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Nathan Harris
Nathan Harris

File: Half Life 2 Episode ...

Semi-logarithmic histograms of the number of MWR episodes as a function of duration were well fit by linear regression (Fig. 3), indicating that the number of episodes to last a given duration followed an exponentially decaying distribution. It was therefore possible to calculate the half-life of reentry (t1/2, the amount of time required for half of initiated episodes to terminate) from the slope of these regressions, λ, (Equation 1).

File: Half Life 2 Episode ...

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Example semi-logarithmic plots demonstrating the exponentially decaying number of MWR episodes to last a given duration. Short wavelength tissue (A) had a shallow slope and resulted in a longer half-life (approximately 26 minutes). Long wavelength tissue (B) had a steep slope and resulted in a shorter half-life (approximately 7 seconds).

A-C: Semi-log plots of MWR half-life as a function of A/BL (A), APD (B), and RC (C). D-F: The mean number of waves per time step (shown in blue) and population variance (shown in red) as functions of A/BL (D), APD (E), and RC (F). G-I: Semi-log plots of the expected duration of reentry (calculated from the population mean and variance) as a function of A/BL (G), APD (H), and RC (I). Note the similar parameter dependencies of MWR half-life and expected duration.

The logarithm of the MWR half-lives as a function of the fibrillogenicity index. For all randomly generated tissues, the fit is poor (A). Limiting the analysis to tissues displaying only MWR results in a substantially improved correlation coefficient (B). Using an RC/APD cutoff of 0.18 to identify likely MWR episodes further improves correlation coefficient (C). 041b061a72




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