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Integrated histological parameters define prognostically relevant groups in atypical endometrial hyperplasia / endometrioid intraepithelial neoplasia
Get PDFBackground: The risk of endometrial cancer (EC) in atypical endometrial hyperplasia/endometrioid intraepithelial neoplasia (AEH/EIN) is highly variable among different series. Recent studies suggested that histological criteria may subdivide AEH/EIN into prognostically relevant groups.
Objective: To assess the risk of EC in AEH/EIN patients stratified according to integrated histological parameters.
Methods: All women with AEH/EIN undergoing hysterectomy within 1 year from diagnosis without undergoing progestin treatment were included. AEH/EINs were subdivided into 3 study groups, based on nuclear atypia and on the presence of focal (<2 mm) stromal disappearance (FSD): low-grade (LG)-AEH/EIN, high-grade (HG)-AEH/EIN, and FSD-AEH/EIN. The rate of EC on the subsequent hysterectomy was assessed in each study group, and differences between study groups were assessed using Fisher’s exact test, with a significant p-value<0.05. Reproducibility was assessed by using Cohen’s k.
Results: Ninety-six patients were included. Overall, 36/96 patients (37.5%) had EC on the subsequent hysterectomy. The number of EC was 4/42 (9.5%) in LG-AH/EIN, 14/28 (50%) in HG-AH/EIN, and 18/26 (69.2%) in FSD-AEH/EIN. The rate of EC was significantly higher in HG-AH/EIN than in LG-AEH/EIN (p<0.001), while it did not significantly differ between HG-AEH/EIN and FSD-AEH/EIN (p=0.176). The reproducibility among pathologists was moderate for LG-AEH/EIN vs HG-AEH/EIN (k=0.58) and substantial for FGD-AEH/EIN vs LG-AEH/EIN (k=0.63) and HG-AEH/EIN (k=0.63).
Conclusion: AEH/EIN can be stratified into prognostically relevant groups based on integrated histological parameters, with a possible major impact on patient management
Short and long-term effects of alpha-band sensory entrainment on neural oscillations and perceptual performance
Get PDFAlpha-band neural oscillations (~7-13 Hz) play a crucial role in encoding and integrating sensory information, organizing both uni- and multi-sensory perceptual experiences. Fluctuations in alpha activity have been linked to changes in sensory cortices excitability, leading to rhythmic modulations of perception, thus suggesting that the alpha rhythm may reflects a reliable electrophysiological index of sensory information processing. Interestingly, alpha activity is not a fixed neural feature but is highly plastic and dynamically shaped by neurocognitive states. A recent framework proposes modulating endogenous alpha oscillations through neural entrainment, where neural oscillations synchronize with external rhythms, inducing resonance phenomena in neural and perceptual activity. This approach allows for the direct investigation of the relationship between alpha activity and perceptual performance, as well as the functional modelling of alpha oscillations. The present thesis investigates how alpha-band sensory entrainment, administered via uni- and multi-sensory modalities, affects alpha oscillatory activity and leads to both short- and long-term changes in perceptual performance. Chapter 2 outlines the role of alpha oscillations in shaping perception, while Chapter 3 addresses their malleability following neural entrainment. Empirical studies will then be presented, demonstrating alpha-band sensory entrainment's potential to modulate oscillatory activity and induce functional changes in perceptual performance. Chapter 4 focuses on the effects of alpha-band entrainment on audiovisual temporal binding mechanisms, while Chapter 5 will explore how individual differences in cognitive-perceptual and socio-communicative styles, particularly in neurotypical individuals with varying levels of autistic and schizotypal traits, may influence the effects of alpha-band entrainment on audiovisual temporal binding processes. Finally, Chapters 6 and 7 present EEG and psychophysical studies on whether alpha-band visual stimulation can induce long-lasting changes in alpha oscillatory activity and visual detection performance. Lastly, Chapter 8 integrates these findings and suggests future applications of alpha-band entrainment for enhancing perceptual performance in both general and clinical populations
Application of machine learning methods for landslide risk mitigation
Get PDFLandslides in complex geological settings are a widespread and dangerous natural hazard that, in the context of climate change, poses significant challenges for modern society. Despite knowledge about triggering mechanisms and monitoring techniques, conducting comprehensive studies of landslide susceptibility and emergency management in regions like Emilia-Romagna, Italy, often entails significant obstacles. This PhD project analyzes the multifaceted aspects of landslide prediction and management in this geologically complex region.
The research initially focused on improving rainfall thresholds for forecasting, comparing conventional empirical-statistical approaches with machine learning (ML) techniques. Results demonstrated that ML methods improved predictive accuracy and reduced false positives. However, this advancement also highlighted the persistent challenge of input data quality and volume. A key innovation emerged: developing a unified platform that integrates the improved rainfall thresholds and ML predictions into operational early warning systems.
The catastrophic rainfall events of May 2023 in Emilia-Romagna posed a significant challenge to our research, necessitating an unprecedented rapid response. Considering this urgent need, a multi-institutional collaboration was quickly established, leading to a comprehensive landslide inventory documenting 80,000 polygons using high-resolution aerial imagery. Our research pivoted to explore rapid automated mapping techniques, starting with trials using the U-Net neural network in severely affected municipalities like Casola Valsenio. More advanced algorithms, such as SegFormer, were subsequently employed across diverse settings including Modigliana, Predappio, and Brisighella. This urgent application of our research offered valuable insights into the practical challenges of rapid landslide response, informing innovations for future methodologies.
In conclusion, this research demonstrates the transformative potential of integrating machine learning with traditional approaches in landslide prediction and management. The improved prediction models, early warning platform, comprehensive landslide inventory, and rapid mapping techniques collectively contribute to building resilient communities capable of effectively responding to and mitigating the impacts of landslides in the face of increasing climate-related risks
Application and development of an artificial intelligence based multiparametric malignancy index (MMI) for interpretation of 3T multiparametric prostate MRI
Get PDFIntroduction: Prostate cancer (PCa) diagnosis and management remain challenging due to its varied progression, from slow-growing forms to aggressive types requiring early intervention. Advances in detection, such as risk-adapted screening and multiparametric MRI (mpMRI), have improved early diagnosis, but balancing high-risk identification with minimizing overdiagnosis is crucial. This study investigates the application of machine learning (ML), specifically a Random Forest (RF) model, to enhance PCa detection accuracy using clinical and radiological features.
Materials and Methods: A cohort of 314 patients aged 55-75 was analyzed, with key variables including PSA levels, PI-RADS scores, prostate volume, and rADC. The RF model was chosen for its robustness in handling mixed data types and complex feature interactions. Patients were stratified into ISUP grades (0, 1, 2+), with non-cancerous (ISUP 0) and aggressive (ISUP 2+) cases distinctly represented. A subset of 95 patients was reserved for testing to evaluate model generalization.
Results: Among the cohort, 182 cases had lower PI-RADS scores (2 and 3), and 132 had higher scores (4 and 5). The RF model achieved 68% accuracy on the test set, with precision and recall for each ISUP grade: ISUP 0 (precision: 0.79, recall: 0.83), ISUP 1 (precision: 0.22, recall: 0.12), and ISUP 2+ (precision: 0.58, recall: 0.74). Feature importance analysis highlighted rADC, prostate volume, and PSA as key predictors, with the model demonstrating strong ability to distinguish between non-cancerous and aggressive PCa cases, supported by an AUC score.
Conclusions: This study highlights the potential of ML to improve PCa diagnostic accuracy. The RF model’s effective integration of clinical and radiological data provides insights into key predictors, aiding in risk stratification. This work also supports the FLUTE project, which aims to enhance PCa diagnostics through federated learning, laying the groundwork for AI-driven diagnostic tools and personalized treatment planning
Intelligent walls by the use of reconfigurable intelligent surfaces
Get PDFThe convergence of advancements in the construction industry with the growing demands of wireless communication technologies is central to the development of next-generation networks. However, modern construction techniques hinder signal propagation, and at higher frequencies, achieving reliable coverage becomes challenging. These challenges underscore the urgent need for innovative techniques to enhance RF coverage within buildings. Therefore, this thesis explores macroscopic realistic models for the design and integration of RIS into buildings structures, offering a novel approach to addressing the signal propagation challenges faced in higher frequency bands such as those utilized in 5G and 6G networks. RIS, which can be embedded within walls, windows, and other architectural elements, provides a flexible and energy-efficient solution for enhancing coverage by dynamically shaping electromagnetic wave behavior. A part of this research focuses on the development of macroscopic RIS models: a Huygens based bilateral model and a ray-based macroscopic model. The latter is validated against existing physical optics methods, demonstrating high accuracy while maintaining computational efficiency. This thesis highlights the potential to optimize indoor coverage in a way that complements modern architectural trends by integrating RIS into building structures. Additionally, experimental studies were conducted to assess material penetration losses across multiple frequency bands. The results indicate substantial signal attenuation through common construction materials which further underscores the importance of intelligent surface deployment in overcoming these obstacles. By aligning advancements in construction with the needs of wireless communication, this thesis presents RIS as a potential transformative solution for smart environments. The proposed framework not only addresses the challenges of high-frequency signal propagation but also emphasizes the possibility of integrating communication technologies within building designs. This work is a contribution to the development of smart buildings and cities, where architectural innovations and wireless communication systems work in harmony to support future applications
Nutritional modulation and support for pediatric patients with cancer and undergoing hematopoietic cell transplantation
Get PDFNutritional status has been demonstrated as a crucial aspect in the treatment of pediatric oncology patients, with measurable impact of morbidity and mortality in children with acute leukemias. Thus, great effort should be made to optimize nutritional evaluation and support. In fact, in pediatric patients undergoing allogeneic hematopoietic cell transplantation (allo-HCT), nutritional support (e.g. enteral nutrition) can be effectively utilized to reduce the incidence of bloodstream infections (BSI). Furthermore, nutritional interventions can be utilized to modulate the gut microbiome (GM) configuration, which has implications for severe HCT-related complications such as acute graft-vs-host disease (GvHD). Other interventional strategies including fecal microbiota transplantation (FMT), can be utilized to modify the GM configurations. In this thesis, we summarize the results of two nationwide survey among the Associazione Italiana di Ematologia ed Oncologia Pediatrica (AIOEP) network aimed to assess the current practices for nutritional evaluation and care, as well as food-handling practices and foodborne infections among pediatric patients undergoing chemotherapy and allo-HCT. Moreover, we compared nutritional and HCT-related outcomes (such as acute GvHD and BSI) in a cohort of pediatric patients undergoing allogeneic HCT between patients receiving nutritional support with Parenteral Nutrition (PN) and Enteral Nutrition (EN). Finally, we evaluate the feasibility and safety of FMT in a cohort of children with steroid-refractory gut GvHD and MDR colonization, observing an exceptional safety profile and clinical response
High-detail geomatic 3D surveying and processing for small-objects robust documentation and investigation in heritage science
Get PDFHeritage Science lies at the intersection of the humanities and sciences, embracing a multidisciplinary approach to studying and preserving cultural heritage. Integrating fields such as history, archaeology, philology, chemistry, biology, physics, and informatics provides a cohesive framework that deepens the understanding of cultural assets. This interdisciplinary collaboration not only enriches historical and archaeological perspectives but also addresses critical material challenges, advancing methods for the conservation and valorisation of heritage. In recent years, geomatic surveying, especially high-detail 3D surveying, has become essential in Heritage Science while also expanding its application to diverse fields such as medicine and industry. This widespread usage has led to inconsistencies in terminology, methodologies, and theoretical frameworks, which may risk positioning 3D surveying as merely a technical tool rather than as a scientific discipline with intrinsic value. This thesis addresses these challenges by providing a structured and comprehensive examination of the theoretical and practical foundations of high-detail 3D surveying within geomatics, particularly in its applications to cultural assets investigation. It opens with an extensive literature review highlighting terminological and conceptual inconsistencies, focusing on three main technologies: laser triangulators, structured-light projection scanning, and close-range digital photogrammetry. Building on this theoretical groundwork, the thesis details the methodologies employed in the experimental phase, particularly emphasising the comparative and integrative applications of structured-light projection scanning and digital photogrammetry. Real-world case studies are also presented to demonstrate the effectiveness of these technologies in the detailed 3D documentation and analysis of cultural assets. Finally, the thesis concludes by discussing the broader implications of its findings and proposing avenues for future research and innovation within the discipline
The transdisciplinary approach of the New European Bauhaus: the evaluation of sustainability, aesthetics and inclusion in heat island mitigation actions
Get PDFDi fronte agli attuali squilibri ambientali dei territori antropizzati è stata riconosciuta come prioritaria un’ampia strategia di rinaturalizzazione della città attraverso soluzioni innovative di resilienza urbana che promuovano l’integrazione strutturale del verde anche tramite la realizzazione delle infrastrutture verdi urbane.
Affrontare efficacemente le sfide del cambiamento climatico richiede un approccio sistemico e transdisciplinare. È necessario adottare pratiche sostenibili e trasferibili, basate su una metodologia di valutazione appropriata e un framework che consenta di misurare gli impatti di medio e lungo termine delle azioni progettuali. Il Project Cycle Management (PCM) e il Logical Framework Approach (LFA) sono universalmente riconosciuti e comunemente adottati dalla Commissione Europea come i due approcci metodologici principali per una efficace gestione di progetto, strutturati e concepiti per evidenziare la logica sequenziale di azioni orientate ad un risultato. L’approccio dell'iniziativa New European Bauhaus (NEB) alla progettazione deve prevedere una consequenzialità efficace e logica dei vari stadi di avanzamento delle azioni verso gli obiettivi e i risultati attesi, misurabili tramite set di indicatori qualitativi e quantitativi che permettano un monitoraggio costante e allo stesso tempo una valutazione pre e post intervento. La tesi vuole fornire agli attori coinvolti nella progettazione di azioni di adattamento al cambiamento climatico, quali amministratori pubblici, project manager, architetti, pianificatori, attori locali, più in generale i “decisori” e i “co-decisori”, una metodologia di valutazione e uno strumento di supporto per la definizione di interventi a scala locale che rispondano in maniera appropriata ai criteri e ambiti di intervento stabiliti dall’iniziativa NEB.Project Cycle Management (PCM) and the Logical Framework Approach (LFA) are universally recognized and commonly adopted by the European Commission as the two main methodological approaches for effective project management, structured and designed to highlight the sequential logic of result-oriented actions. New European Bauhaus (NEB) initiative approach provides an effective and logical consequentiality of the various steps of progress of the actions towards the objectives and expected results, measurable through sets of qualitative and quantitative indicators that allow constant monitoring and at the same time a pre- and post-intervention evaluation. Aims of the research study is to provide the main actors involved in the design of climate change adaptation actions, such as public administrators, project managers, architects, planners, local actors, an evaluation methodology and a support tool for the definition of local scale interventions that respond appropriately to the criteria and areas of intervention established by the NEB initiative
Now we make (it) here: how city transformations impact the creative processes of urban artistic practice
Get PDFThis research investigates the bidirectional relationship between art and the city, focusing on how the artist’s experience of city transformations influences their artistic practices in urban public spaces. While existing literature extensively explores the impact and role of art and artists on cities, less attention has been given to how changes in the urban environment influence the creative processes of artists who engage with it. The central question is: how does artists’ experience of urban change affect their artistic production and the ways they create works for urban public spaces? The interdisciplinary concept of urban artistic practice is introduced to frame urban art-works as a dynamic processes shaping and being shaped by the changing urban environment. The city of Bologna, Italy was selected as a case study, involving an in-depth analysis of twelve local artistic practices across the visual, installation-based and performative arts, with three of them – Antonello Ghezzi, TIST, and Serendippo – examined in detail, with a total of seven artworks analyzed. This qualitative research employed a methodological triangulation of semi-structured interviews and visual ethnography, conducted over fourteen months of fieldwork. Data analysis combined two analysis methods: Iterative Thematic Inquiry (ITI) and Systematic Visuo-textual Analysis (SVTA). At a macro level, the findings revealed three distinct modes of urban artistic practice in Bologna – interactive objects, devices, and programs. At a micro level, the creative processes of the art-works from the three local practices and their interactions with urban sites in Bologna were reconstructed through visuo-textual thick descriptions. This study offers new insights and useful methodological frameworks for understanding the evolving relationship between art, the city, and its transformations
Stochastic modelling of climate risk with applications in insurance and finance
No full textThis thesis explores the intersection of climate change and financial markets, focusing on the challenges posed by increasing climate variability and the development of financial instruments for managing associated risks. Anthropogenic climate change has resulted in rising global temperatures and a growing frequency of extreme weather events, leading to significant economic, environmental, and societal impacts. These events have highlighted the need for innovative solutions in the insurance and financial sectors to address climate risk. The first chapter of the thesis considers the modelling of climate-related variables, particularly those underlying parametric insurance products, which offer alternative risk transfer mechanisms for weather-related exposures. By addressing issues such as spatial dependencies and increasing likelihood of extreme events, the research provides efficient methodologies for valuing and managing these instruments. The second chapter examines carbon markets designed to reduce greenhouse gas emissions and promote a low-carbon economy. We analyze the European Emission Trading Scheme (EU-ETS) with high-frequency data and present a methodology for pricing carbon-related financial products. We conclude this thesis by describing weather regimes, an essential tool for weather forecasting. We describe the methodology for constructing Mediterranean weather regimes and present a consistent data pre-processing method for developing year-round weather regimes that opens the possibility of future research to a dynamic probabilistic framework. The methodologies developed in this research can effectively be used to assess and quantify different aspects of climate risk