Search

Abstract Intravenous thrombolysis is the preferred treatment modality for acute ischemic stroke. In China, written informed consent from patients or proxies must be obtained before intravenous thrombolysis is performed, which always leads to in-hospital delay of thrombolysis. To explore the relationship between characteristics of thrombolysis decision-making and psychological states of proxies of AIS patients. This was a pilot study. 231 proxies of AIS patients were recruited, including 147 males and 84 females. STAI, WFPTS, CAOT, CPS, C-DCS and time-consuming of decision-making were collected by trained nurses during the period from signing informed consent to thrombolysis finished. The general information was collected within 24 h after admission. Pearson correlation analysis and the Ridge regression analysis were used to explore the correlation and causality between psychological indicators (STAI, WFPTS, CAOT, CPS) and decision-making characteristics (C-DCS, Time consuming). Structural equation modeling was used to explore the direct and indirect effect of psychological factors on decision-making characteristics. The mean of anxiety, trust in physicians, and decision conflict were 49.20 ± 9.50, 37.83 ± 6.63 and 30.60 ± 14.77, respectively. The CAOT was associated with C-DCS through the mediation of STAI and WFPTS (p

The highly anisotropic crystal structure of β-Ga2O3 gives rise to a variety of crystal planes, among which the (310) plane is a potentially stable close-packed plane for the O sublattice. In this paper, we report the β-Ga2O3 single crystal and substrates with a (310) major plane grown by the spontaneous nucleation technique in the casting method. High-quality crystal growth and substrate processing were confirmed by the 25.67 arc sec full width at half maximum and the 0.25 nm surface roughness. The nanoindentation experiments revealed the (310) substrate's better elastic recovery than that of (100) substrate. The Young's modulus and hardness of (310) substrates were 200 and 7.6 GPa, respectively. The surface barrier height and the Schottky barrier height were 1.25 and 0.92 eV, respectively. First principles calculations identified the (310)-Ga-I plane as the most stable surface configuration of the (310) plane under oxygen-poor condition, with a surface energy density of 1.48 J/m2. The (310) twin boundary formation around the O sublattice has a high energy density of 0.55 J/m2, suggesting its unlikelihood of spontaneous formation. These properties of (310) plane facilitate a high-quality crystal processing and epitaxial growth, thus endowing potential applications in high-quality power devices. Furthermore, the growth and fabrication of the (310) plane provide a route toward understanding the properties of β-Ga2O3 and advancing the growth techniques of oxide crystals. [ABSTRACT FROM AUTHOR]

Reliable interval forecasts can quantify the potential risk of wind speeds, which can help people make better use of wind energy. In this study, a new probabilistic prediction model, called Quantile Regression Closed-Form Continuous-time Neural Network (QRCfC), is proposed by combining quantile regression and closed-form continuous-time neural network. A new combined model combining QRCfC, secondary decomposition, multi-objective optimization, and dynamic weight combination strategy is proposed, which makes full use of the advantages of each single model to obtain accurate deterministic prediction and reliable probabilistic interval prediction of wind speed. First, the original wind speed series is divided into several subseries using a secondary decomposition technique built on variational mode decomposition and singular spectrum analysis. Then, four base models are used to predict these subseries separately. After that, the predicted values of the four base models are input into QRCfC for training, where the hyperparameters of QRCfC are dynamically adjusted by a multi-objective ant lion optimization algorithm. Finally, to verify the effectiveness of the proposed models, experiments are conducted using data sets from three wind farms in Gansu, China. Simulation results show that the proposed model achieves excellent prediction performance in both deterministic and probabilistic prediction. For example, compared with the unoptimized quantile regression time convolution network, quantile regression long-short time memory, quantile regression gated recurrent unit, and quantile regression neural network, the proposed model reduces the MAPE by 21.89% and the CRPS by 11.14% for 1-step prediction at site 1. [ABSTRACT FROM AUTHOR]

In order to improve the multi-step prediction of wind speed, a hybrid prediction model based on data signal decomposition and grey wolf optimization algorithm was proposed to optimize extreme learning machine. Firstly, the original wind speed time series was decomposed into several intrinsic mode functions and a residual sequence using the complete ensemble empirical mode decomposition with adaptive noise, and the partial autocorrelation function model input. Then, the model was built and the prediction was made on the decomposition subsequence. An extreme learning machine neural network with multi-input-multi-output strategy was constructed, and grey wolf algorithm was used to solve the weight and bias of the optimal hidden layer. Finally, the subsequence was reconstructed and the final prediction result was obtained. Simulation experiments were conducted using multiple sets of measured data with a time resolution of 15 minutes. The root mean square errors of the proposed model in the three wind farms were 0.859, 0.925, and 0.927, respectively, which were lower than other comparative models, verifying the effectiveness of the model in predicting wind speed in the next four hours, i. e. 16 steps prediction. [ABSTRACT FROM AUTHOR]

The effect of an insulation lid on the growth of 4-inch β-Ga2O3 single crystals by the Czochralski method is analyzed by numerical simulation. The insulation lid mainly hinders upward radiant heat transfer from the melt and crucible and increases the axial temperature gradient in the crystal. Such benefits make the melt/crystal interface convex, which is conducive to suppressing spiral growth and growing large crystals with high quality. Materials with low thermal conductivity λ and low emissivity ε are the optimal choices for making an insulation lid. The inner hole has a great influence on the isolation of radiant heat, and it is determined that the maximum size of the inner diameter D i n should not be larger than 130 mm. Thermal stress analysis results indicated that the insulation lid will cause a better stress distribution, illustrating the effect of the insulation lid on the quality of a cylindrical crystal. [ABSTRACT FROM AUTHOR]