A Simple Temporal Information Matching Mechanism for Entity Alignment Between Temporal Knowledge Graphs

Entity alignment (EA) aims to find entities in different knowledge graphs (KGs) that refer to the same object in the real world. Recent studies incorporate temporal information to augment the representations of KGs. The existing methods for EA between temporal KGs (TKGs) utilize a time-aware attention mechanism to incorporate relational and temporal information into entity embeddings. The approaches outperform the previous methods by using temporal information. However, we believe that it is not necessary to learn the embeddings of temporal information in KGs since most TKGs have uniform temporal representations. Therefore, we propose a simple graph neural network (GNN) model combined with a temporal information matching mechanism, which achieves better performance with less time and fewer parameters. Furthermore, since alignment seeds are difficult to label in real-world applications, we also propose a method to generate unsupervised alignment seeds via the temporal information of TKG. Extensive experiments on public datasets indicate that our supervised method significantly outperforms the previous methods and the unsupervised one has competitive performance.Comment: Accepted by COLING 202

High lubricity meets load capacity: cartilage mimicking bilayer structure by brushing up stiff hydrogels from subsurface

Natural articular cartilage has ultralow friction even at high squeezing pressure. Biomimicking cartilage with soft materials has been and remains a grand challenge in the fields of materials science and engineering. Inspired by the unique structural features of the articular cartilage, as well as by its remarkable lubrication mechanisms dictated by the properties of the superficial layers, a novel archetype of cartilage‐mimicking bilayer material by robustly entangling thick hydrophilic polyelectrolyte brushes into the subsurface of a stiff hydrogel substrate is developed. The topmost soft polymer layer provides effective aqueous lubrication, whereas the stiffer hydrogel layer used as a substrate delivers the load‐bearing capacity. Their synergy is capable of attaining low friction coefficients (order 0.010) under heavily loaded conditions (order 10 MPa contact pressure) in water environment, a performance incredibly close to that of natural articular cartilage. The bioinspired material can maintain low friction even when subjected to 50k reciprocating cycles under high contact pressure, with almost no wear observed on the sliding track. These findings are theoretically explained and compounded by multiscale simulations used to shed light on the mechanisms responsible for this remarkable performance. This work opens innovative technology routes for developing cartilage‐mimicking ultralow friction soft materials

The Immungenicity and Cross-Neutralizing Activity of Enterovirus 71 Vaccine Candidate Strains

This study aimed to evaluate enterovirus 71 (EV-A71) vaccine candidate strains, including their genotypes, immunogenicity and cross-neutralization capacity. From clinical samples, EV-A71 strains were separated by using Vero cells. Six strains were chosen for vaccine candidates, and the sequences were analyzed. To detect the immunogenicity of the strains, we used them to immunize NIH mice at 0 and 14 days. Cytopathic effects (CPE) were examined to determine the EV-A71 neutralizing antibody (NTAb) titer 14 d after the first and second inoculations. To evaluate the cross-neutralizing capacity of the EV-A71 vaccine candidate strains, we tested serum immunized mice with ten EV-A71 genotype strains. Six EV-A71 vaccine candidate strains were identified, all belonging to sub-genotype C4, the prevalent genotype in China. The sequence similarity of the VP1 regions of the six candidate vaccine strains and three approved inactivated vaccines was 97.58%–97.77%, and the VP1 amino acid similarity was 98.65%–99.33%. Experiments were performed to evaluate the immunogenicity and cross-neutralizing activity of the EV-A71 vaccine candidate strains. The strains had good immunogenicity 14 d after two immunizations, inducing an NTAb titer ranging from 1:94 to 1:346. The NTAb seroconversion rates 14 d after one immunization were above 80% (except HB0007), and significantly increased immunogenicity of EV-A71 strains was observed post-inoculation. Furthermore, our candidate vaccine strains had broad cross-neutralizing activity after challenge with ten sub-genotypes of EV-A71. The highest NTAb titer/lowest NTAb titer ratios of sera against EV-A71 sub-genotypes were 8.0 (JS0002), 8.0 (JS0005), 21.3 (HB0005), 21.3 (HB0007), 10.7 (HB0040) and 8.0 (GD0002), respectively. Our EV-A71 strains had good immunogenicity and cross-neutralization activity, and have the potential to serve as vaccine strains for multivalent hand, foot and mouth disease vaccines

Urban Public Health: Is There a Pyramid?

Early ecologists identified a pyramidal trophic structure in terms of number, biomass and energy transfer. In 1943, the psychologist Maslow put forward a pyramid model to describe layers of human needs. It is indicated that the pyramid principle is universally applicable in natural, humanistic and social disciplines. Here, we report that a pyramid structure also exists in urban public health (UPH). Based on 18 indicators, the UPH states of four cities (Beijing, Tokyo, New York, and London) are compared from the point of view of five aspects, namely physical health, living conditions, social security, environmental quality, and education and culture. A pyramid structure was found in each city when focusing on 2000–2009 data. The pyramid of Beijing is relatively similar to that of Tokyo, and the pyramids of New York and London are similar to each other. A general development trend in UPH is proposed and represented by different pyramid modes. As a basic conjecture, the UPH pyramid model can be verified and developed with data of more cities over a longer period, and be used to promote healthy urban development

Simulation of dissolved nutrient export from the Dongjiang river basin with a grid-based NEWS model

In this research, a grid-based NEWS model was proposed through coupling the geographic information system (GIS) with the Global NEWS model framework. The model was then applied to the Dongjiang River basin to simulate the dissolved nutrient export from this area. The model results showed that the total amounts of the dissolved nitrogen and phosphorus exported from the Dongjiang River basin were approximately 27154.87 and 1389.33 t, respectively. 90 % of the two loads were inorganic forms (i.e. dissolved inorganic nitrogen and phosphorus, DIN and DIP). Also, the nutrient export loads did not evenly distributed in the basin. The main stream watershed of the Dongjiang River basin has the largest DIN and DIP export loads, while the largest dissolved organic nitrogen and phosphorus (DON and DOP) loads were observed in the middle and upper stream watersheds of the basin, respectively. As for the nutrient exported from each subbasin, different sources had different influences on the output of each nutrient form. For the DIN load in each subbasin, fertilization application, atmospheric deposition and biological fixation were the three main contributors, while eluviation was the most important source for DON. In terms of DIP load, fertilizer application and breeding wastewater were the main contributors, while eluviation and fertilizer application were the two main sources for DOP

Simulation of dissolved nutrient export from the Dongjiang river basin with a grid-based NEWS model

In this research, a grid-based NEWS model was proposed through coupling the geographic information system (GIS) with the Global NEWS model framework. The model was then applied to the Dongjiang River basin to simulate the dissolved nutrient export from this area. The model results showed that the total amounts of the dissolved nitrogen and phosphorus exported from the Dongjiang River basin were approximately 27154.87 and 1389.33 t, respectively. 90 % of the two loads were inorganic forms (i.e. dissolved inorganic nitrogen and phosphorus, DIN and DIP). Also, the nutrient export loads did not evenly distributed in the basin. The main stream watershed of the Dongjiang River basin has the largest DIN and DIP export loads, while the largest dissolved organic nitrogen and phosphorus (DON and DOP) loads were observed in the middle and upper stream watersheds of the basin, respectively. As for the nutrient exported from each subbasin, different sources had different influences on the output of each nutrient form. For the DIN load in each subbasin, fertilization application, atmospheric deposition and biological fixation were the three main contributors, while eluviation was the most important source for DON. In terms of DIP load, fertilizer application and breeding wastewater were the main contributors, while eluviation and fertilizer application were the two main sources for DOP