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To understand the co-evolution in yield-related traits with the breeding, selection, and introduction of genotypes for increased grain yield, field experiments were carried out at two sites in the western area of the Loess Plateau in China that differed in hydrothermal conditions. Sixteen genotypes of spring wheat introduced and grown over the past 120 years were compared in terms of their yield and yield-related traits. As the grain yield increased, the spike number per unit area and the grain number per spike increased linearly, but the 1000-kernel weight was not correlated with grain yield. In the more recent genotypes, anthesis was initiated significantly earlier, although the length of the period from anthesis to maturity remained unchanged. Water use and the Effective Use of Water (EUW) for aboveground biomass before anthesis and the contribution of pre-anthesis aboveground biomass to grain yield all decreased as grain yield increased. Soil water content at anthesis was negatively correlated with aboveground biomass at anthesis, but positively correlated with grain yield. Conclusively, breeding in spring wheat over the past century has increased the yield of new genotypes by (1) increasing the number of grains per unit area; (2) shortening the period of vegetative growth; (3) decreasing EUW and the soil water use before anthesis; thereby (4) retaining more soil water and increasing biomass accumulation after anthesis. Future spring wheat breeding for this dryland region should determine whether the time for grain filling from anthesis to maturity can be extended to enable greater use of environmental resources and higher yields.

BackgroundStroke is a major disease with high morbidity and mortality worldwide. Currently, there is no quantitative method to evaluate the short-term prognosis and length of hospitalization of patients.PurposeWe aimed to develop nomograms as prognosis predictors based on imaging characteristics from non-contrast computed tomography (NCCT) and CT perfusion (CTP) and clinical characteristics for predicting activity of daily living (ADL) and hospitalization time of patients with ischemic stroke.Materials and methodsA total of 476 patients were enrolled in the study and divided into the training set (n = 381) and testing set (n = 95). Each of them owned NCCT and CTP images. We propose to extract imaging features representing as the Alberta stroke program early CT score (ASPECTS) values from NCCT, ischemic lesion volumes from CBF, and TMAX maps from CTP. Based on imaging features and clinical characteristics, we addressed two main issues: (1) predicting prognosis according to the Barthel index (BI)–binary logistic regression analysis was employed for feature selection, and the resulting nomogram was assessed in terms of discrimination capability, calibration, and clinical utility and (2) predicting the hospitalization time of patients–the Cox proportional hazard model was used for this purpose. After feature selection, another specific nomogram was established with calibration curves and time-dependent ROC curves for evaluation.ResultsIn the task of predicting binary prognosis outcome, a nomogram was constructed with the area under the curve (AUC) value of 0.883 (95% CI: 0.781–0.985), the accuracy of 0.853, and F1-scores of 0.909 in the testing set. We further tried to predict discharge BI into four classes. Similar performance was achieved as an AUC of 0.890 in the testing set. In the task of predicting hospitalization time, the Cox proportional hazard model was used. The concordance index of the model was 0.700 (SE = 0.019), and AUCs for predicting discharge at a specific week were higher than 0.80, which demonstrated the superior performance of the model.ConclusionThe novel non-invasive NCCT- and CTP-based nomograms could predict short-term ADL and hospitalization time of patients with ischemic stroke, thus allowing a personalized clinical outcome prediction and showing great potential in improving clinical efficiency.SummaryCombining NCCT- and CTP-based nomograms could accurately predict short-term outcomes of patients with ischemic stroke, including whose discharge BI and the length of hospital stay.Key ResultsUsing a large dataset of 1,310 patients, we show a novel nomogram with a good performance in predicting discharge BI class of patients (AUCs > 0.850). The second nomogram owns an excellent ability to predict the length of hospital stay (AUCs > 0.800).

Dynamics of the horizontal axis wind turbine is investigated in this paper. The wind turbine rotor modelling is based on the nonlinear Eular beam model, the generalized dynamic wake model and the Beddoes-Leishman dynamic stall model are used to predict the aerodynamic loads. The Newton-Rafson iteration is adopted to get the solution in each time step and the second-order backward difference is used in time marching. A horizontal axis wind turbine is analysed in fixed rotor speed and the structural responses in rated conditions and critical wind conditions are obtained. The critical wind velocity is acquired from simulation. The influences of the rotor speed and yaw angle on the critical wind velocity of the rotor are reserched.