MEDIATIZED POLITICS IN CHINA: A PERSPECTIVE OF GOVERNMENT COMMUNICATION ON WEIBO AND WECHAT

The Chinese government has expanded the use of social media to communicate information about government affairs in the Web 2.0 era. This study aims to examine the sources who posted the Chinese government’s messages on Weibo and WeChat, the focus of their posts, and Chinese netizens’ responses to the posts. The issue of the Wuhan doctor Li Wenliang’s death during the Covid-19 pandemic was selected. A census sample of 431 Weibo posts and reposts, 145 WeChat articles, and 27,094 comments were analyzed by using qualitative content analysis. The results revealed that media organizations had more influence than the authorities in communicating the government’s messages. They were the dominant sources to forward government press releases, and posting positive commentaries about government actions. This study also found that there were almost equal positive and negative responses from netizens, whose comments reflect a diversity of opinions. Based on Schramm’s interactive model of communication and the theory of mediatized politics, this study filled the research gap by considering the Chinese government as an active communicator who receives the public’s messages and gives feedback

Geometry-Aware Face Completion and Editing

Face completion is a challenging generation task because it requires generating visually pleasing new pixels that are semantically consistent with the unmasked face region. This paper proposes a geometry-aware Face Completion and Editing NETwork (FCENet) by systematically studying facial geometry from the unmasked region. Firstly, a facial geometry estimator is learned to estimate facial landmark heatmaps and parsing maps from the unmasked face image. Then, an encoder-decoder structure generator serves to complete a face image and disentangle its mask areas conditioned on both the masked face image and the estimated facial geometry images. Besides, since low-rank property exists in manually labeled masks, a low-rank regularization term is imposed on the disentangled masks, enforcing our completion network to manage occlusion area with various shape and size. Furthermore, our network can generate diverse results from the same masked input by modifying estimated facial geometry, which provides a flexible mean to edit the completed face appearance. Extensive experimental results qualitatively and quantitatively demonstrate that our network is able to generate visually pleasing face completion results and edit face attributes as well

GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning

Automatic transistor sizing is a challenging problem in circuit design due to the large design space, complex performance trade-offs, and fast technological advancements. Although there has been plenty of work on transistor sizing targeting on one circuit, limited research has been done on transferring the knowledge from one circuit to another to reduce the re-design overhead. In this paper, we present GCN-RL Circuit Designer, leveraging reinforcement learning (RL) to transfer the knowledge between different technology nodes and topologies. Moreover, inspired by the simple fact that circuit is a graph, we learn on the circuit topology representation with graph convolutional neural networks (GCN). The GCN-RL agent extracts features of the topology graph whose vertices are transistors, edges are wires. Our learning-based optimization consistently achieves the highest Figures of Merit (FoM) on four different circuits compared with conventional black-box optimization methods (Bayesian Optimization, Evolutionary Algorithms), random search, and human expert designs. Experiments on transfer learning between five technology nodes and two circuit topologies demonstrate that RL with transfer learning can achieve much higher FoMs than methods without knowledge transfer. Our transferable optimization method makes transistor sizing and design porting more effective and efficient.Comment: Accepted to the 57th Design Automation Conference (DAC 2020); 6 pages, 8 figure

Does P-type Ohmic Contact Exist in WSe2-metal Interfaces?

Formation of low-resistance metal contacts is the biggest challenge that masks the intrinsic exceptional electronic properties of 2D WSe2 devices. We present the first comparative study of the interfacial properties between ML/BL WSe2 and Sc, Al, Ag, Au, Pd, and Pt contacts by using ab initio energy band calculations with inclusion of the spin-orbital coupling (SOC) effects and quantum transport simulations. The interlayer coupling tends to reduce both the electron and hole Schottky barrier heights (SBHs) and alters the polarity for WSe2-Au contact, while the SOC chiefly reduces the hole SBH. In the absence of the SOC, Pd contact has the smallest hole SBH with a value no less than 0.22 eV. Dramatically, Pt contact surpasses Pd contact and becomes p-type Ohmic or quasi-Ohmic contact with inclusion of the SOC. Our study provides a theoretical foundation for the selection of favorable metal electrodes in ML/BL WSe2 devices

The complete mitochondrial genome of Hapalogenys analis (Perciformes, Haemulidea) except for control region, obtained by whole genome sequencing

In this study, we obtained the complete mitochondrial genome of Hapalogenys analis using whole genome sequencing. With the exception for control region, this mitochondrial genome, consisting of 16,355 base pairs (bp), contains 13 protein-coding genes (PCGs), 2 ribosomal RNAs (rRNAs), and 21 transfer RNAs (tRNAs). This mitochondrial genome also lacks a tRNA-Pro gene after tRNA-Thr gene. The overall base composition shows 25.45% of T, 29.73% of C, 28.68% of A and 16.14% of G, with a slight A + T rich feature (54.13%). Sanger sequencing is needed to confirm the accuracy of control region, as well as the lack of tRNA-Pro gene. The mitogenome data provides useful genetic markers for the studies on the molecular identification, population genetics, phylogenetic analysis and conservation genetics

Human airway-like multilayered tissue on 3D-TIPS printed thermoresponsive elastomer/collagen hybrid scaffolds

Developing a biologically representative complex tissue of the respiratory airway is challenging, however, beneficial for treatment of respiratory diseases, a common medical condition representing a leading cause of death in the world. This study reports a successful development of synthetic human tracheobronchial epithelium based on interpenetrated hierarchical networks composed of a reversely 3D printed porous structure of a thermoresponsive stiffness-softening elastomer nanohybrid impregnated with collagen nanofibrous hydrogel in vitro. Human bronchial epithelial cells (hBEpiCs) were able to attach and grow into an epithelial monolayer on the hybrid scaffolds co-cultured with either human bronchial fibroblasts (hBFs) or human bone-marrow derived mesenchymal stem cells (hBM-MSCs), with substantial enhancement of mucin expression, ciliation, well-constructed intercellular tight junctions and adherens junctions. The multi-layered co-culture 3D scaffolds consisting of a top monolayer of differentiated epithelium, with either hBFs or hBM-MSCs proliferating within the hyperelastic nanohybrid scaffold underneath, created a tissue analogue of the upper respiratory tract, validating these 3D printed guided scaffolds as a platform to support co-culture and cellular organization. In particular, hBM-MSCs in the co-culture system promoted an overall matured physiological tissue analogue of the respiratory system, a promising synthetic tissue for drug discovery, tracheal repair and reconstruction. Statement of significance Respiratory diseases are a common medical condition and represent a leading cause of death in the world. However, the epithelium is one of the most challenging tissues to culture in vitro, and suitable tracheobronchial models, physiologically representative of the innate airway, remain largely elusive. This study presents, for the first time, a systematic approach for the development of functional multilayered epithelial synthetic tissue in vitro via co-culture on a 3D-printed thermoresponsive elastomer interpenetrated with a collagen hydrogel network. The viscoelastic nature of the scaffold with stiffness softening at body temperature provide a promising matrix for soft tissue engineering. The results presented here provide new insights about the epithelium at different surfaces and interfaces of co-culture, and pave the way to offer a customizable reproducible technology to generate physiologically relevant 3D biomimetic systems to advance our understanding of airway tissue regeneration

Development data associated with effects of stiffness softening of 3D-TIPS elastomer nanohybrid scaffolds on tissue ingrowth, vascularization and inflammation in vivo

This DiB article contains data related to the research article entitled “Cellular responses to thermoresponsive stiffness memory elastomer nanohybrid scaffolds by 3D-TIPS” (Wu et al., 2018). Thermoresponsive poly (urea-urethane) nanohybrid elastomer (PUU-POSS) scaffolds were implanted in rats for up to 3 months. The porous structure and tensile mechanical properties of the scaffolds are listed and compared before and after in vitro and in vivo tests. The details of the histological analysis of the explants with different initial stiffness and porous structures at various time points are presented. The images and data presented support the conclusion about the coupled effects of stiffness softening and the hierarchical porous structure modulating tissue ingrowth, vascularization and macrophage polarization in the article (Wu et al., 2018)