91 research outputs found
Non-Markov stochastic dynamics of real epidemic process of respiratory infections
The study of social networks and especially of the stochastic dynamics of the
diseases spread in human population has recently attracted considerable
attention in statistical physics. In this work we present a new statistical
method of analyzing the spread of epidemic processes of grippe and acute
respiratory track infections (ARTI) by means of the theory of discrete
non-Markov stochastic processes. We use the results of our last theory (Phys.
Rev. E 65, 046107 (2002)) to study statistical memory effects, long - range
correlation and discreteness in real data series, describing the epidemic
dynamics of human ARTI infections and grippe. We have carried out the
comparative analysis of the data of the two infections (grippe and ARTI) in one
of the industrial districts of Kazan, one of the largest cities of Russia. The
experimental data are analyzed by the power spectra of the initial time
correlation function and the memory functions of junior orders, the phase
portraits of the four first dynamic variables, the three first points of the
statistical non-Markov parameter and the locally averaged kinetic and
relaxation parameters. The received results give an opportunity to provide
strict quantitative description of the regular and stochastic components in
epidemic dynamics of social networks taking into account their time
discreteness and effects of statistical memory. They also allow to reveal the
degree of randomness and predictability of the real epidemic process in the
specific social network.Comment: 18 pages, 8figs, 1 table
Stratification of the phase clouds and statistical effects of the non-Markovity in chaotic time series of human gait for healthy people and Parkinson patients
In this work we develop a new method of diagnosing the nervous system
diseases and a new approach in studying human gait dynamics with the help of
the theory of discrete non-Markov random processes. The stratification of the
phase clouds and the statistical non-Markov effects in the time series of the
dynamics of human gait are considered. We carried out the comparative analysis
of the data of four age groups of healthy people: children (from 3 to 10 year
olds), teenagers (from 11 to 14 year oulds), young people (from 21 up to 29
year oulds), elderly persons (from 71 to 77 year olds) and Parkinson patients.
The full data set are analyzed with the help of the phase portraits of the four
dynamic variables, the power spectra of the initial time correlation function
and the memory functions of junior orders, the three first points in the
spectra of the statistical non-Markov parameter. The received results allow to
define the predisposition of the probationers to deflections in the central
nervous system caused by Parkinson's disease. We have found out distinct
differencies between the five submitted groups. On this basis we offer a new
method of diagnostics and forecasting Parkinson's disease.Comment: 15 pages, 5 figs, 3 Table
Regular and stochastic behavior of Parkinsonian pathological tremor signals
Regular and stochastic behavior in the time series of Parkinsonian
pathological tremor velocity is studied on the basis of the statistical theory
of discrete non-Markov stochastic processes and flicker-noise spectroscopy. We
have developed a new method of analyzing and diagnosing Parkinson's disease
(PD) by taking into consideration discreteness, fluctuations, long- and
short-range correlations, regular and stochastic behavior, Markov and
non-Markov effects and dynamic alternation of relaxation modes in the initial
time signals. The spectrum of the statistical non-Markovity parameter reflects
Markovity and non-Markovity in the initial time series of tremor. The
relaxation and kinetic parameters used in the method allow us to estimate the
relaxation scales of diverse scenarios of the time signals produced by the
patient in various dynamic states. The local time behavior of the initial time
correlation function and the first point of the non-Markovity parameter give
detailed information about the variation of pathological tremor in the local
regions of the time series. The obtained results can be used to find the most
effective method of reducing or suppressing pathological tremor in each
individual case of a PD patient. Generally, the method allows one to assess the
efficacy of the medical treatment for a group of PD patients.Comment: 39 pages, 10 figures, 1 table Physica A, in pres
Structure of Zinc Coating on Steels Formed by Diffusion Saturation in Nitrogen-Containing Atmosphere
Diffusion technique of metallization is applied for receiving of zinc coatings on low-carbon steel with transitional zone. Structure of diffusion zinc layers after saturation of 09Mn2Si steel in ammonia at different temperatures is examined. Effects on saturation temperature on thickness of diffusion layers are discovered. Process at 600â°C forms diffusion layers with high strengthening level and with smooth microhardness profiles. Elements (Fe, Zn, N) spectrums are analyzed, and phase composition of zinc coating and of transitional zone is determined
Surface Strengthening of High-Alloyed Martensitic Steel by Staged Nitriding
Gas nitriding processes with cyclical rotation of ammonia and ammonia/air atmospheres are suggested for surface strengthening of martensitic Cr-Ni-W-Mo-V steel. One-, two-, and three-staged processes were studied differing by gas atmospheres at the final stage of processes. Microstructure and phase composition of received diffusion layers were examined. Results of microhardness, wear and impact toughness tests are discussed in correspondence with the layers structure
- âŠ