Content-aware approach for improving biomedical image analysis: an interdisciplinary study series

Biomedicine is a highly interdisciplinary research area at the interface of sciences, anatomy, physiology, and medicine. In the last decade, biomedical studies have been greatly enhanced by the introduction of new technologies and techniques for automated quantitative imaging, thus considerably advancing the possibility to investigate biological phenomena through image analysis. However, the effectiveness of this interdisciplinary approach is bounded by the limited knowledge that a biologist and a computer scientist, by professional training, have of each other’s fields. The possible solution to make up for both these lacks lies in training biologists to make them interdisciplinary researchers able to develop dedicated image processing and analysis tools by exploiting a content-aware approach. The aim of this Thesis is to show the effectiveness of a content-aware approach to automated quantitative imaging, by its application to different biomedical studies, with the secondary desirable purpose of motivating researchers to invest in interdisciplinarity. Such content-aware approach has been applied firstly to the phenomization of tumour cell response to stress by confocal fluorescent imaging, and secondly, to the texture analysis of trabecular bone microarchitecture in micro-CT scans. Third, this approach served the characterization of new 3-D multicellular spheroids of human stem cells, and the investigation of the role of the Nogo-A protein in tooth innervation. Finally, the content-aware approach also prompted to the development of two novel methods for local image analysis and colocalization quantification. In conclusion, the content-aware approach has proved its benefit through building new approaches that have improved the quality of image analysis, strengthening the statistical significance to allow unveiling biological phenomena. Hopefully, this Thesis will contribute to inspire researchers to striving hard for pursuing interdisciplinarity.

La prima casa editrice femminista per l'infanzia in Italia: gli albi illustrati di "Dalla parte delle bambine" di Adela Turin

La presente tesi di dottorato propone uno studio sulla casa editrice “Dalla parte delle bambine” di Adela Turin. Attiva dal 1975 al 1982 a Milano, si tratta della prima impresa editoriale femminista per l’infanzia in Italia. Nonostante l’originalità e il successo internazionale dei suoi libri, è stata riscontrata una sorprendente scarsità di studi sull’argomento. Questa ricerca interdisciplinare si propone quindi di colmare questa lacuna, inserendosi nel vivace ambito dello studio della letteratura per l’infanzia in prospettiva di genere. La dissertazione è divisa in cinque capitoli, a cui si aggiunge un’appendice iconografica che raccoglie le copertine dell’intero catalogo di DPDB. Nel primo capitolo viene introdotto il quadro teorico della ricerca, dalla complessità della letteratura per il giovane pubblico all’indagine in ottica di genere. Il secondo capitolo si concentra sulle pubblicazioni per bambine e bambini negli anni Settanta, passando in rassegna innovative esperienze editoriali nonché l’opera di scrittori e scrittrici sensibili alle questioni di genere. La terza sezione si occupa di ricostruire il profilo biografico di Turin e il suo decennale impegno contro il sessismo veicolato dai libri per l’infanzia, per poi concentrarsi sulla storia, il catalogo, la diffusione e la ricezione di DPDB. Il quarto capitolo propone un’analisi qualitativa e quantitativa di un corpus di 20 albi illustrati scritti da Turin, oltre a un confronto fra questi libri e diverse ricerche sulla rappresentazione di genere, allo scopo di evidenziare la peculiarità delle proposte di DPDB. La quinta sezione, infine, si occupa del rapporto con la contemporaneità. Dopo aver tracciato un quadro della complessa situazione dell’educazione di genere in Italia e aver proposto una panoramica di esperienze editoriali per il giovane pubblico attente alle questioni di genere, quest’ultima parte indagherà i contesti in cui gli albi di Turin vengono oggi letti e consigliati, offrendosi come narrazione alternativa e tutt’ora attuale.

Computational creativity: an interdisciplinary approach to sequential learning and creative generations

Creativity seems mysterious; when we experience a creative spark, it is difficult to explain how we got that idea, and we often recall notions like ``inspiration" and ``intuition" when we try to explain the phenomenon. The fact that we are clueless about how a creative idea manifests itself does not necessarily imply that a scientific explanation cannot exist. We are unaware of how we perform certain tasks, such as biking or language understanding, but we have more and more computational techniques that can replicate and hopefully explain such activities. We should understand that every creative act is a fruit of experience, society, and culture. Nothing comes from nothing. Novel ideas are never utterly new; they stem from representations that are already in mind. Creativity involves establishing new relations between pieces of information we had already: then, the greater the knowledge, the greater the possibility of finding uncommon connections, and the more the potential to be creative. In this vein, a beneficial approach to a better understanding of creativity must include computational or mechanistic accounts of such inner procedures and the formation of the knowledge that enables such connections. That is the aim of Computational Creativity: to develop computational systems for emulating and studying creativity. Hence, this dissertation focuses on these two related research areas: discussing computational mechanisms to generate creative artifacts and describing some implicit cognitive processes that can form the basis for creative thoughts.