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Nitrogen doping is an important method to modulate electronic structure of two-dimensional carbon materials. The properties of the doped systems are heavily dependent on the local structure of nitrogen dopants involved, which are often determined by experimental X-ray photoelectron spectra (XPS) and near-edge X-ray absorption fine-structure (NEXAFS) at the nitrogen K-edge. In the present work, the N1s XPS and NEXAFS spectra of nitrogen-doped graphdiynes have been accurately calculated at the density functional theory level. Five representative nitrogen-dopants in graphdiynes, namely [pyridinic, amino, graphitic, and two sp-hybridized N (sp-N-1 and sp-N-2) local structures], are fully examined, from which all experimental features could be correctly assigned. The calculated results can be used to determine the ratio of different nitrogen dopants in graphdiyne at different elevated temperatures reported in previous experiments. Our findings provide the basic references for structure determination of nitrogen doped graphdiyne and new understanding of the underlying structure-property relationships., QC 20190712

The Precision Medicine Initiative is a multicenter effort aiming at formulating personalized treatments leveraging on individual patient data (clinical, genome sequence and functional genomic data) together with the information in large knowledge bases (KBs) that integrate genome annotation, disease association studies, electronic health records and other data types. The biomedical literature provides a rich foundation for populating these KBs, reporting genetic and molecular interactions that provide the scaffold for the cellular regulatory systems and detailing the influence of genetic variants in these interactions. The goal of BioCreative VI Precision Medicine Track was to extract this particular type of information and was organized in two tasks: (i) document triage task, focused on identifying scientific literature containing experimentally verified protein–protein interactions (PPIs) affected by genetic mutations and (ii) relation extraction task, focused on extracting the affected interactions (protein pairs). To assist system developers and task participants, a large-scale corpus of PubMed documents was manually annotated for this task. Ten teams worldwide contributed 22 distinct text-mining models for the document triage task, and six teams worldwide contributed 14 different text-mining systems for the relation extraction task. When comparing the text-mining system predictions with human annotations, for the triage task, the best F-score was 69.06%, the best precision was 62.89%, the best recall was 98.0% and the best average precision was 72.5%. For the relation extraction task, when taking homologous genes into account, the best F-score was 37.73%, the best precision was 46.5% and the best recall was 54.1%. Submitted systems explored a wide range of methods, from traditional rule-based, statistical and machine learning systems to state-of-the-art deep learning methods. Given the level of participation and the individual team results we find the precision

Six stable C84 isomers satisfying isolated pentagon rule (IPR) have been theoretically identified by infrared (IR), X-ray photoelectron (XPS) and near-edge X-ray absorption fine structure (NEXAFS) spectra. The XPS and NEXAFS spectra at the K-edge for all nonequivalent carbon atoms were simulated by the density functional theory method. NEXAFS spectra show stronger dependence than IR and XPS spectra on the six C84 isomers, which can be properly used for isomer identification. Furthermore, spectral components of total spectra for carbon atoms in different local environment have been explored., Export Date: 9 May 2018; Article; CODEN: JPCAF; Correspondence Address: Song, X.-N.; Shandong Province Key Laboratory of Medical Physics and Image Processing Technology, School of Physics and Electronics, Shandong Normal UniversityChina; email: xiuneng@sdnu.edu.cn; Funding details: Shandong Province; Funding details: MOE, Ministry of Education; Funding details: CFSR, Canon Foundation for Scientific Research; Funding details: 11374195, NSFC, National Natural Science Foundation of China; Funding details: 21303096, NSFC, National Natural Science Foundation of China; Funding details: 11404193, NSFC, National Natural Science Foundation of China; Funding text: This work is supported by the National Natural Science Foundation of China (Grant Nos. 11404193, 21303096, and 11374195) and the Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry. Thanks to the support of the Taishan scholar project of Shandong Province. QC 20180528

Previous studies measured gravel bed surfaces by terrestrial laser scanning (TLS) and close-range photogrammetry suggested the presence of at least two different scales of spatial variation in gravel bed surfaces. This study investigated the spatial variation of airborne laser scanning (ALS) point clouds acquired in gravel bed. Due to the large footprint of ALS systems, a smoother surface is expected, but there exists some uncertainty over the precise scale of ALS measurement (hereafter referred to as the spatial support). As a result, we applied the regularization method, which is a variogram upscaling approach, to investigate the true support of ALS data. The regularization results suggested that the gravel bed surface described by the ALS is much smoother than expected in terms of the ALS reported measurement scale. Moreover, we applied the factorial kriging (FK) method, which allows mapping of different scales of variation present in the data separately (different from ordinary kriging which produces a single map), to obtain the river bed topography at each scale of spatial variation. We found that the short-range and long-range FK maps of the TLS-derived DSMs were able to highlight the edges of gravels and clusters of gravels, respectively. The long-range FK maps of the ALS data shows a pattern of gravel-bed clusters and aggregations of gravels. However, the short-range FK maps of the ALS data produced noisy maps, due to the smoothing effect. This analysis, thus, shows clearly that ALS data may be insufficient for geomorphological and hydraulic engineering applications that require the resolution of individual gravels. © 2018 G.-H. Huang et al. published by De Gruyte.