Structure of the Southern Tyrrhenian subduction system: insights from seismological analysis of anisotropy and attenuation

The Southern Tyrrhenian subduction system shows a complex interaction among asthenospheric flow, subducting slab and overriding plate. To shed light on the deformations and mechanical properties of the slab and surrounding mantle, I investigated seismic anisotropy and attenuation properties through the subduction region. I used both teleseisms and slab earthquakes, analyzing shear-wave splitting on SKS and S phases, respectively. The fast polarization directions φ, and the delay time, δt, were retrieved using the method of Silver and Chan [1991. SKS and S φ reveal a complex anisotropy pattern across the subduction zone. SKS-rays sample primarily the sub-slab region showing rotation of fast directions following the curved shape of the slab and very strong anisotropy. S-rays sample mainly the slab, showing variable φ and a smaller δt. SKS and S splitting reveals a well developed toroidal flow at SW edge of the slab, while at its NE edge the pattern is not very clear. This suggests that the anisotropy is controlled by the slab rollback, responsible for about 100 km slab parallel φ in the sub-slab mantle. The slab is weakly anisotropic, suggesting the asthenosphere as main source of anisotropy. To investigate the physical properties of the slab and surrounding regions, I analyzed the seismic P and S wave attenuation. By inverting high-quality S-waves t* from slab earthquakes, 3D attenuation models down to 300 km were obtained. Attenuation results image the slab as low-attenuation body, but with heterogeneous QS and QP structure showing spot of high attenuation , between 100-200 km depth, which could be due dehydration associated to the slab metamorphism. A low QS anomaly is present in the mantle wedge beneath the Aeolian volcanic arc and could indicate mantle melting and slab dehydration.

Design and implementation of bioinformatics tools for large scale genome annotation

The continuous increase of genome sequencing projects produced a huge amount of data in the last 10 years: currently more than 600 prokaryotic and 80 eukaryotic genomes are fully sequenced and publically available. However the sole sequencing process of a genome is able to determine just raw nucleotide sequences. This is only the first step of the genome annotation process that will deal with the issue of assigning biological information to each sequence. The annotation process is done at each different level of the biological information processing mechanism, from DNA to protein, and cannot be accomplished only by in vitro analysis procedures resulting extremely expensive and time consuming when applied at a this large scale level. Thus, in silico methods need to be used to accomplish the task. The aim of this work was the implementation of predictive computational methods to allow a fast, reliable, and automated annotation of genomes and proteins starting from aminoacidic sequences. The first part of the work was focused on the implementation of a new machine learning based method for the prediction of the subcellular localization of soluble eukaryotic proteins. The method is called BaCelLo, and was developed in 2006. The main peculiarity of the method is to be independent from biases present in the training dataset, which causes the over‐prediction of the most represented examples in all the other available predictors developed so far. This important result was achieved by a modification, made by myself, to the standard Support Vector Machine (SVM) algorithm with the creation of the so called Balanced SVM. BaCelLo is able to predict the most important subcellular localizations in eukaryotic cells and three, kingdom‐specific, predictors were implemented. In two extensive comparisons, carried out in 2006 and 2008, BaCelLo reported to outperform all the currently available state‐of‐the‐art methods for this prediction task. BaCelLo was subsequently used to completely annotate 5 eukaryotic genomes, by integrating it in a pipeline of predictors developed at the Bologna Biocomputing group by Dr. Pier Luigi Martelli and Dr. Piero Fariselli. An online database, called eSLDB, was developed by integrating, for each aminoacidic sequence extracted from the genome, the predicted subcellular localization merged with experimental and similarity‐based annotations. In the second part of the work a new, machine learning based, method was implemented for the prediction of GPI‐anchored proteins. Basically the method is able to efficiently predict from the raw aminoacidic sequence both the presence of the GPI‐anchor (by means of an SVM), and the position in the sequence of the post‐translational modification event, the so called ω‐site (by means of an Hidden Markov Model (HMM)). The method is called GPIPE and reported to greatly enhance the prediction performances of GPI‐anchored proteins over all the previously developed methods. GPIPE was able to predict up to 88% of the experimentally annotated GPI‐anchored proteins by maintaining a rate of false positive prediction as low as 0.1%. GPIPE was used to completely annotate 81 eukaryotic genomes, and more than 15000 putative GPI‐anchored proteins were predicted, 561 of which are found in H. sapiens. In average 1% of a proteome is predicted as GPI‐anchored. A statistical analysis was performed onto the composition of the regions surrounding the ω‐site that allowed the definition of specific aminoacidic abundances in the different considered regions. Furthermore the hypothesis that compositional biases are present among the four major eukaryotic kingdoms, proposed in literature, was tested and rejected. All the developed predictors and databases are freely available at: BaCelLo http://gpcr.biocomp.unibo.it/bacello eSLDB http://gpcr.biocomp.unibo.it/esldb GPIPE http://gpcr.biocomp.unibo.it/gpipe

A new snowfall detection algorithm for high latitude regions based on a combination of active and passive sensors

Precipitation retrieval over high latitudes, particularly snowfall retrieval over ice and snow, using satellite-based passive microwave spectrometers, is currently an unsolved problem. The challenge results from the large variability of microwave emissivity spectra for snow and ice surfaces, which can mimic, to some degree, the spectral characteristics of snowfall. This work focuses on the investigation of a new snowfall detection algorithm specific for high latitude regions, based on a combination of active and passive sensors able to discriminate between snowing and non snowing areas. The space-borne Cloud Profiling Radar (on CloudSat), the Advanced Microwave Sensor units A and B (on NOAA-16) and the infrared spectrometer MODIS (on AQUA) have been co-located for 365 days, from October 1st 2006 to September 30th, 2007. CloudSat products have been used as truth to calibrate and validate all the proposed algorithms. The methodological approach followed can be summarised into two different steps. In a first step, an empirical search for a threshold, aimed at discriminating the case of no snow, was performed, following Kongoli et al. [2003]. This single-channel approach has not produced appropriate results, a more statistically sound approach was attempted. Two different techniques, which allow to compute the probability above and below a Brightness Temperature (BT) threshold, have been used on the available data. The first technique is based upon a Logistic Distribution to represent the probability of Snow given the predictors. The second technique, defined Bayesian Multivariate Binary Predictor (BMBP), is a fully Bayesian technique not requiring any hypothesis on the shape of the probabilistic model (such as for instance the Logistic), which only requires the estimation of the BT thresholds. The results obtained show that both methods proposed are able to discriminate snowing and non snowing condition over the Polar regions with a probability of correct detection larger than 0.5, highlighting the importance of a multispectral approach.

Study of the building and decorative materials and techniques used in Hungarian Roman sites

The aims of this research were: - To identify the characteristics, properties and provenance of the building and decorative material found in three Hungarian Roman sites: Nagyharsány, Nemesvámos-Balácapuszta and Aquincum - To provide a database of information on the different sites - To have an overview of main conservation strategies applied in Hungary. Geological studies, macroscopical and microscopical observations, XRD investigations, physical and chemical analyses allowed us to define the characteristics and properties of the different kinds of collected materials. Building stones sampled from Nagyharsány site showed two different kinds of massive limestone belonging to the areas surrounding the villa. Also Building stones sampled from Nemesvámos-Balácapuszta Roman villa proved to be compatible with limestone belonging to local sources. Mural painting fragments show that all samples are units composed of multilayered structures. Mosaic tesserae can be classified as following: -Pale yellow , blackish and pink tesserae are comparable with local limestone; -White tessera, composed of marble, was probably imported from distant regions of the Empire, as the usual practice of Romans. Mortars present different characteristics according to the age, the site and the functions: -Building mortars are generally lime based, white or pale yellow in colour, present a high percentage of aggregates represented by fine sand; -Supporting mortars from both mosaics and mural paintings are reddish or pinkish in colour, due to the presence of high percentage of brick dust and tiles fragments, and present a higher content of MgO. Although the condition of the sites, there is an insignificant content of soluble salts. Database The whole study has allowed us to provide work sheets for each samples, including all characteristics and properties. Furthermore, all sites included in the frame of the research have been described and illustrated on the base of their floor plans, material and construction methodologies. It can be concluded that: 1. In Nagyharsány Archaeological site, it is possible to define a sequence of different construction phases on the base of the study of building material and mortars. The results are comparable with the chronology of the site provided by the archaeologists 2. The material used for construction was of local origin while the more precious ones, used for decorative elements, were probably imported from long distance 3. Construction techniques in Hungary mainly refer to the usual Roman knowledge and practice (Vitruvius); few differences have been found 4. The database will represent an archive for Archaeologists, Historians and Conservators dealing with Roman period in Hungary.

Detailed study of the seismotectonic setting in the Lucanian Apennines and surrounding areas (Southern Italy)

In this research work I analyzed the instrumental seismicity of Southern Italy in the area including the Lucanian Apennines and Bradano foredeep, making use of the most recent seismological database available so far. I examined the seismicity occurred during the period between 2001 and 2006, considering 514 events with magnitudes M ≥ 2.0. In the first part of the work, P- and S-wave arrival times, recorded by the Italian National Seismic Network (RSNC) operated by the Istituto Nazionale di Geofisica e Vulcanologia (INGV), were re-picked along with those of the SAPTEX temporary array (2001–2004). For some events located in the Upper Val d'Agri, I also used data from the Eni-Agip oil company seismic network. I computed the VP/VS ratio obtaining a value of 1.83 and I carried out an analysis for the one-dimensional (1D) velocity model that approximates the seismic structure of the study area. After this preliminary analysis, making use of the records obtained in the SeSCAL experiment, I incremented the database by handpicking new arrival times. My final dataset consists of 15,666 P- and 9228 S-arrival times associated to 1047 earthquakes with magnitude ML ≥ 1.5. I computed 162 fault-plane solutions and composite focal mechanisms for closely located events. I investigated stress field orientation inverting focal mechanism belonging to the Lucanian Apennine and the Pollino Range, both areas characterized by more concentrated background seismicity. Moreover, I applied the double difference technique (DD) to improve the earthquake locations. Considering these results and different datasets available in the literature, I carried out a detailed analysis of single sub-areas and of a swarm (November 2008) recorded by SeSCAL array. The relocated seismicity appears more concentrated within the upper crust and it is mostly clustered along the Lucanian Apennine chain. In particular, two well-defined clusters were located in the Potentino and in the Abriola-Pietrapertosa sector (central Lucanian region). Their hypocentral depths are slightly deeper than those observed beneath the chain. I suggest that these two seismic features are representative of the transition from the inner portion of the chain with NE-SW extension to the external margin characterized by dextral strike-slip kinematics. In the easternmost part of the study area, below the Bradano foredeep and the Apulia foreland, the seismicity is generally deeper and more scattered and is associated to the Murge uplift and to the small structures present in the area. I also observed a small structure NE-SW oriented in the Abriola-Pietrapertosa area (activated with a swarm in November 2008) that could be considered to act as a barrier to the propagation of a potential rupture of an active NW-SE striking faults system. Focal mechanisms computed in this study are in large part normal and strike-slip solutions and their tensional axes (T-axes) have a generalized NE-SW orientation. Thanks to denser coverage of seismic stations and the detailed analysis, this study is a further contribution to the comprehension of the seismogenesis and state of stress of the Southern Apennines region, giving important contributions to seismotectonic zoning and seismic hazard assessment.

The evolution of massive clumps in star forming regions

In this thesis two related arguments are investigated: - The first stages of the process of massive star formation, investigating the physical conditions and -properties of massive clumps in different evolutionary stages, and their CO depletion; - The influence that high-mass stars have on the nearby material and on the activity of star formation. I characterise the gas and dust temperature, mass and density of a sample of massive clumps, and analyse the variation of these properties from quiescent clumps, without any sign of active star formation, to clumps likely hosting a zero-age main sequence star. I briefly discuss CO depletion and recent observations of several molecular species, tracers of Hot Cores and/or shocked gas, of a subsample of these clumps. The issue of CO depletion is addressed in more detail in a larger sample consisting of the brightest sources in the ATLASGAL survey: using a radiative tranfer code I investigate how the depletion changes from dark clouds to more evolved objects, and compare its evolution to what happens in the low-mass regime. Finally, I derive the physical properties of the molecular gas in the photon-dominated region adjacent to the HII region G353.2+0.9 in the vicinity of Pismis 24, a young, massive cluster, containing some of the most massive and hottest stars known in our Galaxy. I derive the IMF of the cluster and study the star formation activity in its surroundings. Much of the data analysis is done with a Bayesian approach. Therefore, a separate chapter is dedicated to the concepts of Bayesian statistics.

Evolutionary genetics of lactase persistence in Eurasian human populations

Although ability to digest lactose generally declines after weaning in all mammals, in some human populations it persists also in adult individuals, a condition named lactase persistence (LP). Studies on the prevalence of the LP phenotype in worldwide human populations have shown that the frequency of this trait is highly variable in different ethnic groups, appearing to be positively correlated with the importance of milk in the diet. In particular, several single-nucleotide polymorphisms (SNPs) in the proximity of the LCT gene have been proved to be associated with LP. Nevertheless, few studies have till now analyzed genetic variation underlying LP in a wide set of Eurasian populations and, especially, in the Italian one. In the present study, we thus typed 40 SNPs surrounding the LCT gene in more than 1,000 samples from Italian and Arabic peninsulas to investigate patterns of LP-related genetic diversity in two regions which have played a pivotal role in the recent human evolutionary history according to their geographical position and historical/archaeological records. Our results underline a high and complex variability of the explored genomic region in both studied populations. In particular, a clear diversification of Northern Italian groups from the rest of the peninsula, was observed, with the formers being genetically more similar to Northern European populations than to Southern Italians. These observation are consistent with known decreasing pattern of LP from Northern to Southern Italy and suggest the possibility of an independent evolution of LP-associated genotypes in Northern Italy. A similar scenario was observed in the Arabian peninsula, with Dhofari Arabs from Southern Oman and Yemeni clustering together with respect to Arabs from Northern Oman and the subgroup of Omanis of Asian origin which appeared instead to be genetically closer to Europeans than to the rest of Arabic groups.

Analysis of the pig genome for the identification of genomic regions affecting production traits

The aim of this work was to identify markers associated with production traits in the pig genome using different approaches. We focused the attention on Italian Large White pig breed using Genome Wide Association Studies (GWAS) and applying a selective genotyping approach to increase the power of the analyses. Furthermore, we searched the pig genome using Next Generation Sequencing (NSG) Ion Torrent Technology to combine selective genotyping approach and deep sequencing for SNP discovery. Other two studies were carried on with a different approach. Allele frequency changes for SNPs affecting candidate genes and at Genome Wide level were analysed to identify selection signatures driven by selection program during the last 20 years. This approach confirmed that a great number of markers may affect production traits and that they are captured by the classical selection programs. GWAS revealed 123 significant or suggestively significant SNP associated with Back Fat Thickenss and 229 associated with Average Daily Gain. 16 Copy Number Variant Regions resulted more frequent in lean or fat pigs and showed that different copies of those region could have a limited impact on fat. These often appear to be involved in food intake and behavior, beside affecting genes involved in metabolic pathways and their expression. By combining NGS sequencing with selective genotyping approach, new variants where discovered and at least 54 are worth to be analysed in association studies. The study of groups of pigs undergone to stringent selection showed that allele frequency of some loci can drastically change if they are close to traits that are interesting for selection schemes. These approaches could be, in future, integrated in genomic selection plans.