The Effect of the Lipid Layer on Tear Film Behaviour

This paper investigates the effect of surfactants during tear film deposition and subsequent thinning. The surfactants occur naturally on the surface of the tear film in the form of a lipid layer. A lubrication model is developed that describes lipid spreading and film height evolution. It is shown that lipids may play an important role in drawing the tear film up the cornea during the opening phase of the blink. Further, nonuniform distributions of lipids may lead to a rapid thinning of the tear film behind the advancing lipid front (shock). Experiments using a fluorescein dye technique and using a tearscope were undertaken in order to visualise the motion of the lipid layer and any associated shocks immediately after a blink. It is found that the lipid layer continues to spread upwards on the cornea after the opening phase of the blink, in agreement with the model. Using the experimental data, lipid particles were tracked in order to determine the surface velocity and these results are compared to the model predictions

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press