An analysis of I.R. Prigogone and J.A. Wheeler’s views concerning emergency of biosystems from the perspective of the third paradigm

10.12737/7652 ◽  
2014 ◽  
Vol 3 (4) ◽  
pp. 47-62 ◽  
Author(s):  
Еськов ◽  
V. Eskov ◽  
Джумагалиева ◽  
L. Dzhumagalieva ◽  
Филатова ◽  
...  
Keyword(s):  
Deterministic Chaos ◽  
Modern Science ◽  
Main Property ◽  
Type Systems ◽  
Distribution Functions ◽  
Living Systems ◽  
Self Organization ◽  
Initial State ◽  
The Third ◽  
Emergent Systems

The main problem of modern science is pointed out: reality of specific three-type systems (TTS) that are usually presented as complexity, and simultaneously impossibility of a description of such systems by a traditional modern reducing approach. Studying properties of system elements cannot help in a description of a complex system itself – complexity (three-type systems, living systems). Hence there arises an acute need in creation of new theories which would operate with maximum uncertainty and unpredictability and provide modeling TTS. The first step in this direction was taken on the grounds of a creation of theory of chaos and self-organization (TCS), according to which complexity cannot repeat an initial state of a system (or a vector parameters x(t0)), measures are not invariant, autocorrelation functions do not converge to zero and Lyapunov exponents are not positive. Chaos of TTS differs from a deterministic chaos and statistical distribution functions f(x) are not appropriate to describe it, because they continuously change. Deterministic, stochastic and chaotic models cannot describe TTS. This is the main property of emergent systems (complexity, TTS), therefore they are described by quasi-attractors.

Non-stationary stationarity in systems of third type and philosophy of instability

2015 ◽  
Vol 4 (2) ◽  
pp. 65-74
Author(s):  
Гавриленко ◽  
T. Gavrilenko ◽  
Еськов ◽  
Valeriy Eskov ◽  
Еськов ◽  
...  
Keyword(s):  
Dynamical Systems ◽  
Complex Systems ◽  
Biological Systems ◽  
Deterministic Chaos ◽  
Stochastic Approach ◽  
Distribution Functions ◽  
Self Organization ◽  
Deterministic Approach ◽  
The Third ◽  
Specific Assessment

There are several criteria in science for stationarity (stability) of different dynamical systems. The stationarity in physics, engineering and chemistry is being interpreted as matching the requirements of dx/dt=0, where x=x(t) - is the vector of system’s state, or the equality of distribution functions f(x) for different samples which characterize the system. However, in case of social or biological systems the matching of the requirements is impossible and there is a problem of specific assessment of stationary regimes of complex systems of the third type. The possibility of studying of such systems within the frame of deterministic chaos, stochastic approach and theory of chaos and self-organization is being discussed. This article explains why I.R. Prigogine refused from materialistic (in fact deterministic) approach in the description of such special systems of third type and tried to get away from the traditional science in the description of biological systems.

The complexity in I. Prigogine and H. Haken’s interpretation differs from the complexity of W. Weaver and TCS

10.12737/6723 ◽  
2014 ◽  
Vol 3 (3) ◽  
pp. 46-56
Author(s):  
Гудкова ◽  
S. Gudkova ◽  
Джумагалиева ◽  
L. Dzhumagalieva ◽  
Еськов ◽  
...  
Keyword(s):  
Modern Science ◽  
Order Parameters ◽  
Distribution Functions ◽  
Synthesis Problem ◽  
Self Organization ◽  
Stochastic Methods ◽  
Type I ◽  
Type Ii ◽  
The Third ◽  
Significant Difference

The present paper shows that the term “complexity” includes absolutely different notions than now it seems to be presented in modern science and philosophy. V.S. Stepin’s postnon-classics has come to this new recognition too close, but, actually, it is a new recognition of uncertainty for systems of the third type (not deterministic and not stochastic). We introduce the interpretation of a type I uncertainty that implies that stochastic methods show systems identified, but methods of the theory of chaos and self-organization and neurocomputing show significant difference of target systems (processes). The concrete examples show the type I uncertainty and give an idea of a type II uncertainty, that implies the coincidence of distribution functions f(x) for different samplings. We prove that neurocomputing method not only differentiates samplings, but also identifies order parameters. In this case we also solve the system synthesis problem.

How close I.R. Prigogine, н. наken and S.P. Kurdumov approached to understanding of inevitability of TCS

10.12737/6722 ◽  
2014 ◽  
Vol 3 (3) ◽  
pp. 39-46
Author(s):  
Еськов ◽  
V. Eskov
Keyword(s):  
Systems Approach ◽  
Cellular Level ◽  
Living Systems ◽  
Self Organization ◽  
System State ◽  
The Third ◽  
Physical Chemical ◽  
Novel Approach ◽  
Life Phenomena ◽  
Living Objects

Advances in molecular biology and biophysics (at molecular-cellular level) do not contribute to understanding of life phenomena. Achievements of synergetics (H. Haken) and complexity theory (I. Prigogine) have intensified differences between physical-chemical understandings of life and systemic understandings. In addition to that, the systems approach provides the understanding of effects of living objects and especially its more organized and evolving part – human and humanity. Human-scaled systems possess the unique property – continuous and chaotic movement of many components of a system state vector x= x(t). Taking this property into consideration causes the denial of any known types of stationary nodes (for example, dx/dt=0) and requires reconsideration of concept of chaos. A novel approach for understanding of living systems (as the third paradigm of natural science) and novel methods of studying of living systems (as theory of chaos and self-organization) are proposed by the third paradigm and theory of chaos and self-organization.

Homeostatic System Can Not Be Described by Stochastics or Deterministic Chaos

2015 ◽  
Vol 22 (4) ◽  
pp. 28-33 ◽  
Author(s):  
Полухин ◽  
V. Polukhin ◽  
Еськов ◽  
V. Eskov ◽  
Эльман ◽  
...  
Keyword(s):  
Distribution Function ◽  
Stationary State ◽  
Natural Science ◽  
Invariant Measures ◽  
Deterministic Chaos ◽  
Living Systems ◽  
Deterministic Approach ◽  
The Third ◽  
Rate Of Increase ◽  
Mixing Property

The living systems (complexity, homeostatic systems) are a special systems of the third type of complexity in natural science and for such systems it is impossible to determine the stationary state in form of dx/dt=0 (deterministic approach) or in the form of invariance of distribution function f(x) for samples acquired in a row of, the any component xi of all vectors of state x=x(t) =(x1,x2,…,xm)T in m‐dimensional phase space of states. At the same time the mixing property doesn’t met (no invariant measures), the autocorrelation functions A(t) don’t tend to zero if t→∞, Lyapunov’s constants can continuously change the sign. Such systems of the third type (complexity) do not meet the condition of Glansdorff – Prigogine’s theorem, i.e. P ‐ the rate of increase of entropy E (P=dE/dt) doesn’t minimized near the point of maximum entropy E (i.e., at point of thermodynamic equilibrium). It is proposed to use the concept of quasi‐attractors to describe the complexity.

Other World, Other Science, Other Models in Complexity Descreaption

10.12737/3328 ◽  
2014 ◽  
Vol 21 (1) ◽  
pp. 138-141
Author(s):  
Еськов ◽  
Valeriy Eskov ◽  
Филатова ◽  
O. Filatova
Keyword(s):  
Phase Space ◽  
State Vector ◽  
Stochastic Systems ◽  
Chaotic Behavior ◽  
Future Generation ◽  
Self Organization ◽  
Stationary Mode ◽  
Initial State ◽  
Heisenberg Uncertainty Principle ◽  
The Third

The understanding of very special systems of third type was created according to W.Weaver efforts. The new theory of chaos – self- organization was created last 40 years and was based on other understanding of stationary mode of third type of systems and its very specific chaotic behavior. The analog of the systems with physical system was discussed too. The third type of systems (opposite of deterministic and stochastic systems) was presented. It was discussed the principle distinguishes between dynamics of such system and traditional systems according to Heisenberg uncertainty principle. Traditional systems have certain and reproducible initial state of its system’s state vector and we can predict its future states. But in the third type of systems the authors have uncertain initial system state and uncertain vector states. It is a unique system which I.R. Prigogine in his famous article to the future generation determines as systems behind the science. The time for researching of such systems has come. For the modeling of biosystems, the authors propose method of quasi-attractor and define five special properties of complex systems. The main of it is connected with uninterrupted chaotic movements (glimmering property) of system’s vector in phase space of state and evolution of such system’s state vector in phase space of state. It was demonstrated that Heizenberg principle of uncertainty has special analog at theory of chaos – self organization. The botton boarder of the left side of inequality for the systems of third type the authors propose the value of quasiattractors, inside of it we chaos uninferrupled and chaotic movements of systems state vector. The value of quasiattractor determine like multiplication of coordinat x its speed dx/dt.

Concept complexity W. Weawer differ from the modern scientists

2015 ◽  
Vol 4 (1) ◽  
pp. 13-22
Author(s):  
Журавлева ◽  
A. Zhuravleva ◽  
Еськов ◽  
V. Eskov ◽  
Гудкова ◽  
...  
Keyword(s):  
Social Relations ◽  
Modern Science ◽  
Self Organization ◽  
Stochastic Methods ◽  
Type I ◽  
The Third ◽  
Basic Model ◽  
Significant Difference

The present paper shows that the term “complexity” includes absolutely different notions than now it seems to be presented in modern science and philosophy. Postnon-classics has come to this new recognition too close, but, actually, it is a new recognition of uncertainty for systems of the third type (not deterministic and not stochastic). We introduce the interpretation of a type I uncertainty that implies that stochastic methods show systems identified, but methods of the theory of chaos and self-organization and neurocomputing show significant difference of target systems (processes). With specific examples presented uncertainty of type 1 and gives an idea of the uncertainty of type 2, when the distribution function f (x) for different samples are the same. At the same neuro-computers not only divides the sample, but also shows the order parameters. In this case, at the same time solve the problem of system synthesis, which in society is now very difficult to solve (the basic model of social relations now – it´s deterministic society).

Color Entanglement in Hadronic Processes for Transverse Momentum Dependent Parton Distribution Functions

2015 ◽  
Vol 37 ◽  
pp. 1560022
Author(s):  
M. G. A. Buffing ◽  
P. J. Mulders
Keyword(s):  
Transverse Momentum ◽  
Parton Distribution ◽  
Distribution Functions ◽  
Parton Distribution Functions ◽  
Initial State ◽  
Color Flow ◽  
Transverse Momentum Dependent ◽  
Gauge Link ◽  
Azimuthal Asymmetries ◽  
Different Parts

In the description of protons, we go beyond the ordinary collinear parton distribution functions (PDFs), by including transverse momentum dependent PDFs (TMDs). As such, we become sensitive to polarization modes of the partons and protons that one cannot probe without accounting for transverse momenta of partons, in particular when looking at azimuthal asymmetries. Hadronic processes require the inclusion of gluon contributions forming the gauge links, which are path-ordered exponentials tracing the color flow. In processes with two hadrons in the initial state, such as Drell-Yan (DY), the gauge links from different parts of the process get entangled. We show that in color disentangling this gauge link structure, one becomes sensitive to this color flow. After disentanglement, particular combinations of TMDs will require a different numerical color factor than one naively might have expected. Such color factors will even play a role for azimuthal asymmetries in the simplest hadronic processes such as DY.

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