Density-functional embedding using a plane-wave basis

The constrained electron density method of embedding a Kohn-Sham system in a substrate system (first described by P. Cortona, Phys. Rev. B {\bf 44}, 8454 (1991) and T.A. Wesolowski and A. Warshel, J. Phys. Chem {\bf 97}, 8050 (1993)) is applied with a plane-wave basis and both local and non-local pseudopotentials. This method divides the electron density of the system into substrate and embedded electron densities, the sum of which is the electron density of the system of interest. Coupling between the substrate and embedded systems is achieved via approximate kinetic energy functionals. Bulk aluminium is examined as a test case for which there is a strong interaction between the substrate and embedded systems. A number of approximations to the kinetic-energy functional, both semi-local and non-local, are investigated. It is found that Kohn-Sham results can be well reproduced using a non-local kinetic energy functional, with the total energy accurate to better than 0.1 eV per atom and good agreement between the electron densities.Comment: 11 pages, 4 figure

The prediction of preference for unfamiliar urban places

Preferences for unfamiliar urban environments were studied as a function of urban categories, viewing time, and four predictor variables: complexity, coherence, identifiability, and mystery. A nonmetric factor analysis of the preference ratings for the longest viewing-time condition yielded five dimensions: Contemporary Life, Alley/Factory, Urban Nature, Unusual Architecture, and Older Buildings. The five categories differed significantly in preference, with Urban Nature by far the most preferred and Alley/Factory distinctly disliked. The combination of low coherence and high complexity characterizes the least liked Alley/Factory category, while the role of mystery in the urban setting is highlighted by the most preferred Urban Nature category. The results point to various ways in which the urban environment could be more responsive to people's preferences.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/43513/1/11111_2005_Article_BF01359051.pd

Geographical and temporal distribution of SARS-CoV-2 clades in the WHO European Region, January to June 2020

We show the distribution of SARS-CoV-2 genetic clades over time and between countries and outline potential genomic surveillance objectives. We applied three available genomic nomenclature systems for SARS-CoV-2 to all sequence data from the WHO European Region available during the COVID-19 pandemic until 10 July 2020. We highlight the importance of real-time sequencing and data dissemination in a pandemic situation. We provide a comparison of the nomenclatures and lay a foundation for future European genomic surveillance of SARS-CoV-2.Peer reviewe