Lockdown, Earnings Losses and Household Asset Buffers in Europe.

Measures taken to contain the spread of COVID-19 affected some workers' capability to work and hence earning more than others. The initial impact may have been mitigated, for instance by relying on savings and assets, but access to these buffers likely varied within and across countries. In this article we estimate COVID-19 potential earnings losses using the Lockdown Working Ability Index and relate this to households' savings and assets observed in the Eurosystem Household Finance and Consumption Survey.

The quantum theory of time: a calculus for q-numbers.

In quantum theory, physical systems are usually assumed to evolve relative to a c-number time. This c-number time is unphysical and has turned out to be unnecessary for explaining dynamics: in the timeless approach to quantum theory developed by Page & Wootters 1983 , 2885. (doi:10.

Everettian relative states in the Heisenberg picture.

Everett's relative-state construction in quantum theory has never been satisfactorily expressed in the Heisenberg picture. What one might have expected to be a straightforward process was impeded by conceptual and technical problems that we solve here. The result is a construction which, unlike Everett's one in the Schrödinger picture, makes manifest the locality of Everettian multiplicity, its inherently approximative nature and its origin in certain kinds of entanglement and locally inaccessible information.

Welfare Resilience at the Onset of the COVID-19 Pandemic in a Selection of European Countries: Impact on Public Finance and Household Incomes.

This paper assesses the impact on household incomes of the COVID-19 pandemic and governments' policy responses in April 2020 in four large and severely hit EU countries: Belgium, Italy, Spain and the UK. We provide comparative evidence on the level of relative and absolute welfare resilience at the onset of the pandemic, by creating counterfactual scenarios using the European tax-benefit model EUROMOD combined with COVID-19-related household surveys and timely labor market data. We find that income poverty increased in all countries due to the pandemic while inequality remained broadly the same.

Unsupervised Machine Learning-Based Clustering of Nanosized Fluorescent Extracellular Vesicles.

Extracellular vesicles (EV) are biological nanoparticles that play an important role in cell-to-cell communication. The phenotypic profile of EV populations is a promising reporter of disease, with direct clinical diagnostic relevance. Yet, robust methods for quantifying the biomarker content of EV have been critically lacking, and require a single-particle approach due to their inherent heterogeneous nature.