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In the wind turbine wake control research, the analytical wake model does not consider the influence of direct control parameters on the wind turbine wake flow field, and its prediction accuracy is by no means satisfying. The numerical simulation method can accurately predict the wake effect, but its low computational efficiency renders it unable to be used in the iterative control optimization study. In this paper, a new wake model coupled with the direct control parameters (tip speed ratio and pitch angle) of a single wind turbine is built based on the machine learning algorithm for which the widely applied Artificial Neural Network (ANN) is applied for instance. By combining the ANN wake model with different wake superposition models, the best combinatorial model for quantitative evaluation of multiple wake interferences is achieved, which not only has great accuracy but also ensures high calculation efficiency. On top of the established combinatorial wake model, three in-line wind turbines are investigated for assessing the effectiveness of wake control optimization with respect to the traditional greedy control. The results show that by optimizing the control parameters (tip speed ratio and pitch angle) of wind turbines, the total power of the three wind turbine units is increased by 1.15~3.48% depending on the incoming wind speeds and distances apart between wind turbines. The power variation of each wind turbine shows that the increase in total power is achieved by the decreased power of the first wind turbine and the increased power of the second and third wind turbines. The research verifies the effectiveness of adopting optimized wind turbine wake control on the total wind farm power improvement numerically. [ABSTRACT FROM AUTHOR]

Background: Since the end of 2022, Azvudine was widely used to treat hospitalized coronavirus disease 2019 (COVID-19) patients in China. However, data on the real-world effectiveness of Azvudine against severe outcomes and post-COVID-19-conditions (PCC) among patients infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variants was limited. This study evaluates the effectiveness of Azvudine in hospitalized COVID-19 patients during a SARS-CoV-2 Omicron BA.5 dominance period., Methods: From 1 November 2022 to 1 July 2023, an SARS-CoV-2 Omicron BA.5 dominant period, we conducted a single-center retrospective cohort study based on hospitalized patients with laboratory-confirmed SARS-CoV-2 infection from a tertiary hospital in Shihezi, China. Patients treated with Azvudine and usual care were propensity-score matched (PSM) at a 1:1 ratio to a control group in which patients received usual care only, with matching based on covariates such as sex, age, ethnicity, number of preexisting conditions, antibiotic use at admission, and baseline complete blood cell count. The primary outcomes were all-cause death and short-term (60 days) PCC post discharge. The secondary outcomes included the initiation of invasive mechanical ventilation and PCC at long-term post discharge (120 days). Cox proportional hazards (PH) regression models were employed to estimate the hazard ratios (HR) of Azvudine treatment for both all-cause death and invasive mechanical ventilation, and logistic regression models were used to estimate the odds ratios (OR) for short-term and long-term PCC. Subgroup analyses were performed based on a part of the matched covariates., Results: A total of 2,639 hospitalized patients with SARS-CoV-2 infection were initially identified, and 2,069 ineligible subjects were excluded from analyses. After matching, 297 Azvudine recipients and 297 matched controls were eligible for analyses. The incidence rate of all-cause death was relatively lower in the Azvudine group than in control group (0.007 per person, 95% confidence interval [CI]: 0.001, 0.024 vs 0.128, 95% CI: 0.092, 0.171), and the use of Azvudine was associated with a significantly lower risk of death (HR: 0.049, 95% CI: 0.012, 0.205). Subgroup analyses suggested protection of Azvudine against the risks of all-cause death among men, age over 65, patients without the preexisting conditions, and patients with antibiotics dispensed at admission. Statistical differences were not observed between the Azvudine group and the control group for the risks of invasive mechanical ventilation or short and long-term PCC., Conclusions: Our findings indicated that Azvudine was associated with lower risk of all-cause death among hospitalized patients with Omicron BA.5 infection in a real-world setting. Further investigation is needed to explore the effectiveness of Azvudine against the PCC after discharge.