Correlation of crystal growth rates in supersaturated solutions

This investigation has shown that crystals of copper sulfate and magnesium sulfate when grown in supersaturated solutions exhibit a growth rate according to the following equation: RL = 5.0 (ΔCDm)1/ρU Vs.292 where, RL, is the growth rate in Microns/min, is the change in concentration, Dm, the diffusivity coefficient, , density of solution, U, viscosity and Vs, solution velocity past the crystal. The equation shown demonstrates that a mass transfer process is taking place from the solution to the crystal surface, and that within the velocity range studied, there was no effect shown by the interface orientation rate. In a crystallizer where there is a mixture of crystals, the larger crystals will grow faster than those of a smaller size due to its higher relative solution velocity. Crystal growth is dependent upon the other factors described in conjunction with the formulae, and the analogy between these factors is described in the main paper

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 research.Peer reviewe