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

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 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

Dante Cruicchi, l'artigiano della pace. Mostra fotografica a 100 anni dalla nascita (1921-2021)

Catalogo della mostra fotografica realizzata da Eloisa Betti, Tito Menzani e Federico Chiaricat

Dispatching Point Selection For A Drone-based Delivery System Operating In A Mixed Euclidean–Manhattan Grid

In this paper, we present a drone-based delivery system that assumes to deal with a mixed-area, i.e., two areas, one rural and one urban, placed side-by-side. In the mixed-areas, called EM-grids, the distances are measured with two different metrics, and the shortest path between two destinations concatenates the Euclidean and Manhattan metrics. Due to payload constraints, the drone serves a single customer at a time returning back to the dispatching point (DP) after each delivery to load a new parcel for the next customer. In this paper, we present the 1 -Median Euclidean–Manhattan grid Problem (MEMP) for EM-grids, whose goal is to determine the drone\u27s DP position that minimizes the sum of the distances between all the locations to be served and the point itself. We study the MEMP on two different scenarios, i.e., one in which all the customers in the area need to be served (full-grid) and another one where only a subset of these must be served (partial-grid). For the full-grid scenario we devise optimal and approximation algorithms, while for the partial-grid scenario we devise an optimal algorithm

A Drone-Based Application for Scouting Halyomorpha Halys Bugs in Orchards with Multifunctional Nets

In this work, we consider the problem of using a drone to collect information within orchards in order to scout insect pests, i.e., the stink bug Halyomorpha halys. An orchard can be modeled as an aisle-graph, which is a regular and constrained data structure formed by consecutive aisles where trees are arranged in a straight line. For monitoring the presence of bugs, a drone flies close to the trees and takes videos and/or pictures that will be analyzed offline. As the drone\u27s energy is limited, only a subset of locations in the orchard can be visited with a fully charged battery. Those places that are most likely to be infested should be selected to promptly detect the pest. We implemented the proposed approach on a DJI drone and evaluated its performance in the real-world environment