Martensite-to-austenite reversion and recrystallization in cryogenically-rolled type 321 metastable austenitic steel

The annealing behavior of cryogenically-rolled type 321 metastable austenitic steel was established. Cryogenic deformation gave rise to martensitic transformation which developed preferentially within deformation bands. Subsequent annealing in the range of 600 C to 700 C resulted in reversion of the strain-induced martensite to austenite. At 800 C, the reversion was followed by static recrystallization. At relatively-low temperatures, the reversion was characterized by a very strong variant selection, which led to the restoration of the crystallographic orientation of the coarse parent austenite grains. An increase in the annealing temperature relaxed the variant-selection tendency and provided subsequent recrystallization thus leading to significant grain refinement. Nevertheless, a significant portion of the original coarse grains was found to be untransformed and therefore the fine-grain structure was fairly heterogeneous

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