Ethno-Nationalistic and Religious-Nationalistic Components of Identity in Post-Soviet Georgia

Deep economic and democratic changes in Georgian society in last 20 years have conditioned the transformation of social environment in such a way that people had to change their views on society and their place in the new social environment. Changing attitudes on social reality affected and transformed the whole system of social identity. Transformation processes were characterized with reduced trust and tolerance among people and different social groups and with increase or weakening of different aspects of basic identities. Difficulties emerging from the process of formation of the identity system hinder the development of integration processes in the society. For a society in transition in the conditions of normative uncertainty and devaluation of values actuality of such problems as are the lack of trust on every level of relationship and disorientation of people, is of high importance. Our starting issue is that nowadays in the framework of construction of social identity basic identity encompasses civil, national, confessional, ideological elements which determine the state of a person in the system of social coordinates. The subject of this sociological research was to study the role of religion and ethnicity in the modern configuration of identity in Georgian society

On the puzzling feature of the silence of precursory electromagnetic emissions

It has been suggested that fracture-induced MHz-kHz electromagnetic (EM) emissions, which emerge from a few days up to a few hours before the main seismic shock occurrence permit a real-time monitoring of the damage process during the last stages of earthquake preparation, as it happens at the laboratory scale. Despite fairly abundant evidence, EM precursors have not been adequately accepted as credible physical phenomena. These negative views are enhanced by the fact that certain 'puzzling features' are repetitively observed in candidate fracture-induced pre-seismic EM emissions. More precisely, EM silence in all frequency bands appears before the main seismic shock occurrence, as well as during the aftershock period. Actually, the view that 'acceptance of 'precursive' EM signals without convincing co-seismic signals should not be expected' seems to be reasonable. In this work we focus on this point. We examine whether the aforementioned features of EM silence are really puzzling ones or, instead, reflect well-documented characteristic features of the fracture process, in terms of: universal structural patterns of the fracture process, recent laboratory experiments, numerical and theoretical studies of fracture dynamics, critical phenomena, percolation theory, and micromechanics of granular materials. Our analysis shows that these features should not be considered puzzling.Comment: arXiv admin note: text overlap with arXiv:cond-mat/0603542 by other author

Reliable Estimation of Minimum Embedding Dimension Through Statistical Analysis of Nearest Neighbors

False nearest neighbors (FNN) is one of the essential methods used in estimating the minimally sufficient embedding dimension in delay-coordinate embedding of deterministic time series. Its use for stochastic and noisy deterministic time series is problematic and erroneously indicates a finite embedding dimension. Various modifications to the original method have been proposed to mitigate this problem, but those are still not reliable for noisy time series. Here, nearest-neighbor statistics are studied for uncorrelated random time series and contrasted with the corresponding deterministic and stochastic statistics. New composite FNN metrics are constructed and their performance is evaluated for deterministic, correlates stochastic, and white random time series. In addition, noise-contaminated deterministic data analysis shows that these composite FNN metrics are robust to noise. All FNN results are also contrasted with surrogate data analysis to show their robustness. The new metrics clearly identify random time series as not having a finite embedding dimension and provide information about the deterministic part of correlated stochastic processes. These metrics can also be used to differentiate between chaotic and random time series

COLOR SELECTION METHODOLOGY AND ARTISTIC SOLUTIONS FOR RESTAURANTS FOR DESIGN

This article describes my own experience in creating design projects for restaurants around the world. The interior has a special role in these buildings, especially paying attention to detail, combining modern and ancient styles

Smooth Local Subspace Projection for Nonlinear Noise Reduction

Many nonlinear or chaotic time series exhibit an innate broad spectrum, which makes noise reduction difficult. Local projective noise reduction is one of the most effective tools. It is based on proper orthogonal decomposition (POD) and works for both map-like and continuously sampled time series. However, POD only looks at geometrical or topological properties of data and does not take into account the temporal characteristics of time series. Here, we present a new smooth projective noise reduction method. It uses smooth orthogonal decomposition (SOD) of bundles of reconstructed short-time trajectory strands to identify smooth local subspaces. Restricting trajectories to these subspaces imposes temporal smoothness on the filtered time series. It is shown that SOD-based noise reduction significantly outperforms the POD-based method for continuously sampled noisy time series

Dynamical systems approach to fatigue damage identification

In this paper, we present a dynamical systems approach to material damage identification. This methodology does not depend on knowledge of the particular damage physics of material fatigue. Instead, it provides experimental means to determine what are practically observable and observed facts of damage accumulation, thus making it possible to develop or experimentally verify appropriate damage evolution laws. A concept of phase space warping is used to develop new damage tracking feature vectors from measured time series through phase space reconstruction. These feature vectors provide critical information about the dimensionality of a damage process that was missing from an old scalar metric described in previous work. Damage identification is achieved by applying either proper orthogonal decomposition or smooth orthogonal decomposition to these vectors. The method is experimentally validated using an elasto-magnetic system, in which a harmonically forced cantilever beam in a non-linear magnetic field accumulates fatigue damage. Both damage identification methods yield a single active damage mode that shows power-law-type monotonic trends, which is also consistent with a result obtained using the old scalar metric. These results are shown to be in good agreement with the Paris fatigue crack growth model during the time period of macroscopic crack growth. Using this simple model, accurate time-to-failure predictions are shown well ahead of actual beam fracture. In addition, this identification scheme provides a much-needed insight into the dimensionality of incipient or early fatigue damage accumulation process, which is shown to be describable by only one scalar damage variable for this specific experiment

Phase synchronization of slip in laboratory slider system

International audienceIn the present study the character of slip regimes in laboratory spring-slider system under weak external periodical forcing has been investigated. We report the experimental evidence of phase synchronization (PS) in a slip dynamics, induced by the external periodic electromagnetic (EM) impact. The quality of synchronization depends on the intensity and frequency of the applied field; the corresponding Arnold's tongue region is constructed. Application of special techniques (measuring phase differences, phase diffusion coefficient, Shannon entropy, Recurrence Quantification Analysis) allows quantitative assessment of the strength of synchronization of microslips with EM impact. It is also shown that the character of power law relationship in acoustic emission amplitude (energy) distribution also undergoes significant changes at changing excitation intensity

Persistent Model Order Reduction for Complex Dynamical Systems Using Smooth Orthogonal Decomposition

Full-scale complex dynamic models are not effective for parametric studies due to the inherent constraints on available computational power and storage resources. A persistent reduced order model (ROM) that is robust, stable, and provides high-fidelity simulations for a relatively wide range of parameters and operating conditions can provide a solution to this problem. The fidelity of a new framework for persistent model order reduction of large and complex dynamical systems is investigated. The framework is validated using several numerical examples including a large linear system and two complex nonlinear systems with material and geometrical nonlinearities. While the framework is used for identifying the robust subspaces obtained from both proper and smooth orthogonal decompositions (POD and SOD, respectively), the results show that SOD outperforms POD in terms of stability, accuracy, and robustness

Electromagnetic and mechanical control of slip: laboratory experiments with slider system

International audienceField and laboratory data reveal the possibility of a significant coupling of elastic and electromagnetic (EM) fields that affect (hamper or initiate) slip. In this work we try to prove experimentally the possibility of controlling the slip regime by relatively weak mechanical or EM impact, in the way it has been done in nonlinear dynamic experiments on the control of chaos. The experimental setup consisted of a system of two plates of roughly finished basalt, where a constant pulling force was applied to the upper (sliding) plate. In addition, the same plate was subjected to mechanical or electric periodic perturbations, which are much weaker when compared to the pulling force. Quite different regimes of slip were excited depending on the amplitude and the frequency of applied weak perturbations. The observed regimes of slip vary from perfect synchronization of slip events, recorded as acoustic emission bursts with the perturbing periodic mechanical or EM impact, to their complete desynchronization. We consider the obtained results as evidence that it is possible to control slip by the application of weak periodic perturbations. The phenomenon can be explained in terms of nonlinear dynamics and synchronization theory

New Invariant Measures to Track Slow Parameter Drifts in Fast Dynamical Systems

Estimates of quantitative characteristics of nonlinear dynamics, e.g., correlation dimension or Lyapunov exponents, require long time series and are sensitive to noise. Other measures (e.g., phase space warping or sensitivity vector fields) are relatively difficult to implement and computationally intensive. In this paper, we propose a new class of features based on Birkhoff Ergodic Theorem, which are fast and easy to calculate. They are robust to noise and do not require large data or computational resources. Application of these metrics in conjunction with the smooth orthogonal decomposition to identify/track slowly changing parameters in nonlinear dynamical systems is demonstrated using both synthetic and experimental data