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  1. Mar 2024
  2. Local file Local file
    Machine Learning for Improving Surface-Layer-Flux Estimates
    1
    1. caozhuyin 10 Mar 2024
      Abstract

      结论：预测结果，好于MOST（MO估计系统地低估了湍流通量的大小，改善了与观测值和减小与观测通量偏离的总幅度。）,不同地点的泛化能力 不足：不含物质通量，预测结果待提升，结果因稳定性而异常，不同季节的泛化能力，运用了不易获得的变量（找到最小观测集）

      This effort demonstrates the potential of ML models to overcome some of the limitations related to the simple regression fits employed to determine the stability correction parameter (only a function of the inverse Obukhov length) and other limitations inherent to the MO formulation of surface-layer fluxes (e.g., assumed homogeneous and stationary conditions).

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  3. Sep 2020
  4. www.thelancet.com www.thelancet.com
    Stability of SARS-CoV-2 in different environmental conditions
    1
    1. ErikStuchly 02 Sep 2020

      Chin, A. W. H., Chu, J. T. S., Perera, M. R. A., Hui, K. P. Y., Yen, H.-L., Chan, M. C. W., Peiris, M., & Poon, L. L. M. (2020). Stability of SARS-CoV-2 in different environmental conditions. The Lancet Microbe, 1(1), e10. https://doi.org/10.1016/S2666-5247(20)30003-3

      is:article lang:en COVID-19 stability environmental condition detection surface contamination temperature infectiousness disinfection virology
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    thelancet.com/journals/lanmic/article/PIIS2666-5247(20)30003-3/fulltext
  5. Feb 2020
  6. www.journalofhospitalinfection.com www.journalofhospitalinfection.com
    Persistence of coronaviruses on inanimate surfaces and its inactivation with biocidal agents
    1
    1. pbk1 09 Feb 2020
      persist on inanimate surfaces like metal, glass or plastic for up to 9 days
      coronavirus half life surface stability
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    journalofhospitalinfection.com/article/S0195-6701(20)30046-3/fulltext