Exploring Influential Factors of Free-Floating Bike-Sharing Usage Frequency before and after COVID-19

In order to better understand the impact of COVID-19 on the free-floating bike-sharing (FFBS) system and the potential role of FFBS played in the pandemic period, this study explores the impact mechanism of travel frequency of FFBS users before and after the pandemic. Using the online questionnaire collected in Nanjing, China, we first analyze the changes of travel frequency, travel distance, and travel duration in these two periods. Then, two ordered logit models are applied to explore the contributing factors of the weekly trip frequency of FFBS users before and after COVID-19. The results show that: (1) While the overall travel duration and travel distance of FFBS users decreased after the pandemic, the trip frequency of FFBS users increased as the travel duration increased. (2) Since COVID-19, attitude perception variables of the comfort level and the low travel price have had significantly positive impacts on the weekly trip frequency of FFBS users. (3) Respondents who use FFBS as a substitution for public transport are more likely to travel frequently in a week after the outbreak of COVID-19. (4) The travel time in off-peak hours of working days, weekends, and holidays has a significantly positive correlation with the trip frequency of FFBS users. Finally, several relevant policy recommendations and management strategies are proposed for the operation and development of FFBS during the similar disruptive public health crisis.

Sustainable production of dimethyl-protected cyclic lysine over Pd/m-Al2O3-Si catalysts and its application in synthesis of antibacterial nylon‑6 copolymers

• Pd/ m- Al 2 O 3 -Si catalyst exhibited high efficiency in converting α- amino -ε- caprolactam (α- ACL) to dimethyl-protected cyclic lysine (DMCL). • The lack of Brönsted acid sites on Pd/ m- Al 2 O 3 -Si surface facilitated the formation of DMCL and suppressed undesirable reaction process. • Pd/ m- Al 2 O 3 -Si catalyst with microspherical morphology performed excellent stability and physical strength during the catalytic process. • The nylon‑6 copolymers produced from the as-synthesized DMCL exhibited a great potential in the synthesis of self-cleaning antibacterial materials. Antibacterial monomers are prerequisites for synthesizing antibacterial polymers, especially during the current COVID-19 pandemic. Dimethyl-protected cyclic lysine (DMCL) is a promising functional monomer for nylon-6 based self-cleaning antibacterial polymers. However, the production of DMCL still faces formidable challenges, such as harsh reaction conditions and low catalyst activities. In this study, we developed a Pd/ m -Al 2 O 3 -Si catalyst, which exhibited high efficiency in converting α -amino- ε -caprolactam (α -ACL) to DMCL, affording a yield of as high as 97.1% at 100 °C and 1 MPa H 2. The lack of Brönsted acid sites on the catalyst surface facilitated the formation of DMCL and suppressed undesirable hydrolysis or cracking by-products from the lactam-based reactant. The recycled experiments showed that Pd/ m -Al 2 O 3 -Si performed excellent stability and physical strength with essentially no damage to its microspheres after the reaction. The nylon‑6 copolymers produced from the as-synthesized DMCL exhibited similar structure and thermal stability with pure nylon-6, showing great potential in synthesizing the self-cleaning antibacterial polymers. This work provides a sustainable and efficient method for producing DMCL and other lysine-based antibacterial monomers, showing a great prospect for the utilization of bio-based chemicals in synthesizing functional polymers. [ FROM AUTHOR] Copyright of Chemical Engineering Journal is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Early Stage Risk Identification and Governance of Major Emerging Infectious Diseases: A Double-Case Study Based on the Chinese Context.

Purpose: Based on the Chinese context, this study uses severe acute respiratory syndrome (SARS) and coronavirus disease 2019 (COVID-19) outbreaks as examples to identify the risk factors that lead to the major emerging infectious diseases outbreak, and put forward risk governance strategies to improve China's biosecurity risk prevention and control capabilities. Material and Methods: This study combines grounded theory and WSR methodology, and utilizes the NVivo 12.0 qualitative analysis software to identify the risk factors that led to the major emerging infectious diseases outbreak. The research data was sourced from 168 publicly available official documents, which are highly authoritative and reliable. Results: This study identified 10 categories of Wuli risk factors, 6 categories of logical Shili risk factors, and 8 categories of human Renli risk factors that contributed to the outbreak of major emerging infectious diseases. These risk factors were distributed across the early stages of the outbreak, and have different mechanisms of action at the macro and micro levels. Conclusion: This study identified the risk factors that lead to the outbreak of major emerging infectious disease, and discovered the mechanism of the outbreak at the macro and micro levels. At the macro level, Wuli risk factors are the forefront antecedents that lead to the outbreak of the crisis, Renli factors are the intermediate regulatory factors, and Shili risk factors are the back-end posterior factors. At the micro level, there are risk coupling, risk superposition, and risk resonance interactions among various risk factors, leading to the outbreak of the crisis. Based on these interactive relationships, this study proposes risk governance strategies that are helpful for policymakers in dealing with similar crises in the future.

A spike-trimer protein-based tetravalent COVID-19 vaccine elicits enhanced breadth of neutralization against SARS-CoV-2 Omicron subvariants and other variants.

Multivalent vaccines combining crucial mutations from phylogenetically divergent variants could be an effective approach to defend against existing and future SARS-CoV-2 variants. In this study, we developed a tetravalent COVID-19 vaccine SCTV01E, based on the trimeric Spike protein of SARS-CoV-2 variants Alpha, Beta, Delta, and Omicron BA.1, with a squalene-based oil-in-water adjuvant SCT-VA02B. In the immunogenicity studies in naïve BALB/c and C57BL/6J mice, SCTV01E exhibited the most favorable immunogenic characteristics to induce balanced and broad-spectrum neutralizing potencies against pre-Omicron variants (D614G, Alpha, Beta, and Delta) and newly emerging Omicron subvariants (BA.1, BA.1.1, BA.2, BA.3, and BA.4/5). Booster studies in C57BL/6J mice previously immunized with D614G monovalent vaccine demonstrated superior neutralizing capacities of SCTV01E against Omicron subvariants, compared with the D614G booster regimen. Furthermore, SCTV01E vaccination elicited naïve and central memory T cell responses to SARS-CoV-2 ancestral strain and Omicron spike peptides. Together, our comprehensive immunogenicity evaluation results indicate that SCTV01E could become an important COVID-19 vaccine platform to combat surging infections caused by the highly immune evasive BA.4/5 variants. SCTV01E is currently being studied in a head-to-head immunogenicity comparison phase 3 clinical study with inactivated and mRNA vaccines (NCT05323461).

Severe acute respiratory syndrome coronavirus 2 virus-like particles induce dendritic cell maturation and modulate T cell immunity.

Dendritic cells (DCs) are professional antigen-presenting cells that play an important role in both innate and acquired immune responses against pathogens. However, the role of DCs in coronavirus disease 2019 (COVID-19) is unclear. Virus-like particles (VLPs) that structurally mimic the original virus are one of the candidates COVID-19 vaccines. In the present study, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) VLPs were used as an alternative to live virus to evaluate the interaction of the virus with DCs. The results revealed that SARS-CoV-2 VLPs induced DC maturation by augmenting cell surface molecule expression (CD80, CD86, and major histocompatibility complex class II (MHC-II)) and inflammatory cytokine production (tumor necrosis factor-α, interleukin (IL)-1ß, IL-6, and IL-12p70) in DCs via the mitogen-activated protein kinase and nuclear factor-κB signaling pathways. In addition, mature DCs induced by SARS-CoV-2 VLPs promoted T cell proliferation, which was dependent on VLPs concentration. Our results suggest that SARS-CoV-2 VLPs regulate the immune response by interacting with DCs. These findings will improve the understanding of SARS-CoV-2 pathogenesis and SARS-CoV-2 vaccine development.

Risk Transmission Mechanism of Domestic Cluster Epidemic Caused by Overseas Imported Cases: Multiple Case Studies Based on Grounded Theory.

The continued severity of the global epidemic situation has led to a rising risk of imported cases in China, and domestic cluster epidemic events caused by imported cases have occurred from time to time, repeatedly causing nation-wide disruption. To deeply explain this phenomenon, this study adopted the grounded theory method, using the 5·21 Guangzhou COVID-19 outbreak and 7·20 Nanjing COVID-19 outbreak as examples to study the risk transmission mechanism of domestic cluster epidemic caused by overseas imported cases. The study found that the risk factors for the phenomenon mainly include the following seven aspects: external protection, operations and supervision, international and domestic environment, contaminated objects, virus characteristics, management efficacy, and individual factors. These risk factors together constitute the "detonator", "risk source", "risk carrier," and "risk amplifier" in the risk transmission process. In addition, this study also found that the transmission mechanism of domestic clusters caused by imported cases is a process of secondary risk amplification. The increase in risk carriers leads to a surge in secondary risks compared with the first, which leads to the outbreak of domestic clusters. Finally, based on the characteristics of the transmission mechanism and risk transmission components, this study provides some suggestions on risk mitigation for public departments to optimize China's epidemic prevention policies.

Data-Driven Building Energy Consumption Prediction Model Based on VMD-SA-DBN

Prediction of building energy consumption using mathematical modeling is crucial for improving the efficiency of building energy utilization, assisting in building energy consumption planning and scheduling, and further achieving the goal of energy conservation and emission reduction. In consideration of the non-linear and non-smooth characteristics of building energy consumption time series data, a short-term, hybrid building energy consumption prediction model combining variational mode decomposition (VMD), a simulated annealing (SA) algorithm, and a deep belief network (DBN) is proposed in this study. In the proposed VMD-SA-DBN model, the VMD algorithm decomposes the time series into different modes to reduce the fluctuation of the data. The SA-DBN prediction model is built for each mode separately, and the DBN network structure parameters are optimized by the SA algorithm. The prediction results of each model are aggregated and reconstructed to obtain the final prediction output. The validity and prediction performance of the proposed model is evaluated on a publicly available dataset, and the results show that the proposed new model significantly improves the accuracy and stability of building energy consumption prediction compared with several typical machine learning methods. The mean absolute percent error (MAPE) of the VMD-SA-DBN model is 63.7%, 65.5%, 46.83%, 64.82%, 44.1%, 36.3%, and 28.3% lower than that of the long short-term memory (LSTM), gated recurrent unit (GRU), VMD-LSTM, VMD-GRU, DBN, SA-DBN, and VMD-DBN models, respectively. The results will help managers formulate more-favorable low-energy emission reduction plans and improve building energy efficiency.

Racial/Ethnic Inequity in Transit-Based Spatial Accessibility to COVID-19 Vaccination Sites.

With the ongoing spread of COVID-19, vaccination stands as an effective measure to control and mitigate the impact of the disease. However, due to the unequal distribution of COVID-19 vaccination sites, people can have different levels of spatial accessibility to COVID-19 vaccination. This study adopts an improved gravity-based model to measure the racial/ethnic inequity in transit-based spatial accessibility to COVID-19 vaccination sites in the Chicago Metropolitan Area. The results show that Black-majority and Hispanic-majority neighborhoods have significantly lower transit-based spatial accessibility to COVID-19 vaccination sites compared to White-majority neighborhoods. This research concludes that minority-dominated inner-city neighborhoods, despite better public transit coverage, are still disadvantaged in terms of transit-based spatial accessibility to COVID-19 vaccination sites. This is probably due to their higher population densities, which increase the competition for the limited supply of COVID-19 vaccination sites within each catchment area.

A Bivalent COVID-19 Vaccine Based on Alpha and Beta Variants Elicits Potent and Broad Immune Responses in Mice against SARS-CoV-2 Variants.

With the emergence and rapid spread of new pandemic variants, especially variants of concern (VOCs), the development of next-generation vaccines with broad-spectrum neutralizing activities is of great importance. In this study, SCTV01C, a clinical stage bivalent vaccine based on trimeric spike extracellular domain (S-ECD) of SARS-CoV-2 variants Alpha (B.1.1.7) and Beta (B.1.351) with a squalene-based oil-in-water adjuvant was evaluated in comparison to its two corresponding (Alpha and Beta) monovalent vaccines in mouse immunogenicity studies. The two monovalent vaccines induced potent neutralizing antibody responses against the antigen-matched variants, but drastic reductions in neutralizing antibody titers against antigen-mismatched variants were observed. In comparison, the bivalent vaccine SCTV01C induced relatively higher and broad-spectrum cross-neutralizing activities against various SARS-CoV-2 variants, including the D614G variant, VOCs (B.1.1.7, B.1.351, P.1, B.1.617.2, B.1.1.529), variants of interest (VOIs) (C.37, B.1.621), variants under monitoring (VUMs) (B.1.526, B.1.617.1, B.1.429, C.36.3) and other variants (B.1.618, 20I/484Q). All three vaccines elicited potent Th1-biased T-cell immune responses. These results provide direct evidence that variant-based multivalent vaccines could play important roles in addressing the critical issue of reduced protective efficacy against the existing and emerging SARS-CoV-2 variants.

Using Pandemic Data to Examine the Government's Pandemic Prevention Measures and Its Support Policies for Vulnerable Groups.

The outbreak of COVID-19 and the uncertainty it brings have created enormous pressure on governments to control the global pandemic and restore economic growth. It is an inevitable choice for governments of various countries to seek to control the pandemic and to provide support such as subsidies to people who lose their jobs or cannot work. However, governments should evaluate their pandemic policies to determine their effectiveness. To maintain social stability and help vulnerable groups, governments also must determine when subsidies are needed and when these support policies should be withdrawn. This research demonstrates that the administration of vaccines and the wearing of masks have a relatively limited impact on preventing the spread of the COVID-19 virus. By contrast, strict school closure policies combined with personal movement restrictions are more helpful in mitigating the spread of the virus. Compared with vaccine policies and wearing masks, controlling internal movement is the most effective way to manage the pandemic in schools. Additionally, economic support such as subsidies for the unemployed and underemployed is not only conducive to prevention of the virus' spread but also to economic recovery and social stability. When the pandemic is brought under control, economic support for vulnerable groups can be gradually reduced or even withdrawn.

Production of SARS-CoV-2 Virus-Like Particles in Insect Cells.

Coronavirus disease (COVID-19) causes a serious threat to human health. Virus-like particles (VLPs) constitute a promising platform in SARS-CoV-2 vaccine development. In this study, the E, M, and S genes were cloned into multiple cloning sites of a new triple expression plasmid with one p10 promoter, two pPH promoters, and three multiple cloning sites. The plasmid was transformed into DH10 BacTMEscherichia coli competent cells to obtain recombinant bacmid. Then the recombinant bacmid was transfected in ExpiSf9TM insect cells to generate recombinant baculovirus. After ExpiSf9TM cells infection with the recombinant baculovirus, the E, M, and S proteins were expressed in insect cells. Finally, SARS-CoV-2 VLPs were self-assembled in insect cells after infection. The morphology and the size of SARS-CoV-2 VLPs are similar to the native virions.