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Valutazione economica delle misure di biosicurezza e della sorveglianza negli allevamenti di suini
Get PDFAntimicrobial resistance (AMR) is a major public health threat, with over 700,000 deaths annually worldwide due to infections caused by resistant pathogens. This number is projected to rise to 10 million by 2050 if no significant action is taken. The overuse and misuse of antibiotics, particularly in livestock production, contributes significantly to AMR. Antibiotics are not only used to treat infections but also as growth promoters in animals, especially in the pig sector. By 2030, the global antimicrobial use for food production is expected to reach 236,757 tons annually, with terrestrial animals accounting for the majority.
In the European Union, Italy has one of the highest levels of veterinary antimicrobial use and AMR. The Italian ClassyFarm system aims to support farmers in improving animal health and reducing antibiotic use. Data indicates that pig farming is most affected by these issues. Biosecurity practices—such as improving animal health and preventing disease transmission—are key to reducing antibiotic use and improving farm productivity. Effective biosecurity requires both management strategies and infrastructure investments.
Despite the proven benefits, many Italian pig farmers remain reluctant to adopt biosecurity measures due to the financial and economic barriers of upgrading farm infrastructure. These measures often involve significant costs for facilities like fencing, disinfection stations, and quarantine systems, with no immediate financial returns.
The focus of this thesis is to generate new insights into the economic impact of biosecurity measures, with a particular focus on the costs associated with their implementation in Italian pig farming. Additionally, the thesis assesses ClassyFarm components that could be further improved to optimize the integrated nature of the system concerning AMU and AMR, considered as indirect indicators of the effectiveness of biosecurity measures implemented in farms.La resistenza agli antimicrobici (AMR) è una grave minaccia per la salute pubblica, con oltre 700.000 morti annuali a livello globale a causa di infezioni provocate da patogeni resistenti. Si prevede che questo numero aumenterà fino a 10 milioni entro il 2050 se non verranno adottate azioni significative. L'uso e l'abuso di antibiotici, in particolare nella produzione animale, contribuiscono in modo significativo all'AMR. Gli antibiotici non vengono utilizzati solo per trattare le infezioni, ma anche come promotori della crescita negli animali, in particolare nel settore suinicolo. Entro il 2030, l'uso globale di antimicrobici per la produzione alimentare dovrebbe raggiungere 236.757 tonnellate all'anno, con gli animali terrestri che rappresentano la maggior parte.
Nell'UE, l'Italia ha uno dei livelli più alti di utilizzo veterinario di antimicrobici e di AMR. Il sistema italiano ClassyFarm mira a supportare gli agricoltori nel migliorare la salute animale e ridurre l'uso di antibiotici. I dati indicano che l'allevamento suino è il settore maggiormente colpito. Le pratiche di biosicurezza, come il miglioramento della salute animale e la prevenzione della trasmissione delle malattie, sono fondamentali per ridurre l'uso di antibiotici e migliorare la produttività delle aziende agricole. Una biosicurezza efficace richiede sia strategie di gestione che investimenti in infrastrutture.
Molti allevatori di suini italiani sono riluttanti ad adottare queste misure a causa delle barriere economiche e finanziarie nell'aggiornare le infrastrutture aziendali, infatti, comportano spesso costi significativi come recinzioni, stazioni di disinfezione e sistemi di quarantena, senza ritorni finanziari immediati.
L'obiettivo di questa tesi è generare nuove informazioni sull'impatto economico delle misure di biosicurezza, con particolare attenzione ai costi associati alla loro implementazione nell'allevamento suino italiano. Inoltre, la tesi valuta i componenti del sistema ClassyFarm che potrebbero essere ulteriormente migliorati per ottimizzare la natura integrata del sistema riguardo l’AMU e all’AMR, considerati come indicatori indiretti dell'efficacia delle misure di biosicurezza
Environmental impact of pathology laboratories. Sentinel lymph node diagnostic methodologies: a case study
Get PDFHealthcare services represent a notable source of environmental impact due to their use of energy-intensive equipment, single-use materials, and chemically complex reagents. Within this context, the diagnostic processing of sentinel lymph nodes serves as a representative procedure through which to evaluate surgical pathology laboratory sustainability. This study employs a Life Cycle Assessment approach to quantify and compare the environmental impacts of two widely used sentinel lymph node diagnostic methodologies: histological ultrastaging and a molecular assay based on one-step nucleic acid amplification. The analysis was conducted at a major Italian research hospital using primary data from clinical workflows, supported by the ecoinvent 3.8 database and modeled in SimaPro. Environmental impacts were characterized using the CML baseline method across 11 midpoint categories. A declared unit, based on a statistically derived median sentinel lymph node, enabled standardized comparison of diagnostic procedures across efficiency scenarios. The results demonstrate that the two methodologies differ substantially in their environmental profiles, with each approach presenting distinct strengths and trade-offs. Histological methods involve more extensive multi-step processing and reagent diversity, while molecular workflows are highly dependent on custom single-use plastics and specialized reagents. Sensitivity and uncertainty analyses provide additional insight into the key drivers of impact and the robustness of the model. This work illustrates how methodological choices in pathology can significantly shape environmental performance and underscores the value of integrating life cycle assesment into the assessment of laboratory practices
Bioherbicides:essential oils and weed management
Get PDFWeeds pose significant challenges to agriculture, causing yield losses and increasing costs. Traditional synthetic herbicides have long been the primary solution due to their high efficacy. However, their overuse has raised environmental and health concerns, and prompted stricter regulatory controls, such as those outlined in the European Green Deal. These factors have intensified the search for sustainable alternatives, including bioherbicides derived from natural compounds like organic acids and essential oils. This research evaluates the potential of organic acids and essential oils for weed management under various experimental conditions. Acetic acid emerged as a promising bioherbicide due to its ability to disrupt plant cell membranes, leading to rapid desiccation and effective weed suppression. Its low environmental persistence and potential for cost-effective production as an industrial byproduct enhance its appeal. Similarly, pelargonic acid demonstrated high efficacy, though its widespread use is hindered by production costs. Essential oils, while effective in some combinations, require further exploration due to their variable performance. The experiments revealed interspecies differences in sensitivity, with dicotyledonous weeds more susceptible than monocotyledons. Application timing and weed growth stages significantly influenced efficacy, as did environmental factors like temperature and evaporation rates. Higher application volumes improved effectiveness, but rapid evaporation limited the field-scale applicability of treatments. Adjuvants such as Camelina oil, chitosan, and essential oils showed potential in enhancing acetic acid’s performance, particularly at lower concentrations. However, they did not consistently outperform acetic acid alone, emphasizing the need for further optimization. Despite its potential, organic acids and essential oils require multiple applications and careful timing to maximize its impact. Its role as a bioherbicide could be particularly valuable in organic and small-scale farming systems. Future research should focus on optimizing formulations, refining application strategies, and integrating acetic acid into broader sustainable weed management programs to enhance its viability as an eco-friendly alternative
Seasonal forecasting of east african rains
Get PDFIn East Africa (EA), rainfall variability significantly impacts socioeconomic and environmental conditions, making accurate seasonal predictions essential. Rainfed agriculture, vital for livelihoods and food security, is highly vulnerable to erratic rainfall, leading to lower yields and financial hardship. Global teleconnections like El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) strongly influence EA’s interannual rainfall variability, though their independent roles are not fully understood. We evaluated EA short rain predictability using C3S model ensembles, assessing 1- to 5-month lead forecasts initialized in September (1993–2016). Most models show skill in predicting OND precipitation anomalies but exhibit low skill in northern and western regions. Along Somalia’s coast and the western Indian Ocean, skill persists into late winter (DJF), likely due to SST anomaly persistence. Models outperform persistence forecasts during mature ENSO/IOD phases. The Dipole Mode Index predicts rainfall anomaly signs, confirming that broader-scale IOD variability associated with changes in the Walker Circulation, not local SST changes, drives EA rainfall. We also assessed long-rain predictability using C3S models initialized in February, evaluating at lead times from MAM to MJJ. Long rain variability is associated with ENSO, with models performing better during active ENSO phases than IOD-dominated periods. Consequently, the C3S seasonal prediction system demonstrates greater skill in reproducing the long rains during active ENSO phases compared to periods dominated by IOD variability. Using Community Earth System models (CESM) experiments, we examined ENSO and IOD’s independent roles in EA short rain variability. Partial correlation and composite analyses highlight IOD’s dominant influence, with warm (cool) SST anomalies linked to above (below) normal OND rainfall. ENSO’s direct impact is weaker and IOD-dependent. CESM_noENSO and CESM_noIOD experiments confirm IOD’s critical role, which persists even without ENSO variability, underscoring its independent influence on EA short rain variability
Distributed machine learning for 6G intelligent vehicular communication networks
No full textThe rapid advancements in 6G technologies are transforming Vehicular Networks (VNs) into smarter, more connected systems. As autonomous vehicles and intelligent transportation systems become central to modern society, ensuring efficient, scalable, and secure communication is paramount. This thesis addresses these challenges by integrating Distributed Learning (DL) techniques with network slicing and integrated Terrestrial and Non‑Terrestrial Networks (T/NTNs) to satisfy the diverse and dynamic requirements of vehicular applications, such as autonomous driving and real-time traffic management, within the 6G ecosystem. The primary aim is to develop an adaptive, scalable, and secure framework, DL-as-a-Service (DLaaS), that enables real-time data processing and ultra-low latency in 6G VNs. DLaaS unifies various DL techniques to optimize both communication and computation while preserving user privacy. It is designed to handle heterogeneous vehicular devices and the complexity of multilayer networks, ensuring seamless operation across integrated T/NTN layers. Methodologically, the thesis introduces Federated Split Transfer Learning and its generalized version to address challenges related to resource-constrained devices and heterogeneous network environments. These DL techniques are tailored to meet the needs of 6G VNs, offering scalable solutions to real-time learning, model synchronization, and privacy protection. The practical viability of these approaches is validated through real‑world simulations and hardware implementations on edge computing platforms. The key findings of this research demonstrate that the proposed frameworks significantly enhance the accuracy, scalability, and latency of VNs. Furthermore, the application of deep reinforcement learning for dynamic adaptive streaming optimizes bitrate allocation, caching, and transcoding, improving quality of experience for users in real-time. These results confirm the feasibility of integrating advanced machine learning techniques and T/NTNs into the design of 6G internet of vehicle systems. In the end, proper conclusive remarks and several future directions are provided for the proposed solutions, offering valuable insights into the future of smart cities and intelligent mobility
Comparative constitutional design for divided societies: a model to explain constitutional asymmetries
No full textComparative studies on constitutional design for divided societies indicate that there is no magic formula to the challenges that these societies pose, as lots of factors influence constitutional design. In the literature on asymmetric federalism, the introduction of constitutional asymmetries is considered a flexible instrument of ethnic conflict resolution, as it provides a mixture of the two main theoretical approaches to constitutional design for divided societies (i.e., integration and accommodation). Indeed, constitutional asymmetries are a complex and multifaceted phenomenon, as their degree of intensity can vary across constitutional systems, and there are both legal and extra-legal factors that may explain such differences.
This thesis argues that constitutional asymmetries provide a flexible model of constitutional design and aims to explore the legal factors that are most likely to explain the different degrees of constitutional asymmetry in divided multi-tiered systems. To this end, the research adopts a qualitative methodology, i.e., Qualitative Comparative Analysis (QCA), which allows an understanding of whether a condition or combination of conditions (i.e., the legal factors) determine the outcome (i.e., high, medium, low degree of constitutional asymmetry, or constitutional symmetry). The QCA is conducted on 16 divided multi-tiered systems, and for each case, the degree of constitutional asymmetry was analyzed by employing standardized indexes on subnational autonomy, allowing for a more precise measure of constitutional asymmetry than has previously been provided in the literature.
Overall, the research confirms the complex nature of constitutional asymmetries, as the degrees of asymmetries vary substantially not only across systems but also within cases among the dimensions of subnational autonomy. The outcome of the Qualitative Comparative Analysis also confirms a path of complex causality since the different degrees of constitutional asymmetry always depend on several legal factors, that combined produce a low, medium, or high degree of constitutional asymmetry or, conversely, constitutional symmetry
Embodied lecturing in engineering in English-Medium Instruction (EMI): exploring the interaction between gestures, (Dis)Fluencies, and pragmatic challenges
Get PDFThis study examines the communicative challenges faced by an Italian first language (L1) lecturer delivering engineering courses through English as a Medium of Instruction (EMI) in an international master’s program in Italy. Using a case study approach, it investigates how variations in speech rate, disfluencies, and verbal and non-verbal strategies affect teaching and learning. Data were collected from a video-recorded lecture, student feedback, and the lecturer’s reflections, with a focus on student perspectives.
Findings reveal significant variations in speech rate, with faster rates during straightforward explanations and slower rates for complex content. Disfluencies were analyzed to differentiate between communication breakdowns and deliberate pauses used to engage students or allow them to process material. Gestures were examined as tools for facilitating understanding or compensating for challenges in lexical retrieval and technical explanations.
While the study reinforces that both students and lecturers cooperate effectively to achieve communicative goals in English as a Lingua Franca in Academic (ELFA) contexts, it also emphasizes the need to further empower EMI lecturers by providing research-based evidence to improve specific areas of communication. Despite the lecturer’s technical expertise, rapid speech, lexical retrieval issues, and occasional misalignments between gestures and speech hindered student comprehension, particularly in STEM vocabulary.
Methodologically, this research expands EMI studies by integrating Second Language Acquisition (SLA), Conversation Analysis (CA), and multimodal approaches. It emphasizes gestures as integral communicative tools rather than mere speech accessories, revealing challenges that may not be expressed verbally. The findings highlight the embodied nature of teaching and the critical role of gestures in either enhancing or hindering comprehension. This study calls for EMI-specific training programs to enhance communicative strategies, meeting the needs of international and domestic students in technical disciplines like engineering
Space charge behaviour in Quantum Dot/Epoxy resin nanocomposites for HVDC applications
Get PDFThis work investigates the feasibility of semiconductive nanostructures, namely Quantum Dots (QDs), as additives in polymeric matrices to improve dielectric properties. The primary aim is to explore how QD incorporation influences space charge behavior in an epoxy resin, DER332. The research begins with an overview of high voltage direct current (HVDC) systems and the increasing relevance of nanodielectric materials in advanced insulation technology. Given the inherent properties of QDs, their role as additives in altering dielectric performance is of notable interest. This study aims to bridge the gap between the fundamental theoretical properties of QDs and their practical application within polymeric insulation materials. Two nanocomposites were fabricated with QD loadings of 0.04% and 0.1%, respectively. A comprehensive experimental campaign, comprising both chemical and electrical measurements, was conducted to assess the effectiveness of QD incorporation into the epoxy matrix. Characterization efforts were focused on analyzing space charge distribution, charge trapping behavior, and the electric field profile within the QD-enhanced samples, also focusing on the conductive and dielectric properties of the analyzed materials. Three main findings emerged from the study: Firstly, the addition of Carbon Quantum Dots creates charge carrier traps within the matrix, leading to modifications in space charge behavior and altering the electric field distribution. Second, a novel method to evaluate space charge dynamics was preliminarily validated through short-term current transient analysis, providing a new potential approach for studying dielectric materials. Finally the results suggest that QDs can potentially enhance the field grading capabilities of epoxy Resins. In conclusion, the significant impact on the dielectric properties of epoxy resin due to the incorporation of a minimal amount of Carbon Quantum Dots requires further investigation, as it has the potential to contribute to the development of innovative materials in the field of insulation engineering
Perfection bias in the workplace: psychosocial antecedents and consequences of gender stereotypical expectations against women
Get PDFDespite the significant progress made in the Labour Market over the last decades, a very high discrepancy emerges in women's employment compared to men. Why is this the case? A very important explanation comes from social stereotypes. Research pointed out that usually, gender stereotypes depict women as more nurturing, empathic, and emotional but less competent – than men. These expectations towards men and women might prevent women from being considered suitable for certain positions. Furthermore, recent evidence showed that, in the workplace, women are evaluated along multiple dimensions. In other words, while men are primarily evaluated on competence, women are evaluated on multiple characteristics (i.e., competence, sociability, and morality). Hence, women need to fulfil more requirements than men to be selected or promoted for a role. This phenomenon has been called perfection bias since findings hint at the fact that women need to fulfil expectations of perfection to be considered suitable in the workplace. But are these expectations identifiable at an implicit level? And being evaluated on multiple dimensions have positive or negative consequences? The research reported in this dissertation tried to answer this question by pursuing a threefold goal. First, we tested whether the multiple expectations placed on women are detectable at an implicit level. To do so, Study 1 (N = 108) explored people's automatic cognitive associations concerning stereotypical characteristics that pertain to the masculine and feminine domains. Second, we developed a tool that should capture the awareness of women about the multiple expectations placed on them in the workplace (Studies 2-4, N = 981) and their impact on women's well-being (Study 5, N = 335). Third, Study 6 (N = 163) investigated the multiple expectations placed on women in an experimental setting corroborating the idea that women should be performative on multiple dimensions to be recruited
Constitutional order and emergency. Theory, models, and practice
Get PDFLa ricerca che si presenta intende ricostruire l’emergenza dal punto di vista della scienza costituzionale, guardando le teorie, i modelli e la prassi in materia di gestione delle emergenze. In particolare, lo studio si sviluppa lungo tre livelli principali: uno, dedicato allo studio degli istituti emergenziali previsti nell’ordinamento italiano, distinguendo la c.d. “Costituzione dell’emergenza” dalla “legislazione dell’emergenza”; un secondo, volto all’approfondimento di un caso di studio, individuato nell’esperienza della pandemia provocata dalla diffusione del virus Covid-19; un terzo, finalizzato a comparare l’ordinamento interno con quello spagnolo, ossimorico nell’approccio alla gestione dei fatti emergenziali.
A tal fine, il lavoro è strutturato in quattro capitoli, più una parte conclusiva dedicata alle considerazioni raggiunte all’esito della ricerca. Nello specifico, l’ordine dei profili esaminati risponde alla logica di contornare la tematica, procedendo gradualmente alla disamina del fenomeno emergenziale su più versanti, coniugando l’analisi teorica del dato normativo con l’osservazione della prassi, analizzando il “modo” della produzione normativa emergenziale e le interazioni e le sovrapposizioni tra i diversi soggetti competenti in materia. In questa prospettiva, il lavoro dottorale si conclude con una riflessione in prospettiva sul “lascito dell’emergenza”, elaborando la tesi conclusiva secondo cui l’emergenza contribuisce ad accelerare tendenze già in atto nell’ordinamento, fungendo in taluni casi da ponte per il consolidamento di processi in corso di definizione.The present research aims to reconstruct the concept of emergency from the perspective of constitutional science, examining the theories, models, and practices related to emergency management. Specifically, the study is developed along three main levels: the first focuses on the analysis of emergency mechanisms within the Italian legal system, distinguishing between the so-called "Constitution of Emergency" and "Emergency Legislation"; the second delves into a case study, identified in the experience of the Covid-19 pandemic; the third aims to compare the Italian legal framework with the Spanish system, which adopts a paradoxical approach to emergency management.
To this end, the research is structured into four chapters, along with a concluding section dedicated to the final considerations drawn from the study. The order of the topics examined follows a logical progression, gradually addressing the phenomenon of emergency from multiple perspectives, combining theoretical analysis of legal norms with the observation of practical applications. It explores the mechanisms of emergency lawmaking and the interactions and overlaps among the different actors involved in the field. From this perspective, the doctoral research concludes with a forward-looking reflection on the "legacy of emergency," advancing the final thesis that emergencies contribute to accelerating trends already underway within the legal system, sometimes serving as a bridge for the consolidation of ongoing processes