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/

Global: Zendy Plus annual

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

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The USNO-B Catalog contains spurious entries that are caused by diffractionspikes and circular reflection halos around bright stars in the originalimaging data. These spurious entries appear in the Catalog as if they were realstars; they are confusing for some scientific tasks. The spurious entries canbe identified by simple computer vision techniques because they producerepeatable patterns on the sky. Some techniques employed here are variants ofthe Hough transform, one of which is sensitive to (two-dimensional)overdensities of faint stars in thin right-angle cross patterns centered onbright ($<13 \mag$) stars, and one of which is sensitive to thin annularoverdensities centered on very bright ($<7 \mag$) stars. After enforcingconservative statistical requirements on spurious-entry identifications, wefind that of the 1,042,618,261 entries in the USNO-B Catalog, 24,148,382 ofthem ($2.3 \percent$) are identified as spurious by diffraction-spike criteriaand 196,133 ($0.02 \percent$) are identified as spurious by reflection-halocriteria. The spurious entries are often detected in more than 2 bands and arenot overwhelmingly outliers in any photometric properties; they thereforecannot be rejected easily on other grounds, i.e., without the use of computervision techniques. We demonstrate our method, and return to the community inelectronic form a table of spurious entries in the Catalog.

Cleaning the USNO-B Catalog through automatic detection of optical artifacts