Non-normal modal logics, quantification, and deontic dilemmas. A study in multi-relational semantics

This dissertation is devoted to the study of non-normal (modal) systems for deontic logics, both on the propositional level, and on the first order one. In particular we developed our study the Multi-relational setting that generalises standard Kripke Semantics. We present new completeness results concerning the semantic setting of several systems which are able to handle normative dilemmas and conflicts. Although primarily driven by issues related to the legal and moral field, these results are also relevant for the more theoretical field of Modal Logic itself, as we propose a syntactical, and semantic study of intermediate systems between the classical propositional calculus CPC and the minimal normal modal logic K.

Multiresolution spherical wavelet analysis in global seismic tomography

Every seismic event produces seismic waves which travel throughout the Earth. Seismology is the science of interpreting measurements to derive information about the structure of the Earth. Seismic tomography is the most powerful tool for determination of 3D structure of deep Earth's interiors. Tomographic models obtained at the global and regional scales are an underlying tool for determination of geodynamical state of the Earth, showing evident correlation with other geophysical and geological characteristics. The global tomographic images of the Earth can be written as a linear combinations of basis functions from a specifically chosen set, defining the model parameterization. A number of different parameterizations are commonly seen in literature: seismic velocities in the Earth have been expressed, for example, as combinations of spherical harmonics or by means of the simpler characteristic functions of discrete cells. With this work we are interested to focus our attention on this aspect, evaluating a new type of parameterization, performed by means of wavelet functions. It is known from the classical Fourier theory that a signal can be expressed as the sum of a, possibly infinite, series of sines and cosines. This sum is often referred as a Fourier expansion. The big disadvantage of a Fourier expansion is that it has only frequency resolution and no time resolution. The Wavelet Analysis (or Wavelet Transform) is probably the most recent solution to overcome the shortcomings of Fourier analysis. The fundamental idea behind this innovative analysis is to study signal according to scale. Wavelets, in fact, are mathematical functions that cut up data into different frequency components, and then study each component with resolution matched to its scale, so they are especially useful in the analysis of non stationary process that contains multi-scale features, discontinuities and sharp strike. Wavelets are essentially used in two ways when they are applied in geophysical process or signals studies: 1) as a basis for representation or characterization of process; 2) as an integration kernel for analysis to extract information about the process. These two types of applications of wavelets in geophysical field, are object of study of this work. At the beginning we use the wavelets as basis to represent and resolve the Tomographic Inverse Problem. After a briefly introduction to seismic tomography theory, we assess the power of wavelet analysis in the representation of two different type of synthetic models; then we apply it to real data, obtaining surface wave phase velocity maps and evaluating its abilities by means of comparison with an other type of parametrization (i.e., block parametrization). For the second type of wavelet application we analyze the ability of Continuous Wavelet Transform in the spectral analysis, starting again with some synthetic tests to evaluate its sensibility and capability and then apply the same analysis to real data to obtain Local Correlation Maps between different model at same depth or between different profiles of the same model.

Catalytic processes for the transformation of ethanol into acetonitrile

This thesis deals with the transformation of ethanol into acetonitrile. Two approaches are investigated: (a) the ammoxidation of ethanol to acetonitrile and (b) the amination of ethanol to acetonitrile. The reaction of ethanol ammoxidation to acetonitrile has been studied using several catalytic systems, such as vanadyl pyrophosphate, supported vanadium oxide, multimetal molibdates and antimonates. The main conclusions are: (I) The surface acidity must be very low, because acidity catalyzes several undesired reactions, such as the formation of ethylene, and of heavy compounds as well. (II) Supported vanadium oxide is the catalyst showing the best catalytic behaviour, but the role of the support is of crucial importance. (III) Both metal molybdates and antimonates show interesting catalytic behaviour, but are poorly active, and probably require harder conditions than those used with the V oxide-based catalysts. (IV) One key point in the reaction network is the rate of reaction between acetaldehyde (the first intermediate) and ammonia, compared to the parallel rates of acetaldehyde transformation into by-products (CO, CO2, HCN, heavy compounds). Concerning the non-oxidative process, two possible strategies are investigated: (a) the ethanol ammonolysis to ethylamine coupled with ethylamine dehydrogenation, and (b) the direct non-reductive amination of ethanol to acetonitrile. Despite the good results obtained in each single step, the former reaction does not lead to good results in terms of yield to acetonitrile. The direct amination can be catalyzed with good acetonitrile yield over catalyst based on supported metal oxides. Strategies aimed at limiting catalyst deactivation have also been investigated.