Musical tension in harmonic intervals: behavioral and neural correlates

Musical tension is what drives our emotional experience in music listening. However, the specific role of the musical elements involved in tension-resolution perception remains largely unclear. This dissertation aims to advance the understanding of tension perception dynamics related to sensory consonance-dissonance. The first experiment aimed to design and validate a new crossmodal proprioceptive device for tension rating that overcomes some of the limitations of known tools. As a result, a psychophysical equation for the matching of physical force and psychological force was presented. The same tool was subsequently used in the second and third experiments to collect ratings of perceived tension and movement in harmonic musical intervals and standard noises. Besides, a visual analog scale (VAS) was used to allow a comparison of these two methods. The results confirmed the close relationship between sensory dissonance and perceived tension. Moreover, stimuli in the higher pitch register were perceived as more tense, confirming the primary role of pitch as a mediator of tension. The comparison between ratings obtained with the proprioceptive device and the VAS highlighted the tendency to give higher tension ratings using the VAS compared to the proprioceptive device. In the last experiment, brain electrical activity was recorded during the presentation of short tension-resolution patterns created using the most tense (perfect unison, fourth, and fifth) and the least tense harmonic intervals (augmented fourth, minor second, and inverted major seventh) to understand how consonance-dissonance can convey meaningful information on perceived tension-resolution. Results showed overall larger effects during the ‘resolution’ condition compare to the ‘tension induction’ condition, indicating that the resolution of harmonic instability towards a state of stability may be more salient than its opposite. A late positive component (LPC) was elicited, possibly reflecting deeper processing of tension-related meaning within a minimal harmonic context.

Study and experimental characterization of the laser welding process for the manufacturing of electric powertrain components in the automotive industry

The PhD project that will be presented in this thesis is focused on the study and optimization of the production process for the manufacturing of electrical powertrain components in the automotive field using the laser beam welding process (LBW). The objective is to define, through experimental activities, an optimized process condition for applications in the electrical field that can be generalized, that is, which guarantees its reproducibility as the types of connections vary and which represents the basis for extending the method to future applications in e-mobility sector. The work developed along two lines of research, the convergence of which made it possible to create prototypes of battery modules based on different types of lithium-ion cells and stator windings for electric motors. On the one hand, the different welding configurations involving the production of batteries based on pouch cells and therefore the welding of aluminum and copper in dissimilar configuration were studied, while for the prismatic cells only one configuration was analyzed. On the other hand, the welding of pure copper hairpins with rectangular shape in edge joint configuration was studied for the production of stator windings. The experimental tests carried out have demonstrated the feasibility of using the LBW process for the production of electric powertrain components entirely designed and developed internally as the types of materials and welding configurations vary; the methodologies required for the characterization methods, necessary for the end-of-line tests, for the evaluation of the properties of the different joint configurations and components (battery and electric motor) were also defined with the aim of obtaining the best performance. The entire doctorate program was conducted in collaboration with Ferrari Auto S.p.A. and the direct industrial application of the issues addressed has been faced.

Theoretical and experimental study of novel hybrid composite and metal-composites interfaces

The growing demand for lightweight solutions in every field of engineering is driving the industry to seek new technological solutions to exploit the full potential of different materials. The combination of dissimilar materials with distinct property ranges embodies a transparent allocation of component functions while allowing an optimal mix of their characteristics. From both technological and design perspectives, the interaction between dissimilar materials can lead to severe defects that compromise a multi-material hybrid component's performance and its structural integrity. This thesis aims to develop methodologies for designing, manufacturing, and monitoring of hybrid metal-composite joints and hybrid composite components. In Chapter 1, a methodology for designing and manufacturing hybrid aluminum/composite co-cured tubes is assessed. In Chapter 2, a full-field methodology for fiber misalignment detection and stiffness prediction for hybrid, long fiber reinforced composite systems is shown and demonstrated. Chapter 3 reports the development of a novel technology for joining short fiber systems and metals in a one-step co-curing process using lattice structures. Chapter 4 is dedicated to a novel analytical framework for the design optimization of two lattice architectures.

Numerical and experimental analysis of 3D printed smart structures and systems

Three dimensional (3D) printers of continuous fiber reinforced composites, such as MarkTwo (MT) by Markforged, can be used to manufacture such structures. To date, research works devoted to the study and application of flexible elements and CMs realized with MT printer are only a few and very recent. A good numerical and/or analytical tool for the mechanical behavior analysis of the new composites is still missing. In addition, there is still a gap in obtaining the material properties used (e.g. elastic modulus) as it is usually unknown and sensitive to printing parameters used (e.g. infill density), making the numerical simulation inaccurate. Consequently, the aim of this thesis is to present several work developed. The first is a preliminary investigation on the tensile and flexural response of Straight Beam Flexures (SBF) realized with MT printer and featuring different interlayer fiber volume-fraction and orientation, as well as different laminate position within the sample. The second is to develop a numerical analysis within the Carrera' s Unified Formulation (CUF) framework, based on component-wise (CW) approach, including a novel preprocessing tool that has been developed to account all regions printed in an easy and time efficient way. Among its benefits, the CUF-CW approach enables building an accurate database for collecting first natural frequencies modes results, then predicting Young' s modulus based on an inverse problem formulation. To validate the tool, the numerical results are compared to the experimental natural frequencies evaluated using a digital image correlation method. Further, we take the CUF-CW model and use static condensation to analyze smart structures which can be decomposed into a large number of similar components. Third, the potentiality of MT in combination with topology optimization and compliant joints design (CJD) is investigated for the realization of automated machinery mechanisms subjected to inertial loads.

Numerical modeling and experimental validation of the recrystallization behaviour in the extrusion of 6XXX aluminum alloys

The microstructure of 6XXX aluminum alloys deeply affects mechanical, crash, corrosion and aesthetic properties of extruded profiles. Unfortunately, grain structure evolution during manufacturing processes is a complex phenomenon because several process and material parameters such as alloy chemical composition, temperature, extrusion speed, tools geometries, quenching and thermal treatment parameters affect the grain evolution during the manufacturing process. The aim of the present PhD thesis was the analysis of the recrystallization kinetics during the hot extrusion of 6XXX aluminum alloys and the development of reliable recrystallization models to be used in FEM codes for the microstructure prediction at a die design stage. Experimental activities have been carried out in order to acquire data for the recrystallization models development, validation and also to investigate the effect of process parameters and die design on the microstructure of the final component. The experimental campaign reported in this thesis involved the extrusion of AA6063, AA6060 and AA6082 profiles with different process parameters in order to provide a reliable amount of data for the models validation. A particular focus was made to investigate the PCG defect evolution during the extrusion of medium-strength alloys such as AA6082. Several die designs and process conditions were analysed in order to understand the influence of each of them on the recrystallization behaviour of the investigated alloy. From the numerical point of view, innovative models for the microstructure prediction were developed and validated over the extrusion of industrial-scale profiles with complex geometries, showing a good matching in terms of the grain size and surface recrystallization prediction. The achieved results suggest the reliability of the developed models and their application in the industrial field for process and material properties optimization at a die-design stage.

Essays in political and gender economics

In the first chapter, “Political power and the influence of minorities: theory and evidence from Italy”, I analyze the relationship between minority and majority in politics, and how it can influence policy outcomes. I first present a theoretical model describing the possible consequences of an increase in a minority’s political power and show how it can increase difficulties in reaching a compromise on policy outcomes between parties. Furthermore, I empirically test these implications by exploiting the introduction in 2012 of a gender quota in Italian local elections: the increase in female politicians had heterogeneous effects on the level of funding for daycare, based on its differential effects on the share of women councillors. The second chapter, “Marriage patterns and the gender gap in labor force participation: evidence from Italy”, presents evidence highlighting a new possible determinant of the large gender gap in the Italian labor force: endogamy intensity. I argue that endogamy helps preserve social norms stigmatizing working women and reduces the probability of divorce, which disincentivizes women’s participation in the labor force. Endogamy is proxied by the degree of concentration of its surnames’ distribution, and I provide evidence that a more intense custom of endogamy contributed to enlarging gender participation gaps across Italian municipalities in 2001. The third chapter, “Information and quality of politicians: is transparency helping voters?”, studies how voting choices are affected by giving voters more personal information on candidates. I exploit the introduction of the “Spazzacorrotti” law in Italy in 2019, which imposed candidates at local elections to publish their CVs and criminal records before elections. I find no effects on elected candidates’ age, gender, educational level, or ideology. Moreover, I present anecdotal evidence that candidates with a criminal record received fewer votes on average, but only in the case of local media exposing it.

The Simon effect and its time courses: an investigation

The objective of the current thesis is to investigate the temporal dynamics (i.e., time courses) of the Simon effect, both from a theoretical and experimental point of view, for a better understanding of whether a) one or more process are responsible for the Simon effect and b) how this/these mechanism/s differently influence performance. In the first theoretical (i.e., “Theoretical Overview”) part, I examined in detail the process and justification for analyzing the temporal dynamics of the Simon effect and the assumptions that underlie interpretation of the results which have been obtained in the existing literature so far. In the second part (“Experimental Investigations”), though, I experimentally investigated several issues which the existing literature left unsolved, in order to get further evidence in favor or in contrast with the mainstream models which are currently used to account for the different Simon effect time courses. Some points about the experiments are worth mentioning: First, all the experiments were conducted in the laboratory, facing participants with stimuli presented on a PC screen and then recording their responses. Both stimuli presentation and response collection was controlled by the E-Prime software. The dependent variables of interest were always behavioral measures of performance, such as velocity and accuracy. Second, the most part of my experiments had been conducted at the Communication Sciences Department (University of Bologna), under Prof. Nicoletti’s supervision. The remaining part, though, had been conducted at the Psychological Sciences Department of Purdue University (West Lafayette, Indiana, USA), where I collaborated for one year as a visiting student with Prof. Proctor and his team. Third, my experimental pool was entirely composed by healthy and young students, since the cognitive functioning of elderly people was not the target of my research.

Social learning and action understanding in human observers: contributions of sensori-motor constraints and prior information

The aim of this thesis was to investigate the respective contribution of prior information and sensorimotor constraints to action understanding, and to estimate their consequences on the evolution of human social learning. Even though a huge amount of literature is dedicated to the study of action understanding and its role in social learning, these issues are still largely debated. Here, I critically describe two main perspectives. The first perspective interprets faithful social learning as an outcome of a fine-grained representation of others’ actions and intentions that requires sophisticated socio-cognitive skills. In contrast, the second perspective highlights the role of simpler decision heuristics, the recruitment of which is determined by individual and ecological constraints. The present thesis aims to show, through four experimental works, that these two contributions are not mutually exclusive. A first study investigates the role of the inferior frontal cortex (IFC), the anterior intraparietal area (AIP) and the primary somatosensory cortex (S1) in the recognition of other people’s actions, using a transcranial magnetic stimulation adaptation paradigm (TMSA). The second work studies whether, and how, higher-order and lower-order prior information (acquired from the probabilistic sampling of past events vs. derived from an estimation of biomechanical constraints of observed actions) interacts during the prediction of other people’s intentions. Using a single-pulse TMS procedure, the third study investigates whether the interaction between these two classes of priors modulates the motor system activity. The fourth study tests the extent to which behavioral and ecological constraints influence the emergence of faithful social learning strategies at a population level. The collected data contribute to elucidate how higher-order and lower-order prior expectations interact during action prediction, and clarify the neural mechanisms underlying such interaction. Finally, these works provide/open promising perspectives for a better understanding of social learning, with possible extensions to animal models.

Integration of cognitive and affective processes in perception and decision-making

The relationship between emotion and cognition is a topic that raises great interest in research. Recently, a view of these two processes as interactive and mutually influencing each other has become predominant. This dissertation investigates the reciprocal influences of emotion and cognition, both at behavioral and neural level, in two specific fields, such as attention and decision-making. Experimental evidence on how emotional responses may affect perceptual and attentional processes has been reported. In addition, the impact of three factors, such as personality traits, motivational needs and social context, in modulating the influence that emotion exerts on perception and attention has been investigated. Moreover, the influence of cognition on emotional responses in decision-making has been demonstrated. The current experimental evidence showed that cognitive brain regions such as the dorsolateral prefrontal cortex are causally implicated in regulation of emotional responses and that this has an effect at both pre and post decisional stages. There are two main conclusions of this dissertation: firstly, emotion exerts a strong influence on perceptual and attentional processes but, at the same time, this influence may also be modulated by other factors internal and external to the individuals. Secondly, cognitive processes may modulate emotional prepotent responses, by serving a regulative function critical to driving and shaping human behavior in line with current goals.

Essays on social networks, altruism and information diffusion

This dissertation consists of three standalone articles that contribute to the economics literature concerning technology adoption, information diffusion, and network economics in one way or another, using a couple of primary data sources from Ethiopia. The first empirical paper identifies the main behavioral factors affecting the adoption of brand new (radical) and upgraded (incremental) bioenergy innovations in Ethiopia. The results highlight the importance of targeting different instruments to increase the adoption rate of the two types of innovations. The second and the third empirical papers of this thesis, use primary data collected from 3,693 high school students in Ethiopia, and shed light on how we should select informants to effectively and equitably disseminate new information, mainly concerning environmental issues. There are different well-recognized standard centrality measures that are used to select informants. These standard centrality measures, however, are based on the network topology---shaped only by the number of connections---and fail to incorporate the intrinsic motivations of the informants. This thesis introduces an augmented centrality measure (ACM) by modifying the eigenvector centrality measure through weighting the adjacency matrix with the altruism levels of connected nodes. The results from the two papers suggest that targeting informants based on network position and behavioral attributes ensures more effective and equitable (gender perspective) transmission of information in social networks than selecting informants on network centrality measures alone. Notably, when the information is concerned with environmental issues.