Social aspects of organic agriculture and other multifunctional benefits - Successful EU models compared with possibilities for organic developments in Croatia

Main objective of the dissertation is to illustrate how social and educational aspects (in close interaction with other multifunctional aspects in organic agriculture) which are developed on different multifunctional organic farms in Italy and Netherlands, as well as established agricultural policy frameworks in these countries, can be compared with the situation in Croatian organics and can contribute to further developent of organic issues in the Repubic of Croatia. So, through different chapters, the dissertation describes the performance of organic agriculture sectors in Italy, Netherlands and Croatia within the national agricultural policy frameworks, it analyzes the role of national institutions and policy in Croatia in connection with Croatia's status of candidate country for enterance into EU and harmonization of legislation with the CAP, as well as analyzes what is the role of national authorities, universities, research centres, but also of private initiatives, NGOs and cooperatives in organic agriculture in Netherlands, Italy and Croatia. Its main part describes how social and educational aspects are interacting with other multifunctional aspects in organic agriculture and analyzes the benefits and contribution of multifunctional activites performed on organic farms to education, healthy nourishment, environment protection and health care. It also assess the strengths and weaknesses of organic agriculture in all researched countries. The dissertation concludes with development opportunities for multifunctional organic agriculture in Croatia, as well as giving perspectives and recommendations for different approaches on the basis of experiences learned from successful EU models accompanied with some personal ideas and proposals.

An equilibrium approach to modelling social interaction

The aim of this work is to put forward a statistical mechanics theory of social interaction, generalizing econometric discrete choice models. After showing the formal equivalence linking econometric multinomial logit models to equilibrium statical mechanics, a multi- population generalization of the Curie-Weiss model for ferromagnets is considered as a starting point in developing a model capable of describing sudden shifts in aggregate human behaviour. Existence of the thermodynamic limit for the model is shown by an asymptotic sub-additivity method and factorization of correlation functions is proved almost everywhere. The exact solution for the model is provided in the thermodynamical limit by nding converging upper and lower bounds for the system's pressure, and the solution is used to prove an analytic result regarding the number of possible equilibrium states of a two-population system. The work stresses the importance of linking regimes predicted by the model to real phenomena, and to this end it proposes two possible procedures to estimate the model's parameters starting from micro-level data. These are applied to three case studies based on census type data: though these studies are found to be ultimately inconclusive on an empirical level, considerations are drawn that encourage further refinements of the chosen modelling approach, to be considered in future work.

Social Housing e Periferie Urbane: Riqualificazione e tecniche Comunicative

Il campo d’interesse della ricerca è stato l’attuale processo di ricentralizzazione del Social Housing nelle periferie urbane in una parte del contesto internazionale, che sembra stia portando le città a ricrearsi e ripensarsi grazie alla presa di coscienza delle differenze esistenti, rispetto al passato, nei nuovi processi di trasformazione nei quali la città è intesa sia come spazio costruito ma anche sociale. In virtù di quest’ultimi due aspetti complementari della città, oggi, il ruolo della periferia contemporanea sembra essere diversamente interpretato, così come gli interventi di riqualificazione di tipo assistenziale - migliorativo tenderebbero a trasformarne i suoi caratteri alla ricerca del “modello di città”. L’interesse alla tematica è inoltre scaturito dalla constatazione che alla base della crisi dei modelli d’intervento pubblico starebbero sia l’insostenibilità economica ma soprattutto l’errata lettura dei bisogni delle famiglie nella loro specificità e diversità e che in tal senso l’eventuale partecipazione della cittadinanza costituirebbe effettivamente una proposta valida, anche per risolvere la crescente domanda abitativa che si pone a livello mondiale. L’obiettivo della ricerca è stato quello d’analizzare, nel contesto internazionale del Social Housing, le caratteristiche di partecipazione e sussidiarietà che connotano particolarmente gli interventi di riqualificazione destinati a famiglie economicamente carenti, nello specifico analizzando i metodi e gli strumenti atti alla comunicazione partecipativa del progetto in aree urbane periferiche italiane e brasiliane. Nella prima e seconda fase della ricerca è stato svolto, rispettivamente, un lavoro di analisi bibliografica sul tema dell’emergenza casa e sulle nuove politiche abitative di sviluppo urbano ed uno specifico sulla tematica della riqualificazione partecipata del Social Housing in aree della periferia urbana, infine nella terza fase sono stati analizzati i casi di studio prescelti dando rilievo all’analisi delle caratteristiche e requisiti prestazionali delle tecniche partecipative di rappresentazione - comunicazione, più idonee ad influenzare positivamente il suddetto processo.

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.

Social housing: interventions of densification in urban regeneration (1995-2010). Critical analysis of strategies adopted in Milan, London, São Paulo

The prospect of the continuous multiplication of life styles, the obsolescence of the traditional typological diagrams, the usability of spaces on different territorial scales, imposes on contemporary architecture the search for new models of living. Limited densities in urban development have produced the erosion of territory, the increase of the harmful emissions and energy consumption. High density housing cannot refuse the social emergency to ensure high quality and low cost dwellings, to a new people target: students, temporary workers, key workers, foreign, young couples without children, large families and, in general, people who carry out public services. Social housing strategies have become particularly relevant in regenerating high density urban outskirts. The choice of this research topic derives from the desire to deal with the recent accommodation emergency, according to different perspectives, with a view to give a contribution to the current literature, by proposing some tools for a correct design of the social housing, by ensuring good quality, cost-effective, and eco-sustainable solutions, from the concept phase, through management and maintenance, until the end of the building life cycle. The purpose of the thesis is defining a framework of guidelines that become effective instruments to be used in designing the social housing. They should also integrate the existing regulations and are mainly thought for those who work in this sector. They would aim at supporting students who have to cope with this particular residential theme, and also the users themselves. The scientific evidence of either the recent specialized literature or the solutions adopted in some case studies within the selected metropolitan areas of Milan, London and São Paulo, it is possible to identify the principles of this new design approach, in which the connection between typology, morphology and technology pursues the goal of a high living standard.

The role of proactive coping strategies and perceived health status for Social well-being and life-project in old age.

The latter part of the 20th century was a period characterized by a fundamental demographic transition of western society. This substantial and structural demographic change proposes several challenges to contemporary society and fosters the emergence of new issues and challenges. Among these, none is more crucial than the comprehension of the mechanisms and the processes that lead people to positive aging. Rowe and Kahn’s model of successful aging highlights the interplay between social engagement with life, health, and functioning for a positive aging experience. Other systemic models of successful aging (Kahana et al., 1996; 2003; Stevernik et al., 2006) emphasize the role of internal and external resources for attaining positive aging. Among these, the proactive coping strategies are indicated as important active strategies for avoiding the depletion of resources, counterbalancing the declines and maintaining social and civic involvement. The study has analyzed the role of proactive coping strategies for two facets of positive aging, the experience of a high social well-being and the presence of personal projects in fundamental life domains. As expected, the proactive coping strategies, referred to as the active management of the environment, the accumulation of resources and the actualization of human potentials are confirmed as positive predictors of high level of social well-being and of many personal projects focused on family, culture, leisure time, civic and social participation. Perceived health status give a significant contribution only to the possession of many personal projects. Gender and level of school education give also a significant contribution to these two dimensions of positive aging, highlighting how positive aging is rooted not only in the possession of personal resources, but also in historical models of education and in positive longitudinal chains related to early development.

Embedded representations of social interactions

Social interactions have been the focus of social science research for a century, but their study has recently been revolutionized by novel data sources and by methods from computer science, network science, and complex systems science. The study of social interactions is crucial for understanding complex societal behaviours. Social interactions are naturally represented as networks, which have emerged as a unifying mathematical language to understand structural and dynamical aspects of socio-technical systems. Networks are, however, highly dimensional objects, especially when considering the scales of real-world systems and the need to model the temporal dimension. Hence the study of empirical data from social systems is challenging both from a conceptual and a computational standpoint. A possible approach to tackling such a challenge is to use dimensionality reduction techniques that represent network entities in a low-dimensional feature space, preserving some desired properties of the original data. Low-dimensional vector space representations, also known as network embeddings, have been extensively studied, also as a way to feed network data to machine learning algorithms. Network embeddings were initially developed for static networks and then extended to incorporate temporal network data. We focus on dimensionality reduction techniques for time-resolved social interaction data modelled as temporal networks. We introduce a novel embedding technique that models the temporal and structural similarities of events rather than nodes. Using empirical data on social interactions, we show that this representation captures information relevant for the study of dynamical processes unfolding over the network, such as epidemic spreading. We then turn to another large-scale dataset on social interactions: a popular Web-based crowdfunding platform. We show that tensor-based representations of the data and dimensionality reduction techniques such as tensor factorization allow us to uncover the structural and temporal aspects of the system and to relate them to geographic and temporal activity patterns.

Data surveillance for infectious diseases: models, complex networks and machine learning

In this thesis, we investigate the role of applied physics in epidemiological surveillance through the application of mathematical models, network science and machine learning. The spread of a communicable disease depends on many biological, social, and health factors. The large masses of data available make it possible, on the one hand, to monitor the evolution and spread of pathogenic organisms; on the other hand, to study the behavior of people, their opinions and habits. Presented here are three lines of research in which an attempt was made to solve real epidemiological problems through data analysis and the use of statistical and mathematical models. In Chapter 1, we applied language-inspired Deep Learning models to transform influenza protein sequences into vectors encoding their information content. We then attempted to reconstruct the antigenic properties of different viral strains using regression models and to identify the mutations responsible for vaccine escape. In Chapter 2, we constructed a compartmental model to describe the spread of a bacterium within a hospital ward. The model was informed and validated on time series of clinical measurements, and a sensitivity analysis was used to assess the impact of different control measures. Finally (Chapter 3) we reconstructed the network of retweets among COVID-19 themed Twitter users in the early months of the SARS-CoV-2 pandemic. By means of community detection algorithms and centrality measures, we characterized users’ attention shifts in the network, showing that scientific communities, initially the most retweeted, lost influence over time to national political communities. In the Conclusion, we highlighted the importance of the work done in light of the main contemporary challenges for epidemiological surveillance. In particular, we present reflections on the importance of nowcasting and forecasting, the relationship between data and scientific research, and the need to unite the different scales of epidemiological surveillance.