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Effects of asymmetric nasal high flow cannula on carbon dioxide in hypercapnic patients: a randomized crossover physiological pilot study.
Get PDFIntroduction and Objectives: Nasal high flow (NHF) therapy is an established form of non-invasive respiratory support, used in both acute and chronic care. A new high-flow nasal cannula with asymmetric prongs has recently been approved, but its clinical benefits remain undefined, especially for patients with Chronic Obstructive Pulmonary Disease (COPD). This doctoral thesis explores potential mechanisms through which NHF may benefit stable COPD patients, based on current literature. Additionally, it presents a physiological study comparing two nasal cannulas (asymmetric vs. standard) in hypercapnic COPD patients conducted at the Respiratory and Critical Care Unit, IRCCS Azienda Ospedaliero Universitaria di Bologna (CODUET Study).
Patients and Methods: A single-center, prospective, crossover, randomized study was conducted to evaluate the effects of two different nasal interfaces (asymmetric vs. standard) on partial pressure of carbon dioxide (PaCO2) levels in 20 hypercapnic COPD patients recovering from acute severe exacerbations. Inclusion criteria were COPD patients with FEV1/FVC 50 mmHg and pH > 7.35). Each patient underwent two 90-minute trials of NHF with either the asymmetric or standard nasal cannula, with a 60-minute washout period between treatments.
Results: Both the asymmetric and standard NHF interfaces effectively reduced PaCO2 levels, with similar outcomes in diaphragm activity, dyspnea, and patient comfort. However, the asymmetric NHF cannula was notably more effective in reducing dead space ventilation and improving ventilatory efficiency, particularly in more severe COPD patients with baseline PaCO2 ≥ 65 mmHg.
Conclusions: While the overall clinical benefit of NHF remains unclear, the study suggests potential advantages of NHF, particularly the asymmetric cannula, in reducing dead space and improving ventilatory efficiency in COPD patients with severe hypercapnia. Both cannulas performed similarly in reducing PaCO2 and improving patient comfort, but the asymmetric design may offer specific benefits for patients with advanced disease
Biosignatures from extreme environments as targets for astrobiological exploration
Get PDFThis PhD thesis focused on a comparative study of stromatolite occurrences in three highly alkaline, basalt-hosted lacustrine environments: Lake Ashenge (Ethiopia), Lake Abbe (Djibouti) and Carri Laufquen Lakes (Argentina). These ecosystems present occurrences of stromatolites observed to grow along the shorelines of (palaeo)lakes and around basaltic substrates, and may have formed in analogous environmental conditions to Jezero crater, a palaeolacustrine system on Mars. A multi-analytical approach was employed to characterise stromatolite formations. Although each site displays distinct macroscale morphologies, they exhibit comparable micromorphologies and microstructures on a microscale, suggesting shared formation process. We proposed two mechanisms of mineralisation: 1) primary precipitation via nanocrystal aggregation; and 2) early diagenetic replacement. Microscopy and spectroscopy analysis revealed biomineralised remnants of stromatolitic biomass, including microbial mats, filamentous cyanobacterial microfossils, and extracellular polymeric substances (EPS) preserved as Mg-bearing carbonates. EPS played a role in both mechanisms of mineralization. Raman and FTIR combined with 13C-NMR demonstrated the preservation of aromatic and aliphatic organic material within filamentous microstructures, likely derived from primary microbial communities. Morphological and geochemical data suggest that photosynthetic organisms dominated these ecosystems, forming microbial mats and palisade structures, preserved in situ. Mineralogical characterisation indicates that Mg-Al-bearing silicates, including phyllosilicates, are associated with filamentous structures and play crucial role to their preservation. This study introduces a novel analytical approach as the first to apply 13C-NMR to lacustrine stromatolites and, to our knowledge, providing the first detailed description of Lake Ashenge stromatolites. Key findings include insights into the organomineralization mechanisms within EPS biofilm, the relationship between sheaths preservation and Mg-Al-silicates, the influence of basaltic substrates on stromatolite formation, and the evaluation of the study areas as planetary field analogues. Studying terrestrial Martian palaeolake analogues is valuable for understanding microbial ecosystems and their fossilization models, as Martian carbonates are particularly promising for preserving ancient life evidence
Post-transplant glomerular diseases recurrence
Get PDFIntroduzione. La recidiva delle nefropatie glomerulari post-trapianto è una importante causa di perdita dell’organo. Le nefropatie come la glomerulosclerosi segmentaria e focale (FSGS), la nefropatia a depositi mesangiali di IgA (IgAN) e la glomerulonefrite membranosa idiopatica (MN) frequentemente recidivano, influenzando negativamente la sopravvivenza del graft. Tuttavia, la conoscenza sull’incidenza e i fattori di rischio di queste recidive è ancora limitata, poiché la maggior parte dei dati proviene da piccoli studi monocentrici. Nel 2017 è stato avviato il progetto TANGO, un network internazionale per raccogliere dati da Centri Trapianti di tutto il mondo. Obiettivi e metodi. Sono stati effettuati tre studi retrospettivi in cui ciascun Centro partecipante ha raccolto dati di pazienti sottoposti a trapianto dal 2005 al 2015 per IgAN e FSGS primitiva, dal 2005 al 2020 per MN idiopatica. Risultati. La recidiva di FSGS si è verificata nel 32% dei casi, con un tasso di perdita del graft del 39%. I fattori di rischio includevano età avanzata all’esordio della nefropatia, BMI più basso e nefrectomia dei reni nativi. Il trattamento più comune era la plasmaferesi associata al Rituximab (RTX), con un 57% di remissioni complete o parziali. Per IgAN, l'incidenza della recidiva è stata del 23% a 15 anni, con un rischio maggiore in caso di DSA preformati o de novo e trapianto pre-emptive. La recidiva aumentava significativamente il rischio di perdita del graft. Per la MN, la recidiva a 10 anni è stata del 31%, con un rischio maggiore se elevato titolo degli anticorpi anti-PLA2R. Il trattamento con RTX era associato a maggiore remissione e ridotto il rischio di perdita del graft. Conclusioni. La recidiva post-trapianto di FSGS, IgAN e MN ha un impatto significativo sulla sopravvivenza del graft. Il network TANGO garantisce una rappresentazione “real life” della problematica, aumentando la dimensione del campione di studio.Background. Post-transplant glomerular diseases recurrence is an important cause of graft loss. Nephropathies such as focal and segmental glomerulosclerosis (FSGS), IgA nephropathy (IgAN) and idiopathic membranous nephropathy (MN) frequently recur, negatively affecting graft survival. However, knowledge about the incidence and risk factors for recurrence is still limited, as most data comes from small monocentric studies. In 2017, the TANGO project was launched, an international network designed to collect data from transplant centers around the world. Objectives and Methods. Three retrospective studies were conducted in which each participating center collected data from patients who underwent transplantation from 2005 to 2015 for primary IgAN and FSGS, and from 2005 to 2020 for idiopathic MN. Results. FSGS recurrence occurred in 32% of cases, with a graft loss rate of 39%. Risk factors included older age at nephropathy onset, lower BMI, and nephrectomy of native kidneys. The most common treatment was plasma exchange (PEX) combined with Rituximab (RTX), with 57% of cases achieving complete or partial remission. For IgAN, the recurrence rate was 23% at 15 years, with higher risk in cases of preformed or de novo donor-specific antibodies (DSA) and preemptive transplantation. Recurrence significantly increased the risk of graft loss. For MN, the recurrence rate at 10 years was 31%, with a higher risk associated with high levels of anti-PLA2R antibodies. RTX treatment was associated with higher remission rates and reduced graft loss risk. Conclusions. Post-transplant recurrence of FSGS, IgAN, and MN has a significant impact on graft survival. The TANGO network provides a "real life" representation of this issue, increasing the study sample size
Multilevel modeling and simulation: methodologies and applications
Get PDFMultilevel modeling and simulation is a methodology that involves the hierarchical decomposition of complex systems into modular, cooperating components, each representing specific aspects of interest. The motivations behind this approach can vary widely, including the ability to leverage existing software, the need for different levels of abstraction and granularity, or the opportunity to better organize model development by separating semantically distinct aspects.
This thesis presents a comprehensive study of multilevel modeling and simulation techniques, providing an overview of their use in scientific literature and discussing the design principles and key issues involved.
The analysis of the current state of the art reveals that while multilevel modeling is widely used across various scientific fields, little effort was directed toward formal and methodological aspects. As a result, there are no precise standards for the design of such models, and ambiguities exist starting with the terminology. To address this gap and better define potential approaches for building a multilevel framework, the thesis proposes some categories of design patterns that address some critical aspects that may be encountered during the development phase, and a metamodel crafted to enhance multilevel modeling clarity and effectiveness.
The proposed design principles were ultimately applied to create multilevel simulations for IoT applications, with a focus on developing a decentralized, efficient sensor data marketplace. This scenario leverages technologies like LoRa and blockchain to support secure and scalable data exchange. Given the complexity of factors involved — including mobility, physical message propagation, data storage and trading — multilevel modeling has proven to be exceptionally effective in managing the complex interactions and dependencies among these components
Optimization of ML-Based BSM triggering with knowledge distillation for FPGA implementation in the CMS Level-1 trigger
Get PDFThe High Luminosity LHC (HL-LHC) Project, launched in 2010, aims to boost the luminosity of the Large Hadron Collider (LHC) at CERN in Geneva tenfold to enhance discoveries and precision measurements. The higher collision rate and pileup will increase particle multiplicity and radiation, requiring improvements in the Trigger system to sustain performance.
In this context, the scope of applications for Machine Learning, particularly Artificial Neural Network algorithms, has experienced an exponential expansion due to their considerable potential for elevating the efficiency and efficacy of data processing in this experimental setting. However, a key challenge in ANN deployment is optimizing data processing for online applications, especially in selecting rare events at the trigger level, such as Beyond Standard Model (BSM) events. This study explores Autoencoders (AEs), which detect anomalies without theoretical priors. Yet, the stringent latency and energy constraints in the Level-1 Trigger domain at CERN’s Compact Muon Solenoid (CMS) require tailored software and hardware strategies, focusing on Field Programmable Gate Arrays (FPGAs). To address this, Knowledge Distillation (KD) is investigated, using a well-trained AE “teacher” to train a compact “student” model for FPGA implementation.
This distillation process can be optimized by refining student architecture, weight quantization, and hyperparameters to balance accuracy, latency, and hardware footprint.
The Offline Response Based KD strategy for the teacher model will be presented, including performance differences when applying quantization before or after selecting the best student architecture. The process of converting a Python-based model into FPGA firmware using hls4ml and proprietary FPGA software will also be detailed. Additionally, Online Response Based KD was explored, with preliminary results provided.
Finally, a new teacher model using a Graph Convolutional Neural Network-based AE was tested for anomaly detection, due to the possibilities opened up by KD to implement advanced algorithms on efficient hardware
Clinical validity and utility of network analysis in clinical practice
Get PDFThis dissertation aims to investigate the clinical validity and utility of fully idiographic network analysis (FINA) in clinical practice. Moving from an exploration of FINA empirical research using FINA to estimate person-specific networks in individuals with mental health conditions, it then explores FINA’s potential in clinical practice. Chapter 1 presents an introduction on the importance of exploring the validity and utility of network analysis in clinical practice. Chapter 2 presents a systematic scoping review of studies applying FINA in mental health, highlighting common methodological practices and trends, while identifying areas for improvement. This review sets the stage for understanding how FINA has been applied to date and highlights further developments needed for its effective application in clinical research and practice. Chapter 3 describes an empirical study testing the clinical validity and utility of FINA by comparing empirical symptom networks, estimated on patient data using FINA, with clinician-predicted symptom networks in their ability to predict subsequent patient functioning. Additionally, the study explores both clinicians’ and patients’ perspectives on FINA’s utility in routine clinical settings. Chapter 4 presents a general discussion on the clinical validity and utility of using NA to construct person-specific networks, with a focus on the findings, limitations, and implications of both the scoping review and empirical study, as well as directions for future research. The overarching goal of this dissertation is to advance personalized, data-driven approaches in clinical psychology by examining the clinical validity of FINA and evaluating its applicability in clinical practice. This work assesses FINA’s potential as a tool for predicting patient functioning and improve treatment through support for more individualized interventions
The object of the employment contract in Industry 4.0. Ius variandi, economic dismissal and role of the trade union.
Get PDFLa presente ricerca indaga gli impatti che Industria 4.0 ha sull’oggetto del contratto di lavoro, in particolare relativamente a due istituti specifici della disciplina giuslavoristica: lo ius variandi e il licenziamento per giustificato motivo oggettivo.
La descrizione dei cambiamenti tecnologici ed organizzativi apportati da Industria 4.0, che viene formulata nel primo capitolo, permette di com-prendere in quale maniera muti la prestazione offerta dal lavoratore. Si ve-rifica in particolare quella che viene definita come soggettivazione della prestazione di lavoro.
Chiarito questo, nel secondo capitolo si prende in esame la disciplina che consente la modifica dei compiti richiesti al lavoratore, per vedere come questo impatti sulla mutata professionalità offerta dal dipendente nei nuovi contesti industriali. Emerge in particolare l’importanza della distinzione tra ius variandi strettamente inteso e potere organizzativo.
Nel terzo capitolo invece si pone l’attenzione sul licenziamento per giusti-ficato motivo oggettivo, che rappresenta la fattispecie chiaramente più de-licata che investe l’attività lavorativa della persona. Proprio per questa ra-gione viene messo in luce come i moderni scenari del lavoro richiedano oggi più che mai la definizione di canoni normativi chiari per il gmo.
Nell’ultimo capitolo, si tenta di tracciare una delle rotte che è possibile seguire per affrontare le problematiche descritte nel corso della tesi. In particolare, si esamina il ruolo che possono giocare i sindacati di fronte alla transizione digitale, suggerendo un approccio collaborativo volto alla co-determinazione delle scelte datoriali riguardanti gli istituti oggetto del presente studio.This research investigates the impacts that Industry 4.0 has on the object of the employment contract, in particular with regard to two specific institutions of the labor law discipline: the ius variandi and dismissal for objective justified reason.
The description of the technological and organizational changes brought about by Industry 4.0, which is formulated in the first chapter, allows us to understand how the performance offered by the worker changes. In particular, what is defined as the subjectivation of the work performance occurs.
Having clarified this, in the second chapter we examine the discipline that allows the modification of the tasks required of the worker, to see this impact on the changed professionalism offered by the employee in the new industrial contexts. In particular, the importance of the distinction between ius variandi strictly understood and organizational power emerges.
In the third chapter, instead, attention is placed on dismissal for objective justified reason, which represents the clearly most delicate case that affects the working activity of the person. Precisely for this reason, it is highlighted how modern work scenarios require today more than ever the definition of clear regulatory standards for the gmo. In the last chapter, an attempt is made to trace one of the routes that can be followed to address the problems described throughout the thesis. In particular, the role that unions can play in the face of digital transition is examined, suggesting a collaborative approach aimed at co-determining employers' choices regarding the institutions that are the subject of this study
Environmental sustainability assessments associated with industrial production processes and resource recovery
Get PDFThe urgency of ensuring future generations the right to live on a healthy planet, while maintaining a decent quality of life, is reflected in the increasing interest in research on improving the environmental performance of industrial processes and supply chains. In this context, the Life Cycle Assessment methodology represents a valuable tool for estimating the potential environmental impacts associated with products, systems, services, and activities. The project consisted of applying LCA and complementary methodologies to processes at both industrial and laboratory scales, in various sectors and fields. The first was water sustainability, where the environmental performances of a potable water supply system were assessed, and the existing water-energy nexus was explored. In the food sector context, an environmental indicator was developed to evaluate the implications of consumers' eating habits into a single comprehensive score, including all the life cycle of meal’s ingredients. Concerning waste valorization, systems for converting waste into valuable resources were examined, identifying the most promising strategies from an environmental perspective. Studies were also conducted on alternative food packaging formulations, highlighting the significant contribution on the total impacts of the manufacturing phase. Lastly, the future challenges related to the environmental sustainability of cryptocurrency mining were examined, finding that the electricity mix decarbonisation is not enough to reduce global warming if it is not accompanied by a reduction of the consumed electricity. Such applications led to the opportunity to develop new methodological approaches to improve the LCA framework, which is solid yet evolving. The studies confirmed the potential of the tool to support the growing public awareness of environmental issues and to assist the policies to reduce the environmental impacts of the anthroposphere at both national and global levels, helping educate citizens interested in environmental sustainability, using a clear and concrete tool to foster greater awareness on the topic
The settlement of southern Mesopotamia from the 5th millennium BCE to the mid-2nd Century CE: a study of settlement archaeology based on remote sensing, predictive models, and field survey data
Get PDFQuesto progetto di ricerca mira a individuare e comprendere lo sviluppo del popolamento e delle strategie di sfruttamento del territorio nell’area dell’alluvio mesopotamico, da Balad fino ad Al-Qurna, dal V millennio a.C. alla metà del II millennio d.C. (dal periodo Ubaid al periodo islamico). La ricerca integra i dataset di FloodPlains (Marchetti et alii 2024), metodologie di remote sensing e machine learning, con l’obiettivo di tracciare un quadro complessivo sull’interazione tra ambiente e società, in uno dei paesaggi più dinamici dell'antichità. In aree mai indagate in precedenza, l’uso di tecniche di intelligenza artificiale ha permesso di automatizzare le analisi di remote sensing, validate successivamente tramite indagini sul campo. Tra le ricognizioni chiave si evidenziano la ricognizione edita e sistematizzata dei dati QADIS e la più recente indagine di Abu Ghraib, con l’obiettivo di approfondire la comprensione delle strutture insediative e della rete idrica antica. Una verifica empirica della linea di costa nell’area del distretto di Amara, ha inoltre fornito una base preliminare per la comprensione della configurazione storica della linea di costa e delle dinamiche insediamentali legate alla progradazione del delta. L'integrazione di questi approcci, unita a un'analisi paleoambientale, permette di tracciare un quadro complesso e dettagliato dei modelli di insediamento e delle dinamiche di sfruttamento del territorio, fornendo un contributo significativo allo studio del popolamento nell'antica Mesopotamia meridionale.This research project aims to identify and understand the development of settlement patterns and land-use strategies in the Mesopotamian alluvium, from Balad to Al-Qurna, spanning from the 5th millennium BCE to the mid-2nd millennium CE (from the Ubaid period to the Islamic period). The study integrates datasets from FloodPlains (Marchetti et alii 2024), remote sensing methodologies, and machine learning techniques to provide a comprehensive overview of the interaction between environment and society in one of the most dynamic landscapes of antiquity. In previously unexplored areas, the use of artificial intelligence techniques has enabled the automation of remote sensing analyses, which were subsequently validated through field surveys. Key investigations include the edited and systematized survey of QADIS data and the more recent Abu Ghraib survey, both aimed at enhancing the understanding of settlement structures and ancient water networks. Additionally, an empirical verification of the coastline in the Amara district has provided a preliminary basis for understanding the historical configuration of the coastline and settlement dynamics related to the delta's progradation. The integration of these approaches, combined with paleoenvironmental analysis, allows for the reconstruction of a complex and detailed picture of settlement patterns and land-use dynamics, offering a significant contribution to the study of ancient settlement in southern Mesopotamia
Cytokine storm-associated encephalopathies
Get PDFBackground and Aims: Cytokine storm-associated encephalopathies arise in response to severe inflammatory conditions and include neurotoxicity related to CAR-T cell therapy (ICANS), neuro-COVID, and febrile infection-related epilepsy syndrome (FIRES). This PhD research explores key biomarkers and clinical manifestations associated with each of these disorders, focusing on the roles of EEG in predicting ICANS, S100B and neurofilament light chain (NfL) in neuro-COVID, and anatomo-electroclinical features in FIRES. Methods: a prospective cohort of CAR-T recipients was assessed with a standardized protocol, involving EEGs recorded before and after infusion to investigate their predictive value for ICANS. For neuro-COVID, S100B and NfL serum levels were analyzed in COVID-19 patients with and without neurological symptoms to assess their diagnostic and prognostic utility. FIRES cases were evaluated to characterize clinical and investigative features. Results: among 68 CAR-T therapy patients, 22 (32%) developed ICANS, the majority of whom had features consistent with a frontal-lobe encephalopathy; two died due to fulminant cerebral edema. EEG abnormalities, particularly theta and delta slowing, were predictive of ICANS. In 279 COVID-19 patients, elevated NfL levels corresponded with Neuro-COVID disease severity, whereas S100B results were less consistent. Four FIRES patients had anatomo-electroclinical features consistent with neuroinflammation and was associated with secondary sclerosing cholangitis in critically ill patients. Discussion: this research highlights the significance of identifying biomarkers and electroclinical features in cytokine storm-associated encephalopathies and lays the groundwork for translational studies aiming to apply diagnostic and therapeutic findings across these syndromes. Future research should prioritize validation of multi-biomarker panels and cross-condition comparisons