This research aims to study the Gruppi di azione patriottica within the Italian Resistance, turning the focus toward the "peripheries." It explores how the directives of the Italian Communist Party were implemented in smaller towns, whether and how they differed from what has already been studied regarding the major cities of the industrialized Center-North in terms of action, organization, and guerrilla practices. The analysis focuses on two case studies, the Pesaro-Urbino area and the lower...
Background: Enhanced Recovery After Surgery (ERAS) protocols are multimodal, evidence-based perioperative pathways designed to reduce surgical stress and accelerate functional recovery. In thoracic surgery, ERAS has been associated with improved clinical outcomes. However, most available evidence derives from high-volume tertiary centres, with limited comparative data on feasibility and effectiveness across institutions with varying levels of maturity and resources. Objective: This thesis aim...
“Artificial Intelligence is developing fast” and is central to legal, social, and ethical discourse for its potential to reshape modern living. Among the evolving applications of Artificial Intelligence (AI), this thesis focuses on autonomous vehicles and their critical impact over mobility paradigms in the European Union. Self-driving models are widely considered to be groundbreaking technology that is beneficial as much as it is disruptive. They are set to reshape mobility by, among other b...
In recent years, the development and clinical implementation of targeted therapies and immunotherapies have significantly changed the therapeutic approach to metastatic colorectal carcinoma (mCRC), leading to substantial improvements in patient outcomes. In this context, molecular characterization plays a central role in guiding treatment decisions and enabling a precision medicine approach. Currently, the main predictive biomarkers used in clinical practice include activating mutations in th...
This thesis investigates the temporal behaviour of the optic nerve sheath diameter (ONSD) as a non-invasive neuromonitoring tool in patients with acute brain injury admitted to the Neuro-Intensive Care Unit. ONSD, measurable at the bedside via transorbital ultrasonography, has been established as a surrogate marker of intracranial pressure (ICP) due to the anatomical continuity between the optic nerve sheath and the intracranial subarachnoid space. However, its dynamic properties — particular...
This thesis examines the significance of the body across T. S. Eliot’s major and minor works, including his published and unedited poetry, drama, and criticism. In light of the significant expansion of the materials available to scholars and of a renewed interest in Eliot generated by innovative methodological approaches, this study offers the first full-length exploration of Eliot’s corporeal poetics. Contrary to previous frameworks that have emphasised the poet’s impersonality and objectivi...
The study investigates the dynamics of verbal impoliteness within public oratory in republican Rome, applying modern theories of pragmatics and linguistic politeness to the study of classical texts, based on the possible overlap of the sociological concept of "face" with the Roman concept of dignitas. Through the analysis of several famous orations by Cicero and a comparison with selected passages from the same author's rhetorical works, the thesis examines how public orators managed the deli...
Artificial Intelligence has entered the era of Foundation Models: large-scale architectures achieving remarkable performance across tasks. However, they are computationally expensive, environmentally demanding, and inherently static, struggling to adapt to evolving data distributions. Concurrently, continual learning research shows neural networks are prone to catastrophic forgetting, making stable long-term adaptation a fundamental challenge. This dissertation argues that compositionality of...
This dissertation, developed within the scope of the National PhD in Artificial Intelligence for Society at the University of Pisa, proposes an ethical design framework for trustworthy artificial intelligence systems called "Endless Tuning". The work responds to the need to employ deep AI systems without replacing human decision-making while simultaneously addressing the so-called "responsibility gap". Drawing on a relational ethics perspective, the research investigates human vulnerability i...
Deep Graph Networks (DGNs) have emerged as the most prominent methodology for processing graph-structured data, achieving remarkable performance on predictive tasks. However, DGNs' inductive biases, the set of assumptions that allow for generalising to unseen data, are obscured by many human-unintelligible parameters; thereby raising concerns about their reliability and compromising their adoption due to conflicts with regulatory frameworks, such as the EU AI Act. The field of Graph Explainab...