Isospin dependence of the Ar+Ni fusion-evaporation cross section

The fundamental goal of this thesis is the determination of the isospin dependence of the Ar+Ni fusion-evaporation cross section. Three Ar isotope beams, with energies of about 13AMeV, have been accelerated and impinged onto isotopically enriched Ni targets, in order to produce Pd nuclei, with mass number varying from 92 to 104. The measurements have been performed by the high performance 4pi detector INDRA, coupled with the magnetic spectrometer VAMOS. Even if the results are very preliminary, the obtained fusion-evaporation cross sections behaviour gives a hint at the possible isospin dependence of the fusion-evaporation cross sections.

Dynamic stabilization of Rayleigh-Taylor instability of ablation fronts in inertial confinement fusion

One of the most important problems in inertial confinement fusion is how to find a way to mitigate the onset of the Rayleigh-Taylor instability which arises in the ablation front during the compression. In this thesis it is studied in detail the possibility of using for such a purpose the well-known mechanism of dynamic stabilization, already applied to other dynamical systems such as the inverted pendulum. In this context, a periodic acceleration superposed to the background gravity generates a vertical vibration of the ablation front itself. The effects of different driving modulations (Dirac deltas and square waves) are analyzed from a theoretical point of view, with a focus on stabilization of ion beam driven ablation fronts, and a comparison is made, in order to look for optimization.

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.

A novel specific genetic translocation in epithelioid hemangioendotelioma, showing a fusion of the WWTR1 and CAMTA1 genes, supports the monoclonality of multifocal epithelioid hemangioendotelioma.

Like other vascular tumors, epithelioid hemangioendothelioma (EHE) is multifocal in approximately 50% of cases, and it is unclear whether the separate lesions represent multifocal disease or metastases. We hypothesized that the identification of an identical WWTR1-CAMTA1 rearrangement in different EHEs from the same patient supports the monoclonal origin of EHE. To test our hypothesis, we undertook a molecular analysis of two multicentric EHEs of the liver, including separate tumor samples from each patient. Matherial and Methods: We retrieved two cases of EHE with available tissue for molecular analysis. In both cases, fluorescence in situ hybridization (FISH) was performed to identify the presence of the WWTR1-CAMTA1 rearrangement to confirm the histologic diagnosis of EHE, as previously described. The reverse transcription-polymerase chain reaction (RT-PCR) products were analyzed by electrophoresis and the RT-PCR–amplified products were sequenced using the Sanger method. Results: FISH analysis revealed signal abnormalities in both WWTR1 and CAMTA1. Combined results confirmed the presence of the t(1;3)(1p36.23;3q25.1) translocation in both cases of EHE. Using RT-PCR analysis, we found that the size of the rearranged bands was identical in the different tumors from each patient. The sequence of the fusion gene confirmed a different WWTR1-CAMTA1 rearrangement in each patient, but an identical WWTR1-CAMTA1 rearrangement in the different lesions from each patient. Discussion: Because of its generally indolent clinical course, EHE is commonly classified as a multifocal, rather than metastatic, disease. In this study, we examined two cases of multifocal liver EHE and found an identical WWTR1-CAMTA1 rearrangement in each lesion from the same patient, but not between the two patients. These findings suggest that multifocal EHE arises from metastasis of the same neoplastic clone rather than from the simultaneous formation of multiple neoplastic clones, which supports the monoclonal origin of multifocal EHE.

Bayesian space-time data fusion for real-time forecasting and map uncertainty

Environmental computer models are deterministic models devoted to predict several environmental phenomena such as air pollution or meteorological events. Numerical model output is given in terms of averages over grid cells, usually at high spatial and temporal resolution. However, these outputs are often biased with unknown calibration and not equipped with any information about the associated uncertainty. Conversely, data collected at monitoring stations is more accurate since they essentially provide the true levels. Due the leading role played by numerical models, it now important to compare model output with observations. Statistical methods developed to combine numerical model output and station data are usually referred to as data fusion. In this work, we first combine ozone monitoring data with ozone predictions from the Eta-CMAQ air quality model in order to forecast real-time current 8-hour average ozone level defined as the average of the previous four hours, current hour, and predictions for the next three hours. We propose a Bayesian downscaler model based on first differences with a flexible coefficient structure and an efficient computational strategy to fit model parameters. Model validation for the eastern United States shows consequential improvement of our fully inferential approach compared with the current real-time forecasting system. Furthermore, we consider the introduction of temperature data from a weather forecast model into the downscaler, showing improved real-time ozone predictions. Finally, we introduce a hierarchical model to obtain spatially varying uncertainty associated with numerical model output. We show how we can learn about such uncertainty through suitable stochastic data fusion modeling using some external validation data. We illustrate our Bayesian model by providing the uncertainty map associated with a temperature output over the northeastern United States.