Maroon Archaeology Beyond the Americas: A View From Kenya

Archaeological research on Maroons—that is, runaway slaves—has been largely confined to the Americas. This essay advocates a more global approach. It specifically uses two runaway slave communities in 19th-century coastal Kenya to rethink prominent interpretive themes in the field, including “Africanisms,” Maroons’ connections to indigenous groups, and Maroon group cohesion and identity. This article’s analysis demonstrates that the comparisons enabled by a more globalized perspective benefit the field. Instead of eliding historical and cultural context, these comparisons support the development of more localized and historically specific understandings of individual runaway slave communities both in Kenya and throughout the New World

A data‐driven approach for predicting nepheline crystallization in high‐level waste glasses

High-level waste (HLW) glasses with high alumina content are prone to nepheline crystallization during the slow canister cooling that is experienced during large-scale production. Because of its detrimental effects on glass durability, nepheline (NaAlSiO4) precipitation must be avoided; however, developing robust, predictive models for nepheline crystallization behavior in compositionally complex HLW glasses is difficult. Using overly conservative constraints to predict nepheline formation can limit the waste loading to lower than the achievable capacity. In this study, a robust data-driven model using five compositional features has been developed to predict nepheline formation. A new descriptor is introduced called the difference based on correlation , which has higher accuracy compared to previous descriptors and also has more balanced false positive and false negative rates. The analysis of the model and the data show an overlap, instead of a distinct compositional boundary, between glasses that form and do not form nepheline. As a result, the model\u27s predictive accuracy is not the same throughout the feature space and instead is dependent on the location of the glass composition in the dimensionally reduced feature space