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

The January Anomaly: Effects of Low Share Price, Transaction Costs, and Bid-Ask Bias.

The January effect is primarily a low-share price effect and less so a market value effect. In the recent 1977-86 period, after-transaction-cost raw and excess January returns are lower on low-price stocks than on high-price stocks. Failure of informed traders to eliminate significantly large before-transaction-cost excess January returns on low-price stocks is potentially explained by higher transactions costs and a bid-ask bias. At the least, the January anomaly found in prior tests is not persistent and, thereby, not likely to be exploitable by typical investors. Copyright 1992 by American Finance Association.

Chemical composition and biological activity of Coriandrum sativum L.: A review

Coriander (Coriandrum sativum L.) also called as Cilantro, Arab parsley, Chinese parsley, Kasbour is cultivated for its seeds and foliage for extraction of essential oil using hydrodistillation. The GC-MS compositional analysis of coriander seed essential oil showed the presence of many compounds viz linalool, camphor, geraniol, α–pinene, γ–terpinene, geranyl acetate and limonene. Essential oil of coriander is known to exhibit wide range of biological activities like antibacterial, antifungal, antioxidant, insecticidal and in addition it also exibit pharmacological activities such as anti-inflammatory, anxiolytic, antimicrobial, diuretic, cognition improvement, antidiabetic, antiseptic, antihypertensive, lipolytic, myorelaxant, anticancerous, antimutagenic, and free radical scavenging activities