Maria Mannone

The mathematical music composition workshop, an endeavor that integrates mathematics and music majors, is a concrete example of a STEAM (science, technology, engineering, arts, and mathematics) project. In this article, the authors analyze how mathematics students and music composition students have worked together, have learned to interpret specialized languages from one another, and have presented their results to a public interested in the relationship that guards these two disciplines. The goal of improving the understanding of abstract mathematical concepts through the application to musical structures is analyzed using the Onto-semiotic Approach (OSA). This framework sheds light on some of the written and oral manifestations of the students who participated. The mathematical competence that the participants were expected to achieve through this interdisciplinary endeavor are privileged in this article over the music education goals (which were also present).

Precision medicine aims to overcome the traditional one-model-fits-the-whole-population approach that is unable to detect heterogeneous disease patterns and make accurate personalized predictions. Heterogeneity is particularly relevant for patients with complications of type 2 diabetes, including diabetic kidney disease (DKD). We focus on a DKD longitudinal dataset, aiming to find specific subgroups of patients with characteristics that have a close response to the therapeutic treatment. We develop an approach based on some particular concepts of category theory and cluster analysis to explore individualized modelings and achieving insights onto disease evolution. This paper exploits the visualization tools provided by category theory, and bridges category-based abstract works and real datasets. We build subgroups deriving clusters of patients at different time points, considering a set of variables characterizing the state of patients. We analyze how specific variables affect the disease progress, and which drug combinations are more effective for each cluster of patients. The retrieved information can foster individualized strategies for DKD treatment.