In current international environment, the important goal of improving China industry is to strengthen the independence of the industrial chain. Sci-tech innovation enterprises are the main carrier. They are also the service objects of the Sci-Tech innovation board (“SSE STAR MARKET”).Some sci-tech innovation enterprises are “capital intensive”, some are “technology intensive”, and the others are both. “Capital intensive” enterprises are controlled by the capital side, “technology intensive” enterprises are controlled by core technical team. The importance of “capital” and “technology” should be reflected in the shareholding ratio, which will impact on corporate governance. This paper aim to find out the relationship between team ownership and enterprise attributes. Team shareholding ratio uses ESOP as indicator (ESOP includes core management shareholding and Employee Stock Ownership Plans), and enterprise attributes are quantified by heavy asset ratio, R&D input, company counterbalance system, and institutional investors shareholding ratio. The research object is the listed companies on the SSE STAR MARKET as of June 30, 2023. Datas range from 2019 to 2023. According to the regression result, it is found that: at first, the heavy asset ratio is negatively correlated with ESOP. The higher heavy asset ratio is. the lower ESOP shareholding ratio the enterprises have. Secondly, company counterbalance system is negatively correlated with ESOP. The higer shareholding ratio of 2-5 major shareholders is, the lower ESOP shareholding ratio the enterprises have. Thirdly, there is no significant influence between institutional investors shareholding ratio and ESOP. Fourthly, there is no significant influence between R&D input and ESOP. But along with heavy asset ratio, there has a significant positive correlation with ESOP. That is, R&D input does not affect ESOP alone, it needs to be combined with heavy asset ratio. Fifthly, the results of sub-industry regression are different from the whole. This paper hopes the study can be further extended to the operation of other sci-tech innovative enterprises, and provide an effective way to build a stable corporate governance structure for those enterprises.

Mindfulness meditation is a form of mental training that helps in managing thoughts and guiding individuals to redirect them to be more positive. In the past years, its popularity has grown immensely. Its main appeal is the broad and versatile ways it can be used especially in a healthcare setting. For instance, research on Alzheimer’s disease and dementia has recently been focused on whether chronic stress has a role in inducing these diseases. Since Alzheimer’s disease has no treatment at this point in time, incorporating mindfulness meditation into Alzheimer’s patients’ care/treatment may have a drastic effect on their quality of life by reducing stress. Ideally, practicing mindfulness meditation at a young age would help reduce the probability of chronic stress causing Alzheimer’s disease. However, many people who have already been diagnosed with Alzheimer’s disease do not have that option. The goal of this research is to find at what stage would the implementation of meditation best help to reduce current symptoms and slow the development of current symptoms and development of Alzheimer’s disease in already diagnosed patients.

Attention Deficit Hyperactivity Disorder is a growing problem today, with diagnoses rising as it negatively affects academic performance, employment opportunities, self-perception, and relationship quality. Treatments have remained fairly similar over the last decade, despite proven side effects and, for some treatments, small effect size. The aim of this review is to determine if Mindfulness-Based Interventions (MBIs) can complement these treatments by targeting executive function(s) directly. To do this, this review analyzes data from 17 papers about the effectiveness of MBIs. Results support the effectiveness of MBIs in the treatment of ADHD; however, various limitations within the design of both this study and research on MBIs in general limit the validity of this conclusion. To remedy this, this paper suggests changes to methods and future avenues of research on MBIs for ADHD.