This thesis presents a new approach for the design and fabrication of bond wire magnetics for power converter applications by using standard IC gold bonding wires and micro-machined magnetic cores. It shows a systematic design and characterization study for bond wire transformers with toroidal and race-track cores for both PCB and silicon substrates. Measurement results show that the use of ferrite cores increases the secondary self-inductance up to 315 µH with a Q-factor up to 24.5 at 100 kHz. Measurement results on LTCC core report an enhancement of the secondary self-inductance up to 23 µH with a Q-factor up to 10.5 at 1.4 MHz. A resonant DC-DC converter is designed in 0.32 µm BCD6s technology at STMicroelectronics with a depletion nmosfet and a bond wire micro-transformer for EH applications. Measures report that the circuit begins to oscillate from a TEG voltage of 280 mV while starts to convert from an input down to 330 mV to a rectified output of 0.8 V at an input of 400 mV. Bond wire magnetics is a cost-effective approach that enables a flexible design of inductors and transformers with high inductance and high turns ratio. Additionally, it supports the development of magnetics on top of the IC active circuitry for package and wafer level integrations, thus enabling the design of high density power components. This makes possible the evolution of PwrSiP and PwrSoC with reliable highly efficient magnetics.

This thesis presents a new Artificial Neural Network (ANN) able to predict at once the main parameters representative of the wave-structure interaction processes, i.e. the wave overtopping discharge, the wave transmission coefficient and the wave reflection coefficient. The new ANN has been specifically developed in order to provide managers and scientists with a tool that can be efficiently used for design purposes. The development of this ANN started with the preparation of a new extended and homogeneous database that collects all the available tests reporting at least one of the three parameters, for a total amount of 16’165 data. The variety of structure types and wave attack conditions in the database includes smooth, rock and armour unit slopes, berm breakwaters, vertical walls, low crested structures, oblique wave attacks. Some of the existing ANNs were compared and improved, leading to the selection of a final ANN, whose architecture was optimized through an in-depth sensitivity analysis to the training parameters of the ANN. Each of the selected 15 input parameters represents a physical aspect of the wave-structure interaction process, describing the wave attack (wave steepness and obliquity, breaking and shoaling factors), the structure geometry (submergence, straight or non-straight slope, with or without berm or toe, presence or not of a crown wall), or the structure type (smooth or covered by an armour layer, with permeable or impermeable core). The advanced ANN here proposed provides accurate predictions for all the three parameters, and demonstrates to overcome the limits imposed by the traditional formulae and approach adopted so far by some of the existing ANNs. The possibility to adopt just one model to obtain a handy and accurate evaluation of the overall performance of a coastal or harbor structure represents the most important and exportable result of the work. / Questa tesi presenta una nuova Rete Neurale Artificiale (RNA) per la predizione dei principali parametri rappresentativi del processo di interazione onda-struttura: la portata di tracimazione ondosa e i coefficienti di trasmissione e riflessione ondosa. Il primo passo ha consistito nella raccolta e organizzazione dei dati disponibili in letteratura. Complessivamente, sono stati assemblati 16'165 dati in unico database omogeneo, includendo una vasta tipologia di opere, fra cui: strutture lisce e impermeabili, strutture permeabili in massi naturali o rivestite di unità artificiali in cemento, opere con e senza nucleo impermeabile, muri a parete verticale, strutture dalla geometria articolata da berme e/o protezioni al piede, strutture a cresta bassa, condizioni di attacco ondoso obliquo. L’assetto finale della RNA è stato definito mediante il confronto e il miglioramento di alcune delle reti esistenti, e in seguito a un’approfondita analisi di sensitività ai diversi parametri di calibrazione del modello. Ciascuno dei 15 parametri di ingresso della rete è finalizzato alla rappresentazione di un diverso aspetto dell’unico fenomeno dell’interazione onda-struttura, descrivendo la tipologia di attacco ondoso (ripidità e obliquità delle onde, indici di frangimento e di shoaling), la sezione geometrica (sommergenza, caratteristiche del paramento a mare, quali presenza o assenza di berme e protezioni al piede, presenza o meno di muro di coronamento) e il tipo di struttura (liscia, o rivestita di una mantellata di massi artificiali o naturali, con o senza nucleo impermeabile). La RNA produce stime accurate dei 3 parametri e supera i limiti imposti dalle formule tradizionali presenti in letteratura e dalle RNA esistenti, usualmente ottimizzate per la predizione di uno solo dei parametri. La possibilità di utilizzare un unico modello che fornisca una stima accurata e rapida della risposta idraulica di una struttura di difesa costiera o portuale alla sollecitazione ondosa rappresenta il risultato più importante ed esportabile di tale lavoro.

In this thesis the potential risks associated to the application of biochar in soil as well the stability of biochar were investigated. The study was focused on the potential risks arising from the occurrence of polycyclic aromatic hydrocarbons (PAHs) in biochar. An analytical method was developed for the determination of the 16 USEPA-PAHs in the original biochar and soil containing biochar. The method was successfully validated with a certified reference material for the soil matrix and compared with methods in use in other laboratories during a laboratory exercise within the EU-COST TD1107. The concentration of 16 USEPA-PAHs along with the 15 EU-PAHs, priority hazardous substances in food, was determined in a suite of currently available biochars for agricultural field applications derived from a variety of parent materials and pyrolysis conditions. Biochars analyzed contained the USEPA and some of the EU-PAHs at detectable levels ranging from 1.2 to 19 µg g-1. This method allowed investigating changes in PAH content and distribution in a four years study following biochar addition in soils in a vineyard (CNR-IBIMET). The results showed that biochar addition determined an increase of the amount of PAHs. However, the levels of PAHs in the soil remained within the maximum acceptable concentration for European countries. The vineyard soil performed by CNR-IBIMET was exploited to study the environmental stability of biochar and its impact on soil organic carbon. The stability of biochar was investigated by analytical pyrolysis (Py-GC-MS) and pyrolysis in the presence of hydrogen (HyPy). The findings showed that biochar amendment significantly influence soil stable carbon fraction concentration during the incubation period. Moreover, HyPy and Py-GC-MS were applied to biochars deriving from three different feedstock at two different pyrolysis temperatures. The results evidenced the influence of feedstock type and pyrolysis conditions on the degree of carbonisation.

This thesis describes the research focused on the study of different electrode supports modified with layered double hydroxides (LDHs) on Co or Ni as M(II) and Al or Fe as M(III) or conducting polymers for energy applications. The LDHs were characterized by electrochemical techniques, FE-SEM, XRD, XPS and XAS. Glassy carbon and Pt electrodes modified with electrosynthesized LDHs were employed in order to investigate their performances as oxygen evolution reaction catalysts and as pseudocapacitor materials. Moreover, the electrochemical synthesis of poly(3,4-ethylenedioxythiophene) (PEDOT) on indium tin oxide (ITO) was carried out in order to exploit an alternative route to fabricate bulk heterojunction solar cells with similar performances but less expensive than those obtained by casting. The photoactive layer was composed by [6,6]-phenyl-C61 butyric acid methyl ester (PCBM) as electron acceptor, while as donor polymer it was employed either the commonly employed rr-poly(3-hexylthiophene) or a polythiophene copolymer, functionalized with a porphyrin derivative in order to improve the absorption in the UV/Vis region. In the second part of the thesis, the LDHs modified electrodes were employed for sensing, taking into account the electrocatalytic oxidation of sugars. Ni/Al or Ni/Fe LDHs were studied with the aim to investigate again the effect of Fe on the electrocatalysis. LDHs prepared both by chemical and electrochemical syntheses were employed with the aim of studying the effect of the order degree on the LDHs performance since this parameter is crucial to improve the “sensing” properties. Furthermore, a sensor for the amperometric detection of sugars in flow systems, based on Co/Al LDH electrosynthesized on Pt electrodes, was developed. A mixture of sugars was submitted to high performance anion chromatography with amperometric detection, using the modified electrode as the working electrode. Moreover, to assess the applicability of the device glucose, fructose, and sucrose content in real samples were successfully determined.

The top quark is the heaviest particle in Standard Model. When it is produced with a large Lorentz boost, its decay products tend to overlap, making the standard reconstruction techniques inefficient; large R jet substructure analysis techniques allow to increase the detection efficiency for these events. Various differential cross section measurements of boosted t-tbar from pp collisions with sqrt(s)=8 TeV are presented: with respect to the mass, to the transverse momentum and the pseudorapidity of the t-tbar system. The results here have been obtained using a sample of 20 fb^-1, recorded by ATLAS during 2012. The events are selected with a cut-based approach in the single lepton plus jets decay channel, where the lepton can be either an electron or a muon. The final background-subtracted distributions are corrected for the distortion introduced by the detector and selection effects using unfolding methods. The measurements are dominated by the systematic uncertainties, and are in agreement with the Standard Model, even if it can be seen a general tendency of the theoretical predictions to overestimate the measured cross section for increasing transverse momentum and mass of the t-tbar system.

Since the discovery of the Higgs boson in 2012, the aim of the correlated physics analyses moved towards the measurement of its properties to verify the consistence with the Standard Model and to study possible signals of physics Beyond Standard Model. In particular, any discrepancy in the Higgs-SM couplings would point to new physics contributions. The ttH channels is a privileged channel for this pourpose, because it depends on a small number of BSM parameters. In this thesis the analysis of the production of a Higgs boson in association with a top and anti-top quark couple and decay into multi-leptonic final states in ATLAS at LHC is described. The analysis is focused on the channel defined by two light leptons of the same sign and no hadronic tau leptons in both Run I and Run II. The analysis is an essential preparatory step for the 2016 data-taking. After introducing the Higgs boson, LHC and the ATLAS experiment, the results of the Run I analysis are presented, which pose a first limit on the deviation of the cross section from the SM. A large part of the thesis is dedicated to the data-driven estimation of the main background of this channel, fake leptons produced in meson decays, using a technique denominated matrix method. This alternative background estimation is explained and applied to the analysis, producing alternative results. In the last part of the thesis, the first stages of the analysis of the 2015 data is shown, in preparation of the 2016 data-taking.

This thesis is the result of a Ph.D. program in Alto Apprendistato carried out at the Dipartimento di Informatica - Scienza e Ingegneria (DISI) of the University of Bologna and at the company devDept Software. With regard to the professional side of my Individual Training Project, I developed technical and scientific skills in 3D geometry of curves and surfaces, CAD, and Finite Element Analysis (FEA). Regarding the academic side, I investigated CAD aspects in the field of Isogeometric Analysis (IGA) on both single and hybrid multipatch physical domains. Simulations are performed in classical FEA systems, which require the conversion of designs, made by CAD systems, into finite element meshes. IGA is a new approach that aims to unify the worlds of CAD and FEA by using the same geometry for analysis as what is used for modeling. That is, the same set of basis functions are adopted both to describe the computational geometry in the CAD tool, and to span the solution space for FEA. The traditional FEA pipeline works on meshes and the most advanced IGA systems work on NURBS or T-spline geometries. Hybrid geometric models (i.e., models in which mesh and NURBS entities coexist), are an emergent way to represent a solid object, but in most CAD systems mesh and NURBS geometries cannot interact with each other, and conversions to a common representation are often needed. In this thesis, we investigate how IGA can be applied on 2D and 3D hybrid models made by both mesh and NURBS entities without requiring laborious and time consuming conversion processes.

As human beings, we trust our five senses, that allow us to experience the world and communicate. Since our birth, the amount of data that every day we can acquire is impressive and such a richness reflects the complexity of humankind in arts, technology, etc. The advent of computers and the consequent progress in Data Science and Artificial Intelligence showed how large amounts of data can contain some sort of “intelligence” themselves. Machines learn and create a superimposed layer of reality. How data generated by humans and machines are related today? To give an answer we will present three projects in the context of “Mixed Reality”, the ideal place where Reality, Virtual Reality and Augmented Reality are increasingly connected as long as data enhance the digital experiences, making them more “real”. We will start with BRAVO, a tool that exploits the brain activity to improve the user’s learning process in real time by means of a Brain-Computer Interface that acquires EEG data. Then we will see AUGMENTED GRAPHICS, a framework for detecting objects in the reality that can be captured easily and inserted in any digital scenario. Based on the moments invariants theory, it looks particularly designed for mobile devices, as it assumes a light concept of object detection and it works without any training set. As third work, GLOVR, a wearable hand controller that uses inertial sensors to offer directional controls and to recognize gestures, particularly suitable for Virtual Reality applications. It features a microphone to record voice sequences that then are translated in tasks by means of a natural language web service. For each project we will summarize the main results and we will trace some future directions of research and development.

Macrocnemus bassanii è un rettile diapside del Triassico medio appartenente al gruppo dei Protorosauria. Le sue principali caratteristiche sono gli arti posteriori molto più lunghi di quelli anteriori e il collo rigido e allungato. Questo lavoro ha lo scopo di chiarire alcuni aspetti ancora poco noti della sua anatomia, in particolare la struttura della regione nasale, la mobilità del quadrato e l’eventuale presenza di placche sternali e di epifisi. Inoltre si vuole comprendere la funzione del collo allungato, che è il principale enigma di questo gruppo di rettili. La sua particolare struttura è probabilmente correlata al tipo di locomozione di Macrocnemus bassanii. Ricostruire il tipo di locomozione è fondamentale per stabilire qual era il ruolo ecologico di questo rettile. Si esaminano infine i rapporti filogenetici tra Macrocnemus bassanii e gli altri taxa appartenenti al gruppo dei protorosauria. / Macrocnemus bassanii is a Middle Trias diapsid reptile that belongs to the group of the Protorosauria. Its main features are the elongated stiff neck and the hindlimbs which are much longer than the forelimbs. The aim of this study is to clarify some aspects of its anatomy that are still controversial, like the structure of the nasal region, the mobility of the quadrate, and the existence of sternal plates and epiphysis. Furthermore it is very important to understand the function of the neck. The neck is the major conundrum of this group of reptiles. Its particular structure is probably correlated to the kind of locomotion of Macrocnemus bassanii. The reconstruction of the kind of locomotion is fundamental to establish what the ecological role of this reptile was. Finally the phylogenetic relationships between Macrocnemus bassanii and the other taxa of the Protorosauria are studied.

Computer-aided diagnosis (CAD) is the use of a computer software to help physicians having a better interpretation of medical images. CAD systems can be viewed as pattern recognition algorithms that identify suspicious signs on a medical image and complement physicians' judgments, by reducing inter-/intra-observer variability and subjectivity. The proposed CAD systems in this thesis have been designed based on the statistical approach to pattern recognition as the most successfully used technique in practice. The main focus of this thesis has been on designing (new) feature extraction and classification algorithms for ultrasound-based CAD purposes. Ultrasound imaging has a broad range of usage in medical applications because it is a safe device which does not use harmful ionizing radiations, it provides clinicians with real-time images, it is portable and relatively cheap. The thesis was concerned with developing new ultrasound-based systems for the diagnosis of prostate cancer (PCa) and myocardial infarction (MI) where these issues have been addressed in two separate parts. In the first part, 1) a new CAD system was designed for prostate cancer biopsy by focusing on handling uncertainties in labels of the ground truth data, 2) the appropriateness of the independent component analysis (ICA) method for learning features from radiofrequency (RF) signals, backscattered from prostate tissues, was examined and, 3) a new ensemble scheme for learning ICA dictionaries from RF signals, backscattered from a tissue mimicking phantom, was proposed. In the second part, 1) principal component analysis (PCA) was used for the statistical modeling of the temporal deformation patterns of the left ventricle (LV) to detect abnormalities in its regional function, 2) a spatio-temporal representation of LV function based on PCA parameters was proposed to detect MI and, 3) a local-to-global statistical shape model based on PCA was presented to detect MI.