Lévy scaling: The diffusion entropy analysis applied to DNA sequences

Scafetta, Nicola; Latora, Vito; Grigolini, Paolo

doi:10.1103/physreve.66.031906

Cited by 55 publications

(63 citation statements)

References 37 publications

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“…Analytical techniques such as wavelet transform and diffusion entropy analysis have been often applied to the analysis of time series arising from demographic data [28], physical processes [6] and biological series [31]. Investigation of nonstationarity has also been extensively done on time series of econometrics data [9] to uncover hidden trends and seasonalities.…”

Section: Related Workmentioning

confidence: 99%

On Nonstationarity of Human Contact Networks

Scellato

Musolesi

Mascolo

et al. 2010

2010 IEEE 30th International Conference on Distributed Computing Systems Workshops

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Abstract-The measurement and the analysis of the temporal patterns arising in human networks is of fundamental importance to many application domains including targeted advertising, opportunistic routing, resource provisioning (e.g., bandwidth allocation in infrastructured wireless networks) and, more in general, modeling of human social behavior.In this paper we present a novel and exhaustive study of the temporal dynamics of human networks and apply it to different sets of wireless network traces. We consider networks of contacts among users (i.e., peer-to-peer opportunistic networks). We show that we are able to quantify how the amount of information associated to the process evolves over time by using techniques based on time series analysis. We also demonstrate how regular patterns appear only at certain time scales: network dynamics appears nonstationary, in the sense that its statistical description is different at various time scales. These results provide a new methodology to accurately and quantitatively investigate the temporal properties of any type of human interactions and open new directions towards a better understanding of the regular nature of human social behavior.

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Section: Related Workmentioning

confidence: 99%

On Nonstationarity of Human Contact Networks

Scellato

Musolesi

Mascolo

et al. 2010

2010 IEEE 30th International Conference on Distributed Computing Systems Workshops

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“…It has been determined [4] that a Lévy-walk can describe the intermittent solar flare signal. Scafetta et al [7,9] established that, in general, the presence of a Lévy-walk process in a given time series can be detected by the joint use of two separate scaling techniques, the Diffusion Entropy Analysis (DEA) and Standard Deviation Analysis (SDA). We apply the same approach to the analysis of temperature data sets and compare them with the Lévy-walk statistics induced by solar flare intermittency.…”

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confidence: 99%

Solar Flare Intermittency and the Earth’s Temperature Anomalies

Scafetta

West

2003

Phys. Rev. Lett.

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We argue that earth's short-term temperature anomalies and the solar flare intermittency are linked. The analysis is based upon the study of the scaling of both the spreading and the entropy of the diffusion generated by the fluctuations of the temperature time series. The joint use of these two methods evidences the presence of a Lévy component in the temporal persistence of the temperature data sets that corresponds to the one that would be induced by the solar flare intermittency. The mean monthly temperature datasets cover the period from 1856 to 2002. PACS numbers: 95.75.Wx, 05.40.Fb, 05.45.Tp, 47.27.Nz The historical recognition that the sun warms the earth has suggested a direct connection between the average global temperature and solar activity. Consequently any significant changes in solar activity should result in equivalent changes in the earth's global temperature. The literature on the solar influence on the earth's temperature is quite extensive [1,2,3], indicating the importance of the problem and that there are many issues that require further investigation. Herein we address the relation between the statistics of solar flare activity and the fluctuations in the earth's global temperature.The dynamics of the sun's surface is turbulent, as is evidenced by changes in solar flare activity, with 11 or 22 year solar cycles [2,3] and strong erratic fluctuations associated with solar flare intermittency [3,4,5,6]. Solar irradiance changes in accordance with the frequency of solar flares because each flare releases more energy than the background irradiance [3]. This time variation in the frequency of solar flares induces a similar pseudoperiodic cycle in the earth's average temperature, as well as produces trends that move the global temperature up or down for tens or even hundreds of years [1,2,3]. However, it is less evident that short-term (weekly and monthly) changes in the global temperature are tied to solar activity whose short-time fluctuations would have the intermittent dynamics of solar flares. Traditional measures, such as cross-correlation functions, would not show the connection between short-time fluctuations in the global temperature and solar flare activity, because of the strong nonlinear hydrodynamic interactions across the earth's surface. For example, the hydrodynamic interaction of the atmosphere over land and water, would suppress any direct correlation between the intermittent sun's irradiance and the earth regions' short-time response.This letter focuses on an alternate approach to establishing the connection between the sun's irradiance and the earth's temperature fluctuations. A link between the two phenomena is detected through a detailed scaling analysis of the time series for the earth's temperature and the time series for the solar flare frequency.Considering a solar flare as an event, the time series for the number of solar flares has been interpreted as a waiting time distribution function between events. The solar flare waiting time distribution function is determ...

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“…For example, in molecular physics, a mass-fractal aggregates creation was investigated as the underlying process for many natural phenomena [2]. In biology, analyses were carried out in fractal-based fluctuations in electrical properties associated with cell membrane conductance and potentials [3], in the scaling effects in fluctuation of DNA sequence pattern [4][5][6], and in DNA signals from Homo Sapiens 22 chromosome [7]. In electronics, fractal conductance fluctuations in low-dimensional semiconductor devices [8][9][10], the chaotic nature of fractal conductance fluctuations in mesoscopic systems [11][12][13], and quantum-mechanical diffusion in semiconducting superlattices [14], were measured.…”

Section: Introductionmentioning

confidence: 99%