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Hyperspectral imaging in cardiac regeneration processes
No full textLe malattie cardiovascolari sono tra le principali cause di morte nei paesi industrializzati. Ad oggi, non esistono vere terapie “rigenerative” e l’uso terapeutico di stimolazioni basate su energie fisiche rimane ancora marginale. In questo studio abbiamo considerato due tecnologie emergenti: la fotobiomodulazione come trattamento terapeutico e l’imaging iperspettrale come strumento diagnostico. I risultati mostrano che il trattamento luminoso su MSC da derma promuove il mantenimento dello stato fisiologico, riducendo l’espressione di marcatori di senescenza come la Vimentina e aumentando l’espressione della Nestina, proteina collegata alla conservazione della capacità di autorinnovamento. L'espressione genica supporta i risultati dell'immunofluorescenza, evidenziando nelle cellule trattate un aumento dell'espressione di geni coinvolti nel mantenimento della pluripotenza, come NANOG e POU5F1, e un aumento dell'espressione di FAM38A e NKX2.5, geni implicati rispettivamente nella morfogenesi delle cellule muscolari e nel processo di differenziamento miocardico. In collaborazione con Eldor Lab abbiamo creato un setup sperimentale composto da una telecamera iperspettrale collegata ad un microscopio a fluorescenza e a un PC, in grado di raccogliere iperstack di immagini in un'ampia gamma di lunghezze d'onda in diverse condizioni biologiche. L'obiettivo era valutare la capacità della telecamera iperspettrale di riconoscere campioni che avessero subito trattamenti diversi. Cellule H9C2, linea clonale da mioblasti embrionali di ratto, sono state sottoposte al trattamento con Rotenone, inibitore del Complesso I mitocondriale, che altera il metabolismo cellulare senza modificare la morfologia della cellula stessa. Abbiamo analizzato le modifiche metaboliche con colorante CellROX Orange. Verificato che le cellule rispondevano al trattamento in modo omogeneo, abbiamo effettuato acquisizioni con la telecamera iperspettrale a tempi diversi su cellule trattate e di controllo. I risultati evidenziano che il setup è in grado di distinguere i profili delle cellule trattate da quelle di controllo e suggeriscono che il segnale derivi da due distinte componenti: la componente cellulare e il mezzo di coltura.Cardiovascular diseases are among the leading causes of death in industrialized countries. Nowadays, there are no true "regenerative" therapies, and the therapeutic use of energy-based stimulations remains marginal. In this study, we considered two emerging technologies: photobiomodulation as a therapeutic treatment and hyperspectral imaging as a diagnostic tool. The results show that light treatment on dermal MSCs promotes the maintenance of the physiological state, reducing the expression of senescence markers such as Vimentin and increasing the expression of Nestin, a protein related to the preservation of self-renewal capacity. Gene expression supports the immunofluorescence results, showing an increased expression in genes involved in maintaining pluripotency, such as NANOG and POU5F1, as well as an increased expression of FAM38A and NKX2.5, genes respectively involved in muscle cell morphogenesis and myocardial differentiation. In collaboration with Eldor Lab, we developed an experimental setup consisting of a hyperspectral camera connected to a fluorescence microscope and a PC, which is able to capture hyperspectral image stacks in a wide range of wavelengths under different biological conditions. The goal was to evaluate the ability of the hyperspectral camera to distinguish samples that had undergone different treatments. H9C2 cells, a clonal line derived from rat embryonic myoblasts, were treated with Rotenone, a Complex I mitochondrial inhibitor that alters cellular metabolism without changing cell’s morphology. We analyzed metabolic changes using CellROX Orange dye. Once it was confirmed that the cells responded homogeneously to the treatment, we performed acquisitions with the hyperspectral camera at different times on treated and control cells. The results highlight that the setup is able to distinguish the profiles of treated cells from control cells and suggest that the signal originates from two distinct components: the cellular component and the culture medium
Innovative joining technologies for weight reduction in vehicles for lowering polluting emissions
No full textThreaded fasteners are vastly used in the industry due to ease of mounting and dismounting and flexibility of design. Nonetheless, several researchers indicate that most failures recorded on nearly any kind of machinery and vehicles are initiated at fasteners. The problems can become significant when material of the threaded fasteners is changed due to change in material properties such as friction behaviour. This thesis aims at self-loosening failure in light weight threaded fasteners. The analysis involves the analytical modelling of the self-loosening phenomenon and development of an experimental test rig for testing self-loosening in threaded fasteners. The purpose of this thesis is to give a systematic glance of the practical loadings applied to the light weight threaded fasteners, used in automobiles and aerospace industry. This can help the scientific and technical community, to correctly orient future investigations on the self-loosening behaviour of light weight threaded fasteners. Moreover, more realistic approach for testing the loading conditions on the automotive, earth moving machinery and aerospace will be possible which will assist in more efficient design of the bolted joints
Techniques and methodologies to support data management and analysis in big data ecosystems
No full textIn recent years, industries have widely adopted digital technologies, reshaping key business operations, processes, and management structures, thus leading to digital transformation. Central to digital transformation is the seamless integration of processes and the exploitation of hidden data value, pushing information systems toward complex ecosystems of data-oriented services that meet diverse data needs and requirements. Big data drives digital transformation, encapsulated by the 4 Vs: volume, velocity, veracity, and variety. While scalable storage solutions exist, managing data variety remains a significant challenge in achieving a unified view of data that is essential for effective transformation. This thesis tackles the challenge of managing data variety in both batch and streaming contexts. NoSQL DBMSs have led to the adoption of polyglot storage systems, which combine the strengths of various technologies and data models. While operational applications benefit from this, analytical applications struggle with inconsistent schemas across different DBMSs and even within a single NoSQL system. As a result, data science is shifting towards a flexible, lightweight approach, moving away from traditional data warehousing. This thesis proposes an approach to support data analysis in a high-variety multistore with heterogeneous schemas and overlapping records. It also presents a case study on a data platform integrating multiple sources using a traditional warehousing approach and a formal study on representing complex, non-standard data distribution strategies. The literature on analyzing schemaless data streams is still in its early stages. This thesis presents a novel schema profiling technique for schemaless data streams within an overlapping sliding window paradigm, along with introducing a self-adaptive stream analysis framework. These approaches are integrated into a dashboard for real-time monitoring of schemaless data streams
A multidisciplinary approach to antibiotic resistance: insights from psychological and microbiological perspectives
No full textThe doctoral thesis targets on antibiotic resistance, both the examination of individual factors influencing it and the influence of antibiotic abuse on the general well-being of people. Antibiotic resistance is one of the most critical public health challenges of the 21st century, exacerbated by the misuse and overuse of antibiotics. While traditionally approached from a medical and microbiological perspective, this doctoral research emphasizes the importance of integrating psychological dimensions into the study of improper antibiotic use. The thesis research aims to explore the psychological, microbiological, and neurological factors that shape antibiotic behaviors, as well as to develop a comprehensive framework based on these findings to address antibiotic resistance. To accomplish this goal, the strategy employed different methodologies: self-report questionnaires for psychological and behavioral assessments, electroencephalography (EEG) for neural activation evaluation, and microbiota sequencing methods to examine microbiological alterations. Four studies have been combined: Study 1 includes psychological and behavioral analysis, examining the role of family attitudes, emotional well-being, and awareness in shaping antibiotic utilization; Study 2 focuses on neurological insights, utilizing EEG to uncover unconscious brain responses to health-related stimuli; Study 3 explores microbiota dynamics, investigating the impact of antibiotic use on vaginal microbiota and resistance genes presence; Study 4 aims to explore the gut-brain axis, observing the bidirectional interactions between gut microbiota and psychological changes during antibiotic therapy. The findings underscore the critical interplay between psychological factors and microbiota health, highlighting how emotional states and awareness influence antibiotic adherence and resistance development. By proposing a multidisciplinary approach, this thesis advocates for integrating psychological support, public health education, and microbiota-targeted interventions to combat antibiotic resistance effectively. This research contributes to a deeper understanding of the psychological and microbiological dynamics at play, offering actionable insights for reducing the global burden of antibiotic resistance while paving the way for holistic health strategies
Sustainability of Hermetia illucens in swine production: an innovative approach considering bioconversion efficiency, larvae and piglet welfare, and meat quality
No full textThis thesis explores the innovative uses of Black Soldier Fly (BSF, Hermetia illucens) larvae, including larval rearing, pig nutrition, and welfare, all aligned with sustainability and circular economy principles. Four studies were conducted on the integration of BSF utilization into the swine production chain. The first study assessed the use BSF larvae to convert various food residues, vegetable-based, omnivorous, and carnivorous diets, evaluating their impact on larval growth and bioconversion. Larvae fed vegetable-based diet showed the lowest growth, while those on omnivorous diets achieved performance and nutritional values comparable to the control (i.e., poultry feed), indicating its suitability for BSF rearing and underscoring the critical role of diet in optimizing BSF production strategies. However, the use of animal-derived ingredients in such diets is currently restricted under European legislation. The second study aimed to optimize the dietary regime of BSF larvae by adopting a welfare-oriented approach, confirming that omnivorous diets offered the best growth, nutritional composition, and larval welfare. The experiments aligned with the “Five Freedoms approach to welfare. The third study evaluated live BSF larvae as environmental enrichment for piglets. Animals receiving live larvae showed more activity, reduced stress, and less damaging behaviors compared to controls, supporting BSF larvae as effective environmental enrichment. The last study evaluated the replacement of soybean meal with BSF larvae meal and the substitution of traditional vegetable fats with BSF-derived fat in the diets of finishing pigs. The results indicated that BSFO maintained similar pig growth and meat quality to standard diets, while BSFLM posed challenges, likely due to chitin content. Overall, BSF larvae demonstrate strong potential as bioconverters of diverse food residues and as valuable feed or enrichment in swine production, fitting well within a circular economy model. Nevertheless, further research and regulatory development are needed to optimize their use and ensure food safety
Managing New Product Development processes in uncertain business environments
No full textNew Product Development (NPD) is critical to organizational growth and survival. In response to growing concerns over the limitations of traditional plan-driven processes, this Doctoral Thesis explores the integration and performance implications of flexible models in NPD through three complementary studies. The first study investigates the hybridization of plan-driven and flexible NPD models, identifying methodologies best suited for integration, effective integration stages, and contextual conditions favouring hybrid approaches. A systematic literature review and four case studies reveal that Agile, Design Thinking, and Lean Startup can be integrated into Stage-Gate models through nested or handed-over hybridization. Three hybrid types are outlined (Agile/Stage-Gate, Design Thinking/Stage-Gate, and Design Thinking and Lean Startup/Stage-Gate) along with four key decision-making dimensions (project type, market, technology, and learning gap) to guide R&D managers in model selection. The second study examines the relationship between NPD Agility and product innovation performance, considering the moderating role of project's innovation goals (incremental vs. radical). Using data from 88 NPD projects in the machinery and equipment industry, it identifies a positive but logarithmic relationship, indicating decreasing returns. This effect is significant for incremental innovation goals, but not for radical projects. The third study assesses the impact of Design Thinking, Lean Startup, and Agile learning cycles on new product performance under different levels of market ambiguity and market volatility. Based on 96 NPD projects in the machinery and equipment industry, it finds that Design Thinking and Agile positively affect performance, while Lean Startup does not. Design Thinking is more effective under high market ambiguity, Agile under low market ambiguity, while market volatility does not moderate these effects. Subgroup results further suggest Design Thinking is best suited to contexts where market ambiguity increases relative to, or together with, market volatility, while Agile seems better suited to environments with low market ambiguity and volatility
The intentional structure of emotions: a Husserlian approach
No full textThis dissertation investigates the nature of emotions through the lens of Husserlian phenomenology, arguing that emotions are not merely reactive states but intentional acts that fulfill a dual function: they both apprehend values and respond to them. While emotions undoubtedly manifest a responsive character, they also grasp objects and states of affairs in terms of their axiological significance, thereby playing an intrinsic value-disclosing role. This study aims to demonstrate that emotions are best understood as intentional processes rather than static, object-directed states. At first glance, this thesis appears paradoxical: how can emotions respond to the value of an object if that very value is apprehended through the emotion itself? To resolve this apparent contradiction, this dissertation draws on Husserl’s concept of functional intentionality, which conceives intentional acts as dynamic processes. By analyzing Husserl’s recently published “Studien zur Struktur des Bewusstseins,” this study reconstructs his account of emotional intentionality, focusing on its structural complexity, affective dimension, and epistemic significance in value experience. The dissertation is structured as follows. Chapter I contextualizes Husserl’s reflections on emotions within his broader phenomenological framework, examining the “Studien” in relation to his earlier work and comparing his approach to that of Brentano and Stumpf. Chapter II investigates the non-objectifying nature of emotions. Chapter III explores Husserl’s analogical method in the study of emotions, demonstrating that he employs analogy as a heuristic tool rather than a mere argumentative strategy. This chapter introduces the concepts of “Wertapperzeption” and “Wertauffassung”, of which “Wertnehmung” represents a specific case. Chapter IV examines Husserl’s notions of emotional coloring and emotional position-taking (Gemütsstellungnahme), emphasizing their role in highlighting the affective and responsive dimension of emotions. It then addresses objections to Husserl’s model. Finally, the dissertation defends the functional and processual nature of emotional intentionality by introducing the concepts of “Hingabe” and emotional motivation
Innovative and unobtrusive system for real-time driver drowsiness monitoring
No full textThis PhD thesis investigates the use of physiological signals to monitor driver state, addressing human factors as primary causes of road accidents. While conventional driver monitoring systems, such as camera-based and behavior-monitoring approaches, have limitations in reliability and response time, physiological signal monitoring offers valuable insight into driver states, including drowsiness detection. Signal acquisition, however, poses challenges in automotive environments, where body-attached devices are impractical.
The thesis initially explores wearable devices for monitoring, specifically the Empatica E4 wristband for capturing Photoplethysmography (PPG) and Electrodermal Activity (EDA) signals. A dedicated measurement campaign tested EDA alone and in combination with PPG, achieving 89% accuracy with EDA and 93% when combined with PPG, demonstrating these signals’ reliability for monitoring. However, limitations of wearables, such as the need to be worn and concerns with safe vehicle communication, led to the development of ANGELS, an innovative steering wheel embedded with sensors to acquire PPG and EDA directly from the driver’s hands.
ANGELS offers a completely unobtrusive alternative, incorporating advanced algorithms to mitigate motion artifacts. These algorithms performed effectively, yielding a mean absolute error (MAE) of 1.19 for heart rate and 1.9 misdetected peaks per minute for EDA. Tested in collaboration with Maserati, ANGELS achieved high drowsiness classification accuracy (77.03%) using a Temporal Convolutional Network (TCN). Additional force sensors were integrated to assess road vibrations' effects on signal quality, and ANGELS was connected to commercial devices for comprehensive driver-state monitoring. The findings underscore the reliability of physiological signals in driver monitoring, with ANGELS emerging as a promising solution for continuous, unobtrusive safety monitoring
Models and decision-making tools for the optimization of the efficiency and environmental impact of logistics and production systems
No full textThis thesis provides a comprehensive analysis and design framework for shuttle-based storage systems (SBSS), addressing key challenges in supply chain efficiency. As globalization and e-commerce drive the need for agile and automated warehousing, SBSS offer high-density storage, flexibility, and scalability. However, assessing their performance remains difficult due to the limitations of existing models, unrealistic assumptions, and the complexity of real-world implementations.
To bridge this gap, this research conducts a critical literature review, establishing a consistent nomenclature and proposing an original taxonomy of system configurations. A comprehensive framework is then developed, integrating analytical and simulation-based tools to estimate performance and optimize system design. The proposed hybrid model combines analytical travel time equations with simulations, improving accuracy in evaluating throughput, space efficiency, and system responsiveness under dynamic operational conditions.
A key innovation is the Space Efficiency Control System (SECS), a visual dashboard that monitors and optimizes storage utilization using time-based key performance indicators (KPIs). Additionally, a warehouse material flow generator simulates storage and retrieval requests when real data is unavailable, ensuring adaptability to different operational contexts. The bay sizing optimization procedure, based on a multi-queue single-server model, further enhances throughput by identifying and reducing system bottlenecks.
These tools collectively form a digital twin of SBSS, providing a user-friendly environment for designing, monitoring, and managing both new and existing systems. This digital twin allows real-time performance assessment, scenario simulation, and system reconfiguration, ensuring adaptability to evolving warehousing and material handling requirements.
Finally, the thesis evaluates the sustainability impact of SBSS using Life Cycle Assessment (LCA), measuring the carbon footprint of automated storage solutions. By addressing research gaps with rigorously developed methodologies, this work advances the state of the art and contributes to the transition to Industry 5.0, where human-machine collaboration, efficiency, and sustainability drive future warehouse innovations
Evolutionary and ecological determinants of human longevity
No full textHuman longevity and aging are shaped by a complex interplay of biological processes and ecological factors, with a significant variability across human populations. This thesis explores the roles of microevolutionary and ecological determinants in shaping human longevity and biological aging, using case studies from the Gran Chaco region in Argentina (Wichí and Criollos) and modern Italy. Biodemographic analysis revealed no significant impact of prolonged isolation or high kinship on biological aging in the Wichí, as assessed by epigenetic clocks. In contrast, Native American ancestry in the Criollos was associated with accelerated aging, highlighting the influence of genomic history on biological aging. Paleogenomic analysis of the modern Italian population identified contributions from ancient ancestries to longevity, with centenarians showing a stronger affinity for Western Hunter-Gatherer (WHG) ancestry, suggesting that ancient genetic components may contribute to promoting longevity. Paleogenomic analyses were also conducted at candidate gene level on the DLX5/6, a gene locus associated with longevity in mouse models. We identified a high frequency of the rs2240294 variant, linked to reduced DLX5/6 expression in Western Hunter-Gatherers (WHG), supporting an ancient evolutionary origin of certain variants related to extended lifespan. Within the ecological framework, analysis of modern rural and urban Italian individuals revealed higher intrinsic epigenetic age acceleration (IEAA) among those born in rural settings, likely influenced by socio-economic disparities and environmental exposures. Additionally, distinct ecological factors—such as nutrition, living environment, social conditions and infection load—significantly influence biological aging, as measured by epigenetic clocks, in the Wichí and Criollos populations, with the indigenous Wichí experiencing greater epigenetic age acceleration. These findings underscore the complex, multifactorial nature of aging as shaped by biodemographic history and ecological contexts, providing valuable insights into the determinants of longevity across diverse human populations