Fit maximum

Statistical analysis of the results was performed using the software Statistica 5.5 (Stat Soft). Maximum lipase activities and time to reach the maximum were calculated through fitting of kinetic curves. The maximum was estimated by derivation of the fits. Empirical models were built to fit maximum lipase activity in the function of incubation temperature (T), moisture of the cake (%M), and supplementation (%00). The experimental error estimated from the duplicates was considered in the parameter estimation. The choice of the best model to describe the influence of the variables on lipase activity was based on the correlation coefficient (r2) and on the x2 test. The model that best fits the experimental data is presented in Table 2. 

Concentration-response curve fitting of activity value y to obtain IC50 (or EC50) ymx and are fitted maximum and minimum values of data if data do not define maximum or minimum asymptote, ymx can be fixed to 100% and yrain to 0% respectively n is hill-slope coefficient and c is inhibitor (or activator) concentration... 

Commercially available coal based activated carbons Filtrasorb-400, Norit ROW 0.8 and Norit ROX 0.8 were chosen as the adsorbents. The adsorbates used for determination of the pore network connectivity of the carbons were ethyl propionate, ethyl butyrate, ethyl isovalerate, isobutyl acetate, benzaldehyde, hexyl acetate, methyl salicylate and 2-ethyl hexyl acetate. For the evaluation of the pore network connectivity, we used the fitted maximum capacity obtained fi om isotherm fitting to calculate the accessible pore volume [7]. 

Where F, assay signal at a given value of C C, the concentration of competing antigen M, fitted maximum fluorescence value K, fitted competitor concentration for which F = M/2 S, fitted slope value. 

SXRD fitting. Maximum deviations in Ti-0 of 8% were found in 100 surface structures computed by DFT in Ref [31]. 

In the maximum-likelihood method used here, the "true" value of each measured variable is also found in the course of parameter estimation. The differences between these "true" values and the corresponding experimentally measured values are the residuals (also called deviations). When there are many data points, the residuals can be analyzed by standard statistical methods (Draper and Smith, 1966). If, however, there are only a few data points, examination of the residuals for trends, when plotted versus other system variables, may provide valuable information. Often these plots can indicate at a glance excessive experimental error, systematic error, or "lack of fit." Data points which are obviously bad can also be readily detected. If the model is suitable and if there are no systematic errors, such a plot shows the residuals randomly distributed with zero means. This behavior is shown in Figure 3 for the ethyl-acetate-n-propanol data of Murti and Van Winkle (1958), fitted with the van Laar equation. 

Because the precision assigned to the upper and lower extrapolated points is relatively poor, it is possible to obtain a maximum or minimum in the curve, even when fitting all real and extrapolated data from 200 to 600°C. Extrema can occur anywhere, but generally they occur very close to either the lower or the upper end. A check of the sign of the slope at 200°C and 600°C easily indicated the presence of an extremum. When an extremum occurred, a new fit was established to avoid it. 

MAIN PROGRAM AND DRIVER FOR FITTING BINARY VLF DATA USING METHOD EASED ON THE MAXIMUM LIKELIHCOO PRINCIPLE ONLY CONTROL VARIABLES APE READ IN THIS ROUTINE. 

Beside all technical reasons the big advantage of a pneumatic test is, that the steam drums can remain within the line because first we have no additional load for the bearing and only small adjustments (for the connection with the pressurisation unit and the tightening of the man ways for the applied low temperature gas test) have to be done to make the drum ready for a pneumatic loading. The pressurised air is available in every paper mill and even if the maximum pressure does not fit, the use of a compressor or pressure bottles produce no problems. 

For each frequency 100 points were taken along a line running from the surface of the conductor into a depth of 30 mm in that region below the coil, where the maximum eddy currents are located (dashed vertical lines in the sketch). These data are fitted by appropriate polynomials to obtain an analytical expression for s (to, z) in the frequency and depth interval mentioned above. 

One limitation of clique detection is that it needs to be run repeatedly with differei reference conformations and the run-time scales with the number of conformations pt molecule. The maximum likelihood method [Bamum et al. 1996] eliminates the need for reference conformation, effectively enabling every conformation of every molecule to a< as the reference. Despite this, the algorithm scales linearly with the number of conformatior per molecule, so enabling a larger number of conformations (up to a few hundred) to b handled. In addition, the method scores each of the possible pharmacophores based upo the extent to which it fits the set of input molecules and an estimate of its rarity. It is nc required that every molecule has to be able to match every feature for the pharmacophor to be considered. 

In this project, we shall predict the wavelength of the absorption maxima of the same four polyenes using the calculated difference (in units of eV), between the LUMO and HOMO of these four molecules (Fig. 8-6). Bear in mind that this is not an ab initio calculation of wavelengths of maximum absorption, because empirically fitted parameters, Yio exist within the program or are... 

To obtain a maximum yield of the acid it is necessary to hydrolyse the by-product, iaoamyl iaovalerate this is most economically effected with methyl alcoholic sodium hydroxide. Place a mixture of 20 g. of sodium hydroxide pellets, 25 ml. of water and 225 ml. of methyl alcohol in a 500 ml. round-bottomed flask fitted with a reflux (double surface) condenser, warm until the sodium hydroxide dissolves, add the ester layer and reflux the mixture for a period of 15 minutes. Rearrange the flask for distillation (Fig. II, 13, 3) and distil off the methyl alcohol until the residue becomes pasty. Then add about 200 ml. of water and continue the distfllation until the temperature reaches 98-100°. Pour the residue in the flask, consisting of an aqueous solution of sodium iaovalerate, into a 600 ml. beaker and add sufficient water to dissolve any solid which separates. Add slowly, with stirring, a solution of 15 ml. of concentrated sulphuric acid in 50 ml. of water, and extract the hberated acid with 25 ml. of carbon tetrachloride. Combine this extract with extract (A), dry with a httle anhydrous magnesium or calcium sulphate, and distil off the carbon tetrachloride (Fig. II, 13, 4 150 ml. distiUing or Claisen flask), and then distil the residue. Collect the wovaleric acid 172-176°. The yield is 56 g. 

To ensure that only ions of any one selected m/z are transmitted (maximum resolution), the parameters (U, V, co) must be chosen such that a/q (or 2U/V) fits a line that passes close to R but... 

The simplest method of reduciag stresses and reactions is to provide additional pipe ia the system ia the form of loops or offset-bonds. When physical limitations restrict the use of additional bends, a multiple arrangement of several small-size pipe mns may sometimes be used. Owiag to stress intensification, the maximum stress generally occurs at elbows, bends, and Ts. Thus, heavier-walled fittings may reduce the stress without significantly impairing flexibiUty. FiaaHy, effectively located restraints can reduce thermal effects on the equipment. 

When experimental data is to be fit with a mathematical model, it is necessary to allow for the facd that the data has errors. The engineer is interested in finding the parameters in the model as well as the uncertainty in their determination. In the simplest case, the model is a hn-ear equation with only two parameters, and they are found by a least-squares minimization of the errors in fitting the data. Multiple regression is just hnear least squares applied with more terms. Nonlinear regression allows the parameters of the model to enter in a nonlinear fashion. The following description of maximum likehhood apphes to both linear and nonlinear least squares (Ref. 231). If each measurement point Uj has a measurement error Ayi that is independently random and distributed with a normal distribution about the true model y x) with standard deviation <7, then the probability of a data set is... 

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