University of Bologna

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    Oceanic Near-inertial internal waves generation, propagation and interaction with mesoscale dynamics

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    Oceans play a key role in the climate system, being the largest heat sinks on Earth. Part of the energy balance of ocean circulation is driven by the Near-inertial internal waves (NIWs). Strong NIWs are observed during a multi-platform, multi-disciplinary and multi-scale campaign led by the NATO-STO CMRE in autumn 2017 in the Ligurian Sea (northwestern Mediterranean Sea). The objectives of this work are as follows: characterise the studied area at different scales; study the NIWs generation and their propagation; estimate the NIWs properties; study the interaction between NIWs and mesoscale structures. This work provides, to the author’s knowledge, the first characterization of NIWs in the Mediterranean Sea. The near-surface NIWs observed at the fixed moorings are locally generated by wind bursts while the deeper waves originate in other regions and arrive at the moorings several days later. Most of the observed NIWs energy propagates downward with a mean vertical group velocity of (2.2±0.3) ⋅10-4 m s-1. On average, the NIWs have an amplitude of 0.13 m s-1 and mean horizontal and vertical wavelengths of 43±25 km and 125±35 m, while shorter wavelengths are observed at the near-coastal mooring, 36±2 km and 33±2 m, respectively. Most of the observed NIWs are blue shifted and reach a value 9% higher than the local inertial frequency. Only two observed NIWs are characterised by a redshift (up to 3% lower than the local inertial frequency). In support of the in situ observations, a high resolution numerical model is implemented using NEMO (Madec et al., 2019). Results show that anticyclones (cyclones) shift the frequency of NIWs to lower (higher) frequencies with respect to the local inertial frequency. Anticyclones facilitate the downward propagation of NIW energy, while cyclones dampen it. Absence of NIWs energy within an anticyclone is also investigated

    The engagement of yugoslav technical cooperation experts in post-colonial Algeria (1962-1990). A global microhistory of east-south relations

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    The venture of socialist Eastern Europe in assisting the development efforts of the post-colonial countries opened up official migratory channels to the Global South for a specific labour group engaged under international technical cooperation programmes. By taking post-colonial Algeria as a space of East-South interactions and intense inter-socialist competition, the thesis studies labour mobility from socialist Yugoslavia of a heterogeneous group labelled “technical cooperation experts” in the period from 1962 to 1990. While CMEA members dispatched to the country personnel in great numbers, after 1965, Yugoslavia failed to do so. Tracing them beyond the institutional level, the thesis aims at detecting and exposing factors which inhibited the attempts to increase the presence of Yugoslav technical experts in Algeria. It argues that instead of building an alternative, solidarity-based aid model, Yugoslav technical cooperation with the developing countries was reduced to mediation in the employment of highly-skilled labour abroad. The cooperation scheme, which differed from one of its Eastern European counterparts, manifested in the employment and legal status as well as everyday life and work experiences of Yugoslav citizens. Relying on the methodological approach of global microhistory, which strongly favours the micro-historical analysis of primary sources in studying global processes, the thesis provides a more comprehensive and nuanced understanding of Yugoslav globalization endeavours. By shifting the focus to the experiences of ordinary people who were under the strong influence of globalization forces of the Cold War era, the thesis adds a “human” dimension to the history of East-South relations

    On the motion planning & control of nonlinear robotic systems

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    In the last decades, we saw a soaring interest in autonomous robots boosted not only by academia and industry, but also by the ever in- creasing demand from civil users. As a matter of fact, autonomous robots are fast spreading in all aspects of human life, we can see them clean houses, navigate through city traffic, or harvest fruits and vegetables. Almost all commercial drones already exhibit unprecedented and sophisticated skills which makes them suitable for these applications, such as obstacle avoidance, simultaneous localisation and mapping, path planning, visual-inertial odometry, and object tracking. The major limitations of such robotic platforms lie in the limited payload that can carry, in their costs, and in the limited autonomy due to finite battery capability. For this reason researchers start to develop new algorithms able to run even on resource constrained platforms both in terms of computation capabilities and limited types of endowed sensors, focusing especially on very cheap sensors and hardware. The possibility to use a limited number of sensors allowed to scale a lot the UAVs size, while the implementation of new efficient algorithms, performing the same task in lower time, allows for lower autonomy. However, the developed robots are not mature enough to completely operate autonomously without human supervision due to still too big dimensions (especially for aerial vehicles), which make these platforms unsafe for humans, and the high probability of numerical, and decision, errors that robots may make. In this perspective, this thesis aims to review and improve the current state-of-the-art solutions for autonomous navigation from a purely practical point of view. In particular, we deeply focused on the problems of robot control, trajectory planning, environments exploration, and obstacle avoidance

    Modeling of clear cell sarcoma of the kidney of the pediatric age

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    Clear cell sarcoma of the kidney (CCSK) is the second most common pediatric renal tumor, characterized in 90% of cases by the presence of internal tandem duplications (ITDs) localized at the last exon of BCOR gene. BCOR protein constitute a core component of the non-canonical Polycomb Repressive Complex1 (PRC1.1), which performs a fundamental silencing activity. ITDs in the last BCOR exon at the level of PUFD domain have been identified in many tumor subtypes and could affect PCGF1 binding and the subsequent PRC1.1 activity, although the exact oncogenic mechanism of ITD remains poorly understood. This project has the objective of investigating the molecular mechanisms underlying the oncogenesis of CCSK, approaching the study with different methodologies. A first model in HEK-293 allowed to obtain important informations about BCOR functionality, suggesting that the presence of ITD generates an altered activity which is very different from a loss-of-function. It has also been observed that BCOR function within the PRC1.1 complex varies with different ITDs. Moreover, it allowed the identification of molecular signatures evoked by the presence of BCOR-ITD, including its role in extracellular matrix interactions and invasiveness promotion. The parallel analysis of WTS data from 8 CCSK cases permitted the identification of a peculiar signature for metastatic CCSKs, highlighting a 20-fold overexpression of FGF3. This factor promoted a significant increase in invasive ability in the cellular model. In order to study BCOR-ITD effects over cell stemness and differentiation, an inducible model is being obtained in H1 cells. This way, it will be possible to study the functionality of BCOR-ITD in a context more similar to the origin of CCSKs, evaluating both the specific interactome and phenotypic consequences caused by the mutation

    Connecting works of art within the semantic web of symbolic meanings

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    My doctoral research is about the modelling of symbolism in the cultural heritage domain, and on connecting artworks based on their symbolism through knowledge extraction and representation techniques. In particular, I participated in the design of two ontologies: one models the relationships between a symbol, its symbolic meaning, and the cultural context in which the symbol symbolizes the symbolic meaning; the second models artistic interpretations of a cultural heritage object from an iconographic and iconological (thus also symbolic) perspective. I also converted several sources of unstructured data, a dictionary of symbols and an encyclopaedia of symbolism, and semi-structured data, DBpedia and WordNet, to create HyperReal, the first knowledge graph dedicated to conventional cultural symbolism. By making use of HyperReal's content, I showed how linked open data about cultural symbolism could be utilized to initiate a series of quantitative studies that analyse (i) similarities between cultural contexts based on their symbologies, (ii) broad symbolic associations, (iii) specific case studies of symbolism such as the relationship between symbols, their colours, and their symbolic meanings. Moreover, I developed a system that can infer symbolic, cultural context-dependent interpretations from artworks according to what they depict, envisioning potential use cases for museum curation. I have then re-engineered the iconographic and iconological statements of Wikidata, a widely used general-domain knowledge base, creating ICONdata: an iconographic and iconological knowledge graph. ICONdata was then enriched with automatic symbolic interpretations. Subsequently, I demonstrated the significance of enhancing artwork information through alignment with linked open data related to symbolism, resulting in the discovery of novel connections between artworks. Finally, I contributed to the creation of a software application. This application leverages established connections, allowing users to investigate the symbolic expression of a concept across different cultural contexts through the generation of a three-dimensional exhibition of artefacts symbolising the chosen concept

    Youth psychosocial adjustment in the context of parental illness: risk and protective factors

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    Young carers might experience both psychological distress and positive changes from living with their chronically ill parent. However, little is known about why some young carers do well with their situation and experience positive outcomes, whereas others do not. In this regard, this dissertation aims to investigate how parental chronic illness affects young carers’ psychosocial adjustment through risk (i.e., unmet needs) and protective factors (i.e., benefit finding, emotion regulation). This main goal has been addressed by conducting three studies presented in Chapters 2–4. Chapter 2 has examined the mediating role of unmet needs on the relationship between illness unpredictability and youth psychosocial adjustment (i.e., quality of life and internalizing problems). In this regard, it has been found that levels of unmet needs significantly mediated the relationship between illness unpredictability and offspring health-related quality of life. In the systematic review with meta-analysis presented within Chapter 3, it has been sought to investigate the mediating role of the protective factors (i.e., benefit finding and emotion regulation) in the relationship between caregiving components and youth psychosocial adjustment in young carers. This study has shown the significant associations between caregiving components and psychosocial adjustment in young carers not only directly, but also indirectly through protective factors. Finally, to expand on previous findings, a qualitative study in Chapter 4 has examined the unique experiences of young carers, as well as the effects of the COVID-19 global pandemic. This study has yielded a deeper understanding of how protective factors may be operated during young carers’ lived experiences before and during the COVID-19 global pandemic. Overall, this dissertation has shed light on the pivotal role played by risk and protective factors in caregiving components that serve as key determinants that can enhance positive psychosocial outcomes as well as concurrently mitigate adverse psychosocial consequences among young carers

    Hardware-software design of embedded systems for intelligent sensing applications

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    This Thesis wants to highlight the importance of ad-hoc designed and developed embedded systems in the implementation of intelligent sensor networks. As evidence four areas of application are presented: Precision Agriculture, Bioengineering, Automotive and Structural Health Monitoring. For each field is reported one, or more, smart device design and developing, in addition to on-board elaborations, experimental validation and in field tests. In particular, it is presented the design and development of a fruit meter. In the bioengineering field, three different projects are reported, detailing the architectures implemented and the validation tests conducted. Two prototype realizations of an inner temperature measurement system in electric motors for an automotive application are then discussed. Lastly, the HW/SW design of a Smart Sensor Network is analyzed: the network features on-board data management and processing, integration in an IoT toolchain, Wireless Sensor Network developments and an AI framework for vibration-based structural assessment

    [In search of] Digital biomarkers for objective pain assessment

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    Pain is a highly complex phenomenon involving intricate neural systems, whose interactions with other physiological mechanisms are not fully understood. Standard pain assessment methods, relying on verbal communication, often fail to provide reliable and accurate information, which poses a critical challenge in the clinical context. In the era of ubiquitous and inexpensive physiological monitoring, coupled with the advancement of artificial intelligence, these new tools appear as the natural candidates to be tested to address such a challenge. This thesis aims to conduct experimental research to develop digital biomarkers for pain assessment. After providing an overview of the state-of-the-art regarding pain neurophysiology and assessment tools, methods for appropriately conditioning physiological signals and controlling confounding factors are presented. The thesis focuses on three different pain conditions: cancer pain, chronic low back pain, and pain experienced by patients undergoing neurorehabilitation. The approach presented in this thesis has shown promise, but further studies are needed to confirm and strengthen these results. Prior to developing any models, a preliminary signal quality check is essential, along with the inclusion of personal and health information in the models to limit their confounding effects. A multimodal approach is preferred for better performance, although unimodal analysis has revealed interesting aspects of the pain experience. This approach can enrich the routine clinical pain assessment procedure by enabling pain to be monitored when and where it is actually experienced, and without the involvement of explicit communication,. This would improve the characterization of the pain experience, aid in antalgic therapy personalization, and bring timely relief, with the ultimate goal of improving the quality of life of patients suffering from pain

    Green approach to Palladium Cross-Coupling reactions and development of new methodologies based on highly abundant metals

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    Transition metal catalyzed cross-coupling reactions represent among the most versatile and useful tools in organic synthesis for the carbon-carbon (C-C) bond formation and have a prominent role in both the academic and pharmaceutical segments. Among them, palladium catalyzed cross-coupling reactions are currently the most versatile. In this thesis, the applications, impact and development of green palladium cross-coupling reactions are discussed. Specifically, we discuss the translation of the Twelve Principles of Green Chemistry and their applications in pharmaceutical organometallic chemistry to stimulate the development of cost-effective and sustainable catalytic processes for the synthesis of active pharmaceutical ingredients (API). The Heck-Cassar-Sonogashira (HCS) and the Suzuki-Miyaura (SM) protocols, using HEP/H2O as green mixture and sulfonated phosphine ligands, allowed to recycle and recover the catalyst, always guaranteeing high yields and fast conversion under mild conditions, with aryl iodides, bromides, triflates and chlorides. No catalyst leakage or metal contamination of the final product were observed during the HCS and SM reactions, respecting the very low limits for metal impurities in medicines established by the International Conference of Harmonization Guidelines Q3D (ICH Q3D). In addition, a deep understanding of the reaction mechanism is very important if the final target is to develop efficient protocols that can be applied at industrial level. Experimental and theoretical studies pointed out the presence of two catalytic cycles depending on the counterion, shedding light on the role of base in catalyst reduction and acetylene coordination in the HCS coupling. Finally, the development of a cross-coupling reaction to form aryldifluoronitriles in the presence of copper is discussed, highlighting the importance of inserting fluorine atoms within biological structures and the use of readily available metals such as copper as an alternative to palladium

    Computational modeling of human atrial cardiomyocytes: integration of electro-mechanical & mechano-electric feedback pathways

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    The cardiomyocytes are very complex consisting of many interlinked non-linear regulatory mechanisms between electrical excitation and mechanical contraction. Thus given a integrated electromechanically coupled system it becomes hard to understand the individual contributor of cardiac electrics and mechanics under both physiological and pathological conditions. Hence, to identify the causal relationship or to predict the responses in a integrated system the use of computational modeling can be beneficial. Computational modeling is a powerful tool that provides complete control of parameters along with the visibility of all the individual components of the integrated system. The advancement of computational power has made it possible to simulate the models in a short timeframe, providing the possibility of increased predictive power of the integrated system. My doctoral thesis is focused on the development of electromechanically integrated human atrial cardiomyocyte model with proper consideration of feedforward and feedback pathways

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