ABSTRACT
The global economy is moving into a new era characterized by digital and green development. To examine the impact of digital industrialization development on the energy supply chain, in relation to the sustainable development of China's energy security, we discuss the nonlinear impact and transmission mechanism of digital industrialization on the supply chain of the energy industry using a panel threshold regression model based on sample data on the development of the provincial natural gas industry in China from 2006 to 2020. We found that there are multiple threshold effects of digital industrialization level development on energy supply chain length, and the results are statistically significant, i.e., digital industrialization development positively contributes to natural gas supply chain length after digital industrialization is raised to or crosses the critical threshold. Meanwhile, the heterogeneity analysis results show that there are differences in the impact of digital industrialization on the energy supply chain from sub-sectors, regional development differences, and different development periods. Therefore, we provide some factual support and experience for achieving the construction goal of "Digital China" and accelerating the digital reform of the energy supply chain as well as transforming and upgrading the economic structure.
ABSTRACT
As the COVID-19 pandemic rampages across the world, the demands of video conferencing surge. To this end, real-time portrait segmentation becomes a popular feature to replace backgrounds of conferencing participants. While feature-rich datasets, models and algorithms have been offered for segmentation that extract body postures from life scenes, portrait segmentation has yet not been well covered in a video conferencing context. To facilitate the progress in this field, we introduce an open-source solution named PP-HumanSeg. This work is the first to construct a large-scale video portrait dataset that contains 291 videos from 23 conference scenes with 14K fine-labeled frames and extensions to multi-camera teleconferencing. Furthermore, we propose a novel Self-supervised Connectivity-aware Learning (SCL) for semantic segmentation, which introduces a self-supervised connectivity-aware loss to improve the quality of segmentation results from the perspective of connectivity. And we propose an ultra-lightweight model with SCL for practical portrait segmentation, which achieves the best trade-off between IoU and the speed of inference. Extensive evaluations on our dataset demonstrate the superiority of SCL and our model.
ABSTRACT
Objective: To systematically evaluate the incidence of adverse reactions to coronavirus disease 2019 (COVID-19) vaccination. Methods: We systematically searched PubMed, Embase, The Cochrane Library, Web of Science, CNKI, WanFang Data, and VIP Database from the inception of each database to August 31, 2021. Randomized controlled clinical trials (RCTs) on the safety of different types of COVID-19 vaccines were retrieved and analyzed. A random or fixed-effects model was used with an odds ratio as the effect size. The quality of each reference was evaluated. The incidence of the adverse reactions of the placebo group and the vaccination group was compared. Heterogeneity and publication bias were taken care of by meta-regression and sub-group analyses. Results: A total of 13 articles were included, with 81 287 subjects. Compared with the placebo group, the vaccination group showed a higher combined risk ratio (RR) of total adverse reactions (RR=1.67, 95% CI: 1.46-1.91, P<0.01), local adverse reactions (RR=2.86, 95% CI: 2.11-3.87, P<0.01), systemic adverse reactions (RR=1.25, 95% CI: 0.92-1.72, P=0.16), pain (RR=2.55, 95% CI: 1.75-3.70, P<0.01), swelling (RR=4.16, 95% CI: 1.71-10.17, P=0.002, fever (RR=2.34, 95% CI: 1.84-2.97, P<0.01), fatigue (RR=1.36, 95% CI: 1.32-1.41, P<0.01) and headache (RR=1.22, 95% CI: 1.18-1.26, P<0.01). The subgroup analysis showed the incidence of adverse reactions of the vaccination group after injection of the three COVID-19 vaccines (inactivated viral vaccines, mRNA vaccines and adenovirus vector vaccines) was higher than that of the placebo group, and the difference between the placebo group and the vaccination group in the mRNA vaccine subgroup and the adenovirus vector vaccine subgroup was statistically significant (P<0.01). The incidence of adverse reactions after injection of COVID-19 vaccine in subgroups of different ages was significantly higher than that in the placebo group (P<0.01). Conclusions: COVID-19 vaccines have a good safety, among which adenovirus vector vaccine has the highest incidence of adverse reactions. Both adolescents and adults vaccinated with novel coronavirus vaccine have a certain proportion of adverse reactions, but the symptoms are mild and can be relieved by themselves. Our meta-analysis can help boost global awareness of vaccine safety, promote mass vaccination, help build regional and global immune barriers and effectively curb the recurrency of COVID-19.
ABSTRACT
Facing the biggest disaster of this century, the coronavirus (COVID-19) pandemic, every school is inevitably seeking any way to keep its students' learning on schedule. Indeed, using ICT to construct an e-learning system emerges as the necessary step. Based on the strategic fit perspective, this article explores the black-box for how a school can apply and integrate its existing resources to implement an effective e-learning working process using ICT and also generate new capabilities to adapt well to the external challenges a disaster brings. Through the collaboration across different departments, applying ICT tools and designing a rotating way of executing them while considering both learning online and in a practical situation, this e-learning implementation construction offers the case study of KW university and its successful adaptation to the coronavirus challenge. This study divided the e-learning implementation process into three stages, and two frameworks, and an analysis model was also constructed consequently. The key findings and implications of this study, as well as suggestions for future research are also offered. © 2020 ACM.