Modeling the cosmological co-evolution of supermassive black holes and galaxies

In this Thesis, we investigate the cosmological co-evolution of supermassive black holes (BHs), Active Galactic Nuclei (AGN) and their hosting dark matter (DM) halos and galaxies, within the standard CDM scenario. We analyze both analytic, semi-analytic and hybrid techniques and use the most recent observational data available to constrain the assumptions underlying our models. First, we focus on very simple analytic models where the assembly of BHs is directly related to the merger history of DM haloes. For this purpose, we implement the two original analytic models of Wyithe & Loeb 2002 and Wyithe & Loeb 2003, compare their predictions to the AGN luminosity function and clustering data, and discuss possible modifications to the models that improve the match to the observation. Then we study more sophisticated semi-analytic models in which however the baryonic physics is neglected as well. Finally we improve the hybrid simulation of De Lucia & Blaizot 2007, adding new semi-analytical prescriptions to describe the BH mass accretion rate during each merger event and its conversion into radiation, and compare the derived BH scaling relations, fundamental plane and mass function, and the AGN luminosity function with observations. All our results support the following scenario: • The cosmological co-evolution of BHs, AGN and galaxies can be well described within the CDM model. • At redshifts z & 1, the evolution history of DM halo fully determines the overall properties of the BH and AGN populations. The AGN emission is triggered mainly by DM halo major mergers and, on average, AGN shine at their Eddington luminosity. • At redshifts z . 1, BH growth decouples from halo growth. Galaxy major mergers cannot constitute the only trigger to accretion episodes in this phase. • When a static hot halo has formed around a galaxy, a fraction of the hot gas continuously accretes onto the central BH, causing a low-energy “radio” activity at the galactic centre, which prevents significant gas cooling and thus limiting the mass of the central galaxies and quenching the star formation at late time. • The cold gas fraction accreted by BHs at high redshifts seems to be larger than at low redshifts.

Clustering of variables around latent components: an application in consumer science

The present work proposes a method based on CLV (Clustering around Latent Variables) for identifying groups of consumers in L-shape data. This kind of datastructure is very common in consumer studies where a panel of consumers is asked to assess the global liking of a certain number of products and then, preference scores are arranged in a two-way table Y. External information on both products (physicalchemical description or sensory attributes) and consumers (socio-demographic background, purchase behaviours or consumption habits) may be available in a row descriptor matrix X and in a column descriptor matrix Z respectively. The aim of this method is to automatically provide a consumer segmentation where all the three matrices play an active role in the classification, getting homogeneous groups from all points of view: preference, products and consumer characteristics. The proposed clustering method is illustrated on data from preference studies on food products: juices based on berry fruits and traditional cheeses from Trentino. The hedonic ratings given by the consumer panel on the products under study were explained with respect to the product chemical compounds, sensory evaluation and consumer socio-demographic information, purchase behaviour and consumption habits.

Measure of Global Specialization and Spatial Clustering for the Identification of "Specialized" Agglomeration

The intensity of regional specialization in specific activities, and conversely, the level of industrial concentration in specific locations, has been used as a complementary evidence for the existence and significance of externalities. Additionally, economists have mainly focused the debate on disentangling the sources of specialization and concentration processes according to three vectors: natural advantages, internal, and external scale economies. The arbitrariness of partitions plays a key role in capturing these effects, while the selection of the partition would have to reflect the actual characteristics of the economy. Thus, the identification of spatial boundaries to measure specialization becomes critical, since most likely the model will be adapted to different scales of distance, and be influenced by different types of externalities or economies of agglomeration, which are based on the mechanisms of interaction with particular requirements of spatial proximity. This work is based on the analysis of the spatial aspect of economic specialization supported by the manufacturing industry case. The main objective is to propose, for discrete and continuous space: i) a measure of global specialization; ii) a local disaggregation of the global measure; and iii) a spatial clustering method for the identification of specialized agglomerations.

Neutronics analyses for fast spectrum nuclear systems and scenario studies for advanced nuclear fuel cycles

The present PhD thesis summarizes the three-years study about the neutronic investigation of a new concept nuclear reactor aiming at the optimization and the sustainable management of nuclear fuel in a possible European scenario. A new generation nuclear reactor for the nuclear reinassance is indeed desired by the actual industrialized world, both for the solution of the energetic question arising from the continuously growing energy demand together with the corresponding reduction of oil availability, and the environment question for a sustainable energy source free from Long Lived Radioisotopes and therefore geological repositories. Among the Generation IV candidate typologies, the Lead Fast Reactor concept has been pursued, being the one top rated in sustainability. The European Lead-cooled SYstem (ELSY) has been at first investigated. The neutronic analysis of the ELSY core has been performed via deterministic analysis by means of the ERANOS code, in order to retrieve a stable configuration for the overall design of the reactor. Further analyses have been carried out by means of the Monte Carlo general purpose transport code MCNP, in order to check the former one and to define an exact model of the system. An innovative system of absorbers has been conceptualized and designed for both the reactivity compensation and regulation of the core due to cycle swing, as well as for safety in order to guarantee the cold shutdown of the system in case of accident. Aiming at the sustainability of nuclear energy, the steady-state nuclear equilibrium has been investigated and generalized into the definition of the ``extended'' equilibrium state. According to this, the Adiabatic Reactor Theory has been developed, together with a New Paradigm for Nuclear Power: in order to design a reactor that does not exchange with the environment anything valuable (thus the term ``adiabatic''), in the sense of both Plutonium and Minor Actinides, it is required indeed to revert the logical design scheme of nuclear cores, starting from the definition of the equilibrium composition of the fuel and submitting to the latter the whole core design. The New Paradigm has been applied then to the core design of an Adiabatic Lead Fast Reactor complying with the ELSY overall system layout. A complete core characterization has been done in order to asses criticality and power flattening; a preliminary evaluation of the main safety parameters has been also done to verify the viability of the system. Burn up calculations have been then performed in order to investigate the operating cycle for the Adiabatic Lead Fast Reactor; the fuel performances have been therefore extracted and inserted in a more general analysis for an European scenario. The present nuclear reactors fleet has been modeled and its evolution simulated by means of the COSI code in order to investigate the materials fluxes to be managed in the European region. Different plausible scenarios have been identified to forecast the evolution of the European nuclear energy production, including the one involving the introduction of Adiabatic Lead Fast Reactors, and compared to better analyze the advantages introduced by the adoption of new concept reactors. At last, since both ELSY and the ALFR represent new concept systems based upon innovative solutions, the neutronic design of a demonstrator reactor has been carried out: such a system is intended to prove the viability of technology to be implemented in the First-of-a-Kind industrial power plant, with the aim at attesting the general strategy to use, to the largest extent. It was chosen then to base the DEMO design upon a compromise between demonstration of developed technology and testing of emerging technology in order to significantly subserve the purpose of reducing uncertainties about construction and licensing, both validating ELSY/ALFR main features and performances, and to qualify numerical codes and tools.

Comparing Different Approaches for Clustering Categorical Data

There are different ways to do cluster analysis of categorical data in the literature and the choice among them is strongly related to the aim of the researcher, if we do not take into account time and economical constraints. Main approaches for clustering are usually distinguished into model-based and distance-based methods: the former assume that objects belonging to the same class are similar in the sense that their observed values come from the same probability distribution, whose parameters are unknown and need to be estimated; the latter evaluate distances among objects by a defined dissimilarity measure and, basing on it, allocate units to the closest group. In clustering, one may be interested in the classification of similar objects into groups, and one may be interested in finding observations that come from the same true homogeneous distribution. But do both of these aims lead to the same clustering? And how good are clustering methods designed to fulfil one of these aims in terms of the other? In order to answer, two approaches, namely a latent class model (mixture of multinomial distributions) and a partition around medoids one, are evaluated and compared by Adjusted Rand Index, Average Silhouette Width and Pearson-Gamma indexes in a fairly wide simulation study. Simulation outcomes are plotted in bi-dimensional graphs via Multidimensional Scaling; size of points is proportional to the number of points that overlap and different colours are used according to the cluster membership.

Cambiamenti dello scenario epidemiologico e clinico dell'epatocarcinoma in Italia nell'ultimo ventennio

Background & Aims: This study investigates whether the aetiologic changes in liver disease and the improved management of hepatocellular carcinoma (HCC) have modified the clinical scenario of this tumour over the last 20 years in Italy. Methods: Retrospective study based on the analysis of the ITA.LI.CA (Italian Liver Cancer) database including 3027 HCC patients managed in 11 centres. Patients were divided into 3 groups according to the period of HCC diagnosis: 1987–1996 (year of the ‘‘Milano criteria’’ publication), 1997–2001 (year of release of the EASL guidelines for HCC), and 2002–2008. Results: The significant changes were: (1) progressive patient ageing; (2) increasing prevalence of HCV infection until 2001, with a subsequent decrease, when the alcoholic aetiology increased; (3) liver function improvement, until 2001; (4) increasing ‘‘incidental’’ at the expense of ‘‘symptomatic’’ diagnoses, until 2001; (5) unchanged prevalence of tumours diagnosed during surveillance (around 50%), with an increasing use of the 6- month schedule; (6) favourable HCC ‘‘stage migration’’, until 2001; (7) increasing use of percutaneous ablation; (8) improving survival, until 2001. Conclusions: Over the last 20 years, several aetiologic and clinical features regarding HCC have changed. The survival improvement observed until 2001 was due to an increasing number of tumours diagnosed in early stages and in a background of compensated cirrhosis, and a growing and better use of locoregional treatments. However, the prevalence of early cancers and survival did not increase further in the last years, a result inciting national policies aimed at implementing surveillance programmes for at risk patients.

Cooperation and competition in the air transport market: current scenario, possible evolutions and analytical tools

dall'avvento della liberalizzazione, aeroporti e vettori hanno vissuto cambiamenti. Il maggior miglioramneto nella gestione degli aeroporti è una gestione più commerciale ed efficiente. Le forme di regolazione economica e le caratteristiche della gestione manageriale sono state indagate. Dodici paesi sono stati scelti per indagare la situazione del trasporto aereo mondiale, fra questi sia paesi con un sistema maturo sia paesi emergenti. La distribuzione del traffico è stata analizzata con l'indice HHI per evidenziare aeroporti con concentrazione maggiore di 0,25 (in accordo con la normativa statunitense); il sistema aeroportuale è stato analizzato con l'indice di Gini e con l'indice di dominanza. Infine, la teoria dei giochi si è dimostrata un valido supporto per studiare il mercato del trasporto aereo anche con l'uso di giochi di tipo DP

A clustering method for robust and reliable large scale functional and structural protein sequence annotation

Bioinformatics, in the last few decades, has played a fundamental role to give sense to the huge amount of data produced. Obtained the complete sequence of a genome, the major problem of knowing as much as possible of its coding regions, is crucial. Protein sequence annotation is challenging and, due to the size of the problem, only computational approaches can provide a feasible solution. As it has been recently pointed out by the Critical Assessment of Function Annotations (CAFA), most accurate methods are those based on the transfer-by-homology approach and the most incisive contribution is given by cross-genome comparisons. In the present thesis it is described a non-hierarchical sequence clustering method for protein automatic large-scale annotation, called “The Bologna Annotation Resource Plus” (BAR+). The method is based on an all-against-all alignment of more than 13 millions protein sequences characterized by a very stringent metric. BAR+ can safely transfer functional features (Gene Ontology and Pfam terms) inside clusters by means of a statistical validation, even in the case of multi-domain proteins. Within BAR+ clusters it is also possible to transfer the three dimensional structure (when a template is available). This is possible by the way of cluster-specific HMM profiles that can be used to calculate reliable template-to-target alignments even in the case of distantly related proteins (sequence identity < 30%). Other BAR+ based applications have been developed during my doctorate including the prediction of Magnesium binding sites in human proteins, the ABC transporters superfamily classification and the functional prediction (GO terms) of the CAFA targets. Remarkably, in the CAFA assessment, BAR+ placed among the ten most accurate methods. At present, as a web server for the functional and structural protein sequence annotation, BAR+ is freely available at http://bar.biocomp.unibo.it/bar2.0.

Evolutionary genetics of lactase persistence in Eurasian human populations

Although ability to digest lactose generally declines after weaning in all mammals, in some human populations it persists also in adult individuals, a condition named lactase persistence (LP). Studies on the prevalence of the LP phenotype in worldwide human populations have shown that the frequency of this trait is highly variable in different ethnic groups, appearing to be positively correlated with the importance of milk in the diet. In particular, several single-nucleotide polymorphisms (SNPs) in the proximity of the LCT gene have been proved to be associated with LP. Nevertheless, few studies have till now analyzed genetic variation underlying LP in a wide set of Eurasian populations and, especially, in the Italian one. In the present study, we thus typed 40 SNPs surrounding the LCT gene in more than 1,000 samples from Italian and Arabic peninsulas to investigate patterns of LP-related genetic diversity in two regions which have played a pivotal role in the recent human evolutionary history according to their geographical position and historical/archaeological records. Our results underline a high and complex variability of the explored genomic region in both studied populations. In particular, a clear diversification of Northern Italian groups from the rest of the peninsula, was observed, with the formers being genetically more similar to Northern European populations than to Southern Italians. These observation are consistent with known decreasing pattern of LP from Northern to Southern Italy and suggest the possibility of an independent evolution of LP-associated genotypes in Northern Italy. A similar scenario was observed in the Arabian peninsula, with Dhofari Arabs from Southern Oman and Yemeni clustering together with respect to Arabs from Northern Oman and the subgroup of Omanis of Asian origin which appeared instead to be genetically closer to Europeans than to the rest of Arabic groups.

Modelling, simulation and control of rotary-wing aircraft in multi-agent scenario

The topic of this thesis is the design and the implementation of mathematical models and control system algorithms for rotary-wing unmanned aerial vehicles to be used in cooperative scenarios. The use of rotorcrafts has many attractive advantages, since these vehicles have the capability to take-off and land vertically, to hover and to move backward and laterally. Rotary-wing aircraft missions require precise control characteristics due to their unstable and heavy coupling aspects. As a matter of fact, flight test is the most accurate way to evaluate flying qualities and to test control systems. However, it may be very expensive and/or not feasible in case of early stage design and prototyping. A good compromise is made by a preliminary assessment performed by means of simulations and a reduced flight testing campaign. Consequently, having an analytical framework represents an important stage for simulations and control algorithm design. In this work mathematical models for various helicopter configurations are implemented. Different flight control techniques for helicopters are presented with theoretical background and tested via simulations and experimental flight tests on a small-scale unmanned helicopter. The same platform is used also in a cooperative scenario with a rover. Control strategies, algorithms and their implementation to perform missions are presented for two main scenarios. One of the main contributions of this thesis is to propose a suitable control system made by a classical PID baseline controller augmented with L1 adaptive contribution. In addition a complete analytical framework and the study of the dynamics and the stability of a synch-rotor are provided. At last, the implementation of cooperative control strategies for two main scenarios that include a small-scale unmanned helicopter and a rover.

Advanced statistical models for the segregation, identification and measurement of coexisting sound sources

Long-term monitoring of acoustical environments is gaining popularity thanks to the relevant amount of scientific and engineering insights that it provides. The increasing interest is due to the constant growth of storage capacity and computational power to process large amounts of data. In this perspective, machine learning (ML) provides a broad family of data-driven statistical techniques to deal with large databases. Nowadays, the conventional praxis of sound level meter measurements limits the global description of a sound scene to an energetic point of view. The equivalent continuous level Leq represents the main metric to define an acoustic environment, indeed. Finer analyses involve the use of statistical levels. However, acoustic percentiles are based on temporal assumptions, which are not always reliable. A statistical approach, based on the study of the occurrences of sound pressure levels, would bring a different perspective to the analysis of long-term monitoring. Depicting a sound scene through the most probable sound pressure level, rather than portions of energy, brought more specific information about the activity carried out during the measurements. The statistical mode of the occurrences can capture typical behaviors of specific kinds of sound sources. The present work aims to propose an ML-based method to identify, separate and measure coexisting sound sources in real-world scenarios. It is based on long-term monitoring and is addressed to acousticians focused on the analysis of environmental noise in manifold contexts. The presented method is based on clustering analysis. Two algorithms, Gaussian Mixture Model and K-means clustering, represent the main core of a process to investigate different active spaces monitored through sound level meters. The procedure has been applied in two different contexts: university lecture halls and offices. The proposed method shows robust and reliable results in describing the acoustic scenario and it could represent an important analytical tool for acousticians.

Relationship between phenotype and environment in marine calcifying organisms: exploring growth and shell properties of different mollusks species in past and modern scenario

Coastal ecosystems represent an inestimable source of biodiversity, being among the most productive areas on the planet. Despite the great ecological and economic value of those environments, many threats endanger the species living in this ecosystem, like the rapid warming and the sea acidification, among many other. Benthic calcifying organisms (e.g. mollusks, corals and echinoderms) in particular, are among the most exposed to those hazards. These organisms use calcium carbonate as a structural and protective material through the biomineralization process, biologically controlled by the organism, but nevertheless, strongly influenced by the environmental surroundings. Evaluating how a changing environment can influence the process of biomineralization is critical to understand how those species of great ecological and economic importance will face the ongoing climate change. This thesis investigates the mechanism of biomineralization in different mollusks’ species of the Adriatic Sea, providing detailed descriptions of shells skeletal, biometric and growth parameters. Applying a multidisciplinary and multi-scale research approach, the influence of external environmental factors on the process of shell formation has been investigated. To achieve this purpose analysis were conducted both on current populations and on fossil remain, which allows to investigate ecological responses to past climate transitions. Mollusks’ shells in fact are one of the best tools to understand climate change in the past, present and future, since they record the environmental conditions prevailed during their life, reflected on the geochemical properties, microstructure and growth of the shell. This approach allowed to overcome the time scale limit imposed by field and laboratory survey, and better understand species long term adaptive response to changing environment, a crucial issue to define proper conservation and management strategies. Furthermore, the investigation of fossil record of mollusks assemblages offered the opportunity to evaluate the long-term biotic response to anthropogenic stressors in the north Adriatic Sea.