Lei Jiang

Family firms not only play an important role in economic growth but should also be held partly responsible for environmental degradation. Employing normative stakeholder theory and analyzing unique Chinese survey data via stepwise regression models, our findings indicate that second-generation successors did not significantly impact family firms' environmental investment. However, among second-generation successors, we find that successors with international experience positively impacted environmental investment. The propensity score matching (PSM) and two-stage least squares estimation (2SLS) approaches confirm our results. As an interdisciplinary study, our research is of great value to the environmental responsibility and family business literature.

Through a literature analysis, this study proposes that the difference between scientific innovation and technological innovation has been ignored in the current research on the level of scientific and technological innovation and its influencing factors. Combined with multidimensional proximity and knowledge type of current research, a theoretical induction has been carried on their corresponding relation with scientific innovation and technological innovation, research hypotheses were proposed the multidimensional proximity effect on the mode and degree of scientific innovation and technological innovation, five theoretical factors, which are the economic development level, regional economic structure, the level of opening to the outside world, science and technology input and education input, are proposed to affect the level of scientific innovation and technological innovation. In this study, the Yangtze River Delta region of China from 2001 to 2018 is selected as the research sample, and the two hypotheses proposed are tested through a mixed method of exploratory spatial data analysis and spatial panel econometric model. The main conclusions are as follows: i) As an exogenous variable, geographical proximity has a small impact on the level of scientific innovation, but a large impact on the level of technological innovation; ii) As endogenous variables, theoretical influencing factors may not play a significant role in the actual environment due to the complex influence of multidimensional proximity; iii) Based on the idea of improving multidimensional proximity and the actual situation of the region and the city, we can formulate policies conducive to improving the regional and urban innovation environment.

Patients requiring deep brain stimulation due to intracerebral metallic foreign substances have not been reported elsewhere in the world. Additionally, the long-term effects of metallic foreign bodies on deep brain stimulation are unknown. A 79-year-old man with a 5-year history of Parkinson's disease reported that, 40 years ago, while playing with a pistol, a metallic bullet was accidentally discharged into the left brain through the edge of the left eye, causing no discomfort other than blurry vision in the left eye. DBS was performed due to the short duration of efficacy for oral medication. Because the bullet was on the left subthalamic nucleus electrode trajectory and the patient's right limb was primarily stiff, the patient received globus pallidus interna -DBS implantation in the left hemisphere and STN-DBS implantation in the right hemisphere. During a 6-month postoperative follow-up, the patient's PD symptoms were effectively managed with no noticeable discomfort.

Financial internationalization leads to similar fluctuations and spillover effects in financial markets around the world, resulting in cross-border financial risks. This study examines comovements across G20 international stock markets while considering the volatility similarity and spillover effects. We provide a new approach using an ICA- based ARMA-APARCH-M model to shed light on whether there are spillover effects among G20 stock markets with similar dynamics. Specifically, we first identify which G20 stock markets have similar volatility features using a fuzzy C-means time series clustering method and then investigate the dominant source of volatility spillovers using the ICA-based ARMA-APARCH-M model. The evidence has shown that the ICA method can more accurately capture market comovements with nonnormal distributions of the financial time series data by transforming the multivariate time series into statistically independent components. Our findings indicate that the G20 stock markets are clustered into three categories according to volatility similarity. There are spillover effects in stock market comovements of each group and the dominant source can be identified. This study has important implications for investors in international financial markets and for policymakers in G20 countries.