Objective: To explore the relation among new graduates’ career maturity, work value,adaptation status and work performance. Methods: Chinese Student Career Maturity Inventory and Work Value Inventory for College Students were used to test 257 new employees’ career maturity and work value. Job Satisfaction, Role Ambiguity, Role Conflict and Turnover Intention Scales were administered to the employees 3 months later to assess the adaptation status. Their job performance data were collected at the same time with adaptation status, and were collected again after 1 year. Results: ①Sub-factors of career maturity and work value can predict adaptation status, including job satisfaciotn, turnover intention, role ambiguity and role conflict; ②Work value dimension of Reputation, performance after 3 months of joining the company, role ambiguity can significantly predict performance after one year. Conclusion: Newly graduated employees’ work value, career maturity can be predicted by adaptation status and job performance. Further follow-up studies are need for the influence of long-term work.

Predicting the protein binding rate of drugs in plasma is helpful to us in understanding the pharmacokinetic characteristics of drugs, with much value of reference for early research on drug discovery. In this study, plasma protein binding rate information of 2 452 clinical drugs were collected.Two pieces of software, Molecular Operating Environment (MOE) and Mordred, were used to calculate molecular descriptors, which were used as input features of the model.Extreme gradient boosting (XGBoost) algorithm and random forest (RF) algorithm were then used to build a machine learning model.The results showed that, compared with MOE, the prediction performance of the constructed model was better using the molecular descriptor calculated by Mordred as the input of the model.The prediction performance results of the model constructed using the XGBoost algorithm and the RF algorithm were similar, and the R2 of the optimal model were both 0.715.According to the research results, it can be concluded that the drug plasma protein binding rate is closely related to some physical and chemical properties of the drug molecule, such as water solubility, octanol/water partition coefficient and conjugated double bonds.Using these parameters to predict the plasma protein binding rate of drugs has the advantages of convenience and efficiency, which can provide reference for related pharmacokinetic studies.