We analyse seismicity during the 6-year period 2012-2017 in the new time domain termed natural time in the Chiapas region where the M8.2 earthquake occurred, Mexico's largest earthquake in more than a century, in order to study the complexity measures associated with fluctuations of entropy as well as with entropy change under time reversal. We find that almost three months before the M8.2 earthquake, i.e., on 14 June 2017, the complexity measure associated with the fluctuations of entropy change under time reversal shows an abrupt increase, which, however, does not hold for the complexity measure associated with the fluctuations of entropy in forward time. On the same date, the entropy change under time reversal has been previously found to exhibit a minimum [Physica A 506, 625-634 (2018)]; we thus find here that this minimum is also accompanied by increased fluctuations of the entropy change under time reversal. In addition, we find a simultaneous increase of the Tsallis entropic index q.
This paper describes the spatial and temporal variation of aquatic invertebrate assemblages associated with root masses of Eichhornia crassipes collected at 12 sites between
Abstract. Seismic electric signals (SES) have been considered precursors of strong earthquakes, and, recently, their dynamics have been investigated within the Natural Time Domain (NTD) (Varotsos et al., 2004). In this paper we apply the NTD approach and the chaotic map signal analysis to two geoelectric time series recorded in a seismically very active area of Mexico, where two strong earthquakes, M = 6.6 and M = 7.4, occurred on 24 October 1993 and 14 September 1995, respectively. The low frequency geoelectric signals measured display periods with dichotomic behavior. Our findings point out to an increase of the correlation degree of the geoelectric signals before the occurrence of strong earthquakes; furthermore, the power spectrum and entropy in NTD are in good agreement with the results published in literature. Our results were validated by the analysis of a chaotic map simulated time series, which revealed the typical characteristics of artificial noise.
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