Processing of spectrally resolved x-ray images of inertial confinement fusion implosion cores recorded with multimonochromatic x-ray imagers

[EN] We discuss the processing of data recorded with multimonochromatic x-ray imagers (MMI) in inertial confinement fusion experiments. The MMI records hundreds of gated, spectrally resolved images that can be used to unravel the spatial structure of the implosion core. In particular, we present a new method to determine the centers in all the array of images, a better reconstruction technique of narrowband implosion core images, two algorithms to determine the shape and size of the implosion core volume based on reconstructed broadband images recorded along three-quasiorthogonal lines of sight, and the removal of artifacts from the space-integrated spectra.

Bayesian Analysis of Linear Inverse Problems with Applications in Economics and Finance

In my PhD thesis I propose a Bayesian nonparametric estimation method for structural econometric models where the functional parameter of interest describes the economic agent's behavior. The structural parameter is characterized as the solution of a functional equation, or by using more technical words, as the solution of an inverse problem that can be either ill-posed or well-posed. From a Bayesian point of view, the parameter of interest is a random function and the solution to the inference problem is the posterior distribution of this parameter. A regular version of the posterior distribution in functional spaces is characterized. However, the infinite dimension of the considered spaces causes a problem of non continuity of the solution and then a problem of inconsistency, from a frequentist point of view, of the posterior distribution (i.e. problem of ill-posedness). The contribution of this essay is to propose new methods to deal with this problem of ill-posedness. The first one consists in adopting a Tikhonov regularization scheme in the construction of the posterior distribution so that I end up with a new object that I call regularized posterior distribution and that I guess it is solution of the inverse problem. The second approach consists in specifying a prior distribution on the parameter of interest of the g-prior type. Then, I detect a class of models for which the prior distribution is able to correct for the ill-posedness also in infinite dimensional problems. I study asymptotic properties of these proposed solutions and I prove that, under some regularity condition satisfied by the true value of the parameter of interest, they are consistent in a "frequentist" sense. Once I have set the general theory, I apply my bayesian nonparametric methodology to different estimation problems. First, I apply this estimator to deconvolution and to hazard rate, density and regression estimation. Then, I consider the estimation of an Instrumental Regression that is useful in micro-econometrics when we have to deal with problems of endogeneity. Finally, I develop an application in finance: I get the bayesian estimator for the equilibrium asset pricing functional by using the Euler equation defined in the Lucas'(1978) tree-type models.

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.

Multiple testing in spatial epidemiology: a Bayesian approach

In this work we aim to propose a new approach for preliminary epidemiological studies on Standardized Mortality Ratios (SMR) collected in many spatial regions. A preliminary study on SMRs aims to formulate hypotheses to be investigated via individual epidemiological studies that avoid bias carried on by aggregated analyses. Starting from collecting disease counts and calculating expected disease counts by means of reference population disease rates, in each area an SMR is derived as the MLE under the Poisson assumption on each observation. Such estimators have high standard errors in small areas, i.e. where the expected count is low either because of the low population underlying the area or the rarity of the disease under study. Disease mapping models and other techniques for screening disease rates among the map aiming to detect anomalies and possible high-risk areas have been proposed in literature according to the classic and the Bayesian paradigm. Our proposal is approaching this issue by a decision-oriented method, which focus on multiple testing control, without however leaving the preliminary study perspective that an analysis on SMR indicators is asked to. We implement the control of the FDR, a quantity largely used to address multiple comparisons problems in the eld of microarray data analysis but which is not usually employed in disease mapping. Controlling the FDR means providing an estimate of the FDR for a set of rejected null hypotheses. The small areas issue arises diculties in applying traditional methods for FDR estimation, that are usually based only on the p-values knowledge (Benjamini and Hochberg, 1995; Storey, 2003). Tests evaluated by a traditional p-value provide weak power in small areas, where the expected number of disease cases is small. Moreover tests cannot be assumed as independent when spatial correlation between SMRs is expected, neither they are identical distributed when population underlying the map is heterogeneous. The Bayesian paradigm oers a way to overcome the inappropriateness of p-values based methods. Another peculiarity of the present work is to propose a hierarchical full Bayesian model for FDR estimation in testing many null hypothesis of absence of risk.We will use concepts of Bayesian models for disease mapping, referring in particular to the Besag York and Mollié model (1991) often used in practice for its exible prior assumption on the risks distribution across regions. The borrowing of strength between prior and likelihood typical of a hierarchical Bayesian model takes the advantage of evaluating a singular test (i.e. a test in a singular area) by means of all observations in the map under study, rather than just by means of the singular observation. This allows to improve the power test in small areas and addressing more appropriately the spatial correlation issue that suggests that relative risks are closer in spatially contiguous regions. The proposed model aims to estimate the FDR by means of the MCMC estimated posterior probabilities b i's of the null hypothesis (absence of risk) for each area. An estimate of the expected FDR conditional on data (\FDR) can be calculated in any set of b i's relative to areas declared at high-risk (where thenull hypothesis is rejected) by averaging the b i's themselves. The\FDR can be used to provide an easy decision rule for selecting high-risk areas, i.e. selecting as many as possible areas such that the\FDR is non-lower than a prexed value; we call them\FDR based decision (or selection) rules. The sensitivity and specicity of such rule depend on the accuracy of the FDR estimate, the over-estimation of FDR causing a loss of power and the under-estimation of FDR producing a loss of specicity. Moreover, our model has the interesting feature of still being able to provide an estimate of relative risk values as in the Besag York and Mollié model (1991). A simulation study to evaluate the model performance in FDR estimation accuracy, sensitivity and specificity of the decision rule, and goodness of estimation of relative risks, was set up. We chose a real map from which we generated several spatial scenarios whose counts of disease vary according to the spatial correlation degree, the size areas, the number of areas where the null hypothesis is true and the risk level in the latter areas. In summarizing simulation results we will always consider the FDR estimation in sets constituted by all b i's selected lower than a threshold t. We will show graphs of the\FDR and the true FDR (known by simulation) plotted against a threshold t to assess the FDR estimation. Varying the threshold we can learn which FDR values can be accurately estimated by the practitioner willing to apply the model (by the closeness between\FDR and true FDR). By plotting the calculated sensitivity and specicity (both known by simulation) vs the\FDR we can check the sensitivity and specicity of the corresponding\FDR based decision rules. For investigating the over-smoothing level of relative risk estimates we will compare box-plots of such estimates in high-risk areas (known by simulation), obtained by both our model and the classic Besag York Mollié model. All the summary tools are worked out for all simulated scenarios (in total 54 scenarios). Results show that FDR is well estimated (in the worst case we get an overestimation, hence a conservative FDR control) in small areas, low risk levels and spatially correlated risks scenarios, that are our primary aims. In such scenarios we have good estimates of the FDR for all values less or equal than 0.10. The sensitivity of\FDR based decision rules is generally low but specicity is high. In such scenario the use of\FDR = 0:05 or\FDR = 0:10 based selection rule can be suggested. In cases where the number of true alternative hypotheses (number of true high-risk areas) is small, also FDR = 0:15 values are well estimated, and \FDR = 0:15 based decision rules gains power maintaining an high specicity. On the other hand, in non-small areas and non-small risk level scenarios the FDR is under-estimated unless for very small values of it (much lower than 0.05); this resulting in a loss of specicity of a\FDR = 0:05 based decision rule. In such scenario\FDR = 0:05 or, even worse,\FDR = 0:1 based decision rules cannot be suggested because the true FDR is actually much higher. As regards the relative risk estimation, our model achieves almost the same results of the classic Besag York Molliè model. For this reason, our model is interesting for its ability to perform both the estimation of relative risk values and the FDR control, except for non-small areas and large risk level scenarios. A case of study is nally presented to show how the method can be used in epidemiology.

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.

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.

Reliability and consistency affect the integration of visual depth cues

Abstract Originalsprache (englisch) Visual perception relies on a two-dimensional projection of the viewed scene on the retinas of both eyes. Thus, visual depth has to be reconstructed from a number of different cues that are subsequently integrated to obtain robust depth percepts. Existing models of sensory integration are mainly based on the reliabilities of individual cues and disregard potential cue interactions. In the current study, an extended Bayesian model is proposed that takes into account both cue reliability and consistency. Four experiments were carried out to test this model's predictions. Observers had to judge visual displays of hemi-cylinders with an elliptical cross section, which were constructed to allow for an orthogonal variation of several competing depth cues. In Experiment 1 and 2, observers estimated the cylinder's depth as defined by shading, texture, and motion gradients. The degree of consistency among these cues was systematically varied. It turned out that the extended Bayesian model provided a better fit to the empirical data compared to the traditional model which disregards covariations among cues. To circumvent the potentially problematic assessment of single-cue reliabilities, Experiment 3 used a multiple-observation task, which allowed for estimating perceptual weights from multiple-cue stimuli. Using the same multiple-observation task, the integration of stereoscopic disparity, shading, and texture gradients was examined in Experiment 4. It turned out that less reliable cues were downweighted in the combined percept. Moreover, a specific influence of cue consistency was revealed. Shading and disparity seemed to be processed interactively while other cue combinations could be well described by additive integration rules. These results suggest that cue combination in visual depth perception is highly flexible and depends on single-cue properties as well as on interrelations among cues. The extension of the traditional cue combination model is defended in terms of the necessity for robust perception in ecologically valid environments and the current findings are discussed in the light of emerging computational theories and neuroscientific approaches.

In vivo consequences of AML1-ETO fusion protein expression for hematopoiesis

The t(8;21) (q22;q22) translocation fusing the ETO (also known as MTG8) gene on human chromosome 8 with the AML1 (also called Runx1 or CBFα) gene on chromosome 21 is one of the most common genetic aberrations found in acute myeloid leukemia (AML). This chromosomal translocation occurs in 12 % of de novo AML cases and in up to 40 % of the AML-M2 subtype of the French-American-British classification. To date, the in vivo function of aberrant AML1-ETO fusion protein expression has been investigated by several groups. However, in these studies, controversial results were reported and some key issues remain unknown. Importantly, the consequences of aberrant AML1-ETO expression for self-renewing hematopoietic stem cells (HSCs), multipotent hematopoietic progenitors (MPPs) and lineage-restricted precursors are not known. rn The aim of this thesis was to develop a novel experimental AML1-ETO in vivo model that (i) overcomes the current lack of insight into the pre-leukemic condition of t(8;21)-associated AML, (ii) clarifies the in vivo consequences of AML1-ETO for HSCs, MPPs, progenitors and more mature blood cells and (iii) generates an improved mouse model suitable for mirroring the human condition. For this purpose, a conditional tet on/off mouse model expressing the AML1-ETO fusion protein from the ROSA26 (R26) locus was generated. rn Aberrant AML1-ETO activation in compound ROSA26/tetOAML1-ETO (R26/AE) mice caused high rates of mortality, an overall disruption of hematopoietic organs and a profound alteration of hematopoiesis. However, since the generalized activity of the R26 locus did not recapitulate the leukemic condition found in human patients, it was important to restrict AML1-ETO expression to blood cell lineages. Therefore, bone marrow cells from non-induced R26/AE mice were adoptively transplanted into sublethal irradiated RAG2-/- recipient mice. First signs of phenotypical differences between AML1-ETO-expressing and control mice were observed after eight to nine months of transgene induction. AML1-ETO-expressing mice showed profound changes in hematopoietic organs accompanied by manifest extramedullary hematopoiesis. In addition, a block in early erythropoiesis, B- and T-cell maturation was observed and granulopoiesis was significantly enhanced. Most interestingly, conditional activation of AML1-ETO in chimeric mice did not increase HSCs, MPPs, common lymphoid precursors (CLPs), common myeloid progenitors (CMPs) and megakaryocyte-erythrocyte progenitors (MEPs) but promoted the selective amplification of granulocyte-macrophage progenitors (GMPs). rn The results of this thesis provide clear experimental evidence how aberrant AML1-ETO modulates the developmental properties of normal hematopoiesis and establishes for the first time that AML1-ETO does not increase HSCs, MPPs and common lineage-restricted progenitor pools but specifically amplifies GMPs. The here presented mouse model not only clarifies the role of aberrant AML1-ETO for shaping hematopoietic development but in addition has strong implications for future therapeutic strategies and will be an excellent pre-clinical tool for developing and testing new approaches to treat and eventually cure AML.rn

Sensor Data Fusion e applicazioni

Un trattato che illustra tutto quello che riguarda il Sensor Data Fusion sin dagli strumenti basilari fino alle applicazioni di specializzate

Flagellin:allergen fusion proteins as novel vaccines for the treatment of severe type I allergies

Over the last decades the prevalence of food allergies has continually increased on a world wide scale. While there are effective treatments available for bee and wasp venom allergic patients, there is currently no established therapy for the treatment of severe food allergies. Aim of the project was to genetically fuse different food allergens with the immune modulating Toll-like receptor 5 (TLR5)-ligand flagellin and to test these constructs for their immune modulatory capacities both in vitro and in vivo. Chicken ovalbumin (Ova) as model antigen, Pru p 3, and Ara h 2 the respective major allergens from peach and peanut were used as allergens. The potential vaccine candidates were characterized by protein biochemical methods (purity, folding, endotoxin contaminations). Moreover, their immune modulating effects on cell culture lines (TLR5-receptor activation) and primary mouse immune cells (myeloid and plasmacytoid dendritic cells) were investigated. Additionally, the prophylactic and therapeutic use of the flagellin Ova fusion protein (rflaA:Ova) were investigated in a mouse model of intestinal allergy. In myeloid dendritic cells (mDC) stimulation with the fusion proteins led to a strong cell activation and cytokine secretion. Here, the fusion proteins proved to be a much stronger stimulus than the equimolar amount of both proteins provided alone or as a mixture. Noteworthy, stimulation with rflaA:Ova induced the secretion of the anti-inflammatory cytokine IL-10 from mDC. In co-culture experiments this IL-10 secretion suppressed the Ova-induced secretion of Th1 and Th2 cytokines from Ova-specific CD4 T cells. Using MyD88-deficient mDC this repression of cytokine secretion was shown to be TLR-dependent. Finally, the potency of the rflaA:Ova construct was investigated in a mouse model of Ova-induced intestinal allergy. In a prophylactic vaccination approach rflaA:Ova was shown to prevent the establishment of the intestinal allergy and all associated symptoms (weight loss, temperature drop, soft faeces). This fusion protein-mediated protection was accompanied by a reduced T cell activation, and reduced Th2 cytokines in intestinal homogenates. These effects were paralleled by a strong induction of Ova-specific IgG2a antibodies in rflaA:Ova-vaccinated sera, while Ova-specific IgE antibody production was significantly reduced. Therapeutic vaccination with rflaA:Ova reduced allergic symptoms and T cell activation but did not influence weight loss and antibody production. In all in vivo experiments vaccination with both proteins either provided alone or as a mixture did not have comparable effects. Future experiments aim at elucidating the mechanism and further optimization of the therapeutic vaccination approach. The results presented in this thesis demonstrate, that fusion proteins containing flagellin have strong immune modulatory capacities both in vitro and in vivo. Therefore, such constructs are promising vaccine candidates for the therapy of type I allergies.