We develop a fully Bayesian inferential framework to quantify uncertainty in
Models defined by general systems of analytically intractable differential
Equations. This approach provides a statistical alternative to deterministic
Numerical integration for estimation of complex dynamic systems, and
We develop an immersed-boundary approach to modeling reaction-diffusion
Processes in dispersions of reactive spherical particles, from the
Diffusion-limited to the reaction-limited setting. We represent each reactive
Particle with a minimally-resolved "blob" using many less degrees of freedom
Aims and objectives. To explore the assumption that people with ID are unable to communicate effectively about pain by examining the extent to which they were reported as using language and behaviour that was readily understandable to others to communicate pain as distinct from di...
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