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The sensitivity was then calculated by the following equation: [(-log?N/N0)/mJ?cm?2]. Statistical analysis.? A two-way (two factor) analysis of variance (ANOVA) was used to analyze the sensitivity for disinfection measurements. The ANOVA test compared the levels of each factor (PRF and duty cycle) and determined whether any of the levels had statistically different log kills per radiant exposure averages compared with the other levels within that factor. To determine whether a factor had levels with statistically significant differences in average log kills per J?cm?2, the P-value for each factor, calculated from the ANOVA test, was analyzed. If the P-value for duty cycle or pulses per second was less than the predetermined alpha (��) of 0.05, then it was concluded that at least two of the levels had statistically significant averages, and a Tukey http://www.selleckchem.com/products/DAPT-GSI-IX.html post hoc test was used to determine http://www.selleck.cn/products/dabrafenib-gsk2118436.html exactly which pairs of levels were significantly different for a specific factor. Using an �� cutoff of 0.05 meant that we were allowing at most a 5% chance of finding a statistically significant factor or significant difference between levels of a factor by random chance. In essence, the calculated P-value was the probability that the same results and differences would have been found assuming that the null hypothesis (all levels of a specific factor have equal means for kills per J?cm?2) was true. Additionally, two-way ANOVA test calculated how much of the observed variation in the kills per J?cm?2 calculations was accounted for by each factor in the study. http://www.selleckchem.com/products/Adriamycin.html Surface plots were also included in the statistical analysis to illustrate combinations of levels for the two factors that had higher averages of log kills per J?cm?2. With duty cycle on the y-axis and PRF on the x-axis, bands were created within the surface plots to display average log kills per J?cm?2 for combinations of the two factors. The same two-way ANOVA method was used to analyze how PRF and duty cycle affected the time-effectiveness and energy-effectiveness calculations. However, because the energy-effectiveness and time-effectiveness calculations were calculated in a similar fashion, the statistical results were exactly the same for the two measures. Figure?4 illustrates the varying sensitivity of E. coli for disinfection, as a function of duty cycle and PRF. Statistically significant correlations were found between sensitivity and duty cycle (P-value?