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Christian L. Vestergaard

Researcher at Technical University of Denmark

Publications -  38
Citations -  1524

Christian L. Vestergaard is an academic researcher from Technical University of Denmark. The author has contributed to research in topics: Computer science & Population. The author has an hindex of 16, co-authored 29 publications receiving 1236 citations. Previous affiliations of Christian L. Vestergaard include Pasteur Institute & Aix-Marseille University.

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Data on face-to-face contacts in an office building suggests a low-cost vaccination strategy based on community linkers

TL;DR: It is shown that a vaccination strategy targeting linkers efficiently prevents large outbreaks of rapidly spreading epidemics and may help the design of efficient, low-cost vaccination or social-distancing strategies.
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Optimal estimation of diffusion coefficients from single-particle trajectories

TL;DR: An explicit, unbiased, and practically optimal covariance-based estimator that is regression-free and far superior to commonly used methods based on measured mean squared displacements, and outperforms the analytically intractable and computationally more demanding maximum likelihood estimator (MLE).
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The effect of salt reduction on sensory quality and microbial growth in hotdog sausages, bacon, ham and salami.

TL;DR: How moderately and greatly reduced NaCl affected yield, sensory quality and microbial growth in hotdog sausages, bacon, cooked cured ham and salami, and salt taste, juiciness and texture were the sensory parameters most affected by the NaCl reduction.
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Filopodial retraction force is generated by cortical actin dynamics and controlled by reversible tethering at the tip

TL;DR: The dynamics of filopodial extension and retraction are determined by the difference between the actin polymerization rate at the tip and the retrograde flow at the base of the filopodium, reminiscent of a process used by pathogens to invade cells.
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Temporal Gillespie Algorithm: Fast Simulation of Contagion Processes on Time-Varying Networks

TL;DR: A temporal Gillespie algorithm is presented that is applicable to general Poisson (constant-rate) processes on temporal networks, stochastically exact, and up to multiple orders of magnitude faster than traditional simulation schemes based on rejection sampling.