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    A deep learning framework for real-time forecasting of 2-D inundation maps: the FloodSformer model

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    This thesis aims to contribute to the advancement of data-driven models for flood forecasting, with a specific focus on developing and implementing a deep-learning model for real-time prediction of the spatiotemporal evolution of two-dimensional (2D) inundation maps over complex large topographies. Unlike traditional flood forecasting methods, which are often computationally intensive and time-consuming, the proposed model, named FloodSformer (FS), leverages state-of-the-art deep learning techniques, integrating autoencoder and transformer architectures. This combination enables the FS model to effectively extract and process complex spatiotemporal information from a sequence of consecutive water depth maps and upstream inflow discharges, to predict inundation maps of subsequent instants through an autoregressive procedure. The FS model has been rigorously tested across a diverse range of scenarios, including both dam-break scenarios and river flood events, considering a variety of synthetic and real-world case studies. To assess the model's applicability to practical flood forecasting, its performance has been measured in terms of both predictive accuracy and computational efficiency. In addition, extensive sensitivity analyses have been conducted to explore the influence of key hyperparameters: the types of flood events used for training and the spatial resolution of the maps. Datasets were numerically generated using a 2D hydrodynamic model. The results indicate that the FS model is capable of accurately forecasting long-duration flood events over complex and large-scale bathymetries, comprising up to millions of computational cells. Remarkably, FS achieves these results with computational times on the order of minutes, which is significantly lower than the physical time of the simulated events (with physical-to-computational time ratios up to 10,000). Furthermore, the model demonstrates predictive accuracy comparable to that of traditional physically based hydrodynamic models, achieving average root mean square errors in the range of 10-20 cm across different real-world test cases. The sensitivity analyses further indicate that larger and more diverse datasets significantly enhance the model's accuracy and generalization capabilities. Additionally, when compared to a state-of-the-art convolutional neural network architecture, the FS model consistently outperformed in terms of predictive accuracy of river flood scenarios over complex terrain topographies. In conclusion, the FS model is a versatile and high-performing tool for flood prediction, with significant potential for applications in flood risk management and emergency response planning

    SensEat. Towards a smart Menù: Design, Information and Customer satisfaction.

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    Questa tesi esplora lo sviluppo di un menù innovativo, pensato per fungere da "identikit" dei piatti e migliorare l'interazione tra cliente e proposta gastronomica. L’obiettivo è ripensare il menù tradizionale trasformandolo in uno strumento informativo ed emozionale che presenti ogni piatto in modo completo e coinvolgente. Attraverso un design funzionale e narrativo, il menù comunica sia dettagli tradizionali che inediti, rendendo l’esperienza culinaria più appagante e consapevole. Questo approccio mira a incrementare il gradimento del consumatore, valorizzando al contempo l’identità del ristorante e dei suoi piatti.This thesis explores the development of an innovative menu designed to serve as a “sketch” of the dishes and improve the interaction between the customer and the food proposal. The goal is to rethink the traditional menu by transforming it into an informative and emotional tool that presents each dish in a comprehensive and engaging way. Through functional and narrative design, the menu communicates both traditional and novel details, making the dining experience more fulfilling and mindful. This approach aims to increase consumer enjoyment while enhancing the identity of the restaurant and its dishes

    Interazioni neurocomportamentali tra la codifica del tipo di presa e la postura in scimmie in movimento libero

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    Classical paradigms investigating the role of premotor cortex in grasping behavior have predominantly focused on distal components of movement, such as grip control, often overlooking the potential contributions of axial-proximal variables related to body posture. Although behavioral studies showed that the body posture taken by the animal influences grasping execution, neurophysiological studies on grasping were conducted on primates restrained in a primate chair, where axial components are largely abolished. Thus, it is unclear whether and to what extent postural components affect premotor activity during grasping. Using a wireless neural recording system synchronized with two cameras, we extracted single unit activity and body postures from two freely moving macaques while they reached and grasped two different objects positioned at four distinct locations within the cage. The majority of grasp-related neurons changed their activity depending on the spatial position of the object, with only a few that retained the same modulation across all positions. Within grasp-related neurons, most were grip-selective. Again, the majority of these cells changed their grip-selectivity depending on the spatial position of the object, with only a small group of cells maintaining the same grip tuning across all four positions. To probe the causal role of the cortical sites exhibiting grasp-related activity, we applied long-trains head-free intracortical microstimulation (ICMS). Although this difference was non statistically significant, stimulating sites hosting grasp-related and grip-selective neurons predominantly evoked axio-proximal responses, whereas hand responses were less frequent. Taken together, these results show that axial-proximal components influence premotor activity related to distal movements, providing evidence that the premotor cortex may encode a dynamic control of axial-proximal and distal synergies. Within a neuroethological framework, this study highlights how distal control emerges from continuous interaction with complex postural constraints, emphasizing the necessity of naturalistic conditions for better understanding motor organization.I paradigmi classici che indagano il ruolo della corteccia premotoria nel comportamento di presa si sono prevalentemente concentrati sulle componenti distali del movimento, come il controllo della presa, trascurando spesso i potenziali contributi delle variabili assiali-prossimali legate alla postura del corpo. Sebbene studi comportamentali abbiano dimostrato che la postura assunta dall’animale influenza l’esecuzione della presa, gli studi neurofisiologici sulla presa sono stati condotti su primati immobilizzati in una sedia per primati, dove i componenti assiali sono in gran parte aboliti. Pertanto, non è chiaro se e in che misura i componenti posturali influenzino l’attività premotoria durante la presa. Utilizzando un sistema di registrazione neurale wireless sincronizzato con due telecamere, abbiamo estratto l'attività delle singole unità neuronali e le posture corporee da due macachi in movimento libero mentre raggiungevano e afferravano due oggetti diversi posizionati in quattro posizioni distinte all’interno della gabbia. La maggior parte dei neuroni correlati alla presa ha modificato la propria attività in funzione della posizione spaziale dell'oggetto, con solo pochi neuroni che hanno mantenuto la stessa modulazione in tutte le posizioni. Tra i neuroni correlati alla presa, la maggior parte era selettiva per il tipo di presa. Anche in questo caso, la maggioranza di queste cellule ha modificato la propria selettività di presa in base alla posizione spaziale dell'oggetto, con solo un piccolo gruppo di cellule che ha mantenuto lo stesso adattamento alla presa in tutte e quattro le posizioni. Per indagare il ruolo causale dei siti corticali che mostrano attività correlata alla presa, abbiamo applicato microstimolazione intracorticale (ICMS) a lungo termine su animali con la testa libera. Sebbene questa differenza non fosse statisticamente significativa, la stimolazione dei siti contenenti neuroni correlati alla presa e selettivi per il tipo di presa ha prevalentemente evocato risposte assiali-prossimali, mentre le risposte della mano sono state meno frequenti. Nel complesso, questi risultati dimostrano che i componenti assiali-prossimali influenzano l’attività premotoria correlata ai movimenti distali, fornendo evidenze che la corteccia premotoria possa codificare un controllo dinamico delle sinergie tra componenti assiali-prossimali e distali. All’interno di un quadro neuroetologico, questo studio evidenzia come il controllo distale emerga da un’interazione continua con complesse restrizioni posturali, sottolineando la necessità di condizioni naturalistiche per una migliore comprensione dell’organizzazione motoria

    THERMO-MECHANICAL OPTIMIZATION OF MATERIALS AND STRUCTURES

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    This thesis presents a comprehensive investigation into topology optimization (TO) and its applications to structural and thermal systems. It spans theoretical developments, computational implementations, and practical validations, with a focus on enhancing efficiency, accuracy, and versatility in addressing complex engineering challenges. The development and application of the Immersed Level-Set Topology Optimization (ILSTO) framework, which decouples the finite element (FE) mesh from the level-set (LS) grid, enabling precise boundary representations without the computational burden of adaptive meshing is the central novelty of the thesis. The research is organized into three thematic areas: (1) the design and characterization of advanced lattice and metamaterial structures, including Triply Periodic Minimal Surface geometries and porous metaplates (2) a critical review and development of numerical approaches in TO, highlighting the potential of LS-based methods and their integration into multi-physics frameworks; and (3) applications of ILSTO in thermo-mechanical TO, addressing problems involving conflicting objectives such as minimizing structural compliance and thermal transport simultaneously. Key contributions include novel strategies for mapping field variables between the FE mesh and LS grid, enhanced convergence criteria, and innovative interpolation schemes to balance computational cost and solution accuracy. The findings demonstrate the robustness of the ILSTO framework in solving complex TO problems while maintaining flexibility for extensions to nonlinear material models thus soft robotics applications, multi-scale designs, and integration into commercial FEM software. This work not only bridges theoretical and practical advancements in TO but also lays the foundation for future developments in high-performance structural design, offering insights into optimizing multi-functional materials and systems for engineering applications

    Artificial Intelligence of Things: Implementation, Performance Analysis, Computational Feasibility

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    The main objective of this Thesis dissertation is to explore AI models in the context of resource-constrained IoT devices for a variety of applications. In particular, this dissertation aims to develop, optimize, and deploy ML/DL models intended for embedded systems, considering a number of trade-offs between accuracy, computational efficiency, and constraints during deployment that are critical for the real-world evaluations. Thus, investigating the balance between computational complexity and prediction accuracy in the collaboration between AI and tiny IoT devices will provide a deeper understanding of their potential and assist in selecting the most feasible and efficient approaches depending on the application

    Consumer perception of products derived from agri-food waste

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    L’elaborato si propone di indagare le percezioni, le attitudini e la disponibilità a pagare dei consumatori nei confronti di prodotti cosmetici realizzati a partire dagli scarti del caffè, in un'ottica di economia circolare. Dapprima è stata svolta una revisione della letteratura, finalizzata a identificare i fattori che influenzano le scelte e il comportamento dei consumatori riguardo i sottoprodotti derivati da scarti agroalimentari. Contemporaneamente, sono stati esaminati diversi casi studio di aziende che utilizzano sottoprodotti agroalimentari, con un focus specifico su quelli derivati dal caffè, utilizzati per realizzare prodotti finiti o specifiche formulazioni. Successivamente, è stata effettuata un’analisi empirica tramite la somministrazione di un questionario a un campione di 155 persone, che ha permesso di comprendere le percezioni dei consumatori circa l'utilizzo di fondi di caffè esausti in prodotti cosmetici. Infine, attraverso l'elaborazione dei risultati sono stati creati cinque cluster, per ciascuno dei quali sono state formulate proposte di marketing per cercare di favorire l’utilizzo e la valorizzazione di soluzioni cosmetiche sostenibili per il mercato italiano.The study aims to investigate consumers' perceptions, attitudes, and willingness to pay for cosmetic products made from coffee waste, with a view to promoting the circular economy. First, a literature review was conducted to identify the factors that influence consumer choices and behavior regarding by-products derived from agri-food waste. At the same time, several case studies of companies using agri-food by-products were examined, with a specific focus on those derived from coffee, used to make finished products or specific formulations. Subsequently, an empirical analysis was carried out by administering a questionnaire to a sample of 155 people, which provided insight into consumers' perceptions of the use of used coffee grounds in cosmetic products. Finally, five clusters were created by processing the results, and marketing proposals were formulated for each of them to try to promote the use and enhancement of sustainable cosmetic solutions for the Italian market

    Valutazione neuropsicologica della fase prodromica della demenza a corpi di Lewy : sviluppo e validazione di una batteria di test specializzata

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    Dementia with Lewy Bodies (DLB) represents the second most common form of neurodegenerative dementia after Alzheimer’s Disease (AD), yet one of its prodromal stages, known as mild cognitive impairment with Lewy bodies (MCI-LB), remains challenging to identify due to overlapping clinical features with MCI due to Alzheimer’s Disease (MCI-AD). This study aimed to develop and validate a neuropsychological battery capable of detecting domain-specific cognitive profiles to support early differential diagnosis between MCI-LB and MCI-AD. A sample of individuals diagnosed with MCI-LB and MCI-AD underwent a comprehensive neuropsychological assessment. Between-group comparisons were conducted using parametric and non-parametric tests, along with effect size calculations. Logistic regression was applied to identify the most informative combination of predictors. Significant differences emerged in verbal episodic memory, which was more impaired in MCI-AD, and in attention, working memory, and visuospatial-executive functions, more compromised in MCI-LB. The regression model, that included Digit Span Backward, Delayed Prose Recall, VOSP Number Location, and the Clock Drawing Test, demonstrated excellent classification performance (AUC = 0.892; McFadden's pseudo-R² = 0.36), with good sensitivity and specificity. These findings confirm the primary hypothesis that these two conditions exhibit distinct cognitive profiles, specifically in the domains most affected by each individual condition. Specifically, MCI-LB was associated with greater impairments in attentional and executive functioning, along with mild visuospatial deficits, while MCI-AD showed more pronounced difficulties in episodic verbal memory. These findings are consistent with the distinct neuropathological patterns of the two conditions: early medial temporal lobe involvement in AD (Braak & Braak, 1991) and fronto-subcortical and parietal dysfunctions in DLB due to alpha-synuclein pathology (Beach et al., 2009; McKeith et al., 2020). The study highlights the clinical utility of a domain-specific cognitive approach in the early detection of MCI-LB.La demenza a corpi di Lewy (DLB) rappresenta la seconda forma più comune di demenza neurodegenerativa dopo la malattia di Alzheimer (AD). Tuttavia, una delle sue fasi prodromiche, nota come deterioramento cognitivo lieve associata a corpi di Lewy (MCI-LB), risulta ancora difficile da identificare a causa delle sovrapposizioni cliniche con la MCI dovuta alla malattia di Alzheimer (MCI-AD). Questo studio si è proposto di sviluppare e validare una batteria neuropsicologica in grado di rilevare profili cognitivi per supportare la diagnosi differenziale precoce tra MCI-LB e MCI-AD. Un campione di individui con diagnosi di MCI-LB e MCI-AD è stato sottoposto a una valutazione neuropsicologica approfondita. I confronti tra gruppi sono stati condotti utilizzando test parametrici e non parametrici, con calcolo dell’entità dell’effetto. È stata inoltre applicata un’analisi di regressione logistica per identificare la combinazione di predittori più informativa. Sono emerse differenze significative nella memoria episodica verbale, maggiormente compromessa nella MCI-AD, e nelle funzioni attentive, di memoria di lavoro e visuospaziali-esecutive, più alterate nella MCI-LB. Il modello di regressione, che includeva Digit span all’indietro, test della memoria di prosa, VOSP Number Location e il Test dell’Orologio, ha mostrato un’eccellente capacità nella classificazione della condizione (AUC = 0.892; pseudo-R² di McFadden = 0.36), con buona sensibilità e specificità. Questi risultati confermano l’ipotesi principale secondo cui le due condizioni presentano profili cognitivi distinti, specificamente nei domini maggiormente coinvolti in ciascuna. In particolare, la MCI-LB era associata a maggiori compromissioni delle funzioni attentive ed esecutive, insieme a lievi deficit visuospaziali, mentre la MCI-AD mostrava difficoltà più marcate nella memoria episodica verbale. Tali evidenze sono coerenti con i differenti pattern neuropatologici delle due condizioni: il precoce coinvolgimento del lobo temporale mediale nell’AD (Braak & Braak, 1991) e le disfunzioni fronto-sottocorticali e parietali nella DLB, associate alla patologia da alfa-sinucleina (Beach et al., 2009; McKeith et al., 2020). Lo studio sottolinea l’utilità clinica di un approccio neuropsicologico mirato per la rilevazione precoce della MCI-LB

    Chemogenetic manipulation of histaminergic neurons (TMN^HA) influences feeding behavior and body weight

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    Il comportamento alimentare è il risultato di una complessa integrazione tra segnali centrali e periferici, fondamentali per il mantenimento dell’omeostasi energetica. Tra i neuromodulatori coinvolti in questo processo, l’istamina cerebrale ha un ruolo cruciale nella regolazione dell’appetito e del metabolismo energetico. I neuroni istaminergici, localizzati nel nucleo tuberomammillare dell’ipotalamo, proiettano diffusamente nel sistema nervoso centrale e agiscono tramite diversi sottotipi recettoriali, modulando in modo dinamico l’assunzione di cibo. Tuttavia, le evidenze finora disponibili derivano prevalentemente da approcci farmacologici o modelli di deplezione cronica, che non permettono di chiarire in modo selettivo e temporizzato il ruolo funzionale di queste cellule. La presente tesi si propone di approfondire la funzione dei neuroni istaminergici nel controllo dell’alimentazione mediante un approccio chemogenetico, basato sull’espressione di recettori DREADD nei topi HDC-Cre. Questo metodo consente di modulare specificamente l’attività dei neuroni istaminergici in vivo, valutando l’impatto della loro attivazione sul comportamento alimentare e sul peso corporeo. I risultati forniscono nuove evidenze sul contributo del sistema istaminergico alla regolazione omeostatica dell’appetito e aprono la strada a future applicazioni terapeutiche per disturbi metabolici e disfunzioni alimentari. ​Feeding behavior results from a complex integration of central and peripheral signals that are essential for maintaining energy homeostasis. Among the neuromodulators involved, brain histamine plays a pivotal role in regulating appetite and energy metabolism. Histaminergic neurons, located in the tuberomammillary nucleus of the hypothalamus, project widely throughout the central nervous system and modulate food intake through different receptor subtypes. However, current knowledge is mostly based on pharmacological approaches or chronic depletion models, which lack temporal and cell-type specificity. This thesis aims to investigate the role of histaminergic neurons in the control of feeding behavior using a chemogenetic approach, by expressing DREADD receptors in HDC-Cre mice. This method allows precise in vivo modulation of histaminergic neuron activity to assess the effects of their activation on food intake and body weight. The findings provide new insights into the contribution of the histaminergic system to the homeostatic regulation of appetite and offer potential therapeutic avenues for the treatment of metabolic disorders and eating dysfunctions.

    Functional properties and firing features of monkey premotor neurons during sleep

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    Decades of neurophysiological research in awake, behaving primates have elucidated the role of the premotor (PM) cortex in controlling movement execution, encoding of objects and actions performed by others through a variety of neuronal cell classes, such as motor, canonical, peripersonal and mirror neurons. How do the firing properties of these neurons change during the different stages of sleep compared to wakefulness? In this study, we addressed this issue by leveraging a recently developed neurobehavioral platform for wireless intracortical recordings from the PM cortex of two Rhesus Macaques during both wakefulness and natural unconstrained nighttime sleep. First, we developed a novel unsupervised method to automatically classify different brain states using only intracortical biomarkers. Next, we tested single neuron properties during a reaching-grasping visuo-motor task in a traditional laboratory setting to functionally characterize neurons as self-type, other-type, or self-and-other type, and then studied their firing properties during sleep on the night following the testing. Interestingly, self-type and self-and-other type neurons characterized by narrow spikes exhibited strong suppression during NREM sleep while enhanced their activity during REM sleep as during wakefulness. In contrast, we found a set of cells apparently task-unrelated during wakefulness that mostly exhibited broad spikes and significantly increased their activity during NREM sleep relative to wakefulness and REM sleep. These findings uncover a previously unknown sleep micro-architecture within the premotor cortex, suggesting a switch between PM cortex neuronal populations involved in the orchestration of behavior during wakefulness and a subpopulation that remain silent during wakefulness but becomes active during NREM sleep, possibly contributing to sleep-related functions

    Climate change adaptation in urban regeneration practices: the contribution of soil desealing to contrast the urban heat island

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    L’impermeabilizzazione del suolo rende le città sempre più calde: le superfici asfaltate e cementificate assorbono notevolmente le radiazioni solari durante la giornata, trattengono il calore e lo rilasciano gradualmente durante le ore notturne, rendendo, soprattutto nei periodi estivi, l’ambiente urbano insalubre e invivibile, arrecando disagi agli utenti e contribuendo ad intensificare il fenomeno dell’isola di calore urbana. Pertanto, in un contesto in cui politiche e strategie urbane mirano sempre più a migliorare l’assetto ecologico-ambientale della città consolidata e, allo stesso tempo, ad aumentare la resilienza sociale delle comunità ivi insediate, le attività di questa ricerca di tesi mirano a comprendere come la desigillazione di suoli inutilmente impermeabilizzati possa assicurare un contributo alle azioni locali di adattamento al cambiamento climatico. L’inserimento nella pianificazione territoriale e nei processi di rigenerazione urbana di azioni volte a rinaturalizzare parti del suolo è da considerarsi, infatti, fondamentale nell’ottica di una politica più sostenibile, a tutela dell’ambiente e dei cittadini. In particolar modo, questo elaborato di tesi è finalizzato a valutare la propensione di porzioni urbane della città di Parma ad accumulare calore, attraverso un’analisi di criticità locali rispetto a temperature eccessive, servendosi degli innovativi sistemi di visione aerea a bassa quota a pilotaggio remoto (droni) per rilievi territoriali di precisione. Lo studio adotta l’approccio riaffermato nel V Rapporto di Valutazione (AR5) dell’IPCC, che definisce il rischio come una funzione di pericolosità, esposizione e vulnerabilità. Applicando questo modello, la ricerca identifica le aree più a rischio per il fenomeno dell’isola di calore urbana. Ne consegue, sulle stesse, un interesse prioritario per interventi di desigillazione volti a ridurre le temperature e, al contempo, a migliorare il comfort e il benessere locale. Elementi di originalità sono stati, dunque, l’approfondimento e la sperimentazione di nuove tecnologie di telerilevamento applicate ai droni in grado di fornire informazioni utili ad un’urbanistica di precisione e attenta a promuovere azioni e strategie per contrastare i cambiamenti climatici. In particolare, si è sperimentata l’efficacia di questi sistemi per l’individuazione di criticità climatiche locali di dettaglio in merito alle elevate temperature (ricognizione delle temperature superficiali – LST), riferendosi quindi all’effetto isola di calore urbana, e alla qualità del verde (attraverso l’analisi dell’indice di vegetazione – NDVI) e dell’aria della zona d’interesse, aspetti che influenzano anche il benessere bioclimatico dei cittadini. Infine, discutendo gli esiti di un’attività di ricerca sperimentale, condotta nell’ambito del progetto “Green in Parma”, dai caratteri di Terza Missione universitaria per la divulgazione scientifica in contesti locali, si è favorita la riflessione critica sulle opportunità e sulla possibile rilevanza della desigillazione in processi partecipati proposti da comunità resilienti, per contrastare gli impatti del cambiamento climatico secondo una logica bottom-up che possa integrare e stimolare in modo virtuoso gli interventi top-down.Soil sealing contributes to increasingly hotter cities: asphalt and concrete surfaces absorb significant amounts of solar radiation during the day, retain heat, and gradually release it at night. This process exacerbates the urban heat island effect, particularly in summer, creating unhealthy and unlivable environments and causing discomfort to urban inhabitants. In a context where urban policies and strategies are increasingly focused on improving the ecological and environmental framework of consolidated cities while enhancing the social resilience of local communities, this thesis investigates how desealing unnecessarily sealed surfaces can contribute to local climate change adaptation efforts. The integration of soil renaturalisation actions into urban planning and regeneration processes is crucial in fostering more sustainable policies that protect both the environment and citizens. This study focuses on evaluating the propensity for heat accumulation in specific urban areas of Parma through an analysis of local vulnerabilities to excessive temperatures. It employs innovative unmanned aerial systems (drones) for high-precision territorial surveys. This study adopts the approach reaffirmed in the IPCC Fifth Assessment Report (AR5), which defines risk as a function of hazard, exposure, and vulnerability. By applying this framework, the research identifies the areas most at risk from the urban heat island phenomenon. These areas are of priority interest for desealing interventions aimed at reducing temperatures and simultaneously enhancing local comfort and well-being. A key contribution of this research is the in-depth exploration and experimentation with advanced drone- based remote sensing technologies. These tools have proven effective in providing valuable data for precision urban planning and in supporting targeted actions and strategies to mitigate climate change impacts. Specifically, the study tested the utility of drones in identifying localised climatic vulnerabilities, such as high surface temperatures (land surface temperature – LST) and evaluating vegetation health (normalised difference vegetation index – NDVI) and air quality, factors that directly influence citizens’ bioclimatic well-being. Finally, the outcomes of an experimental research initiative conducted as part of the “Green in Parma” project, an example of the university’s Third Mission aimed at scientific dissemination in local contexts, prompted critical reflection on the potential of desealing interventions. These findings underscore the importance of participatory, bottom-up approaches to complement and enhance top-down urban planning initiatives, fostering resilience and countering the impacts of climate change in a synergistic manner

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