This model supposes that the adsorption takes place at a specific adsorption surface.
Definition 2.1 (Epistemic Model) Suppose that \(G\) is a strategic game, \(S\) is the set of strategy profiles of \(G\), and \ \A\) is the set of players.
This model supposes that magma is composed of numerous elemental spherical cells which have one gas bubble at the center of each cell (Fig. 2).
The SK model supposes that a uniformly strained film (the wetting layer) grows pseudomorphically on the substrate below some thickness of Ge or Ge1-x Si x.
Thus, the medical model supposes that the question of who counts as disabled can be answered in a way that is value-free and that abstracts from existing social practices and the physical environment those practices have constructed.
The idea is simple: replace the plausibility orderings with probability distributions: Definition 2.6 (Epistemic-Probability Model) Suppose that \(G\) is a strategic game, \(S\) is the set of strategy profiles of \(G\), and \ \A\) is the set of players.
We suppose that players have a fixed endowment that they can allocate across links, and in the baseline model, suppose that link strength is an additively separable and convex function of individual investments, and that agents use the path which maximizes the product of link strengths.
Whereas the matrix effect model supposes that predator penetrate from habitat of higher predator density to habitat of lower predator density, thus causing an edge effect in the latter, according to the ecotonal effect model predators preferentially use edge habitats over habitat interiors.
The removal of copper and cadmium from zeolite as a function of time can be mathematically expressed in terms of different kinetic adsorption models such as: Pseudo-first-order kinetic model supposes that the rate of change of adsorbate uptake with time is directly proportional to the difference in the equilibrium concentration and the amount of adsorbate uptake with time (Ho and McKay 1998).
The communication model supposes that the mobility between two places i and j is a function of the distance (d_{ij}) separating the two locations, and of the intensity of communication between these two locations, (c_{ij}): T_{ij} = k frac{c_{ij}}{d_{ij}^{beta}}, (18) where k is a normalization constant.
