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Objective: To provide a basis for the early identification and treatment of severe and critical coronavirus disease 2019 (COVID - 19) by analyzing the clinical characteristics of the death cases. Methods: We retrospectively analyzed the clinical characteristics of 71 COVID - 19 cases which died during hospitalization. The clinical data included general data, underlying disease, clinical manifestation, biochemical laboratory examination, imaging examination, complications, and treatment, then the influencing factors of in - hospital survival were analyzed. Results: Most of the 71 patients were ≥60 years old (78. 9%) and had underlying diseases (74. 6%), in which hypertension ranked first, and fever was the most common first symptom. Biochemical laboratory tests showed that D-Dimer and C-reactive protein maintained at high levels during hospitalization, and lymphocyte count declined. Leukocyte/neutrophil counts, neutrophil to lymphocyte ratio, procalcitonin, creatine kinase, and lactate dehydrogenase increased. The main imaging features of the dead cases were the multifocal ground glass changes and consolidation of the lungs. The most common complications were acute respiratory distress syndrome (89. 9%), shock (34. 3%), and acute myocardial injury (30. 4%). 90% of the patients received auxiliary ventilation, and the decrease of blood oxygen saturation and the increase of procalcitonin may be the risk factors for shorter in-hospital survival. Conclusion: Severe and critical COVID-19 patients show different characteristics in clinical manifestations, biochemical laboratory examination, imaging examination, complications, and treatment reactions, which need early identification and treatment, and bewaring of acute respiratory distress syndrome and multiple organs failure. © 2022 Editorial Board of Medical Journal of Wuhan University. All rights reserved.
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This paper examines whether green assets can hedge against economic policy uncertainty (EPU) via asymmetric time-varying connectedness and EGARCH models. Using daily data in China spanning from March 2014 to June 2022, we find that (1) an evident asymmetric connectedness exists between green assets and EPU. (2) Green bond, carbon emission allowances and some green stocks can act as hedging or safety-haven assets against EPU, and the conclusion remains robust to an alternative proxy of EPU. (3) The minimum variance and connectedness portfolios provide superior performance during pre- and post-COVID-19 periods, respectively, thereby carrying substantial portfolio implications. © 2023 Elsevier Inc.
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Pickering emulsions were prepared by phacoemulsification in an ice water bath with squalene as the oil phase and an aluminum adjuvant as the particle stabilizer. The effects of formulation and process conditions on the size and distribution of the Pickering emulsions were investigated. Pickering emulsions prepared under the optimal prescription and process conditions were mixed with a peptide antigen to obtain a peptide vaccine. The optimal prescription and process condition of the Pickering emulsion is as follows: squalene as the oil phase, ultra-pure water as the water phase with 5 mg/ml aluminum adjuvant, and an ultrasonication time of 4 min at 200 W power. BALB/c mice were immunized with the peptide vaccine, and the ability of the Pickering emulsion as an immunological adjuvant to improve the efficacy of the peptide vaccine was evaluated. Under optimal conditions, a Pickering emulsion with a small particle size (430.8 nm), uniform distribution (polydispersion index of 16.9%), and zeta potential of 31.5 mV, was obtained. Immunological results showed that the serum specific antibody level in the vaccinated group reached 1×104 after three immunizations. The proportion of CD4+T cells and CD4/CD8 cells was significantly higher (P < 0.05) in the vaccinated groups than the blank control group. Further, cytokine (TNF-α) secretion decreased in the aluminum adjuvant and Pickering emulsion groups but increased in the Freund's adjuvant group. All three vaccinated groups of mice exhibited low but detectable levels of IFN-γ secretion. © 2023
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Graphical The three-layer surgical mask was recognized by the World Health Organization as an effective-protection tool for reducing SARS-CoV-2 transmission during the COVID-19 pandemic;however, the contribution of each layer of this mask to the particle size–dependent filtration performance resistance remains unclear. Here, both experimental work and numerical simulation were conducted to study the role of each mask layer in particle size–dependent filtration and respiratory resistance. By using scanning electron microscopy images of a commercial three-layer mask, composed of two spun-bond and one melt-blown nonwoven polypropylene fabric layers, four representative models were constructed, in which the computational fluid dynamics of multiphase flow were performed. The pressure drop of all models under different flow conditions was measured next. Numerical simulation was then verified by comparing the experimental results in the present study and other theoretical works. The filtration efficiency of the spun-bond polypropylene nonwoven fabric layer was much lower than that of the melt-blown nonwoven polypropylene fabric layer for the particle diameter in the range of 0.1–2.0 μm. Both the spun-bond and melt-blown nonwoven polypropylene fabric layers demonstrated extremely low filtration efficiency for particles was less than 0.3 μm in diameter, with the maximum filtration efficiency being only 30%. The present results may facilitate rational design of mask products in terms of layer number and structural design.
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Novel Coronavirus Pneumonia (NCP) is a class B infectious disease, which is prevented and controlled according to class A infectious diseases. Recently, children's NCP cases have gradually increased, and children's fever outpatient department has become the first strategic pass to stop the epidemic.Strengthening the management of the fever diagnosis process is very important for early detection of suspected children, early isolation, early treatment and prevention of cross-infection. This article proposes prevention and control strategies for fever diagnosis, optimizes processes, prevents cross-infection, health protection and disinfection of medical staff, based on the relevant diagnosis, treatment, prevention and control programs of the National Health and Health Commission and on the diagnosis and treatment experience of experts in various provinces and cities. The present guidance summarizes current strategies on pre-diagnosis;triage, diagnosis, treatment, and prevention of 2019-nCoV infection in common fever, suspected and confirmed children, which provide practical suggestions on strengthening the management processes of children's fever in outpatient department during the novel coronavirus pneumonia epidemic period.Copyright © 2020 by the Chinese Medical Association.
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Effectively predicting the evolution of COVID-19 is of great significance to contain the pandemic. Extensive previous studies proposed a great number of SIR variants, which are efficient to capture the transmission characteristics of COVID-19. However, the parameter estimation methods in previous studies are based on data from epidemiological investigations, which inevitably have caused a large delay. The popularity of digital trajectory data world-wide makes it possible to understand epidemic spreading from human mobility perspective. The major advantage of digital trajectory data lies in that the co-location level of a population is reflected at every moment, making it possible to forecast the evolution in advance. We showed that the mobility data contributed by mobile phone users could be exploited to estimate the contact probability between individuals, thus revealing the dynamic transmission of COVID-19. Specifically, we developed an estimation method to obtain human co-location levels and quantified the variations of human mobility during the epidemic. Then, we extended the infection rate with a real-time co-location level to further forecast the transmission of an epidemic, predicting the epidemic size much more accurately than conventional methods. Finally, the proposed method was applied to evaluate the quantitative effect of different non-pharmacological interventions by predicting the epidemic situations with various mobility characteristics. The empirical results and simulations corroborated our theoretical analysis, providing effective guidance to contain the pandemic. IEEE
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Non-contact human-machine interaction is the future trend for wearable technologies. This demand is recently highlighted by the pandemic of coronavirus disease (COVID-19). Herein, an anti-fatigue and highly conductive hydrogel thermocell with photo-thermal conversion ability for non-contact self-powering applications is designed. Double hydrogen-bonding enhanced supramolecular hydrogel is obtained with N-acryloyl glycinamide (NAGA) and diacrylate capped Pluronic F68 (F68-DA) via one-step photo-initiated polymerization. The supramolecular hydrogel can accommodate saturated electrolytes to fulfill the triple function of ionic crosslinking, heat-to-electricity conversion, and light response of thermocell. Eminently, the thermocell stands out by virtue of its high seebeck coefficient (-2.17 mV K−1) and extraordinary toughness (Fatigue threshold ≈ 3120 J m−2). The self-powering ability under the control of light heating is explored, and a model of a non-contact "light-remoted” sensor with self-powered and sensing integrated performance remote-controlled by light is constructed. It is believed that this study will pave the way for the non-contact energy supply of wearable devices. © 2023 Wiley-VCH GmbH.
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The Novel Coronavirus outbreak has since spread rapidly across the globe, seriously affecting the quality of life and economic development of all countries. By predicting the epidemic situation in a certain area, government departments can take corresponding measures to prevent and control the epidemic according to the forecast results. However, with the implementation of various prevention and control measures, vaccination and the impact of virus mutation, the traditional epidemic model and regression model have limitations in the prediction performance, there is a large error in the prediction accuracy. To improve the prediction accuracy, this paper proposes an Attentional mechanism-based LSTM network (A-LSTM), which takes the multiple factors affecting the epidemic trend as the input of the model. Bidirectional A-LSTM is constructed by a-LSTM neural network unit, and the best fitting degree is obtained by training in bidirectional A-LSTM network. Multivariate Bi-A-LSTM epidemic prevention and control prediction model was obtained. In this paper, the actual data as reference, the average absolute error, average absolute percentage error, root mean square error as the evaluation index of the model, and the improved model and other models are compared, experimental results show that the improved model is more accurate than the traditional model in prediction accuracy. © 2022 IEEE.
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The applications of microneedles (MNs) are becoming popular with the promise of efficient and advanced drug delivery. MNs were developed to overcome the limitations of conventional drug delivery systems and bypass biological barriers. While most MN applications in the past decades focused on transdermal biomedical appli-cations, recent advancements in engineering and technology have enabled MNs to be used in a wide range of non-transdermal applications. Compared with the other types of MNs, polymer-based MN composites have attracted more attention for non-transdermal drug delivery because they exhibit excellent biological properties, including being nontoxic, biocompatible, and biodegradable, making them ideal biomaterials for drug delivery applications that overcome the metabolic constraints of drug delivery for macromolecular payloads across a variety of tissues and organs other than the skin. This review provides an overview of recent advancements in polymer-based MN composite carriers that aim to overcome the delivery challenges for non-transdermal drug delivery, specifically in the vascular, ocular, gastrointestinal tract, buccal transmucosal, periodontal, cardio-vascular, and vaginal tissue. Furthermore, this review will discuss future perspectives and challenges for poly-meric MN composites in non-transdermal drug delivery that must be resolved.
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The COVID-19 pandemic has brought about unprecedented opportunities to introduce control systems topics in the undergraduate engineering curriculum. This paper describes two computer modeling assignments based on MATLAB with Simulink developed for CHE 461: Process Dynamics and Control taught at Arizona State University during the fall 2020 semester. A myriad of important concepts, among these dynamic modeling using conservation and accounting principles, linearization, state-space system and transfer function model representations, PID feedback control and Internal Model Control design can be applied to the problem and explained to students in the context of a significant world event representing a unique “process” system, notably the COVID-19 pandemic.
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Host-virus associations have co-evolved under ecological and evolutionary selection pressures that shape cross-species transmission and spillover to humans. Observed virus-host associations provide relevant context for newly discovered wildlife viruses to assess knowledge gaps in host-range and estimate pathways for potential human infection. Using models to predict virus-host networks, we predicted the likelihood of humans as hosts for 513 newly discovered viruses detected by large-scale wildlife surveillance at high-risk animal-human interfaces in Africa, Asia, and Latin America. Predictions indicated that novel coronaviruses are likely to infect a greater number of host species than viruses from other families. Our models further characterize novel viruses through prioritization scores and directly inform surveillance targets to identify host ranges for newly discovered viruses.
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Viruses , Zoonoses , Africa , Animals , Animals, Wild , Host Specificity , Humans , Zoonoses/epidemiologyABSTRACT
In the year of 2020. the Covid-19 global epidemic poses a major challenge to national and global governance. On the one hand, this epidemic is a test of national responses to major public emergencies, and on the other hand, it exposes the dilemma of global governance in non-traditional security areas. International health organizations, including the World Health Organization (WHO), have not played their proper role in the prevention and control of the epidemic, while national actors have been brought back to the center of global governance. After the Covid-19, non-traditional security threats have brought harm to countries and international communities even beyond the traditional security threats. Against this backdrop, the failure of global governance by international organizations and major power politics has been demonstrated, while the governance capacity of national state has provided the strongest support for the global governance system in terms of cross-border solutions, and diversified development ideas. China's concept of global governance is rooted in its national governance philosophy. It has evolved from its original position as a participant in the global governance system to a recent position as a defender and facilitator, and then to the current position as an innovator and leader after several transformations of governmental functions. Being a responsible power, China is continuously strengthening the modernization of its national governance capacity, advocating the concept of consultation, contribution and shared benefits, and promoting the reform of the global governance system. © 2022 Aalborg University. All rights reserved.
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During the Spring Festival of 2020, a new type of COVID-19 pneumonia epidemic that raged across the country spread rapidly and became a sudden force majeure event in economic operations. In the context of greater downward pressure on the economy, the epidemic has brought many problems and huge challenges to business management. Corresponding data show that the epidemic has had a certain degree of negative impact on China's overall economy and various industries. When we further subdivide the industry by industry, we can clearly find that the construction industry has been severely affected by this epidemic. This is mainly caused by the characteristics of the industry. The construction industry is faced with the uncertainty of the source of construction workers and the concentration of personnel, which makes the resumption and operation of this industry extremely difficult. This article will analyze the challenges that the epidemic poses to construction companies from the aspects of construction companies' project duration, costs, operations, staff turnover, and employee work status. This paper will put forward relevant countermeasures and suggestions from the perspective of project management and control, enterprise production and operation, enterprise own capacity construction, and industrial ecological chain. © ASCE.
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Responding to the global crisis of SARS-CoV-2 (COVID-19), the centrifugal step emulsification microfluidics supporting droplet digital Loop-mediated isothermal amplification (LAMP) is presented to quantify the SARS-COV-2 N Gene in this study. The designed centrifugal step emulsification chip with a triangular nozzle shows a robust droplet generation for sample division for LAMP, and the influence by channel flow resistance is experimentally analyzed. In addition, an evaporation-resisted structure is applied to address the reagent loss in the heating process caused by PDMS material. The devices and solution are potential to be a promising tool for the quantification of SARS-CoV-2.
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OBJECTIVES: This study aimed to evaluate associations between mental distress and COVID-19-related changes in behavioral outcomes and potential modifiers (age, gender, educational attainment) of such associations. STUDY DESIGN: This was a cross-sectional study. METHODS: An online survey using anonymous network sampling was conducted in China from April to May 2020 using a 74-item questionnaire. A national sample of 10,545 adults in 31 provinces provided data on sociodemographic characteristics, COVID-19-related mental distress, and changes in behavioral outcomes. Structural equation models were used for data analyses. RESULTS: After adjusting for covariates, greater mental distress was associated with increased smoking (odds ratio [OR] = 1.42, 95% confidence interval [CI]: 1.20-1.68 and OR = 1.54, 95% CI: 1.31-1.82 per one standard deviation [SD] increase in mental distress) and alcohol consumption (OR = 1.67, 95% CI: 1.45-1.92 and OR = 1.47, 95% CI: 1.24-1.75 per one SD increase in mental distress) among current smokers and drinkers and with both increased and decreased physical activity (ORs ranged from 1.32 to 1.56). Underweight adults were more likely to lose body weight (≥1 kg; OR = 1.63, 95% CI: 1.30-2.04), whereas overweight adults were more likely to gain weight (OR = 1.61, 95% CI: 1.46-1.78) by the same amount. Association between mental distress and change in physical activity was stronger in adults aged ≥40 years (ORs ranged from 1.43 to 2.05) and those with high education (ORs ranged from 1.43 to 1.77). Mental distress was associated with increased smoking in males (OR = 1.60, 95% CI: 1.37-1.87) but not females (OR = 1.11, 95% CI: 0.82-1.51). CONCLUSIONS: Greater mental distress was associated with some positive and negative changes in behavioral outcomes during the pandemic. These findings inform the design of tailored public health interventions aimed to mitigate long-term negative consequences of mental distress on outcomes.
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COVID-19 , Pandemics , Adult , China/epidemiology , Cross-Sectional Studies , Humans , Male , SARS-CoV-2ABSTRACT
How to boost the economy and achieve more sustainable development with enhanced quality, efficiency, and fairness by leveraging digital technology in the post-COVID-19 era has been an important agenda faced by many countries. As China’s new infrastructure initiative has the potential to open a new pathway for economic resilience, its policy characteristics and orientation have attracted more and more attention by policy makers and researchers. Taking the new infrastructure policies issued by Chinese local governments since 2020 as a data source, this paper, on the one hand, uses text mining and social network analysis to reveal the scope and coverage of the construction of new infrastructure and its orientation. On the other hand, a quantitative evaluation of 12 provincial policies grounded on a revised framework and policy modeling consistency index approach was conducted. The results show that Chinese governments adopt a bottom-up incrementalism planning mode for the policy steering of the construction of new infrastructure. This policy arrangement is a kind of goal-oriented modulation that makes planning more adaptive and participatory to enhance the infrastructure sustainability. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
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As an emerging technology, additive manufacturing (AM) is able to fabricate products with complex geometries using various materials. In particular, cyber-enabled AM systems have recently become widely applied in many real-world applications. It significantly improves the flexibility and productivity of AM but poses the system under high risks of cyber-physical attacks. For example, cyber-physical attack could maliciously tamper the product design and process parameters, which, in turn, leads to significant alteration of the desired properties in AM products. Therefore, there is an urgent need in incorporating advanced technologies to improve the cyber-physical security for the cyber-enabled AM systems. In this study, two common types of cyber-physical attacks regarding the G-code security were investigated, namely, unintended design modifications and intellectual property theft. To effectively secure the G-code against these two attacks, a new methodology is developed in this study, which consists of a novel blockchain-based data storage approach and an effective asymmetry encryption technique. The proposed method was also applied to a real-world AM case for ensuring the cyber-physical security of the face shield fabrication, which is critical during the COVID-19 pandemic. Based on the proposed methodology, malicious tampering can be accurately detected in time, and meanwhile, the risk of unauthorized access of the G-code file is greatly eliminated as well. © 2020 American Society of Mechanical Engineers (ASME). All rights reserved.
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Combined with the big data report of Baidu epidemic, and based on the transmission route and characteristics of "COVID-19" Virus, using GIS spatial analysis technology and related mathematical models, the correspondence between the epidemic development distribution and the spatial pattern of the basin in the Yunnan Plateau was simulated, and the basin distribution, traffic accessibility, urban scale, and tourism fever were found. Destination fever is closely related to the development of the epidemic. Changing the mode of transportation in the basin, changing the mode of land use, constructing regional public health facilities, and improving the community living circle have a suppressive effect on the spread of the epidemic. According to the simulation conclusions, this article focuses on blocking the spread of the epidemic and guaranteeing the treatment and basic life of the personnel during the disaster. It proposes the considerations of the territorial space planning of the Yunnan Plateau basin in response to the epidemic from the region (province) -basin area-community and governance level.