Objective: Pulmonary complications could badly affect the recovery of neurological function and neurological prognosis of neurological critically ill patients. This study evaluated the effect of high-flow nasal cannula therapy on decreasing pulmonary complications in neurologically critically ill patients.Patients and Methods: The patients admitted to the intensive care unit with serious neurological disease and receiving oxygen therapy were retrospectively reviewed. Patients were divided into the HFNC group and the conventional oxygen therapy group. We analyzed the data within these two groups, including (...) patients’ baseline data, short-term outcomes of respiratory complications, general outcomes including hospital stay, ICU stay and mortality, and neurological functions. To analyze the relevant factors, we performed multivariable logistic regression analysis.Results: A total of 283 patients met the criteria, including 164 cases in the HFNC group and 119 cases in the COT group. The HFNC group had remarkably less mechanical ventilation requirement with lower phlegm viscosity. Even more, ICU stay and total hospital stay were significantly shortened in the HNFC group.Conclusion: HFNC decreased pulmonary complications in neurologically critically ill patients and improved recovery of neurological function and neurological prognosis. (shrink)

In recent years, the green aviation technology draws more attention, and more hybrid power units have been applied to the aerial vehicles. To achieve the high performance and long lifetime of components during varied working conditions, the effective regulation of the energy management is necessary for the vehicles with hybrid power unit. In this paper, power prediction-based model predictive control for energy management strategy is proposed for the vehicle equipped with HPU based on turboshaft engine in order to maintain proper (...) battery’s state of charge and decrease turboshaft engine’s exhaust gas temperature. First, a modeling approach based on data-driven method is adopted to obtain the mathematical model of turboshaft engine considering time delay and inertial of states. An integrated power predictor consisting of the classification of input status and the subpredictors are developed based on the deep learning method to improve the accuracy of the prediction model of the model predictive control. Subsequently, an EMS based on MPC using the proposed power predictor is introduced to regulate the SOC of battery and the EGT of turboshaft engine. The comparison with experimental results shows the high accuracy of mathematical model of turboshaft engine. The simulation results show the effectiveness of the proposed EMS for the vehicle, and the effects of different weight coefficients of objective function on the proposed EMS are discussed. (shrink)

本书收录了胡适、梁启超、冯友兰、萧公权等名家论中国哲学史、中国思想史的文章20余篇.