Il conflitto tra ragione e passioni nel pensiero morale, economico e politico di Bernard Mandeville

Effects of the conflict between reason and passion in Bernard Mandeville’s moral, economic and political thought My PhD dissertation focuses on Bernard Mandeville (1670-1732), a Dutch philosopher who moved to London in his late twenties. The aspect of Mandeville’s thought I take into account in my research is the conflicting relation between reason and passions, and the consequences that Mandeville’s view of this conflict has in the development of his theory of human nature which, I argue, is what grounds his moral, economic and, above all, political theory. According to Mandeville, reason is fundamentally weak. Passions influence with more strength human actions, and, eventually, are the ones which motivate them. The role of reason is merely instrumental, restricted to finding appropriate means in order to reach the desired ends, which are capricious and inconstant, since they all come from unstable passions. Reason cannot take decisions meant to act in the long term, pursuing an object which has not a selfish and temporary nature. There is no possibility, thus, that men’s actions aim just to achieve a good and just society, without their interests being directly involved. The basically selfish root of every desire leads Mandeville to claim that there is neither benevolence nor altruism which guides human behaviour. Hence he expresses a judgement on the moral character of human beings, always busy with their self-satisfaction, and hardly ever considering what would be good on a wider perspective, including other people’s sake. The anthropological features ascribed to men by Mandeville, are those which lead him to prefer a political system where governors are not supposed to have particular abilities, either from an intellectual or from a moral point of view, and peace and order are preserved by the bureaucratic machine, which is meant to work with the least effort on the part of the politicians, and no big harm can be done even by corrupted or wicked governors. This system is adopted with an eye at remedying human deficiencies: Mandeville takes into primary account, when he thinks of how to build a peaceful and functioning society, that everyone is concerned with his selfish interest, and that the rationality of a single politician, or of a group of them belonging to a same generation, cannot find a good “solution” to govern men able to last over the long period, and to work in different ages. This implies a refusal of the Hobbesian theory of the pactum subjectionis, which has the character of a rational and definitive choice, and leads Mandeville to consider the order which arises spontaneously, without any plan or rational intervention.

Inside standard and hyperspectral low-dose CT variational imaging: parameter identification and material decomposition

The main contribution of this thesis is the proposal of novel strategies for the selection of parameters arising in variational models employed for the solution of inverse problems with data corrupted by Poisson noise. In light of the importance of using a significantly small dose of X-rays in Computed Tomography (CT), and its need of using advanced techniques to reconstruct the objects due to the high level of noise in the data, we will focus on parameter selection principles especially for low photon-counts, i.e. low dose Computed Tomography. For completeness, since such strategies can be adopted for various scenarios where the noise in the data typically follows a Poisson distribution, we will show their performance for other applications such as photography, astronomical and microscopy imaging. More specifically, in the first part of the thesis we will focus on low dose CT data corrupted only by Poisson noise by extending automatic selection strategies designed for Gaussian noise and improving the few existing ones for Poisson. The new approaches will show to outperform the state-of-the-art competitors especially in the low-counting regime. Moreover, we will propose to extend the best performing strategy to the hard task of multi-parameter selection showing promising results. Finally, in the last part of the thesis, we will introduce the problem of material decomposition for hyperspectral CT, which data encodes information of how different materials in the target attenuate X-rays in different ways according to the specific energy. We will conduct a preliminary comparative study to obtain accurate material decomposition starting from few noisy projection data.