Local Earthquake Tomography by trans-dimensional Monte Carlo Sampling

In this study a new, fully non-linear, approach to Local Earthquake Tomography is presented. Local Earthquakes Tomography (LET) is a non-linear inversion problem that allows the joint determination of earthquakes parameters and velocity structure from arrival times of waves generated by local sources. Since the early developments of seismic tomography several inversion methods have been developed to solve this problem in a linearized way. In the framework of Monte Carlo sampling, we developed a new code based on the Reversible Jump Markov Chain Monte Carlo sampling method (Rj-McMc). It is a trans-dimensional approach in which the number of unknowns, and thus the model parameterization, is treated as one of the unknowns. I show that our new code allows overcoming major limitations of linearized tomography, opening a new perspective in seismic imaging. Synthetic tests demonstrate that our algorithm is able to produce a robust and reliable tomography without the need to make subjective a-priori assumptions about starting models and parameterization. Moreover it provides a more accurate estimate of uncertainties about the model parameters. Therefore, it is very suitable for investigating the velocity structure in regions that lack of accurate a-priori information. Synthetic tests also reveal that the lack of any regularization constraints allows extracting more information from the observed data and that the velocity structure can be detected also in regions where the density of rays is low and standard linearized codes fails. I also present high-resolution Vp and Vp/Vs models in two widespread investigated regions: the Parkfield segment of the San Andreas Fault (California, USA) and the area around the Alto Tiberina fault (Umbria-Marche, Italy). In both the cases, the models obtained with our code show a substantial improvement in the data fit, if compared with the models obtained from the same data set with the linearized inversion codes.

A bayesian model for mixed responses and skew laten variable to measure HRQoL in children

The aim of the thesi is to formulate a suitable Item Response Theory (IRT) based model to measure HRQoL (as latent variable) using a mixed responses questionnaire and relaxing the hypothesis of normal distributed latent variable. The new model is a combination of two models already presented in literature, that is, a latent trait model for mixed responses and an IRT model for Skew Normal latent variable. It is developed in a Bayesian framework, a Markov chain Monte Carlo procedure is used to generate samples of the posterior distribution of the parameters of interest. The proposed model is test on a questionnaire composed by 5 discrete items and one continuous to measure HRQoL in children, the EQ-5D-Y questionnaire. A large sample of children collected in the schools was used. In comparison with a model for only discrete responses and a model for mixed responses and normal latent variable, the new model has better performances, in term of deviance information criterion (DIC), chain convergences times and precision of the estimates.

Multidimensional item response theory models with general and specific latent traits for ordinal data

The aim of the thesis is to propose a Bayesian estimation through Markov chain Monte Carlo of multidimensional item response theory models for graded responses with complex structures and correlated traits. In particular, this work focuses on the multiunidimensional and the additive underlying latent structures, considering that the first one is widely used and represents a classical approach in multidimensional item response analysis, while the second one is able to reflect the complexity of real interactions between items and respondents. A simulation study is conducted to evaluate the parameter recovery for the proposed models under different conditions (sample size, test and subtest length, number of response categories, and correlation structure). The results show that the parameter recovery is particularly sensitive to the sample size, due to the model complexity and the high number of parameters to be estimated. For a sufficiently large sample size the parameters of the multiunidimensional and additive graded response models are well reproduced. The results are also affected by the trade-off between the number of items constituting the test and the number of item categories. An application of the proposed models on response data collected to investigate Romagna and San Marino residents' perceptions and attitudes towards the tourism industry is also presented.

Constraints on neutrino mass fraction using Redshift Space Distortions

Redshift Space Distortions (RSD) are an apparent anisotropy in the distribution of galaxies due to their peculiar motion. These features are imprinted in the correlation function of galaxies, which describes how these structures distribute around each other. RSD can be represented by a distortions parameter $\beta$, which is strictly related to the growth of cosmic structures. For this reason, measurements of RSD can be exploited to give constraints on the cosmological parameters, such us for example the neutrino mass. Neutrinos are neutral subatomic particles that come with three flavours, the electron, the muon and the tau neutrino. Their mass differences can be measured in the oscillation experiments. Information on the absolute scale of neutrino mass can come from cosmology, since neutrinos leave a characteristic imprint on the large scale structure of the universe. The aim of this thesis is to provide constraints on the accuracy with which neutrino mass can be estimated when expoiting measurements of RSD. In particular we want to describe how the error on the neutrino mass estimate depends on three fundamental parameters of a galaxy redshift survey: the density of the catalogue, the bias of the sample considered and the volume observed. In doing this we make use of the BASICC Simulation from which we extract a series of dark matter halo catalogues, characterized by different value of bias, density and volume. This mock data are analysed via a Markov Chain Monte Carlo procedure, in order to estimate the neutrino mass fraction, using the software package CosmoMC, which has been conveniently modified. In this way we are able to extract a fitting formula describing our measurements, which can be used to forecast the precision reachable in future surveys like Euclid, using this kind of observations.

Statistical learning of random probability measures

The study of random probability measures is a lively research topic that has attracted interest from different fields in recent years. In this thesis, we consider random probability measures in the context of Bayesian nonparametrics, where the law of a random probability measure is used as prior distribution, and in the context of distributional data analysis, where the goal is to perform inference given avsample from the law of a random probability measure. The contributions contained in this thesis can be subdivided according to three different topics: (i) the use of almost surely discrete repulsive random measures (i.e., whose support points are well separated) for Bayesian model-based clustering, (ii) the proposal of new laws for collections of random probability measures for Bayesian density estimation of partially exchangeable data subdivided into different groups, and (iii) the study of principal component analysis and regression models for probability distributions seen as elements of the 2-Wasserstein space. Specifically, for point (i) above we propose an efficient Markov chain Monte Carlo algorithm for posterior inference, which sidesteps the need of split-merge reversible jump moves typically associated with poor performance, we propose a model for clustering high-dimensional data by introducing a novel class of anisotropic determinantal point processes, and study the distributional properties of the repulsive measures, shedding light on important theoretical results which enable more principled prior elicitation and more efficient posterior simulation algorithms. For point (ii) above, we consider several models suitable for clustering homogeneous populations, inducing spatial dependence across groups of data, extracting the characteristic traits common to all the data-groups, and propose a novel vector autoregressive model to study of growth curves of Singaporean kids. Finally, for point (iii), we propose a novel class of projected statistical methods for distributional data analysis for measures on the real line and on the unit-circle.

Monte Carlo Simulations of Novel Scintillator Detectors and Dosimetry Calculations

Monte Carlo (MC) simulation techniques are becoming very common in the Medical Physicists community. MC can be used for modeling Single Photon Emission Computed Tomography (SPECT) and for dosimetry calculations. 188Re, is a promising candidate for radiotherapeutic production and understanding the mechanisms of the radioresponse of tumor cells "in vitro" is of crucial importance as a first step before "in vivo" studies. The dosimetry of 188Re, used to target different lines of cancer cells, has been evaluated by the MC code GEANT4. The simulations estimate the average energy deposition/per event in the biological samples. The development of prototypes for medical imaging, based on LaBr3:Ce scintillation crystals coupled with a position sensitive photomultiplier, have been studied using GEANT4 simulations. Having tested, in the simulation, surface treatments different from the one applied to the crystal used in our experimental measurements, we found out that the Energy Resolution (ER) and the Spatial Resolution (SR) could be improved, in principle, by machining in a different way the lateral surfaces of the crystal. We have then studied a system able to acquire both echographic and scintigraphic images to let the medical operator obtain the complete anatomic and functional information for tumor diagnosis. The scintigraphic part of the detector is simulated by GEANT4 and first attempts to reconstruct tomographic images have been made using as method of reconstruction a back-projection standard algorithm. The proposed camera is based on slant collimators and LaBr3:Ce crystals. Within the Field of View (FOV) of the camera, it possible to distinguish point sources located in air at a distance of about 2 cm from each other. In particular conditions of uptake, tumor depth and dimension, the preliminary results show that the Signal to Noise Ratio (SNR) values obtained are higher than the standard detection limit.

The XENON1T experiment: Monte Carlo background estimation and sensitivity curves study

Despite the scientific achievement of the last decades in the astrophysical and cosmological fields, the majority of the Universe energy content is still unknown. A potential solution to the “missing mass problem” is the existence of dark matter in the form of WIMPs. Due to the very small cross section for WIMP-nuleon interactions, the number of expected events is very limited (about 1 ev/tonne/year), thus requiring detectors with large target mass and low background level. The aim of the XENON1T experiment, the first tonne-scale LXe based detector, is to be sensitive to WIMP-nucleon cross section as low as 10^-47 cm^2. To investigate the possibility of such a detector to reach its goal, Monte Carlo simulations are mandatory to estimate the background. To this aim, the GEANT4 toolkit has been used to implement the detector geometry and to simulate the decays from the various background sources: electromagnetic and nuclear. From the analysis of the simulations, the level of background has been found totally acceptable for the experiment purposes: about 1 background event in a 2 tonne-years exposure. Indeed, using the Maximum Gap method, the XENON1T sensitivity has been evaluated and the minimum for the WIMP-nucleon cross sections has been found at 1.87 x 10^-47 cm^2, at 90% CL, for a WIMP mass of 45 GeV/c^2. The results have been independently cross checked by using the Likelihood Ratio method that confirmed such results with an agreement within less than a factor two. Such a result is completely acceptable considering the intrinsic differences between the two statistical methods. Thus, in the PhD thesis it has been proven that the XENON1T detector will be able to reach the designed sensitivity, thus lowering the limits on the WIMP-nucleon cross section by about 2 orders of magnitude with respect to the current experiments.

A Bayesian changepoint analysis on spatio-temporal point processes

Changepoint analysis is a well established area of statistical research, but in the context of spatio-temporal point processes it is as yet relatively unexplored. Some substantial differences with regard to standard changepoint analysis have to be taken into account: firstly, at every time point the datum is an irregular pattern of points; secondly, in real situations issues of spatial dependence between points and temporal dependence within time segments raise. Our motivating example consists of data concerning the monitoring and recovery of radioactive particles from Sandside beach, North of Scotland; there have been two major changes in the equipment used to detect the particles, representing known potential changepoints in the number of retrieved particles. In addition, offshore particle retrieval campaigns are believed may reduce the particle intensity onshore with an unknown temporal lag; in this latter case, the problem concerns multiple unknown changepoints. We therefore propose a Bayesian approach for detecting multiple changepoints in the intensity function of a spatio-temporal point process, allowing for spatial and temporal dependence within segments. We use Log-Gaussian Cox Processes, a very flexible class of models suitable for environmental applications that can be implemented using integrated nested Laplace approximation (INLA), a computationally efficient alternative to Monte Carlo Markov Chain methods for approximating the posterior distribution of the parameters. Once the posterior curve is obtained, we propose a few methods for detecting significant change points. We present a simulation study, which consists in generating spatio-temporal point pattern series under several scenarios; the performance of the methods is assessed in terms of type I and II errors, detected changepoint locations and accuracy of the segment intensity estimates. We finally apply the above methods to the motivating dataset and find good and sensible results about the presence and quality of changes in the process.

Advanced aspects of radiation protection in the use of particle accelerators in the medical field

In this work, the well-known MC code FLUKA was used to simulate the GE PETrace cyclotron (16.5 MeV) installed at “S. Orsola-Malpighi” University Hospital (Bologna, IT) and routinely used in the production of positron emitting radionuclides. Simulations yielded estimates of various quantities of interest, including: the effective dose distribution around the equipment; the effective number of neutron produced per incident proton and their spectral distribution; the activation of the structure of the cyclotron and the vault walls; the activation of the ambient air, in particular the production of 41Ar, the assessment of the saturation yield of radionuclides used in nuclear medicine. The simulations were validated against experimental measurements in terms of physical and transport parameters to be used at the energy range of interest in the medical field. The validated model was also extensively used in several practical applications uncluding the direct cyclotron production of non-standard radionuclides such as 99mTc, the production of medical radionuclides at TRIUMF (Vancouver, CA) TR13 cyclotron (13 MeV), the complete design of the new PET facility of “Sacro Cuore – Don Calabria” Hospital (Negrar, IT), including the ACSI TR19 (19 MeV) cyclotron, the dose field around the energy selection system (degrader) of a proton therapy cyclotron, the design of plug-doors for a new cyclotron facility, in which a 70 MeV cyclotron will be installed, and the partial decommissioning of a PET facility, including the replacement of a Scanditronix MC17 cyclotron with a new TR19 cyclotron.

Sistemi liquido cristallini complessi: simulazioni al calcolatore e studi ESR

The aim of this PhD thesis was to study at a microscopic level different liquid crystal (LC) systems, in order to determine their physical properties, resorting to two distinct methodologies, one involving computer simulations, and the other spectroscopic techniques, in particular electron spin resonance (ESR) spectroscopy. By means of the computer simulation approach we tried to demonstrate this tool effectiveness for calculating anisotropic static properties of a LC material, as well as for predicting its behaviour and features. This required the development and adoption of suitable molecular models based on a convenient intermolecular potentials reflecting the essential molecular features of the investigated system. In particular, concerning the simulation approach, we have set up models for discotic liquid crystal dimers and we have studied, by means of Monte Carlo simulations, their phase behaviour and self­-assembling properties, with respect to the simple monomer case. Each discotic dimer is described by two oblate Gay­Berne ellipsoids connected by a flexible spacer, modelled by a harmonic "spring" of three different lengths. In particular we investigated the effects of dimerization on the transition temperatures, as well as on the characteristics of molecular aggregation displayed and the relative orientational order. Moving to the experimental results, among the many experimental techniques that are typically employed to evaluate LC system distinctive features, ESR has proved to be a powerful tool in microscopic scale investigation of the properties, structure, order and dynamics of these materials. We have taken advantage of the high sensitivity of the ESR spin probe technique to investigate increasingly complex LC systems ranging from devices constituted by a polymer matrix in which LC molecules are confined in shape of nano- droplets, as well as biaxial liquid crystalline elastomers, and dimers whose monomeric units or lateral groups are constituted by rod-like mesogens (11BCB). Reflection-mode holographic-polymer dispersed liquid crystals (H-PDLCs) are devices in which LCs are confined into nanosized (50­-300 nm) droplets, arranged in layers which alternate with polymer layers, forming a diffraction grating. We have determined the configuration of the LC local director and we have derived a model of the nanodroplet organization inside the layers. Resorting also to additional information on the nanodroplet size and shape distribution provided by SEM images of the H-PDLC cross-section, the observed director configuration has been modeled as a bidimensional distribution of elongated nanodroplets whose long axis is, on the average, parallel to the layers and whose internal director configuration is a uniaxial quasi- monodomain aligned along the nanodroplet long axis. The results suggest that the molecular organization is dictated mainly by the confinement, explaining, at least in part, the need for switching voltages significantly higher and the observed faster turn-off times in H-PDLCs compared to standard PDLC devices. Liquid crystal elastomers consist in cross-linked polymers, in which mesogens represent the monomers constituting the main chain or the laterally attached side groups. They bring together three important aspects: orientational order in amorphous soft materials, responsive molecular shape and quenched topological constraints. In biaxial nematic liquid crystalline elastomers (BLCEs), two orthogonal directions, rather than the one of normal uniaxial nematic, can be controlled, greatly enhancing their potential value for applications as novel actuators. Two versions of a side-chain BLCEs were characterized: side­-on and end­-on. Many tests have been carried out on both types of LCE, the main features detected being the lack of a significant dynamical behaviour, together with a strong permanent alignment along the principal director, and the confirmation of the transition temperatures already determined by DSC measurements. The end­-on sample demonstrates a less hindered rotation of the side group mesogenic units and a greater freedom of alignment to the magnetic field, as already shown by previous NMR studies. Biaxial nematic ESR static spectra were also obtained on the basis of Molecular Dynamics generated biaxial configurations, to be compared to the experimentally determined ones, as a mean to establish a possible relation between biaxiality and the spectral features. This provides a concrete example of the advantages of combining the computer simulation and spectroscopic approaches. Finally, the dimer α,ω-bis(4'-cyanobiphenyl-4-yl)undecane (11BCB), synthesized in the "quest" for the biaxial nematic phase has been analysed. Its importance lies in the dimer significance as building blocks in the development of new materials to be employed in innovative technological applications, such as faster switching displays, resorting to the easier aligning ability of the secondary director in biaxial phases. A preliminary series of tests were performed revealing the population of mesogenic molecules as divided into two groups: one of elongated straightened conformers sharing a common director, and one of bent molecules, which display no order, being equally distributed in the three dimensions. Employing this model, the calculated values show a consistent trend, confirming at the same time the transition temperatures indicated by the DSC measurements, together with rotational diffusion tensor values that follow closely those of the constituting monomer 5CB.

Measurement of top quark pairs production cross-section in the semi-leptonic channel with the ATLAS experiment

This thesis is about three major aspects of the identification of top quarks. First comes the understanding of their production mechanism, their decay channels and how to translate theoretical formulae into programs that can simulate such physical processes using Monte Carlo techniques. In particular, the author has been involved in the introduction of the POWHEG generator in the framework of the ATLAS experiment. POWHEG is now fully used as the benchmark program for the simulation of ttbar pairs production and decay, along with MC@NLO and AcerMC: this will be shown in chapter one. The second chapter illustrates the ATLAS detectors and its sub-units, such as calorimeters and muon chambers. It is very important to evaluate their efficiency in order to fully understand what happens during the passage of radiation through the detector and to use this knowledge in the calculation of final quantities such as the ttbar production cross section. The last part of this thesis concerns the evaluation of this quantity deploying the so-called "golden channel" of ttbar decays, yielding one energetic charged lepton, four particle jets and a relevant quantity of missing transverse energy due to the neutrino. The most important systematic errors arising from the various part of the calculation are studied in detail. Jet energy scale, trigger efficiency, Monte Carlo models, reconstruction algorithms and luminosity measurement are examples of what can contribute to the uncertainty about the cross-section.

Measurement of the atmospheric muon charge ratio with the OPERA detector

The atmospheric muon charge ratio, defined as the number of positive over negative charged muons, is an interesting quantity for the study of high energy hadronic interactions in atmosphere and the nature of the primary cosmic rays. The measurement of the charge ratio in the TeV muon energy range allows to study the hadronic interactions in kinematic regions not yet explored at accelerators. The OPERA experiment is a hybrid electronic detector/emulsion apparatus, located in the underground Gran Sasso Laboratory, at an average depth of 3800 meters water equivalent (m.w.e.). OPERA is the first large magnetized detector that can measure the muon charge ratio at the LNGS depth, with a wide acceptance for cosmic ray muons coming from above. In this thesis, the muon charge ratio is measured using the spectrometers of the OPERA detector in the highest energy region. The charge ratio was computed separately for single and for multiple muon events, in order to select different primary cosmic ray samples in energy and composition. The measurement as a function of the surface muon energy is used to infer parameters characterizing the particle production in atmosphere, that will be used to constrain Monte Carlo predictions. Finally, the experimental results are interpreted in terms of cosmic ray and particle physics models.

Towards a Reconstruction of Thermal Properties of Light Nuclei from Fusion - Evaporation reactions

This thesis work has been developed in the framework of a new experimental campaign, proposed by the NUCL-EX Collaboration (INFN III Group), in order to progress in the understanding of the statistical properties of light nuclei, at excitation energies above particle emission threshold, by measuring exclusive data from fusion-evaporation reactions. The determination of the nuclear level density in the A~20 region, the understanding of the statistical behavior of light nuclei with excitation energies ~3 A.MeV, and the measurement of observables linked to the presence of cluster structures of nuclear excited levels are the main physics goals of this work. On the theory side, the contribution to this project given by this work lies in the development of a dedicated Monte-Carlo Hauser-Feshbach code for the evaporation of the compound nucleus. The experimental part of this thesis has consisted in the participation to the measurement 12C+12C at 95 MeV beam energy, at Laboratori Nazionali di Legnaro - INFN, using the GARFIELD+Ring Counter(RCo) set-up, from the beam-time request to the data taking, data reduction, detector calibrations and data analysis. Different results of the data analysis are presented in this thesis, together with a theoretical study of the system, performed with the new statistical decay code. As a result of this work, constraints on the nuclear level density at high excitation energy for light systems ranging from C up to Mg are given. Moreover, pre-equilibrium effects, tentatively interpreted as alpha-clustering effects, are put in evidence, both in the entrance channel of the reaction and in the dissipative dynamics on the path towards thermalisation.

Computational strategies to include protein flexibility in Ligand Docking and Virtual Screening

The dynamic character of proteins strongly influences biomolecular recognition mechanisms. With the development of the main models of ligand recognition (lock-and-key, induced fit, conformational selection theories), the role of protein plasticity has become increasingly relevant. In particular, major structural changes concerning large deviations of protein backbones, and slight movements such as side chain rotations are now carefully considered in drug discovery and development. It is of great interest to identify multiple protein conformations as preliminary step in a screening campaign. Protein flexibility has been widely investigated, in terms of both local and global motions, in two diverse biological systems. On one side, Replica Exchange Molecular Dynamics has been exploited as enhanced sampling method to collect multiple conformations of Lactate Dehydrogenase A (LDHA), an emerging anticancer target. The aim of this project was the development of an Ensemble-based Virtual Screening protocol, in order to find novel potent inhibitors. On the other side, a preliminary study concerning the local flexibility of Opioid Receptors has been carried out through ALiBERO approach, an iterative method based on Elastic Network-Normal Mode Analysis and Monte Carlo sampling. Comparison of the Virtual Screening performances by using single or multiple conformations confirmed that the inclusion of protein flexibility in screening protocols has a positive effect on the probability to early recognize novel or known active compounds.