Social life and political trust in China: Searching for machers and schmoozers

Previous literature has provided little evidence regarding the ways in which China’s burgeoning social life and rapid urbanization shape Chinese people’s level of trust in their government leaders. This article builds on Robert Putnam’s conceptualization of maching and schmoozing as formal and informal forms of social involvement, respectively. Using the 2012 Chinese General Social Survey, we identify four types of participants in social involvement, namely the inactives, machers, schmoozers and all-rounders, to untangle various aspects of social life in China. Our empirical analysis shows that the sociodemographic positions of the four types of social involvement are largely distinct. Our findings also contribute to the study of political trust by offering insight into the complicated associations between social involvement, hukou status and political trust in contemporary Chinese society

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

A New Method for Xenogeneic Bone Graft Deproteinization: Comparative Study of Radius Defects in a Rabbit Model.

Deproteinization is an indispensable process for the elimination of antigenicity in xenograft bones. However, the hydrogen peroxide (H2O2) deproteinized xenograft, which is commonly used to repair bone defect, exhibits limited osteoinduction activity. The present study was designed to develop a new method for deproteinization and compare the osteogenic capacities of new pepsin deproteinized xenograft bones with those of conventional H2O2 deproteinized ones.Bones were deproteinized in H2O2 or pepsin for 8 hours. The morphologies were compared by HE staining. The content of protein and collagen I were measured by the Kjeldahl method and HPLC-MS, respectively. The physical properties were evaluated by SEM and mechanical tests. For in vivo study, X-ray, micro-CT and HE staining were employed to monitor the healing processes of radius defects in rabbit models transplanted with different graft materials.Compared with H2O2 deproteinized bones, no distinct morphological and physical changes were observed. However, pepsin deproteinized bones showed a lower protein content, and a higher collagen content were preserved. In vivo studies showed that pepsin deproteinized bones exhibited better osteogenic performance than H2O2 deproteinized bones, moreover, the quantity and quality of the newly formed bones were improved as indicated by micro-CT analysis. From the results of histological examination, the newly formed bones in the pepsin group were mature bones.Pepsin deproteinized xenograft bones show advantages over conventional H2O2 deproteinized bones with respect to osteogenic capacity; this new method may hold potential clinical value in the development of new biomaterials for bone grafting

Timing-driven placement for carbon nanotube circuits

© 2015 IEEE. Carbon nanotube field effect transistors (CNFETs), which use carbon nanotubes (CNTs) as the transistor channel, are promising substitution of conventional CMOS technology. However, due to the stochastic assembly process of CNTs, the number of CNTs in each CNFET has a large variation, resulting in a vast circuit delay variation and timing yield degradation. To overcome it, we propose a timing-driven placement method for CNFET circuits. It exploits a unique feature of CNFET circuits, namely, asymmetric spatial correlation: CNFETs that lie along the CNT growth direction are highly correlated in terms of their electrical properties. Our method distributes CNFETs of the same critical paths to different rows perpendicular to the CNT growth direction during both global and detailed placement phases, while optimizing the timing of these critical paths. Experimental results demonstrated that our approach reduces both the mean and the variance of circuit delay, leading to an improvement in timing yield

The micro-CT analysis showed the bone quantity and quality in different groups (<i>n</i> = 5).

<p>The following parameters were measured at the indicated time points: bone volume fraction (BVF), tissue mineral content (TMC), tissue mineral density (TMD), trabecular number (Tb.N), trabecular separation (Tb.sp), trabecular thickness (Tb.th) and structure model index (SMI). Compared with H₂O₂, ^*<i>P</i> < 0.05.</p

The micro-CT analysis showed the bone quantity and quality in different groups (<i>n</i> = 5).

<p>The following parameters were measured at the indicated time points: bone volume fraction (BVF), tissue mineral content (TMC), tissue mineral density (TMD), trabecular number (Tb.N), trabecular separation (Tb.sp), trabecular thickness (Tb.th) and structure model index (SMI). Compared with H₂O₂, ^*<i>P</i> < 0.05.</p