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ADAM (a disintegrin and metalloproteinase) 10 is a key member of the ADAM family of disintegrin and metalloproteinases which process membrane-associated proteins to soluble forms in a process known as 'shedding'. Among the major targets of ADAM10 are Notch, EphrinA2 and CD44. In many cell-based studies of shedding, the activity of ADAM10 appears to overlap with that of ADAM17, which has a similar active-site topology relative to the other proteolytically active ADAMs. The tissue inhibitors of metalloproteinases, TIMPs, have proved useful in the study of ADAM function, since TIMP-1 inhibits ADAM10, but not ADAM17; however, both enzymes are inhibited by TIMP-3. In the present study, we show that, in comparison with ADAM17 and the MMPs (matrix metalloproteinases), the N-terminal domains of TIMPs alone are insufficient for the inhibition of ADAM10. This knowledge could form the basis for the design of directed inhibitors against different metalloproteinases.

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Safety factors required to control fatigue damage of deepwater metallic risers caused by Vortex-Induced Vibration (VIV) are considered. Four different riser configurations are studied: • Case I and II: Vertical tensioned 12” risers suspended from a spar buoy at water depths of 500m and 1500m. • Case III and IV: Steel catenary risers suspended from a spar buoy, both at 1000m. For Case III, the riser diameter is 12”, while for Case IV it is 30”. For each riser configuration, relevant design and analysis parameters which are subject to uncertainty are identified. For these quantities, random variables are established including model uncertainties. Subsequently, repeated analyses of fatigue damage are performed by varying the input parameters within representative intervals. The results are applied to fit analytical expressions (i.e., so-called response surfaces) utilized to describe the limit state function and to develop the probabilistic model for reliability analysis of the risers. By combining the random variables for the input parameters with the results from the parameter variations, the relationship between the fatigue safety factor and the failure probability is established for each riser configuration.

It is said that nature attempts to solve the ‘problem of life’ through evolution. ‘Solutions’ are proposed which are then tested in the world around us. Natural selection ensures that the best characteristics are inherited by subsequent generations. This paper gives details of a new method of automated riser design and optimization using techniques based on evolutionary theory. Genetic algorithms are a subset of evolutionary computation which rely on natural selection to evolve good designs. A given design (e.g. riser system) is represented by a ‘genome’ in which the design variables are encoded in the form of ‘genes’. The optimization software interfaces with an industry standard marine simulation package for design evaluation which gives rise to a great deal of flexibility and few limitations on model complexity. The software can be used for whole system design including multiple risers or as an assistant for the optimization of specific design variables. The software is capable of evaluating systems using both static and dynamic simulations for any number of loadcase scenarios. The design of a titanium catenary gas export riser intended for Statoil’s Kristin semi-submersible platform in the North Sea is used to illustrate the method. The design created by the evolutionary software is a significant improvement on the design created using a traditional approach. The results demonstrate improvements in dynamic response together with a reduction in the riser bill of materials cost of approximately one-third, whilst the time spent on design was reduced by nearly an order of magnitude.