Statistics of Extreme Values in Time Series with Intermediate-Term Correlations

It will be discussed the statistics of the extreme values in time series characterized by finite-term correlations with non-exponential decay. Precisely, it will be considered the results of numerical analyses concerning the return intervals of extreme values of the fluctuations of resistance and defect-fraction displayed by a resistor with granular structure in a nonequilibrium stationary state. The resistance and defect-fraction are calculated as a function of time by Monte Carlo simulations using a resistor network approach. It will be shown that when the auto-correlation function of the fluctuations displays a non-exponential and non-power-law decay, the distribution of the return intervals of extreme values is a stretched exponential, with exponent largely independent of the threshold. Recently, a stretched exponential distribution of the return intervals of extreme values has been identified in long-term correlated time series by Bunde et al. (2003) and Altmann and Kantz (2005). Thus, the present results show that the stretched exponential distribution of the return intervals is not an exclusive feature of long-term correlated time series.Comment: 6 pages, 7 figures, conference paper, in Noise and Stochastics in Complex Systems and Finance, ed. by J. Kertez, S. Bornhold, R. N. Mantegna, Procs. of SPIE, vol. 6601, 19, 200

Distribution of Return Intervals of Extreme Events

The distribution of return intervals of extreme events is studied in time series characterized by finite-term correlations with non-exponential decay. Precisely, it has been analyzed the statistics of the return intervals of extreme values of the resistance fluctuations displayed by resistors with granular structure in nonequilibrium stationary states. The resistance fluctuations are calculated by Monte Carlo simulations using a resistor network approach. It has been found that for highly disordered networks, when the auto-correlation function displays a non-exponential and non-power-law decay, the distribution of return intervals of the extreme values is a stretched exponential, with exponent independent of the threshold.Comment: 10 pages, 6 figures, Next-SigmaPhi Int. Conference, News Expectations and Trends in Statistical Physics, 13-18 August 2005, Kolymbari - Crete (Greece

Distribution of Return Periods of Rare Events in Correlated Time Series

We study the effect on the distribution of return periods of rare events of the presence in a time series of finite-term correlations with non-exponential decay. Precisely, we analyze the auto-correlation function and the statistics of the return intervals of extreme values of the resistance fluctuations displayed by a resistor with granular structure in a nonequilibrium stationary state. The resistance fluctuations, $\delta R$, are calculated by Monte Carlo simulations using the SBRN model introduced some years ago by Pennetta, Tref\'an and Reggiani and based on a resistor network approach. A rare event occurs when $\delta R$ overcomes a threshold value $q$ significantly higher than the average value of the resistance. We have found that for highly disordered networks, when the auto-correlation function displays a non-exponential decay but yet the resistance fluctuations are characterized by a finite correlation time, the distribution of return intervals of the extreme values is well described by a stretched exponential, with exponent largely independent of the threshold $q$. We discuss this result and some of the main open questions related to it, also in connection with very recent findings by other authors concerning the observation of stretched exponential distributions of return intervals of extreme events in long-term correlated time series.Comment: 10 pages, 8 figures, Procs. of 4th. Int. Conf. on Unsolved Problems on Noise and Fluctuations in Physics, Biology and High Technology (UPoN05), 6-10 June 2005, Gallipoli (Italy), AIP Conf. Procs. (in print

Trapping-detrapping fluctuations in organic space-charge layers

A trapping-detrapping model is proposed for explaining the current fluctuation behavior in organic semiconductors (polyacenes) operating under current-injection conditions. The fraction of ionized traps obtained from the current-voltage characteristics, is related to the relative current noise spectral density at the trap-filling transition. The agreement between theory and experiments validates the model and provides an estimate of the concentration and energy level of deep traps

A network model to investigate structural and electrical properties of proteins

One of the main trend in to date research and development is the miniaturization of electronic devices. In this perspective, integrated nanodevices based on proteins or biomolecules are attracting a major interest. In fact, it has been shown that proteins like bacteriorhodopsin and azurin, manifest electrical properties which are promising for the development of active components in the field of molecular electronics. Here we focus on two relevant kinds of proteins: The bovine rhodopsin, prototype of GPCR protein, and the enzyme acetylcholinesterase (AChE), whose inhibition is one of the most qualified treatments of Alzheimer disease. Both these proteins exert their functioning starting with a conformational change of their native structure. Our guess is that such a change should be accompanied with a detectable variation of their electrical properties. To investigate this conjecture, we present an impedance network model of proteins, able to estimate the different electrical response associated with the different configurations. The model resolution of the electrical response is found able to monitor the structure and the conformational change of the given protein. In this respect, rhodopsin exhibits a better differential response than AChE. This result gives room to different interpretations of the degree of conformational change and in particular supports a recent hypothesis on the existence of a mixed state already in the native configuration of the protein.Comment: 25 pages, 12 figure

Studio teorico e computazionale delle proprieta' elettriche dimacromolecole di interesse biologico

Il progetto svolto dall'unita' di Lecce, sotto il coordinamento locale di C. Pennetta, aveva come scopo principale quello di sviluppare uno studio teorico-computazionale delle proprietà elettriche di grandi molecole di interesse biologico ed, in particolar modo, di proteine. Questo obiettivo e' stato sostanzialmente raggiunto con lo sviluppo di un modello innovativo che stima la modifica delle proprieta' elettriche di proteine o di altre macromolecole di interesse biologico dovuta a cambiamenti di conformazione. Il progetto dell'unita' di Lecce, dell'importo di 21,5 Keuro, rientrava nel progetto PRIN 2005, dal titolo "Strumentazione elettronica integrata per lo studio di variazioni conformazionali di proteine tramite misure elettriche, coordinato nazionalmente dal prof. M. Sampietro del Politecnico di Milano. Il progetto era articolato in tre unita': Milano (coordinata da M. Sampietro), responsabile dello sviluppo di apparecchiature elettroniche fortemente innovative, atte alla misura di correnti estremamente deboli, Roma Sapienza (coordinata da M. Barteri), responsabile della preparazione e funzionalizzazione delle superfici, Lecce, responsabile della modellizzazione teorica

, Steady State of Random Reistor Networks under Biased Percolation: a Framework for Noise in Disordered Media ?

pubblicato in “Unsolved Problems of Noise and Fluctuations”, ed. S.M. Bezrukov, AIP Conf.Proc., 665, Melville, New York, 200