Steady State, Oscillation, and Chaos in Population Dynamics

1997 ◽  
pp. 44-53
Author(s):  
Matthias Ruth ◽  
Bruce Hannon
Keyword(s):  
Population Dynamics ◽  
Steady State ◽  
Steady State Oscillation

scholarly journals An Algorithm for the Stochastic Simulation of Gene Expression and Heterogeneous Population Dynamics

2011 ◽  
Vol 9 (1) ◽  
pp. 89-112 ◽  
Author(s):  
Daniel A. Charlebois ◽  
Jukka Intosalmi ◽  
Dawn Fraser ◽  
Mads Kærn
Keyword(s):  
Gene Expression ◽  
Population Dynamics ◽  
Steady State ◽  
Stochastic Simulation ◽  
Molecular Level ◽  
Single Cells ◽  
Heterogeneous Population ◽  
Population Heterogeneity ◽  
Time Dependent ◽  
Cell Populations

AbstractWe present an algorithm for the stochastic simulation of gene expression and heterogeneous population dynamics. The algorithm combines an exact method to simulate molecular-level fluctuations in single cells and a constant-number Monte Carlo method to simulate time-dependent statistical characteristics of growing cell populations. To benchmark performance, we compare simulation results with steady-state and time-dependent analytical solutions for several scenarios, including steady-state and time-dependent gene expression, and the effects on population heterogeneity of cell growth, division, and DNA replication. This comparison demonstrates that the algorithm provides an efficient and accurate approach to simulate how complex biological features influence gene expression. We also use the algorithm to model gene expression dynamics within “bet-hedging” cell populations during their adaption to environmental stress. These simulations indicate that the algorithm provides a framework suitable for simulating and analyzing realistic models of heterogeneous population dynamics combining molecular-level stochastic reaction kinetics, relevant physiological details and phenotypic variability.

Chinese Demography: The State of the Field

1990 ◽  
Vol 49 (4) ◽  
pp. 807-834 ◽  
Author(s):  
William Lavely ◽  
James Lee ◽  
Wang Feng
Keyword(s):  
Population Dynamics ◽  
Steady State ◽  
Chinese Population ◽  
Human Population ◽  
The State ◽  
Chinese Society ◽  
Demographic Research ◽  
The Past ◽  
Comparative Population ◽  
State Of The Field

As recently as one decade ago, there was no “field” of Chinese demography. There were virtually no demographers of China and little available data. It is fair to say that China was at once the largest and the least known of any human population.The change has been sudden. New sources of data now place China among the better-documented national populations. Publications on Chinese population have boomed. In consequence, we can now speak of a field of Chinese demography, although it is hardly in a steady “state.” We can only outline the explosion of demographic research that is continually expanding and refining our understanding of Chinese population today and in the past. This outpouring of data and knowledge provides unprecedented opportunities for the study of Chinese society and offers unusual challenges to our understanding of comparative population dynamics.

Loop Gain of the Common-Drain Colpitts Oscillator

2010 ◽  
Vol 56 (4) ◽  
pp. 423-426 ◽  
Author(s):  
Marian Kazimierczuk ◽  
Dakshina Murthy-Bellur
Keyword(s):  
Steady State ◽  
Characteristic Equation ◽  
Transfer Functions ◽  
Complex Conjugate ◽  
Small Signal ◽  
Loop Gain ◽  
Colpitts Oscillator ◽  
Feedback Network ◽  
Steady State Oscillation ◽  
The Common

Loop Gain of the Common-Drain Colpitts OscillatorThis paper presents the derivations of the voltage transfer functions of the amplifier A, the feedback network β, and the loop gainTof the common-drain (CD) Colpitts oscillator, using the small-signal model of the CD Colpitts oscillator. The derivation of the characteristic equation of the CD Colpitts oscillator is presented. Using the characteristic equation, the equation for the oscillation frequency of the sinusoidal output voltage and the condition for steady-state oscillation are derived. The characteristic equation is used to obtain a plot of trajectories of the poles of the CD Colpitts oscillator by varying the MOSFET small-signal transconductancegm. The locations of the complex conjugate poles depicting starting and steady-state conditions for oscillations are also presented.

scholarly journals Steady-state thermodynamics for population dynamics in fluctuating environments with side information

2022 ◽  
Vol 2022 (1) ◽  
pp. 013501
Author(s):  
Hideyuki Miyahara
Keyword(s):  
Population Dynamics ◽  
Steady State ◽  
Population Growth ◽  
Numerical Simulations ◽  
Side Information ◽  
Steady States ◽  
Fluctuating Environments ◽  
Clausius Inequality

Abstract Steady-state thermodynamics (SST) is a relatively newly emerging subfield of physics, which deals with transitions between steady states. In this paper, we find an SST-like structure in population dynamics of organisms that can sense their fluctuating environments. As heat is divided into two parts in SST, we decompose population growth into two parts: housekeeping growth and excess growth. Then, we derive the Clausius equality and inequality for excess growth. Using numerical simulations, we demonstrate how the Clausius inequality behaves depending on the magnitude of noise and strategies that organisms employ. Finally, we discuss the novelty of our findings and compare them with a previous study.

Sign in / Sign up

Export Citation Format

Share Document