The anionic peroxidase associated with the suberization response in potato (Solanum tuberosum L.) tubers during wound healing has been purified and partially characterized at the biochemical level. It is a 45-kD, class III (plant secretory) peroxidase that is localized to suberizing tissues and shows a preference for feruloyl (omethoxyphenol)-substituted substrates (order of substrate preference: feruloyl > caffeoyl > p-coumaryl Ϸ syringyl) such as those that accumulate in tubers during wound healing. There was little influence on oxidation by side chain derivatization, although hydroxycinnamates were preferred over the corresponding hydroxycinnamyl alcohols. The substrate specificity pattern is consistent with the natural substrate incorporation into potato wound suberin. In contrast, the cationic peroxidase(s) induced in response to wound healing in potato tubers is present in both suberizing and nonsuberizing tissues and does not discriminate between hydroxycinnamates and hydroxycinnamyl alcohols. A synthetic polymer prepared using E-[8-13 C]ferulic acid, H 2 O 2 , and the purified anionic enzyme contained a significant amount of cross-linking through C-8, albeit with retention of unsaturation.

The Saturation of Tactical Aviator Load Limits (STALL) is defined as the intersection of asymptotically high and low load limits. In a closed queuing system consisting of M homogeneous demand generators, it has been shown that response time becomes asymptotically linear as M increases. This provides a quantitative basis for specifying the saturation point if one knows both arrival rate and service rate (the inverse of task duration). Early in system development, one can typically estimate arrival rates based on mission analyses. But task durations cannot be estimated until procedures have been defined, based on system design. At this stage, it is useful to determine the design requirements. Given the imposed load, how fast must servicing be to keep up with demand? Logically, service rates must exceed arrival rates, but the question is: by how much? Two related criteria can apply: the number of backlogged demands, or the system response time. STALL computes statistics for both. Preliminary model validation has been accomplished, using simulation runs to study model robustness to systematic violations of assumptions. Predictive validity depends on being able to demonstrate that the assumptions are valid in a particular application. The simulations demonstrate what can happen when that match is not successfully achieved. These studies demonstrated that the predictions will typically be most robust for an over-saturated system. The model is least sensitive to violations of the servicing assumptions. Furthermore, it is easy to relax the assumption of homogeneous demand generators by developing planned model extensions.

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