Hyperbolic Graph Diffusion Model

Diffusion generative models (DMs) have achieved promising results in image and graph generation. However, real-world graphs, such as social networks, molecular graphs, and traffic graphs, generally share non-Euclidean topologies and hidden hierarchies. For example, the degree distributions of graphs are mostly power-law distributions. The current latent diffusion model embeds the hierarchical data in a Euclidean space, which leads to distortions and interferes with modeling the distribution. Instead, hyperbolic space has been found to be more suitable for capturing complex hierarchical structures due to its exponential growth property. In order to simultaneously utilize the data generation capabilities of diffusion models and the ability of hyperbolic embeddings to extract latent hierarchical distributions, we propose a novel graph generation method called, Hyperbolic Graph Diffusion Model (HGDM), which consists of an auto-encoder to encode nodes into successive hyperbolic embeddings, and a DM that operates in the hyperbolic latent space. HGDM captures the crucial graph structure distributions by constructing a hyperbolic potential node space that incorporates edge information. Extensive experiments show that HGDM achieves better performance in generic graph and molecule generation benchmarks, with a $48\%$ improvement in the quality of graph generation with highly hierarchical structures.Comment: accepted by AAAI 202

Spectral Graphormer: Spectral Graph-based Transformer for Egocentric Two-Hand Reconstruction using Multi-View Color Images

We propose a novel transformer-based framework that reconstructs two high fidelity hands from multi-view RGB images. Unlike existing hand pose estimation methods, where one typically trains a deep network to regress hand model parameters from single RGB image, we consider a more challenging problem setting where we directly regress the absolute root poses of two-hands with extended forearm at high resolution from egocentric view. As existing datasets are either infeasible for egocentric viewpoints or lack background variations, we create a large-scale synthetic dataset with diverse scenarios and collect a real dataset from multi-calibrated camera setup to verify our proposed multi-view image feature fusion strategy. To make the reconstruction physically plausible, we propose two strategies: (i) a coarse-to-fine spectral graph convolution decoder to smoothen the meshes during upsampling and (ii) an optimisation-based refinement stage at inference to prevent self-penetrations. Through extensive quantitative and qualitative evaluations, we show that our framework is able to produce realistic two-hand reconstructions and demonstrate the generalisation of synthetic-trained models to real data, as well as real-time AR/VR applications.Comment: Accepted to ICCV 202

Interactions between curcumin and human salt-induced kinase 3 elucidated from computational tools and experimental methods

Natural products are widely used for treating mitochondrial dysfunction-related diseases and cancers. Curcumin, a well-known natural product, can be potentially used to treat cancer. Human salt-induced kinase 3 (SIK3) is one of the target proteins for curcumin. However, the interactions between curcumin and human SIK3 have not yet been investigated in detail. In this study, we studied the binding models for the interactions between curcumin and human SIK3 using computational tools such as homology modeling, molecular docking, molecular dynamics simulations, and binding free energy calculations. The open activity loop conformation of SIK3 with the ketoenol form of curcumin was the optimal binding model. The I72, V80, A93, Y144, A145, and L195 residues played a key role for curcumin binding with human SIK3. The interactions between curcumin and human SIK3 were also investigated using the kinase assay. Moreover, curcumin exhibited an IC50 (half-maximal inhibitory concentration) value of 131 nM, and it showed significant antiproliferative activities of 9.62 ± 0.33 µM and 72.37 ± 0.37 µM against the MCF-7 and MDA-MB-23 cell lines, respectively. This study provides detailed information on the binding of curcumin with human SIK3 and may facilitate the design of novel salt-inducible kinases inhibitors

ACCELERATED DURABILITY ASSESSMENT OF TORSION BEAM REAR AXLE

According to the understanding of the actual load effect on the rear axle,the invalid load interval of critical modulated signal can be decided to compile the multi-level program spectrum. The loading mode of bench test is simplified on the basis of recognization of the failure correlated load on the rear axle. Accordingly,the durability test of torsion beam rear axle is completed from the work above. The results show that the failure region of bench test is coincident with road test which can reach the accelerated assessment of durability,the acceleration factor is 5. 68

Simulated Soil Organic Carbon Density Changes from 1980 to 2016 in Shandong Province Dry Farmlands Using the CENTURY Model

The changes in cultivated soil organic carbon (SOC) have significant effects on soil fertility and atmospheric carbon dioxide (CO2) concentration. Shandong Province is an important agricultural and grain production area in China. Dry farmland accounts for 74.15% of the province’s area, so studies on dynamic SOC changes would be helpful to understand its contribution to the Chinese national carbon (C) inventory. Using the spatial overlay analysis of the soil layer (1:10,000,000) and the land use layer (1:10,000,000), 2329 dry farmland soil polygons were obtained to drive the CENTURY model to simulate SOC dynamics in Shandong Province from the period 1980 to 2016. The results showed that the CENTURY model can be used to simulate the dry farmland SOC in Shandong Province. From the period 1980 to 2016, the soil organic carbon storage (SOCS) and soil organic carbon density (SOCD) showed an initial increase and then decreased, especially after reaching a maximum in 2009. In 2016, the SOCS was 290.58 × 106 t, an increase of 26.99 × 106 t compared with 1980. SOCD in the dry farmland increased from 23.69 t C ha−1 in 1980 to 25.94 t C ha−1 in 2016. The dry farmland of Shandong Province was a C sink from 1980 to 2016. Among the four soil orders, inceptisols SOCD dominated, and accounted for 47.81% of the dry farmland, followed by >entisols > vertisols > alfisols. Entisols SOCD growth rate was the highest (0.23 t C ha−1year−1). Compared to 1980, SOCD in 2016 showed an increasing trend in the northeast, northwest and southeast regions, while it followed a downward trend in the southwest

Chance constraint based risk-aware optimal power flow for cascading failure prevention

Once part or whole of the power system is exposed to some dangerous situations, e.g., malicious terrorist attacks or extreme weather conditions, the potential cascading failure is a severe threat to the power system. However, some feasible prevention control strategies can be used to enhance the system robust to cope with the impact of cascading failure. This paper proposed a chance constraint based optimal power flow model considering the impact of cascading failure. Compared to the conventional optimal power flow model, the proposed one can obtain the optimal generation profile that satisfies the chance constraint on the risk level of cascading failure. Power redispatch that is implemented according to the obtained generation profile can be seen as a prevention strategy, which can reduce the threat of cascading failure to an acceptable level. PSO algorithm and Monte Carlo method were used to search for the optimal solution. Case studies on the IEEE 39-bus system illustrate the effectiveness of the proposed model

Effects of Urban Vibrancy on an Urban Eco-Environment: Case Study on Wuhan City

In the context of rapid urbanisation and an emerging need for a healthy urban environment, revitalising urban spaces and its effects on the urban eco-environment in Chinese cities have attracted widespread attention. This study assessed urban vibrancy from the dimensions of density, accessibility, liveability, diversity, and human activity, with various indicators using an adjusted spatial TOPSIS (technique for order preference by similarity to an ideal solution) method. The study also explored the effects of urban vibrancy on the urban eco-environment by interpreting PM 2.5 and land surface temperature using “big” and “dynamic” data, such as those from mobile and social network data. Thereafter, spatial modelling was performed to investigate the influence of urban vibrancy on air pollution and temperature with inverted and extracted remote sensing data. This process identified spatial heterogeneity and spatial autocorrelation. The majority of the dimensions, such as density, accessibility, liveability, and diversity, are negatively correlated with PM 2.5, thereby indicating that the advancement of urban vibrancy in these dimensions potentially improves air quality. Conversely, improved accessibility increases the surface temperature in most of the districts, and large-scale infrastructure construction generally contributes to the increase. Diversity and human activity appear to have a cooling effect. In the future, applying spatial heterogeneity is advised to assess urban vibrancy and its effect on the urban eco-environment, to provide valuable references for spatial urban planning, improve public health and human wellbeing, and ensure sustainable urban development