Da Oriente al Nord Europa, dalla piazza alla tavola. Lo studio dei registri dei dazi come fonte per la storia dell'alimentazione. Il caso delle "vacchette" della città di Bologna (XIV-XV secolo)

Questo progetto di ricerca si pone l'obiettivo di gettare luce sul commercio delle spezie nel Medioevo, a partire dai preziosi dati contenuti nei registri del dazio di Bologna (1388-1448), nei quali venivano raccolti tutti i prodotti afferenti al cosiddetto "dazio della mercanzia" che transitavano in città per poi proseguire il viaggio verso altre destinazioni. Nel Medioevo, Bologna rappresentava un importante snodo per collegare i principali empori del mare Adriatico (prima fra tutti Venezia) con i mercati della Toscana, come Firenze, Pisa e il suo sbocco marittimo, Porto Pisano, da cui le spezie salpavano in direzione di altre regioni europee, come la Francia, l'Inghilterra, la penisola iberica e le Fiandre. I quantitativi di spezie giornalieri, mensili, annuali e totali costituiscono un dato inedito ed inaspettato: infatti, un prodotto tradizionalmente descritto dalla storiografia come raro, prezioso e difficile da reperire, affluiva in realtà con sorprendente costanza e raggiungendo volumi molto elevati. Considerando che Bologna, nonostante la sua importanza nel panorama italiano, rappresentava pur sempre uno snodo "minore" nella complessa rete di circuiti commerciali su cui erano solite viaggiare le spezie (come le grandi rotte marittime, per esempio), questi quantitativi tanto elevati di spezie ci obbligano a riflettere su quanto detto sino ad ora sul commercio di questi prodotti nel Medioevo e a mettere i dati bolognesi a confronto con quelli provenienti da altre fonti. Affiancando al tradizionale metodo storiografico un approccio "empirico", che tenga conto delle caratteristiche materiali ed organolettiche delle spezie, nonché delle informazioni provenienti da un ampio numero di fonti – non necessariamente legate al periodo preso in esame – è possibile riaprire il dibattito attorno a questo tema, che ha ancora molto da offrire alla ricerca storico alimentare.

Digital 3D reconstruction as a research environment in art and architecture history: uncertainty classification and visualisation

The dissertation addresses the still not solved challenges concerned with the source-based digital 3D reconstruction, visualisation and documentation in the domain of archaeology, art and architecture history. The emerging BIM methodology and the exchange data format IFC are changing the way of collaboration, visualisation and documentation in the planning, construction and facility management process. The introduction and development of the Semantic Web (Web 3.0), spreading the idea of structured, formalised and linked data, offers semantically enriched human- and machine-readable data. In contrast to civil engineering and cultural heritage, academic object-oriented disciplines, like archaeology, art and architecture history, are acting as outside spectators. Since the 1990s, it has been argued that a 3D model is not likely to be considered a scientific reconstruction unless it is grounded on accurate documentation and visualisation. However, these standards are still missing and the validation of the outcomes is not fulfilled. Meanwhile, the digital research data remain ephemeral and continue to fill the growing digital cemeteries. This study focuses, therefore, on the evaluation of the source-based digital 3D reconstructions and, especially, on uncertainty assessment in the case of hypothetical reconstructions of destroyed or never built artefacts according to scientific principles, making the models shareable and reusable by a potentially wide audience. The work initially focuses on terminology and on the definition of a workflow especially related to the classification and visualisation of uncertainty. The workflow is then applied to specific cases of 3D models uploaded to the DFG repository of the AI Mainz. In this way, the available methods of documenting, visualising and communicating uncertainty are analysed. In the end, this process will lead to a validation or a correction of the workflow and the initial assumptions, but also (dealing with different hypotheses) to a better definition of the levels of uncertainty.

Applied biomaterials from sustainable sources

If we look back in time at the history of humanity, we can state that our generation is living an era of outstanding efficiency and progress because of globalization and global competition, even if this is resulting in the rapid depletion of energy sources and raw materials. The environmental impact of non-biodegradable plastic wastes is of increasing global concern: nowadays, imagining a world without synthetic plastics seems impossible, though their large-scale production and their extensive use have only spread since the end of the World War II. In recent years, the demand for sustainable materials has increased significantly and, with a view to circular economy, research has also focused on the enhancement and subsequent reuse of waste materials produced by industrial processing, intensive farming and the agricultural sector. Plastic polymers have been the most practical and economical solution for decades due to their low cost, prompt availability and excellent optical, mechanical and barrier properties. Biodegradable polymers could replace them in many applications, thus reducing the problems of traditional plastics disposability and the dependence on petroleum. Natural biopolymers are in fact characterized by a high biocompatibility and biodegradability and have already prompted research in the field of regenerative medicine. During my PhD, my goal was to use natural polymers from sustainable sources as raw materials to produce biomaterials, which are materials designed to interface with biological systems to evaluate, support or replace any tissue, organ, or function of the body. I focused on the use of the most abundant biopolymers in nature to produce biomaterials in the form of films, scaffolds and cements. After a complete characterization, the materials were proposed for suitable applications in different fields, from tissue engineering to cosmetics and food packaging. Some of the obtained results were published on international scientific and peer-reviewed journals.

Applying machine learning: a multi-role perspective

Machine (and deep) learning technologies are more and more present in several fields. It is undeniable that many aspects of our society are empowered by such technologies: web searches, content filtering on social networks, recommendations on e-commerce websites, mobile applications, etc., in addition to academic research. Moreover, mobile devices and internet sites, e.g., social networks, support the collection and sharing of information in real time. The pervasive deployment of the aforementioned technological instruments, both hardware and software, has led to the production of huge amounts of data. Such data has become more and more unmanageable, posing challenges to conventional computing platforms, and paving the way to the development and widespread use of the machine and deep learning. Nevertheless, machine learning is not only a technology. Given a task, machine learning is a way of proceeding (a way of thinking), and as such can be approached from different perspectives (points of view). This, in particular, will be the focus of this research. The entire work concentrates on machine learning, starting from different sources of data, e.g., signals and images, applied to different domains, e.g., Sport Science and Social History, and analyzed from different perspectives: from a non-data scientist point of view through tools and platforms; setting a problem stage from scratch; implementing an effective application for classification tasks; improving user interface experience through Data Visualization and eXtended Reality. In essence, not only in a quantitative task, not only in a scientific environment, and not only from a data-scientist perspective, machine (and deep) learning can do the difference.