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

Effect of Soil Temperature on Reproduction of Root-knot Nematodes in Flue-cured Tobacco with Homozygous Rk1 and/or Rk2 Resistance Genes

Most commercial flue-cured tobacco cultivars contain the Rk1 resistance gene, which provides resistance to races 1 and 3 of Meloidogyne incognita and race 1 of M. arenaria. A number of cultivars now possess a second root-knot resistance gene, Rk2. High soil temperatures have been associated with a breakdown of root-knot resistance genes in a number of crops. Three greenhouse trials were performed from 2014 to 2015 investigate the effect of high soil temperature on the efficacy of Rk1 and/or Rk2 genes in reducing parasitism by a population of M. incognita race 3. Trials were arranged in randomized complete block design in open-top growth chambers set at 25°, 30°, and 35°C. Plants were inoculated with 3,000 eggs and data were collected 35 days post-inoculation. Galling, numbers of egg masses and eggs, and reproductive index were compared across cultivar entries. Nematode reproduction was reduced at 25°C and 30°C on entries possessing Rk1 and Rk1Rk2 compared to the susceptible entry and the entry possessing only Rk2. However, there were often no significant differences in reproduction at 35°C between entries with Rk1 and/or Rk2 compared to the susceptible control, indicating an increase of root-knot nematode parasitism on resistant entries at higher temperatures. Although seasonal differences in nematode reproduction were observed among experiments, relative differences among tobacco genotypes remained generally consistent

Yorba Times: Global Issues

During the Spring 2017 semester, Dr. Noah Asher Golden\u27s Teaching of Writing K-12 students partnered with the Journalism class at Yorba Academy for the Arts. Through collaboration over a four-month period, Chapman\u27s future teachers and Yorba\u27s junior high journalists engaged a deep writing process to write a series of features, editorials, and news articles related to a number of global issues. Thank you to Ms. Andrea Lopez, Ms. Tracy Knibb, and the Lloyd E. and Elisabeth H. Klein Family Foundation for supporting this project.https://digitalcommons.chapman.edu/yorba-chapman/1002/thumbnail.jp

Deep Underground Neutrino Experiment (DUNE) Near Detector Conceptual Design Report

International audienceThe Deep Underground Neutrino Experiment (DUNE) is an international, world-class experiment aimed at exploring fundamental questions about the universe that are at the forefront of astrophysics and particle physics research. DUNE will study questions pertaining to the preponderance of matter over antimatter in the early universe, the dynamics of supernovae, the subtleties of neutrino interaction physics, and a number of beyond the Standard Model topics accessible in a powerful neutrino beam. A critical component of the DUNE physics program involves the study of changes in a powerful beam of neutrinos, i.e., neutrino oscillations, as the neutrinos propagate a long distance. The experiment consists of a near detector, sited close to the source of the beam, and a far detector, sited along the beam at a large distance. This document, the DUNE Near Detector Conceptual Design Report (CDR), describes the design of the DUNE near detector and the science program that drives the design and technology choices. The goals and requirements underlying the design, along with projected performance are given. It serves as a starting point for a more detailed design that will be described in future documents

DUNE Offline Computing Conceptual Design Report

This document describes Offline Software and Computing for the Deep Underground Neutrino Experiment (DUNE) experiment, in particular, the conceptual design of the offline computing needed to accomplish its physics goals. Our emphasis in this document is the development of the computing infrastructure needed to acquire, catalog, reconstruct, simulate and analyze the data from the DUNE experiment and its prototypes. In this effort, we concentrate on developing the tools and systems thatfacilitate the development and deployment of advanced algorithms. Rather than prescribing particular algorithms, our goal is to provide resources that are flexible and accessible enough to support creative software solutions as HEP computing evolves and to provide computing that achieves the physics goals of the DUNE experiment