The 17th National Annual Conference on Neurological Infectious Diseases and Cerebrospinal Fluid Cytology of the Chinese Medical Association Neurology Branch was successfully held

The 17th National Annual Conference on Neurological Infectious Diseases and Cerebrospinal Fluid Cytology of the Chinese Medical Association Neurology Branch was successfully held in Wuhan, Hubei, China. During the conference, many well-known neurology experts in China conducted in-depth and detailed discussions on the research progress of infectious diseases of the nervous system and cerebrospinal fluid cytology, which benefited the participants a lot.Copyright © 2021

Establishment of medical service protocols in large public hospitals for the prevention and control of coronavirus disease 2019.

Coronavirus disease 2019(COVID-19) poses a challenge to hospitals for the prevention and control of public health emergencies. As the main battlefield of preventing and controlling COVID-19, large public hospitals should develop service protocols of diagnosis and treatment for outpatient, emergency, hospitalization, surgery, and discharge. The construction of medical protocols should be based on the risk factors of key points and focused on pre-inspection triage and screening, to establish a rapid response mechanism to deal with exogenous and endogenous risk factors. Implementation of all-staff training and assessment, strengthening the information system, and use of medical internet service are important. This study explores the construction of medical protocols in large public hospitals during the pandemic, and provides a reference for the orderly diagnosis and treatment in hospitals during the pandemic.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.

Effect of marine economic development pilot policies on regional economic resilience: Based on quasi-natural experiments from coastal areas in China

China began to implement marine economic development pilot policies from 2011 in order to promote land and marine development in a coordinated way, transform and optimize marine industrial layout, formulate and improve the policy and institutional construction of ocean development, promote marine economic power strategy, and improve the level of regional economic resilience in coastal area. Tourism industry is an important part of regional economy of coastal areas. Taking the marine economic development pilot policies as a quasi-natural experiment and based on the panel data of cities in coastal areas of China from 2007 to 2020, a multi-period difference-in-differences (DID) model was used to assess the impact of these pilot policies on regional economic resilience and tourism economic resilience. The results show that the implementation of marine economic development pilot policies can significantly promote regional economic resilience and tourism economic resilience. COVID-19, as a moderating variable, has significantly weakened the effect of marine economic development pilot policies on regional economic resilience. In terms of regional heterogeneity, the establishment of marine economic development pilots has a more significant policy effect on regional economic resilience in the central and southern coastal areas, while the policy effect on tourism economic resilience is more significant in the eastern coastal areas. In view of these findings, it is of great significance for cities to prevent systemic risks and improve regional economic resilience, by means of reasonably expanding marine economic development pilots and planning coastal regional economic systems according to local conditions. © 2023, Editorial office of PROGRESS IN GEOGRAPHY. All rights reserved.

Epidemiological Survey of the Prevalence and Associated Factors of Mental Disorders in Xinjiang Uygur Autonomous Region

Background Socioeconomic development,lifestyle changes and the COVID-19 pandemic all have an impact on people's mental and physical health,which may affect the prevalence of mental disorders. Currently,there is still no sufficient epidemiological information of mental disorders in Xinjiang. Objective To investigate the prevalence and influencing factors of common mental disorders among people aged 15 and above in northern Xinjiang,then compare the data with those of their counterparts in southern Xinjiang,and summarize the overall prevalence of common mental disorders in Xinjiang,providing a scientific basis for the formulation of corresponding mental health plans. Methods From November 2021 to July 2022,a multistage,stratified,random sampling method was used to select 3 853 residents from northern Xinjiang to attend a survey. General Demographic Questionnaire,and self-assessment scales(the 12-Item General Health Questionnaire,Mood Disorder Questionnaire,Symptom Checklist-90,etc.) and other assessment scales(Hamilton Depression Inventory,Bech-Rafaelsen Mania Rating Scale,Brief Psychiatric Rating Scale,etc.) were used as survey instruments. Mental disorders were diagnosed by the ICD-10 classification of mental and behavioral disorders by two psychiatrists with at least five years' working experience, or by a chief or associate chief psychiatrist when there is an inconsistency between the diagnoses made by the two psychiatrists. Results The point prevalence rate and age-adjusted rate of common mental disorders in northern Xinjiang were 9.71% (374/3 853) and 10.07%,respectively. The point prevalence rate and age-adjusted rate of common mental disorders in the whole Xinjiang were 9.69%(750/7 736)and 9.90%,respectively. The point prevalence rates of mood disorders,anxiety disorders,schizophrenia,organic mental disorders,and mental retardation in northern Xinjiang were 4.83%(374/7 736),3.63% (281/7 736),0.63%(49/7 736),0.23%(18/7 736),and 0.36%(28/7 736),respectively. Multivariate Logistic regression analysis for northern Xinjiang showed that:the risk of mood disorders in females was 1.854 times higher than that in males 〔95%CI(1.325,2.593)〕;The risk of mood disorders increased by 5.210 times in 25-34-year-olds 〔95%CI(1.348, 20.143)〕 and 3.863 times in 35-44-year-olds 〔95%CI(1.030,14.485)〕 compared with that in those aged ≥ 65 years;The risk of mood disorders increased by 0.199 times in those with high school or technical secondary school education 〔95%CI (0.078,0.509)〕 and 0.147 times in those with two- or three-year college and above education 〔95%CI(0.056,0.388)〕 compared with that in illiteracies. The risk of anxiety disorder in females was 1.627 times higher than that in males 〔95%CI (1.144, 2.315)〕;The risk of anxiety disorder increased by 0.257 times in 15-24-year-olds 〔95%CI(0.091,0.729)〕,0.243 times in 45-54-year-olds 〔95%CI(0.101,0.583)〕,and 0.210 times in 55-64-year-olds 〔95%CI(0.067,0.661)〕 compared to that of those aged ≥ 65 years old. The risk of schizophrenia among people living in villages or towns was 4.762 times higher than that of those living in cities 〔95%CI(1.705,13.300)〕;The risk of schizophrenia among people with high school or technical secondary school education was 0.079 times higher than that of illiteracies 〔95%CI(0.015,0.405)〕. Conclusion The prevalence of mood disorders and anxiety disorders is high among all types of mental disorders in Xinjiang. Females,rural people,or low educated people in northern Xinjiang are more prone to various types of mental disorders. © 2023 Chinese General Practice. All rights reserved.

Opening the black box of Library Hi Tech: a social network and bibliometric analysis

Purpose: This paper presents a comprehensive study using bibliometric and social network analysis (SNA) to depict the academic community, research hotspots and the correlation between research performance and social network measurements within Library Hi Tech. Design/methodology/approach: Publications from Library Hi Tech between 2010 and 2022 are reviewed and analysed through coauthorship analysis, co-occurrence analysis, SNA and the Spearman rank correlation test. Findings: The annual number of publications in Library Hi Tech increased from 2016 to 2022, indicating that this research has gradually gained global attention. The USA and China are the most significant contributors to the relevant publications. Scholars in this field mainly engage in small-scale cooperation. Academic libraries, digital libraries, libraries, information technology and COVID-19 were hot topics during the study period. In light of the COVID-19 pandemic, there was a marked increase in research on healthcare. Academic interest in the internet of Things and social media has proliferated recently and may soon attract more attention. Spearman rank correlation analysis shows that research performance (i.e. publication count and citation count) is significantly and positively correlated with social network measurements (i.e. degree centrality, betweenness centrality, closeness centrality and eigenvector centrality) in studies of Library Hi Tech. Originality/value: This paper reveals a systematic picture of the research landscape of Library Hi Tech and provides a potential guide for future research. The relationship between scientific research performance and social network measurements can be objectively identified based on statistical knowledge. © 2023, Emerald Publishing Limited.

Changes in contents of PM2.5 components over Jinan city before and after implementation of epidemic control measures during the 2020 Spring Festival

To understand the influence of coronavirus disease control policies on changes in characteristics of particulate matter smaller than 2.5 μm (PM2.5), concentrations of various PM2.5 components in Jinan city before and after implementation of the epidemic control measures during the 2020 Spring Festival were studied using online monitoring data. Standardized multiple linear regression was used to analyze the contribution of meteorological factors to the variations in concentrations of PM2.5 components. After the epidemic control measures were implemented, the concentrations of PM2.5 components in the area decreased significantly, and the rate at which the daily average concentration was exceeded decreased by 24.8%. The concentrations of all PM2.5 components decreased to various degrees, with those of trace elements (TE), elemental carbon (EC), and nitrate (NO3−) having decreased significantly by 50.3%, 46.8%, and 31.5%, respectively. In terms of component proportions, those of TE and EC decreased after the epidemic control measures were initiated whereas those of ammonium (NH4+), organic matter (OM), sulfate (SO4 2− ), and mineral dust increased;the proportion of NO3 − changed slightly, and the total proportion of secondary ions SO4 2−, NO3−, and NH4 + increased by 14.3%. Comparison of the proportions of PM2.5 components showed that after the epidemic control measures were implemented, the proportions of NO3 − and EC in PM2.5 that cause a light pollution level decreased whereas those of OM, SO4 2−, and NH4 + increased. This indicated that people traveled less, motor vehicle emissions decreased, work at construction sites stopped, and NO3 − proportion was greatly reduced while epidemic control measures were in place. However, afterward, decrease in concentrations of PM2.5 components and increase in secondary transformation of volatile organic compounds led to an increase in OM concentration. Compared with those before the epidemic control measures were implemented, the NO2/SO2 and NO3– /SO4 2− ratios fell significantly, and their average values decreased by 30.0% and 14.0%, respectively, indicating that the contribution of mobile sources (e.g., automobile exhaust) to pollution had decreased during the epidemic control period. Under the influence of the control measures, the OC concentration also decreased for excellent, good, and mild pollution levels;however, the secondary organic carbon concentration increased, indicating that secondary conversions did not decrease under the epidemic control conditions. Standardized multiple linear regression analyses of meteorological factors showed that changes in the height of the boundary layer contributed the most (46.5%) to changes in concentrations of PM2.5 components before the epidemic control measures were implemented;afterward, humidity was the primary factor governing the increase in these concentrations. © 2022, The Science Press. All rights reserved.

Development of an Indirect ELISA Antibodies Detection Method on Tandem-epitope Peptide of African Swine Fever Virus p30 and p54 Proteins.

Here, we report the development of an indirect ELISA antibodies detection method for African swine fever virus (ASFV). Two purified monoclonal antibodies (mAbs) against ASFV p30 and p54 protein were used as targets and a phage-displayed 12-mer peptide library was used to conduct four rounds of biopanning to screen peptide epitopes, then amino acids GGG was used as a linker to synthesize tandem-epitope peptide of ASFV p30 and p54 protein which was used as coating antigen. The optimum reaction conditions of indirect ELISA were determined by chessboard titration, and clinical serum samples were used to evaluate the specificity, sensitivity, stability and conformity of this method. The biopanning experiment indicated that 146PAEPYTT152 was a core domain of the B cell linear epitope of p54 protein. The optimization results of ELISA reaction conditions showed that the tandem-epitope peptide coupled with ovalbumin (OVA) at N-terminal had low background of non-specific serum reaction. And the optimum reaction effect was obtained when the polypeptide antigen was coated with carbonate buffer in 2 mug.mL-1, the serum was diluted 100-fold with blocking solution (1% gelatin solution), and the HRP-antibody was diluted 5 000 times with 0.05% PBST solution. The cut-off value was determined to be 0.339. Furthermore, the results of specificity, sensitivity and stability tests showed that there is no cross-reaction in positive serum samples of classical swine fever virus (CSFV), porcine reproductive and respiratory syndrome virus (PRRSV), porcine circovirus type 2 (PCV2), porcine parvovirus (PPV) and porcine pseudorabies virus (PRV), the detection limit of ASFV positive sera is 1:1 600, and the method had high repeatability. Finally, Total 320 swine serum samples were detected simultaneously by the present established method and commercial ASFV antibody detection kit. The results showed that the relative specificity and sensitivity of the two methods were 97.6% and 97.3%, respectively. And the coincidence rate was 97.5%. In conclusion, this method showed good specificity, sensitivity, repeatability and coincidence rate, that had the potential value of developing clinical diagnostic kit.Copyright © 2022 Editorial Board, Institute of Animal Science of the Chinese Academy of Agricultural Sciences. All rights reserved.

Exploration and Practice of Teacher-student Collaboration in Micro-lecture Construction under the Epidemic Situation

In the case of COVID-19 epidemic, online education supported by computing technology is playing an increasingly important role, while online education resources, especially micro-lectures, are seriously insufficient, which greatly hinders the development of online education. In this paper, a micro-lecture resource construction scheme for online courses with teacher-student collaboration was proposed based on the learning pyramid theory. The practice proved that this scheme can make full use of students' technical foundation in the Internet era to build micro-lectures, which can not only improve the quality of online courses, but also build curriculum resources quickly and with high quality, thus providing a strong resource guarantee for the follow-up online teaching. © 2022 Association for Computing Machinery.

Research on Distribution Capacity of Fresh Food E-commerce Company Based on Fuzzy Synthetic Evaluation

With the introduction of the new retail model and the explosion of COVID-19, more and more community residents are using fresh food e-commerce companies to buy the fresh produce they need on a daily basis. In this paper, three fresh produce e-commerce companies with a high market share were selected as research subjects and their company financial reports were used as raw data, and then the intra-city distribution capability of fresh food e-commerce companies was studied based on the raw data. Firstly, the weights of the primary and secondary indicators were calculated using the hierarchical analysis and entropy methods respectively, and the weights were fused. After that, a fuzzy synthetic evaluation of each of the three fresh food e-commerce companies was conducted, which in turn quantified the evaluation results. Finally, the quantified evaluation results are compared and appropriate recommendations are given for each fresh food e-commerce company. © 2022 IEEE.

Guidance on strengthening the management processes of children's fever in outpatient department during the novel coronavirus pneumonia epidemic period (First Edition).

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.

SA-FGDEM: A Self-adaptive E-Learning Performance Prediction Model

With the rapid development of computer computing power and the severe challenges brought by the COVID-19, e-learning, as the optimal solution for most students and other learner groups, plays an extremely important role in maintaining the normal operation of educational institutions. As the user community continues to expand, it has become increasingly important to guarantee the quality of teaching and learning. One way to ensure the quality of online education is to construct e-learning behavior data to build learning performance predictors. Still, most studies have ignored the intrinsic correlation between e-learning behaviors. Therefore, this study proposes an adaptive feature fusion-based e-learning performance prediction model (SA-FGDEM) relying on the theoretical model of learning behav-ior classification. The experimental results show that the feature space mined by fine-grained differential evolution algorithm and the adaptive feature fusion combined with differential evolution algorithm can support e-learning performance prediction more effectively and is better than the benchmark method. © 2022 IEEE.

CFD modelling of infection control in indoor environments: A focus on room-level air recirculation systems

The emergence of viral variants has driven a continuous pandemic with a higher possibility of airborne transmission and a larger scale of infective cases, posing greater demands on indoor risk control. However, the role of room-level air recirculation systems (RRSs) in infection control remains unclear due to insufficient detailed research. There are also fewer analyses of the filtering rating of recirculation filters from the perspective of multi-scale particle size. Thus, a simulation procedure to assess the performance of RRSs on infection control that accounts the transient recirculation of real virus-laden particles in multi-scale sizes was proposed, and focusing on recirculation filter strategies to balance the risk limitation and energy cost. A poorly ventilated winter classroom was selected as a typical environment equipped with RRSs to operate this procedure. Different RRS strategies (i.e., wall-mounted air conditioners (WMAC), floor-standing air conditioners (FSAC) and 4-way cassette air conditioners (WCAC)) were compared. The results show the important contribution of recirculated particles to accumulating the overall infection risk of susceptible occupants towards a high basic reproduction number (Ro > 1). Then, there is a strong correlation of the spatial distributions between high-risk zones and large vortexes at the breathing height of susceptible occupants. Considering rating suitability and filtration effectiveness, the optimization of recirculation filters on energy and cost can be suggested with comparable benefits of infection control. © 2023 Elsevier B.V.

Pathogenic infection characteristics and risk factors for bovine respiratory disease complex based on the detection of lung pathogens in dead cattle in northeast China.

Bovine respiratory disease complex (BRDC) involves multiple pathogens, shows diverse lung lesions, and is a major concern in calves. Pathogens from 160 lung samples of dead cattle from 81 cattle farms in northeast China from 2016 to 2021 were collected to characterize the molecular epidemiology and risk factors of BRDC and to assess the major pathogens involved in bovine suppurative or caseous necrotizing pneumonia. The BRDC was diagnosed by autopsy, pathogen isolation, PCR, or reverse transcription-PCR detection, and gene sequencing. More than 18 species of pathogens, including 491 strains of respiratory pathogens, were detected. The positivity rate of bacteria in the 160 lung samples was 31.77%, including Trueperella pyogenes (9.37%), Pasteurella multocida (8.35%), Histophilus somni (4.48%), Mannheimia haemolytica (2.44%), and other bacteria (7.13%). The positivity rate of Mycoplasma spp. was 38.9%, including M. bovis (7.74%), M. dispar (11.61%), M. bovirhinis (7.94%), M. alkalescens (6.11%), M. arginini (0.81%), and undetermined species (4.68%). Six species of viruses were detected with a positivity rate of 29.33%, including bovine herpesvirus-1 (BoHV-1; 13.25%), bovine respiratory syncytial virus (BRSV; 5.50%), bovine viral diarrhea virus (BVDV; 4.89%), bovine parainfluenza virus type-3 (BPIV-3; 4.28%), bovine parainfluenza virus type-5 (1.22%), and bovine coronavirus (2.24%). Mixed infections among bacteria (73.75%), viruses (50%), and M. bovis (23.75%) were the major features of BRDC in these cattle herds. The risk analysis for multi-pathogen co-infection indicated that BoHV-1 and H. somni; BVDV and M. bovis, P. multocida, T. pyogenes, or Mann. haemolytica; BPIV-3 and M. bovis; BRSV and M. bovis, P. multocida, or T. pyogenes; P. multocida and T. pyogenes; and M. bovis and T. pyogenes or H. somni showed co-infection trends. A survey on molecular epidemiology indicated that the occurrence rate of currently prevalent pathogens in BRDC was 46.15% (6/13) for BoHV-1.2b and 53.85% (7/13) for BoHV-1.2c, 53.3% (8/15) for BVDV-1b and 46.7% (7/15) for BVDV-1d, 29.41% (5/17) for BPIV-3a and 70.59% (12/17) for BPIV-3c, 100% (2/2) for BRSV gene subgroup IX, 91.67% (33/36) for P. multocida serotype A, and 8.33% (3/36) for P. multocida serotype D. Our research discovered new subgenotypes for BoHV-1.2c, BRSV gene subgroup IX, and P. multocida serotype D in China's cattle herds. In the BRDC cases, bovine suppurative or caseous necrotizing pneumonia was highly related to BVDV [odds ratio (OR) = 4.18; 95% confidence interval (95% CI): 1.6-10.7], M. bovis (OR = 2.35; 95% CI: 1.1-4.9), H. somni (OR = 8.2; 95% CI: 2.6-25.5) and T. pyogenes (OR = 13.92; 95% CI: 5.8-33.3). The risk factor analysis found that dairy calves <3 mo and beef calves >3 mo (OR = 5.39; 95% CI: 2.7-10.7) were more susceptible to BRDC. Beef cattle were more susceptible to bovine suppurative or caseous necrotizing pneumonia than dairy cattle (OR = 2.32; 95% CI: 1.2-4.4). These epidemiological data and the new pathogen subgenotypes will be helpful in formulating strategies of control and prevention, developing new vaccines, improving clinical differential diagnosis by necropsy, predicting the most likely pathogen, and justifying antimicrobial use.

Mobilizing care? WeChat for older adults' digital kinship and informal care in Wuhan households

The COVID-19 pandemic saw the digital amplify all aspects of our lives—work, sociality, health, intimacy, care, and inequality. In a time of restrictions and physical distancing, the role of the digital for social inclusion—especially for older adults—was heightened with many having to care at a distance. Our study focuses on older adults from Wuhan and the role of the dominant social media app, WeChat, for intergenerational informal care through digital literacy during and after the pandemic. Often characterized in global media as the place where the virus began, many of the quotidian experiences of Wuhan people have been overlooked. We reflect upon ethnographic fieldwork conducted in Wuhan in 2020–2021 with 10 households. We are particularly interested in how kinship care practices in Wuhan households—as sites for complex configurations of intergenerational practices that converge digital, social, and material worlds—have shifted during the pandemic. We ask: what are the learnings, opportunities and limitations around smartphone apps like WeChat for informal care as part of filial piety? In sum, what are the possibilities and limitations for mobilizing care? © The Author(s) 2023.

Preparation of the Monoclonal Antibody against the African Swine Fever Virus p54 Protein and Identification of the Antigenic Epitope.

The aim of this paper was to prepare specific monoclonal antibody (mAb) against African swine fever virus (ASFV) p54 protein. The p54 protein was expressed in Escherichia coli expression system and used as the antigen in mAb production. The spleen cells from the immunized BALB/c mice were fused with myeloma cells SP2/0. To screen the positive hybridoma cells, the purified p54 protein was used as envelope antigen for indirect ELISA. After four times' subcloning, the supernatant of hybridoma cells were used to identify mAb subtype, ascites were prepared via in vivo induction method in mice and then the mAb was purified. The titer of the mAb was detected by indirect ELISA, and the specificity of the mAb was identified by cross reactivity assay, IFA and Western blot. According to the predicted secondary structure of p54 protein, using the stepwise truncation method identified the epitope region of mAbs, and labeled the region in tertiary structure of p54 protein. Results were as follows: six hybridoma cells secreting p54 monoclonal antibody were successfully screened and named 28G12-1, 31G7-1, 31G7-2, 35F10-1, 35F10-2, 38D3-1, respectively. The heavy chains of 28G12-1, 31G7-1, and 31G7-2 were IgG2a type, the heavy chains of 35F10-1, 35F10-2, 38D3-1 were IgG1 type, light chains were all kappa chains. The lowest titer of mAb was 1:25 600, and having no cross reaction with PRRSV, PRV, PEDV, PPV, SADS-CoV, PCV2, the specificity was strong. All six monoclonal antibodies could recognize the 127-146 aa on carboxyl end. In this study, ASFV p54 protein and p54 monoclonal antibody were successfully obtained, and the epitopes of six mAbs were identified, these experimental data laid a foundation for the functional research of p54 protein and the study of ASFV epitope vaccine. Copyright © 2023 Editorial Board, Institute of Animal Science of the Chinese Academy of Agricultural Sciences. All rights reserved.

Optimization of Needle Plane Measurement for Dorsal Hand Injection Based on Linear Structured Light Scanning

Medical professionals have started favoring the use of non-contact intravenous injection robots owing to their importance during the COVID-19 outbreak. However, there are currently few studies considering the robot's needle insertion angle, and most of the needle insertion operations are performed at a steep angle. This increases the rate of puncture failure, and sometimes causes significant pain in patients depending on their individual differences. Therefore, the intravenous injection of the dorsal hand is performed in this study to investigate the determination of the robot's needle insertion angle. with a focus on the optimization of the measurement data to ensure accuracy in the calculation of the needle insertion angle. First, the space point cloud of the needle insertion area on the dorsal hand is obtained by combining a monocular camera with the linear structured light scanning method , and the dorsal hand plane is obtained via fitting dorsal hand point clouds using the least squares method. During the calibration process for the linear structured light system , the measurement error is eliminated by formulating an error function and using the optimization method to iteratively solve it. Subsequently. the needle insertion angle is determined based on the obtained needle insertion area plane. Finally, experiments are conducted for the accuracy verification of the proposed method. Based on the experimental results, the average error in the optimized structured light plane position is approximately 0. 1 mm, and this serves as a foundation for subsequent automatic injection studies.

Social distance monitoring of site workers for COVID-19 using context-guided data augmentation, deep learning, and homography transformation

Because of the COVID-19 pandemic, many industries have developed efforts to minimize COVID-19’s spread. For example, the construction industry in Melbourne practices social distancing and downsizes the number of workers on the job site. The surveillance system integrated with deep learning models has been extensively utilized to enhance construction safety. However, such 2D-based approaches suffer from occlusions, and the workers may not be accurately detected under this circumstance. To this end, this paper proposes a novel context-guided data augmentation method to enhance deep learning models’ performance under occlusions. The context-guided method can automatically augment images by adding occlusions to the objects. Using this way, deep learning models can learn the object’s features in various occlusion scenarios. Later, this method is validated by a real-time social distancing violation detection system. Specifically, this system utilizes a modified YOLOv4 model to detect workers by bounding boxes. Then, the DeepSORT algorithm is used to track the worker trajectories. Finally, homography transformation is used to calculate the distance between workers in each frame. The system has revealed robust results using the data augmentation method, and promising results indicate that the system can well support worker health during COVID-19.

Behavioral plasticity mediates adaptation to changes in food provisioning following the COVID-19 lockdown in black-headed gulls (Larus ridibundus)

The 2020 COVID-19 lockdown provides an opportunity to assess how the anthropause affected the behavior of birds. Black-headed gulls (Larus ridibundus) wintering at Dianchi Lake (Yunnan Province, southwestern China) prefer to forage on easily accessible human-provided food at various sites along the lake. Following the closure of the lake because of the pandemic, synthetic food was provided at a single location. We expected that the home range size and distribution of gulls would change in response to these changes in food provisioning. A total of 91 gulls were tagged with satellite transmitters in November 2018 and March 2019, and their movements were tracked during the winter months. We analyzed their home range size and spatial distribution in four periods, SCP2019, SOP2019, SCP2020, and SOP2020 (Scenic Opening/Closing Period in 2019/2020), and the difference between SOP2019 and SCP2019 was used as the control group. The eutrophication level in the wintering periods "Nov. 2018-Apr. 2019" and "Oct. 2019-Apr. 2020" was determined using the Normalized Difference Vegetation Index (NDVI), and the coverage ratio of algal blooms and NDVI were used as indicators of the amount of naturally available food. The home range sizes of gulls were reduced in SCP2020 compared with SOP2019, SCP2019, and SOP2020. The gulls were most abundant in the 600-900 m buffer zone and least abundant in the 0-300 m buffer zone in SCP2019;they were most abundant in the 0-300 m buffer zone and least abundant in the 900-2000 m buffer zone in SCP2020. These patterns were consistent with variation in the NDVI and the coverage ratio of algal blooms among buffer zones. Changes in wintering behaviors in SCP2020 relative to other periods suggested that gulls modified their behavior following anthropause-related changes in the distribution and provisioning of food. Our findings provide insights into the role of behavioral plasticity in mediating adaptation to changes in human activities in birds.

Global Economic Effects of COVID-19: Analysis Based on Hybrid Model

Global economy has been destroyed by the COVID-19 pandemic, which has rendered many of the world's population impoverished. More uncertainties about the social policies will appear. Meanwhile, there are many researchers devoted themselves into using machine learning to analyze the economics. tarting from the decrease of population, the health crisis has translated to an economic crisis. The spread of the virus encouraged social distancing which led to the shutdown of financial markets, corporate offices, business and event. In this paper, we use the dataset provided by Kaggle platform to analyze the economic effects COVID-19 brings. We choose serval metrics, such as the Human Development Index, the total death caused by virus. The model is a hybrid one which combine AdaBoost and Linear Regression. AdaBoost is a kind of boosting model with an optimal performance. We also do the compared experiments using the metric: MSE, the result shows that our model owns the best performance with the lowest MSE score 7.23. The KNN, Random Forest are respectively 2.58 and 2.55 higher than that of our hybrid model. © 2022 SPIE. All rights reserved.

Dynamic connectedness of China's green bonds and asset classes

This paper quantifies the co-movement and time-varying integration between China's green bonds and other asset classes across different time domains using the wavelet coherence and time-frequency connectedness model based on the time-varying parameter VAR (TVP-VAR). First, we predominantly detect a strong positive co-movement of green and conventional bonds, especially in the medium and long term. Second, strong bidirectional spillovers exist between green bonds and treasury, corporate, and financial bonds regardless of the time horizon. Lastly, cross-market spillovers between the green bonds and the stock, energy, low-carbon stock market were quite limited in the short-run but strengthened towards the long-term except during the 2015 China stock market crash and the COVID-19 recession when short-term integration rose sharply. The results document some practical enlightenment for investors and policymakers with various time horizons. © 2022 Elsevier Inc.