La performance rituale delle Nava Durgā: musica e danza tra i Banmālā di Bhaktapur, Nepal

Il presente lavoro è il risultato di cinque anni di ricerca sulla performance rituale delle Nava Durgā del popolo newar a Bhaktapur (Nepal). Dal 1512, per circa nove mesi all'anno, gli uomini della casta inferiore Banmālā reincarnano le nove manifestazioni femminili della dea Durgā ed eseguono le danze in maschera. La performance della Nava Durgā è una pratica culturale molto complessa, composta da suoni, danze, processioni, momenti di venerazione (pūjā), rituali tantrici e momenti sacrificali. Gli aspetti musicali e teatrali della performance costituiscono il focus dell’indagine di questo studio. Dopo una descrizione analitica degli strumenti musicali utilizzati nella performance, alcuni elementi sonori vengono trascritti e analizzati mettendo in luce le caratteristiche tipiche della musica newar. I contenuti narrativi delle danze e il ciclo vitale delle Nava Durgā rispecchiano la vita hindu. La loro interpretazione viene realizzata in base alle osservazioni etnografiche; alcuni temi che costituiscono gli obiettivi dei devoti hindu (puruṣārtha) vengono esaminati attraverso l’approccio storico e quello etnografico, anche al fine di sottolineare il ruolo didascalico e formativo della performance. Un altro argomento discusso in questo lavoro consiste nell'identità dei danzatori Banmālā e quella del popolo newar in generale; questo aspetto è emerso in modo rilevante anche durante le fasi di mediatizzazione della performance delle Nava Durgā avvenute nel periodo del COVID-19. Da questo punto di vista, il presente lavoro costituisce un contributo alla diffusione della conoscenza della tradizione delle Nava Durgā; questo converge con l'obiettivo dei Banmālā di aumentare la visibilità della performance al fine di affermare la propria identità sia nel contesto nazionale che in quello internazionale.

Waste prevention: policy instruments and business model innovation

Waste prevention (WP) is a strategy which helps societies and individuals to strive for sufficiency in resource consumption within planetary boundaries alongside sustainable and equitable well-being and to decouple the concepts of well-being and life satisfaction from materialism. Within this dissertation, some instruments to promote WP are analysed, by adopting two perspectives: firstly, the one of policymakers, at different governance levels, and secondly, the one of business in the electrical and electronic equipment (EEE) sector. At a national level, the role of WP programmes and market-based instruments (extended producer responsibility, pay-as-you-throw schemes, deposit-refund systems, environmental taxes) in boosting prevention of municipal solid waste is investigated. Then, focusing on the Emilia-Romagna Region (Italy), the performances of the waste management system are assessed over a long period, including some years before and after an institutional reform of the waste management governance regime. The impact of a centralisation (at a regional level) of both planning and economic regulation of the waste services on waste generation and WP is analysed. Finally, to support the regional decision-makers in the prioritisation of publicly funded projects for WP, a framework for the sustainability assessment, the evaluation of success, and the prioritisation of WP measures was applied to some projects implemented by Municipalities in the Region. Trying to close the research gap between engineering and business, WP strategies are discussed as drivers for business model (BM) innovation in EEE sector. Firstly, an innovative approach to a digital tracking solution for professional EEE management is analysed. New BMs which facilitate repair, reuse, remanufacturing, and recycling are created and discussed. Secondly, the impact of BMs based on servitisation and on producer ownership on the extension of equipment lifetime is analysed, by performing a review of real cases of organizations in the EEE sector applying result- and use-oriented BMs.

Digital Forensics AI: on Practicality, Optimality, and Interpretability of Digital Evidence Mining Techniques

Digital forensics as a field has progressed alongside technological advancements over the years, just as digital devices have gotten more robust and sophisticated. However, criminals and attackers have devised means for exploiting the vulnerabilities or sophistication of these devices to carry out malicious activities in unprecedented ways. Their belief is that electronic crimes can be committed without identities being revealed or trails being established. Several applications of artificial intelligence (AI) have demonstrated interesting and promising solutions to seemingly intractable societal challenges. This thesis aims to advance the concept of applying AI techniques in digital forensic investigation. Our approach involves experimenting with a complex case scenario in which suspects corresponded by e-mail and deleted, suspiciously, certain communications, presumably to conceal evidence. The purpose is to demonstrate the efficacy of Artificial Neural Networks (ANN) in learning and detecting communication patterns over time, and then predicting the possibility of missing communication(s) along with potential topics of discussion. To do this, we developed a novel approach and included other existing models. The accuracy of our results is evaluated, and their performance on previously unseen data is measured. Second, we proposed conceptualizing the term “Digital Forensics AI” (DFAI) to formalize the application of AI in digital forensics. The objective is to highlight the instruments that facilitate the best evidential outcomes and presentation mechanisms that are adaptable to the probabilistic output of AI models. Finally, we enhanced our notion in support of the application of AI in digital forensics by recommending methodologies and approaches for bridging trust gaps through the development of interpretable models that facilitate the admissibility of digital evidence in legal proceedings.