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Feminist approach to organizational culture for sustainable work and green reporting
Get PDFThe Feminist approach to organizational culture for sustainable work and green reporting advocates for reshaping organizational culture to promote equity, sustainability, and inclusivity in workplaces and businesses. In the fields of Environmental and Social Accounting and feminist accounting, this perspective emphasizes transparency, social responsibility, and a holistic view of businesses, supporting initiatives such as sustainable reporting for local enterprises, encouraging accountability, community-oriented growth and addressing unequal practices in the workplace. Starting from a bibliometric analysis of feminist research in management and accounting, this thesis draws from three feminist accounting topics to bridge the gap between theory and practice. The first topic features an exploration of Social Environmental Accounting topics in LATAM undergraduate education to emphasize the potential of holistic business views that promote critical thinking and sustainable practices. The second topic deepens into female participation in organizations and their career advancements, a central topic of feminist accounting. By measuring gender differences in a performance review process, we aim to understand the factors that provoke performance gender differences for employees. The last one is a case study that follows the path of the Spiaggia Sostenibile project, aimed at designing the first sustainable reporting for beach establishments in Rimini, highlighting how small-scale local efforts can contribute to broader sustainability goals. Integrating critical theory, empirical research, and practical applications allows the accounting field not only to measure but also to become a tool to transform realities for the benefit of equity and sustainability
Advancements in diagnostic, therapeutic, and monitoring options for canine and feline diabetes mellitus, canine hypoadrenocorticism, and canine hypercortisolism
Get PDFThis thesis presents advancements in diagnostic, therapeutic, and monitoring approaches for small animal endocrinopathies, focusing on canine and feline diabetes mellitus (DM), canine hypoadrenocorticism (HA), and canine hypercortisolism (HC). A prospective randomized crossover study assessed the effects of a homemade diet versus a commercial diet on glycemic control and variability in diabetic dogs, with the homemade diet showing superior glucose-lowering effects. Novel insulin analogs, including insulin glargine 300 U/mL and insulin degludec 100 U/mL, were evaluated for once-daily administration, offering practical alternatives to traditional twice-daily insulin protocols. Additionally, the thesis explored the effects of transmucosal glucagon powder (Baqsimi) on blood glucose concentrations in healthy cats, suggesting potential applications for managing hypoglycemic episodes in diabetic patients.
The accuracy of the FreeStyle Libre 3 continuous glucose monitoring system (CGMS) was evaluated in diabetic and healthy cats, demonstrating good performance across a wide glycemic range. The Eversense XL, a novel CGMS with a lifespan of up to 180 days, was assessed in diabetic dogs, highlighting its potential to improve long-term adherence despite limitations such as sensor movement and calibration requirements.
The thesis also presents the results of two prospective studies: one investigating the prevalence of canine eunatremic, eukalemic hypoadrenocorticism and the other examining the recovery timeline of the hypothalamic-pituitary-adrenal axis in dogs treated with intermediate-acting glucocorticoids. Furthermore, the diagnostic performance of urinary cortisol, urinary cortisol-to-creatinine ratio (UCCR), and low-dose dexamethasone suppression test were evaluated following a change in the Immulite 2000 antibody used for cortisol measurement.
Finally, the thesis examined the impact of a therapeutic commercial diet formulated for calcium oxalate urolithiasis on calcium-phosphate homeostasis in dogs with HC treated with trilostane.
In conclusion, this thesis provides valuable insights into endocrine diseases, aiding clinicians in improving the diagnosis and daily management of canine and feline DM, canine HA, and canine HC
Integrating domain knowledge in data-driven AI approaches
Get PDFMachine Learning (ML) continues to revolutionize various fields, achieving significant advancements across domains such as computer vision, game AI, natural language processing, and speech recognition. However, purely data-driven models face limitations, particularly in scenarios with insufficient data or applications bound by critical constraints, such as regulatory standards or security guidelines. Moreover, there is an increasing demand for interpretable and explainable models in socially sensitive domains like healthcare and education. Integrating prior knowledge into ML models has emerged as a promising approach to address these challenges. Traditionally, this has been achieved through labeling or feature engineering, but recent trends focus on incorporating formal knowledge representations to improve model robustness and performance.
In this thesis, we explore the integration of two distinct forms of knowledge representation: logic rules and dynamical systems. First, we examine the advantages of logic-based reasoning for generative tasks by developing the first neuro-symbolic generative model that integrates probabilistic logic programming into variational autoencoders. This approach significantly differs from existing neuro-symbolic methods, which predominantly focus on discriminative tasks. Second, we investigate the integration of dynamical systems into ML models, particularly in the context of automated ranking tasks, by modeling the evolution of fairness and quality metrics as a dynamical system. Additionally, we conduct a comprehensive analysis of an existing framework that combines ML with differential equations.
This thesis's contributions are supported by theoretical foundations and validated through experimental results, demonstrating the efficacy of integrating formal knowledge representations into data-driven AI approaches
The “liquid” role of the public administration and the empowerment of the private sector in the use of contractual partnership instruments
Get PDFLa tesi analizza il grado di flessibilità concesso dal “nuovo” Codice dei contratti pubblici all’Amministrazione e, specularmente, l’attribuzione di responsabilità pubblica a carico del privato nell’ambito della gestione di una operazione economica di Partenariato Pubblico-Privato (“PPP”). Il D.lgs. n. 36 del 2023, infatti, ri-disegna dalle fondamenta il paradigma della cooperazione partenariale e tale novità, che incide, a monte, sulla dinamica relazionale tra potere pubblico e autonomia privata, pone il problema di comprendere come, a valle, si riassestino le posizioni dei ruoli della P.a. e degli operatori economici privati coinvolti nella gestione dell’operazione stessa. Pertanto, l’analisi di cui al presente scritto si focalizza, innanzitutto, sull’ontologia che permea il concetto di “operazione economica”, e soprattutto sul suo carattere di “globalità”, per poi concentrarsi sulle ricadute, normative e pratiche, che tale nuova visione apporta tanto alla fase genetica del PPP, quanto alla fase esecutiva. Lo scopo ultimo della ricerca è comprendere se il Codice dei contratti pubblici sia in grado di regolare il PPP in modo tale da garantire all’Amministrazione una flessibilità tale – simbolicamente raffigurata allo stato “liquido” - da opporsi alla tradizionale rigidità impostale dai vincoli pubblicistici, cui corrisponde, per converso, un avanzamento del privato quale responsabile della gestione dell’operazione economica di cui è partner. Anche in ragione del carattere innovativo e, soprattutto, di recente adozione dell’impalcatura normativa recata dal D.lgs. n. 36 del 2023, è opportuno volgere lo sguardo verso altri ordinamenti, come quello francese, in cui il fenomeno partenariale trova già da tempo una disciplina organica, al fine di far emergere, attraverso il metodo comparatistico, le peculiarità che permeano la disciplina nostrana.This thesis analyses the degree of flexibility granted by the “new” Public Contracts Code to the Administration and, specularly, the attribution of public responsibility to the private party in the context of the management of an economic Public-Private Partnership (“PPP”) operation. Legislative Decree No. 36 of 2023 shapes the paradigm of partnership cooperation and such novelty, which affects, upstream, the relational dynamic between public power and private autonomy, poses the problem of understanding how, downstream, the positions of the roles of the Public Administration and of the private economic operators involved in the management of the operation itself are rearranged. Therefore, the analysis focuses, first of all, on the concept of “economic transaction”, and above all on its character of “globality”, and then concentrates on the normative and practical repercussions that this new vision brings both to the genetic phase of the PPP and to the executive phase. The ultimate aim of the research is to understand whether the Public Contracts Code is able to regulate the PPP in such a way as to guarantee the Administration such flexibility - symbolically depicted in a “liquid” state - as to oppose the traditional rigidity imposed on it by public-sector constraints, to which corresponds, conversely, an advancement of the private party as the manager of the economic operation in which it is a partner. As far as the analysis on the PPP is concerned, it is appropriate to look at other legal systems, such as the French one, in which the partnership phenomenon has long since found an organic discipline, in order to bring out, through the comparative method, the peculiarities that permeate the Italian discipline
Risk assessment for climate adaptation taking into account nature-based solutions, geophysical processes and multidisciplinarity
Get PDFThe world is experiencing an escalating threat from Hydro-Meteorological Hazards (HMHs), resulting in Risks (HMRs) for territories, people, and ecosystems. Climate projections indicate the frequency and intensity of HMHs may further increase urging tangible strategies for mitigation and adaptation. Climate significantly influences societal policies and governance, depending on socio-economic and environmental conditions. In this context, risk assessment is an essential tool to analyze the world's complexity and implement proper countermeasures.
The following Thesis proposes a novel holistic, yet predictive, framework for the assessment of HMRs. Contributions to HMRs are quantified as economic losses and carbon-dioxide emissions, and classified into six research fields, namely, healthcare, society, ecosystem, heritage, infrastructure, and agriculture. The framework is tested for a heat-wave event in the Metropolitan City of Bologna (Italy).
The final output is expressed as a cost per day to aid policy decision-making processes. The framework integrates societal capacities to cope with HMHs through adaptation and mitigation measures. Promising measures include Nature-based Solutions (NbS) which aim to provide both human well-being and biodiversity benefits. The novel framework stands as a tool for the assessment of NbS effectiveness taking into account a library of indicators concerning environmental performance, risk reduction, and provision of co-benefits.
The selection of indicators is based on previous NbS interventions, followed by the definition of an assessment methodology, and the selection of suitable modeling and monitoring techniques. The effectiveness may change during the NbS life cycle across the design, implementation, maintenance, monitoring, and restoration phases. An example is proposed for a sand dune in Lido di Volano (Ferrara, Italy). A formulation is proposed to estimate the long-term local impact of NbS interventions.
In conclusion, the novel framework aims to be a valuable tool for climate adaptation through research analyses, the integration into early warning systems, and the definition of land-management strategies
Machine aided diagnosis and melanoma: histopathological findings
Get PDFThe incidence of cutaneous melanoma has risen in recent years. Histopathological examination remains the gold standard for diagnosing cutaneous melanoma; however, it is often complex. The need to streamline workflows and develop new diagnostic support methods for cutaneous melanoma has driven increased research into the application of artificial intelligence. Our study is structured into three main sections: (i) automated silhouette definition and its diagnostic significance, (ii) extraction of nuclear features and classification modeling, and (iii) assessment of Breslow thickness. Automating clinical procedures provides invaluable support, leading to faster and more reliable sample evaluations. Our study can expedite the screening of whole slide image by prioritizing histopathology slides that exhibit high-risk melanoma features over those with low-risk nevus characteristics
Sustainable exploitation of hidden resources: approaches for metal recovery and environmental remediation
Get PDFCombustion residues, such as Fly (FA) and Bottom ash (BA), are produced during the incineration process in Municipal Solid Waste Incineration (MSWI) plants. Mine tailing (MT) is another industrial waste produced during the extraction of valuable resources from ores in mining operations. The present study considered these anthropogenic materials as alternative sources of strategic elemental resources. BA, FA, and MT samples are characterized by X-Ray Fluorescence (XRF) and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) for accurate determination of 49 elements, by applying both total and pseudo-total digestion. The analytical recovery of elements shows higher concentrations in BA than FA, especially industrial base metals, such as, Fe, Al, K, and Cu, and valuable elements (of strategic importance for the EU) like Co, Ba, and REEs. In time series analysis (2013-2022), FA material showed that Zn, Mg, P, Ti, and REEs like La, Ce, and PTEs (Pb, As, and Cd) are higher especially in Lime-doped FA (FAL) category than the Soda-doped FA (FAS) during the pre-pandemic period (2013 and 2020) than the post-pandemic period (2021 and 2022) for two MSWI plants waste considered. Pandemic-related changes throughout these years reflected the waste composition, in particular an increase in disposable materials and electronic waste burning. Gamma and Alpha Spectroscopy analysis explored the enrichment in radionuclides in FA and BA, identifying elevated activities for natural radionuclides (40K and 210Pb), which were almost constant during the years considered. In the characterization of four MT samples from active mines (Pb-Zn, Fe, Au, Cu), the pseudo-total digestion (aqua regia) showed the maximum leachable fraction of PTEs, encouraging the potential recovery considering MTs as a low-grade ore. The bibliometric analysis showed the research trends, suggesting that MSWI-ashes and MT can be subjected to sustainable treatment strategies for the circular economy
Smart contracts for certified operations in industrial distributed applications
Get PDFThe integration of smart contracts and blockchain technology is gaining momentum in industrial applications, especially in safety-critical systems such as predictive maintenance and real-time anomaly detection. These systems typically rely on sensor networks to collect data and stream it to cloud infrastructures for storage, analysis, and visualization. However, industrial applications pose unique challenges: they require sustainable storage solutions for long-term continuous monitoring, while ensuring data integrity and tamper-proof operations. At the same time, the performance of smart contracts in production-grade environments becomes critical, as industrial systems depend on them to handle high transaction volumes and maintain scalability under real-world conditions.
The first section of this thesis presents a blockchain-based framework enabling certified data removal for continuous monitoring systems. Smart contracts define and run data retention policies, enabling the secure deletion of non-compliant data. This solution is applied to a real-world Structural Health Monitoring (SHM) use case, where the blockchain guarantees the tamper-proof deletion of data in a railway bridge monitoring application. In the second part, the focus shifts to the benchmarking of smart contracts in production-grade deployments. A step-by-step methodology is proposed for simulating real-world environments and evaluating smart contracts through key performance indicators such as Average Transaction Latency (ATL) and Average Transaction Throughput (ATT). The final aim is enabling organizations to make data-driven decisions regarding the introduction of smart contracts in industrial applications, evaluating various network constraints and blockchain configurations. Finally, these two contributions merge into an experimental study examining a production-grade deployment of the proposed smart contract using the discussed methodology. A framework for benchmarking is implemented to assist users in evaluating smart contracts automatically. The results show how the methodology enables organizations to make informed decisions regarding smart contract deployment and scalability through quantification of network limitations and blockchain configuration effects
Quantum Fisher Information for simulation of many-body systems and new Quantum Cellular Automata protocols for computation
Get PDFThis work is divided into two parts. The first focuses on Quantum Fisher Information (QFI), exploring its properties and role in quantum geometry, phase estimation, and multipartite entanglement. Specifically, we study ground state QFI in one-dimensional spin-1 models, using it to witness multipartite entanglement. The models examined include the Bilinear-Biquadratic model and the XXZ spin-1 chain, all with nearest-neighbor interactions and open boundary conditions. We show that the scaling of QFI with strictly non-local observables characterizes phase diagrams, particularly in topological phases, where it exhibits maximal scaling. To conclude this part, we demonstrate how QFI can serve as a hybrid quantum-classical optimizer in variational algorithms for NISQ devices. Specifically, we evaluate the Quantum Approximate Optimization Algorithm (QAOA) using the Quantum Natural Gradient as an optimizer, showing that even with quantum noise, the QFI-based Natural Gradient improves convergence, reducing iterations compared to its classical counterpart.
The second part introduces Quantum Cellular Automata (QCA) as an alternative paradigm for quantum computation, highlighting their versatility and applications. Finally, we discuss how non-unitary QCA can solve the density classification task, mapping global density information to local density. Two approaches are considered: one preserving number density and one performing majority voting. For the number-preserving case, we propose two QCAs that reach a fixed-point solution with a time complexity scaling almost quadratically with system size, both implementable via continuous-time Lindblad dynamics. Additionally, a third QCA, a hybrid rule combining discrete-time and continuous-time three-body interactions, solves the majority voting problem in linear time with system size
Immersive virtual reality as a tool to encourage physical activity for psycho-physical well-being in the workplace
Get PDFLa sedentarietà è uno dei fattori di rischio comportamentali più incisivi per lo sviluppo di patologie fisiche e mentali e richiama la necessità di un’azione globale coordinata. Nel 2018, la World Health Organization ha pubblicato il Global Action Plan on Physical Activity, che invita gli Stati membri a incentivare stili di vita attivi, con particolare attenzione all’uso di innovazioni tecnologiche e ai contesti di maggior rilievo per la collettività, come il mondo del lavoro. La realtà virtuale immersiva (IVR) rappresenta uno strumento promettente per incrementare la pratica di attività motoria; tuttavia, la ricerca in questo ambito è ancora ai suoi albori ed è necessario approfondire le conoscenze sul potenziale ruolo della IVR nella promozione dell’attività fisica. Con questo scopo, è stata condotta una systematic review degli studi che hanno esplorato l’efficacia della IVR come strumento per migliorare l’esperienza dell’attività motoria al fine di motivare la pratica di esercizio fisico. Successivamente, è stato implementato uno studio pilota con l’obiettivo primario di condurre un’analisi preliminare sulla fattibilità e l’accettabilità di un intervento di attività motoria supportata da IVR (Immersive Virtual Reality- Physical Activity, IVR-PA), e con l’obiettivo secondario di condurre un’analisi esplorativa sull’effetto dell’intervento. I risultati della systematic review e dello studio pilota convergono nell‘incoraggiare l’applicazione della IVR-PA come approccio innovativo per promuovere l’attività fisica e migliorare il benessere sul luogo di lavoro. Sono comunque essenziali ulteriori indagini per affrontare le limitazioni dello studio attuale e per approfondire la applicabilità e la generalizzabilità degli interventi di IVR-PA, anche in contesti differenti, come nel percorso iniziato durante il mio dottorato di ricerca.Sedentary behavior is one of the major behavioral risk factors for the development of physical and mental health conditions, highlighting the need for a coordinated global response. In 2018, the World Health Organization released the Global Action Plan on Physical Activity, calling on member states to encourage active lifestyles, with a focus on promoting technological innovations and essential social environments, including the workplace. Immersive Virtual Reality (IVR) represents a promising tool to enhance physical activity engagement; however, research in this field is still in its early stages, and further investigation is needed to better understand IVR’s potential role in promoting physical activity. For this purpose, a systematic review was conducted to explore studies assessing the effectiveness of IVR in improving the experience of physical activity to encourage exercise participation. Subsequently, a pilot study was implemented with the primary objective of conducting a preliminary analysis of the feasibility and acceptability of an IVR-supported physical activity intervention (Immersive Virtual Reality-Physical Activity, IVR-PA), and a secondary objective of exploring its effects. The results of the systematic review and pilot study support the application of IVR-PA as an innovative approach to promoting physical activity and improving workplace well-being. However, further research is essential to address the limitations of the current study and to explore the applicability and generalizability of IVR-PA interventions in different settings, as part of the ongoing research in my doctoral studies