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Molecules 2019, 24, x 4 of 14 (LC) 2FI Molecules 2019, 24, 1388 Quadratic 0.3127 0.6684 0.0064 0.0042 0.7948 0.7534 0.4137 –0.9670 4 of 14 The most suitable model for each response was identified from having an adjusted R2 and The most suitable model for each response was identified from having an adjusted R2 and predicted R2 close to 1, with a significant sequential model sum of squares (p < 0.05) and non-significant predicted R2 close to 1, with a significant sequential model sum of squares (p < 0.05) and non- lack of fit (p > 0.05). Thus, the particle size, zeta potential, and EE were fitted to a quadratic second-order significant lack of fit (p > 0.05). Thus, the particle size, zeta potential, and EE were fitted to a quadratic polynomial model. In case of LC, although the adjusted R2 and predicted R2 values of the linear second-order polynomial model. In case of LC, although the adjusted R2 and predicted R2 values of model were approx. 0.77 or 0.65, respectively, they were the highest values compared to those of the the linear model were approx. 0.77 or 0.65, respectively, they were the highest values compared to interaction and quadratic models. Consequently, the linear model was generated and interpreted those of the interaction and quadratic models. Consequently, the linear model was generated and as the best model for this response. The equations for the four generated models are shown in interpreted as the best model for this response. The equations for the four generated models are Equations (1)–(4): shown in Equations (1) to Equations (4): YY1==36346.747.7+71+31.932.9X2X+1 +181.80.60X6X+2 +37347.41.81X8X−3 8..80X1X2 ++4422.0.055X1XX3 ++303.03.43X4X2XX3 ++ 1 123121323 (1()1) 22 22 22 57.02X1 −33.47X2 + 257.95X3 57.02X1 − 33.47X2 + 257.95X3 Y2- = 25.77−0.0234X1 + 1.49X2 − 7.53X3 + 0.8270X1X2 − 0.3109X1X3 + 1.34X2X3 + Y =−25.77−0.0234X +1.49X −7.53X +0.8270X X −0.3109X X +1.34X X + (2) 2 123121323 222 1.21X1 − 0.8977X2 + 5.68X3 (2) (3) (3) Y4 = 11.35 + 6.59X1 − 0.9431X2 − 4.34X3 (4) In the polynomial equation, a positive value indicates a synergistic effect through which the 1.21X12 − 0.8977X22 + 5.68X32 Y3 = 48.04 + 1.08X1 0.2771X2 1.47X3 + 0.1547X1X2 1.59X1X3 0.2248X2X3 + 0.5616X12 Y =48.04+1.08X −0.2771X −1.47X +0.1547X X −1.59X X −0.2248X X + 3 1 2 32 212 13 23 1.67X2 + 1.50X3 0.5616X12 − 1.67X22 + 1.50X32 Y4 = 11.35 + 6.59X1 − 0.9431X2 − 4.34X3 (4) In the polynomial equation, a positive value indicates a synergistic effect through which the response increases proportionally to the factor. In contrast, a negative value indicates an antagonistic response increases proportionally to the factor. In contrast, a negative value indicates an antagonistic effect through which the response decreases proportionally to the factor. These synergistic and effect through which the response decreases proportionally to the factor. These synergistic and antagonistic interactions between factors and responses were also confirmed by the three- antagonistic interactions between factors and responses were also confirmed by the three-dimensional dimensional response surface plots, shown in Figure 1. Lastly, Table 3 summarizes the significance response surface plots, shown in Figure 1. Lastly, Table 3 summarizes the significance of each factor of each factor studied in the models generated for each response. studied in the models generated for each response. (A) (B) Figure 1. Cont.PDF Image | Synergistic Effects of Photo-Irradiation and Curcumin-Chitosan
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