The Dynamic Effects of Perceptions of Dread Risk and Unknown Risk on SNS Sharing Behavior During Emerging Infectious Disease Events: Do Crisis Stages Matter?

In response to the increasing prevalence of emerging infectious disease (EID) threats, individuals are turning to social media platforms to share relevant information in ever greater numbers. In this study, we examine whether risk perceptions related to user-generated content have dynamic impacts on social networking site (SNS) sharing behavior in different crisis stages. To answer this question, we applied psychometric analysis to evaluate how dread risk and unknown risk can characterize EID threats. Drawing broadly on the literature of risk perceptions, self-perception theory, and crisis stages, we relied on microblogs collected from Sina Weibo, utilizing the vector autoregression model to analyze dynamic relationships. We found that perceptions of dread risk have a dominant and immediate impact on SNS sharing behavior in the buildup, breakout, and termination stages of EID events. Perceptions of unknown risk have a dominant and persistent impact on sharing behavior in the abatement stage. The joint effect of these two types of risk perception reveal an antagonism impact on SNS sharing behavior, and perceptions of dread- and unknown risk have interaction effects from the buildup to termination stages of EID events. To check robustness, we analyzed keywords related to perceptions of dread- and unknown risk. The results of this study support the empirical application of Slovic’s risk perception framework for understanding the characteristics of EID threats and provide a picture of how perceptions of dread- and unknown risk exert differential time-varying effects on SNS sharing behavior during EID events. We also discuss theoretical and practical implications for the crisis management of EID threats. This study is among the first that uses user-generated content in social media to investigate dynamic risk perceptions and their relationship to SNS sharing behavior, which may help provide a basis for timely and efficient risk communication

Systematic elucidation of independently modulated genes in Lactiplantibacillus plantarum reveals a trade-off between secondary and primary metabolism

Lactiplantibacillus plantarum is a probiotic bacterium widely used in food and health industries, but its gene regulatory information is limited in existing databases, which impedes the research of its physiology and its applications. To obtain a better understanding of the transcriptional regulatory network of L. plantarum, independent component analysis of its transcriptomes was used to derive 45 sets of independently modulated genes (iModulons). Those iModulons were annotated for associated transcription factors and functional pathways, and active iModulons in response to different growth conditions were identified and characterized in detail. Eventually, the analysis of iModulon activities reveals a trade-off between regulatory activities of secondary and primary metabolism in L. plantarum

FaceScape: 3D Facial Dataset and Benchmark for Single-View 3D Face Reconstruction

In this paper, we present a large-scale detailed 3D face dataset, FaceScape, and the corresponding benchmark to evaluate single-view facial 3D reconstruction. By training on FaceScape data, a novel algorithm is proposed to predict elaborate riggable 3D face models from a single image input. FaceScape dataset provides 18,760 textured 3D faces, captured from 938 subjects and each with 20 specific expressions. The 3D models contain the pore-level facial geometry that is also processed to be topologically uniformed. These fine 3D facial models can be represented as a 3D morphable model for rough shapes and displacement maps for detailed geometry. Taking advantage of the large-scale and high-accuracy dataset, a novel algorithm is further proposed to learn the expression-specific dynamic details using a deep neural network. The learned relationship serves as the foundation of our 3D face prediction system from a single image input. Different than the previous methods, our predicted 3D models are riggable with highly detailed geometry under different expressions. We also use FaceScape data to generate the in-the-wild and in-the-lab benchmark to evaluate recent methods of single-view face reconstruction. The accuracy is reported and analyzed on the dimensions of camera pose and focal length, which provides a faithful and comprehensive evaluation and reveals new challenges. The unprecedented dataset, benchmark, and code have been released to the public for research purpose.Comment: 14 pages, 13 figures, journal extension of FaceScape(CVPR 2020). arXiv admin note: substantial text overlap with arXiv:2003.1398

Systematic elucidation of independently modulated genes in Lactiplantibacillus plantarum reveals a trade‐off between secondary and primary metabolism

Abstract Lactiplantibacillus plantarum is a probiotic bacterium widely used in food and health industries, but its gene regulatory information is limited in existing databases, which impedes the research of its physiology and its applications. To obtain a better understanding of the transcriptional regulatory network of L. plantarum, independent component analysis of its transcriptomes was used to derive 45 sets of independently modulated genes (iModulons). Those iModulons were annotated for associated transcription factors and functional pathways, and active iModulons in response to different growth conditions were identified and characterized in detail. Eventually, the analysis of iModulon activities reveals a trade‐off between regulatory activities of secondary and primary metabolism in L. plantarum

Study on the Effect of Rock Mass Structure on CO₂ Transient Fissure Excavation

As a new rock breaking method, CO2 transient cracking has been widely used in rock excavation projects in recent years. However, in the actual construction process, there are often situations where the fracturing effect varies due to different rock mass structures. Through theoretical analysis and on-site cracking tests, this article studies the effect of CO2 transient cracking under the control of different rock mass structures. The results show that: (1) the dynamic compressive strength of rock directly determines the number and range of dynamic impact fractures; the original fractures of rock mass and those caused by dynamic impact in the first stage jointly determine the effect of high-pressure gas expansion in the second stage. (2) The arrangement of holes along the strata is conducive to the action of high-pressure expanding gas along the soft structural plane in the rock mass, which is conducive to the fracturing of the rock mass; the amount of crack formation is small, but the influence range is large. (3) The cracking effect of carbon dioxide transient cracking applied to massive rock mass is better than that of monolithic rock mass, while the cracking effect of layered rock mass with soil interlayer is poor. The research results are of great significance for improving the effectiveness of carbon dioxide transient-induced cracking excavation and guiding actual construction

A novel approach for rapid high-throughput selection of recombinant functional rat monoclonal antibodies

Abstract Background Most monoclonal antibodies against mouse antigens have been derived from rat spleen-mouse myeloma fusions, which are valuable tools for purposes ranging from general laboratory reagents to therapeutic drugs, and yet selecting and expressing them remains a time-consuming and inefficient process. Here, we report a novel approach for the rapid high-throughput selection and expression of recombinant functional rat monoclonal antibodies with different isotypes. Results We have developed a robust system for generating rat monoclonal antibodies through several processes involving simultaneously immunizing rats with three different antigens expressing in a mixed cell pools, preparing hybridoma cell pools, in vitro screening and subsequent cloning of the rearranged light and heavy chains into a single expression plasmid using a highly efficient assembly method, which can decrease the time and effort required by multiple immunizations and fusions, traditional clonal selection and expression methods. Using this system, we successfully selected several rat monoclonal antibodies with different IgG isotypes specifically targeting the mouse PD-1, LAG-3 or AFP protein from a single fusion. We applied these recombinant anti-PD-1 monoclonal antibodies (32D6) in immunotherapy for therapeutic purposes that produced the expected results. Conclusions This method can be used to facilitate an increased throughput of the entire process from multiplex immunization to acquisition of functional rat monoclonal antibodies and facilitate their expression and feasibility using a single plasmid