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Xu, J. (author)
Deep Neural Networks (DNNs) have found extensive applications across diverse fields, such as image classification, speech recognition, and natural language processing. However, their susceptibility to various adversarial attacks, notably the backdoor attack, has repeatedly been demonstrated in recent years. <br/>The backdoor attack aims to...
doctoral thesis 2025
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Huber, Katharina T (author), van Iersel, L.J.J. (author), Moulton, Vincent (author), Scholz, Guillaume E. (author)
In evolutionary biology, networks are becoming increasingly used to represent evolutionary histories for species that have undergone non-treelike or reticulate evolution. Such networks are essentially directed acyclic graphs with a leaf set that corresponds to a collection of species, and in which non-leaf vertices with indegree 1 correspond...
journal article 2025
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Ma, C. (author), Sánchez-García, Iván (author), Wang, R. (author), Galán, Hitos (author), Denkova, A.G. (author), Serra Crespo, Pablo (author)
Chromium-51 (51Cr) is an attractive radionuclide for diagnosis, which is usually applied for red cells and platelet radiolabeling. However, commercially available 51Cr produced in nuclear reactors via neutron activation requires long irradiation times and complex separation methods. In this work, five metal–organic frameworks (MIL-100 (Cr), MIL...
journal article 2025
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Bastiaanssen, C.K.J.M.L. (author)
Interactions are essential to life. At the cellular level, the most fundamental processes rely on interactions between DNA, RNA, and proteins. Given that the structure and function of these molecules are determined by their sequence, it is ultimately the sequence that dictates the strength and specificity of these interactions. Thus, to improve...
doctoral thesis 2024
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Hu, D. (author)
IN advancing the ’More thanMoore’ paradigm, heterogeneous integration has emerged to facilitate the creation of highly efficient, compact, and multi-functional semiconductor systems. Addressing the challenges related to power efficiency, superior performance, and integration density, low-temperature nanoparticle sintering technology has become...
doctoral thesis 2024
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de Hoog, E. (author)
Hydraulic transport pipelines are used in dredging, (wet) mining and deep sea mining. These pump-pipeline systems are typically designed using steady-state principles. However, recent cases have shown that steady-state design does not always guarantee stable pipelines. Transients like self-amplifying density waves have shown to be able to...
doctoral thesis 2024
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Borgart, A. (author)
Shell structures can be either calculated with complex mathematics and differential geometry, or with the help of finite element method (FEM) software. Neither method gives the designer sufficient insight about the behaviour of the shell in the early design stage. The first method is for most designers too complex, it requires proficiency in at...
doctoral thesis 2024
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Slokom, M. (author)
In the field of machine learning (ML), the goal is to leverage algorithmic models to generate predictions, transforming raw input data into valuable insights. However, the ML pipeline, consisting of input data, models, and output data, is susceptible to various vulnerabilities and attacks. These attacks include re-identification, attribute...
doctoral thesis 2024
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Van de Cauter, L. (author)
Within the intricate landscape of immunology, the captivating cellular process of engulfing external objects, known as phagocytosis, has sparked scientific interest for several decades. This essential process, how for example macrophages devour and engulf bacteria, not only fuels the imagination, but also represents our first line of defense...
doctoral thesis 2024
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Mier Escurra, C. (author)
The energy transition towards decarbonization and modernization of the electric network requires the development of new technologies. Offshore windfarms, essential to this transition, rely on Gas-Insulated Systems (GIS) due to their compactness and extended lifespan. Despite the reliability of GIS, the high maintenance costs and severe...
doctoral thesis 2024
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Gomez Ortega, A. (author)
Our routine interactions with connected products and services result in the collection and indefinite storage of personal digital-trace data. These data are increasingly entangled with our lives. What we experience is scattered around multiple data points: our browsing history can account for our interests and worries, our messaging logs can...
doctoral thesis 2024
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Rout, S. (author)
Cardiovascular diseases (CVDs) claimed 17.9 million lives annually (2019), representing 32% of total deaths, with 85% attributed to heart attacks and strokes worldwide. Atrial fibrillation (AF) is the most frequent type of cardiac arrhythmia that has a worldwide prevalence of 46 million individuals worldwide. The absence of P-waves in the...
doctoral thesis 2024
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Simoes dos Santos, D. (author)
Cardiovascular diseases stand as the leading cause of death worldwide. Cardiovascular diseases are a group of disorders of the heart and blood vessels, such as atherosclerosis, congenital heart diseases, rheumatic heart diseases, and arrhythmias. Early detection of cardiovascular issues is imperative for effective treatment, and the...
doctoral thesis 2024
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van Aarle, C. (author)
doctoral thesis 2024
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Prosko, C.G. (author)
Hybrid semiconducting-superconducting mesoscopic circuits are the basis of topological and parity quantum bits or 'qubits'. Both qubits are expected to be intrinsically protected from decoherence, making them promising candidates for fault-tolerant quantum computation. As topological phases effectively manifest exotic nonabelian particles which...
doctoral thesis 2024
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van Riggelen, F. (author)
In this thesis, research is presented that explores the characteristics and possibilities of hole spin qubits defined in quantum dots in a germanium/silicon germanium heterostructure. The results of the most important experiments are concerned with distributing quantum information: either by entangling three qubits as the basis for the phase...
doctoral thesis 2024
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Li, Y. (author)
Improving the efficiency in deploying deep neural networks (DNNs) and processing complex high-dimensional data has drawn increasing attention in recent years. Yet, the deployment of large DNN models is challenged by the high computational complexity and energy consumption, making it difficult to run on resource-constrained devices such as mobile...
doctoral thesis 2024
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Brethouwer, J.F. (author)
In this thesis, we use mathematical models to assist the Dutch Ministry of Defence with understanding and decision-making within contemporary conflicts and crises. We explore ways to reduce the spread of COVID-19, study dynamics in the Sino-Indian border dispute, and investigate the value of scouting in conflicts involving autonomous systems. ...
doctoral thesis 2024
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Dekhovich, A. (author)
Deep learning models have made enormous strides over the past decade. However, they still have some disadvantages when dealing with changing data streams. One of these flaws is the phenomenon called catastrophic forgetting. It occurs when a model learns multiple tasks sequentially, having access only to the data of the current task. However,...
doctoral thesis 2024
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Intriago Zambrano, J.C. (author)
Recently, there has been a growing need for sustainable agriculture to increase food security, alleviate poverty, and contribute to climate change mitigation. Smallholder farmers (SFs) play a key role in this endeavor as they are a considerable segment of the global farming population. Despite their relevance, SFs face several challenges that...
doctoral thesis 2024
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