L'intelligenza emotiva in età evolutiva

Emotional Intelligence (EI) has increasingly gained widespread popularity amongst both lay people and scientists in a wide range of contexts and across several research areas. In spite of rigorous inquiry into its applications in educational, social, health and clinical settings, substantial disagreement exists regarding the definition of EI, with respect to both terminology and operationalizations. Actually, there is a consensus about a conceptual distinction between Trait EI, or trait emotional self-efficacy (Petrides & Furnham, 2001), and Ability EI, or cognitive-emotional ability (Mayer & Salovey, 1997). Trait EI is measured via self-report questionnaires, whereas Ability EI is assessed via maximum performance tests. Moreover, EI is the broadest of the emotional constructs, and it subsumes various constructs, as Emotional Awareness (Lane & Schwartz, 1987). To date, EI research has focused primarily on adults, with fewer studies conducted with child samples. The aim of the present study is to investigate the role of different models of EI in childhood and early adolescence (N = 670; 353 females; Mage= 10.25 years ; SD = 1.57). In addition, a further goal is to evaluate the relationship of each construct with personality, non verbal cognitive intelligence, school performance, peer relationships, and affective disorders (anxiety and depression). Results shows significant correlations between Trait EI and Emotional Awareness, whereas Trait and Ability EI appear as independent constructs. We also found significant positive associations between age and Ablity EI and Emotional Awareness (although with add of verbal productivity), while gender differences emerged in favour of females in all EI-related measures. The results provide evidence that Trait EI is partially determined by all of the Big Five personality dimensions, but independent of cognitive ability. Finally, the present study highlights the role of EI on social interactions, school performance and, especially, a negative relationship between Trait EI and psychopathology.

Detection and Modeling of Boundary Layer Height

This thesis tackles the problem of the automated detection of the atmospheric boundary layer (BL) height, h, from aerosol lidar/ceilometer observations. A new method, the Bayesian Selective Method (BSM), is presented. It implements a Bayesian statistical inference procedure which combines in an statistically optimal way different sources of information. Firstly atmospheric stratification boundaries are located from discontinuities in the ceilometer back-scattered signal. The BSM then identifies the discontinuity edge that has the highest probability to effectively mark the BL height. Information from the contemporaneus physical boundary layer model simulations and a climatological dataset of BL height evolution are combined in the assimilation framework to assist this choice. The BSM algorithm has been tested for four months of continuous ceilometer measurements collected during the BASE:ALFA project and is shown to realistically diagnose the BL depth evolution in many different weather conditions. Then the BASE:ALFA dataset is used to investigate the boundary layer structure in stable conditions. Functions from the Obukhov similarity theory are used as regression curves to fit observed velocity and temperature profiles in the lower half of the stable boundary layer. Surface fluxes of heat and momentum are best-fitting parameters in this exercise and are compared with what measured by a sonic anemometer. The comparison shows remarkable discrepancies, more evident in cases for which the bulk Richardson number turns out to be quite large. This analysis supports earlier results, that surface turbulent fluxes are not the appropriate scaling parameters for profiles of mean quantities in very stable conditions. One of the practical consequences is that boundary layer height diagnostic formulations which mainly rely on surface fluxes are in disagreement to what obtained by inspecting co-located radiosounding profiles.

Enhancing Workers’ Well-Being. Scientific and social relevance of managing stress in the workplace

Purpose. Despite work-related stress is one of the most studied topic in organizational psychology, many aspects as for example the use of different measures (e.g. subjective and objective, qualitative and quantitative) are still under debate. According to this, in order to enhance knowledge concerning which factors and processes contribute to create healthy workplaces, this thesis is composed by four different studies aiming to understand: a) the role of relevant antecedents (e.g. leadership, job demands, work-family conflict, social support etc.) and outcomes (e.g. workplace phobia, absenteeism etc.) of work-related stress; and b) how to manage psychosocial risk factors in the workplace. The studies. The first study focused on how disagreement between supervisors and their employees on leadership style (transformational and transactional) could affect workers well-being and work team variables. The second and third study used both subjective and objective data in order to increase the quality of the reliability of the results gained. Particularly, the second study focused on job demand and its relationship with objective sickness leave. Findings showed that despite there is no direct relationship between these two variables, job demand affects work-family conflict, which in turn affect exhaustion, which leads to absenteeism. The third study analysed the role of a new concept never studied before in organizational settings (workplace phobia), as a health outcome in the JD-R model, demonstrating also its relationship with absenteeism. The last study highlighted the added value of using the mixed methods research approach in order to detect and analyse context-specific job demands which could affects workers’ health. Conclusion. The findings of this thesis answered both to open questions in the scientific literature and to the social request of managing psychosocial risk factors in the workplace in order to enhance workers well-being.

The market manipulation regime in the European Union

Market manipulation is an illegal practice that enables a person can profit from practices that artificially raise or lower the prices of an instrument in the financial markets. Its prohibition is based on the 2003 Market Abuse Directive in the EU. The current market manipulation regime was broadly considered as a big success except for enforcement and supervisory inconsistencies in the Member States at the initial. A review of the market manipulation regime began at the end of 2007, which became quickly incorporated into the wider EU crisis-era reform program. A number of weaknesses of current regime have been identified, which include regulatory gaps caused by the development of trading venues and financial products, regulatory gaps concerning cross-border and cross-markets manipulation (particular commodity markets), legal uncertainty as a result of various implementation, and inefficient supervision and enforcement. On 12 June 2014, a new regulatory package of market abuse, Market Abuse Regulation and Directive on criminal sanctions for market abuse, has been adopted. And several changes will be made concerning the EU market manipulation regime. A wider scope of the regime and a new prohibition of attempted market manipulation will ensure the prevention of market manipulation at large. The AMPs will be subject to strict scrutiny of ESMA to reduce divergences in implementation. In order to enhance efficiency of supervision and enforcement, powers of national competent authorities will be strengthened, ESMA is imposed more power to settle disagreement between national regulators, and the administrative and criminal sanctioning regimes are both further harmonized. In addition, the protection of fundamental rights is stressed by the new market manipulation regime, and some measures are provided to guarantee its realization. Further, the success EU market manipulation regime could be of significant reference to China, helping China to refine its immature regime.

Black Hole and Galaxy Growth over Cosmic Time: the Chandra COSMOS Legacy Survey

The study of supermassive black hole (SMBH) accretion during their phase of activity (hence becoming active galactic nuclei, AGN), and its relation to the host-galaxy growth, requires large datasets of AGN, including a significant fraction of obscured sources. X-ray data are strategic in AGN selection, because at X-ray energies the contamination from non-active galaxies is far less significant than in optical/infrared surveys, and the selection of obscured AGN, including also a fraction of heavily obscured AGN, is much more effective. In this thesis, I present the results of the Chandra COSMOS Legacy survey, a 4.6 Ms X-ray survey covering the equatorial COSMOS area. The COSMOS Legacy depth (flux limit f=2x10^(-16) erg/s/cm^(-2) in the 0.5-2 keV band) is significantly better than that of other X-ray surveys on similar area, and represents the path for surveys with future facilities, like Athena and X-ray Surveyor. The final Chandra COSMOS Legacy catalog contains 4016 point-like sources, 97% of which with redshift. 65% of the sources are optically obscured and potentially caught in the phase of main BH growth. We used the sample of 174 Chandra COSMOS Legacy at z>3 to place constraints on the BH formation scenario. We found a significant disagreement between our space density and the predictions of a physical model of AGN activation through major-merger. This suggests that in our luminosity range the BH triggering through secular accretion is likely preferred to a major-merger triggering scenario. Thanks to its large statistics, the Chandra COSMOS Legacy dataset, combined with the other multiwavelength COSMOS catalogs, will be used to answer questions related to a large number of astrophysical topics, with particular focus on the SMBH accretion in different luminosity and redshift regimes.