Occupation theory composite

The Ariens composite occupation theory was soon supplemented by that of Stephenson (1956). Using new, precise data for the effect of acetylcholine and histamine on guinea-pig ileum, Stephenson found, from the slope of the con-centration-versus-effect curve, that the activity was not proportional to the number of receptors occupied. He was led to conclude, (a) that a maximal effect can be produced by the occupation of only a small proportion (even an exceedingly small proportion) of available receptors, (b) that response was not linearly proportional to the number of receptors occupied, and (c) that different drugs have different capacities to initiate a response, and hence that they occupy different proportions of the receptors when producing equal responses. This... 

The Ariens composite occupation theory was soon supplemented by that of Stephenson (1956). Using new, and more precise data for the effect of acetylcholine and histamine on guinea-pig ileum, Stephenson found, from the slope of the concentration-versus-effect curve, that the activity was not proportional to the number of receptors occupied. He was led to conclude,... 

I would like to suggest that the reader would take up the simulation of a crystal structure, which is of interest for him or her. The study of solids by means of the first-principle simulation based on the density functional theory allows one to obtain new and useful data. The definite advantage of the method is a possibility in a variation of a composition, a type of the crystal structure and the unit cell. The computer simulation is a promising addition to experimental results. Besides, it is a creative and fascinating occupation for a researcher. 

Percolation theory rationalizes sizes and distribution of connected black and white domains and the effects of cluster formation on macroscopic properties, for example, electric conductivity of a random composite or diffusion coefficient of a porous rock. A percolation cluster is defined by a set of connected sites of one color (e.g., white ) surrounded by percolation sites of the complementary color (i.e., black ). If p is sufficiently small, the size of any connected cluster is likely to be small compared to the size of the sample. There will be no continuously connected path between the opposite faces of the sample. On the other hand, the network should be entirely connected if p is close to 1. Therefore, at some well-defined intermediate value of p, the percolation threshold, pc, a transition occurs in the topological structure of the percolation network that transforms it from a system of disconnected white clusters to a macroscopically connected system. In an infinite lattice, the site percolation threshold is the smallest occupation probability p of sites, at which an infinite cluster of white sites emerges. 

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