Application of Fuzzy Set Theory in Option of Response Spectra

In order to consider the fuzziness of seismic intensity indecated by zoning map and seismic code in seismic design of structure, an innovative method in option of design spectrum in consideration of fuzziness of regional seismic hazard and site condition is presented herein. The solution of the problem can be divided into two steps: 1. to define and establish a fuzzy set for predicting and judging regional seismic hazard and site condition by applying fuzzy mathematics; 2. further to find out fuzzy vector of design spectrum depending on the fuzzy set of regional seismic hazard and site condition by applying fuzzy comprehensive Judgement theory

Facilitating Graph Neural Networks with Random Walk on Simplicial Complexes

Node-level random walk has been widely used to improve Graph Neural Networks. However, there is limited attention to random walk on edge and, more generally, on $k$-simplices. This paper systematically analyzes how random walk on different orders of simplicial complexes (SC) facilitates GNNs in their theoretical expressivity. First, on $0$-simplices or node level, we establish a connection between existing positional encoding (PE) and structure encoding (SE) methods through the bridge of random walk. Second, on $1$-simplices or edge level, we bridge edge-level random walk and Hodge $1$-Laplacians and design corresponding edge PE respectively. In the spatial domain, we directly make use of edge level random walk to construct EdgeRWSE. Based on the spectral analysis of Hodge $1$-Laplcians, we propose Hodge1Lap, a permutation equivariant and expressive edge-level positional encoding. Third, we generalize our theory to random walk on higher-order simplices and propose the general principle to design PE on simplices based on random walk and Hodge Laplacians. Inter-level random walk is also introduced to unify a wide range of simplicial networks. Extensive experiments verify the effectiveness of our random walk-based methods.Comment: Accepted by NeurIPS 202

Distance-Restricted Folklore Weisfeiler-Leman GNNs with Provable Cycle Counting Power

The ability of graph neural networks (GNNs) to count certain graph substructures, especially cycles, is important for the success of GNNs on a wide range of tasks. It has been recently used as a popular metric for evaluating the expressive power of GNNs. Many of the proposed GNN models with provable cycle counting power are based on subgraph GNNs, i.e., extracting a bag of subgraphs from the input graph, generating representations for each subgraph, and using them to augment the representation of the input graph. However, those methods require heavy preprocessing, and suffer from high time and memory costs. In this paper, we overcome the aforementioned limitations of subgraph GNNs by proposing a novel class of GNNs -- $d$-Distance-Restricted FWL(2) GNNs, or $d$-DRFWL(2) GNNs. $d$-DRFWL(2) GNNs use node pairs whose mutual distances are at most $d$ as the units for message passing to balance the expressive power and complexity. By performing message passing among distance-restricted node pairs in the original graph, $d$-DRFWL(2) GNNs avoid the expensive subgraph extraction operations in subgraph GNNs, making both the time and space complexity lower. We theoretically show that the discriminative power of $d$-DRFWL(2) GNNs strictly increases as $d$ increases. More importantly, $d$-DRFWL(2) GNNs have provably strong cycle counting power even with $d=2$: they can count all 3, 4, 5, 6-cycles. Since 6-cycles (e.g., benzene rings) are ubiquitous in organic molecules, being able to detect and count them is crucial for achieving robust and generalizable performance on molecular tasks. Experiments on both synthetic datasets and molecular datasets verify our theory. To the best of our knowledge, our model is the most efficient GNN model to date (both theoretically and empirically) that can count up to 6-cycles

Filling Conversation Ellipsis for Better Social Dialog Understanding

The phenomenon of ellipsis is prevalent in social conversations. Ellipsis increases the difficulty of a series of downstream language understanding tasks, such as dialog act prediction and semantic role labeling. We propose to resolve ellipsis through automatic sentence completion to improve language understanding. However, automatic ellipsis completion can result in output which does not accurately reflect user intent. To address this issue, we propose a method which considers both the original utterance that has ellipsis and the automatically completed utterance in dialog act and semantic role labeling tasks. Specifically, we first complete user utterances to resolve ellipsis using an end-to-end pointer network model. We then train a prediction model using both utterances containing ellipsis and our automatically completed utterances. Finally, we combine the prediction results from these two utterances using a selection model that is guided by expert knowledge. Our approach improves dialog act prediction and semantic role labeling by 1.3% and 2.5% in F1 score respectively in social conversations. We also present an open-domain human-machine conversation dataset with manually completed user utterances and annotated semantic role labeling after manual completion.Comment: Accepted to AAAI 202

Deep Geophysical Anomalies Beneath the Changbaishan Volcano

Subsurface imaging is key to understanding the origin of intraplate volcanoes. The Changbaishan volcano, located about 2,000 km away from the western Pacific subduction zone, has several debated origins. To investigate this, we compared regional seismic tomography with the electrical resistivity results and obtained high-resolution 1D and quasi-2D velocity-depth profiles. We show that the upper mantle is characterized by two anomalies exhibiting distinct features which cannot be explained by the same mechanism. We document a localized low-velocity anomaly atop the 410-km discontinuity, where the P-wave velocity is reduced more than that of the S-wave (i.e., lower Vp/Vs). We propose that this anomaly is caused by the reduction of the effective moduli during the phase transformation of olivine. The other anomaly, located between 300 and 370 km depth, reveals a significant reduction of the S-wave velocity (i.e., higher Vp/Vs), associated with a reduction of the electrical resistivity, altogether consistent with partial melting

A Biomimetic 3D-Self-Forming Approach for Microvascular Scaffolds

The development of science and technology often drew lessons from natural phenomena. Herein, inspired by drying-driven curling of apple peels, hydrogel-based micro-scaled hollow tubules (MHTs) are proposed for biomimicking microvessels, which promote microcirculation and improve the survival of random skin flaps. MHTs with various pipeline structures are fabricated using hydrogel in corresponding shapes, such as Y-branches, anastomosis rings, and triangle loops. Adjustable diameters can be achieved by altering the concentration and cross-linking time of the hydrogel. Based on this rationale, biomimetic microvessels with diameters of 50-500 mu m are cultivated in vitro by coculture of MHTs and human umbilical vein endothelial cells. In vivo studies show their excellent performance to promote microcirculation and improve the survival of random skin flaps. In conclusion, the present work proposes and validifies a biomimetic 3D self-forming method for the fabrication of biomimetic vessels and microvascular scaffolds with high biocompatibility and stability based on hydrogel materials, such as gelatin and hyaluronic acid.Peer reviewe

A Biomimetic 3D-Self-Forming Approach for Microvascular Scaffolds

The development of science and technology often drew lessons from natural phenomena. Herein, inspired by drying-driven curling of apple peels, hydrogel-based micro-scaled hollow tubules (MHTs) are proposed for biomimicking microvessels, which promote microcirculation and improve the survival of random skin flaps. MHTs with various pipeline structures are fabricated using hydrogel in corresponding shapes, such as Y-branches, anastomosis rings, and triangle loops. Adjustable diameters can be achieved by altering the concentration and cross-linking time of the hydrogel. Based on this rationale, biomimetic microvessels with diameters of 50-500 mu m are cultivated in vitro by coculture of MHTs and human umbilical vein endothelial cells. In vivo studies show their excellent performance to promote microcirculation and improve the survival of random skin flaps. In conclusion, the present work proposes and validifies a biomimetic 3D self-forming method for the fabrication of biomimetic vessels and microvascular scaffolds with high biocompatibility and stability based on hydrogel materials, such as gelatin and hyaluronic acid

NO-sGC Pathway Modulates Ca2+ Release and Muscle Contraction in Zebrafish Skeletal Muscle

Vertebrate skeletal muscle contraction and relaxation is a complex process that depends on Ca2+ ions to promote the interaction of actin and myosin. This process can be modulated by nitric oxide (NO), a gas molecule synthesized endogenously by (nitric oxide synthase) NOS isoforms. At nanomolar concentrations NO activates soluble guanylate cyclase (sGC), which in turn activates protein kinase G via conversion of GTP into cyclic GMP. Alternatively, NO post-translationally modifies proteins via S-nitrosylation of the thiol group of cysteine. However, the mechanisms of action of NO on Ca2+ homeostasis during muscle contraction are not fully understood and we hypothesize that NO exerts its effects on Ca2+ homeostasis in skeletal muscles mainly through negative modulation of Ca2+ release and Ca2+ uptake via the NO-sGC-PKG pathway. To address this, we used 5–7 days-post fecundation-larvae of zebrafish, a well-established animal model for physiological and pathophysiological muscle activity. We evaluated the response of muscle contraction and Ca2+ transients in presence of SNAP, a NO-donor, or L-NAME, an unspecific NOS blocker in combination with specific blockers of key proteins of Ca2+ homeostasis. We also evaluate the expression of NOS in combination with dihydropteridine receptor, ryanodine receptor and sarco/endoplasmic reticulum Ca2+ ATPase. We concluded that endogenous NO reduced force production through negative modulation of Ca2+ transients via the NO-sGC pathway. This effect could be reversed using an unspecific NOS blocker or sGC blocker