scholarly journals Stochastic motion in an expanding noncommutative fluid

2021 ◽  
Vol 103 (12) ◽  
Author(s):  
M. A. Anacleto ◽  
C. H. G. Bessa ◽  
F. A. Brito ◽  
E. J. B. Ferreira ◽  
E. Passos
Keyword(s):  
Stochastic Motion

Certain problems with the application of stochastic diffusion processes for description of chemical engineering phenomena; Kolmogorov and classic diffusion equations

1988 ◽  
Vol 53 (6) ◽  
pp. 1181-1197
Author(s):  
Vladimír Kudrna
Keyword(s):  
Mass Transfer ◽  
Partial Differential Equations ◽  
Differential Equations ◽  
Chemical Engineering ◽  
Diffusion Processes ◽  
Parabolic Type ◽  
Diffusion Equations ◽  
Stochastic Motion ◽  
Energy Component ◽  
Classic Form

The paper presents alternative forms of partial differential equations of the parabolic type used in chemical engineering for description of heat and mass transfer. It points at the substantial difference between the classic form of the equations, following from the differential balances of mass and enthalpy, and the form following from the concept of stochastic motion of particles of mass or energy component. Examples are presented of the processes that may be described by the latter method. The paper also reviews the cases when the two approaches become identical.

Stochastic Motion in a Central Field with a Weak Non—Rotating Bar Perturbation

1995 ◽  
pp. 537-543 ◽  
Author(s):  
Pablo M. Cincotta ◽  
Josué A. Núñez ◽  
Juan C. Muzzio
Keyword(s):  
Central Field ◽  
Stochastic Motion

Assessing and visualizing uncertainty of 3D geological surfaces using level sets with stochastic motion

2019 ◽  
Vol 122 ◽  
pp. 54-67 ◽  
Author(s):  
Liang Yang ◽  
David Hyde ◽  
Ognjen Grujic ◽  
Celine Scheidt ◽  
Jef Caers
Keyword(s):  
Level Sets ◽  
Stochastic Motion

ROBUSTNESS, STABILITY AND EFFICIENCY OF PHAGE λ GENETIC SWITCH: DYNAMICAL STRUCTURE ANALYSIS

2004 ◽  
Vol 02 (04) ◽  
pp. 785-817 ◽  
Author(s):  
X.-M. ZHU ◽  
L. YIN ◽  
L. HOOD ◽  
P. AO
Keyword(s):  
Saddle Points ◽  
Life Cycles ◽  
Transverse Force ◽  
Structure Theory ◽  
Exponential Dependence ◽  
Mathematical Framework ◽  
Dynamical Structure ◽  
Stochastic Fluctuation ◽  
Stochastic Motion ◽  
Genetic Switch

Based on the dynamical structure theory for complex networks recently developed by one of us and on the physical-chemical models for gene regulation, developed by Shea and Ackers in the 1980's, we formulate a direct and concise mathematical framework for the genetic switch controlling phage λ life cycles, which naturally includes the stochastic effect. The dynamical structure theory states that the dynamics of a complex network is determined by its four elementary components: The dissipation (analogous to degradation), the stochastic force, the driving force determined by a potential, and the transverse force. The potential may be interpreted as a landscape for the phage development in terms of attractive basins, saddle points, peaks and valleys. The dissipation gives rise to the adaptivity of the phage in the landscape defined by the potential: The phage always has the tendency to approach the bottom of the nearby attractive basin. The transverse force tends to keep the network on the equal-potential contour of the landscape. The stochastic fluctuation gives the phage the ability to search around the potential landscape by passing through saddle points.With molecular parameters in our model fixed primarily by the experimental data on wild-type phage and supplemented by data on one mutant, our calculated results on mutants agree quantitatively with the available experimental observations on other mutants for protein number, lysogenization frequency, and a lysis frequency in lysogen culture. The calculation reproduces the observed robustness of the phage λ genetic switch. This is the first mathematical description that successfully represents such a wide variety of major experimental phenomena. Specifically, we find: (1) The explanation for both the stability and the efficiency of phage λ genetic switch is the exponential dependence of saddle point crossing rate on potential barrier height, a result of the stochastic motion in a landscape; and (2) The positive feedback of cI repressor gene transcription, enhanced by the CI dimer cooperative binding, is the key to the robustness of the phage λ genetic switch against mutations and fluctuations in kinetic parameter values.

Stochastic motion of the propagating front in bistable media

1983 ◽  
Vol 96 (9) ◽  
pp. 453-456 ◽  
Author(s):  
A.S. Mikhailov ◽  
L. Schimansky-Geier ◽  
W. Ebeling
Keyword(s):  
Stochastic Motion
Sign in / Sign up

Export Citation Format

Share Document