Using national FADN database to describe Italian farms and arable fields. A comparison of sustainability level between organic versus conventional regimes.

The study defines a new farm classification and identifies the arable land management. These aspects and several indicators are taken into account to estimate the sustainability level of farms, for organic and conventional regimes. The data source is Italian Farm Account Data Network (RICA) for years 2007-2011, which samples structural and economical information. An environmental data has been added to the previous one to better describe the farm context. The new farm classification describes holding by general informations and farm structure. The general information are: adopted regime and farm location in terms of administrative region, slope and phyto-climatic zone. The farm structures describe the presence of main productive processes and land covers, which are recorded by FADN database. The farms, grouped by homogeneous farm structure or farm typology, are evaluated in terms of sustainability. The farm model MAD has been used to estimate a list of indicators. They describe especially environmental and economical areas of sustainability. Finally arable lands are taken into account to identify arable land managements and crop rotations. Each arable land has been classified by crop pattern. Then crop rotation management has been analysed by spatial and temporal approaches. The analysis reports a high variability inside regimes. The farm structure influences indicators level more than regimes, and it is not always possible to compare the two regimes. However some differences between organic and conventional agriculture have been found. Organic farm structures report different frequency and geographical location than conventional ones. Also different connections among arable lands and farm structures have been identified.

Bioimaging of animal embryogenesis: mathematical methods and computational algorithms

Some fundamental biological processes such as embryonic development have been preserved during evolution and are common to species belonging to different phylogenetic positions, but are nowadays largely unknown. The understanding of cell morphodynamics leading to the formation of organized spatial distribution of cells such as tissues and organs can be achieved through the reconstruction of cells shape and position during the development of a live animal embryo. We design in this work a chain of image processing methods to automatically segment and track cells nuclei and membranes during the development of a zebrafish embryo, which has been largely validates as model organism to understand vertebrate development, gene function and healingrepair mechanisms in vertebrates. The embryo is previously labeled through the ubiquitous expression of fluorescent proteins addressed to cells nuclei and membranes, and temporal sequences of volumetric images are acquired with laser scanning microscopy. Cells position is detected by processing nuclei images either through the generalized form of the Hough transform or identifying nuclei position with local maxima after a smoothing preprocessing step. Membranes and nuclei shapes are reconstructed by using PDEs based variational techniques such as the Subjective Surfaces and the Chan Vese method. Cells tracking is performed by combining informations previously detected on cells shape and position with biological regularization constraints. Our results are manually validated and reconstruct the formation of zebrafish brain at 7-8 somite stage with all the cells tracked starting from late sphere stage with less than 2% error for at least 6 hours. Our reconstruction opens the way to a systematic investigation of cellular behaviors, of clonal origin and clonal complexity of brain organs, as well as the contribution of cell proliferation modes and cell movements to the formation of local patterns and morphogenetic fields.

Electrothermal characterization and nonlinear modelling of GaN transistors for telecommunication circuit design

This thesis starts showing the main characteristics and application fields of the AlGaN/GaN HEMT technology, focusing on reliability aspects essentially due to the presence of low frequency dispersive phenomena which limit in several ways the microwave performance of this kind of devices. Based on an equivalent voltage approach, a new low frequency device model is presented where the dynamic nonlinearity of the trapping effect is taken into account for the first time allowing considerable improvements in the prediction of very important quantities for the design of power amplifier such as power added efficiency, dissipated power and internal device temperature. An innovative and low-cost measurement setup for the characterization of the device under low-frequency large-amplitude sinusoidal excitation is also presented. This setup allows the identification of the new low frequency model through suitable procedures explained in detail. In this thesis a new non-invasive empirical method for compact electrothermal modeling and thermal resistance extraction is also described. The new contribution of the proposed approach concerns the non linear dependence of the channel temperature on the dissipated power. This is very important for GaN devices since they are capable of operating at relatively high temperatures with high power densities and the dependence of the thermal resistance on the temperature is quite relevant. Finally a novel method for the device thermal simulation is investigated: based on the analytical solution of the tree-dimensional heat equation, a Visual Basic program has been developed to estimate, in real time, the temperature distribution on the hottest surface of planar multilayer structures. The developed solver is particularly useful for peak temperature estimation at the design stage when critical decisions about circuit design and packaging have to be made. It facilitates the layout optimization and reliability improvement, allowing the correct choice of the device geometry and configuration to achieve the best possible thermal performance.

Tracing AGN accretion and star formation in Herschel galaxies

In this Thesis, we study the physical properties and the cosmic evolution of AGN and their host galaxies since z∼3. Our analysis exploits samples of star forming galaxies detected with Herschel at far-IR wavelengths (from 70 up to 500 micron) in different extragalactic surveys, such as COSMOS and the deep GOODS (South and North) fields. The broad-band ancillary data available in COSMOS and the GOODS fields, allows us to implement Herschel and Spitzer photometry with multi-wavelength ancillary data. We perform a multicomponent SED-fitting decomposition to decouple the emission due to star formation from that due to AGN accretion, and to estimate both host-galaxy parameters (such as stellar mass, M* and star formation rate, SFR), and nuclear intrinsic bolometric luminosities. We use the individual estimates of AGN bolometric luminosity obtained through SED-fitting decomposition to reconstruct the redshit evolution of the AGN bolometric luminosity function since z∼3. The resulting trends are used to estimate the overall AGN accretion rate density at different cosmic epochs and to trace the first ever estimate of the AGN accretion history from an IR survey. Later on, we focus our study on the connection between AGN accretion and integrated galaxy properties. We analyse the relationships of AGN accretion with galaxy properties in the SFR-M* plane and at different cosmic epochs. Finally, we infer what is the parameter that best correlates with AGN accretion, comparing our results with previous studies and discussing their physical implications in the context of current scenarios of AGN/galaxy evolution.

The XENON1T experiment: Monte Carlo background estimation and sensitivity curves study

Despite the scientific achievement of the last decades in the astrophysical and cosmological fields, the majority of the Universe energy content is still unknown. A potential solution to the “missing mass problem” is the existence of dark matter in the form of WIMPs. Due to the very small cross section for WIMP-nuleon interactions, the number of expected events is very limited (about 1 ev/tonne/year), thus requiring detectors with large target mass and low background level. The aim of the XENON1T experiment, the first tonne-scale LXe based detector, is to be sensitive to WIMP-nucleon cross section as low as 10^-47 cm^2. To investigate the possibility of such a detector to reach its goal, Monte Carlo simulations are mandatory to estimate the background. To this aim, the GEANT4 toolkit has been used to implement the detector geometry and to simulate the decays from the various background sources: electromagnetic and nuclear. From the analysis of the simulations, the level of background has been found totally acceptable for the experiment purposes: about 1 background event in a 2 tonne-years exposure. Indeed, using the Maximum Gap method, the XENON1T sensitivity has been evaluated and the minimum for the WIMP-nucleon cross sections has been found at 1.87 x 10^-47 cm^2, at 90% CL, for a WIMP mass of 45 GeV/c^2. The results have been independently cross checked by using the Likelihood Ratio method that confirmed such results with an agreement within less than a factor two. Such a result is completely acceptable considering the intrinsic differences between the two statistical methods. Thus, in the PhD thesis it has been proven that the XENON1T detector will be able to reach the designed sensitivity, thus lowering the limits on the WIMP-nucleon cross section by about 2 orders of magnitude with respect to the current experiments.

Silk Fibroin: a biopolymer platform for innovative pharmaceutical formulation and biomedical devices.

The protein silk fibroin (SF) from the silkworm Bombyx mori is a FDA-approved biomaterial used over centuries as sutures wire. Importantly, several evidences highlighted the potential of silk biomaterials obtained by using so-called regenerated silk fibroin (RSF) in biomedicine, tissue engineering and drug delivery. Indeed, by a water-based protocol, it is possible to obtain protein water-solution, by extraction and purification of fibroin from silk fibres. Notably, RSF can be processed in a variety of biomaterials forms used in biomedical and technological fields, displaying remarkable properties such as biocompatibility, controllable biodegradability, optical transparency, mechanical robustness. Moreover, RSF biomaterials can be doped and/or chemical functionalized with drugs, optically active molecules, growth factors and/or chemicals In this view, activities of my PhD research program were focused to standardize the process of extraction and purification of protein to get the best physical and chemical characteristics. The analysis of the chemo-physical properties of the fibroin involved both the RSF water-solution and the protein processed in film. Chemo-physical properties have been studied through: vibrational (FT-IR and Raman-FT) and optical (absorption and emission UV-VIS) spectroscopy, nuclear magnetic resonance (1H and 13C NMR), thermal analysis and thermo-gravimetric scan (DSC and TGA). In the last year of my PhD, activities were focused to study and define innovative methods of functionalization of the silk fibroin solution and films. Indeed, research program was the application of different methods of manufacturing approaches of the films of fibroin without the use of harsh treatments and organic solvents. New approaches to doping and chemical functionalization of the silk fibroin were studied. Two different methods have been identified: 1) biodoping that consists in the doping of fibroin with optically active molecules through the addition of fluorescent molecules in the standard diet used for the breeding of silkworms; 2) chemical functionalization via silylation.