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The overall seismicity of Pakistan from 1820 to 2020 is analysed in terms of its multifractal behaviour. Seismic events of magnitude ML = 3.0 and above are spatially clustered into four distinct groups, each one corresponding to a different region of high seismic activity. The Multifractal Detrended Fluctuation Analysis (MFDA) method applied on each cluster reveals pronounced inter-cluster heterogeneity in terms of the resulting generalised Hurst exponent and fractality spectrum, possibly due to the particular tectonic characteristics of the regions under investigation. Additional results on the variability of the Gutenberg–Richter b-value across the defined clusters further corroborate the uniqueness of the seismic profile of each region. [ABSTRACT FROM AUTHOR]

This paper reports kHz EM observations recorded by the Kardamas station in Ilia, Greece a few days before four near-field earthquakes occurred within a 24 km radius, with epicentral depths below 29 km. This work investigated the fractal features hidden in the EM observations via power-law analysis. All EM signals exhibited characteristic fractal epochs with organisation in space and time. A significant number of accurate fractal segments were delineated in the majority of the EM observations. A significant number of fractal areas corresponded to predictable Class I fBm category with 1 ≤ b ≤ 3 (0 ≤ H ≤ 1). Numerous persistent key-periods are reported with 2 < b ≤ 3 (0.5 ≤ H ≤ 1) which are deemed as signs of impeding earthquakes according to the literature. Numerous segments were found with strong persistent b-values in the range (2.3 ≤ b ≤ 3) (0.65 ≤ H ≤ 1) and b-values corresponding to switching between antipersistency and persistency with (1.7 ≤ b < 2.3) (0.35 ≤ H < 0.65). These are deemed as the most significant precursory signs. Interpretations are given via the asperity model. [ABSTRACT FROM AUTHOR]

This paper reports the multifractal characteristics of lengthy PM10 time series from five stations in the Greater Athens Area (GAA), Greece. A novel methodology based on the multifractal detrended fluctuation analysis (MFDFA) is applied to raw and shuffled series in 74 segments in 11 date-periods, previously located, with very strong self-organised critical (SOC) and fractal properties. The MFDFA identified multifractality in all segments. Generalised and classical Hurst exponents are in the range 0.8–1.5 and 9–4.5 for the raw and shuffled series, while the multifractal f (a) − a is within 0.5–1.2 and 0.1–2, respectively. The f (a) − a data are fitted to polynomials to calculate the multifractal parameters W, F W H M and f m a x . While these are bimodal, a new parameter, F W H M / f m a x , is normally distributed, and due to this, it is employed to locate the important multifractal behaviour via the F W H M / f m a x outliers. Five date-periods are found. The date-period 8 January 2015 has extraordinary multifractality for raw and shuffled series for both the AGP and LYK stations. This date-period is one of the three reported in the most recent combination study. Finally, sliding window MFDFA evolution plots of all the series are given. The results provide very strong evidence of the multifractality of the PM10 time series. [ABSTRACT FROM AUTHOR]

The present study reports measurements of radon in groundwater conducted in China between January and December 2013. During the measurement period, a great Ms = 6.6 earthquake occurred in Gansu Province, China. The paper analyses data derived from three nearby stations via monofractal and multifractal detrended fluctuations analysis and explores whether pre-earthquake fractal and long-memory trends exist in the time series. Several critical epochs with characteristic pre-seismic long-lasting fractal patterns are identified in segmented parts of the series. In the whole data series, the fluctuation function, scaling exponent and generalised Hurst exponent depend on the fractal scales, which indicates multifractality. The multifractal spectrum of the raw, shuffled and truncated series showed a significant increase in the degree of fluctuation that can be explained as a pre-earthquake indicator attributable to the Gansu earthquake due to its very large magnitude. [ABSTRACT FROM AUTHOR]

This paper addressed a fractal evolution of 11 one-month lasting MHz electromagnetic disturbances, recorded in Greece prior to nine significant earthquakes of 2009. Time-space wavelet-based power spectral techniques were employed in the analysis. All investigated signals evolved naturally to epochs of fractal organization in space and time. Continuous organization was detected in seven signals. Significant number of successive () power-law-values were observed lying between 1.5 and 3.0 or above. The majority of fractal segments exhibited anti-persistent () or persistent () behaviour. Switching between persistency and anti-persistency was also found. Locality and sensitivity were traced. Findings were considered indicative of self-organized critical states of the last stages of preparation of the investigated earthquakes. Results implied fractional Brownian modelling. Explanations were proposed in view of the asperity model. Persistent–anti-persistent MHz anomalies were due to self-organized micro-cracking of the heterogeneous medium of the earth's crust which may have led the system's evolution towards global failure. The precursory value of the signals was discussed. [ABSTRACT FROM PUBLISHER]

This paper utilises statistical and entropy methods for the investigation of a 17-year PM10 time series recorded from five stations in Athens, Greece, in order to delineate existing stochastic and self-organisation trends. Stochastic patterns are analysed via lumping and sliding, in windows of various lengths. Decreasing trends are found between Windows 1 and 3500–4000, for all stations. Self-organisation is studied through Boltzmann and Tsallis entropy via sliding and symbolic dynamics in selected parts. Several values are below −2 (Boltzmann entropy) and 1.18 (Tsallis entropy) over the Boltzmann constant. A published method is utilised to locate areas for which the PM10 system is out of stochastic behaviour and, simultaneously, exhibits critical self-organised tendencies. Sixty-six two-month windows are found for various dates. From these, nine are common to at least three different stations. Combining previous publications, two areas are non-stochastic and exhibit, simultaneously, fractal, long-memory and self-organisation patterns through a combination of 15 different fractal and SOC analysis techniques. In these areas, block-entropy (range 0.650–2.924) is significantly lower compared to the remaining areas of non-stochastic but self-organisation trends. It is the first time to utilise entropy analysis for PM10 series and, importantly, in combination with results from previously published fractal methods. Data Set License: license under which the dataset is made available (CC0, CC-BY, CC-BY-SA, CC-BY-NC, etc.) [ABSTRACT FROM AUTHOR]

This article reports fractal dimension analysis applied to soil CO2 fluxes measured in an Italian seismic area. The work was carried out with the use of a calibrated flux chamber unit. The fractal dimension (FD) from isotropic variograms was used as a method to understand related scale-dependent phenomena. The aim was to investigate the spatial variability of CO2 flux measurements in four directions (horizontal, vertical, 45° and 135° directions) related to different distances between the measuring points and from a fault. High fractal dimension values were found (2.5 ≤ FD ≤ 3.0). These imply strong anti-persistent behavior near to and far from the fault. Lower fractal dimensions were addressed at longer distances from the fault. [ABSTRACT FROM AUTHOR]