Mimicking Polymer Processing Conditions on the Meso-Scale: Relaxation and Crystallization in Polyethylene Systems after Uni- and Biaxial Stretching.

Highly varying process conditions drive polymers into nonequilibrium molecular conformations. This has direct implications for the resulting structural and mechanical properties. This study rigorously investigated processing-property relations from a microscopic perspective.

Treatment Harms in Paediatric Primary Care.

The aim of this study was to describe the epidemiology in children of harms detectable from general practice records, and to identify risk factors. The SHARP study examined 9076 patient records from 44 general practices in New Zealand, with an enrolled population of 210,559 patients. "Harm" was defined as disease, injury, disability, suffering, and death, arising from the health system.

Evaluation of the Prescribing Skills Assessment implementation, performance and medical student experience in Australia and New Zealand.

Aims: The UK Prescribing Safety Assessment was modified for use in Australia and New Zealand (ANZ) as the Prescribing Skills Assessment (PSA). We investigated the implementation, student performance and acceptability of the ANZ PSA for final-year medical students.

Methods: This study used a mixed-method approach involving student data (n = 6440) for 2017-2019 (PSA overall score and 8 domain subscores).

Efficient Quality Diversity Optimization of 3D Buildings through 2D Pre-Optimization.

Quality diversity algorithms can be used to efficiently create a diverse set of solutions to inform engineers' intuition. But quality diversity is not efficient in very expensive problems, needing hundreds of thousands of evaluations. Even with the assistance of surrogate models, quality diversity needs hundreds or even thousands of evaluations, which can make its use infeasible.

Determining Lennard-Jones Parameters Using Multiscale Target Data through Presampling-Enhanced, Surrogate-Assisted Global Optimization.

Force field-based models are a Newtonian mechanics approximation of reality and are inherently noisy. Coupling models from different molecular scale domains (including single, gas-phase molecules up to multimolecule, condensed phase ensembles) is difficult, which is also the case for finding solutions that transfer well between the scales. In this contribution, we introduce a surrogate-assisted algorithm to optimize Lennard-Jones parameters for target data from different scale domains to overcome the difficulties named above.