L’abitare come relazione sociale: il significato della casa e i processi di coesione sociale di vicinato

Se le trasformazioni sociali in atto tendono a esasperare il senso di incertezza, sradicamento ed individualismo, sussistono pratiche che si contrappongono alle tendenze dominanti, finalizzate a ricucire i legami sociali su scala locale. La progettazione urbano-architettonica interiorizza il nuovo bisogno di comunità originando soluzioni abitative tese a favorire gli scambi informali fra vicini, facendo leva sul concetto di capitale sociale, attaccamento al quartiere, identità del luogo e partecipazione. La casa, simbolo di stabilità e sicurezza ma anche di privacy, privatismo familiare, diventa sempre più oggetto di studi, domanda sociale e intervento politico. Soprattutto è sempre più intesa come un nodo di relazioni familiari in una rete di relazioni sociali più ampie. Casa e quartiere incidono nella esperienza di benessere e socialità familiare? In che modo gli spazi urbani e architettonici influenzano la coesione sociale? Quale il ruolo degli abitanti nello sviluppare socialità e integrazione? Sono queste le domande che ci siamo posti per rilevare le dinamiche sociali e culturali dell’abitare attraverso uno studio di caso condotto in due quartieri simili. Dalla ricerca emerge come il significato della casa non sia univoco ma cambi rispetto al ciclo di vita familiare e a quello economico e ciò incide nella partecipazione alle attività di quartiere. Mostriamo inoltre come lo spazio fisico costruito crea importanti opportunità per gli scambi informali e per il benessere familiare e individuale dei bambini ma che, il contesto sociale sia una discriminate fondamentale. Nel quartiere dove è presente una organizzazione di abitanti il numero delle relazioni di vicinato aumenta, cambiano anche la qualità delle relazioni e le distanze fisiche fra i vicini. Emerge inoltre che la reciprocità è il principale strumento di costruzione della coesione comunitaria interna e crea un atteggiamento di apertura e fiducia che va al di là dei confini di quartiere.

Characterization of DNA sequence properties through network and statistical approaches

In this thesis we will see that the DNA sequence is constantly shaped by the interactions with its environment at multiple levels, showing footprints of DNA methylation, of its 3D organization and, in the case of bacteria, of the interaction with the host organisms. In the first chapter, we will see that analyzing the distribution of distances between consecutive dinucleotides of the same type along the sequence, we can detect epigenetic and structural footprints. In particular, we will see that CG distance distribution allows to distinguish among organisms of different biological complexity, depending on how much CG sites are involved in DNA methylation. Moreover, we will see that CG and TA can be described by the same fitting function, suggesting a relationship between the two. We will also provide an interpretation of the observed trend, simulating a positioning process guided by the presence and absence of memory. In the end, we will focus on TA distance distribution, characterizing deviations from the trend predicted by the best fitting function, and identifying specific patterns that might be related to peculiar mechanical properties of the DNA and also to epigenetic and structural processes. In the second chapter, we will see how we can map the 3D structure of the DNA onto its sequence. In particular, we devised a network-based algorithm that produces a genome assembly starting from its 3D configuration, using as inputs Hi-C contact maps. Specifically, we will see how we can identify the different chromosomes and reconstruct their sequences by exploiting the spectral properties of the Laplacian operator of a network. In the third chapter, we will see a novel method for source clustering and source attribution, based on a network approach, that allows to identify host-bacteria interaction starting from the detection of Single-Nucleotide Polymorphisms along the sequence of bacterial genomes.

Analysis of technological accidents triggered by natural events (Natech) in the perspective of climate change

The severe accidents deriving from the impact of natural events on industrial installations have become a matter of growing concern in the last decades. In the literature, these events are typically referred to as Natech accidents. Several peculiarities distinguish them from conventional industrial accidents caused by internal factors, such as the possible occurrence of multiple simultaneous failures, and the enhanced probability of cascading events. The research project provides a comprehensive overview of Natech accidents that occurred in the Chemical and Process Industry, allowing for the identification of relevant aspects of Natech events. Quantified event trees and probability of ignition are derived from the collected dataset, providing a step forward in the quantitative risk assessment of Natech accidents. The investigation of past Natech accidents also demonstrated that wildfires may cause technological accidents. Climate change and global warming are promoting the conditions for wildfire development and rapid spread. Hence, ensuring the safety of industrial facilities exposed to wildfires is paramount. This was achieved defining safety distances between wildland vegetation and industrial equipment items. In addition, an innovative methodology for the vulnerability assessment of Natech and Domino scenarios triggered by wildfires was developed. The approach accounted for the dynamic behaviour of wildfire events and related technological scenarios. Besides, the performance of the emergency response and the related intervention time in the case of cascading events caused by natural events were evaluated. Overall, the tools presented in this thesis represent a step forward in the Quantitative Risk Assessment of Natech accidents. The methodologies developed also provide a solid basis for the definition of effective strategies for risk mitigation and reduction. These aspects are crucial to improve the resilience of industrial plants to natural hazards, especially considering the effects that climate change may have on the severity of such events.