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In this study, we theoretically propose a surface plasmon resonance (SPR) biosensor composed of a plasmonic gold film, double negative (DNG) metamaterial, graphene-MoS2-COOH Van der Waals heterostructures and gold nanoparticles (Au NPs). We use a novel scheme of Goos-Hanchen (GH) shift to study the biosensing performances of our proposed plasmonic biosensor. The calculation results show that, both an extreme low reflectivity of 8.52x10(-10) and significantly enhanced GH sensitivity of 2.1530x10(7) mu m/RIU can be obtained, corresponding to the optimal configuration: 32 nm Au film/120 nm metamaterial/4-layer graphene/4-layer MoS2-COOH. In addition, there is a theoretically excellent linear response between the concentration of target analytes (SARS-CoV-2 and S protein) and the change in differential GH shift. Our proposed biosensor promises to be a useful tool for performing the novel coronavirus detection.
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Since the outbreak of the COVID-19 pandemic, power generation and the associated CO2 emissions in major countries have experienced a decline and rebound. Knowledge on how an economic crisis affects the emission dynamics of the power sector would help alleviate the emission rebound in the post-COVID-19 era. In this study, we investigate the mechanism by which the 2008 global financial crisis sways the dynamics of power decarbonization. The method couples the logarithmic mean Divisia index (LMDI) and environmentally extended input-output analysis. Results show that, from 2009 to 2011, global power generation increased rapidly at a rate higher than that of GDP, and the related CO2 emissions and the emission intensity of global electricity supply also rebounded;the rapid economic growth in fossil power-dominated countries (e.g., China, the United States, and India) was the main reason for the growth of electricity related CO2 emissions;and the fixed capital formation was identified as the major driver of the rebound in global electricity consumption. Lessons from the 2008 financial crisis can provide insights for achieving a low-carbon recovery after the COVID-19 crisis, and specific measures have been proposed, for example, setting electricity consumption standards for infrastructure construction projects to reduce electricity consumption induced by the fixed capital formation, and attaching energy efficiency labels and carbon footprint labels to metal products (e.g., iron and steel, aluminum, and fabricated metal products), large quantities of which are used for fixed capital formation. © 2023 The Authors
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In this study, we theoretically propose a surface plasmon resonance (SPR) biosensor composed of a plasmonic gold film, double negative (DNG) metamaterial, graphene-MoS2-COOH Van der Waals heterostructures and gold nanoparticles (Au NPs). We use a novel scheme of Goos-Hanchen (GH) shift to study the biosensing performances of our proposed plasmonic biosensor. The calculation results show that, both an extreme low reflectivity of 8.52×10-10 and significantly enhanced GH sensitivity of 2.1530×107 μm/RIU can be obtained, corresponding to the optimal configuration: 32 nm Au film/120 nm metamaterial/4-layer graphene/4-layer MoS2-COOH. In addition, there is a theoretically excellent linear response between the concentration of target analytes (SARS-CoV-2 and S protein) and the change in differential GH shift. Our proposed biosensor promises to be a useful tool for performing the novel coronavirus detection. © 2023 SPIE.
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Introduction: Several studies have reported attenuated humoral responses following SARS-CoV-2 mRNA vaccination in Multiple Sclerosis (MS) patients on anti-CD20 therapies and fingolimod. However, neutralising antibodies (NAbs) against the receptorbinding domain of the SARS-CoV-2 spike protein were quantified in only a few reports and there is limited data in neuromyelitis optica spectrum disorder (NMOSD) patients. Objectives and Aims: To measure serum NAbs levels prior to, and, at several time points after the first (V1) and second (V2) SARS-CoV-2 mRNA vaccination in patients with neuroimmunological conditions on various immunotherapies, and, to identify the factors associated with poor humoral responses. Method(s): This was a prospective observational study performed at the National Neuroscience Institute, Singapore. Patients with MS (n=77), NMOSD (n=33), myelin oligodendrocyte glycoprotein- antibody associated disease (n=6), autoimmune encephalitis (n=3), other CNS inflammatory diseases (n=5), myasthenia gravis (n=9) and healthy controls (HCs, n=42) were recruited. No subjects had COVID-19 infection prior to V1, V2 and the sampling time points. NAbs were measured using the Genscript cPassTM surrogate virus neutralisation test. Result(s): No patients or HCs had detectable NAbs prior to V1. Two to 4 weeks after V1, patients on anti-CD20 therapies had lower NAbs levels (p=0.010) compared to HCs and untreated patients. Two to 6 weeks post V2, patients on disease-modifying anti-rheumatic drugs (DMARDs) (p=0.010), fingolimod (p<0.0001) and anti-CD20 therapies (p<0.0001) showed decreased NAbs levels compared to HCs and untreated patients. This was also observed 8 to 16 weeks post V2 - DMARDs (p=0.046), fingolimod (p<0.0001) and anti-CD20 therapies (p<0.0001). NAbs levels decreased in both HCs and patients with increasing time interval following V2. There was no correlation between NAbs levels and the time interval from last anti-CD20 treatment to V1 (p=0.508). A multivariable logistic regression model adjusted for age, expanded disability status scale, gender, mRNA vaccine type, ethnicity and body mass index, revealed that fingolimod (p=0.026) and anti-CD20 therapies (p=0.003) were independent predictors of undetectable NAbs following V2. Conclusion(s): Fingolimod and anti-CD20 therapies are associated with attenuated NAbs levels post-vaccination. Future studies are needed to determine whether this translates to an increased risk of COVID-19 infection.
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Objective To explore the characteristics and nursing measures of medical rescue support in space station. Methods According to the characteristics of medical rescue support task of manned space mission, practical nursing schemes and corresponding nursing measures were formulated from the aspects of personnel selection, personnel training, material preparation, process formulation, training exercise and epidemic prevention. Results The "Shenzhou-12" mission includes the whole launch phase, operation phase and return phase. There are many tasks that cover a long time. The contents of medical rescue support include personnel's physical and mental quality, technical ability, environmental equipment, the possible injuries of astronauts, and the normalization of COVID-19's task guarantee. In view of this content, a practical nursing scheme was formulated to enable nurses to quickly master and skillfully cooperate with the treatment, win more time for the treatment and improve the overall rescue level. Conclusions Various process plans have been integrated and optimized for medical rescue support of space mission. The equipment carried is advanced, and can be used in various complex environments and complex working conditions. The rescue support personnel have also done their best, kept improving and solidified the state. We should constantly sum up experience, explore and study new problems, and make new achievements in medical rescue support for space missions. © 2022 Chinese Medical Association. All rights reserved.
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The prevalence of depression and anxiety disorders has increased dramatically in the last two years due to the global COVID-19 epidemic, which leads to a shortage of traditional mental health care resources. To address these issues, we propose to use the digital, immersive, and private features of virtual reality technology to assist in the treatment of mental illness. We designed and completed a garden scene for virtual reality horticultural therapy based on the basic principles of traditional horticultural therapy. In order to study the effectiveness of the gardening scenario, we recruited 30 subjects to explore the effectiveness of mood regulation. A survey of a PANAS scale was conducted before and after the garden scene, and a user experience scale was presented to the subjects after the experiment. The ANOVA results showed that there were significant differences between anxious, distressed and self-loathing before and after the experiment. This demonstrates that virtual reality horticulture therapy has a mood-improving effect. In future works, we will improve the design of VR gardening scenarios and conduct more in-depth research on virtual reality horticulture therapy. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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In the version of this article initially published, the first name of Chuansheng Zheng was misspelled as Chuangsheng. The error has been corrected in the HTML and PDF versions of the article. © The Author(s) 2022.
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This paper is one of the few studies that discusses the impacts and challenges of banking business, especially online credit loans (also known as Internet loans or consumption loans) from the aspects of social environment, economic development, public policy, and technological environment changes under the impact of COVID-19 epidemic. Based on authors' years of experiences in banking industry, they find that online loan products are facing with numerous problems, such as unclear position of online loan products, management dilemma of employees, dilemma between social responsibilities and debt collection, mismatch between risk and income, high bad-loan ratio issues and so on. To find effective ways to solve those problems, authors combined experience with practice and put forward several possible directions, such as seizing the opportunities of digital transformation to develop financial technology, expanding online products, establishing a new financial environment under changed consuming scene, and utilizing the strict supervision mechanism to expand traditional banking business.
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Artificial intelligence provides a promising solution for streamlining COVID-19 diagnoses;however, concerns surrounding security and trustworthiness impede the collection of large-scale representative medical data, posing a considerable challenge for training a well-generalized model in clinical practices. To address this, we launch the Unified CT-COVID AI Diagnostic Initiative (UCADI), where the artificial intelligence (AI) model can be distributedly trained and independently executed at each host institution under a federated learning framework without data sharing. Here we show that our federated learning framework model considerably outperformed all of the local models (with a test sensitivity/specificity of 0.973/0.951 in China and 0.730/0.942 in the United Kingdom), achieving comparable performance with a panel of professional radiologists. We further evaluated the model on the hold-out (collected from another two hospitals without the federated learning framework) and heterogeneous (acquired with contrast materials) data, provided visual explanations for decisions made by the model, and analysed the trade-offs between the model performance and the communication costs in the federated training process. Our study is based on 9,573 chest computed tomography scans from 3,336 patients collected from 23 hospitals located in China and the United Kingdom. Collectively, our work advanced the prospects of utilizing federated learning for privacy-preserving AI in digital health. The COVID-19 pandemic sparked the need for international collaboration in using clinical data for rapid development of diagnosis and treatment methods. But the sensitive nature of medical data requires special care and ideally potentially sensitive data would not leave the organization which collected it. Xiang Bai and colleagues present a privacy-preserving AI framework for CT-based COVID-19 diagnosis and demonstrate it on data from 23 hospitals in China and the United Kingdom.
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Disasters such as the COVID-19 pandemic outbreak can bring challenges to trades all over the world. How to enhance the supply chain resilience and strengthen the competitiveness of enterprises in emergency situations has become a significant topic. To improve the emergency response capability of supply chains, this study aims at establishing a novel decision-making method to deal with the supplier selection problem during the COVID-19 pandemic outbreak based on a novel preference information represent tool, the hesitant fuzzy linguistic preference relation (HFLPR). To achieve this goal, we first introduce the cut of hesitant fuzzy linguistic elements and transform each hesitant fuzzy linguistic element in an HFLPR into the corresponding semantic considering the degree of confidence of the decision-makers regarding the evaluation values. Then, the utility matrix of an HFLPR is proposed. Afterwards, we construct two dual linear programming models to obtain interval weights from an HFLPR based on the concept of the least upper and the greatest lower bounds. An approach to ranking the obtained interval weights is introduced based on the concept of possibility degree between intervals. The procedure is summarised for the facility of implementation and we apply it to a case study about the resilient supplier selection during the COVID-19 pandemic outbreak. Some comparative analyses are presented to demonstrate the advantages of our method.
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Objective: To investigate the characteristics of disease transmission, diagnosis, and treatment of COVID‑19 in children. Methods: We retrospectively studied 20 children with COVID‑19 from 4 medical centers in Hubei, China. Results: Among the 20 children, 18 (90.0%) were contaminated by close contact and characterized by family clustering. Seven cases (35.0%) had all family members infected, and 11 cases (55.0%) were confirmed by either of the parents infected. Twelve cases (60.0%) had fever, which was the primary symptom in 10 cases (50.0%). Only one child was in severe degree and combined with severe underlying disease (congenital heart disease). Seven cases (35.0%) presented typical ground‑glass opacity in CT. All patients were confirmed to be infected with SARS‑CoV‑2. Eleven cases (55.0%) had normal white blood cell counts, and one case (5.0%) with severe COVID‑19 showed a continuous decline in T cells subsets. Conclusion: COVID‑19 in children is transmitted by close contact and characterized by family clustering. Fever is the most common symptom or initial symptom. However, the sustained low levels of T cells and underlying diseases are risk factors for severe COVID‑19 children. © 2021, Editorial Board of Medical Journal of Wuhan University. All right reserved.
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Amid the Covid-19 pandemic, how to attract back visitors has been a major problem for museums across the world. Among diverse museum activities, human-guided tours remain under-studied to date. A post-hoc case analysis on Xuhui Art Museum provided empirical evidence demonstrating the potential power of guided tours. Quantitative methods in content analysis and semantic network analysis were employed to identify general features of visitor comments from both visitor books and social media. An in-depth interview was also conducted with the Chief Curator. Results reveal that the work of 'jiangjie', or tour guiding, is greatly appreciated and plays a vital role in improving visitor experience and satisfaction. This study calls for re-evaluation of the functions, potential and effects of tour guiding, and a renewal of live tours for better on-site experience in a post COVID-19 period.
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Due to the outbreak of the novel coronavirus (or known as COVID-19), people are advised to wear masks when they stay outdoors in many countries. This could result in difficulty for some public safety surveillance systems involving face detection or tracking. Therefore, the development of face detection and tracking algorithms for people wearing face masks is particularly important. In this paper, a real-time tracking algorithm for people with or without face masks is proposed. This algorithm is trained on public face datasets with faces without masks. Although the training does not involve face images of people wearing face masks, we show that the proposed algorithm is robust as it is able to perform well in face tracking for people wearing face masks. We also discuss the possible scenarios where the algorithm could lose track of the target when experimenting in tracking masked faces. This can motivate future research in this area.
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Purpose: Male cancer survivors represent an important at-risk population for COVID-19. The COVID-19 pandemic requires a global response for this most vulnerable population. This study purpose was to explore whether fear of COVID-19 and fear of cancer recurrence are related to the likelihood of remaining at work following treatment in male cancer survivors. Survivors and methods: A cross-sectional survey was used. Data were collected in China in May to June 2020. The Fear of COVID-19 Scale, Fear of Cancer Recurrence (FCR) Inventory-Short Form and work sustainability subscale of the Readiness for Return to Work Scale were completed by male cancer survivors. Results: A total of 121 employed male cancer survivors participated in this study. Fear of COVID-19 and fear of cancer recurrence were both negatively correlated with work sustainability (β = −0.11, and β = −0.19, respectively). Significant interaction effects between fear of COVID-19 and fear of cancer recurrence were observed (β = 0.46, P <0.01). Advanced disease stage, undergoing radiation therapy and having recently completed cancer treatment were all factors related to lower work sustainability scores (β = −0.28, β = −0.15, and β = −0.17, respectively). The overall path model yielded a good fit: χ2/df = 1.12 (P = 0.24), RMSEA = 0.07, TLI = 0.98, CFI = 0.99, IFI = 0.92, and NFI = 0.96. Conclusion: Fear of COVID-19 is a mediator between fear of cancer recurrence and work sustainability among Chinese male cancer survivors. The findings also indicated that male cancer survivors with higher FCR levels reported less confidence in their ability to remain at work. This information can assist in the development of new interventions and educational programs for cancer survivors, healthcare providers and employers, to improve employees’ ability to remain at work. © 2021. The Authors. Published by IMR Press.
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Objective: To evaluate the diagnostic performance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immunoglobulin M (IgM) and immunoglobulin G (IgG) antibodies detection and their clinical diagnostic value in suspected COVID-19 patients. Methods: A retrospective study was conducted to collect 301 cases of hospitalized diagnozed or suspected COVID-19 patients in Wuhan Pulmonary Hospital from January 3, 2020 to February 28, 2020. Among these cases, 197 patients with positive results for SARS-CoV-2 nucleic acid test were included as confirmed case group. And 104 patients with negative results were included as the suspected case group. Then 114 people with normal physical examination results from August, 2019 to October, 2019 reported by Wuhan University, and 104 hospitalized patients with tuberculosis confirmed in Wuhan Pulmonary Hospital from January, 2019 to February, 2019, were set as control group (non-COVID-19 group). All cases were detected with serum SARS-CoV-2 IgM and IgG antibodies by automatic chemiluminescence immunoassay. The patients in the suspected case group were clinically analyzed according to the Chinese diagnosis and treatment plan (7th trial version) of novel coronavirus pneumonia diagnostic criteria. Results: For the respective detection of serum SARS-CoV-2 IgM and SARS-CoV-2 IgG in the confirmed case group and control group, the clinical sensitivity was 65.99% (130/197) and 96.95% (191/197), the specificity was 97.71%(213/218) and 91.74%(200/218), the positive predictive value was 96.30% and 91.39%, the negative predictive value was 76.07% and 97.09%, the positive likelihood ratio was 28.82 and 11.74, the negative likelihood ratio was 0.348 and 0.033, and the total coincidence rate was 82.65% and 94.22%, respectively. For the combined detection of SARS-CoV-2 IgM and SARS-CoV-2 IgG in the confirmed case group and control group, the clinical sensitivity was 96.95% (191/197), the specificity was 89.45%(195/218), the positive predictive value was 89.25, the negative predictive value was 97.01, the positive likelihood ratio was 9.19, the negative likelihood ratio was 0.034, and the total coincidence rate was 93.01%. In the suspected case group, the rate of positive results in SARS-CoV-2 IgG was 80.77% (84/104), the rate of positive results in SARS-CoV-2 IgM was 34.62%(36/104), the rate of positive results in SARS-CoV-2 IgG+IgM were 34.62%(36/104), and the rate of negative results in SARS-CoV-2 IgG+IgM were 19.23% (20/104). Conclusion: The combined detection of serum SARS-CoV-2 IgM and IgG have a good coincidence rate with the clinical diagnosis of COVID-19. The combined detection can be used as an important means for rapid screening and diagnosis of SARS-CoV-2 infection, and also can be used for differential diagnosis of SARS-CoV-2 infection in tuberculosis patients. And the combined detection of serum SARS-CoV-2 IgM and IgG is an effective supplement for the diagnosis of COVID-19 in patients with suspected nucleic acid negative results of SARS-CoV-2. © 2021, Editorial Board of Medical Journal of Wuhan University. All right reserved.
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The corona virus disease 2019 (COVID-19) has emerged as a fatal virus. This deadly virus has taken the whole world into clutches and many people have embraced death due to this invincible bug. The death toll is rising with every tick of time. The aspiration behind this article is to discover the preventive measure that should be taken to cope with this intangible enemy. We study the prime notions of novel sort of topology accredited Pythagorean m-polar fuzzy topology along with its prime attributes. We slightly amend the well-acknowledged multi-criteria decision analysis tool TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) to befit the proposed multi-criteria group decision making (MCGDM) problem of exploring the most effective method for curing from COVID-19 employing the proposed model.
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During the outbreak and epidemic of coronavirus disease 2019(COVID-19), anesthesiologists are not only the high-risk group of secondary infection, but also undertake tasks to initiate clinical research so that the regular pattern of disease could be summarized, which will produce clinical evidences for clinical decision-making and optimization of anesthesia therapy as soon as possible.The clinical research evidences of anaesthesia are of great importance for improving the prevention and control strategy of infectious diseases and implementing relevant measures effectively.The recommendations from the epidemiological perspective are provided on how to conduct clinical research on anesthesiology during epidemic of the COVID-19 in the present paper: (1) The case report and case series research should be initiated promptly once the infectious cases treated in anesthesia department are diagnosed;(2)To focus on need of evidence of decision-making of diagnosis and treatment, to summarize general rules timely and to promote the rapidly production of evidence;(3) To establish a special cohort of COVID-19 so that more prognosis studies could be carried out;(4) To explore the risk factors which result in hospital infection among medical staffs so that hospital infection could be controlled.The purpose of this study is to provide clinicians with methodological suggestions on how to carry out high-quality clinical research in the epidemic period of infectious diseases, and to close the gap between clinical and public health. © 2020 Chinese Medical Association
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SESSION TITLE: Late-breaking Abstract Posters SESSION TYPE: Original Investigation Posters PRESENTED ON: October 18-21, 2020 PURPOSE: There are no published studies concerning the clinical characteristics of patients with coronavirus disease 2019 (COVID-19) resident in high altitude. We aim to analyze the unique cohort and investigated the relationship among the patients resident in different altitude areas of Sichuan province, China. METHODS: We retrospectively reviewed the medical data including clinical features, imaging findings, laboratory characteristics and received treatment of confirmed cases of COVID-19 with WHO interim guidance in Sichuan province from Jan 12th to March 12th, 2020. Outcomes were also compared between patients from high-altitude and non-high-altitude area. RESULTS: 537 patients were included in this study, 78 were from high-altitude area and 459 from non-high-altitude area. The high-altitude area group was less likely had a clear travel history of Wuhan (9.0% vs. 64.3%, p<0.001) or contact with people from Wuhan (10.3% vs. 25.5%, p=0.003) within recent two weeks, but more likely contact with people infected of COVID-19 never been to Wuhan (60.3% vs. 3.3%, p<0.001) or of unknown origin (20.5% vs.7.0%, p<0.001). The high-altitude area group was more likely asymptomatic before admission (50.6% vs. 8.7%, p<0.001). Less patients with cough, sputum production and fever in the cohort comparing with those in non-high-altitude area. Lower body temperature, slower heart rate, and lower blood pressure relatively on admission were also found in high-altitude patients as well. The period from onset of illness to visit was 3 days (range, 1-7 days) and to diagnosis was 4 days (range,1-7 days), which were both significantly shorter in the group of high-altitude area. The patients from high-altitude had significantly higher lymphocyte count, lower platelet count and lower level of erythrocyte sedimentation rate (p all＜0.05). Less patients with abnormally elevated C-reactive protein were also observed in high-altitude group (p＜0.05). The most common patterns seen in these population on chest CT were bilateral distribution, ground-glass opacity, and consolidation and nodules. Multifocal distribution and consolidation were noted and showed significant in high-altitude patients. The proportion of patients with mild illness was significantly higher in the high-altitude area group (16[20.5%] vs. 33[7.2%], p<0.001). More likely to receiving antiviral and glucocorticoid therapies and less likely to receiving antibiotic drugs were shown in the patients in high-altitude area. Multivariate logistic analysis indicated that age, gender, diabetes and recent travel history of Wuhan were predictors of severe pneumonia. CONCLUSIONS: The disease severity of COVID-19 in Sichuan province was milder than Wuhan. More patients in high-altitude area were asymptomatic. It could owe to the active prevention, early detection and timely treatment. CLINICAL IMPLICATIONS: Active prevention, early detection and timely treatment is critical in COVID-19. DISCLOSURES: No relevant relationships by Aamer Chughtai, source=Web Response No relevant relationships by Lu Guo, source=Admin input no disclosure on file for Caiyu Jiang;no disclosure on file for Xiayin Peng;no disclosure on file for Hong Pu;no disclosure on file for Weiwei Qiang;no disclosure on file for Yang Yang;