Masked Face Recognition System Based on Attention Mechanism

With the continuous development of deep learning, the face recognition field has also developed rapidly. However, with the massive popularity of COVID-19, face recognition with masks is a problem that is now about to be tackled in practice. In recognizing a face wearing a mask, the mask obscures most of the facial features of the face, resulting in the general face recognition model only capturing part of the facial information. Therefore, existing face recognition models are usually ineffective in recognizing faces wearing masks. This article addresses this problem in the existing face recognition model and proposes an improvement of Facenet. We use ConvNeXt-T as the backbone of the network model and add the ECA (Efficient Channel Attention) mechanism. This enhances the feature extraction of the unobscured part of the face to obtain more useful information, while avoiding dimensionality reduction and not increasing the model complexity. We design new face recognition models by investigating the effects of different attention mechanisms on face mask recognition models and the effects of different data set ratios on experimental results. In addition, we construct a large set of faces wearing masks so that we can efficiently and quickly train the model. Through experiments, our model proved to be 99.76% accurate for real faces wearing masks. A combined accuracy of 99.48% for extreme environments such as too high or lousy contrast and brightness.

Jian-Ti-Kang-Yi decoction alleviates poly(I:C)-induced pneumonia by inhibiting inflammatory response, reducing oxidative stress, and modulating host metabolism.

Jian-Ti-Kang-Yi decoction (JTKY) is widely used in the treatment of COVID-19. However, the protective mechanisms of JTKY against pneumonia remain unknown. In this study, polyinosinic-polycytidylic acid (poly(I:C)), a mimic of viral dsRNA, was used to induce pneumonia in mice; the therapeutic effects of JTKY on poly(I:C)-induced pneumonia model mice were evaluated. In addition, the anti-inflammatory and anti-oxidative potentials of JTKY were also investigated. Lastly, the metabolic regulatory effects of JTKY in poly(I:C)-induced pneumonia model mice were studied using untargeted metabolomics. Our results showed that JTKY treatment decreased the wet-to-dry ratio in the lung tissue, total protein concentration, and total cell count of the bronchoalveolar lavage fluid (BALF). Hematoxylin and Eosin (HE) and Masson staining indicated that the JTKY treatment alleviated the pathological changes and decreased the fibrotic contents in the lungs. JTKY treatment also decreased the expression of pro-inflammatory cytokines [interleukin (IL)-1ß, IL-6, and tumor necrosis factor-alpha (TNF-α)] and increased the levels of immunomodulatory cytokines (IL-4 and IL-10) in the BALF and serum. Flow cytometry analysis showed that the JTKY treatment lowered the ratio of CD86+/CD206+ macrophages in the BALF, decreased inducible nitric oxide synthase (iNOS) level, and increased arginase 1 (Arg-1) level in lung. JTKY also lowered CD11b+Ly6G+ neutrophils in BALF and decreased myeloperoxidase (MPO) activity in lung. Moreover, it also elevated superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities and decreased methane dicarboxylic aldehyde (MDA) level in lung. Untargeted metabolomic analysis showed that the JTKY treatment could affect 19 metabolites in lung, such as L-adrenaline, L-asparagine, ornithine, and alpha-ketoglutaric acid. These metabolites are associated with the synthesis and degradation of ketone bodies, butanoate, alanine, aspartate, and glutamate metabolism, and tricarboxylic acid (TCA) cycle processes. In conclusion, our study demonstrated that treatment with JTKY ameliorated poly(I:C)-induced pneumonia. The mechanism of action of JTKY may be associated with the inhibition of the inflammatory response, the reduction of oxidative stress, and the regulation of the synthesis and degradation of ketone bodies, TCA cycle, and metabolism of alanine, aspartate, glutamate, and butanoate processes in lung.

Masked Face Recognition System Based on Attention Mechanism

With the continuous development of deep learning, the face recognition field has also developed rapidly. However, with the massive popularity of COVID-19, face recognition with masks is a problem that is now about to be tackled in practice. In recognizing a face wearing a mask, the mask obscures most of the facial features of the face, resulting in the general face recognition model only capturing part of the facial information. Therefore, existing face recognition models are usually ineffective in recognizing faces wearing masks. This article addresses this problem in the existing face recognition model and proposes an improvement of Facenet. We use ConvNeXt-T as the backbone of the network model and add the ECA (Efficient Channel Attention) mechanism. This enhances the feature extraction of the unobscured part of the face to obtain more useful information, while avoiding dimensionality reduction and not increasing the model complexity. We design new face recognition models by investigating the effects of different attention mechanisms on face mask recognition models and the effects of different data set ratios on experimental results. In addition, we construct a large set of faces wearing masks so that we can efficiently and quickly train the model. Through experiments, our model proved to be 99.76% accurate for real faces wearing masks. A combined accuracy of 99.48% for extreme environments such as too high or lousy contrast and brightness.

Jian-Ti-Kang-Yi decoction alleviates poly(I:C)-induced pneumonia by inhibiting inflammatory response, reducing oxidative stress, and modulating host metabolism

Jian-Ti-Kang-Yi decoction (JTKY) is widely used in the treatment of COVID-19. However, the protective mechanisms of JTKY against pneumonia remain unknown. In this study, polyinosinic-polycytidylic acid (poly(I:C)), a mimic of viral dsRNA, was used to induce pneumonia in mice;the therapeutic effects of JTKY on poly(I:C)-induced pneumonia model mice were evaluated. In addition, the anti-inflammatory and anti-oxidative potentials of JTKY were also investigated. Lastly, the metabolic regulatory effects of JTKY in poly(I:C)-induced pneumonia model mice were studied using untargeted metabolomics. Our results showed that JTKY treatment decreased the wet-to-dry ratio in the lung tissue, total protein concentration, and total cell count of the bronchoalveolar lavage fluid (BALF). Hematoxylin and Eosin (HE) and Masson staining indicated that the JTKY treatment alleviated the pathological changes and decreased the fibrotic contents in the lungs. JTKY treatment also decreased the expression of pro-inflammatory cytokines [interleukin (IL)-1β, IL-6, and tumor necrosis factor-alpha (TNF-α)] and increased the levels of immunomodulatory cytokines (IL-4 and IL-10) in the BALF and serum. Flow cytometry analysis showed that the JTKY treatment lowered the ratio of CD86+/CD206+ macrophages in the BALF, decreased inducible nitric oxide synthase (iNOS) level, and increased arginase 1 (Arg-1) level in lung. JTKY also lowered CD11b+Ly6G+ neutrophils in BALF and decreased myeloperoxidase (MPO) activity in lung. Moreover, it also elevated superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) activities and decreased methane dicarboxylic aldehyde (MDA) level in lung. Untargeted metabolomic analysis showed that the JTKY treatment could affect 19 metabolites in lung, such as L-adrenaline, L-asparagine, ornithine, and alpha-ketoglutaric acid. These metabolites are associated with the synthesis and degradation of ketone bodies, butanoate, alanine, aspartate, and glutamate metabolism, and tricarboxylic acid (TCA) cycle processes. In conclusion, our study demonstrated that treatment with JTKY ameliorated poly(I:C)-induced pneumonia. The mechanism of action of JTKY may be associated with the inhibition of the inflammatory response, the reduction of oxidative stress, and the regulation of the synthesis and degradation of ketone bodies, TCA cycle, and metabolism of alanine, aspartate, glutamate, and butanoate processes in lung.

Qing-Wen-Jie-Re Mixture Ameliorates Poly (I:C)-Induced Viral Pneumonia Through Regulating the Inflammatory Response and Serum Metabolism.

Qing-Wen-Jie-Re mixture (QWJR) has been used in the treatment of the coronavirus disease 2019 (COVID-19) in China. However, the protective mechanisms of QWJR on viral pneumonia remain unclear. In the present study, we first investigated the therapeutic effects of QWJR on a rat viral pneumonia model established by using polyinosinic-polycytidylic acid (poly (I:C)). The results indicated that QWJR could relieve the destruction of alveolar-capillary barrier in viral pneumonia rats, as represented by the decreased wet/dry weight (W/D) ratio in lung, total cell count and total protein concentration in bronchoalveolar lavage fluid (BALF). Besides, QWJR could also down-regulate the expression of inflammatory factors such as tumor necrosis factor-alpha (TNF-α), interleukin (IL)-1ß and IL-6. More M1-type macrophage polarization was detected by calculating CD86+ cells and CD206+ cells and validated by the decline of inducible nitric oxide synthase (iNOS) and elevated arginase-1 (Arg-1) in lung. Finally, serum untargeted metabolomics analysis demonstrated that QWJR might take effect through regulating arginine metabolism, arachidonic acid (AA) metabolism, tricarboxylic acid (TCA) cycle, nicotinate and nicotinamide metabolism processes.

Corrigendum to: Do Stay at Home Orders and Cloth Face Coverings Control COVID-19 in New York City? Results From a SIER Model Based on Real-world Data.

[This corrects the article DOI: 10.1093/ofid/ofaa442.].

Severe Acute Respiratory Syndrome Coronavirus 2 Viral RNA Load Status and Antibody Distribution Among Patients and Asymptomatic Carriers in Central China.

This study aimed to monitor severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral loads and specific serum-antibodies (immunoglobulin [Ig] G and M) among confirmed patients and asymptomatic carriers from returning healthy travelers. The throat swabs, sputum, and stool samples from 57 hospitalized coronavirus disease (COVID-19) patients and 8 asymptomatic carriers, among 170 returning healthy travelers were tested using reverse-transcription real-time polymerase chain reaction. SARS-CoV-2 IgM/IgG antibodies were detected via serum chemiluminescence assay. Sequential results showed higher viral RNA loads in the throat, sputum, and stool samples at 3-12 and 6-21 days after symptom onset among severely ill COVID-19 patients. Shorter viral habitation time (1-8 days) was observed in the oropharyngeal site and intestinal tract of asymptomatic carriers. The IgG and IgM response rates were 19/37 (51.4%) and 23/37 (62.6%) among the 29 confirmed patients and 8 asymptomatic carriers, respectively, within 66 days from symptom or detection onset. The median duration between symptom onset and positive IgG and IgM results was 30 (n=23; interquartile range [IQR]=20-66) and 23 (n=19; IQR=12-28) days, respectively. Of 170 returning healthy-travelers to China, 4.7% were asymptomatic carriers (8/170) within 2 weeks, and the IgG and IgM positivity rate was 12.8% (12/94). IgM/IgG-positivity confirmed 3 suspected SARS-CoV-2 cases, despite negative results for SARS-CoV-2 RNA. Compared with other respiratory viral infectious diseases, COVID-19 has fewer asymptomatic carriers, lower antibody response rates, and a longer antibody production duration in recovered patients and the contacted healthy population. This is an indication of the complexity of COVID-19 transmission.

Prelicensure Nursing Students' COVID-19 Attitude Impact on Nursing Career Decision during Pandemic Threat in Taiwan: A Cross-Sectional Study.

The COVID-19 pandemic may cause a nursing shortage. Prelicensure nursing students who are exposed to high-stress COVID-19 events are related to defective career decision-making. This study validated the COVID-19 attitude scale and clarified how their attitudes about COVID-19 affected their behavioral intentions toward career decision-making. We conducted a cross-sectional study and recruited a convenience sample of 362 prelicensure nursing students from Northern and Central Taiwan. Two measurements were applied, including the Nursing Students Career Decision-making instrument and COVID-19 attitude scale. We used AMOS (version 22.0) to perform a confirmatory factor analysis. The Cronbach α of the COVID-19 attitude scale was 0.74 and consisted of four factors. The most positive attitude was the nursing belief factor, and the least positive factor was emotional burden. Prelicensure nursing students' COVID-19 attitudes were significantly positively associated with their career decision-making attitudes and perceived control (ß = 0.41 and ß = 0.40, respectively; p < 0.001). All the key latent variables explained significantly 23% of the variance in the career decision-making behavioral intentions module. In conclusion, the COVID-19 attitude scale is valid. Although the prelicensure nursing students' COVID-19 attitudes had no direct effect on career decision-making intentions, they had a direct effect on career decision-making attitudes and the perceived control.

Medical Mask Wearing During Treatment for Patients Undergoing Radiotherapy in COVID-19 Pandemic - An Experience of Protocol Setup and Dosimetric Evaluation for Particle/Proton Beam Therapy.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic has caused extreme challenges for the healthcare system. Medical masks have been proven to effectively block disease transmission. Radiotherapeutic departments are at unique risk for disease exposure with the repeated daily treatment schedule. A protocol of mask wearing during daily treatment was established, and the effect of wearing medical masks on dosimetry during proton beam therapy (PBT) was validated. METHODS: A department protocol of medical mask wearing was initiated after the COVID-19 pandemic. Medical masks that were made under standardized specification and regulation were obtained for analyses. The physical and dosimetric characteristics of these medical masks were measured by different proton energies using commercialized measurement tools. RESULTS: Patients and staff were able to adopt the protocol on a weekly basis, and no adverse events were reported. The average physical thickness of a single piece of medical mask was 0.5 mm with a water equivalent thickness (WET) of 0.1 mm. CONCLUSION: Our study revealed that mask wearing for patients undergoing daily radiotherapy is feasible and can provide basic protection for patients and staff. The impact of mask wearing on dosimetry was only 0.1 mm in WET, which has no impact on clinical PBT treatment. A medical mask-wearing policy can be applied safely without dosimetric concerns and should be considered as a standard practice for PBT centers during the COVID-19 pandemic.

Do Stay at Home Orders and Cloth Face Coverings Control COVID-19 in New York City? Results From a SIER Model Based on Real-world Data.

BACKGROUND: Public health interventions have been implemented to contain the outbreak of coronavirus disease 2019 (COVID-19) in New York City. However, the assessment of those interventions-for example, social distancing and cloth face coverings-based on real-world data from published studies is lacking. METHODS: The Susceptible-Exposed-Infectious-Removed (SEIR) compartmental model was used to evaluate the effect of social distancing and cloth face coverings on the daily culminative laboratory confirmed cases in New York City (NYC) and COVID-19 transmissibility. The latter was measured by Rt reproduction numbers in 3 phases that were based on 2 interventions implemented during this timeline. RESULTS: Transmissibility decreased from phase 1 to phase 3. The initial R0 was 4.60 in phase 1 without any intervention. After social distancing, the Rt value was reduced by 68%, while after the mask recommendation, it was further reduced by ~60%. CONCLUSIONS: Interventions resulted in significant reduction of confirmed case numbers relative to predicted values based on the SEIR model without intervention. Our findings highlight the effectiveness of social distancing and cloth face coverings in slowing down the spread of severe acute respiratory syndrome coronavirus 2 in NYC.