No abstract

Abstract. The problem of earthquake prediction and the methods of identification of geophysical precursory signals are discussed. To get information on the dynamics of earthquake preparation processes, fluctuations in geophysical time series are analyzed with the method of flicker-noise spectroscopy. Integral indices -power spectra and various moments ("structural functions") -are used as information relations. We demonstrate that the method allows us to reveal earthquake precursors.

No abstract

No abstract

List of symbolslength of wire specimens l k size (in elementary units) of rougher partitions N box number P i relative 'weight' of ith box q real index R maximum depth (is implied to be equal to width) of wire surface dimplelike defects R/d relative depth of wire surface dimplelike defects a=dt/dq ordinary derivative d 50 elongation (l/d=50) D 40 =D 1 −D 40 evaluation of degree of order index D 2 =D 1 −D 2 degree of order index s e elastic limit s UTS ultimate tensile stress s 0•2%nominal yield stress t(q) exponent of x(q) x(q) generalised correlation function (partition function)

PACS 72.70.+m, 77.22.Jp Owing to the influence of environment and impact of energy fluxes (electric polarisation, heating, photon irradiation, etc.) physical and chemical properties of porous semiconductors (and other materials as well) experience changes which have to be monitored in order to distinguish the moment when the properties become out of a working range. There is a necessity of forecasting the development of catastrophic events in the porous film. In the present work we study the possibility of predicting the occurrence of the electrical breakdown in thin porous films through analysis of the fluctuations of the electric current in the vicinity of this event using a novel method called Dynamic Flicker Noise Spectroscopy -DFNS.

In this work we analyze the surface roughness of porous silicon films and show that it is possible to quantify some fine differences in the morphology of different samples and even in different points of the surface of one sample using a novel method of Flicker Noise Spectroscopy (FNS). High informative potential of the method is now illustrated by applying it to the analysis of laterally non-uniform porous silicon films produced by the local anodization of silicon using a point cathode placed in the vicinity of the silicon wafer. The possibilities for future explorations are shown.

Applications of the Flicker-Noise Spectroscopy (FNS) to analysis of electroencephalograms (EEG) are demonstrated. We present the double correlation function for the EEG measured in the C4 and O2 points for two patients -a healthy ("normal") child and a sick Schizophrenia child. The drastic differences in the behavior of the two-correlators manifest the information meaning of the similar dependences. We conclude that the FNS approach could be considered as a new instrument to early diagnostics of various brain diseases.