• COVID-19
• 01 natural sciences close

The 2019 coronavirus disease (COVID-19) has affected more than 200 countries. Wearing masks can effectively cut off the virus spreading route since the coronavirus is mainly spreading by respiratory droplets. However, the common surgical masks cannot be reused, resulting in the increasing economic and resource consumption around the world. Herein, we report a superhydrophobic, photo-sterilize, and reusable mask based on graphene nanosheet-embedded carbon (GNEC) film, with high-density edges of standing structured graphene nanosheets. The GNEC mask exhibits an excellent hydrophobic ability (water contact angle: 157.9°) and an outstanding filtration efficiency with 100% bacterial filtration efficiency (BFE). In addition, the GNEC mask shows the prominent photo-sterilize performance, heating up to 110 °C quickly under the solar illumination. These high performances may facilitate the combat against the COVID-19 outbreaks, while the reusable masks help reducing the economic and resource consumption.Supplementary material (further details of electron cyclotron resonance (ECR) sputtering system, deposition of GNEC film, fabrication of GNEC mask, and characterization of the GNEC mask) is available in the online version of this article at 10.1007/s12274-020-3158-1.

Severe Acute Respiratory Syndrome Coronavirus-2 is a zoonotic virus with a possible origin in bats and potential transmission to humans through an intermediate host. When zoonotic viruses jump to a new host, they undergo both mutational and natural selective pressures that result in non-synonymous and synonymous adaptive changes, necessary for efficient replication and rapid spread of diseases in new host species. The nucleotide composition and codon usage pattern of SARS-CoV-2 indicate the presence of a highly conserved, gene-specific codon usage bias. The codon usage pattern of SARS-CoV-2 is mostly antagonistic to human and bat codon usage. SARS-CoV-2 codon usage bias is mainly shaped by the natural selection, while mutational pressure plays a minor role. The time-series analysis of SARS-CoV-2 genome indicates that the virus is slowly evolving. Virus isolates from later stages of the outbreak have more biased codon usage and nucleotide composition than virus isolates from early stages of the outbreak. Supplementary Information The online version contains supplementary material available at 10.1007/s00239-021-10008-2.

In the wake of the coronavirus disease 2019 (COVID-19) pandemic, staff and students at universities worldwide were forced to swiftly adapt to distance learning in order to continue with tertiary ed...

The ongoing COVID-19 outbreak has expanded rapidly throughout China. Major behavioral, clinical, and state interventions are underway currently to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, have affected COVID-19 spread in China. We use real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation on transmission in cities across China and ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was well explained by human mobility data. Following the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases are still indicative of local chains of transmission outside Wuhan. This study shows that the drastic control measures implemented in China have substantially mitigated the spread of COVID-19. One sentence summary: The spread of COVID-19 in China was driven by human mobility early on and mitigated substantially by drastic control measures implemented since the end of January.

As the COVID-19 pandemic continues to unfold, payers across the USA have stepped up to alleviate patients' financial burden by waiving cost-sharing for COVID-19 testing and treatment. However, there has been no substantive discussion of potential long-term effects of COVID-19 on patient health or their financial and policy implications. After recovery, patients remain at risk for lung disease, heart disease, frailty, and mental health disorders. There may also be long-term sequelae of adverse events that develop in the course of COVID-19 and its treatment. These complications are likely to place additional medical, psychological, and economic burdens on all patients, with lower-income individuals, the uninsured and underinsured, and individuals experiencing homelessness being most vulnerable. Thus, there needs to be a comprehensive plan for preventing and managing post-COVID-19 complications to quell their clinical, economic, and public health consequences and to support patients experiencing delayed morbidity and disability as a result.

Risk mitigation of COVID-19 in the indoor environment requires an articulated strategy for creating a bridge between science and the business community that focuses on knitting together four core capabilities—environmental microbiology, transmission science, building science, and social science—advancing scientific knowledge. The purpose of this article is to share insights from the CLEAN 2020 Summit, which assembled leaders from business, policy, standards development, science, and engineering working to mitigate risk of transmission in the built environment. The Summit worked to assess current challenges and pain points felt by industries from around the globe as well as innovative solutions applied to meet these challenges. Although SARS-CoV-2 and the COVID-19 diseases are unique, the foundation of knowledge to assess and mitigate the risk of viral transmission in the built environment is robust. There are opportunities to improve science and engineering technology solutions, processes, and procedures to better meet the dynamic needs of the evolving pandemic.

Abstract Recent decades have witnessed a steady increase in efforts from a range of actors to facilitate and support meaningful and effective engagement with coastal communities and stakeholders. Indeed, this move towards improved participatory approaches are increasingly framed as being integral to successful and sustainable management of coastal resources and spaces, including in the context of climate adaptation The effectiveness of the processes, structures and frameworks underpinning coastal community engagement has always been subject to external and internal drivers; however, the global threat posed by COVID-19 presented, and continues to present, an unexpected shift in approach, and the need for rapid adaptation by those of us working within these spheres. Using the Coastal Communities Adapting Together (CCAT) project as a case study, we explore how engagement with coastal communities and stakeholders in the project areas of Fingal, Ireland, and Pembrokeshire, Wales, has been impacted and forced to adapt as a result of COVID-19. Through a qualitative data collection process, we explore how project teams across different scales have rapidly adapted their models of community and stakeholder engagement, identify successes and failures, and explore challenges that have been faced. Finally, we consider if the legacy of COVID-19 has provided an opportunity for coastal community engagement approaches being used across the globe to become more diverse, adapting to new technologies and increasing accessibility and effectiveness. Insights identified as fundamental to successful adaptation and enhancing resilience include: a rapid response to change, adoption of a diversity of techniques, broadened participation and supported social learning and knowledge exchange.

Abstract In the field of agriculture, there are many individual micro businesses with low investment capacity and awareness of IT utilization, and it is difficult to obtain a return on investment . In recent years, edge computing and Artificial Intelligence (AI) technologies have attracted a lot of attention in the agricultural industry to cover the labor shortage. Also, safer vegetables are required by peoples due to COVID-19 epidemic and radioactive pollution. In this paper, we propose an agricultural support system called VegeCareAI for agricultural workers. The proposed system supports vegetable classification , plant disease classification and insect pest classification to improve the crops’ productively. The support system can show the growth condition of vegetables. When there are some problems, the VegeCareAI presents information on how to deal with diseases and insect pests. From the results, we found that our proposed VegeCareAI tool has advantage for supporting several crops. For vegetable classification, our training data for 300 epochs predicted six kinds of vegetables correctly. For plant disease classification, for 400 epochs the accuracy is more than 96% accuracy for both potato and corn leaves. For insect pest classification, the accuracy of corn insect pests is more than 73%, but the results of different life cycles showed low classification accuracy , which present a future challenge.