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In the current situation of coronavirus disease 2019, "to prevent import from abroad and to defend internal rebound" is the general principle. Facing the changes in the epidemic situation, especially the winter and spring epidemics, it is a huge challenge to carry out a scientific, precise and flexible program for the prevention and control of healthcare-associated infections so that to ensure the safety of healthcare workers and patients. After more than one year of anti-epidemic work, Peking Union Medical College Hospital has summarized and formulated a four-level retractable and releasable hierarchical program of prevention and control. It is dynamically adjusted according to the responsive level of public health emergencies in Beijing and the relevant regulations of epidemic prevention and control. All departments can also respond quickly to ensure the resumption of work. This program provides reference for the prevention and control of coronavirus disease 2019 and other sudden infectious diseases.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.
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In order to improve the cure rate of critically ill patients in Wuhan epidemic area and reduce the fatality rate, the state have dispatched medical staffs from the whole country to support Wuhan and treat critically ill patients in dedicated facilities. A medical team from the First Affiliated Hospital of Xi'an Jiaotong University, consisting of 133 medical staffs major in critical care medicine, respiralogy, infection, cardiology, and general surgery, entirely took over the critical care unit of the East Hospital of the Renmin Hospital of Wuhan University, and formed a multidisciplinary collaboration team with local medical staffs to treat patients together. Up to March 13th in 2020, the author's medical team has admitted a total of 109 patients, of which 48 had been discharged up on recovery. Critically ill patients with Corona Virus Disease 2019 mainly have elder age, comorbidities, complicated conditions, and difficult diagnosis and treatment. The author and the author's team combined with clinical practice, share experience and strategies of general surgery related issues in the treatment of critically ill patients, providing reference for collegues in general surgery.Copyright © 2020 by the Chinese Medical Association.
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Objective To evaluate the role of live webcast as a new medium in the propaganda and education of liver transplant recipients. Methods According to the contents of live webcast propaganda and education meeting for liver transplant recipients, relevant data of the live webcast meeting were counted and analyzed, including baseline data of participants, participation pattern, viewing frequency and duration, etc. The characteristics between live webcast and traditional propaganda and education meetings were compared. Results By the end of the live webcast meeting, 273 participants were registered, including 2 oversea participants and 271 from China. These domestic participants were from 26 provinces, autonomous regions and municipalities in China. The total number of views was 1 526. Participants attended the meeting by clicking direct link (n=243), WeChat group access (n=22), WeChat chat access (n=7) and Dingding App access (n=1). The viewing duration was (68±5) min. Compared with the traditional method, the number and places of registers of the live webcast propaganda and education meeting were increased. The questioning methods and filling out follow-up information were more convenient. Participants could attend the meeting free from charge anywhere, and saved more time. The live webcast propaganda and education meeting was not affected by the COVID-19 pandemic, and data statistical method was optimized. Conclusions Live webcast as a new medium, has a wide range of advantages, which provides a novel form of propaganda and education for the recipients after liver transplantation. It is of significance to improve the long-term survival rate and to enhance the quality of life of recipients after liver transplantation. © 2020 The authors.
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The COVID-19 pandemic has accelerated the digitalization of assessment, creating new challenges for measurement professionals, including big data management, test security, and analyzing new validity evidence. In response to these challenges, Machine Learning (ML) emerges as an increasingly important skill in the toolbox of measurement professionals in this new era. However, most ML tutorials are technical and conceptual-focused. Therefore, this tutorial aims to provide a practical introduction to ML in the context of educational measurement. We also supplement our tutorial with several examples of supervised and unsupervised ML techniques applied to marking a short-answer question. Python codes are available on GitHub. In the end, common misconceptions about ML are discussed. © 2023 by the National Council on Measurement in Education.
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Due to the coronavirus pandemic, portable electrical impedance tomography (EIT) systems [1]-[3] have been considered as the only variable wearable medical lung imaging solution for monitoring the treatment of pneumonia patients and their recovery. Generally, the EIT system is classified into passive EIT (P-EIT) [3]-[6] or active electrode EIT (AE-EIT) [2]. The AE-EIT system is preferred as it amplifies and digitalizes the small signals while minimizing the noises incurred by motion artifacts, complex long wire connection, large variation in electrode contact, and stray capacitance problems, which is important for high-performance imaging applications. © 2022 IEEE.
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In classifying chest X-rays (CXR), machine learning, particularly transfer learning, has been widely implemented and has demonstrated an excellent range of accuracy. In this study, ResNet-50, ResNet-101, and VGG16, three popular transfer learning models, were compared in a CXR classification task. This study used a dataset containing CXRs of 3616 COVID-19-positive cases, CXRs of 1345 viral pneumonia cases, CXRs of 6012 lung opacity (non-Covid lung infection) cases, as well as CXRs of 10,192 normal individuals and corresponding lung masks. The study used Keras and TensorFlow to import the pre-trained models and compare them using the exact same training sets, testing sets, and validation sets. The ResNet-50 achieves a classification accuracy of 90%, the ResNet-101 achieves a classification accuracy of 91%, and the VGG16 achieves a classification accuracy of 89%. This research reached the conclusion that ResNet-101 performs better in such image multiclassification tasks. We speculate that this is because ResNet-101 was trained based on residual learning which is easy to optimize. © 2022 SPIE. All rights reserved.
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The global Coronavirus pandemic is of urgent concern with its high transmission rate and rapid spread throughout the world from 2019. This paper introduces an Ultraviolet-C (UVC) device to be fitted on escalators which was designed to inactivate bacteria and viruses on the surfaces of handrails during escalator operation. Through a combination method of measurement and finite element analysis (FEA) simulation, the authors accurately calculated the UVC intensity, dosage, and distribution of the UVC device on a surface. The authors also describe how the UVC device works and detail the disinfection efficacy of the device to inactivate bacteria and viruses. In this work, efficacy of the device against two bacteria (E. Coli and S. Aureus) and two corona viruses (HCoV-229E and HCoV-OC43) were tested. All tests were conducted in two modes of the UVC device: continuous mode and pulsed cyclic mode. Based on the test results and combining UVC parameters, the disinfection efficacy of the UVC device was analysed. The investigation found, i) the relationship between the disinfection efficacy and the UVC parameters of the device, ii) the relationship between the disinfection efficacies of continuous and pulsed test mode and iii) the dosage for killing 99% pathogens (D99) of the UVC device for the two bacteria and viruses based on escalator operation. © 2022, Lift and Escalator Symposium Educational Trust. All rights reserved.
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Fine particulate matter (PM2.5) affects climate change and human health. Therefore, the prediction of PM2.5 level is particularly important for regulatory planning. The main objective of the study is to predict PM2.5 concentration employing an artificial neural network (ANN). The annual change in PM2.5 in Liaocheng from 2014 to 2021 shows a gradual decreasing trend. The air quality in Liaocheng during lockdown and after lockdown periods in 2020 was obviously improved compared with the same periods of 2019. The ANN employed in the study contains a hidden layer with 6 neurons, an input layer with 11 parameters, and an output layer. First, the ANN is used with 80% of data for training, then with 10% of data for verification. The value of correlation coefficient (R) for the training and validation data is 0.9472 and 0.9834, respectively. In the forecast period, it is demonstrated that the ANN model with Bayesian regularization (BR) algorithm (trainbr) obtained the best forecasting performance in terms of R (0.9570), mean absolute error (4.6 mu g/m(3)), and root mean square error (6.6 mu g/m(3)), respectively. The ANN model has produced accurate results. These results prove that the ANN is effective in monthly PM2.5 concentration predicting due to the fact that it can identify nonlinear relationships between the input and output variables.
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This article discussed air quality changes in the Beijing-Tianjin-Tangshan (BTT) region. The air quality index (AQI) values, and the concentrations of PM2.5, PM10, SO2, CO, NO2, and O-3 in the BTT region during the COVID-19 outbreak in 2020 were, respectively, 79.4, 47.2 mu g m(-3), 73.4 mu g m(-3), 10.3 mu g m(-3), 0.87 mg m(-3), 33.6 mu g m(-3), and 90.7 mu g m(-3). However, they were, respectively, 102.7, 61.4 mu g m(-3), 121.0 mu g m(-3), 9.0 mu g m(-3), 0.88 mg m(-3), 40.1 mu g m(-3), and 84.0 mu g m(-3) during the same period in 2021, which is an increase of 29.2%, 30.1%, 64.8%, -12.9%, 1.94 %, 19.5%, and -7.4% compared with the values in 2020. The combined proportions of grade I and grade II during the COVID-19 outbreak in 2020 were 16.7% higher than those in the same period in 2021, so the air quality has deteriorated rapidly from 2020 to the post-COVID era in 2021. The possible reasons for poorer air quality are that the frequency of dusty weather and air pollutant discharge has increased, and meteorological conditions have been relatively unfavorable. The average AQI values, and concentrations of PM2.5, PM10, SO2, CO, NO2, and O-3 during the post-COVID period in 2021 respectively decreased by 14.8%, 29.0%, 14.6%, 22.5%, 37.4%, 14.8%, and 8.7%, compared with those in 2020. It is also worth noting that all the changes in air pollution during the post-COVID era have been consistent. The combined proportions of grade I and grade II during post-COVID period in 2021 were 18.4% higher than those during the same period of 2020, which indicates that the air quality during post-COVID 2021 has obviously improved compared with those in the same period of 2020. The possible reasons are a series of clean air policies and clean air actions, as well as favorable atmospheric diffusion conditions. These results indicate that clean air policies play a very important role in improving air quality.
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Deep ultraviolet light-emitting diodes (DUV LEDs) are promising light sources for disinfection, especially during the pandemic of novel coronavirus (COVID-19). Despite much effort in the development of DUV LEDs, the device temperature and ideality factor are key parameters of devices, which are often neglected. Here, we developed a simple and convenient method to study the behavior of a 280 nm AlGaN-based DUV LED, obtaining the electrical, optical, and thermal properties within one measurement. From the experimental results, we find that the light output power and wall-plug efficiency of the AlGaN-based DUV LED are strongly affected by device temperature, ideality factor (beta), and series resistance (R-s). beta decreases from 9.3 to 8.1 at 40 mA when the temperature increases from 302 to 317 K. We compared these results with simulations and found that the high potential barriers inside the device and the carrier concentration in n-type or p-type layers, especially the hole concentration in p-type layers, are the two key factors for the high value of the ideality factor from the LED structure. As the device temperature increases, carriers with higher energy would overcome some potential barriers and Mg acceptor activation would be more efficient, which are beneficial for carrier transportation. However, these also lead to the carrier overflow and weaken the radiative recombination rate. The trade-off role of device temperature in carriers between transportation and overflow is needed to be considered in the future development of DUV LEDs with higher efficiency and higher brightness.
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Thieno[3,4-c]pyrrole-4,6-dione (TPD) unit has been widely used to construct a great deal of D-π-A p-type copolymers due to its strong electron-deficient property. However, there are limited reports on the TPD-based n-type materials, particularly small molecule non-fullerene acceptors (NFAs), mainly due to the time-consuming synthetic routes. Herein, two new TPD-based NFAs named as TPD-Th1 and TPD-Th3 were successfully obtained, adopting indacenodithiophene (IDT) as the central core and rhodanine (R) or 2-(1,1-dicyanomethylene)rhodanine (RCN) as the terminal electron-withdrawing unit. Both TPD-Th1 and TPD-Th3 exhibit highly planar structure due to the intramolecular noncovalently conformational locking between the O atom on the TPD unit and H atoms of two neighboring thiophene ring. The optimized PTB7-Th:TPD-Th3 photovoltaic devices show a much higher power conversion efficiency (PCE) of 5.53% in comparison with PTB7-Th:TPD-Th1 (PCE = 0.62%). The latter lower PCE could be attributed to the unmatched LUMO energy levels. Our results open a unique way to utilize TPD to construct small molecule NFAs to achieve a relatively high VOC and PCE. © 2020
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We examine a period in which the in-principle prohibition of share repurchases was relaxed in 2018 to allow for the repurchase of shares whose prices dropped materially or were below book value. We find that share-loan pledges by controlling shareholders are significantly and positively associated with share repurchases for a sample of 3,531 Chinese firms. This finding is robust using entropy and propensity score matched samples, 2SLS IV regressions, regression discontinuity design (RDD), and two exogenous shocks (the China-US trade war in 2018 and the COVID-19 pandemic in 2020). The association remains robust but becomes less strong with state ownership and with above industry average firm agency problems, leverage ratios and financial constraints/distress (i.e., other share repurchase motives). Our findings highlight the importance of financial market regulations on share-loan pledging and share repurchases in emerging markets during periods of heightened firm-specific and systemic margin call risk and impending liquidation of share-loan pledges.
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Objective: Taking the five syndromes of light (syndromes of damp and heat stagnating lung), normal (syndrome of dampness-toxicity stagnating lung), severe (syndrome of flaring heat in qi and ying), critical (syndrome of inner blocking causing collapse), and recovery (syndrome of qi-yin deficiency) period and their corresponding compounds in the seventh edition of Diagnosis and Treatment of COVID-19 as the research object, the mechanisms of various syndromes and compounds used in the stage treatment of COVID-19 by traditional Chinese medicine (TCM) was analyzed by using the method of network pharmacology. Methods: The active components and their targets of five syndromes corresponding compounds were obtained from databases and literatures such as TCMSP, the targets of the five syndrome manifestations were retrieved using databases such as Gene Card. The protein-protein interaction (PPI) networks and KEGG pathway enrichment analysis were constructed based on the intersection targets of five syndromes and active components of their corresponding compounds. Results: The intersection targets numbers of the syndromes of damp and heat stagnating lung, syndrome of dampness-toxicity stagnating lung, syndrome of flaring heat in qi and ying, syndrome of inner blocking causing collapse, and syndrome of qi-yin deficiency and their the active ingredients of the corresponding compounds were 252, 322, 402, 140, and 399, respectively, and the intersection targets mainly included VEGFA, EGFR, CASP3, AKT1 and so on. The types of pathways for the five compounds interventions were generally similar, but the emphases of each compound intervention pathway were different. Syndromes of damp and heat stagnating lung and syndrome of dampness-toxicity stagnating lung corresponding compounds focused on interfering with the virus and enhancing the body's immune response. Syndrome of flaring heat in qi and ying and syndrome of inner blocking causing collapse corresponding compounds focused on alleviating abnormalities of the nervous system to restore the body consciousness. Syndrome of qi-yin deficiency corresponding compounds further participated in the process of cell growth and enhanced the body's immunity. Conclusion: The five compounds treated COVID-19 through multiple components, multiple targets, and multiple pathways. The five compounds for the treatment of COVID-19 are mainly through anti-virus, suppression of inflammation, enhancement of immune response and protection of main target organs, which indicate the TCM characteristics of dialectical treatment and correspondence between prescriptions and syndromes, and explained the rationality of TCM to treat COVID-19 by stages. © 2021, Editorial Office of Chinese Traditional and Herbal Drugs. All right reserved.
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The COVID-19 pandemic changes the mode of life, and forces people to keep social distance or even separate from each other. Education and research, as a type of activities that usually needs many people gather at the same space, need network video technologies to keep participants separating from each other. In this paper, we analyze three different types of education and research activities, and try to give the appropriate solutions of the network video technologies for each particular activity. © 2020, Science Press. All right reserved.
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BACKGROUND Coronavirus disease 2019 (COVID-19) is spreading around the world, presenting mainly as respiratory symptoms. Some patients have obvious digestive system symptoms, or even present with only digestive system symptoms. Therefore, it is of great significance to clarify the digestive system manifestations in COVID-19 patients. AIM To explore the digestive system manifestations of 350 patients with COVID-19 hospitalized at our hospital, to provide reference for the diagnosis and treatment of COVID-19. METHODS The data of 350 COVID-19 inpatients at our hospital, such as general conditions, initial symptoms, disease severity, digestive system symptoms, and liver function, were retrospectively analyzed. The digestive system symptoms and liver function indexes were compared between non-critically ill patients and critically ill patients. Statistical methods involved independent sample median test, continuity correction chi-square test, and one-way analysis of variance. RESULTS All the 350 patients were definitely diagnosed with COVID-19, including 176 (50.3%) males and 174 (49.7%) females. They ranged in age from 17 to 94 years, with a median age of 59 years. There were 254 (72.6%) non-critically ill patients and 96 (27.4%) critically ill patients. The initial symptoms were mainly fever, dry cough, fatigue, and chest tightness;262 (74.9%) cases showed fever, 189 (54.0%) showed dry cough, 237 (67.7%) showed fatigue, and 195 (55.7%) showed chest tightness. Seventy-nine (22.6%) cases showed digestive system symptoms, mainly diarrhea, vomiting, and abdominal pain;42 (12.0%) cases showed diarrhea, 48 (13.7%) showed vomiting, and 3 (0.9%) showed abdominal pain. Five (1.4%) cases presented with digestive system symptoms as the initial symptoms. One hundred and fifty (42.9%) cases had abnormal liver function indexes (increase in at least one of ALT, AST, TBIL, and DBIL), of which 73 (20.9%) had elevated ALT, 98 (28.0%) had elevated AST, 60 (17.1%) had elevated DBIL, and 27 (7.7%) had elevated TBIL. Serum albumin (ALB) was reduced in 275 (78.6%) patients. The percentage of non-critically ill patients with digestive system symptoms (52/254, 20.5%) was not statistically significant from that of critically ill patients (52/254 [20.5%] vs 27/96 [28.1%],χ 2 = 2.334, P > 0.05). The abnormal rate of liver function indexes (87/254, 34.3%) was significantly lower in non-critically ill patients than in critically ill patients (87/254 [34.3%] vs 63/96 [65.6%], χ 2 = 28, P < 0.05). The percentage of patients with ALB decline was significantly lower in non-critically ill patients than in critically ill patients (182/254 [71.7%] vs 93/96 [96.9%],χ 2 = 26.322, P < 0.05). In both non-critically ill and critically ill patients, the increase in liver function indexes was mostly not more than 2 × upper limit of normal, and ALB was mostly in the range of 30-40 g/ L. Compared with the non-diarrhea group (236/308, 76.6%), the percentage of patients with ALB reduction in the diarrhea group (39/42, 92.9%) was statistically lower (χ 2 = 5.785, P < 0.05). There was no statistically significant difference in duration of onset between groups with different albumin concentrations (P > 0.05). CONCLUSION Hospitalized COVID-19 patients may show some digestive system symptoms, with diarrhea and vomiting being most common. A few patients present with digestive system symptoms as the initial manifestation, which is more likely to cause misdiagnosis. Some patients with COVID-19 show liver injury, although most of cases are mild, and no liver failure occurs. Compared with non-critically ill patients, the incidence of digestive system symptoms is generally similar to that of non-critically ill patients, but the incidence and degree of abnormal liver function indexes are higher in critically ill patients. Most patients with COVID-19 may have decreased serum albumin, and patients with diarrhea are more likely to have serum albumin decline. The above conclusions may help increase the awareness of COVID-19 among clinicians and improve their treatment skill .
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In order to improve the cure rate of critically ill patients in Wuhan epidemic area and reduce the fatality rate, the state have dispatched medical staffs from the whole country to support Wuhan and treat critically ill patients in dedicated facilities. A medical team from the First Affiliated Hospital of Xi'an Jiaotong University, consisting of 133 medical staffs major in critical care medicine, respiralogy, infection, cardiology, and general surgery, entirely took over the critical care unit of the East Hospital of the Renmin Hospital of Wuhan University, and formed a multidisciplinary collaboration team with local medical staffs to treat patients together. Up to March 13th in 2020, the author's medical team has admitted a total of 109 patients, of which 48 had been discharged up on recovery. Critically ill patients with Corona Virus Disease 2019 mainly have elder age, comorbidities, complicated conditions, and difficult diagnosis and treatment. The author and the author's team combined with clinical practice, share experience and strategies of general surgery related issues in the treatment of critically ill patients, providing reference for collegues in general surgery. Copyright © 2020 by the Chinese Medical Association.
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Confined spaces increase the chance of aerosol infection, and window ventilation plays an important role in reducing the risk of infection and maintaining the fresh air required for human health. In order to analyze the window opening patterns of people in different regions during the COVID-19 outbreak, information on the frequency and duration of window ventilation and the demographic information were obtained through an electronic questionnaire survey, which surveyed 7784 subjects in 31 provinces in China. The ventilation behavior of different population and the main influencing factors were then analyzed. The results shows that: (1) During the COVID-19 epidemic, 99.7% of the subjects opened windows for ventilation;Among them, 69.2% of the subjects had more than two times of daily ventilation, and 38.2% had more than three times of daily ventilation, indicating a significant difference in ventilation frequency between different groups. (2) The daily ventilation duration of residents in each region was in the range of 93-126 min, and the ventilation duration for residents in the affected areas was longer. Compared with the non-epidemic period, the ventilation time of residents in all regions decreased significantly during the epidemic period. (3) The influencing factors of ventilation behavior of Chinese population during the epidemic mainly included the epidemic related factors and non-epidemic related factors. Among them, the epidemic related factors included control measures in the community and the distribution of hospitals around the community. The ventilation frequency was higher for the population, who resided in communities with epidemic control measures and nearby designated hospitals. The non-epidemic related factors included the type of dwelling, floor and ambient temperature. Compared with the units or apartments, the ventilation frequency of people living in bungalows was higher than those living in units or apartments. (4) Residents living in the middle floor of a flat or apartment building had the longest ventilation time, while those living on the lower floor had the shortest ventilation time. The window ventilation frequency and duration were positively correlated with the ambient temperature, that is, the ventilation frequency and duration of residents in areas with higher ambient temperature were higher than those in areas with lower ambient temperature. This study indicates that 99.7% of the residents had window ventilation behavior, and the daily ventilation time in various regions was in the range of 93-126 min during the COVID-19 epidemic, which was shorter than that during the non-epidemic period. © 2020, Editorial Board, Research of Environmental Sciences. All right reserved.