Exploring Social Media for Early Detection of Depression in COVID-19 Patients

The COVID-19 pandemic has caused substantial damage to global health. Even though three years have passed, the world continues to struggle with the virus. Concerns are growing about the impact of COVID-19 on the mental health of infected individuals, who are more likely to experience depression, which can have long-lasting consequences for both the affected individuals and the world. Detection and intervention at an early stage can reduce the risk of depression in COVID-19 patients. In this paper, we investigated the relationship between COVID-19 infection and depression through social media analysis. Firstly, we managed a dataset of COVID-19 patients that contains information about their social media activity both before and after infection. Secondly, We conducted an extensive analysis of this dataset to investigate the characteristic of COVID-19 patients with a higher risk of depression. Thirdly, we proposed a deep neural network for early prediction of depression risk. This model considers daily mood swings as a psychiatric signal and incorporates textual and emotional characteristics via knowledge distillation. Experimental results demonstrate that our proposed framework outperforms baselines in detecting depression risk, with an AUROC of 0.9317 and an AUPRC of 0.8116. Our model has the potential to enable public health organizations to initiate prompt intervention with high-risk patients. © 2023 ACM.

Support vector regression model for flight demand forecasting

Flight demand forecasting is a particularly critical component for airline revenue management because of the direct influence on the booking limits that determine airline profits. The traditional flight demand forecasting models generally only take day of the week (DOW) and the current data collection point (DCP) adds up bookings as the model input and uses linear regression, exponential smoothing, pick-up as well as other models to predict the final bookings of flights. These models can be regarded as time series flight demand forecasting models based on the interval between the current date and departure date. They fail to consider the early bookings change features in the specific flight pre-sale period, and have weak generalization ability, at last, they will lead to poor adaptability to the random changes of flight bookings. The support vector regression (SVR) model, which is derived from machine learning, has strong adaptability to nonlinear random changes of data and can adaptively learn the random disturbances of flight bookings. In this paper, flight bookings are automatically divided into peak, medium, and off (PMO) according to the season attribute. The SVR model is trained by using the vector composed of historical flight bookings and adding up bookings of DCP in the early stage of the flight pre-sale period. Compared with the traditional models, the priori information of flight is increased. We collect 2 years of domestic route bookings data of an airline in China before COVID-19 as the training and testing datasets, and divide these data into three categories: tourism, business, and general, the numerical results show that the SVR model significantly improves the forecasting accuracy and reduces RMSE compared with the traditional models. Therefore, this study provides a better choice for flight demand forecasting.

Predictive value of C-reactive protein-to-albumin ratio for risk of 28-day mortality in patients with severe pneumonia

Objectives: To explore the predictive value of C-reactive protein (CRP)-to-albumin (ALB) ratio (CAR) for the risk of 28-day mortality in patients with severe pneumonia.Methods: A total of 152 patients with severe pneumonia treated from January 2020 to January 2022 were enrolled and assigned into survival group (n=107) and death group (n=45) according to their survival status after treatment for 28 d. Their clinical data were compared, and the influencing factors for 28-day mortality were explored by multiple logistic regression analysis. The receiver operating characteristic (ROC) curve was plotted to assess the value of CAR for predicting 28-day mortality risk. A risk prediction model was constructed, and its prediction efficiency was evaluated.Results: The death group had significantly older age, Acute Physiology and Chronic Health Evaluation (APACHE) II score, Murray Lung Injury Score, Sequential Organ Failure Assessment score, white blood cell count, neutrophil count, red cell volume distribution width, neutrophil-to-lymphocyte ratio (NLR), fibrinogen, procalcitonin, blood lactic acid (Lac), CRP and CAR and significantly lower oxygenation index and ALB than those of the survival group (p<0.05). APACHE II score, NLR, Lac and CAR were independent risk factors for 28-day mortality (p<0.05). AUC of the established prediction model was 0.826, with sensitivity of 88.45 % and specificity of 87.32 %, indicating high discrimination. The nomogram model had clinical value when the risk threshold probability was 11-93 %.Conclusions: CAR is an independent risk factor that shows a high predictive value for the 28-day mortality risk in patients with severe pneumonia.

Integrating the technology acceptance model on online learning effectiveness of emerging adult learners in Guangzhou, China

Due to the Zero-COVID policies implemented in China, students have accepted online education for curriculum learning for a considerable period of time. The objective of the current study was to determine the relationship between perceived usefulness, perceived ease of use, gender, and the online learning effectiveness of emerging adult learners in Guangzhou, China, who were enrolled in a continuing education program. The research framework was created in accordance with the Technology Acceptance Model (TAM). The convenient sampling and snowball sampling methods were used to collect 123 respondents for the study. Findings revealed that perceived usefulness and perceived ease of use were positively associated with online learning effectiveness, but gender was not. The study recommended that school administrators enhance students' perceived usefulness and perceived ease of use to improve the online learning effectiveness. The findings of this study will provide scholars with insights for improving the investment effectiveness of adult education programs. In addition, because online learning tends to be more adaptable and economical than traditional classes, the increase in learning effectiveness can provide schools with justifications to continue utilizing online education even after the pandemic. © 2023 Conscientia Beam. All Rights Reserved.

PHASE 1 CLINICAL TRIALS OF A Q-GRIFFITHSIN NASAL SPRAY FOR SARS-CoV-2 PROPHYLAXIS

Background: The currently approved vaccines do not induce sterilizing immunity against SAR-CoV-2 infection, and immunity wanes over time. A robust broad spectrum topical prophylaxis strategy could protect vulnerable populations in the face of continuous evolution of SARS-CoV-2. The algal antiviral lectin Griffithsin (GRFT), and an engineered oxidation-resistant variant Q-GRFT have robust entry inhibitory activity against SARS-CoV variants of concern, in addition to other respiratory viruses with pandemic potential. We designed a nasal spray to deliver Q-GRFT to the upper respiratory tract mucosa for on-demand use as a broad-spectrum prophylactic. Two clinical trials (Phase 1a and 1b) were conducted to assess safety, tolerability, and pharmacokinetics of Q-GRFT nasal spray in healthy adults. Method(s): Healthy adult volunteers were enrolled in a Phase 1a double blinded, randomized study to receive a single dose of either intranasal Q-GRFT (3.0 mg, 2 sprays per nostril) or placebo at 2:1 ratio. Following a safety review, the Phase 1b study was initiated. Eleven volunteers in Group 1 received 3.0 mg dose once daily, for 7 days. After a safety review, 11 volunteers in Group 2 received a total of 6.0 mg Q-GRFT (3.0 mg twice daily for 7 days). Topical Q-GRFT concentrations were measured by ELISA in collected nasal and nasopharyngeal fluids. Drug levels in plasma were assayed to determine systemic exposure. Viral microneutralization cytopathic effect (CPE) assays were performed against SARS-CoV-2 Omicron BA-5 and MERS-CoV. Result(s): Eighteen adults (24-54 years;Males 58.3%, Females 41.7%;12 Q-GRFT, 6 Placebo), and 22 adults (aged 23-59 years;Males 52.4%, Females 47.6%) were enrolled in Phase 1a and 1b, respectively. In Phase 1a, a single dose of Q-GRFT maintained quantifiable levels in nasal passages and nasopharynx for up to 24 hours. Similarly, Q-GRFT was quantifiable in nasal and nasopharyngeal regions in the Phase 1b study. No dose accumulation effect or systemic exposure was observed. Nasal and nasopharyngeal swab eluates inhibited SARS-CoV-2 Omicron BA.5 and MERS-CoV in CPE assays. Q-GRFT did not modify olfactory sensation. No severe adverse events were reported. Thus, the nasal spray was deemed safe. Conclusion(s): Intranasal Q-GRFT was safe and enhanced mucosal SARSCoV-2 inhibitory activity in human volunteers. The results support further development of Q-GRFT as a broad-spectrum prophylactic against coronaviruses to curb ongoing infections, and for future pandemic preparedness.

Factors influencing the interval from isolation to diagnosis of local COVID-19 in Shaanxi Province.

Objective To understand the epidemiological characteristics of COVID-19 in Shaanxi Province from December 9, 2021 to January 20, 2022, and analyze the factors influencing the interval from isolation to diagnosis. Methods We collected the data of local COVID-19 cases from December 9, 2021 to January 20, 2022 published on the official website of Health Commission of Shaanxi Province. Descriptive statistical method was used to analyze the epidemiological characteristics of COVID-19 in Shaanxi Province. Mann-Whitney U test and Kruskal-Wallis H test were used to compare the differences between groups. The unconditional Logistic regression model was applied to analyze the factors influencing the interval between isolation and diagnosis. Results The outbreak of COVID-19 in Shaanxi Province started on December 9, 2021 and ended on January 20, 2022. The overall change trend of the outbreak showed an "inverted V" shape. A total of 2,080 confirmed local cases were reported, and the main type of disease was mild, with an incidence rate of 5.26/100,000. Xi'an had the most cases, accounting for 98. 69% of the total. The reported cases were mainly concentrated in people aged 21 to 55 years old, with a male-to-female sex ratio of 1.19:1. The median interval from isolation to diagnosis was 3 days, the shortest interval being 0 day and the longest interval being 21 days. Unconditional Logistic regression model analysis showed that the way of finding cases was the factor influencing the interval from isolation to diagnosis. Compared with the way of isolation of the key population, the way of the nucleic acid screening could reduce the risk of late detection of confirmed cases by 89% (OR = 0.11, 95% CI: 0. 07 - 0.16). Conclusion The way of finding cases is the factor influencing the interval from isolation to diagnosis. In the face of the recent intensification of the spread of Omicron variant in mainland China, accurate and rapid identification and detection of confirmed cases can not only reduce the risk of the spread of the epidemic, but also endeavor more time and initiative for the treatment of patients, which is the key to curbing the spread of the epidemic.Copyright © 2023 Xi'an Medical University. All rights reserved.

SARS‑CoV‑2 vaccine and antibody

The Coronavirus Disease 2019 (COVID-19) is caused by SARS-CoV-2 infection. Its pandemic has become a global threat and has dealt a heavy blow to public health, life and the world economy. At present, there is still no specific drug for this virus. In order to improve the resistance of susceptible population, extensive vaccination has been started all over the world. This paper summarizes the research on SARS-CoV-2 vaccine and antibody, in order to provide reference for the prevention and treatment of COVID-19. © 2023 Editorial Board of Medical Journal of Wuhan University. All rights reserved.

Factors influencing the interval from isolation to diagnosis of local COVID-19 in Shaanxi Province.

Objective To understand the epidemiological characteristics of COVID-19 in Shaanxi Province from December 9, 2021 to January 20, 2022, and analyze the factors influencing the interval from isolation to diagnosis. Methods We collected the data of local COVID-19 cases from December 9, 2021 to January 20, 2022 published on the official website of Health Commission of Shaanxi Province. Descriptive statistical method was used to analyze the epidemiological characteristics of COVID-19 in Shaanxi Province. Mann-Whitney U test and Kruskal-Wallis H test were used to compare the differences between groups. The unconditional Logistic regression model was applied to analyze the factors influencing the interval between isolation and diagnosis. Results The outbreak of COVID-19 in Shaanxi Province started on December 9, 2021 and ended on January 20, 2022. The overall change trend of the outbreak showed an "inverted V" shape. A total of 2,080 confirmed local cases were reported, and the main type of disease was mild, with an incidence rate of 5.26/100,000. Xi'an had the most cases, accounting for 98. 69% of the total. The reported cases were mainly concentrated in people aged 21 to 55 years old, with a male-to-female sex ratio of 1.19:1. The median interval from isolation to diagnosis was 3 days, the shortest interval being 0 day and the longest interval being 21 days. Unconditional Logistic regression model analysis showed that the way of finding cases was the factor influencing the interval from isolation to diagnosis. Compared with the way of isolation of the key population, the way of the nucleic acid screening could reduce the risk of late detection of confirmed cases by 89% (OR = 0.11, 95% CI: 0. 07 - 0.16). Conclusion The way of finding cases is the factor influencing the interval from isolation to diagnosis. In the face of the recent intensification of the spread of Omicron variant in mainland China, accurate and rapid identification and detection of confirmed cases can not only reduce the risk of the spread of the epidemic, but also endeavor more time and initiative for the treatment of patients, which is the key to curbing the spread of the epidemic.Copyright © 2023 Xi'an Medical University. All rights reserved.

The Gift of Ancient Times: a Breakthrough in The Tracing of Modern Human Genes

The 2022 Nobel Prize in Physiology or Medicine was awarded to Swedish biologist Svante Pääbo for his decisive contribution to paleoanthropogenomics and human origins. There are various theories about the origin of human beings, and the current mainstream view is: out of the African doctrine. In other words, ancient humans had about three times of migrations. The first time was Homo erectus, the second was Neanderthals and Denisovans, and the third was the ancestors of modern humans. All migrated from Africa to Eurasia. While pioneering a new discipline, paleoanthropogenomics, Svante Pääbo has been refining the "Out of Africa Theory”. With the help of various biological techniques, he delved into the origin of human beings from the perspective of genomics and found that some genetic imprints from ancient humans were retained in our bodies. For example, the STAT2 gene and TLR gene associated with immunity, the EPAS1 gene that contributes to hypoxic respiration and the six genes of chromosome 3 are highly positively correlated with the incidence of COVID-19. This research means that we can go back to the root of certain diseases, rather than limiting our eyes to the genes themselves, and exploring where a gene comes from will be a new way of studying diseases. We summarized his innovations in related biotechnology in the process of research, his exploration of ancient humans based on mitochondrial and nuclear genes and related results, and introduced some genes derived from ancient humans and their related information. © 2022 Institute of Biophysics,Chinese Academy of Sciences. All rights reserved.

Effect of low-to-moderate dose glucocorticoids on viral clearance in COVID-19: a retrospective study.

Objective: To study the effect of low-to-moderate dose glucocorticoid therapy on viral clearance in patients with COVID-19. Methods: A total of 72 patients diagnosed with COVID-19 from January 19 to February 17, 2020 at the First Affiliated Hospital, Zhejiang University School of Medicine were recruited. All patients received oral arbidol and combination of lopinavir/ritonavir or darunavir/cobistitat for antiviral therapy, and symptomatic supportive care. Among them, 51 patients received methylprednisolone (0.75-1.50 mg.kg-1.d-1) (glucocorticoid treatment group), and 21 patients did not use glucocorticoid (control group). The time of virologic negative conversion in sputum and the time of radiologic recovery in lung since onset were compared between the two groups. The Kruskal-Wallis test or Fisher exact test was used to compare the difference between groups. Results: The median ages of the glucocorticoid group and the control group were 52 (45, 62) and 46 (32, 56) years (chi2=4.365, P<0.05). The clinical conditions at hospital admission were different between the two groups (P<0.01). The severe cases accounted for 52.0%, while moderate cases in the control group accounted for 71.4%. The median times from the onset to virologic negative conversion in the two groups were 15 (13, 20) and 14 (12, 20) days (P>0.05). The median times from onset to radiologic recovery were 13 (11, 15) and 13 (12, 17) days in the two groups (P>0.05). In moderate cases, the median times from the onset to virologic conversion in sputum were 13 (11, 18) days in the glucocorticoid group and 13 (12, 15) days in the control group (P>0.05). The median times from onset to radiologic recovery in lung were 12 (10, 15) and 13 (12, 17) days, respectively (P>0.05). Conclusion(s): Low-to-moderate glucocorticoid treatment has no effect on the time of virus clearance in patients with different clinical types of COVID-19, and also no effect on accelerating radiologic recovery in lung, so it is not recommended.Copyright © 2020 by the Chinese Medical Association.

Effect of low-to-moderate dose glucocorticoids on viral clearance in COVID-19: a retrospective study.

Objective: To study the effect of low-to-moderate dose glucocorticoid therapy on viral clearance in patients with COVID-19. Methods: A total of 72 patients diagnosed with COVID-19 from January 19 to February 17, 2020 at the First Affiliated Hospital, Zhejiang University School of Medicine were recruited. All patients received oral arbidol and combination of lopinavir/ritonavir or darunavir/cobistitat for antiviral therapy, and symptomatic supportive care. Among them, 51 patients received methylprednisolone (0.75-1.50 mg.kg-1.d-1) (glucocorticoid treatment group), and 21 patients did not use glucocorticoid (control group). The time of virologic negative conversion in sputum and the time of radiologic recovery in lung since onset were compared between the two groups. The Kruskal-Wallis test or Fisher exact test was used to compare the difference between groups. Results: The median ages of the glucocorticoid group and the control group were 52 (45, 62) and 46 (32, 56) years (chi2=4.365, P<0.05). The clinical conditions at hospital admission were different between the two groups (P<0.01). The severe cases accounted for 52.0%, while moderate cases in the control group accounted for 71.4%. The median times from the onset to virologic negative conversion in the two groups were 15 (13, 20) and 14 (12, 20) days (P>0.05). The median times from onset to radiologic recovery were 13 (11, 15) and 13 (12, 17) days in the two groups (P>0.05). In moderate cases, the median times from the onset to virologic conversion in sputum were 13 (11, 18) days in the glucocorticoid group and 13 (12, 15) days in the control group (P>0.05). The median times from onset to radiologic recovery in lung were 12 (10, 15) and 13 (12, 17) days, respectively (P>0.05). Conclusion(s): Low-to-moderate glucocorticoid treatment has no effect on the time of virus clearance in patients with different clinical types of COVID-19, and also no effect on accelerating radiologic recovery in lung, so it is not recommended.Copyright © 2020 by the Chinese Medical Association.

Effect of low-to-moderate dose glucocorticoids on viral clearance in COVID-19: a retrospective study.

Objective: To study the effect of low-to-moderate dose glucocorticoid therapy on viral clearance in patients with COVID-19. Methods: A total of 72 patients diagnosed with COVID-19 from January 19 to February 17, 2020 at the First Affiliated Hospital, Zhejiang University School of Medicine were recruited. All patients received oral arbidol and combination of lopinavir/ritonavir or darunavir/cobistitat for antiviral therapy, and symptomatic supportive care. Among them, 51 patients received methylprednisolone (0.75-1.50 mg.kg-1.d-1) (glucocorticoid treatment group), and 21 patients did not use glucocorticoid (control group). The time of virologic negative conversion in sputum and the time of radiologic recovery in lung since onset were compared between the two groups. The Kruskal-Wallis test or Fisher exact test was used to compare the difference between groups. Results: The median ages of the glucocorticoid group and the control group were 52 (45, 62) and 46 (32, 56) years (chi2=4.365, P<0.05). The clinical conditions at hospital admission were different between the two groups (P<0.01). The severe cases accounted for 52.0%, while moderate cases in the control group accounted for 71.4%. The median times from the onset to virologic negative conversion in the two groups were 15 (13, 20) and 14 (12, 20) days (P>0.05). The median times from onset to radiologic recovery were 13 (11, 15) and 13 (12, 17) days in the two groups (P>0.05). In moderate cases, the median times from the onset to virologic conversion in sputum were 13 (11, 18) days in the glucocorticoid group and 13 (12, 15) days in the control group (P>0.05). The median times from onset to radiologic recovery in lung were 12 (10, 15) and 13 (12, 17) days, respectively (P>0.05). Conclusion(s): Low-to-moderate glucocorticoid treatment has no effect on the time of virus clearance in patients with different clinical types of COVID-19, and also no effect on accelerating radiologic recovery in lung, so it is not recommended.Copyright © 2020 by the Chinese Medical Association.

Nanozyme: a New Approach for Anti-microbial Infections

Bacteria and viruses always posed a threat to human health. Most impressively, SARS-CoV-2 has raged around the world for almost three years, causing huge loss to human health. Facing increasing challenges of drug-resistance and poor treatment efficacy, new solutions are urgently needed to combat pathogenic microorganisms. Recently, nanozymes with intrinsic enzyme-like activities emerged as a promising new type of "antibiotics”. Nanozymes exhibit superior antibacterial and antiviral activities under physiological conditions by efficiently catalyzing generation of a large number of reactive oxygen species. Moreover, enhanced therapeutic effects are achieved in nanozyme-based therapy aided by the unique physicochemical properties of nanomaterials such as photothermal and photodynamic effects. This paper reviews the latest research progress in the field of anti-microbial nanozymes, systematically summarizes and analyzes the principles of nanozymes in the treatment of bacteria and viruses from a mechanistic point of view. An outlook on the future direction and the challenges of new anti-microbial infection nanomaterials are proposed to provide inspiration for developing next generation anti-microbial nanozymes. © 2023 Science Press. All rights reserved.

The influence of board governance structure on tourism enterprises resilience–based on the data of listed Chinese tourism enterprises

Previous research has shown that firms' resources and management capabilities can contribute significantly to differences in firm resilience. However, little is known about the effect of board governance structures on tourism enterprise resilience during industry crises. This study is the first to explore the effects of board governance structure on tourism firms' resilience in the context of the COVID-19 pandemic. Thus, this study constructed an econometric model, applying ordinary least squares and two-stage least squares with instrumental variables. The model was empirically tested using data from listed Chinese tourism companies for 14 months before and after the COVID-19 outbreak. The study's findings show that board structure significantly impacts tourism enterprises' risk resilience. The role of the board governance structure is significantly heterogeneous owing to differences in the proportion of independent directors, the shareholding ratio of directors and the dual role levels of the chairman and general manager of tourism firms. This study extends the growing tourism resilience literature by adding the important variable of board governance structure. The contribution of this study lies in providing strategic suggestions for tourism firms to enhance their resilience by adjusting their board governance structure, thereby increasing their ability to weather unexpected crisis events. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Modeling for understanding of coronavirus disease-2019 (COVID-19) spread and design of an isolation room in a hospital

We have modeled the transmission of coronavirus 2019 in the isolation room of a patient suffering from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at the Royal Brompton Hospital in London. An adaptive mesh computational fluid dynamics model was used for simulation of three-dimensional spatial distribution of SARS-CoV-2 in the room. The modeling set-up is based on data collected in the room during the patient stay. Many numerical experiments have been carried out to provide an optimal design layout of the overall isolation room. Our focus has been on (1) the location of the air extractor and filtration rates, (2) the bed location of the patient, and (3) consideration of the health and safety of the staff working in the area. © 2023 Author(s).

Research on a New Optical Fiber Sensor with High Sensitivity

In order to improve the sensitivity and linearity of the sensor, it is proposed to change the surface roughness of the optical fiber and the type of probe. Firstly, the D-type optical fiber with rough surface is prepared by the self-built wheel optical fiber side polishing system, and then one end of the optical fiber is coated with a layer of Ag film,which can be used as a mirror, so as to obtain the D-type optical fiber probe. Finally, when detecting the sensing characteristics of the probe, it is found that the change of the refractive index of the measured solution will cause the absorption of different energy, which will change the optical power received by the optical power meter. A series of experiments results show that the prepared D-type optical fiber sensor not only has very strong stability, but also has very good linearity. In particular, the sensitivity and linear correlation coefficient of the sensor with polishing loss of 18 dB are as high as 66. 02 dB/RIU and 99. 58%,respectively. The measurement and calculation of the accuracy of refractive index show that the accuracy can be as high as 0. 000 04. The results show that the sensing structure has the potential to be widely used in biochemical sensing (such as COVID-19 pandemic) and realtime monitoring of environmental pollution. © 2022 Sichuan Institute of Piezoelectric and Acoustooptic Technology. All rights reserved.

Work–family conflict, educational involvement, and adolescent academic engagement during COVID-19: An investigation of developmental differences

Objective: In this research, we examine the mediating effect of educational involvement between parental work–family conflict and adolescent academic engagement during COVID-19, as well as the differences among developmental stages. Background: Online learning during the COVID-19 lockdown created challenges for adolescent academic engagement. One of the toughest challenges was that parents experienced increased work–family conflict, making it difficult for them to be involved in adolescent education. In this context, it is essential to understand the impact of parental work–family conflict on adolescent academic engagement. Method: A total of 886 dual-income families participated in the study. Mothers and fathers completed the questionnaire, including questions regarding work–family conflict and educational involvement. Adolescents completed an academic engagement scale. Results: The structural equation model in the total sample showed that parental educational involvement mediated the effect of maternal work–family conflict on adolescent academic engagement. In addition, paternal educational involvement mediated the effect of paternal work–family conflict on adolescent academic engagement. Multigroup analysis indicated the impact of work–family conflict only existed in middle and late adolescence, and mother played a more important role in late adolescence. Conclusion: The study results confirmed the mediating role of parental educational involvement between the relationship of paternal work–family conflict and adolescent academic engagement. Furthermore, this relationship may vary for families with an adolescent at different developmental stages. © 2023 National Council on Family Relations.

A grid management system for COVID-19 antigen detection based on image recognition

Objective: To develop a SARS-CoV-2 antigen detection management system for Chinese residents under community grid management, which is supported by "health information technology" and "neural network image recognition", so as to give full play to the advantages of "grid management". This system is applied to the normalized prevention and control of COVID-19 epidemic. Method(s): The model of image recognition algorithm was built based on deep learning and convolution neural network (CNN) artificial intelligence algorithm. The improved Canny edge detection algorithm was used to monitor and locate the image edge, and then the image segmentation and judgment value calculation were completed according to projection method. The system construction was completed combing with the grid number design. Result(s): The proposed method had been tested and showed the accuracy of the algorithm. With a certain robustness, the algorithm error was proved to be small. Based on the image recognition algorithm model, the development of SARS-CoV-2 antigen detection management system covering user login, paper-strip test image upload, paper-strip test management, grid management, grid warning and regional traffic management was completed. Conclusion(s): Antigen detection is an important supplementary means of COVID-19 epidemic prevention and control in the new stage. The SARS-CoV-2 antigen detection management system for Chinese residents under community grid managemen based on image recognition enables mobile communication devices to recognize the image of SARS-CoV-2 antigen detection results, which is helpful to form a grid management mode for the epidemic and improve the management framework of epidemic monitoring, detection, early warning and prevention and control.Copyright © 2023 The Authors

A new Cosine-Weibull model: Distributional properties with applications to basketball and medical sectors

The two-parameter classical Weibull distribution is commonly implemented to cater for the product's reliability, model the failure rates, analyze lifetime phenomena, etc. In this work, we study a novel version of the Weibull model for analyzing real-life events in the sports and medical sectors. The newly derived version of the Weibull model, namely, a new cosine-Weibull (NC -Weibull) distribution. The importance of this research is that it suggests a novel version of the Wei-bull model without adding any additional parameters. Different distributional properties of the NC-Weibull distribution are obtained. The maximum likelihood approach is implemented to esti-mate the parameters of the NC-Weibull distribution. Finally, three applications are analyzed to prove the superiority of the NC-Weibull distribution over some other existing probability models considered in this study. The first and second applications, respectively, show the mortality rates of COVID-19 patients in Italy and Canada. Whereas, the third data set represents the injury rates of the basketball players collected during the 2008-2009 and 2018-2019 national basketball associ-ation seasons. Based on four selection criteria, it is observed that the NC-Weibull distribution may be a more suitable model for considering the sports and healthcare data sets.(c) 2022 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Alexandria University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/ 4.0/).

Nanozyme: a New Approach for Anti-microbial Infections

Bacteria and viruses always posed a threat to human health. Most impressively, SARS-CoV-2 has raged around the world for almost three years, causing huge loss to human health. Facing increasing challenges of drug-resistance and poor treatment efficacy, new solutions are urgently needed to combat pathogenic microorganisms. Recently, nanozymes with intrinsic enzyme-like activities emerged as a promising new type of "antibiotics". Nanozymes exhibit superior antibacterial and antiviral activities under physiological conditions by efficiently catalyzing generation of a large number of reactive oxygen species. Moreover, enhanced therapeutic effects are achieved in nanozyme-based therapy aided by the unique physicochemical properties of nanomaterials such as photothermal and photodynamic effects. This paper reviews the latest research progress in the field of anti-microbial nanozymes, systematically summarizes and analyzes the principles of nanozymes in the treatment of bacteria and viruses from a mechanistic point of view. An outlook on the future direction and the challenges of new anti-microbial infection nanomaterials are proposed to provide inspiration for developing next generation anti-microbial nanozymes.