Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks

We propose a distance supervised relation extraction approach for long-tailed, imbalanced data which is prevalent in real-world settings. Here, the challenge is to learn accurate "few-shot" models for classes existing at the tail of the class distribution, for which little data is available. Inspired by the rich semantic correlations between classes at the long tail and those at the head, we take advantage of the knowledge from data-rich classes at the head of the distribution to boost the performance of the data-poor classes at the tail. First, we propose to leverage implicit relational knowledge among class labels from knowledge graph embeddings and learn explicit relational knowledge using graph convolution networks. Second, we integrate that relational knowledge into relation extraction model by coarse-to-fine knowledge-aware attention mechanism. We demonstrate our results for a large-scale benchmark dataset which show that our approach significantly outperforms other baselines, especially for long-tail relations.Comment: To be published in NAACL 201

A Review of the Circle of Willis: Investigative Methods, Anatomical Variations and Correlated Ischemic Brain Diseases

The Circle of Willis (CoW) is the most important collateral pathway communicating between the bilateral carotid system and the posterior circulation. Many techniques have been used to investigate the configuration and function of the CoW and their advantages and disadvantages are reviewed here. In previous studies, morphometric variation in CoW has been widely detected; however, the frequency of variation ranges largely, between 10% and 85%. Some differences in reported frequency may reflect differences in: the definition of CoW variation, the methods used to examine variation and study populations. Two conclusions, however, are clear: (i) the prevalence of variation in the posterior circle is higher than in that of the anterior circle; and (ii) variations in the CoW are correlated with cerebral or carotid vessel diseases. Although the cause of the variants remains unclear, both genetic background and hemodynamics could play important roles. Lastly, the correlation between the CoW and ischemic brain diseases is discussed. In future, artificial intelligence will be helpful for evaluating the CoW

A Strategy for Prompt Phase Transfer of Upconverting Nanoparticles Through Surface Oleate-Mediated Supramolecular Assembly of Amino-β-Cyclodextrin

Lanthanide-doped upconverting nanoparticles (UCNPs) are promising for applications as wide as biosensing, bioimaging, controlled drug release, and cancer therapy. These applications require surface engineering of as-prepared nanocrystals, commonly coated with hydrophobic ligand of oleic acid, to enable an aqueous dispersion. However, literature-reported approaches often require a long time and/or multiple step treatment, along with several fold upconversion luminescence (UCL) intensity decrease. Here, we describe a strategy allowing oleate-capped UCNPs to become water-soluble and open-modified, with almost undiminished UCL, through ultrasonication of minutes. The prompt phase transfer was enabled by oleate-mediated supramolecular self-assembly of amino modified β-cyclodextrin (amino-β-CD) onto UCNPs surface. We showed that this method is valid for a wide range of UCNPs with quite different sizes (6–400 nm), various dopant types (Er, Tm, and Ho), and hierarchical structures (core, core-shell). Importantly, the amino group of amino-β-CD on the surface of treated UCNPs provide possibilities to introduce entities for biotargeting or functionalization, as exemplified here, a carboxylic-containing near infrared dye (Cy 7.5) that sensitizes UCNPs to enhance their UCL by ~4,820 fold when excited at ~808 nm. The described method has implications for all types of oleate-capped inorganic nanocrystals, facilitating their myriad bioapplications

Factors affecting sustainability of smart city services in China:From the perspective of citizens’ sense of gain

The citizen-centric smart city has become an essential paradigm for dealing with the problems caused by rapid urbanization. The Chinese government proposed enhancing citizens' sense of gain to achieve the citizen-centric development goal. To develop a more realistic improving path for the sustainability of smart city services (SCS), it is necessary to clarify the factors that affect citizens' sense of gain of smart city services (CSGSCS). To achieve this objective, 9 hypotheses were developed based on the modified expectation confirmation theory. Hypothesis testing, mediating effect testing, and heterogeneity analysis was conducted based on data collected from Nanjing citizens. The results indicate that: 1) Expectation-Perception Performance, including Content of SCS, Channel of SCS, and Support of SCS, all have positive direct effects on CSGSCS; 2) Expectation Confirmation directly affects CSGSCS and mediates the positive effect of the Expectation-Perception Performance on CSGSCS; 3) Heterogeneity of age and usage frequency have significant effects on CSGSCS. Finally, three policy implications were proposed, including encouraging citizens to participate in SCS supply, bridging the digital divide created by SCS, and improving the policy and legal system on SCS. This research enriches the academic framework and provides guidance for sustainable supply of SCS in similar cities around the world.</p

REC-MV: REconstructing 3D Dynamic Cloth from Monocular Videos

Reconstructing dynamic 3D garment surfaces with open boundaries from monocular videos is an important problem as it provides a practical and low-cost solution for clothes digitization. Recent neural rendering methods achieve high-quality dynamic clothed human reconstruction results from monocular video, but these methods cannot separate the garment surface from the body. Moreover, despite existing garment reconstruction methods based on feature curve representation demonstrating impressive results for garment reconstruction from a single image, they struggle to generate temporally consistent surfaces for the video input. To address the above limitations, in this paper, we formulate this task as an optimization problem of 3D garment feature curves and surface reconstruction from monocular video. We introduce a novel approach, called REC-MV, to jointly optimize the explicit feature curves and the implicit signed distance field (SDF) of the garments. Then the open garment meshes can be extracted via garment template registration in the canonical space. Experiments on multiple casually captured datasets show that our approach outperforms existing methods and can produce high-quality dynamic garment surfaces. The source code is available at https://github.com/GAP-LAB-CUHK-SZ/REC-MV.Comment: CVPR2023; Project Page:https://lingtengqiu.github.io/2023/REC-MV

The Identification of Stemness-Related Genes in the Risk of Head and Neck Squamous Cell Carcinoma

ObjectivesThis study aimed to identify genes regulating cancer stemness of head and neck squamous cell carcinoma (HNSCC) and evaluate the ability of these genes to predict clinical outcomes.Materials and MethodsThe stemness index (mRNAsi) was obtained using a one-class logistic regression machine learning algorithm based on sequencing data of HNSCC patients. Stemness-related genes were identified by weighted gene co-expression network analysis and least absolute shrinkage and selection operator analysis (LASSO). The coefficient of LASSO was applied to construct a diagnostic risk score model. The Cancer Genome Atlas database, the Gene Expression Omnibus database, Oncomine database and the Human Protein Atlas database were used to validate the expression of key genes. Interaction network analysis was performed using String database and DisNor database. The Connectivity Map database was used to screen potential compounds. The expressions of stemness-related genes were validated using quantitative real‐time polymerase chain reaction (qRT‐PCR).ResultsTTK, KIF14, KIF18A and DLGAP5 were identified. Stemness-related genes were upregulated in HNSCC samples. The risk score model had a significant predictive ability. CDK inhibitor was the top hit of potential compounds.ConclusionStemness-related gene expression profiles may be a potential biomarker for HNSCC

A hybrid molecular sensitizer for triplet fusion upconversion

Triplet fusion upconversion is useful for a broad spectrum of applications ranging from solar cells, photoredox catalysis, to biophotonics applications, especially in the near-infrared (NIR,>700 nm) range. This upconverting system typically demands efficient conversion of spin-singlet harvested energy through intersystem crossing to spin-triplet states, accessible only in rare metallic-coordinating macrocycle compounds or heavy-metal-containing semiconductor quantum dots for triplet sensitization. Herein, we describe an organic–inorganic system for NIR-to-visible triplet fusion upconversion, interfacing commonly-seen, non-metallic, infrared dyes (IR806, IR780, indyocynine green, and CarCl) and lanthanide nanocrystal (sodium ytterbium fluoride) as a hybrid molecular sensitizer, which extracts molecular spin-singlet energy to nanocrystal-enriched ytterbium dopants at ~48% efficiency (IR806, photoexciation at 808 nm). Moreover, ytterbium sub-lattice energy migration increases the interaction possibility between the nanocrystal and the freely-diffusing rubrenes in solution, resulting in 24-fold (IR806) to 1740-fold (indocyanine green) upconversion (600 nm) increase, depending on the IR dye type, as compared to the one without ytterbium nanotransducers. Ab initio quantum chemistry calculations identify enhanced spin-orbital coupling in the ytterbium-IR806 complex and high energy transfer rate in the ytterbium-rubrene interaction (1010 s 1). Employing inorganic lanthanide nanocrystals as nanotransducers unleashes the potential use of non-metallic infrared organic dyes for triplet fusion upconversion

Short term doxycycline treatment induces sustained improvement in myocardial infarction border zone contractility.

Decreased contractility in the non-ischemic border zone surrounding a MI is in part due to degradation of cardiomyocyte sarcomeric components by intracellular matrix metalloproteinase-2 (MMP-2). We recently reported that MMP-2 levels were increased in the border zone after a MI and that treatment with doxycycline for two weeks after MI was associated with normalization of MMP-2 levels and improvement in ex-vivo contractile protein developed force in the myocardial border zone. The purpose of the current study was to determine if there is a sustained effect of short term treatment with doxycycline (Dox) on border zone function in a large animal model of antero-apical myocardial infarction (MI). Antero-apical MI was created in 14 sheep. Seven sheep received doxycycline 0.8 mg/kg/hr IV for two weeks. Cardiac MRI was performed two weeks before, and then two and six weeks after MI. Two sheep died prior to MRI at six weeks from surgical/anesthesia-related causes. The remaining 12 sheep completed the protocol. Doxycycline induced a sustained reduction in intracellular MMP-2 by Western blot (3649±643 MI+Dox vs 9236±114 MI relative intensity; p = 0.0009), an improvement in ex-vivo contractility (65.3±2.0 MI+Dox vs 39.7±0.8 MI mN/mm2; p&lt;0.0001) and an increase in ventricular wall thickness at end-systole 1.0 cm from the infarct edge (12.4±0.6 MI+Dox vs 10.0±0.5 MI mm; p = 0.0095). Administration of doxycycline for a limited two week period is associated with a sustained improvement in ex-vivo contractility and an increase in wall thickness at end-systole in the border zone six weeks after MI. These findings were associated with a reduction in intracellular MMP-2 activity