Calculation of factor effect

There are two sets of coefficients taken into account when computing the actual parameters from the baseline ones.

One consists of a coefficient which has one value for every cell and every external or internal factor, and which tells how much is the factor relevant to the cell. For example, it may tell that the cell is vagally inervated, or that the cell is placed in a region in which oxygenation changes. This coefficient is called coefficient of relevance of the factor for the cell.

For every factor and for every cell category, there is a transfer function, which tells how does each factor influence every parameter of cells in that category. The functions used for this purpose are from a class named limited linear transfer functions. There are four function arguments, named $\psi_0 < \psi_1$, $\tau_0 < \tau_1$. When the value of the factor is less than $\psi_0$ then the value of the function is $\tau_0$. When the value of the factor is more than $\psi_1$ then the value of the function is $\tau_1$. When the value of the factor is between $\psi_0$ and $\psi_1$ the value of the function varies linearly between $\tau_0$ and $\tau_1$.

For every cell, the factors are applied as follows: every factor is multiplied by the relevance coefficient for the cell. Then, the $\tau$ value for the result of applying the relevance coefficient to the factor is computed for every parameter in the cell. Then, for every parameter, the product of these $\tau$ values is computed and the result is multiplied with the basic value of the parameter, thus resulting the value of the actual parameter. This is repeated at the initiation of every cycle for every cell.

The baseline value of a factor with respect to a cell is the value for which the $\tau$ of the factor for the cell is 1.0.

PROBLEM. Wouldn't it be more normal for the relevance coefficient to amplify/diminish the difference between the 1 and the value of $\tau$? In this case a relevance coefficient of 0.0 would make $\tau$ 1.0 and make the factor irrelevant. A gradient towards the maximum intended effect of the factor would be obtained by varying the relevance coefficient between 0.0 and 1.0.