Medicalizing gender: from intersex to DSD, from the laboratory to patient groups

The subject of this research, the medicalization of the gendered body, is a shifting object. It has changed its medical name from Intersex to DSD (Disorders -or Divergence- of Sex Development), since the beginning of this research project. Loosely speaking it addresses the gendered components of the body, and their subsequent consideration. Drawing closer, it addresses how modern medicine treats people who manifest variations of one of the gendered components of the body, inserting their bodies into pathological categories now called DSD. This shifting terrain of different modes of viewing the gendered body has grown to include many variations, no longer solely interested in the mythical hermaphrodite. The locus of this investigation is in the interaction between these patient groups and doctors in Italy.

Verso una sociologia della sostenibilità: il caso delle Città in Transizione. Prospettive e limiti di un percorso bottom-up

Oggetto di indagine del lavoro è il movimento ambientalista e culturale delle Città in Transizione che rappresentano esperimenti di ri-localizzazione delle risorse volte a preparare le comunità (paesi, città, quartieri) ad affrontare la duplice sfida del cambiamento climatico e del picco del petrolio. A partire dal Regno Unito, la rete delle Transition Towns si è in pochi anni estesa significativamente e conta oggi più di mille iniziative. L’indagine di tale movimento ha richiesto in prima battuta di focalizzare l’attenzione sul campo disciplinare della sociologia dell’ambiente. L’attenzione si è concentrata sul percorso di riconoscimento che ha reso la sociologia dell’ambiente una branca autonoma e sul percorso teorico-concettuale che ha caratterizzato la profonda spaccatura paradigmatica proposta da Catton e Dunlap, che hanno introdotto nel dibattito sociologico il Nuovo Paradigma Ecologico, prendendo le distanze dalla tradizionale visione antropocentrica della sociologia classica. Vengono poi presentate due delle più influenti prospettive teoriche della disciplina, quella del Treadmill of Production e la più attuale teoria della modernizzazione ecologica. La visione che viene adottata nel lavoro di tesi è quella proposta da Spaargaren, fautore della teoria della modernizzazione ecologica, secondo il quale la sociologia dell’ambiente può essere collocata in uno spazio intermedio che sta tra le scienze ambientali e la sociologia generale, evidenziando una vocazione interdisciplinare richiamata anche dal dibattito odierno sulla sostenibilità. Ma le evidenze empiriche progressivamente scaturite dallo studio di questo movimento che si autodefinisce culturale ed ambientalista hanno richiesto una cornice teorica più ampia, quella della modernità riflessiva e della società del rischio, in grado di fornire categorie concettuali spendibili nella descrizione dei problemi ambientali e nell’indagine del mutamento socio-culturale e dei suoi attori. I riferimenti empirici dello studio sono tre specifiche realtà locali in Transizione: York in Transition per il Regno Unito, Monteveglio (Bo) e Scandiano (Re) in Transizione per l’Italia.

Intercultural Performance and Dialogue. From Richard Schechner Performance Studies Onwards

Attraverso un excursus storico, teorico e metodologico, questa tesi di dottorato analizza la nascita, gli sviluppi e l’attuale dimensione costitutivo-identitaria dei Performance Studies, un ambito di ricerca accademica che, nato negli Stati Uniti alla fine degli anni Settanta, ha sempre palesato una natura restia nei confronti di qualunque tentativo definitorio. Se i Performance Studies concepiscono la performance sia come oggetto d’analisi sia come lente metodologica, e se, come evidenziato da Richard Schechner, praticamente tutto può essere “elevato a performance” e quindi indagato secondo le categorie analitiche di questa disciplina, ecco allora che, con uno slittamento transitivo e “meta-metodologico”, questa ricerca dottorale ha scelto come proprio oggetto di studio i Performance Studies stessi, osservandoli “as performance” e avvalendosi degli strumenti metodologici suggeriti dal suo stesso oggetto d’analisi. Questo lavoro indaga come l’oggetto di studio dei Performance Studies sia, seguendo la teoria schechneriana, il “behaved behavior”, e dunque come di conseguenza, il repertorio, prima ancora che l’archivio, possa essere considerato il fedele custode delle “pratiche incorporate”. Soffermandosi su esempi di “reenactment” performativo come quelli messi in atto da Marina Abramović e Clifford Owens, così come sui tentativi condotti dalla sezione dell’Intangible Cultural Heritage dell’UNESCO, suggerisce validi esempi di “archiviazione” della performance. L’elaborato prende poi in esame casi che esemplificano la proficua identificazione tra “studiare performance” e “fare performance”, sottolinea il ruolo cruciale e imprenscindibile determinato dal lavoro di ricerca sul campo inteso come “osservazione partecipante”, ed evidenzia il costante coinvolgimento sociale e politico assunto dai Performance Studies. Questa dissertazione affronta e supporta l’efficacia dei Performance Studies nel proporsi come uno strumento innovativo in grado di analizzare un mondo sempre più performativo nelle sue dinamiche. La loro natura tanto interdisciplinare quanto interculturale sembra farne una lente adeguata attraverso cui promuovere livelli diversi di performance dialogica tra culture localmente distinte ma globalmente assimilabili.

Monoidal categories for the physics of integrable models

Scopo di questa tesi é di evidenziare le connessioni tra le categorie monoidali, l'equazione di Yang-Baxter e l’integrabilità di alcuni modelli. Oggetto prinacipale del nostro lavoro é stato il monoide di Frobenius e come sia connesso alle C∗-algebre. In questo contesto la totalità delle dimostrazioni sfruttano la strumentazione dell'algebra diagrammatica. Nel corso del lavoro di tesi sono state riprodotte tali dimostrazioni tramite il più familiare linguaggio dell’algebra multilineare allo scopo di rendere più fruibili questi risultati ad un raggio più ampio di potenziali lettori.

High-mass Drell-Yan cross-section and search for new phenomena in multi-electron/positron final states with the ATLAS detector

The Standard Model of particle physics is a very successful theory which describes nearly all known processes of particle physics very precisely. Nevertheless, there are several observations which cannot be explained within the existing theory. In this thesis, two analyses with high energy electrons and positrons using data of the ATLAS detector are presented. One, probing the Standard Model of particle physics and another searching for phenomena beyond the Standard Model.rnThe production of an electron-positron pair via the Drell-Yan process leads to a very clean signature in the detector with low background contributions. This allows for a very precise measurement of the cross-section and can be used as a precision test of perturbative quantum chromodynamics (pQCD) where this process has been calculated at next-to-next-to-leading order (NNLO). The invariant mass spectrum mee is sensitive to parton distribution functions (PFDs), in particular to the poorly known distribution of antiquarks at large momentum fraction (Bjoerken x). The measurementrnof the high-mass Drell-Yan cross-section in proton-proton collisions at a center-of-mass energy of sqrt(s) = 7 TeV is performed on a dataset collected with the ATLAS detector, corresponding to an integrated luminosity of 4.7 fb-1. The differential cross-section of pp -> Z/gamma + X -> e+e- + X is measured as a function of the invariant mass in the range 116 GeV < mee < 1500 GeV. The background is estimated using a data driven method and Monte Carlo simulations. The final cross-section is corrected for detector effects and different levels of final state radiation corrections. A comparison isrnmade to various event generators and to predictions of pQCD calculations at NNLO. A good agreement within the uncertainties between measured cross-sections and Standard Model predictions is observed.rnExamples of observed phenomena which can not be explained by the Standard Model are the amount of dark matter in the universe and neutrino oscillations. To explain these phenomena several extensions of the Standard Model are proposed, some of them leading to new processes with a high multiplicity of electrons and/or positrons in the final state. A model independent search in multi-object final states, with objects defined as electrons and positrons, is performed to search for these phenomenas. Therndataset collected at a center-of-mass energy of sqrt(s) = 8 TeV, corresponding to an integrated luminosity of 20.3 fb-1 is used. The events are separated in different categories using the object multiplicity. The data-driven background method, already used for the cross-section measurement was developed further for up to five objects to get an estimation of the number of events including fake contributions. Within the uncertainties the comparison between data and Standard Model predictions shows no significant deviations.

Deep learning for computer vision: a comparison between convolutional neural networks and hierarchical temporal memories on object recognition tasks

In recent years, Deep Learning techniques have shown to perform well on a large variety of problems both in Computer Vision and Natural Language Processing, reaching and often surpassing the state of the art on many tasks. The rise of deep learning is also revolutionizing the entire field of Machine Learning and Pattern Recognition pushing forward the concepts of automatic feature extraction and unsupervised learning in general. However, despite the strong success both in science and business, deep learning has its own limitations. It is often questioned if such techniques are only some kind of brute-force statistical approaches and if they can only work in the context of High Performance Computing with tons of data. Another important question is whether they are really biologically inspired, as claimed in certain cases, and if they can scale well in terms of "intelligence". The dissertation is focused on trying to answer these key questions in the context of Computer Vision and, in particular, Object Recognition, a task that has been heavily revolutionized by recent advances in the field. Practically speaking, these answers are based on an exhaustive comparison between two, very different, deep learning techniques on the aforementioned task: Convolutional Neural Network (CNN) and Hierarchical Temporal memory (HTM). They stand for two different approaches and points of view within the big hat of deep learning and are the best choices to understand and point out strengths and weaknesses of each of them. CNN is considered one of the most classic and powerful supervised methods used today in machine learning and pattern recognition, especially in object recognition. CNNs are well received and accepted by the scientific community and are already deployed in large corporation like Google and Facebook for solving face recognition and image auto-tagging problems. HTM, on the other hand, is known as a new emerging paradigm and a new meanly-unsupervised method, that is more biologically inspired. It tries to gain more insights from the computational neuroscience community in order to incorporate concepts like time, context and attention during the learning process which are typical of the human brain. In the end, the thesis is supposed to prove that in certain cases, with a lower quantity of data, HTM can outperform CNN.

Model categories

The purpose of this thesis is to present some fundamental results about model categories, and to give some examples of categories that can be equipped with a model structure.

Regular and exact categories

Lo scopo del lavoro è quello di presentare alcune proprietà di base delle categorie regolari ed esatte nel contesto della teoria delle categoria algebrica.

Tor network forensics and hidden service deanonymization

The cybernetics revolution of the last years improved a lot our lives, having an immediate access to services and a huge amount of information over the Internet. Nowadays the user is increasingly asked to insert his sensitive information on the Internet, leaving its traces everywhere. But there are some categories of people that cannot risk to reveal their identities on the Internet. Even if born to protect U.S. intelligence communications online, nowadays Tor is the most famous low-latency network, that guarantees both anonymity and privacy of its users. The aim of this thesis project is to well understand how the Tor protocol works, not only studying its theory, but also implementing those concepts in practice, having a particular attention for security topics. In order to run a Tor private network, that emulates the real one, a virtual testing environment has been configured. This behavior allows to conduct experiments without putting at risk anonymity and privacy of real users. We used a Tor patch, that stores TLS and circuit keys, to be given as inputs to a Tor dissector for Wireshark, in order to obtain decrypted and decoded traffic. Observing clear traffic allowed us to well check the protocol outline and to have a proof of the format of each cell. Besides, these tools allowed to identify a traffic pattern, used to conduct a traffic correlation attack to passively deanonymize hidden service clients. The attacker, controlling two nodes of the Tor network, is able to link a request for a given hidden server to the client who did it, deanonymizing him. The robustness of the traffic pattern and the statistics, such as the true positive rate, and the false positive rate, of the attack are object of a potential future work.

Imagery of a moving object: the role of occipital cortex and human MT/V5+

Visual imagery – similar to visual perception – activates feature-specific and category-specific visual areas. This is frequently observed in experiments where the instruction is to imagine stimuli that have been shown immediately before the imagery task. Hence, feature-specific activation could be related to the short-term memory retrieval of previously presented sensory information. Here, we investigated mental imagery of stimuli that subjects had not seen before, eliminating the effects of short-term memory. We recorded brain activation using fMRI while subjects performed a behaviourally controlled guided imagery task in predefined retinotopic coordinates to optimize sensitivity in early visual areas. Whole brain analyses revealed activation in a parieto-frontal network and lateral–occipital cortex. Region of interest (ROI) based analyses showed activation in left hMT/V5+. Granger causality mapping taking left hMT/V5+ as source revealed an imagery-specific directed influence from the left inferior parietal lobule (IPL). Interestingly, we observed a negative BOLD response in V1–3 during imagery, modulated by the retinotopic location of the imagined motion trace. Our results indicate that rule-based motion imagery can activate higher-order visual areas involved in motion perception, with a role for top-down directed influences originating in IPL. Lower-order visual areas (V1, V2 and V3) were down-regulated during this type of imagery, possibly reflecting inhibition to avoid visual input from interfering with the imagery construction. This suggests that the activation in early visual areas observed in previous studies might be related to short- or long-term memory retrieval of specific sensory experiences.

Neural networks engaged in tactile object manipulation: patterns of expression among healthy individuals

Somatosensory object discrimination has been shown to involve widespread cortical and subcortical structures in both cerebral hemispheres. In this study we aimed to identify the networks involved in tactile object manipulation by principal component analysis (PCA) of individual subjects. We expected to find more than one network.