Abstract: Systems, methods and media are provided for optimizing similar item recommendations in a semi-structured environment. In one embodiment a system includes at least one processor and a memory storing instructions that, when executed by the at least one processor, cause the system to perform operations comprising, at least identifying a seed item; retrieving a subset of recommended items relevant to the seed item; and ranking the subset of recommended items based on an item conversion probability, wherein the ranking of the subset of recommended items is based on a machine learning technique, and wherein a binary or multi-class label is used as training input to the machine learning technique.

Abstract: The present disclosure relates generally to the field of tubes for carrying fluids. More specifically, the present disclosure relates to a tube having an oval shaped cross-section. In some embodiments, the tube with oval cross-section comprises a tube within a cavity in a gas turbine engine.

Abstract: A method of making a granulation comprising the steps of (a) combining sucralose, a polar solvent, a wettable material and an active agent, thereby forming a mixture; and (b) drying the mixture, thereby forming the granulation.