International Migration, Integration and Social Cohesion online publications
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Predictive algorithms in perioperative haemodynamic management
Full text linkDit proefschrift richt zich op de effectiviteit van de Hypotension Prediction Index (HPI), een voorspeller van lage bloeddruk, bij het verminderen van hypotensie tijdens hartchirurgie en intensivecare-opname (IC). Het evalueert de vergelijkbaarheid van invasieve en niet-invasieve HPI-modaliteiten, waarbij op groepsniveau grotendeels vergelijkbare prestaties werden gevonden, met kleine verschillen in voorspellende tijdvensters.Daarnaast worden zorgen besproken over de voorspellende nauwkeurigheid van eerdere HPI-validatiestudies. Hoewel HPI veelbelovend is, suggereren sommige bevindingen dat standaard bloeddrukparameters vergelijkbare resultaten kunnen bieden. Daarom werd in een nieuwe vergelijkende analyse gekozen voor een klinisch relevante benadering om deze suggesties te onderzoeken. Hierbij werd de vergelijking gemaakt tussen HPI-pop-upalarmen en de MAP-alarmen in veelgebruikte bloeddrukmonitoren, ingesteld op een drempelwaarde tussen 70 en 75 mmHg. Deze analyses tonen aan dat het machine-learning-gebaseerde HPI-algoritme voordelen biedt op het gebied van voorspellen en mogelijk voorkomen van hypotensie. Een belangrijke exploratieve analyse liet echter zien dat een kleine aanpassing aan de MAP-alarmen, door het toevoegen van een tijdsafhankelijke functie, de voorspellende prestaties vergelijkbaar maakte.Tot slot wordt een gerandomiseerde studie besproken die is uitgevoerd tijdens hartchirurgie en postoperatieve IC-verblijven om HPI-geleide zorg te vergelijken met standaardzorg. HPI bleek effectief in het verminderen van hypotensie zonder een toename van hypertensieve gebeurtenissen. De studie toont aan dat HPI minder onnodige alarmen genereert dan conventionele bloeddrukmonitoren en voordelen biedt in de klinische praktijk. De resultaten ondersteunen de haalbaarheid en effectiviteit van HPI bij complexe chirurgische procedures en benadrukken het potentieel van innovatieve technologieën om de hemodynamische zorg te verbeteren
Visualizing, quantifying, and understanding nanowear of hard multi-asperity contacts
Full text linkWear takes place across the scale of contacts, involving different mechanisms, making predictive understanding difficult to build. At the macroscopic scale, the famous empirical Archard law predicts a linear relationship between the volume of material worn, the applied load and slid distance, normalized by the hardness of the softest material at the interface. This law describes wear extremely well in the context of debris formation, covering a wide range of wear mechanisms (fatigue, fracture, fretting, etc.) causing the softer material to wear down. For single asperity contacts, tribochemical (or stress-assisted) processes have been found to be the dominant mechanism driving wear. Derived from the Arrhenius equation governing chemical reaction rates, such processes describe the removal of single (or groups of) atoms by the supply of energy in the form of stress that enables the breaking of covalent bonds at the interface. On the one hand, attempts have been made to scale down the Archard law to single asperity context to understand how contact junction size is crucial in the transition from gradual to fracture type wear. On the other hand, efforts are made to observe tribochemical wear at multi-asperity contacts. In this thesis, we have experimentally studied promising systems to bridge the small-scale single asperity contact understanding to the large multi-asperity contact empirically understood. Our results indicate that tribochemical wear on hard, multi-asperity contacts can be detected but also understood (and manipulated) by changing the environmental conditions
The terms of critique:On art as critique in <i>October </i>journal
Full text linkThis dissertation examines the terms of critique in the art critical journal October. Founded in 1976, October emerged in response to the perceived redundancy of Clement Greenberg’s formalist art criticism and the rise of socially engaged art practices. Seeking to reconcile modernism’s self-critical focus with socio-political concerns, the journal became a platform for rethinking art’s role as a form of critique. Drawing on influences such as French Theory and the Frankfurt School, October advanced an understanding of art as a critical practice that interrogates the ideological, historical, and institutional conditions of its production and reception, extending this inquiry to broader questions of subjectivity, epistemology, and socio-historical analysis.The dissertation focuses on two primary paradigms of critique within October: Rosalind Krauss’ poststructuralist deconstruction and Benjamin Buchloh’s Marxist-inspired immanent critique. Both approaches emphasize art’s capacity to challenge dominant structures but differ in their theoretical foundations and methodologies. Krauss foregrounds the destabilization of fixed meanings and categories through poststructuralist critique, while Buchloh emphasizes art’s engagement with the socio-historical conditions of late capitalism. However, both paradigms also encounter internal contradictions that limit their capacity to address contemporary issues. Taking critique not only as its object but also as its method, the dissertation develops an immanent critique of these paradigms, ultimately proposing a new framework for art as critique.<br/
Making the connection:Improving the clinical and regulatory management of leukodystrophies
Full text linkLeukodystrophies comprise a group of rare neurogenetic disorders primarily affecting the white matter of the nervous system. Patients typically suffer from severe and progressive neurological disabilities. Advancements in diagnostics and pathophysiological understanding pave the way for therapy development. At the start of this PhD trajectory, the management perspective of metachromatic leukodystrophy (MLD) and vanishing white matter (VWM) was about to change: imminent approval of gene therapy for MLD and start of the first therapeutic trial in VWM. In this thesis, the role of international collaborations and patient registries is illustrated. We initiated the MLD initiative, a collaborative network and registry for MLD supported by a grant from the Dutch Healthcare Institute, and used the VWM consortium and VWM registry to advance therapeutic development and disease management in VWM
Invasive ventilation and closed-loop ventilation in critically ill patients
Full text linkThe aim of this thesis was to investigate the association of ventilation strategies, including closed-loop ventilation, with clinical outcomes in critically ill patients.In the first part of this thesis, we focused on patients with COVID–ARDS.Using the PRoVAcT–COVID database, we explored whether different PEEP/FiO₂ strategies were associated with better outcomes. In a large multicenter cohort, a high PEEP/low FiO₂ strategy was associated with improved ICU survival. Further analysis showed that this effect was moderated by respiratory subphenotypes— only patients with the low mechanical power phenotype appeared to benefit. We then studied the timing of spontaneous ventilation initiation and found that an early transition to spontaneous breathing was not associated with improved outcomes. Additionally, we investigated the incidence of air leaks and found it to be relatively high but comparable to rates in pre–COVID ARDS. The second part of this thesis focused on closed–loop ventilation.A systematic review of 51 randomized controlled trials highlighted that closed–loop ventilation may optimize ventilator settings and reduce workload. In a prospective cross–over study in ABI patients, we demonstrated that automated ventilation significantly increased the proportion of breaths within optimal protective zones and reduced the proportion in critical zones, outperforming conventional ventilation. These findings support the effectiveness of closed–loop ventilation in improving the delivery of lung- and brain-protective ventilation.<br/
Artificial intelligence for intelligent care:How machine learning algorithms can enhance the personalised treatment of patients with haemophilia A
Full text linkThis thesis explores the integration of machine learning with pharmacometrics to enhance the treatment of haemophilia A, a rare X-linked bleeding disorder characterized by an increased risk of spontaneous bleeding. The introduction provides an overview of the disorder, the history of prophylactic treatment, and the role of pharmacokinetics (PK) in personalized care, concluding with a discussion of future therapies such as non-factor replacement. The potential of machine learning is introduced, emphasizing algorithms like random forests, neural networks, and Gaussian Processes, alongside challenges specific to pharmacometrics such as data sparsity and interpretability. Recent ML applications in pharmacometrics are reviewed, discussing usage as part of data preparation, hypothesis generation, and predictive modelling. The thesis then presents deep compartment models (DCMs), a hybrid framework combining neural networks with differential equations, which simplifies PK modelling, handles sparse data effectively, and outperforms traditional methods in speed and accuracy. Variational inference (VI) is proposed as an alternative to conventional mixed-effects estimation, yielding stable and precise results. Applications of machine learning algorithms for improving haemophilia A treatment are detailed, including models for predicting factor VIII (FVIII) pharmacokinetics in prophylactic and perioperative settings and for optimizing dosing based on bleeding risk using repeated time-to-event (RTTE) models. The OPTI-CLOT web-portal is introduced as a platform for personalized dosing recommendations. The thesis concludes by advocating for hybrid machine learning approaches to address challenges in personalized treatment, offering insights for broader adoption in rare disease management
Immune stimulation and immunometabolism of the first line of defense in the lung
Full text linkPneumonia is an acute respiratory infection of the bronchial tree and alveoli of the lungs that can be classified as community-acquired pneumonia (CAP), or hospital-acquired pneumonia (HAP), the latter often affecting the immunocompromised or patients on an intensive care unit. In this context, the emergence of multidrug-resistant (MDR) bacteria, such as Klebsiella (K.) pneumoniae or Pseudomonas (P.) aeruginosa, poses a major risk. Apart from the development of new antibiotic agents, there is an increasing interest in drugs that can modulate or “boost” the host immune response; one of such agents is flagellin, a Toll-like receptor (TLR)5 ligand that induces an inflammatory reaction in respiratory epithelial cells upon topical administration. Next to the airway epithelium, alveolar macrophages (AMs) play an important role in the first line of defense in the lung, by phagocytosing pollutants and pathogens, and secreting inflammatory cytokines. Immunometabolic features of AMs, however, are largely unknown, while these could provide targets for improving immune cell function. This thesis seeks to enhance our understanding of innate immunity in the lung, with the specific aim to improve local host defense in the context of pneumonia. In Part I, we investigate the effect of local flagellin administration on the immune response of the airway epithelium, and whether this could serve as an adjunctive therapeutic to antibiotic treatment of bacterial lung infections. Part II focuses on the immunometabolic requirements of human AMs upon stimulation with lipopolysaccharide (LPS), component of the Gram-negative bacterial cell wall, and evaluates a model to generate AM-like cells from human monocytes
Big Tech in check:News media's watchdog role in the digital age
Full text linkAs Big Tech corporations like Microsoft, Amazon, Meta, Apple, and Alphabet wield growing influence over society, concerns about their accountability remain unresolved. Their transnational operations, financial power, and lobbying efforts have outpaced regulatory mechanisms, creating an accountability gap. This dissertation investigates the role of news media as watchdogs, assessing whether and how they hold Big Tech accountable for their societal impact.Adopting a mixed-methods approach, the dissertation is structured into two parts. The first examines the perceptions of journalists, lobbyists, and news audiences regarding news media’s watchdog role through interviews and surveys. Findings reveal that while journalists acknowledge the importance of accountability reporting, their willingness to adopt an active watchdog stance is influenced by complex relationships with expert sources. Meanwhile, audiences expect stronger media oversight of Big Tech, yet perceive journalism as falling short, affecting trust in news institutions. The second part shifts to a performative lens, analyzing news coverage to assess how journalists frame Big Tech’s role. While media outlets expose and critique Big Tech’s influence, corporations strategically shape public narratives to legitimize their power and align themselves with societal values. A bridging chapter blends perceptual and performative approaches and reflects on the use of reconstruction interviews.To conclude, this dissertation argues that accountability should be understood as a dynamic, communicative exchange. It underscores the need for independent, transparent, and adaptive journalism to maintain its legitimacy and safeguard democratic values
The City of Nature:Women and the Making of Green Space in Eighteenth-Century Amsterdam and Berlin
Full text linkThe long eighteenth century marked a transformative moment in the history of urban life when the age-old fantasy of a green city, a “city of nature,” was first translated into a tangible reality, involving men and women from across the class spectrum in its making. In this period, people also began to form a notion of urban nature as a family of related spatial typologies. This created new, imaginary links between cities and opened novel avenues of cultural exchange, such as those that developed between Amsterdam and Berlin. The City of Nature charts the shared landscape of green spaces that evolved in these two cities and shows this common ground to have been an inherently inequitable terrain in which hierarchies of gender and class became manifest. I argue that the process of urban greening as it unfolded in the long eighteenth century stood in relation to parallel shifts in gender ideologies and in the lived relations between men and women. The City of Nature shows that in the gardens, promenades, parks, and peri-urban landscapes of eighteenth-century Amsterdam and Berlin, the burgeoning gendered social positions of the modern age were cultivated – and contested – through everyday acts, discourse, and design. While the study reveals the city of nature to have been no less patriarchal in its set-up than the “grey” city, it makes the case that green spaces provided an important avenue for women to interfere in the urban landscape and to make space on their own terms
Teaching towards historical expertise:Developing students’ ability to reason causally in history
Full text linkExplaining historical events is an important goal in history education, but not much is known about pedagogical approaches to support this reasoning. In this dissertation, we therefore developed and investigated a learning-environment intended to foster students’ ability for causal historical reasoning. Based on the model of domain learning and the framework of historical reasoning, we defined causal historical reasoning as a construct consisting of (knowledge of) second-order concepts, causal strategies and epistemological beliefs.In the first study, we designed a lesson-unit on the First World War and conducted a quasi-experimental study with 11th-grade preuniversity students. In a second study, we replicated the experiment in a randomized controlled design. We concluded that explicit teaching constituted an indispensable principle in developing causal historical reasoning. Students in the experimental (explicit) condition showed greater improvement on the knowledge of causal strategies and second-order concepts. Furthermore, these students reported learning-gains related to epistemological aspects of causal explanations. At post-test in the experimental condition, a strong correlation was found between epistemological beliefs and students’ interest. Applying knowledge of causal historical reasoning in a document-based writing-task remained difficult for students. A qualitative study showed that students were able to integrate aspects of causal historical reasoning in their texts, but that they struggled with the argumentative nature of the task. Throughout the studies, epistemological beliefs surfaced as an important dimension of students’ historical reasoning, but assessing these beliefs was complex. Therefore, in the final study, we developed a new questionnaire aimed at evaluating naïve and nuanced epistemological beliefs.<br/