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

Review of solar energetic particle models

Solar Energetic Particle (SEP) events are interesting from a scientific perspective as they are the product of a broad set of physical processes from the corona out through the extent of the heliosphere, and provide insight into processes of particle acceleration and transport that are widely applicable in astrophysics. From the operations perspective, SEP events pose a radiation hazard for aviation, electronics in space, and human space exploration, in particular for missions outside of the Earth’s protective magnetosphere including to the Moon and Mars. Thus, it is critical to improve the scientific understanding of SEP events and use this understanding to develop and improve SEP forecasting capabilities to support operations. Many SEP models exist or are in development using a wide variety of approaches and with differing goals. These include computationally intensive physics-based models, fast and light empirical models, machine learning-based models, and mixed-model approaches. The aim of this paper is to summarize all of the SEP models currently developed in the scientific community, including a description of model approach, inputs and outputs, free parameters, and any published validations or comparisons with data.</p

Anion redox as a means to derive layered manganese oxychalcogenides with exotic intergrowth structures.

Topochemistry enables step-by-step conversions of solid-state materials often leading to metastable structures that retain initial structural motifs. Recent advances in this field revealed many examples where relatively bulky anionic constituents were actively involved in redox reactions during (de)intercalation processes. Such reactions are often accompanied by anion-anion bond formation, which heralds possibilities to design novel structure types disparate from known precursors, in a controlled manner. Here we present the multistep conversion of layered oxychalcogenides Sr2MnO2Cu1.5Ch2 (Ch = S, Se) into Cu-deintercalated phases where antifluorite type [Cu1.5Ch2]2.5- slabs collapsed into two-dimensional arrays of chalcogen dimers. The collapse of the chalcogenide layers on deintercalation led to various stacking types of Sr2MnO2Ch2 slabs, which formed polychalcogenide structures unattainable by conventional high-temperature syntheses. Anion-redox topochemistry is demonstrated to be of interest not only for electrochemical applications but also as a means to design complex layered architectures

Anion redox as a means to derive layered manganese oxychalcogenides with exotic intergrowth structures.

Topochemistry enables step-by-step conversions of solid-state materials often leading to metastable structures that retain initial structural motifs. Recent advances in this field revealed many examples where relatively bulky anionic constituents were actively involved in redox reactions during (de)intercalation processes. Such reactions are often accompanied by anion-anion bond formation, which heralds possibilities to design novel structure types disparate from known precursors, in a controlled manner. Here we present the multistep conversion of layered oxychalcogenides Sr2MnO2Cu1.5Ch2 (Ch = S, Se) into Cu-deintercalated phases where antifluorite type [Cu1.5Ch2]2.5- slabs collapsed into two-dimensional arrays of chalcogen dimers. The collapse of the chalcogenide layers on deintercalation led to various stacking types of Sr2MnO2Ch2 slabs, which formed polychalcogenide structures unattainable by conventional high-temperature syntheses. Anion-redox topochemistry is demonstrated to be of interest not only for electrochemical applications but also as a means to design complex layered architectures

Transcriptome and DNA methylome analyses reveal underlying mechanisms for the racial disparity in uterine fibroids

Uterine fibroids (leiomyomas) affect Black women disproportionately in terms of prevalence, incidence, and severity of symptoms. The causes of this racial disparity are essentially unknown. We hypothesized that myometria of Black women are more susceptible to developing fibroids and examined the transcriptomic and DNA methylation profiles of myometria and fibroids from Black and White women for comparison. Myometrial samples cluster by race in both their transcriptome and DNA methylation profiles, whereas fibroid samples only cluster by race in the latter. More differentially expressed genes (DEGs) were detected in the Black and White myometrial sample comparison than in the fibroid comparison. Leiomyoma gene set expression analysis identified four clusters of DEGs, including a cluster of 24 genes with higher expression in myometrial samples from Black women. One of the DEGs in this group, VWF, was significantly hypomethylated at two CpG probes that are near a putative enhancer site in myometrial samples from Black women and in all fibroids and that correlate with VWF expression levels. These results suggest that the molecular basis for the disparity in fibroid disease between Black and White women could be found in the myometria before fibroid development and not in the fibroids themselves

An efficient algorithm for online square detection

A square is a string that can be divided into two identical substrings. The problem of square detection has found applications in areas such as bioinformatics and data compression. There are many offline algorithms for the problem. In this paper, we give the first online algorithm for deciding whether a string contains a square. Our algorithm runs in total O (h log2 h) time where h is the length of the longest prefix of the input string that does not contain a square. © 2006 Elsevier B.V. All rights reserved.link_to_subscribed_fulltex