NNKGC: Improving Knowledge Graph Completion with Node Neighborhoods

Knowledge graph completion (KGC) aims to discover missing relations of query entities. Current text-based models utilize the entity name and description to infer the tail entity given the head entity and a certain relation. Existing approaches also consider the neighborhood of the head entity. However, these methods tend to model the neighborhood using a flat structure and are only restricted to 1-hop neighbors. In this work, we propose a node neighborhood-enhanced framework for knowledge graph completion. It models the head entity neighborhood from multiple hops using graph neural networks to enrich the head node information. Moreover, we introduce an additional edge link prediction task to improve KGC. Evaluation on two public datasets shows that this framework is simple yet effective. The case study also shows that the model is able to predict explainable predictions.Comment: DL4KG Workshop, ISWC 202

Going Beyond Local: Global Graph-Enhanced Personalized News Recommendations

Precisely recommending candidate news articles to users has always been a core challenge for personalized news recommendation systems. Most recent works primarily focus on using advanced natural language processing techniques to extract semantic information from rich textual data, employing content-based methods derived from local historical news. However, this approach lacks a global perspective, failing to account for users' hidden motivations and behaviors beyond semantic information. To address this challenge, we propose a novel model called GLORY (Global-LOcal news Recommendation sYstem), which combines global representations learned from other users with local representations to enhance personalized recommendation systems. We accomplish this by constructing a Global-aware Historical News Encoder, which includes a global news graph and employs gated graph neural networks to enrich news representations, thereby fusing historical news representations by a historical news aggregator. Similarly, we extend this approach to a Global Candidate News Encoder, utilizing a global entity graph and a candidate news aggregator to enhance candidate news representation. Evaluation results on two public news datasets demonstrate that our method outperforms existing approaches. Furthermore, our model offers more diverse recommendations.Comment: 10 pages, Recsys 202

Gut microbiome and reproductive endocrine diseases: a Mendelian randomization study

BackgroundObservation studies have confirmed the association between the gut microbiome and reproductive endocrine diseases (REDs), namely, polycystic ovary syndrome (PCOS), endometriosis, and female infertility. However, their association has never been confirmed by a two-sample Mendelian randomization (MR) analysis.MethodsWe conducted a two-sample MR analysis to evaluate the relationship between the gut microbiome and the three aforementioned REDs. In order to get more comprehensive results, two different thresholds were adopted to select instrumental variables (IVs): one was a locus-wide significance threshold (P <1.0×10–5) and the other was a genome-wide significance level (P< 5×10-8). Summary-level statistics for the gut microbiome and REDs were collected from public databases. Inverse-variance weighted (IVW) was the main method used to estimate causality, and sensitivity analyses were conducted to validate the MR results.ResultsAt the locus-wide significance level, we identified that the genera Streptococcus (OR=1.52, 95%CI: 1.13-2.06, P=0.006) and RuminococcaceaeUCG005 (OR=1.39, 95%CI: 1.04-1.86, P=0.028) were associated with a high risk of PCOS, while Sellimonas (OR= 0.69, 95%CI: 0.58-0.83, P=0.0001) and RuminococcaceaeUCG011(OR=0.76, 95%CI: 0.60-0.95, P=0.017) were linked to a low PCOS risk. The genus Coprococcus2 (OR=1.20, 95%CI: 1.01-1.43, P=0.039) was correlated with an increased risk of female infertility, while Ruminococcus torques (OR=0.69, 95%CI: 0.54-0.88, P=0.002) were negatively associated with the risk of female infertility. The genera Olsenella (OR= 1.11, 95%CI: 1.01-1.22, P=0.036), Anaerotruncus (OR= 1.25, 95%CI: 1.03-1.53, P=0.025), and Oscillospira (OR= 1.21, 95%CI: 1.01-1.46, P=0.035) were linked to a high risk of endometriosis. However, the results showed that the gut microbiome did not possess a causal link with REDs risk based on the genome-wide significance level. Sensitivity analyses further confirmed the robustness of the MR results.ConclusionOur study provides evidence that gut microbiome is closely related with REDs. Subsequent studies should be conducted to promote microbiome-orientated therapeutic strategies for managing REDs

Laboratory Investigation of the Water Damage Resistance of Tuff Asphalt Mixture Modified with Additives

To improve the water damage resistance performance of a tuff asphalt mixture, a tuff mixture with cement and a liquid anti-stripping agent was used as the research object, and limestone and tuff mixtures without additives were selected as contrast samples. Through an improved boiling test and a water stability test before and after aging, the modification effect of the tuff mixture with additives of different types and contents on water damage resistance was evaluated to obtain the appropriate type and content of additives. On this basis, the other road performance measures of the selected mixture were further evaluated by immersion rutting and beam bending tests to verify the modification effect of the additive on the tuff mixture. Results showed that adding the appropriate cement content to the tuff mixture provided excellent resistance to the water damage effect. An optimal content of 2% cement additive in the mixture was obtained, and its high-temperature anti-rutting and low-temperature bending performance were also verified. Adhesion between tuff aggregates and asphalt polymer under water conditions was significantly improved and close to that of limestone aggregates. The modification effect of water stability after mixture aging was better than that of the anti-stripping agent. The residual stability and freeze–thaw splitting strength ratio of 2% cement content mixture were increased by about 21.5% and 16.7%, respectively, compared with those of the tuff mixture control

Laboratory Investigation of the Water Damage Resistance of Tuff Asphalt Mixture Modified with Additives

To improve the water damage resistance performance of a tuff asphalt mixture, a tuff mixture with cement and a liquid anti-stripping agent was used as the research object, and limestone and tuff mixtures without additives were selected as contrast samples. Through an improved boiling test and a water stability test before and after aging, the modification effect of the tuff mixture with additives of different types and contents on water damage resistance was evaluated to obtain the appropriate type and content of additives. On this basis, the other road performance measures of the selected mixture were further evaluated by immersion rutting and beam bending tests to verify the modification effect of the additive on the tuff mixture. Results showed that adding the appropriate cement content to the tuff mixture provided excellent resistance to the water damage effect. An optimal content of 2% cement additive in the mixture was obtained, and its high-temperature anti-rutting and low-temperature bending performance were also verified. Adhesion between tuff aggregates and asphalt polymer under water conditions was significantly improved and close to that of limestone aggregates. The modification effect of water stability after mixture aging was better than that of the anti-stripping agent. The residual stability and freeze–thaw splitting strength ratio of 2% cement content mixture were increased by about 21.5% and 16.7%, respectively, compared with those of the tuff mixture control

Strain-Enabled S-Arylation and S-Alkenylation of Sulfinamides

Converting commercially available and affordable chiral sulfinamides to pharmaceutically important chiral sulfoximines via SIV-functionalization is synthetically appealing, however, remains little developed due to the competing N-functionalization pathway. To address this challenge, we disclose a strain-enabled stereospecific and chemoselective S-arylation and S-alkenylation of sulfinamides using arynes and cyclic alkynes. The origin of high SIV-selectivity is elucidated by density functional theory (DFT) calculations, which reveals the potential involvement of a novel concerted mechanism. This method affords unprecedented chemical diversity on groups attached to the nitrogen center (N-R) that is valuable for diversity-oriented drug discover

Retrieval of 500 m Aerosol Optical Depths from MODIS Measurements over Urban Surfaces under Heavy Aerosol Loading Conditions in Winter

International audienceModerate Resolution Imaging Spectroradiometer (MODIS) aerosol products are used worldwide for their reliable accuracy. However, the aerosol optical depth (AOD) usually retrieved by the operational dark target (DT) algorithm of MODIS has been missing for most of the urban regions in Central China. This was due to a high surface reflectance and heavy aerosol loading, especially in winter, when a high cloud cover fraction and the frequent occurrence of haze events reduce the number of effective satellite observations. The retrieval of the AOD from limited satellite data is much needed and important for further aerosol investigations. In this paper, we propose an improved AOD retrieval method for 500 m MODIS data, which is based on an extended surface reflectance estimation scheme and dynamic aerosol models derived from ground-based sun-photometric observations. This improved method was applied to retrieve AOD during heavy aerosol loading and effectively complements the scarcity of AOD in correspondence with urban surface of a higher spatial resolution. The validation results showed that the retrieved AOD was consistent with MODIS DT AOD (R =~0.87; RMSE =~0.11) and ground measurements (R =~0.89; RMSE =~0.15) from both the Terra and the Aqua satellite. The method can be easily applied to different urban environments affected by air pollution and contributes to the research on aerosol