Search

The concept of Dynamical Diseases provides a framework to understand physiological control systems in pathological states due to their operating in an abnormal range of control parameters: this allows for the possibility of a return to normal condition by a redress of the values of the governing parameters. The analogy with bifurcations in dynamical systems opens the possibility of mathematically modeling clinical conditions and investigating possible parameter changes that lead to avoidance of their pathological states. Since its introduction, this concept has been applied to a number of physiological systems, most notably cardiac, hematological, and neurological. A quarter century after the inaugural meeting on dynamical diseases held in Mont Tremblant, Québec [Bélair et al., Dynamical Diseases: Mathematical Analysis of Human Illness (American Institute of Physics, Woodbury, NY, 1995)], this Focus Issue offers an opportunity to reflect on the evolution of the field in traditional areas as well as contemporary data-based methods. [ABSTRACT FROM AUTHOR]

Choice in the behavior of organisms involves novelty, which may be unpredictable. Yet in retrospect, we can usually provide a rationale for the choice. A deterministic view of life cannot explain this. The solution to this paradox is that organisms can harness stochasticity through which they can generate many possible solutions to environmental challenges. They must then employ a comparator to find the solution that fits the challenge. What therefore is unpredictable in prospect can become comprehensible in retrospect. Harnessing stochastic and/or chaotic processes is essential to the ability of organisms to have agency and to make choices. [ABSTRACT FROM AUTHOR]

In this article, a spatiotemporal dynamical system model (tree model) is utilized for investigating the features of forced and unforced turbulence in a dispersed phase two-phase system. The tree model includes a variable for spatial dimension in addition to variables of wavenumber and time, which display both spatial and temporal intermittencies. The focus of this paper is to study the turbulence modulation due to the presence of rigid particles. The study considers particles with the sizes of 32, 64, and 128 times the Kolmogorov length scale. Specifically, the study of the energy dissipation rate (EDR) at the particle-fluid interface is considered. Two models, namely, A and B with different types of interaction connections between nearby shells, are used first to compare the results of the particle-laden case with decaying turbulence. The number of tree connections in the model is found to affect the amount of augmentation of EDR near the particle surface. Model B is studied further with different sizes of particles in forced turbulence cases and compared to the unladen case with the same parameters. Also, the model expression is studied in the forced turbulence case of dual particles separated by given distances. The results of spatiotemporal shell models provide new approach of handling high Reynolds turbulence in dispersed phase multiphase systems. [ABSTRACT FROM AUTHOR]