015-06-01
If dark matter (DM) is composed by particles which are nongravitationally coupled to ordinary matter, their annihilations or decays in cosmic structures can result in detectable radiation. We show that the most powerful technique to detect a particle DM signal outside the Local Group is to study the angular cross-correlation of nongravitational signals with low-redshift gravitational probes. This method allows us to enhance the signal to noise from the regions of the Universe where the DM-induced emission is preferentially generated. We demonstrate the power of this approach by focusing on GeV-TeV DM and on the recent cross-correlation analysis between the 2MASS galaxy catalogue and the Fermi-LAT γ -ray maps. We show that this technique is more sensitive than other extragalactic γ -ray probes, such as the energy spectrum and angular autocorrelation of the extragalactic background, and emission from clusters of galaxies. Intriguingly, we find that the measured cross-correlation can be well fitted by a DM component, with a thermal annihilation cross section and mass between 10 and 100 GeV, depending on the small-scale DM properties and γ -ray production mechanism. This solicits further data collection and dedicated analyses.
NASA Astrophysics Data System (ADS)
Timashev, Serge F.; Panischev, Oleg Yu.; Polyakov, Yuriy S.; Demin, Sergey A.; Kaplan, Alexander Ya.
2012-02-01
We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical Sciences. The EEG signals for these subjects were compared with the signals for a control sample of chronically depressed children/adolescents. The purpose of the study is to look for diagnostic signs of subjects' susceptibility to schizophrenia in the FNS parameters for specific electrodes and cross-correlations between the signals simultaneously measured at different points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes at locations F3 and F4, which are symmetrically positioned in the left and right frontal areas of cerebral cortex, respectively, demonstrates an essential role of frequency-phase synchronization, a phenomenon representing specific correlations between the characteristic frequencies and phases of excitations in the brain. We introduce quantitative measures of frequency-phase synchronization and systematize the values of FNS parameters for the EEG data. The comparison of our results with the medical diagnoses for 84 subjects performed at NCPH makes it possible to group the EEG signals into 4 categories corresponding to different risk levels of subjects' susceptibility to schizophrenia. We suggest that the introduced quantitative characteristics and classification of cross-correlations may be used for the diagnosis of schizophrenia at the early stages of its development.
Stefenelli, Mario; Todt, Juraj; Riedl, Angelika; Ecker, Werner; Müller, Thomas; Daniel, Rostislav; Burghammer, Manfred; Keckes, Jozef
2013-10-01
Novel scanning synchrotron cross-sectional nanobeam and conventional laboratory as well as synchrotron Laplace X-ray diffraction methods are used to characterize residual stresses in exemplary 11.5 µm-thick TiN coatings. Both real and Laplace space approaches reveal a homogeneous tensile stress state and a very pronounced compressive stress gradient in as-deposited and blasted coatings, respectively. The unique capabilities of the cross-sectional approach operating with a beam size of 100 nm in diameter allow the analysis of stress variation with sub-micrometre resolution at arbitrary depths and the correlation of the stress evolution with the local coating microstructure. Finally, advantages and disadvantages of both approaches are extensively discussed.
Zhou, Yan; Cao, Hui
2013-01-01
We propose an augmented classical least squares (ACLS) calibration method for quantitative Raman spectral analysis against component information loss. The Raman spectral signals with low analyte concentration correlations were selected and used as the substitutes for unknown quantitative component information during the CLS calibration procedure. The number of selected signals was determined by using the leave-one-out root-mean-square error of cross-validation (RMSECV) curve. An ACLS model was built based on the augmented concentration matrix and the reference spectral signal matrix. The proposed method was compared with partial least squares (PLS) and principal component regression (PCR) using one example: a data set recorded from an experiment of analyte concentration determination using Raman spectroscopy. A 2-fold cross-validation with Venetian blinds strategy was exploited to evaluate the predictive power of the proposed method. The one-way variance analysis (ANOVA) was used to access the predictive power difference between the proposed method and existing methods. Results indicated that the proposed method is effective at increasing the robust predictive power of traditional CLS model against component information loss and its predictive power is comparable to that of PLS or PCR.
Masud, Mohammad Shahed; Borisyuk, Roman; Stuart, Liz
2017-07-15
This study analyses multiple spike trains (MST) data, defines its functional connectivity and subsequently visualises an accurate diagram of connections. This is a challenging problem. For example, it is difficult to distinguish the common input and the direct functional connection of two spike trains. The new method presented in this paper is based on the traditional pairwise cross-correlation function (CCF) and a new combination of statistical techniques. First, the CCF is used to create the Advanced Correlation Grid (ACG) correlation where both the significant peak of the CCF and the corresponding time delay are used for detailed analysis of connectivity. Second, these two features of functional connectivity are used to classify connections. Finally, the visualization technique is used to represent the topology of functional connections. Examples are presented in the paper to demonstrate the new Advanced Correlation Grid method and to show how it enables discrimination between (i) influence from one spike train to another through an intermediate spike train and (ii) influence from one common spike train to another pair of analysed spike trains. The ACG method enables scientists to automatically distinguish between direct connections from spurious connections such as common source connection and indirect connection whereas existing methods require in-depth analysis to identify such connections. The ACG is a new and effective method for studying functional connectivity of multiple spike trains. This method can identify accurately all the direct connections and can distinguish common source and indirect connections automatically. Copyright © 2017 Elsevier B.V. All rights reserved.
Needlet estimation of cross-correlation between CMB lensing maps and LSS
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bianchini, Federico; Renzi, Alessandro; Marinucci, Domenico, E-mail: fbianchini@sissa.it, E-mail: renzi@mat.uniroma2.it, E-mail: marinucc@mat.uniroma2.it
In this paper we develop a novel needlet-based estimator to investigate the cross-correlation between cosmic microwave background (CMB) lensing maps and large-scale structure (LSS) data. We compare this estimator with its harmonic counterpart and, in particular, we analyze the bias effects of different forms of masking. In order to address this bias, we also implement a MASTER-like technique in the needlet case. The resulting estimator turns out to have an extremely good signal-to-noise performance. Our analysis aims at expanding and optimizing the operating domains in CMB-LSS cross-correlation studies, similarly to CMB needlet data analysis. It is motivated especially by nextmore » generation experiments (such as Euclid) which will allow us to derive much tighter constraints on cosmological and astrophysical parameters through cross-correlation measurements between CMB and LSS.« less
DCCA cross-correlation in blue-chips companies: A view of the 2008 financial crisis in the Eurozone
NASA Astrophysics Data System (ADS)
Guedes, E.; Dionísio, A.; Ferreira, P. J.; Zebende, G. F.
2017-08-01
In this paper we analyze the blue-chips (up to 50% of the total index) companies in the Eurozone. Our motivation being analysis of the effect of the 2008 financial crisis. For this purpose, we apply the DCCA cross-correlation coefficient (ρDCCA) between the country stock market index and their respective blue-chips. Then, with the cross-correlation coefficient, we qualify and quantify how each blue-chip is adherent to its country index, evaluating the type of cross-correlation among them. Subsequently, for each blue-chip, we propose to study the 2008 financial crisis by measuring the adherence between post and pre-crisis. From this analysis, we can construct an adhesion map of each company with respect to the global index. Our database is formed of 12 Eurozone countries.
Cross-correlation photothermal optical coherence tomography with high effective resolution.
Tang, Peijun; Liu, Shaojie; Chen, Junbo; Yuan, Zhiling; Xie, Bingkai; Zhou, Jianhua; Tang, Zhilie
2017-12-01
We developed a cross-correlation photothermal optical coherence tomography (CC-PTOCT) system for photothermal imaging with high lateral and axial resolution. The CC-PTOCT system consists of a phase-sensitive OCT system, a modulated pumping laser, and a digital cross-correlator. The pumping laser was used to induce the photothermal effect in the sample, causing a slight phase modulation of the OCT signals. A spatial phase differentiation method was employed to reduce phase accumulation. The noise brought by the phase differentiation method and the strong background noise were suppressed efficiently by the cross-correlator, which was utilized to extract the photothermal signals from the modulated signals. Combining the cross-correlation technique with spatial phase differentiation can improve both lateral and axial resolution of the PTOCT imaging system. Clear photothermal images of blood capillaries of a mouse ear in vivo were successfully obtained with high lateral and axial resolution. The experimental results demonstrated that this system can enhance the effective transverse resolution, effective depth resolution, and contrast of the PTOCT image effectively, aiding the ongoing development of the accurate 3D functional imaging.
Power law cross-correlations between price change and volume change of Indian stocks
NASA Astrophysics Data System (ADS)
Hasan, Rashid; Mohammed Salim, M.
2017-05-01
We study multifractal long-range correlations and cross-correlations of daily price change and volume change of 50 stocks that comprise Nifty index of National Stock Exchange, Mumbai, using MF-DFA and MF-DCCA methods. We find that the time series of price change are uncorrelated, whereas anti-persistent long-range multifractal correlations are found in volume change series. We also find antipersistent long-range multifractal cross-correlations between the time series of price change and volume change. As multifractality is a signature of complexity, we estimate complexity parameters of the time series of price change, volume change, and cross-correlated price-volume change by fitting the fourth-degree polynomials to their multifractal spectra. Our results indicate that the time series of price change display high complexity, whereas the time series of volume change and cross-correlated price-volume change display low complexity.
Cross-correlations between West Texas Intermediate crude oil and the stock markets of the BRIC
NASA Astrophysics Data System (ADS)
Ma, Feng; Wei, Yu; Huang, Dengshi; Zhao, Lin
2013-11-01
In this paper, we investigate the cross-correlation properties between West Texas Intermediate crude oil and the stock markets of the BRIC. We use not only the qualitative analysis of the cross-correlation test, but also take the quantitative analysis of the MF-DXA, confirming the cross-correlation relationship between West Texas Intermediate crude oil and the stock markets of the BRIC (Brazil, Russia, India and China) respectively, which have strongly multifractal features, and the cross-correlations are more strongly multifractal in the short term than in the long term. Furthermore, based on the multifractal spectrum, we also find the multifractality strength between the crude oil WTI and Chinese stock market is stronger than the multifractality strength of other pairs. Based on the Iraq war (Mar 20, 2003) and the Financial crisis in 2008, we divide sample period into four segments to research the degree of the multifractal (ΔH) and the market efficiency (and the risk). Finally, we employ the technique of the rolling window to calculate the time-varying EI (efficiency index) and dependent on the EI, we can easily observe the change of stock markets. Furthermore, we explore the relationship between bivariate cross-correlation exponents (Hxy(q)) and the generalized Hurst exponents.
Associations Between Tobacco Marketing and Use Among Urban Youth in India
ERIC Educational Resources Information Center
Arora, Monika; Reddy, K. Srinath; Stigler, Melissa H.; Perry, Cheryl L.
2008-01-01
Objectives: To study if receptivity and exposure to tobacco marketing are correlated with tobacco use and psychosocial risk factors for tobacco use among a sample of urban Indian youth. Methods: Analysis of cross-sectional survey data from Project MYTRI, a group randomized intervention trial, in Delhi and Chennai, India, collected from sixth and…
Methods of Muscle Activation Onset Timing Recorded During Spinal Manipulation.
Currie, Stuart J; Myers, Casey A; Krishnamurthy, Ashok; Enebo, Brian A; Davidson, Bradley S
2016-05-01
The purpose of this study was to determine electromyographic threshold parameters that most reliably characterize the muscular response to spinal manipulation and compare 2 methods that detect muscle activity onset delay: the double-threshold method and cross-correlation method. Surface and indwelling electromyography were recorded during lumbar side-lying manipulations in 17 asymptomatic participants. Muscle activity onset delays in relation to the thrusting force were compared across methods and muscles using a generalized linear model. The threshold combinations that resulted in the lowest Detection Failures were the "8 SD-0 milliseconds" threshold (Detection Failures = 8) and the "8 SD-10 milliseconds" threshold (Detection Failures = 9). The average muscle activity onset delay for the double-threshold method across all participants was 149 ± 152 milliseconds for the multifidus and 252 ± 204 milliseconds for the erector spinae. The average onset delay for the cross-correlation method was 26 ± 101 for the multifidus and 67 ± 116 for the erector spinae. There were no statistical interactions, and a main effect of method demonstrated that the delays were higher when using the double-threshold method compared with cross-correlation. The threshold parameters that best characterized activity onset delays were an 8-SD amplitude and a 10-millisecond duration threshold. The double-threshold method correlated well with visual supervision of muscle activity. The cross-correlation method provides several advantages in signal processing; however, supervision was required for some results, negating this advantage. These results help standardize methods when recording neuromuscular responses of spinal manipulation and improve comparisons within and across investigations. Copyright © 2016 National University of Health Sciences. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Liu, X.; Beroza, G. C.; Nakata, N.
2017-12-01
Cross-correlation of fully diffuse wavefields provides Green's function between receivers, although the ambient noise field in the real world contains both diffuse and non-diffuse fields. The non-diffuse field potentially degrades the correlation functions. We attempt to blindly separate the diffuse and the non-diffuse components from cross-correlations of ambient seismic noise and analyze the potential bias caused by the non-diffuse components. We compute the 9-component noise cross-correlations for 17 stations in southern California. For the Rayleigh wave components, we assume that the cross-correlation of multiply scattered waves (diffuse component) is independent from the cross-correlation of ocean microseismic quasi-point source responses (non-diffuse component), and the cross-correlation function of ambient seismic data is the sum of both components. Thus we can blindly separate the non-diffuse component due to physical point sources and the more diffuse component due to cross-correlation of multiply scattered noise based on their statistical independence. We also perform beamforming over different frequency bands for the cross-correlations before and after the separation, and we find that the decomposed Rayleigh wave represents more coherent features among all Rayleigh wave polarization cross-correlation components. We show that after separating the non-diffuse component, the Frequency-Time Analysis results are less ambiguous. In addition, we estimate the bias in phase velocity on the raw cross-correlation data due to the non-diffuse component. We also apply this technique to a few borehole stations in Groningen, the Netherlands, to demonstrate its applicability in different instrument/geology settings.
Exact solutions for rate and synchrony in recurrent networks of coincidence detectors.
Mikula, Shawn; Niebur, Ernst
2008-11-01
We provide analytical solutions for mean firing rates and cross-correlations of coincidence detector neurons in recurrent networks with excitatory or inhibitory connectivity, with rate-modulated steady-state spiking inputs. We use discrete-time finite-state Markov chains to represent network state transition probabilities, which are subsequently used to derive exact analytical solutions for mean firing rates and cross-correlations. As illustrated in several examples, the method can be used for modeling cortical microcircuits and clarifying single-neuron and population coding mechanisms. We also demonstrate that increasing firing rates do not necessarily translate into increasing cross-correlations, though our results do support the contention that firing rates and cross-correlations are likely to be coupled. Our analytical solutions underscore the complexity of the relationship between firing rates and cross-correlations.
NASA Astrophysics Data System (ADS)
He, Ling-Yun; Chen, Shu-Peng
2011-01-01
Nonlinear dependency between characteristic financial and commodity market quantities (variables) is crucially important, especially between trading volume and market price. Studies on nonlinear dependency between price and volume can provide practical insights into market trading characteristics, as well as the theoretical understanding of market dynamics. Actually, nonlinear dependency and its underlying dynamical mechanisms between price and volume can help researchers and technical analysts in understanding the market dynamics by integrating the market variables, instead of investigating them in the current literature. Therefore, for investigating nonlinear dependency of price-volume relationships in agricultural commodity futures markets in China and the US, we perform a new statistical test to detect cross-correlations and apply a new methodology called Multifractal Detrended Cross-Correlation Analysis (MF-DCCA), which is an efficient algorithm to analyze two spatially or temporally correlated time series. We discuss theoretically the relationship between the bivariate cross-correlation exponent and the generalized Hurst exponents for time series of respective variables. We also perform an empirical study and find that there exists a power-law cross-correlation between them, and that multifractal features are significant in all the analyzed agricultural commodity futures markets.
Retrieval of Body-Wave Reflections Using Ambient Noise Interferometry Using a Small-Scale Experiment
NASA Astrophysics Data System (ADS)
Dantas, Odmaksuel Anísio Bezerra; do Nascimento, Aderson Farias; Schimmel, Martin
2018-02-01
We report the retrieval of body-wave reflections from noise records using a small-scale experiment over a mature oil field. The reflections are obtained by cross-correlation and stacking of the data. We used the stacked correlograms to create virtual source-to-receiver common shot gathers and are able to obtain body-wave reflections. Surface waves that obliterate the body-waves in our noise correlations were attenuated following a standard procedure from active source seismics. Further different strategies were employed to cross-correlate and stack the data: classical geometrical normalized cross-correlation (CCGN), phase cross-correlation (PCC), linear stacking**** and phase weighted stacking (PWS). PCC and PWS are based on the instantaneous phase coherence of analytic signals. The four approaches are independent and reveal the reflections; nevertheless, the combination of PWS and CCGN provided the best results. Our analysis is based on 2145 cross-correlations of 600 s data segments. We also compare the resulted virtual shot gathers with an active 2D seismic line near the passive experiment. It is shown that our ambient noise analysis reproduces reflections which are present in the active seismic data.
Inference for High-dimensional Differential Correlation Matrices.
Cai, T Tony; Zhang, Anru
2016-01-01
Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantees are given. Minimax rate of convergence is established and the proposed estimator is shown to be adaptively rate-optimal over collections of paired correlation matrices with approximately sparse differences. Simulation results show that the procedure significantly outperforms two other natural methods that are based on separate estimation of the individual correlation matrices. The procedure is also illustrated through an analysis of a breast cancer dataset, which provides evidence at the gene co-expression level that several genes, of which a subset has been previously verified, are associated with the breast cancer. Hypothesis testing on the differential correlation matrices is also considered. A test, which is particularly well suited for testing against sparse alternatives, is introduced. In addition, other related problems, including estimation of a single sparse correlation matrix, estimation of the differential covariance matrices, and estimation of the differential cross-correlation matrices, are also discussed.
Understanding sunscreen SPF performance using cross-polarized UVA reflectance photography.
Crowther, J M
2018-04-01
Objective methods for understanding sunscreen behaviour in vitro before they are applied to the skin have failed to keep pace with the ever-increasing demands for higher SPF scores where the products are absorbing more and more similar levels of UV. A novel method for visualizing the spreading and location of SPF ingredients based on cross-polarized UVA reflectance photography is described here which gives new insights into the formation of final film morphology and how it correlates with in vivo SPF efficacy for a set of test products. High-resolution UVA-based images of sunscreen films spread onto PMMA plates were captured using a modified commercial SLR camera in a custom imaging system. Visual grading and image analysis were used to describe the overall UVA absorbance and streakiness of the resultant films, and the data compared with both in vivo and calculated in vitro SPF scores for the products. Differences were observed between the products in terms of how they spread during application. A strong correlation was observed between the evenness of the resultant film as determined from the photographs and final in vivo SPF scores. Cross-polarized UVA reflectance photography has been demonstrated to be a valuable new method for assessing sunscreen distribution after spreading and to differentiate product based on film morphology, as well as strongly correlating with final in vivo behaviour. © 2017 Society of Cosmetic Scientists and the Société Française de Cosmétologie.
Experimental Demonstration of In-Place Calibration for Time Domain Microwave Imaging System
NASA Astrophysics Data System (ADS)
Kwon, S.; Son, S.; Lee, K.
2018-04-01
In this study, the experimental demonstration of in-place calibration was conducted using the developed time domain measurement system. Experiments were conducted using three calibration methods—in-place calibration and two existing calibrations, that is, array rotation and differential calibration. The in-place calibration uses dual receivers located at an equal distance from the transmitter. The received signals at the dual receivers contain similar unwanted signals, that is, the directly received signal and antenna coupling. In contrast to the simulations, the antennas are not perfectly matched and there might be unexpected environmental errors. Thus, we experimented with the developed experimental system to demonstrate the proposed method. The possible problems with low signal-to-noise ratio and clock jitter, which may exist in time domain systems, were rectified by averaging repeatedly measured signals. The tumor was successfully detected using the three calibration methods according to the experimental results. The cross correlation was calculated using the reconstructed image of the ideal differential calibration for a quantitative comparison between the existing rotation calibration and the proposed in-place calibration. The mean value of cross correlation between the in-place calibration and ideal differential calibration was 0.80, and the mean value of cross correlation of the rotation calibration was 0.55. Furthermore, the results of simulation were compared with the experimental results to verify the in-place calibration method. A quantitative analysis was also performed, and the experimental results show a tendency similar to the simulation.
Morgan, Katy E; Forbes, Andrew B; Keogh, Ruth H; Jairath, Vipul; Kahan, Brennan C
2017-01-30
In cluster randomised cross-over (CRXO) trials, clusters receive multiple treatments in a randomised sequence over time. In such trials, there is usual correlation between patients in the same cluster. In addition, within a cluster, patients in the same period may be more similar to each other than to patients in other periods. We demonstrate that it is necessary to account for these correlations in the analysis to obtain correct Type I error rates. We then use simulation to compare different methods of analysing a binary outcome from a two-period CRXO design. Our simulations demonstrated that hierarchical models without random effects for period-within-cluster, which do not account for any extra within-period correlation, performed poorly with greatly inflated Type I errors in many scenarios. In scenarios where extra within-period correlation was present, a hierarchical model with random effects for cluster and period-within-cluster only had correct Type I errors when there were large numbers of clusters; with small numbers of clusters, the error rate was inflated. We also found that generalised estimating equations did not give correct error rates in any scenarios considered. An unweighted cluster-level summary regression performed best overall, maintaining an error rate close to 5% for all scenarios, although it lost power when extra within-period correlation was present, especially for small numbers of clusters. Results from our simulation study show that it is important to model both levels of clustering in CRXO trials, and that any extra within-period correlation should be accounted for. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
NASA Technical Reports Server (NTRS)
Cragin, B. L.; Hanson, W. B.; Mcclure, J. P.; Valladares, C. E.
1985-01-01
Equatorial bottomside sinusoidal (BSS) irregularities have been studied by applying techniques of cross-correlation and spectral analysis to the Atmosphere Explorer data set. The phase of the cross-correlations of the plasma number density is discussed and the two drift velocity components observed using the retarding potential analyzer and ion drift meter on the satellite are discussed. Morphology is addressed, presenting the geographical distributions of the occurrence of BSS events for the equinoxes and solstices. Physical processes including the ion Larmor flux, interhemispheric plasma flows, and variations in the lower F region Pedersen conductivity are invoked to explain the findings.
Optical Correlation Techniques In Fluid Dynamics
NASA Astrophysics Data System (ADS)
Schatzel, K.; Schulz-DuBois, E. O.; Vehrenkamp, R.
1981-05-01
Three flow measurement techniques make use of fast digital correlators. (1) Most widely spread is photon correlation velocimetry using crossed laser beams and detecting Doppler shifted light scattered by small particles in the flow. Depending on the processing of the photon correlogram, this technique yields mean velocity, turbulence level, or even the detailed probability distribution of one velocity component. An improved data processing scheme is demonstrated on laminar vortex flow in a curved channel. (2) Rate correlation based upon threshold crossings of a high pass filtered laser Doppler signal can he used to obtain velocity correlation functions. The most powerful setup developed in our laboratory uses a phase locked loop type tracker and a multibit correlator to analyse time-dependent Taylor vortex flow. With two optical systems and trackers, crosscorrelation functions reveal phase relations between different vortices. (3) Making use of refractive index fluctuations (e. g. in two phase flows) instead of scattering particles, interferometry with bidirectional fringe counting and digital correlation and probability analysis constitute a new quantitative technique related to classical Schlieren methods. Measurements on a mixing flow of heated and cold air contribute new ideas to the theory of turbulent random phase screens.
Comparison of two target classification techniques
NASA Astrophysics Data System (ADS)
Chen, J. S.; Walton, E. K.
1986-01-01
Radar target classification techniques based on backscatter measurements in the resonance region (1.0-20.0 MHz) are discussed. Attention is given to two novel methods currently being tested at the radar range of Ohio State University. The methods include: (1) the nearest neighbor (NN) algorithm for determining the radar cross section (RCS) magnitude and range corrected phase at various operating frequencies; and (2) an inverse Fourier transformation of the complex multifrequency radar returns of the time domain, followed by cross correlation analysis. Comparisons are made of the performance of the two techniques as a function of signal-to-error noise ratio for different types of processing. The results of the comparison are discussed in detail.
Rainfall Observed Over Bangladesh 2000-2008: A Comparison of Spatial Interpolation Methods
NASA Astrophysics Data System (ADS)
Pervez, M.; Henebry, G. M.
2010-12-01
In preparation for a hydrometeorological study of freshwater resources in the greater Ganges-Brahmaputra region, we compared the results of four methods of spatial interpolation applied to point measurements of daily rainfall over Bangladesh during a seven year period (2000-2008). Two univariate (inverse distance weighted and spline-regularized and tension) and two multivariate geostatistical (ordinary kriging and kriging with external drift) methods were used to interpolate daily observations from a network of 221 rain gauges across Bangladesh spanning an area of 143,000 sq km. Elevation and topographic index were used as the covariates in the geostatistical methods. The validity of the interpolated maps was analyzed through cross-validation. The quality of the methods was assessed through the Pearson and Spearman correlations and root mean square error measurements of accuracy in cross-validation. Preliminary results indicated that the univariate methods performed better than the geostatistical methods at daily scales, likely due to the relatively dense sampled point measurements and a weak correlation between the rainfall and covariates at daily scales in this region. Inverse distance weighted produced the better results than the spline. For the days with extreme or high rainfall—spatially and quantitatively—the correlation between observed and interpolated estimates appeared to be high (r2 ~ 0.6 RMSE ~ 10mm), although for low rainfall days the correlations were poor (r2 ~ 0.1 RMSE ~ 3mm). The performance quality of these methods was influenced by the density of the sample point measurements, the quantity of the observed rainfall along with spatial extent, and an appropriate search radius defining the neighboring points. Results indicated that interpolated rainfall estimates at daily scales may introduce uncertainties in the successive hydrometeorological analysis. Interpolations at 5-day, 10-day, 15-day, and monthly time scales are currently under investigation.
Muscle synergies during bench press are reliable across days.
Kristiansen, Mathias; Samani, Afshin; Madeleine, Pascal; Hansen, Ernst Albin
2016-10-01
Muscle synergies have been investigated during different types of human movement using nonnegative matrix factorization. However, there are not any reports available on the reliability of the method. To evaluate between-day reliability, 21 subjects performed bench press, in two test sessions separated by approximately 7days. The movement consisted of 3 sets of 8 repetitions at 60% of the three repetition maximum in bench press. Muscle synergies were extracted from electromyography data of 13 muscles, using nonnegative matrix factorization. To evaluate between-day reliability, we performed a cross-correlation analysis and a cross-validation analysis, in which the synergy components extracted in the first test session were recomputed, using the fixed synergy components from the second test session. Two muscle synergies accounted for >90% of the total variance, and reflected the concentric and eccentric phase, respectively. The cross-correlation values were strong to very strong (r-values between 0.58 and 0.89), while the cross-validation values ranged from substantial to almost perfect (ICC3, 1 values between 0.70 and 0.95). The present findings revealed that the same general structure of the muscle synergies was present across days and the extraction of muscle synergies is thus deemed reliable. Copyright © 2016 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Pelliccia, Daniele; Sen, Tanaji
2014-11-01
The coherent radiation emitted by an electron bunch provides a diagnostic signal that can be used to estimate its longitudinal distribution. Commonly only the amplitude of the intensity spectrum can be measured and the associated phase must be calculated to obtain the bunch profile. Very recently an iterative method was proposed to retrieve this phase. However ambiguities associated with non-uniqueness of the solution are always present in the phase retrieval procedure. Here we present a method to overcome the ambiguity problem by first performing multiple independent runs of the phase retrieval procedure and then second, sorting the good solutions by means of cross-correlation analysis. Results obtained with simulated bunches of various shapes and experimental measured spectra are presented, discussed and compared with the established Kramers-Kronig method. It is shown that even when the effect of the ambiguities is strong, as is the case for a double peak in the profile, the cross-correlation post-processing is able to filter out unwanted solutions. We show that, unlike the Kramers-Kronig method, the combined approach presented is able to faithfully reconstruct complicated bunch profiles.
Nookaew, Intawat; Papini, Marta; Pornputtapong, Natapol; Scalcinati, Gionata; Fagerberg, Linn; Uhlén, Matthias; Nielsen, Jens
2012-01-01
RNA-seq, has recently become an attractive method of choice in the studies of transcriptomes, promising several advantages compared with microarrays. In this study, we sought to assess the contribution of the different analytical steps involved in the analysis of RNA-seq data generated with the Illumina platform, and to perform a cross-platform comparison based on the results obtained through Affymetrix microarray. As a case study for our work we, used the Saccharomyces cerevisiae strain CEN.PK 113-7D, grown under two different conditions (batch and chemostat). Here, we asses the influence of genetic variation on the estimation of gene expression level using three different aligners for read-mapping (Gsnap, Stampy and TopHat) on S288c genome, the capabilities of five different statistical methods to detect differential gene expression (baySeq, Cuffdiff, DESeq, edgeR and NOISeq) and we explored the consistency between RNA-seq analysis using reference genome and de novo assembly approach. High reproducibility among biological replicates (correlation ≥0.99) and high consistency between the two platforms for analysis of gene expression levels (correlation ≥0.91) are reported. The results from differential gene expression identification derived from the different statistical methods, as well as their integrated analysis results based on gene ontology annotation are in good agreement. Overall, our study provides a useful and comprehensive comparison between the two platforms (RNA-seq and microrrays) for gene expression analysis and addresses the contribution of the different steps involved in the analysis of RNA-seq data. PMID:22965124
Dynamic Time Warping compared to established methods for validation of musculoskeletal models.
Gaspar, Martin; Welke, Bastian; Seehaus, Frank; Hurschler, Christof; Schwarze, Michael
2017-04-11
By means of Multi-Body musculoskeletal simulation, important variables such as internal joint forces and moments can be estimated which cannot be measured directly. Validation can ensued by qualitative or by quantitative methods. Especially when comparing time-dependent signals, many methods do not perform well and validation is often limited to qualitative approaches. The aim of the present study was to investigate the capabilities of the Dynamic Time Warping (DTW) algorithm for comparing time series, which can quantify phase as well as amplitude errors. We contrast the sensitivity of DTW with other established metrics: the Pearson correlation coefficient, cross-correlation, the metric according to Geers, RMSE and normalized RMSE. This study is based on two data sets, where one data set represents direct validation and the other represents indirect validation. Direct validation was performed in the context of clinical gait-analysis on trans-femoral amputees fitted with a 6 component force-moment sensor. Measured forces and moments from amputees' socket-prosthesis are compared to simulated forces and moments. Indirect validation was performed in the context of surface EMG measurements on a cohort of healthy subjects with measurements taken of seven muscles of the leg, which were compared to simulated muscle activations. Regarding direct validation, a positive linear relation between results of RMSE and nRMSE to DTW can be seen. For indirect validation, a negative linear relation exists between Pearson correlation and cross-correlation. We propose the DTW algorithm for use in both direct and indirect quantitative validation as it correlates well with methods that are most suitable for one of the tasks. However, in DV it should be used together with methods resulting in a dimensional error value, in order to be able to interpret results more comprehensible. Copyright © 2017 Elsevier Ltd. All rights reserved.
Structure and Dynamics Analysis on Plexin-B1 Rho GTPase Binding Domain as a Monomer and Dimer
2015-01-01
Plexin-B1 is a single-pass transmembrane receptor. Its Rho GTPase binding domain (RBD) can associate with small Rho GTPases and can also self-bind to form a dimer. In total, more than 400 ns of NAMD molecular dynamics simulations were performed on RBD monomer and dimer. Different analysis methods, such as root mean squared fluctuation (RMSF), order parameters (S2), dihedral angle correlation, transfer entropy, principal component analysis, and dynamical network analysis, were carried out to characterize the motions seen in the trajectories. RMSF results show that after binding, the L4 loop becomes more rigid, but the L2 loop and a number of residues in other regions become slightly more flexible. Calculating order parameters (S2) for CH, NH, and CO bonds on both backbone and side chain shows that the L4 loop becomes essentially rigid after binding, but part of the L1 loop becomes slightly more flexible. Backbone dihedral angle cross-correlation results show that loop regions such as the L1 loop including residues Q25 and G26, the L2 loop including residue R61, and the L4 loop including residues L89–R91, are highly correlated compared to other regions in the monomer form. Analysis of the correlated motions at these residues, such as Q25 and R61, indicate two signal pathways. Transfer entropy calculations on the RBD monomer and dimer forms suggest that the binding process should be driven by the L4 loop and C-terminal. However, after binding, the L4 loop functions as the motion responder. The signal pathways in RBD were predicted based on a dynamical network analysis method using the pathways predicted from the dihedral angle cross-correlation calculations as input. It is found that the shortest pathways predicted from both inputs can overlap, but signal pathway 2 (from F90 to R61) is more dominant and overlaps all of the routes of pathway 1 (from F90 to P111). This project confirms the allosteric mechanism in signal transmission inside the RBD network, which was in part proposed in the previous experimental study. PMID:24901636
Exact Solutions for Rate and Synchrony in Recurrent Networks of Coincidence Detectors
Mikula, Shawn; Niebur, Ernst
2009-01-01
We provide analytical solutions for mean firing rates and cross-correlations of coincidence detector neurons in recurrent networks with excitatory or inhibitory connectivity with rate-modulated steady-state spiking inputs. We use discrete-time finite-state Markov chains to represent network state transition probabilities, which are subsequently used to derive exact analytical solutions for mean firing rates and cross-correlations. As illustrated in several examples, the method can be used for modeling cortical microcircuits and clarifying single-neuron and population coding mechanisms. We also demonstrate that increasing firing rates do not necessarily translate into increasing cross-correlations, though our results do support the contention that firing rates and cross-correlations are likely to be coupled. Our analytical solutions underscore the complexity of the relationship between firing rates and cross-correlations. PMID:18439133
Approximate string matching algorithms for limited-vocabulary OCR output correction
NASA Astrophysics Data System (ADS)
Lasko, Thomas A.; Hauser, Susan E.
2000-12-01
Five methods for matching words mistranslated by optical character recognition to their most likely match in a reference dictionary were tested on data from the archives of the National Library of Medicine. The methods, including an adaptation of the cross correlation algorithm, the generic edit distance algorithm, the edit distance algorithm with a probabilistic substitution matrix, Bayesian analysis, and Bayesian analysis on an actively thinned reference dictionary were implemented and their accuracy rates compared. Of the five, the Bayesian algorithm produced the most correct matches (87%), and had the advantage of producing scores that have a useful and practical interpretation.
NASA Astrophysics Data System (ADS)
Ferreira, Paulo; Kristoufek, Ladislav
2017-11-01
We analyse the covered interest parity (CIP) using two novel regression frameworks based on cross-correlation analysis (detrended cross-correlation analysis and detrending moving-average cross-correlation analysis), which allow for studying the relationships at different scales and work well under non-stationarity and heavy tails. CIP is a measure of capital mobility commonly used to analyse financial integration, which remains an interesting feature of study in the context of the European Union. The importance of this features is related to the fact that the adoption of a common currency is associated with some benefits for countries, but also involves some risks such as the loss of economic instruments to face possible asymmetric shocks. While studying the Eurozone members could explain some problems in the common currency, studying the non-Euro countries is important to analyse if they are fit to take the possible benefits. Our results point to the CIP verification mainly in the Central European countries while in the remaining countries, the verification of the parity is only residual.
Yan, Zhengbing; Kuang, Te-Hui; Yao, Yuan
2017-09-01
In recent years, multivariate statistical monitoring of batch processes has become a popular research topic, wherein multivariate fault isolation is an important step aiming at the identification of the faulty variables contributing most to the detected process abnormality. Although contribution plots have been commonly used in statistical fault isolation, such methods suffer from the smearing effect between correlated variables. In particular, in batch process monitoring, the high autocorrelations and cross-correlations that exist in variable trajectories make the smearing effect unavoidable. To address such a problem, a variable selection-based fault isolation method is proposed in this research, which transforms the fault isolation problem into a variable selection problem in partial least squares discriminant analysis and solves it by calculating a sparse partial least squares model. As different from the traditional methods, the proposed method emphasizes the relative importance of each process variable. Such information may help process engineers in conducting root-cause diagnosis. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Constrained Analysis of Fluorescence Anisotropy Decay:Application to Experimental Protein Dynamics
Feinstein, Efraim; Deikus, Gintaras; Rusinova, Elena; Rachofsky, Edward L.; Ross, J. B. Alexander; Laws, William R.
2003-01-01
Hydrodynamic properties as well as structural dynamics of proteins can be investigated by the well-established experimental method of fluorescence anisotropy decay. Successful use of this method depends on determination of the correct kinetic model, the extent of cross-correlation between parameters in the fitting function, and differences between the timescales of the depolarizing motions and the fluorophore's fluorescence lifetime. We have tested the utility of an independently measured steady-state anisotropy value as a constraint during data analysis to reduce parameter cross correlation and to increase the timescales over which anisotropy decay parameters can be recovered accurately for two calcium-binding proteins. Mutant rat F102W parvalbumin was used as a model system because its single tryptophan residue exhibits monoexponential fluorescence intensity and anisotropy decay kinetics. Cod parvalbumin, a protein with a single tryptophan residue that exhibits multiexponential fluorescence decay kinetics, was also examined as a more complex model. Anisotropy decays were measured for both proteins as a function of solution viscosity to vary hydrodynamic parameters. The use of the steady-state anisotropy as a constraint significantly improved the precision and accuracy of recovered parameters for both proteins, particularly for viscosities at which the protein's rotational correlation time was much longer than the fluorescence lifetime. Thus, basic hydrodynamic properties of larger biomolecules can now be determined with more precision and accuracy by fluorescence anisotropy decay. PMID:12524313
Ivancevich, Nikolas M.; Dahl, Jeremy J.; Smith, Stephen W.
2010-01-01
Phase correction has the potential to increase the image quality of 3-D ultrasound, especially transcranial ultrasound. We implemented and compared 2 algorithms for aberration correction, multi-lag cross-correlation and speckle brightness, using static and moving targets. We corrected three 75-ns rms electronic aberrators with full-width at half-maximum (FWHM) auto-correlation lengths of 1.35, 2.7, and 5.4 mm. Cross-correlation proved the better algorithm at 2.7 and 5.4 mm correlation lengths (P < 0.05). Static cross-correlation performed better than moving-target cross-correlation at the 2.7 mm correlation length (P < 0.05). Finally, we compared the static and moving-target cross-correlation on a flow phantom with a skull casting aberrator. Using signal from static targets, the correction resulted in an average contrast increase of 22.2%, compared with 13.2% using signal from moving targets. The contrast-to-noise ratio (CNR) increased by 20.5% and 12.8% using static and moving targets, respectively. Doppler signal strength increased by 5.6% and 4.9% for the static and moving-targets methods, respectively. PMID:19942503
Ivancevich, Nikolas M; Dahl, Jeremy J; Smith, Stephen W
2009-10-01
Phase correction has the potential to increase the image quality of 3-D ultrasound, especially transcranial ultrasound. We implemented and compared 2 algorithms for aberration correction, multi-lag cross-correlation and speckle brightness, using static and moving targets. We corrected three 75-ns rms electronic aberrators with full-width at half-maximum (FWHM) auto-correlation lengths of 1.35, 2.7, and 5.4 mm. Cross-correlation proved the better algorithm at 2.7 and 5.4 mm correlation lengths (P < 0.05). Static cross-correlation performed better than moving-target cross-correlation at the 2.7 mm correlation length (P < 0.05). Finally, we compared the static and moving-target cross-correlation on a flow phantom with a skull casting aberrator. Using signal from static targets, the correction resulted in an average contrast increase of 22.2%, compared with 13.2% using signal from moving targets. The contrast-to-noise ratio (CNR) increased by 20.5% and 12.8% using static and moving targets, respectively. Doppler signal strength increased by 5.6% and 4.9% for the static and moving-targets methods, respectively.
Statistical tests for power-law cross-correlated processes
NASA Astrophysics Data System (ADS)
Podobnik, Boris; Jiang, Zhi-Qiang; Zhou, Wei-Xing; Stanley, H. Eugene
2011-12-01
For stationary time series, the cross-covariance and the cross-correlation as functions of time lag n serve to quantify the similarity of two time series. The latter measure is also used to assess whether the cross-correlations are statistically significant. For nonstationary time series, the analogous measures are detrended cross-correlations analysis (DCCA) and the recently proposed detrended cross-correlation coefficient, ρDCCA(T,n), where T is the total length of the time series and n the window size. For ρDCCA(T,n), we numerically calculated the Cauchy inequality -1≤ρDCCA(T,n)≤1. Here we derive -1≤ρDCCA(T,n)≤1 for a standard variance-covariance approach and for a detrending approach. For overlapping windows, we find the range of ρDCCA within which the cross-correlations become statistically significant. For overlapping windows we numerically determine—and for nonoverlapping windows we derive—that the standard deviation of ρDCCA(T,n) tends with increasing T to 1/T. Using ρDCCA(T,n) we show that the Chinese financial market's tendency to follow the U.S. market is extremely weak. We also propose an additional statistical test that can be used to quantify the existence of cross-correlations between two power-law correlated time series.
NASA Astrophysics Data System (ADS)
Pollyea, R.; Mohammadi, N.; Taylor, J. E.
2017-12-01
The annual earthquake rate in Oklahoma increased dramatically between 2009 and 2016, owing in large part to the rapid proliferation of salt water disposal wells associated with unconventional oil and gas recovery. This study presents a geospatial analysis of earthquake occurrence and SWD injection volume within a 68,420 km2 area in north-central Oklahoma between 2011 and 2016. The spatial co-variability of earthquake occurrence and SWD injection volume is analyzed for each year of the study by calculating the geographic centroid for both earthquake epicenter and volume-weighted well location. In addition, the spatial cross correlation between earthquake occurrence and SWD volume is quantified by calculating the cross semivariogram annually for a 9.6 km × 9.6 km (6 mi × 6 mi) grid over the study area. Results from these analyses suggest that the relationship between volume-weighted well centroids and earthquake centroids generally follow pressure diffusion space-time scaling, and the volume-weighted well centroid predicts the geographic earthquake centroid within a 1σ radius of gyration. The cross semivariogram calculations show that SWD injection volume and earthquake occurrence are spatially cross correlated between 2014 and 2016. These results also show that the strength of cross correlation decreased from 2015 to 2016; however, the cross correlation length scale remains unchanged at 125 km. This suggests that earthquake mitigation efforts have been moderately successful in decreasing the strength of cross correlation between SWD volume and earthquake occurrence near-field, but the far-field contribution of SWD injection volume to earthquake occurrence remains unaffected.
NASA Astrophysics Data System (ADS)
Ikegawa, Shinichi; Horinouchi, Takeshi
2016-06-01
Accurate wind observation is a key to study atmospheric dynamics. A new automated cloud tracking method for the dayside of Venus is proposed and evaluated by using the ultraviolet images obtained by the Venus Monitoring Camera onboard the Venus Express orbiter. It uses multiple images obtained successively over a few hours. Cross-correlations are computed from the pair combinations of the images and are superposed to identify cloud advection. It is shown that the superposition improves the accuracy of velocity estimation and significantly reduces false pattern matches that cause large errors. Two methods to evaluate the accuracy of each of the obtained cloud motion vectors are proposed. One relies on the confidence bounds of cross-correlation with consideration of anisotropic cloud morphology. The other relies on the comparison of two independent estimations obtained by separating the successive images into two groups. The two evaluations can be combined to screen the results. It is shown that the accuracy of the screened vectors are very high to the equatorward of 30 degree, while it is relatively low at higher latitudes. Analysis of them supports the previously reported existence of day-to-day large-scale variability at the cloud deck of Venus, and it further suggests smaller-scale features. The product of this study is expected to advance the dynamics of venusian atmosphere.
A fractional Fourier transform analysis of a bubble excited by an ultrasonic chirp.
Barlow, Euan; Mulholland, Anthony J
2011-11-01
The fractional Fourier transform is proposed here as a model based, signal processing technique for determining the size of a bubble in a fluid. The bubble is insonified with an ultrasonic chirp and the radiated pressure field is recorded. This experimental bubble response is then compared with a series of theoretical model responses to identify the most accurate match between experiment and theory which allows the correct bubble size to be identified. The fractional Fourier transform is used to produce a more detailed description of each response, and two-dimensional cross correlation is then employed to identify the similarities between the experimental response and each theoretical response. In this paper the experimental bubble response is simulated by adding various levels of noise to the theoretical model output. The method is compared to the standard technique of using time-domain cross correlation. The proposed method is shown to be far more robust at correctly sizing the bubble and can cope with much lower signal to noise ratios.
Understanding the multifractality in portfolio excess returns
NASA Astrophysics Data System (ADS)
Chen, Cheng; Wang, Yudong
2017-01-01
The multifractality in stock returns have been investigated extensively. However, whether the autocorrelations in portfolio returns are multifractal have not been considered in the literature. In this paper, we detect multifractal behavior of returns of portfolios constructed based on two popular trading rules, size and book-to-market (BM) ratio. Using the multifractal detrended fluctuation analysis, we find that the portfolio returns are significantly multifractal and the multifractality is mainly attributed to long-range dependence. We also investigate the multifractal cross-correlation between portfolio return and market average return using the detrended cross-correlation analysis. Our results show that the cross-correlations of small fluctuations are persistent, while those of large fluctuations are anti-persistent.
NASA Astrophysics Data System (ADS)
Chen, Xiwen; Huang, Zufang; Xi, Gangqin; Chen, Yongjian; Lin, Duo; Wang, Jing; Li, Zuanfang; Sun, Liqing; Chen, Jianxin; Chen, Rong
2012-03-01
Second-harmonic generation (SHG) is proved to be a high spatial resolution, large penetration depth and non-photobleaching method. In our study, SHG method was used to investigate the normal and cancerous thyroid tissue. For SHG imaging performance, system parameters were adjusted for high-contrast images acquisition. Each x-y image was recorded in pseudo-color, which matches the wavelength range in the visible spectrum. The acquisition time for a 512×512-pixels image was 1.57 sec; each acquired image was averaged four frames to improve the signal-to-noise ratio. Our results indicated that collagen presence as determined by counting the ratio of the SHG pixels over the whole pixels for normal and cancerous thyroid tissues were 0.48+/-0.05, 0.33+/-0.06 respectively. In addition, to quantitatively assess collagen-related changes, we employed GLCM texture analysis to the SHG images. Corresponding results showed that the correlation both fell off with distance in normal and cancerous group. Calculated value of Corr50 (the distance where the correlation crossed 50% of the initial correlation) indicated significant difference. This study demonstrates that SHG method can be used as a complementary tool in thyroid histopathology.
Estimation of Sensory Analysis Cupping Test Arabica Coffee Using NIR Spectroscopy
NASA Astrophysics Data System (ADS)
Safrizal; Sutrisno; Lilik, P. E. N.; Ahmad, U.; Samsudin
2018-05-01
Flavors have become the most important coffee quality parameters now day, many coffee consuming countries require certain taste scores for the coffee to be ordered, the currently used cupping method of appraisal is the method designed by The Specialty Coffee Association Of America (SCAA), from several previous studies was found that Near-Infrared Spectroscopy (NIRS) can be used to detect chemical composition of certain materials including those associated with flavor so it is possible also to be applied to coffee powder. The aim of this research is to get correlation between NIRS spectrum with cupping scoring by tester, then look at the possibility of testing coffee taste sensors using NIRS spectrum. The coffee samples were taken from various places, altitudes and postharvest handling methods, then the samples were prepared following the SCAA protocol, for sensory analysis was done in two ways, with the expert tester and with the NIRS test. The calibration between both found that Without pretreatment using PLS get RMSE cross validation 6.14, using Multiplicative Scatter Correction spectra obtained RMSE cross validation 5.43, the best RMSE cross-validation was 1.73 achieved by de-trending correction, NIRS can be used to predict the score of cupping.
Das, Atanu; Mukhopadhyay, Chaitali
2007-10-28
We have performed molecular dynamics (MD) simulation of the thermal denaturation of one protein and one peptide-ubiquitin and melittin. To identify the correlation in dynamics among various secondary structural fragments and also the individual contribution of different residues towards thermal unfolding, principal component analysis method was applied in order to give a new insight to protein dynamics by analyzing the contribution of coefficients of principal components. The cross-correlation matrix obtained from MD simulation trajectory provided important information regarding the anisotropy of backbone dynamics that leads to unfolding. Unfolding of ubiquitin was found to be a three-state process, while that of melittin, though smaller and mostly helical, is more complicated.
NASA Astrophysics Data System (ADS)
Das, Atanu; Mukhopadhyay, Chaitali
2007-10-01
We have performed molecular dynamics (MD) simulation of the thermal denaturation of one protein and one peptide—ubiquitin and melittin. To identify the correlation in dynamics among various secondary structural fragments and also the individual contribution of different residues towards thermal unfolding, principal component analysis method was applied in order to give a new insight to protein dynamics by analyzing the contribution of coefficients of principal components. The cross-correlation matrix obtained from MD simulation trajectory provided important information regarding the anisotropy of backbone dynamics that leads to unfolding. Unfolding of ubiquitin was found to be a three-state process, while that of melittin, though smaller and mostly helical, is more complicated.
A phase coherence approach to identifying co-located earthquakes and tremor
NASA Astrophysics Data System (ADS)
Hawthorne, J. C.; Ampuero, J.-P.
2018-05-01
We present and use a phase coherence approach to identify seismic signals that have similar path effects but different source time functions: co-located earthquakes and tremor. The method used is a phase coherence-based implementation of empirical matched field processing, modified to suit tremor analysis. It works by comparing the frequency-domain phases of waveforms generated by two sources recorded at multiple stations. We first cross-correlate the records of the two sources at a single station. If the sources are co-located, this cross-correlation eliminates the phases of the Green's function. It leaves the relative phases of the source time functions, which should be the same across all stations so long as the spatial extent of the sources are small compared with the seismic wavelength. We therefore search for cross-correlation phases that are consistent across stations as an indication of co-located sources. We also introduce a method to obtain relative locations between the two sources, based on back-projection of interstation phase coherence. We apply this technique to analyse two tremor-like signals that are thought to be composed of a number of earthquakes. First, we analyse a 20 s long seismic precursor to a M 3.9 earthquake in central Alaska. The analysis locates the precursor to within 2 km of the mainshock, and it identifies several bursts of energy—potentially foreshocks or groups of foreshocks—within the precursor. Second, we examine several minutes of volcanic tremor prior to an eruption at Redoubt Volcano. We confirm that the tremor source is located close to repeating earthquakes identified earlier in the tremor sequence. The amplitude of the tremor diminishes about 30 s before the eruption, but the phase coherence results suggest that the tremor may persist at some level through this final interval.
A blind search for a common signal in gravitational wave detectors
NASA Astrophysics Data System (ADS)
Liu, Hao; Creswell, James; von Hausegger, Sebastian; Jackson, Andrew D.; Naselsky, Pavel
2018-02-01
We propose a blind, template-free method for the extraction of a common signal between the Hanford and Livingston detectors and apply it especially to the GW150914 event. We construct a log-likelihood method that maximizes the cross-correlation between each detector and the common signal and minimizes the cross-correlation between the residuals. The reliability of this method is tested using simulations with an injected common signal. Finally, our method is used to assess the quality of theoretical gravitational wave templates for GW150914.
Precise Relative Earthquake Magnitudes from Cross Correlation
Cleveland, K. Michael; Ammon, Charles J.
2015-04-21
We present a method to estimate precise relative magnitudes using cross correlation of seismic waveforms. Our method incorporates the intercorrelation of all events in a group of earthquakes, as opposed to individual event pairings relative to a reference event. This method works well when a reliable reference event does not exist. We illustrate the method using vertical strike-slip earthquakes located in the northeast Pacific and Panama fracture zone regions. Our results are generally consistent with the Global Centroid Moment Tensor catalog, which we use to establish a baseline for the relative event sizes.
NASA Astrophysics Data System (ADS)
Diallo, M. S.; Holschneider, M.; Kulesh, M.; Scherbaum, F.; Ohrnberger, M.; Lück, E.
2004-05-01
This contribution is concerned with the estimate of attenuation and dispersion characteristics of surface waves observed on a shallow seismic record. The analysis is based on a initial parameterization of the phase and attenuation functions which are then estimated by minimizing a properly defined merit function. To minimize the effect of random noise on the estimates of dispersion and attenuation we use cross-correlations (in Fourier domain) of preselected traces from some region of interest along the survey line. These cross-correlations are then expressed in terms of the parameterized attenuation and phase functions and the auto-correlation of the so-called source trace or reference trace. Cross-corelation that enter the optimization are selected so as to provide an average estimate of both the attenuation function and the phase (group) velocity of the area under investigation. The advantage of the method over the standard two stations method using Fourier technique is that uncertainties related to the phase unwrapping and the estimate of the number of 2π cycle skip in the phase phase are eliminated. However when mutliple modes arrival are observed, its become merely impossible to obtain reliable estimate the dipsersion curves for the different modes using optimization method alone. To circumvent this limitations we using the presented approach in conjunction with the wavelet propagation operator (Kulesh et al., 2003) which allows the application of band pass filtering in (ω -t) domain, to select a particular mode for the minimization. Also by expressing the cost function in the wavelet domain the optimization can be performed either with respect to the phase, the modulus of the transform or a combination of both. This flexibility in the design of the cost function provides an additional mean of constraining the optimization results. Results from the application of this dispersion and attenuation analysis method are shown for both synthetic and real 2D shallow seismic data sets. M. Kulesh, M. Holschneider, M. S. Diallo, Q. Xie and F. Scherbaum, Modeling of Wave Dispersion Using Wavelet Transfrom (Submitted to Pure and Applied Geophysics).
Improved Characterization of Far-Regional and Near-Teleseismic Phases Observed in Central Asia
2010-07-02
Pn/P travel-time residuals as a function of epicentral distance. To generate this figure, we retrieved International Seismic Centre (ISC) bulletins...spectral frequency-wave number methods (e.g., Capon, 1969), multiple signal characteristic ( MUSIC ; Stoica and Nehorai, 1989), cross-correlation (Tibuleac...root and cross-correlation implementations. Methods such as MUSIC do not suffer these limitations and can perform well on far-regional arrivals
Human erythrocytes analyzed by generalized 2D Raman correlation spectroscopy
NASA Astrophysics Data System (ADS)
Wesełucha-Birczyńska, Aleksandra; Kozicki, Mateusz; Czepiel, Jacek; Łabanowska, Maria; Nowak, Piotr; Kowalczyk, Grzegorz; Kurdziel, Magdalena; Birczyńska, Malwina; Biesiada, Grażyna; Mach, Tomasz; Garlicki, Aleksander
2014-07-01
The most numerous elements of the blood cells, erythrocytes, consist mainly of two components: homogeneous interior filled with hemoglobin and closure which is the cell membrane. To gain insight into their specific properties we studied the process of disintegration, considering these two constituents, and comparing the natural aging process of human healthy blood cells. MicroRaman spectra of hemoglobin within the single RBC were recorded using 514.5, and 785 nm laser lines. The generalized 2D correlation method was applied to analyze the collected spectra. The time passed from blood donation was regarded as an external perturbation. The time was no more than 40 days according to the current storage limit of blood banks, although, the average RBC life span is 120 days. An analysis of the prominent synchronous and asynchronous cross peaks allow us to get insight into the mechanism of hemoglobin decomposition. Appearing asynchronous cross-peaks point towards globin and heme separation from each other, while synchronous shows already broken globin into individual amino acids. Raman scattering analysis of hemoglobin "wrapping", i.e. healthy erythrocyte ghosts, allows for the following peculiarity of their behavior. The increasing power of the excitation laser induced alterations in the assemblage of membrane lipids. 2D correlation maps, obtained with increasing laser power recognized as an external perturbation, allows for the consideration of alterations in the erythrocyte membrane structure and composition, which occurs first in the proteins. Cross-peaks were observed indicating an asynchronous correlation between the senescent-cell antigen (SCA) and heme or proteins vibrations. The EPR spectra of the whole blood was analyzed regarding time as an external stimulus. The 2D correlation spectra points towards participation of the selected metal ion centers in the disintegration process.
Kettaneh, A; Heude, B; Lommez, A; Borys, J M; Ducimetière, P; Charles, M A
2005-12-01
To evaluate the reproducibility of the measurement of% body fat by bipedal biometrical impedance analysis (BIA) compared with anthropometric measurements of adiposity in children and the correlations between these methods in children and adults. A cross-sectional study in a total of 1080 adults and children enrolled in 1999 in the Fleurbaix-Laventie Ville Santé II (FLVS II) population-based study in northern France. The reproducibility of anthropometrical and BIA methods was determined by a nested analysis of variance of repeated measurements by 2 investigators and a bipedal BIA device (Tanita TBF 310) in 64 pupils of two 5th grade classes. The correlation of BIA and anthropometric adiposity measurements with the unknown relative fat mass or volume of the body estimated by a latent adiposity variable (LAV) was established by the triads' method in 1080 subjects of the FLVS II cohort. The reproducibility was similar for the sum of skinfolds, waist circumference and BIA% fat measurements (intraclass correlation coefficients: 0.979-0.992). Correlation coefficient between BIA body fat% and the LAV was higher than 0.86 in all sex and Tanner stage related groups, and similar in children and adults, except in pubertal boys (0.76). With a high level of reproducibility, foot-to-foot BIA analysis provides a valuable measurement of total% fat for epidemiologic studies in children. However further studies are needed before extrapolating these results to overweight children.
Weak lensing magnification in the Dark Energy Survey Science Verification data
NASA Astrophysics Data System (ADS)
Garcia-Fernandez, M.; Sanchez, E.; Sevilla-Noarbe, I.; Suchyta, E.; Huff, E. M.; Gaztanaga, E.; Aleksić, J.; Ponce, R.; Castander, F. J.; Hoyle, B.; Abbott, T. M. C.; Abdalla, F. B.; Allam, S.; Annis, J.; Benoit-Lévy, A.; Bernstein, G. M.; Bertin, E.; Brooks, D.; Buckley-Geer, E.; Burke, D. L.; Carnero Rosell, A.; Carrasco Kind, M.; Carretero, J.; Crocce, M.; Cunha, C. E.; D'Andrea, C. B.; da Costa, L. N.; DePoy, D. L.; Desai, S.; Diehl, H. T.; Eifler, T. F.; Evrard, A. E.; Fernandez, E.; Flaugher, B.; Fosalba, P.; Frieman, J.; García-Bellido, J.; Gerdes, D. W.; Giannantonio, T.; Gruen, D.; Gruendl, R. A.; Gschwend, J.; Gutierrez, G.; James, D. J.; Jarvis, M.; Kirk, D.; Krause, E.; Kuehn, K.; Kuropatkin, N.; Lahav, O.; Lima, M.; MacCrann, N.; Maia, M. A. G.; March, M.; Marshall, J. L.; Melchior, P.; Miquel, R.; Mohr, J. J.; Plazas, A. A.; Romer, A. K.; Roodman, A.; Rykoff, E. S.; Scarpine, V.; Schubnell, M.; Smith, R. C.; Soares-Santos, M.; Sobreira, F.; Tarle, G.; Thomas, D.; Walker, A. R.; Wester, W.; DES Collaboration
2018-05-01
In this paper, the effect of weak lensing magnification on galaxy number counts is studied by cross-correlating the positions of two galaxy samples, separated by redshift, using the Dark Energy Survey Science Verification data set. This analysis is carried out for galaxies that are selected only by its photometric redshift. An extensive analysis of the systematic effects, using new methods based on simulations is performed, including a Monte Carlo sampling of the selection function of the survey.
NASA Astrophysics Data System (ADS)
Haendel, A.; Ohrnberger, M.; Krüger, F.
2016-11-01
Knowledge of the quality factor of near-surface materials is of fundamental interest in various applications. Attenuation can be very strong close to the surface and thus needs to be properly assessed. In recent years, several researchers have studied the retrieval of attenuation coefficients from the cross correlation of ambient seismic noise. Yet, the determination of exact amplitude information from noise-correlation functions is, in contrast to the extraction of traveltimes, not trivial. Most of the studies estimated attenuation coefficients on the regional scale and within the microseism band. In this paper, we investigate the possibility to derive attenuation coefficients from seismic noise at much shallower depths and higher frequencies (>1 Hz). The Euroseistest area in northern Greece offers ideal conditions to study quality factor retrieval from ambient noise for different rock types. Correlations are computed between the stations of a small scale array experiment (station spacings <2 km) that was carried out in the Euroseistest area in 2011. We employ the correlation of the coda of the correlation (C3) method instead of simple cross correlations to mitigate the effect of uneven noise source distributions on the correlation amplitude. Transient removal and temporal flattening are applied instead of 1-bit normalization in order to retain relative amplitudes. The C3 method leads to improved correlation results (higher signal-to-noise ratio and improved time symmetry) compared to simple cross correlations. The C3 functions are rotated from the ZNE to the ZRT system and we focus on Love wave arrivals on the transverse component and on Love wave quality factors QL. The analysis is performed for selected stations being either situated on soft soil or on weathered rock. Phase slowness is extracted using a slant-stack method. Attenuation parameters are inferred by inspecting the relative amplitude decay of Love waves with increasing interstation distance. We observe that the attenuation coefficient γ and QL can be reliably extracted for stations situated on soft soil whereas the derivation of attenuation parameters is more problematic for stations that are located on weathered rock. The results are in acceptable conformance with theoretical Love wave attenuation curves that were computed using 1-D shear wave velocity and quality factor profiles from the Euroseistest area.
Cross-sample entropy of foreign exchange time series
NASA Astrophysics Data System (ADS)
Liu, Li-Zhi; Qian, Xi-Yuan; Lu, Heng-Yao
2010-11-01
The correlation of foreign exchange rates in currency markets is investigated based on the empirical data of DKK/USD, NOK/USD, CAD/USD, JPY/USD, KRW/USD, SGD/USD, THB/USD and TWD/USD for a period from 1995 to 2002. Cross-SampEn (cross-sample entropy) method is used to compare the returns of every two exchange rate time series to assess their degree of asynchrony. The calculation method of confidence interval of SampEn is extended and applied to cross-SampEn. The cross-SampEn and its confidence interval for every two of the exchange rate time series in periods 1995-1998 (before the Asian currency crisis) and 1999-2002 (after the Asian currency crisis) are calculated. The results show that the cross-SampEn of every two of these exchange rates becomes higher after the Asian currency crisis, indicating a higher asynchrony between the exchange rates. Especially for Singapore, Thailand and Taiwan, the cross-SampEn values after the Asian currency crisis are significantly higher than those before the Asian currency crisis. Comparison with the correlation coefficient shows that cross-SampEn is superior to describe the correlation between time series.
Computationally Efficient 2D DOA Estimation with Uniform Rectangular Array in Low-Grazing Angle.
Shi, Junpeng; Hu, Guoping; Zhang, Xiaofei; Sun, Fenggang; Xiao, Yu
2017-02-26
In this paper, we propose a computationally efficient spatial differencing matrix set (SDMS) method for two-dimensional direction of arrival (2D DOA) estimation with uniform rectangular arrays (URAs) in a low-grazing angle (LGA) condition. By rearranging the auto-correlation and cross-correlation matrices in turn among different subarrays, the SDMS method can estimate the two parameters independently with one-dimensional (1D) subspace-based estimation techniques, where we only perform difference for auto-correlation matrices and the cross-correlation matrices are kept completely. Then, the pair-matching of two parameters is achieved by extracting the diagonal elements of URA. Thus, the proposed method can decrease the computational complexity, suppress the effect of additive noise and also have little information loss. Simulation results show that, in LGA, compared to other methods, the proposed methods can achieve performance improvement in the white or colored noise conditions.
Computationally Efficient 2D DOA Estimation with Uniform Rectangular Array in Low-Grazing Angle
Shi, Junpeng; Hu, Guoping; Zhang, Xiaofei; Sun, Fenggang; Xiao, Yu
2017-01-01
In this paper, we propose a computationally efficient spatial differencing matrix set (SDMS) method for two-dimensional direction of arrival (2D DOA) estimation with uniform rectangular arrays (URAs) in a low-grazing angle (LGA) condition. By rearranging the auto-correlation and cross-correlation matrices in turn among different subarrays, the SDMS method can estimate the two parameters independently with one-dimensional (1D) subspace-based estimation techniques, where we only perform difference for auto-correlation matrices and the cross-correlation matrices are kept completely. Then, the pair-matching of two parameters is achieved by extracting the diagonal elements of URA. Thus, the proposed method can decrease the computational complexity, suppress the effect of additive noise and also have little information loss. Simulation results show that, in LGA, compared to other methods, the proposed methods can achieve performance improvement in the white or colored noise conditions. PMID:28245634
A variance-decomposition approach to investigating multiscale habitat associations
Lawler, J.J.; Edwards, T.C.
2006-01-01
The recognition of the importance of spatial scale in ecology has led many researchers to take multiscale approaches to studying habitat associations. However, few of the studies that investigate habitat associations at multiple spatial scales have considered the potential effects of cross-scale correlations in measured habitat variables. When cross-scale correlations in such studies are strong, conclusions drawn about the relative strength of habitat associations at different spatial scales may be inaccurate. Here we adapt and demonstrate an analytical technique based on variance decomposition for quantifying the influence of cross-scale correlations on multiscale habitat associations. We used the technique to quantify the variation in nest-site locations of Red-naped Sapsuckers (Sphyrapicus nuchalis) and Northern Flickers (Colaptes auratus) associated with habitat descriptors at three spatial scales. We demonstrate how the method can be used to identify components of variation that are associated only with factors at a single spatial scale as well as shared components of variation that represent cross-scale correlations. Despite the fact that no explanatory variables in our models were highly correlated (r < 0.60), we found that shared components of variation reflecting cross-scale correlations accounted for roughly half of the deviance explained by the models. These results highlight the importance of both conducting habitat analyses at multiple spatial scales and of quantifying the effects of cross-scale correlations in such analyses. Given the limits of conventional analytical techniques, we recommend alternative methods, such as the variance-decomposition technique demonstrated here, for analyzing habitat associations at multiple spatial scales. ?? The Cooper Ornithological Society 2006.
NASA Astrophysics Data System (ADS)
Molero, B.; Leroux, D. J.; Richaume, P.; Kerr, Y. H.; Merlin, O.; Cosh, M. H.; Bindlish, R.
2018-01-01
We conduct a novel comprehensive investigation that seeks to prove the connection between spatial scales and timescales in surface soil moisture (SM) within the satellite footprint ( 50 km). Modeled and measured point series at Yanco and Little Washita in situ networks are first decomposed into anomalies at timescales ranging from 0.5 to 128 days, using wavelet transforms. Then, their degree of spatial representativeness is evaluated on a per-timescale basis by comparison to large spatial scale data sets (the in situ spatial average, SMOS, AMSR2, and ECMWF). Four methods are used for this: temporal stability analysis (TStab), triple collocation (TC), percentage of correlated areas (CArea), and a new proposed approach that uses wavelet-based correlations (WCor). We found that the mean of the spatial representativeness values tends to increase with the timescale but so does their dispersion. Locations exhibit poor spatial representativeness at scales below 4 days, while either very good or poor representativeness at seasonal scales. Regarding the methods, TStab cannot be applied to the anomaly series due to their multiple zero-crossings, and TC is suitable for week and month scales but not for other scales where data set cross-correlations are found low. In contrast, WCor and CArea give consistent results at all timescales. WCor is less sensitive to the spatial sampling density, so it is a robust method that can be applied to sparse networks (one station per footprint). These results are promising to improve the validation and downscaling of satellite SM series and the optimization of SM networks.
NASA Astrophysics Data System (ADS)
Yu, Lingyu; Bao, Jingjing; Giurgiutiu, Victor
2004-07-01
Embedded ultrasonic structural radar (EUSR) algorithm is developed for using piezoelectric wafer active sensor (PWAS) array to detect defects within a large area of a thin-plate specimen. Signal processing techniques are used to extract the time of flight of the wave packages, and thereby to determine the location of the defects with the EUSR algorithm. In our research, the transient tone-burst wave propagation signals are generated and collected by the embedded PWAS. Then, with signal processing, the frequency contents of the signals and the time of flight of individual frequencies are determined. This paper starts with an introduction of embedded ultrasonic structural radar algorithm. Then we will describe the signal processing methods used to extract the time of flight of the wave packages. The signal processing methods being used include the wavelet denoising, the cross correlation, and Hilbert transform. Though hardware device can provide averaging function to eliminate the noise coming from the signal collection process, wavelet denoising is included to ensure better signal quality for the application in real severe environment. For better recognition of time of flight, cross correlation method is used. Hilbert transform is applied to the signals after cross correlation in order to extract the envelope of the signals. Signal processing and EUSR are both implemented by developing a graphical user-friendly interface program in LabView. We conclude with a description of our vision for applying EUSR signal analysis to structural health monitoring and embedded nondestructive evaluation. To this end, we envisage an automatic damage detection application utilizing embedded PWAS, EUSR, and advanced signal processing.
Estimation of TOA based MUSIC algorithm and cross correlation algorithm of appropriate interval
NASA Astrophysics Data System (ADS)
Lin, Wei; Liu, Jun; Zhou, Yineng; Huang, Jiyan
2017-03-01
Localization of mobile station (MS) has now gained considerable attention due to its wide applications in military, environmental, health and commercial systems. Phrase angle and encode data of MSK system model are two critical parameters in time-of-arrival (TOA) localization technique; nevertheless, precise value of phrase angle and encode data are not easy to achieved in general. In order to meet the actual situation, we should consider the condition that phase angle and encode data is unknown. In this paper, a novel TOA localization method, which combine MUSIC algorithm and cross correlation algorithm in an appropriate interval, is proposed. Simulations show that the proposed method has better performance than music algorithm and cross correlation algorithm of the whole interval.
2010-01-01
Background Glucocorticoids (GC) represent the core treatment modality for many inflammatory diseases. Its mode of action is difficult to grasp, not least because it includes direct modulation of many components of the extracellular matrix as well as complex anti-inflammatory effects. Protein expression profile of skin proteins is being changed with topical application of GC, however, the knowledge about singular markers in this regard is only patchy and collaboration is ill defined. Material/Methods Scar formation was observed under different doses of GC, which were locally applied on the back skin of mice (1 to 3 weeks). After euthanasia we analyzed protein expression of collagen I and III (picrosirius) in scar tissue together with 16 additional protein markers, which are involved in wound healing, with immunhistochemistry. For assessing GC's effect on co-expression we compared our results with a model of random figures to estimate how many significant correlations should be expected by chance. Results GC altered collagen and protein expression with distinct results in different areas of investigation. Most often we observed a reduced expression after application of low dose GC. In the scar infiltrate a multivariate analysis confirmed the significant impact of both GC concentrations. Calculation of Spearman's correlation coefficient similarly resulted in a significant impact of GC, and furthermore, offered the possibility to grasp the entire interactive profile in between all variables studied. The biological markers, which were connected by significant correlations could be arranged in a highly cross-linked network that involved most of the markers measured. A marker highly cross-linked with more than 3 significant correlations was indicated by a higher variation of all its correlations to the other variables, resulting in a standard deviation of > 0.2. Conclusion In addition to immunohistochemical analysis of single protein markers multivariate analysis of co-expressions by use of correlation coefficients reveals the complexity of biological relationships and identifies complex biological effects of GC on skin scarring. Depiction of collaborative clusters will help to understand functional pathways. The functional importance of highly cross-linked proteins will have to be proven in subsequent studies. PMID:20509951
Goswami, Mousumi; Singh, Darrel; Massod, Shahid S; Nganba, Khundrakpam
2016-01-01
Purpose To determine the prevalence of Streptococcus mutans (MS) in mother-child pairs and to evaluate the correlation in the levels of salivary MS of working and nonworking mothers with that of their children and their associations with other related factors. Materials and methods A cross-sectional study was carried out among 100 mother-child pairs residing in New Multan Nagar Colony, New Delhi, India. A total of 50 children with their mothers were included in the working group and another 50 were included in the nonworking group. A questionnaire regarding the feeding habits, oral hygiene habits, daily intake of sugars of the children along with their weaning time was carried out. All mothers and children were clinically examined for recording decayed, extracted, and filled teeth (deft)/decayed, missing, and filled teeth (DMFT), and whole unstimulated saliva was collected and cultured for MS in the laboratory. The data were collected and subjected to statistical analysis using chi-square, Spearman’s correlation, and logistic regression analysis. Results The prevalence of salivary MS in the children was 69%. A statistically significant correlation was found between the oral levels of MS in nonworking and working mother-child pairs. Regression analysis showed that those children who feed by bottle for more than 12 months, have daily sweet intake, have sugars in feeding bottle and have higher defts were more likely to have mutans score of 1 or 2. Conclusion The mother, working or nonworking, being the primary care provider is the major source of transmission of MS to their child irrespective of the amount of time spent with them. How to cite this article Sharma P, Goswami M, Singh D, Massod SS, Nganba K. Correlation of Streptococcus mutans count in Mother-child Pair of Working and Nonworking Mothers: A Cross-sectional Study. Int J Clin Pediatr Dent 2016;9(4):342-348. PMID:28127167
Updated tomographic analysis of the integrated Sachs-Wolfe effect and implications for dark energy
NASA Astrophysics Data System (ADS)
Stölzner, Benjamin; Cuoco, Alessandro; Lesgourgues, Julien; Bilicki, Maciej
2018-03-01
We derive updated constraints on the integrated Sachs-Wolfe (ISW) effect through cross-correlation of the cosmic microwave background with galaxy surveys. We improve with respect to similar previous analyses in several ways. First, we use the most recent versions of extragalactic object catalogs, SDSS DR12 photometric redshift (photo-z ) and 2MASS Photo-z data sets, as well as those employed earlier for ISW, SDSS QSO photo-z and NVSS samples. Second, we use for the first time the WISE × SuperCOSMOS catalog, which allows us to perform an all-sky analysis of the ISW up to z ˜0.4 . Third, thanks to the use of photo-z s , we separate each data set into different redshift bins, deriving the cross-correlation in each bin. This last step leads to a significant improvement in sensitivity. We remove cross-correlation between catalogs using masks which mutually exclude common regions of the sky. We use two methods to quantify the significance of the ISW effect. In the first one, we fix the cosmological model, derive linear galaxy biases of the catalogs, and then evaluate the significance of the ISW using a single parameter. In the second approach we perform a global fit of the ISW and of the galaxy biases varying the cosmological model. We find significances of the ISW in the range 4.7 - 5.0 σ thus reaching, for the first time in such an analysis, the threshold of 5 σ . Without the redshift tomography we find a significance of ˜4.0 σ , which shows the importance of the binning method. Finally we use the ISW data to infer constraints on the dark energy redshift evolution and equation of state. We find that the redshift range covered by the catalogs is still not optimal to derive strong constraints, although this goal will be likely reached using future datasets such as from Euclid, LSST, and SKA.
NASA Technical Reports Server (NTRS)
Bhatia, A. K.; Temkin, A.; Fisher, Richard R. (Technical Monitor)
2001-01-01
We report on the first part of a study of electron-hydrogen scattering, using a method which allows for the ab initio calculation of total and elastic cross sections at higher energies. In its general form the method uses complex 'radial' correlation functions, in a (Kohn) T-matrix formalism. The titled method, abbreviated Complex Correlation Kohn T (CCKT) method, is reviewed, in the context of electron-hydrogen scattering, including the derivation of the equation for the (complex) scattering function, and the extraction of the scattering information from the latter. The calculation reported here is restricted to S-waves in the elastic region, where the correlation functions can be taken, without loss of generality, to be real. Phase shifts are calculated using Hylleraas-type correlation functions with up to 95 terms. Results are rigorous lower bounds; they are in general agreement with those of Schwartz, but they are more accurate and outside his error bounds at a couple of energies,
NASA Technical Reports Server (NTRS)
Viswanathan, A. V.; Tamekuni, M.
1973-01-01
An exact linear analysis method is presented for predicting buckling of structures with arbitrary uniform cross section. The structure is idealized as an assemblage of laminated plate-strip elements, curved and planar, and beam elements. Element edges normal to the longitudinal axes are assumed to be simply supported. Arbitrary boundary conditions may be specified on any external longitudinal edge of plate-strip elements. The structure or selected elements may be loaded in any desired combination of inplane transverse compression or tension side load and axial compression load. The analysis simultaneously considers all possible modes of instability and is applicable for the buckling of laminated composite structures. Numerical results correlate well with the results of previous analysis methods.
Extension of the Haseman-Elston regression model to longitudinal data.
Won, Sungho; Elston, Robert C; Park, Taesung
2006-01-01
We propose an extension to longitudinal data of the Haseman and Elston regression method for linkage analysis. The proposed model is a mixed model having several random effects. As response variable, we investigate the sibship sample mean corrected cross-product (smHE) and the BLUP-mean corrected cross product (pmHE), comparing them with the original squared difference (oHE), the overall mean corrected cross-product (rHE), and the weighted average of the squared difference and the squared mean-corrected sum (wHE). The proposed model allows for the correlation structure of longitudinal data. Also, the model can test for gene x time interaction to discover genetic variation over time. The model was applied in an analysis of the Genetic Analysis Workshop 13 (GAW13) simulated dataset for a quantitative trait simulating systolic blood pressure. Independence models did not preserve the test sizes, while the mixed models with both family and sibpair random effects tended to preserve size well. Copyright 2006 S. Karger AG, Basel.
Random matrix approach to cross correlations in financial data
NASA Astrophysics Data System (ADS)
Plerou, Vasiliki; Gopikrishnan, Parameswaran; Rosenow, Bernd; Amaral, Luís A.; Guhr, Thomas; Stanley, H. Eugene
2002-06-01
We analyze cross correlations between price fluctuations of different stocks using methods of random matrix theory (RMT). Using two large databases, we calculate cross-correlation matrices
NASA Astrophysics Data System (ADS)
Wang, Ting-Ting; Ma, Yu-Gang; Zhang, Chun-Jian; Zhang, Zheng-Qiao
2018-03-01
The proton-proton momentum correlation function from different rapidity regions is systematically investigated for the Au + Au collisions at different impact parameters and different energies from 400 A MeV to 1500 A MeV in the framework of the isospin-dependent quantum molecular dynamics model complemented by the Lednický-Lyuboshitz analytical method. In particular, the in-medium nucleon-nucleon cross-section dependence of the correlation function is brought into focus, while the impact parameter and energy dependence of the momentum correlation function are also explored. The sizes of the emission source are extracted by fitting the momentum correlation functions using the Gaussian source method. We find that the in-medium nucleon-nucleon cross section obviously influences the proton-proton momentum correlation function, which is from the whole-rapidity or projectile or target rapidity region at smaller impact parameters, but there is no effect on the mid-rapidity proton-proton momentum correlation function, which indicates that the emission mechanism differs between projectile or target rapidity and mid-rapidity protons.
Spatio-temporal coordination among functional residues in protein
NASA Astrophysics Data System (ADS)
Dutta, Sutapa; Ghosh, Mahua; Chakrabarti, J.
2017-01-01
The microscopic basis of communication among the functional sites in bio-macromolecules is a fundamental challenge in uncovering their functions. We study the communication through temporal cross-correlation among the binding sites. We illustrate via Molecular Dynamics simulations the properties of the temporal cross-correlation between the dihedrals of a small protein, ubiquitin which participates in protein degradation in eukaryotes. We show that the dihedral angles of the residues possess non-trivial temporal cross-correlations with asymmetry with respect to exchange of the dihedrals, having peaks at low frequencies with time scales in nano-seconds and an algebraic tail with a universal exponent for large frequencies. We show the existence of path for temporally correlated degrees of freedom among the functional residues. We explain the qualitative features of the cross-correlations through a general mathematical model. The generality of our analysis suggests that temporal cross-correlation functions may provide convenient theoretical framework to understand bio-molecular functions on microscopic basis.
Inference for High-dimensional Differential Correlation Matrices *
Cai, T. Tony; Zhang, Anru
2015-01-01
Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantees are given. Minimax rate of convergence is established and the proposed estimator is shown to be adaptively rate-optimal over collections of paired correlation matrices with approximately sparse differences. Simulation results show that the procedure significantly outperforms two other natural methods that are based on separate estimation of the individual correlation matrices. The procedure is also illustrated through an analysis of a breast cancer dataset, which provides evidence at the gene co-expression level that several genes, of which a subset has been previously verified, are associated with the breast cancer. Hypothesis testing on the differential correlation matrices is also considered. A test, which is particularly well suited for testing against sparse alternatives, is introduced. In addition, other related problems, including estimation of a single sparse correlation matrix, estimation of the differential covariance matrices, and estimation of the differential cross-correlation matrices, are also discussed. PMID:26500380
Development and evaluation of modified envelope correlation method for deep tectonic tremor
NASA Astrophysics Data System (ADS)
Mizuno, N.; Ide, S.
2017-12-01
We develop a new location method for deep tectonic tremors, as an improvement of widely used envelope correlation method, and applied it to construct a tremor catalog in western Japan. Using the cross-correlation functions as objective functions and weighting components of data by the inverse of error variances, the envelope cross-correlation method is redefined as a maximum likelihood method. This method is also capable of multiple source detection, because when several events occur almost simultaneously, they appear as local maxima of likelihood.The average of weighted cross-correlation functions, defined as ACC, is a nonlinear function whose variable is a position of deep tectonic tremor. The optimization method has two steps. First, we fix the source depth to 30 km and use a grid search with 0.2 degree intervals to find the maxima of ACC, which are candidate event locations. Then, using each of the candidate locations as initial values, we apply a gradient method to determine horizontal and vertical components of a hypocenter. Sometimes, several source locations are determined in a time window of 5 minutes. We estimate the resolution, which is defined as a distance of sources to be detected separately by the location method, is about 100 km. The validity of this estimation is confirmed by a numerical test using synthetic waveforms. Applying to continuous seismograms in western Japan for over 10 years, the new method detected 27% more tremors than a previous method, owing to the multiple detection and improvement of accuracy by appropriate weighting scheme.
Application of artificial neural network to fMRI regression analysis.
Misaki, Masaya; Miyauchi, Satoru
2006-01-15
We used an artificial neural network (ANN) to detect correlations between event sequences and fMRI (functional magnetic resonance imaging) signals. The layered feed-forward neural network, given a series of events as inputs and the fMRI signal as a supervised signal, performed a non-linear regression analysis. This type of ANN is capable of approximating any continuous function, and thus this analysis method can detect any fMRI signals that correlated with corresponding events. Because of the flexible nature of ANNs, fitting to autocorrelation noise is a problem in fMRI analyses. We avoided this problem by using cross-validation and an early stopping procedure. The results showed that the ANN could detect various responses with different time courses. The simulation analysis also indicated an additional advantage of ANN over non-parametric methods in detecting parametrically modulated responses, i.e., it can detect various types of parametric modulations without a priori assumptions. The ANN regression analysis is therefore beneficial for exploratory fMRI analyses in detecting continuous changes in responses modulated by changes in input values.
Leak Detection and Location of Water Pipes Using Vibration Sensors and Modified ML Prefilter.
Choi, Jihoon; Shin, Joonho; Song, Choonggeun; Han, Suyong; Park, Doo Il
2017-09-13
This paper proposes a new leak detection and location method based on vibration sensors and generalised cross-correlation techniques. Considering the estimation errors of the power spectral densities (PSDs) and the cross-spectral density (CSD), the proposed method employs a modified maximum-likelihood (ML) prefilter with a regularisation factor. We derive a theoretical variance of the time difference estimation error through summation in the discrete-frequency domain, and find the optimal regularisation factor that minimises the theoretical variance in practical water pipe channels. The proposed method is compared with conventional correlation-based techniques via numerical simulations using a water pipe channel model, and it is shown through field measurement that the proposed modified ML prefilter outperforms conventional prefilters for the generalised cross-correlation. In addition, we provide a formula to calculate the leak location using the time difference estimate when different types of pipes are connected.
Leak Detection and Location of Water Pipes Using Vibration Sensors and Modified ML Prefilter
Shin, Joonho; Song, Choonggeun; Han, Suyong; Park, Doo Il
2017-01-01
This paper proposes a new leak detection and location method based on vibration sensors and generalised cross-correlation techniques. Considering the estimation errors of the power spectral densities (PSDs) and the cross-spectral density (CSD), the proposed method employs a modified maximum-likelihood (ML) prefilter with a regularisation factor. We derive a theoretical variance of the time difference estimation error through summation in the discrete-frequency domain, and find the optimal regularisation factor that minimises the theoretical variance in practical water pipe channels. The proposed method is compared with conventional correlation-based techniques via numerical simulations using a water pipe channel model, and it is shown through field measurement that the proposed modified ML prefilter outperforms conventional prefilters for the generalised cross-correlation. In addition, we provide a formula to calculate the leak location using the time difference estimate when different types of pipes are connected. PMID:28902154
Non-intrusive torque measurement for rotating shafts using optical sensing of zebra-tapes
NASA Astrophysics Data System (ADS)
Zappalá, D.; Bezziccheri, M.; Crabtree, C. J.; Paone, N.
2018-06-01
Non-intrusive, reliable and precise torque measurement is critical to dynamic performance monitoring, control and condition monitoring of rotating mechanical systems. This paper presents a novel, contactless torque measurement system consisting of two shaft-mounted zebra tapes and two optical sensors mounted on stationary rigid supports. Unlike conventional torque measurement methods, the proposed system does not require costly embedded sensors or shaft-mounted electronics. Moreover, its non-intrusive nature, adaptable design, simple installation and low cost make it suitable for a large variety of advanced engineering applications. Torque measurement is achieved by estimating the shaft twist angle through analysis of zebra tape pulse train time shifts. This paper presents and compares two signal processing methods for torque measurement: rising edge detection and cross-correlation. The performance of the proposed system has been proven experimentally under both static and variable conditions and both processing approaches show good agreement with reference measurements from an in-line, invasive torque transducer. Measurement uncertainty has been estimated according to the ISO GUM (Guide to the expression of uncertainty in measurement). Type A analysis of experimental data has provided an expanded uncertainty relative to the system full-scale torque of ±0.30% and ±0.86% for the rising edge and cross-correlation approaches, respectively. Statistical simulations performed by the Monte Carlo method have provided, in the worst case, an expanded uncertainty of ±1.19%.
Relative velocity change measurement based on seismic noise analysis in exploration geophysics
NASA Astrophysics Data System (ADS)
Corciulo, M.; Roux, P.; Campillo, M.; Dubuq, D.
2011-12-01
Passive monitoring techniques based on noise cross-correlation analysis are still debated in exploration geophysics even if recent studies showed impressive performance in seismology at larger scale. Time evolution of complex geological structure using noise data includes localization of noise sources and measurement of relative velocity variations. Monitoring relative velocity variations only requires the measurement of phase shifts of seismic noise cross-correlation functions computed for successive time recordings. The existing algorithms, such as the Stretching and the Doublet, classically need great efforts in terms of computation time, making them not practical when continuous dataset on dense arrays are acquired. We present here an innovative technique for passive monitoring based on the measure of the instantaneous phase of noise-correlated signals. The Instantaneous Phase Variation (IPV) technique aims at cumulating the advantages of the Stretching and Doublet methods while proposing a faster measurement of the relative velocity change. The IPV takes advantage of the Hilbert transform to compute in the time domain the phase difference between two noise correlation functions. The relative velocity variation is measured through the slope of the linear regression of the phase difference curve as a function of correlation time. The large amount of noise correlation functions, classically available at exploration scale on dense arrays, allows for a statistical analysis that further improves the precision of the estimation of the velocity change. In this work, numerical tests first aim at comparing the IPV performance to the Stretching and Doublet techniques in terms of accuracy, robustness and computation time. Then experimental results are presented using a seismic noise dataset with five days of continuous recording on 397 geophones spread on a ~1 km-squared area.
Background Noise Reduction Using Adaptive Noise Cancellation Determined by the Cross-Correlation
NASA Technical Reports Server (NTRS)
Spalt, Taylor B.; Brooks, Thomas F.; Fuller, Christopher R.
2012-01-01
Background noise due to flow in wind tunnels contaminates desired data by decreasing the Signal-to-Noise Ratio. The use of Adaptive Noise Cancellation to remove background noise at measurement microphones is compromised when the reference sensor measures both background and desired noise. The technique proposed modifies the classical processing configuration based on the cross-correlation between the reference and primary microphone. Background noise attenuation is achieved using a cross-correlation sample width that encompasses only the background noise and a matched delay for the adaptive processing. A present limitation of the method is that a minimum time delay between the background noise and desired signal must exist in order for the correlated parts of the desired signal to be separated from the background noise in the crosscorrelation. A simulation yields primary signal recovery which can be predicted from the coherence of the background noise between the channels. Results are compared with two existing methods.
Klebanov, Lev; Chen, Linlin; Yakovlev, Andrei
2007-11-07
This work was undertaken in response to a recently published paper by Okoniewski and Miller (BMC Bioinformatics 2006, 7: Article 276). The authors of that paper came to the conclusion that the process of multiple targeting in short oligonucleotide microarrays induces spurious correlations and this effect may deteriorate the inference on correlation coefficients. The design of their study and supporting simulations cast serious doubt upon the validity of this conclusion. The work by Okoniewski and Miller drove us to revisit the issue by means of experimentation with biological data and probabilistic modeling of cross-hybridization effects. We have identified two serious flaws in the study by Okoniewski and Miller: (1) The data used in their paper are not amenable to correlation analysis; (2) The proposed simulation model is inadequate for studying the effects of cross-hybridization. Using two other data sets, we have shown that removing multiply targeted probe sets does not lead to a shift in the histogram of sample correlation coefficients towards smaller values. A more realistic approach to mathematical modeling of cross-hybridization demonstrates that this process is by far more complex than the simplistic model considered by the authors. A diversity of correlation effects (such as the induction of positive or negative correlations) caused by cross-hybridization can be expected in theory but there are natural limitations on the ability to provide quantitative insights into such effects due to the fact that they are not directly observable. The proposed stochastic model is instrumental in studying general regularities in hybridization interaction between probe sets in microarray data. As the problem stands now, there is no compelling reason to believe that multiple targeting causes a large-scale effect on the correlation structure of Affymetrix gene expression data. Our analysis suggests that the observed long-range correlations in microarray data are of a biological nature rather than a technological flaw.
Evaluating and interpreting cross-taxon congruence: Potential pitfalls and solutions
NASA Astrophysics Data System (ADS)
Gioria, Margherita; Bacaro, Giovanni; Feehan, John
2011-05-01
Characterizing the relationship between different taxonomic groups is critical to identify potential surrogates for biodiversity. Previous studies have shown that cross-taxa relationships are generally weak and/or inconsistent. The difficulties in finding predictive patterns have often been attributed to the spatial and temporal scales of these studies and on the differences in the measure used to evaluate such relationships (species richness versus composition). However, the choice of the analytical approach used to evaluate cross-taxon congruence inevitably represents a major source of variation. Here, we described the use of a range of methods that can be used to comprehensively assess cross-taxa relationships. To do so, we used data for two taxonomic groups, wetland plants and water beetles, collected from 54 farmland ponds in Ireland. Specifically, we used the Pearson correlation and rarefaction curves to analyse patterns in species richness, while Mantel tests, Procrustes analysis, and co-correspondence analysis were used to evaluate congruence in species composition. We compared the results of these analyses and we described some of the potential pitfalls associated with the use of each of these statistical approaches. Cross-taxon congruence was moderate to strong, depending on the choice of the analytical approach, on the nature of the response variable, and on local and environmental conditions. Our findings indicate that multiple approaches and measures of community structure are required for a comprehensive assessment of cross-taxa relationships. In particular, we showed that selection of surrogate taxa in conservation planning should not be based on a single statistic expressing the degree of correlation in species richness or composition. Potential solutions to the analytical issues associated with the assessment of cross-taxon congruence are provided and the implications of our findings in the selection of surrogates for biodiversity are discussed.
Sánchez de Medina, Verónica; El Riachy, Milad; Priego-Capote, Feliciano; Luque de Castro, María Dolores
2015-11-01
Recent technological advances to improve the quality of virgin olive oil (VOO) have been focused on olive breeding programs by selecting outstanding cultivars and target progenies. Fatty acid (FA) composition, with special emphasis on oleic acid (C18:1) and palmitic acid (C16:0), is one of the most critical quality factors to be evaluated in VOO. For this reason, the profile of FAs is frequently used as a decision tool in olive breeding programs. A method based on gas chromatography with flame ionization detection (GC-FID) was used to study the influence of genotype on the concentration of ten of the most important FAs in VOOs from target crosses Arbequina × Arbosana, Picual × Koroneiki and Sikitita × Arbosana and their corresponding genitors Arbequina, Arbosana, Koroneiki, Picual and Sikitita. For this purpose, a targeted approach was selected for determination of esterified FAs (EFAs) and non-esterified FAs (NEFAs) in a dual analysis by the same chromatographic method. A Pearson analysis revealed correlations between pairs of FAs, which allowed detecting metabolic connections through desaturation and elongation enzymes. An ANOVA test (with P < 0.01) led to identification of C16:0 EFA, C16:1 EFA and C18:1 EFA and also C16:1 NEFA and C18:0 NEFA as the FAs more influenced by cross breeding. Statistical analysis was carried out by unsupervised analysis using principal component analysis (PCA) and cluster analysis (CA) to look for variability sources. Crosses with a common genitor (Arbequina × Arbosana and Sikitita × Arbosana) were partially overlapped in the PCAs using the profile of FAs. The CA results revealed clear differences between Sikitita × Arbosana and Picual × Koroneiki crosses in the composition of the most significant FAs, while Arbequina × Arbosana was not properly discriminated from the other crosses. © 2014 Society of Chemical Industry.
Zhou, Yong; Liang, Jinyang; Maslov, Konstantin I.; Wang, Lihong V.
2013-01-01
We propose a cross-correlation-based method to measure blood flow velocity by using photoacoustic microscopy. Unlike in previous auto-correlation-based methods, the measured flow velocity here is independent of particle size. Thus, an absolute flow velocity can be obtained without calibration. We first measured the flow velocity ex vivo, using defibrinated bovine blood. Then, flow velocities in vessels with different structures in a mouse ear were quantified in vivo. We further measured the flow variation in the same vessel and at a vessel bifurcation. All the experimental results indicate that our method can be used to accurately quantify blood velocity in vivo. PMID:24081077
Dynamical Analysis of Stock Market Instability by Cross-correlation Matrix
NASA Astrophysics Data System (ADS)
Takaishi, Tetsuya
2016-08-01
We study stock market instability by using cross-correlations constructed from the return time series of 366 stocks traded on the Tokyo Stock Exchange from January 5, 1998 to December 30, 2013. To investigate the dynamical evolution of the cross-correlations, crosscorrelation matrices are calculated with a rolling window of 400 days. To quantify the volatile market stages where the potential risk is high, we apply the principal components analysis and measure the cumulative risk fraction (CRF), which is the system variance associated with the first few principal components. From the CRF, we detected three volatile market stages corresponding to the bankruptcy of Lehman Brothers, the 2011 Tohoku Region Pacific Coast Earthquake, and the FRB QE3 reduction observation in the study period. We further apply the random matrix theory for the risk analysis and find that the first eigenvector is more equally de-localized when the market is volatile.
Cross-correlation of weak lensing and gamma rays: implications for the nature of dark matter
NASA Astrophysics Data System (ADS)
Tröster, Tilman; Camera, Stefano; Fornasa, Mattia; Regis, Marco; van Waerbeke, Ludovic; Harnois-Déraps, Joachim; Ando, Shin'ichiro; Bilicki, Maciej; Erben, Thomas; Fornengo, Nicolao; Heymans, Catherine; Hildebrandt, Hendrik; Hoekstra, Henk; Kuijken, Konrad; Viola, Massimo
2017-05-01
We measure the cross-correlation between Fermi gamma-ray photons and over 1000 deg2 of weak lensing data from the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS), the Red Cluster Sequence Lensing Survey (RCSLenS), and the Kilo Degree Survey (KiDS). We present the first measurement of tomographic weak lensing cross-correlations and the first application of spectral binning to cross-correlations between gamma rays and weak lensing. The measurements are performed using an angular power spectrum estimator while the covariance is estimated using an analytical prescription. We verify the accuracy of our covariance estimate by comparing it to two internal covariance estimators. Based on the non-detection of a cross-correlation signal, we derive constraints on weakly interacting massive particle (WIMP) dark matter. We compute exclusion limits on the dark matter annihilation cross-section <σannv>, decay rate Γdec and particle mass mDM. We find that in the absence of a cross-correlation signal, tomography does not significantly improve the constraining power of the analysis. Assuming a strong contribution to the gamma-ray flux due to small-scale clustering of dark matter and accounting for known astrophysical sources of gamma rays, we exclude the thermal relic cross-section for particle masses of mDM ≲ 20 GeV.
Introduction of Total Variation Regularization into Filtered Backprojection Algorithm
NASA Astrophysics Data System (ADS)
Raczyński, L.; Wiślicki, W.; Klimaszewski, K.; Krzemień, W.; Kowalski, P.; Shopa, R. Y.; Białas, P.; Curceanu, C.; Czerwiński, E.; Dulski, K.; Gajos, A.; Głowacz, B.; Gorgol, M.; Hiesmayr, B.; Jasińska, B.; Kisielewska-Kamińska, D.; Korcyl, G.; Kozik, T.; Krawczyk, N.; Kubicz, E.; Mohammed, M.; Pawlik-Niedźwiecka, M.; Niedźwiecki, S.; Pałka, M.; Rudy, Z.; Sharma, N. G.; Sharma, S.; Silarski, M.; Skurzok, M.; Wieczorek, A.; Zgardzińska, B.; Zieliński, M.; Moskal, P.
In this paper we extend the state-of-the-art filtered backprojection (FBP) method with application of the concept of Total Variation regularization. We compare the performance of the new algorithm with the most common form of regularizing in the FBP image reconstruction via apodizing functions. The methods are validated in terms of cross-correlation coefficient between reconstructed and real image of radioactive tracer distribution using standard Derenzo-type phantom. We demonstrate that the proposed approach results in higher cross-correlation values with respect to the standard FBP method.
NASA Astrophysics Data System (ADS)
Zhou, Wei-Xing; Sornette, Didier
2007-07-01
We have recently introduced the “thermal optimal path” (TOP) method to investigate the real-time lead-lag structure between two time series. The TOP method consists in searching for a robust noise-averaged optimal path of the distance matrix along which the two time series have the greatest similarity. Here, we generalize the TOP method by introducing a more general definition of distance which takes into account possible regime shifts between positive and negative correlations. This generalization to track possible changes of correlation signs is able to identify possible transitions from one convention (or consensus) to another. Numerical simulations on synthetic time series verify that the new TOP method performs as expected even in the presence of substantial noise. We then apply it to investigate changes of convention in the dependence structure between the historical volatilities of the USA inflation rate and economic growth rate. Several measures show that the new TOP method significantly outperforms standard cross-correlation methods.
Antenna systems for base station diversity in urban small and micro cells
NASA Astrophysics Data System (ADS)
Eggers, Patrick C. F.; Toftgard, Jorn; Oprea, Alex M.
1993-09-01
This paper describes cross-correlation properties for compact urban base station antenna configurations, nearly all resulting in very low envelope cross-correlation coefficients of about 0.1 to 0.3. A focus is set on polarization diversity systems for their potential in improving link quality when hand-held terminals are involved. An expression is given for the correlation function of compound space and polarization diversity systems. Dispersion and envelope dynamic statistics are presented for the measured environments. For microcell applications, it is found that systems such as GSM having a bandwidth of 200 MHz or less can use narrowband cross-correlation analysis directly.
Phase Time and Envelope Time in Time-Distance Analysis and Acoustic Imaging
NASA Technical Reports Server (NTRS)
Chou, Dean-Yi; Duvall, Thomas L.; Sun, Ming-Tsung; Chang, Hsiang-Kuang; Jimenez, Antonio; Rabello-Soares, Maria Cristina; Ai, Guoxiang; Wang, Gwo-Ping; Goode Philip; Marquette, William;
1999-01-01
Time-distance analysis and acoustic imaging are two related techniques to probe the local properties of solar interior. In this study, we discuss the relation of phase time and envelope time between the two techniques. The location of the envelope peak of the cross correlation function in time-distance analysis is identified as the travel time of the wave packet formed by modes with the same w/l. The phase time of the cross correlation function provides information of the phase change accumulated along the wave path, including the phase change at the boundaries of the mode cavity. The acoustic signals constructed with the technique of acoustic imaging contain both phase and intensity information. The phase of constructed signals can be studied by computing the cross correlation function between time series constructed with ingoing and outgoing waves. In this study, we use the data taken with the Taiwan Oscillation Network (TON) instrument and the Michelson Doppler Imager (MDI) instrument. The analysis is carried out for the quiet Sun. We use the relation of envelope time versus distance measured in time-distance analyses to construct the acoustic signals in acoustic imaging analyses. The phase time of the cross correlation function of constructed ingoing and outgoing time series is twice the difference between the phase time and envelope time in time-distance analyses as predicted. The envelope peak of the cross correlation function between constructed ingoing and outgoing time series is located at zero time as predicted for results of one-bounce at 3 mHz for all four data sets and two-bounce at 3 mHz for two TON data sets. But it is different from zero for other cases. The cause of the deviation of the envelope peak from zero is not known.
Ye, Feng; Liu, Yaohua; Whitfield, Ross; Osborn, Ray; Rosenkranz, Stephan
2018-04-01
The CORELLI instrument at Oak Ridge National Laboratory is a statistical chopper spectrometer designed and optimized to probe complex disorder in crystalline materials through diffuse scattering experiments. On CORELLI, the high efficiency of white-beam Laue diffraction combined with elastic discrimination have enabled an unprecedented data collection rate to obtain both the total and the elastic-only scattering over a large volume of reciprocal space from a single measurement. To achieve this, CORELLI is equipped with a statistical chopper to modulate the incoming neutron beam quasi-randomly, and then the cross-correlation method is applied to reconstruct the elastic component from the scattering data. Details of the implementation of the cross-correlation method on CORELLI are given and its performance is discussed.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ye, Feng; Liu, Yaohua; Whitfield, Ross
The CORELLI instrument at Oak Ridge National Laboratory is a statistical chopper spectrometer designed and optimized to probe complex disorder in crystalline materials through diffuse scattering experiments. On CORELLI, the high efficiency of white-beam Laue diffraction combined with elastic discrimination have enabled an unprecedented data collection rate to obtain both the total and the elastic-only scattering over a large volume of reciprocal space from a single measurement. To achieve this, CORELLI is equipped with a statistical chopper to modulate the incoming neutron beam quasi-randomly, and then the cross-correlation method is applied to reconstruct the elastic component from the scattering data.more » Lastly, details of the implementation of the cross-correlation method on CORELLI are given and its performance is discussed.« less
Ye, Feng; Liu, Yaohua; Whitfield, Ross; ...
2018-03-26
The CORELLI instrument at Oak Ridge National Laboratory is a statistical chopper spectrometer designed and optimized to probe complex disorder in crystalline materials through diffuse scattering experiments. On CORELLI, the high efficiency of white-beam Laue diffraction combined with elastic discrimination have enabled an unprecedented data collection rate to obtain both the total and the elastic-only scattering over a large volume of reciprocal space from a single measurement. To achieve this, CORELLI is equipped with a statistical chopper to modulate the incoming neutron beam quasi-randomly, and then the cross-correlation method is applied to reconstruct the elastic component from the scattering data.more » Lastly, details of the implementation of the cross-correlation method on CORELLI are given and its performance is discussed.« less
NASA Astrophysics Data System (ADS)
Yun, Lingtong; Zhao, Hongzhong; Du, Mengyuan
2018-04-01
Quadrature and multi-channel amplitude-phase error have to be compensated in the I/Q quadrature sampling and signal through multi-channel. A new method that it doesn't need filter and standard signal is presented in this paper. And it can combined estimate quadrature and multi-channel amplitude-phase error. The method uses cross-correlation and amplitude ratio between the signal to estimate the two amplitude-phase errors simply and effectively. And the advantages of this method are verified by computer simulation. Finally, the superiority of the method is also verified by measure data of outfield experiments.
Yang, Yang; Xiao, Li; Qu, Wenzhong; Lu, Ye
2017-11-01
Recent theoretical and experimental studies have demonstrated that a local Green's function can be retrieved from the cross-correlation of ambient noise field. This technique can be used to detect fatigue cracking in metallic structures, owing to the fact that the presence of crack can lead to a change in Green's function. This paper presents a method of structural fatigue cracking characterization method by measuring Green's function reconstruction from noise excitation and verifies the feasibility of crack detection in poor noise source distribution. Fatigue cracks usually generate nonlinear effects, in which different wave amplitudes and frequency compositions can cause different nonlinear responses. This study also undertakes analysis of the capacity of the proposed approach to identify fatigue cracking under different noise amplitudes and frequency ranges. Experimental investigations of an aluminum plate are conducted to assess the cross-correlations of received noise between sensor pairs and finally to detect the introduced fatigue crack. A damage index is proposed according to the variation between cross-correlations obtained from the pristine crack closed state and the crack opening-closure state when sufficient noise amplitude is used to generate nonlinearity. A probability distribution map of damage is calculated based on damage indices. The fatigue crack introduced in the aluminum plate is successfully identified and oriented, verifying that a fatigue crack can be detected by reconstructing Green's functions from an imperfect diffuse field in which ambient noise sources exist locally. Copyright © 2017 Elsevier B.V. All rights reserved.
Noar, Seth M; Mehrotra, Purnima
2011-03-01
Traditional theory testing commonly applies cross-sectional (and occasionally longitudinal) survey research to test health behavior theory. Since such correlational research cannot demonstrate causality, a number of researchers have called for the increased use of experimental methods for theory testing. We introduce the multi-methodological theory-testing (MMTT) framework for testing health behavior theory. The MMTT framework introduces a set of principles that broaden the perspective of how we view evidence for health behavior theory. It suggests that while correlational survey research designs represent one method of testing theory, the weaknesses of this approach demand that complementary approaches be applied. Such approaches include randomized lab and field experiments, mediation analysis of theory-based interventions, and meta-analysis. These alternative approaches to theory testing can demonstrate causality in a much more robust way than is possible with correlational survey research methods. Such approaches should thus be increasingly applied in order to more completely and rigorously test health behavior theory. Greater application of research derived from the MMTT may lead researchers to refine and modify theory and ultimately make theory more valuable to practitioners. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
Analyse dynamique des lignes de grande portee sous charges de vent
NASA Astrophysics Data System (ADS)
Ashby, Mathieu
There are two types of electric crossing : i) subterranean / submarine line ii) overhead-line crossing. We always consider the last one as a more economic option. The inconvenience of an overhead-line crossing would be the environmental constraints among which the existing obstacles, the clearance for the navigation and the aesthetics demanded by the public. The overhead-line crossings usually have conductors of long ranges which are outside of the field of application for the current transmission line codes. These are limited to reaches of a length included between 200 m and 800 m, as well as a height of support lower than 60 m. However, for reaches over 800 m and over a height over 60 m, the criteria of conception in the transmission line codes for the calculation of wind loads are not applicable. In this study we concentrate on loads on the supports owed to the limit wind applied to bare conductors and insulators chains The objective of the present study is to examine the effect of the temporal and spatial correlation of the wind load along the conductors on a finite element model. A special attention was brought to the evaluation of the importance of the dynamic load transmitted on by the conductors and the insulators chains for the case of a turbulent wind load. The numerical study on finite element model for the example of a overhead-line crossing was done with the software ADINA. The wind load for the finite element model for the example of a overhead-line crossing was generated by the software WindGen which uses the method of Simiu-Scanlan and the method of spectral representation developed by Shinozuka-Deodatis. Wind loads generated where integrated into the finite element model ADINA for a dynamic analysis of the overhead-line crossing. For the first part, the current methods are used to calculate the efforts in supports due to the wind loads with an engineering approach and a comparaison approach. The current methods are then compared with the efforts obtained from an advanced method, transient dynamic and spectral stochastic, and specifically for the case of a simple overhead-line and an overhead-line crossings. For the second part, the effect of the longitudinal correlation of the wind load on two parallel conductors was examined. Finally, dynamic experiments on an insulators chain were made to determine the variation of the damping and the rigidity of the system for different type of insulators, different speed of application of the load and the inclination of the insulator. Key words : transient dynamics, spectral stochastic, turbulent wind, conductor, aerodynamic damping, structural damping, spatial correlation, wind spectra
DOE Office of Scientific and Technical Information (OSTI.GOV)
De Putter, Roland; Doré, Olivier; Das, Sudeep
2014-01-10
Cross correlations between the galaxy number density in a lensing source sample and that in an overlapping spectroscopic sample can in principle be used to calibrate the lensing source redshift distribution. In this paper, we study in detail to what extent this cross-correlation method can mitigate the loss of cosmological information in upcoming weak lensing surveys (combined with a cosmic microwave background prior) due to lack of knowledge of the source distribution. We consider a scenario where photometric redshifts are available and find that, unless the photometric redshift distribution p(z {sub ph}|z) is calibrated very accurately a priori (bias andmore » scatter known to ∼0.002 for, e.g., EUCLID), the additional constraint on p(z {sub ph}|z) from the cross-correlation technique to a large extent restores the cosmological information originally lost due to the uncertainty in dn/dz(z). Considering only the gain in photo-z accuracy and not the additional cosmological information, enhancements of the dark energy figure of merit of up to a factor of four (40) can be achieved for a SuMIRe-like (EUCLID-like) combination of lensing and redshift surveys, where SuMIRe stands for Subaru Measurement of Images and Redshifts). However, the success of the method is strongly sensitive to our knowledge of the galaxy bias evolution in the source sample and we find that a percent level bias prior is needed to optimize the gains from the cross-correlation method (i.e., to approach the cosmology constraints attainable if the bias was known exactly).« less
Source localization of non-stationary acoustic data using time-frequency analysis
NASA Astrophysics Data System (ADS)
Stoughton, Jack; Edmonson, William
2005-04-01
An improvement in temporal locality of the generalized cross-correlation (GCC) for angle of arrival (AOA) estimation can be achieved by employing 2-D cross-correlation of infrasonic sensor data transformed to its time-frequency (TF) representation. Intermediate to the AOA evaluation is the time delay between pairs of sensors. The signal class of interest includes far field sources which are partially coherent across the array, nonstationary, and wideband. In addition, signals can occur as multiple short bursts, for which TF representations may be more appropriate for time delay estimation. The GCC tends to smooth out such temporal energy bursts. Simulation and experimental results will demonstrate the improvement in using a TF-based GCC, using the Cohen class, over the classic GCC method. Comparative demonstration of the methods will be performed on data captured on an infrasonic sensor array located at NASA Langley Research Center (LaRC). The infrasonic data sources include Delta IV and Space Shuttle launches from Kennedy Space Center which belong to the stated signal class. Of interest is to apply this method to the AOA estimation of atmospheric turbulence. [Work supported by NASA LaRC Creativity and Innovation project: Infrasonic Detection of Clear Air Turbulence and Severe Storms.
K-Fold Crossvalidation in Canonical Analysis.
ERIC Educational Resources Information Center
Liang, Kun-Hsia; And Others
1995-01-01
A computer-assisted, K-fold cross-validation technique is discussed in the framework of canonical correlation analysis of randomly generated data sets. Analysis results suggest that this technique can effectively reduce the contamination of canonical variates and canonical correlations by sample-specific variance components. (Author/SLD)
[Gaussian process regression and its application in near-infrared spectroscopy analysis].
Feng, Ai-Ming; Fang, Li-Min; Lin, Min
2011-06-01
Gaussian process (GP) is applied in the present paper as a chemometric method to explore the complicated relationship between the near infrared (NIR) spectra and ingredients. After the outliers were detected by Monte Carlo cross validation (MCCV) method and removed from dataset, different preprocessing methods, such as multiplicative scatter correction (MSC), smoothing and derivate, were tried for the best performance of the models. Furthermore, uninformative variable elimination (UVE) was introduced as a variable selection technique and the characteristic wavelengths obtained were further employed as input for modeling. A public dataset with 80 NIR spectra of corn was introduced as an example for evaluating the new algorithm. The optimal models for oil, starch and protein were obtained by the GP regression method. The performance of the final models were evaluated according to the root mean square error of calibration (RMSEC), root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP) and correlation coefficient (r). The models give good calibration ability with r values above 0.99 and the prediction ability is also satisfactory with r values higher than 0.96. The overall results demonstrate that GP algorithm is an effective chemometric method and is promising for the NIR analysis.
NASA Astrophysics Data System (ADS)
Deng, Wei; Wang, Jun
2015-06-01
We investigate and quantify the multifractal detrended cross-correlation of return interval series for Chinese stock markets and a proposed price model, the price model is established by oriented percolation. The return interval describes the waiting time between two successive price volatilities which are above some threshold, the present work is an attempt to quantify the level of multifractal detrended cross-correlation for the return intervals. Further, the concept of MF-DCCA coefficient of return intervals is introduced, and the corresponding empirical research is performed. The empirical results show that the return intervals of SSE and SZSE are weakly positive multifractal power-law cross-correlated, and exhibit the fluctuation patterns of MF-DCCA coefficients. The similar behaviors of return intervals for the price model is also demonstrated.
Cross-correlations between the US monetary policy, US dollar index and crude oil market
NASA Astrophysics Data System (ADS)
Sun, Xinxin; Lu, Xinsheng; Yue, Gongzheng; Li, Jianfeng
2017-02-01
This paper investigates the cross-correlations between the US monetary policy, US dollar index and WTI crude oil market, using a dataset covering a period from February 4, 1994 to February 29, 2016. Our study contributes to the literature by examining the effect of the US monetary policy on US dollar index and WTI crude oil through the MF-DCCA approach. The empirical results show that the cross-correlations between the three sets of time series exhibit strong multifractal features with the strength of multifractality increasing over the sample period. Employing a rolling window analysis, our empirical results show that the US monetary policy operations have clear influences on the cross-correlated behavior of the three time series covered by this study.
Fractionated analysis of paired-electrode nerve recordings.
Fiore, Lorenzo; Lorenzetti, Walter; Ratti, Giovannino; Geppetti, Laura
2003-12-30
Multi-unit activity recorded from two electrodes positioned at a distance on a nerve may be analysed by cross-correlation, but units similar in direction and velocity of propagation cannot be distinguished and separately evaluated by this method. To overcome this limit, we added two features, represented by the impulse amplitudes of the paired recordings, to the dimension given by the impulse delay. The analysis was fractionated according to the new dimensions. In experimental recordings from the locomotor appendage of the lobster Homarus americanus, the fractionated analysis proved capable of identifying the contributions of single active units, even if these were superimposed and indiscernible in the global cross-correlation histogram. Up to 5 motor and 10 sensory units could be identified. The shape of the paired impulses was evaluated by an averaging procedure. Analogous evaluations on simulated recordings made it possible to estimate the influences exerted on performance by variations in noise level and in the number and firing rate of active units. The global signal could be resolved into single units even under the worst conditions. Accuracy in evaluating the amount of unit activity varied, exceeding 90% in about half of the cases tested; a similar performance was attained by evaluation of the impulse shapes.
The Persian developmental sentence scoring as a clinical measure of morphosyntax in children.
Jalilevand, Nahid; Kamali, Mohammad; Modarresi, Yahya; Kazemi, Yalda
2016-01-01
Background: Developmental Sentence Scoring (DSS) was developed as a numerical measurement and a clinical method based on the morphosyntactic acquisition in the English language. The aim of this study was to develop a new numerical tool similar to DSS to assess the morphosyntactic abilities in Persian-speaking children. Methods: In this cross-sectional and comparative study, the language samples of 115 typically developing Persian-speaking children aged 30 - 65 months were audio recorded during the free play and picture description sessions. The Persian Developmental Sentence Score (PDSS) and the Mean Length of Utterance (MLU) were calculated. Pearson correlation and one - way Analysis of variance (ANOVA) were used for data analysis. Results: The correlation between PDSS and MLU in morphemes (convergent validity) was significant with a correlation coefficient of 0.97 (p< 0.001). The value Cronbach's Alpha (α= 0.79) in the grammatical categories and the split-half coefficient (0.86) indicated acceptable internal consistency reliability. Conclusion: The PDSS could be used as a reliable numerical measurement to estimate the syntactic development in Persian-speaking children.
The Persian developmental sentence scoring as a clinical measure of morphosyntax in children
Jalilevand, Nahid; Kamali, Mohammad; Modarresi, Yahya; Kazemi, Yalda
2016-01-01
Background: Developmental Sentence Scoring (DSS) was developed as a numerical measurement and a clinical method based on the morphosyntactic acquisition in the English language. The aim of this study was to develop a new numerical tool similar to DSS to assess the morphosyntactic abilities in Persian-speaking children. Methods: In this cross-sectional and comparative study, the language samples of 115 typically developing Persian-speaking children aged 30 - 65 months were audio recorded during the free play and picture description sessions. The Persian Developmental Sentence Score (PDSS) and the Mean Length of Utterance (MLU) were calculated. Pearson correlation and one – way Analysis of variance (ANOVA) were used for data analysis. Results: The correlation between PDSS and MLU in morphemes (convergent validity) was significant with a correlation coefficient of 0.97 (p< 0.001). The value Cronbach's Alpha (α= 0.79) in the grammatical categories and the split-half coefficient (0.86) indicated acceptable internal consistency reliability. Conclusion: The PDSS could be used as a reliable numerical measurement to estimate the syntactic development in Persian-speaking children. PMID:28210600
Analysis of spectra using correlation functions
NASA Technical Reports Server (NTRS)
Beer, Reinhard; Norton, Robert H.
1988-01-01
A novel method is presented for the quantitative analysis of spectra based on the properties of the cross correlation between a real spectrum and either a numerical synthesis or laboratory simulation. A new goodness-of-fit criterion called the heteromorphic coefficient H is proposed that has the property of being zero when a fit is achieved and varying smoothly through zero as the iteration proceeds, providing a powerful tool for automatic or near-automatic analysis. It is also shown that H can be rendered substantially noise-immune, permitting the analysis of very weak spectra well below the apparent noise level and, as a byproduct, providing Doppler shift and radial velocity information with excellent precision. The technique is in regular use in the Atmospheric Trace Molecule Spectroscopy (ATMOS) project and operates in an interactive, realtime computing environment with turn-around times of a few seconds or less.
The Gaussian Graphical Model in Cross-Sectional and Time-Series Data.
Epskamp, Sacha; Waldorp, Lourens J; Mõttus, René; Borsboom, Denny
2018-04-16
We discuss the Gaussian graphical model (GGM; an undirected network of partial correlation coefficients) and detail its utility as an exploratory data analysis tool. The GGM shows which variables predict one-another, allows for sparse modeling of covariance structures, and may highlight potential causal relationships between observed variables. We describe the utility in three kinds of psychological data sets: data sets in which consecutive cases are assumed independent (e.g., cross-sectional data), temporally ordered data sets (e.g., n = 1 time series), and a mixture of the 2 (e.g., n > 1 time series). In time-series analysis, the GGM can be used to model the residual structure of a vector-autoregression analysis (VAR), also termed graphical VAR. Two network models can then be obtained: a temporal network and a contemporaneous network. When analyzing data from multiple subjects, a GGM can also be formed on the covariance structure of stationary means-the between-subjects network. We discuss the interpretation of these models and propose estimation methods to obtain these networks, which we implement in the R packages graphicalVAR and mlVAR. The methods are showcased in two empirical examples, and simulation studies on these methods are included in the supplementary materials.
Spectral density mapping at multiple magnetic fields suitable for 13C NMR relaxation studies
NASA Astrophysics Data System (ADS)
Kadeřávek, Pavel; Zapletal, Vojtěch; Fiala, Radovan; Srb, Pavel; Padrta, Petr; Přecechtělová, Jana Pavlíková; Šoltésová, Mária; Kowalewski, Jozef; Widmalm, Göran; Chmelík, Josef; Sklenář, Vladimír; Žídek, Lukáš
2016-05-01
Standard spectral density mapping protocols, well suited for the analysis of 15N relaxation rates, introduce significant systematic errors when applied to 13C relaxation data, especially if the dynamics is dominated by motions with short correlation times (small molecules, dynamic residues of macromolecules). A possibility to improve the accuracy by employing cross-correlated relaxation rates and on measurements taken at several magnetic fields has been examined. A suite of protocols for analyzing such data has been developed and their performance tested. Applicability of the proposed protocols is documented in two case studies, spectral density mapping of a uniformly labeled RNA hairpin and of a selectively labeled disaccharide exhibiting highly anisotropic tumbling. Combination of auto- and cross-correlated relaxation data acquired at three magnetic fields was applied in the former case in order to separate effects of fast motions and conformational or chemical exchange. An approach using auto-correlated relaxation rates acquired at five magnetic fields, applicable to anisotropically moving molecules, was used in the latter case. The results were compared with a more advanced analysis of data obtained by interpolation of auto-correlated relaxation rates measured at seven magnetic fields, and with the spectral density mapping of cross-correlated relaxation rates. The results showed that sufficiently accurate values of auto- and cross-correlated spectral density functions at zero and 13C frequencies can be obtained from data acquired at three magnetic fields for uniformly 13C -labeled molecules with a moderate anisotropy of the rotational diffusion tensor. Analysis of auto-correlated relaxation rates at five magnetic fields represents an alternative for molecules undergoing highly anisotropic motions.
Causality constraints in conformal field theory
Hartman, Thomas; Jain, Sachin; Kundu, Sandipan
2016-05-17
Causality places nontrivial constraints on QFT in Lorentzian signature, for example fixing the signs of certain terms in the low energy Lagrangian. In d dimensional conformal field theory, we show how such constraints are encoded in crossing symmetry of Euclidean correlators, and derive analogous constraints directly from the conformal bootstrap (analytically). The bootstrap setup is a Lorentzian four-point function corresponding to propagation through a shockwave. Crossing symmetry fixes the signs of certain log terms that appear in the conformal block expansion, which constrains the interactions of low-lying operators. As an application, we use the bootstrap to rederive the well knownmore » sign constraint on the (Φ) 4 coupling in effective field theory, from a dual CFT. We also find constraints on theories with higher spin conserved currents. As a result, our analysis is restricted to scalar correlators, but we argue that similar methods should also impose nontrivial constraints on the interactions of spinning operators« less
Properties of galaxies around the most massive SMBHs
NASA Astrophysics Data System (ADS)
Shirasaki, Yuji; Komiya, Yutaka; Ohishi, Masatoshi; Mizumoto, Yoshihiko
2015-08-01
We present result of the clustering analysis performed between AGNs and galaxies. AGN samples with redshift 0.1 - 1.0 were extracted from AGN properties catalogs which contain virial mass estimates of SMBHs. Galaxy samples were extracted from SDSS DR8 catalog and UKIDSS DR9 LAS catalog. The catalogs of SDSS and UKIDSS were merged and used to estimate the IR-opt color and IR magnitude in the rest frame by SED fitting. As we had no redshift information on the galaxy samples, stacking method was applied. We investigated the BH mass dependence of cross correlation length, red galaxy fraction at their environment, and luminosity function of galaxies. We found that the cross correlation length increase above M_BH >= 10^{8.2} Msol, and red galaxies dominate the environment of AGNs with M_BH >= 10^{9} Msol. This result indicates that the most massive SMBHs are mainly fueled by accretion of hot halo gas.
Properties of galaxies around the most massive SMBHs
NASA Astrophysics Data System (ADS)
Shirasaki, Yuji; Komiya, Yutaka; Ohishi, Masatoshi; Mizumoto, Yoshihiko
We present result of the clustering analysis performed between AGNs and galaxies. AGN samples with redshift 0.1-1.0 were extracted from AGN properties catalogs which contain virial mass estimates of SMBHs. Galaxy samples were extracted from SDSS DR8 catalog and UKIDSS DR9 LAS catalog. The catalogs of SDSS and UKIDSS were merged and used to estimate the IR-opt color and IR magnitude in the rest frame by SED fitting. As we had no redshift information on the galaxy samples, stacking method was applied. We investigated the BH mass dependence of cross correlation length, red galaxy fraction at their environment, and luminosity function of galaxies. We found that the cross correlation length increase above M BH >= 108.2 M ⊙, and red galaxies dominate the environment of AGNs with M BH >= 109 M ⊙. This result indicates that the most massive SMBHs are mainly fueled by accretion of hot halo gas.
Imaging subsurface hydrothermal structure using a dense geophone array in Yellowstone
NASA Astrophysics Data System (ADS)
Wu, S. M.; Lin, F. C.; Farrell, J.; Smith, R. B.
2016-12-01
The recent development of ambient noise cross-correlation and the availability of large N seismic arrays allow for the study of detailed shallow crustal structure. In this study, we apply multi-component noise cross-correlation to explore shallow hydrothermal structure near Old Faithful geyser in Yellowstone National Park using a temporary geophone array. The array was composed of 133 three-component 5-Hz geophones and was deployed for two weeks during November 2015. The average station spacing is 50 meters and the full aperture of the array is around 1 km with good azimuthal and spatial coverage. The Upper Geyser Basin, where Old Faithful is located, has the largest concentration of geysers in the world. This unique active hydrothermal environment and hence the extremely inhomogeneous noise source distribution makes the construction of empirical Green's functions difficult based on the traditional noise cross-correlation method. In this presentation, we show examples of the constructed cross-correlation functions and demonstrate their spatial and temporal relationships with known hydrothermal activity. We also demonstrate how useful seismic signals can be extracted from these cross-correlation functions and used for subsurface imaging. In particular, we will discuss the existence of a recharge cavity beneath Old Faithful revealed by the noise cross-correlations. In addition, we also investigated the temporal structure variation based on time-lapse noise cross-correlations and these preliminary results will also be discussed.
NASA Astrophysics Data System (ADS)
Mansouri, Nabila; Watelain, Eric; Ben Jemaa, Yousra; Motamed, Cina
2018-03-01
Computer-vision techniques for pedestrian detection and tracking have progressed considerably and become widely used in several applications. However, a quick glance at the literature shows a minimal use of these techniques in pedestrian behavior and safety analysis, which might be due to the technical complexities facing the processing of pedestrian videos. To extract pedestrian trajectories from a video automatically, all road users must be detected and tracked during sequences, which is a challenging task, especially in a congested open-outdoor urban space. A multipedestrian tracker based on an interframe-detection-association process was proposed and evaluated. The tracker results are used to implement an automatic tool for pedestrians data collection when crossing the street based on video processing. The variations in the instantaneous speed allowed the detection of the street crossing phases (approach, waiting, and crossing). These were addressed for the first time in the pedestrian road security analysis to illustrate the causal relationship between pedestrian behaviors in the different phases. A comparison with a manual data collection method, by computing the root mean square error and the Pearson correlation coefficient, confirmed that the procedures proposed have significant potential to automate the data collection process.
Convergence at the faces of development workings
DOE Office of Scientific and Technical Information (OSTI.GOV)
Borisenko, A.A.
1977-07-01
Since 1963 we have been carrying out investigations in pits of the Pechora coalfield to establish the general laws of roof-floor convergence in the face areas of development workings and their role in gas bursts. We also considered how various methods of working on the seam influence the amount of type of convergence. The observations were made in 20 workings in five pits of Vorkutaugol Group, cut by cutter-loaders and by drilling and blasting at depths between 350 and 600 m; the cross-sectional areas of the workings ranged frm 3.7 to 12.0 m/sup 2/. The aggregated data on daily convergencemore » values was analyzed by the multiple correlation method with the aid of a computer. The aim of the analysis was to elucidate the influence of six factors on the daily convergence values: the depth below the surface, the corrected seam strength, the cross-sectional area of the working, the initial distance from the face to the measurement prop, the daily advance, and the thickness of the seam. The combined correlation coefficient was rather low - 0.49 with a reliability of 9.13. The greatest influence on the convergence values is exerted by the cross-sectional area and by the distance from the face (the partial correlation coefficients being 0.281 and 0.310, respectively), and lesser influences are exerted by the depth below the surface and by the corrected strength of the seam (partial correlationcoefficients 0.164 and 0.178); the influences of seam thickness and daily face advance are very slight. The multiple correlation results indicate that a very great influence is exerted by disregarded factors, among which the most important are undoubtedly the properties of the surrounding rocks.« less
Assessment of 48 Stock markets using adaptive multifractal approach
NASA Astrophysics Data System (ADS)
Ferreira, Paulo; Dionísio, Andreia; Movahed, S. M. S.
2017-11-01
In this paper, Stock market comovements are examined using cointegration, Granger causality tests and nonlinear approaches in context of mutual information and correlations. Since underlying data sets are affected by non-stationarities and trends, we also apply Adaptive Multifractal Detrended Fluctuation Analysis (AMF-DFA) and Adaptive Multifractal Detrended Cross-Correlation Analysis (AMF-DXA). We find only 170 pair of Stock markets cointegrated, and according to the Granger causality and mutual information, we realize that the strongest relations lies between emerging markets, and between emerging and frontier markets. According to scaling exponent given by AMF-DFA, h(q = 2) > 1, we find that all underlying data sets belong to non-stationary process. According to Efficient Market Hypothesis (EMH), only 8 markets are classified in uncorrelated processes at 2 σ confidence interval. 6 Stock markets belong to anti-correlated class and dominant part of markets has memory in corresponding daily index prices during January 1995 to February 2014. New-Zealand with H = 0 . 457 ± 0 . 004 and Jordan with H = 0 . 602 ± 0 . 006 are far from EMH. The nature of cross-correlation exponents based on AMF-DXA is almost multifractal for all pair of Stock markets. The empirical relation, Hxy ≤ [Hxx +Hyy ] / 2, is confirmed. Mentioned relation for q > 0 is also satisfied while for q < 0 there is a deviation from this relation confirming behavior of markets for small fluctuations is affected by contribution of major pair. For larger fluctuations, the cross-correlation contains information from both local (internal) and global (external) conditions. Width of singularity spectrum for auto-correlation and cross-correlation are Δαxx ∈ [ 0 . 304 , 0 . 905 ] and Δαxy ∈ [ 0 . 246 , 1 . 178 ] , respectively. The wide range of singularity spectrum for cross-correlation confirms that the bilateral relation between Stock markets is more complex. The value of σDCCA indicates that all pairs of stock market studied in this time interval belong to cross-correlated processes.
35 years of Ambient Noise: Can We Evidence Daily to Climatic Relative Velocity Changes ?
NASA Astrophysics Data System (ADS)
Lecocq, T.; Pedersen, H.; Brenguier, F.; Stammler, K.
2014-12-01
The broadband Grafenberg array (Germany) has been installed in 1976 and, thanks to visionary scientists and network maintainers, the continuous data acquired has been preserved until today. Using state of the art pre-processing and cross-correlation techniques, we are able to extract cross-correlation functions (CCF) between sensor pairs. It has been shown recently that, provided enough computation power is available, there is no need to define a reference CCF to compare all days to. Indeed, one can compare each day to all days, computing the "all-doublet". The number of calculations becomes huge (N vs ref = N calculations, N vs N= N*N), but the result, once inverted, is way more stable because of the N observations per day. This analysis has been done on a parallelized version of MSNoise (http://msnoise.org), running on the VEGA cluster hosted at the Université Libre de Bruxelles (ULB, Belgium). Here, we present preliminary results of the analysis of two stations, GRA1 and GRA2, the first two stations installed in March 1976. The interferogram (observation of the CCF through time, see Figure) already shows interesting features in the ballistic wave shape, highly correlated to the seasons. A reasonably high correlation can still be seen outside the ballistic arrival, after +-5 second lag time. The lag times between 5 and 25 seconds are then used to compute the dv/v using the all-doublet method. We expect to evidence daily to seasonal, or even to longer period dv/v variations and/or noise source position changes using this method. Once done with 1 sensor pair, the full data of the Grafenberg array will be used to enhance the resolution even more.
An image registration-based technique for noninvasive vascular elastography
NASA Astrophysics Data System (ADS)
Valizadeh, Sina; Makkiabadi, Bahador; Mirbagheri, Alireza; Soozande, Mehdi; Manwar, Rayyan; Mozaffarzadeh, Moein; Nasiriavanaki, Mohammadreza
2018-02-01
Non-invasive vascular elastography is an emerging technique in vascular tissue imaging. During the past decades, several techniques have been suggested to estimate the tissue elasticity by measuring the displacement of the Carotid vessel wall. Cross correlation-based methods are the most prevalent approaches to measure the strain exerted in the wall vessel by the blood pressure. In the case of a low pressure, the displacement is too small to be apparent in ultrasound imaging, especially in the regions far from the center of the vessel, causing a high error of displacement measurement. On the other hand, increasing the compression leads to a relatively large displacement in the regions near the center, which reduces the performance of the cross correlation-based methods. In this study, a non-rigid image registration-based technique is proposed to measure the tissue displacement for a relatively large compression. The results show that the error of the displacement measurement obtained by the proposed method is reduced by increasing the amount of compression while the error of the cross correlationbased method rises for a relatively large compression. We also used the synthetic aperture imaging method, benefiting the directivity diagram, to improve the image quality, especially in the superficial regions. The best relative root-mean-square error (RMSE) of the proposed method and the adaptive cross correlation method were 4.5% and 6%, respectively. Consequently, the proposed algorithm outperforms the conventional method and reduces the relative RMSE by 25%.
Microchannel plate cross-talk mitigation for spatial autocorrelation measurements
NASA Astrophysics Data System (ADS)
Lipka, Michał; Parniak, Michał; Wasilewski, Wojciech
2018-05-01
Microchannel plates (MCP) are the basis for many spatially resolved single-particle detectors such as ICCD or I-sCMOS cameras employing image intensifiers (II), MCPs with delay-line anodes for the detection of cold gas particles or Cherenkov radiation detectors. However, the spatial characterization provided by an MCP is severely limited by cross-talk between its microchannels, rendering MCP and II ill-suited for autocorrelation measurements. Here, we present a cross-talk subtraction method experimentally exemplified for an I-sCMOS based measurement of pseudo-thermal light second-order intensity autocorrelation function at the single-photon level. The method merely requires a dark counts measurement for calibration. A reference cross-correlation measurement certifies the cross-talk subtraction. While remaining universal for MCP applications, the presented cross-talk subtraction, in particular, simplifies quantum optical setups. With the possibility of autocorrelation measurements, the signal needs no longer to be divided into two camera regions for a cross-correlation measurement, reducing the experimental setup complexity and increasing at least twofold the simultaneously employable camera sensor region.
Zhu, Zhaozhong; Anttila, Verneri; Smoller, Jordan W; Lee, Phil H
2018-01-01
Advances in recent genome wide association studies (GWAS) suggest that pleiotropic effects on human complex traits are widespread. A number of classic and recent meta-analysis methods have been used to identify genetic loci with pleiotropic effects, but the overall performance of these methods is not well understood. In this work, we use extensive simulations and case studies of GWAS datasets to investigate the power and type-I error rates of ten meta-analysis methods. We specifically focus on three conditions commonly encountered in the studies of multiple traits: (1) extensive heterogeneity of genetic effects; (2) characterization of trait-specific association; and (3) inflated correlation of GWAS due to overlapping samples. Although the statistical power is highly variable under distinct study conditions, we found the superior power of several methods under diverse heterogeneity. In particular, classic fixed-effects model showed surprisingly good performance when a variant is associated with more than a half of study traits. As the number of traits with null effects increases, ASSET performed the best along with competitive specificity and sensitivity. With opposite directional effects, CPASSOC featured the first-rate power. However, caution is advised when using CPASSOC for studying genetically correlated traits with overlapping samples. We conclude with a discussion of unresolved issues and directions for future research.
NASA Astrophysics Data System (ADS)
Niemeijer, Meindert; Dumitrescu, Alina V.; van Ginneken, Bram; Abrámoff, Michael D.
2011-03-01
Parameters extracted from the vasculature on the retina are correlated with various conditions such as diabetic retinopathy and cardiovascular diseases such as stroke. Segmentation of the vasculature on the retina has been a topic that has received much attention in the literature over the past decade. Analysis of the segmentation result, however, has only received limited attention with most works describing methods to accurately measure the width of the vessels. Analyzing the connectedness of the vascular network is an important step towards the characterization of the complete vascular tree. The retinal vascular tree, from an image interpretation point of view, originates at the optic disc and spreads out over the retina. The tree bifurcates and the vessels also cross each other. The points where this happens form the key to determining the connectedness of the complete tree. We present a supervised method to detect the bifurcations and crossing points of the vasculature of the retina. The method uses features extracted from the vasculature as well as the image in a location regression approach to find those locations of the segmented vascular tree where the bifurcation or crossing occurs (from here, POI, points of interest). We evaluate the method on the publicly available DRIVE database in which an ophthalmologist has marked the POI.
Multifractal detrended cross correlation analysis of neuro-degenerative diseases-An in depth study
NASA Astrophysics Data System (ADS)
Dutta, Srimonti; Ghosh, Dipak; Chatterjee, Sucharita
2018-02-01
This work revisits our previous study on human gait diseases, (Dutta et al., 2013) where we have studied the autocorrelation of human gait pattern in normal and diseased set. Significant difference in results was observed for normal and diseased set. However we were not able to distinguish between sets of Parkinson's and Huntington's disease. In this paper we attempt to study whether cross correlations between two feet of human gait pattern can help to distinguish between different diseased set. The results reveal that study of cross correlations can help to distinguish between Parkinson's and Huntington's disease.
Automated vessel segmentation using cross-correlation and pooled covariance matrix analysis.
Du, Jiang; Karimi, Afshin; Wu, Yijing; Korosec, Frank R; Grist, Thomas M; Mistretta, Charles A
2011-04-01
Time-resolved contrast-enhanced magnetic resonance angiography (CE-MRA) provides contrast dynamics in the vasculature and allows vessel segmentation based on temporal correlation analysis. Here we present an automated vessel segmentation algorithm including automated generation of regions of interest (ROIs), cross-correlation and pooled sample covariance matrix analysis. The dynamic images are divided into multiple equal-sized regions. In each region, ROIs for artery, vein and background are generated using an iterative thresholding algorithm based on the contrast arrival time map and contrast enhancement map. Region-specific multi-feature cross-correlation analysis and pooled covariance matrix analysis are performed to calculate the Mahalanobis distances (MDs), which are used to automatically separate arteries from veins. This segmentation algorithm is applied to a dual-phase dynamic imaging acquisition scheme where low-resolution time-resolved images are acquired during the dynamic phase followed by high-frequency data acquisition at the steady-state phase. The segmented low-resolution arterial and venous images are then combined with the high-frequency data in k-space and inverse Fourier transformed to form the final segmented arterial and venous images. Results from volunteer and patient studies demonstrate the advantages of this automated vessel segmentation and dual phase data acquisition technique. Copyright © 2011 Elsevier Inc. All rights reserved.
Determining Protease Activity In Vivo by Fluorescence Cross-Correlation Analysis
Kohl, Tobias; Haustein, Elke; Schwille, Petra
2005-01-01
To date, most biochemical approaches to unravel protein function have focused on purified proteins in vitro. Whereas they analyze enzyme performance under assay conditions, they do not necessarily tell us what is relevant within a living cell. Ideally, cellular functions should be examined in situ. In particular, association/dissociation reactions are ubiquitous, but so far there is no standard technique permitting online analysis of these processes in vivo. Featuring single-molecule sensitivity combined with intrinsic averaging, fluorescence correlation spectroscopy is a minimally invasive technique ideally suited to monitor proteins. Moreover, endogenous fluorescence-based assays can be established by genetically encoding fusions of autofluorescent proteins and cellular proteins, thus avoiding the disadvantages of in vitro protein labeling and subsequent delivery to cells. Here, we present an in vivo protease assay as a model system: Green and red autofluorescent proteins were connected by Caspase-3- sensitive and insensitive protein linkers to create double-labeled protease substrates. Then, dual-color fluorescence cross-correlation spectroscopy was employed to study the protease reaction in situ. Allowing assessment of multiple dynamic parameters simultaneously, this method provided internal calibration and improved experimental resolution for quantifying protein stability. This approach, which is easily extended to reversible protein-protein interactions, seems very promising for elucidating intracellular protein functions. PMID:16055538
NASA Astrophysics Data System (ADS)
Yuan, Congcong; Jia, Xiaofeng; Liu, Shishuo; Zhang, Jie
2018-02-01
Accurate characterization of hydraulic fracturing zones is currently becoming increasingly important in production optimization, since hydraulic fracturing may increase the porosity and permeability of the reservoir significantly. Recently, the feasibility of the reverse time migration (RTM) method has been studied for the application in imaging fractures during borehole microseismic monitoring. However, strong low-frequency migration noise, poorly illuminated areas, and the low signal to noise ratio (SNR) data can degrade the imaging results. To improve the quality of the images, we propose a multi-cross-correlation staining algorithm to incorporate into the microseismic reverse time migration for imaging fractures using scattered data. Under the modified RTM method, our results are revealed in two images: one is the improved RTM image using the multi-cross-correlation condition, and the other is an image of the target region using the generalized staining algorithm. The numerical examples show that, compared with the conventional RTM, our method can significantly improve the spatial resolution of images, especially for the image of target region.
NASA Astrophysics Data System (ADS)
Khalili, Ashkan
Wave propagation analysis in 1-D and 2-D composite structures is performed efficiently and accurately through the formulation of a User-Defined Element (UEL) based on the wavelet spectral finite element (WSFE) method. The WSFE method is based on the first order shear deformation theory which yields accurate results for wave motion at high frequencies. The wave equations are reduced to ordinary differential equations using Daubechies compactly supported, orthonormal, wavelet scaling functions for approximations in time and one spatial dimension. The 1-D and 2-D WSFE models are highly efficient computationally and provide a direct relationship between system input and output in the frequency domain. The UEL is formulated and implemented in Abaqus for wave propagation analysis in composite structures with complexities. Frequency domain formulation of WSFE leads to complex valued parameters, which are decoupled into real and imaginary parts and presented to Abaqus as real values. The final solution is obtained by forming a complex value using the real number solutions given by Abaqus. Several numerical examples are presented here for 1-D and 2-D composite waveguides. Wave motions predicted by the developed UEL correlate very well with Abaqus simulations using shear flexible elements. The results also show that the UEL largely retains computational efficiency of the WSFE method and extends its ability to model complex features. An enhanced cross-correlation method (ECCM) is developed in order to accurately predict damage location in plates. Three major modifications are proposed to the widely used cross-correlation method (CCM) to improve damage localization capabilities, namely actuator-sensor configuration, signal pre-processing method, and signal post-processing method. The ECCM is investigated numerically (FEM simulation) and experimentally. Experimental investigations for damage detection employ a PZT transducer as actuator and laser Doppler vibrometer as sensor. Both numerical and experimental results show that the developed method is capable of damage localization with high precision. Further, ECCM is used to detect and localize debonding in a composite material skin-stiffener joint. The UEL is used to represent the healthy case whereas the damaged case is simulated using Abaqus. It is shown that the ECCM successfully detects the location of the debond in the skin-stiffener joint.
Panarese, Alessandro; Alia, Claudia; Micera, Silvestro; Caleo, Matteo; Di Garbo, Angelo
2016-01-01
Purpose Limited restoration of function is known to occur spontaneously after an ischemic injury to the primary motor cortex. Evidence suggests that Pre-Motor Areas (PMAs) may “take over” control of the disrupted functions. However, little is known about functional reorganizations in PMAs. Forelimb movements in mice can be driven by two cortical regions, Caudal and Rostral Forelimb Areas (CFA and RFA), generally accepted as primary motor and pre-motor cortex, respectively. Here, we examined longitudinal changes in functional coupling between the two RFAs following unilateral photothrombotic stroke in CFA (mm from Bregma: +0.5 anterior, +1.25 lateral). Methods Local field potentials (LFPs) were recorded from the RFAs of both hemispheres in freely moving injured and naïve mice. Neural signals were acquired at 9, 16 and 23 days after surgery (sub-acute period in stroke animals) through one bipolar electrode per hemisphere placed in the center of RFA, with a ground screw over the occipital bone. LFPs were pre-processed through an efficient method of artifact removal and analysed through: spectral,cross-correlation, mutual information and Granger causality analysis. Results Spectral analysis demonstrated an early decrease (day 9) in the alpha band power in both the RFAs. In the late sub-acute period (days 16 and 23), inter-hemispheric functional coupling was reduced in ischemic animals, as shown by a decrease in the cross-correlation and mutual information measures. Within the gamma and delta bands, correlation measures were already reduced at day 9. Granger analysis, used as a measure of the symmetry of the inter-hemispheric causal connectivity, showed a less balanced activity in the two RFAs after stroke, with more frequent oscillations of hemispheric dominance. Conclusions These results indicate robust electrophysiological changes in PMAs after stroke. Specifically, we found alterations in transcallosal connectivity, with reduced inter-hemispheric functional coupling and a fluctuating dominance pattern. These reorganizations may underlie vicariation of lost functions following stroke. PMID:26752066
NASA Astrophysics Data System (ADS)
Lin, G.
2012-12-01
We investigate the seismic and magmatic activity during an 11-month-long seismic swarm between 1989 and 1990 beneath Mammoth Mountain (MM) at the southwest rim of Long Valley caldera in eastern California. This swarm is believed to be results of a shallow intrusion of magma beneath MM. It was followed by the emissions of carbon dioxide (CO2) gas, which caused tree-killings in 1990 and posed a significant human health risk around MM. In this study, we develop a new three-dimensional (3-D) P-wave velocity model using first-arrival picks by applying the simul2000 tomographic algorithm. The resulting 3-D model is correlated with the surface geological features at shallow depths and is used to constrain absolute earthquake locations for all local events in our study. We compute both P- and S-wave differential times using a time-domain waveform cross-correlation method. We then apply similar event cluster analysis and differential time location approach to further improve relative event location accuracy. A dramatic sharpening of seismicity pattern is obtained after these processes. The estimated uncertainties are a few meters in relative location and ~100 meters in absolute location. We also apply a high-resolution approach to estimate in situ near-source Vp/Vs ratios using differential times from waveform cross-correlation. This method provides highly precise results because cross-correlation can measure differential times to within a few milliseconds and can achieve a precision of 0.001 in estimated Vp/Vs ratio. Our results show a circular ring-like seismicity pattern with a diameter of 2 km between 3 and 8 km depth. These events are distributed in an anomalous body with low Vp and high Vp/Vs, which may be caused by over-pressured magmatically derived fluids. At shallower depths, we observe very low Vp/Vs anomalies beneath MM from the surface to 1 km below sea level whose locations agree with the proposed CO2 reservoir in previous studies. The systematic spatial and temporal migration of seismicity suggests fluid involvement in the seismic swarm. Our results will provide more robust constraints on the crustal structure and volcanic processes beneath Mammoth Mountain.
Tang, Rongnian; Chen, Xupeng; Li, Chuang
2018-05-01
Near-infrared spectroscopy is an efficient, low-cost technology that has potential as an accurate method in detecting the nitrogen content of natural rubber leaves. Successive projections algorithm (SPA) is a widely used variable selection method for multivariate calibration, which uses projection operations to select a variable subset with minimum multi-collinearity. However, due to the fluctuation of correlation between variables, high collinearity may still exist in non-adjacent variables of subset obtained by basic SPA. Based on analysis to the correlation matrix of the spectra data, this paper proposed a correlation-based SPA (CB-SPA) to apply the successive projections algorithm in regions with consistent correlation. The result shows that CB-SPA can select variable subsets with more valuable variables and less multi-collinearity. Meanwhile, models established by the CB-SPA subset outperform basic SPA subsets in predicting nitrogen content in terms of both cross-validation and external prediction. Moreover, CB-SPA is assured to be more efficient, for the time cost in its selection procedure is one-twelfth that of the basic SPA.
NASA Astrophysics Data System (ADS)
Patej, Anna; Eisenstein, Daniel J.
2018-04-01
We develop a formalism for measuring the cosmological distance scale from baryon acoustic oscillations (BAO) using the cross-correlation of a sparse redshift survey with a denser photometric sample. This reduces the shot noise that would otherwise affect the auto-correlation of the sparse spectroscopic map. As a proof of principle, we make the first on-sky application of this method to a sparse sample defined as the z > 0.6 tail of the Sloan Digital Sky Survey's (SDSS) BOSS/CMASS sample of galaxies and a dense photometric sample from SDSS DR9. We find a 2.8σ preference for the BAO peak in the cross-correlation at an effective z = 0.64, from which we measure the angular diameter distance DM(z = 0.64) = (2418 ± 73 Mpc)(rs/rs, fid). Accordingly, we expect that using this method to combine sparse spectroscopy with the deep, high quality imaging that is just now becoming available will enable higher precision BAO measurements than possible with the spectroscopy alone.
NASA Astrophysics Data System (ADS)
Kosuga, M.
2013-12-01
The location of early aftershocks is very important to obtain information of mainshock fault, however, it is often difficult due to the long-lasting coda wave of mainshock and successive occurrence of afterrshocks. To overcome this difficulty, we developed a method of location using seismogram envelopes as templates, and applied the method to the early aftershock sequence of the 2004 Mid-Niigata Prefecture (Chuetsu) Earthquake (M = 6.8) in central Japan. The location method composes of three processes. The first process is the calculation of cross-correlation coefficients between a continuous (target) and template envelopes. We prepare envelopes by taking the logarithm of root-mean-squared amplitude of band-pass filtered seismograms. We perform the calculation by shifting the time window to obtain a set of cross-correlation values for each template. The second process is the event detection (selection of template) and magnitude estimate. We search for the events in descending order of cross-correlation in a time window excluding the dead times around the previously detected events. Magnitude is calculated by the amplitude ratio of target and template envelopes. The third process is the relative event location to the selected template. We applied this method to the Chuetsu earthquake, a large inland earthquake with extensive aftershock activity. The number of detected events depends on the number of templates, frequency range, and the threshold value of cross-correlation. We set the threshold as 0.5 by referring to the histogram of cross-correlation. During a period of one-hour from the mainshock, we could detect more events than the JMA catalog. The location of events is generally near the catalog location. Though we should improve the methods of relative location and magnitude estimate, we conclude that the proposed method works adequately even just after the mainshock of large inland earthquake. Acknowledgement: We thank JMA, NIED, and the University of Tokyo for providing arrival time data, and waveform data. This work was supported by JSPS KAKENHI Grant Number 23540487.
NASA Astrophysics Data System (ADS)
Raghuwanshi, Shailesh Kumar; Gwal, Ashok Kumar
Abstract: In this study we have used the Empirical Mode Decomposition (EMD) method in conjunction with the Cross Correlation analysis to analyze ionospheric foF2 parameter Japan earthquake with magnitude M = 6.9. The data are collected from Kokubunji (35.70N, 139.50E) and Yamakawa (31.20N, 130.60E) ionospheric stations. The EMD method was used for removing the geophysical noise from the foF2 data and then to calculate the correlation coefficient between them. It was found that the ionospheric foF2 parameter shows anomalous change few days before the earthquake. The results are in agreement with the theoretical model evidencing ionospheric modification prior to Japan earthquake in a certain area around the epicenter.
Takaoka, Anna; Babar, Natasha; Hogan, Julia; Kim, MiJung; Price, Marianne O.; Price, Francis W.; Trokel, Stephen L.; Paik, David C.
2016-01-01
Purpose Current literature contains scant information regarding the extent of enzymatic collagen cross-linking in the keratoconus (KC) cornea. The aim of the present study was to examine levels of enzymatic lysyl oxidase–derived cross-links in stromal collagen in KC tissue, and to correlate the cross-link levels with collagen fibril stability as determined by thermal denaturation temperature (Tm). Methods Surgical KC samples (n = 17) and Eye-Bank control (n = 11) corneas of age 18 to 68 years were analyzed. The samples were defatted, reduced (NaBH4), hydrolyzed (6N HCl at 110°C for 18 hours), and cellulose enriched before analysis by C8 high-performance liquid chromatography equipped with parallel fluorescent and mass detectors in selective ion monitoring mode (20 mM heptafluorobutyric acid/methanol 70:30 isocratic at 1 mL/min). Nine different cross-links were measured, and the cross-link density was determined relative to collagen content (determined colorimetrically). The Tm was determined by differential scanning calorimetry. Results Cross-links detected were dihydroxylysinonorleucine (DHLNL), hydroxylysinonorleucine, lysinonorleucine (LNL), and histidinohydroxylysinonorleucine in both control and KC samples. Higher DHLNL levels were detected in KC, whereas the dominant cross-link, LNL, was decreased in KC samples. Decreased LNL levels were observed among KC ≤ 40 corneas. There was no difference in total cross-link density between KC samples and the controls. Pyridinolines, desmosines, and pentosidine were not detected. There was no notable correlation between cross-link levels with fibril instability as determined by Tm. Conclusions Lower levels of LNL in the KC cornea suggest that there might be a cross-linking defect either in fibrillar collagen or the microfibrillar elastic network composed of fibrillin. PMID:26780316
Fire Risk Assessment of Some Indian Coals Using Radial Basis Function (RBF) Technique
NASA Astrophysics Data System (ADS)
Nimaje, Devidas; Tripathy, Debi Prasad
2017-04-01
Fires, whether surface or underground, pose serious and environmental problems in the global coal mining industry. It is causing huge loss of coal due to burning and loss of lives, sterilization of coal reserves and environmental pollution. Most of the instances of coal mine fires happening worldwide are mainly due to the spontaneous combustion. Hence, attention must be paid to take appropriate measures to prevent occurrence and spread of fire. In this paper, to evaluate the different properties of coals for fire risk assessment, forty-nine in situ coal samples were collected from major coalfields of India. Intrinsic properties viz. proximate and ultimate analysis; and susceptibility indices like crossing point temperature, flammability temperature, Olpinski index and wet oxidation potential method of Indian coals were carried out to ascertain the liability of coal to spontaneous combustion. Statistical regression analysis showed that the parameters of ultimate analysis provide significant correlation with all investigated susceptibility indices as compared to the parameters of proximate analysis. Best correlated parameters (ultimate analysis) were used as inputs to the radial basis function network model. The model revealed that Olpinski index can be used as a reliable method to assess the liability of Indian coals to spontaneous combustion.
Scale for positive aspects of caregiving experience: development, reliability, and factor structure.
Kate, N; Grover, S; Kulhara, P; Nehra, R
2012-06-01
OBJECTIVE. To develop an instrument (Scale for Positive Aspects of Caregiving Experience [SPACE]) that evaluates positive caregiving experience and assess its psychometric properties. METHODS. Available scales which assess some aspects of positive caregiving experience were reviewed and a 50-item questionnaire with a 5-point rating was constructed. In all, 203 primary caregivers of patients with severe mental disorders were asked to complete the questionnaire. Internal consistency, test-retest reliability, cross-language reliability, split-half reliability, and face validity were evaluated. Principal component factor analysis was run to assess the factorial validity of the scale. RESULTS. The scale developed as part of the study was found to have good internal consistency, test-retest reliability, cross-language reliability, split-half reliability, and face validity. Principal component factor analysis yielded a 4-factor structure, which also had good test-retest reliability and cross-language reliability. There was a strong correlation between the 4 factors obtained. CONCLUSION. The SPACE developed as part of this study has good psychometric properties.
James, S. R.; Knox, H. A.; Abbott, R. E.; ...
2017-04-13
Cross correlations of seismic noise can potentially record large changes in subsurface velocity due to permafrost dynamics and be valuable for long-term Arctic monitoring. We applied seismic interferometry, using moving window cross-spectral analysis (MWCS), to 2 years of ambient noise data recorded in central Alaska to investigate whether seismic noise could be used to quantify relative velocity changes due to seasonal active-layer dynamics. The large velocity changes (>75%) between frozen and thawed soil caused prevalent cycle-skipping which made the method unusable in this setting. We developed an improved MWCS procedure which uses a moving reference to measure daily velocity variationsmore » that are then accumulated to recover the full seasonal change. This approach reduced cycle-skipping and recovered a seasonal trend that corresponded well with the timing of active-layer freeze and thaw. Lastly, this improvement opens the possibility of measuring large velocity changes by using MWCS and permafrost monitoring by using ambient noise.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Xiaolin; Ye, Li; Wang, Xiaoxiang
2012-12-15
Several recent reports suggested that hydroxylated polybrominated diphenyl ethers (HO-PBDEs) may disturb thyroid hormone homeostasis. To illuminate the structural features for thyroid hormone activity of HO-PBDEs and the binding mode between HO-PBDEs and thyroid hormone receptor (TR), the hormone activity of a series of HO-PBDEs to thyroid receptors β was studied based on the combination of 3D-QSAR, molecular docking, and molecular dynamics (MD) methods. The ligand- and receptor-based 3D-QSAR models were obtained using Comparative Molecular Similarity Index Analysis (CoMSIA) method. The optimum CoMSIA model with region focusing yielded satisfactory statistical results: leave-one-out cross-validation correlation coefficient (q{sup 2}) was 0.571 andmore » non-cross-validation correlation coefficient (r{sup 2}) was 0.951. Furthermore, the results of internal validation such as bootstrapping, leave-many-out cross-validation, and progressive scrambling as well as external validation indicated the rationality and good predictive ability of the best model. In addition, molecular docking elucidated the conformations of compounds and key amino acid residues at the docking pocket, MD simulation further determined the binding process and validated the rationality of docking results. -- Highlights: ► The thyroid hormone activities of HO-PBDEs were studied by 3D-QSAR. ► The binding modes between HO-PBDEs and TRβ were explored. ► 3D-QSAR, molecular docking, and molecular dynamics (MD) methods were performed.« less
Preliminary analysis of cross beam data from the Gun Barrel Hill site
NASA Technical Reports Server (NTRS)
Sandborn, V. A.; Bice, A. R.; Cliff, W. C.; Hablutzel, B. C.
1974-01-01
Preliminary evaluation of cross beam data taken at the Gun Barrell Hill test site of ESSA is presented. The evaluation is made using the analog Princeton Time Correlator. A study of the frequency band width limitations of the Princeton Time Correlator is made. Based on the band width limitations, it is possible to demonstrate that nearly identical correlation is obtained for frequencies from .01 to 3.9 hertz. Difficulty is encountered in that maximums in the correlation curves do not occur at zero time lag for zero beam separations.
Uwaezuoke, S N; Okoli, C V; Ubesie, A C; Ikefuna, A N
2016-01-01
To assess the prevalence of primary hypertension and its correlation with anthropometric indices among a population of Nigerian adolescents. A cross-sectional study of secondary school adolescents aged 10-19 years in Enugu, Nigeria, using multi-staged sampling method. Anthropometry and blood pressures were measured using standardized instruments. Data analysis was with the Statistical Package for Social Sciences (SPSS) Version 20.0 (Chicago, IL, USA). A total of 2419 adolescents (mean age, 14.80 ± 2.07 years) were included in the study. Prevalence of hypertension was 10.7%. Systolic and diastolic hypertension were observed in 232 (9.6%) and 85 (3.5%) of the participants, respectively. Forty-two of the 137 obese (30.7%) compared to 158 among the 1777 (7.7%) with normal body mass index (BMI) (P < 0.001) had systolic hypertension. Waist circumference (r = 0.37) and BMI (r = 0.37) significantly and positively correlated with systolic hypertension. Obese and overweight adolescents had higher prevalence of primary hypertension than their counterparts with normal BMI.
The overnight effect on the Taiwan stock market
NASA Astrophysics Data System (ADS)
Tsai, Kuo-Ting; Lih, Jiann-Shing; Ko, Jing-Yuan
2012-12-01
This study examines statistical regularities among three components of stocks and indices: daytime (trading hour) return, overnight (off-hour session) return, and total (close-to-close) return. Owing to the fact that the Taiwan Stock Exchange (TWSE) has the longest non-trading periods among major markets, the TWSE is selected to explore the correlation among the three components and compare it with major markets such as the New York Stock Exchange (NYSE) and the National Association of Securities Dealers Automated Quotation (NASDAQ). Analysis results indicate a negative cross correlation between the sign of daytime return and the sign of overnight return; possibly explaining why most stocks feature a negative cross correlation between daytime return and overnight return [F. Wang, S.-J. Shieh, S. Havlin, H.E. Stanley, Statistical analysis of the overnight and daytime return, Phys. Rev. E 79 (2009) 056109]. Additionally, the cross correlation between the magnitude of returns is analyzed. According to those results, a larger magnitude of overnight return implies a higher probability that the sign of the following daytime return is the opposite of the sign of overnight return. Namely, the predictability of daytime return might be improved when a stock undergoes a large magnitude of overnight return. Furthermore, the cross correlations of 29 indices of worldwide markets are discussed.
ERIC Educational Resources Information Center
Edmonds, Lisa A.
2013-01-01
Purpose: The purpose of this study was to determine (a) correlates of informativeness and efficiency in discourse and (b) potential cross-linguistic and stimulus type (picture vs. nonpicture) differences in measures of informativeness and efficiency in Spanish/English bilingual adults in the United States. Method: Eighty-eight Spanish/English…
Modified multidimensional scaling approach to analyze financial markets.
Yin, Yi; Shang, Pengjian
2014-06-01
Detrended cross-correlation coefficient (σDCCA) and dynamic time warping (DTW) are introduced as the dissimilarity measures, respectively, while multidimensional scaling (MDS) is employed to translate the dissimilarities between daily price returns of 24 stock markets. We first propose MDS based on σDCCA dissimilarity and MDS based on DTW dissimilarity creatively, while MDS based on Euclidean dissimilarity is also employed to provide a reference for comparisons. We apply these methods in order to further visualize the clustering between stock markets. Moreover, we decide to confront MDS with an alternative visualization method, "Unweighed Average" clustering method, for comparison. The MDS analysis and "Unweighed Average" clustering method are employed based on the same dissimilarity. Through the results, we find that MDS gives us a more intuitive mapping for observing stable or emerging clusters of stock markets with similar behavior, while the MDS analysis based on σDCCA dissimilarity can provide more clear, detailed, and accurate information on the classification of the stock markets than the MDS analysis based on Euclidean dissimilarity. The MDS analysis based on DTW dissimilarity indicates more knowledge about the correlations between stock markets particularly and interestingly. Meanwhile, it reflects more abundant results on the clustering of stock markets and is much more intensive than the MDS analysis based on Euclidean dissimilarity. In addition, the graphs, originated from applying MDS methods based on σDCCA dissimilarity and DTW dissimilarity, may also guide the construction of multivariate econometric models.
Causative impact of air pollution on evapotranspiration in the North China Plain.
Yao, Ling
2017-10-01
Atmospheric dispersion conditions strongly impact air pollution under identical surface emissions. The degree of air pollution in the Jing-Jin-Ji region is so severe that it may impose feedback on local climate. Reference evapotranspiration (ET 0 ) plays a significant role in the estimation of crop water requirements, as well as in studies on climate variation and change. Since the traditional correlation analysis cannot capture the causality, we apply the convergent cross mapping method (CCM) in this study to observationally investigate whether the air pollution impacts ET 0 . The results indicate that southwest regions of Jing-Jin-Ji always suffer higher PM 2.5 concentration than north regions through the whole year, and correlation analysis suggests that PM 2.5 concentration has a significant negative effect on ET 0 in most cities. The causality detection with CCM quantitatively demonstrates the significantly causative influence of PM 2.5 concentration on ET 0 , higher PM 2.5 concentration decreasing ET 0 . However, CCM analysis suggests that PM 2.5 concentration has a relatively weak causal influence on ET 0 while the correlation analysis gives the near zero correlation coefficient in Zhangjiakou city, indicating that the causative influence of PM 2.5 concentration on ET 0 is better revealed with CCM method than the correlation analysis. Considering that ET 0 is strongly associated with crop water requirement, the amount of water for agricultural irrigation could be reduced at high PM 2.5 concentrations. These findings can be utilized to improve the efficiency of water resources utilization, and reduce the exploiting amount of groundwater in the Jing-Jin-Ji region, although PM 2.5 is detrimental to human health. Copyright © 2017 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Hincks, Adam D.; Hajian, Amir; Addison, Graeme E.
2013-05-01
We cross-correlate the 100 μm Improved Reprocessing of the IRAS Survey (IRIS) map and galaxy clusters at 0.1 < z < 0.3 in the maxBCG catalogue taken from the Sloan Digital Sky Survey, measuring an angular cross-power spectrum over multipole moments 150 < l < 3000 at a total significance of over 40σ. The cross-spectrum, which arises from the spatial correlation between unresolved dusty galaxies that make up the cosmic infrared background (CIB) in the IRIS map and the galaxy clusters, is well-fit by a single power law with an index of -1.28±0.12, similar to the clustering of unresolved galaxies from cross-correlating far-infrared and submillimetre maps at longer wavelengths. Using a recent, phenomenological model for the spectral and clustering properties of the IRIS galaxies, we constrain the large-scale bias of the maxBCG clusters to be 2.6±1.4, consistent with existing analyses of the real-space cluster correlation function. The success of our method suggests that future CIB-optical cross-correlations using Planck and Herschel data will significantly improve our understanding of the clustering and redshift distribution of the faint CIB sources.
Kim, Young Saing; Kim, Eun Young; Kang, Shin Myung; Ahn, Hee Kyung; Kim, Hyung Sik
2017-09-01
Skeletal muscle depletion is an important prognostic factor in patients with chronic obstructive pulmonary disease (COPD); a recent study demonstrated significant correlations between pectoralis muscle area on an axial CT image and COPD-related traits. The purpose of this study was to evaluate the relation between pectoralis muscle areas on CT scans and total body skeletal muscle mass (SMM) in healthy subjects. For 434 subjects that underwent a low-dose chest CT and bioelectrical impedance analysis (BIA) during health screening from January to June of 2014, cross-sectional area of pectoralis muscles were measured in CT scans. Pearson's correlation and multiple linear regression analysis were used to assess the relationship between cross-sectional CT areas of pectoralis muscles and BIA-assessed SMMs. Mean age was 50 ± 10 years (78·8% were male). The mean cross-sectional area of pectoralis muscles was 24·1 cm 2 ± 6·8. A moderate correlation was observed between pectoralis muscle area and BIA-based SMM (r = 0·665, P<0.001). Multivariable analysis showed CT determined pectoralis muscle area was significantly associated with BIA-assessed SMM after adjusting for gender, weight, height and age (β = 0·14 ± 0·02, P<0·001). Cross-sectional area of the pectoralis muscles on single axial CT images shows moderate correlation with total body SMM determined by BIA in healthy subjects. © 2015 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.
The coupling analysis between stock market indices based on permutation measures
NASA Astrophysics Data System (ADS)
Shi, Wenbin; Shang, Pengjian; Xia, Jianan; Yeh, Chien-Hung
2016-04-01
Many information-theoretic methods have been proposed for analyzing the coupling dependence between time series. And it is significant to quantify the correlation relationship between financial sequences since the financial market is a complex evolved dynamic system. Recently, we developed a new permutation-based entropy, called cross-permutation entropy (CPE), to detect the coupling structures between two synchronous time series. In this paper, we extend the CPE method to weighted cross-permutation entropy (WCPE), to address some of CPE's limitations, mainly its inability to differentiate between distinct patterns of a certain motif and the sensitivity of patterns close to the noise floor. It shows more stable and reliable results than CPE does when applied it to spiky data and AR(1) processes. Besides, we adapt the CPE method to infer the complexity of short-length time series by freely changing the time delay, and test it with Gaussian random series and random walks. The modified method shows the advantages in reducing deviations of entropy estimation compared with the conventional one. Finally, the weighted cross-permutation entropy of eight important stock indices from the world financial markets is investigated, and some useful and interesting empirical results are obtained.
Simple, empirical approach to predict neutron capture cross sections from nuclear masses
NASA Astrophysics Data System (ADS)
Couture, A.; Casten, R. F.; Cakirli, R. B.
2017-12-01
Background: Neutron capture cross sections are essential to understanding the astrophysical s and r processes, the modeling of nuclear reactor design and performance, and for a wide variety of nuclear forensics applications. Often, cross sections are needed for nuclei where experimental measurements are difficult. Enormous effort, over many decades, has gone into attempting to develop sophisticated statistical reaction models to predict these cross sections. Such work has met with some success but is often unable to reproduce measured cross sections to better than 40 % , and has limited predictive power, with predictions from different models rapidly differing by an order of magnitude a few nucleons from the last measurement. Purpose: To develop a new approach to predicting neutron capture cross sections over broad ranges of nuclei that accounts for their values where known and which has reliable predictive power with small uncertainties for many nuclei where they are unknown. Methods: Experimental neutron capture cross sections were compared to empirical mass observables in regions of similar structure. Results: We present an extremely simple method, based solely on empirical mass observables, that correlates neutron capture cross sections in the critical energy range from a few keV to a couple hundred keV. We show that regional cross sections are compactly correlated in medium and heavy mass nuclei with the two-neutron separation energy. These correlations are easily amenable to predict unknown cross sections, often converting the usual extrapolations to more reliable interpolations. It almost always reproduces existing data to within 25 % and estimated uncertainties are below about 40 % up to 10 nucleons beyond known data. Conclusions: Neutron capture cross sections display a surprisingly strong connection to the two-neutron separation energy, a nuclear structure property. The simple, empirical correlations uncovered provide model-independent predictions of neutron capture cross sections, extending far from stability, including for nuclei of the highest sensitivity to r -process nucleosynthesis.
NASA Astrophysics Data System (ADS)
Saltos, Andrea
In efforts to perform accurate dosimetry, Oakes et al. [Nucl. Intrum. Mehods. (2013)] introduced a new portable solid state neutron rem meter based on an adaptation of the Bonner sphere and the position sensitive long counter. The system utilizes high thermal efficiency neutron detectors to generate a linear combination of measurement signals that are used to estimate the incident neutron spectra. The inversion problem associated to deduce dose from the counts in individual detector elements is addressed by applying a cross-correlation method which allows estimation of dose with average errors less than 15%. In this work, an evaluation of the performance of this system was extended to take into account new correlation techniques and neutron scattering contribution. To test the effectiveness of correlations, the Distance correlation, Pearson Product-Moment correlation, and their weighted versions were performed between measured spatial detector responses obtained from nine different test spectra, and the spatial response of Library functions generated by MCNPX. Results indicate that there is no advantage of using the Distance Correlation over the Pearson Correlation, and that weighted versions of these correlations do not increase their performance in evaluating dose. Both correlations were proven to work well even at low integrated doses measured for short periods of time. To evaluate the contribution produced by room-return neutrons on the dosimeter response, MCNPX was used to simulate dosimeter responses for five isotropic neutron sources placed inside different sizes of rectangular concrete rooms. Results show that the contribution of scattered neutrons to the response of the dosimeter can be significant, so that for most cases the dose is over predicted with errors as large as 500%. A possible method to correct for the contribution of room-return neutrons is also assessed and can be used as a good initial estimate on how to approach the problem.
Minimum spanning tree filtering of correlations for varying time scales and size of fluctuations
NASA Astrophysics Data System (ADS)
Kwapień, Jarosław; Oświecimka, Paweł; Forczek, Marcin; DroŻdŻ, Stanisław
2017-05-01
Based on a recently proposed q -dependent detrended cross-correlation coefficient, ρq [J. Kwapień, P. Oświęcimka, and S. Drożdż, Phys. Rev. E 92, 052815 (2015), 10.1103/PhysRevE.92.052815], we generalize the concept of the minimum spanning tree (MST) by introducing a family of q -dependent minimum spanning trees (q MST s ) that are selective to cross-correlations between different fluctuation amplitudes and different time scales of multivariate data. They inherit this ability directly from the coefficients ρq, which are processed here to construct a distance matrix being the input to the MST-constructing Kruskal's algorithm. The conventional MST with detrending corresponds in this context to q =2 . In order to illustrate their performance, we apply the q MSTs to sample empirical data from the American stock market and discuss the results. We show that the q MST graphs can complement ρq in disentangling "hidden" correlations that cannot be observed in the MST graphs based on ρDCCA, and therefore, they can be useful in many areas where the multivariate cross-correlations are of interest. As an example, we apply this method to empirical data from the stock market and show that by constructing the q MSTs for a spectrum of q values we obtain more information about the correlation structure of the data than by using q =2 only. More specifically, we show that two sets of signals that differ from each other statistically can give comparable trees for q =2 , while only by using the trees for q ≠2 do we become able to distinguish between these sets. We also show that a family of q MSTs for a range of q expresses the diversity of correlations in a manner resembling the multifractal analysis, where one computes a spectrum of the generalized fractal dimensions, the generalized Hurst exponents, or the multifractal singularity spectra: the more diverse the correlations are, the more variable the tree topology is for different q 's. As regards the correlation structure of the stock market, our analysis exhibits that the stocks belonging to the same or similar industrial sectors are correlated via the fluctuations of moderate amplitudes, while the largest fluctuations often happen to synchronize in those stocks that do not necessarily belong to the same industry.
Temporal cross-correlation asymmetry and departure from equilibrium in a bistable chemical system.
Bianca, C; Lemarchand, A
2014-06-14
This paper aims at determining sustained reaction fluxes in a nonlinear chemical system driven in a nonequilibrium steady state. The method relies on the computation of cross-correlation functions for the internal fluctuations of chemical species concentrations. By employing Langevin-type equations, we derive approximate analytical formulas for the cross-correlation functions associated with nonlinear dynamics. Kinetic Monte Carlo simulations of the chemical master equation are performed in order to check the validity of the Langevin equations for a bistable chemical system. The two approaches are found in excellent agreement, except for critical parameter values where the bifurcation between monostability and bistability occurs. From the theoretical point of view, the results imply that the behavior of cross-correlation functions cannot be exploited to measure sustained reaction fluxes in a specific nonlinear system without the prior knowledge of the associated chemical mechanism and the rate constants.
Lu, Shao Hua; Li, Bao Qiong; Zhai, Hong Lin; Zhang, Xin; Zhang, Zhuo Yong
2018-04-25
Terahertz time-domain spectroscopy has been applied to many fields, however, it still encounters drawbacks in multicomponent mixtures analysis due to serious spectral overlapping. Here, an effective approach to quantitative analysis was proposed, and applied on the determination of the ternary amino acids in foxtail millet substrate. Utilizing three parameters derived from the THz-TDS, the images were constructed and the Tchebichef image moments were used to extract the information of target components. Then the quantitative models were obtained by stepwise regression. The correlation coefficients of leave-one-out cross-validation (R loo-cv 2 ) were more than 0.9595. As for external test set, the predictive correlation coefficients (R p 2 ) were more than 0.8026 and the root mean square error of prediction (RMSE p ) were less than 1.2601. Compared with the traditional methods (PLS and N-PLS methods), our approach is more accurate, robust and reliable, and can be a potential excellent approach to quantify multicomponent with THz-TDS spectroscopy. Copyright © 2017 Elsevier Ltd. All rights reserved.
Independent component analysis applied to long bunch beams in the Los Alamos Proton Storage Ring
NASA Astrophysics Data System (ADS)
Kolski, Jeffrey S.; Macek, Robert J.; McCrady, Rodney C.; Pang, Xiaoying
2012-11-01
Independent component analysis (ICA) is a powerful blind source separation (BSS) method. Compared to the typical BSS method, principal component analysis, ICA is more robust to noise, coupling, and nonlinearity. The conventional ICA application to turn-by-turn position data from multiple beam position monitors (BPMs) yields information about cross-BPM correlations. With this scheme, multi-BPM ICA has been used to measure the transverse betatron phase and amplitude functions, dispersion function, linear coupling, sextupole strength, and nonlinear beam dynamics. We apply ICA in a new way to slices along the bunch revealing correlations of particle motion within the beam bunch. We digitize beam signals of the long bunch at the Los Alamos Proton Storage Ring with a single device (BPM or fast current monitor) for an entire injection-extraction cycle. ICA of the digitized beam signals results in source signals, which we identify to describe varying betatron motion along the bunch, locations of transverse resonances along the bunch, measurement noise, characteristic frequencies of the digitizing oscilloscopes, and longitudinal beam structure.
du Mas des Bourboux, Helion; Le Goff, Jean-Marc; Blomqvist, Michael; ...
2017-08-08
We present a measurement of baryon acoustic oscillations (BAO) in the cross-correlation of quasars with the Lyα-forest flux-transmission at a mean redshift z = 2.40. The measurement uses the complete SDSS-III data sample: 168,889 forests and 234,367 quasars from the SDSS Data Release DR12. In addition to the statistical improvement on our previous study using DR11, we have implemented numerous improvements at the analysis level allowing a more accurate measurement of this cross-correlation. We also developed the first simulations of the cross-correlation allowing us to test different aspects of our data analysis and to search for potential systematic errors inmore » the determination of the BAO peak position. We measure the two ratios D H(z = 2.40)=r d = 9.01 ± 0.36 and D M(z = 2.40)=r d = 35.7 ±1.7, where the errors include marginalization over the non-linear velocity of quasars and the metal - quasar cross-correlation contribution, among other effects. These results are within 1.8σ of the prediction of the flat-ΛCDM model describing the observed CMB anisotropies.We combine this study with the Lyα-forest auto-correlation function (Bautista et al. 2017), yielding D H(z = 2.40)=r d = 8.94 ± 0.22 and D M(z = 2.40)=r d = 36.6 ± 1.2, within 2.3σ of the same flat-ΛCDM model.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
du Mas des Bourboux, Helion; Le Goff, Jean-Marc; Blomqvist, Michael
We present a measurement of baryon acoustic oscillations (BAO) in the cross-correlation of quasars with the Lyα-forest flux-transmission at a mean redshift z = 2.40. The measurement uses the complete SDSS-III data sample: 168,889 forests and 234,367 quasars from the SDSS Data Release DR12. In addition to the statistical improvement on our previous study using DR11, we have implemented numerous improvements at the analysis level allowing a more accurate measurement of this cross-correlation. We also developed the first simulations of the cross-correlation allowing us to test different aspects of our data analysis and to search for potential systematic errors inmore » the determination of the BAO peak position. We measure the two ratios D H(z = 2.40)=r d = 9.01 ± 0.36 and D M(z = 2.40)=r d = 35.7 ±1.7, where the errors include marginalization over the non-linear velocity of quasars and the metal - quasar cross-correlation contribution, among other effects. These results are within 1.8σ of the prediction of the flat-ΛCDM model describing the observed CMB anisotropies.We combine this study with the Lyα-forest auto-correlation function (Bautista et al. 2017), yielding D H(z = 2.40)=r d = 8.94 ± 0.22 and D M(z = 2.40)=r d = 36.6 ± 1.2, within 2.3σ of the same flat-ΛCDM model.« less
Khokhlova, V N
1999-01-01
The multiunit activity of neurons in the motor cortex was recorded in 6 rabbits during glutamate (or physiological saline) iontophoretic application. Interaction between the neighboring neurons was evaluated by means of statistical cross-correlation analysis of spike trains. It was found that glutamate did not produce significant changes in cross-correlations.
Comparative assessment of three standardized robotic surgery training methods.
Hung, Andrew J; Jayaratna, Isuru S; Teruya, Kara; Desai, Mihir M; Gill, Inderbir S; Goh, Alvin C
2013-10-01
To evaluate three standardized robotic surgery training methods, inanimate, virtual reality and in vivo, for their construct validity. To explore the concept of cross-method validity, where the relative performance of each method is compared. Robotic surgical skills were prospectively assessed in 49 participating surgeons who were classified as follows: 'novice/trainee': urology residents, previous experience <30 cases (n = 38) and 'experts': faculty surgeons, previous experience ≥30 cases (n = 11). Three standardized, validated training methods were used: (i) structured inanimate tasks; (ii) virtual reality exercises on the da Vinci Skills Simulator (Intuitive Surgical, Sunnyvale, CA, USA); and (iii) a standardized robotic surgical task in a live porcine model with performance graded by the Global Evaluative Assessment of Robotic Skills (GEARS) tool. A Kruskal-Wallis test was used to evaluate performance differences between novices and experts (construct validity). Spearman's correlation coefficient (ρ) was used to measure the association of performance across inanimate, simulation and in vivo methods (cross-method validity). Novice and expert surgeons had previously performed a median (range) of 0 (0-20) and 300 (30-2000) robotic cases, respectively (P < 0.001). Construct validity: experts consistently outperformed residents with all three methods (P < 0.001). Cross-method validity: overall performance of inanimate tasks significantly correlated with virtual reality robotic performance (ρ = -0.7, P < 0.001) and in vivo robotic performance based on GEARS (ρ = -0.8, P < 0.0001). Virtual reality performance and in vivo tissue performance were also found to be strongly correlated (ρ = 0.6, P < 0.001). We propose the novel concept of cross-method validity, which may provide a method of evaluating the relative value of various forms of skills education and assessment. We externally confirmed the construct validity of each featured training tool. © 2013 BJU International.
Mathematical and Statistical Software Index.
1986-08-01
geometric) mean HMEAN - harmonic mean MEDIAN - median MODE - mode QUANT - quantiles OGIVE - distribution curve IQRNG - interpercentile range RANGE ... range mutliphase pivoting algorithm cross-classification multiple discriminant analysis cross-tabul ation mul tipl e-objecti ve model curve fitting...Statistics). .. .. .... ...... ..... ...... ..... .. 21 *RANGEX (Correct Correlations for Curtailment of Range ). .. .. .... ...... ... 21 *RUMMAGE II (Analysis
Mathematical Creativity and Mathematical Aptitude: A Cross-Lagged Panel Analysis
ERIC Educational Resources Information Center
Tyagi, Tarun Kumar
2016-01-01
Cross-lagged panel correlation (CLPC) analysis has been used to identify causal relationships between mathematical creativity and mathematical aptitude. For this study, 480 8th standard students were selected through a random cluster technique from 9 intermediate and high schools of Varanasi, India. Mathematical creativity and mathematical…
NASA Astrophysics Data System (ADS)
Gammans, Christine Naomi Louise
On January 3, 2011, an Mw 4.5 earthquake occurred in the Tushar Mountains near Circleville, Utah (38.248°N, -112.329°W, 7.75 km depth, and origin time of 12:06:36.58). The Tushar Mountains are located in the transition zone between the stable Colorado Plateau (CP) to the east and the deforming Basin and Range (BR) province to the west. In this area, seismicity associated with the Intermountain Seismic Belt is relatively common. The University of Utah Seismograph Stations (UUSS) detected and located 97 aftershocks in the 33 weeks following the mainshock. On January 6, UUSS installed a portable station in the source region. Using three aftershocks recorded by the portable station as master events, including the largest (Mw 3.8), we relocated the mainshock/aftershock sequence. These refined locations were used as initial locations for the HypoDD method of Waldhauser and Ellsworth [2001] to produce a second, improved set of relocations. In addition to P- and S-arrival time picks, we used the lag-times from waveform cross-correlations as input to HypoDD. We analyzed the fault geometry apparent in the final locations by comparing them to known moment-tensor focal planes and by applying principal component analysis to measure the degree of planarity and orientation of the sequence as a whole. Additionally, using cross-correlation analysis, we identified aftershocks best suited for an empirical Green's function analysis of the mainshock and a strike-slip aftershock that occurred on January 6. From the events chosen by cross-correlation, we were able to obtain source-time functions that were used to obtain fault dimensions, stress drops, and evidence for or against directivity. Lastly, we determined focal mechanisms for ten of the events using first-motion methods. The results of the combined analyses indicate that the mainshock occurred on a low-angle normal fault and that the entire sequence occurred on at least two different fault planes.
Double Photoionization of helium atom using Screening Potential Approach
NASA Astrophysics Data System (ADS)
Saha, Haripada
2014-05-01
The triple differential cross section for double Photoionization of helium atom will be investigated using our recently extended MCHF method. It is well known that electron correlation effects in both the initial and the final states are very important. To incorporate these effects we will use the multi-configuration Hartree-Fock method to account for electron correlation in the initial state. The electron correlation in the final state will be taken into account using the angle-dependent screening potential approximation. The triple differential cross section (TDCS) will be calculated for 20 eV photon energy, which has experimental results. Our results will be compared with available experimental and the theoretical observations.
Rudolph, G; Bechmann, M; Berninger, T; Kutschbach, E; Held, U; Tornow, R P; Kalpadakis, P; Zol'nikova, I V; Shamshinova, A M
2001-01-01
A new method of multifocal electroretinography making use of scanning laser ophthalmoscope with a wavelength of 630 nm (SLO-m-ERG), evoking short spatial visual stimuli on the retina, is proposed. Algorithm of presenting the visual stimuli and analysis of distribution of local electroretinograms on the surface of the retina is based on short m-sequences. Mathematical cross correlation analysis shows a three-dimensional distribution of bioelectrical activity of the retina in the central visual field. In normal subjects the cone bioelectrical activity is the maximum in the macular area (corresponding to the density of cone distribution) and absent in the blind spot. The method detects the slightest pathological changes in the retina under control of the site of stimulation and ophthalmoscopic picture of the fundus oculi. The site of the pathological process correlates with the topography of changes in bioelectrical activity of the examined retinal area in diseases of the macular area and pigmented retinitis detectable by ophthalmoscopy.
A phase match based frequency estimation method for sinusoidal signals
NASA Astrophysics Data System (ADS)
Shen, Yan-Lin; Tu, Ya-Qing; Chen, Lin-Jun; Shen, Ting-Ao
2015-04-01
Accurate frequency estimation affects the ranging precision of linear frequency modulated continuous wave (LFMCW) radars significantly. To improve the ranging precision of LFMCW radars, a phase match based frequency estimation method is proposed. To obtain frequency estimation, linear prediction property, autocorrelation, and cross correlation of sinusoidal signals are utilized. The analysis of computational complex shows that the computational load of the proposed method is smaller than those of two-stage autocorrelation (TSA) and maximum likelihood. Simulations and field experiments are performed to validate the proposed method, and the results demonstrate the proposed method has better performance in terms of frequency estimation precision than methods of Pisarenko harmonic decomposition, modified covariance, and TSA, which contribute to improving the precision of LFMCW radars effectively.
Experimental and simulation flow rate analysis of the 3/2 directional pneumatic valve
NASA Astrophysics Data System (ADS)
Blasiak, Slawomir; Takosoglu, Jakub E.; Laski, Pawel A.; Pietrala, Dawid S.; Zwierzchowski, Jaroslaw; Bracha, Gabriel; Nowakowski, Lukasz; Blasiak, Malgorzata
The work includes a study on the comparative analysis of two test methods. The first method - numerical method, consists in determining the flow characteristics with the use of ANSYS CFX. A modeled poppet directional valve 3/2 3D CAD software - SolidWorks was used for this purpose. Based on the solid model that was developed, simulation studies of the air flow through the way valve in the software for computational fluid dynamics Ansys CFX were conducted. The second method - experimental, entailed conducting tests on a specially constructed test stand. The comparison of the test results obtained on the basis of both methods made it possible to determine the cross-correlation. High compatibility of the results confirms the usefulness of the numerical procedures. Thus, they might serve to determine the flow characteristics of directional valves as an alternative to a costly and time-consuming test stand.
Techniques for investigation of an apparent outbreak of infections with Candida glabrata.
Arif, S; Barkham, T; Power, E G; Howell, S A
1996-01-01
A cluster of Candida glabrata isolates recovered from seven patients in an intensive care unit over a 10-week period were compared with a collection of isolates from six epidemiologically distinct outpatients and a reference strain by several DNA typing methods. Restriction enzyme analysis with HinII distinguished 13 strains from the 14 sources and was the method of choice. Pulsed-field gel electrophoresis and random amplification of polymorphic DNA both detected nine types from the 14 sources; however, the results of these two methods did not always correlate. These methods demonstrated that five of the seven patients had distinguishable strains and that cross-infection was unlikely. PMID:8862586
Pseudorange error analysis for precise indoor positioning system
NASA Astrophysics Data System (ADS)
Pola, Marek; Bezoušek, Pavel
2017-05-01
There is a currently developed system of a transmitter indoor localization intended for fire fighters or members of rescue corps. In this system the transmitter of an ultra-wideband orthogonal frequency-division multiplexing signal position is determined by the time difference of arrival method. The position measurement accuracy highly depends on the directpath signal time of arrival estimation accuracy which is degraded by severe multipath in complicated environments such as buildings. The aim of this article is to assess errors in the direct-path signal time of arrival determination caused by multipath signal propagation and noise. Two methods of the direct-path signal time of arrival estimation are compared here: the cross correlation method and the spectral estimation method.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gong, S.; Labanca, I.; Rech, I.
2014-10-15
Fluorescence correlation spectroscopy (FCS) is a well-established technique to study binding interactions or the diffusion of fluorescently labeled biomolecules in vitro and in vivo. Fast FCS experiments require parallel data acquisition and analysis which can be achieved by exploiting a multi-channel Single Photon Avalanche Diode (SPAD) array and a corresponding multi-input correlator. This paper reports a 32-channel FPGA based correlator able to perform 32 auto/cross-correlations simultaneously over a lag-time ranging from 10 ns up to 150 ms. The correlator is included in a 32 × 1 SPAD array module, providing a compact and flexible instrument for high throughput FCS experiments.more » However, some inherent features of SPAD arrays, namely afterpulsing and optical crosstalk effects, may introduce distortions in the measurement of auto- and cross-correlation functions. We investigated these limitations to assess their impact on the module and evaluate possible workarounds.« less
NASA Astrophysics Data System (ADS)
Armstrong, Geoffrey S.; Bendiak, Brad
2006-07-01
Four-dimensional nuclear magnetic resonance spectroscopy of oligosaccharides that correlates 1H-1H ROESY cross peaks to two additional 13C frequency dimensions is reported. The 13C frequencies were introduced by derivatization of all free hydroxyl groups with doubly 13C-labeled acetyl isotags. Pulse sequences were optimized for processing with the filter diagonalization method. The extensive overlap typically observed in 2D ROESY 1H-1H planes was alleviated by resolution of ROESY cross peaks in the two added dimensions associated with the carbon frequencies of the isotags. This enabled the interresidue 1H-1H ROESY cross peaks to be unambiguously assigned hence spatially proximate sugar spin systems across glycosidic bonds could be effectively ascertained. An experiment that selectively amplifies interresidue ROESY 1H-1H cross peaks is also reported. It moves the magnetization of an intraresidue proton normally correlated to a sugar H-1 signal orthogonally along the z axis prior to a Tr-ROESY mixing sequence. This virtually eliminates the incoherent intraresidue ROESY transfer, suppresses coherent TOCSY transfer, and markedly enhances the intensity of interresidue ROESY cross peaks.
Armstrong, Geoffrey S; Bendiak, Brad
2006-07-01
Four-dimensional nuclear magnetic resonance spectroscopy of oligosaccharides that correlates 1H-1H ROESY cross peaks to two additional 13C frequency dimensions is reported. The 13C frequencies were introduced by derivatization of all free hydroxyl groups with doubly 13C-labeled acetyl isotags. Pulse sequences were optimized for processing with the filter diagonalization method. The extensive overlap typically observed in 2D ROESY 1H-1H planes was alleviated by resolution of ROESY cross peaks in the two added dimensions associated with the carbon frequencies of the isotags. This enabled the interresidue 1H-1H ROESY cross peaks to be unambiguously assigned hence spatially proximate sugar spin systems across glycosidic bonds could be effectively ascertained. An experiment that selectively amplifies interresidue ROESY 1H-1H cross peaks is also reported. It moves the magnetization of an intraresidue proton normally correlated to a sugar H-1 signal orthogonally along the z axis prior to a Tr-ROESY mixing sequence. This virtually eliminates the incoherent intraresidue ROESY transfer, suppresses coherent TOCSY transfer, and markedly enhances the intensity of interresidue ROESY cross peaks.
Kasahara, Kota; Fukuda, Ikuo; Nakamura, Haruki
2014-01-01
The dynamic cross correlation (DCC) analysis is a popular method for analyzing the trajectories of molecular dynamics (MD) simulations. However, it is difficult to detect correlative motions that appear transiently in only a part of the trajectory, such as atomic contacts between the side-chains of amino acids, which may rapidly flip. In order to capture these multi-modal behaviors of atoms, which often play essential roles, particularly at the interfaces of macromolecules, we have developed the "multi-modal DCC (mDCC)" analysis. The mDCC is an extension of the DCC and it takes advantage of a Bayesian-based pattern recognition technique. We performed MD simulations for molecular systems modeled from the (Ets1)2-DNA complex and analyzed their results with the mDCC method. Ets1 is an essential transcription factor for a variety of physiological processes, such as immunity and cancer development. Although many structural and biochemical studies have so far been performed, its DNA binding properties are still not well characterized. In particular, it is not straightforward to understand the molecular mechanisms how the cooperative binding of two Ets1 molecules facilitates their recognition of Stromelysin-1 gene regulatory elements. A correlation network was constructed among the essential atomic contacts, and the two major pathways by which the two Ets1 molecules communicate were identified. One is a pathway via direct protein-protein interactions and the other is that via the bound DNA intervening two recognition helices. These two pathways intersected at the particular cytosine bases (C110/C11), interacting with the H1, H2, and H3 helices. Furthermore, the mDCC analysis showed that both pathways included the transient interactions at their intermolecular interfaces of Tyr396-C11 and Ala327-Asn380 in multi-modal motions of the amino acid side chains and the nucleotide backbone. Thus, the current mDCC approach is a powerful tool to reveal these complicated behaviors and scrutinize intermolecular communications in a molecular system.
Kimball, A B; Augustin, M; Gordon, K B; Krueger, G G; Pariser, D; Fakharzadeh, S; Goyal, K; Calabro, S; Lee, S; Lin, R; Li, N; Srivastava, B; Guenther, L
2018-05-10
The interdependence between socioeconomic status and disease control in patients with severe psoriasis is not well understood. To assess whether worse disease control among patients with historically severe psoriasis correlated with negative socioeconomic status, we conducted a cross-sectional analysis from Psoriasis Longitudinal Assessment and Registry (PSOLAR), a large, observational study of psoriasis patients receiving, or eligible to receive, conventional systemic or biologic therapies. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.
Quiroga-Lombard, Claudio S; Hass, Joachim; Durstewitz, Daniel
2013-07-01
Correlations among neurons are supposed to play an important role in computation and information coding in the nervous system. Empirically, functional interactions between neurons are most commonly assessed by cross-correlation functions. Recent studies have suggested that pairwise correlations may indeed be sufficient to capture most of the information present in neural interactions. Many applications of correlation functions, however, implicitly tend to assume that the underlying processes are stationary. This assumption will usually fail for real neurons recorded in vivo since their activity during behavioral tasks is heavily influenced by stimulus-, movement-, or cognition-related processes as well as by more general processes like slow oscillations or changes in state of alertness. To address the problem of nonstationarity, we introduce a method for assessing stationarity empirically and then "slicing" spike trains into stationary segments according to the statistical definition of weak-sense stationarity. We examine pairwise Pearson cross-correlations (PCCs) under both stationary and nonstationary conditions and identify another source of covariance that can be differentiated from the covariance of the spike times and emerges as a consequence of residual nonstationarities after the slicing process: the covariance of the firing rates defined on each segment. Based on this, a correction of the PCC is introduced that accounts for the effect of segmentation. We probe these methods both on simulated data sets and on in vivo recordings from the prefrontal cortex of behaving rats. Rather than for removing nonstationarities, the present method may also be used for detecting significant events in spike trains.
Directly imaging steeply-dipping fault zones in geothermal fields with multicomponent seismic data
Chen, Ting; Huang, Lianjie
2015-07-30
For characterizing geothermal systems, it is important to have clear images of steeply-dipping fault zones because they may confine the boundaries of geothermal reservoirs and influence hydrothermal flow. Elastic reverse-time migration (ERTM) is the most promising tool for subsurface imaging with multicomponent seismic data. However, conventional ERTM usually generates significant artifacts caused by the cross correlation of undesired wavefields and the polarity reversal of shear waves. In addition, it is difficult for conventional ERTM to directly image steeply-dipping fault zones. We develop a new ERTM imaging method in this paper to reduce these artifacts and directly image steeply-dipping fault zones.more » In our new ERTM method, forward-propagated source wavefields and backward-propagated receiver wavefields are decomposed into compressional (P) and shear (S) components. Furthermore, each component of these wavefields is separated into left- and right-going, or downgoing and upgoing waves. The cross correlation imaging condition is applied to the separated wavefields along opposite propagation directions. For converted waves (P-to-S or S-to-P), the polarity correction is applied to the separated wavefields based on the analysis of Poynting vectors. Numerical imaging examples of synthetic seismic data demonstrate that our new ERTM method produces high-resolution images of steeply-dipping fault zones.« less
NASA Astrophysics Data System (ADS)
Choi, A.; Heymans, C.; Blake, C.; Hildebrandt, H.; Duncan, C. A. J.; Erben, T.; Nakajima, R.; Van Waerbeke, L.; Viola, M.
2016-12-01
We determine the accuracy of galaxy redshift distributions as estimated from photometric redshift probability distributions p(z). Our method utilizes measurements of the angular cross-correlation between photometric galaxies and an overlapping sample of galaxies with spectroscopic redshifts. We describe the redshift leakage from a galaxy photometric redshift bin j into a spectroscopic redshift bin I using the sum of the p(z) for the galaxies residing in bin j. We can then predict the angular cross-correlation between photometric and spectroscopic galaxies due to intrinsic galaxy clustering when I ≠ j as a function of the measured angular cross-correlation when I = j. We also account for enhanced clustering arising from lensing magnification using a halo model. The comparison of this prediction with the measured signal provides a consistency check on the validity of using the summed p(z) to determine galaxy redshift distributions in cosmological analyses, as advocated by the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS). We present an analysis of the photometric redshifts measured by CFHTLenS, which overlaps the Baryon Oscillation Spectroscopic Survey (BOSS). We also analyse the Red-sequence Cluster Lensing Survey, which overlaps both BOSS and the WiggleZ Dark Energy Survey. We find that the summed p(z) from both surveys are generally biased with respect to the true underlying distributions. If unaccounted for, this bias would lead to errors in cosmological parameter estimation from CFHTLenS by less than ˜4 per cent. For photometric redshift bins which spatially overlap in 3D with our spectroscopic sample, we determine redshift bias corrections which can be used in future cosmological analyses that rely on accurate galaxy redshift distributions.
Cross-Correlation Asymmetries and Causal Relationships between Stock and Market Risk
Borysov, Stanislav S.; Balatsky, Alexander V.
2014-01-01
We study historical correlations and lead-lag relationships between individual stock risk (volatility of daily stock returns) and market risk (volatility of daily returns of a market-representative portfolio) in the US stock market. We consider the cross-correlation functions averaged over all stocks, using 71 stock prices from the Standard & Poor's 500 index for 1994–2013. We focus on the behavior of the cross-correlations at the times of financial crises with significant jumps of market volatility. The observed historical dynamics showed that the dependence between the risks was almost linear during the US stock market downturn of 2002 and after the US housing bubble in 2007, remaining at that level until 2013. Moreover, the averaged cross-correlation function often had an asymmetric shape with respect to zero lag in the periods of high correlation. We develop the analysis by the application of the linear response formalism to study underlying causal relations. The calculated response functions suggest the presence of characteristic regimes near financial crashes, when the volatility of an individual stock follows the market volatility and vice versa. PMID:25162697
Cross-correlation asymmetries and causal relationships between stock and market risk.
Borysov, Stanislav S; Balatsky, Alexander V
2014-01-01
We study historical correlations and lead-lag relationships between individual stock risk (volatility of daily stock returns) and market risk (volatility of daily returns of a market-representative portfolio) in the US stock market. We consider the cross-correlation functions averaged over all stocks, using 71 stock prices from the Standard & Poor's 500 index for 1994-2013. We focus on the behavior of the cross-correlations at the times of financial crises with significant jumps of market volatility. The observed historical dynamics showed that the dependence between the risks was almost linear during the US stock market downturn of 2002 and after the US housing bubble in 2007, remaining at that level until 2013. Moreover, the averaged cross-correlation function often had an asymmetric shape with respect to zero lag in the periods of high correlation. We develop the analysis by the application of the linear response formalism to study underlying causal relations. The calculated response functions suggest the presence of characteristic regimes near financial crashes, when the volatility of an individual stock follows the market volatility and vice versa.
NASA Astrophysics Data System (ADS)
Mei, Dongcheng; Xie, Chongwei; Zhang, Li
2003-11-01
We study the effects of correlations between additive and multiplicative noise on relaxation time in a bistable system driven by cross-correlated noise. Using the projection-operator method, we derived an analytic expression for the relaxation time Tc of the system, which is the function of additive (α) and multiplicative (D) noise intensities, correlation intensity λ of noise, and correlation time τ of noise. After introducing a noise intensity ratio and a dimensionless parameter R=D/α, and then performing numerical computations, we find the following: (i) For the case of R<1, the relaxation time Tc increases as R increases. (ii) For the cases of R⩾1, there is a one-peak structure on the Tc-R plot and the effects of cross-correlated noise on the relaxation time are very notable. (iii) For the case of R<1, Tc almost does not change with both λ and τ, and for the cases of R⩾1, Tc decreases as λ increases, however Tc increases as τ increases. λ and τ play opposite roles in Tc, i.e., λ enhances the fluctuation decay of dynamical variable and τ slows down the fluctuation decay of dynamical variable.
General ultrafast pulse measurement using the cross-correlation single-shot sonogram technique.
Reid, Derryck T; Garduno-Mejia, Jesus
2004-03-15
The cross-correlation single-shot sonogram technique offers exact pulse measurement and real-time pulse monitoring via an intuitive time-frequency trace whose shape and orientation directly indicate the spectral chirp of an ultrashort laser pulse. We demonstrate an algorithm that solves a fundamental limitation of the cross-correlation sonogram method, namely, that the time-gating operation is implemented using a replica of the measured pulse rather than the ideal delta-function-like pulse. Using a modified principal-components generalized projections algorithm, we experimentally show accurate pulse retrieval of an asymmetric double pulse, a case that is prone to systematic error when one is using the original sonogram retrieval algorithm.
Processing methods for photoacoustic Doppler flowmetry with a clinical ultrasound scanner
NASA Astrophysics Data System (ADS)
Bücking, Thore M.; van den Berg, Pim J.; Balabani, Stavroula; Steenbergen, Wiendelt; Beard, Paul C.; Brunker, Joanna
2018-02-01
Photoacoustic flowmetry (PAF) based on time-domain cross correlation of photoacoustic signals is a promising technique for deep tissue measurement of blood flow velocity. Signal processing has previously been developed for single element transducers. Here, the processing methods for acoustic resolution PAF using a clinical ultrasound transducer array are developed and validated using a 64-element transducer array with a -6 dB detection band of 11 to 17 MHz. Measurements were performed on a flow phantom consisting of a tube (580 μm inner diameter) perfused with human blood flowing at physiological speeds ranging from 3 to 25 mm / s. The processing pipeline comprised: image reconstruction, filtering, displacement detection, and masking. High-pass filtering and background subtraction were found to be key preprocessing steps to enable accurate flow velocity estimates, which were calculated using a cross-correlation based method. In addition, the regions of interest in the calculated velocity maps were defined using a masking approach based on the amplitude of the cross-correlation functions. These developments enabled blood flow measurements using a transducer array, bringing PAF one step closer to clinical applicability.
NASA Astrophysics Data System (ADS)
Gómez-García, C.; Brenguier, F.; Boué, P.; Shapiro, N. M.; Droznin, D. V.; Droznina, S. Ya; Senyukov, S. L.; Gordeev, E. I.
2018-05-01
Continuous noise-based monitoring of seismic velocity changes provides insights into volcanic unrest, earthquake mechanisms and fluid injection in the sub-surface. The standard monitoring approach relies on measuring travel time changes of late coda arrivals between daily and reference noise cross-correlations, usually chosen as stacks of daily cross-correlations. The main assumption of this method is that the shape of the noise correlations does not change over time or, in other terms, that the ambient-noise sources are stationary through time. These conditions are not fulfilled when a strong episodic source of noise, such as a volcanic tremor for example, perturbs the reconstructed Green's function. In this paper we propose a general formulation for retrieving continuous time series of noise-based seismic velocity changes without the requirement of any arbitrary reference cross-correlation function. Instead, we measure the changes between all possible pairs of daily cross-correlations and invert them using different smoothing parameters to obtain the final velocity change curve. We perform synthetic tests in order to establish a general framework for future applications of this technique. In particular, we study the reliability of velocity change measurements versus the stability of noise cross-correlation functions. We apply this approach to a complex dataset of noise cross-correlations at Klyuchevskoy volcanic group (Kamchatka), hampered by loss of data and the presence of highly non-stationary seismic tremors.
A Mathematical View of Water Table Fluctuations in a Shallow Aquifer in Brazil.
Neto, Dagmar C; Chang, Hung K; van Genuchten, Martinus Th
2016-01-01
Detailed monitoring of the groundwater table can provide important data about both short- and long-term aquifer processes, including information useful for estimating recharge and facilitating groundwater modeling and remediation efforts. In this paper, we presents results of 4 years (2002 to 2005) of monitoring groundwater water levels in the Rio Claro Aquifer using observation wells drilled at the Rio Claro campus of São Paulo State University in Brazil. The data were used to follow natural periodic fluctuations in the water table, specifically those resulting from earth tides and seasonal recharge cycles. Statistical analyses included methods of time-series analysis using Fourier analysis, cross-correlation, and R/S analysis. Relationships could be established between rainfall and well recovery, as well as the persistence and degree of autocorrelation of the water table variations. We further used numerical solutions of the Richards equation to obtain estimates of the recharge rate and seasonable groundwater fluctuations. Seasonable soil moisture transit times through the vadose zone obtained with the numerical solution were very close to those obtained with the cross-correlation analysis. We also employed a little-used deep drainage boundary condition to obtain estimates of seasonable water table fluctuations, which were found to be consistent with observed transient groundwater levels during the period of study. © 2015, National Ground Water Association.
Patient Safety Incidents and Nursing Workload 1
Carlesi, Katya Cuadros; Padilha, Kátia Grillo; Toffoletto, Maria Cecília; Henriquez-Roldán, Carlos; Juan, Monica Andrea Canales
2017-01-01
ABSTRACT Objective: to identify the relationship between the workload of the nursing team and the occurrence of patient safety incidents linked to nursing care in a public hospital in Chile. Method: quantitative, analytical, cross-sectional research through review of medical records. The estimation of workload in Intensive Care Units (ICUs) was performed using the Therapeutic Interventions Scoring System (TISS-28) and for the other services, we used the nurse/patient and nursing assistant/patient ratios. Descriptive univariate and multivariate analysis were performed. For the multivariate analysis we used principal component analysis and Pearson correlation. Results: 879 post-discharge clinical records and the workload of 85 nurses and 157 nursing assistants were analyzed. The overall incident rate was 71.1%. It was found a high positive correlation between variables workload (r = 0.9611 to r = 0.9919) and rate of falls (r = 0.8770). The medication error rates, mechanical containment incidents and self-removal of invasive devices were not correlated with the workload. Conclusions: the workload was high in all units except the intermediate care unit. Only the rate of falls was associated with the workload. PMID:28403334
Complex Correlation Calculation of e-H Total Cross Sections
NASA Technical Reports Server (NTRS)
Bhatia, A. K.; Temkin, A.; Fisher, Richard R. (Technical Monitor)
2001-01-01
Calculation of e-H total and elastic partial wave cross sections is being carried out using the complex correlation variational T-matrix method. In this preliminary study, elastic partial wave phase shifts are calculated with the correlation functions which are confined to be real. In that case the method reduces to the conventional optical potential approach with projection operators. The number of terms in the Hylleraas-type wave function for the S phase shifts is 95 while for the S it is 56, except for k=0.8 where it is 84. Our results, which are rigorous lower bounds, are given. They are seen to be in general agreement with those of Schwartz, but they are of 0 greater accuracy and outside of his error limits for k=0.3 and 0.4 for S. The main aim of this approach' is the application to higher energy scattering. By virtue of the complex correlation functions, the T matrix is not unitary so that elastic and total scattering cross sections are independent of each other. Our results will be compared specifically with those of Bray and Stelbovics.
Complex Correlation Calculation of e(-) - H Total Cross Sections
NASA Technical Reports Server (NTRS)
Bhatia, A. K.; Temkin, A.; Fisher, Richard R. (Technical Monitor)
2001-01-01
Calculation of e(-) - H total and elastic partial wave cross sections is being carried out using the complex correlation variational T-matrix method. In this preliminary study, elastic partial wave phase shifts are calculated with the correlation functions which are confined to be real. In that case the method reduces to the conventional optical potential approach with 2 projection operators. The number of terms in the Hylleraas-type wave function for the S-1 phase shifts is 95 while for the S-3 it is 56, except for k = 0.8 where it is 84. Our results, which are rigorous lower bounds, are seen to be in general agreement with those of Schwartz, but they are of greater accuracy and outside of his error limits for k = 0.3 and 0.4 for S-1. The main aim of this approach is the application to higher energy scattering. By virtue of the complex correlation functions, the T-matrix is not unitary so that elastic and total scattering cross sections are independent of each other. Our results will be compared specifically with those of Bray and Stelbovics.
Barua, Nabanita; Sitaraman, Chitra; Goel, Sonu; Chakraborti, Chandana; Mukherjee, Sonai; Parashar, Hemandra
2016-01-01
Context: Analysis of diagnostic ability of macular ganglionic cell complex and retinal nerve fiber layer (RNFL) in glaucoma. Aim: To correlate functional and structural parameters and comparing predictive value of each of the structural parameters using Fourier-domain (FD) optical coherence tomography (OCT) among primary open angle glaucoma (POAG) and ocular hypertension (OHT) versus normal population. Setting and Design: Single centric, cross-sectional study done in 234 eyes. Materials and Methods: Patients were enrolled in three groups: POAG, ocular hypertensive and normal (40 patients in each group). After comprehensive ophthalmological examination, patients underwent standard automated perimetry and FD-OCT scan in optic nerve head and ganglion cell mode. The relationship was assessed by correlating ganglion cell complex (GCC) parameters with mean deviation. Results were compared with RNFL parameters. Statistical Analysis: Data were analyzed with SPSS, analysis of variance, t-test, Pearson's coefficient, and receiver operating curve. Results: All parameters showed strong correlation with visual field (P < 0.001). Inferior GCC had highest area under curve (AUC) for detecting glaucoma (0.827) in POAG from normal population. However, the difference was not statistically significant (P > 0.5) when compared with other parameters. None of the parameters showed significant diagnostic capability to detect OHT from normal population. In diagnosing early glaucoma from OHT and normal population, only inferior GCC had statistically significant AUC value (0.715). Conclusion: In this study, GCC and RNFL parameters showed equal predictive capability in perimetric versus normal group. In early stage, inferior GCC was the best parameter. In OHT population, single day cross-sectional imaging was not valuable. PMID:27221682
NASA Astrophysics Data System (ADS)
Huamán Bustamante, Samuel G.; Cavalcanti Pacheco, Marco A.; Lazo Lazo, Juan G.
2018-07-01
The method we propose in this paper seeks to estimate interface displacements among strata related with reflection seismic events, in comparison to the interfaces at other reference points. To do so, we search for reflection events in the reference point of a second seismic trace taken from the same 3D survey and close to a well. However, the nature of the seismic data introduces uncertainty in the results. Therefore, we perform an uncertainty analysis using the standard deviation results from several experiments with cross-correlation of signals. To estimate the displacements of events in depth between two seismic traces, we create a synthetic seismic trace with an empirical wavelet and the sonic log of the well, close to the second seismic trace. Then, we relate the events of the seismic traces to the depth of the sonic log. Finally, we test the method with data from the Namorado Field in Brazil. The results show that the accuracy of the event estimated depth depends on the results of parallel cross-correlation, primarily those from the procedures used in the integration of seismic data with data from the well. The proposed approach can correctly identify several similar events in two seismic traces without requiring all seismic traces between two distant points of interest to correlate strata in the subsurface.
Physical activity level and fall risk among community-dwelling older adults.
Low, Sok Teng; Balaraman, Thirumalaya
2017-07-01
[Purpose] To find the physical activity level and fall risk among the community-dwelling Malaysian older adults and determine the correlation between them. [Subjects and Methods] A cross-sectional study was conducted in which, the physical activity level was evaluated using the Rapid Assessment of Physical Activity questionnaire and fall risk with Fall Risk Assessment Tool. Subjects recruited were 132 community-dwelling Malaysian older adults using the convenience sampling method. [Results] The majority of the participants were under the category of under-active regular light-activities and most of them reported low fall risk. The statistical analysis using Fisher's exact test did not show a significant correlation between physical activity level and fall risk. [Conclusion] The majority of community-dwelling Malaysian older adults are performing some form of physical activity and in low fall risk category. But this study did not find any significant correlation between physical activity level and fall risk among community-dwelling older adults in Malaysia.
NASA Astrophysics Data System (ADS)
Rak, Rafał; Drożdż, Stanisław; Kwapień, Jarosław; Oświȩcimka, Paweł
2015-11-01
We consider a few quantities that characterize trading on a stock market in a fixed time interval: logarithmic returns, volatility, trading activity (i.e., the number of transactions), and volume traded. We search for the power-law cross-correlations among these quantities aggregated over different time units from 1 min to 10 min. Our study is based on empirical data from the American stock market consisting of tick-by-tick recordings of 31 stocks listed in Dow Jones Industrial Average during the years 2008-2011. Since all the considered quantities except the returns show strong daily patterns related to the variable trading activity in different parts of a day, which are the most evident in the autocorrelation function, we remove these patterns by detrending before we proceed further with our study. We apply the multifractal detrended cross-correlation analysis with sign preserving (MFCCA) and show that the strongest power-law cross-correlations exist between trading activity and volume traded, while the weakest ones exist (or even do not exist) between the returns and the remaining quantities. We also show that the strongest cross-correlations are carried by those parts of the signals that are characterized by large and medium variance. Our observation that the most convincing power-law cross-correlations occur between trading activity and volume traded reveals the existence of strong fractal-like coupling between these quantities.
A cross-correlation study of the Fermi-LAT γ-ray diffuse extragalactic signal
Xia, Jun -Qing; Cuoco, Alessandro; Branchini, Enzo; ...
2011-09-12
In this work, starting from 21 months of data from the Fermi Large Area Telescope (LAT), we derive maps of the residual isotropic γ-ray emission, a relevant fraction of which is expected to be contributed by the extragalactic diffuse γ-ray background (EGB). We search for the auto-correlation signals in the above γ-ray maps and for the cross-correlation signal with the angular distribution of different classes of objects that trace the large-scale structure of the Universe. We compute the angular two-point auto-correlation function of the residual Fermi-LAT maps at energies E > 1 GeV, E > 3 GeV and E >more » 30 GeV well above the Galactic plane and find no significant correlation signal. This is, indeed, what is expected if the EGB were contributed by BL Lacertae (BLLacs), Flat Spectrum Radio Quasars (FSRQs) or star-forming galaxies, since, in this case, the predicted signal is very weak. Then, we search for the Integrated Sachs–Wolfe (ISW) signature by cross-correlating the Fermi-LAT maps with the 7-year Wilkinson Microwave Anisotropy Probe ( WMAP7) cosmic microwave background map. We find a cross-correlation consistent with zero, even though the expected signal is larger than that of the EGB auto-correlation. Lastly, in an attempt to constrain the nature of the γ-ray background, we cross-correlate the Fermi-LAT maps with the angular distributions of objects that may contribute to the EGB: quasi-stellar objects (QSOs) in the Sloan Digital Sky Survey Data Release 6 (SDSS-DR6) catalogue, NRAO VLA Sky Survey (NVSS) galaxies, Two Micron All Sky Survey (2MASS) galaxies and Luminous Red Galaxies (LRGs) in the SDSS catalogue. The cross-correlation is always consistent with zero, in agreement with theoretical expectations, but we find (with low statistical significance) some interesting features that may indicate that some specific classes of objects contribute to the EGB. A χ 2 analysis confirms that the correlation properties of the 21-month data do not provide strong constraints of the EGB origin. However, the results suggest that the situation will significantly improve with the 5- and 10-yr Fermi-LAT data. In future, the EGB analysis will then allow placing significant constraints on the nature of the EGB and might provide, in addition, a detection of the ISW signal.« less
Aloba, Olutayo; Ajao, Olayinka; Alimi, Taiwo; Esan, Olufemi
2016-01-01
Objectives: To examine the construct and correlates of hopelessness among family caregivers of Nigerian psychiatric patients. Materials and Methods: This is a cross-sectional, descriptive study involving 264 family caregiver-patients’ dyads recruited from two university teaching hospitals psychiatric clinics in Southwestern Nigeria. Results: Exploratory factor analysis revealed a two-factor 9-item model of the Beck Hopelessness Scale (BHS) among the family caregivers. Confirmatory factor analysis of the model revealed satisfactory indices of fitness (goodness of fit index = 0.97, comparative fit index = 0.96, Chi-square/degree of freedom (CMIN/DF) = 1.60, root mean square error of approximation = 0.048, expected cross-validation index = 0.307, and standardized root mean residual = 0.005). Reliability of the scale was modestly satisfactory (Cronbach's alpha 0.72). Construct validity of scale was supported by significant correlations with the family caregivers’ scores on the Zarit Burden Interview, mini international neuropsychiatric interview suicidality module, General Health Questionnaire-12 (GHQ-12), and Patient Health Questionnaire-9. The greatest variance in the family caregivers’ scores on the BHS was contributed by their scores on the psychological distress scale (GHQ-12). Conclusions: The BHS has adequate psychometric properties among Nigerian psychiatric patients’ family caregivers. There is the need to pay attention to the psychological well-being of the family caregivers of Nigerian psychiatric patients. PMID:28163498
Core Noise Diagnostics of Turbofan Engine Noise Using Correlation and Coherence Functions
NASA Technical Reports Server (NTRS)
Miles, Jeffrey H.
2009-01-01
Cross-correlation and coherence functions are used to look for periodic acoustic components in turbofan engine combustor time histories, to investigate direct and indirect combustion noise source separation based on signal propagation time delays, and to provide information on combustor acoustics. Using the cross-correlation function, time delays were identified in all cases, clearly indicating the combustor is the source of the noise. In addition, unfiltered and low-pass filtered at 400 Hz signals had a cross-correlation time delay near 90 ms, while the low-pass filtered at less than 400 Hz signals had a cross-correlation time delay longer than 90 ms. Low-pass filtering at frequencies less than 400 Hz partially removes the direct combustion noise signals. The remainder includes the indirect combustion noise signal, which travels more slowly because of the dependence on the entropy convection velocity in the combustor. Source separation of direct and indirect combustion noise is demonstrated by proper use of low-pass filters with the cross-correlation function for a range of operating conditions. The results may lead to a better idea about the acoustics in the combustor and may help develop and validate improved reduced-order physics-based methods for predicting direct and indirect combustion noise.
Wu, Wei; Chen, Gui-Yun; Wu, Ming-Qing; Yu, Zhen-Wei; Chen, Kun-Jie
2017-03-20
A two-dimensional (2D) scatter plot method based on the 2D hyperspectral correlation spectrum is proposed to detect diluted blood, bile, and feces from the cecum and duodenum on chicken carcasses. First, from the collected hyperspectral data, a set of uncontaminated regions of interest (ROIs) and four sets of contaminated ROIs were selected, whose average spectra were treated as the original spectrum and influenced spectra, respectively. Then, the difference spectra were obtained and used to conduct correlation analysis, from which the 2D hyperspectral correlation spectrum was constructed using the analogy method of 2D IR correlation spectroscopy. Two maximum auto-peaks and a pair of cross peaks appeared at 656 and 474 nm. Therefore, 656 and 474 nm were selected as the characteristic bands because they were most sensitive to the spectral change induced by the contaminants. The 2D scatter plots of the contaminants, clean skin, and background in the 474- and 656-nm space were used to distinguish the contaminants from the clean skin and background. The threshold values of the 474- and 656-nm bands were determined by receiver operating characteristic (ROC) analysis. According to the ROC results, a pixel whose relative reflectance at 656 nm was greater than 0.5 and relative reflectance at 474 nm was lower than 0.3 was judged as a contaminated pixel. A region with more than 50 pixels identified was marked in the detection graph. This detection method achieved a recognition rate of up to 95.03% at the region level and 31.84% at the pixel level. The false-positive rate was only 0.82% at the pixel level. The results of this study confirm that the 2D scatter plot method based on the 2D hyperspectral correlation spectrum is an effective method for detecting diluted contaminants on chicken carcasses.
Determination of differential arrival times by cross-correlating worldwide seismological data
NASA Astrophysics Data System (ADS)
Godano, M.; Nolet, G.; Zaroli, C.
2012-12-01
Cross-correlation delays are the preferred body wave observables in global tomography. Heterogeneity is the main factor influencing delay times found by cross-correlation. Not only the waveform, but also the arrival time itself is affected by differences in seismic velocity encountered along the way. An accurate method for estimating differential times of seismic arrivals across a regional array by cross-correlation was developed by VanDecar and Crosson [1990]. For the estimation of global travel time delays in different frequency bands, Sigloch and Nolet [2006] developed a method for the estimation of body wave delays using a matched filter, which requires the separate estimation of the source time function. Sigloch et al. [2008] found that waveforms often cluster in and opposite the direction of rupture propagation on the fault, confirming that the directivity effect is a major factor in shaping the waveform of large events. We propose a generalization of the VanDecar-Crosson method to which we add a correction for the directivity effect in the seismological data. The new method allows large events to be treated without the need to estimate the source time function for the computation of a matched synthetic waveform. The procedure consists in (1) the detection of the directivity effect in the data and the determination of a rupture model (unilateral or bilateral) explaining the differences in pulse duration among the stations, (2) the determination of an apparent fault rupture length explaining the pulse durations, (3) the removal of the delay due to the directivity effect in the pulse duration , by stretching or contracting the seismograms for directive and anti-directive stations respectively and (4) the application of a generalized VanDecar and Crosson method using only delays between pairs of stations that have an acceptable correlation coefficient. We validate our method by performing tests on synthetic data. Results show that the error between theoretical and measured differential arrival time are significantly reduced for the corrected data. We illustrate our method on data from several real earthquakes.
Correlates of Incarceration Among Young Methamphetamine Users in Chiang Mai, Thailand
Thomson, Nicholas; Sutcliffe, Catherine G.; Sirirojn, Bangorn; Keawvichit, Rassamee; Wongworapat, Kanlaya; Sintupat, Kamolrawee; Aramrattana, Apinun
2009-01-01
Objectives. We examined correlates of incarceration among young methamphetamine users in Chiang Mai, Thailand in 2005 to 2006. Methods. We conducted a cross-sectional study among 1189 young methamphetamine users. Participants were surveyed about their recent drug use, sexual behaviors, and incarceration. Biological samples were obtained to test for sexually transmitted and viral infections. Results. Twenty-two percent of participants reported ever having been incarcerated. In multivariate analysis, risk behaviors including frequent public drunkenness, starting to use illicit drugs at an early age, involvement in the drug economy, tattooing, injecting drugs, and unprotected sex were correlated with a history of incarceration. HIV, HCV, and herpes simplex virus type 2 (HSV-2) infection were also correlated with incarceration. Conclusions. Incarcerated methamphetamine users are engaging in behaviors and being exposed to environments that put them at increased risk of infection and harmful practices. Alternatives to incarceration need to be explored for youths. PMID:18923109
Using waveform cross correlation for automatic recovery of aftershock sequences
NASA Astrophysics Data System (ADS)
Bobrov, Dmitry; Kitov, Ivan; Rozhkov, Mikhail
2017-04-01
Aftershock sequences of the largest earthquakes are difficult to recover. There can be several hundred mid-sized aftershocks per hour within a few hundred km from each other recorded by the same stations. Moreover, these events generate thousands of reflected/refracted phases having azimuth and slowness close to those from the P-waves. Therefore, aftershock sequences with thousands of events represent a major challenge for automatic and interactive processing at the International Data Centre (IDC) of the Comprehensive Nuclear-Test-Ban Organization (CTBTO). Standard methods of detection and phase association do not use all information contained in signals. As a result, wrong association of the first and later phases, both regular and site specific, produces enormous number of wrong event hypotheses and destroys valid event hypotheses in automatic IDC processing. In turn, the IDC analysts have to reject false and recreate valid hypotheses wasting precious human resources. At the current level of the IDC catalogue completeness, the method of waveform cross correlation (WCC) can resolve most of detection and association problems fully utilizing the similarity of waveforms generated by aftershocks. Array seismic stations of the International monitoring system (IMS) can enhance the performance of the WCC method: reduce station-specific detection thresholds, allow accurate estimate of signal attributes, including relative magnitude, and effectively suppress irrelevant arrivals. We have developed and tested a prototype of an aftershock tool matching all IDC processing requirements and merged it with the current IDC pipeline. This tool includes creation of master events consisting of real or synthetic waveform templates at ten and more IMS stations; cross correlation (CC) of real-time waveforms with these templates, association of arrivals detected at CC-traces in event hypotheses; building events matching the IDC quality criteria; and resolution of conflicts between events hypotheses created by neighboring master-events. The final cross correlation standard event lists (XSEL) is a start point for interactive analysis with standard tools. We present select results for the biggest earthquakes, like Sumatra 2004 and Tohoku 2011, as well as for several smaller events with hundreds of aftershocks. The sensitivity and resolution of the aftershock tool is demonstrated on the example of mb=2.2 aftershock found after the September 9, 2016 DPRK test.
Tsartsalis, Stergios; Tournier, Benjamin B; Habiby, Selim; Ben Hamadi, Meriem; Barca, Cristina; Ginovart, Nathalie; Millet, Philippe
2018-04-30
SPECT imaging with two radiotracers at the same time is feasible if two different radioisotopes are employed, given their distinct energy emission spectra. In the case of 123 I and 125 I, dual SPECT imaging is not straightforward: 123 I emits photons at a principal energy emission spectrum of 143.1-179.9 keV. However, it also emits at a secondary energy spectrum (15-45 keV) that overlaps with the one of 125 I and the resulting cross-talk of emissions impedes the accurate quantification of 125 I. In this paper, we describe three different methods for the correction of this cross-talk and the simultaneous in vivo [ 123 I]IBZM and [ 125 I]R91150 imaging of D 2/3 and 5-HT 2A receptors in the rat brain. Three methods were evaluated for the correction of the effect of cross-talk in a series of simultaneous, [ 123 I]IBZM and [ 125 I]R91150 in vivo and phantom SPECT scans. Method 1 employs a dual-energy window (DEW) approach, in which the cross-talk on 125 I is considered a stable fraction of the energy emitted from 123 I at the principal emission spectrum. The coefficient describing the relationship between the emission of 123 I at the principal and the secondary spectrum was estimated from a series of single-radiotracer [ 123 I]IBZM SPECT studies. In Method 2, spectral factor analysis (FA) is applied to separate the radioactivity from 123 I and 125 I on the basis of their distinct emission patterns across the energy spectrum. Method 3 uses a modified simplified reference tissue model (SRTM C ) to describe the kinetics of [ 125 I]R91150. It includes the coefficient describing the cross-talk on 125 I from 123 I in the model parameters. The results of the correction of cross-talk on [ 125 I]R91150 binding potential (BP ND ) with each of the three methods, using cerebellum as the reference region, were validated against the results of a series of single-radiotracer [ 123 I]R91150 SPECT studies. In addition, the DEW approach (Method 1), considered to be the most straightforward to apply of the three, was further applied in a dual-radiotracer SPECT study of the relationship between D 2/3 and 5-HT 2A receptor binding in the striatum, both at the voxel and at the regional level. Average regional BP ND values of [ 125 I]R91150, estimated on the cross-talk corrected dual-radiotracer SPECT studies provided satisfactory correlations with the BP ND values for [ 123 I]R91150 from single-radiotracer studies: r = 0.92, p < 0.001 for Method 1, r = 0.92, p < 0.001 for Method 2, r = 0.92, p < 0.001, for Method 3. The coefficient describing the ratio of the 123 I-emitted radioactivity at the 125 I-emission spectrum to the radioactivity that it emits at its principal emission spectrum was 0.34 in vivo. Dual-radiotracer in vivo SPECT studies corrected with Method 1 demonstrated a positive correlation between D 2/3 and 5-HT 2A receptor binding in the rat nucleus accumbens at the voxel level. At the VOI-level, a positive correlation was confirmed in the same region (r = 0.78, p < 0.01). Dual-radiotracer SPECT imaging using 123 I and 125 I-labeled radiotracers is feasible if the cross-talk of 123 I on the 125 I emission spectrum is properly corrected. The most straightforward approach is Method 1, in which a fraction (34%) of the radioactivity emitted from 123 I at its principal energy spectrum is subtracted from the measured radioactivity at the spectrum of 125 I. With this method, a positive correlation between the binding of [ 123 I]IBZM and [ 125 I]R91150 was demonstrated in the rat nucleus accumbens. This result highlights the interest of dual-radiotracer SPECT imaging to study multiple neurotransmitter systems at the same time and under the same biological conditions. Copyright © 2018 Elsevier Inc. All rights reserved.
NASA Technical Reports Server (NTRS)
Ganga, Ken; Cheng, ED; Meyer, Stephan; Page, Lyman
1993-01-01
This letter describes results of a cross-correlation between the 170 GHz partial-sky survey, made with a 3.8 deg beam balloon-borne instrument, and the COBE DMR 'Fit Technique' reduced galaxy all-sky map with a beam of 7 deg. The strong correlation between the data sets implies that the observed structure is consistent with thermal variations in a 2.7 K emitter. A chi-square analysis applied to the correlation function rules out the assumption that there is no structure in either of the two maps. A second test shows that if the DMR map has structure but the 170 GHz map does not, the probability of obtaining the observed correlation is small. Further analyses support the assumption that both maps have structure and that the 170 GHz-DMR cross-correlation is consistent with the analogous DMR correlation function. Maps containing various combinations of noise and Harrison-Zel'dovich power spectra are simulated and correlated to reinforce the result. The correlation provides compelling evidence that both instruments have observed fluctuations consistent with anisotropies in the cosmic microwave background.
INTERNAL PROPER MOTIONS IN THE ESKIMO NEBULA
DOE Office of Scientific and Technical Information (OSTI.GOV)
García-Díaz, Ma. T.; Gutiérrez, L.; Steffen, W.
We present measurements of internal proper motions at more than 500 positions of NGC 2392, the Eskimo Nebula, based on images acquired with WFPC2 on board the Hubble Space Telescope at two epochs separated by 7.695 yr. Comparisons of the two observations clearly show the expansion of the nebula. We measured the amplitude and direction of the motion of local structures in the nebula by determining their relative shift during that interval. In order to assess the potential uncertainties in the determination of proper motions in this object, in general, the measurements were performed using two different methods, used previously in themore » literature. We compare the results from the two methods, and to perform the scientific analysis of the results we choose one, the cross-correlation method, because it is more reliable. We go on to perform a ''criss-cross'' mapping analysis on the proper motion vectors, which helps in the interpretation of the velocity pattern. By combining our results of the proper motions with radial velocity measurements obtained from high resolution spectroscopic observations, and employing an existing 3D model, we estimate the distance to the nebula to be 1.3 kpc.« less
NASA Astrophysics Data System (ADS)
DeWalle, David R.; Boyer, Elizabeth W.; Buda, Anthony R.
2016-12-01
Forecasts of ecosystem changes due to variations in atmospheric emissions policies require a fundamental understanding of lag times between changes in chemical inputs and watershed response. Impacts of changes in atmospheric deposition in the United States have been documented using national and regional long-term environmental monitoring programs beginning several decades ago. Consequently, time series of weekly NADP atmospheric wet deposition and monthly EPA-Long Term Monitoring stream chemistry now exist for much of the Northeast which may provide insights into lag times. In this study of Appalachian forest basins, we estimated lag times for S, N and Cl by cross-correlating monthly data from four pairs of stream and deposition monitoring sites during the period from 1978 to 2012. A systems or impulse response function approach to cross-correlation was used to estimate lag times where the input deposition time series was pre-whitened using regression modeling and the stream response time series was filtered using the deposition regression model prior to cross-correlation. Cross-correlations for S were greatest at annual intervals over a relatively well-defined range of lags with the maximum correlations occurring at mean lags of 48 months. Chloride results were similar but more erratic with a mean lag of 57 months. Few high-correlation lags for N were indicated. Given the growing availability of atmospheric deposition and surface water chemistry monitoring data and our results for four Appalachian basins, further testing of cross-correlation as a method of estimating lag times on other basins appears justified.
Fast first arrival picking algorithm for noisy microseismic data
NASA Astrophysics Data System (ADS)
Kim, Dowan; Byun, Joongmoo; Lee, Minho; Choi, Jihoon; Kim, Myungsun
2017-01-01
Most microseismic events occur during hydraulic fracturing. Thus microseismic monitoring, by recording seismic waves from microseismic events, is one of the best methods for locating the positions of hydraulic fractures. However, since microseismic events have very low energy, the data often have a low signal-to-noise ratio (S/N ratio) and it is not easy to pick the first arrival time. In this study, we suggest a new fast picking method optimised for noisy data using cross-correlation and stacking. In this method, a reference trace is selected and the time differences between the first arrivals of the reference trace and those of the other traces are computed by cross-correlation. Then, all traces are aligned with the reference trace by time shifting, and the aligned traces are summed together to produce a stacked reference trace that has a considerably improved S/N ratio. After the first arrival time of the stacked reference trace is picked, the first arrival time of each trace is calculated automatically using the time differences obtained in the cross-correlation process. In experiments with noisy synthetic data and field data, this method produces more reliable results than the traditional method, which picks the first arrival time of each noisy trace separately. In addition, the computation time is dramatically reduced.
Li, Zhenghua; Cheng, Fansheng; Xia, Zhining
2011-01-01
The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.
The Global Pattern of Urbanization and Economic Growth: Evidence from the Last Three Decades
Chen, Mingxing; Zhang, Hua; Liu, Weidong; Zhang, Wenzhong
2014-01-01
The relationship between urbanization and economic growth has been perplexing. In this paper, we identify the pattern of global change and the correlation of urbanization and economic growth, using cross-sectional, panel estimation and geographic information systems (GIS) methods. The analysis has been carried out on a global geographical scale, while the timescale of the study spans the last 30 years. The data shows that urbanization levels have changed substantially during these three decades. Empirical findings from cross-sectional data and panel data support the general notion of close links between urbanization levels and GDP per capita. However, we also present significant evidence that there is no correlation between urbanization speed and economic growth rate at the global level. Hence, we conclude that a given country cannot obtain the expected economic benefits from accelerated urbanization, especially if it takes the form of government-led urbanization. In addition, only when all facets are taken into consideration can we fully assess the urbanization process. PMID:25099392
The global pattern of urbanization and economic growth: evidence from the last three decades.
Chen, Mingxing; Zhang, Hua; Liu, Weidong; Zhang, Wenzhong
2014-01-01
The relationship between urbanization and economic growth has been perplexing. In this paper, we identify the pattern of global change and the correlation of urbanization and economic growth, using cross-sectional, panel estimation and geographic information systems (GIS) methods. The analysis has been carried out on a global geographical scale, while the timescale of the study spans the last 30 years. The data shows that urbanization levels have changed substantially during these three decades. Empirical findings from cross-sectional data and panel data support the general notion of close links between urbanization levels and GDP per capita. However, we also present significant evidence that there is no correlation between urbanization speed and economic growth rate at the global level. Hence, we conclude that a given country cannot obtain the expected economic benefits from accelerated urbanization, especially if it takes the form of government-led urbanization. In addition, only when all facets are taken into consideration can we fully assess the urbanization process.
Vijayaraj, Ramadoss; Devi, Mekapothula Lakshmi Vasavi; Subramanian, Venkatesan; Chattaraj, Pratim Kumar
2012-06-01
Three-dimensional quantitative structure activity relationship (3D-QSAR) study has been carried out on the Escherichia coli DHFR inhibitors 2,4-diamino-5-(substituted-benzyl)pyrimidine derivatives to understand the structural features responsible for the improved potency. To construct highly predictive 3D-QSAR models, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods were used. The predicted models show statistically significant cross-validated and non-cross-validated correlation coefficient of r2 CV and r2 nCV, respectively. The final 3D-QSAR models were validated using structurally diverse test set compounds. Analysis of the contour maps generated from CoMFA and CoMSIA methods reveals that the substitution of electronegative groups at the first and second position along with electropositive group at the third position of R2 substitution significantly increases the potency of the derivatives. The results obtained from the CoMFA and CoMSIA study delineate the substituents on the trimethoprim analogues responsible for the enhanced potency and also provide valuable directions for the design of new trimethoprim analogues with improved affinity. © 2012 John Wiley & Sons A/S.
Marshall, Brendan M; Moran, Kieran A
2015-12-01
Previous studies investigating the biomechanical factors associated with maximal countermovement jump height have typically used cross-sectional data. An alternative but less common approach is to use pre-to-posttraining change data, where the relationship between an improvement in jump height and a change in a factor is examined more directly. Our study compared the findings of these approaches. Such an evaluation is necessary because cross-sectional studies are currently a primary source of information for coaches when examining what factors to train to enhance performance. The countermovement jump of 44 males was analyzed before and after an 8-week training intervention. Correlations with jump height were calculated using both cross-sectional (pretraining data only) and pre-to-posttraining change data. Eight factors identified in the cross-sectional analysis were not significantly correlated with a change in jump height in the pre-to-post analysis. Additionally, only 6 of 11 factors identified in the pre-to-post analysis were identified in the cross-sectional analysis. These findings imply that (a) not all factors identified in a cross-sectional analysis may be critical to jump height improvement and (b) cross-sectional analyses alone may not provide an insight into all of the potential factors to train to enhance jump height. Coaches must be aware of these limitations when examining cross-sectional studies to identify factors to train to enhance jump ability. Additional findings highlight that although exercises prescribed to improve jump height should aim to enhance concentric power production at all joints, a particular emphasis on enhancing hip joint peak power may be warranted.
The q-dependent detrended cross-correlation analysis of stock market
NASA Astrophysics Data System (ADS)
Zhao, Longfeng; Li, Wei; Fenu, Andrea; Podobnik, Boris; Wang, Yougui; Stanley, H. Eugene
2018-02-01
Properties of the q-dependent cross-correlation matrices of the stock market have been analyzed by using random matrix theory and complex networks. The correlation structures of the fluctuations at different magnitudes have unique properties. The cross-correlations among small fluctuations are much stronger than those among large fluctuations. The large and small fluctuations are dominated by different groups of stocks. We use complex network representation to study these q-dependent matrices and discover some new identities. By utilizing those q-dependent correlation-based networks, we are able to construct some portfolios of those more independent stocks which consistently perform better. The optimal multifractal order for portfolio optimization is around q = 2 under the mean-variance portfolio framework, and q\\in[2, 6] under the expected shortfall criterion. These results have deepened our understanding regarding the collective behavior of the complex financial system.
Liang, Yunyun; Liu, Sanyang; Zhang, Shengli
2016-12-01
Apoptosis, or programed cell death, plays a central role in the development and homeostasis of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful for understanding the apoptosis mechanism. The prediction of subcellular localization of an apoptosis protein is still a challenging task, and existing methods mainly based on protein primary sequences. In this paper, we introduce a new position-specific scoring matrix (PSSM)-based method by using detrended cross-correlation (DCCA) coefficient of non-overlapping windows. Then a 190-dimensional (190D) feature vector is constructed on two widely used datasets: CL317 and ZD98, and support vector machine is adopted as classifier. To evaluate the proposed method, objective and rigorous jackknife cross-validation tests are performed on the two datasets. The results show that our approach offers a novel and reliable PSSM-based tool for prediction of apoptosis protein subcellular localization. Copyright © 2016 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Lu, Xinsheng; Sun, Xinxin; Ge, Jintian
2017-05-01
This paper investigates the dynamic relationship between Japanese Yen exchange rates and market anxiety during the period from January 5, 1998 to April 18, 2016. A quantitative technique of multifractal detrended cross-correlation analysis (MF-DCCA) is used to explore the multifractal features of the cross-correlations between USD/JPY, AUD/JPY exchange rates and the market anxiety gauge VIX. The investigation shows that the causal relationship between Japanese Yen exchange rates and VIX are bidirectional in general, and the cross-correlations between the two sets of time series are multifractal. Strong evidence suggests that the cross-correlation exponents tend to exhibit different volatility patterns in response to diverse external shocks such as financial distress and widening in interest rate spread, suggesting that the cross-correlated behavior between Japanese Yen exchange rates and VIX are susceptible to economic uncertainties and risks. In addition, the performances of two market anxiety gauges, the VIX and the TED spread, are compared and the sources of multifractality are also traced. Thus, this paper contributes to the literature by shedding light on the unique driving forces of the Yen exchange rate fluctuations in the international foreign exchange market.
NASA Astrophysics Data System (ADS)
Abramowicz, H.; Abt, I.; Adamczyk, L.; Adamus, M.; Aggarwal, R.; Andreev, V.; Antonelli, S.; Aushev, V.; Baghdasaryan, A.; Begzsuren, K.; Behnke, O.; Behrens, U.; Belousov, A.; Bertolin, A.; Bloch, I.; Bolz, A.; Boudry, V.; Brandt, G.; Brisson, V.; Britzger, D.; Brock, I.; Brook, N. H.; Brugnera, R.; Bruni, A.; Buniatyan, A.; Bussey, P. J.; Bylinkin, A.; Bystritskaya, L.; Caldwell, A.; Campbell, A. J.; Avila, K. B. Cantun; Capua, M.; Catterall, C. D.; Cerny, K.; Chekelian, V.; Chwastowski, J.; Ciborowski, J.; Ciesielski, R.; Contreras, J. G.; Cooper-Sarkar, A. M.; Corradi, M.; Cvach, J.; Dainton, J. B.; Daum, K.; Dementiev, R. K.; Devenish, R. C. E.; Diaconu, C.; Dobre, M.; Dusini, S.; Eckerlin, G.; Egli, S.; Elsen, E.; Favart, L.; Fedotov, A.; Feltesse, J.; Fleischer, M.; Fomenko, A.; Foster, B.; Gallo, E.; Garfagnini, A.; Gayler, J.; Geiser, A.; Gizhko, A.; Gladilin, L. K.; Goerlich, L.; Gogitidze, N.; Golubkov, Yu. A.; Gouzevitch, M.; Grab, C.; Grebenyuk, A.; Greenshaw, T.; Grindhammer, G.; Grzelak, G.; Gwenlan, C.; Haidt, D.; Henderson, R. C. W.; Hladkỳ, J.; Hlushchenko, O.; Hochman, D.; Hoffmann, D.; Horisberger, R.; Hreus, T.; Huber, F.; Ibrahim, Z. A.; Iga, Y.; Jacquet, M.; Janssen, X.; Jomhari, N. Z.; Jung, A. W.; Jung, H.; Kadenko, I.; Kananov, S.; Kapichine, M.; Karshon, U.; Katzy, J.; Kaur, P.; Kiesling, C.; Kisielewska, D.; Klanner, R.; Klein, M.; Klein, U.; Kleinwort, C.; Kogler, R.; Korzhavina, I. A.; Kostka, P.; Kotański, A.; Kovalchuk, N.; Kowalski, H.; Kretzschmar, J.; Krücker, D.; Krüger, K.; Krupa, B.; Kuprash, O.; Kuze, M.; Landon, M. P. J.; Lange, W.; Laycock, P.; Lebedev, A.; Levchenko, B. B.; Levonian, S.; Levy, A.; Libov, V.; Lipka, K.; Lisovyi, M.; List, B.; List, J.; Lobodzinski, B.; Löhr, B.; Lohrmann, E.; Longhin, A.; Lukina, O. Yu.; Makarenko, I.; Malinovski, E.; Malka, J.; Martyn, H.-U.; Masciocchi, S.; Maxfield, S. J.; Mehta, A.; Meyer, A. B.; Meyer, H.; Meyer, J.; Mikocki, S.; Idris, F. Mohamad; Mohammad Nasir, N.; Morozov, A.; Müller, K.; Myronenko, V.; Nagano, K.; Nam, J. D.; Naumann, Th.; Newman, P. R.; Nicassio, M.; Niebuhr, C.; Nowak, G.; Olsson, J. E.; Onderwaater, J.; Onishchuk, Yu.; Ozerov, D.; Pascaud, C.; Patel, G. D.; Paul, E.; Perez, E.; Perlański, W.; Petrukhin, A.; Picuric, I.; Pirumov, H.; Pitzl, D.; Pokrovskiy, N. S.; Polifka, R.; Polini, A.; Przybycień, M.; Radescu, V.; Raicevic, N.; Ravdandorj, T.; Reimer, P.; Rizvi, E.; Robmann, P.; Roosen, R.; Rostovtsev, A.; Rotaru, M.; Ruspa, M.; Šálek, D.; Sankey, D. P. C.; Sauter, M.; Sauvan, E.; Saxon, D. H.; Schioppa, M.; Schmitt, S.; Schneekloth, U.; Schoeffel, L.; Schöning, A.; Schörner-Sadenius, T.; Sefkow, F.; Selyuzhenkov, I.; Shcheglova, L. M.; Shushkevich, S.; Shyrma, Yu.; Skillicorn, I. O.; Słomiński, W.; Solano, A.; Soloviev, Y.; Sopicki, P.; South, D.; Spaskov, V.; Specka, A.; Stanco, L.; Steder, M.; Stefaniuk, N.; Stella, B.; Stern, A.; Stopa, P.; Straumann, U.; Surrow, B.; Sykora, T.; Sztuk-Dambietz, J.; Tassi, E.; Thompson, P. D.; Tokushuku, K.; Tomaszewska, J.; Traynor, D.; Truöl, P.; Tsakov, I.; Tseepeldorj, B.; Tsurugai, T.; Turcato, M.; Turkot, O.; Tymieniecka, T.; Valkárová, A.; Vallée, C.; Van Mechelen, P.; Vazdik, Y.; Verbytskyi, A.; Abdullah, W. A. T. Wan; Wegener, D.; Wichmann, K.; Wing, M.; Wünsch, E.; Yamada, S.; Yamazaki, Y.; Žáček, J.; Żarnecki, A. F.; Zawiejski, L.; Zenaiev, O.; Zhang, Z.; Zhautykov, B. O.; Žlebčík, R.; Zohrabyan, H.; Zomer, F.
2018-06-01
Measurements of open charm and beauty production cross sections in deep inelastic ep scattering at HERA from the H1 and ZEUS Collaborations are combined. Reduced cross sections are obtained in the kinematic range of negative four-momentum transfer squared of the photon 2.5 GeV^2≤Q^2 ≤2000 GeV^2 and Bjorken scaling variable 3 \\cdot 10^{-5} ≤ x_Bj ≤ 5 \\cdot 10^{-2}. The combination method accounts for the correlations of the statistical and systematic uncertainties among the different datasets. Perturbative QCD calculations are compared to the combined data. A next-to-leading order QCD analysis is performed using these data together with the combined inclusive deep inelastic scattering cross sections from HERA. The running charm- and beauty-quark masses are determined as m_c(m_c) = 1.290^{+0.046}_{-0.041} (exp/fit) {}^{+0.062}_{-0.014} (model) {}^{+0.003}_{-0.031} (parameterisation) GeV and m_b(m_b) = 4.049^{+0.104}_{-0.109} (exp/fit) {}^{+0.090}_{-0.032} (model) {}^{+0.001}_{-0.031} (parameterisation) GeV.
A cross-correlation-based estimate of the galaxy luminosity function
NASA Astrophysics Data System (ADS)
van Daalen, Marcel P.; White, Martin
2018-06-01
We extend existing methods for using cross-correlations to derive redshift distributions for photometric galaxies, without using photometric redshifts. The model presented in this paper simultaneously yields highly accurate and unbiased redshift distributions and, for the first time, redshift-dependent luminosity functions, using only clustering information and the apparent magnitudes of the galaxies as input. In contrast to many existing techniques for recovering unbiased redshift distributions, the output of our method is not degenerate with the galaxy bias b(z), which is achieved by modelling the shape of the luminosity bias. We successfully apply our method to a mock galaxy survey and discuss improvements to be made before applying our model to real data.
Heydari, Payam; Varmazyar, Sakineh; Variani, Ali Safari; Hashemi, Fariba; Ataei, Seyed Sajad
2017-10-01
Test of maximal oxygen consumption is the gold standard for measuring cardio-pulmonary fitness. This study aimed to determine correlation of Gerkin, Queen's College, George, and Jackson methods in estimating maximal oxygen consumption, and demographic factors affecting maximal oxygen consumption. This descriptive cross-sectional study was conducted in a census of medical emergency students (n=57) in Qazvin University of Medical Sciences in 2016. The subjects firstly completed the General Health Questionnaire (PAR-Q) and demographic characteristics. Then eligible subjects were assessed using exercise tests of Gerkin treadmill, Queen's College steps and non-exercise George, and Jackson. Data analysis was carried out using independent t-test, one way analysis of variance and Pearson correlation in the SPSS software. The mean age of participants was 21.69±4.99 years. The mean of maximal oxygen consumption using Gerkin, Queen's College, George, and Jackson tests was 4.17, 3.36, 3.64, 3.63 liters per minute, respectively. Pearson statistical test showed a significant correlation among fours tests. George and Jackson tests had the greatest correlation (r=0.85, p>0.001). Results of tests of one-way analysis of variance and t-test showed a significant relationship between independent variable of weight and height in four tests, and dependent variable of maximal oxygen consumption. Also, there was a significant relationship between variable of body mass index in two tests of Gerkin and Queen's College and variable of exercise hours per week with the George and Jackson tests (p>0.001). Given the obtained correlation, these tests have the potential to replace each other as necessary, so that the non-exercise Jackson test can be used instead of the Gerkin test.
Characterizing the functional MRI response using Tikhonov regularization.
Vakorin, Vasily A; Borowsky, Ron; Sarty, Gordon E
2007-09-20
The problem of evaluating an averaged functional magnetic resonance imaging (fMRI) response for repeated block design experiments was considered within a semiparametric regression model with autocorrelated residuals. We applied functional data analysis (FDA) techniques that use a least-squares fitting of B-spline expansions with Tikhonov regularization. To deal with the noise autocorrelation, we proposed a regularization parameter selection method based on the idea of combining temporal smoothing with residual whitening. A criterion based on a generalized chi(2)-test of the residuals for white noise was compared with a generalized cross-validation scheme. We evaluated and compared the performance of the two criteria, based on their effect on the quality of the fMRI response. We found that the regularization parameter can be tuned to improve the noise autocorrelation structure, but the whitening criterion provides too much smoothing when compared with the cross-validation criterion. The ultimate goal of the proposed smoothing techniques is to facilitate the extraction of temporal features in the hemodynamic response for further analysis. In particular, these FDA methods allow us to compute derivatives and integrals of the fMRI signal so that fMRI data may be correlated with behavioral and physiological models. For example, positive and negative hemodynamic responses may be easily and robustly identified on the basis of the first derivative at an early time point in the response. Ultimately, these methods allow us to verify previously reported correlations between the hemodynamic response and the behavioral measures of accuracy and reaction time, showing the potential to recover new information from fMRI data. 2007 John Wiley & Sons, Ltd
NASA Astrophysics Data System (ADS)
Shahzad, Syed Jawad Hussain; Nor, Safwan Mohd; Mensi, Walid; Kumar, Ronald Ravinesh
2017-04-01
This study examines the power law properties of 11 US credit and stock markets at the industry level. We use multifractal detrended fluctuation analysis (MF-DFA) and multifractal detrended cross-correlation analysis (MF-DXA) to first investigate the relative efficiency of credit and stock markets and then evaluate the mutual interdependence between CDS-equity market pairs. The scaling exponents of the MF-DFA approach suggest that CDS markets are relatively more inefficient than their equity counterparts. However, Banks and Financial credit markets are relatively more efficient. Basic Materials (both CDS and equity indices) is the most inefficient sector of the US economy. The cross-correlation exponents obtained through MF-DXA also suggest that the relationship of the CDS and equity sectors within and across markets is multifractal for all pairs. Within the CDS market, Basic Materials is the most dependent sector, whereas equity market sectors can be divided into two distinct groups based on interdependence. The pair-wise dependence between Basic Materials sector CDSs and the equity index is also the highest. The degree of cross-correlation shows that the sectoral pairs of CDS and equity markets belong to a persistent cross-correlated series within selected time intervals.
Robust image alignment for cryogenic transmission electron microscopy.
McLeod, Robert A; Kowal, Julia; Ringler, Philippe; Stahlberg, Henning
2017-03-01
Cryo-electron microscopy recently experienced great improvements in structure resolution due to direct electron detectors with improved contrast and fast read-out leading to single electron counting. High frames rates enabled dose fractionation, where a long exposure is broken into a movie, permitting specimen drift to be registered and corrected. The typical approach for image registration, with high shot noise and low contrast, is multi-reference (MR) cross-correlation. Here we present the software package Zorro, which provides robust drift correction for dose fractionation by use of an intensity-normalized cross-correlation and logistic noise model to weight each cross-correlation in the MR model and filter each cross-correlation optimally. Frames are reliably registered by Zorro with low dose and defocus. Methods to evaluate performance are presented, by use of independently-evaluated even- and odd-frame stacks by trajectory comparison and Fourier ring correlation. Alignment of tiled sub-frames is also introduced, and demonstrated on an example dataset. Zorro source code is available at github.com/CINA/zorro. Copyright © 2016 Elsevier Inc. All rights reserved.
Continuous correction of differential path length factor in near-infrared spectroscopy
Moore, Jason H.; Diamond, Solomon G.
2013-01-01
Abstract. In continuous-wave near-infrared spectroscopy (CW-NIRS), changes in the concentration of oxyhemoglobin and deoxyhemoglobin can be calculated by solving a set of linear equations from the modified Beer-Lambert Law. Cross-talk error in the calculated hemodynamics can arise from inaccurate knowledge of the wavelength-dependent differential path length factor (DPF). We apply the extended Kalman filter (EKF) with a dynamical systems model to calculate relative concentration changes in oxy- and deoxyhemoglobin while simultaneously estimating relative changes in DPF. Results from simulated and experimental CW-NIRS data are compared with results from a weighted least squares (WLSQ) method. The EKF method was found to effectively correct for artificially introduced errors in DPF and to reduce the cross-talk error in simulation. With experimental CW-NIRS data, the hemodynamic estimates from EKF differ significantly from the WLSQ (p<0.001). The cross-correlations among residuals at different wavelengths were found to be significantly reduced by the EKF method compared to WLSQ in three physiologically relevant spectral bands 0.04 to 0.15 Hz, 0.15 to 0.4 Hz and 0.4 to 2.0 Hz (p<0.001). This observed reduction in residual cross-correlation is consistent with reduced cross-talk error in the hemodynamic estimates from the proposed EKF method. PMID:23640027
Continuous correction of differential path length factor in near-infrared spectroscopy
NASA Astrophysics Data System (ADS)
Talukdar, Tanveer; Moore, Jason H.; Diamond, Solomon G.
2013-05-01
In continuous-wave near-infrared spectroscopy (CW-NIRS), changes in the concentration of oxyhemoglobin and deoxyhemoglobin can be calculated by solving a set of linear equations from the modified Beer-Lambert Law. Cross-talk error in the calculated hemodynamics can arise from inaccurate knowledge of the wavelength-dependent differential path length factor (DPF). We apply the extended Kalman filter (EKF) with a dynamical systems model to calculate relative concentration changes in oxy- and deoxyhemoglobin while simultaneously estimating relative changes in DPF. Results from simulated and experimental CW-NIRS data are compared with results from a weighted least squares (WLSQ) method. The EKF method was found to effectively correct for artificially introduced errors in DPF and to reduce the cross-talk error in simulation. With experimental CW-NIRS data, the hemodynamic estimates from EKF differ significantly from the WLSQ (p<0.001). The cross-correlations among residuals at different wavelengths were found to be significantly reduced by the EKF method compared to WLSQ in three physiologically relevant spectral bands 0.04 to 0.15 Hz, 0.15 to 0.4 Hz and 0.4 to 2.0 Hz (p<0.001). This observed reduction in residual cross-correlation is consistent with reduced cross-talk error in the hemodynamic estimates from the proposed EKF method.
Mapping brain activity in gradient-echo functional MRI using principal component analysis
NASA Astrophysics Data System (ADS)
Khosla, Deepak; Singh, Manbir; Don, Manuel
1997-05-01
The detection of sites of brain activation in functional MRI has been a topic of immense research interest and many technique shave been proposed to this end. Recently, principal component analysis (PCA) has been applied to extract the activated regions and their time course of activation. This method is based on the assumption that the activation is orthogonal to other signal variations such as brain motion, physiological oscillations and other uncorrelated noises. A distinct advantage of this method is that it does not require any knowledge of the time course of the true stimulus paradigm. This technique is well suited to EPI image sequences where the sampling rate is high enough to capture the effects of physiological oscillations. In this work, we propose and apply tow methods that are based on PCA to conventional gradient-echo images and investigate their usefulness as tools to extract reliable information on brain activation. The first method is a conventional technique where a single image sequence with alternating on and off stages is subject to a principal component analysis. The second method is a PCA-based approach called the common spatial factor analysis technique (CSF). As the name suggests, this method relies on common spatial factors between the above fMRI image sequence and a background fMRI. We have applied these methods to identify active brain ares during visual stimulation and motor tasks. The results from these methods are compared to those obtained by using the standard cross-correlation technique. We found good agreement in the areas identified as active across all three techniques. The results suggest that PCA and CSF methods have good potential in detecting the true stimulus correlated changes in the presence of other interfering signals.
Cardiovascular regulation during sleep quantified by symbolic coupling traces
NASA Astrophysics Data System (ADS)
Suhrbier, A.; Riedl, M.; Malberg, H.; Penzel, T.; Bretthauer, G.; Kurths, J.; Wessel, N.
2010-12-01
Sleep is a complex regulated process with short periods of wakefulness and different sleep stages. These sleep stages modulate autonomous functions such as blood pressure and heart rate. The method of symbolic coupling traces (SCT) is used to analyze and quantify time-delayed coupling of these measurements during different sleep stages. The symbolic coupling traces, defined as the symmetric and diametric traces of the bivariate word distribution matrix, allow the quantification of time-delayed coupling. In this paper, the method is applied to heart rate and systolic blood pressure time series during different sleep stages for healthy controls as well as for normotensive and hypertensive patients with sleep apneas. Using the SCT, significant different cardiovascular mechanisms not only between the deep sleep and the other sleep stages but also between healthy subjects and patients can be revealed. The SCT method is applied to model systems, compared with established methods, such as cross correlation, mutual information, and cross recurrence analysis and demonstrates its advantages especially for nonstationary physiological data. As a result, SCT proves to be more specific in detecting delays of directional interactions than standard coupling analysis methods and yields additional information which cannot be measured by standard parameters of heart rate and blood pressure variability. The proposed method may help to indicate the pathological changes in cardiovascular regulation and also the effects of continuous positive airway pressure therapy on the cardiovascular system.
NASA Astrophysics Data System (ADS)
Patej, A.; Eisenstein, D. J.
2018-07-01
We develop a formalism for measuring the cosmological distance scale from baryon acoustic oscillations (BAO) using the cross-correlation of a sparse redshift survey with a denser photometric sample. This reduces the shot noise that would otherwise affect the autocorrelation of the sparse spectroscopic map. As a proof of principle, we make the first on-sky application of this method to a sparse sample defined as the z > 0.6 tail of the Sloan Digital Sky Survey's (SDSS) BOSS/CMASS sample of galaxies and a dense photometric sample from SDSS DR9. We find a 2.8σ preference for the BAO peak in the cross-correlation at an effective z = 0.64, from which we measure the angular diameter distance DM(z = 0.64) = (2418 ± 73 Mpc)(rs/rs, fid). Accordingly, we expect that using this method to combine sparse spectroscopy with the deep, high-quality imaging that is just now becoming available will enable higher precision BAO measurements than possible with the spectroscopy alone.
Statistical properties of Galactic CMB foregrounds: dust and synchrotron
NASA Astrophysics Data System (ADS)
Kandel, D.; Lazarian, A.; Pogosyan, D.
2018-07-01
Recent Planck observations have revealed some of the important statistical properties of synchrotron and dust polarization, namely, the B to E mode power and temperature-E (TE) mode cross-correlation. In this paper, we extend our analysis in Kandel et al. that studied the B to E mode power ratio for polarized dust emission to include TE cross-correlation and develop an analogous formalism for synchrotron signal, all using a realistic model of magnetohydrodynamical turbulence. Our results suggest that the Planck results for both synchrotron and dust polarization can be understood if the turbulence in the Galaxy is sufficiently sub-Alfvénic. Making use of the observed poor magnetic field-density correlation, we show that the observed positive TE correlation for dust corresponds to our theoretical expectations. We also show how the B to E ratio as well as the TE cross-correlation can be used to study media magnetization, compressibility, and level of density-magnetic field correlation.
NASA Astrophysics Data System (ADS)
Soetrisno, D. P.
2017-06-01
Pedestrian crossing facilities are effective enough to avoid pedestrians with vehicles, but its utilization is still quite low. It indicated that safety is not the only factor that influences a person to utilize the pedestrian crossing facilities. In addition, the availability of supporting elements of the pedestrian is still not quite attention, which is also became a factor that causes the pedestrians doesn’t utilize the pedestrian crossing facilities. Therefore, this research was structured to examine the relationship between the availability of the supporting elements of the pedestrian with pedestrian crossing facility usage based on user preferences. Data collection method used is primary survey consist of observation and the questionnaire. Sampling techniques used is purposive sampling with the number of respondents as many as 211 respondents by using questionnaire with ordinal scales to identify respondents’ consideration level of supporting elements pedestrian and crossing facility utilization factors. The survey is done on 15 crossing facilities area in 3 different locations with the same characteristics of land use in the form of higher education area (university area) and trades and services activities area. The analysis technique used is frequency distribution analysis in order to identify preference pedestrian on the availability of supporting elements of pedestrian and pedestrian crossing facility utilization factors, and chi square analysis is used to analyze the relationship between the availability of the supporting elements of the pedestrian with pedestrian crossing facility utilization. Based on the chi square analysis results with significance 5 % obtained the result that there are six supporting elements of pedestrian having correlation to the factors of pedestrian crossing facility utilization consist of the availability of sidewalk, pedestrian lights, Street Lighting Lamps, Pedestrian Crossing Markings Facilities, Sign Crossings Facilities, vegetation, and dustbin. So the result of this research can be considered for the government as main stakehoder especially the local government in preparing policy to provide supporting elements of pedestrian that should be on the area of pedestrian crossing facilities.
Research on fully distributed optical fiber sensing security system localization algorithm
NASA Astrophysics Data System (ADS)
Wu, Xu; Hou, Jiacheng; Liu, Kun; Liu, Tiegen
2013-12-01
A new fully distributed optical fiber sensing and location technology based on the Mach-Zehnder interferometers is studied. In this security system, a new climbing point locating algorithm based on short-time average zero-crossing rate is presented. By calculating the zero-crossing rates of the multiple grouped data separately, it not only utilizes the advantages of the frequency analysis method to determine the most effective data group more accurately, but also meets the requirement of the real-time monitoring system. Supplemented with short-term energy calculation group signal, the most effective data group can be quickly picked out. Finally, the accurate location of the climbing point can be effectively achieved through the cross-correlation localization algorithm. The experimental results show that the proposed algorithm can realize the accurate location of the climbing point and meanwhile the outside interference noise of the non-climbing behavior can be effectively filtered out.
Passive monitoring of a sea dike during a tidal cycle using sea waves as a seismic noise source
NASA Astrophysics Data System (ADS)
Joubert, Anaëlle; Feuvre, Mathieu Le; Cote, Philippe
2018-05-01
Over the past decade, ambient seismic noise has been used successfully to monitor various geological objects with high accuracy. Recently, it has been shown that surface seismic waves propagating within a sea dike body can be retrieved from the cross-correlation of ambient seismic noise generated by sea waves. We use sea wave impacts to monitor the response of a sea dike during a tidal cycle using empirical Green's functions. These are obtained either by cross-correlation or deconvolution, from signals recorded by sensors installed linearly on the crest of a dike. Our analysis is based on delay and spectral amplitude measurements performed on reconstructed surface waves propagating along the array. We show that localized variations of velocity and attenuation are correlated with changes in water level as a probable consequence of water infiltration inside the structure. Sea dike monitoring is of critical importance for safety and economic reasons, as internal erosion is generally only detected at late stages by visual observations. The method proposed here may provide a solution for detecting structural weaknesses, monitoring progressive internal erosion, and delineating areas of interest for further geotechnical studies, in view to understanding the erosion mechanisms involved.
Imaging Subsurface Structure of Tehran/Iran region using Ambient Seismic Noise Tomography
NASA Astrophysics Data System (ADS)
Shirzad Iraj, Taghi; Shmomali, Z. Hossein
2013-04-01
Tehran, capital of Iran, is surrounded by many active faults (including Mosha, North Tehran and North and/or South Rey faults), however our knowledge about the 3D velocity structure of the study area is limited. Recent developments in seismology have shown that cross-correlation of a long time ambient seismic noise recorded by pair of stations, contain information about the Green's function between the stations. Thus ambient seismic noise carries valuable information of propagation path which can be extracted. We obtained 2D model of shear wave velocity (Vs) for Tehran/Iran area using seismic ambient noise tomography (ANT) method. In this study, we use continuous vertical component of data recorded by TDMMO (Tehran Disaster Mitigation and Management Organization) and IRSC (Iranian Seismological Center) networks in the Tehran/Iran area. The TDMMO and IRSC networks are equipped with CMG-5TD Guralp sensor and SS-1 Kinemetrics sensor respectively. We use data from 25 stations for 12 months from 2009/Oct. to 2010/Oct. Data processing is similar to that explained in detail by Bensen et al. (2007) including processed daily base data. The mean, trend, and instrument response were removed and the data were decimated to 10 sps. One-bit time-domain normalization was then applied to suppress the influence of instrument irregularities and earthquake signals followed by spectral normalization between 0.1-1.0 Hz (period 1-10 sec). After cross-correlation processing, we implement a new stacking method to stack many cross-correlation functions bases on the highest energy in a time interval which we expect to receive the Rayleigh wave fundamental mode. We then obtained group velocity of Rayleigh wave by using phase match filtering and frequency-time analysis techniques. Finally, we applied iterative inversion method to extract Vs model of shallow structure in the Tehran/Iran area.
Method and apparatus for in-situ characterization of energy storage and energy conversion devices
Christophersen, Jon P [Idaho Falls, ID; Motloch, Chester G [Idaho Falls, ID; Morrison, John L [Butte, MT; Albrecht, Weston [Layton, UT
2010-03-09
Disclosed are methods and apparatuses for determining an impedance of an energy-output device using a random noise stimulus applied to the energy-output device. A random noise signal is generated and converted to a random noise stimulus as a current source correlated to the random noise signal. A bias-reduced response of the energy-output device to the random noise stimulus is generated by comparing a voltage at the energy-output device terminal to an average voltage signal. The random noise stimulus and bias-reduced response may be periodically sampled to generate a time-varying current stimulus and a time-varying voltage response, which may be correlated to generate an autocorrelated stimulus, an autocorrelated response, and a cross-correlated response. Finally, the autocorrelated stimulus, the autocorrelated response, and the cross-correlated response may be combined to determine at least one of impedance amplitude, impedance phase, and complex impedance.
Dynamic evolution of cross-correlations in the Chinese stock market.
Ren, Fei; Zhou, Wei-Xing
2014-01-01
The analysis of cross-correlations is extensively applied for the understanding of interconnections in stock markets and the portfolio risk estimation. Current studies of correlations in Chinese market mainly focus on the static correlations between return series, and this calls for an urgent need to investigate their dynamic correlations. Our study aims to reveal the dynamic evolution of cross-correlations in the Chinese stock market, and offer an exact interpretation for the evolution behavior. The correlation matrices constructed from the return series of 367 A-share stocks traded on the Shanghai Stock Exchange from January 4, 1999 to December 30, 2011 are calculated over a moving window with a size of 400 days. The evolutions of the statistical properties of the correlation coefficients, eigenvalues, and eigenvectors of the correlation matrices are carefully analyzed. We find that the stock correlations are significantly increased in the periods of two market crashes in 2001 and 2008, during which only five eigenvalues significantly deviate from the random correlation matrix, and the systemic risk is higher in these volatile periods than calm periods. By investigating the significant contributors of the deviating eigenvectors in different time periods, we observe a dynamic evolution behavior in business sectors such as IT, electronics, and real estate, which lead the rise (drop) before (after) the crashes. Our results provide new perspectives for the understanding of the dynamic evolution of cross-correlations in the Chines stock markets, and the result of risk estimation is valuable for the application of risk management.
Dynamic Evolution of Cross-Correlations in the Chinese Stock Market
Ren, Fei; Zhou, Wei-Xing
2014-01-01
The analysis of cross-correlations is extensively applied for the understanding of interconnections in stock markets and the portfolio risk estimation. Current studies of correlations in Chinese market mainly focus on the static correlations between return series, and this calls for an urgent need to investigate their dynamic correlations. Our study aims to reveal the dynamic evolution of cross-correlations in the Chinese stock market, and offer an exact interpretation for the evolution behavior. The correlation matrices constructed from the return series of 367 A-share stocks traded on the Shanghai Stock Exchange from January 4, 1999 to December 30, 2011 are calculated over a moving window with a size of 400 days. The evolutions of the statistical properties of the correlation coefficients, eigenvalues, and eigenvectors of the correlation matrices are carefully analyzed. We find that the stock correlations are significantly increased in the periods of two market crashes in 2001 and 2008, during which only five eigenvalues significantly deviate from the random correlation matrix, and the systemic risk is higher in these volatile periods than calm periods. By investigating the significant contributors of the deviating eigenvectors in different time periods, we observe a dynamic evolution behavior in business sectors such as IT, electronics, and real estate, which lead the rise (drop) before (after) the crashes. Our results provide new perspectives for the understanding of the dynamic evolution of cross-correlations in the Chines stock markets, and the result of risk estimation is valuable for the application of risk management. PMID:24867071
Aeroacoustic measurements on a NACA 0012 applying the Coherent Particle Velocity method
NASA Astrophysics Data System (ADS)
Plogmann, B.; Würz, W.
2013-07-01
Aeroacoustic measurements on two NACA 0012 airfoil sections with different chord length and sharp trailing edge were conducted at the Laminar Wind Tunnel (LWT) of the University of Stuttgart. The LWT is a closed test section wind tunnel with a very low turbulence level and an acoustically optimized diffusor section allowing for high-quality aerodynamic as well as aeroacoustic measurements. Trailing edge noise measurements were performed using the Coherent Particle Velocity (CPV) method, which is based on a cross-spectral analysis of two hot-wire sensor signals placed on the suction and the pressure side of the airfoil trailing edge, respectively. At high angles of attack, the cross-spectral analysis of the two sensor signals used for the measurement of the trailing edge noise can be prone to a disturbing influence of hydrodynamic fluctuations. Hence, continuous shifts in the phasing of the cross-correlation are observed mainly for low sensor distances to the trailing edge. The quantitative evaluation of the trailing edge noise predominately in the low frequency range is, therefore, considerably disturbed. A new approach is proposed, which allows for the correction of the cross-correlation function based on the averaged single wire auto-spectrum. The results are compared to measurements with increased sensor distance and show good agreement. In the following, trailing edge noise measurements were performed on a NACA 0012 airfoil in a wide range of angles of attack ( α = 0°-8°) and free-stream velocities (u_{infty} = 30{-}70 {{m/s}}). The tripped flow cases exhibit a very good consistency for the scaling of the 1/3 octave spectra based on outer variables. Moreover, a common intersection point of the sound pressure level was observed for trailing edge noise spectra measured at constant free-stream velocity and different angles of attack. In cases without boundary layer tripping, the presence of an acoustic feedback loop was observed and linked to the presence of a laminar separation bubble on the pressure side in the vicinity of the trailing edge. Finally, a comparison of the aeroacoustic measurements based on the CPV method showed reasonably good agreement with published data obtained with both a microphone array and the Coherent Output Power method in open-test section facilities.
Fairchild, Karen D.; Lake, Douglas E.; Kattwinkel, John; Moorman, J. Randall; Bateman, David A; Grieve, Philip G; Isler, Joseph R; Sahni, Rakesh
2016-01-01
Background Subtle changes in vital signs and their interactions occur in preterm infants prior to overt deterioration from late-onset septicemia (LOS) or necrotizing enterocolitis (NEC). Optimizing predictive algorithms may lead to earlier treatment. Methods For 1065 very low birth weight (VLBW) infants in two NICUs, mean, SD, and cross-correlation of respiratory rate, heart rate (HR), and oxygen saturation (SpO2) were analyzed hourly (131 infant-years’ data). Cross-correlation (co-trending) between two vital signs was measured allowing a lag of +/− 30 seconds. Cases of LOS and NEC were identified retrospectively (n=186) and vital sign models were evaluated for ability to predict illness diagnosed in the ensuing 24h. Results The best single illness predictor within and between institutions was cross-correlation of HR-SpO2. The best combined model (mean SpO2, SD HR, and cross correlation of HR-SpO2,) trained at one site with ROC area 0.695 had external ROC area of 0.754 at the other site, and provided additive value to an established HR characteristics index for illness prediction (Net Reclassification Improvement 0.25, 95% CI 0.113, 0.328). Conclusion Despite minor inter-institutional differences in vital sign patterns of VLBW infants, cross-correlation of HR-SpO2 and a 3-variable vital sign model performed well at both centers for preclinical detection of sepsis or NEC. PMID:28001143
Application of the spectral-correlation method for diagnostics of cellulose paper
NASA Astrophysics Data System (ADS)
Kiesewetter, D.; Malyugin, V.; Reznik, A.; Yudin, A.; Zhuravleva, N.
2017-11-01
The spectral-correlation method was described for diagnostics of optically inhomogeneous biological objects and materials of natural origin. The interrelation between parameters of the studied objects and parameters of the cross correlation function of speckle patterns produced by scattering of coherent light at different wavelengths is shown for thickness, optical density and internal structure of the material. A detailed study was performed for cellulose electric insulating paper with different parameters.
Technical Note: Detection of gas bubble leakage via correlation of water column multibeam images
NASA Astrophysics Data System (ADS)
Schneider von Deimling, J.; Papenberg, C.
2011-07-01
Hydroacoustic detection of natural gas release from the seafloor has been conducted in the past by using singlebeam echosounders. In contrast modern multibeam swath mapping systems allow much wider coverage, higher resolution, and offer 3-D spatial correlation. However, up to the present, the extremely high data rate hampers water column backscatter investigations. More sophisticated visualization and processing techniques for water column backscatter analysis are still under development. We here present such water column backscattering data gathered with a 50 kHz prototype multibeam system. Water column backscattering data is presented in videoframes grabbed over 75 s and a "re-sorted" singlebeam presentation. Thus individual gas bubbles rising from the 24 m deep seafloor clearly emerge in the acoustic images and rise velocities can be determined. A sophisticated processing scheme is introduced to identify those rising gas bubbles in the hydroacoustic data. It applies a cross-correlation technique similar to that used in Particle Imaging Velocimetry (PIV) to the acoustic backscatter images. Tempo-spatial drift patterns of the bubbles are assessed and match very well measured and theoretical rise patterns. The application of this processing scheme to our field data gives impressive results with respect to unambiguous bubble detection and remote bubble rise velocimetry. The method can identify and exclude the main driver for misinterpretations, i.e. fish-mediated echoes. Even though image-based cross-correlation techniques are well known in the field of fluid mechanics for high resolution and non-inversive current flow field analysis, this technique was never applied in the proposed sense for an acoustic bubble detector.
Topaktaş, Berkhan; Dündar, Cihad; Pekşen, Yıldız
2017-01-01
Due to social and emotional changes alongside the cognitive and logical changes in adolescence, alterations occur in the adolescent's communication with family and friends in this period, and social support assumes greater importance. From each of the two middle and high schools in the Ilkadim district of Samsun, a total 688 students were employed by a two-stage sampling method in this cross-sectional study. The data were collected from sociodemographic information, Multidimensional Scale of Perceived Social Support (MSPSS), Brief Symptom Inventory (BSI) and Future Expectations Scale for Adolescents (FESA) questionnaires distributed under the supervision of guidance counselors in these schools between December 2014 and February 2015. The Mann- Whitney U test and Spearman's Rank Correlation were used for statistical analysis. The significance level was accepted as p<0.05 for all tests. In the study group, MSPSS Family subscale had a stronger correlational relationship with all the BSI subscales including global indices and also with total score of FESA and subscales with the exception of the Marriage and Family subscale than the other two MSPSS subscales. There were moderate negative correlation between scores of MSPSS and BSI, and a low-moderate positive correlation was observed between total MSPSS and FESA scores of adolescents. The results demonstrated that adolescents who exercise regularly and avoid smoking and alcohol have higher perceptions of social support. Perceived social support from family may be more effective than perceived social support from friends or a significant other in the development of psychological well-being and positive future expectations of Turkish adolescents.
Ji, Hong; Petro, Nathan M; Chen, Badong; Yuan, Zejian; Wang, Jianji; Zheng, Nanning; Keil, Andreas
2018-02-06
Over the past decade, the simultaneous recording of electroencephalogram (EEG) and functional magnetic resonance imaging (fMRI) data has garnered growing interest because it may provide an avenue towards combining the strengths of both imaging modalities. Given their pronounced differences in temporal and spatial statistics, the combination of EEG and fMRI data is however methodologically challenging. Here, we propose a novel screening approach that relies on a Cross Multivariate Correlation Coefficient (xMCC) framework. This approach accomplishes three tasks: (1) It provides a measure for testing multivariate correlation and multivariate uncorrelation of the two modalities; (2) it provides criterion for the selection of EEG features; (3) it performs a screening of relevant EEG information by grouping the EEG channels into clusters to improve efficiency and to reduce computational load when searching for the best predictors of the BOLD signal. The present report applies this approach to a data set with concurrent recordings of steady-state-visual evoked potentials (ssVEPs) and fMRI, recorded while observers viewed phase-reversing Gabor patches. We test the hypothesis that fluctuations in visuo-cortical mass potentials systematically covary with BOLD fluctuations not only in visual cortical, but also in anterior temporal and prefrontal areas. Results supported the hypothesis and showed that the xMCC-based analysis provides straightforward identification of neurophysiological plausible brain regions with EEG-fMRI covariance. Furthermore xMCC converged with other extant methods for EEG-fMRI analysis. © 2018 The Authors Journal of Neuroscience Research Published by Wiley Periodicals, Inc.
2006-04-21
purposes, such as scientific study of earthquake interactions in a fault zone or seismic sources associated with magma conduits in a volcano , relative... Kilauea , J. Geophys. Res., 99, 375-393. HARRIS, D.B. (1991), A waveform correlation method for identifying quarry explosions, Bull. Seismol. Soc. Am
Cross-Level Effects Between Neurophysiology and Communication During Team Training.
Gorman, Jamie C; Martin, Melanie J; Dunbar, Terri A; Stevens, Ronald H; Galloway, Trysha L; Amazeen, Polemnia G; Likens, Aaron D
2016-02-01
We investigated cross-level effects, which are concurrent changes across neural and cognitive-behavioral levels of analysis as teams interact, between neurophysiology and team communication variables under variations in team training. When people work together as a team, they develop neural, cognitive, and behavioral patterns that they would not develop individually. It is currently unknown whether these patterns are associated with each other in the form of cross-level effects. Team-level neurophysiology and latent semantic analysis communication data were collected from submarine teams in a training simulation. We analyzed whether (a) both neural and communication variables change together in response to changes in training segments (briefing, scenario, or debriefing), (b) neural and communication variables mutually discriminate teams of different experience levels, and (c) peak cross-correlations between neural and communication variables identify how the levels are linked. Changes in training segment led to changes in both neural and communication variables, neural and communication variables mutually discriminated between teams of different experience levels, and peak cross-correlations indicated that changes in communication precede changes in neural patterns in more experienced teams. Cross-level effects suggest that teamwork is not reducible to a fundamental level of analysis and that training effects are spread out across neural and cognitive-behavioral levels of analysis. Cross-level effects are important to consider for theories of team performance and practical aspects of team training. Cross-level effects suggest that measurements could be taken at one level (e.g., neural) to assess team experience (or skill) on another level (e.g., cognitive-behavioral). © 2015, Human Factors and Ergonomics Society.
The Correlation between Teacher Empowerment and Principal Leadership Behaviors in High Schools
ERIC Educational Resources Information Center
Kirgan, Benjamin G.
2010-01-01
This study will examine the correlation between teacher empowerment and transformational leadership in large high schools. A cross-correlational analysis will be conducted to test for significant relationships among the six dimensions of teacher empowerment (as described by Short & Rinehart, 1994), and the eight dimensions of transformational…
Automated Processing of Two-Dimensional Correlation Spectra
Sengstschmid; Sterk; Freeman
1998-04-01
An automated scheme is described which locates the centers of cross peaks in two-dimensional correlation spectra, even under conditions of severe overlap. Double-quantum-filtered correlation (DQ-COSY) spectra have been investigated, but the method is also applicable to TOCSY and NOESY spectra. The search criterion is the intrinsic symmetry (or antisymmetry) of cross-peak multiplets. An initial global search provides the preliminary information to build up a two-dimensional "chemical shift grid." All genuine cross peaks must be centered at intersections of this grid, a fact that reduces the extent of the subsequent search program enormously. The program recognizes cross peaks by examining the symmetry of signals in a test zone centered at a grid intersection. This "symmetry filter" employs a "lowest value algorithm" to discriminate against overlapping responses from adjacent multiplets. A progressive multiplet subtraction scheme provides further suppression of overlap effects. The processed two-dimensional correlation spectrum represents cross peaks as points at the chemical shift coordinates, with some indication of their relative intensities. Alternatively, the information is presented in the form of a correlation table. The authenticity of a given cross peak is judged by a set of "confidence criteria" expressed as numerical parameters. Experimental results are presented for the 400-MHz double-quantum-filtered COSY spectrum of 4-androsten-3,17-dione, a case where there is severe overlap. Copyright 1998 Academic Press.
Selling blood and gametes during tough economic times: insights from Google search.
Wu, Jonathan A; Ngo, Tin C; Rothman, Cappy; Breyer, Benjamin N; Eisenberg, Michael L
2015-10-01
To use Google Insights search volume and publicly available economic indicators to test the hypothesis that sperm, egg, and blood donations increase during economic downturns and to demonstrate the feasibility of using Google search volume data to predict national trends in actual sperm, egg, and blood donations rates. Cross-correlation statistical analysis comparing Google search data for terms relating to blood, egg, and sperm donations with various economic indicators including the S&P 500 closing values, gross domestic product (GDP), the U.S. Index of Leading Indicators (U.S. Leading Index), gross savings rate, mortgage interest rates, unemployment rate, and consumer price index (CPI) from 2004-2011. A secondary analysis determined the Pearson correlation coefficient between Google search data with actual sperm, egg, and blood donation volume in the U.S. as measured by California Cryobank, the National Assisted Reproductive Technology Surveillance System, and the National Blood Collection and Utilization Survey, respectively. Significance of cross-correlation and Pearson correlation analysis as indicated by p value. There were several highly significant cross-correlation relationships between search volume and various economic indicators. Correlation between Google search volume for the term 'sperm donation,' 'egg donation,' and 'blood donation' with actual number of sperm, egg and blood donations in the United States demonstrated Pearson correlation coefficients of 0.2 (p > 0.10), -0.1 (p > 0.10), and 0.07 (p > 0.10), respectively. Temporal analysis showed an improved correlation coefficient of 0.9 (p < 0.05) for blood donation when shifted 12 months later relative to Google search volume. Google search volume data for search terms relating to sperm, egg, and blood donation increase during economic downturns. This finding suggests gamete and bodily fluid donations are influenced by market forces like other commodities. Google search may be useful for predicting blood donation trends but is more limited in predicting actual semen and oocyte donation patterns.
Statistical regularities of Carbon emission trading market: Evidence from European Union allowances
NASA Astrophysics Data System (ADS)
Zheng, Zeyu; Xiao, Rui; Shi, Haibo; Li, Guihong; Zhou, Xiaofeng
2015-05-01
As an emerging financial market, the trading value of carbon emission trading market has definitely increased. In recent years, the carbon emission allowances have already become a way of investment. They are bought and sold not only by carbon emitters but also by investors. In this paper, we analyzed the price fluctuations of the European Union allowances (EUA) futures in European Climate Exchange (ECX) market from 2007 to 2011. The symmetric and power-law probability density function of return time series was displayed. We found that there are only short-range correlations in price changes (return), while long-range correlations in the absolute of price changes (volatility). Further, detrended fluctuation analysis (DFA) approach was applied with focus on long-range autocorrelations and Hurst exponent. We observed long-range power-law autocorrelations in the volatility that quantify risk, and found that they decay much more slowly than the autocorrelation of return time series. Our analysis also showed that the significant cross correlations exist between return time series of EUA and many other returns. These cross correlations exist in a wide range of fields, including stock markets, energy concerned commodities futures, and financial futures. The significant cross-correlations between energy concerned futures and EUA indicate the physical relationship between carbon emission and energy production process. Additionally, the cross-correlations between financial futures and EUA indicate that the speculation behavior may become an important factor that can affect the price of EUA. Finally we modeled the long-range volatility time series of EUA with a particular version of the GARCH process, and the result also suggests long-range volatility autocorrelations.
NASA Astrophysics Data System (ADS)
Li, Xuxu; Li, Xinyang; wang, Caixia
2018-03-01
This paper proposes an efficient approach to decrease the computational costs of correlation-based centroiding methods used for point source Shack-Hartmann wavefront sensors. Four typical similarity functions have been compared, i.e. the absolute difference function (ADF), ADF square (ADF2), square difference function (SDF), and cross-correlation function (CCF) using the Gaussian spot model. By combining them with fast search algorithms, such as three-step search (TSS), two-dimensional logarithmic search (TDL), cross search (CS), and orthogonal search (OS), computational costs can be reduced drastically without affecting the accuracy of centroid detection. Specifically, OS reduces calculation consumption by 90%. A comprehensive simulation indicates that CCF exhibits a better performance than other functions under various light-level conditions. Besides, the effectiveness of fast search algorithms has been verified.
Reducing Uncertainties in Hydrocarbon Prediction through Application of Elastic Domain
NASA Astrophysics Data System (ADS)
Shamsuddin, S. Z.; Hermana, M.; Ghosh, D. P.; Salim, A. M. A.
2017-10-01
The application of lithology and fluid indicators has helped the geophysicists to discriminate reservoirs to non-reservoirs from a field. This analysis is conducted to select the most suitable lithology and fluid indicator for the Malaysian basins that could lead to better eliminate pitfalls of amplitude. This paper uses different rock physics analysis such as elastic impedance, Lambda-Mu-Rho, and SQp-SQs attribute. Litho-elastic impedance log is generated by correlating the gamma ray log with extended elastic impedance log. The same application is used for fluid-elastic impedance by correlation of EEI log with water saturation or resistivity. The work is done on several well logging data collected from different fields in Malay basin and its neighbouring basin. There's an excellent separation between hydrocarbon sand and background shale for Well-1 from different cross-plot analysis. Meanwhile, the Well-2 shows good separation in LMR plot. The similar method is done on the Well-3 shows fair separation of silty sand and gas sand using SQp-SQs attribute which can be correlated with well log. Based on the point distribution histogram plot, different lithology and fluid can be separated clearly. Simultaneous seismic inversion results in acoustic impedance, Vp/Vs, SQp, and SQs volumes. There are many attributes available in the industry used to separate the lithology and fluid, however some of the methods are not suitable for the application to the basins in Malaysia.
A Timing Estimation Method Based-on Skewness Analysis in Vehicular Wireless Networks.
Cui, Xuerong; Li, Juan; Wu, Chunlei; Liu, Jian-Hang
2015-11-13
Vehicle positioning technology has drawn more and more attention in vehicular wireless networks to reduce transportation time and traffic accidents. Nowadays, global navigation satellite systems (GNSS) are widely used in land vehicle positioning, but most of them are lack precision and reliability in situations where their signals are blocked. Positioning systems base-on short range wireless communication are another effective way that can be used in vehicle positioning or vehicle ranging. IEEE 802.11p is a new real-time short range wireless communication standard for vehicles, so a new method is proposed to estimate the time delay or ranges between vehicles based on the IEEE 802.11p standard which includes three main steps: cross-correlation between the received signal and the short preamble, summing up the correlated results in groups, and finding the maximum peak using a dynamic threshold based on the skewness analysis. With the range between each vehicle or road-side infrastructure, the position of neighboring vehicles can be estimated correctly. Simulation results were presented in the International Telecommunications Union (ITU) vehicular multipath channel, which show that the proposed method provides better precision than some well-known timing estimation techniques, especially in low signal to noise ratio (SNR) environments.
NASA Astrophysics Data System (ADS)
Gliss, Jonas; Stebel, Kerstin; Kylling, Arve; Solvejg Dinger, Anna; Sihler, Holger; Sudbø, Aasmund
2017-04-01
UV SO2 cameras have become a common method for monitoring SO2 emission rates from volcanoes. Scattered solar UV radiation is measured in two wavelength windows, typically around 310 nm and 330 nm (distinct / weak SO2 absorption) using interference filters. The data analysis comprises the retrieval of plume background intensities (to calculate plume optical densities), the camera calibration (to convert optical densities into SO2 column densities) and the retrieval of gas velocities within the plume as well as the retrieval of plume distances. SO2 emission rates are then typically retrieved along a projected plume cross section, for instance a straight line perpendicular to the plume propagation direction. Today, for most of the required analysis steps, several alternatives exist due to ongoing developments and improvements related to the measurement technique. We present piscope, a cross platform, open source software toolbox for the analysis of UV SO2 camera data. The code is written in the Python programming language and emerged from the idea of a common analysis platform incorporating a selection of the most prevalent methods found in literature. piscope includes several routines for plume background retrievals, routines for cell and DOAS based camera calibration including two individual methods to identify the DOAS field of view (shape and position) within the camera images. Gas velocities can be retrieved either based on an optical flow analysis or using signal cross correlation. A correction for signal dilution (due to atmospheric scattering) can be performed based on topographic features in the images. The latter requires distance retrievals to the topographic features used for the correction. These distances can be retrieved automatically on a pixel base using intersections of individual pixel viewing directions with the local topography. The main features of piscope are presented based on dataset recorded at Mt. Etna, Italy in September 2015.
NASA Astrophysics Data System (ADS)
Witter, A. E.; Klinger, D. M.; Fan, X.; Lam, M.; Mathers, D. T.; Mabury, S. A.
2002-10-01
The forensic analysis of cocaine on currencies was optimized using a fractional, two-level experimental design that compared methanol and HCl extraction, SPE versus heptane pre-concentration, and extracted versus total ion chromatography. Subsequent student-initiated questions about levels of cocaine on U.S. and world currencies helped make connections to societal issues while teaching method optimization and chromatography. A significant correlation was found between the levels of cocaine and the age of the bills. Levels of cocaine on various world currencies followed expected drug-trafficking patterns with the highest levels found in the most developed countries.
Damage estimation of sewer pipe using subtitles of CCTV inspection video
NASA Astrophysics Data System (ADS)
Park, Kitae; Kim, Byeongcheol; Kim, Taeheon; Seo, Dongwoo
2017-04-01
Recent frequent occurrence of urban sinkhole serves as a momentum of the periodic inspection of sewer pipelines. Sewer inspection using a CCTV device needs a lot of time and efforts. Many of previous studies which reduce the laborious tasks are mainly interested in the developments of image processing S/W and exploring H/W. And there has been no attempt to find meaningful information from the existing CCTV images stored by the sewer maintenance manager. This study adopts a cross-correlation based image processing method and extracts sewer inspection device's location data from CCTV images. As a result of the analysis of location-time relation, it show strong correlation between device stand time and the sewer damages. In case of using this method to investigate sewer inspection CCTV images, it will save the investigator's efforts and improve sewer maintenance efficiency and reliability.
Revealing time bunching effect in single-molecule enzyme conformational dynamics.
Lu, H Peter
2011-04-21
In this perspective, we focus our discussion on how the single-molecule spectroscopy and statistical analysis are able to reveal enzyme hidden properties, taking the study of T4 lysozyme as an example. Protein conformational fluctuations and dynamics play a crucial role in biomolecular functions, such as in enzymatic reactions. Single-molecule spectroscopy is a powerful approach to analyze protein conformational dynamics under physiological conditions, providing dynamic perspectives on a molecular-level understanding of protein structure-function mechanisms. Using single-molecule fluorescence spectroscopy, we have probed T4 lysozyme conformational motions under the hydrolysis reaction of a polysaccharide of E. coli B cell walls by monitoring the fluorescence resonant energy transfer (FRET) between a donor-acceptor probe pair tethered to T4 lysozyme domains involving open-close hinge-bending motions. Based on the single-molecule spectroscopic results, molecular dynamics simulation, a random walk model analysis, and a novel 2D statistical correlation analysis, we have revealed a time bunching effect in protein conformational motion dynamics that is critical to enzymatic functions. Bunching effect implies that conformational motion times tend to bunch in a finite and narrow time window. We show that convoluted multiple Poisson rate processes give rise to the bunching effect in the enzymatic reaction dynamics. Evidently, the bunching effect is likely common in protein conformational dynamics involving in conformation-gated protein functions. In this perspective, we will also discuss a new approach of 2D regional correlation analysis capable of analyzing fluctuation dynamics of complex multiple correlated and anti-correlated fluctuations under a non-correlated noise background. Using this new method, we are able to map out any defined segments along the fluctuation trajectories and determine whether they are correlated, anti-correlated, or non-correlated; after which, a cross correlation analysis can be applied for each specific segment to obtain a detailed fluctuation dynamics analysis.
Leverage effect and its causality in the Korea composite stock price index
NASA Astrophysics Data System (ADS)
Lee, Chang-Yong
2012-02-01
In this paper, we investigate the leverage effect and its causality in the time series of the Korea Composite Stock Price Index from November of 1997 to September of 2010. The leverage effect, which can be quantitatively expressed as a negative correlation between past return and future volatility, is measured by using the cross-correlation coefficient of different time lags between the two time series of the return and the volatility. We find that past return and future volatility are negatively correlated and that the cross correlation is moderate and decays over 60 trading days. We also carry out a partial correlation analysis in order to confirm that the negative correlation between past return and future volatility is neither an artifact nor influenced by the traded volume. To determine the causality of the leverage effect within the decay time, we additionally estimate the cross correlation between past volatility and future return. With the estimate, we perform a statistical hypothesis test to demonstrate that the causal relation is in favor of the return influencing the volatility rather than the other way around.
Cross-validation of the Beunen-Malina method to predict adult height.
Beunen, Gaston P; Malina, Robert M; Freitas, Duarte I; Maia, José A; Claessens, Albrecht L; Gouveia, Elvio R; Lefevre, Johan
2010-08-01
The purpose of this study was to cross-validate the Beunen-Malina method for non-invasive prediction of adult height. Three hundred and eight boys aged 13, 14, 15 and 16 years from the Madeira Growth Study were observed at annual intervals in 1996, 1997 and 1998 and re-measured 7-8 years later. Height, sitting height and the triceps and subscapular skinfolds were measured; skeletal age was assessed using the Tanner-Whitehouse 2 method. Adult height was measured and predicted using the Beunen-Malina method. Maturity groups were classified using relative skeletal age (skeletal age minus chronological age). Pearson correlations, mean differences and standard errors of estimate (SEE) were calculated. Age-specific correlations between predicted and measured adult height vary between 0.70 and 0.85, while age-specific SEE varies between 3.3 and 4.7 cm. The correlations and SEE are similar to those obtained in the development of the original Beunen-Malina method. The Beunen-Malina method is a valid method to predict adult height in adolescent boys and can be used in European populations or populations from European ancestry. Percentage of predicted adult height is a non-invasive valid method to assess biological maturity.
Image velocimetry for clouds with relaxation labeling based on deformation consistency
NASA Astrophysics Data System (ADS)
Horinouchi, Takeshi; Murakami, Shin-ya; Kouyama, Toru; Ogohara, Kazunori; Yamazaki, Atsushi; Yamada, Manabu; Watanabe, Shigeto
2017-08-01
Correlation-based cloud tracking has been extensively used to measure atmospheric winds, but still difficulty remains. In this study, aiming at developing a cloud tracking system for Akatsuki, an artificial satellite orbiting Venus, a formulation is developed for improving the relaxation labeling technique to select appropriate peaks of cross-correlation surfaces which tend to have multiple peaks. The formulation makes an explicit use of consistency inherent in the type of cross-correlation method where template sub-images are slid without deformation; if the resultant motion vectors indicate a too-large deformation, it is contradictory to the assumption of the method. The deformation consistency is exploited further to develop two post processes; one clusters the motion vectors into groups within each of which the consistency is perfect, and the other extends the groups using the original candidate lists. These processes are useful to eliminate erroneous vectors, distinguish motion vectors at different altitudes, and detect phase velocities of waves in fluids such as atmospheric gravity waves. As a basis of the relaxation labeling and the post processes as well as uncertainty estimation, the necessity to find isolated (well-separated) peaks of cross-correlation surfaces is argued, and an algorithm to realize it is presented. All the methods are implemented, and their effectiveness is demonstrated with initial images obtained by the ultraviolet imager onboard Akatsuki. Since the deformation consistency regards the logical consistency inherent in template matching methods, it should have broad application beyond cloud tracking.
Long-term behaviour and cross-correlation water quality analysis of the River Elbe, Germany.
Lehmann, A; Rode, M
2001-06-01
This study analyses weekly data samples from the river Elbe at Magdeburg between 1984 and 1996 to investigate the changes in metabolism and water quality in the river Elbe since the German reunification in 1990. Modelling water quality variables by autoregressive component models and ARIMA models reveals the improvement of water quality due to the reduction of waste water emissions since 1990. The models are used to determine the long-term and seasonal behaviour of important water quality variables. Organic and heavy metal pollution parameters showed a significant decrease since 1990, however, no significant change of chlorophyll-a as a measure for primary production could be found. A new procedure for testing the significance of a sample correlation coefficient is discussed, which is able to detect spurious sample correlation coefficients without making use of time-consuming prewhitening. The cross-correlation analysis is applied to hydrophysical, biological, and chemical water quality variables of the river Elbe since 1984. Special emphasis is laid on the detection of spurious sample correlation coefficients.
Perspectives of Cross-Correlation in Seismic Monitoring at the International Data Centre
NASA Astrophysics Data System (ADS)
Bobrov, Dmitry; Kitov, Ivan; Zerbo, Lassina
2014-03-01
We demonstrate that several techniques based on waveform cross-correlation are able to significantly reduce the detection threshold of seismic sources worldwide and to improve the reliability of arrivals by a more accurate estimation of their defining parameters. A master event and the events it can find using waveform cross-correlation at array stations of the International Monitoring System (IMS) have to be close. For the purposes of the International Data Centre (IDC), one can use the spatial closeness of the master and slave events in order to construct a new automatic processing pipeline: all qualified arrivals detected using cross-correlation are associated with events matching the current IDC event definition criteria (EDC) in a local association procedure. Considering the repeating character of global seismicity, more than 90 % of events in the reviewed event bulletin (REB) can be built in this automatic processing. Due to the reduced detection threshold, waveform cross-correlation may increase the number of valid REB events by a factor of 1.5-2.0. Therefore, the new pipeline may produce a more comprehensive bulletin than the current pipeline—the goal of seismic monitoring. The analysts' experience with the cross correlation event list (XSEL) shows that the workload of interactive processing might be reduced by a factor of two or even more. Since cross-correlation produces a comprehensive list of detections for a given master event, no additional arrivals from primary stations are expected to be associated with the XSEL events. The number of false alarms, relative to the number of events rejected from the standard event list 3 (SEL3) in the current interactive processing—can also be reduced by the use of several powerful filters. The principal filter is the difference between the arrival times of the master and newly built events at three or more primary stations, which should lie in a narrow range of a few seconds. In this study, one event at a distance of about 2,000 km from the main shock was formed by three stations, with the stations and both events on the same great circle. Such spurious events are rejected by checking consistency between detections at stations at different back azimuths from the source region. Two additional effective pre-filters are f-k analysis and F prob based on correlation traces instead of original waveforms. Overall, waveform cross-correlation is able to improve the REB completeness, to reduce the workload related to IDC interactive analysis, and to provide a precise tool for quality check for both arrivals and events. Some major improvements in automatic and interactive processing achieved by cross-correlation are illustrated using an aftershock sequence from a large continental earthquake. Exploring this sequence, we describe schematically the next steps for the development of a processing pipeline parallel to the existing IDC one in order to improve the quality of the REB together with the reduction of the magnitude threshold.
NASA Technical Reports Server (NTRS)
Prosser, W. H.; Jackson, K. E.; Kellas, S.; Smith, B. T.; McKeon, J.; Friedman, A.
1995-01-01
Transverse matrix cracking in cross-ply gr/ep laminates was studied with advanced acoustic emission (AE) techniques. The primary goal of this research was to measure the load required to initiate the first transverse matrix crack in cross-ply laminates of different thicknesses. Other methods had been previously used for these measurements including penetrant enhanced radiography, optical microscopy, and audible acoustic microphone measurements. The former methods required that the mechanical test be paused for measurements at load intervals. This slowed the test procedure and did not provide the required resolution in load. With acoustic microphones, acoustic signals from cracks could not be clearly differentiated from other noise sources such as grip damage, specimen slippage, or test machine noise. A second goal for this work was to use the high resolution source location accuracy of the advanced acoustic emission techniques to determine whether the crack initiation site was at the specimen edge or in the interior of the specimen.In this research, advanced AE techniques using broad band sensors, high capture rate digital waveform acquisition, and plate wave propagation based analysis were applied to cross-ply composite coupons with different numbers of 0 and 90 degree plies. Noise signals, believed to be caused by grip damage or specimen slipping, were eliminated based on their plate wave characteristics. Such signals were always located outside the sensor gage length in the gripped region of the specimen. Cracks were confirmed post-test by microscopic analysis of a polished specimen edge, backscatter ultrasonic scans, and in limited cases, by penetrant enhanced radiography. For specimens with three or more 90 degree plies together, there was an exact 1-1 correlation between AE crack signals and observed cracks. The ultrasonic scans and some destructive sectioning analysis showed that the cracks extended across the full width of the specimen. Furthermore, the locations of the cracks from the AE data were in excellent agreement with the locations measured with the microscope. The high resolution source location capability of this technique, combined with an array of sensors, was able to determine that the cracks initiated at the specimen edges, rather than in the interior. For specimens with only one or two 90 degree plies, the crack-like signals were significantly smaller in amplitude and there was not a 1-1 correlation to observed cracks. This was similar to previous results. In this case, however, ultrasonic and destructive sectioning analysis revealed that the cracks did not extend across the specimen. They initiated at the edge, but did not propagate any appreciable distance into the specimen. This explains the much smaller AE signal amplitudes and the difficulty in correlating these signals to actual cracks in this, as well as in the previous study.
Cai, Jia; Tang, Yi
2018-02-01
Canonical correlation analysis (CCA) is a powerful statistical tool for detecting the linear relationship between two sets of multivariate variables. Kernel generalization of it, namely, kernel CCA is proposed to describe nonlinear relationship between two variables. Although kernel CCA can achieve dimensionality reduction results for high-dimensional data feature selection problem, it also yields the so called over-fitting phenomenon. In this paper, we consider a new kernel CCA algorithm via randomized Kaczmarz method. The main contributions of the paper are: (1) A new kernel CCA algorithm is developed, (2) theoretical convergence of the proposed algorithm is addressed by means of scaled condition number, (3) a lower bound which addresses the minimum number of iterations is presented. We test on both synthetic dataset and several real-world datasets in cross-language document retrieval and content-based image retrieval to demonstrate the effectiveness of the proposed algorithm. Numerical results imply the performance and efficiency of the new algorithm, which is competitive with several state-of-the-art kernel CCA methods. Copyright © 2017 Elsevier Ltd. All rights reserved.
Fotina, I; Lütgendorf-Caucig, C; Stock, M; Pötter, R; Georg, D
2012-02-01
Inter-observer studies represent a valid method for the evaluation of target definition uncertainties and contouring guidelines. However, data from the literature do not yet give clear guidelines for reporting contouring variability. Thus, the purpose of this work was to compare and discuss various methods to determine variability on the basis of clinical cases and a literature review. In this study, 7 prostate and 8 lung cases were contoured on CT images by 8 experienced observers. Analysis of variability included descriptive statistics, calculation of overlap measures, and statistical measures of agreement. Cross tables with ratios and correlations were established for overlap parameters. It was shown that the minimal set of parameters to be reported should include at least one of three volume overlap measures (i.e., generalized conformity index, Jaccard coefficient, or conformation number). High correlation between these parameters and scatter of the results was observed. A combination of descriptive statistics, overlap measure, and statistical measure of agreement or reliability analysis is required to fully report the interrater variability in delineation.
1981-10-07
new instrument (cf. Fig. 1) is simply a four - quadrant ring-diode multi- 5 plier (Fig. 2). The reference frequency (RF) and local oscillator (LO) inputs...movement, and scan speed of the corner-cube. Other Components. A rotating-sector chopper modulates the laser pulse train at a frequency of approximately 50...the cross-correlation experiment. In this application, the detection bandpass is simply displaced from DC to the chopper frequency; problems arising
Uncertainty Quantification Techniques of SCALE/TSUNAMI
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rearden, Bradley T; Mueller, Don
2011-01-01
The Standardized Computer Analysis for Licensing Evaluation (SCALE) code system developed at Oak Ridge National Laboratory (ORNL) includes Tools for Sensitivity and Uncertainty Analysis Methodology Implementation (TSUNAMI). The TSUNAMI code suite can quantify the predicted change in system responses, such as k{sub eff}, reactivity differences, or ratios of fluxes or reaction rates, due to changes in the energy-dependent, nuclide-reaction-specific cross-section data. Where uncertainties in the neutron cross-section data are available, the sensitivity of the system to the cross-section data can be applied to propagate the uncertainties in the cross-section data to an uncertainty in the system response. Uncertainty quantification ismore » useful for identifying potential sources of computational biases and highlighting parameters important to code validation. Traditional validation techniques often examine one or more average physical parameters to characterize a system and identify applicable benchmark experiments. However, with TSUNAMI correlation coefficients are developed by propagating the uncertainties in neutron cross-section data to uncertainties in the computed responses for experiments and safety applications through sensitivity coefficients. The bias in the experiments, as a function of their correlation coefficient with the intended application, is extrapolated to predict the bias and bias uncertainty in the application through trending analysis or generalized linear least squares techniques, often referred to as 'data adjustment.' Even with advanced tools to identify benchmark experiments, analysts occasionally find that the application models include some feature or material for which adequately similar benchmark experiments do not exist to support validation. For example, a criticality safety analyst may want to take credit for the presence of fission products in spent nuclear fuel. In such cases, analysts sometimes rely on 'expert judgment' to select an additional administrative margin to account for gap in the validation data or to conclude that the impact on the calculated bias and bias uncertainty is negligible. As a result of advances in computer programs and the evolution of cross-section covariance data, analysts can use the sensitivity and uncertainty analysis tools in the TSUNAMI codes to estimate the potential impact on the application-specific bias and bias uncertainty resulting from nuclides not represented in available benchmark experiments. This paper presents the application of methods described in a companion paper.« less
Pitarokoili, Kalliopi; Kronlage, Moritz; Bäumer, Philip; Schwarz, Daniel; Gold, Ralf; Bendszus, Martin; Yoon, Min-Suk
2018-01-01
Background: We present a clinical, electrophysiological, sonographical and magnetic resonance neurography (MRN) study examining the complementary role of two neuroimaging methods of the peripheral nervous system for patients with chronic inflammatory demyelinating polyneuropathy (CIDP). Furthermore, we explore the significance of cross-sectional area (CSA) increase through correlations with MRN markers of nerve integrity. Methods: A total of 108 nerve segments on the median, ulnar, radial, tibial and fibular nerve, as well as the lumbar and cervical plexus of 18 CIDP patients were examined with high-resonance nerve ultrasound (HRUS) and MRN additionally to the nerve conduction studies. Results: We observed a fair degree of correlation of the CSA values for all nerves/nerve segments between the two methods, with a low random error in Bland–Altman analysis (bias = HRUS-CSA − MRN-CSA, −0.61 to −3.26 mm). CSA in HRUS correlated with the nerve T2-weighted (nT2) signal increase as well as with diffusion tensor imaging parameters such as fractional anisotropy, a marker of microstructural integrity. HRUS-CSA of the interscalene brachial plexus correlated significantly with the MRN-CSA and nT2 signal of the L5 and S1 roots of the lumbar plexus. Conclusions: HRUS allows for reliable CSA imaging of all peripheral nerves and the cervical plexus, and CSA correlates with markers of nerve integrity. Imaging of proximal segments as well as the estimation of nerve integrity require MRN as a complementary method. PMID:29552093
Lindahl, Marianne; Andersen, Signe; Joergensen, Annette; Frandsen, Christian; Jensen, Liselotte; Benedikz, Eirikur
2018-01-01
The aim of this study was to translate and culturally adapt the Short Musculoskeletal Function Assessment (SMFA) into Danish (SMFA-DK) and assess the psychometric properties. SMFA was translated and cross-culturally adapted according to a standardized procedure. Minor changes in the wording in three items were made to adapt to Danish conditions. Acute patients (n = 201) and rehabilitation patients (n = 231) with musculoskeletal problems aged 18-87 years were included. The following analysis were made to evaluate psychometric quality of SMFA-DK: Reliability with Chronbach's alpha, content validity as coding according to the International Classification of Functioning, Disability and Health (ICF), floor/ceiling effects, construct validity as factor analysis, correlations between SMFA-DK and Short Form 36 and also known group method. Responsiveness and effect size were calculated. Cronbach's alpha values were between 0.79 and 0.94. SMFA-DK captured all components of the ICF, and there were no floor/ceiling effects. Factor analysis demonstrated four subscales. SMFA-DK correlated good with the SF-36 subscales for the rehabilitation patients and lower for the newly injured patients. Effect sizes were excellent and better for SMFA-DK than for SF-36. The study indicates that SMFA-DK can be a valid and responsive measure of outcome in rehabilitation settings.
Theoretical analysis of stack gas emission velocity measurement by optical scintillation
NASA Astrophysics Data System (ADS)
Yang, Yang; Dong, Feng-Zhong; Ni, Zhi-Bo; Pang, Tao; Zeng, Zong-Yong; Wu, Bian; Zhang, Zhi-Rong
2014-04-01
Theoretical analysis for an online measurement of the stack gas flow velocity based on the optical scintillation method with a structure of two parallel optical paths is performed. The causes of optical scintillation in a stack are first introduced. Then, the principle of flow velocity measurement and its mathematical expression based on cross correlation of the optical scintillation are presented. The field test results show that the flow velocity measured by the proposed technique in this article is consistent with the value tested by the Pitot tube. It verifies the effectiveness of this method. Finally, by use of the structure function of logarithmic light intensity fluctuations, the theoretical explanation of optical scintillation spectral characteristic in low frequency is given. The analysis of the optical scintillation spectrum provides the basis for the measurement of the stack gas flow velocity and particle concentration simultaneously.
In Vivo Fluorescence Correlation and Cross-Correlation Spectroscopy
NASA Astrophysics Data System (ADS)
Mütze, Jörg; Ohrt, Thomas; Petrášek, Zdeněk; Schwille, Petra
In this manuscript, we describe the application of Fluorescence Correlation Spectroscopy (FCS), Fluorescence Cross-Correlation Spectroscopy (FCCS), and scanning FCS (sFCS) to two in vivo systems. In the first part, we describe the application of two-photon standard and scanning FCS in Caenorhabditis elegans embryos. The differentiation of a single fertilized egg into a complex organism in C. elegans is regulated by a number of protein-dependent processes. The oocyte divides asymmetrically into two daughter cells of different developmental fate. Two of the involved proteins, PAR-2 and NMY-2, are studied. The second investigated system is the mechanism of RNA interference in human cells. An EGFP based cell line that allows to study the dynamics and localization of the RNA-induced silencing complex (RISC) with FCS in vivo is created, which has so far been inaccessible with other experimental methods. Furthermore, Fluorescence Cross-Correlation Spectroscopy is employed to highlight the asymmetric incorporation of labeled siRNAs into RISC.
A General Method for Targeted Quantitative Cross-Linking Mass Spectrometry.
Chavez, Juan D; Eng, Jimmy K; Schweppe, Devin K; Cilia, Michelle; Rivera, Keith; Zhong, Xuefei; Wu, Xia; Allen, Terrence; Khurgel, Moshe; Kumar, Akhilesh; Lampropoulos, Athanasios; Larsson, Mårten; Maity, Shuvadeep; Morozov, Yaroslav; Pathmasiri, Wimal; Perez-Neut, Mathew; Pineyro-Ruiz, Coriness; Polina, Elizabeth; Post, Stephanie; Rider, Mark; Tokmina-Roszyk, Dorota; Tyson, Katherine; Vieira Parrine Sant'Ana, Debora; Bruce, James E
2016-01-01
Chemical cross-linking mass spectrometry (XL-MS) provides protein structural information by identifying covalently linked proximal amino acid residues on protein surfaces. The information gained by this technique is complementary to other structural biology methods such as x-ray crystallography, NMR and cryo-electron microscopy[1]. The extension of traditional quantitative proteomics methods with chemical cross-linking can provide information on the structural dynamics of protein structures and protein complexes. The identification and quantitation of cross-linked peptides remains challenging for the general community, requiring specialized expertise ultimately limiting more widespread adoption of the technique. We describe a general method for targeted quantitative mass spectrometric analysis of cross-linked peptide pairs. We report the adaptation of the widely used, open source software package Skyline, for the analysis of quantitative XL-MS data as a means for data analysis and sharing of methods. We demonstrate the utility and robustness of the method with a cross-laboratory study and present data that is supported by and validates previously published data on quantified cross-linked peptide pairs. This advance provides an easy to use resource so that any lab with access to a LC-MS system capable of performing targeted quantitative analysis can quickly and accurately measure dynamic changes in protein structure and protein interactions.
Local normalization: Uncovering correlations in non-stationary financial time series
NASA Astrophysics Data System (ADS)
Schäfer, Rudi; Guhr, Thomas
2010-09-01
The measurement of correlations between financial time series is of vital importance for risk management. In this paper we address an estimation error that stems from the non-stationarity of the time series. We put forward a method to rid the time series of local trends and variable volatility, while preserving cross-correlations. We test this method in a Monte Carlo simulation, and apply it to empirical data for the S&P 500 stocks.
Apparatus and Method for Measuring Strain in Optical Fibers using Rayleigh Scatter
NASA Technical Reports Server (NTRS)
Froggatt, Mark E. (Inventor); Moore, Jason P. (Inventor)
2003-01-01
An apparatus and method for measuring strain in an optical fiber using the spectral shift of Rayleigh scattered light. The interference pattern produced by an air gap reflector and backscattered radiation is measured. Using Fourier Transforms, the spectrum of any section of fiber can be extracted. Cross correlation with an unstrained measurement produces a correlation peak. The location of the correlation peak indicates the strain level in the selected portion of optical fiber.
Periodontal inflamed surface area as a novel numerical variable describing periodontal conditions
2017-01-01
Purpose A novel index, the periodontal inflamed surface area (PISA), represents the sum of the periodontal pocket depth of bleeding on probing (BOP)-positive sites. In the present study, we evaluated correlations between PISA and periodontal classifications, and examined PISA as an index integrating the discrete conventional periodontal indexes. Methods This study was a cross-sectional subgroup analysis of data from a prospective cohort study investigating the association between chronic periodontitis and the clinical features of ankylosing spondylitis. Data from 84 patients without systemic diseases (the control group in the previous study) were analyzed in the present study. Results PISA values were positively correlated with conventional periodontal classifications (Spearman correlation coefficient=0.52; P<0.01) and with periodontal indexes, such as BOP and the plaque index (PI) (r=0.94; P<0.01 and r=0.60; P<0.01, respectively; Pearson correlation test). Porphyromonas gingivalis (P. gingivalis) expression and the presence of serum P. gingivalis antibodies were significant factors affecting PISA values in a simple linear regression analysis, together with periodontal classification, PI, bleeding index, and smoking, but not in the multivariate analysis. In the multivariate linear regression analysis, PISA values were positively correlated with the quantity of current smoking, PI, and severity of periodontal disease. Conclusions PISA integrates multiple periodontal indexes, such as probing pocket depth, BOP, and PI into a numerical variable. PISA is advantageous for quantifying periodontal inflammation and plaque accumulation. PMID:29093989
Gong, Gordon; Mattevada, Sravan; O'Bryant, Sid E
2014-04-01
Exposure to arsenic causes many diseases. Most Americans in rural areas use groundwater for drinking, which may contain arsenic above the currently allowable level, 10µg/L. It is cost-effective to estimate groundwater arsenic levels based on data from wells with known arsenic concentrations. We compared the accuracy of several commonly used interpolation methods in estimating arsenic concentrations in >8000 wells in Texas by the leave-one-out-cross-validation technique. Correlation coefficient between measured and estimated arsenic levels was greater with inverse distance weighted (IDW) than kriging Gaussian, kriging spherical or cokriging interpolations when analyzing data from wells in the entire Texas (p<0.0001). Correlation coefficient was significantly lower with cokriging than any other methods (p<0.006) for wells in Texas, east Texas or the Edwards aquifer. Correlation coefficient was significantly greater for wells in southwestern Texas Panhandle than in east Texas, and was higher for wells in Ogallala aquifer than in Edwards aquifer (p<0.0001) regardless of interpolation methods. In regression analysis, the best models are when well depth and/or elevation were entered into the model as covariates regardless of area/aquifer or interpolation methods, and models with IDW are better than kriging in any area/aquifer. In conclusion, the accuracy in estimating groundwater arsenic level depends on both interpolation methods and wells' geographic distributions and characteristics in Texas. Taking well depth and elevation into regression analysis as covariates significantly increases the accuracy in estimating groundwater arsenic level in Texas with IDW in particular. Published by Elsevier Inc.
The Utility of the Extended Images in Ambient Seismic Wavefield Migration
NASA Astrophysics Data System (ADS)
Girard, A. J.; Shragge, J. C.
2015-12-01
Active-source 3D seismic migration and migration velocity analysis (MVA) are robust and highly used methods for imaging Earth structure. One class of migration methods uses extended images constructed by incorporating spatial and/or temporal wavefield correlation lags to the imaging conditions. These extended images allow users to directly assess whether images focus better with different parameters, which leads to MVA techniques that are based on the tenets of adjoint-state theory. Under certain conditions (e.g., geographical, cultural or financial), however, active-source methods can prove impractical. Utilizing ambient seismic energy that naturally propagates through the Earth is an alternate method currently used in the scientific community. Thus, an open question is whether extended images are similarly useful for ambient seismic migration processing and verifying subsurface velocity models, and whether one can similarly apply adjoint-state methods to perform ambient migration velocity analysis (AMVA). Herein, we conduct a number of numerical experiments that construct extended images from ambient seismic recordings. We demonstrate that, similar to active-source methods, there is a sensitivity to velocity in ambient seismic recordings in the migrated extended image domain. In synthetic ambient imaging tests with varying degrees of error introduced to the velocity model, the extended images are sensitive to velocity model errors. To determine the extent of this sensitivity, we utilize acoustic wave-equation propagation and cross-correlation-based migration methods to image weak body-wave signals present in the recordings. Importantly, we have also observed scenarios where non-zero correlation lags show signal while zero-lags show none. This may be a valuable missing piece for ambient migration techniques that have yielded largely inconclusive results, and might be an important piece of information for performing AMVA from ambient seismic recordings.
McCleary, Richard; Chew, Kenneth S Y; Merrill, Vincent; Napolitano, Carol
2002-01-01
This study addresses a possible link between suicide and casino gambling. Resident suicide rates are analyzed for (a) a 1990 cross-section of 148 U.S. metropolitan areas and (b) before and after the advent of legalized casinos in five U.S. counties. Data are drawn from government and gaming industry sources. In cross-section, metro area suicide is strongly correlated with region, accidental death and homicide rates, age and race composition, and economic vitality, followed by a modest net positive correlation with casino presence. By contrast, the time series analysis yields no evidence of a gambling effect.
NASA Astrophysics Data System (ADS)
Velten, Hermano; Fazolo, Raquel Emy; von Marttens, Rodrigo; Gomes, Syrios
2018-05-01
As recently pointed out in [Phys. Rev. D 96, 083502 (2017), 10.1103/PhysRevD.96.083502] the evolution of the linear matter perturbations in nonadiabatic dynamical dark energy models is almost indistinguishable (quasidegenerated) to the standard Λ CDM scenario. In this work we extend this analysis to CMB observables in particular the integrated Sachs-Wolfe effect and its cross-correlation with large scale structure. We find that this feature persists for such CMB related observable reinforcing that new probes and analysis are necessary to reveal the nonadiabatic features in the dark energy sector.
Brief communication: Landslide motion from cross correlation of UAV-derived morphological attributes
NASA Astrophysics Data System (ADS)
Peppa, Maria V.; Mills, Jon P.; Moore, Phil; Miller, Pauline E.; Chambers, Jonathan E.
2017-12-01
Unmanned aerial vehicles (UAVs) can provide observations of high spatio-temporal resolution to enable operational landslide monitoring. In this research, the construction of digital elevation models (DEMs) and orthomosaics from UAV imagery is achieved using structure-from-motion (SfM) photogrammetric procedures. The study examines the additional value that the morphological attribute of openness
, amongst others, can provide to surface deformation analysis. Image-cross-correlation functions and DEM subtraction techniques are applied to the SfM outputs. Through the proposed integrated analysis, the automated quantification of a landslide's motion over time is demonstrated, with implications for the wider interpretation of landslide kinematics via UAV surveys.
Dynamical behavior of the correlation between meteorological factors
NASA Astrophysics Data System (ADS)
You, Cheol-Hwan; Chang, Ki-Ho; Lee, Jun-Ho; Kim, Kyungsik
2017-12-01
We study the temporal and spatial variation characteristics of meteorological factors (temperature, humidity, and wind velocity) at a meteorological tower located on Bosung-gun of South Korea. We employ the detrended cross-correlation analysis (DCCA) method to extract the overall tendency of the hourly variation from data of meteorological factors. The relationships between meteorological factors are identified and quantified by using DCCA coefficients. From our results, we ascertain that the DCCA coefficient between temperature and humidity at time lag m = 24 has the smallest value at the height of 10 m of the measuring tower. Particularly, the DCCA coefficient between temperature and wind speed at time lag m = 24 has the largest value at a height of 10 m of the measuring tower
ERIC Educational Resources Information Center
Lancia, Leonardo; Fuchs, Susanne; Tiede, Mark
2014-01-01
Purpose: The aim of this article was to introduce an important tool, cross-recurrence analysis, to speech production applications by showing how it can be adapted to evaluate the similarity of multivariate patterns of articulatory motion. The method differs from classical applications of cross-recurrence analysis because no phase space…
Watts, Kristen; Lagalante, Anthony
2018-06-06
Art conservation science is in need of a relatively nondestructive way of rapidly identifying the binding media within a painting cross-section and isolating binding media to specific layers within the cross-section. Knowledge of the stratigraphy of cross-sections can be helpful for removing possible unoriginal paint layers on the artistic work. Desorption electrospray ionization-mass spectrometry (DESI-MS) was used in ambient mode to study cross-sections from mock-up layered paint samples and samples from a 17th century baroque painting. The DESI spray was raster scanned perpendicular to the cross-section layers to maximize lateral resolution then analyzed with a triple quadrupole mass analyzer in linear ion trap mode. From these scans, isobaric mass maps were created to map the locations of masses indicative of particular binding media onto the cross-sections. Line paint-outs of pigments in different binding media showed specific and unique ions to distinguish between the modern acrylic media and the lipid containing binding media. This included: OP (EO) 9 surfactant in positive ESI for acrylic (m/z 621), and oleic (m/z 281), stearic (m/z 283), and azelaic (m/z 187) acids in negative ESI for oil and egg tempera. DESI-MS maps of mock-up cross-sections of layered pigmented binding media showed correlation between these ions and the layers with a spatial resolution of 100 μm. DESI-MS is effective in monitoring binding media within an intact painting cross-section via mass spectrometric methods. This includes distinguishing between lipid-containing and modern binding materials present in a known mockup cross section matrix as well as identifying lipid binding media in a 17th century baroque era painting. This article is protected by copyright. All rights reserved.
NASA Technical Reports Server (NTRS)
Macdoran, P. F. (Inventor)
1984-01-01
The columnar electron content of the ionosphere between a spacecraft and a receiver is measured in realtime by cross correlating two coherently modulated signals transmitted at different frequencies (L1,L2) from the spacecraft to the receiver using a cross correlator. The time difference of arrival of the modulated signals is proportional to electron content of the ionosphere. A variable delay is adjusted relative to a fixed delay in the respective channels (L1,L2) to produce a maximum at the cross correlator output. The difference in delay required to produce this maximum is a measure of the columnar electron content of the ionosphere. A plurality of monitoring stations and spacecraft (Global Positioning System satellites) are employed to locate any terrestrial event that produces an ionospheric disturbance.
NASA Astrophysics Data System (ADS)
Iwasaki, Y.; Mochizuki, K.; Ishise, M.; Todd, E. K.; Schwartz, S. Y.; Henrys, S. A.; Savage, M. K.; Sheehan, A.; Ito, Y.; Wallace, L.; Webb, S. C.; Zal, H. J.; Yamada, T.; Shinohara, M.
2017-12-01
From May 2014 to June 2015 a marine seismic and geodetic experiment was conducted at the Hikurangi subduction margin. During this experiment, a slow-slip event (SSE) with equivalent moment magnitude of Mw 6.8 occurred for two weeks starting in late September 2014, directly beneath the ocean bottom seismometer (OBS) network (Wallace et al., 2016). In this study, we used the continuous waveform data recorded by these OBSs. We calculated a cross correlation coefficient between the two horizontal components and applied a polarization analysis every 10 seconds for 30 second-long OBS waveform records. As a result, we detected the continuous arrival of S-wave signals that appeared to have started in the latter half of the SSE. This continuous signal was identified as tremor and its source location was determined by the envelope cross-correlation method (Todd et al., 2017, in prep). Our result, however, suggests that these signals occur continuously rather than as sporadic individual events, and that they last for more than two weeks. Polarization directions changed at the same time and then remained stable through the two week duration. Such stable polarized directions can only be identified during this period. Our analysis requires fewer OBS than other methods for monitoring such S-wave signals, which may enable us to detect as yet unidentified signals in the Hikurangi margin where seismic attenuation has been shown to be large. The continuous signals with a stable polarization direction were only observed at OBS stations in a limited region, which suggests that the signals were generated near the up-dip edge of the slow slip area and surrounding a subducted seamount. Sources of the continuous signals appear to have migrated from south to north . This observation is consistent with the location of individual tremors identified with envelope cross-correlation methods (Todd et al., 2017, in prep). The slow slip along the plate interface circumvented the subducted seamount (Wallace et al., 2016). By comparing our result with the slip distribution, we can put more constraints on relationship between frictional properties along the plate interface and subducting topographic features such as seamounts. Migration of the sources of the continuous signal may further provide us with information on rupture propagation of the slow slip.
Wig, Gagan S.; Laumann, Timothy O.; Cohen, Alexander L.; Power, Jonathan D.; Nelson, Steven M.; Glasser, Matthew F.; Miezin, Francis M.; Snyder, Abraham Z.; Schlaggar, Bradley L.; Petersen, Steven E.
2014-01-01
We describe methods for parcellating an individual subject's cortical and subcortical brain structures using resting-state functional correlations (RSFCs). Inspired by approaches from social network analysis, we first describe the application of snowball sampling on RSFC data (RSFC-Snowballing) to identify the centers of cortical areas, subdivisions of subcortical nuclei, and the cerebellum. RSFC-Snowballing parcellation is then compared with parcellation derived from identifying locations where RSFC maps exhibit abrupt transitions (RSFC-Boundary Mapping). RSFC-Snowballing and RSFC-Boundary Mapping largely complement one another, but also provide unique parcellation information; together, the methods identify independent entities with distinct functional correlations across many cortical and subcortical locations in the brain. RSFC parcellation is relatively reliable within a subject scanned across multiple days, and while the locations of many area centers and boundaries appear to exhibit considerable overlap across subjects, there is also cross-subject variability—reinforcing the motivation to parcellate brains at the level of individuals. Finally, examination of a large meta-analysis of task-evoked functional magnetic resonance imaging data reveals that area centers defined by task-evoked activity exhibit correspondence with area centers defined by RSFC-Snowballing. This observation provides important evidence for the ability of RSFC to parcellate broad expanses of an individual's brain into functionally meaningful units. PMID:23476025
Photogrammetric Analysis of Attractiveness in Indian Faces
Duggal, Shveta; Kapoor, DN; Verma, Santosh; Sagar, Mahesh; Lee, Yung-Seop; Moon, Hyoungjin
2016-01-01
Background The objective of this study was to assess the attractive facial features of the Indian population. We tried to evaluate subjective ratings of facial attractiveness and identify which facial aesthetic subunits were important for facial attractiveness. Methods A cross-sectional study was conducted of 150 samples (referred to as candidates). Frontal photographs were analyzed. An orthodontist, a prosthodontist, an oral surgeon, a dentist, an artist, a photographer and two laymen (estimators) subjectively evaluated candidates' faces using visual analog scale (VAS) scores. As an objective method for facial analysis, we used balanced angular proportional analysis (BAPA). Using SAS 10.1 (SAS Institute Inc.), the Turkey's studentized range test and Pearson correlation analysis were performed to detect between-group differences in VAS scores (Experiment 1), to identify correlations between VAS scores and BAPA scores (Experiment 2), and to analyze the characteristic features of facial attractiveness and gender differences (Experiment 3); the significance level was set at P=0.05. Results Experiment 1 revealed some differences in VAS scores according to professional characteristics. In Experiment 2, BAPA scores were found to behave similarly to subjective ratings of facial beauty, but showed a relatively weak correlation coefficient with the VAS scores. Experiment 3 found that the decisive factors for facial attractiveness were different for men and women. Composite images of attractive Indian male and female faces were constructed. Conclusions Our photogrammetric study, statistical analysis, and average composite faces of an Indian population provide valuable information about subjective perceptions of facial beauty and attractive facial structures in the Indian population. PMID:27019809
Locating scatterers while drilling using seismic noise due to tunnel boring machine
NASA Astrophysics Data System (ADS)
Harmankaya, U.; Kaslilar, A.; Wapenaar, K.; Draganov, D.
2018-05-01
Unexpected geological structures can cause safety and economic risks during underground excavation. Therefore, predicting possible geological threats while drilling a tunnel is important for operational safety and for preventing expensive standstills. Subsurface information for tunneling is provided by exploratory wells and by surface geological and geophysical investigations, which are limited by location and resolution, respectively. For detailed information about the structures ahead of the tunnel face, geophysical methods are applied during the tunnel-drilling activity. We present a method inspired by seismic interferometry and ambient-noise correlation that can be used for detecting scatterers, such as boulders and cavities, ahead of a tunnel while drilling. A similar method has been proposed for active-source seismic data and validated using laboratory and field data. Here, we propose to utilize the seismic noise generated by a Tunnel Boring Machine (TBM), and recorded at the surface. We explain our method at the hand of data from finite-difference modelling of noise-source wave propagation in a medium where scatterers are present. Using the modelled noise records, we apply cross-correlation to obtain correlation gathers. After isolating the scattered arrivals in these gathers, we cross-correlate again and invert for the correlated traveltime to locate scatterers. We show the potential of the method for locating the scatterers while drilling using noise records due to TBM.
Liu, Jun; Khattak, Asad J
2017-12-01
Drivers undertaking risky behaviors at highway-rail grade crossings are often severely injured in collisions with trains. Among these behaviors, gate-violation (referring to driving around or through the gates that were activated and lowered by an approaching train) seems to be one of the most dangerous actions a driver might take at a gated crossing; it may compromise the intended safety improvement made by adding gates at crossings. This study develops a nuanced conceptual framework that uses path analysis to explore the contributing factors to gate-violation behaviors and the correlation between gate-violation behaviors and the crash consequence - the driver injury severity. Further, using geo-spatial modeling techniques, this study explores whether the correlates of gate-violation behaviors and their associations with injury severity are stationary across diverse geographic contexts of the United States. Geo-spatial modeling shows that the correlates of gate-violation and its associations with injury severity vary substantially across the United States. Spatial variations in correlates of gate-violation and injury severity are mapped by estimating geographically weighted regressions; the maps can serve as an instrument for screening safety improvements and help identify regions that need safety improvements. For example, the results show that two-quadrant gates are more likely to have gate-violation crashes than four-quadrant gates in Iowa, Illinois, Wisconsin and Minnesota. These states may need to receive more attentions on the enforcement of inhibiting gate-violation at crossings with two-quadrant gates or have the priority over other states to upgrade these crossings to four-quadrant gates if financially feasible. Copyright © 2017. Published by Elsevier Ltd.
Through-the-Wall Radar Simulations for Complex Room Imaging
2010-05-01
obtained by combining images from different aspect angles. We demonstrate the advantages of using cross -polarization for detecting human targets. We...3. Numerical Results 6 3.1 SAR Images from a Ground-based Radar System ..........................................................6 3.2 Using Cross ...bottom row contains the cross -correlation between the images created by the two methods. ....................16 vi Acknowledgments This study
Wang, Yuan; Wu, Mingwei; Ai, Chunzhi; Wang, Yonghua
2015-01-01
Presently, 151 widely-diverse pyridinylimidazole-based compounds that show inhibitory activities at the TNF-α release were investigated. By using the distance comparison technique (DISCOtech), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) methods, the pharmacophore models and the three-dimensional quantitative structure-activity relationships (3D-QSAR) of the compounds were explored. The proposed pharmacophore model, including two hydrophobic sites, two aromatic centers, two H-bond donor atoms, two H-bond acceptor atoms, and two H-bond donor sites characterizes the necessary structural features of TNF-α release inhibitors. Both the resultant CoMFA and CoMSIA models exhibited satisfactory predictability (with Q2 (cross-validated correlation coefficient) = 0.557, R2ncv (non-cross-validated correlation coefficient) = 0.740, R2pre (predicted correlation coefficient) = 0.749 and Q2 = 0.598, R2ncv = 0.767, R2pre = 0.860, respectively). Good consistency was observed between the 3D-QSAR models and the pharmacophore model that the hydrophobic interaction and hydrogen bonds play crucial roles in the mechanism of actions. The corresponding contour maps generated by these models provide more diverse information about the key intermolecular interactions of inhibitors with the surrounding environment. All these models have extended the understanding of imidazole-based compounds in the structure-activity relationship, and are useful for rational design and screening of novel 2-thioimidazole-based TNF-α release inhibitors. PMID:26307982