Preoperative evaluation and timing of surgery for adult patients after covid-19 infection: Recommendations of peking union medical college hospital (2023).

With the adjustment of China's epidemic prevention and control guidelines regarding coronavirus disease of 2019(COVID-19), the preoperative evaluation and timing of surgery for patients after COVID-19 infection have become the focus of attention for both healthcare workers and patients. Based on the latest study and related clinical experience, Peking Union Medical College Hospital (PUMCH) has therefore compiled this multidisciplinary, evidence-based recommendation for concise, individualized, and practical preoperative evaluation and timing of surgery for patients after COVID-19 infection. The recommendations emphasize patients' COVID-19 infection history, the severity of symptoms, and medical/physiologic recovery status during preoperative evaluation. The determination of appropriate length of time between recovery from COVID-19 and surgery/procedure should take into account of patients' underlying health conditions, the severity of the COVID-19 infection course, and the types of surgery and anesthesia scheduled, to minimize postoperative complications. The recommendations are intended to aid healthcare workers in evaluating these patients, scheduling them for the optimal timing of surgery, and optimizing perioperative management and postoperative recovery.Copyright © 2023, Peking Union Medical College Hospital. All rights reserved.

ELASTIC: Edge Workload Forecasting based on Collaborative Cloud-Edge Deep Learning

With the rapid development of edge computing in the post-COVID19 pandemic period, precise workload forecasting is considered the basis for making full use of the edge limited resources, and both edge service providers (ESPs) and edge service consumers (ESCs) can benefit significantly from it. Existing paradigms of workload forecasting (i.e., edge-only or cloud-only) are improper, due to failing to consider the inter-site correlations and might suffer from significant data transmission delays. With the increasing adoption of edge platforms by web services, it is critical to balance both accuracy and efficiency in workload forecasting. In this paper, we propose ELASTIC, which is the first study that leverages a cloud-edge collaborative paradigm for edge workload forecasting with multi-view graphs. Specifically, at the global stage, we design a learnable aggregation layer on each edge site to reduce the time consumption while capturing the inter-site correlation. Additionally, at the local stage, we design a disaggregation layer combining both the intra-site correlation and inter-site correlation to improve the prediction accuracy. Extensive experiments on realistic edge workload datasets collected from China's largest edge service provider show that ELASTIC outperforms state-of-the-art methods, decreases time consumption, and reduces communication cost. © 2023 ACM.

Severe coronavirus disease 2019: Is it acute respiratory distress syndrome?.

The outbreak of coronavirus disease 2019 (COVID-19) poses a major global threat. Although we have learned a lot about COVID-19 from clinical studies and autopsy findings, there is still a lot of confusion. One of the biggest controversies is whether severe COVID-19 can be diagnosed as acute respiratory distress syndrome (ARDS). Severe COVID-19 may meet ARDS Berlin criteria, but it differs from ARDS caused by other etiologies and is characterized by later onset time, relatively normal lung compliance in some cases, significant hypercapnia, lung CT findings, and significant coagulation activation in lungs. Some reports classify COVID-19-related ARDS into different phenotypes, but most of them are based on observational studies, with high bias. To date, we have not fully understood the pathophysiology of COVID-19-related ARDS. Premature phenotyping may mislead mechanical ventilation strategies. We expect evidence from large clinical studies.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.

Attitudes amidst the pandemic: Virtual delivery of care in an adult cystic fibrosis population

Background: The COVID-19 pandemic has altered how we deliver care to people with cystic fibrosis (CF) across the spectrum of disease severity. Because of lockdowns and avoiding exposure to COVID-19 by limiting inperson clinic visits, clinical care has pivoted from standard practices to virtual care in combination with in-person traditional visits. This approach has allowed patients to be monitored and treated in a timely manner. Such virtual visits have the advantage of reducing the time commitment for clinic visits because the patient does not have to travel to and from the hospital, but virtual care lacks the ability to conduct a physical examination and to obtain objective and standardized testing of key measurements known to be associated with health outcomes in CF. The objective of this study was to evaluate the attitude of patients to virtual delivery of care and their comfort level with such care. Method(s): This is a prospective, cross-sectional survey of adults with CF who are followed at St. Michael's Adult CF Center in Toronto, Canada. An online survey was created using SurveyMonkey to assess attitudes toward and satisfaction with virtual care. The survey was emailed to participants and included the Canadian CF Registry ID;a reminder email sent a week later. Baseline demographic and clinical data were obtained from the Canadian CF Registry and presented as median (range) or proportions as appropriate. Questions using a 3-point Likert scale will be categorized into agree, neutral, and disagree. Result(s): A total of 210 participants (53.0% female) completed the survey (median age 37.8, range 19.2-78.9). Median age of diagnosis was 2.2, 95.7% were Caucasian, 76.0% had completed post-secondary education, 63.0% were employed and 11.0% were students, 75% were pancreatic insufficient, 39.0% had CF-related diabetes, and 12.4% were post lung-transplant. Median percentage predicted forced expiratory volume in 1 second was 65.8% (range 17.9-126.9%), and median body mass index was 23.6 kg/m2 (range 15.5-45.7 kg/m2). Eighty-one percent of respondents had had a virtual visit before completing the survey. Sixty percent of respondents felt that in-person visits were the preferred way of completing a medical assessment, and 27.0% preferred virtual visits. Seventy-three percent felt it was important for the virtual visit to occur at the booked time, 59.0% had concerns that their lung function was not assessed during virtual visits, 46.0% felt they were losing the benefits of allied health team assessments with virtual visits, and 40.0% worried that their health would decline if primarily seen virtually. Just over half of respondents wanted to continue with virtual visits in some capacity after the pandemic. The optimal proportion of in-person visits was felt to be 50.0%. More than 85% of respondents were comfortable with technology (phone or computer) and had reliable access to the Internet to conduct virtual visits. Seventy percent of people would like to have access to a home spirometer, but cost was a barrier. Conclusion(s): From the patient's perspective, in-person visits were still the preferred way to complete a medical assessment, which seemed to be driven by concerns over lack of methods for assessment, particularly lung function, and access to the multidisciplinary team. Home spirometers, if freely available, might increase comfort with virtual appointments.Copyright © 2022, European Cystic Fibrosis Society. All rights reserved

How does indoor physical environment differentially affect learning performance in various classroom types?

Classroom indoor physical environment (CIPE) crucially impacts learning performance (LP). Along with the extended school hours caused by COVID-19, an investigation was conducted at Zhejiang Sci-Tech University to explore the effect of CIPE on LP in different classroom types under natural working condition of transitional seasons. Based on a six-day physical environment measurement and learning performance test, then five CIPE parameters and three LP indicators of four learning abilities were obtained. Through the statistical analysis, the results demonstrated that all CIPE parameters had some correlation or influence on LP, briefly, (1) Low carbon dioxide concentration (CCD, below 700 ppm) was a positive significant factor for all learning abilities, and relative humidity (RH) was a negative factor for comprehension memory ability (CMA) (significant) and logic deduction ability (LDA) (general) to varying degrees, with center illumination (Ic) being a positive significant factor for CMA only. (2) Deeper abilities, like CMA and LDA, were more susceptible to air temperature (Ta) and RH, with the former being positive and the latter being negative. (3) Compared to other types, LP in compact classrooms was more vulnerable to CIPE parameters, such as the positive influence of Ta and CCD, due to the greater variation in CIPE. The findings revealed the differential relationships between the CIPE and LP in various classroom types, guiding classroom design that couples the dual optimization of CIPE and LP. Limitations remain, however, and need to be supplemented by more future research, e.g. year-round experiments and medical instrumentation assistance. © 2023 Elsevier Ltd

Application of OMO Teaching Mode in Music Education in Colleges

With the development of COVID-19, more and more courses begin to be transferred to online teaching. The OMO teaching mode that focuses on offline teaching within a certain period of time and completes online teaching interaction at a later stage has become a trend. Based on the current teaching practice of music education in Colleges and universities, the paper combines teaching with Internet new media technology under the current environmental situation, realizes the new mode of offline and online joint teaching, realizes student-centered unlimited learning, completes the informatization and real-Time teaching, and improves the teaching results. © 2022 ACM.

An inquiry into the Pakistani statecraft in tackling COVID-19

As the second largest country in South Asia, Pakistan has succeeded relatively well in tackling COVID-19 after it broke out in 2020. Due to this, it is necessary to inquire into Pakistan's statecraft to find out how it responded to the pandemic issue, first domestically and then globally. As one of the key neighboring countries of China where the large-scale pandemic started, Pakistan has been very vulnerable to the epidemic. However, the Pakistani government led by Imran Khan has achieved a remarkable record in controlling COVID-19. No doubt, the domestic progress in Pakistan is destined to enhance its reputation abroad. For example, the international community has extended encouraging words and deeds to Pakistan, while some developed EU countries have policies designed by Pakistani Goverment because Islamabad has adopted successful social security and financial stimulus strategies. This study aims to give a balanced understanding of what policy, approaches, and strategies have been used by the current ruling elites of Pakistan;and how the domestic achievements have effectively bolstered its prestigious image on the global stage. © The Author(s) 2023.

A novel neural network model fusion approach for improving medical named entity recognition in online health expert question-answering services

Because of the frequent occurrence of chronic diseases, the COVID-19 pandemic, etc., online health expert question-answering (HQA) services have been unable to cope with the rapidly increasing demand for online consultations. Building a virtual health assistant based on medical named entity recognition (NER) can effectively assist with the consultation process, but the unstandardized expressions within HQA text pose a serious challenge for medical NER tasks. The main goal of this study is to propose a novel deep medical NER approach based on a collaborative decision strategy (CDS), i.e., co_decision_NER (CDN), that can identify standard and nonstandard medical entities in the HQA context. We collected 10,000 question–answer pairs from HaoDF, extracted medical entities from 15 entity categories, and used a CDS to fuse the advantages of different NER models. Ultimately, CDN achieved a performance (precision = 84.50%, recall = 84.30%, F1 = 84.40%) that was significantly better than that of the state-of-the-art (SOTA) method. Our empirical analysis suggests that the entity types Disease (DIS), Sign (SIG), Test (TES), Drug (DRU), Surgery (SUR), Precaution (PRE), and Region (REG) can be most easily expressed arbitrarily in the doctor–patient interaction scenario of HQA services. In addition, CDN can identify not only standard but also nonstandard medical entities, effectively alleviating the severe out-of-vocabulary (OOV) problem faced by HQA services when performing medical NER tasks. The core contribution of this study is the development of a novel neural network model fusion algorithm that can improve the performance of entity recognition in medical domain-specific tasks. © 2023 Elsevier Ltd

Prussian Blue@Zeolitic imidazolate framework composite toward solar-triggered biodecontamination

Metal-organic frameworks (MOFs) featuring composition and bandstructure diversity, are an emerging class of photoresponsive disinfectants. In this study, we demonstrated the superiority of core–shell arranged photoactive MOFs (prussian blue (PB) and zeolitic imidazolate framework (ZIF-8)) for pathogen inactivation in terms of biocidal efficiency and broad-spectrum sensitivity. Reactive oxygen species (ROS) production was significantly promoted after the integration of PB due to the photosensitization effect and initiation of in situ Fenton reaction. Favorably, another inactivation channel was also opened owing to the unique photothermal effect of PB. Attributed to the facilitated ROS intracellular penetration by heat, the composite outperforms not only individual component but anatase TiO2 in pathogen elimination. Specifically, the Staphylococcus aureus (S. aureus) inactivation efficiency of the composite (6.6 log) is 2, 1.8 and 5.1 times higher than that of PB (3.3 log), ZIF-8 (3.7 log) and TiO2 (1.3 log) over 45 min of simulated sunlight illumination. Significantly, the infectivity of Bacillus anthracis and murine coronavirus in droplets on composite-coated filter surface could be greatly reduced (approximately 3 log reduction in colony number/coronavirus titer) within few minutes of solar exposure, indicative of the great potential of MOF composites toward life-threatening microbial infection prevention. © 2022 Elsevier B.V.

Investigation on the cross-infection control performance of interactive cascade ventilation in multi-scenario of winter

With the wide spread of COVID-19, numerous cases demonstrate that proper ventilation method can reduce the cross-infection risk obviously. Interactive cascade ventilation (ICV) as a recently proposed ventilation method, the advantage of indoor environment construction has been proven. However, few studies are conducted to investigate the virus prevention and control characteristics of ICV, which is particularly important under epidemic normalizing. Hence, this study explored and compared the cross-infection control performance of three ventilation strategies, namely mixing ventilation (MV), stratum ventilation (SV), and interactive cascade ventilation (ICV), with a validated CFD model. A typical office was selected as the background scene, where an infected person coughs, sneezes with standing or sitting at different positions. Exposure doses, health infection risk, and disease burden (DB) were employed as the evaluation indicators under different ventilation methods of multi-scenario. The research results indicated that the average aerosol exposure dose among the human respiratory region under ICV was 0.29 g/day, which was reduced by 67 % and 50 % compared with MV and SV. In addition, only in ICV can the health infection risk meets the EPA standard. The average disease health burden for exposed persons under ICV was 0.93 × 10−6 DALYs pppy, which was 37 % and 70 % lower than SV and MV. The findings obtained from this study confirm that ICV performs excellently in reducing the cross-infection risk, providing the theoretical basis for future epidemic prevention and control. © 2022 Elsevier Ltd

Monitoring the impact of the COVID-19 lockdown on air quality in Lanzhou: Implications for future control strategies

China implemented a one-month lockdown after the 2020 Spring Festival to prevent the spread of COVID-19. The closure measures provide a rare opportunity to understand the resulting changes in air pollution levels and to test the effectiveness of previous environmental protection measures. We used the time series decomposition method to quantify the air pollution in Lanzhou during the closure period. The results showed that during the epidemic lockdown period, although the concentration of SO2 in Lanzhou decreased substantially, there was a significant increase in the concentration of O3 (by 19.14%), followed by a gradual return to the normal level. Most of the changes during the COVID-19 lockdown were within the range of fluctuations over the past five years. The trend of decreasing SO2 and CO in 2020 was less than that during 2015–2019, and the continuous decline of the PM10 concentration exceeded expectations. NO2, PM2.5 and O3 maintained the trend of the previous five years. Our results show that temporary social closure measures have a limited effect on improving air quality in Lanzhou, and they emphasize the importance of reducing the O3 concentration in the future. Copyright © 2023 Liu, Yu, Ma, Liu, Dong and Xia.

Four-dimensional variational assimilation for SO2emission and its application around the COVID-19 lockdown in the spring 2020 over China

Emission inventories are essential for modelling studies and pollution control, but traditional emission inventories are usually updated after a few years based on the statistics of "bottom-up"approach from the energy consumption in provinces, cities, and counties. The latest emission inventories of multi-resolution emission inventory in China (MEIC) was compiled from the statistics for the year 2016 (MEIC_2016). However, the real emissions have varied yearly, due to national pollution control policies and accidental special events, such as the coronavirus disease (COVID-19) pandemic. In this study, a four-dimensional variational assimilation (4DVAR) system based on the "top-down"approach was developed to optimise sulfur dioxide (SO2) emissions by assimilating the data of SO2 concentrations from surface observational stations. The 4DVAR system was then applied to obtain the SO2 emissions during the early period of COVID-19 pandemic (from 17 January to 7 February 2020), and the same period in 2019 over China. The results showed that the average MEIC_2016, 2019, and 2020 emissions were 42.2×106, 40.1×106, and 36.4×106 kg d-1. The emissions in 2020 decreased by 9.2 % in relation to the COVID-19 lockdown compared with those in 2019. For central China, where the lockdown measures were quite strict, the mean 2020 emission decreased by 21.0 % compared with 2019 emissions. Three forecast experiments were conducted using the emissions of MEIC_2016, 2019, and 2020 to demonstrate the effects of optimised emissions. The root mean square error (RMSE) in the experiments using 2019 and 2020 emissions decreased by 28.1 % and 50.7 %, and the correlation coefficient increased by 89.5 % and 205.9 % compared with the experiment using MEIC_2016. For central China, the average RMSE in the experiments with 2019 and 2020 emissions decreased by 48.8 % and 77.0 %, and the average correlation coefficient increased by 44.3 % and 238.7 %, compared with the experiment using MEIC_2016 emissions. The results demonstrated that the 4DVAR system effectively optimised emissions to describe the actual changes in SO2 emissions related to the COVID lockdown, and it can thus be used to improve the accuracy of forecasts. Copyright: © 2022 Yiwen Hu et al.

SARS-CoV-2 RBD and its variants can induce platelet activation and clearance: Implications for vaccinations and antibody therapy against COVID-19

Background: Severe COVID-19 is associated with platelet activation, thrombosis, and thrombocytopenia, but the mechanisms remain unclear. Similarly, very rare cases of COVID-19 vaccine-induced-thrombotic-thrombocytopenia (VITT) are also poorly understood. Both infection and vaccination utilize the receptor-binding domain (RBD) of the spike protein for virus-host cell entry and to elicit an immune response, respectively. Interestingly, the RBD contains an RGD integrin-binding motif that may facilitate platelet binding. Aim(s): To determine whether the RBD binds platelets and causes platelet activation/clearance. Method(s): We intravenously injected different doses (0.25, 0.5, 1.0mug/g) of recombinant RBD into mice and measured platelet counts post-injection using a Z2 Series Coulter. Flow cytometry detected RBD/RBD variants binding to platelets and associated platelet activation, apoptosis, and desialylation. Human gel-filtered platelet aggregation was induced by ADP, Collagen and Thrombin. Six anti-RBD monoclonal antibodies (mAbs) were generated and tested in a SARS-CoV-2 Vero cell infection model with the envelop gene quantified by RT-qPCR to determine the virus replication. Result(s): RBD injection caused platelet clearance in a dose-dependent manner. The RBD could also bind to platelets, induce activation and potentiate platelet aggregation in vitro. Our preliminary data also showed the RBD Delta variant has greater potential in inducing platelet activation. Interestingly, the RBD bound beta3-/-platelets ~50% less relative than wildtype mice. Consistently, mutating the RGD motif to RGE, and preincubating platelets with the beta3 inhibitor Eptifibatide also reduced RBD binding to platelets. Our novel anti-RBD mAbs 4F2 and 4H12 inhibited RBD-induced platelet activation and RBD-potentiated platelet aggregation in vitro, and prevented RBD-induced platelet clearance in vivo. Importantly, these mAbs also inhibited SARS-CoV-2 viral replication in a dose-dependent manner. Conclusion(s): Our data demonstrate that the RBD could directly bind to platelets partially via beta3 integrin. RBD-induced platelet activation and clearance may contribute to thrombosis and thrombocytopenia observed in clinical cases of COVID-19 and VITT.

Inorganic Coatings and Films for Antibacterial and Antivirus Functionality

The global pandemic of COVID-19 has caused serious harm to people's healthy life and the normal operation of society. People have paid more attention to the prevention and control of microbial contamination such as bacteria and viruses. Blocking the spread of disease-causing microorganisms through indirect contact with humans through contaminated surfaces, or avoiding direct contact with them, is the primary way to protect us from harm. Current solutions include designing antibacterial and antiviral surface coatings and developing personal protective equipment made from self-cleaning films or fabrics. In this paper, the work of several widely studied metals, metal oxides, metal organic framework materials, etc. with antibacterial and antiviral functionality is reviewed, their microbial inactivation mechanisms as well as performance are summarized and discussed. In the end, the future perspectives on emerging research directions and challenges in the development of antibacterial and antiviral coatings and films are presented.

Teaching and Learning during COVID: Lessons Learned and Future Impacts

The COVID-19 pandemic has forced educational institutions and many industries to move to an online communication model. Educators and students across the world, for the most part, have been working to accommodate socially distanced and virtual schools while addressing the associated fears and concerns. For educational institutions, online synchronous meetings using Zoom or similar software platforms have replaced face-to-face teachings. The approach to handle the teaching disruptions caused by the pandemic is somewhat similar among educational institutions. The disturbance seems to be more manageable for the lecture-based courses than the laboratory classes. This paper is based on our experience in teaching electrical engineering courses. We observed several sudden changes that we contributed to this disturbance, among them a drop in student satisfaction and learning achievements. Since the only difference between the pre-pandemic and pandemic period was the delivery methodology, to better understand the root of the problem, we constructed four research questions and applied the available data for student learning outcomes for three different electrical engineering courses with different delivery mechanisms. The data indicate that interventions that will make the courses more interactive will have the highest impact. The paper concludes with an observation regarding the enrollment numbers during the pandemic and discusses some possible scenarios. © American Society for Engineering Education, 2022.

[Epidemiological characteristics of a local cluster epidemic caused by 2019-nCoV Delta variant in Ningbo, 2021].

Objective: To understand the epidemiological characteristics of a local clustered epidemic caused by 2019-nCoV Delta variant in Ningbo and provide reference for the improvement of COVID-19 epidemic prevention and control. Methods: Case finding was conducted based on case definitions, and field epidemiological investigation of COVID-19 cases was carried out. In which Nasal and oropharyngeal swabs of the cases were collected for pathogen testing, and the results were analyzed with descriptive epidemiological methods. Results: A total of 74 COVID-19 cases were reported in this epidemic, and the cases were mainly mild ones, accounting for 87.84% (65/74), and there were no severe or critical cases. The epidemic curve showed a human-to-human transmission mode, indicating that a transmission for at least six generations had occurred. The age of the COVID-19 patients ranged from 2 years to 80 years, and 27.03% (20/74) of the cases were older than 60 years. The cases were mainly workers (55.41%, 41/74) and housework/the unemployed (27.03%, 20/74). The COVID-19 epidemic was limited, and no further spread to other areas occurred. The transmission chain among the cases was clear, and the gene sequencing results confirmed that the current epidemic was caused by 2019-nCoV Delta variant, which was highly homologous to the strains from other province. Conclusion: The local COVID-19 epidemic in Ningbo was caused by imported cases of COVID-19 from other province, and local community spread occurred through daily contacts between cases and contacts.