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Whilst, in many countries, the sudden enforced transfer to large-scale distance learning in state schools as a result of COVID_19 lockdown measures caused turmoil, it also provided an unprecedented opportunity to understand more about key factors associate ...
As an important connection of terrestrial and marine ecosystems, rivers input multitudinous (micro)plastics into the oceans. However, comparisons of field and estimated riverine inputs of (micro)plastics and contributions of multiple parameters are limited ...
The problem of covariance estimation for replicated surface-valued processes is examined from the functional data analysis perspective. Considerations of statistical and computational efficiency often compel the use of separability of the covariance, even ...
We present a framework for performing regression when both covariate and response are probability distributions on a compact interval. Our regression model is based on the theory of optimal transportation, and links the conditional Frechet mean of the resp ...
Although theories of emotion associate negative emotional symptoms with cognitive biases in information processing, they rarely specify the details. Here, we characterize cognitive biases in information processing of pleasant and unpleasant information, an ...
Characteristics of the spent nuclear fuel (SNF) are typically calculated, requiring validation a priori. The validation process relies on the difference between calculations and measurements, namely the bias. Usually, predicting the bias based on benchmark ...
This thesis focuses on non-parametric covariance estimation for random surfaces, i.e.~functional data on a two-dimensional domain. Non-parametric covariance estimation lies at the heart of functional data analysis, andconsiderations of statistical and comp ...
In this paper, we present an exact (i.e. non-approximated) and linear measurement model for hybrid AC/DC micro-grids for recursive state estimation (SE). More specifically, an exact linear model of a voltage source converter (VSC) is proposed. It relies on ...
Cosmological N-body simulations provide numerical predictions of the structure of the Universe against which to compare data from ongoing and future surveys, but the growing volume of the Universe mapped by surveys requires correspondingly lower statistica ...
We probe the accuracy of linear ridge regression employing a three-body local density representation derived from the atomic cluster expansion. We benchmark the accuracy of this framework in the prediction of formation energies and atomic forces in molecul ...
