下岗（失业）求职人员再就业的预测因素研究

How to improve the reemployment of lay-offs and unemployed is a big concern of Chinese society now. Based on literatures in related fields, the thesis investigated predictive factors of job-seeking behavior, reemployment status, quality of reemployment, psychological health among lay-offs (unemployed), and also the relationship between reemployment and psychological health. Lay-off (unemployed) participants for this study were recruited from four public employment centers in Beijing. participants completed two surveys. Results mainly demonstrated: 1 There were significant relationships between Job-seeking self-efficacy, motivation control and job-seeking frequency; age was negatively associated with job-seeking frequency and mental health; 2 Joh-seeking support was highlighted as the only lagged predictor of reemployment status; job-seeking frequency predicted job satisfaction of reemployed individuals; 3 The mental health of reemployed was significantly improved; but mental health of continously unemployed people deteriorated during these three months. High quality reemployment significantly improved mental health, low quality reemployment had no effect on mental health. The research demostrated some psychological factors predicting reemployment and relationships between reemployment and mental health. The results can improve the understanding relationships of reemployment and psychological factors. The results also can improve effective reemployment counseling and reemployment social services.

Using HPLC retention parameters to estimate fish bioconcentration factors of organic compounds

Reversed-phase high performance liquid chromatography (RP-HPLC) was employed to develop predictive models for fish bioconcentration factors (BCF) of organic compounds. Estimation of BCF from RP-HPLC retention parameters on octadecyl-bonded silica gel (ODS), cyanopropyl-bonded silica gel (CN), and phenyl-bonded silica gel (Ph) columns were investigated. The results show that, for a set of compounds belonging to different chemical classes, the CN stationary phase is the best one among the three columns and better than n-octanol/water model for BCF estimation. A multi-column RP-HPLC model, using the retention parameters on the CN and Ph columns as the variables of multiple linear regression equations, was further evaluated to estimate BCF of organic compounds belonging to different chemical classes, and the results show that the multi-column RP-HPLC model is better than that of any single RP-HPLC column for BCF estimation.