Cost analysis of launching telemedicine services by Peking union Medicalcollege hospital during the pandemic of Coronavirus disease 2019.

Objective To assess the cost of launching telemedicine services by Peking Union Medical College Hospital (PUMCH) during coronavirus disease 2019 pandemic. Methods The patients using telemedicine services were enrolled during the period of pilot run from February 10th to April 15th, 2020. The study was done from the social perspective. A decision-tree model was constructed to compare the costs between telemedicine services and conventional clinical services for outpatients. The main outcome was measured as incre- mental cost-effective ness ratios (ICER). Sensitivity analysis was conducted by using one-way sensitivity analysis. Results During a period of forty-seven days, the online fever clinic was applied 3055 person-times(2070 patients) and the online outpatient clinic were applied 36 549 person-times(20 467 patients). On average, 44 febrile cases/d and 435 nonfebrile cases/d were reduced in the outpatient clinic. It helped to reduce roughly 1/4 (febrile) and 1/5(nonfebrile) of total numbers of the patients in the outpatient clinic during the peak period of the epidemic. If calculated according to the actual free-of-charge condition, the ICER was -64.7 yuans/person-time. If the actual cost of each consultant of telemedicine service was estimated according to the level of outpatient-service fee, the ICER was -5.5 yuans/person-time. The results of sensitivity analysis showed that the main factors affecting the ICERs were transportation cost, lost wages, and the efficiency of telemedicine services. Conclusions Launching telemedicine services helped to relieve the pressure at the outpatient clinics, and has the potential to provide significant cost saving compared to conventional clinic services for outpatients. It is worth considering applying this practice widely in the medical and health services.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.

Remote telemedicine strategy based on multi-risks intervention by intelligent wearable health devices in elderly comorbidities patients with coronary heart disease

Background: Telemedicine based on wearable intelligent health devices becomes increasingly promissing for the elderly due to the accelerated aging population. Especially during COVID-19 pandemic, more elderly coronary heart disease patients with chronic comorbidities are in less secondary prevention management at home. Objective(s): To explore the prevention effect on main cardiovascular risk factors and repeated hospitalization in elderly comorbidities patients by telemedicine intervention based on multi-parameter wearable monitoring devices. Method(s): Total of 337 patients with comorbidities of coronary heart disease, hypertension and diabetes, with age more than 65 years old were recruited in the study from October 2019 to January 2021. They were randomly divided into control group and telemedcine intervention group. The latter used remote multi-parameter wearable devices to measure blood pressure, glycemic and electrocardiograph at home every day. A real-time monitoring platform would alarm any abnormal data to the doctors. Both doctors and patients can read the measurement results on a real-time mobile phone APP and interact with each other remotely twice a week routinely. A medical team remotely indicated the medications, while offering guidance on lifestyle. In contrast, the control group adopted traditional outpatient medical strategy to manage diseases. Result(s): A total of 306 patients were enrolled in the follow-up experiment finally: 153 in the intervention group and 153 in the control group. Patient characteristics at baseline were balanced between two groups. After 12 months, compared with the control group, the intervention group saw the following metrics significantly reduced: Systolic blood pressure (SBP) (131.66+/-9.43 vs 137.20+/-12.02 mmHg, P=0.000), total cholesterol (TC) (3.65+/-0.79 vs 4.08+/-0.82 mmol/L, P=0.001), low density lipoprotein cholesterol (LDL-C) (2.06+/-0.53 vs 2.38+/-0.61 mmol/L, P=0.002), and fasting blood glucose (FBG) (6.26+/-0.75 vs 6.81+/-0.97 mmol/L, P=0.000), while the following metrics went up significantly: Blood pressure control rate (77.3% vs 59.1%, P=0.039), blood lipid control rate(39.4% vs 21.2%, P=0.037), glycemic control rate (71.2% vs 51.5%, P=0.031), and medication adherence score (7.10+/-0.77 vs 6.80+/-0.73, P=0.020). Linear regression model analysis indicates that when interaction frequency >=1.53, 2.47 and 1.15 times/week, the SBP, LDL-C and FBG levels would be controlled, respectively. Cox survival analysis finds that the hospitalization rate of intervention group is significantly lower than that of the control group (24.18% vs 35.29%, P=0.031). Conclusion(s): The telemedicine interactive intervention based on multiparameter wearable devices provides effectively improvement of cardiovascular risk controlling, medication adherence, while reducing the hospitalization rate of patients. A frequency of doctor-patient interactions more than 2 times/week is beneficial for disease management the elderly at home. (Figure Presented) .

Infection control status of novel coronavirus pneumonia and radiation safety at CT workplace.

CT is an important imaging tool for the diagnosis of novel coronavirus pneumonia (COVID-19), therefore, it's necessary to strictly control the disinfection of CT workplace and equipment and biosafety to avoid the place from becoming a potential infection source and to reduce the risk of infection of patients and radiological staff. It is also necessary to reduce the CT scan dose to minimize the radiation hazards on patients under the premise of ensuring the CT image quality and diagnostic efficiency. Based on the survey that novel coronavirus residues after disinfection at some CT workplace in domestic and overseas and the application of low-dose CT scan in diagnosis of COVID-19, as well as the current situation of radiological protection management in emergency hospital, this paper summarizes and proposes suggestions on infection control and radiological protection for CT workplace to strengthen the defense line of COVID-19 prevention and control.Copyright © 2021 by the Chinese Medical Association.

Viral and Host Small RNA Response to SARS-CoV-2 Infection

After two years into the pandemic of the coronavirus disease 2019 (COVID-19), it remains unclear how the host RNA interference (RNAi) pathway and host miRNAs regulate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and impact the development of COVID-19. In this study, we profiled small RNAs in SARS-CoV-2-infected human ACE2-expressing HEK293T cells and observed dysregulated host small RNA groups, including specific host miRNAs that are altered in response to SARS-CoV-2 infection. By comparing dysregulated miRNAs in different SARS-CoV-2-infected samples, we identified miRNA-210-3p, miRNA-30-5p, and miR-146a/b as key host miRNAs that may be involved in SARS-CoV-2 infection. Furthermore, by comparing virally derived small RNAs (vsmRNAs) in different SARS-CoV-2-infected samples, we observed multiple hot spots in the viral genome that are prone to generating vsmRNAs, and their biogenesis can be dependent on the antiviral isoform of Dicer. Moreover, we investigated the biogenesis of a recently identified SARS-CoV-2 viral miRNA encoded by ORF7a and found that it is differentially expressed in different infected cell lines or in the same cell line with different viral doses. Our results demonstrate the involvement of both host small RNAs and vsmRNAs in SARS-CoV-2 infection and identify these small RNAs as potential targets for anti-COVID-19 therapeutic development. © 2022 by the authors.

The impact of ICT use on entrepreneurial performance: evidence from Chinese microenterprises

Following the outbreak of COVID-19, information and communication technology (ICT), as a part of digital technology, was of particular help to microenterprises in obtaining resources. Drawing upon Conservation of Resources Theory, we investigated the impact of ICT use on entrepreneurial performance. To examine our hypotheses, data were collected from 206 Chinese microenterprises. The results suggest that ICT use was positively related to entrepreneurial performance, that network capabilities mediated the relationship between ICT use and entrepreneurial performance and that perceived ICT usefulness moderated the relationship between ICT use and network capabilities. Finally, the implications, limitations and future research directions will be discussed. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Exploring the Effect of Social Media and Spatial Characteristics During the COVID-19 Pandemic in China

The declaration of COVID-19 as a pandemic has largely amplified the spread of related information on social platforms, such as Twitter, Facebook and WeChat. In this work, we investigate how the disease and information co-evolve in the population. We focus on COVID-19 and its information during the period when the disease was widely spread in China, i.e., from January 25th to March 24th, 2020. The co-evolution between disease and information is explored via the spatial analysis of the two spreading processes. We visualize the geo-location of both disease and information at the province level and find that disease is more geo-localized compared to information. High correlation between disease and information data is observed, and also people care about the spread of disease only when it comes to their neighborhood. Regard to the content of the information, we obtain that positive messages are more negatively correlated with the disease compared to negative and neutral messages. Additionally, two machine learning algorithms, i.e., linear regression and random forest, are introduced to further predict the number of infected using characteristics, such as disease spatial related and information-related features. We obtain that both the disease spatial related characteristics of nearby cities and information-related characteristics can help to improve the prediction accuracy. The methodology proposed in this paper may shed light on new clues of emerging infections prediction. © 2013 IEEE.

I/Q Channel Selection for 24 GHz CW Radar to Non-Contact Vital Signs Detection for Health Check System

With the increasing improvement of quality of life (QOL), health has become an item of concern. However, owing to Covid-19, most organizations cannot do annual health check-ups because they require contact with people and it is difficult to maintain social distance. Consequently, in an era of increasing epidemics, non-contact methods are paramount. In this paper, we present a non-contact breathing and heart rate measurement system integrated into an application using 24 GHz medical radar to support the health check work. In this system, we solve the problem of imbalance between the two signal channels of the radar to increase the accuracy of the breathing and heart rate extraction. © 2022 IEEE.

Remote telemedicine strategy based on multi-risks intervention by intelligent wearable health devices in elderly comorbidities patients with coronary heart disease

Background: Telemedicine based on wearable intelligent health devices becomes increasingly promissing for the elderly due to the accelerated aging population. Especially during COVID-19 pandemic, more elderly coronary heart disease patients with chronic comorbidities are in less secondary prevention management at home. Objective: To explore the prevention effect on main cardiovascular risk factors and repeated hospitalization in elderly comorbidities patients by telemedicine intervention based on multi-parameter wearable monitoring devices. Methods: Total of 337 patients with comorbidities of coronary heart disease, hypertension and diabetes, with age more than 65 years old were recruited in the study from October 2019 to January 2021. They were randomly divided into control group and telemedcine intervention group. The latter used remote multi-parameter wearable devices to measure blood pressure, glycemic and electrocardiograph at home every day. A real-time monitoring platform would alarm any abnormal data to the doctors. Both doctors and patients can read the measurement results on a real-time mobile phone APP and interact with each other remotely twice a week routinely. A medical team remotely indicated the medications, while offering guidance on lifestyle. In contrast, the control group adopted traditional outpatient medical strategy to manage diseases. Results: A total of 306 patients were enrolled in the follow-up experiment finally: 153 in the intervention group and 153 in the control group. Patient characteristics at baseline were balanced between two groups. After 12 months, compared with the control group, the intervention group saw the following metrics significantly reduced: systolic blood pressure (SBP) (131.66±9.43 vs 137.20±12.02 mmHg, P=0.000), total cholesterol (TC) (3.65±0.79 vs 4.08±0.82 mmol/L, P=0.001), low density lipoprotein cholesterol (LDL-C) (2.06±0.53 vs 2.38±0.61 mmol/L, P=0.002), and fasting blood glucose (FBG) (6.26±0.75 vs 6.81±0.97 mmol/L, P=0.000), while the following metrics went up significantly: blood pressure control rate (77.3% vs 59.1%, P=0.039), blood lipid control rate(39.4% vs 21.2%, P=0.037), glycemic control rate (71.2% vs 51.5%, P=0.031), and medication adherence score (7.10±0.77 vs 6.80±0.73, P=0.020). Linear regression model analysis indicates that when interaction frequency ≥1.53, 2.47 and 1.15 times/week, the SBP, LDL-C and FBG levels would be controlled, respectively. Cox survival analysis finds that the hospitalization rate of intervention group is significantly lower than that of the control group (24.18% vs 35.29%, P=0.031). Conclusion: The telemedicine interactive intervention based on multi-parameter wearable devices provides effectively improvement of cardiovascular risk controlling, medication adherence, while reducing the hospitalization rate of patients. A frequency of doctor-patient interactions more than 2 times/week is beneficial for disease management the elderly at home. Funding Acknowledgement: Type of funding sources: Foundation. Main funding source(s): Key scientific research project of Health CommissionFigure 1. ResultsFigure 2. Flowchart and intervention strategy

Real-Time Medical Radar-based Vital Sign Monitoring System Implemented with Signal Quality Classification Algorithm

Owing to the Covid-19 epidemic, medical radar has become a potential non-contact method in patient monitoring. However, this radar type is sensitive to external interference. The output signal obtained by the radar when a patient makes random body movements can significantly reduce the accuracy of vital sign detection algorithms. In addition, algorithms should be developed for actual application. In this study, we present an improved model of the 24-GHz radar signal quality classification system and a technique to enhance the resolution of respiration rate (RR) and heart rate (HR) for short time interval signals. Moreover, a complete system including signal quality assessment and vital signs extraction is implemented in real time on the Lab-VIEW software. The signal quality classification was evaluated on the measured signals of 10 healthy subjects. Accordingly, the obtained results indicate that with specific features, the accuracy of signal quality classification reaches 89.8%-100% while real-time RR and HR extraction results demonstrate significant agreement between radar measurement and the contact-type sensor. © 2022 IEEE.

Exploring the effect of social media and spatial characteristics during the COVID-19 pandemic in China

The declaration of COVID-19 as a pandemic has largely amplified the spread of related information on social platforms, such as Twitter, Facebook and WeChat. In this work, we investigate how the disease and information co-evolve in the population. We focus on COVID-19 and its information during the period when the disease was widely spread in China, i.e., from January 25th to March 24th, 2020. The co-evolution between disease and information is explored via the spatial analysis of the two spreading processes. We visualize the geo-location of both disease and information at the province level and find that disease is more geo-localized compared to information. High correlation between disease and information data is observed, and also people care about the spread of disease only when it comes to their neighborhood. Regard to the content of the information, we obtain that positive messages are more negatively correlated with the disease compared to negative and neutral messages. Additionally, two machine learning algorithms, i.e., linear regression and random forest, are introduced to further predict the number of infected using characteristics, such as disease spatial related and information-related features. We obtain that both the disease spatial related characteristics of nearby cities and information-related characteristics can help to improve the prediction accuracy. The methodology proposed in this paper may shed light on new clues of emerging infections prediction. Author

Adapting New Learners and New Resources to Micro Open Learning via Online Computation

Since the outbreak of COVID-19, an alternative way to keep students on the track, meanwhile, prevent them from being at the risk of infection is in highly demand. Many education providers had made a move in trial of delivering knowledge and learning materials remotely. Along with this trend, learning management systems, open educational resources (OERs) and OER platforms, mini applications in social media and video-conference software were combined in a rush to create a multi-channel delivery mode to make learning resources openly available round-the-clock. Learning activities in this fast migration to online were regularly found to be carried out in gradual and fragmented time spans. Due to the little-known learner information along with the continuously released new OERs, the cold start problem still hinders the innovative mode of delivery and adaptive micro learning. To overcome the data sparsity, an online computation is proposed to benefit OER providers and instructors. A lightweight learner-micro-OER profile and two algorithmic solutions are provided to tackle the new user and new item cold start problem, respectively. Learning paths are generated and optimized in terms of heuristic rules to form the initial recommendation list. By adopting the same set of rules, newly released micro OERs are inserted into established learning paths to increase their discoverability. IEEE

Construction and Research of SCUIR Propagation Model Based on Time-varying Parameters

Novel coronavirus is a new type of virus, and its transmission characteristics are different from previous virus. Infected people not only have an incubation period, but also a large number of asymptomatic infections. Based on the classic model SEIR, this study redefines the latent state as close contact state, introduces an asymptomatic state of infection, and the influence of time on the state transition parameters in the model is considered, proposed a new transmission model which includes five types of states: susceptible state, close contact state, asymptomatic infection state, infected state, and removed state. The model uses the actual epidemic data of Hubei Province to conduct experiments, and uses RMSE and MAPE as evaluation indicators to compare the experimental results. The results show that the fitting accuracy of the SCUIR model has been significantly improved. Compared with the traditional model, the fitting error is reduced by 8.3%~47.6%, and hidden data that is difficult to count in the epidemic can be calculated, which further characterizes the mechanism of epidemic transmission. © 2022, The Editorial Department of Complex Systems and Complexity Science. All right reserved.

An Industrial Heat Source Extraction Method: BP Neural Network Using Temperature Feature Template

Aiming at the problem of insufficient quantity and spatial refinement in the extraction of industrial heat source from annual scale thermal anomaly data, a neural network industrial heat source extraction method based on temperature feature template is proposed by using VIIRS active fire data. This study took Beijing-Tianjin-Hebei and its surrounding areas as the study area, Firstly, according to the spatial aggregation characteristics of industrial heat sources, the heat source objects were divided by the OPTICS algorithm. Secondly, according to the thermal radiation characteristics of the heat sources, the temperature characteristic template of industrial heat sources and non-industrial heat sources were constructed. Finally, the BP neural network was used to extract industrial heat source objects using the temperature feature template and heat source statistical characteristics as parameters. The results show that: (1) the extraction precision of industrial heat source of the neural network algorithm of temperature feature template proposed in this paper reached 96.31%. Compared with time filtering and logistic regression methods, the extraction precision of industrial heat sources was improved by 8.45% and 7.53%, respectively;(2) From 2015 to 2020, the number of industrial heat sources in the six provinces and cities in Beijing-Tianjin-Hebei and its surrounding areas decreased by 27.46%. The number of industrial heat source objects and heat anomalies in Hebei Province decreased by 8.06% and 7.44% annually, respectively, which was the largest decrease compared with other provinces and cities. The concentration of industrial heat sources in Shandong and Tianjin increased by 25.72% and 86.64%, respectively, indicating that the industrial transformation and upgrade policies in the two places have achieved remarkable results;(3) Tangshan, Handan, Lvliang, and Changzhi accounted for 31.37% of the total industrial heat sources in the study area, which are the main cities in Beijing-Tianjin-Hebei and its surrounding areas. The degree of industrial heat source accumulation and energy consumption in seven cities such as Linfen and Taiyuan was higher than those in other cities;The degree of industrial heat source accumulation and energy consumption in 11 cities such as Beijing and Zhoukou was lower than those in other cities;(4) From January to May 2020, the number of industrial heat anomalies in Beijing-Tianjin-Hebei and its surrounding areas remained unchanged or increased compared with the same period in 2019 and 2021. The COVID-19 had no significant impact on the industrial heat source in the study area. The number of industrial heat anomalies in Wuhan in January and February 2020 decreased by more than 66.67% compared with that in the same period in 2019 and 2021, the number of industrial heat anomalies from March to May 2020 was lower than that in the same period of 2019. The COVID-19 has had a significant impact on industrial heat sources in Wuhan from January to May 2020. This study reflects the current situation and trend of industrial heat source development in Beijing-Tianjin-Hebei and its surrounding areas, which provides a valuable reference for the formulation and adjustment of relevant policies such as reducing energy consumption and improving secondary industry concentration. © 2022, Science Press. All right reserved.

[Application of remote "Internet+" interactive mode in the management of patients with hypertension during normalized epidemic prevention and control of COVID-19].

Objective: To explore the effect of remote "Internet+" interactive management strategy on blood pressure control in patients with hypertension during normalized epidemic prevention and control of COVID-19. Methods: This is a randomized controlled study. A total of 394 patients with hypertension who were treated in Chinese People's Liberation Army General Hospital from October 2019 to December 2020 were randomly divided into experimental group (197 cases) and control group (197 cases). The experimental group adopted remote "Internet+" interaction mode to carry out remote blood pressure intervention, and the control group received traditional blood pressure control mode, and the intervention time was 6 months. Evaluation indicators included blood pressure level, blood pressure lowering speed, time to target blood pressure, blood pressure measurement times, communication times with doctors, medication compliance, blood pressure measurement compliance and disease awareness after 6 months of intervention. The evaluation indexes of the two groups were compared, and the bivariate Pearson correlation analysis was used to explore the relationship between the speed of blood pressure reduction and the times of blood pressure measurement and doctor communication in all patients. Results: A total of 394 patients with hypertension were included in this study, including 209 males, aged (67.6±2.8) years old. After 6 months of intervention, the systolic and diastolic blood pressure of the two groups were both lower than the baseline blood pressure before intervention (both P<0.05), the systolic blood pressure ((125.7±11.7) mmHg (1 mmHg=0.133 kPa) vs. (132.6±12.9) mmHg, P<0.001) and diastolic blood pressure ((72.4±10.7) mmHg vs. (79.8±11.6) mmHg, P<0.001) in the experimental group were lower than those in the control group. The blood pressure reduction speed of the experimental group was faster than that of the control group ((18.63±1.59) mmHg/d vs. (13.26±2.85) mmHg/d, P<0.001), and the time to reach the target blood pressure in the experimental group was shorter than that in the control group ((23.69±2.93) d vs. (47.12±5.81) d, P<0.001). Compared with the control group, the blood pressure measurement times ((0.98±0.13) times/d vs. (0.20±0.40) times/d, P<0.05) and the number of communications with doctors ((0.97±0.16) times/week vs. (0.12±0.32) times/week, P<0.05) were significantly higher in the experimental group. Correlation analysis showed that the speed of blood pressure reduction was positively correlated with the number of blood pressure measurements (r=0.419, P<0.01) and the number of communications with doctors (r=0.857, P<0.01). The proportion of standardized medication (93.91% (185/197) vs. 51.78% (102/197), P<0.001), timely measurement (97.46% (192/197) vs. 47.21% (93/197), P<0.001) and high-degree disease awareness (94.42% (186/197) vs. 49.24% (97/197), P<0.001) were significantly higher in the experimental group than those in the control group. Conclusions: The remote "Internet+" interactive management strategy can effectively improve patients' blood pressure control. The doctor-patient interaction can improve medication compliance and measurement compliance of patients, and help shorten the time to reach the target blood pressure.

Cost analysis of launching telemedicine services by Peking union Medicalcollege hospital during the pandemic of Coronavirus disease 2019

Objective  To assess the cost of launching telemedicine services by Peking Union Medical College Hospital (PUMCH) during coronavirus disease 2019 pandemic.  Methods  The patients using telemedicine services were enrolled during the period of pilot run from February 10th to April 15th, 2020. The study was done from the social perspective. A decision-tree model was constructed to compare the costs between telemedicine services and conventional clinical services for outpatients. The main outcome was measured as incre- mental cost-effective ness ratios (ICER). Sensitivity analysis was conducted by using one-way sensitivity analysis.  Results  During a period of forty-seven days, the online fever clinic was applied 3055 person-times(2070 patients) and the online outpatient clinic were applied 36 549 person-times(20 467 patients). On average, 44 febrile cases/d and 435 nonfebrile cases/d were reduced in the outpatient clinic. It helped to reduce roughly 1/4 (febrile) and 1/5(nonfebrile) of total numbers of the patients in the outpatient clinic during the peak period of the epidemic. If calculated according to the actual free-of-charge condition, the ICER was -64.7 yuans/person-time. If the actual cost of each consultant of telemedicine service was estimated according to the level of outpatient-service fee, the ICER was -5.5 yuans/person-time. The results of sensitivity analysis showed that the main factors affecting the ICERs were transportation cost, lost wages, and the efficiency of telemedicine services.  Conclusions  Launching telemedicine services helped to relieve the pressure at the outpatient clinics, and has the potential to provide significant cost saving compared to conventional clinic services for outpatients. It is worth considering applying this practice widely in the medical and health services. © 2021, Peking Union Medical College Hospital. All rights reserved.

[A retrospective safety study on screening of the samples in the clinical biobank of Beijing Hospital].

To investigate whether the laboratory specimens preserved in Beijing Hospital Biobank during a specific period had been contaminated by SARS-Cov-2 through a cross-sectional study, and to establish a retrospective biobank safety screening system. Laboratory specimens were collected from the Department of Respiratory and Critical Care Medicine and the Fever Clinic of Beijing Hospital from November 1, 2019 to January 22, 2020, nucleic acid and serological antibody testing were performed for SARS-CoV-2 in these specimens (including 79 serum, 20 urine, 42 feces and 21 bronchoalveolar lavage fluid specimens). The safety of the stored samples during this period was defined by negative and positive results. Both the nucleic acid test and serological antibody test showed negative for SARS-CoV-2, indicating that these specimens were safely stored in the biobank. High-risk specimens collected in our hospital during the early stage of the COVID-19 outbreak are free of SARS-CoV-2, and a safety screening strategy for the clinical biobank is established to ensure the biosafety of these samples.

Using Big Data to Discover Chaos in China's Futures Market During COVID-19

COVID-19 was first reported in China and quickly spread throughout the world. Weak investor confidence in government efforts to control the pandemic seriously affected global financial markets. This study investigated chaos in China's futures market during COVID-19, focusing on the degree of chaos at different periods during the pandemic. We constructed a phase diagram to observe the attractor trajectory of index futures (IFs). During the COVID-19 outbreak, overall chaos in China's futures market was increasing, and there was a clear correlation between market volatility and the macroenvironment (mainly government regulation). The Hurst index, calculated by rescaled range (R/S) analysis, was 0.46. The price and return of IFs showed long-term correlation and fractal characteristics;the relevant dimensions of the futures market were 2.17. Overall, under the influence of an emergency (COVID-19), chaos in China's financial market intensified, creating a need for timely government intervention and macrocontrol of the market. This study's findings can help improve the government's understanding of the phenomenon of financial chaos caused by emergencies. This study also provides theoretical guidance for controlling financial chaos and maintaining healthy economic development when faced with similar events in the future.

Infection control status of novel coronavirus pneumonia and radiation safety at CT workplace

CT is an important imaging tool for the diagnosis of novel coronavirus pneumonia (COVID-19), therefore, it's necessary to strictly control the disinfection of CT workplace and equipment and biosafety to avoid the place from becoming a potential infection source and to reduce the risk of infection of patients and radiological staff. It is also necessary to reduce the CT scan dose to minimize the radiation hazards on patients under the premise of ensuring the CT image quality and diagnostic efficiency. Based on the survey that novel coronavirus residues after disinfection at some CT workplace in domestic and overseas and the application of low-dose CT scan in diagnosis of COVID-19, as well as the current situation of radiological protection management in emergency hospital, this paper summarizes and proposes suggestions on infection control and radiological protection for CT workplace to strengthen the defense line of COVID-19 prevention and control. Copyright © 2021 by the Chinese Medical Association.

Finger-vein recognition using a novel enhancement method with convolutional neural network

Finger vein biometric technology has gained a lot of popularity over recent years. This is primarily due to the increased security and reliability level that comes with its non-intrusive nature. Non-intrusiveness became inevitable due to the pandemic of COVID-19. This paper introduces a unique and lightweight image enhancement method for person identification using Convolutional Neural Networks (CNN). As pre-processing steps, Contrast Limited Adaptive Histogram Equalization (CLAHE) followed by gamma correction is applied. Afterward, the image is sharpened and then passed through the median filter. These steps are followed by applying power law and contrast adjustment. As a final step, CLAHE is used yet again to bring out the enhanced vascular structure. The method was appraised using the four different openly accessible databases. These are regarded as the most challenging available finger vein database-s by many researchers. For recognition purposes, CNN was used with transfer learning. Transfer learning is implemented by modifying the 13 convolutional layers of VGG-16. The proposed model architecture also includes five max-pooling layers, one ReLU, and one Softmax layer. It is observed that with transfer learning, the accuracy could have reached up to 99% on finger-vein recognition on the experimented dataset, thus proved to be a highly accurate approach for finger vein recognition.

The Impact of Population Migration on the Spread of COVID-19: A Case Study of Guangdong Province and Hunan Province in China

On the eve of the Spring Festival in 2020, the coronavirus disease 2019 (COVID-19) was reported. Subsequently, the Chinese government at all levels took emergency measures to control the spread of COVID-19 among people. Guangdong and Hunan are large population floating provinces. The spread of COVID-19 is affected by population migration. Before the Spring Festival, Guangdong and Hunan Provinces dominated population export and import, respectively;after the Spring Festival, the trend of population flow was reversed by the resumption of work. Taking Guangdong and Hunan as examples, we establish a three-stage dynamical model to study the impact of population migration on the spread of COVID-19. The result reveals that Guangdong Province mainly emigrated the population and the scale of infection was reduced before the Spring Festival. However, the situation in Hunan Province was just the opposite. After the Spring Festival, work resumption was taking place across China and the migration of Guangdong may cause a second outbreak of the epidemic. While people in Hunan leave the province to work, the migration of population will have little effect on the spread of COVID-19. © Copyright © 2020 Xing, Li, Li and Sun.