Evaluation of the sustainability level of a dairy and poultry farm: The Response-Inducing Sustainability Evaluation (RISE) method

Within this master thesis, various aspects related to the issue of sustainability in the food sector were addressed, focusing on the greenhouse gas emissions derived from livestock production. The increment in population number and wealth is directly related to the growing demand for meat products, which is, in turn, related to an increase in greenhouse gas emissions. Consumers are becoming more and more aware of these environmental issues and, therefore, sustainability factors are becoming even more relevant also from the environmental point of view. A very useful tool in this field is Response-Inducing Sustainability Evaluation (RISE), a software that allows you to determine the sustainability of a farm under many aspects, like energy consumption, livestock management and soil use. The RISE software processes the information obtained through a questionnaire submitted by the farmer, in which 10 different areas of sustainability in the farm are covered. For each theme, the results are expressed clearly with a score that goes from 0 to 100. The experimentation discussed in this work included two different projects, one regarding a dairy farm and the other regarding a poultry farm. The first one was conducted on a dairy farm in Germany and the results allowed to highlight the weakest areas of the farm on which recommendations were given for ecological improvement. The second project was conducted on a chicken broiler farm in Italy, on an experimental basis since it was the first time that the software was applied to poultry. The results pointed out the aspects that can be improved in the RISE software in order to make it more suitable for future poultry studies.

Forecasts on the dark energy anisotropic stress for the esa euclid survey

The cosmological constant Λ seems to be a not satisfactory explanation of the late-time accelerated expansion of the Universe, for which a number of experimental evidences exist; therefore, it has become necessary in the last years to consider alternative models of dark energy, meant as cause of the accelerated expansion. In the study of dark energy models, it is important to understand which quantities can be determined starting from observational data, without assuming any hypothesis on the cosmological model; such quantities have been determined in Amendola, Kunz et al., 2012. In the same paper it has been further shown that it is possible to estabilish a relation between the model-independent parameters and the anisotropic stress η, which can be also expressed as a combination of the functions appearing in the most general Lagrangian for the scalar-tensor theories, the Horndeski Lagrangian. In the present thesis, the Fisher matrix formalism is used to perform a forecast on the constraints that will be possible to make on the anisotropic stress η in the future, starting from the estimated uncertainties for the galaxy clustering and weak lensing measurements which will be performed by the European Space Agency Euclid mission, to be launched in 2020. Further, constraints coming from supernovae-Ia observations are considered. The forecast is performed for two cases in which (a) η is considered as depending from redshift only and (b) η is constant and equal to one, as in the ΛCDM model.

DTN discovery and routing: from space applications to terrestrial networks.

L'argomento di questa tesi è l'architettura di rete Delay-/Disruption-Tolerant Networking (DTN), progettata per operare nelle reti “challenged”, dove la suite di protocolli TCP/IP risulta inefficace a causa di lunghi ritardi di propagazione del segnale, interruzioni e disturbi di canale, ecc. Esempi di reti “challenged” variano dalle reti interplanetarie alle Mobile Ad-Hoc Networks (MANETs). Le principali implementazioni dell'architettura DTN sono DTN2, implementazione di riferimento, e ION, sviluppata da NASA JPL per applicazioni spaziali. Una grande differenza tra reti spaziali e terrestri è che nello spazio i movimenti dei nodi sono deterministici, mentre non lo sono per i nodi mobili terrestri, i quali generalmente non conoscono la topologia della rete. Questo ha portato allo sviluppo di diversi algoritmi di routing: deterministici per le reti spaziali e opportunistici per quelle terrestri. NASA JPL ha recentemente deciso di estendere l'ambito di applicazione di ION per supportare anche scenari non deterministici. Durante la tesi, svolta presso NASA JPL, mi sono occupato di argomenti diversi, tutti finalizzati a questo obiettivo. Inizialmente ho testato la nuova implementazione dell'algoritmo IP Neighbor Discovery (IPND) di ION, corretti i bug e prodotta la documentazione ufficiale. Quindi ho contribuito ad integrare il Contact Graph Routing (CGR) di ION nel simulatore DTN “ONE” utilizzando la Java Native Interface (JNI) come ponte tra il codice Java di ONE e il codice C di ION. In particolare ho adattato tutte le librerie di ION necessarie per far funzionare CGR all'interno dell'ambiente di ONE. Infine, dopo aver analizzato un dataset di tracce reali di nodi mobili, ho contribuito a progettare e a sviluppare OCGR, estensione opportunistica del CGR, quindi ne ho curato l'integrazione in ONE. I risultati preliminari sembrano confermare la validità di OCGR che, una volta messo a punto, può diventare un valido concorrente ai più rinomati algoritmi opportunistici.

Mathematical models for cellular aggregation: the chemotactic instability and clustering formation

In this thesis we present a mathematical formulation of the interaction between microorganisms such as bacteria or amoebae and chemicals, often produced by the organisms themselves. This interaction is called chemotaxis and leads to cellular aggregation. We derive some models to describe chemotaxis. The first is the pioneristic Keller-Segel parabolic-parabolic model and it is derived by two different frameworks: a macroscopic perspective and a microscopic perspective, in which we start with a stochastic differential equation and we perform a mean-field approximation. This parabolic model may be generalized by the introduction of a degenerate diffusion parameter, which depends on the density itself via a power law. Then we derive a model for chemotaxis based on Cattaneo's law of heat propagation with finite speed, which is a hyperbolic model. The last model proposed here is a hydrodynamic model, which takes into account the inertia of the system by a friction force. In the limit of strong friction, the model reduces to the parabolic model, whereas in the limit of weak friction, we recover a hyperbolic model. Finally, we analyze the instability condition, which is the condition that leads to aggregation, and we describe the different kinds of aggregates we may obtain: the parabolic models lead to clusters or peaks whereas the hyperbolic models lead to the formation of network patterns or filaments. Moreover, we discuss the analogy between bacterial colonies and self gravitating systems by comparing the chemotactic collapse and the gravitational collapse (Jeans instability).

Edge-aware Graph Attention Networks: Joint Reasoning On Text and Knowledge Graphs for Biomedical Question Answering

Much of the real-world dataset, including textual data, can be represented using graph structures. The use of graphs to represent textual data has many advantages, mainly related to maintaining a more significant amount of information, such as the relationships between words and their types. In recent years, many neural network architectures have been proposed to deal with tasks on graphs. Many of them consider only node features, ignoring or not giving the proper relevance to relationships between them. However, in many node classification tasks, they play a fundamental role. This thesis aims to analyze the main GNNs, evaluate their advantages and disadvantages, propose an innovative solution considered as an extension of GAT, and apply them to a case study in the biomedical field. We propose the reference GNNs, implemented with methodologies later analyzed, and then applied to a question answering system in the biomedical field as a replacement for the pre-existing GNN. We attempt to obtain better results by using models that can accept as input both node and edge features. As shown later, our proposed models can beat the original solution and define the state-of-the-art for the task under analysis.