Abstract: The disclosure describes embodiments of systems, methods, and non-transitory computer readable storage media that utilize a machine learning model and a credit value model to generate user interface elements that present credit values and credit value conditions in real time for user accounts. For instance, the disclosed systems can generate an activity score using an activity machine learning model with internal user activity data of a user account. Then, utilizing a credit value model with the activity score and a user activity condition, the disclosed systems can determine a dynamic credit value range for the user account. Indeed, the disclosed systems can display user interface elements with selectable credit values from the dynamic credit value range. Additionally, the disclosed systems can utilize the credit value model to determine and display one or more dynamic credit value conditions for a selected credit value received from the selectable credit values.

Abstract: There is provided a process for increasing the yellowness of polyester polymer particles, preforms, bottles, and concentrates, containing a polyester polymer such as polyethylene terephthalate and copolymers by adding a yellow colorant and reheat agent particles comprising titanium, alloys of titanium, titanium nitride, titanium boride, titanium carbide, or combinations thereof to a melt phase polymerization process for making the polyester polymer to adding any one of the colorant or particles to a polyester polymer.