The detailed studies of the structural and magnetic properties of hexaferrites Ba<inf>1−x</inf>Sr<inf>x</inf>Fe<inf>12</inf>O<inf>19</inf> for 0.0 ≤ x ≤ 0.75

The monophase polycrystalline hexaferrites Ba1−xSrxFe12O19 for 0 ≤ x ≤ 0.75 were prepared using the sol–gel synthesis method. The average crystallite size (Dac) ranged from 47 to 50 nm with Sr doping. The crystal structure and magnetic properties have been studied using X-ray diffraction (XRD) and neutron diffraction (ND). The structure of the studied hexaferrites is described by the hexagonal symmetry of P63/mmc space group. Field-emission scanning electron microscopy (FE-SEM) revealed the heterogeneous distribution of the grain sizes, which takes the hexagonal shape. Energy-dispersive X-ray spectroscopy (EDS) showed that the element compositions agree with the used components for each prepared sample. The substitution of Ba2+ ions by Sr2+ enhances the thermal stability of these hexaferrites. The magnetic hysteresis loops for the studied hexaferrite samples were obtained at room temperature. Different magnetic parameters are given in this work. The magnetocrystalline anisotropy parameter (Keff) initially increases for x ≤ 0.5 and then decreases for (x = 0.75). According to the analysis of neutron data, the magnetic structure formed by the Fe3+ ions, is located in five non-equivalent crystallographic sites with tetrahedral (Fe3-4f1), octahedral (Fe1-2a, Fe4-4f2, and Fe5-12k), and trigonal bipyramidal (Fe2-2b) coordinations. The strontium doping BaFe12O19 (BFO) hexaferrite affects the crystal lattice parameters, bond lengths, bond angles, and ordered magnetic moments of iron. Finally, the enhancement of the thermal stability and some magnetic parameters of the studied hexaferrite samples could be important for applications

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