ABSTRACT
The identification of the source of heavy metal pollution and its quantification are the prerequisite of soil pollution control. The APCS-MLR, UNMIX and PMF models were employed to apportion pollution sources of Cu, Zn, Pb, Cd, Cr and Ni of the farmland soil in the vicinity of an abandoned iron and steel plant. The sources, contribution rates and applicability of the models were evaluated. The potential ecological risk index revealed greatest ecological risk from Cd. The results of source apportionment illustrated that the APCS-MLR and UNMIX models could verify each other for accurate allocation of pollution sources. The industrial sources were the main sources of pollution (32.41~38.42%), followed by agricultural sources (29.35~31.65%) and traffic emission sources (21.03~21.51%); and the smallest proportion was from natural sources of pollution (11.2~14.42%). The PMF model was easily affected by outliers and its fitting degree was not ideal, leading to be unable to get more accurate results of source analysis. The combination of multiple models could effectively improve the accuracy of pollution source analysis of soil heavy metals. These results provide some scientific basis for further remediation of heavy metal pollution in farmland soil.
ABSTRACT
This study aimed to investigate the impact of entrepreneurial educational support (NEES), entrepreneurial activities support (NEAS), and entrepreneurial commercialization support (NECS) on the nascent entrepreneurial intention (NEI) by mediating roles of entrepreneurial self-efficacy (NESE), opportunity recognition (OR), and the moderating effect of meaning in life (MLI). Data were gathered using a survey questionnaire from the 868 management, engineering, technical, and vocational institute students of China. The NEI model was analyzed using the partial least squares structural equation modeling through Smart-PLS software. The findings of the study reveal that NEES, NEAS, and NECS have a positive effect on NEI. Meanwhile, results indicate that NESE and OR partially mediate the relationship between entrepreneurship support programs and nascent entrepreneurial intention. Furthermore, the relationship between NESE and the NEI was insignificantly influenced by MLI, and the relationship between OR and the NEI was significantly moderated by MLI. Lastly, implications and limitations are also discussed in this article.
ABSTRACT
This study aims to help enterprises enhance their innovation capabilities in the environment of knowledge economy globalization and stand out in the fierce industry competition. Firstly, data on existing higher education theories and innovation theories are analyzed. Secondly, two companies in the sample data are selected for detailed analysis. Finally, research conclusion and corresponding talent management strategies are presented. The results show that the cumulative contribution value of employees is 87.496%. The cumulative contribution value of human capital is 70.322%. The contribution value of cumulative innovation performance is 61.658%. The cumulative contribution value of R&D investment is 45.306%. The coefficient for the overall sample size is 0.509. The employee quality coefficient is 0.452. The correlation coefficient for educational attainment is 0.598. The high-tech service industry has the highest correlation coefficient at 0.504. The auto industry has the highest coefficient at 0.669. The experimental research has drawn the following conclusion: (1) Talents positively affect enterprise innovation performance; (2) Research and Development (R&D) investment has a positive correlation with enterprise innovation performance; (3) R&D investment has a positive correlation with talents. Through experimental research, the education level of employees is measured by academic qualifications, but the essence of academic qualification measurement is the level of knowledge and skills that employees have. In summary, the study can extend the strategic analysis of the cultivation of innovative talents and play a valuable auxiliary role in cultivating innovative talents.
ABSTRACT
Breast cancer (BC) is one of the most common cancers among women in both developed and developing countries with a rising incidence. Using the MMTV-PyMT transgenic mouse model and xenografted breast cancer model, we found that R5, a neutralizing antibody to Robo1, significantly inhibited BC growth and metastasis. Angiogenesis is involved in the growth and metastasis of BC. Interestingly, R5 significantly decreases microvessel density in BC tissues, and inhibits blood vessel formation and development in in vivo chick embryo chorioallantoic membrane (CAM), yolk sac membrane (YSM) and Matrigel plug models. To investigate whether its anti-breast cancer efficacy is ascribed to its direct antiangiogenic properties, xenografted breast cancer model on CAM was established. Furthermore, R5 significantly reduces the tube formation of the vascular plexus on xenografted breast tumor on CAM. R5 also suppresses the migration and the tubular structure formation of human umbilical vein endothelial cells (HUVECs) by down-regulating the expression of filamin A (FLNA). These findings show that R5 has the potential to be a promising agent for the treatment of BC by suppressing the tumor-induced angiogenesis.
