Temporal and Spatial Evolution of Economic Quality Difference between North and South China

Based on the “Five development Concepts”, this paper uses the entropy method to measure the economic quality of 336 prefecture-level regions and above in China from 1991 to 2020, and uses Dagum Gini coefficient, Kernel density estimation, spatial autocorrelation and standard deviation ellipse to explore the spatio-temporal evolution characteristics of North-South economic quality differences. The main conclusions are as follows: 1) From 1991 to 2020, the economic quality of the north and south continues to grow, and the spatial distribution pattern shows a relatively significant feature of “the south is relatively high, the north is relatively low” and “the coastal economic belt is relatively high, and the inland city is relatively low”. 2) In the past 30 years, the relative difference between the north and south regions has fluctuated and decreased, while the absolute difference has increased. 3) The economic quality of southern cities has a more significant spatial agglomeration. HH agglomeration and LL agglomeration are dominant in the south, while LL agglomeration is more inclined in the north. 4) The economic mass center of gravity in the north and the south showed a migration trend of “northeast-north” and “northwest-southwest” respectively

Pretraining Language Models with Text-Attributed Heterogeneous Graphs

In many real-world scenarios (e.g., academic networks, social platforms), different types of entities are not only associated with texts but also connected by various relationships, which can be abstracted as Text-Attributed Heterogeneous Graphs (TAHGs). Current pretraining tasks for Language Models (LMs) primarily focus on separately learning the textual information of each entity and overlook the crucial aspect of capturing topological connections among entities in TAHGs. In this paper, we present a new pretraining framework for LMs that explicitly considers the topological and heterogeneous information in TAHGs. Firstly, we define a context graph as neighborhoods of a target node within specific orders and propose a topology-aware pretraining task to predict nodes involved in the context graph by jointly optimizing an LM and an auxiliary heterogeneous graph neural network. Secondly, based on the observation that some nodes are text-rich while others have little text, we devise a text augmentation strategy to enrich textless nodes with their neighbors' texts for handling the imbalance issue. We conduct link prediction and node classification tasks on three datasets from various domains. Experimental results demonstrate the superiority of our approach over existing methods and the rationality of each design. Our code is available at https://github.com/Hope-Rita/THLM.Comment: Accepted by EMNLP 2023 Finding

DiffCloth: Differentiable Cloth Simulation with Dry Frictional Contact

Cloth simulation has wide applications in computer animation, garment design, and robot-assisted dressing. This work presents a differentiable cloth simulator whose additional gradient information facilitates cloth-related applications. Our differentiable simulator extends a state-of-the-art cloth simulator based on Projective Dynamics (PD) and with dry frictional contact. We draw inspiration from previous work to propose a fast and novel method for deriving gradients in PD-based cloth simulation with dry frictional contact. Furthermore, we conduct a comprehensive analysis and evaluation of the usefulness of gradients in contact-rich cloth simulation. Finally, we demonstrate the efficacy of our simulator in a number of downstream applications, including system identification, trajectory optimization for assisted dressing, closed-loop control, inverse design, and real-to-sim transfer. We observe a substantial speedup obtained from using our gradient information in solving most of these applications

Minimizing L1 over L2 norms on the gradient

In this paper, we study the L1/L2 minimization on the gradient for imaging applications. Several recent works have demonstrated that L1/L2 is better than the L1 norm when approximating the L0 norm to promote sparsity. Consequently, we postulate that applying L1/L2 on the gradient is better than the classic total variation (the L1 norm on the gradient) to enforce the sparsity of the image gradient. To verify our hypothesis, we consider a constrained formulation to reveal empirical evidence on the superiority of L1/L2 over L1 when recovering piecewise constant signals from low-frequency measurements. Numerically, we design a specific splitting scheme, under which we can prove subsequential and global convergence for the alternating direction method of multipliers (ADMM) under certain conditions. Experimentally, we demonstrate visible improvements of L1/L2 over L1 and other nonconvex regularizations for image recovery from low-frequency measurements and two medical applications of MRI and CT reconstruction. All the numerical results show the efficiency of our proposed approach.Comment: 26 page

Semaphorin 7A Promotes VEGFA/VEGFR2-Mediated Angiogenesis and Intraplaque Neovascularization in ApoE-/- Mice

Excessive neovascularization of atherosclerotic lesions increases plaque vulnerability and the susceptibility to rupture. Semaphorin 7A (Sema7A), a semaphorin family member, was recently reported to promote atherosclerotic plaque formation by mediating d-flow-induced endothelial phenotypic change and leukocyte adhesion. To extend our understanding of the proatherogenic role of Sema7A, we investigated the role of endothelial Sema7A in angiogenesis and atherosclerotic neovascularization. Sema7A overexpression in human umbilical vein endothelial cells (HUVECs) significantly upregulated VEGFA/VEGFR2 and promoted cell migration and angiogenesis. This enhancing effect was eliminated by the blockage of Sema7A receptor, β1 integrin. Inhibition of FAK or ERK1/2 downstream of β1 integrin signaling significantly inhibited cell migration and angiogenesis via ROCK (Rho-associated coiled forming protein kinase) and MYPT (myosin phosphatase targeting subunit), which are responsible for actin polymerization. Consistently, in vivo studies showed a remarkable reduction in VEGFA/VEGFR2 expression and neovascularization in the atherosclerotic plaques of Sema7A-/-ApoE-/- mice compared with Sema7A+/+ApoE-/- littermates. Supportively, Sema7A deficiency reduced the accumulation of T cells, macrophages, and dendritic cells, and enhanced plaque stability in ApoE-/- mice. Together, our findings show that Sema7A promotes VEGFA/VEGFR2-mediated neovascularization in a β1 integrin-dependent manner, supporting a crucial role of Sema7A in the progression of human atherosclerosis