Different countries have introduced different urgent policies to control the spread of the novel coronavirus. The compliance behavior of these anti-epidemic policies has always been an important concern to governments, and its effects need to be tested. In recent years, many scholars have paid attention to the mechanism and intervention of policy compliance behavior, which helps to explain the mechanism of anti-epidemic compliance behavior, and to improve the effectiveness of anti-epidemic policy. Therefore, considering the characters of youth groups in the context of the novel coronavirus, this study takes campus anti-epidemic compliance behavior as the research topic, based on 680 effective samples of college students in China, in order to examine the effectiveness of these policies using an investigation experiment. This study revealed that the ‘Nudge’ policy instrument was the most effective way to guide individuals’ behavior during the coronavirus outbreak, the ‘Sermon’ instrument was the least recognized, and the ‘Whip’ instrument (a traditional and classical policy instrument) had its normal effect on individuals’ behavior. Additionally, it found that high accessibility in policy implementation results in more significant policy behavior. By taking the effects of different policy behaviors into consideration, governments may produce better and more effective policy implementation and compliance during the anti-epidemic period.

Heterogeneity and limited comprehension of chronic autoimmune disease pathophysiology cause accurate diagnosis a challenging process. With the increasing resources of single-cell sequencing data, a reasonable way could be found to address this issue. In our study, with the use of large-scale public single-cell RNA sequencing (scRNA-seq) data, analysis of dataset integration (3.1 × 105 PBMCs from fifteen SLE patients and eight healthy donors) and cellular cross talking (3.8 × 105 PBMCs from twenty-eight SLE patients and eight healthy donors) were performed to identify the most crucial information characterizing SLE. Our findings revealed that the interactions among the PBMC subpopulations of SLE patients may be weakened under the inflammatory microenvironment, which could result in abnormal emergences or variations in signaling patterns within PBMCs. In particular, the alterations of B cells and monocytes may be the most significant findings. Utilizing this powerful information, an efficient mathematical model of unbiased random forest machine learning was established to distinguish SLE patients from healthy donors via not only scRNA-seq data but also bulk RNA-seq data. Surprisingly, our mathematical model could also accurately identify patients with rheumatoid arthritis and multiple sclerosis, not just SLE, via bulk RNA-seq data (derived from 688 samples). Since the variations in PBMCs should predate the clinical manifestations of these diseases, our machine learning model may be feasible to develop into an efficient tool for accurate diagnosis of chronic autoimmune diseases.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a lineage B coronavirus, causing the worldwide outbreak of Corona Virus Disease 2019 (COVID-19). Despite genetically closed to SARS-CoV, SARS-CoV-2 seems to possess enhanced infectivity and subtle different clinical features, which may hamper the early screening of suspected patients as well as the control of virus transmission. Unfortunately, there are few tools to predict the potential target organ damage and possible clinical manifestations caused by such novel coronavirus. Methods: To solve this problem, we use the online single-cell sequence datasets to analyze the expression of the major receptor in host cells that mediates the virus entry, including angiotensin converting enzyme 2 (ACE2), and its co-expressed membrane endopeptidases. Results: The results indicated the differential expression of ADAM10 and ADAM17 might contribute to the ACE2 shedding and affect the membrane ACE2 abundance. We further confirm a putative furin-cleavage site reported recently in the spike protein of SARS-CoV-2, which may facilitate the virus-cell fusion. Based on these findings, we develop an approach that comprehensively analyzed the virus receptor expression, ACE2 shedding, membrane fusion activity, virus uptake and virus replication to evaluate the infectivity of SARS-CoV-2 to different human organs. Conclusion: Our results indicate that, in addition to airway epithelia, cardiac tissue and enteric canals are susceptible to SARS-CoV-2 as well.

In order to accelerate the rapid development of the automobile manufacturing industry and improve the competitiveness, a welding control system of automobile dashboard bracket based on Siemens PLC is designed. The welding control unit of automobile dashboard bracket takes Siemens PLC as the control core, to realize real-time control with welding fixtures, robots, the sliding door with monitoring, the shutter door and other parts through a touch screen. The entire design system realizes welding control of automobile dashboard bracket, meeting production process requirements, effectively reducing costs and improving production efficiency.

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