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Domain decomposition methods are widely used tools for solving partial differential equations in parallel. However, despite their long history, there is a lack of rigorous convergence theory for equations with non-symmetric differential operators. This includes both nonlinear elliptic equations and linear parabolic equations. The aim of this thesis is therefore twofold: First, to construct framewo
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Over the last century, many women have contributed to the field of control engineering. Nevertheless, women are generally in the minority. This article highlights the contribution of women since the inception of control engineering to highlight good exemples to coming generations. A repository of portraits of women in control engineering is currently being curated and made available through the un
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Ex vivo (outside of the body) working heart models enable the evaluation of isolated hearts. They are envisioned to play an important role in increasing the currently low utilization rate of donor hearts for transplantation. For the heart to work in isolation, an afterload (flow impedance) is needed. To date, afterload devices have been constructed by combining multiple constituent elements such a
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Fast simulation of linear time-invariant (LTI) pharmacokinetic (PK) models is crucial to mixed-effect modeling techniques, used extensively in pharmacological research and development. The by far most common LTI PK models are particularly structured compartmental systems with one, two or three compartments. Here we develop and demonstrate very efficient, and down to machine precision exact, simula
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BACKGROUND: Lower respiratory infections caused by ssRNA viruses are a major health burden globally. Translational mouse models are a valuable tool for medical research, including research on respiratory viral infections. In in vivo mouse models, synthetic dsRNA can be used as a surrogate for ssRNA virus replication. However, studies investigating how genetic background of mice impacts the murine
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The debate about the implications of algorithms on antitrust lawenforcement has so far focused on multi-firm conduct in general andcollusion in particular. The implications of algorithms on abuse ofdominance have been largely neglected. This article seeks to fill this gap inthe existing literature by exploring how the increasingly precise practice ofindividualized targeting by algorithms can facil