Temporal-spatial Distribution and Short-range Prediction Indicators of Hail Weather in East Central Haixi Prefecture of Qinghai Province

[ Objective] The study aimed to discuss the temporal-spatial distribution and short-range prediction indicators of hail weather in east central Haixi Prefecture of Qinghai Province. [Method] Using hail data of six stations in east central Haixi Prefecture from 1960 to 2010, the temporal and spatial distribution of hail weather was analyzed firstly. Afterwards, based on the high-altitude factual data of 30 case studies of hail during 2006 -2010, its high-altitude and ground weather situation and physical quantity field were studied to summarize short-term circulation pattern and shod- range prediction characteristics of hail weather. [ Result] In east central Haixi, hail appeared from April to September, and it was most frequently from May to August. Meanwhile, hail was frequent from 14：00 to 20：00. Among the six stations, hail was most frequent in Tianjun but least frequent in Wulan. Moreover, hail disaster mainly occurred in Wulan and Tianjun. In addition, there were three typos of circulation pattern of hail weather at 500 hPa. Hail mainly occurred under the effect of northwest airflow, and it had shortwave trough, cold center or trough, jet stream core or one of the three. Hail appeared frequently under the situation of upper-level divergence and low-level convergence, and abundant water vapor and water vapor flux convergence at low levels were important conditions for hailing. [ Conclusion] The research could provide scientific references for improving the accuracy of hail forecast.

Prediction of the geological indicators in TBM tunnel based on optimized proportion of surrounding rock grades

With tunnel boring machine being used in underground engineering,accurate geological indicators have been the important basis for tunnel boring machine(TBM)construction.Back propagation neural network(BPNN)has been used to predict the geological indicators of tunnels in previous studies.Nevertheless,these studies ignored the imbalance proportion of surrounding rock grades,leading to the indiscriminate use of data,thus affecting the predictive effect of BPNN.In order to prove the importance of the proportion of surround-ing rock grade in geological prediction,we mainly attempt to utilize particle swarm optimization(PSO)to optimize the proportion of sample data,and integrate with BPNN to establish a PSO-BPNN theoretical model to predict geological indicators.At the same time,combined with the actual engineering data,5 tunneling indicators were selected as input and 4 geological indicators were selected as out-put by a variety of dimensionality reduction methods.The geological indicators are density,uniaxial compressive strength,internal fric-tion angle(u)and Poisson’s ratio(e).On this basis,the PSO-BPNN prediction model was established in detail.By comparing the prediction of traditional BPNN,PSO-BPNN and other optimization-integrated models,the result shows that optimized proportion of surrounding rock grades reduces the prediction error and improves the interpretability of the prediction model.Meanwhile,we com-bined the theory of surrounding rock partition to illustrate the rationality of surrounding rock proportion in PSO result,that is,the proportion of complex surrounding rock should be increased appropriately to improve the prediction result.Ultimately,based on the optimization-integrated models with engineering data and the surrounding rock classification theory,the importance of proportion of surrounding rock grades for tunnel geological prediction is confirmed.

Research progress on the electrophysiological indicators to predict the efficacy of vagus nerve stimulation for drug-refractory epilepsy

Vagus nerve stimulation(VNS)is an important treatment option for drug-refractory epilepsy(DRE),with well-established efficacy and safety in clinical practice for more than 20 years.However,it is very difficult to find the optimal electrophysiological indicators for the effectiveness of VNS on DRE because the mechanism of action is unknown.In this review,we provide an update of the potential applications of VNS outcomes in patients with drug-resistant epilepsy.Electroencephalographic(EEG)activity,event-related potentials,EEG synchronization levels,magnetoencephalographic,laryngeal muscle evoked potentials,and heart rate variability are potential biomarkers for VNS outcomes in people with DRE.

Numerical simulation study on the thermal environment in heading face

Based on κ-ε turbulence model, the distributions of the velocity field, tempera- ture field, thermal comfort index, PMV-PPD （Predicted Mean Vote-Predicted Percentage Dissatisfied）, and air quality index, mean age of air were obtained of Zhouyuanshan Coal Mine in -650 m level of a heading face by CFD（Computational Fluid Dynamics）software, Airpak 2.0. Moreover, the human thermal comfort and the air quality of the heading face were analyzed with PMV-PPD and mean age of air indices, which received an intuitive visualization and accurate evaluation results. In order to create a safe, comfortable, and economical underground operating environment, a scientific, rational, and comprehensive prediction and evaluation needed to provide a theoretical and technical basis for coal mine ventilation, cooling, heat harm treatment, and prevention. Meanwhile, from the human thermal comfort and air quality to research the underground environment, it embodied the concept of being human oriented.

Cheminformatics analysis of natural products and indication distribution prediction

As a valuable resource for drug discovery, natural products remain largely unexplored. The cheminformatics analysis of natural product databases could help us know better about natural products, providing valuable information in drug design. In this study, we collected an in-home natural product library consisting of more than 220 000 molecules. The results showed that natural products were distributed more diversely than synthetic compounds and approved drugs in chemical space, and natural products still possessed better scaffold diversity. Besides, natural product scaffolds had more potential in some specific indications, such as antiarthritic, antihypertensive, antiallergic and analgesic. However, the utilization rate of natural product scaffolds is relatively low, especially in terms of potential indications. Therefore, we recommend the greater use of natural products while designing lead libraries.