scholarly journals Analysis of the transmembrane potential of embryos exposed to action of nickel, cobalt, tin and zinc

2018 ◽  
Vol 9 (2) ◽  
pp. 216-222
Author(s):  
G. V. Galyk ◽  
Z. Y. Fedorovych ◽  
E. I. Lychkovsky ◽  
D. I. Sanagursky
Keyword(s):  
Correlation Functions ◽  
Cross Correlation ◽  
Transmembrane Potential ◽  
Development Stage ◽  
Time Shift ◽  
Transmembrane Potentials ◽  
Nickel Cobalt ◽  
Cross Correlation Analysis ◽  
The Cross ◽  
Degree Of Similarity

Germ cells of aquatic organisms are complex systems whose growth and development depends on many factors, one of which is the composition of the aquatic environment. We used parameters in our analysis from aggregate data available from published literature. They are data of the transmembrane potential of the germinal cells of Misgurnus fossilis (Linnaeus, 1758) at the development stage from 180th to 360th minutes. Embryos were incubated in an environment with nickel, cobalt, tin, and zinc ions and without them. Plotted lines of the transmembrane potential were digitized and calibrated at intervals of 10 minutes. Rows of numerical values of the transmembrane potentials were obtained. These rows were used for calculation of autocorrelation and cross-cross-correlation functions. It was established that the transmembrane potential describes nonperiodic and quasi-periodic oscillations. The higher statistically significant values of the autocorrelation coefficients were observed in the first lags. Autocorrelation analysis indicates that the periods of oscillations of the transmembrane potential increase with the action of nickel, cobalt, tin and zinc on the germ. The phenomena and processes that occur in the germ cell are well reflected at the initial stages of the auto-correction and are lost when the magnitude of the lag increases. The degree of similarity of transmembrane potentials with the help of cross-correlation analysis is quantitatively characterized. The distribution of fluctuations of cross-correlation functions with complex dynamics, which arise with time shifts both in the forward and reverse directions, were established. It is established that for large values of time shifts, the cross-correlation coefficient is a low-informative indicator, since information about the influence of the factor on the living system is lost. A graph for a given time shift was constructed. The connection between the nodes is the magnitude of the cross-correlation coefficients between the vapor of the transmembrane potentials, which indicate the degree of similarity of the bioelectric processes. Graphs will be used for qualitative and quantitative study of system dynamics. The obtained results confirm the existence of a close relationship between environmental nickel, cobalt, tin, and zinc and the oscillation of transmembrane potential during early embryogenesis.

Bounds on the Cross-Correlation Functions of State m-Sequences

1987 ◽  
Vol 35 (3) ◽  
pp. 305-312 ◽  
Author(s):  
A. Shaar ◽  
C. Woodcock ◽  
P. Davies
Keyword(s):  
Correlation Functions ◽  
Cross Correlation ◽  
The Cross ◽  
M Sequences

Analyzing the Impact of COVID-19 on the Cross-Correlations between Financial Search Engine Data and Movie Box Office

2020 ◽  
pp. 2150021
Author(s):  
Renyu Wang ◽  
Yujie Xie ◽  
Hong Chen ◽  
Guozhu Jia
Keyword(s):  
Financial Market ◽  
Cross Correlation ◽  
Multifractal Spectrum ◽  
Movie Industry ◽  
Box Office ◽  
Cross Correlation Analysis ◽  
Cross Correlations ◽  
The Cross ◽  
Google Search ◽  
The Impact

This paper explores the COVID-19 influences on the cross-correlation between the movie market and the financial market. The nonlinear cross-correlations between movie box office data and Google search volumes of financial terms such as Dow Jones Industrial Average (DJIA), NASDAQ and PMI are investigated based on multifractal detrended cross-correlation analysis (MF-DCCA). The empirical results show there are nonlinear cross-correlations between movie market and financial market. Metrics such as Hurst exponents, singular exponents and multifractal spectrum demonstrate that the cross-correlation between movie market and financial market is persistent, and the cross-correlation in long term is more stable than that in short term. In the COVID-19 period, the multifractal features of cross-correlation become stronger implying that COVID-19 enhanced the complexity between the movie industry and the financial market. Furthermore, through the rolling window analysis, the Hurst exponent dynamic trends indicate that COVID-19 has a clear influence on the cross-correlation between movie market and financial market.

Multiscale Multifractal Detrended Cross-Correlation Analysis of High-Frequency Financial Time Series

2019 ◽  
Vol 18 (03) ◽  
pp. 1950014 ◽  
Author(s):  
Jingjing Huang ◽  
Danlei Gu
Keyword(s):  
Time Series ◽  
Correlation Analysis ◽  
High Frequency ◽  
Cross Correlation ◽  
Financial Time Series ◽  
Chinese Market ◽  
Change Of Scale ◽  
Cross Correlation Analysis ◽  
Cross Correlations ◽  
The Cross

In order to obtain richer information on the cross-correlation properties between two time series, we introduce a method called multiscale multifractal detrended cross-correlation analysis (MM-DCCA). This method is based on the Hurst surface and can be used to study the non-linear relationship between two time series. By sweeping through all the scale ranges of the multifractal structure of the complex system, it can present more information than the multifractal detrended cross-correlation analysis (MF-DCCA). In this paper, we use the MM-DCCA method to study the cross-correlations between two sets of artificial data and two sets of 5[Formula: see text]min high-frequency stock data from home and abroad. They are SZSE and SSEC in the Chinese market, and DJI and NASDAQ in the US market. We use Hurst surface and Hurst exponential distribution histogram to analyze the research objects and find that SSEC, SZSE and DJI, NASDAQ all show multifractal properties and long-range cross-correlations. We find that the fluctuation of the Hurst surface is related to the positive and negative of [Formula: see text], the change of scale range, the difference of national system, and the length of time series. The results show that the MM-DCCA method can give more abundant information and more detailed dynamic processes.

MULTISCALE DETRENDED CROSS-CORRELATION ANALYSIS OF STOCK MARKETS

Fractals ◽  
2014 ◽  
Vol 22 (04) ◽  
pp. 1450007 ◽  
Author(s):  
YI YIN ◽  
PENGJIAN SHANG
Keyword(s):  
Correlation Analysis ◽  
Stock Markets ◽  
Cross Correlation ◽  
Statistical Characteristics ◽  
Detailed Knowledge ◽  
Stock Indices ◽  
Regional Markets ◽  
Cross Correlation Analysis ◽  
Cross Correlations ◽  
The Cross

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.

Pipeline system identification through cross-correlation analysis

2002 ◽  
Vol 216 (3) ◽  
pp. 133-142 ◽  
Author(s):  
S B M Beck ◽  
N J Williamson ◽  
N D Sims ◽  
R Stanway
Keyword(s):  
Correlation Analysis ◽  
Cross Correlation ◽  
Correlation Technique ◽  
Pipeline System ◽  
Pipe Network ◽  
Cross Correlation Analysis ◽  
Valve Position ◽  
Single Sensor ◽  
The Cross ◽  
Cross Correlation Technique

The pipeline systems used to carry liquids and gases for the ventilation of buildings, water distributions networks, and the oil and chemical industries are usually monitored by a multiplicity of pressure, flow, and valve position sensors. By comparing the input signal to a valve with the pressure reading from the network using cross-correlation analysis, the technique described in this paper enables a single sensor to be used for monitoring. Specifically, the offset and gradient change of the cross-correlation function show the time delay between the input wave and the acquired output signal. These reflections arise from junctions, valves, and terminations, which can be located effectively using the cross-correlation technique. Investigations using a T-shaped pipe network have been conducted with a valve inserted in the pipeline to introduce artificial water hammer-type perturbations into the system. Both computational and experimental data are presented and the results are compared with the actual pipe network geometry. It is shown that it is possible to identify the location of various features of the network from the reflections and thus to perform either system characterisation or condition monitoring.

scholarly journals Automated Threshold Determination of Auditory Evoked Brainstem Responses by Cross-correlation Analysis with Varying Sweep Number

2019 ◽  
Author(s):  
Haoyu Wang ◽  
Bei Li ◽  
Xu Ding ◽  
Xueling Wang ◽  
Zhiwu Huang ◽  
...  
Keyword(s):  
Cross Correlation ◽  
Test Procedure ◽  
Auditory Brainstem ◽  
Time Shift ◽  
Strong Response ◽  
Reliable Determination ◽  
Threshold Determination ◽  
Cross Correlation Analysis ◽  
Brainstem Response

ABSTRACTAuditory brainstem response (ABR) is widely employed to evaluate the hearing function, both in clinics and basic research. Despite many attempts for automation over decades, reliable determination of threshold stimulus level still relies on human visual identification of waveform, which oftentimes is subjective. Here, we report a robust procedure for automatic and accurate threshold determination in both mouse and human ABR. Contrary to prior approaches, in our new threshold determination algorithm, the on-going averaging is stopped once the waveform is confirmed by a cross-correlation time shift approach. The flexible ending sweep numbers for different stimuli is used to inform the threshold determination. We found a good match of the threshold readings between the algorithm and the human judges. Moreover, in the algorithm, smaller sweep number is required for strong response from supra-threshold level, and thus a considerable portion of sweeps can be saved in comparison to the case with level averaging of a fix number. These features are attractive and implementation of this method in commercial devices will make the ABR test procedure more objective and efficient.

scholarly journals CROSS-CORRELATION ANALYSIS OF THE SPATIAL INTERACTIONS BETWEEN TISSUE COMPARTMENTS OF THE RENAL CORPUSCLE

2011 ◽  
Vol 21 (3) ◽  
pp. 151
Author(s):  
Terry M Mayhew
Keyword(s):  
Correlation Functions ◽  
Cross Correlation ◽  
Functional Integration ◽  
Spatial Interactions ◽  
Renal Corpuscle ◽  
Cross Correlation Analysis ◽  
Cross Covariance ◽  
Kidney Morphology ◽  
Tissue Compartments ◽  
Urinary Space

The renal corpuscle is a multi-compartment unit of kidney morphology which is important for normal ultrafiltration of blood. Its structure is perturbed during ontogeny, disease and experimental manipulation. Transmission electron microscopy and second-order stereological tools (cross covariance and cross correlation functions) were used to examine 3-D spatial interactions between the main tissue compartments (glomerular capillaries, podocytes, mesangium, urinary space) of the renal corpuscle in normal adult rats. Volume densities, covariance and correlation functions were estimated by counting test points (randomly positioned) and linear dipole probes (randomly positioned and orientated) superimposed on random samples of photomontages prepared from ultrathin resin sections. Differences in clustering exist between compartments (at distances < 8 μm, mesangium is the most tightly-clustered and capillaries the least tightly-clustered compartment; > 8 μm, compartments are neither hypodisperse nor hyperdisperse). Despite this, cross correlation functions for linked sets of compartments (capillary-mesangium, capillary-podocytes, capillary-urinary space, mesangium-podocytes, mesangium-urinary space and podocytes-urinary space) did not vary with dipole distance. This indicates that the spatial relations between linked compartments do not favour attraction or repulsion. In addition, inter-individual variation is greater for some linked compartments than others. Variation is less for compartments (capillary-podocyte and capillary-urinary space) which contribute to the ultrafiltration barrier and this probably reflects the structural and functional integration evident at this site as well as the higher volume densities (and smaller inter-subject variation) for capillaries.

Dynamic Cross-Correlations between Investors’ Attention and CSI300 Index Futures

2019 ◽  
Vol 18 (04) ◽  
pp. 1950022
Author(s):  
Xiong Xiong ◽  
Kewei Xu ◽  
Dehua Shen
Keyword(s):  
Cross Correlation ◽  
Futures Market ◽  
Relative Activity ◽  
Short Term ◽  
Index Futures ◽  
Search Volume ◽  
Cross Correlation Analysis ◽  
Cross Correlations ◽  
The Cross

Using search volume on Baidu Index as the proxy for investors’ attention, we investigate the dynamic nonlinear relationship between investors’ attention and CSI300 index futures market. Multifractal detrend cross-correlation analysis (MF-DCCA) is employed to explore the multifractal features of the cross-correlations between investors’ attention and the return and relative activity of index futures market. We find that the power-law cross-correlations between investors’ attention and CSI300 index futures market are stronger in the short term than in the long term, and the cross-correlations are significantly multifractal. Precisely, the cross-correlation between abnormal search volume (ASV) and the relative activity is persistent, and the cross-correlation between ASV and return of IF is persistent in the short term but weakly anti-persistent in the long term. Besides, we also find that, with the restriction on index futures market, the cross-correlations between investors’ attention and CSI300 index futures market become less stable.

scholarly journals Multiwavelength cross-correlation analysis of the simulated cosmic web

2020 ◽  
Vol 494 (4) ◽  
pp. 5603-5618 ◽  
Author(s):  
C Gheller ◽  
F Vazza
Keyword(s):  
Faraday Rotation ◽  
Cross Correlation ◽  
Future Generation ◽  
Matter Distribution ◽  
X Ray ◽  
Galaxy Distribution ◽  
Cross Correlation Analysis ◽  
The Galaxy ◽  
The Cross ◽  
Diffuse Matter

ABSTRACT We used magnetohydrodynamical cosmological simulations to investigate the cross-correlation between different observables (i.e. X-ray emission, Sunyaev–Zeldovich (SZ) signal at 21 cm, H i temperature decrement, diffuse synchrotron emission, and Faraday Rotation) as a probe of the diffuse matter distribution in the cosmic web. We adopt a uniform and simplistic approach to produce synthetic observations at various wavelengths, and we compare the detection chances of different combinations of observables correlated with each other and with the underlying galaxy distribution in the volume. With presently available surveys of galaxies and existing instruments, the best chances to detect the diffuse gas in the cosmic web outside of haloes is by cross-correlating the distribution of galaxies with SZ observations. We also find that the cross-correlation between the galaxy network and the radio emission or the Faraday Rotation can already be used to limit the amplitude of extragalactic magnetic fields, well outside of the cluster volume usually explored by existing radio observations, and to probe the origin of cosmic magnetism with the future generation of radio surveys.

Development of technologies for reducing the error of traditional algorithms of correlation analysis of noisy signals

2020 ◽  
pp. 9-16
Author(s):  
Telman A. Aliev ◽  
Naila F. Musaeva ◽  
Narmin E. Rzayeva ◽  
Ana I. Mammadova
Keyword(s):  
Correlation Analysis ◽  
Correlation Functions ◽  
Cross Correlation ◽  
Observation Time ◽  
Noisy Signal ◽  
Factors Affecting ◽  
Useful Signal ◽  
Noisy Signals ◽  
Traditional Technologies ◽  
The Cross

The authors analyze the factors affecting the errors in the estimates of the correlation functions of the noisy signals when using traditional calculation algorithms. It is shown that the sum noise of the noisy signal in many cases consists of the noise caused by external factors and the noise caused by the initiation of various defects during the operation of control objects. For this reason, in order to eliminate the error in the results of the correlation analysis of noisy signals, it is necessary to create algorithms and technologies for determining the estimate of the noise variance and the cross-correlation functions between the useful signal and the noise. For this purpose, appropriate algorithms and technologies are proposed that open up the possibility of reducing the error of traditional technologies for determining the estimates of correlation functions. With the purpose of reducing the error of the results of correlation analysis, a technology is proposed for determining the approximate equivalent samples of the noise of the noisy signals. It is shown that using the equivalent noise samples, it is possible to obtain results that are identical to the results of using real samples of the noise in the correlation analysis of the same signals. Moreover, by extracting the equivalent noise samples from the noisy signal, the equivalent samples of the useful signal are also determined, which allow determining the estimates equivalent to the estimates of the correlation functions of the useful signal. At the same time, having equivalent noise samples and useful signal samples, the estimates of the cross-correlation function between the useful signal and the noise are determined. The study have shown that despite certain errors in the equivalent samples compared to the true samples, with a sufficient observation time using equivalent samples, the error of traditional technologies for the correlation analysis of noisy signals can be significantly reduced. These technologies can also be used to correct errors in the results of the analysis of experimental data in information-measuring and other measuring complexes and systems, which will significantly improve their metrological characteristics.

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