Given the complexities of a cell's variable exposure to autocrine/juxtacrine signaling in culture, this model incorporates a plausible basis for a variable activity of an autocrine signaling pathway eliciting heterogeneous expression of intracellular components.
It has two states, "yes" and "no," and changes from one to the other on the basis of a single variable, like the presence or absence of the RNA it is looking for.
In essence, the Ea calculated on the basis of a progress variable i is the Ea associated with the rate-limiting step for the formation of species i.
The first step involves splitting of the root node (i.e. the node representing the entire data set) into child nodes on the basis of a predictor variable.
Although comparison of 16S rDNA sequence types was useful in confirming that detected DNAs were derived from strains of A. phagocytophilum, the insensitivity of this locus for intraspecies delineation led us to attempt sequence typing on the basis of a more variable locus, msp4 (6, 28 ).
When knowledge about HIV/AIDS was assessed on the basis of a composite variable, more females were distributed at either extreme, i.e. more females had a 'poor knowledge' but, at the same time, more females had a 'good knowledge' compared with the males.
As a second novelty, this paper proposes a new approach for on-line secondary path modeling on the basis of a new variable-step-size (VSS) LMS algorithm in feedforward ANC systems.
On the basis of a three-variable Box Behnken design (BBD), RSM was used to determine the effect of pH values (range 3.2 6), light intensity (range 10 20×102 μW/cm2) and bias potential (range 0.1 1.1 V) on the levels of response, i.e. decolourization efficiency.
Response surface methodology in the Basis of a three-variable Box Behnken design was applied to determine the effect of pH values (4, 7 and 10), concentration of 2-nitrophenol (10, 20 and 30 ppm), and concentration of H2O2 (30, 60 and 90 ppm) on the levels of response and optimized these operational parameters.
As mentioned above, OLS can be useful for making a prediction of the dependent variable on the basis of a specific independent variable, but often underestimates the regression slope, in particular for low correlations [ 4].
