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Emergency Communication and Crowdsourced Information: From Digital Noise to Actionable Intelligence
No full textNegli ultimi decenni, la diffusione delle tecnologie mobili e dei social media ha profondamente trasformato le dinamiche di scambio delle informazioni durante le emergenze. Agendo come veri e propri “sensori umani”, i cittadini producono continuamente grandi volumi di dati che possono accrescere la consapevolezza situazionale delle autorità competenti. Tuttavia, l’utilizzo operativo di tali informazioni rimane ancora limitato. Criticità legate all’affidabilità, alla verifica e alla rappresentatività dei dati ne ostacolano spesso l’integrazione nei flussi operativi della risposta alle emergenze, con il rischio di generare una rappresentazione distorta della situazione in atto. Muovendo da questi limiti, il presente progetto di dottorato analizza una specifica tipologia di informazione crowdsourced: i dati delle chiamate di emergenza, in particolare quelli raccolti attraverso il Numero Unico Europeo 112, che mette direttamente in contatto i cittadini con tutti i servizi di emergenza. L’obiettivo generale della ricerca è dimostrare come i dati delle chiamate di emergenza possano migliorare la consapevolezza situazionale, supportare i processi decisionali e contribuire allo sviluppo di sistemi di gestione delle crisi intelligenti e adattivi.
La tesi adotta una struttura articolata in articoli scientifici e si compone di quattro capitoli principali. Il primo capitolo definisce le basi concettuali e metodologiche della ricerca, mostrando come il livello informativo generato dalle chiamate di emergenza superi i dati provenienti dai social media sia in termini di qualità sia di volume. Il secondo capitolo approfondisce l’analisi valutando in che modo le chiamate di emergenza possano affinare e integrare il quadro situazionale prodotto dalle reti di sensori meteorologici. Il terzo capitolo va oltre le capacità spazio-temporali dei dati delle chiamate per esplorare come l’intelligenza collettiva emergente da tali informazioni possa orientare sia le strategie operative sia le politiche più ampie di comunicazione del rischio. Il quarto e ultimo capitolo esamina se le potenzialità individuate nel corso della tesi possano essere effettivamente tradotte in applicazioni operative nei prossimi anni, indagando se le centrali di risposta alle emergenze siano pronte a evolvere da semplici unità di smistamento delle chiamate a infrastrutture avanzate di monitoraggio territoriale, supportate da tecnologie emergenti come l’intelligenza artificiale.
Nel complesso, i risultati dimostrano che i dati delle chiamate di emergenza superano i principali limiti delle informazioni provenienti dai social media, offrendo registrazioni affidabili, accuratamente geolocalizzate e automaticamente verificate, in grado di arricchire i sistemi di monitoraggio tradizionali con informazioni in tempo reale sulle condizioni locali. Questa ricerca contribuisce al crescente filone di studi sull’utilizzo dei contenuti generati dai cittadini a supporto della protezione civile, ponendo le basi per futuri sistemi di supporto alle decisioni di tipo ibrido, capaci di integrare le reti sensoriali convenzionali con informazioni di origine sociale, aprendo la strada a modelli di gestione delle emergenze più adattivi, informati dai dati e incentrati sui cittadini.In recent decades, the proliferation of mobile technologies and social media has profoundly transformed the dynamics of information exchange during emergencies. Acting as “human sensors,” citizens continuously produce vast volumes of data that can enhance the situational awareness of authorities. However, the operational uptake of such data remains limited. Concerns related to reliability, verification, and representativeness often hinder their integration into emergency response workflows, potentially leading to a distorted situational picture.
Building upon these limitations, this PhD project investigates a specific type of crowdsourced information – emergency call data – specifically those collected through the European 112 number, which directly connects citizens to all emergency services. The overarching aim of the project is to demonstrate how emergency call data can enhance situational awareness, inform decision-making, and contribute to the development of intelligent and adaptive crisis management systems.
This thesis adopts a paper-based structure comprising four main chapters. The first chapter establishes the conceptual and methodological foundations, demonstrating that the information layer generated by emergency calls surpasses social media data in terms of both quality and volume. The second chapter deepens the analysis by assessing how emergency calls can refine and complement the situational picture produced by meteorological sensor networks. The third chapter moves beyond the spatio-temporal capabilities of emergency call data to explore how the collective intelligence emerging from these calls can inform both operational strategies and broader risk communication policies. The fourth and final chapter examines whether the potentials identified throughout the thesis can be effectively operationalized in the coming years. It investigates whether emergency response centers are ready to evolve from simple dispatching units into advanced territorial monitoring infrastructures, supported by emerging technologies such as artificial intelligence.
Overall, the findings demonstrate that emergency call data overcome the main limitations of social media information, offering reliable, precisely geolocated, and automatically verified records that enrich traditional monitoring systems with real-time insights into local conditions. This research contributes to the growing body of literature on the use of citizen-generated content for civil protection purposes, laying the foundation for future hybrid decision-support systems that integrate conventional sensor networks with socially generated information—paving the way toward more adaptive, data-informed, and citizen-centered models of emergency management
Ultrafast carrier dynamics and electronic properties of PtSe2/MoSe2and WSe22D TMDC layered structures on mica: combined THz spectroscopy and DFT study
No full textA detailed investigation of structure, electronic and optical properties of two transition metal dichalcogenide (TMDC) structures is presented in this study. Sample 1 consists of epitaxially grown bilayer of PtSe2 (2 monolayers) on MoSe2 (1 monolayer) deposited on mica substrate - reported here for the first time. Sample 2 comprises a trilayer of WSe2 grown on mica. The photoconductivities of both samples were characterized using optical pump-terahertz probe spectroscopy under above- and near-bandgap excitations at 400 nm and 800 nm. Both structures exhibit rapid carrier generation and relaxation dynamics, with notable variations depending on excitation wavelength and structures. Complementary density functional theory (DFT) calculations are performed to evaluate the electronic and optical properties of free-standing single layers of MoSe2, PtSe2 and WSe2 and their combined structures corresponding to Sample 1 and Sample 2. The experimental results show strong agreement with calculated band structures. This consistency between experiment and theory underscores the potential of these TMDC structures for future applications in terahertz and high-frequency electronic devices
Second cross-clamp in less invasive mitral valve repair for degenerative mitral regurgitation: Predictors and outcomes
No full textObjective: To evaluate the incidence, echocardiographic patterns, operative strategies, and results of patients receiving a second cross-clamping in the large population of the Mini Mitral International Registry. Methods: We examined 4577 patients with degenerative mitral regurgitation (MR) who underwent less invasive mitral repair. Patients with nondegenerative disease, planned valve replacement, and surgery without cross-clamping were excluded. Multivariable logistic regression model was applied to investigate predictors of second cross-clamping and the relationship between second cross-clamping and outcomes. Results: Second cross-clamping was used in 128 cases (2.8%). Reasons for re-cross-clamping included residual pathology in 71.9% of the patients (n = 92) and systolic anterior motion (SAM) in 28.1% (n = 36). Re-repair was performed in 104 patients (81.3%), and replacement was performed in 24 (18.7%). After re-repair, 92 patients (94.9%) had no or mild MR, 4 patients (4.1%) had moderate MR, and 1 patient (1%) had severe MR. A residual SAM was observed in 2 patients (2.3%). Bileaflet prolapse (odds ratio [OR], 2.21) and predicted risk of SAM (OR, 3.04) were identified as risk factors for second cross-clamping. No association between second cross-clamping and mortality or major postoperative complications was found; however, second cross-clamping was associated with an increased risk of respiratory insufficiency (OR, 4.6) and longer intensive care unit (ICU) stay (β = 0.35). Conclusions: Second cross-clamping after less invasive mitral repair is infrequent but may be required, particularly in patients with bileaflet pathology or at increased risk of SAM. Most re-repairs were successful, with <20% of patients requiring replacement. Second cross-clamping was associated with higher risk of respiratory insufficiency and prolonged ICU stay
UPREGULATION OF PARAOXONASE-2 IN CLEAR CELL RENAL CELL CARCINOMA: POTENTIAL FOR ANTICANCER THERAPY
No full textIl carcinoma renale a cellule chiare (ccRCC) è il sottotipo più comune tra le neoplasie renali ed è caratterizzato sia da una scarsa sensibilità alla chemioterapia e radioterapia che da una grande capacità di metastatizzare. Nonostante i recenti progressi nell’identificazione di nuove molecole bersaglio, la prognosi dei pazienti con ccRCC rimane negativa ed un terzo dei pazienti con carcinoma a cellule renali presenta malattia metastatica al momento della diagnosi. Pertanto, è necessario scoprire nuove molecole per la diagnosi precoce, per una prognosi più accurata o per la sviluppo di una terapia mirata. In questo studio, abbiamo focalizzato la nostra attenzione sull'enzima Paraoxonasi-2 (PON2), che appartiene alla famiglia delle paraoxonasi umane (PON). PON2 è un enzima intracellulare legato alla membrana, espresso in modo ubiquitario nei tessuti umani, la cui upregolazione è stata descritta in diversi tipi di tumori solidi, suggerendo il suo possibile coinvolgimento nella progressione del cancro e nella chemio-radioresistenza. Per approfondire il coinvolgimento dell’enzima PON2 nel metabolismo delle cellule tumorali, le linee cellulari ccRCC umane sono state trasfettate con vettori plasmidici codificanti short hairpin RNA (shRNA) che hanno come target l’mRNA di PON2. Successivamente sono stati valutati gli effetti del silenziamento del gene PON2 sulla vitalità cellulare, sulla migrazione e sulla sensibilità al trattamento chemioterapico. I nostri risultati hanno dimostrato che PON2 potrebbe rappresentare un interessante bersaglio terapeutico per il ccRCC, poiché la downregolazione dell’enzima ha comportato una diminuzione della capacità proliferativa e di migrazione cellulare, e una maggiore sensibilità delle cellule alla chemioterapia.Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal malignancies which is characterized by lack of sensitivity to chemo- and radiotherapy and a marked ability to metastasize. Despite recent advances in identifying novel molecular targets, the prognosis of ccRCC patients remains poor, and one-third of ccRCC patients show metastatic disease at diagnosis. Hence, identifying novel molecules for diagnosis, more accurate prognosis or for targeted therapy is mandatory. In this study, we focused on the enzyme Paraoxonase-2 (PON2) which belongs to human paraoxonase (PON) family. PON2 is an intracellular membrane-bound enzyme ubiquitously expressed in human tissues whose upregulation was described in a variety of solid tumors suggesting its possible role in cancer progression and chemo-radio-resistance. To explore the role of PON2 in tumor cell metabolism, human ccRCC cell lines were transfected with plasmid vectors coding short hairpin RNAs targeting PON2 transcript. The effects of PON2 gene silencing on cell viability, migration, and sensitivity to chemotherapeutic treatment were subsequently assessed. Our results demonstrated that PON2 may represent an interesting therapeutic target for ccRCC since enzyme downregulation resulted in a decreased cell proliferation and migration ability, and enhanced cell sensitivity to chemotherapy
Wearable measurement systems for cardiorespiratory and biomechanical monitoring
No full textNegli ultimi dieci anni, le tecnologie indossabili sono diventate uno strumento fondamentale per il monitoraggio continuo delle funzioni fisiologiche e biomeccaniche umane. La loro crescente diffusione in ambito sanitario e sportivo riflette la necessità di sistemi non invasivi e discreti, in grado di fornire dati affidabili al di fuori di ambienti di laboratorio controllati.
Parametri cardiorespiratori quali la frequenza cardiaca (HR) e la frequenza respiratoria (BR) riflettono l’attività integrata dei sistemi cardiovascolare e respiratorio e i meccanismi autonomici che ne regolano l’adattamento alle richieste fisiologiche. I dispositivi wearable capaci di acquisire segnali elettrocardiografici (ECG) e respiratori consentono un monitoraggio continuo e in tempo reale nella vita quotidiana, supportando l’identificazione precoce di alterazioni fisiologiche e il follow-up a lungo termine.
Allo stesso modo, le unità di misura inerziali (IMU) rivestono un ruolo sempre più rilevante nell’analisi biomeccanica in ambito sportivo e quotidiano. La loro capacità di acquisire il movimento in condizioni reali permette di valutare le prestazioni, la qualità del movimento, l’affaticamento e il rischio di infortunio con elevata validità ecologica.
L’obiettivo di questa tesi è contribuire al progresso del monitoraggio wearable in due ambiti: fisiologia cardiorespiratoria e biomeccanica applicata allo sport.
Il primo filone di ricerca riguarda il monitoraggio fisiologico. Un dispositivo ECG wireless (WECG) è stato valutato in condizioni di riposo e dinamiche per caratterizzarne le prestazioni metrologiche e la capacità di estrarre HR e caratteristiche morfologiche clinicamente rilevanti. Successivamente, è stato progettato, realizzato e caratterizzato un sensore respiratorio basato su un composito stampato in 3D di poliuretano termoplastico e carbon black (CB-TPU), in grado di rilevare i movimenti toracici durante la respirazione. Sebbene studiati separatamente, questi dispositivi rappresentano passi fondamentali verso un sistema wearable integrato per la valutazione cardiopolmonare.
Il secondo filone di ricerca affronta il monitoraggio biomeccanico attraverso la caratterizzazione metrologica di un sistema wearable basato su IMU, integrato in un gilet sportivo e posizionato nella regione dorsale superiore (T1–T3). Due studi sperimentali hanno valutato la durata del passo e l’altezza del salto. Inoltre, sono stati sviluppati modelli di machine learning per classificare i livelli di attività e rilevare azioni specifiche dello sport, potenziando le capacità del sistema per il monitoraggio in campo.Over the past decade, wearable technology has become a key tool for the continuous monitoring of human physiological and biomechanical functions. Its growing adoption in healthcare and sports science reflects the demand for unobtrusive systems capable of providing reliable data outside controlled laboratory environments.
Cardiorespiratory parameters such as heart rate (HR) and breathing rate (BR) reflect the integrated activity of the cardiovascular and respiratory systems and their autonomic regulation. Wearable devices capable of acquiring electrocardiographic (ECG) and respiratory signals enable real-time and continuous monitoring in daily life, supporting early detection of physiological alterations and long-term health assessment.
Similarly, inertial measurement units (IMUs) play an increasingly important role in biomechanical analysis in both sports and daily contexts. Their ability to capture movement under real-world conditions allows the evaluation of performance, movement quality, fatigue, and injury risk with high ecological validity.
The aim of this thesis is to contribute to wearable monitoring in two domains: cardiorespiratory physiology and sports biomechanics.
The first research direction focuses on physiological monitoring. A wireless ECG device (WECG) was evaluated in resting and dynamic conditions to characterize its metrological performance and its ability to extract HR and clinically relevant morphological features. Subsequently, a respiratory sensor based on a 3D-printed composite of thermoplastic polyurethane and carbon black (CB-TPU) was designed, produced, and characterized for detecting chest movements during breathing. Although investigated separately, these devices represent foundational steps toward an integrated cardiopulmonary wearable system.
The second research direction addresses biomechanical monitoring through the metrological characterization of an IMU-based wearable system integrated into a sports vest and positioned on the upper back (T1–T3). Two experimental studies evaluated stride duration and jump height. Furthermore, machine learning models were developed to classify activity levels and detect sport-specific actions, enhancing the system’s capabilities for field-based sports monitoring
From Sensing to Understanding: A Spatial Intelligence Paradigm for 3D Artificial Intelligence
No full textRecent advances in artificial intelligence, computer vision, and computer graphics have allowed artificial systems to evolve from passive visual perception toward a deeper, structured understanding of three-dimensional environments. This evolution has transformed the concept of spatial intelligence, shifting it from a notion rooted purely in human reasoning to the computational domain. In this context, spatial intelligence is defined as the capability of an artificial system to perceive, represent, interpret, and act upon three-dimensional environments by integrating visual, spatial, and semantic information across the full pipeline. This progress has been shaped by the convergence of multiple disciplines, including computer vision, computer graphics, robotics, embodied agents, and generative world models. Nevertheless, current systems remain fragmented, excelling in specific tasks but lacking a cohesive, human-centered paradigm that links sensing, modeling, and deployment across domains. Building on this, this thesis introduces a spatial intelligence paradigm for 3D artificial intelligence, grounded in mature AI technologies and aimed at unifying sensing, neural synthesis, generative modeling, and interaction within a coherent, application-oriented approach.
Methodologically, the thesis is structured around three interconnected pillars: multimodal sensing, vision-language modeling, and real-world generalization. Within multimodal sensing, the work investigates how heterogeneous spatial data, ranging from multi-view images to 3D assets, can be transformed into coherent 3D representations using neural rendering and generative AI approaches. Two case studies are presented: an end-to-end neural rendering framework for fashion design based on Neural Radiance Fields and 3D Gaussian Splatting, and a comparative framework for cultural heritage that evaluates generative 3D methods in terms of both 2D visual quality and 3D structural fidelity.
The second pillar, vision-language modeling, explores how multimodal large language models and diffusion-based generators can bridge linguistic and spatial representations. This is demonstrated through two systems: an XR platform for context-aware, diffusion-driven 3D content generation, and a novel framework for visual reconstruction from EEG brain activity, combining neural decoding with multimodal generation and introducing a boosted reconstruction stage to enhance image quality. Both systems are validated through quantitative metrics and user-centered evaluations.
Finally, the real-world generalization pillar addresses the integration of spatial AI models into interactive, human-in-the-loop environments. Specifically, a system for single-image-to-3D generation, that combines multimodal reasoning, multi-view question answering, and iterative refinement through human feedback with a user interface is proposed, and an immersive analytics platform for fashion that incorporates 3D product interaction, visual analytics, and trend visualization within an XR environment.
Overall, this work presents a unified, operational paradigm for spatial intelligence, demonstrating how modern AI systems can be integrated, from sensing and representation to generation and interaction, across heterogeneous domains such as cultural heritage, fashion, and neuroscience. Beyond technical contributions, the thesis emphasizes the importance of human-centered design, interpretability, and interaction, positioning spatial intelligence not only as a computational capability, but as a collaborative interface between artificial systems and human creativity, cognition, and decision-making
Reinforcement Learning Meets Logic Programming : Towards Explainable AI
No full textThis paper introduces a neuro-symbolic framework designed to predict and explain subsequent facts from current observations. Facts are generated through causal relationships, which can be modeled by a set of propositional logic rules representing the domain knowledge. However, these rules remain unknown to the agent. By observing the facts, the agent constructs an approximation of them, which is then used to predict and explain new facts. The proposed framework can learn and adapt to different environments modeled by various forms of logic programs, also handling negation and recursion. Most notably, it can handle dynamic environments whose structure evolves over time. In these scenarios, the agent modifies its understanding of the environment to capture new observations, guaranteeing that its model of the domain knowledge remains up-to-date. To achieve this goal, our approach leverages the A2C (Advantage Actor-Critic) reinforcement learning algorithm. This choice allows us to integrate reinforcement learning principles into our logic framework. Through this research, we aspire to contribute to the development of explainable neuro-symbolic Artificial Intelligence systems in dynamic environments
The CB1 receptor: unraveling its dysregulation by endocrine disruptions in human osteoblasts and its physiological role in sperm cells
No full textThe endocannabinoid system (ECS) is a conserved regulatory network involved in the maintenance of cellular homeostasis, including that of bone and male reproductive system.
Although its role in skeletal biology remains not completely defined, increasing evidence suggests that ECS components, particularly the endocannabinoid receptor (CB1) receptor, contribute to osteoblast differentiation, extracellular matrix (ECM) remodeling and bone metabolism. On the other hand, endocrine disrupting chemicals (EDCs) such as bisphenol A (BPA) and perfluorooctanoic acid (PFOA) interfere with osteogenic and oxidative pathways and have been shown to affect ECS signaling, though the mechanisms remain unclear. In the first part of the PhD thesis, we examined how acute and chronic exposure to PFOA and BPA, alone or combined, affect osteoblast homeostasis with a focus on CB1 regulation. Using 2D and 3D hFOB1.19 models, the studies demonstrated that these contaminants alter spheroids morphology, ECM deposition and mineralization, and modulate antioxidant and osteogenic markers. Specifically, acute exposure to PFOA induced a transient CB1-related response linked to collagen remodeling, whereas chronic exposure disrupted ECM deposition and mineralization, independently of CB1 regulation, both after single and combined exposure to PFOA and BPA.
Regarding the reproductive system, CB1 localization and function were explored in spermatozoa. High-resolution imaging revealed previously unrecognized intracellular CB1 localization extending to the sperm nuclei, which is conserved across mammalian species and persists after the acrosome reaction. Functionally, CB1 activation through selective agonist restored histone H4K12 acetylation in asthenozoospermic samples, demonstrating its involvement in human sperm chromatin remodeling. The nuclear localization of CB1 in sperm was also confirmed in somatic cells, such as osteoblast and astrocytes, further suggesting potential transcriptional and /or epigenetic functions in these cells as well.
Overall, the results here obtained uncover novel mechanistic roles of CB1 in bone and sperm biology and also demonstrate its susceptibility to environmental contaminants such as BPA and PFOA
In vitro modeling of myometrial disorders microenvironment- challenges and methodological advances to unveil pathogenetic mechanism and therapeutic targets
No full textThree-dimensional culture systems provide more physiologically relevant models of uterine tissues than conventional two-dimensional monolayers, as they better preserve cell–cell and cell–matrix interactions and allow extracellular matrix (ECM) deposition within tissue-like architectures. Uterine smooth muscle tumors, including benign leiomyomas and malignant leiomyosarcomas, arise from the myometrium and pose a major clinical challenge, from highly prevalent fibroids to rare but aggressive sarcomas.
This thesis reports the development and characterization of 3D spheroid models of human myometrium, leiomyoma, and leiomyosarcoma generated by an agarose-based manual method and by extrusion-base bioprinting in commercial and in-house hydrogels. Phase-contrast and fluorescence microscopy, histological and histochemical staining, and Field Emission-Scanning Electron Microscopy demonstrated that these scaffolds support viable, proliferative, and structurally organized spheroids suitable for quantitative morphometric, ultrastructural and molecular analyses. These platforms were then used to investigate the endocrine disruptor bisphenol A (BPA) in uterine smooth muscle pathophysiology by assessing cell viability in 2D and 3D systems (MTT and PrestoBlue assays) and evaluating fibrogenic responses through COL1A1, fibronectin and activin A mRNA expression by RT-PCR and for fibronectin and COL1A1 protein expression by immunohistochemistry after exposure to biologically relevant BPA concentrations.
Overall, the data indicate that bioprinted 3D uterine spheroids constitute robust and versatile models to dissect ECM remodeling and endocrine disruption in myometrial tumors. In addition, preliminary findings suggest that low-dose BPA may contribute to the pathogenesis of myometrial neoplasms, particularly leiomyomas, reinforcing the need to integrate environmental endocrine disruptors into uterine tumor biology and risk assessment frameworks
Infrared Thermography Study of Thermal Footprints Generated by Ordinary and Extraordinary Respiratory Activities in Persons Wearing Face Masks
Get PDFThe airborne diffusion of saliva droplets during respiratory activities is one of the major factors in the spread of infections. During the COVID-19 pandemic, the use of protective face masks was essential to reduce the risk of infection and spread of SARS-CoV-2. The face mask is able to significantly reduce the saliva droplet emission in front of the person. However, the use of masks also produces a particle leakage towards the back of the person, which could increase the infection risk of people behind the subject. Most of the experimental investigations applied invasive and/or complex experimental techniques to evaluate the face masks leakage. The primary objective of this study is to develop a novel, non-invasive methodology for assessing rearward droplet emission associated with the use of protective face masks. Specifically, a thermographic analysis of the thermal footprint released during ordinary and extraordinary respiratory activities is presented, evaluating the maximum temperature, the detection time, and the spread area of the thermal footprint. Both surgical and FFP2 face masks were tested. Two different subjects were involved in the experimentation to evaluate the influence of face conformation. The findings indicate that the area influenced by droplet dispersion is larger when wearing a surgical mask compared to an FFP2 mask, with the highest recorded temperatures observed for the surgical mask. The thermal footprint was found to be strongly dependent on individual facial morphology and mask fit. Notably, the FFP2 mask also altered the position of the thermal footprint, which was primarily confined to the region near the neck