The Universe 10 Billion years ago: Morphologies, Star-formation rates and Galactic-scale winds in z ∼ 2 Galaxies

This thesis is devoted to the study of the properties of high-redsfhit galaxies in the epoch 1 < z < 3, when a substantial fraction of galaxy mass was assembled, and when the evolution of the star-formation rate density peaked. Following a multi-perspective approach and using the most recent and high-quality data available (spectra, photometry and imaging), the morphologies and the star-formation properties of high-redsfhit galaxies were investigated. Through an accurate morphological analyses, the built up of the Hubble sequence was placed around z ~ 2.5. High-redshift galaxies appear, in general, much more irregular and asymmetric than local ones. Moreover, the occurrence of morphological k-­correction is less pronounced than in the local Universe. Different star-formation rate indicators were also studied. The comparison of ultra-violet and optical based estimates, with the values derived from infra-red luminosity showed that the traditional way of addressing the dust obscuration is problematic, at high-redshifts, and new models of dust geometry and composition are required. Finally, by means of stacking techniques applied to rest-frame ultra-violet spectra of star-forming galaxies at z~2, the warm phase of galactic-scale outflows was studied. Evidence was found of escaping gas at velocities of ~ 100 km/s. Studying the correlation of inter-­stellar absorption lines equivalent widths with galaxy physical properties, the intensity of the outflow-related spectral features was proven to depend strongly on a combination of the velocity dispersion of the gas and its geometry.

Applying machine learning: a multi-role perspective

Machine (and deep) learning technologies are more and more present in several fields. It is undeniable that many aspects of our society are empowered by such technologies: web searches, content filtering on social networks, recommendations on e-commerce websites, mobile applications, etc., in addition to academic research. Moreover, mobile devices and internet sites, e.g., social networks, support the collection and sharing of information in real time. The pervasive deployment of the aforementioned technological instruments, both hardware and software, has led to the production of huge amounts of data. Such data has become more and more unmanageable, posing challenges to conventional computing platforms, and paving the way to the development and widespread use of the machine and deep learning. Nevertheless, machine learning is not only a technology. Given a task, machine learning is a way of proceeding (a way of thinking), and as such can be approached from different perspectives (points of view). This, in particular, will be the focus of this research. The entire work concentrates on machine learning, starting from different sources of data, e.g., signals and images, applied to different domains, e.g., Sport Science and Social History, and analyzed from different perspectives: from a non-data scientist point of view through tools and platforms; setting a problem stage from scratch; implementing an effective application for classification tasks; improving user interface experience through Data Visualization and eXtended Reality. In essence, not only in a quantitative task, not only in a scientific environment, and not only from a data-scientist perspective, machine (and deep) learning can do the difference.

I beni relazionali nella ricerca sociologica: che cosa sono e quali effetti producono

This paper studies relational goods as immaterial assets creating real effects in society. The work starts answering to this question: what kind of effects do relational goods produce? After an accurate literature examination we suppose relational goods are social relations of second order. In the hypotesis they come from the emergence of two distinct social relations: interpersonal and reflexive relations. We describe empirical evidences of these emergent assets in social life and we test the effects they produce with a model. In the work we focus on four targets. First of all we describe the emergence of relational goods through a mathematical model. Then we individualize social realities where relational goods show evident effects and we outline our scientific hypotesis. The following step consists in the formulation of empirical tests. At last we explain final results. Our aim is to set apart the constitutive structure of relational goods into a checkable model coherently with the empirical evidences shown in the research. In the study we use multi-variate analysis techniques to see relational goods in a new way and we use qualitative and quantitative strategies. Relational goods are analysed both as dependent and independent variable in order to consider causative factors acting in a black-box model. Moreover we analyse effects of relational goods inside social spheres, especially in third sector and capitalistic economy. Finally we attain to effective indexes of relational goods in order to compare them with some performance indexes.

Quantifying the Economics of Medical Malpractice - A View from a Civil Law Perspective

Life is full of uncertainties. Legal rules should have a clear intention, motivation and purpose in order to diminish daily uncertainties. However, practice shows that their consequences are complex and hard to predict. For instance, tort law has the general objectives of deterring future negligent behavior and compensating the victims of someone else's negligence. Achieving these goals are particularly difficult in medical malpractice cases. To start with, when patients search for medical care they are typically sick in the first place. In case harm materializes during the treatment, it might be very hard to assess if it was due to substandard medical care or to the patient's poor health conditions. Moreover, the practice of medicine has a positive externality on the society, meaning that the design of legal rules is crucial: for instance, it should not result in physicians avoiding practicing their activity just because they are afraid of being sued even when they acted according to the standard level of care. The empirical literature on medical malpractice has been developing substantially in the past two decades, with the American case being the most studied one. Evidence from civil law tradition countries is more difficult to find. The aim of this thesis is to contribute to the empirical literature on medical malpractice, using two civil law countries as a case-study: Spain and Italy. The goal of this thesis is to investigate, in the first place, some of the consequences of having two separate sub-systems (administrative and civil) coexisting within the same legal system, which is common in civil law tradition countries with a public national health system (such as Spain, France and Portugal). When this holds, different procedures might apply depending on the type of hospital where the injury took place (essentially whether it is a public hospital or a private hospital). Therefore, a patient injured in a public hospital should file a claim in administrative courts while a patient suffering an identical medical accident should file a claim in civil courts. A natural question that the reader might pose is why should both administrative and civil courts decide medical malpractice cases? Moreover, can this specialization of courts influence how judges decide medical malpractice cases? In the past few years, there was a general concern with patient safety, which is currently on the agenda of several national governments. Some initiatives have been taken at the international level, with the aim of preventing harm to patients during treatment and care. A negligently injured patient might present a claim against the health care provider with the aim of being compensated for the economic loss and for pain and suffering. In several European countries, health care is mainly provided by a public national health system, which means that if a patient harmed in a public hospital succeeds in a claim against the hospital, public expenditures increase because the State takes part in the litigation process. This poses a problem in a context of increasing national health expenditures and public debt. In Italy, with the aim of increasing patient safety, some regions implemented a monitoring system on medical malpractice claims. However, if properly implemented, this reform shall also allow for a reduction in medical malpractice insurance costs. This thesis is organized as follows. Chapter 1 provides a review of the empirical literature on medical malpractice, where studies on outcomes and merit of claims, costs and defensive medicine are presented. Chapter 2 presents an empirical analysis of medical malpractice claims arriving to the Spanish Supreme Court. The focus is on reversal rates for civil and administrative decisions. Administrative decisions appealed by the plaintiff have the highest reversal rates. The results show a bias in lower administrative courts, which tend to focus on the State side. We provide a detailed explanation for these results, which can rely on the organization of administrative judges career. Chapter 3 assesses predictors of compensation in medical malpractice cases appealed to the Spanish Supreme Court and investigates the amount of damages attributed to patients. The results show horizontal equity between administrative and civil decisions (controlling for observable case characteristics) and vertical inequity (patients suffering more severe injuries tend to receive higher payouts). In order to execute these analyses, a database of medical malpractice decisions appealed to the Administrative and Civil Chambers of the Spanish Supreme Court from 2006 until 2009 (designated by the Spanish Supreme Court Medical Malpractice Dataset (SSCMMD)) has been created. A description of how the SSCMMD was built and of the Spanish legal system is presented as well. Chapter 4 includes an empirical investigation of the effect of a monitoring system for medical malpractice claims on insurance premiums. In Italy, some regions adopted this policy in different years, while others did not. The study uses data on insurance premiums from Italian public hospitals for the years 2001-2008. This is a significant difference as most of the studies use the insurance company as unit of analysis. Although insurance premiums have risen from 2001 to 2008, the increase was lower for regions adopting a monitoring system for medical claims. Possible implications of this system are also provided. Finally, Chapter 5 discusses the main findings, describes possible future research and concludes.

Law, Informal Institutions and Trust: an Experimental Perspective

This dissertation has studied how legal and non-legal mechanisms affect the levels of trust and trustworthiness in an economy, and whether and when subtle psychological factors are crucial for establishing trust and even for recovering trust from a breach of contract. The first Chapter has addressed the question of whether formal legal enforcement crowds out or crowds in the amount of trust in a society. We find that formal legal mechanisms, especially formal contracts backed by a powerful authority, normally undermine trust except when they are perceived as legitimate, or when there are no strong social norms of fairness (i.e. the population in a society is considerably heterogeneous), or when the environment in which repeated commercial relationships take place becomes highly uncertain. The second Chapter has examined whether the endogenous adoption of a collective punishment institution can help a society coordinate on an efficient outcome, characterized by high levels of trust and trustworthiness. The experimental results show that the endogenous introduction of collective punishment by means of a majority-voting rule does not significantly improve coordination on the efficient equilibrium. Not all subjects seem to be able to anticipate the change in behavior induced by the introduction of the mechanism, and a majority of them vote against it. The third Chapter has explored whether high-trustors adapt their behavior in response to others’ trustworthiness or untrustworthiness more quickly, which in turn supports them to maintain higher default expectations of others’ trustworthiness relative to low-trustors. Our experimental results reveal that high-trustors are better than low-trustors at predicting others’ trustworthiness because they are less susceptible to the anticipated aversive emotions aroused by the potential betrayal and thereby have a higher willingness to acquire the valuable information about their partner’s actions.

Exact and heuristic algorithms for the integrated planning of multi-energy systems

The aim of this thesis is to present exact and heuristic algorithms for the integrated planning of multi-energy systems. The idea is to disaggregate the energy system, starting first with its core the Central Energy System, and then to proceed towards the Decentral part. Therefore, a mathematical model for the generation expansion operations to optimize the performance of a Central Energy System system is first proposed. To ensure that the proposed generation operations are compatible with the network, some extensions of the existing network are considered as well. All these decisions are evaluated both from an economic viewpoint and from an environmental perspective, as specific constraints related to greenhouse gases emissions are imposed in the formulation. Then, the thesis presents an optimization model for solar organic Rankine cycle in the context of transactive energy trading. In this study, the impact that this technology can have on the peer-to-peer trading application in renewable based community microgrids is inspected. Here the consumer becomes a prosumer and engages actively in virtual trading with other prosumers at the distribution system level. Moreover, there is an investigation of how different technological parameters of the solar Organic Rankine Cycle may affect the final solution. Finally, the thesis introduces a tactical optimization model for the maintenance operations’ scheduling phase of a Combined Heat and Power plant. Specifically, two types of cleaning operations are considered, i.e., online cleaning and offline cleaning. Furthermore, a piecewise linear representation of the electric efficiency variation curve is included. Given the challenge of solving the tactical management model, a heuristic algorithm is proposed. The heuristic works by solving the daily operational production scheduling problem, based on the final consumer’s demand and on the electricity prices. The aggregate information from the operational problem is used to derive maintenance decisions at a tactical level.

The interplay of multiplicity and effective energy for (multi) strange hadron production in pp collisions at the LHC

The enhanced production of strange hadrons in heavy-ion collisions relative to that in minimum-bias pp collisions is historically considered one of the first signatures of the formation of a deconfined quark-gluon plasma. At the LHC, the ALICE experiment observed that the ratio of strange to non-strange hadron yields increases with the charged-particle multiplicity at midrapidity, starting from pp collisions and evolving smoothly across interaction systems and energies, ultimately reaching Pb-Pb collisions. The understanding of the origin of this effect in small systems remains an open question. This thesis presents a comprehensive study of the production of $K^{0}_{S}$, $\Lambda$ ($\bar{\Lambda}$) and $\Xi^{-}$ ($\bar{\Xi}^{+}$) strange hadrons in pp collisions at $\sqrt{s}$ = 13 TeV collected in LHC Run 2 with ALICE. A novel approach is exploited, introducing, for the first time, the concept of effective energy in the study of strangeness production in hadronic collisions at the LHC. In this work, the ALICE Zero Degree Calorimeters are used to measure the energy carried by forward emitted baryons in pp collisions, which reduces the effective energy available for particle production with respect to the nominal centre-of-mass energy. The results presented in this thesis provide new insights into the interplay, for strangeness production, between the initial stages of the collision and the produced final hadronic state. Finally, the first Run 3 results on the production of $\Omega^{\pm}$ ($\bar{\Omega}^{+}$) multi-strange baryons are presented, measured in pp collisions at $\sqrt{s}$ = 13.6 TeV and 900 GeV, the highest and lowest collision energies reached so far at the LHC. This thesis also presents the development and validation of the ALICE Time-Of-Flight (TOF) data quality monitoring system for LHC Run 3. This work was fundamental to assess the performance of the TOF detector during the commissioning phase, in the Long Shutdown 2, and during the data taking period.