An optimal estimator for the correlation of CMB anisotropies with Large Scale Structures and its application to WMAP-7year and NVSS

In the thesis we present the implementation of the quadratic maximum likelihood (QML) method, ideal to estimate the angular power spectrum of the cross-correlation between cosmic microwave background (CMB) and large scale structure (LSS) maps as well as their individual auto-spectra. Such a tool is an optimal method (unbiased and with minimum variance) in pixel space and goes beyond all the previous harmonic analysis present in the literature. We describe the implementation of the QML method in the {\it BolISW} code and demonstrate its accuracy on simulated maps throughout a Monte Carlo. We apply this optimal estimator to WMAP 7-year and NRAO VLA Sky Survey (NVSS) data and explore the robustness of the angular power spectrum estimates obtained by the QML method. Taking into account the shot noise and one of the systematics (declination correction) in NVSS, we can safely use most of the information contained in this survey. On the contrary we neglect the noise in temperature since WMAP is already cosmic variance dominated on the large scales. Because of a discrepancy in the galaxy auto spectrum between the estimates and the theoretical model, we use two different galaxy distributions: the first one with a constant bias $b$ and the second one with a redshift dependent bias $b(z)$. Finally, we make use of the angular power spectrum estimates obtained by the QML method to derive constraints on the dark energy critical density in a flat $\Lambda$CDM model by different likelihood prescriptions. When using just the cross-correlation between WMAP7 and NVSS maps with 1.8° resolution, we show that $\Omega_\Lambda$ is about the 70\% of the total energy density, disfavouring an Einstein-de Sitter Universe at more than 2 $\sigma$ CL (confidence level).

Spectrum Sensing Algorithms for Cognitive Radio Applications

Future wireless communications systems are expected to be extremely dynamic, smart and capable to interact with the surrounding radio environment. To implement such advanced devices, cognitive radio (CR) is a promising paradigm, focusing on strategies for acquiring information and learning. The first task of a cognitive systems is spectrum sensing, that has been mainly studied in the context of opportunistic spectrum access, in which cognitive nodes must implement signal detection techniques to identify unused bands for transmission. In the present work, we study different spectrum sensing algorithms, focusing on their statistical description and evaluation of the detection performance. Moving from traditional sensing approaches we consider the presence of practical impairments, and analyze algorithm design. Far from the ambition of cover the broad spectrum of spectrum sensing, we aim at providing contributions to the main classes of sensing techniques. In particular, in the context of energy detection we studied the practical design of the test, considering the case in which the noise power is estimated at the receiver. This analysis allows to deepen the phenomenon of the SNR wall, providing the conditions for its existence and showing that presence of the SNR wall is determined by the accuracy of the noise power estimation process. In the context of the eigenvalue based detectors, that can be adopted by multiple sensors systems, we studied the practical situation in presence of unbalances in the noise power at the receivers. Then, we shift the focus from single band detectors to wideband sensing, proposing a new approach based on information theoretic criteria. This technique is blind and, requiring no threshold setting, can be adopted even if the statistical distribution of the observed data in not known exactly. In the last part of the thesis we analyze some simple cooperative localization techniques based on weighted centroid strategies.

Ab initio quantum mechanical investigation of structural and chemical-physical properties of selected minerals for minero-petrological, structural ceramic and biomaterial applications

The purpose of this thesis is the atomic-scale simulation of the crystal-chemical and physical (phonon, energetic) properties of some strategically important minerals for structural ceramics, biomedical and petrological applications. These properties affect the thermodynamic stability and rule the mineral-environment interface phenomena, with important economical, (bio)technological, petrological and environmental implications. The minerals of interest belong to the family of phyllosilicates (talc, pyrophyllite and muscovite) and apatite (OHAp), chosen for their importance in industrial and biomedical applications (structural ceramics) and petrophysics. In this thesis work we have applicated quantum mechanics methods, formulas and knowledge to the resolution of mineralogical problems ("Quantum Mineralogy”). The chosen theoretical approach is the Density Functional Theory (DFT), along with periodic boundary conditions to limit the portion of the mineral in analysis to the crystallographic cell and the hybrid functional B3LYP. The crystalline orbitals were simulated by linear combination of Gaussian functions (GTO). The dispersive forces, which are important for the structural determination of phyllosilicates and not properly con-sidered in pure DFT method, have been included by means of a semi-empirical correction. The phonon and the mechanical properties were also calculated. The equation of state, both in athermal conditions and in a wide temperature range, has been obtained by means of variations in the volume of the cell and quasi-harmonic approximation. Some thermo-chemical properties of the minerals (isochoric and isobaric thermal capacity) were calculated, because of their considerable applicative importance. For the first time three-dimensional charts related to these properties at different pressures and temperatures were provided. The hydroxylapatite has been studied from the standpoint of structural and phonon properties for its biotechnological role. In fact, biological apatite represents the inorganic phase of vertebrate hard tissues. Numerous carbonated (hydroxyl)apatite structures were modelled by QM to cover the broadest spectrum of possible biological structural variations to fulfil bioceramics applications.

Stream sediments analysis for geochemical mapping of Romagna Apennines (Northern Italy): monitoring and management tool of environmental resources at various scales

Geochemical mapping is a valuable tool for the control of territory that can be used not only in the identification of mineral resources and geological, agricultural and forestry studies but also in the monitoring of natural resources by giving solutions to environmental and economic problems. Stream sediments are widely used in the sampling campaigns carried out by the world's governments and research groups for their characteristics of broad representativeness of rocks and soils, for ease of sampling and for the possibility to conduct very detailed sampling In this context, the environmental role of stream sediments provides a good basis for the implementation of environmental management measures, in fact the composition of river sediments is an important factor in understanding the complex dynamics that develop within catchment basins therefore they represent a critical environmental compartment: they can persistently incorporate pollutants after a process of contamination and release into the biosphere if the environmental conditions change. It is essential to determine whether the concentrations of certain elements, in particular heavy metals, can be the result of natural erosion of rocks containing high concentrations of specific elements or are generated as residues of human activities related to a certain study area. This PhD thesis aims to extract from an extensive database on stream sediments of the Romagna rivers the widest spectrum of informations. The study involved low and high order stream in the mountain and hilly area, but also the sediments of the floodplain area, where intensive agriculture is active. The geochemical signals recorded by the stream sediments will be interpreted in order to reconstruct the natural variability related to bedrock and soil contribution, the effects of the river dynamics, the anomalous sites, and with the calculation of background values be able to evaluate their level of degradation and predict the environmental risk.

Characterization of the Caspr2 and NLGN2 ligands: a proteomic and biochemical approach

Autism Spectrum Disorder (ASD) is a range of early-onset conditions classified as neurodevelopmental disorders, characterized by deficits in social interactions and communication, as well as by restricted interest and repetitive behaviors. Among the proteins associated with this spectrum of disease there are Caspr2, α-NRXN1, NLGN1-4. Caspr2 is involved in the clustering of K+ channels at the juxtaparanodes, where it is proposed to bind TAG-1. Recent works reported a synaptic localization of Caspr2, but little is know on its role in this compartment. NRXNs and their ligand NLGNs, instead, have a well-defined role in the formation and maintenance of synapses. Among the neuroligins, NLGN2 binds NRXNs with the lowest affinity, suggesting that it could have other not yet characterized ligands. The aim of this work was to better characterize the binding of Caspr2 to TAG-1 and to identify new potential binding partner for Caspr2 and NLGN2. Unexpectedly, using Isothermal Titration Calorimetry and co-immunoprecipitation experiments the direct association of the first two proteins could not be verified and the results indicate that the first evidences reporting it were biased by false-positive artifacts. These findings, together with the uncharacterized synaptic localization of Caspr2, made the identification of new potential binding partners for this protein necessary. To find new proteins that associate with Caspr2 and NLGN2, affinity chromatography in tandem with mass spectrometry experiments were performed. Interestingly, about 25 new potential partners were found for these two proteins and NLGN1, that was originally included as a control: 5 of those, namely SFRP1, CLU, APOE, CNTN1 and TNR, were selected for further investigations. Only the association of CLU to NLGN2 was confirmed. In the future, screenings of the remaining candidates have to be carried out and the functional role for the proposed NLGN2-CLU complex has to be studied.

Molecular genetics of inherited cystic kidney diseases: new diagnostic approaches

Background. Hhereditary cystic kidney diseases are a heterogeneous spectrum of disorders leading to renal failure. Clinical features and family history can help to distinguish the recessive from dominant diseases but the differential diagnosis is difficult due the phenotypic overlap. The molecular diagnosis is often the only way to characterize the different forms. A conventional molecular screening is suitable for small genes but is expensive and time-consuming for large size genes. Next Generation Sequencing (NGS) technologies enables massively parallel sequencing of nucleic acid fragments. Purpose. The first purpose was to validate a diagnostic algorithm useful to drive the genetic screening. The second aim was to validate a NGS protocol of PKHD1 gene. Methods. DNAs from 50 patients were submitted to conventional screening of NPHP1, NPHP5, UMOD, REN and HNF1B genes. 5 patients with known mutations in PKHD1 were submitted to NGS to validate the new method and a not genotyped proband with his parents were analyzed for a diagnostic application. Results. The conventional molecular screening detected 8 mutations: 1) the novel p.E48K of REN in a patient with cystic nephropathy, hyperuricemia, hyperkalemia and anemia; 2) p.R489X of NPHP5 in a patient with Senior Loken Syndrome; 3) pR295C of HNF1B in a patient with renal failure and diabetes.; 4) the NPHP1 deletion in 3 patients with medullar cysts; 5) the HNF1B deletion in a patient with medullar cysts and renal hypoplasia and in a diabetic patient with liver disease. The NGS of PKHD1 detected all known mutations and two additional variants during the validation. The diagnostic NGS analysis identified the patient’s compound heterozygosity with a maternal frameshift mutation and a paternal missense mutation besides a not transmitted paternal missense mutation. Conclusions. The results confirm the validity of our diagnostic algorithm and suggest the possibility to introduce this NGS protocol to clinical practice.