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Induzione del fenotipo osteogenico in cellule staminali mesenchimali umane mediata da apatite multi-drogata contenente ioni Ga, Mg, Sr e Zn
No full textL’elevata incidenza di fratture ossee rappresenta il motivo di una richiesta crescente di metodi innovativi per un loro trattamento efficace. Infatti, sebbene il tessuto osseo abbia una naturale capacità rigenerativa, questa non è sufficiente in caso di difetti estesi.
L’ingegneria dei tessuti biologici opera in questo contesto attraverso la produzione di biomateriali: materiali naturali o sintetici che interagiscono con sistemi biologici al fine di supportare, riparare o sostituire tessuti.
Utilizzare biomateriali stimolanti che inducano la produzione di concentrazioni ottimali di fattori di crescita nelle cellule prossime alla frattura al fine della guarigione può infatti facilitare il risanamento dell’osso danneggiato. Inoltre la presenza di cellule staminali mesenchimali nei tessuti adulti suggerisce la possibilità di indurne differenziamento verso il fenotipo osteogenico.
Biomateriali particolarmente promettenti per questo scopo sono le apatiti sintetiche, in quanto altamente compatibili con la parte minerale dell’osso, costituita prevalentemente da uno specifico tipo di apatite che è l’idrossiapatite.
Una strategia presentata in numerosi studi recenti consiste nel “drogare” biomateriali promettenti con ioni dotati di differenti proprietà, in modo da creare loro combinazioni che accelerino la guarigione. In questo elaborato viene illustrato l’effetto ottenuto mediante drogaggio di apatite con ioni gallio, magnesio, stronzio e/o zinco, singolarmente e in sinergia. Nei primi due capitoli verranno fornite conoscenze di base sulle cellule staminali mesenchimali e sul tessuto osseo, descrivendo quindi, nel terzo capitolo, il valore degli ioni nel processo di rigenerazione ossea
Hybrid Moving Bed Biofilm Reactor under different conditions for Increased Diclofenac Removal from Wastewater
Get PDFPharmaceutical micropollutants are a growing concern for aquatic ecosystems, with diclofenac (DCF) standing out due to its high use, persistence, and toxicity. Conventional wastewater treatment plants (WWTPs) cannot fully remove pharmaceuticals, causing continuous emissions into rivers and lakes. This has led to tighter regulations, such as Switzerland’s Water Protection Ordinance (limit 0.05 µg/L) and the EU Directive 2024/3019, which requires at least 80% removal of selected drugs.
This study tested a pilot-scale Hybrid Moving Bed Biofilm Reactor (HMBBR) as a retrofittable biological option for DCF elimination under real wastewater conditions. Objectives were to assess biofilm growth on clean carriers and the effect of sludge retention time (SRT) on biofilm colonization and micropollutant removal. A three-line pilot plant operated for 112 days with SRTs of 2, 3, and 5 days. Batch tests compared biofilm carriers with suspended activated sludge from pilot- and full-scale WWTPs.
Results showed successful biofilm development on clean carriers while maintaining stable removal of carbon, nitrogen, and phosphorus. Shorter SRTs promoted faster biofilm formation and better DCF removal: at influent concentrations of 10 µg/L, elimination reached 80% at 2 days SRT, versus 72% and 67% at 3 and 5 days. Batch experiments confirmed that biofilm-associated biomass degraded DCF more effectively than suspended sludge, emphasizing the central role of biofilms.
Overall, findings indicate that reducing SRT shifts functional capacity from suspended to attached biomass, improving both nitrification and micropollutant elimination. HMBBRs therefore show promise as cost-effective and flexible technologies for advanced pharmaceutical treatment. Future work should examine long-term biofilm dynamics, links between nitrification and DCF degradation, microbial communities involved, and techno-economic feasibility to enable large-scale application
Previsione e razionalizzazione del fabbisogno ricambi. il caso IEMCA.
No full textLa gestione dei ricambi rappresenta un elemento strategico per garantire disponibilità e continuità operativa, richiedendo al tempo stesso un attento bilanciamento tra livello di servizio e immobilizzo di capitale a magazzino. In questo contesto, la previsione del fabbisogno gioca un ruolo centrale, poiché previsioni più accurate permettono di dimensionare le scorte riducendo rischi di stock-out e overstock.
La tesi affronta in modo integrato gestione economica dei ricambi e previsione della domanda. Dopo una prima parte teorica dedicata ai modelli classici di gestione e ai metodi previsionali consolidati, vengono analizzate tecniche avanzate di machine learning e deep learning, con particolare attenzione alla clusterizzazione tramite k-means e alle reti neurali multilayer perceptron (MLP).
L’attività applicativa, svolta nell’ambito di un tirocinio aziendale, ha previsto due fasi interconnesse. In primo luogo, è stata ricostruita la situazione attuale (as-is) del magazzino ricambi, individuando criticità gestionali e proponendo interventi migliorativi a breve, medio e lungo termine. In secondo luogo, sono stati sperimentati diversi modelli predittivi per la stima del fabbisogno, confrontando approcci di machine learning e deep learning su dati storici aziendali. I risultati hanno mostrato che, nelle condizioni attuali e con i dataset disponibili, non è stato possibile individuare metodi previsionali pienamente affidabili , ma l’analisi ha permesso di evidenziare potenzialità e limiti delle diverse tecniche, fornendo indicazioni utili per sviluppi futuri.
In conclusione, il lavoro dimostra come l’integrazione tra gestione economica del magazzino e metodologie di previsione rimanga una prospettiva promettente sebbene non siano stati ancora raggiunti risultati soddisfacenti sul piano previsionale
Studio e progettazione di un pre-amplificatore a basso rumore per trasduttori direzionali
No full textLa riduzione del rumore riveste un ruolo determinante ai fini dell'acquisizione accurata di segnali e la conseguente estrazione delle grandezze di interesse. Ciò si applica, in particolare, a segnali ultrasonici acquisiti da particolari trasduttori chiamati Frequency Steerable Acoustic Transducers (FSAT) che permettono di orientare la direzione di propagazione del fascio in funzione del contenuto spettrale dell’onda incidente/trasmessa. Tuttavia, l'interfacciamento elettronico può essere critico a causa della bassa ampiezza dei segnali prodotti e della loro sensibilità ai disturbi.
Il presente lavoro si concentra sullo studio e la progettazione di configurazioni circuitali a basso rumore atte a costituire il front-end elettronico, preservando il più possibile la qualità del segnale acquisito. Dopo avere provveduto alla modellazione elettrica dell'FSAT, sono state analizzate soluzioni già presenti in letteratura, adattandoli ai casi specifici, e sono stati valutati con attenzioni gli amplificatori operazionali e i componenti di filtraggio.
Le simulazioni effettuate hanno inoltre mostrato che l’approccio consente di ridurre in modo significativo il rumore complessivo, mantenendo la sola componente utile del segnale. I risultati ottenuti confermano la possibilità di avere un’interfaccia elettronica funzionale, capace di garantire stabilità e alta qualità del segnale in uscita, un requisito fondamentale per l'uso dei trasduttori FSAT in applicazioni reali
Sintesi e caratterizzazione di poliesteri fluorescenti
No full textLa crescente richiesta di materiali avanzati per applicazioni in campo biomedico, diagnostico e sensoristico ha spinto lo sviluppo di nuove classi di polimeri altamente ingegnerizzati, capaci di rispondere alle esigenze tecnologiche. In questo quadro la presente tesi riporta la progettazione, sintesi e caratterizzazione di poliesteri fluorescenti ottenuti tramite polimerizzazione di monomeri funzionalizzati contenenti fluorofori dichetopirrolopirrolici (DPP). Il processo di polimerizzazione è stato ottimizzato per ottenere pesi molecolari tali da massimizzare l’intensità della fluorescenza senza influenzare negativamente la processabilità. Particolare attenzione è stata dedicata allo sviluppo di polimeri meccanocromici, in grado dunque di modificare le proprie caratteristiche ottiche al variare dello stress meccanico applicato ad essi. Questo comportamento è stato ottenuto grazie a fenomeni come interazioni π–π tra segmenti fluorofori in catena. Nello specifico, sono state valutate diverse strutture, con un focus su materiali reticolati e blend fisici tra polimero fluorescente e matrici elastomeriche. I materiali così ottenuti mostrano cambiamenti reversibili della fluorescenza in risposta a stress, rendendoli promettenti per l’impiego come sensori strutturali o per il monitoraggio in tempo reale di deformazioni meccaniche per applicazioni ingegneristiche. Parallelamente, i poliesteri fluorescenti sono stati nanostrutturati per ottenere materiali facilmente processabili in ambiente acquoso e quindi potenzialmente impiegabili in ambito biomedico. In particolare, il lavoro è stato focalizzato sull’ottenimento di nanoparticelle stabili in acqua, eliminando dunque il problema dell’utilizzo di solventi organici e della stabilità del polimero in soluzione, attraverso tecniche di emulsione ed evaporazione. L’introduzione di diverse quantità di surfattante ha portato all’ottenimento di nanoparticelle dall’elevata riproducibilità e stabilità, con diametro fino a 22 nm
Recyclable composites based on thermoreversible resins reinforced with recycled carbon fibres
No full textComposite materials combine excellent mechanical properties with low density, finding applications from aerospace to sports and electronics. However, their cross-linked nature makes end-of-life management challenging, raising concerns about sustainability. Current recycling methods focus mainly on recovering carbon fibres, while matrix recovery remains problematic. To address this, thermosets with inherent recyclability offer opportunities to reduce waste, recover valuable components, and extend material lifespan through self-healing. Building on the expertise of Picchioni’s group in self-healing furan/maleimide systems and Giorgini’s group in composite recycling, this research develops recyclable composites based on thermoreversible resins reinforced with recycled carbon fibres. A polyketone (PK30) was functionalised at different levels, cross-linked with a bio-based bismaleimide, and fully characterised (EA, FT-IR, NMR, TGA, DSC). Finally, composites with 30 wt% recycled T700 fibres were produced and tested, including after several recycling steps
An analysis of the UK’s response to post-Brexit hospitality workforce shortages: revisiting the BHA-KPMG 2017 report
No full textIn 2016, the UK made a shocking decision to withdraw from the EU (i.e. Brexit), including the Single Market and the Freedom of Movement. As an industry with high reliance on EU workers, hospitality was significantly affected by the sudden drop in their main foreign labour supply. This thesis reviews the KPMG 2017 report for the British Hospitality Association (BHA) and aims to evaluate the capability of the Youth Mobility Scheme and wage increase strategies in solving the sector’s recruitment issues, as well as providing an update on the workforce trends and patterns four years after the Brexit transition completed. Since the timeline coincides with the coronavirus pandemic, it is also mentioned to account for any potential overlapping effects. A quantitative design is applied on secondary data collected from official agencies. With the use of various analytical software, the data was processed and examined. The findings indicates that despite the sharp decline in EU migrants, the industry has, at least temporarily, recovered to its pre-Brexit (i.e. pre-2020) operational levels. The Youth Mobility Scheme appears to have effectively expanded the foreign labour replacements, which has been crucial in easing the hospitality workforce requirements. Although both wage and the number of British employees has experienced a small increase, the industry’s real median wage is still considerably below the UK average, thus they couldn’t be responsible for these new hires. Moreover, in line with the 2017 report’s projections, the sector’s growth rate has dropped resulting from the UK’s separation from the EU. Due to the data limitations and the fact that the impacts of Brexit are still unfolding, the study suggests a need for future updates and explorations into other potential measures
Best practices in cycling tourism: insights from a comparative analysis of Mallorca and Romagna
No full textThis thesis explores the role of cycling tourism as a strategic tool to address seasonality in coastal destinations. Traditional seaside tourism in Mediterranean countries is highly concentrated in the summer months, leading to economic and environmental challenges during low seasons. Cycling tourism offers a sustainable opportunity to diversify tourism activities and extend the visitor season. Drawing on academic literature and best practice frameworks, the research adopts a comparative case study approach, analyzing Mallorca (Spain) as a well-established cycling destination and Romagna (Italy) as an emerging one. Using institutional websites, promotional materials, and tourism data, nine best practice indicators, derived from Mundet et al. (2022), were examined across both destinations. The analysis highlights Mallorca’s strong infrastructure, climate advantages, and event portfolio, which have consolidated its international reputation. Romagna, despite being at an earlier stage, demonstrates strategic innovation through targeted marketing, specialized services, and integration of cycling with cultural and gastronomic experiences. The study concludes that cycling tourism can play a significant role in mitigating seasonality by attracting different visitor segments in shoulder seasons, supporting local economies, and promoting sustainable tourism development. These findings offer valuable insights for coastal destinations seeking to diversify their tourism offer and enhance competitiveness
Towards the development of air quality digital twin
No full textNowadays, digital twin models are being implemented by cities to manage multiple factors through a single tool, enabling real-time assessment and prediction of policy impacts. This includes monitoring atmospheric conditions, particularly pollutant concentrations, through hyper-realistic models known as air quality digital twins.
Since 2023, the city of Bologna has been developing its own digital twin project. This thesis contributes to it by evaluating the compatibility between state-of-the-art air quality models—those extracting roughness from bulk morphometric parameters—and nearly continuous aerodynamic roughness values derived from DEMs within the digital twin framework.
The main goal is to assess the impact on air quality predictions of using very high-resolution geometrical data obtained from aerial orthophotos, acquired during the digital twin’s development. To this end, the ADMS-Urban dispersion model was run in several configurations, differing in methodology and spatial resolution of urban geometry inputs.
Although prior studies show that changes in spatial resolution affect aerodynamic roughness and, subsequently, pollutant dispersion, this work stands out due to the refined definition of the alternative geometry. It compares pollutant concentrations and roughness values derived from bulk parameters versus high-definition Lidar data over a short summer 2023 period, when intensive field measurements and aerial scans were conducted.
Roughness based on Lidar data is systematically higher, often leading to lower pollutant concentrations, mainly due to increased resolution. Yet, the high-resolution models don’t consistently outperform traditional models; improvements appear only for some pollutants and stations. While this method isn't ready for operational use, the observed spatial variability influence encourages further integration between these two approaches
Pivoting as a necessary strategy in startup development: a literature perspective and the Econova-AI case
No full textThis thesis investigates strategic pivoting as a fundamental capability in the lifecycle of startups, examining its theoretical foundations, determinants, and practical implications. It explores how founding dynamics, early funding strategies, and evolving environmental conditions interact to shape a venture’s capacity to adapt its business model in response to market, technological, and regulatory changes. While the existing literature often treats founding, financing, and pivoting as isolated phenomena, this work argues for an integrated perspective, demonstrating how their interplay determines a startup’s long-term adaptability.
Through an extensive literature review, the study develops a conceptual framework linking founding decisions and resource acquisition strategies to pivoting success. This framework is then applied to the case of Econova-AI, an Italian deep-tech startup operating at the intersection of artificial intelligence and sustainability regulation. Econova-AI’s evolution, from an ESG reporting platform to broader AI-driven sustainability solutions, Illustrates how ventures can leverage strategic pivoting to navigate regulatory uncertainty, shifting customer needs, and resource constraints.
The research contributes both theoretically and practically: it enriches the academic understanding of pivoting as a core entrepreneurial capability and provides actionable insights for entrepreneurs, investors, and policymakers. By emphasizing the need to design for adaptability from the outset, this thesis highlights pivoting not as a sign of failure, but as a deliberate, necessary, and value-creating process in the development of successful startups