Comment on the Results of the Long-Term Estimation of the Non-equilibrium Factor F = 0.75

2014 ◽  
Vol 106 (3) ◽  
pp. 428-430
Author(s):  
J. Thomas
Entropy ◽  
2019 ◽  
Vol 21 (2) ◽  
pp. 179 ◽  
Author(s):  
Ramon Álvarez-Estrada

We review and improve previous work on non-equilibrium classical and quantum statistical systems, subject to potentials, without ab initio dissipation. We treat classical closed three-dimensional many-particle interacting systems without any “heat bath” ( h b ), evolving through the Liouville equation for the non-equilibrium classical distribution W c , with initial states describing thermal equilibrium at large distances but non-equilibrium at finite distances. We use Boltzmann’s Gaussian classical equilibrium distribution W c , e q , as weight function to generate orthogonal polynomials ( H n ’s) in momenta. The moments of W c , implied by the H n ’s, fulfill a non-equilibrium hierarchy. Under long-term approximations, the lowest moment dominates the evolution towards thermal equilibrium. A non-increasing Liapunov function characterizes the long-term evolution towards equilibrium. Non-equilibrium chemical reactions involving two and three particles in a h b are studied classically and quantum-mechanically (by using Wigner functions W). Difficulties related to the non-positivity of W are bypassed. Equilibrium Wigner functions W e q generate orthogonal polynomials, which yield non-equilibrium moments of W and hierarchies. In regimes typical of chemical reactions (short thermal wavelength and long times), non-equilibrium hierarchies yield approximate Smoluchowski-like equations displaying dissipation and quantum effects. The study of three-particle chemical reactions is new.


2003 ◽  
Vol 103 (3) ◽  
pp. 269-271 ◽  
Author(s):  
A. Clouvas ◽  
S. Xanthos ◽  
M. Antonopoulos-Domis
Keyword(s):  

2012 ◽  
Vol 102 (4) ◽  
pp. 459-462 ◽  
Author(s):  
Naomi H. Harley ◽  
Jing Chen ◽  
Passaporn Chittaporn ◽  
Atsuyuki Sorimachi ◽  
Shinji Tokonami

2011 ◽  
Vol 149 (2) ◽  
pp. 155-158 ◽  
Author(s):  
J. Chen ◽  
D. Moir ◽  
A. Sorimachi ◽  
M. Janik ◽  
S. Tokonami
Keyword(s):  

1998 ◽  
Vol 236 (1-2) ◽  
pp. 231-238 ◽  
Author(s):  
T. Martinez ◽  
J. Lartigue ◽  
M. Navarrete ◽  
L. Cabrera ◽  
P. Gonzalez ◽  
...  

2021 ◽  
Author(s):  
Akira Sasaki ◽  
Sébastien Lion ◽  
Mike Boots

AbstractUnderstanding the evolutionary drivers determining the transmission rate and virulence of pathogens remains an important challenge for evolutionary theory with clear implications to the control of human, agricultural and wildlife infectious disease. Although disease is often very dynamic, classical theory examines the long-term outcome of evolution at equilibrium and, in simple models, typically predicts that R0 is maximized. For example, immune escape may lead to complex disease dynamics including repeated epidemics, fluctuating selection and diversification. Here we model the impact of antigenic drift and escape on the evolution of virulence and show analytically that these non-equilibrium dynamics select for more acute pathogens with higher virulence. Specifically, under antigenic drift and when partial cross immunity leads to antigenic escape, our analysis predicts the long-term maximization of the intrinsic growth rate of the parasite resulting in more acute and virulent pathogens than those predicted by classic R0 maximization. Furthermore, it follows that these pathogens will have a lower R0 leading to implications for epidemic, endemic behavior and control. Our analysis predicts both the timings and outcomes of antigenic shifts leading to repeated epidemics and predicts the increase in variation in both antigenicity and virulence before antigenic escape. There is considerable variation in the degree of antigenic escape that occurs across pathogens and our results may help to explain the difference in virulence between related pathogens most clearly seen in the human A, B and C influenzas. More generally our results show the importance of examining the evolutionary consequences of non-equilibrium dynamics.


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