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Zhonghua Yu Fang Yi Xue Za Zhi ; 57(5): 659-666, 2023 May 06.
Article in Chinese | MEDLINE | ID: covidwho-2323871


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.

COVID-19 , Male , Humans , Adult , Adolescent , Young Adult , Middle Aged , Infant, Newborn , Infant , Child, Preschool , Child , SARS-CoV-2 , Infectious Disease Incubation Period , Asymptomatic Infections
Topics in Antiviral Medicine ; 31(2):216, 2023.
Article in English | EMBASE | ID: covidwho-2318367
Journal of Hospitality and Tourism Education ; 35(1):73-87, 2023.
Article in English | Scopus | ID: covidwho-2246289
Food Bioscience ; 52, 2023.
Article in English | Scopus | ID: covidwho-2237584


As a non-thermal food processing technology, Electron beam (E-beam) irradiation has been used to enhance microbial safety by deactivating unwanted spoilage and pathogenic microorganisms in food industry. This study evaluated the effects of E-beam irradiation at doses killing SARS-COV-2 on qualities and sensory attributes. The results showed that irradiation caused little effect on the proximate composition, amino acid content, texture, and sensory attributes (P > 0.05). However, E-beam increased TBARS (Thiobarbituric acid reactive substances) and lowered vitamin E content in dose-dependently. Irradiation up to 10 kGy significantly decreased unsaturated fatty acid (UFA) content and inhibited the increase in TVB-N (The total volatile basic nitrogen) while reducing cohesiveness and chewiness (P < 0.05). E-beam irradiation with 7–10 kGy caused greater ΔE values (ΔE > 5) via the significant increase of b*, accompanied by big visual difference in shrimp (P < 0.05). A dose of 4 kGy E-beam irradiation was recommended without altering its physicochemical properties and sensory attributes. © 2023 Elsevier Ltd

2022 International Conference on Smart Transportation and City Engineering, STCE 2022 ; 12460, 2022.
Article in English | Scopus | ID: covidwho-2228771


Under the influence of the fifth industrial revolution and the outbreak of COVID-19, the digital transformation of enterprises has entered a new stage of rapid development. Digital transformation has become the trend of enterprise operation in the digital economy era. In this context, enterprise laboratory asset operation has also become an important aspect of enterprise digital operation. It is urgent to build a set of enterprise laboratory asset digital evaluation system to assist the implementation of enterprise digital strategy. Based on the characteristics of laboratory assets and the closed-loop theory of asset operation management, this paper analyzes and studies the laboratory asset management, establishes a targeted evaluation index system of digital asset management, focuses on the composition of the digital operation system of laboratory assets, and constructs a management index evaluation system of assets, efficiency, cost and other dimensions, so as to create a real-time, comprehensive and comprehensive evaluation system The closed-loop and full cycle digital management ecological environment realizes the effective integration of laboratory resource fragmentation information and the complete embodiment of digitization, provides service support for continuously improving asset management performance, and provides support for further improving enterprise economic efficiency and operation level. © 2022 SPIE.

2022 International Conference on Smart Transportation and City Engineering, STCE 2022 ; 12460, 2022.
Article in English | Scopus | ID: covidwho-2223543
Journal of Theoretical and Applied Electronic Commerce Research ; 17(4):1741-1768, 2022.
Article in English | Web of Science | ID: covidwho-2200472
5th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2022 ; : 225-234, 2022.
Article in English | Scopus | ID: covidwho-2120784
Journal of Hospitality and Tourism Education ; 2022.
Article in English | Scopus | ID: covidwho-2017324
Transboundary and Emerging Diseases ; 69(2):632-644, 2022.
Article in English | Africa Wide Information | ID: covidwho-1971026
47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 ; 2022-May:8177-8181, 2022.
Article in English | Scopus | ID: covidwho-1948777
Open Forum Infectious Diseases ; 8(SUPPL 1):S89-S91, 2021.
Article in English | EMBASE | ID: covidwho-1746775
2021 International Conference on Data Analytics for Business and Industry, ICDABI 2021 ; : 478-485, 2021.
Article in English | Scopus | ID: covidwho-1699573
SAGE Open ; 11(4), 2021.
Article in English | Scopus | ID: covidwho-1505093
2020 International Conference on Robots and Intelligent Systems, ICRIS 2020 ; : 378-382, 2020.
Article in English | Scopus | ID: covidwho-1447857
35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence ; 35:4846-4854, 2021.
Article in English | Web of Science | ID: covidwho-1381752
2020 Ninth International Conference of Educational Innovation through Technology ; : 199-204, 2020.
Article in English | Web of Science | ID: covidwho-1273044