<div><p>We compare spot patterns generated by Turing mechanisms with those generated by replication cascades, in a model one-dimensional reaction-diffusion system. We determine the stability region of spot solutions in parameter space as a function of a natural control parameter (feed-rate) where degenerate patterns with different numbers of spots coexist for a fixed feed-rate. While it is possible to generate identical patterns via both mechanisms, we show that replication cascades lead to a wider choice of pattern profiles that can be selected through a tuning of the feed-rate, exploiting hysteresis and directionality effects of the different pattern pathways.</p></div
In this thesis we analyse three different reaction-diffusion models These are: the Gray-Scott model...
We examine the selection and competition of patterns in the Brusselator model, one of the simplest ...
Pattern formation in many biological systems takes place during growth of the underlying domain. We ...
We compare spot patterns generated by Turing mechanisms with those generated by replication cascades...
We compare spot patterns generated by Turing mechanisms with those generated by replication cascades...
We compare spot patterns generated by Turing mechanisms with those generated by replication cascades...
We compare spot patterns generated by Turing mechanisms with those generated by replication cascades...
We compare spot patterns generated by Turing mechanisms with those generated by replication cascades...
Turing's theory of pattern formation has been used to describe the formation of self-organized perio...
This paper studies the pattern selection in a spatially-periodic problem of a simplified reaction-di...
We consider a reaction-diffusion system with discontinuous reaction terms modeled by non-ideal relay...
We consider a reaction-diffusion system with discontinuous reaction terms modeled by non-ideal relay...
This paper studies the pattern selection in a spatially-periodic problem of a simplified reaction-di...
Pattern formation in many biological systems takes place during growth of the underlying domain. We ...
<p>Two space dimensions are considered, with system size and periodic boundary conditions. Typical ...
In this thesis we analyse three different reaction-diffusion models These are: the Gray-Scott model...
We examine the selection and competition of patterns in the Brusselator model, one of the simplest ...
Pattern formation in many biological systems takes place during growth of the underlying domain. We ...
We compare spot patterns generated by Turing mechanisms with those generated by replication cascades...
We compare spot patterns generated by Turing mechanisms with those generated by replication cascades...
We compare spot patterns generated by Turing mechanisms with those generated by replication cascades...
We compare spot patterns generated by Turing mechanisms with those generated by replication cascades...
We compare spot patterns generated by Turing mechanisms with those generated by replication cascades...
Turing's theory of pattern formation has been used to describe the formation of self-organized perio...
This paper studies the pattern selection in a spatially-periodic problem of a simplified reaction-di...
We consider a reaction-diffusion system with discontinuous reaction terms modeled by non-ideal relay...
We consider a reaction-diffusion system with discontinuous reaction terms modeled by non-ideal relay...
This paper studies the pattern selection in a spatially-periodic problem of a simplified reaction-di...
Pattern formation in many biological systems takes place during growth of the underlying domain. We ...
<p>Two space dimensions are considered, with system size and periodic boundary conditions. Typical ...
In this thesis we analyse three different reaction-diffusion models These are: the Gray-Scott model...
We examine the selection and competition of patterns in the Brusselator model, one of the simplest ...
Pattern formation in many biological systems takes place during growth of the underlying domain. We ...