http://popups.lib.uliege.be/1373-5411/index.php?id=428 Index terms fr 0 http://popups.lib.uliege.be/1373-5411/index.php?id=1193 A method to sort out temporal correlations in financial data within the Detrended Fluctuation Analysis (DFA) statistical method is used. Both linear and cubic detrendings are considered. Our findings are surprisingly similar to those for DNA sequences which appeared as a mosaic of coding and non-coding patches. Fri, 05 Jul 2024 15:46:35 +0200 Fri, 05 Jul 2024 15:46:45 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=1193 http://popups.lib.uliege.be/1373-5411/index.php?id=867 The paradigm of dynamical systems as frame of description has been extremely successful for a variety of controlled systems. The ingredients of such an approach are an (assumed or known) fixed number of degrees of freedom, a phase space, state variables, and a (usually differential) equation of motion governing the temporal evolution of the system, or its movement in phase space along certain trajectories. Our focus of investigation are forest ecosystems. We will argue that they constitute a kind of system which does not belong to this class. The presence of memory effects and evolutionary processes demonstrate that the local history of these systems, embedded in an environment which is also partially created by them, is of utmost importance. There is no phase space for these systems. We therefore conjecture to characterize the system by its input-output mapping, considering it as a filter. Properties of this filter are quantified by time series analysis tools, identifying relevant time scales, correlations, periodicities, recurrences and other temporal structures. We show examples from hydrology and solution chemistry. Mon, 01 Jul 2024 14:03:28 +0200 Mon, 01 Jul 2024 14:03:39 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=867 http://popups.lib.uliege.be/1373-5411/index.php?id=424 Rose-Hindmarsh model is a simple and typical system for describing neuronal firing activities. This paper studies its chaotic firing phenomena, identification of unstable periodic orbits and chaos control in certain parameter regime. Firstly, irregular firing behaviors of the model are proved to be chaotic by numerically calculating the attractor's Lyapunov exponents and fractal dimension. Secondly, low order unstable periodic orbits embedded in the chaotic attractor are identified by simply analyzing interspike interval time series in their return maps. Finally, chaotic firings are stabilized to the period one and period two firing patterns respectively by delayed feedback control. Our preliminary work shows that the method of identification of unstable periodic orbits combined with delayed feedback control can effectively suppress irregular chaotic firings for the model. The technique presented in this paper is in accordance with those features of neuronal systems and may be a simple and actuated scheme for controlling chaotic firings of real neurons in physiological conditions. Thu, 27 Jun 2024 10:47:01 +0200 Thu, 27 Jun 2024 10:47:11 +0200 http://popups.lib.uliege.be/1373-5411/index.php?id=424