Design-expert software

The optimal conditions for nisin biosynthesis and lactic acid formation were obtained by further numerical analysis of the response surface using Design-Expert software and are presented in Table 7. The solution to the maximal nisin biosynthesis was 12.04 g/L for yeast extract, 0.57 g/L for KH2P04, and 0.57 g/L for MgS04. The solution to the maximal lactic acid production was 11.78 g/L for yeast extract, 0.64 g/L for KH2P04, and 0.63... 

Figure 3 shows a half-normal probability plot of the effect estimates obtained from the Design-Expert software package. Three main effects, A (pressure), B (power), and E (gap) are important. Because the main effects are aliased with three-factor interactions, this interpretation is probably correct. There are also two two-factor interaction alias chains that are important, AB = CE and AC = BE. Because AB is the interaction of two strong main effects, those of pressure and... 

Design-Expert Software. Version 6 User s Guide (2000). Stat-Ease Inc., Minneapolis. 

Chemometric Design Expert software was used to generate and manipulate the factorial data Neural network was carried out using the back propagation algorithm (WEKA) ... 

Hooda, A. Nanda, A. Jain, M. Kumar, V. Rathee, P. Optimization and evaluation of gastroretentive ranitidine HCl microspheres by using design expert software. Int. J. Biol. Macromol. 2012, 51 (5), 691-700. 

The experimental data were analyzed using design-expert software including analysis of variance (ANOVA). The values of coefCfcients for parameters (/5, p., / , /3y) in Equation (1), p-values, the determination coefCiient (R ) and adjusted determination coefCfcient (r,j ) were calculated by regression analysis. 

Design Expert software version 2.05. Minneapolis Stat-Ease, 1989. 

An experimental design was produced using Design-Expert software from Stat-Ease, Inc. Statistically designed experiments were produced D-optimally for the mixture variables. Nineteen different formulations and six replicates were needed... 

Plackett-Burman experimental design and results were shown in Table 3. Endoinulinase activity data was analyzed by variance analysis through Design-Expert software in Table 3, gaining the significance of various influencing factors (Table 4). 

Endoinulinase activity was analyzed by stepwise regression with Design-Expert software in Table 3, getting the Endoinulinase activity as response value s optimal regression equation ... 

The statistical analysis of experimental data was performed using Design-Expert software (Version 8.0.3, Stat-Ease, Minneapolis, MN, 2010) including analysis of variance (ANOVA). A design of 30 experiments for independent variables and responses for AFD and CA are listed in Table 2. 

After the responses were obtained, they were subjected to multiple nonlinear regression and optimization using the software Design-Expert (V6.0 Stat-Ease, Minneapolis, MN). Second-order polynomialmodels were applied to correlate these variables. Only the estimates of coefficients with significant levels higher than 90% (i.e., p < 0.10) were included in the final model. An F-test was used to evaluate the significance of the models. 

Several software programs are available to help you design and track DOEs including Minitab, Sigma XL, Design Expert, and JMP. 

A three-factor and three-level Box-Behnken design was applied for the optimization procedure using Design Expert 6 software (Stat-Ease). Several factors—the amounts of sucrose, cellobiose, and dextransucrase—used to prepare each of the 17 formulations are given in Tables 1 and 2. These high, medium, and low levels were selected from the preliminary experimentation. Optimization was performed using a desirability function to obtain the levels of Xj, A2, and X3. 

According to the results of the single factor experiment, reaction time was set in the range of 10-20 h, reaction temperature 20°C-40°C, dialysis time 6-10 h, DS and yield were employed as response value. A response surface method experiment was designed by a software — Design Expert 6.0. The results are shown in Table 5.2. 

A design infrastructure must provide flexibility in the choice of materials and structures. For instance, circuit models based on fixed features or stack-ups will not be as useful to designers as models that allow a designer to choose different variable parameters. Another major point to keep in mind is that different software tools are typically used to realize a successful design. One software tool can rarely effectively simulate and analyze both the individual building blocks and the total circuit. Finally, any design infrastructure must involve materials and fabrication experts to support design expertise. 

---