The core motivation for this study emanates from Voronin S.'s seminal work on the universality of the zeta function. This universality positions the zeta function as a pivotal element in the conceptual framework of global artificial intelligence, suggesting its potential as a foundational component. A critical barrier to harnessing this promising universality has been the absence of efficient algorithms capable of actualizing this concept.

This paper presents and discusses the pedagogical implication of teaching Shared Value, presenting a case study about a contamination lab namely the case of the Shared Value Living Lab (SVLL) which took place at the University of Torino (UniTO) in Italy. The paper analyzes the pedagogical side of CSV (arguments, topics, learning methodologies, etc.) in the framework of recent theories and approaches of teaching sustainability in business school and in the cooperation between industry and academia, as well. Our research methodology relies on the analysis and comparison of one case study under an intrinsic as it enables researchers to find “interactivity” and connectedness between the individuals participating. The SVLL case is an interesting example of co-creation of social value between academia and its stakeholders. First, it represents an inclusive project linking society and business; second, SVLL acted as a hub putting in contact different interlocutors; third, SVLL training stimulated the acquisition of soft skill in students (interviews, managing relations, represents the project outside university, explaining the project to people, research curiosity) through contamination activities. With our study, we demonstrate the change in students participating in the SVLL may not only be cognitive but also affective, making students feel hopeful, empowered and liberated, and ready to contribute to a more profound change towards the vast array of pro-sustainability behaviors.

We assume that poetic devices have an implicit goal: producing an overall sound scheme that will induce the reader to associate intended and expressed meaning to the sound of the poem. Sounds may be organized into categories and assigned presumed meaning as suggested by traditional literary studies. In my work, I have extracted automatically the sound grids of all the sonnets by William Shakespeare and have combined them with the themes expressed by their contents. In a first experiment I have computed lexically and semantically based sentiment analysis obtaining an 80% of agreement. In a second experiment sentiment analysis has been substituted by Appraisal Theory thus obtaining a more fine-grained interpretation which in some cases contradicts the first one. The computation for the second poet - regarded by many critics the best of last century - includes both vowels and consonants. In addition, it combines automatic semantically and lexically based sentiment analysis with sound grids. The results produce visual maps that clearly separate poems into three clusters: negative harmony, positive harmony and disharmony where the latter instantiates the need by the poet to encompass the opposites in a desperate attempt to reconcile them.