Measurement of R(D∗)\mathcal{R}(D^*) with Three-Prong τ\tau Decays at LHCb

The observable $\mathcal{R} ( D^{(*)} ) = \mathcal{B}\left( B^{0}\to D^{(*)-} \tau^{+} \nu_{\tau} \right) / \mathcal{B}\left( B^{0}\to D^{(*)-} \mu^{+} \nu_{\mu} \right)$ is a probe for Lepton Universality violation, so it is sensitive to New Physics processes. The current combination of the measurements of $\mathcal{R} ( D^{(*)} )$ differs from Standard Model predictions with a $4\sigma$ significance. A measurement of $\mathcal{R} ( D^* )$ using three-prong $\tau$ decays is currently ongoing at LHCb. The statistical precision of this analysis is 6.7%, i.e. the smallest statistical uncertainty for a single measurement of this observable. Therefore this measurement will be important to confirm or disprove the current discrepancy from the theoretical expectations.Comment: Proceeding of the 52nd Rencontres de Moriond EW 2017, La Thuile, Italy, March 18-25, 201

Controlled text generation with adversarial learning

LAUREA MAGISTRALEOggi le reti neurali profonde sono utilizzate in ogni campo dell’Intelligenza Artificiale, avendo dimostrato prestazioni molto elevate su compiti complessi quando è disponibile un’enorme quantità di dati. Tuttavia, mentre esistono molte aree in cui questa tecnologia è considerata completa ed utilizzabile, molti altri settori sono ancora agli inizi e i ricercatori sono attivi per scoprire nuove tecniche che potrebbero dare origine a future applicazioni. È il caso della Generazione Testuale, dove i primi risultati sono stati pubblicati solo di recente. La tesi fornirà un’indagine approfondita sui moderni metodi di Deep Learning utilizzati nell’elaborazione del linguaggio naturale con particolare attenzione alla fase di generazione. Alcune di queste nuove tecnologie d’avanguardia saranno discusse in dettaglio; in particolare le reti generative avversarie (GAN), che si sono dimostrate molto promettenti in altri campi come la generazione di immagini, di farmaci e di suoni e che possono essere utilizzate anche con il testo. In seguito verrà proposta una nuova architettura per la generazione di testo basata su pubblicazioni allo stato dell’arte dello scorso anno. Il modello proposto è un miglioramento concettuale da una generazione di testo non condizionato ad un approccio condizionato. Oggi la maggioranza di lavori che applicano GAN al testo si collocano nella prima categoria. Noi proponiamo di migliorare la procedura di generazione con una guida sul tema e sugli argomenti trattati. L’obiettivo è quello di inserire l’umano all’interno del processo di generazione dandogli la possibilità di forzare la generazione vincolata da semplici frasi o concetti. Questo apre la direzione a nuove forme di generazione del testo con un determinato stile, sentimento o semantica. Per svolgere il lavoro è stato necessario combinare tecniche e competenze di Natural Language Processing e Deep Learning per comprendere e dare un contributo in un settore in continua evoluzione nel quale ogni mese vengono pubblicati lavori innovativi.Nowadays Deep Learning Networks are used in every field of Artificial Intelligence, having proved very high performance on complex tasks when a huge amount of data is available. However, while there are many areas in which this technology is considered complete and applicable, many others are still at their infancy and researchers are very active to discover new techniques that may give rise to new applications in the future. This is the case of Text Generation where the first results have been published only very recently, where few prototypes exist, and in English language only. The thesis will give an in-depth survey on modern Deep Learning methods used in Natural Language Processing with a specific focus on Natural Language Generation. Some of these new cutting-edge technologies will be discussed in detail; in particular generative adversarial networks, which have been proved to be very attractive in other fields such as image generation, drug generation and sound generation and can be applied to text too. Then a new architecture for text generation will be proposed and discussed in its implementation: it leverages on last year state-of-the-art works. The proposed model is a conceptual improvement from an unconditioned text generation, where most of the text generation GANs lies, to a conditioned approach. We propose to enhance the generation procedure with guidance on the topic that the text generation system should write about. The goal is to insert the human inside the generation process giving it the possibility to force the generation constrained by simple sentences or concepts as input. This opens the direction to new forms of text generation with a specific style, sentiment or semantic. It was necessary to combine techniques and skills of Natural Language Processing and Deep Learning to understand and make a contribution in an everchanging sector in which innovative works are published every month

The Box Crab Calappa hepatica as a Nuclear Species for the Opportunistic Foraging Behaviour of the Flowery Flounder, Bothus mancus, in the Indo-Pacific

Some predatory fishes may exhibit opportunistic feeding behaviour by exploiting potential prey that is distracted, displaced, or exposed by the activities of a third party that acts as a ‘nuclear’ species. Other fishes mostly perform the role of ‘nuclear’ species, but benthic invertebrates, such as octopuses, have also been reported. Crabs are rarely observed in this role, with only a few records from the tropical Atlantic Ocean. Here, we report the temporary association between two specimens of the flowery flounder, Bothus mancus (family Bothidae), and a box crab, Calappa hepatica (family Calappidae), from the Philippines, representing the first record of a crab–fish feeding association in the Indo-Pacific region

CP violation in D0→K+K- and D0→π+π- decays and lepton-flavour universality test with the decay B0→D*-τ+ντ

The LHCb experiment has been designed to exploit the potential of heavy-flavour production in highly energetic pp collisions at the Large Hadron Collider, in order to look for indirect signs of physics beyond the Standard Model of particle physics. This thesis presents two distinct measurements performed using LHCb data. The first is that of the ratio of branching fractions R(D*)=B(B→D*-τ+ντ)/B(B→D*-l+νl), with the τ lepton decaying to final states containing three charged pions, performed using a data sample of pp collisions at the centre-of-mass energies of 7 and 8 Tev, corresponding to 3fb-1 of integrated luminosity. The result is R(D*)=0.291±0.019±0.026±0.013, where the first uncertainty is statistical, the second systematic and the third due to the knowledge of the B(B→D*-π+π-π+) branching fraction, as this decay is used in the analysis as a normalisation for the intermediate measurement of B(B→D*-τ+ντ). This corresponds to one of the most precise single measurements of R(D*) and to the first performed with the three-prong decay of the τ lepton to date. The measured value of R(D*) is compatible with previous determinations and with the Standard Model expectation. The second measurement presented in this thesis is that of the difference between the CP asymmetries in D0→K+K- and D0→π+π- decays, performed using a data sample of pp collisions at the centre-of-mass energy of 13 Tev, corresponding to 6fb-1 of integrated luminosity. The value of ΔACP=ACP(K+K-)-ACP(π+π-), measured by reconstructing D0 mesons which originate from D*+→D0π+ decays or from B→D0μνX decays, is ΔACP=(-17.1±3.0±1.0)x10-4, where the first uncertainty is statistical and the second systematic. By combining this result with previous LHCb measurements based on Run-1 data, the value of ΔACP results to be ΔACP=(-15.4±2.9)x10-4, which differs from zero by 5.3 standard deviations. This is the first observation of CP violation in the decay of a charm hadron

CBE Clima Tool: a free and open-source web application for climate analysis tailored to sustainable building design

Buildings that are designed specifically to respond to the local climate can be more comfortable, energy-efficient, and with a lower environmental impact. However, there are many social, cultural, and economic obstacles that might prevent the wide adoption of designing climate-adapted buildings. One of the said obstacles can be removed by enabling practitioners to easily access and analyse local climate data. The CBE Clima Tool (Clima) is a free and open-source web application that offers easy access to publicly available weather files (in EPW format) specifically created for building energy simulation and design. It provides a series of interactive visualization of the variables therein contained and several derived ones. It is aimed at students, educators, and practitioners in the architecture and engineering fields. Since its launch has been consistently recording over 3000 monthly unique users from over 70 countries worldwide, both in professional and educational settings.Comment: Submitted to Software

Intervista a Filippo Focardi. Deportazione e Shoah. Tra memoria e testimonianze

L’intervista a Filippo Focardi si concentra principalmente sugli snodi della costruzione della memoria rispetto a temi centrali della storia della Seconda guerra mondiale, come il sistema concentrazionario nazista e fascista. Sono infatti trattati temi quali la memoria della deportazione e dell’internamento, le relazioni tra Italia e Germania e la ricerca di una memoria europea dopo la fine della Guerra Fredda.The interview with Filippo Focardi focuses mainly on the construction of memory about central issues in the history of the World War II, such as the Nazi and fascist concentration system. Themes such as the memory of deportation and imprisonment, relations between Italy and Germany, and the search for a European memory after the end of the Cold War are discussed

Intervista a Filippo Focardi. Deportazione e Shoah. Tra memoria e testimonianze

L’intervista è stata realizzata a partire dall’incontro omonimo tenutosi a Marzabotto il 27 gennaio 2023, nel quale sono stati discussi i volumi Nel cantiere della memoria. Fascismo, Resistenza, Shoah, Foibe (Roma, Viella 2020) e Le vittime italiane del nazionalsocialismo. Le memorie dei sopravvissuti tra testimonianza e ricerca storica (Roma, Viella 2021), di cui è rispettivamente autore e curatore Filippo Focardi, Professore ordinario all’Università di Padova e Direttore scientifico dell’Istituto Nazionale Ferruccio Parri. L’intervista è stata realizzata da Eloisa Betti e Federico Chiaricati. Si ringrazia per la collaborazione Elisa Guiotto

Energy-Constrained Delivery of Goods with Drones Under Varying Wind Conditions

In this paper, we study the feasibility of sending drones to deliver goods from a depot to a customer by solving what we call the Mission-Feasibility Problem (MFP). Due to payload constraints, the drone can serve only one customer at a time. To this end, we propose a novel framework based on time-dependent cost graphs to properly model the MFP and tackle the delivery dynamics. When the drone moves in the delivery area, the global wind may change thereby affecting the drone's energy consumption, which in turn can increase or decrease. This issue is addressed by designing three algorithms, namely: (i) compute the route of minimum energy once, at the beginning of the mission, (ii) dynamically reconsider the most convenient trip towards the destination, and (iii) dynamically select only the best local choice. We evaluate the performance of our algorithms on both synthetic and real-world data. The changes in the drone's energy consumption are reflected by changes in the cost of the edges of the graphs. The algorithms receive the new costs every time the drone flies over a new vertex, and they have no full knowledge in advance of the weights. We compare them in terms of the percentage of missions that are completed with success (the drone delivers the goods and comes back to the depot), with delivered (the drone delivers the goods but cannot come back to the depot), and with failure (the drone neither delivers the goods nor comes back to the depot).Comment: typo author's nam

Optimal Routing Schedules for Robots Operating in Aisle-Structures

In this paper, we consider the Constant-cost Orienteering Problem (COP) where a robot, constrained by a limited travel budget, aims at selecting a path with the largest reward in an aisle-graph. The aisle-graph consists of a set of loosely connected rows where the robot can change lane only at either end, but not in the middle. Even when considering this special type of graphs, the orienteering problem is known to be NP-hard. We optimally solve in polynomial time two special cases, COP-FR where the robot can only traverse full rows, and COP-SC where the robot can access the rows only from one side. To solve the general COP, we then apply our special case algorithms as well as a new heuristic that suitably combines them. Despite its light computational complexity and being confined into a very limited class of paths, the optimal solutions for COP-FR turn out to be competitive even for COP in both real and synthetic scenarios. Furthermore, our new heuristic for the general case outperforms state-of-art algorithms, especially for input with highly unbalanced rewards

How the Wind Can Be Leveraged for Saving Energy in a Truck-Drone Delivery System

In this work, we investigate the impact of the wind in a drone-based delivery system. For the first time, to the best of our knowledge, we adapt the trajectory of the drone to the wind. We consider a truck-drone tandem delivery system. The drone actively reacts to the wind adopting the “most tailwind” trajectory available between the truck’s path and the delivery. The truck moves on a predefined route and carries the drone close to the delivery point. We propose the Minimum-energy Drone-trajectory Problem (MDP) which aims, when the wind affects the delivery area, at planning minimum-energy trajectories for the drone to serve the customers starting from and returning to the truck. We then propose two algorithms that optimally solve MDP under two different routes of the truck. We also analytically study the feasibility of sending drones with limited battery to deliver packages. Finally, we first numerically compare our algorithms on randomly generated synthetic and real data, and then we evaluate our model simulating the drone’s flight in the BlueSky simulator