Pattern recognition analysis on heavy ion reaction data

One of the problems in the analysis of nucleus-nucleus collisions is to get information on the value of the impact parameter b. This work consists in the application of pattern recognition techniques aimed at associating values of b to groups of events. To this end, a support vec- tor machine (SVM) classifier is adopted to analyze multifragmentation reactions. This method allows to backtracing the values of b through a particular multidimensional analysis. The SVM classification con- sists of two main phase. In the first one, known as training phase, the classifier learns to discriminate the events that are generated by two different model:Classical Molecular Dynamics (CMD) and Heavy- Ion Phase-Space Exploration (HIPSE) for the reaction: 58Ni +48 Ca at 25 AMeV. To check the classification of events in the second one, known as test phase, what has been learned is tested on new events generated by the same models. These new results have been com- pared to the ones obtained through others techniques of backtracing the impact parameter. Our tests show that, following this approach, the central collisions and peripheral collisions, for the CMD events, are always better classified with respect to the classification by the others techniques of backtracing. We have finally performed the SVM classification on the experimental data measured by NUCL-EX col- laboration with CHIMERA apparatus for the previous reaction.

Valutazione delle performance degli scalpelli da perforazione: studi teorici, analisi dati e valutazioni tecnico-economiche

The study is aimed to calculate an innovative numerical index for bit performance evaluation called Bit Index (BI), applied on a new type of bit database named Formation Drillability Catalogue (FDC). A dedicated research programme (developed by Eni E&P and the University of Bologna) studied a drilling model for bit performance evaluation named BI, derived from data recorded while drilling (bit records, master log, wireline log, etc.) and dull bit evaluation. This index is calculated with data collected inside the FDC, a novel classification of Italian formations aimed to the geotechnical and geomechanical characterization and subdivisions of the formations, called Minimum Interval (MI). FDC was conceived and prepared at Eni E&P Div., and contains a large number of significant drilling parameters. Five wells have been identified inside the FDC and have been tested for bit performance evaluation. The values of BI are calculated for each bit run and are compared with the values of the cost per metre. The case study analyzes bits of the same type, diameters and run in the same formation. The BI methodology implemented on MI classification of FDC can improve consistently the bit performances evaluation, and it helps to identify the best performer bits. Moreover, FDC turned out to be functional to BI, since it discloses and organizes formation details that are not easily detectable or usable from bit records or master logs, allowing for targeted bit performance evaluations. At this stage of development, the BI methodology proved to be economic and reliable. The quality of bit performance analysis obtained with BI seems also more effective than the traditional “quick look” analysis, performed on bit records, or on the pure cost per metre evaluation.

Sviluppo di sistemi per l'analisi della combustione in tempo reale per motori endotermici alternativi

I moderni motori a combustione interna diventano sempre più complessi L'introduzione della normativa antinquinamento EURO VI richiederà una significativa riduzione degli inquinanti allo scarico. La maggiore criticità è rappresentata dalla riduzione degli NOx per i motori Diesel da aggiungersi a quelle già in vigore con le precedenti normative. Tipicamente la messa a punto di una nuova motorizzazione prevede una serie di test specifici al banco prova. Il numero sempre maggiore di parametri di controllo della combustione, sorti come conseguenza della maggior complessità meccanica del motore stesso, causa un aumento esponenziale delle prove da eseguire per caratterizzare l'intero sistema. L'obiettivo di questo progetto di dottorato è quello di realizzare un sistema di analisi della combustione in tempo reale in cui siano implementati diversi algoritmi non ancora presenti nelle centraline moderne. Tutto questo facendo particolare attenzione alla scelta dell'hardware su cui implementare gli algoritmi di analisi. Creando una piattaforma di Rapid Control Prototyping (RCP) che sfrutti la maggior parte dei sensori presenti in vettura di serie; che sia in grado di abbreviare i tempi e i costi della sperimentazione sui motopropulsori, riducendo la necessità di effettuare analisi a posteriori, su dati precedentemente acquisiti, a fronte di una maggior quantità di calcoli effettuati in tempo reale. La soluzione proposta garantisce l'aggiornabilità, la possibilità di mantenere al massimo livello tecnologico la piattaforma di calcolo, allontanandone l'obsolescenza e i costi di sostituzione. Questa proprietà si traduce nella necessità di mantenere la compatibilità tra hardware e software di generazioni differenti, rendendo possibile la sostituzione di quei componenti che limitano le prestazioni senza riprogettare il software.

Non-Markovian stochastic processes and their applications: from anomalous diffusion to time series analysis

This work provides a forward step in the study and comprehension of the relationships between stochastic processes and a certain class of integral-partial differential equation, which can be used in order to model anomalous diffusion and transport in statistical physics. In the first part, we brought the reader through the fundamental notions of probability and stochastic processes, stochastic integration and stochastic differential equations as well. In particular, within the study of H-sssi processes, we focused on fractional Brownian motion (fBm) and its discrete-time increment process, the fractional Gaussian noise (fGn), which provide examples of non-Markovian Gaussian processes. The fGn, together with stationary FARIMA processes, is widely used in the modeling and estimation of long-memory, or long-range dependence (LRD). Time series manifesting long-range dependence, are often observed in nature especially in physics, meteorology, climatology, but also in hydrology, geophysics, economy and many others. We deepely studied LRD, giving many real data examples, providing statistical analysis and introducing parametric methods of estimation. Then, we introduced the theory of fractional integrals and derivatives, which indeed turns out to be very appropriate for studying and modeling systems with long-memory properties. After having introduced the basics concepts, we provided many examples and applications. For instance, we investigated the relaxation equation with distributed order time-fractional derivatives, which describes models characterized by a strong memory component and can be used to model relaxation in complex systems, which deviates from the classical exponential Debye pattern. Then, we focused in the study of generalizations of the standard diffusion equation, by passing through the preliminary study of the fractional forward drift equation. Such generalizations have been obtained by using fractional integrals and derivatives of distributed orders. In order to find a connection between the anomalous diffusion described by these equations and the long-range dependence, we introduced and studied the generalized grey Brownian motion (ggBm), which is actually a parametric class of H-sssi processes, which have indeed marginal probability density function evolving in time according to a partial integro-differential equation of fractional type. The ggBm is of course Non-Markovian. All around the work, we have remarked many times that, starting from a master equation of a probability density function f(x,t), it is always possible to define an equivalence class of stochastic processes with the same marginal density function f(x,t). All these processes provide suitable stochastic models for the starting equation. Studying the ggBm, we just focused on a subclass made up of processes with stationary increments. The ggBm has been defined canonically in the so called grey noise space. However, we have been able to provide a characterization notwithstanding the underline probability space. We also pointed out that that the generalized grey Brownian motion is a direct generalization of a Gaussian process and in particular it generalizes Brownain motion and fractional Brownain motion as well. Finally, we introduced and analyzed a more general class of diffusion type equations related to certain non-Markovian stochastic processes. We started from the forward drift equation, which have been made non-local in time by the introduction of a suitable chosen memory kernel K(t). The resulting non-Markovian equation has been interpreted in a natural way as the evolution equation of the marginal density function of a random time process l(t). We then consider the subordinated process Y(t)=X(l(t)) where X(t) is a Markovian diffusion. The corresponding time-evolution of the marginal density function of Y(t) is governed by a non-Markovian Fokker-Planck equation which involves the same memory kernel K(t). We developed several applications and derived the exact solutions. Moreover, we considered different stochastic models for the given equations, providing path simulations.

Analisi congiunturale e strutturale delle economie regionali: un approccio "fuzzy" alla specializzazione produttiva

Nel 2009 l'Italia attraversa la più grande crisi economica del secondo dopoguerra. Lo studio di ciò che accade, attraverso uno sguardo attento alle principali variabili congiunturali prodotte nel paese, è fondamentale per capire quali sono state le cause che hanno portato a questa situazione e per dare la possibilità  ai policy maker di limitarne gli effetti in futuro. Ma l'Italia non è un territorio dalle caratteristiche monolitiche, è un aggregato di parti molto diverse fra loro. Analizzando il territorio italiano come insieme delle sue parti, osserveremo le medesime condizioni economiche ripetersi in ogni territorio del paese? L'esperienza ci suggerisce di no. La tesi vuole evidenziare come e quanto la struttura caratteristica del tessuto produttivo regionale è responsabile anche della performance economica. La tesi è quindi caratterizzata da due parti. Da un lato si è cercato di analizzare quali siano le differenze nei cicli economici regionali, dall'altro, attraverso l'utilizzo di un sistema di valutazione "fuzzy", si è cercato di ricostruire la natura strutturale delle regioni, al fine di determinare quali siano le specializzazioni che ogni territorio è in grado di mettere in campo. La tesi si conclude con un'analisi comparativa degli indici di dissimilarità  tra cicli regionali e nazionale e i livelli sintetici di specializzazione, si è verificato che esiste una relazione forte che lega le caratteristiche strutturali delle regioni alle distanze tra i loro cicli, dimostrando quindi la tesi che struttura regionale e performance economica siano strettamente interconnesse.

Algorithms for on-line image registration from multiple views

Images of a scene, static or dynamic, are generally acquired at different epochs from different viewpoints. They potentially gather information about the whole scene and its relative motion with respect to the acquisition device. Data from different (in the spatial or temporal domain) visual sources can be fused together to provide a unique consistent representation of the whole scene, even recovering the third dimension, permitting a more complete understanding of the scene content. Moreover, the pose of the acquisition device can be achieved by estimating the relative motion parameters linking different views, thus providing localization information for automatic guidance purposes. Image registration is based on the use of pattern recognition techniques to match among corresponding parts of different views of the acquired scene. Depending on hypotheses or prior information about the sensor model, the motion model and/or the scene model, this information can be used to estimate global or local geometrical mapping functions between different images or different parts of them. These mapping functions contain relative motion parameters between the scene and the sensor(s) and can be used to integrate accordingly informations coming from the different sources to build a wider or even augmented representation of the scene. Accordingly, for their scene reconstruction and pose estimation capabilities, nowadays image registration techniques from multiple views are increasingly stirring up the interest of the scientific and industrial community. Depending on the applicative domain, accuracy, robustness, and computational payload of the algorithms represent important issues to be addressed and generally a trade-off among them has to be reached. Moreover, on-line performance is desirable in order to guarantee the direct interaction of the vision device with human actors or control systems. This thesis follows a general research approach to cope with these issues, almost independently from the scene content, under the constraint of rigid motions. This approach has been motivated by the portability to very different domains as a very desirable property to achieve. A general image registration approach suitable for on-line applications has been devised and assessed through two challenging case studies in different applicative domains. The first case study regards scene reconstruction through on-line mosaicing of optical microscopy cell images acquired with non automated equipment, while moving manually the microscope holder. By registering the images the field of view of the microscope can be widened, preserving the resolution while reconstructing the whole cell culture and permitting the microscopist to interactively explore the cell culture. In the second case study, the registration of terrestrial satellite images acquired by a camera integral with the satellite is utilized to estimate its three-dimensional orientation from visual data, for automatic guidance purposes. Critical aspects of these applications are emphasized and the choices adopted are motivated accordingly. Results are discussed in view of promising future developments.

Role of αvβ3 – Integrin and TLR2 in the innate response to Herpes Simplex Virus infection and Delivery of retargeted oncolytic Herpes Simplex via carrier cells

In the first part of my thesis I studied the mechanism of initiation of the innate response to HSV-1. Innate immune response is the first line of defense set up by the cell to counteract pathogens infection and it is elicited by the activation of a number of membrane or intracellular receptors and sensors, collectively indicated as PRRs, Patter Recognition Receptors. We reported that the HSV pathogen-associated molecular patterns (PAMP) that activate Toll-like receptor 2 (TLR2) and lead to the initiation of innate response are the virion glycoproteins gH/gL and gB, which constitute the conserved fusion core apparatus across the Herpesvirus. Specifically gH/gL is sufficient to initiate a signaling cascade which leads to NF-κB activation. Then, by gain and loss-of-function approaches, we found that αvβ3-integrin is a sensor of and plays a crucial role in the innate defense against HSV-1. We showed that αvβ3-integrin signals through a pathway that concurs with TLR2, affects activation/induction of interferons type 1, NF-κB, and a polarized set of cytokines and receptors. Thus, we demonstrated that gH/gL is sufficient to induce IFN1 and NF-κB via this pathway. From these data, we proposed that αvβ3-integrin is considered a class of non-TLR pattern recognition receptors. In the second part of my thesis I studied the capacity of human mesenchymal stromal cells isolated by fetal membranes (FM-hMSCs) to be used as carrier cells for the delivery of retargeted R-LM249 virus. The use of systemically administrated carrier cells to deliver oncolytic viruses to tumoral targets is a promising strategy in oncolytic virotherapy. We observed that FM-hMSCs can be infected by R-LM249 and we optimized the infection condition; then we demonstrate that stromal cells sustain the replication of retargeted R-LM249 and spread it to target tumoral cells. From these preliminary data FM-hMSCs resulted suitable to be used as carrier cells