University of Modena and Reggio Emilia
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Evaluating Infrastructure-Less Cooperative Parking Guidance via Agent-Based Simulation
No full textEfficient parking management in urban environments remains a critical challenge, exacerbating traffic congestion and emissions. This paper presents an agent-based simulation study, conducted in SUMO, to evaluate the feasibility of intelligent vehicles cooperating to assist drivers in locating available parking spots without relying on external infrastructure. Agents infer parking availability by observing vehicle locking and unlocking events, dynamically updating a shared real-time heatmap of potential parking areas. Through comprehensive simulations, we explore the minimal adoption threshold required for the system to deliver tangible benefits in terms of reduced search times and improved urban mobility. Results indicate that even moderate participation significantly enhances parking efficiency, demonstrating the practicality and effectiveness of distributed, infrastructure-free agent cooperation for smart urban mobility solutions
Beyond the Stethoscope: Robotic Empathy in Pediatric Cardiology. The Emerging Role of Social Robots. A Pilot Study
No full textChildren diagnosed with autism spectrum disorder (ASD) often present with restricted interests, stereotyped behaviors, and differences in social communication that can increase distress during clinical encounters. These characteristics may exacerbate anxiety and oppositional behaviours in medical settings. Conversely, the predictable and repetitive way social robots operate appears to align with the cognitive style exhibited by many people with autism and may offer opportunities to reduce situational stress. This pilot study investigated the potential of a humanoid social robot (NAO) to improve cooperation and reduce observable distress during pediatric cardiological assessments in children diagnosed with ASD. Twenty-four patients (aged 5–18) underwent cardiac evaluation in the presence of NAO, which was programmed to interact via stories, movements, dances, and sound cues. Primary outcomes showed lower observed distress during robot-assisted visits compared with retrospective caregiver reports of routine noninvasive visits. Secondary outcomes included shorter procedure times and fewer motion-related artifacts during diagnostic recordings
Generating Synthetic Data with Large Language Models for Low-Resource Sentence Retrieval
No full textSentence similarity search is a fundamental task in information retrieval, enabling applications such as search engines, question answering, and textual analysis. However, retrieval systems often struggle when training data are scarce, as is the case for low-resource languages or specialized domains such as ancient texts. To address this challenge, we propose a novel paradigm for domain-specific sentence similarity search, where the embedding space is shaped by a combination of limited real data and a large amount of synthetic data generated by Large Language Models (LLMs). Specifically, we employ LLMs to generate domain-specific sentence pairs and fine-tune a sentence embedding model, effectively distilling knowledge from the LLM to the retrieval model. We validate our method through a case study on biblical intertextuality in Latin, demonstrating that synthetic data augmentation significantly improves retrieval effectiveness in a domain with scarce annotated resources. More broadly, our approach offers a scalable and adaptable framework for enhancing retrieval in domain-specific contexts. Source code and trained models are available at https://github.com/aimagelab/biblical-retrieval-synthesis
Italian Divas in 19th Century London
No full textBy the early 19th century, Italian-language opera was firmly established in London and continued to attract audiences with its cosmopolitan prestige, despite the steady rise of English-language opera. As the century progressed, sopranos such as Giuditta Pasta, who performed regularly in London and brought several Rossini and Bellini roles to English audiences, Giulia Grisi and Adelina Patti, all achieved the status of world-famous divas. Their fame was greatly aided by technological advances that facilitated touring, as well as the rise of print culture and the impact of photography, which helped to turn singers into celebrities through advance publicity and the circulation of singers’ cartes de visite. This article focuses on the reception of Italian female singers in nineteenth-century London and discusses the extent to which they came to define the age of international touring stardom, while also shaping notions of ‘Italianità’. On the prestigious London stages they rivalled other foreign opera divas, such as Sweden’s Jenny Lind and Spain’s Maria Malibran. Like that of the international Italian theatre actresses who defined the 19th-century ‘gilded stage’, the success of Italian opera in England was largely due to the appeal of seeing famous female singers competing in popular leading roles
ALD-Derived WO3–x Leads to Nearly Wake-Up-Free Ferroelectric Hf0.5Zr0.5O2 at Elevated Temperatures
No full textBreaking the memory wall in advanced computing architectures will require complex 3D integration of emerging memory materials such as ferroelectrics─either within the back-end-of-line (BEOL) of CMOS front-end processes or through advanced 3D packaging technologies. Achieving this integration demands that memory materials exhibit high thermal resilience, with the capability to operate reliably at elevated temperatures, such as 125°C, due to the substantial heat generated by front-end transistors. However, silicon-compatible HfO2-based ferroelectrics tend to exhibit antiferroelectric-like behavior in this temperature range, accompanied by a more pronounced wake-up effect, posing significant challenges to their thermal reliability. Here, we report that by introducing a thin tungsten oxide (WO3–x) layer─known as an oxygen reservoir─and carefully tuning its oxygen content, ultrathin Hf0.5Zr0.5O2 (5 nm) films can be made robust against the ferroelectric-to-antiferroelectric transition at elevated temperatures. This approach not only minimizes polarization loss in the pristine state but also effectively suppresses the wake-up effect, reducing the required wake-up cycles from 105 to only 10 at 125°C, a qualifying temperature for back-end memory integrated with front-end logic, as defined by the JEDEC standard. First-principles density functional theory (DFT) calculations reveal that WO3 enhances the stability of the ferroelectric orthorhombic phase (o-phase) at elevated temperatures by increasing the tetragonal-to-orthorhombic phase energy gap and promoting favorable phonon mode evolution, thereby supporting o-phase formation under both thermodynamic and kinetic constraints
L’approccio di rete nelle neuroscienze e nella psicopatologia: dai piccoli mondi ai sistemi complessi
No full textQuesta tesi di dottorato indaga l’applicazione della scienza delle reti alle neuroscienze e alla psicopatologia, con l’obiettivo generale di promuovere il progresso teorico, l’innovazione metodologica e l’approfondimento empirico in un’ampia gamma di ambiti clinici. È il risultato di tre anni di ricerca dedicati a illustrare l’utilità clinica della scienza delle reti, sia nello studio complesso delle popolazioni con disturbi psichiatrici, sia nelle indagini psicometriche volte a esaminare i test e le loro strutture fattoriali sottostanti, sia nelle analisi finalizzate a predire fenotipi clinici e traiettorie di trattamento farmacologico.
La tesi è organizzata in tre sezioni principali.
La prima parte descrive le basi concettuali e metodologiche, introducendo i principi dei sistemi complessi e della scienza delle reti, e considerando la loro rilevanza per la psicologia, la psichiatria e le neuroscienze cognitive. Particolare attenzione è rivolta alla transizione dai modelli a variabili latenti ai metodi basati su reti, con enfasi sugli approcci transdiagnostici e dimensionali. Inoltre, vengono affrontati i temi della stabilità delle reti, delle transizioni critiche e dell’isteresi, in relazione alla resilienza, alla ricaduta e alle dinamiche dei sistemi complessi.
La seconda parte comprende applicazioni empiriche dell’analisi di rete in diversi disegni di studio e campioni clinici. Le reti di correlazione parziale vengono applicate per rappresentare le interazioni tra sintomi nella depressione, nel disturbo bipolare e nel burden dei caregiver di bambini affetti da cancro. I Mixed Graphical Models dimostrano di essere in grado di gestire dati di tipo misto, consentendo di identificare profili di rischio differenziale per i tentativi di suicidio, esiti neuropsicologici differenziati per sesso e fattori di apatia nel declino cognitivo. L’Exploratory Graph Analysis viene applicata a indagini psicometriche strutturali su apatia e schizotipia, offrendo una tecnica data-driven in confronto con i metodi di analisi fattoriale tradizionali. La Network Intervention Analysis affronta gli approcci longitudinali, mostrando l’interazione dinamica tra sintomi e interventi in psichiatria e oncologia pediatrica, nonché lo sviluppo dei disturbi psicotici sotto trattamento antipsicotico. Infine, le reti di similarità tra pazienti, combinate con approcci di machine learning, vengono applicate a livello individuale per scopi di classificazione, con applicazioni nella malattia di Alzheimer, nella psicosi e nella predizione personalizzata dei profili di gravità clinica.
I dati di tutti gli studi presentati in questa tesi sono stati raccolti in numerosi centri clinici nazionali e internazionali, includendo popolazioni e categorie diagnostiche eterogenee. Questo quadro multicentrico ha offerto un’opportunità unica per valutare i modelli basati su reti in contesti clinici diversificati, rafforzando così la validità esterna e la rilevanza traslazionale dei risultati.
La terza parte riflette sulle questioni metodologiche e sulle prospettive integrative, valutando criticamente i limiti e i punti di forza della metodologia delle reti.
In sintesi, questa tesi analizza e amplia la letteratura esistente, fornendo nuove evidenze che dimostrano come l’analisi di rete possa colmare il divario tra la teoria dei sistemi complessi e le neuroscienze applicate, offrendo metodi innovativi per studiare le interazioni multidimensionali, affinare i modelli nosologici e promuovere un modello di medicina più preciso, predittivo, preventivo e personalizzato.This PhD thesis investigates the application of network science to neuroscience and psychopathology, with the overarching aim of advancing theoretical understanding, methodological innovation, and empirical insights across a wide range of clinical domains. It is the result of three years of research dedicated to illustrating the clinical utility of network science, both in the complex study of populations with psychiatric disorders, in psychometric investigations examining tests and their underlying factorial structures, and in analyses aimed at predicting clinical phenotypes and pharmacological treatment trajectories. The thesis is organised into three main sections.
The first part describes the conceptual and methodological foundations, introducing the principles of complex systems and network science and considering their relevance to psychology, psychiatry, and cognitive neuroscience. Particular attention is placed on the transition from latent-variable models to network methods, with emphasis on transdiagnostic and dimensional viewpoints. In addition, the issues of network stability, critical transitions, and hysteresis are considered as they relate to resilience, relapse, and complex system dynamics.
The second part comprises empirical applications of network analysis across study designs and clinical samples. Partial correlation networks are applied to represent symptom interactions in depression, bipolar disorder, and caregiver burden in children diagnosed with cancer. Mixed Graphical Models show they are capable of dealing with mixed-type data such that differential risk profiles for suicide attempts, sex-differentiated neuropsychological outcomes, and apathy factors in cognitive decline can be recognised.
Exploratory Graph Analysis is applied to structural psychometric investigations of apathy and schizotypy, offering data-driven technique in comparison with alternative factor analytic methods. Network Intervention Analysis addresses longitudinal approaches, demonstrating the dynamic interplay of symptoms and interventions in psychiatry and paediatric oncology, and the development of psychotic disorders under antipsychotic treatment. Finally, similarity networks of patients coupled with machine learning approaches are applied at the level of the patient for classification purposes, with applications in Alzheimer's disease, psychosis, and personalised prediction of clinical severity profiles.
Data for all studies presented in this thesis were collected across multiple national and international clinical centres, encompassing diverse populations and diagnostic categories. This multicentric framework provided a unique opportunity to evaluate network-based models across heterogeneous clinical contexts, thereby strengthening the external validity and translational relevance of the findings.
The third part reflects on methodological issues and integrative perspectives, critically evaluating network methodology's limitations and assets.
In summary, this thesis analyses and extends existing literature, and provides novel evidence demonstrating how network analysis can bridge the gap between complex systems theory and applied neuroscience, by offering innovative methods to study multidimensional interactions, refine nosological models, and foster a model of medicine that is more precise, predictive, preventive, and personalised
La stereo-EEG ad alta intensità rivela le dinamiche spazio-temporali delle aree di insorgenza delle crisi epilettiche in un modello animale di epilessia del lobo temporale
No full textL'epilessia del lobo temporale (TLE) rappresenta una delle forme più comuni di epilessia acquisita nell'adulto, che colpisce circa 65 milioni di persone nel mondo. Caratterizzata da crisi epilettiche spontanee e ricorrenti, la TLE risulta farmacoresistente in oltre il 30-40% dei pazienti. In base alla localizzazione del fuoco epilettico, si distingue una forma mesiale (mTLE), che ha origine in strutture limbiche profonde (ippocampo, amigdala o regioni paraippocampali), e una forma neocorticale (nTLE), in cui le crisi originano nella neocorteccia temporale.
Studi preclinici su modelli animali di TLE sono stati condotti utilizzando un numero limitato (2-3) di elettrodi di registrazione simultanei, impedendo una definizione spaziale adeguata per raggiungere conclusioni certe sulle regioni maggiormente coinvolte nell’esordio delle crisi. Questa tesi si propone di mappare le aree limbiche e corticali temporali, finora in gran parte poco indagate, utilizzando registrazioni video-stereo-elettroencefalografiche (sEEG) in un modello animale di TLE.
È stato utilizzato il modello “pilocarpina”, in grado di riprodurre le peculiarità comportamentali, istologiche ed elettrografiche della TLE umana. Due settimane dopo l’induzione dello stato epilettico (SE), gli animali sono stati sottoposti a chirurgia stereotassica per l’impianto di elettrodi epidurali (mirati alle aree corticali) e profondi (in diverse regioni temporali), configurando tre differenti montaggi. L’attività cerebrale registrata è stata analizzata a posteriori fino alla 15a settimana post-SE.
Durante la fase cronica della patologia, sono state classificate quattro tipologie di crisi: le crisi focali con generalizzazione bilaterale tonico-clonica (FBTCS), che rappresentano il 66,9% degli eventi ictali, e tre sottotipi di crisi focali non generalizzate (NGS), classificate in base alla loro propagazione: (i) NGS con evoluzione omologa controlaterale (27,85%), (ii) NGS con diffusione monolaterale (4,34%) e (iii) NGS confinate alla zona d’origine (0,91%).
La maggior parte degli animali analizzati ha mostrato la presenza di fuochi epilettici multipli, sebbene siano stati osservati anche ratti con epilessia monofocale. Tutte le regioni cerebrali investigate sono risultate potenzialmente epilettogene. In accordo con quanto osservato nei pazienti umani, l’ippocampo ventrale è emerso come il sito principale di esordio delle crisi epilettiche, seguito dalla corteccia entorinale e dall’ippocampo dorsale. L’analisi spaziotemporale dei fuochi epilettici ha rivelato una dinamica temporale variabile nel tempo, senza un chiaro schema di attivazione ricorrente. Inoltre, non è stata trovata una correlazione diretta tra il numero di fuochi attivi e la frequenza delle crisi. Per comprendere meglio le dinamiche neurofisiologiche associate a ciascun tipo di crisi, sono stati analizzati i pattern di inizio e terminazione delle crisi, identificando cinque categorie distinte per ciascuna fase, che rispecchiano da vicino quelle descritte nei pazienti umani. L’analisi della densità spettrale di potenza (PSD) ha confermato differenze significative nella composizione e distribuzione delle onde cerebrali tra FBTCS e NGS, rafforzando la rilevanza traslazionale di questo modello animale.
In conclusione, questo studio dimostra che una caratterizzazione completa della TLE richiede l’uso di montages ad alta risoluzione spaziale, che integrino elettrodi sia epidurali sia di profondità. I dati raccolti rivelano nuove caratteristiche del modello alla pilocarpina mai descritte prima, confermando ulteriormente il suo valore come modello sperimentale traslabile per lo studio della TLE.Temporal lobe epilepsy (TLE) is one of the most common forms of acquired epilepsy in adults, affecting approximately 65 million people worldwide. Characterized by spontaneous and recurrent seizures, TLE is drug-resistant in over 30–40% of patients. Depending on the location of the epileptic focus, TLE can be classified into a mesial form (mTLE), originating in deep limbic structures (such as the hippocampus, amygdala, or parahippocampal regions), and a neocortical form (nTLE), where seizures arise from the temporal neocortex.
Preclinical studies on TLE animal models have been conducted using a small number (2-3) of simultaneous recording electrodes, preventing an adequate spatial definition to reach certain conclusions on the regions most involved in the seizure onset. This thesis aims to map limbic and temporal cortical areas, so far largely under-investigated, using video-stereo-electroencephalographic (sEEG) recordings in an animal model of TLE.
The pilocarpine model was employed to reproduce the behavioural, histological, and electrographic features of human TLE. Two weeks after the induction of status epilepticus (SE), animals underwent stereotaxic surgery for the implantation of epidural electrodes (targeting frontal, prefrontal, and occipital cortical areas) and depth electrodes (targeting several temporal regions), assembled in three distinct montages. Continuous video-sEEG monitoring was performed for at least three days per week, up to the 15th week post-SE.
During the chronic phase of the disease, 4 main seizure types were identified: focal to bilateral tonic-clonic seizures (FBTCS), representing 66.9% of all events, and three subtypes of non-generalized seizures (NGS), based on their propagation pathway: (i) NGS with contralateral homologous evolution (27.85%), (ii) NGS with monolateral spread (4.34%), and (iii) focal non-spreading NGS (0.91%).
Most of the animals analysed exhibited multiple epileptic foci, although rats with monofocal epilepsy were observed. All investigated brain regions proved to be potentially epileptogenic. In agreement with the human condition, the ventral hippocampus emerged as the primary site of seizure onset, followed by the entorhinal cortex and dorsal hippocampus. Spatiotemporal analysis of the epileptic foci revealed a temporal dynamicity over time, with no clearly defined activation pattern emerging. Furthermore, no direct correlation was found between the number of active foci and seizure frequency. To better understand the neurophysiological dynamics associated with each seizure type, patterns of seizure onset and seizure termination were analysed, identifying five distinct categories for each phase, which closely resemble those described in human patients. Power spectral density (PSD) analysis confirmed significant differences in the composition and distribution of brain waves between FBTCS and NGS, reinforcing the translational relevance of this animal model.
In conclusion, this study demonstrates that a complete characterization of TLE pathology requires the use of high spatial resolution montages that integrate both epidural and depth electrodes. Our data reveal new features of the pilocarpine model that have never been reported before, reinforcing the translational relevance of this TLE animal model