The fluctuations, under time reversal, of the natural time and the entropy distinguish similar looking electric signals of different dynamics

We show that the scale dependence of the fluctuations of the natural time itself under time reversal provides a useful tool for the discrimination of seismic electric signals (critical dynamics) from noises emitted from man made sources as well as for the determination of the scaling exponent. We present recent data of electric signals detected at the Earth's surface, which confirm that the value of the entropy in natural time as well as its value under time reversal are smaller than that of the entropy of a "uniform" distribution.Comment: 29 pages including 24 figure and 1 Tabl

Comment on "Effects of Thickness on the Spin Susceptibility of the Two Dimensional Electron Gas"

A comment on a recent paper (PRL {\bf 94}, 226405 (2005)) by S. De Palo, M. Botti, S. Moroni, and Gaetano Senatore

Identifying the occurrence time of an impending mainshock: A very recent case

The procedure by means of which the occurrence time of an impending mainshock can be identified by analyzing in natural time the seismicity in the candidate area subsequent to the recording of a precursory Seismic Electric Signals (SES) activity is reviewed. Here, we report the application of this procedure to an Mw5.4 mainshock that occurred in Greece on 17 November 2014 and was strongly felt in Athens. This mainshock (which is pretty rare since it is the strongest in that area for more than half a century) was preceded by an SES activity recorded on 27 July 2014 and the results of the natural time analysis reveal that the system approached the critical point (mainshock occurrence) early in the morning on 15 November 2014. Similar SES activities that have been recently recorded are also presented. Furthermore, in a Note we discuss the case of the Mw5.3 earthquake that was also strongly felt in Athens on 19 July 2019.Comment: An early version of this paper appeared in Earthq. Sci. 28 (2015) 215-222 [doi:10.1007/s11589-015-0122-3], whereas in the present version new data collected during 2019 and 2020 have been added. 8 pages, 11 figure

Natural entropy fluctuations discriminate similar looking electric signals emitted from systems of different dynamics

Complexity measures are introduced, that quantify the change of the natural entropy fluctuations at different length scales in time-series emitted from systems operating far from equilibrium. They identify impending sudden cardiac death (SD) by analyzing fifteen minutes electrocardiograms, and comparing to those of truly healthy humans (H). These measures seem to be complementary to the ones suggested recently [Phys. Rev. E {\bf 70}, 011106 (2004)] and altogether enable the classification of individuals into three categories: H, heart disease patients and SD. All the SD individuals, who exhibit critical dynamics, result in a common behavior.Comment: Published in Physical Review

Entropy of seismic electric signals: Analysis in natural time under time-reversal

Electric signals have been recently recorded at the Earth's surface with amplitudes appreciably larger than those hitherto reported. Their entropy in natural time is smaller than that, $S_u$, of a ``uniform'' distribution. The same holds for their entropy upon time-reversal. This behavior, as supported by numerical simulations in fBm time series and in an on-off intermittency model, stems from infinitely ranged long range temporal correlations and hence these signals are probably Seismic Electric Signals (critical dynamics). The entropy fluctuations are found to increase upon approaching bursting, which reminds the behavior identifying sudden cardiac death individuals when analysing their electrocardiograms.Comment: 7 pages, 4 figures, copy of the revised version submitted to Physical Review Letters on June 29,200

Entropy in the natural time-domain

A surrogate data analysis is presented, which is based on the fluctuations of the ``entropy'' $S$ defined in the natural time-domain [Phys. Rev. E {\bf 68}, 031106, 2003]. This entropy is not a static one as, for example, the Shannon entropy. The analysis is applied to three types of time-series, i.e., seismic electric signals, ``artificial'' noises and electrocardiograms, and ``recognizes'' the non-Markovianity in all these signals. Furthermore, it differentiates the electrocardiograms of healthy humans from those of the sudden cardiac death ones. If $\delta S$ and $\delta S_{shuf}$ denote the standard deviation when calculating the entropy by means of a time-window sweeping through the original data and the ``shuffled'' (randomized) data, respectively, it seems that the ratio $\delta S_{shuf}/\delta S$ plays a key-role. The physical meaning of $\delta S_{shuf}$ is investigated.Comment: Published in Physical Review