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The open form in Helmuth Plessner. Toward an eccentric architecture.
Get PDFLa tesi analizza gli scritti di Helmuth Plessner precedenti il suo esilio nel 1933, evidenziando il suo contributo al dibattito sull’architettura tedesca del primo Novecento. Le riflessioni di Plessner sono collocate nel contesto intellettuale e storico dell’industrializzazione, dello stato tedesco unificato e dell’epoca di Weimar. Egli critica l’incapacità dei suoi contemporanei di cogliere l’“essenza” della tecnica, identificandola come origine delle crisi culturali, politiche e sociali del tempo e proponendo la creazione di nuovi valori culturali e forme estetiche che bilancino le condizioni materiali con la libertà umana. In un articolo meno noto sulla storia dell’arte, Plessner critica sia le Kunstwissenschaften sia il rifiuto della forma tipico di Espressionismo e Astrattismo, fondando la sua analisi sulla molteplicità qualitativa della natura. Questa prospettiva supera dicotomie come corpo e mente o natura e cultura, opponendosi al dominio tecnoscientifico. In questo quadro, l’architettura si presenta come un campo che permette di armonizzare esigenze funzionali e libertà estetica e la cui comprensione è resa possibile dal corpo umano nella sua interezza. La filosofia plessneriana dell’architettura si basa quindi sulla sua filosofia dell'organico del 1928, che enfatizza la “forma vivente” come tensione tra Gestalt e Gestaltung. Nello stesso periodo, gli architetti moderni integrano queste idee, ispirandosi alla biologia filosofica per riconciliare la tecnica industriale con le esigenze estetiche: la lezione di Plessner sulla “forma aperta”, presentata al Deutscher Werkbund, costituisce uno dei modi possibili per concepire tale riconciliazione.This thesis examines Helmuth Plessner’s writings prior to his 1933 exile, highlighting his contribution to early 20th-century German architectural debates. Plessner’s reflections are situated within the intellectual and historical context of industrialization, the unification of the German state, and the Weimar era. He critiques his contemporaries’ inability to grasp the “essence” of technology, identifying it as a root cause of the cultural, political, and social crises of the time. He advocates for creating new cultural values and aesthetic forms that balance material conditions with human freedom. In a lesser-known article on art history, Plessner critiques both Kunstwissenschaften and the rejection of form characteristic of Expressionism and Abstractism, grounding his analysis in nature’s qualitative multiplicity. This perspective transcends dichotomies such as body and mind or nature and culture while opposing the dominance of technoscientific paradigms. Within this framework, architecture emerges as a realm capable of harmonizing functional demands with aesthetic freedom, a balance understood through the human body in its entirety. Plessner’s philosophy of architecture is rooted in his 1928 philosophy of the organic, emphasizing “living form” as a tension between Gestalt and Gestaltung. During the same period, modern architects integrated these ideas, drawing from philosophical biology to reconcile industrial technology with aesthetic needs. Plessner’s lecture on the “open form,” presented to the Deutscher Werkbund, exemplifies one possible way to conceptualize this reconciliation
Advanced robot hand myoelectric control strategies for improved human-robot interaction
Get PDFHuman hands -and human beings, in general- are the gold standards for researchers in the domain of robot hand design and control. Consequently, electromyographic signals represent one of the primary tools adopted in human-in-the-loop robot hand control applications. Indeed, myoelectric control has the potential to enable a natural and seamless interaction between humans and robots, thus promoting embodiment and sense of agency over the robotic device. However, the longstanding obstacles faced by myoelectric control solutions are still in place. Therefore, this thesis presents the research work carried out to address some of these challenges. The main contributions regard the development of advanced myoelectric control strategies for improved, natural, and intuitive human-robot-environment interaction. The proposed solutions suggest improvements to the myoelectric control loop from two different perspectives. Well-known challenges of intent estimation approaches (e.g., the need for point-by-point dataset labeling and the difficulty of performing nonlinear fitting) are addressed through the use of new tools, like the dynamic time warping algorithm, to build a minimally supervised regression paradigm, or through the adaptation of old tools, like non-negative matrix factorization, in a self-supervised fashion. Moreover, feedback information is exploited to design a shared autonomy framework that leverages a probabilistic approach to handle the uncertainties and variability of humans, robots, and the environment during grip strength regulation applications. Finally, a small parenthesis addresses the problem of human-robot-environment interaction in household settings from a complementary standpoint, outlining end-effector design requirements and relative quantitative analysis
Resistance to targeted therapy and immunotherapy in Non-Small Cell Lung Cancer (NSCLC) and development of novel therapeutic approaches
Get PDFLung cancer is the first cause of cancer death worldwide and has been recently declared the most common tumor in the world. Non-small cell lung cancer (NSCLC) accounts for 85-90% of lung cancers and is characterized by poor prognosis and late diagnosis. The introduction of tyrosine kinase inhibitors (TKIs) targeting oncogenic mutations has redefined treatment options for oncogene-driven NSCLC. Immune checkpoint inhibitors (ICIs) have also provided a breakthrough in treating tumors with unknown or undruggable mutations. However, therapeutic resistance remains a major challenge, often driven by tumor heterogeneity and resistant subclonal populations that lead to disease progression despite initial responses. Additionally, some mutations currently lack effective therapies, leaving patients underserved by treatments. This PhD project aimed to investigate the mechanisms of resistance to these therapies, identify prognostic markers of therapy response and explore novel strategies for NSCLC treatment. To this end, we established a panel of primary cell cultures and patient-derived xenografts from tumors of patients whose disease progressed during TKI- or ICI-based therapies. Within this panel, we focused on specific cell models, each offering unique insights into NSCLC resistance. These models allowed us to explore the role of tumor heterogeneity in TKI resistance, characterizing the ROS1-rearranged ADK-VR2 and EGFR-mutated LIBM-ADK-11 cell lines. We also examined novel strategies for tumors with orphan mutations, using the BRAF class III-mutated ADK-14 and PDX-ADK-36 cell lines. Moreover, we examined mechanisms underlying resistance or adverse responses to ICIs, including hyperprogression, utilizing the KRAS-mutated ADK-17 and ADK-18 cell lines. For this purpose, we also employed a preclinical in vivo model of ICI resistance developed in syngeneic immunocompetent mice, using the transgenic murine BoLC.8M3 cell line, which carries a KRAS mutation and is p53 knock-down. Together, these models provide a comprehensive platform to understand resistance mechanisms in NSCLC and support the development of more effective therapies
Impact of hysterectomy on quality of life in patients undergoing minimally invasive surgery for posterior deep endometriosis
Get PDFIntroduzione. L’endometriosi è una patologia cronica che colpisce il 10% delle donne in età fertile, riducendone significativamente la qualità della vita. In molti casi, le pazienti richiedono un trattamento definitivo, spesso rappresentato dall’asportazione delle lesioni endometriosiche con isterectomia totale. Tuttavia, l’isterectomia per endometriosi profonda è associata a un tasso significativo di complicanze e alcune donne riportano persistenza dei sintomi post-intervento. Questo studio mira a valutare l’efficacia e la sicurezza dell’isterectomia nelle pazienti sottoposte a chirurgia mininvasiva per endometriosi profonda rispetto a interventi che preservano l’utero.
Materiali e metodi. Questo studio prospettico di coorte ha incluso pazienti di età compresa tra i 40 e i 50 anni, suffipare, sottoposte a chirurgia laparoscopica per endometriosi profonda posteriore. La popolazione è stata divisa in due gruppi: con isterectomia (gruppo di studio) e senza isterectomia (gruppo di controllo). Sono stati raccolti dati preoperatori, incluse valutazioni dei sintomi dolorosi tramite Numerical Rating Scale (NRS) e della qualità della vita tramite questionari validati (EHP-5 e SF-12), oltre a dati perioperatori sulle complicanze. Le pazienti sono state rivalutate a 6 e 12 mesi.
Risultati. Tra novembre 2021 e agosto 2023 sono state arruolate 118 pazienti, di cui 108 hanno completato il follow-up: 38 nel gruppo di studio e 70 nel gruppo di controllo. Le pazienti sottoposte a isterectomia presentavano un’età maggiore (45.0 vs 43.0 anni, p=0.001), sintomi più severi (NRS 6.4 vs 4.4, p=0.002) e una qualità della vita peggiore (EHP-5 52.2 vs 44.3, p=0.046) al baseline. Il tasso di complicanze postoperatorie era del 25.9%, senza differenze tra i gruppi. A 6 e 12 mesi, il gruppo di studio ha mostrato miglioramenti più marcati nei sintomi e nella qualità della vita.
Conclusioni. L’isterectomia è un’opzione sicura ed efficace per pazienti affette da endometriosi con sintomi severi che desiderano un trattamento definitivo e non intendono preservare la fertilità.Introduction
Endometriosis is a chronic condition affecting 10% of women of reproductive age, significantly reducing their quality of life. In many cases, patients seek a definitive treatment, often involving the removal of endometriotic lesions through total hysterectomy. However, hysterectomy for deep endometriosis is associated with a significant rate of complications, and some women report persistent symptoms post-surgery. This study aims to evaluate the efficacy and safety of hysterectomy in patients undergoing minimally invasive surgery for deep endometriosis compared to uterus-preserving interventions.
Materials and Methods
This prospective cohort study included patients aged 40 to 50 years, with no desire for childbearing, who underwent laparoscopic surgery for posterior deep endometriosis. The population was divided into two groups: hysterectomy (study group) and uterus-preserving surgery (control group). Preoperative data were collected, including pain symptom assessment via the Numerical Rating Scale (NRS) and quality of life evaluation using validated questionnaires (EHP-5 and SF-12), as well as perioperative data on complications. Patients were reassessed at 6 and 12 months.
Results
Between November 2021 and August 2023, 118 patients were enrolled, of whom 108 completed follow-up: 38 in the study group and 70 in the control group. Patients undergoing hysterectomy were older (45.0 vs. 43.0 years, p=0.001), had more severe symptoms (NRS 6.4 vs. 4.4, p=0.002), and a worse baseline quality of life (EHP-5 52.2 vs. 44.3, p=0.046). The postoperative complication rate was 25.9%, with no differences between groups. At 6 and 12 months, the study group showed more significant improvements in symptoms and quality of life.
Conclusions
Hysterectomy is a safe and effective option for patients with severe endometriosis symptoms seeking definitive treatment and not intending to preserve fertility
Ab initio potentials for atomistic simulations via deep learning
Get PDFComputational chemists face a critical challenge in calculating molecular systems' potential energy at the quantum level. While density functional theory provides a solution, it demands substantial computational resources. To address this limitation, researchers have developed machine learning potentials that deliver near-quantum accuracy while requiring only molecular mechanics-level computational power. In this work of thesis we present OBIWAN, a novel feed-forward neural network with unique structural features that includes a new type of general-purpose neural network layer. A key advantage of OBIWAN is its efficient scaling when incorporating unseen atomic species. This design allows users to add new atom types without modifying the network's architecture. As a consequence, OBIWAN can build upon previous training when working with new datasets, leading to rapid convergence. This ability to avoid starting from scratch aligns also with sustainable computing practices by reducing overall computational requirements
Computer vision in medicine and beyond: deep learning approaches to solve real-world problems
Get PDFDeep Learning has transformed the way we analyze and interpret complex data, enabling the discovery of intricate patterns and the automation of specialized, time-consuming tasks. This thesis explores its application across various domains, with a primary focus on medical imaging but also extending to earth sciences. By leveraging computer vision, this work demonstrates how deep learning can extract meaningful information from images to address challenging problems effectively.
The research primarily employs Convolutional Neural Networks (CNNs) combined with advanced image processing techniques to enhance data quality and interpretability. Several case studies illustrate the versatility of these methods. In the medical field, deep learning is applied to electron microscopy images of kidney biopsies, where it enables precise segmentation and measurement of anatomical structures, achieving results comparable to expert assessments. Another application focuses on analyzing Whole Slide Images in the context of myeloid disorders, providing valuable prognostic insights through large-scale image analysis. The thesis also addresses the segmentation of pulmonary airways in lung fibrosis, a particularly complex task for both human experts and AI models. The proposed approach, developed as part of an international challenge, ranks among the top-performing solutions. Beyond the medical domain, deep learning is used to interpret sedimentary core images, demonstrating its ability to automate expert-driven analysis and contributing to the creation of a publicly available dataset in this field.
The methods developed in this thesis achieve state-of-the-art performance, often matching or surpassing human expertise, and underline the importance of interdisciplinary collaboration in advancing AI-driven solutions. Future directions include refining the proposed models, extending their applicability to new challenges, and integrating transformer-based architectures to enhance the processing of multimodal data
Modelling and experimentation on machines and integrated systems for energy conversion and storage based on waste heat valorization
Get PDFThe growing global energy demand and environmental concerns necessitate a transition from fossil fuels to sustainable solutions, increasing the use of renewable energy sources. Additionally, recovering low-grade waste heat from industrial processes, represents a major untapped opportunity for improving energy efficiency. However, the variability of waste heat sources necessitates customized solutions. This thesis explores advanced energy conversion technologies, focusing on Organic Rankine Cycles (ORCs), High-Temperature Heat Pumps (HTHPs), and Carnot Batteries (CBs) to optimize heat-to-power (H2P) and power-to-heat (P2H) processes.
The first part investigates ORC and HTHP applications for electricity and thermal energy generation. Experimental studies on partial evaporation in ORCs highlight their potential for ultra-low-temperature heat recovery, demonstrating stable power production even under challenging off-design conditions. A validated off-design model assesses ORC integration in residential solar thermal systems and waste heat recovery from data centers, evaluating low-GWP working fluids. Results show that while R134a maximizes power output, alternative fluids improve environmental performance. For industrial applications, an innovative HTHP-based heat recovery system for ceramic manufacturing is proposed, achieving significant fuel savings and CO2 reductions while enhancing process efficiency.
The second part examines CB integration for energy storage, improving renewable energy utilization. A novel CB prototype is developed and integrated with a district heating system, implementing an optimized rule-based control strategy to maximize economic benefits. Further analysis explores CB applications in data centers, demonstrating potential financial viability when coupled with photovoltaic power plants. Additionally, a thermodynamic assessment of a closed Brayton CB using supercritical CO2 is conducted for large-scale, high-temperature applications, identifying trade-offs between efficiency, cogeneration performance, and economic feasibility.
By combining experimental data, modelling, and techno-economic assessments, this research advances H2P and P2H technologies, supporting their industrial and residential deployment. The findings contribute to improving energy efficiency, reducing emissions, and fostering a more sustainable and resilient energy future
Design and control of a robotic manipulator for kiwi harvesting
Get PDFThis thesis presents the design and control of a robotic manipulator intended for kiwi harvesting, addressing the increasing need for automation in agriculture due to labour shortages and the pursuit of precision farming. The research introduces a novel, low-cost robotic solution integrated with a mobile platform to automate the harvesting process in kiwi orchards. The system involves the design of a custom anthropomorphic manipulator, including actuator selection, gripper design, and mobile platform integration, specifically adapted for the kiwi harvesting task. The control architecture incorporates a combination of low-level motion control on an Arduino-based platform and high-level trajectory planning using ROS 2 and MoveIt 2, allowing for efficient navigation and adaptability in an orchard environment. The perception system combines depth and RGB cameras to detect and localize fruits with high precision, enhancing the robot’s ability to autonomously identify, approach, and pick kiwi fruits. The effectiveness of the system is evaluated through simulations and field experiments, demonstrating its capability to harvest kiwis effectively while maintaining fruit quality. Future work aims to address challenges related to system robustness in diverse environmental conditions and further improve the adaptability of the harvesting mechanism
Study of Neutrino interactions on Hydrogen in the SAND detector of DUNE
Get PDFThe Deep Underground Neutrino Experiment (DUNE) is a next-generation long-baseline neutrino oscillation project. Its primary goals are to measure the possible violation phase (delta CP) and determine the sign of the mass squared difference (), which is crucial for understanding the neutrino mass hierarchy. DUNE will exploit a Far Detector consisting of four multi-kiloton Liquid Argon Time Projection Chambers (LArTPCs) and a Near Detector (ND) complex situated near the neutrino source at Fermilab.
One of the main limitations on the achievable precision on the measure of the neutrino flux, are the large uncertainties on neutrino cross-section on nuclei, which stems from the choice of a nuclear model and of final state interactions, that cannot be calculated in perturbative QCD.
The measurement of neutrino interactions on free nucleon would instead allows to minimize the uncertainties on the flux, because the neutrino cross-section on free nucleon is known with much lower uncertainty.
The SAND detector uses a low-density tracker in a magnetic field combined with a high-granularity calorimeter with high neutron detection efficiency and exceptional timing resolution to distinguish interactions on Hydrogen from those on nuclei.
This thesis explores a detailed approach to achieve precise (anti)neutrino on Hydrogen measurements by statistically subtracting interactions on thin graphite targets (pure C) from those on polypropylene (C3H6) targets (solid Hydrogen concept).
With the neutrino-Hydrogen cross-section known to percent-level precision, this study demonstrates that SAND can measure the flux with uncertainties at the few-percent level, with margins for future improvements
Design of new personalized therapeutic approaches for diffuse large B-cell lymphoma
Get PDFIl linfoma non Hodgkin B diffuso a grandi cellule è la forma più frequente di linfoma non-Hodgkin. Il 60% dei pazienti ottiene una risposta completa dopo la prima linea standard di chemioimmunoterapia. Tuttavia circa il 25% dei pazienti ha una ricaduta di malattia o progressione entro due anni dal termine del trattamento. Risulta quindi evidente come siano necessarie strategie innovative volte a migliorare e mantenere la risposta alla prima linea e ad individuare i pazienti a maggior rischio di ricaduta. Recenti ricerche sul ruolo del microbiota intestinale hanno evidenziato come questo possa influenzare il decorso della terapia attraverso meccanismi sia diretti che indiretti. Anche se preliminari, i dati indicano un possibile impatto della terapia con R-CHOP sulla struttura mutualistica del GM dell’ospite.
Alla luce di tali evidenze è stato condotto uno studio prospettico, in collaborazione con l’Istituto Tumori IRCSS di Meldola, con l’obiettivo di caratterizzare il microbiota dei pazienti affetti da DLBCL all’esordio e di valutare eventuali correlazioni con le risposte ottenute e le tossicità rilevate. I dati da noi raccolti confermano la presenza di un profilo disbiotico e pro infiammatorio del microbiota nei pazienti affetti da DLBCL all’esordio rispetto al gruppo di controllo. Nei pazienti affetti da DLBCL, al baseline e all’EOT, è stata riscontrata un'abbondanza superiore di Proteobacteria e delle famiglie Enterobacteriaceae e Streptococcaceae rispetto ai controlli.
La struttura del microbiota nel DLBCL è influenzata, e influenza a sua volta, la malattia, lo stato di sorveglianza immunitaria del paziente, la risposta alla terapia e gli effetti collaterali. Comprendere questi fattori e il loro impatto sarà fondamentale al fine di sviluppare linee terapeutiche personalizzate.Diffuse large B-cell non-Hodgkin lymphoma is the most common form of non-Hodgkin lymphoma. Sixty percent of patients achieve a complete response after standard first-line chemoimmunotherapy. However, approximately 25% of patients experience disease relapse or progression within two years of completing treatment. It is therefore clear that innovative strategies are needed to improve and maintain first-line response and identify patients at greatest risk of relapse.
Recent research on the role of the intestinal microbiota has highlighted how it can influence the course of therapy through both direct and indirect mechanisms. Although preliminary, the data indicate a possible impact of R-CHOP therapy on the mutualistic structure of the host GM.
In light of these evidences, a prospective study was conducted, in collaboration with the IRCSS Cancer Institute of Meldola, with the aim of characterizing the microbiota of patients with DLBCL at onset and of evaluating any correlations with the responses obtained and the toxicities detected.
The data we collected confirm the presence of a dysbiotic and pro-inflammatory profile of the microbiota in patients with DLBCL at onset compared to the control group. In patients with DLBCL, at baseline and at EOT, a higher abundance of Proteobacteria and the Enterobacteriaceae and Streptococcaceae families was found compared to controls.
The structure of the microbiota in DLBCL is influenced by the disease, the patient's immune surveillance status, the response to therapy and side effects. Understanding these factors and their impact will be fundamental in order to develop personalized therapy