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In Wang & Pan (J. Fluid Mech., vol. 918, 2021, A19), the authors developed the first ensemble-based data assimilation (DA) capability for the reconstruction and forecast of ocean surface waves, namely the EnKF-HOS method coupling an ensemble Kalman filter (EnKF) and the high-order spectral (HOS) method. In this work, we continue to enrich the method by allowing it to simultaneously estimate the ocean current field, which is in general not known a priori and can (slowly) vary in both space and time. To achieve this goal, we incorporate the effect of ocean current (as unknown parameters) on waves to build the HOS-C method as the forward prediction model, and obtain a simultaneous estimation of (current) parameters and (wave) states via an iterative EnKF (IEnKF) method that is necessary to handle the complexity in this DA problem. The new algorithm, named the IEnKF-HOS-C method, is first tested in synthetic problems with various forms (steady/unsteady, uniform/non-uniform) of current. It is shown that the IEnKF-HOS-C method is able to not only estimate the current field accurately, but also boost the prediction accuracy of the wave field (even) relative to the state-of-the-art EnKF-HOS method. Finally, using real data from a shipborne radar, we show that the IEnKF-HOS-C method successfully recovers the current speed that matches the in situ measurement by a floating buoy.
The aim of this study was to present the clinical characteristics and dynamic changes in laboratory parameters of the coronavirus disease 2019 (COVID-19) in Guangzhou, and explore the probable early warning indicators of disease progression.
We enrolled all the patients diagnosed with COVID-19 in the Guangzhou No. 8 People’s Hospital. The patients’ demographic and epidemiologic data were collected, including chief complaints, lab results, and imaging examination findings.
The characteristics of the patients in Guangzhou are different from those in Wuhan. The patients were younger in age, predominately female, and their condition was not commonly combined with other diseases. A total of 75% of patients suffered fever on admission, followed by cough occurring in 62% patients. Comparing the mild/normal and severe/critical patients, being male, of older age, combined with hypertension, abnormal blood routine test results, raised creatine kinase, glutamic oxaloacetic transaminase, lactate dehydrogenase, C-reactive protein, procalcitonin, D-dimer, fibrinogen, activated partial thromboplastin time, and positive proteinuria were early warning indicators of severe disease.
The patients outside epidemic areas showed different characteristics from those in Wuhan. The abnormal laboratory parameters were markedly changed 4 weeks after admission, and also were different between the mild and severe patients. More evidence is needed to confirm highly specific and sensitive potential early warning indicators of severe disease.
Under conventional solidification conditions, immiscible alloy melt would undergo large-scale composition segregation after liquid–liquid phase separation, resulting in the loss of properties and application value. In the present study, the ternary immiscible Al70Bi10Sn20 alloy was chosen to study the effect of cooling rate on its resultant microstructure by casting the melt under different cooling conditions. The results indicated that the Al–Bi–Sn alloy with a slow cooling rate exhibits a strong spatial phase separation trend during solidification. However, as the cooling rate increases, the decreasing volume fraction of the segregated Bi–Sn-rich regions indicates the efficient suppression of spatial phase separation. The relatively dispersed distribution of Bi–Sn phase in the Al-rich matrix can be obtained by quenching the melt into water. The influence mechanism of cooling rate on the microstructure of the alloy is also discussed. The present study is beneficial to further tailoring the microstructure of immiscible alloys.