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Stocks price prediction is a current hot spot with great promise and challenges. Recently, there have been many stock price prediction methods. However, the prediction accuracy of these methods is still far from satisfactory. In this paper, we propose a stock price prediction method that incorporates multiple data sources and the investor sentiment, which can be called SILSTM. Firstly, we crawl multiple data sources on the Internet and preprocess them respectively. These data involve stock historical data, technical indicators, and non-traditional data sources, such as stock posts and financial news. Then, we use the sentiment analysis method based on convolutional neural network for the non-traditional data, which can calculate the investors' sentiment index. Finally, we combine sentiment index, technical indicators and stock historical transaction data as the feature set of stock price prediction and adopt the long short-term memory network for predicting the China Shanghai A-share market. The experiments show that the predicted stock closing price is closer to the true closing price than the single data source, and the mean absolute error can achieve 2.386835, which is better than traditional methods. We verified the effectiveness on the real data sets of five listed companies. [ABSTRACT FROM AUTHOR]

• Clinical trials of drug research and development approved by NMPA. • A total of 9,401 clinical trials were analyzed in this article. • Analyzed the phase, indication, dosage form, applicant of the clinical trials. • Analyzed the status and provided proposal for drug R&D in China. The research and development (R&D) of new drugs indicates scientific progress and economic development. However, little is known regarding ongoing or recent clinical trials in China. We analyzed data from clinical trials published before December 31, 2019, and found that the annual registration numbers are increasing annually in the country. Based on clinical indications, most tested drugs target cancers, nervous system, infections, and the cardiovascular system. Furthermore, clinical trials are mostly concentrated in Beijing, Shanghai, and Jiangsu, and conducted by large pharmaceutical companies, with multiple trials for several generic drugs. Going forward, it will be necessary to promote R&D in China of clinically relevant innovative drugs, drug delivery systems, and novel traditional Chinese medicine (TCM) and biological products, as well as to have a balanced distribution of clinical trials to sustainably meet public health needs. [ABSTRACT FROM AUTHOR]