Improved mask detection based on YOLOv5s

COVID-19 epidemic is not over. The correct wearing of masks can effectively prevent the spread of the virus. Aiming at a series of problems of existing mask-wearing detection algorithms, such as only detecting whether to wear or not, being unable to detect whether to wear correctly, difficulty in detecting small targets in dense scenes, and low detection accuracy, It is suggested to use a better algorithm based on YOLOv5s. It improves the generalization and transmission performance of the model by changing the ACON activation function. Then Bifpn is used to replace PAN to effectively integrate the target features of different sizes extracted by the network. Finally, To enable the network to pay attention to a wide area, CA is introduced to the backbone. This embeds the location information into the channel attention. © 2023 SPIE.

The effects of channel width on particle sedimentation in fluids using a coupled lattice Boltzmann-discrete element model

Understanding particle settlement in channeled fluids has wide applications, such as fine particulate matter, coronavirus particle transport, and the migration of solid particles in water. Various factors have been investigated but few studies have acknowledged the channel's effect on settlement dynamics. This study developed a coupled interpolated bounce-back lattice Boltzmann-discrete element model and examined how a channel's width affects particle settlement. A factor k denoting the ratio of the channel's width and the particle diameter was defined. The terminal settling velocity for a single particle is inversely proportional to k, and the time that the particle takes to reach the terminal velocity is positively related to k. When k is greater than 15, the channel width's effects are negligible. For dual particles of the same size, the drafting-kissing-tumbling (DKT) process occurs infinitely in a periodic pattern, with the two particles swapping positions and settling around the channel's centerline. The smaller the k, the sooner the DKT process occurs. The particles collide with the channel wall when k <= 10. For dual particles of different sizes, the DKT process occurs once so that the bigger particle leads the settlement. Both particles settle along the channel's centerline in a steady state. The bigger the k, the bigger the difference in their terminal settling velocities until k = 15. The small particle collides with the channel wall if released under the big particle when k = 6. The findings of this study are expected to inform channeling or pipeline design in relevant engineering practices.

Challenges and Opportunities: Dance Education in the Digital Era

Because of the COVID-19 pandemic, dance education, which is heavily dependent on a face-to-face model, had to change and continue in a virtual environment. How did the rapid adoption of online technologies affect tertiary dance educators' teaching? More importantly, what were the practical ideas and effective tools/strategies learned to move dance scholarship and practice into a post-pandemic era? This study investigates nine tertiary dance educators from Europe, Oceania, North America, and Asia, who conducted online dance classes during the pandemic. This study has utilized multiple sources of data (images, videos, and writings) from dance educators to explore the challenges, benefits, and innovations in the context of virtual dance teaching. Dance educators have shared their views on teaching dance online: tools they have utilized as well as pros and cons with regards to different pedagogies and learning spaces. Findings indicate that the present online model will have a significant impact on future dance education. This article shares lessons and insights on tools, pedagogies, and strategies, which not only support dance education in a post-pandemic era but can also benefit other practice-based subjects at large. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Pericytes may facilitate SARS-CoV-2 entry into the nervous system

Objective: Although the neurological and olfactory symptoms of coronavirus disease 2019 have been identified, the neurotropic properties of the causative virus, severe acute respiratory syndrome-associated coronavirus 2 (SARS-CoV-2), remain unknown. We sought to identify the susceptible cell types and potential routes of SARS-CoV-2 entry into the central nervous system, olfactory system, and respiratory system. Method(s): We collected single-cell RNA data from normal brain and nasal epithelium specimens, along with bronchial, tracheal, and lung specimens in public datasets. The susceptible cell types that express SARS-CoV-2 entry genes were identified using single-cell RNA sequencing and the expression of the key genes at protein levels was verified by immunohistochemistry. We compared the coexpression patterns of the entry receptor angiotensin-converting enzyme 2 (ACE2) and the spike protein priming enzyme transmembrane serine protease (TMPRSS)/cathepsin L among the specimens. Result(s): The SARS-CoV-2 entry receptor ACE2 and the spike protein priming enzyme TMPRSS/cathepsin L were coexpressed by pericytes in brain tissue;this coexpression was confirmed by immunohistochemistry. In the nasal epithelium, ciliated cells and sustentacular cells exhibited strong coexpression of ACE2 and TMPRSS. Neurons and glia in the brain and nasal epithelium did not exhibit coexpression of ACE2 and TMPRSS. However, coexpression was present in ciliated cells, vascular smooth muscle cells, and fibroblasts in tracheal tissue;ciliated cells and goblet cells in bronchial tissue;and alveolar epithelium type 1 cells, AT2 cells, and ciliated cells in lung tissue. Conclusion(s): Neurological symptoms in patients with coronavirus disease 2019 could be associated with SARS-CoV-2 invasion across the blood-brain barrier via pericytes. Additionally, SARS-CoV-2-induced olfactory disorders could be the result of localized cell damage in the nasal epithelium.Copyright © Wolters Kluwer Health, Inc. All rights reserved.

[Performance of screening of contacts of COVID-19 cases in same flight].

Objective: To understand the performance of 2019-nCoV nucleic acid detection in screening of contacts of COVID-19 cases in same flights and provide evidence for the effective screening of persons at high risk for the infection in domestic flights. Methods: The information of passengers who took same domestic flights with COVID-19 cases in China from April 1, 2020 to April 30, 2022 were retrospectively collected,and χ2 test was used to analyze positive nucleic acid detection rates in the passengers in different times before the onsets of the index cases, in different seat rows and in epidemic periods of different 2019-nCoV variants. Results: During the study period, a total of 433 index cases were identified among 23 548 passengers in 370 flights. Subsequently, 72 positive cases of 2019-nCoV nucleic acid were detected in the passengers, in whom 57 were accompanying persons of the index cases. Further analysis of the another 15 passengers who tested positive for the nucleic acid showed that 86.67% of them had onsets or positive detections within 3 days after the diagnosis of the index cases, and the boarding times were all within 4 days before the onsets of the index cases. The positive detection rate in the passengers who seated in first three rows before and after the index cases was 0.15% (95%CI: 0.08%-0.27%), significantly higher than in the passengers in other rows (0.04%, 95%CI: 0.02%-0.10%, P=0.007),and there was no significant difference in the positive detection rate among the passengers in each of the 3 rows before and after the index cases (P=0.577). No significant differences were found in the positive detection rate in the passengers, except the accompanying persons, among the epidemics caused by different 2019-nCoV variants (P=0.565). During the Omicron epidemic period, all the positive detections in the passengers, except the accompanying persons, were within 3 days before the onset of the index cases. Conclusions: The screening test of 2019-nCoV nucleic acid can be conducted in the passengers took the same flights within 4 days before the onsets of the index cases on board. Passengers who seated within 3 rows from the index cases can considered as the close contacts at high risk for 2019-nCoV, for whom screening should be conducted first and special managements are needed. The passengers in other rows can be classified as general risk persons for screening and management.

Extracellular Disintegration of Viral Proteins as an Innovative Strategy for Developing Broad-Spectrum Antivirals Against Coronavirus

The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has claimed millions of lives and caused innumerable economic losses worldwide. Unfortunately, state-of-the-art treatments still lag behind the continual emergence of new variants. Key to resolving this issue is developing antivirals to deactivate coronaviruses regardless of their structural evolution. Here, we report an innovative antiviral strategy involving extracellular disintegration of viral proteins with hyperanion-grafted enediyne (EDY) molecules. The core EDY generates reactive radical species and causes significant damage to the spike protein of coronavirus, while the hyperanion groups ensure negligible cytotoxicity of the molecules. The EDYs exhibit antiviral activity down to nanomolar concentrations, and the selectivity index of up to 20,000 against four kinds of human coronavirus, including the SARS-CoV-2 Omicron variant, suggesting the high potential of this new strategy in combating the COVID-19 pandemic and a future "disease X."

Stress management system development as a condition for human evolution in response to emerging threats

The focus of this article is on how contemporary youth groups are experiencing the stress associated with the transition to distance learning due to the COVID-19 pandemic, quarantine measures, and the demands of social isolation. Considering the world historical experience of building the theory and system of stress management, some organizational measures of improvement of higher education institutions' activity as the main resource of overcoming stress condition of students and study groups are offered.

The impact of COVID-19 on logistics and coping strategies: A literature review

The COVID-19 pandemic has posed many challenges to the continuous development of logistics and has received increasing attention from all sectors of society. This paper systematically reviews 85 related papers;sets the framework of literature analysis on the basis of five fields of logistics: life, e-commerce, healthcare, air transportation, and emergency;systematically composes and analyzes the scope and content of the impact of the COVID-19 pandemic on logistics in different fields;and comprehensively shows the current status of research on the impact of COVID-19 on the continuous development of logistics. On this basis, we combed out the diverse measures of government, enterprises, and related institutions for the logistics problems that have emerged, and put forward some prospects for future research in this field in terms of multi-period strategies, multi-factor evaluation, degree of impacts, and quantification of effects. The work in this paper has some reference value and significance for mitigating or eliminating the negative impact of COVID-19 on the continuous development process of logistics in multiple fields, rationalizing the epidemic response measures and expanding and deepening the research on this topic. © 2023 The Authors. Regional Science Policy & Practice © 2023 Regional Science Association International.

Application of ultrasound-guided peripheral arterial puncture in severe patients with Coronavirus disease 2019 under three-level protection

Objective To explore the application of ultrasound-guided arterial line placement in severe patients with COVID-19. Methods From February to April 2020, we retrospectively collected and analyzed the clinical data of critical patients with COVID-19 with an indwelling peripheral arterial catheter treated by the medical team of Peking Union Medical College Hospital. Patients with ultrasound-guided peripheral arterial catheterization were taken as the study group, while patients whose arterial catheter was placed by traditional palpation were taken as the control group. The puncture condition and complication rate were compared between the two groups. Results A total of 60 severe patients with COVID-19 who met the inclusion and exclusion criteria were enrolled in this study. There were 30 cases in the study group and 30 cases in the control group. In the study group, the success rate of the first catheterization of the peripheral artery (63.3% vs. 26.7%) and the total puncture success rate [(79.43+/- 25.79)% vs. (53.07+/-30.21)%] were higher than those in the control group (all P < 0.05), the puncture times(1.43+/-0.56 vs. 2.50+/-1.28) were less than those of the control group (P < 0.05). The rates of 24-hour disuse (6.7% vs. 30.0%), local hematoma (10.0% vs. 36.7%), occlusion, and tortuous (3.3% vs. 40.0%) in the study group were lower than those in the control group (all P < 0.05). Conclusion Under the three-level protection, ultrasound-guided arterial catheter placement for severe patients with COVID-19 can improve the success rate of catheter placement, reduce puncture times, and reduce the incidence of complications.Copyright © 2021, Peking Union Medical College Hospital. All rights reserved.

Teaching Effect after Changing Mode of Continuing Medical Education during the COVID-19 Pandemic

Objective To explore the teaching effect of the teaching mode changed from traditional teaching to online teaching after the outbreak of coronavirus disease 2019 (COVID-19) pandemic. Methods Relying on the Beijing Women's Health Care Technology Improvement Project, the online and offline continuing medical education was carried out, to train the obstetrician and gynecologist working in 16 maternal and child health care hospitals in 16 administrative regions of Beijing, which was planned from September 2020 to December 2025. This study retrospectively collected the assessment results of the two teaching modes from March 2021 to December 2021 (the first year of the teaching plan), and compared the teaching effects. Results Online teaching completed three sessions of 30 live online conference courses, with about 25 000 participants, including 4757 obstetricians and gynecologists from 16 maternal and child health care hospitals in Beijing. A total of 82 on-site teaching courses were held for offline teaching, and 1771 gynecologists and obstetricians from 16 maternity and child care hospitals in Beijing participated in the study. The scores of online teaching and offline teaching were 90.88+/-4.88 and 88.65+/-4.35, respectively. Conclusions Online teaching maybe has similar teaching effects as offline teaching. Compared with offline teaching, online teaching has more advantages, such as convenience, efficiency and economy, which is worthy of promotion and application in the context of the COVID-19 pandemic.Copyright © 2022, Peking Union Medical College Hospital. All rights reserved.

[Latent period and incubation period with associated factors of COVID-19 caused by Omicron variant].

Objective: To estimate the latent period and incubation period of Omicron variant infections and analyze associated factors. Methods: From January 1 to June 30, 2022, 467 infections and 335 symptomatic infections in five local Omicron variant outbreaks in China were selected as the study subjects. The latent period and incubation period were estimated by using log-normal distribution and gamma distribution models, and the associated factors were analyzed by using the accelerated failure time model (AFT). Results: The median (Q1, Q3) age of 467 Omicron infections including 253 males (54.18%) was 26 (20, 39) years old. There were 132 asymptomatic infections (28.27%) and 335 (71.73%) symptomatic infections. The mean latent period of 467 Omicron infections was 2.65 (95%CI: 2.53-2.78) days, and 98% of infections were positive for nucleic acid test within 6.37 (95%CI: 5.86-6.82) days after infection. The mean incubation period of 335 symptomatic infections was 3.40 (95%CI: 3.25-3.57) days, and 97% of them developed clinical symptoms within 6.80 (95%CI: 6.34-7.22) days after infection. The results of the AFT model analysis showed that compared with the group aged 18-49 years old, the latent period [exp(ß)=1.36 (95%CI: 1.16-1.60), P<0.001] and incubation period [exp(ß)=1.24 (95%CI: 1.07-1.45), P=0.006] of infections aged 0-17 years old were prolonged. The latent period [exp(ß)=1.38 (95%CI: 1.17-1.63), P<0.001] and the incubation period [exp(ß)=1.26 (95%CI: 1.06-1.48), P=0.007] of infections aged 50 years old and above were also prolonged. Conclusion: The latent period and incubation period of most Omicron infections are within 7 days, and age may be a influencing factor of the latent period and incubation period.

Ultra-sensitive Detection of Alzheimer's Biosmarkers Using Plasmonic Optical Fiber Sensors

The emergence of the Covid-19 pandemic has drawn great attention to vulnerable people affected by major diseases. Among them, Alzheimer's disease (AD) is the most prevalent disease. However, a long-standing challenge is to achieve early diagnosis of AD by detecting biomarkers such as amyloid beta (Aβ42), thus avoiding the labor of specialized hospital personnel and the high cost of imaging examinations using positron emission tomography. In this paper, we report a straightforward approach to realize a non-invasive lab-around fiber (LaF) optical sensor for AD biomarker detection, which is based on a tilted fiber Bragg grating (TFBG) combined with a nanoscale metallic thin film. We successfully demonstrated the detection of Aβ42 in complex biological matrices with a detection limit of 5 pg/mL. Therefore, our TFBG-SPR biosensor platform enables large-scale early disease screening and has great potential for clinical applications in early AD diagnosis. © 2022 IEEE.

Machine Learning-Based Scoring System for Early Prognosis Evaluation of Patients with Coronavirus Disease 2019

Background The global spread of coronavirus disease 2019 (COVID-19) continues to threaten human health security, exerting considerable pressure on healthcare systems worldwide. While prognostic models for COVID-19 hospitalized or intensive care patients are currently available, prognostic models developed for large cohorts of thousands of individuals are still lacking. Methods Between February 4 and April 16, 2020, we enrolled 3,974 patients admitted with COVID-19 disease in the Wuhan Huo-Shen-Shan Hospital and the Maternal and Child Hospital, Hubei Province, China. (1) Screening of key prognostic factors: A univariate Cox regression analysis was performed on 2,649 patients in the training set, and factors affecting prognosis were initially screened. Subsequently, a random survival forest model was established through machine analysis to further screen for factors that are important for prognosis. Finally, multivariate Cox regression analysis was used to determine the synergy among various factors related to prognosis. (2) Establishment of a scoring system: The nomogram algorithm established a COVID-19 patient death risk assessment scoring system for the nine selected key prognostic factors, calculated the C index, drew calibration curves and drew training set patient survival curves. (3) Verification of the scoring system: The scoring system assessed 1,325 patients in the test set, splitting them into high- and low-risk groups, calculated the C-index, and drew calibration and survival curves. Results The cross-sectional study found that age, clinical classification, sex, pulmonary insufficiency, hypoproteinemia, and four other factors (underlying diseases: blood diseases, malignant tumor;complications: digestive tract bleeding, heart dysfunction) have important significance for the prognosis of the enrolled patients with COVID-19. Herein, we report the discovery of the effects of hypoproteinemia and hematological diseases on the prognosis of COVID-19. Meanwhile, the scoring system established here can effectively evaluate objective scores for the early prognoses of patients with COVID-19 and can divide them into high- and low-risk groups (using a scoring threshold of 117.77, a score below which is considered low risk). The efficacy of the system was better than that of clinical classification using the current COVID-19 guidelines (C indexes, 0.95 vs. 0.89). Conclusions Age, clinical typing, sex, pulmonary insufficiency, hypoproteinemia, and four other factors were important for COVID-19 survival. Compared with general statistical methods, this method can quickly and accurately screen out the relevant factors affecting prognosis, provide an order of importance, and establish a scoring system based on the nomogram model, which is of great clinical significance. © Wolters Kluwer Health, Inc. All rights reserved.

Residential Segregation as a Barrier to Covid-19 Booster Coverage in Deep South

Background: Coronavirus disease 2019 (COVID-19) had been a stronger hit in Deep South compared with other developed regions in the United States, and vaccination remains a top priority for all eligible individuals. However, there are limited data regarding the progress of booster coverage in the Deep South and how the coverage varies by county and age group, which is of critical importance for future vaccine planning. Racial/ethnic disparities were found in the COVID-19 vaccination, but the vast majority of evidence was generated from studies at the individual level. There is an urgent need for evidence at the population level to reveal and evaluate the booster coverage in racial/ethnic minority communities, which could identify vulnerable communities and inform future healthcare policymaking and resource allocation. We evaluated county-level COVID-19 booster coverage by age group in the Deep South and examined its relationship with residential segregation. Method(s): We conducted an ecological study at the population level by integrating COVID-19 vaccine surveillance data, residential segregation index, and county-level factors across the 418 counties of five Deep South states from December 15, 2021 to October 19, 2022. We analyzed the cumulative percentages of county-level COVID-19 booster coverage by age group (e.g., 12 to 17 years old, 18 to 64 years old, and at least 65 years old) by the end of the study period. We examined the longitudinal relationships between residential segregation, interaction of time and residential segregation, and COVID-19 booster coverage using the Poisson mixed model. Result(s): As of October 19, 2022, among the 418 counties, the median percentage of booster coverage was 40% (interquartile range [IQR]: 37.8-43.0%). Compared with elders, youth and adults had lower percentages of booster uptake. There was geospatial heterogeneity in the COVID-19 booster coverage. Results of the Poisson mixed model found that as time increased, higher segregated counties had lower percentages of booster coverage. Such relationships were consistent across the age groups. Conclusion(s): The progress of county-level COVID-19 booster coverage in the Deep South was slow and varied by age group. Residential segregation precluded the county-level COVID-19 booster coverage across age groups. Future efforts regarding vaccine planning should focus on youth and adults. Healthcare facilities and resources are needed in racial/ethnic minority communities. Residential segregation and COVID-19 booster coverage by age group in the 418 counties across the five Deep South states from December 15, 2021 to October 19, 2022.

Automatic Diagnosis of COVID-19 Based on Machine Learning

The lives and health of individuals are significantly threatened by the extremely infectious and dangerous Corona Virus Disease 2019 (COVID-19). For the containment of the epidemic, quick and precise COVID-19 detection and diagnosis are essential. Currently, artificial diagnosis based on medical imaging and nucleic acid detection are the major approaches used for COVID-19 detection and diagnosis. However, nucleic acid detection takes a long time and requires a dedicated test box, while manual diagnosis based on medical images relies too much on professional knowledge, and analysis takes a long time, and it is difficult to find hidden lesions. Thanks to the rapid development of pattern recognition algorithms, building a COVID-19 diagnostic model based on machine learning and clinical symptoms has become a feasible rapid detection solution. In this paper, support vector machines and random forest algorithms are used to build a COVID-19 diagnostic model, respectively. Based on the quantitative comparison of the performance of the two methods, the future development trends in this field are discussed. © 2023 IEEE.

The strategy on One Health development in China based on SWOT analysis.

The pandemic of Corona Virus Disease 2019 (COVID-19) worldwide has prompted the use One Health concept to solve health problems and improve the public health governance system. Using the Superiority Weakness Opportunity Threats (SWOT) analysis method to analyze the opportunities and challenges brought by the current development of One Health in China. The results show that the current advantage is that the Chinese government attaches great importance to One Health, and Chinese scholars are also actively involved in the development of One Health, but there are still disadvantages of weak foundation and low international influence. At the same time, with the opportunity for more recognition of the concept of One Health in the world, China is facing challenges such as insufficient talent competitiveness and unbalanced development in the development of One Health. In this regard, this paper puts forward the strategies and key research contents for developing One Health in China to provide ideas for promoting the development of One Health in China.Copyright © 2022, National Institute of Parasitic Diseases. All rights reserved.

High-Performance Flexible Humidity Sensor Based on MoOX Nanoparticle Films for Monitoring Human Respiration and Non-Contact Sensing

Flexible humidity sensors with high sensitivity, fast response time, and outstanding reliability have the potential to revolutionize electronic skin, healthcare, and non-contact sensing. In this study, we employed a straightforward nanocluster deposition technique to fabricate a resistive humidity sensor on a flexible substrate, using molybdenum oxide nanoparticles (MoOx NPs). We systematically evaluated the humidity-sensing behaviors of the MoOx NP film-based sensor and found that it exhibited exceptional sensing capabilities. Specifically, the sensor demonstrated high sensitivity (18.2 near zero humidity), a fast response/recovery time (1.7/2.2 s), and a wide relative humidity (RH) detection range (0-95%). The MoOx NP film, with its closely spaced granular nanostructure and high NP packing density, exhibited insensitivity to mechanical deformation, small hysteresis, good repeatability, and excellent stability. We also observed that the device exhibited distinct sensing kinetics in the range of high and low RH. Specifically, for RH > 43%, the response time showed a linear prolongation with increased RH. This behavior was attributed to two factors: the higher physical adsorption energy of H2O molecules and a multilayer physical adsorption process. In terms of applications, our sensor can be easily attached to a mask and has the potential to monitor human respiration owing to its high sensing performance. Additionally, the sensor was capable of dynamically tracking RH changes surrounding human skin, enabling a non-contact sensing capability. More significantly, we tested an integrated sensor array for its ability to detect moisture distribution in the external environment, demonstrating the potential of our sensor for contactless human-machine interaction. We believe that this innovation is particularly valuable during the COVID-19 epidemic, where cross-infection may be averted by the extensive use of contactless sensing. Overall, our findings demonstrate the tremendous potential of MoOx NP-based humidity sensors for a variety of applications, including healthcare, electronic skin, and non-contact sensing.

A Gesture Controlled System to Train and Guide the Healthcare Workers While Donning and Doffing Personal Protective Equipment

During the COVID-19 outbreak, many healthcare workers (HCWs) have been infected because they failed to comply with the correct process of donning and doffing personal protective equipment (PPE). Based on this, we develop a gesture-controlled system that not only can train HCWs but also can give HCWs real-time guidance during the process of donning and doffing PPE. It can effectively prevent the infection of HCWs. We first use the hand detection algorithm to locate the position of the HCWs, helping them to enter the proper area. Then they can use our gesture recognition algorithm to control the playback of the videos which guides them in donning and doffing PPE. We verify the effectiveness of the system through a series of experiments. The results show the great value of our system in the protection of HCWs. © 2022 IEEE.