This research, starting from the dynamism that has always characterised private law, focuses on the evolution of profiling to the point of “personalisation”, especially from the perspective of vulnerable individuals, taking as its paradigm the study of Generative Artificial Intelligence, and in particular the socalled “Large Language Models”. Actually, the post-digital era is a direct consequence of the Fourth Industrial Revolution, a category that can be traced back to the study of complexit...
This thesis reports the development of an integrated theranostic platform that combines nanomedicine and advanced optical technologies to overcome the major limitations of conventional cancer treatments. Rooted in the principles of theranostics—the concurrent integration of diagnostic and therapeutic functionalities—the proposed approach aims to advance personalized medicine by enhancing therapeutic efficacy while minimizing systemic toxicity. In Chapter 1, the underlying theoretical framewor...
Earth Observation (EO) plays a key role in climate monitoring, urban planning, and natural resource management, producing increasingly large and complex datasets. While traditional Artificial Intelligence techniques, particularly classical Machine Learning and Deep Learning, have significantly improved the analysis of EO data, they are beginning to encounter important limitations in terms of computational cost, scalability, and model efficiency. This doctoral thesis investigates Quantum Compu...
Cancer is a global health burden, highlighting the limitations of traditional diagnostic approaches, which are often invasive, subjective, and limited in their capacity for timely detection. Addressing these challenges through the development of innovative diagnostic tools that enable accurate, non-invasive and objective assessment is crucial for advancing early diagnosis, optimizing treatment strategies, and improving patient outcomes. This thesis explores the transformative potential of adv...
Cancer is a global health burden, highlighting the limitations of traditional diagnostic approaches, which are often invasive, subjective, and limited in their capacity for timely detection. Addressing these challenges through the development of innovative diagnostic tools that enable accurate, non-invasive and objective assessment is crucial for advancing early diagnosis, optimizing treatment strategies, and improving patient outcomes. This thesis explores the transformative potential of adv...
This thesis focuses on developing and numerically analyzing chemical looping technologies and integrated processes for sustainable energy conversion and storage. Chemical looping involves the cyclic reduction and oxidation of solid oxygen carriers to facilitate reactions such as combustion, gasification and methanation, with applications in low-carbon energy generation and renewable fuel production. The research presented in this thesis is organized into three main directions: (a) the develop...
The healthcare sector is undergoing a profound transformation driven by the integration of Internet of Things (IoT) technologies and Artificial Intelligence (AI), leading to the emergence of the Smart Health paradigm. This new approach shifts healthcare from a traditional reactive and hospital centered model to a proactive, patient centered system that leverages continuous monitoring through wearable sensors and intelligent data analysis. Miniaturized devices collect real time physiological a...
The global energy landscape is undergoing a profound transformation, driven by the need to address climate change, rising energy demand, and the consequent reconfiguration of energy production and consumption systems. In line with policy directives, the energy transition focuses on increasing the integration of renewable energy sources (RES), reducing greenhouse gas (GHG) emissions, and improving energy efficiency. This process is strongly supported by widespread electrification across all se...