Propagation of Bankruptcy Risk over Scale-Free Economic Networks.

The propagation of bankruptcy-induced shocks across domestic and global economies is sometimes very dramatic; this phenomenon can be modelled as a dynamical process in economic networks. Economic networks are usually scale-free, and scale-free networks are known to be vulnerable with respect to targeted attacks, i.e., attacks directed towards the biggest nodes of the network. Here we address the following question: to what extent does the scale-free nature of economic networks and the vulnerability of the biggest nodes affect the propagation of economic shocks? We model the dynamics of bankruptcies as the propagation of financial contagion across the banking sector over a scale-free network of banks, and perform Monte-Carlo simulations based on synthetic networks. In addition, we analyze the public data regarding the bankruptcy of US banks from the Federal Deposit Insurance Corporation. The dynamics of the shock propagation is characterized in terms of the Bank Failures Diffusion Index, i.e., the average number of new bankruptcies triggered by the bankruptcy of a single bank, and in terms of the Shannon entropy of the whole network. The simulation results are in-line with the empirical findings, and indicate the important role of the biggest banks in the dynamics of economic shocks.

Generation of large pollution patches via collisions of sticky floating parcels driven by wind and surface currents.

We study the evolution of large systems of sticky patches of pollution that float on the sea surface and are moved around by realistic wind and simulated surface currents. The study area is the Gulf of Finland in the eastern Baltic Sea that hosts extremely heavy cargo and tanker traffic. It is assumed that patches merge at collision. Collisions are enhanced by wind impact that depends on the patch size. We implement a space partitioning algorithm for fast simulations of large systems of >8000 patches and perform a series of simulations with different initial size and location of the patches. The resulting empirical distribution of the number of patches of different size is governed universally by a stretched-exponential power law f(x) = A exp (-xb). This indicates that the evolution of large systems of pollution patches on the sea surface exhibits classic self-organization and scale invariance properties. This may be the key effect explaining how the patchiness of waste in marine environment is formed under the impact of different drivers.

Methods of electroencephalographic signal analysis for detection of small hidden changes.

The aim of this study was to select and evaluate methods sensitive to reveal small hidden changes in the electroencephalographic (EEG) signal. Two original methods were considered.Multifractal method of scaling analysis of the EEG signal based on the length distribution of low variability periods (LDLVP) was developed and adopted for EEG analysis. The LDLVP method provides a simple route to detecting the multifractal characteristics of a time-series and yields somewhat better temporal resolution than the traditional multifractal analysis.The method of modulation with further integration of energy of the recorded signal was applied for EEG analysis. This method uses integration of differences in energy of the EEG segments with and without stressor.Microwave exposure was used as an external stressor to cause hidden changes in the EEG. Both methods were evaluated on the same EEG database. Database consists of resting EEG recordings of 15 subjects without and with low-level microwave exposure (450 MHz modulated at 40 Hz, power density 0.16 mW/cm2). The significant differences between recordings with and without exposure were detected by the LDLVP method for 4 subjects (26.7%) and energy integration method for 2 subjects (13.3%).The results show that small changes in time variability or energy of the EEG signals hidden in visual inspection can be detected by the LDLVP and integration of differences methods.

Sticky particles in compressible flows: aggregation and Richardson's law.

The evolution of the distance r(t) between a pair of passive tracer particles in rough compressible velocity fields is studied. The scaling behavior depends on the stickiness of the particles. Sticky particles start aggregating in moderately compressible flows, which can be realized on the free-slip surface of a turbulent fluid; nonsticky particles can aggregate only in less common strongly compressible flows (even then, the aggregation rate remains lower). Aggregation gives rise to an anomalous scaling law for the mean-square-distance growth rate, slower than Richardson's law. These findings help understand the results of recent experiments.

Integration of differences in EEG analysis reveals changes in human EEG caused by microwave.

Three different methods in combination with integration of differences in signals were applied for EEG analysis to distinguish changes in EEG caused by microwave: S-parameter, power spectral density and length distribution of low variability periods. The experiments on the effect of modulated low-level microwaves on human EEG were carried out on four different groups of healthy volunteers exposed to 450 MHz microwave radiation modulated with 7 Hz, 14 Hz, 21 Hz, 40 Hz, 70 Hz, 217 or 1000 Hz frequencies. The field power density at the scalp was 0.16 mW/cm2. The EEG analysis performed for individuals with three different methods showed that statistically significant changes occur in the EEG rhythms energy and dynamics between 12% and 30% of subjects.

Gradient-limited surfaces: formation of geological landscapes.

A simple scenario of the formation of geological landscapes is suggested, and the respective lattice model is derived. Numerical analysis shows that the arising non-Gaussian surfaces are characterized by the scale-dependent Hurst exponent varying from 0.7 to 1, in agreement with experimental data.