Close-response curve

FIGURE 1.14 Major attributes of agonist close-response curves. Maximal responses solely reflect efficacy while the potency (location along the concentration axis) reflects a complex function of both efficacy and affinity. 

FIGURE 10.1 Possible close-response curves that could yield the ordinate value shown at a concentration of 20 pM compound. 

General Procedure A set of close-response curves to an agonist are obtained, one in the absence of and the others in the presence of a range of concentrations of the antagonist. The magnitude of the displacement of the curves along the concentration axis is used to determine the potency of the antagonist. 

Fig. 6.29 Closed-loop frequency response showing best flatband response (curve (b)) and response with...

Resolution can be defined in two other ways minimum detectable signal level applicable when the response is in the vicinity of the output noise level, and minimum detectable signal change level applicable at any operating point along the domain of the response curve when the measurand change is close to the noise level. 

In view of the future development of sensors driven by increasing demand for accuracy and precision, and by the opening of new fields close to the biological area (which is oriented toward nano-biosensor fabrication), it appears even more important to properly use the most relevant sensor keywords, such as response curve, sensitivity, noise, drift, resolution, and selectivity. 

For larger extents of dispersion, DjuL > 0.01, the shape of impulse response curves f(0) depends on whether reactor boundaries are assumed open or closed. Equation (72) gives the form of such curves when both boundaries are open and Fig. 17 is a plot of eqn. (72) for specific values... 

Figure 13.8 Tracer response curves for closed vessels and large deviations from plug flow.

Figure 13.13 Step response curves for large deviations from plug flow in closed vessels.

As mentioned earlier, obtaining and interpreting the actual experimental flow pattern is usually impractical. Hence, the approach taken is to postulate a flow model which reasonably approximates real flow, and then use this flow model for predictive purposes. Naturally, if a flow model closely reflects a real situation, its predicted response curves will closely match the tracer-response curve of the real vessel this is one of the requirements in selecting a satisfactory model. 

With these as the components of combined models the problem then is to find the volumes of the various regions and the rate of each type of flow occurring such that the response curves of the model match as closely as possible the response curves for the real vessel. 

Cohen and C00N(27) determined the relationships in Table 7.4 so as to give responses having large decay ratios, minimum offset and minimum area under the closed-loop response curve. 

Sensors of this type were constructed as multi-electrode arrays bearing chohnesterases of differing sensitivity to organo-phosphates, and the assay extended to milk [35]. Both spiked milk and milk from shops inhibited the activity of the electrodes. In two instances, estimates of the level of organo-phosphates in spiked milk made using sensors were very close to those made using GC-MS. This appears to have been a fortunate co-incidence as the response curves used for calibration were not linear. Nine out of ten milk samples from shops inhibited at least some members of the array. In only one case did the GC-MS assay find insecticides in the samples, but the insecticides were not organo-phosphates. The inhibition shown by the enzyme-based arrays was reversible by pyridine-2-aldoxime... 

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