Spatial adaptive settlement systems in archaeology. Modelling long-term settlement formation from spatial micro interactions

Doctoral thesis (2023)

Despite research history spanning more than a century, settlement patterns still hold a promise to contribute to the theories of large-scale processes in human history. Mostly they have been presented as ... [more ▼]

Despite research history spanning more than a century, settlement patterns still hold a promise to contribute to the theories of large-scale processes in human history. Mostly they have been presented as passive imprints of past human activities and spatial interactions they shape have not been studied as the driving force of historical processes. While archaeological knowledge has been used to construct geographical theories of evolution of settlement there still exist gaps in this knowledge. Currently no theoretical framework has been adopted to explore them as spatial systems emerging from micro-choices of small population units. The goal of this thesis is to propose a conceptual model of adaptive settlement systems based on complex adaptive systems framework. The model frames settlement system formation processes as an adaptive system containing spatial features, information flows, decision making population units (agents) and forming cross scale feedback loops between location choices of individuals and space modified by their aggregated choices. The goal of the model is to find new ways of interpretation of archaeological locational data as well as closer theoretical integration of micro-level choices and meso-level settlement structures. The thesis is divided into five chapters, the first chapter is dedicated to conceptualisation of the general model based on existing literature and shows that settlement systems are inherently complex adaptive systems and therefore require tools of complexity science for causal explanations. The following chapters explore both empirical and theoretical simulated settlement patterns based dedicated to studying selected information flows and feedbacks in the context of the whole system. Second and third chapters explore the case study of the Stone Age settlement in Estonia comparing residential location choice principles of different periods. In chapter 2 the relation between environmental conditions and residential choice is explored statistically. The results confirm that the relation is significant but varies between different archaeological phenomena. In the third chapter hunter-fisher-gatherer and early agrarian Corded Ware settlement systems were compared spatially using inductive models. The results indicated a large difference in their perception of landscape regarding suitability for habitation. It led to conclusions that early agrarian land use significantly extended land use potential and provided a competitive spatial benefit. In addition to spatial differences, model performance was compared and the difference was discussed in the context of proposed adaptive settlement system model. Last two chapters present theoretical agent-based simulation experiments intended to study effects discussed in relation to environmental model performance and environmental determinism in general. In the fourth chapter the central place foragingmodel was embedded in the proposed model and resource depletion, as an environmental modification mechanism, was explored. The study excluded the possibility that mobility itself would lead to modelling effects discussed in the previous chapter. The purpose of the last chapter is the disentanglement of the complex relations between social versus human-environment interactions. The study exposed non-linear spatial effects expected population density can have on the system and the general robustness of environmental inductive models in archaeology to randomness and social effect. The model indicates that social interactions between individuals lead to formation of a group agency which is determined by the environment even if individual cognitions consider the environment insignificant. It also indicates that spatial configuration of the environment has a certain influence towards population clustering therefore providing a potential pathway to population aggregation. Those empirical and theoretical results showed the new insights provided by the complex adaptive systems framework. Some of the results, including the explanation of empirical results, required the conceptual model to provide a framework of interpretation. [less ▲]

Supporting Safety Analysis of Deep Neural Networks with Automated Debugging and Repair

Doctoral thesis (2023)

Three Essays on the General Equilibrium Effects of Human Interactions

Doctoral thesis (2023)

The overarching theme of this PhD thesis is human mobility and its externalities, particularly in the context of labour and health economics. Through rigorous modelling and analysis, the three chapters of ... [more ▼]

The overarching theme of this PhD thesis is human mobility and its externalities, particularly in the context of labour and health economics. Through rigorous modelling and analysis, the three chapters of the thesis demonstrate the potential benefits of policies that regulate human mobility. In the first chapter of my PhD, I examine how language training can improve the functioning of the labour market, with a particular focus on immigrants with high skills who face language barriers. I argue that fully funding the cost of language acquisition for migrants can bring significant benefits to the economy and migrants, but may marginally worsen the labour market performance of low-skilled natives. Using a search and matching framework with two-dimensional skill heterogeneity, I model the effects of a language acquisition subsidy on migrants' labour market integration and its impact on natives' labour market performance. My study finds that subsidizing language acquisition costs may increase the GDP of the German economy by approximately ten billion dollars by decreasing the aggregate unemployment rate and skill mismatch rate and increasing the share of job vacancies requiring high generic skills. The second chapter of my PhD explores the challenges involved in devising social contact limitation policies as a means of controlling infectious disease transmission. Using an economic-epidemiological model of COVID-19 transmission, I evaluate the effectiveness of different intervention strategies and their consequences on public health, social welfare and economic outcomes. The findings emphasize the importance of responsiveness in implementing social contact limitations, rather than solely focusing on their stringency, and suggest that early interventions lead to the lowest losses in economy and mental well-being for a given number of life losses. The study has broader implications for managing the societal impact of infectious diseases and highlights the need to continue refining our understanding of these trade-offs and developing adaptable models and policy tools to safeguard public health while minimizing social and economic consequences. Overall, the study offers a robust and versatile framework for understanding and navigating the challenges posed by public health crises and pandemics. The third chapter of my PhD builds on the economic-epidemiological model developed in Chapter 2 to analyze the multifaceted effects of vaccine hesitancy in controlling the spread of infectious diseases, with a particular focus on the COVID-19 pandemic in Belgium. The study utilizes actual vaccination rates by age group until June 2021 and simulates the following months by incorporating realistic properties such as temporary immunity, age-specific vaccination hesitancy rates, daily vaccination capacity, and vaccine efficacy rate. The baseline scenario with an overall 27.1$\%$ vaccine hesitancy rate indicates that current vaccination rates in Belgium are sufficient to control the spread of COVID-19 without imposing social contact limitations. However, hypothetical scenarios with higher disease transmission rates demonstrate the high costs of vaccine hesitancy, resulting in significant losses in labour supply, mental well-being, and life losses. Throughout this thesis, I have described the costs and benefits induced by mobility, and shown that mobility policies make winners and losers. In Chapter 1, subsidizing the cost of language acquisition for migrants can bring significant benefits to the economy and migrants, but may marginally worsen the labour market performance of low-skilled natives. In Chapter 2, stringent policies alleviate health losses, but they impact economic activity and mental health. In Chapter 3, the health externalities generated by human interactions impose a potential tradeoff between values, namely the freedom to move and the freedom to choose to get vaccinated. In each of these chapters, I quantify these tradeoffs. Another important insight from this thesis is the need to incorporate behavioural aspects into macro models evaluating the consequences of policies related to human mobility. In the thesis, these aspects include individual investments in language training, decision-making on infection avoidance, social contacts, labour supply, and vaccination decisions. can lead to more effective policies that balance the interests of various stakeholders. Overall, this thesis contributes to the literature on human mobility by highlighting the potential benefits and challenges associated with it, and the need for nuanced and responsive policymaking that takes into account behavioural aspects and externalities. The insights gained from this thesis can be relevant for future research in economics on topics related to human mobility, public health, and labour market integration. [less ▲]

Le Phénomène des textes jumeaux : l’acte d’autocorrection (dialogue entre Andreï Tarkovski et Arséni Tarkovski, et autres exemples de textes jumeaux d’un écrivain/artiste des XXe et XXIe siècles)

Doctoral thesis (2023)

This thesis analyses the texts of authors who developed the capacity to regularly apply different systems of expression in their creative writing/art. These writers/artists generally experiment with ... [more ▼]

This thesis analyses the texts of authors who developed the capacity to regularly apply different systems of expression in their creative writing/art. These writers/artists generally experiment with poetic/prosaic, verbal/visual forms or several languages. One of the artistic results that they can produce, consciously or unconsciously, is a “twin text,” the object of the current study. The objective of the present research is to establish the concept of twin texts as a cultural supranational phenomenon, propose a method to identify and study them, and suggest reasons why the author creates them systematically. The twin texts are two or more « texts » (verbal and/or visual) that are linked to each other on the thematic level by repeating their images or plots or by showing the same characters, often in a contradictory way. Twin texts can be the result of a non-monolingual situation and non-identified artistic position of an author. For these reasons, we find twin texts among émigré and translingual writers, « non-professionals » (prose writers creating poems or artists applying verbal forms of expression, and vice versa), and other writers/artists whose identity can be defined as « multiple ». By elaborating a series of images, the author of twin texts is placed in a situation described by Mikhail Bakhtin as polyphonic. By being above the meanings his/her works contain, the author of twin texts establishes a space for dialogue. In other words, the writer/artist is not above the text, but above all the texts, « avant-texte », to borrow this term from genetic criticism. [less ▲]

Learning Optimisation Algorithms over Graphs

Doctoral thesis (2023)

The paradigm of learning to optimise relies on the following principle: instead of designing an algorithm to solve a problem, we design an algorithm which will automate the design of such a solver. The ... [more ▼]

The paradigm of learning to optimise relies on the following principle: instead of designing an algorithm to solve a problem, we design an algorithm which will automate the design of such a solver. The initial idea was to alleviate the limitations stated by the No Free Lunch Theorem by producing an algorithm which efficiency is less dependent upon known instances of the problem to tackle. Hyper-heuristics constitute the main learning-to-optimise techniques. These rely on a high-level algorithm performing a search process into a space of low-level heuristics to tackle a given problem. Because the latter search space is problem-dependent, the vast majority of hyper-heuristics are designed to tackle a specific problem. Due to this lack of generality, existing works fully redesign hyper-heuristics when tackling a new problem, despite the fact that they may share a similar structure. In this dissertation, we tackle this challenge by proposing a generic way for learning to optimise any problem. To this end, this thesis introduces three main contributions: (i) an analysis of the formal functioning of learning-to-optimise techniques; (ii) a model of generic hyper-heuristic, named Algorithm Learner for Graph Optimisation problems (ALGO), constituting the central point of this work; (iii) a real-world use case where we use our generic hyper-heuristic to automate the design of behaviours within a swarm of drones. In the first part, we provide a formalism for optimisation and learning concepts, which we use to describe the large body of knowledge that combines two layers of optimisation and/or learning. We then put an emphasis on approaches using learning to improve an optimisation process, i.e., aiming at learning to optimise. In the second part, we present ALGO, our model of generic hyper-heuristic. We explain how we abstract from a given problem with a graph structure so that it can be used to tackle any optimisation problem. We also detail the steps to follow in order to use ALGO to tackle a given problem. We finally present the modularity of ALGO with inner components that a user can implement. The second part ends with a validation of our model, i.e., using ALGO to tackle a classical optimisation problem. In the third part, we use ALGO to tackle the problem of area surveillance with a swarm of drones. We demonstrate that ALGO constitutes a novel and efficient way to automate the design of such a distributed and multi-objective problem. [less ▲]

Essays On Skills, Labor Market Institutions and Wage Inequality

Doctoral thesis (2023)

Security and Privacy of Resource Constrained Devices

Doctoral thesis (2023)

The thesis aims to present a comprehensive and holistic overview on cybersecurity and privacy & data protection aspects related to IoT resource-constrained devices. Chapter 1 introduces the current ... [more ▼]

The thesis aims to present a comprehensive and holistic overview on cybersecurity and privacy & data protection aspects related to IoT resource-constrained devices. Chapter 1 introduces the current technical landscape by providing a working definition and architecture taxonomy of ‘Internet of Things’ and ‘resource-constrained devices’, coupled with a threat landscape where each specific attack is linked to a layer of the taxonomy. Chapter 2 lays down the theoretical foundations for an interdisciplinary approach and a unified, holistic vision of cybersecurity, safety and privacy justified by the ‘IoT revolution’ through the so-called infraethical perspective. Chapter 3 investigates whether and to what extent the fast-evolving European cybersecurity regulatory framework addresses the security challenges brought about by the IoT by allocating legal responsibilities to the right parties. Chapters 4 and 5 focus, on the other hand, on ‘privacy’ understood by proxy as to include EU data protection. In particular, Chapter 4 addresses three legal challenges brought about by the ubiquitous IoT data and metadata processing to EU privacy and data protection legal frameworks i.e., the ePrivacy Directive and the GDPR. Chapter 5 casts light on the risk management tool enshrined in EU data protection law, that is, Data Protection Impact Assessment (DPIA) and proposes an original DPIA methodology for connected devices, building on the CNIL (French data protection authority) model. [less ▲]

From Standards of International Law for Outer Space Resources Exploitation to Sustainable Mining

Doctoral thesis (2023)

As space activities continue to develop and increase in number, so do environmental concerns in outer space. For decades now, humanity has continuously sent satellites into Earth orbits without caring for ... [more ▼]

As space activities continue to develop and increase in number, so do environmental concerns in outer space. For decades now, humanity has continuously sent satellites into Earth orbits without caring for potential environmental consequences in outer space. Ultimately, these actions have proven to raise issues regarding the sustainability of the activity; issues which are now being addressed legally. Satellites were the first venture of humanity into space, and it is fair to admit we did not know better at the time. We do now. With the development of new types of space missions, such as space resources-related activities, it is safe to assume that new serious environmental problems will arise as well. Based on previous experience both on Earth and in outer space, it is logical, but also imperative, to question the environmental impact of these space resources activities and to consider legal solutions to promote and facilitate their sustainability. Accordingly, this research assesses the applicability of existing rules and mechanisms promoting environmental protection and sustainability in outer space to the case of the exploitation of space resources. To that end, an array of mechanisms is considered such as the framework of the UN Space Treaties, international environmental law, non-legally binding instruments, such as the space debris mitigation guidelines and COSPAR’s planetary protection policy, as well as national space legislations. Ultimately, this work aims at drafting the roadmap for the environmentally sustainable exploitation of space resources from a legal standpoint. It recommends the adoption of a mix of interdisciplinary approaches which balances a national effective approach with international guiding rules. [less ▲]

The Application of the European Account Preservation Order in Germany, Luxembourg and Spain: A Comparative-Empirical Analysis

Doctoral thesis (2023)

Regulation (EU) 655/2014, establishing a European Account Preservation Order (‘EAPO Regulation’), introduced the very cross-border interim measure at the European Union level. As its name indicates, it ... [more ▼]

Regulation (EU) 655/2014, establishing a European Account Preservation Order (‘EAPO Regulation’), introduced the very cross-border interim measure at the European Union level. As its name indicates, it permits the direct cross-border attachment of funds in bank accounts. Furthermore, it contains a specific mechanism to search for the debtors’ bank accounts that does not exist in all EU-Member States. Although the EAPO is a self-standing procedure, it combines uniform standards with other aspects of the procedure that depend on national law. This dissertation studies and compares the application of the EAPO Regulation in three jurisdictions: Germany, Luxembourg, and Spain. It aims to understand the incorporation of the EAPO procedure within a national civil procedural system and the impact national law has on the EAPO procedure as a whole. The comparative approach determines the different ways Member States apply the EAPO procedures. This comparative analysis follows both a theoretical and empirical approach. The empirical approach relies on qualitative and quantitative data on the functioning of the EAPO obtained from stakeholders, case law databases, and institutional statistical data. The empirical side of the research seeks to identify specific issues courts and practitioners encounter in real-life EAPO cases, and whether such issues are the same or different depending on the jurisdiction where the EAPO is applied. Relying on the outcome of the comparative-empirical analysis, specific policy-making recommendations are designed and intended to improve the application of the EAPO at the EU and the national level. [less ▲]

CONNECTION TECHNOLOGIES FOR FAST ERECTION OF STEEL STRUCTURES FOR BUILDINGS (FEOSBUILD)

Doctoral thesis (2023)

Steel-concrete hybrid building systems offer sustainable and effective structural solutions for multi-story and high-rise buildings considering that steel is a completely recyclable material and that the ... [more ▼]

Steel-concrete hybrid building systems offer sustainable and effective structural solutions for multi-story and high-rise buildings considering that steel is a completely recyclable material and that the most advantageous mechanical properties of steel and concrete could be used simultaneously against the effects of tension and compression stress resultants. On the other hand, a small percentage of multi-story buildings and a small number of high-rise structures are actually constructed using steel-concrete hybrid building technologies. This is mostly a result of general contractors’ orientation toward the completion of construction projects using traditional reinforced-concrete construction techniques. Therefore, they generally do not employ a sufficient and competent workforce to execute labor-intensive and complex on-site manufacturing activities such as welding of fin plates and pre-tensioning applications for high-strength bolts required to assemble steel beams and reinforced-concrete columns and walls of steel-concrete hybrid building systems. In order to reduce labor-intensive on-site tasks, general construction contractors typically utilize conventional construction approaches using only reinforced concrete building systems. As a result, the structural and environmental benefits of steel-concrete hybrid building systems could not be widely adopted by the construction industry. This research project proposes three different novel structural joint configurations with cutting-edge saw-tooth interface mechanical interlock bolted connection, bolt-less plug-in connection, and grouted joint details for beam-to-column joints of steel-concrete hybrid building systems. The proposed joint configurations eliminate on-site welding and enable the accommodation of construction and manufacturing tolerances in three spatial directions to achieve fast erection strategies for the construction of steel-concrete hybrid building systems. Therefore, the outcomes of the research project make it possible for general construction contractors to use their existing workforce to complete construction tasks for steel-concrete hybrid building systems without the requirement of specialized tools or training. In this study, a total of six separate experimental test campaigns were established to determine the load-deformation behaviors of the proposed joint configurations and to identify their load-bearing components. In order to show that the suggested joint configurations are appropriate for mass production without the utilization of special equipment or machinery, the experimental test prototypes of the proposed joint configurations were produced in partnership with commercial producers. The experimental test campaigns were simulated with numerical models by means of advanced computer-aided finite element analyses for the identification of the ultimate deformation limits of the proposed joint components and to clarify their progressive failure mechanisms under quasi-static loading conditions. A set of analytical resistance models were developed to estimate the load-bearing capacities of the proposed joint configurations based on the failure modes identified by the observations made during the experimental tests and in accordance with the output results of the numerical simulations. Based on the analytical expressions, the most significant, in other words, the basic variables impacting the load-bearing capacities of the proposed joint configurations were identified. Additionally, the load-deformation behaviors of the proposed joint configurations were further investigated with numerical parametric studies by parametrizing the basic variables to understand their impact on the load-deformation behaviors of the proposed joint configurations. To verify the accuracy of the analytical resistance models of the proposed joint configurations, the estimations of the analytical expressions were compared with the output results of the numerical parametric studies. Based on the distribution of the estimations of the analytical expression against the output result of the numerical parametric studies, characteristic and design partial safety factors were established according to EN1990, Annex D for the analytical resistance models of the saw-tooth interface mechanical interlock bolted connection and bolt-less plug-in connection. The estimations of the analytical resistance model of grouted joint details for beam-to-column joints of steel-concrete hybrid building systems were also compared with the output results of a numerical parametric study but no partial safety factor was established for this joint detail. [less ▲]

Observing unseen flowlines and their contribution to near stream endmembers in forested headwater catchments.

Doctoral thesis (2023)

The general scope of the PhD research project falls within the framework of developing integrated catchment hydro-biogeochemical theories in the context of the Critical Zone (CZ). Significant advances in ... [more ▼]

The general scope of the PhD research project falls within the framework of developing integrated catchment hydro-biogeochemical theories in the context of the Critical Zone (CZ). Significant advances in the understanding of water transit time theory, subsurface structure controls, and the quantification of catchment scale weathering rates have resulted in the convergence of classical biogeochemical and hydrological theories. This will potentially pave the way for a more mechanistic understanding of CZ because many challenges still exist. Perhaps the most difficult of all is a unifying hydro-biogeochemical theory that can compare catchments across gradients of climate, geology, and vegetation. Understanding the processes driving the evolution of chemical tracers as they move through space and time is of cardinal importance to validating mixing hypotheses and assisting in determining the residence time of water in CZ. The specific aim of the study is to investigate what physical and biogeochemical processes are driving variations in observable endmembers in stream discharge as a function of the hydrological state at headwater catchment scale. This requires looking beyond what can be observed in the stream and what is called ”unseen flowlines” in this thesis. The Weierbach Experimental Catchment (WEC) in Luxembourg provides a unique opportunity to study these processes, with an extensive biweekly groundwater chemistry dataset spanning over ten years. Additionally, WEC has been the subject of numerous published works in the domain of CZ science, adding to an already detailed hydrological and geochemical understanding of the system. Multivariate analysis techniques were used to identify the unseen flowlines in the catchment. Together with the excising hydrological perception model and a geochemical modelling approach, these flowlines were rigorously investigated to understand what processes drive their respective manifestations in the system. The existing perceptual model for WEC was updated by the new findings and tested on 27 flood events to assess if it could adequately explain the c − Q behaviour observed during these periods. The novelty of the study lies in the fact that it uses both data-driven modelling approaches and geochemical processbased modelling to look beyond what can be observed in the near-stream environment of headwaters. [less ▲]

Senescence as a Converging Mechanism in Parkinson's Disease

Doctoral thesis (2023)

Neurodegenerative diseases are one of the leading causes of disability and mortality, affecting millions of people worldwide. Parkinson’s disease (PD) is the second most common neurodegenerative disease ... [more ▼]

Neurodegenerative diseases are one of the leading causes of disability and mortality, affecting millions of people worldwide. Parkinson’s disease (PD) is the second most common neurodegenerative disease globally, and while it was first described over 200 years ago, curative treatments remain elusive. One of the main challenges in developing effective therapeutic strategies for PD is the complex molecular pathophysiology of the disease has not been well recapitulated in classically used animal models systems, and studies using post-mortem tissue from patients only represents the end point of disease. Human derived brain organoid models have revolutionized the field of neurological disease modeling, as they are able to recapitulate key cellular and physiological features reminiscent of the human brain. This thesis describes the use of human midbrain organoids (hMO) to model and gain a deeper understanding of genetic forms of PD. In the first manuscript, patient-specific hMO harboring a triplication in the SNCA gene (3xSNCA hMO) were able to recapitulate the key neuropathological hallmarks of PD. We observed the progressive loss and dysfunction of midbrain dopaminergic neurons in 3xSNCA hMO, and the accumulation of pathological α-synuclein including elevated levels of pS129 α-synuclein and the presence of α-synuclein aggregates. We also identified a phenotype indicative of senescence in the 3xSNCA hMO, which represents a mechanism that has recently gained more attention as a driving factor in PD pathogenesis and progression. The second manuscript of this thesis investigated the pathogenic role of LRRK2-G2019S in astrocytes using a combination of post-mortem brain tissue, induced pluripotent stem cell derived astrocytes and hMO. The iPSC derived astrocytes and organoids recapitulated the phenotypes seen in the post-mortem tissue, emphasizing the validity of these models in reflecting the in vivo situation. Interestingly, single-cell RNA sequencing of the hMO revealed that astrocytes from the LRRK2-G2019S organoids showed a senescent-like phenotype. Thus, this thesis highlights the relevance of senescence as a converging mechanism in PD. Finally, this thesis explores the future development of organoid models as they are combined with technologies such as microfluidic devices as in Manuscript III to improve their complexity and reproducibility. Ultimately, this will lead to the development of more representative models that can better recapitulate and model PD as well as other neurodegenerative disorders. [less ▲]

The Standards Effect: The public instrumentalisation of technical standards in EU law

Doctoral thesis (2023)

Altered Images: A Comparative Study of Medical Portraits by Henry Tonks and Raphaël Freida in the Great War

Doctoral thesis (2023)

Estimating terrestrial water storage variations from GNSS vertical displacements in the Island of Haiti

Doctoral thesis (2023)

In the field of hydro-geodesy, ill-posed inverse problems are very common. Those problems need to be regularized to find a stabilized solution. Usually, to solve those problems, two regularization methods ... [more ▼]

In the field of hydro-geodesy, ill-posed inverse problems are very common. Those problems need to be regularized to find a stabilized solution. Usually, to solve those problems, two regularization methods are often used, Tikhonov’s regularization and Truncated Singular Value Decomposition (TSVD), with some common regularization parameter choice methods such as L-curve or General Cross Validation (GCV). This study aims to test the capacity of the Least Squares Collocation (LSC) method to estimate the terrestrial water storage variations as an original approach. First, for the forward model, we calculated the hydrological crustal loading deformation in the island of Haiti by convolving Farrell (1972) Green's function with the surface mass loading from the Global Land Data Assimilation (GLDAS). After, a dense synthetic Global Navigation Satellite System (GNSS) network is used with the LSC method to estimate the Terrestrial Water Storage (TWS) variations for the inverse problem. LSC is a natural way to stabilize an ill-posed inverse problem. Unlike Tikhonov’s or TSVD regularization method, LSC allows us to stabilize the inverse problem by including more physical information. The latter is introduced through a covariance function characterizing the observations, the parameters, and the functional link between them. One of the advantages of the LSC method is that it does not require any regularization parameter. First, we showed that, for the island of Haiti, the near field can extend until 24° around a GNSS station. Secondly, we proved that the hydrology-induced vertical deformation is part of the GNSS vertical displacement over the island. Finally, we demonstrated that the LSC may be used as a method to estimate TWS variations in dense GNSS network area. [less ▲]

Quantifying the abuse potentiality in the investor treaty protection regime (ICSID Convention): the investment fund case study

Doctoral thesis (2023)

Applications of Boolean modelling to study and stratify dynamics of a complex disease

Doctoral thesis (2023)

Interpretation of omics data is needed to form meaningful hypotheses about disease mechanisms. Pathway databases give an overview of disease-related processes, while mathematical models give qualitative ... [more ▼]

Interpretation of omics data is needed to form meaningful hypotheses about disease mechanisms. Pathway databases give an overview of disease-related processes, while mathematical models give qualitative and quantitative insights into their complexity. Similarly to pathway databases, mathematical models are stored and shared on dedicated platforms. Moreover, community-driven initiatives such as disease maps encode disease-specific mechanisms in both computable and diagrammatic form using dedicated tools for diagram biocuration and visualisation. To investigate the dynamic properties of complex disease mechanisms, computationally readable content can be used as a scaffold for building dynamic models in an automated fashion. The dynamic properties of a disease are extremely complex. Therefore, more research is required to better understand the complexity of molecular mechanisms, which may advance personalized medicine in the future. In this study, Parkinson’s disease (PD) is analyzed as an example of a complex disorder. PD is associated with complex genetic, environmental causes and comorbidities that need to be analysed in a systematic way to better understand the progression of different disease subtypes. Studying PD as a multifactorial disease requires deconvoluting the multiple and overlapping changes to identify the driving neurodegenerative mechanisms. Integrated systems analysis and modelling can enable us to study different aspects of a disease such as progression, diagnosis, and response to therapeutics. Therefore, more research is required to better understand the complexity of molecular mechanisms, which may advance personalized medicine in the future. Modelling such complex processes depends on the scope and it may vary depending on the nature of the process (e.g. signalling vs metabolic). Experimental design and the resulting data also influence model structure and analysis. Boolean modelling is proposed to analyse the complexity of PD mechanisms. Boolean models (BMs) are qualitative rather than quantitative and do not require detailed kinetic information such as Petri nets or Ordinary Differential equations (ODEs). Boolean modelling represents a logical formalism where available variables have binary values of one (ON) or zero (OFF), making it a plausible approach in cases where quantitative details and kinetic parameters 9 are not available. Boolean modelling is well validated in clinical and translational medicine research. In this project, the PD map was translated into BMs in an automated fashion using different methods. Therefore, the complexity of disease pathways can be analysed by simulating the effect of genomic burden on omics data. In order to make sure that BMs accurately represent the biological system, validation was performed by simulating models at different scales of complexity. The behaviour of the models was compared with expected behavior based on validated biological knowledge. The TCA cycle was used as an example of a well-studied simple network. Different scales of complex signalling networks were used including the Wnt-PI3k/AKT pathway, and T-cell differentiation models. As a result, matched and mismatched behaviours were identified, allowing the models to be modified to better represent disease mechanisms. The BMs were stratified by integrating omics data from multiple disease cohorts. The miRNA datasets from the Parkinson’s Progression Markers Initiative study (PPMI) were analysed. PPMI provides an important resource for the investigation of potential biomarkers and therapeutic targets for PD. Such stratification allowed studying disease heterogeneity and specific responses to molecular perturbations. The results can support research hypotheses, diagnose a condition, and maximize the benefit of a treatment. Furthermore, the challenges and limitations associated with Boolean modelling in general were discussed, as well as those specific to the current study. Based on the results, there are different ways to improve Boolean modelling applications. Modellers can perform exploratory investigations, gathering the associated information about the model from literature and data resources. The missing details can be inferred by integrating omics data, which identifies missing components and optimises model accuracy. Accurate and computable models improve the efficiency of simulations and the resulting analysis of their controllability. In parallel, the maintenance of model repositories and the sharing of models in easily interoperable formats are also important. [less ▲]

Towards a Computational Model of General Cognitive Control Using Artificial Intelligence, Experimental Psychology and Cognitive Neuroscience

Doctoral thesis (2023)

Cognitive control is essential to human cognitive functioning as it allows us to adapt and respond to a wide range of situations and environments. The possibility to enhance cognitive control in a way ... [more ▼]

Cognitive control is essential to human cognitive functioning as it allows us to adapt and respond to a wide range of situations and environments. The possibility to enhance cognitive control in a way that transfers to real life situations could greatly benefit individuals and society. However, the lack of a formal, quantitative definition of cognitive control has limited progress in developing effective cognitive control training programs. To address this issue, the first part of the thesis focuses on gaining clarity on what cognitive control is and how to measure it. This is accomplished through a large-scale text analysis that integrates cognitive control tasks and related constructs into a cohesive knowledge graph. This knowledge graph provides a more quantitative definition of cognitive control based on previous research, which can be used to guide future research. The second part of the thesis aims at furthering a computational understanding of cognitive control, in particular to study what features of the task (i.e., the environment) and what features of the cognitive system (i.e., the agent) determine cognitive control, its functioning, and generalization. The thesis first presents CogEnv, a virtual cognitive assessment environment where artificial agents (e.g., reinforcement learning agents) can be directly compared to humans in a variety of cognitive tests. It then presents CogPonder, a novel computational method for general cognitive control that is relevant for research on both humans and artificial agents. The proposed framework is a flexible, differentiable end-to-end deep learning model that separates the act of control from the controlled act, and can be trained to perform the same cognitive tests that are used in cognitive psychology to assess humans. Together, the proposed cognitive environment and agent architecture offer unique new opportunities to enable and accelerate the study of human and artificial agents in an interoperable framework. Research on training cognition with complex tasks, such as video games, may benefit from and contribute to the broad view of cognitive control. The final part of the thesis presents a profile of cognitive control and its generalization based on cognitive training studies, in particular how it may be improved by using action video game training. More specifically, we contrasted the brain connectivity profiles of people that are either habitual action video game players or do not play video games at all. We focused in particular on brain networks that have been associated with cognitive control. Our results show that cognitive control emerges from a distributed set of brain networks rather than individual specialized brain networks, supporting the view that action video gaming may have a broad, general impact of cognitive control. These results also have practical value for cognitive scientists studying cognitive control, as they imply that action video game training may offer new ways to test cognitive control theories in a causal way. Taken together, the current work explores a variety of approaches from within cognitive science disciplines to contribute in novel ways to the fascinating and long tradition of research on cognitive control. In the age of ubiquitous computing and large datasets, bridging the gap between behavior, brain, and computation has the potential to fundamentally transform our understanding of the human mind and inspire the development of intelligent artificial agents. [less ▲]

Reading aloud practices: Providing joint accessibility to text within an unfamiliar interface-mediated game activity

Doctoral thesis (2023)

This work examines the practice of reading aloud in the interactional context of adult participants engaging in an interface-mediated collaborative game activity. With a conversation analytic approach ... [more ▼]

This work examines the practice of reading aloud in the interactional context of adult participants engaging in an interface-mediated collaborative game activity. With a conversation analytic approach onto video data of user studies, empirical cases of reading aloud are presented. It is shown how participants multimodally co-organise reading aloud in-interaction for providing accessibility to game text in a game that is unfamiliar to them. With reading aloud, participants meet the interactional challenge of making game text audibly accessible that is not always visually accessible for all participant alike. This practice is not only conducted for another but with another in a truly joint fashion, working as a continuer to accomplish the unfamiliar game. [less ▲]

Soil viral particles as tracers of surface water sources and flow paths

Doctoral thesis (2023)

Albeit recent technological developments (e.g. field deployable instruments operating at high temporal frequencies), experimental hydrology is a discipline that remains measurement limited. From this ... [more ▼]

Albeit recent technological developments (e.g. field deployable instruments operating at high temporal frequencies), experimental hydrology is a discipline that remains measurement limited. From this perspective, trans-disciplinary approaches may create valuable opportunities to enlarge the number of tools available for investigating hydrological processes. Tracing experiments are usually performed in order to investigate the water flow pathways and water sources in underground areas. Since the 19th century, researchers have worked with hydrological tracers to do this. Among them, the fluorescent dyes and the isotopes are the most commonly used to follow the water flow while others like salts or bacteriophages are employed as additional tracers to those mentioned above. Bacteriophages are the least known of all, but it has been studied since the 1960s as hydrological tracers, especially in karstic environments. The purpose is to evaluate the potential for bacteriophages naturally occurring in soils to serve as a new environmental tracer of hydrological processes. We hypothesize that such viral particles can be a promising tool in water tracing experiments since they are safe for ecosystems. In both fields of hydrology and virology, the knowledge regarding the fate of bacteriophages within the pedosphere is still limited. Their study would not only allow proposing potential new candidates to enlarge the hydrological tracers available, but also improving the current knowledge about the bacteriophage communities in soil and their interactions with certain environmental factors. For this purpose, we aim at describing the bacteriophage communities occurring in the soil through shotgun metagenomics analysis. Those viruses are widely spread in the pedosphere, and we assume that they have specific signatures according to the type of soil. Then, bacteriophage populations will be investigated in the soil water to analyse the dis/similarities between the two communities as well as their dynamics in the function of the precipitation events. This way, with a relatively high abundance of soil and soil water and a capacity of being mobilised, good bacteriophage candidates could be selected as hydrological tracers. [less ▲]

Robust estimation in exponential families: from theory to practice

Doctoral thesis (2023)

REMOTE PLASMA CHEMICAL VAPOUR DEPOSITION FOR GAS DIFFUSION LAYER AND PROTON EXCHANGE MEMBRANE SYNTHESIS FOR FUEL CELLS

Doctoral thesis (2023)

Climate change due to the increase in GHG emissions and energy crisis due to scarcity of fossil fuel availability are an ever growing issue for the planet and countries. The decarbonization and the ... [more ▼]

Climate change due to the increase in GHG emissions and energy crisis due to scarcity of fossil fuel availability are an ever growing issue for the planet and countries. The decarbonization and the sustainability of the energy sector is one of the top priority to achieve a resilient system. Hydrogen has been considered for decades to be used as an alternative for fossil fuel and now is the time of development for an hydrogen based economy. Fuel cells are devices that convert the hydrogen chemical energy into electrical energy and is one the main component considered for the hydrogen economy. However, much is yet to be achieved to make their manufacturing as cheap and as efficient as possible. Chemical vapour deposition (CVD) is a technique used to synthesize solid materials from gaseous precursors which has the advantages, over wet chemistry, to reduce wastes of production, to be cheap, to make pure solid materials and to be easily scalable. In this thesis we investigated the possibility to use CVD to produce two major components of fuel cells, namely the gas diffusion layer and the proton exchange membrane. The results were highly promising regarding the elaboration of gas diffusion layers and a CVD prototype was assembled to make the highly complex copolymerization of proton exchange membrane a reality with promising initial results. [less ▲]

Analyzing the Unanalyzable: an Application to Android Apps

Doctoral thesis (2023)

In general, software is unreliable. Its behavior can deviate from users’ expectations because of bugs, vulnerabilities, or even malicious code. Manually vetting software is a challenging, tedious, and ... [more ▼]

In general, software is unreliable. Its behavior can deviate from users’ expectations because of bugs, vulnerabilities, or even malicious code. Manually vetting software is a challenging, tedious, and highly-costly task that does not scale. To alleviate excessive costs and analysts’ burdens, automated static analysis techniques have been proposed by both the research and practitioner communities making static analysis a central topic in software engineering. In the meantime, mobile apps have considerably grown in importance. Today, most humans carry software in their pockets, with the Android operating system leading the market. Millions of apps have been proposed to the public so far, targeting a wide range of activities such as games, health, banking, GPS, etc. Hence, Android apps collect and manipulate a considerable amount of sensitive information, which puts users’ security and privacy at risk. Consequently, it is paramount to ensure that apps distributed through public channels (e.g., the Google Play) are free from malicious code. Hence, the research and practitioner communities have put much effort into devising new automated techniques to vet Android apps against malicious activities over the last decade. Analyzing Android apps is, however, challenging. On the one hand, the Android framework proposes constructs that can be used to evade dynamic analysis by triggering the malicious code only under certain circumstances, e.g., if the device is not an emulator and is currently connected to power. Hence, dynamic analyses can -easily- be fooled by malicious developers by making some code fragments difficult to reach. On the other hand, static analyses are challenged by Android-specific constructs that limit the coverage of off-the-shell static analyzers. The research community has already addressed some of these constructs, including inter-component communication or lifecycle methods. However, other constructs, such as implicit calls (i.e., when the Android framework asynchronously triggers a method in the app code), make some app code fragments unreachable to the static analyzers, while these fragments are executed when the app is run. Altogether, many apps’ code parts are unanalyzable: they are either not reachable by dynamic analyses or not covered by static analyzers. In this manuscript, we describe our contributions to the research effort from two angles: ① statically detecting malicious code that is difficult to access to dynamic analyzers because they are triggered under specific circumstances; and ② statically analyzing code not accessible to existing static analyzers to improve the comprehensiveness of app analyses. More precisely, in Part I, we first present a replication study of a state-of-the-art static logic bomb detector to better show its limitations. We then introduce a novel hybrid approach for detecting suspicious hidden sensitive operations towards triaging logic bombs. We finally detail the construction of a dataset of Android apps automatically infected with logic bombs. In Part II, we present our work to improve the comprehensiveness of Android apps’ static analysis. More specifically, we first show how we contributed to account for atypical inter-component communication in Android apps. Then, we present a novel approach to unify both the bytecode and native in Android apps to account for the multi-language trend in app development. Finally, we present our work to resolve conditional implicit calls in Android apps to improve static and dynamic analyzers. [less ▲]

Signal Processing Contributions to Contactless Monitoring of Vital Signs Using Radars

Doctoral thesis (2023)

Vital signs are a group of biological indicators that show the status of the body’s life-sustaining functions. They provide an objective measurement of the essential physiological functions of a living ... [more ▼]

Vital signs are a group of biological indicators that show the status of the body’s life-sustaining functions. They provide an objective measurement of the essential physiological functions of a living organism, and their assessment is the critical first step for any clinical evaluation. Monitoring vital sign information provides valuable insight into the patient's condition, including how they are responding to medical treatment and, more importantly, whether the patient is deteriorating. However, conventional contact-based devices are inappropriate for long-term continuous monitoring. Besides mobility restrictions and stress, they can cause discomfort, and epidermal damage, and even lead to pressure necrosis. On the other hand, the contactless monitoring of vital signs using radar devices has several advantages. Radar signals can penetrate through different materials and are not affected by skin pigmentation or external light conditions. Additionally, these devices preserve privacy, can be low-cost, and transmit no more power than a mobile phone. Despite recent advances, accurate contactless vital sign monitoring is still challenging in practical scenarios. The challenge stems from the fact that when we breathe, or when the heart beats, the tiny induced motion of the chest wall surface can be smaller than one millimeter. This means that the vital sign information can be easily lost in the background noise, or even masked by additional body movements from the monitored subject. This thesis aims to propose innovative signal processing solutions to enable the contactless monitoring of vital signs in practical scenarios. Its main contributions are threefold: a new algorithm for recovering the chest wall movements from radar signals; a novel random body movement and interference mitigation technique; and a simple, yet robust and accurate, adaptive estimation framework. These contributions were tested under different operational conditions and scenarios, spanning ideal simulation settings, real data collected while imitating common working conditions in an office environment, and a complete validation with premature babies in a critical care environment. The proposed algorithms were able to precisely recover the chest wall motion, effectively reducing the interfering effects of random body movements, and allowing clear identification of different breathing patterns. This capability is the first step toward frequency estimation and early non-invasive diagnosis of cardiorespiratory problems. In addition, most of the time, the adaptive estimation framework provided breathing and heart rate estimates within the predefined error intervals, being capable of tracking the reference values in different scenarios. Our findings shed light on the strengths and limitations of this technology and lay the foundation for future studies toward a complete contactless solution for vital signs monitoring. [less ▲]

Quantification of Influencing Factors of an Energy-Efficient Longitudinal Control of Battery Electric Vehicles

Doctoral thesis (2023)

Global warming forces the automotive industry to reduce real driving emissions and thus, its CO2 footprint. Besides maximizing the individual efficiency of powertrain components, there is also energy ... [more ▼]

Global warming forces the automotive industry to reduce real driving emissions and thus, its CO2 footprint. Besides maximizing the individual efficiency of powertrain components, there is also energy-saving potential in the choice of the driving strategy. Thus, model predictive control based advanced driver assistance systems to reduce the energy consumption during driving gains a significant interest in the literature. However, this results in a complex control system with many parameter dependencies that could possibly affect the energy efficiency of the vehicle. Most of these parameters are subject to uncertainties. Thus, the important question remains how these parameter uncertainties affect the energy efficiency of the system and how a driver assistance system should be designed to be robust against these uncertainties. To answer this question this thesis applies variance-based sensitivity analyses to design an appropriate driver assistance system and to quantify the influences of the uncertain system and controller parameters. First, a detailed vehicle and powertrain model of a battery electric vehicle is evolved and verified on component test benches. The parameter uncertainties and their sensitivities were investigated on typical urban and interurban commuter routes using quantitative variance-based sensitivity analysis methods. Based on these findings an economic nonlinear model predictive control eco-cruise control is derived which takes the identified parameter dependencies into account. The developed economic nonlinear model predictive control system is evaluated on artificial drive cycles and compared to a linear model predictive control approach as often outlined in the literature. Afterwards, the closed loop control system, consisting of the developed economic nonlinear model predictive control and the detailed vehicle model, is analyzed on typical urban and interurban commuter routes using variance-based sensitivity analysis. The findings and parameter dependencies are outlined and discussed. It has been shown, that vehicle parameters as well as controller parameters impact the energy consumption and the driving time of the vehicle. It has been outlined that if the as influential identified parameters are optimized, an average energy-saving potential on the investigated routes of 10.5% exists by only increasing the driving time of 0.7%. [less ▲]

ON THE RELATION BETWEEN STOCHASTIC THERMODYNAMICS AND LINEAR IRREVERSIBLE THERMODYNAMICS

Doctoral thesis (2022)

Cheminformatics and Computational Approaches for Identifying and Managing Unknown Chemicals in the Environment

Doctoral thesis (2022)

In most societies, using chemical products has become a part of daily life. Worldwide, over 350,000 chemicals have been registered for use in e.g., daily household consumption, industrial processes ... [more ▼]

In most societies, using chemical products has become a part of daily life. Worldwide, over 350,000 chemicals have been registered for use in e.g., daily household consumption, industrial processes, agriculture, etc. However, despite the benefits chemicals may bring to society, their usage, production, and disposal, which leads to their eventual release into the environment has multiple implications. Anthropogenic chemicals have been detected in myriad ecosystems all over the planet, as well as in the tissues of wildlife and humans. The potential consequences of such chemical pollution are not fully understood, but links to the onset of human disease and threats to biodiversity have been attributed to the presence of chemicals in our environment. Mitigating the potential negative effects of chemicals typically involves regulatory steps and multiple stakeholders. One key aspect thereof is environmental monitoring, which consists of environmental sampling, measurement, data analysis, and reporting. In recent years, advancements in Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS), open chemical databases, and software have enabled researchers to identify known (e.g., pesticides) as well as unknown environmental chemicals, commonly referred to as suspect or non-target compounds. However, identifying unknown chemicals, particularly non-targets, remains extremely challenging because of the lack of a priori knowledge on the analytes - all that is available are their mass spectrometry signals. In fact, the number of unknown features in a typical mass spectrum of an environmental sample is in the range of thousands to tens of thousands, and therefore requires feature prioritisation before identification within a suitable workflow. In this dissertation work, collaborations with two regulatory authorities responsible for environmental monitoring sought to identify relevant unknown compounds in the environment, specifically by developing computational workflows for unknown identification in LC-HRMS data. The first collaboration culminated in Publication A, which involved a joint project with the Zürcher Amt für Wasser, Energie und Luft. Environmental samples taken from wastewater treatment plant sites in Switzerland were retrospectively analysed using a pre-screening workflow that prioritised features suitable for non-target identification. For this purpose, a multi-step Quality Control algorithm that checks the quality of mass spectral data in terms of peak intensities, alignment, and signal-to-noise ratio was developed and used within pre-screening. This algorithm was incorporated into the R package Shinyscreen. Features that were prioritised by pre-screening then underwent identification using the in silico fragmentation tool MetFrag. To obtain these identifications, MetFrag was coupled to various open chemical information resources such as spectral databases like MassBank Europe and MassBank of North America, as well as suspect lists from the NORMAN Suspect List Exchange and the CompTox Chemicals Dashboard database. One confirmed and twenty-one tentative compound identifications were achieved and reported according to an established confidence level scheme. Comprehensive data interpretation and detailed communication of MetFrag’s results was performed as a means of formulating evidence-based recommendations that may inform future environmental monitoring campaigns. Building on the pre-screening and identification workflow developed in Publication A, Publication B resulted from a collaboration with the Luxembourgish Administration de la gestion de l’eau that sought to identify, and where possible quantify unknown chemicals in Luxembourgish surface waters. More specifically, surface water samples collected as part of a two-year national monitoring campaign were measured using LC-HRMS and screened for pharmaceutical parent compounds and their transformation products. Compared to pharmaceutical compound information, which is publicly available from local authorities (and was used in the suspect list), information on transformation products is relatively scarce. Therefore, new approaches were developed in this work to mine data from the PubChem database as well as from the literature in order to formulate a suspect list containing pharmaceutical transformation products, in addition to their parent compounds. Overall, 94 pharmaceuticals and 14 transformation products were identified, of which 88 and 2 were confirmed identifications respectively. The spatio-temporal occurrence and distribution of these compounds throughout the Luxembourgish environment were analysed using advanced data visualisations that highlighted patterns in certain regions and time periods of high incidence. These findings may support future chemicals management measures, particularly in environmental monitoring. Another challenging aspect of managing chemicals is that they mostly exist as complex mixtures within the environment as well as chemical products. Substances of Unknown or Variable composition, Complex reaction products or Biological materials (UVCBs) make up 20-40% of international chemical registries and include chlorinated paraffins, polymer mixtures, petroleum fractions, and essential oils. However, little is known about their chemical identities and/or compositions, which poses formidable obstacles to assessing their environmental fate and toxicity, let alone identification in the environment. Publication C addresses the challenges of UVCBs by taking an interdisciplinary approach in reviewing the literature that incorporates considerations of their chemical representations, toxicity, environmental fate, exposure, and regulatory approaches. Improved substance registration requirements, grouping techniques to simplify assessment, and the use of Mixture InChI to represent UVCBs in a findable, accessible, interoperable, and reusable (FAIR) way in databases are amongst the key recommendations of this work. A specific type of UVCB, mixtures of homologous compounds, are commonly detected in environmental samples, including many High Production Volume (HPV) compounds such as surfactants. Compounds forming homologous series are related by a common core fragment and repeating chemical subunit, and can be represented using general formulae (e.g., CnF2n+1COOH) and/or Markush structures. However, a significant identification bottleneck is the inability to match their characteristic analytical signals in LC-HRMS data with chemicals in databases; while comb-like elution patterns and constant differences in mass-to-charge ratio indicate the presence of homologous series in samples, most chemical databases do not contain annotated homologous series. To address this gap, Publication D introduces a cheminformatics algorithm, OngLai, to detect homologous series within compound datasets. OngLai, openly implemented in Python using the RDKit, detects homologous series based on two inputs: a list of compounds and the chemical structure of a repeating unit. OngLai was applied to three open datasets from environmental chemistry, exposomics, and natural products, in which thousands of homologous series with a CH2 repeating unit were detected. Classification of homologous series in compound datasets is expected to advance their analytical detection in samples. Overall, the work in this dissertation contributed to the advancement of identifying and managing unknown chemicals in the environment using cheminformatics and computational approaches. All work conducted followed Open Science and FAIR data principles: all code, datasets, analyses, and results generated, including the final peer-reviewed publications, are openly available to the public. These efforts are intended to spur further developments in unknown chemical identification and management towards protecting the environment and human health. [less ▲]

Gene Prioritization in the Epilepsies

Doctoral thesis (2022)

Essays on Ethics, Religion and Finance

Doctoral thesis (2022)

Talent management in a context: four empirical essays

Doctoral thesis (2022)

Recent research has determined that talent management is a highly context-sensitive phenomenon. Indeed, the way talent is defined and managed varies from one context to another. Although talent management ... [more ▼]

Recent research has determined that talent management is a highly context-sensitive phenomenon. Indeed, the way talent is defined and managed varies from one context to another. Although talent management has been studied for the last two decades, the majority of scientific works still focus on the context of large multinational corporations with a prevalence of managerial views. Therefore, this thesis aims to contribute to the literature by challenging the dominant understandings of talent management through examining the phenomenon in the contexts that are less explored. To that end, four empirical studies were conducted constituting this thesis. The first study explores how talent is defined and managed in the not-for-profit sector. Based on the interviews with 34 leaders of 34 mission-driven organizations, it offers a unique definition of a talent and an understanding of how TM is implemented in this sector. The second study analytically contextualizes talent management in micro-, small- and medium-sized enterprises. Based on 31 interviews with TM leaders of 27 aerospace companies, this research proposes three types of TM in this context, namely “strategic”, “entrepreneurial” and “ad hoc”. The third study, in the context of the high technology industry, explores understanding of talent management not only from the perspective of managers but also that of talent. It is based on the discussions with 20 managers and 20 talents from the aerospace industry and identifies three views on TM: talents’, managers’ and shared. Finally, the fourth study explores gender differences in quitting intentions of talent in the knowledge-based field. Drawing on the survey responses from 119 talented individuals, it shows that gender moderates relationships between talent intention to quit and its main antecedents. This thesis provides an important theoretical contribution to the talent management literature and offers useful practical implications for organizational leaders, managers, talented individuals and policy-makers. [less ▲]

INVESTIGATION OF SURFACE SPUTTERING AND IONIZATION PROCESSES UNDER NON-REACTIVE LIGHT ION IRRADIATION: TOWARDS 4D SIMS IMAGING

Doctoral thesis (2022)

The progressive trend to miniaturize samples presents a challenge to materials characterization techniques in terms of both lateral resolution and chemical sensitivity. The latest generation of focused ... [more ▼]

The progressive trend to miniaturize samples presents a challenge to materials characterization techniques in terms of both lateral resolution and chemical sensitivity. The latest generation of focused ion beam (FIB) platforms has allowed to advance in a variety of different fields, including nanotechnology, geology, soil, and life sciences. State-of-the-art ultra-high resolution electron microscopy (EM) devices coupled with secondary ion mass spectrometry (SIMS) systems have enabled to perform in-situ morphological and chemical imaging of micro- and even nanosized objects to better understand materials by studying their properties correlatively. However, SIMS images are prone to artefacts induced by the sample topography as the sputtering yield changes with respect to the primary ion beam incidence angle. Knowing the exact sample topography is crucial to understand SIMS images. Moreover, using non-reactive primary ions (Ne+) produced in a gas field ion source (GFIS) allows to image in SIMS with an excellent lateral resolution of < 20 nm, but it comes with a lower ionization probability compared to reactive sources (e.g., Cs+) and due to small probe sizes only a limited number of atoms are sputtered, resulting in low signal statistics. This thesis focused first on taking advantage of high-resolution in-situ EM-SIMS platforms for applications in specific research fields and to go beyond traditional correlative 2D imaging workflows by developing adapted methodologies for 3D surface reconstruction correlated with SIMS (3D + 1). Applying this method to soil microaggregates and sediments allowed not only to enhance their visualization but also to acquire a deeper understanding of materials’ intrinsic transformation processes, in particular the organic carbon sequestration in soil biogeochemistry. To gain knowledge of the influence of the topography on surface sputtering, using model samples the change of the sputtering yield under light ion bombardment (He+, Ne+) for different ranges of incidence angles of the primary ion beam was studied experimentally. This data was compared to Monte Carlo simulation results and fitted with existing sputtering model functions. We showed thus that these models developed and studied for heavier ions (Ar+, Cs+) are also applicable to light ions (He+, Ne+). Additionally, an algorithm used to correct SIMS images with respect to topographical artefacts resulting from local changes of the sputtering yield was presented. Finally, the contribution of oxygen on positive SI yields was studied for non-reactive primary ions (25 keV Ne+) under high primary ion current densities (up to 10^20 ions/(cm2 ∙ s)). It was shown that in order to maximize and maintain a high ionization probability oxygen needs to be provided continuously to the surface. Secondary ion signal enhancement of up to three orders of magnitude were achieved for silicon, opening the doors for SIMS imaging at both highest spatial resolution and high sensitivity. [less ▲]

ESSAYS IN FINANCIAL ECONOMICS

Doctoral thesis (2022)

This thesis consists of three main chapters, which study different topics of financial economics. The first two chapters are applied theory studies of heterogenous agents in continuous time, where the ... [more ▼]

This thesis consists of three main chapters, which study different topics of financial economics. The first two chapters are applied theory studies of heterogenous agents in continuous time, where the primary focus is endogenised portfolio choice of risky assets by agents in a general equilibrium framework. While chapter 1 studies risky-asset allocation in general, trying to match inequality data, chapter 2 models housing choice and studies the effects of different shocks on the real estate market. These first two chapters represent working papers which are written jointly with Christos Koulovatianos. Chapter 3 is an empirical paper on post-earnings announcement drift and how to better capture this anomaly using a bigger set of publicly available information. The third working paper is written jointly with Anna Ignashkina. Chapter 1 is entitled “Income and wealth inequality in heterogeneous-agent models in con- tinuous time.” In this chapter we analyse wealth inequality and how it is affected by the heterogeneity of the risk-taking pattern. Wealth inequality in the United States reached un- precedented levels over the last thirty years. The puzzle of the heavy tail of wealth distribution remains unresolved. We build a heterogeneous-agent model in continuous time with endogenous portfolio choice to test if risk-taking of the wealthy can explain the thick upper tail of wealth distribution for the US data. We incorporate the recent evidence of Guvenen et al. (2014) of income process’s non-normality in our model. We find that asset holdings play an important role in explaining increased inequality, especially when accompanied by non-normal income process. In both general equilibrium and partial setting we show that the non-normality of the income process contributes significantly to the formation of the convex risk-taking pattern against income. We also find that the rise in volatility of capital markets observed in the last 30 years can explain trends in inequality and interest rates. Chapter 2 is entitled “A Heterogeneous-Agent Model of Household Mortgages in Luxem- bourg: Responses to the Covid-19 Shock.” As it is well-known, the covid-19 pandemic lockdowns 8 did not have an impact on every worker in the same way. More social professions were affected in a more adverse manner by the lockdowns, experiencing severe income losses, while many ser- vices professions could continue working remotely as before, experiencing no income losses. In order to study the impact of these asymmetric idiosyncratic income shocks on household balance sheets in Luxembourg and on house prices, we calibrate a continuous-time heterogeneous-agent model of homeownership to pre- and post-covid income data. We compute the transition dy- namics of the net-worth distribution of households and study alternative scenarios of shocks to the mortgage rates that may stem from overall credit market conditions and central-bank policies. Our general results are that the mortgage market in Luxembourg is resilient. Yet, our model raises alert for some vulnerable households and provides a tool for policy evaluation in the future. Chapter 3 is entitled “Information aggregation and post-earnings announcement drift.” In this chapter we propose a new measure of surprise information that aggregates different signals coming together with earnings reports, complementing the standard earnings-surprise measure for analysis of Post-earnings announcement drift (PEAD). We find that new factors, such as revenue surprises and aggregated non-financial information available in earnings reports, are important determinants of post-earnings returns. Surprisingly, these new factors amplify, rather than mitigate, the PEAD anomaly. In dynamic portfolios, weekly returns to PEAD increase by 72 basis points, if more financial metrics are taken into account, compared to the standard approach. Similarly, with analyses of textual metrics, we demonstrate that changes in the text are associated with a longer drift. [less ▲]

SCALABLE AND PRACTICAL AUTOMATED TESTING OF DEEP LEARNING MODELS AND SYSTEMS

Doctoral thesis (2022)

With the recent advances of Deep Neural Networks (DNNs) in real-world applications, such as Automated Driving Systems (ADS) for self-driving cars, ensuring the reliability and safety of such DNN-Enabled ... [more ▼]

With the recent advances of Deep Neural Networks (DNNs) in real-world applications, such as Automated Driving Systems (ADS) for self-driving cars, ensuring the reliability and safety of such DNN-Enabled Systems (DES) emerges as a fundamental topic in software testing. Automatically generating new and diverse test data that lead to safety violations of DES presents the following challenges: (1) there can be many safety requirements to be considered at the same time, (2) running a high-fidelity simulator is often very computationally intensive, (3) the space of all possible test data that may trigger safety violations is too large to be exhaustively explored, (4) depending upon the accuracy of the DES under test, it may be infeasible to find a scenario causing violations for some requirements, and (5) DNNs are often developed by a third party, who does not provide access to internal information of the DNNs. In this dissertation, in collaboration with IEE sensing, we address the aforementioned challenges by providing scalable and practical automated solutions for testing Deep Learning (DL) models and systems. Specifically, we present the following in the dissertation. 1. We conduct an empirical study to compare offline testing and online testing in the context of Automated Driving Systems (ADS). We also investigate whether simulator-generated data can be used in lieu of real-world data. Furthermore, we investigate whether offline testing results can be used to help reduce the cost of online testing. 2. We propose an approach to generate test data using many-objective search algorithms tailored for test suite generation to generate test data for DNN with many outputs. We also demonstrate a way to learn conditions that cause the DNN to mispredict the outputs. 3. In order to reduce the number of computationally expensive simulations, we propose an automated approach, SAMOTA, to generate data for DNN-enabled automated driving systems, using many- objective search and surrogate-assisted optimisation. 4. The environmental conditions (e.g., weather, lighting) often stay the same during a simulation, which can limit the scope of testing. To address this limitation, we present an automated approach, MORLAT, to dynamically interact with the environment during simulation. MORLAT relies on reinforcement learning and many-objective optimisation. We evaluate our approaches using state-of-the-art deep neural networks and systems. The results show that our approaches perform statistically better than the alternatives [less ▲]

MULTI-OMICS ANALYSIS OF DIFFERENTIATING DOPAMINERGIC NEURONS IDENTIFIES NOVEL FACTORS NECESSARY FOR LINEAGE SPECIFICATION

Doctoral thesis (2022)

Midbrain dopaminergic neurons (mDANs) control voluntary movement, cognition, and reward behavior and are implicated in human diseases such as Parkinson’s disease (PD). Many transcription factors (TFs ... [more ▼]

Midbrain dopaminergic neurons (mDANs) control voluntary movement, cognition, and reward behavior and are implicated in human diseases such as Parkinson’s disease (PD). Many transcription factors (TFs) controlling human mDAN differentiation have been described but much of the regulatory landscape remains undefined. The location and the low number of these cells in the brain have limited the application of epigenomic assays, as they usually require a high number of cells. Thanks to the emergence of induced pluripotent stem cell (iPSC) technology, differentiation protocols for the derivation of mDANs were developed, making access to this neuronal subtype easier, facilitating its study. However, current protocols for the differentiation of human iPSC towards mDANs produce a mixture of developmentally immature and incompletely specified cells together with more physiological cells. Differentiation protocols are based on the developmental knowledge generated from animal studies and the translation of this knowledge to humans appears not to be completely compatible. Therefore, a better understanding of human development is needed, encouraging the use of human-based models. A proper understanding of the epigenetic landscape of human mDAN differentiation will have direct implications for uncovering gene regulatory mechanisms, disease-associated variants (as most of them are in the non-coding regions of the genome), and cell identity. In this study, a human tyrosine hydroxylase (TH) reporter line of iPSC was used for the generation of time series transcriptomic and epigenomic profiles from differentiating mDANs. TH is the rate-limiting enzyme for dopamine production and therefore a specific marker for mDANs. In the reporter line, mCherry was expressed under the control of the TH promoter, which allowed to isolate mDANs from the cultures by FACS. Integration of time-point-specific chromatin accessibility and associated TF binding motifs with paired transcriptome profiles across 50 days of differentiation was performed using an adapted version of the EPIC-DREM pipeline. Time-point-specific gene regulatory interactions were obtained and served to identify putative key TFs controlling mDAN differentiation. Low-input ChIP-seq for histone H3 lysine 27 acetylation (H3K27ac) was performed to identify and prioritize key TFs controlled by super-enhancer regions. LBX1, NHLH1, and NR2F1/2 were found to be necessary for mDAN differentiation. Overexpression of either LBX1 or NHLH1 was also able to increase mDAN numbers. LBX1 was found to regulate cholesterol biosynthesis and translation possibly via mTOR signaling. NHLH1 was found to be necessary for the induction of miR-124, a potent neurogenic microRNA. Interestingly, miR-124 and NHLH1 appear to be part of a positive feedback loop. Thus, the results from this study provide novel insights into the regulatory landscape of human mDAN differentiation. In addition, as the identified candidates from EPIC-DREM did not show selective expression in mDANs, the data produced was further explored for the identification of novel expression selective TFs in these cells. ZFHX4 was selected as a relevant TF for mDANs that was also downregulated in PD patients. It presented a high and specific expression during development and in adult mDANs from human brains. Depletion of ZFHX4 during differentiation affected mDAN neurogenesis. However, CRISPR-mediated overexpression of ZFHX4 during differentiation did not affect mDAN numbers. Transcriptomic analysis revealed a role of ZFHX4 in controlling cell cycle and cell division on mDANs. ZFHX4 seems to be regulating cell cycle control by interaction with E2F TFs and the NuRD complex, as these proteins have also been associated with this function and appeared in the analysis performed. Overall, the present study provides a novel profile of mDANs during differentiation that can be used for many other applications apart from the one presented here, like the identification of disease-associated variants affecting these neurons. Incorporating epigenetic information into the current transcriptomic knowledge increased the understanding of this neuronal subtype and uncovered important pathways involved in the biology of these cells and most probably with implications to disease. [less ▲]

Brain development at single cell resolution in health and disease

Doctoral thesis (2022)

Using RNA sequencing, we can examine distinctions between different cell types and capture a moment in time of the dynamic activities taking place inside a cell. Researchers in fields like developmental ... [more ▼]

Using RNA sequencing, we can examine distinctions between different cell types and capture a moment in time of the dynamic activities taking place inside a cell. Researchers in fields like developmental biology have embraced this technology quickly as it has improved over the past few years, and there are now many single-cell RNA sequencing datasets accessible. A surge in the development of computational analysis techniques has occurred along with the invention of technologies for generating single-cell RNA sequencing data. In my thesis, I examine computational methods and tools for single-cell RNA sequencing data analysis in 3 distinct projects. In the fetal brain project, I tried to decipher the complexity of the human brain and its development, and the link between development and neuropsychiatric diseases at early fetal brain development. I provide a unique resource of fetal brain development across a number of functionally distinct brain regions in a brain region-specific manner at single nuclei resolution. In total, I retrieved 50,937 single nuclei from four individual time points (Early; gestational weeks 18 and 19, and late; gestational weeks 23 and 24) and four distinct brain regions (cortical plate, hippocampus, thalamus, and striatum). In my dissertation, I also tried to investigate the underlying mechanisms of Parkinsons disease (PD), the second-most prevalent neurodegenerative disorder, characterized by the loss of dopaminergic neurons (mDA) in the midbrain. I examined the disease process using single cells of mDA neurons developed from human induced pluripotent stem cells (hiPSCs) expressing the ILE368ASN mutation in the PINK1 gene, at four different maturation time points. Differential expression analysis resulted in a potential core network of PD development which linked known genetic risk factors of PD to mitochondrial and ubiquitination processes. In the final part of my thesis, I perform an analysis of a dataset from brain biopsies from patients with Intracerebral hemorrhage (ICH) stroke. In this project, I tried to investigate the dynamic spectrum of polarization of the immune cells to pro/anti-inflammatory states. I also tried to identify markers that potentially can be used to predict the outcome of the ICH patients. Overall, my thesis discusses a wide range of single-cell RNA sequencing tools and methods, as well as how to make sense of real datasets using already-developed tools. These discoveries may eventually lead to a more thorough understanding of Parkinson’s disease, ICH stroke but also psychiatric diseases and may facilitate the creation of novel treatments. v [less ▲]

Renewable Lignin Nanoparticles as an Alternative Reinforcing Filler for Elastomers

Doctoral thesis (2022)

Essays on the Economics of International Migration

Doctoral thesis (2022)

Les politiques linguistiques familiales dans trois familles transnationales d’origine chinoise au Grand-Duché de Luxembourg : plurilinguisme, idéologies linguistiques et éducatives, identités

Doctoral thesis (2022)

Du fait de la mondialisation galopante, des familles transnationales se déplacent, s’installent et s’intègrent dans un nouvel environnement linguistique et culturel autre que leur pays d’origine. Notre ... [more ▼]

Du fait de la mondialisation galopante, des familles transnationales se déplacent, s’installent et s’intègrent dans un nouvel environnement linguistique et culturel autre que leur pays d’origine. Notre travail de thèse s’intéresse à l’étude des politiques linguistiques au sein de trois familles transnationales d’origine chinoise au Grand-Duché de Luxembourg, où le multilinguisme constitue tant un défi qu’une opportunité pour leur intégration dans la société luxembourgeoise. Entre héritage et intégration, la confrontation interculturelle ne s’effectue pas sans tension. Il s’agit, pour les familles, d’une part, de maintenir leur langue d’origine (le chinois) et, d’autre part, d’apprendre des langues scolaires (le luxembourgeois, le français, l’allemand) et l’anglais dans le système d’éducation luxembourgeois. Notre objectif est d’étudier les idéologies linguistiques et éducatives des parents, le développement du plurilinguisme chez l’enfant et les questions identitaires qui méritent réflexion dans un environnement multilingue et interculturel. Comment les parents conceptualisent-ils le développement du plurilinguisme chez leurs enfants au Luxembourg ? Quelles sont les considérations et les aspirations des parents quant à l’éducation de leurs enfants au sens large en contexte multilingue et interculturel ? Comment et dans quelle mesure la construction et la négociation des idéologies linguistiques des membres des trois familles s’articulent-elles autour du niveau individuel, du niveau familial et du niveau social ? Nous avons opté pour une approche qualitative et ethnolinguistique. L’entretien semi-directif, l’observation participante et l’enregistrement des interactions familiales ont été mobilisés comme outils principaux de recueil des données sur le terrain. L’analyse thématique, l’étude de cas et l’analyse transversale ont constitué notre démarche d’analyse, avec un accent mis sur l’identification et l’appréhension des idéologies linguistiques et éducatives. L’analyse des données nous permet de conclure que le mécanisme de rapports entre l’héritage linguistique, la conformité aux exigences scolaires et la valorisation de l’anglais comme lingua franca s’avère d’autant plus complexe que les familles chinoises ont à faire face à plus d’une langue dans un environnement multilingue comme celui du Luxembourg. Primo, les parents chinois démontrent un engagement ferme vis-à-vis du maintien du chinois standard chez leurs enfants, mais avec des attentes variées quant aux compétences à acquérir. Secundo, face à la multitude de langues en jeu, ils témoignent d’une ambivalence évidente dans leur conception du rôle et de l’ordre de priorité des différentes langues, mais aussi, pour ce qui est de l’aspiration au plurilinguisme et à la mentalité monolingue. Et, tertio, leur appréciation des valeurs des langues et leur construction du rôle de celles-ci se fondent essentiellement sur le pragmatisme et l’affirmation identitaire. Il est mis en exergue également que les idéologies linguistiques et éducatives des parents au niveau individuel s’articulent avec l’environnement social. Ce travail de thèse contribue à faire avancer nos connaissances sur les politiques linguistiques familiales dans les familles transnationales, notamment celles d’origine non occidentale dans un pays occidental marqué par le multilinguisme. [less ▲]

SITE-SELECTIVE ATMOSPHERIC PRESSURE PLASMA-ENHANCED CHEMICAL VAPOUR DEPOSITION PROCESS FOR MICROMETRIC DEPOSITION – SIMULATION AND EXPERIMENTAL STUDY

Doctoral thesis (2022)

Atmospheric Pressure Plasma has been used to enhance and/or initiate the Chemical Vapour Deposition (AP-PECVD) to deposit thin films or functional layer coatings over a large surface area on a large range ... [more ▼]

Atmospheric Pressure Plasma has been used to enhance and/or initiate the Chemical Vapour Deposition (AP-PECVD) to deposit thin films or functional layer coatings over a large surface area on a large range of substrates. Now an ability to localise the AP-PECVD coating on an area of interest and control the deposition’s dimension showed its potential application as a viable technique to perform Additive Manufacturing (AM). Additive Manufacturing (AM) is a bottom-up approach in which 2-D patterning or 3-D structures are built using a layer-by-layer deposition. AM allowed easy design optimization and quickly provided the customized parts on demands, thus making itself a very popular technique in the mainstream manufacturing process. As such, it has a wide application in automotive, optics, electronics, aeronautics, medical and biotechnology fields. However, the existing AM printing techniques have some limitations regarding high-resolution printing deposition in a wide variety of substrates and very often get restricted to the types of precursors that could be printed. Whereas, due to the high energetic/reactive species in non-thermal plasma, the AP-PECVD deposition has been obtained using a wide range of precursors on a versatile surface. Thus, there has been a growing interest in performing an area selective localised AP-PECVD coating, mainly by adapting the design of the PECVD reactor. Hence, this thesis aims to design, optimize and study a one-step mask-free AP-PECVD plasma process that could locally deposit the material of interest with high precision to perform AM. In the thesis, the technical approach undertaken by the home-built prototype “plasma torch” is to decouple the plasma generator annular tube and the precursor injector central capillary. This approach has allowed a way to tune the diameter of the deposited dot by changing the dimension of the precursor injector, which has been demonstrated by the deposition of the micro-dot as small as 400µm in diameter. Further, the flexibility to move the capillary tube without significant changes in the plasma torch's overall geometry has also allowed for selectively injecting the precursor (Methylmethacrylate, MMA) in the spatial plasma post-discharge region. Thanks to this setting, the deposited dot has high retention of monomer's chemistry (functional group) and unprecedented molecular weights (oligomeric chain up to 18 MMA units). Hence, initially, a novel area selective AP-PECVD plasma torch design has been demonstrated, and its performance has been defined to obtain the micro resolution coating. During the research work, gas flow rates have been identified as a crucial parameter in obtaining the localised coating; three kinetic regimes with different coating morphology have been discovered. By performing a thorough computational fluid dynamic (CFD) simulation of the torch phenomena, it has been possible to establish a parallel between the fluid behaviour and the deposition size. The deposition was found to be confined in a zone created by the dynamical behaviour of gas, i.e., re-circulating vortices between the torch and substrate. Hence, later the gas flow rate was used to tune the diameter of the confinement zone, which in return changed the diameter of the deposited dot. The gas flow dynamic impacts the involved species, i.e., reactive plasma species, precursor molecules, and the open-air interaction and distribution on the surface of the substrate. When organosilicon precursors with the presence or absence of vinyl bond and/or ethoxy groups are used, it results in different depositional chemical reactions and depositional patterns. The correlation between the depositional patterns and the mass fraction distribution of involved species has been obtained thanks to the performed CFD simulation done in parallel. Further, the likelihood of deposition mechanisms like "vinyl group opening by free radical" for vinyl containing precursor resulting in silicon oxycarbide-like (SiOxCyH) structural deposition, and the Reactive Oxygen Species (ROS)-induced "fragmentation and adsorption" deposition mechanism resulting in silica SiOx like structural deposition for siloxane containing precursor has been suggested and discussed. The understanding gained from this systematic case study implies the importance of reactive plasma species in the underlying deposition mechanisms; hence, it has been suggested that tuning/tailoring its distribution can alter the chemical nature of deposition and its pattens. Overall, this thesis work provides insight into area selective AP-PECVD coating (plasma printing) and demonstrates that plasma technology is a viable option for additive manufacturing. The findings would be helpful in both designing the AP-PECVD plasma torch and selecting precursors for the desired organic/inorganic deposition. Thanks to the insight gained during the thesis work, the home-designed prototype of the plasma torch has been upgraded to implement in a commercial 3-D printer. [less ▲]

Australian Indigenous Life Writing: Analysing Discourses with Word Embedding Modelling

Doctoral thesis (2022)

The genre of Australian Aboriginal autobiography is a literature of significant socio-political importance, with authors sharing a history different to the one previously asserted by the European settlers ... [more ▼]

The genre of Australian Aboriginal autobiography is a literature of significant socio-political importance, with authors sharing a history different to the one previously asserted by the European settlers which ignored or misrepresented Australia's First People. While there has been a number of studies looking at the works belonging to this genre from various perspectives, Australian Indigenous life writing has never been approached from the digital humanities point of view which, given the constant development of computer technologies and growing availability of digital sources, offers humanities researchers many opportunities for exploring textual collections from various angles. With this research work I contribute to closing the above-mentioned research gap and discuss the results of the interdisciplinary research project within the scope of which I created a bibliography of published Australian Indigenous life writing works, designed and assembled a corpus and created word embedding models of this corpus which I then used to explore the discourses of identity, land, sport, and foodways, as well as gender biases present in the texts in the context of postcolonial literary studies and Australian history. Studying these discourses is crucial for gaining a better understanding of the contemporary Australian society as well as the nation's history. Word embeddings modelling has recently been used in digital humanities as an exploratory technique to complement and guide traditional close reading approaches, which is justified by their potential to identify word use patterns in a collection of texts. In this dissertation, I provide a case study of how word embedding modelling can be used to investigate humanities research questions and reflect on the issues which researchers may face while working with such models, approaching various aspects of the research project from the perspectives of digital source and tool criticism. I demonstrate how word embedding model of the analysed corpus represents discourses through relationships between word vectors that reflect the historical, political, and cultural environment of the authors and some unique experiences and perspectives related to their racial and gender identities. I show how the narrators reconstruct the analysed discourses to achieve the main goals of Australian Indigenous life writing as a genre - reclaiming identity and rewriting history. [less ▲]

New Security Primitives and Better Performance through Parameter Trade-Offs

Doctoral thesis (2022)

Sexual health and emotion regulation: investigating a reciprocal relationship

Doctoral thesis (2022)

Sexual disorders are characterized by difficulties in the ability to respond sexually or to obtain sexual pleasure. Epidemiological data indicate that about 40-45% of adult women and 20-30% of adult men ... [more ▼]

Sexual disorders are characterized by difficulties in the ability to respond sexually or to obtain sexual pleasure. Epidemiological data indicate that about 40-45% of adult women and 20-30% of adult men have at least one manifest sexual disorder during their lifetime. The etiology of sexual disorders is multifactorial, encompassing physiological, affective, interpersonal, and psychological, context-dependent-factors, which may predispose, precipitate, or maintain the sexual dysfunction. Psychological and emotional factors may either contribute to the development of sexual problems or be a consequence thereof. Emotional reactions and thoughts during sexual activity can also affect sexual functionality. With respect to emotions, different patterns for individuals with and without sexual dysfunction have been reported. Similarly, the difficulty or inability to face experiences or process emotions adequately, also termed emotion dysregulation, has been associated with coping strategies detrimental to health and with a variety of mental disorders. Such context suggest that emotion regulation may be important for sexual health and most likely also in the treatment of sexual problems. By deepen our knowledge of the role of emotion regulation for sexual health it would be possible to have an impact in both sexuality research and in a clinical level by providing evidence to base future of therapy programmes for people with sexual concerns. The overall objectives of the SHER project are: a) to determine the associations between emotion regulation and sexual health and; b) to develop and evaluate an internet-based intervention protocol designed to improve emotion regulation skills for people with sexual disorders. The project employed different methods, namely a literature scoping review, a cross-sectional online survey and a randomized controlled trial intervention with a three months follow-up. The dissertation presents three studies (four manuscripts) from the SHER project. The first study aimed at reviewing the existing literature on the effects of emotion regulation on sexual function and satisfaction. After searching in different databases and applying the inclusion and exclusion criteria, twenty-seven articles were analyzed. As a conclusion, was identified that emotion regulation was associated with poorer sexual health outcomes, difficulties in the sexual response cycle and overall lower sexual satisfaction. In addition, the few experimental studies (either in laboratory settings or in intervention trials) found positive effects of promoting emotion regulation change on sexual function and satisfaction. The aim of the second study was to determine whether distinct profiles in terms of preferred emotion regulation strategies are differentially associated with sexual and mental health. The sample consisted of 5436 participants aged between 18 and 77 years (M= 25.80, SD= 6.96). A gender stratified cluster analysis was performed to classify individuals according to their scores on scales measuring emotion regulation strategies (cognitive reappraisal and emotional suppression), sexual health (assessed using gender-specific self-report questionnaires), anxiety and depression symptoms. For both men and women, the results showed a four-cluster solution: low reappraisal and high suppression, n=1243; high reappraisal and low suppression, n=1695; high reappraisal and high suppression, n=1425; low reappraisal and low suppression, n=1073. Better sexual and mental health scores were found for participants with high cognitive reappraisal and low expressive suppression scores. High expressive suppression was associated with higher anxiety and depression scores and worse sexual health. We concluded by suggesting that provision of care for sexological patients should include an assessment of their emotion regulation abilities and emotion regulation training interventions fostering reappraisal should be offered when appropriate. The third study, aimed at developing and testing an internet-based emotion regulation training for sexual health (TREpS). First, an intervention protocol was established and published indicating the objectives, procedures and expected outcomes of the intervention. Later, a second manuscript reported the findings of the intervention. The intervention was composed of eight modules, delivered weekly. The module contents encompassed psychoeducation on sexual health and emotion regulation, a set of different strategies to deal with emotions (relaxation techniques, cognitive flexibility, non-judgmental awareness, self-acceptance and compassion, emotion analysis) and sexual emotional exposures. Participants were assessed in three different time points: baseline, end of the intervention and at three months after the intervention ending. Initially 60 participants met the inclusion criteria and were allocated in two groups. Nonetheless, differently than what was expected, the intervention yielded a very large dropout rate (83.4 %). In this circumstance, some changes to the study protocol have been performed, e.g., the reduction of the follow-up interval period and the complete assessment of the initially waitlist-control group in the three different time points. Since the adherence rate was very low the gathered data was insufficient to investigate treatment effects. Among the participants who completed the intervention larger and moderate effect sizes were observed between assessments for emotion regulation, depression, lubrication, orgasm and thoughts of sexual failure and abuse during sexual activity. [less ▲]

Post-quantum Remote Device Authentication and Data Analysis Protocols for IoT

Doctoral thesis (2022)

Advances in networking and hardware technology have made the design and deployment of Internet of Things (IoTs) and decentralised applications a trend. For example, the fog computing concept and its ... [more ▼]

Advances in networking and hardware technology have made the design and deployment of Internet of Things (IoTs) and decentralised applications a trend. For example, the fog computing concept and its associated edge computing technologies are pushing computations to the edge so that data aggregation can be avoided to some extent. This naturally brings benefits such as efficiency and privacy, but on the other hand, it forces data analysis tasks to be carried out in a distributed manner. Hence, we will focus on establishing a secure channel between an edge device and a server and performing data analysis with privacy protection. In this thesis, we first studied the state-of-art Key Exchange (KE) and Authenticated Key Exchange (AKE) protocols in the literature, including security properties, security models for various security properties, existing KE and AKE schemes of pre-quantum and post-quantum era with varied authentication factors. As a result of the above research, a novel IoT-oriented security model for AKE protocol is introduced. In addition to the general security properties satisfaction, we also define several detailed security games for the desired security properties of perfect forward secrecy, key compromise impersonation resilience and server compromise impersonation resilience. Furthermore, by studying the current multi-factor AKE protocols in the literature, we are inspired by the usage of bigdata in the IoT setting for the authentication and session key establishment propose. With this in mind, we proposed a bigdata-facilitated two-party AKE protocol for IoT systems that uses the bigdata as one of the authentication factors. Moreover, we also proposed a modular framework for constructing IoT-server AKE in post-quantum setting. It is flexible that it can integrate with a public key encryption and a KE component. In addition to this, we notice that as IoT generates and collects more and more data, the need to perform data analysis increases at the same time. In order to avoid the performance limitations of IoT devices, ease the burden of the server, and also guarantee the quality of service of IoT applications, we presented a privacy-preserving decentralised Singular Value Decomposition (SVD) for fog architecture, which could be considered as a multi-IoT and multi-server setting and provides protection for the bigdata set. Next, we would like to further integrate the SVD results from different subsets using a federated learning mechanism. Privacy protection is always a fundamental requirement we need to consider; with this in mind, we proposed a privacy-preserving federated SVD scheme with secure aggregation. The results from the different edge devices are securely aggregated with the server and returned to the individual devices for further applications. [less ▲]

Evolutionary Algorithm-based Adversarial Attacks Against Image Classification Convolutional Neural Networks

Doctoral thesis (2022)

Economic Inequality and Social Mobility: Challenges of the Past and the Present

Doctoral thesis (2022)

RESOURCE MANAGEMENT TECHNIQUES FOR FLEXIBLE BROADBAND SATELLITE COMMUNICATION SYSTEMS

Doctoral thesis (2022)

The application of Satellite Communications (SatCom) has recently evolved from providing simple Direct-To-Home television (DTHTV) to enable a range of broadband internet services. Typically, it offers ... [more ▼]

The application of Satellite Communications (SatCom) has recently evolved from providing simple Direct-To-Home television (DTHTV) to enable a range of broadband internet services. Typically, it offers services to the broadcast industry, the aircraft industry, the maritime sector, government agencies, and end-users. Furthermore, SatCom has a significant role in the era of 5G and beyond in terms of integrating satellite networks with terrestrial networks, offering backhaul services, and providing coverage for the Internet of Things (IoT) applications. Moreover, thanks to the satellite's wide coverage area, it can provide services to remote areas where terrestrial networks are inaccessible or expensive to connect. Due to the wide range of satellite applications outlined above, the demand for satellite service from user terminals is rapidly increasing. Conventionally, satellites use multi-beam technology with uniform resource allocation to provide service to users/beams. In this case, the satellite's resources, such as power and bandwidth, are evenly distributed among the beams. However, this resource allocation method is inefficient since it does not consider the heterogeneous demands of each beam, which may result in a beam with a low demand receiving too many resources while a beam with a high demand receiving few resources. Consequently, we may not satisfy some beam demands. Additionally, satellite resources are limited due to spectrum regulations and onboard batteries constraint, which require proper utilization. Therefore, the next generation of satellites must address the above main challenges of conventional satellites. For this, in this thesis, novel advanced resource management techniques are proposed to manage satellite resources efficiently while accommodating heterogeneous beam demands. In the above context, the second and third chapters of the thesis explore on-demand resource allocation methods with no precoding technique. These methods aim to closely match the beam traffic demand by using the minimum transmit power and utilized bandwidth while having tolerable interference among the beams. However, an advanced interference mitigation technique is required in a high interference scenario. Thus, in the fourth chapter of the thesis, we propose a combination of resource allocation and interference management strategies to mitigate interference and meet high-demand requirements with less power and bandwidth consumption. In this context, the performance of the resource management method for systems with full precoding, that is, all beams are precoded; without precoding, that is, no precoding is applied to any beams; and with partial precoding, that is, some beams are precoded, is investigated and compared. Thanks to emerging technologies, the next generation of satellite communication systems will deploy onboard digital payloads; thus, advanced resource management techniques can be implemented. In this case, the digital payload can be configured to change the bandwidth, carrier frequency, and transmit power of the system in response to heterogeneous traffic demands. Typically, onboard digital payloads consist of payload processors, each operating with specific power and bandwidth to process each beam signal. There are, however, only a limited number of processors, thus requiring proper management. Furthermore, the processors consume more energy to process the signals, resulting in high power consumption. Therefore, payload management will be crucial for future satellite generation. In this context, the fifth chapter of the thesis proposes a demand-aware onboard payload processor management method, which switches on the processors according to the beam demand. In this case, for low demand, fewer processors are in-use, while more processors become necessary as demand increases. Demand-aware resource allocation techniques may require optimization of large variables. Consequently, this may increase the computational time complexity of the system. Thus, the sixth chapter of the thesis explores the methods of combining demand-aware resource allocation and deep learning (DL) to reduce the computational complexity of the system. In this case, a demand-aware algorithm enables bandwidth and power allocation, while DL can speed up computation. Finally, the last chapter provides the main conclusions of the thesis, as well as the future research directions. [less ▲]

CIRCULAR ARCHITECTURE: MODELS AND STRATEGIES TO REUSE AND RECYCLE BUILDINGS

Doctoral thesis (2022)

How we design, construct and live in our houses as well as go to work can mitigate carbon dioxide (CO2) emissions and global climate change. Furthermore, the complex world we live in is in an ongoing ... [more ▼]

How we design, construct and live in our houses as well as go to work can mitigate carbon dioxide (CO2) emissions and global climate change. Furthermore, the complex world we live in is in an ongoing transformation process. The housing shortage problem is increasing as the world population and cities are increasingly growing. Thereby, we must think of all the other issues that come along with population growth, such as increased demand for built space, mobility, expansion of cities into green areas, use of resources, and materials scarcity. Various projects from history have used alternatives to solve the problem of social housing, such as increasing density in cities through housing complexes, fast and low-cost constructions with prefabricated methods and materials, and modularisation systems. However, the current architecture is not designed to meet users’ future needs and reduce the environmental impact. A proposal to change this situation would be to go back to the beginning of architecture’s conception and to design it differently. In addition, nowadays, there is an increasing focus on moving towards sustainable and circular living spaces based on shared, adaptable and modular built environments to improve residents’ quality of life. For this reason, the main objective of this thesis is to study the potential of architecture that can reconfigure spatially and temporally, and produce alternative generic models to reuse and recycle architectural elements and spaces for functional flexibility through time. To approach the discussion, a documentary research methodology was applied to study the modular, prefabricated and ecological architectural typologies to address recyclability in buildings. The Atlas with case studies and architectural design strategies emerged from the analyses of projects from Durant to the 21st century. Furthermore, this thesis is a part of the research project Eco-Construction for Sustainable Development (ECON4SD), which is co-funded by the EU in partnership with the University of Luxembourg, and it presents three new generic building typologies. They are named according to their strong characteristics: Prototype 1 - Slab typology, a building designed as a concrete shelf structure in which timber housing units can be plugged in and out; Prototype 2 - Tower typology, a tower building with a flexible floor plan combining working and residential facilities with adjacent multi-purpose facilities; and Prototype 3 - Block typology, a structure characterised by the entire disassembly. The three new typologies combine modularity, prefabrication, flexibility and disassembly strategies to address the increasing demand for multi-use, reusable and resourceefficient housing units. The prototypes continually adapt to the occupants’ needs as the infrastructure incorporates repetition, exposed structure, central core, terrace, open floors, unfinished spaces, prefabrication, combined activities, and have reduced and different housing unit sizes, in which parts can be disassembled. They also densify the region that they are being implemented in. Moreover, the new circular typologies can offer more generous public and shared space for the occupants within the same building size as an ordinary building. The alternative design allows the reconversion of existing buildings or the reconstruction of the same buildings in other places reducing waste and increases its useful lifespan. Once the building is adapted and reused as much as possible, and the life cycle comes to an end, it can be disassembled, and the materials can be sorted for reusable or recyclable resources. The results demonstrate that circular architecture is feasible, realistic, adapts through time, increases material use, avoids unnecessary demolition, reduces construction waste and CO2 emissions and extends the useful life of the buildings. [less ▲]

Data-driven patient-specific breast modeling: a simple, automatized, and robust computational pipeline

Doctoral thesis (2022)

Background: Breast-conserving surgery is the most acceptable option for breast cancer removal from an invasive and psychological point of view. During the surgical procedure, the imaging acquisition using ... [more ▼]

Background: Breast-conserving surgery is the most acceptable option for breast cancer removal from an invasive and psychological point of view. During the surgical procedure, the imaging acquisition using Magnetic Image Resonance is performed in the prone configuration, while the surgery is achieved in the supine stance. Thus, a considerable movement of the breast between the two poses drives the tumor to move, complicating the surgeon's task. Therefore, to keep track of the lesion, the surgeon employs ultrasound imaging to mark the tumor with a metallic harpoon or radioactive tags. This procedure, in addition to an invasive characteristic, is a supplemental source of uncertainty. Consequently, developing a numerical method to predict the tumor movement between the imaging and intra-operative configuration is of significant interest. Methods: In this work, a simulation pipeline allowing the prediction of patient-specific breast tumor movement was put forward, including personalized preoperative surgical drawings. Through image segmentation, a subject-specific finite element biomechanical model is obtained. By first computing an undeformed state of the breast (equivalent to a nullified gravity), the estimated intra-operative configuration is then evaluated using our developed registration methods. Finally, the model is calibrated using a surface acquisition in the intra-operative stance to minimize the prediction error. Findings: The capabilities of our breast biomechanical model to reproduce real breast deformations were evaluated. To this extent, the estimated geometry of the supine breast configuration was computed using a corotational elastic material model formulation. The subject-specific mechanical properties of the breast and skin were assessed, to get the best estimates of the prone configuration. The final results are a Mean Absolute Error of 4.00 mm for the mechanical parameters E_breast = 0.32 kPa and E_skin = 22.72 kPa. The optimized mechanical parameters are congruent with the recent state-of-the-art. The simulation (including finding the undeformed and prone configuration) takes less than 20 s. The Covariance Matrix Adaptation Evolution Strategy optimizer converges on average between 15 to 100 iterations depending on the initial parameters for a total time comprised between 5 to 30 min. To our knowledge, our model offers one of the best compromises between accuracy and speed. The model could be effortlessly enriched through our recent work to facilitate the use of complex material models by only describing the strain density energy function of the material. In a second study, we developed a second breast model aiming at mapping a generic model embedding breast-conserving surgical drawing to any patient. We demonstrated the clinical applications of such a model in a real-case scenario, offering a relevant education tool for an inexperienced surgeon. [less ▲]

A Software Vulnerabilities Odysseus: Analysis, Detection, and Mitigation

Doctoral thesis (2022)

Programming has become central in the development of human activities while not being immune to defaults, or bugs. Developers have developed specific methods and sequences of tests that they implement to ... [more ▼]

Programming has become central in the development of human activities while not being immune to defaults, or bugs. Developers have developed specific methods and sequences of tests that they implement to prevent these bugs from being deployed in releases. Nonetheless, not all cases can be thought through beforehand, and automation presents limits the community attempts to overcome. As a consequence, not all bugs can be caught. These defaults are causing particular concerns in case bugs can be exploited to breach the program’s security policy. They are then called vulnerabilities and provide specific actors with undesired access to the resources a program manages. It damages the trust in the program and in its developers, and may eventually impact the adoption of the program. Hence, to attribute a specific attention to vulnerabilities appears as a natural outcome. In this regard, this PhD work targets the following three challenges: (1) The research community references those vulnerabilities, categorises them, reports and ranks their impact. As a result, analysts can learn from past vulnerabilities in specific programs and figure out new ideas to counter them. Nonetheless, the resulting quality of the lessons and the usefulness of ensuing solutions depend on the quality and the consistency of the information provided in the reports. (2) New methods to detect vulnerabilities can emerge among the teachings this monitoring provides. With responsible reporting, these detection methods can provide hardening of the programs we rely on. Additionally, in a context of computer perfor- mance gain, machine learning algorithms are increasingly adopted, providing engaging promises. (3) If some of these promises can be fulfilled, not all are not reachable today. Therefore a complementary strategy needs to be adopted while vulnerabilities evade detection up to public releases. Instead of preventing their introduction, programs can be hardened to scale down their exploitability. Increasing the complexity to exploit or lowering the impact below specific thresholds makes the presence of vulnerabilities an affordable risk for the feature provided. The history of programming development encloses the experimentation and the adoption of so-called defence mechanisms. Their goals and performances can be diverse, but their implementation in worldwide adopted programs and systems (such as the Android Open Source Project) acknowledges their pivotal position. To face these challenges, we provide the following contributions: • We provide a manual categorisation of the vulnerabilities of the worldwide adopted Android Open Source Project up to June 2020. Clarifying to adopt a vulnera- bility analysis provides consistency in the resulting data set. It facilitates the explainability of the analyses and sets up for the updatability of the resulting set of vulnerabilities. Based on this analysis, we study the evolution of AOSP’s vulnerabilities. We explore the different temporal evolutions of the vulnerabilities affecting the system for their severity, the type of vulnerability, and we provide a focus on memory corruption-related vulnerabilities. • We undertake the replication of a machine-learning based detection algorithms that, besides being part of the state-of-the-art and referenced to by ensuing works, was not available. Named VCCFinder, this algorithm implements a Support- Vector Machine and bases its training on Vulnerability-Contributing Commits and related patches for C and C++ code. Not in capacity to achieve analogous performances to the original article, we explore parameters and algorithms, and attempt to overcome the challenge provided by the over-population of unlabeled entries in the data set. We provide the community with our code and results as a replicable baseline for further improvement. • We eventually list the defence mechanisms that the Android Open Source Project incrementally implements, and we discuss how it sometimes answers comments the community addressed to the project’s developers. We further verify the extent to which specific memory corruption defence mechanisms were implemented in the binaries of different versions of Android (from API-level 10 to 28). We eventually confront the evolution of memory corruption-related vulnerabilities with the implementation timeline of related defence mechanisms. [less ▲]

Computational Tools for Evaluation and Programing of Deep Brain Stimulation

Doctoral thesis (2022)

Deep brain stimulation (DBS) is a surgical therapy to alleviate symptoms of numerous movement and psychiatric disorders by electrical stimulation of specific neural tissues via implanted electrodes ... [more ▼]

Deep brain stimulation (DBS) is a surgical therapy to alleviate symptoms of numerous movement and psychiatric disorders by electrical stimulation of specific neural tissues via implanted electrodes. Precise electrode implantation is important to target the right brain area. After the surgery, DBS parameters, including stimulation amplitude, frequency, pulse width, and selection of electrode’s active contacts, are adjusted during programming sessions. Programming sessions are normally done by trial and error. Thus, they can be long and tiring. The main goal of the thesis is to make the post-operative experience, particularly the programming session, easier and faster by using visual aids to create a virtual reconstruction of the patient’s case. This enables in silico testing of different scenarios before applying them to the patient. A quick and easy-to-use deep learning-based tool for deep brain structure segmentation is developed with 89% ± 3 accuracy (DBSegment). It is much easier to implement compared to widely-used registration-based methods, as it requires less dependencies and no parameter tuning. Therefore, it is much more practical. Moreover, it segments 40 times faster than the registration-based method. This method is combined with an electrode localization method to reconstruct patients’ cases. Additionally, we developed a tool that simulates DBS-induced electric field distributions in less than a seconds (FastField). This is 1000 times faster than standard methods based on finite elements, with nearly the same performance (92%). The speed of the electric field simulation is particularly important for DBS parameter initialization, which we initialize by solving an optimization problem (OptimDBS). A grid search method confirms that our novel approach convergences to the global minimum. Finally, all the developed methods are tested on clinical data to ensure their applicability. In conclusion, this thesis develops various novel user-friendly tools, enabling efficient and accurate DBS reconstruction and parameter initialization. The methods are by far the quickest among open-source tools. They are easy to use and publicly available, FastField within the LeadDBS toolbox, and DBSegment as a Python pip package and a Docker image. We hope they can boost the DBS post-operative experience, maximize the therapy’s efficacy, and ameliorate DBS research. [less ▲]