Challenges and Opportunities of Machine Learning for Clinical and Omics Data

Clinical and omics data are a promising field of application for machine learning techniques even though these methods are not yet systematically adopted in healthcare institutions. Despite artificial intelligence has proved successful in terms of prediction of pathologies or identification of their causes, the systematic adoption of these techniques still presents challenging issues due to the peculiarities of the analysed data. The aim of this thesis is to apply machine learning algorithms to both clinical and omics data sets in order to predict a patient's state of health and get better insights on the possible causes of the analysed diseases. In doing so, many of the arising issues when working with medical data will be discussed while possible solutions will be proposed to make machine learning provide feasible results and possibly become an effective and reliable support tool for healthcare systems.

Asymmetric aminocatalysis: a modern strategy for molecules, challenges and life

The studies conducted during my Phd thesis were focused on two different directions: 1. In one case we tried to face some long standing problems of the asymmetric aminocatalysis as the activation of encumbered carbonyl compounds and the control of the diastereoisomeric ratio in the diastero- and enantioselective construction of all carbon substituted quaternary stereocenters adjacent a tertiary one. In this section (Challenges) was described the asymmetric aziridination of ,-unsaturated ketones, the activation of ,-unsaturated -branched aldehydes and the Michael addition of oxindoles to enals and enones. For the activation via iminium ion formation of sterically demanding substrates, as ,-unsaturated ketones and ,-unsaturated -branched aldehydes, we exploited a chiral primary amine in order to overcome the problem of the iminium ion formation between the catalyst and encumbered carbonylic componds. For the control of diastereoisomeric ratio in the diastero- and enantioselective construction of all carbon substituted quaternary stereocenters adjacent a tertiary one we envisaged that a suitable strategy was the Michael addition to 3 substituted oxindoles to enals activated via LUMO-lowering catalysis. In this synthetic protocol we designed a new bifunctional catalyst with an amine moiety for activate the aldehyde and a tioureidic fragment for direct the approach of the oxindole. This part of the thesis (Challenges) could be considered pure basic research, where the solution of the synthetic problem was the goal itself of the research. 2. In the other hand (Molecules) we applied our knowledge about the carbonylic compounds activation and about cascade reaction to the synthesis of three new classes of spirooxindole in enantiopure form. The construction of libraries of these bioactive compounds represented a scientific bridge between medicinal chemistry or biology and the asymmetric catalysis.

The challenges and the limitations in Life Cycle Impact Assessment for metal oxide nanoparticles, a case study on nano- TiO2

Life Cycle Assessment (LCA) is a chain-oriented tool to evaluate the environment performance of products focussing on the entire life cycle of these products: from the extraction of resources, via manufacturing and use, to the final processing of the disposed products. Through all these stages consumption of resources and pollutant releases to air, water, soil are identified and quantified in Life Cycle Inventory (LCI) analysis. Subsequently to the LCI phase follows the Life Cycle Impact Assessment (LCIA) phase; that has the purpose to convert resource consumptions and pollutant releases in environmental impacts. The LCIA aims to model and to evaluate environmental issues, called impact categories. Several reports emphasises the importance of LCA in the field of ENMs. The ENMs offer enormous potential for the development of new products and application. There are however unanswered questions about the impacts of ENMs on human health and the environment. In the last decade the increasing production, use and consumption of nanoproducts, with a consequent release into the environment, has accentuated the obligation to ensure that potential risks are adequately understood to protect both human health and environment. Due to its holistic and comprehensive assessment, LCA is an essential tool evaluate, understand and manage the environmental and health effects of nanotechnology. The evaluation of health and environmental impacts of nanotechnologies, throughout the whole of their life-cycle by using LCA methodology. This is due to the lack of knowledge in relation to risk assessment. In fact, to date, the knowledge on human and environmental exposure to nanomaterials, such ENPs is limited. This bottleneck is reflected into LCA where characterisation models and consequently characterisation factors for ENPs are missed. The PhD project aims to assess limitations and challenges of the freshwater aquatic ecotoxicity potential evaluation in LCIA phase for ENPs and in particular nanoparticles as n-TiO2.

Sustainability in buildings and waste sector: metrics, challanges, and opportunities

Nowadays, the scientific community has devoted a consistent effort to the sustainable development of the waste management sector and resource efficiency in building infrastructures. Waste is the fourth largest source sector of emissions and the municipal solid waste management system is considered as the most complex system to manage, due to its diverse composition and fragmentation of producers and responsibilities. Nevertheless, given the deep complexity that characterize the waste management sector, sustainability is still a challenging task. Interestingly, open issues arise when dealing with the sustainability of the waste sector. In this thesis, some recent advances in the waste management sector have been presented. Specifically, through the analysis of four author publications this thesis attempted to fill the gap in the following open issues: (i) the waste collection and generation of waste considering the pillars of sustainability; (ii) the environmental and social analysis in designing building infrastructures; (iv) the role of the waste collection in boosting sustainable systems of waste management; (v) the ergonomics impacts of waste collection. For this purpose, four author publications in international peer – reviewed journals were selected among the wholly author's contributions (i.e., final publication stage).

Characterization of pyrolysis and oxidation processes of biomaterials, biomasses and biofuels

The urgent need for alternative solutions mitigating the impacts of human activities on the environment has strongly opened new challenges and opportunities in view of the energy transition. Indeed, the automotive industry is going through a revolutionary moment in its quest to reduce its carbon footprint, with biofuels being one of the viable alternatives. The use of different classes of biofuels as fuel additives/standalone components has attracted the attention of many researchers. Despite their beneficial effects, biofuel’s combustion can also result in the production of undesirable pollutants, requiring complete characterization of the phenomena occurring during their production and consumption. Industrial scale-up of biomass conversion is challenging owing to the complexity of its chemistry and transport phenomena involved in the process. In this view, the role of solid-phase and gas-phase chemistry is paramount. Thus, this study is devoted to detailed analysis of physical-chemical phenomena characterizing biomass pyrolysis and biofuel oxidation. The pyrolysis mechanism has been represented by 20 reactions whereas, the gas-phase kinetic models; manually upgraded model (KiBo_MU) and automated model (KiBo_AG), comprises 141 species and 453 reactions, and 631 species and 28329 reactions, respectively. The accuracy of the kinetic models was tested against experimental data and the models captured experimental trends very well. While the development and validation of detailed kinetic mechanisms is the main deliverable of this project, the realized procedure integrating schematic classifications with methodologies for the identification of common decomposition pathways and intermediates represents an additional source of novelty. Besides, the fundamentally oriented nature of the adopted method allows the identification of most relevant reactions and species under the operating conditions different industrial applications, paving the way for reduced kinetic mechanisms. Ultimately, the resulting detailed mechanisms can be used to integrate with more complex fluid dynamics model to accurately reproduce the behavior of real systems and reactors.

Design and implementation of a novel multi-constellation FPGA-based dual frequency GNSS receiver for space applications

The PhD activity described in the document is part of the Microsatellite and Microsystem Laboratory of the II Faculty of Engineering, University of Bologna. The main objective is the design and development of a GNSS receiver for the orbit determination of microsatellites in low earth orbit. The development starts from the electronic design and goes up to the implementation of the navigation algorithms, covering all the aspects that are involved in this type of applications. The use of GPS receivers for orbit determination is a consolidated application used in many space missions, but the development of the new GNSS system within few years, such as the European Galileo, the Chinese COMPASS and the Russian modernized GLONASS, proposes new challenges and offers new opportunities to increase the orbit determination performances. The evaluation of improvements coming from the new systems together with the implementation of a receiver that is compatible with at least one of the new systems, are the main activities of the PhD. The activities can be divided in three section: receiver requirements definition and prototype implementation, design and analysis of the GNSS signal tracking algorithms, and design and analysis of the navigation algorithms. The receiver prototype is based on a Virtex FPGA by Xilinx, and includes a PowerPC processor. The architecture follows the software defined radio paradigm, so most of signal processing is performed in software while only what is strictly necessary is done in hardware. The tracking algorithms are implemented as a combination of Phase Locked Loop and Frequency Locked Loop for the carrier, and Delay Locked Loop with variable bandwidth for the code. The navigation algorithm is based on the extended Kalman filter and includes an accurate LEO orbit model.