3D probability tomography: theoretical developments and applications to high-resolution geophysical prospecting

The theory of the 3D multipole probability tomography method (3D GPT) to image source poles, dipoles, quadrupoles and octopoles, of a geophysical vector or scalar field dataset is developed. A geophysical dataset is assumed to be the response of an aggregation of poles, dipoles, quadrupoles and octopoles. These physical sources are used to reconstruct without a priori assumptions the most probable position and shape of the true geophysical buried sources, by determining the location of their centres and critical points of their boundaries, as corners, wedges and vertices. This theory, then, is adapted to the geoelectrical, gravity and self potential methods. A few synthetic examples using simple geometries and three field examples are discussed in order to demonstrate the notably enhanced resolution power of the new approach. At first, the application to a field example related to a dipole–dipole geoelectrical survey carried out in the archaeological park of Pompei is presented. The survey was finalised to recognize remains of the ancient Roman urban network including roads, squares and buildings, which were buried under the thick pyroclastic cover fallen during the 79 AD Vesuvius eruption. The revealed anomaly structures are ascribed to wellpreserved remnants of some aligned walls of Roman edifices, buried and partially destroyed by the 79 AD Vesuvius pyroclastic fall. Then, a field example related to a gravity survey carried out in the volcanic area of Mount Etna (Sicily, Italy) is presented, aimed at imaging as accurately as possible the differential mass density structure within the first few km of depth inside the volcanic apparatus. An assemblage of vertical prismatic blocks appears to be the most probable gravity model of the Etna apparatus within the first 5 km of depth below sea level. Finally, an experimental SP dataset collected in the Mt. Somma-Vesuvius volcanic district (Naples, Italy) is elaborated in order to define location and shape of the sources of two SP anomalies of opposite sign detected in the northwestern sector of the surveyed area. The modelled sources are interpreted as the polarization state induced by an intense hydrothermal convective flow mechanism within the volcanic apparatus, from the free surface down to about 3 km of depth b.s.l..

Circoli collaterali porto-sistemici all'eco-color-Doppler addominale in pazienti con ipertensione portale cirrotica: correlazione con il gradiente porto-epatico e valore prognostico

Background. Abdominal porto-systemic collaterals (APSC) on Color-Doppler ultrasound are a frequent finding in portal hypertensive cirrhotic patients. In patients with cirrhosis, an HVPG ≥ 16mmHg has been shown to be associated with increased mortality in two studies. Non-invasive indicators of HVPG ≥ 16 mmHg might define a subgroup of high-risk patients, but data on this aspect are lacking. Aims. We aimed to investigate whether HVPG predicts mortality in patients with clinically significant portal hypertension, and if APSC may predict a severe portal hypertensive state (i.e. HVPG≥16mmHg) in patients with cirrhosis and untreated portal hypertension. Methods. We analysed paired HVPG and ultrasonographic data of 86 untreated portal hypertensive cirrhotic patients. On abdominal echo-color-Doppler data on presence, type and number of APSC were prospectively collected. HVPG was measured following published guidelines. Clinical, laboratory and endoscopic data were available in all cases. First decompensation of cirrhosis and liver-disease related mortality on follow-up (mean 28±20 months) were recorded. Results. 73% of patients had compensated cirrhosis, while 27% were decompensated. All patients had an HVPG≥10 mmHg (mean 17.8±5.1 mmHg). 58% of compensated patients and 82% of decompensated patients had an HVPG over 16 mmHg. 25% had no varices, 28% had small varices, and 47% had medium/large varices. HVPG was higher in patients with esophageal varices vs. patients without varices (19.0±4.8 vs. 14.1±4.2mmHg, p<0.0001), and correlated with Child-Pugh score (R=0.494,p=0.019). 36 (42%) patients had APSC were more frequent in decompensated patients (60% vs. 35%, p=0.03) and in patients with esophageal varices (52% vs. 9%,p=0.001). HVPG was higher in patients with APSC compared with those without PSC (19.9± 4.6 vs. 16.2± 4.9mmHg, p=0.001). The prevalence of APSC was higher in patients with HVPG≥16mmHg vs. those with HVPG<16mmHg (57% vs. 13%,p<0.0001). Decompensation was significantly more frequent in patients with HVPG≥16mmHg vs. HVPG<16mmHg (35.1% vs. 11.5%, p=0.02). On multivariate analysis only HVPG and bilirubin were independent predictors of first decompensation. 10 patients died during follow-up. All had an HVPG≥16 mmHg (26% vs. 0% in patients with HVPG <16mmHg,p=0.04). On multivariate analysis only MELD score and HVPG ≥16mmHg were independent predictors of mortality. In compensated patients the detection of APSC predicted an HVPG≥16mmHg with 92% specificity, 54% sensitivity, positive and negative likelihood ratio 7.03 and 0.50, which implies that the demonstration of APSC on ultrasound increased the probability of HVPG≥16mmHg from 58% to 91%. Conclusions. HVPG maintains an independent prognostic value in the subset of patients with cirrhosis and clinically significant portal hypertension. The presence of APSC is a specific indicator of severe portal hypertension in patients with cirrhosis. Detection of APSC on ultrasound allows the non-invasive identification of a subgroup of compensated patients with bad prognosis, avoiding the invasive measurement of HVPG.

A Law and Economics Analysis of Lobbying Regulation Towards an optimal structure through the Cost Indicator Index

This research primarily represents a contribution to the lobbying regulation research arena. It introduces an index which for the first time attempts to measure the direct compliance costs of lobbying regulation. The Cost Indicator Index (CII) offers a brand new platform for qualitative and quantitative assessment of adopted lobbying laws and proposals of those laws, both in the comparative and the sui generis dimension. The CII is not just the only new tool introduced in the last decade, but it is the only tool available for comparative assessments of the costs of lobbying regulations. Beside the qualitative contribution, the research introduces an additional theoretical framework for complementary qualitative analysis of the lobbying laws. The Ninefold theory allows a more structured assessment and classification of lobbying regulations, both by indication of benefits and costs. Lastly, this research introduces the Cost-Benefit Labels (CBL). These labels might improve an ex-ante lobbying regulation impact assessment procedure, primarily in the sui generis perspective. In its final part, the research focuses on four South East European countries (Slovenia, Serbia, Montenegro and Macedonia), and for the first time brings them into the discussion and calculates their CPI and CII scores. The special focus of the application was on Serbia, whose proposal on the Law on Lobbying has been extensively analysed in qualitative and quantitative terms, taking into consideration specific political and economic circumstances of the country. Although the obtained results are of an indicative nature, the CII will probably find its place within the academic and policymaking arena, and will hopefully contribute to a better understanding of lobbying regulations worldwide.

Phenotypic and genotypic characterisation of antimicrobial resistance in Escherichia coli indicator of animal, food and human origin.

This thesis presents AMR phenotypic evaluation and whole genome sequencing analysis of 288 Escherichia coli strains isolated from different sources (livestock, companion animal, wildlife, food and human) in Italy. Our data reflects general resistance trends in Europe, reporting tetracycline, ampicillin, sulfisoxazole and aminoglycosides resistance as the most common phenotypic AMR profile among livestock, pets, wildlife and humans. Identification of human and animal (livestock and companion animal) AMR profiles in niches with a rare (fishery, mollusc) or absent (vegetable, wild animal, wild boar) direct exposure to antimicrobials, suggests widespread environmental pollution with ARGs conferring resistance to these antimicrobials. Phenotypic resistance to highest priority critically important antimicrobials was mainly observed in food-producing animals and related food such as rabbit, poultry, beef and swine. Discrepancies between AMR phenotypic pattern and genetic profile were observed. In particular, phenotypic aminoglycoside, cephalosporin, meropenem, colistin resistance and ESBL profile did not have a genetic explanation in different cases. This data could suggest the diffusion of new genetic variants of ARGs, associated to these antimicrobial classes. Generally, our collection shows a virulence profile typical of extraintestinal pathogenic Escherichia coli (ExPEC) pathotype. Different pandemic and emerging ExPEC lineages were identified, in particular in poultry meat (ST10; ST23; ST69, ST117; ST131). Rabbit was suggested as a source of ST20-ST40 potential hybrid pathogens. Wildlife carried a high average number (10) of VAGs (mostly associated to ExPEC pathotype) and different predominant ExPEC lineages (ST23, ST117, ST648), suggesting its possible involvement in maintenance and diffusion of virulence determinants. In conclusion, our study provides important knowledge related to the phenotypic/genetic AMR and virulence profiles circulating in E. coli in Italy. The role of different niches in AMR dynamics has been discussed. In particular, food-producing animals are worthy of continued investigation as a source of potential zoonotic pathogens, meanwhile wildlife might contribute to VAGs spread.

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.