English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Open

Small-angle X-ray and neutron scattering (SAXS and SANS) are powerfultechniques in material science and soft matter. In this study, it was addressedhow multiple SAXS or SANS datasets are best weighted when doing simultaneousfitting. Three weighting schemes were tested: (1) equal weighting of alldatapoints, (2) equal weighting of each dataset through normalization with thenumber of datapoints, (3) weighting proportional to the information content.The weighing schemes were assessed by model refinement against synthetic dataunder numerous conditions. The first weighting scheme led to the most accurateparameter estimation, especially when one dataset substantially outnumbered theother(s). Furthermore, it was demonstrated that inclusion of Gaussian priorssignificantly improved the accuracy of the refined parameters, as compared tocommon practice, where each parameter is constrained uniformly within anallowed interval.

Optimal weights and priors in simultaneous fitting of multiple small-angle scattering datasets