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 complete mitochondrial genome of the Riparia riparia (Passeriformes: Hirundinidae)

The Sand Martin (Riparia riparia) belongs to Hirundinidae. In this study, the complete mitochondrial genome of R. riparia was sequenced and characterized. The genome was 17,963 bases in length (GenBank accession no. OK537984) including 13 protein-coding genes, two ribosomal RNA (rRNA) genes, 22 transfer RNA (tRNA) genes, and two control regions. The overall base composition of R. riparia mitogenome was 30.5% for A, 31.8% for C, 14.5% for G, and 23.2% for T. Phylogenetic analysis revealed that R. riparia was genetically closest to the species of genus Tachycineta. R. riparia mitogenome could contribute to our understanding of the phylogeny and evolution of this species

Evolutionary PSO-based emergency monitoring geospatial edge service chain in the emergency communication network

Emergency communication networks play a vital role in disaster monitoring, transmission, and application during disaster emergency response (DER), however, the performance and stability of edge nodes in the emergency communication networks are often weak due to limited communication and computation resources. This weakness directly affects the quality of service (QoS) of the geospatial edge service (GES) chains involved in emergency monitoring. Existing research predominantly addresses service compositions in stable environments, neglecting the aggregation of efficient and robust GES chains in emergency communication networks. This study proposes an evolutionary particle swarm optimization (EPSO)-based emergency monitoring GES chain in an emergency communication network. It includes a GES chain model of emergency environment monitoring for tailing areas, as well as the designs of the particle chromosome encoding method, fitness evaluation model, and particle chromosome swarm update operators of the EPSO-based GES chain. Finally, the study conducts emergency environment monitoring experiments for tailing areas using the proposed method. Experiments results demonstrate that the proposed method significantly enhances the efficiency, stability, and reliability of emergency monitoring GES chains in the emergency communication network. This is crucial to providing fast and reliable services for DER during natural disasters

Characteristics of Microbiota in Different Segments of the Digestive Tract of <i>Lycodon rufozonatus</i>

The gastrointestinal tract of animals contains microbiota, forming a complex microecosystem. Gut microbes and their metabolites can regulate the development of host innate and adaptive immune systems. Animal immune systems maintain intestinal symbiotic microbiota homeostasis. However, relatively few studies have been published on reptiles, particularly snakes, and even fewer studies on different parts of the digestive tracts of these animals. Herein, we used 16S rRNA gene sequencing to investigate the microbial community composition and adaptability in the stomach and small and large intestines of Lycodon rufozonatus. Proteobacteria, Bacteroidetes, and Firmicutes were most abundant in the stomach; Fusobacteria in the small intestine; and Proteobacteria, Bacteroidetes, Fusobacteria, and Firmicutes in the large intestine. No dominant genus could be identified in the stomach; however, dominant genera were evident in the small and large intestines. The microbial diversity index was significantly higher in the stomach than in the small and large intestines. Moreover, the influence of the microbial community structure on function was clarified through function prediction. Collectively, the gut microbes in the different segments of the digestive tract revealed the unique features of the L. rufozonatus gut microbiome. Our results provide insights into the co-evolutionary relationship between reptile gut microbiota and their hosts

Bidirectional Optical Flow NeRF: High Accuracy and High Quality under Fewer Views

Neural Radiance Fields (NeRF) can implicitly represent 3D-consistent RGB images and geometric by optimizing an underlying continuous volumetric scene function using a sparse set of input views, which has greatly benefited view synthesis tasks. However, NeRF fails to estimate correct geometry when given fewer views, resulting in failure to synthesize novel views. Existing works rely on introducing depth images or adding depth estimation networks to resolve the problem of poor synthetic view in NeRF with fewer views. However, due to the lack of spatial consistency of the single-depth image and the poor performance of depth estimation with fewer views, the existing methods still have challenges in addressing this problem. So this paper proposes Bidirectional Optical Flow NeRF(BOF-NeRF), which addresses this problem by mining optical flow information between 2D images. Our key insight is that utilizing 2D optical flow images to design a loss can effectively guide NeRF to learn the correct geometry and synthesize the right novel view. We also propose a view-enhanced fusion method based on geometry and color consistency to solve the problem of novel view details loss in NeRF. We conduct extensive experiments on the NeRF-LLFF and DTU MVS benchmarks for novel view synthesis tasks with fewer images in different complex real scenes. We further demonstrate the robustness of BOF-NeRF under different baseline distances on the Middlebury dataset. In all cases, BOF-NeRF outperforms current state-of-the-art baselines for novel view synthesis and scene geometry estimation

Synergistic Effect in Plasmonic CuAu Alloys as Co-Catalyst on SnIn₄S₈ for Boosted Solar-Driven CO₂ Reduction

The photoreduction of CO2 to chemical fuels represents a promising technology to mitigate the current energy dilemma and global warming problems. Unfortunately, the original photocatalysts suffer from many side reactions and a poor CO2 conversion efficiency. The rational combination of active co-catalyst with pristine photocatalysts for promoting the adsorption and activation of CO2 is of vital importance to tackle this grand challenge. Herein, we rationally designed a SnIn4S8 nanosheet photocatalyst simultaneously equipped with CuAu alloys. The experimental results proved that the CuAu alloy can trap the electrons and enhance the separation and transport efficiency of the photogenerated carrier in the photocatalyst, alleviating the kinetical difficulty of the charge transfer process because of the preferable localized surface plasmon resonance (LSPR). Furthermore, the CuAu alloy works as the synergistic site to increase the CO2 adsorption and activation capacity. The optimized CuAu-SnIn4S8 photocatalyst exhibited a superior performance with CO generation rates of 27.87 μmol g−1 h−1 and CH4 of 7.21 μmol g−1 h−1, which are about 7.6 and 2.5 folds compared with SnIn4S8. This work highlights the critical role of alloy cocatalysts in boosting a CO2 activation and an efficient CO2 reduction, thus contributing to the development of more outstanding photocatalytic systems

Effect of different forage-to-concentrate ratios on ruminal bacterial structure and real-time methane production in sheep.

Emission from ruminants has become one of the largest sources of anthropogenic methane emission in China. The structure of the rumen flora has a significant effect on methane production. To establish a more accurate prediction model for methane production, the rumen flora should be one of the most important parameters. The objective of the present study was to investigate the relationship among changes in rumen flora, nutrient levels, and methane production in sheep fed with the diets of different forage-to-concentration ratios, as well as to screen for significantly different dominant genera. Nine rumen-cannulated hybrid sheep were separated into three groups and fed three diets with forage-to-concentration ratios of 50:50, 70:30, and 90:10. Three proportions of the diets were fed according to a 3 × 3 incomplete Latin square, design during three periods of 15d each. The ruminal fluid was collected for real-time polymerase chain reaction (real-time PCR), high-throughput sequencing and in vitro rumen fermentation in a new real-time fermentation system wit. Twenty-two genera were screened, the abundance of which varied linearly with forage-to-concentration ratios and methane production. In addition, during the 12-hour in vitro fermentation, the appearance of peak concentration was delayed by 26-27min with the different structure of rumen bacteria. The fiber-degrading bacteria were positively correlated with this phenomenon, but starch-degrading and protein-degrading bacteria were negative correlated. These results would facilitate macro-control of rumen microorganisms and better management of diets for improved nutrition in ruminants. In addition, our findings would help in screening bacterial genera that are highly correlated with methane production

Defect‐Tailoring Mediated Electron–Hole Separation in Single‐Unit‐Cell Bi 3

Solar photocatalysis is a potential solution to satisfying energy demand and its resulting environmental impact. However, the low electron-hole separation efficiency in semiconductors has slowed the development of this technology. The effect of defects on electron-hole separation is not always clear. A model atomically thin structure of single-unit-cell Bi3 O4 Br nanosheets with surface defects is proposed to boost photocatalytic efficiency by simultaneously promoting bulk- and surface-charge separation. Defect-rich single-unit-cell Bi3 O4 Br displays 4.9 and 30.9 times enhanced photocatalytic hydrogen evolution and nitrogen fixation activity, respectively, than bulk Bi3 O4 Br. After the preparation of single-unit-cell structure, the bismuth defects are controlled to tune the oxygen defects. Benefiting from the unique single-unit-cell architecture and defects, the local atomic arrangement and electronic structure are tuned so as to greatly increase the charge separation efficiency and subsequently boost photocatalytic activity. This strategy provides an accessible pathway for next-generation photocatalysts.Ministry of Education (MOE)National Research Foundation (NRF)This work was financially supported by the National Natural Science Foundation of China (Nos. 21676128 and 21576123) and Singapore National Research Foundation under NRF RF Award No. NRF-RF2013-08, MOE2016-T2-1-131, MOE2018-T3-1-002, Tier 1 2017-T1-001-075. The electron microscopy done at ORNL (S.-Z.Y. and M.F.C.) was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Science and Engineering Division and through a user project supported by ORNL’s Center for Nanophase Materials Sciences, which was sponsored by the Scientific User Facilities Division of U.S. Department of Energy. This research used resources of the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which was supported by National Science Foundation under Grant Nos. ACI-1053575 and DMR160118

Electrochemical CO ₂ Reduction with Atomic Iron‐Dispersed on Nitrogen‐Doped Graphene

Electrochemical reduction of CO2 provides an opportunity to reach a carbon‐neutral energy recycling regime, in which CO2 emissions from fuel use are collected and converted back to fuels. The reduction of CO2 to CO is the first step toward the synthesis of more complex carbon‐based fuels and chemicals. Therefore, understanding this step is crucial for the development of high‐performance electrocatalyst for CO2 conversion to higher order products such as hydrocarbons. Here, atomic iron dispersed on nitrogen‐doped graphene (Fe/NG) is synthesized as an efficient electrocatalyst for CO2 reduction to CO. Fe/NG has a low reduction overpotential with high Faradic efficiency up to 80%. The existence of nitrogen‐confined atomic Fe moieties on the nitrogen‐doped graphene layer is confirmed by aberration‐corrected high‐angle annular dark‐field scanning transmission electron microscopy and X‐ray absorption fine structure analysis. The Fe/NG catalysts provide an ideal platform for comparative studies of the effect of the catalytic center on the electrocatalytic performance. The CO2 reduction reaction mechanism on atomic Fe surrounded by four N atoms (Fe–N4) embedded in nitrogen‐doped graphene is further investigated through density functional theory calculations, revealing a possible promotional effect of nitrogen doping on graphene