Reasoning with incomplete and imprecise preferences

Preferences are present in many real life situations but it is often difficult to quantify them giving a precise value. Sometimes preference values may be missing because of privacy reasons or because they are expensive to obtain or to produce. In some other situations the user of an automated system may have a vague idea of whats he wants. In this thesis we considered the general formalism of soft constraints, where preferences play a crucial role and we extended such a framework to handle both incomplete and imprecise preferences. In particular we provided new theoretical frameworks to handle such kinds of preferences. By admitting missing or imprecise preferences, solving a soft constraint problem becomes a different task. In fact, the new goal is to find solutions which are the best ones independently of the precise value the each preference may have. With this in mind we defined two notions of optimality: the possibly optimal solutions and the necessary optimal solutions, which are optimal no matter we assign a precise value to a missing or imprecise preference. We provided several algorithms, bases on both systematic and local search approaches, to find such kind of solutions. Moreover, we also studied the impact of our techniques also in a specific class of problems (the stable marriage problems) where imprecision and incompleteness have a specific meaning and up to now have been tackled with different techniques. In the context of the classical stable marriage problem we developed a fair method to randomly generate stable marriages of a given problem instance. Furthermore, we adapted our techniques to solve stable marriage problems with ties and incomplete lists, which are known to be NP-hard, obtaining good results both in terms of size of the returned marriage and in terms of steps need to find a solution.

Epidemiology and population genetics of Podosphaera fusca and Golovinomyces orontii, causal agents of cucurbit powdery mildew

In 2010, 2011 and 2012 growing seasons, the occurrence of the ascomycetes Podosphaera fusca and Golovinomyces orontii, causal agents of powdery mildew disease, was monitored on cultivated cucurbits located in Bologna and Mantua provinces to determine the epidemiology of the species. To identify the pathogens, both morphological and molecular identifications were performed on infected leaf samples and a Multiplex-PCR was performed to identify the mating type genes of P. fusca isolates. The investigations indicated a temporal succession of the two species with the earlier infections caused by G. orontii, that seems to be the predominant species till the middle of July when it progressively disappears and P. fusca becomes the main species infecting cucurbits till the end of October. The temporal variation is likely due to the different overwintering strategies of the two species instead of climatic conditions. Only chasmothecia of P. fusca were recorded and mating type alleles ratio tended to be 1:1. Considering that only chasmothecia of P. fusca were found, molecular-genetic analysis were carried out to find some evidence of recombination within this species by MLST and AFLP methods. Surprisingly, no variations were observed within isolates for the 8 MLST markers used. According to this result, AFLP analysis showed a high similarity within isolates, with SM similarity coefficient ranging between 0.91-1.00 and also, sequencing of 12 polymorphic bands revealed identity to some gene involved in mutation and selection. The results suggest that populations of P. fusca are likely to be a clonal population with some differences among isolates probably due to agricultural practices such as fungicides treatments and cultivated hosts. Therefore, asexual reproduction, producing a lot of fungal biomass that can be easily transported by wind, is the most common and useful way to the spread and colonization of the pathogen.

Obsessed With Work: A multi-causal and multi-rater approach to workaholism

Workaholism is defined as the combination of two underlying dimensions: working excessively and working compulsively. The present thesis aims at achieving the following purposes: 1) to test whether the interaction between environmental and personal antecedents may enhance workaholism; 2) to develop a questionnaire aimed to assess overwork climate in the workplace; 3) to contrast focal employees’ and coworkers’ perceptions of employees’ workaholism and engagement. Concerning the first purpose, the interaction between overwork climate and person characteristics (achievement motivation, perfectionism, conscientiousness, self-efficacy) was explored on a sample of 333 Dutch employees. The results of moderated regression analyses showed that the interaction between overwork climate and person characteristics is related to workaholism. The second purpose was pursued with two interrelated studies. In Study 1 the Overwork Climate Scale (OWCS) was developed and tested using a principal component analysis (N = 395) and a confirmatory factor analysis (N = 396). Two overwork climate dimensions were distinguished, overwork endorsement and lacking overwork rewards. In Study 2 the total sample (N = 791) was used to explore the association of overwork climate with two types of working hard: work engagement and workaholism. Lacking overwork rewards was negatively associated with engagement, whereas overwork endorsement showed a positive association with workaholism. Concerning the third purpose, using a sample of 73 dyads composed by focal employees and their coworkers, a multitrait-multimethod matrix and a correlated trait-correlated method model, i.e. the CT-C(M–1) model, were examined. Our results showed a considerable agreement between raters on focal employees' engagement and workaholism. In contrast, we observed a significant difference concerning the cognitive dimension of workaholism, working compulsively. Moreover, we provided further evidence for the discriminant validity between engagement and workaholism. Overall, workaholism appears as a negative work-related state that could be better explained by assuming a multi-causal and multi-rater approach.