La traduzione interculturale nell’Austria-Ungheria della Jahrhundertwende Analisi critica delle traduzioni in tedesco e in italiano del romanzo ungherese I ragazzi della Via Pál di Ferenc Molnár

Riconoscendo l’importanza delle traduzioni all’interno della cosiddetta repubblica democratica dell’infanzia, il lavoro analizza le prime traduzioni tedesche e italiane del classico della letteratura per l’infanzia I ragazzi della Via Pál di Ferenc Molnár, al fine di metterne in luce i processi non solo prettamente traduttivi, ma anche più ampiamente culturali, che hanno influenzato la prima ricezione del romanzo in due contesti linguistici spesso legati per tradizione storico-letteraria alla letteratura ungherese. Rispettando la descrizione ormai comunemente accettata della letteratura per ragazzi come luogo di interazione tra più sistemi – principalmente quello letterario, quello pedagogico e quello sociale –, il lavoro ricostruisce innanzitutto le dinamiche proprie dei periodi storici di interesse, focalizzando l’attenzione sulla discussione circa l’educazione patriottica e militare del bambino. In relazione a questa tematica si approfondisce l’aspetto della “leggerezza” nell’opera di Molnár, ricostruendo attraverso le recensioni del tempo la prima ricezione del romanzo in Ungheria e presentando i temi del patriottismo e del gioco alla guerra in dialogo con le caratteristiche linguistico-formali del romanzo. I risultati raggiunti – una relativizzazione dell’intento prettamente pedagogico a vantaggio di una visione critica della società e del militarismo a tutti i costi – vengono messi alla prova delle traduzioni. L’analisi critica si basa su un esame degli elementi paratestuali, sull’individuazione di processi di neutralizzazione dell’alterità culturale e infine sull’esame delle isotopie del “gioco alla guerra” e dei “simboli della patria”. Si mostra come, pur senza un intervento censorio o manipolazioni sensibili al testo, molte traduzioni italiane accentuano l’aspetto patriottico e militaresco in chiave pedagogica. Soprattutto in Italia, il romanzo viene uniformato così al contesto letterario ed educativo dell’epoca, mentre in area tedesca la ricezione nell’ambito della letteratura per ragazzi sembra aprire al genere del romanzo delle bande.

Graph algorithms for bioinformatics

Biological data are inherently interconnected: protein sequences are connected to their annotations, the annotations are structured into ontologies, and so on. While protein-protein interactions are already represented by graphs, in this work I am presenting how a graph structure can be used to enrich the annotation of protein sequences thanks to algorithms that analyze the graph topology. We also describe a novel solution to restrict the data generation needed for building such a graph, thanks to constraints on the data and dynamic programming. The proposed algorithm ideally improves the generation time by a factor of 5. The graph representation is then exploited to build a comprehensive database, thanks to the rising technology of graph databases. While graph databases are widely used for other kind of data, from Twitter tweets to recommendation systems, their application to bioinformatics is new. A graph database is proposed, with a structure that can be easily expanded and queried.

Network assimilation methodology and sectorization of water distribution systems by graph mining and optimization algorithm

Water Distribution Networks (WDNs) play a vital importance rule in communities, ensuring well-being band supporting economic growth and productivity. The need for greater investment requires design choices will impact on the efficiency of management in the coming decades. This thesis proposes an algorithmic approach to address two related problems:(i) identify the fundamental asset of large WDNs in terms of main infrastructure;(ii) sectorize large WDNs into isolated sectors in order to respect the minimum service to be guaranteed to users. Two methodologies have been developed to meet these objectives and subsequently they were integrated to guarantee an overall process which allows to optimize the sectorized configuration of WDN taking into account the needs to integrated in a global vision the two problems (i) and (ii). With regards to the problem (i), the methodology developed introduces the concept of primary network to give an answer with a dual approach, of connecting main nodes of WDN in terms of hydraulic infrastructures (reservoirs, tanks, pumps stations) and identifying hypothetical paths with the minimal energy losses. This primary network thus identified can be used as an initial basis to design the sectors. The sectorization problem (ii) has been faced using optimization techniques by the development of a new dedicated Tabu Search algorithm able to deal with real case studies of WDNs. For this reason, three new large WDNs models have been developed in order to test the capabilities of the algorithm on different and complex real cases. The developed methodology also allows to automatically identify the deficient parts of the primary network and dynamically includes new edges in order to support a sectorized configuration of the WDN. The application of the overall algorithm to the new real case studies and to others from literature has given applicable solutions even in specific complex situations.

Learning representations for graph-structured socio-technical systems

The recent widespread use of social media platforms and web services has led to a vast amount of behavioral data that can be used to model socio-technical systems. A significant part of this data can be represented as graphs or networks, which have become the prevalent mathematical framework for studying the structure and the dynamics of complex interacting systems. However, analyzing and understanding these data presents new challenges due to their increasing complexity and diversity. For instance, the characterization of real-world networks includes the need of accounting for their temporal dimension, together with incorporating higher-order interactions beyond the traditional pairwise formalism. The ongoing growth of AI has led to the integration of traditional graph mining techniques with representation learning and low-dimensional embeddings of networks to address current challenges. These methods capture the underlying similarities and geometry of graph-shaped data, generating latent representations that enable the resolution of various tasks, such as link prediction, node classification, and graph clustering. As these techniques gain popularity, there is even a growing concern about their responsible use. In particular, there has been an increased emphasis on addressing the limitations of interpretability in graph representation learning. This thesis contributes to the advancement of knowledge in the field of graph representation learning and has potential applications in a wide range of complex systems domains. We initially focus on forecasting problems related to face-to-face contact networks with time-varying graph embeddings. Then, we study hyperedge prediction and reconstruction with simplicial complex embeddings. Finally, we analyze the problem of interpreting latent dimensions in node embeddings for graphs. The proposed models are extensively evaluated in multiple experimental settings and the results demonstrate their effectiveness and reliability, achieving state-of-the-art performances and providing valuable insights into the properties of the learned representations.

Supporting requirement elicitation and ontology testing in knowledge graph engineering

Knowledge graphs and ontologies are closely related concepts in the field of knowledge representation. In recent years, knowledge graphs have gained increasing popularity and are serving as essential components in many knowledge engineering projects that view them as crucial to their success. The conceptual foundation of the knowledge graph is provided by ontologies. Ontology modeling is an iterative engineering process that consists of steps such as the elicitation and formalization of requirements, the development, testing, refactoring, and release of the ontology. The testing of the ontology is a crucial and occasionally overlooked step of the process due to the lack of integrated tools to support it. As a result of this gap in the state-of-the-art, the testing of the ontology is completed manually, which requires a considerable amount of time and effort from the ontology engineers. The lack of tool support is noticed in the requirement elicitation process as well. In this aspect, the rise in the adoption and accessibility of knowledge graphs allows for the development and use of automated tools to assist with the elicitation of requirements from such a complementary source of data. Therefore, this doctoral research is focused on developing methods and tools that support the requirement elicitation and testing steps of an ontology engineering process. To support the testing of the ontology, we have developed XDTesting, a web application that is integrated with the GitHub platform that serves as an ontology testing manager. Concurrently, to support the elicitation and documentation of competency questions, we have defined and implemented RevOnt, a method to extract competency questions from knowledge graphs. Both methods are evaluated through their implementation and the results are promising.