Sviluppo di un'applicazione bioinformatica per la gestione dei dati di antibiotico sensibilità di isolati clinici

Il problema dell'antibiotico-resistenza è un problema di sanità pubblica per affrontare il quale è necessario un sistema di sorveglianza basato sulla raccolta e l'analisi dei dati epidemiologici di laboratorio. Il progetto di dottorato è consistito nello sviluppo di una applicazione web per la gestione di tali dati di antibiotico sensibilità di isolati clinici utilizzabile a livello di ospedale. Si è creata una piattaforma web associata a un database relazionale per avere un’applicazione dinamica che potesse essere aggiornata facilmente inserendo nuovi dati senza dover manualmente modificare le pagine HTML che compongono l’applicazione stessa. E’ stato utilizzato il database open-source MySQL in quanto presenta numerosi vantaggi: estremamente stabile, elevate prestazioni, supportato da una grande comunità online ed inoltre gratuito. Il contenuto dinamico dell’applicazione web deve essere generato da un linguaggio di programmazione tipo “scripting” che automatizzi operazioni di inserimento, modifica, cancellazione, visualizzazione di larghe quantità di dati. E’ stato scelto il PHP, linguaggio open-source sviluppato appositamente per la realizzazione di pagine web dinamiche, perfettamente utilizzabile con il database MySQL. E’ stata definita l’architettura del database creando le tabelle contenenti i dati e le relazioni tra di esse: le anagrafiche, i dati relativi ai campioni, microrganismi isolati e agli antibiogrammi con le categorie interpretative relative al dato antibiotico. Definite tabelle e relazioni del database è stato scritto il codice associato alle funzioni principali: inserimento manuale di antibiogrammi, importazione di antibiogrammi multipli provenienti da file esportati da strumenti automatizzati, modifica/eliminazione degli antibiogrammi precedenti inseriti nel sistema, analisi dei dati presenti nel database con tendenze e andamenti relativi alla prevalenza di specie microbiche e alla chemioresistenza degli stessi, corredate da grafici. Lo sviluppo ha incluso continui test delle funzioni via via implementate usando reali dati clinici e sono stati introdotti appositi controlli e l’introduzione di una semplice e pulita veste grafica.

Robotic Sensing and Manipulation of Deformable Linear Objects with Learning-based methods

Nowadays robotic applications are widespread and most of the manipulation tasks are efficiently solved. However, Deformable-Objects (DOs) still represent a huge limitation for robots. The main difficulty in DOs manipulation is dealing with the shape and dynamics uncertainties, which prevents the use of model-based approaches (since they are excessively computationally complex) and makes sensory data difficult to interpret. This thesis reports the research activities aimed to address some applications in robotic manipulation and sensing of Deformable-Linear-Objects (DLOs), with particular focus to electric wires. In all the works, a significant effort was made in the study of an effective strategy for analyzing sensory signals with various machine learning algorithms. In the former part of the document, the main focus concerns the wire terminals, i.e. detection, grasping, and insertion. First, a pipeline that integrates vision and tactile sensing is developed, then further improvements are proposed for each module. A novel procedure is proposed to gather and label massive amounts of training images for object detection with minimal human intervention. Together with this strategy, we extend a generic object detector based on Convolutional-Neural-Networks for orientation prediction. The insertion task is also extended by developing a closed-loop control capable to guide the insertion of a longer and curved segment of wire through a hole, where the contact forces are estimated by means of a Recurrent-Neural-Network. In the latter part of the thesis, the interest shifts to the DLO shape. Robotic reshaping of a DLO is addressed by means of a sequence of pick-and-place primitives, while a decision making process driven by visual data learns the optimal grasping locations exploiting Deep Q-learning and finds the best releasing point. The success of the solution leverages on a reliable interpretation of the DLO shape. For this reason, further developments are made on the visual segmentation.

Affordances and Language: How the Level of Object Familiarity modulates the Manipulation and Categorization of Objects across Development

According to much evidence, observing objects activates two types of information: structural properties, i.e., the visual information about the structural features of objects, and function knowledge, i.e., the conceptual information about their skilful use. Many studies so far have focused on the role played by these two kinds of information during object recognition and on their neural underpinnings. However, to the best of our knowledge no study so far has focused on the different activation of this information (structural vs. function) during object manipulation and conceptualization, depending on the age of participants and on the level of object familiarity (familiar vs. non-familiar). Therefore, the main aim of this dissertation was to investigate how actions and concepts related to familiar and non-familiar objects may vary across development. To pursue this aim, four studies were carried out. A first study led to the creation of the Familiar and Non-Familiar Stimuli Database, a set of everyday objects classified by Italian pre-schoolers, schoolers, and adults, useful to verify how object knowledge is modulated by age and frequency of use. A parallel study demonstrated that factors such as sociocultural dynamics may affect the perception of objects. Specifically, data for familiarity, naming, function, using and frequency of use of the objects used to create the Familiar And Non-Familiar Stimuli Database were collected with Dutch and Croatian children and adults. The last two studies on object interaction and language provide further evidence in support of the literature on affordances and on the link between affordances and the cognitive process of language from a developmental point of view, supporting the perspective of a situated cognition and emphasizing the crucial role of human experience.

Price manipulation: theoretical models and empirical investigation

Understanding why market manipulation is conducted, under which conditions it is the most profitable and investigating the magnitude of these practices are crucial questions for financial regulators. Closing price manipulation induced by derivatives’ expiration is the primary subject of this thesis. The first chapter provides a mathematical framework in continuous time to study the incentive to manipulate a set of securities induced by a derivative position. An agent holding a European-type contingent claim, depending on the price of a basket of underlying securities, is considered. The agent can affect the price of the underlying securities by trading on each of them before expiration. The elements of novelty are at least twofold: (1) a multi-asset market is considered; (2) the problem is solved by means of both classic optimisation and stochastic control techniques. Both linear and option payoffs are considered. In the second chapter an empirical investigation is conducted on the existence of expiration day effects on the UK equity market. Intraday data on FTSE 350 stocks over a six-year period from 2015-2020 are used. The results show that the expiration of index derivatives is associated with a rise in both trading activity and volatility, together with significant price distortions. The expiration of single stock options appears to have little to no impact on the underlying securities. The last chapter examines the existence of patterns in line with closing price manipulation of UK stocks on option expiration days. The main contributions are threefold: (1) this is one of the few empirical studies on manipulation induced by the options market; (2) proprietary equity orderbook and transaction data sets are used to define manipulation proxies, providing a more detailed analysis; (3) the behaviour of proprietary trading firms is studied. Despite the industry concerns, no evidence is found of this type of manipulative behaviour.