Based on the China Migrants Dynamic Survey (CMDS) data from 2018 and the data from 58 large- and medium-sized cities in China, in this paper a hierarchical linear model was used to investigate the impact of demographic characteristics, social participation, and economic and social development on the perceived social integration of new urban immigrants at the individual and urban levels. The results revealed the following: (1) social participation, gender, age, education, health status, flow time and housing type of new urban immigrants had a significant positive impact on their perceived social integration, while income showed a U-shaped relationship with the sense of urban social integration; (2) macro-urban characteristics regulated the correlation between micro-individual factors and perceived social integration; (3) the significant advantages of new urban immigrants with higher education and more social participation in the process of integration into urban society were more obvious in cities with higher levels of economic development or public services. These findings enriched relevant research on the factors influencing the social integration of new urban immigrants and provided valuable insight with which the government could use to improve urban construction and promote the equalization of basic public services.

In the context of a rapidly aging population, improving the parents’ health outcomes, especially in parents with poorer health, is essential for narrowing elderly health inequality. Using data from the China Health and Retirement Longitudinal Study, we took the university enrollment expansion policy as the instrumental variable and employed the two-stage least square (2SLS) and instrumental variable quantile regression (IVQR) approaches to explore the spillovers of offspring education on the elderly parents’ frailty index. The results show that one additional year of offspring educational attainment was associated with a 0.017 or 4.66% decline in the parents’ frailty index. These spillovers are stronger where parents are cohabiting with their children than when separating (more than 2 times higher). Moreover, there is substantial heterogeneity that is determined by the gender of parents. The spillover on mothers is greater than that on fathers. Further analysis of a cohort of parents with different frailty indexes reveals that the upward spillovers of offspring education on parents’ health are non-linear and non-averaged. The spillovers may diminish as parents own health improves. These spillovers suppress the “Matthew Effect”, which can lead to the further widening of health inequality.

Since the turn of the twenty-first century, the issue of aging has gained international attention. Both developed and developing nations are currently dealing with this issue. To ensure the sustained and healthy growth of the economy and society in the face of an aging society, it is especially important to establish a scientific old-age insurance system and a reasonable retirement system. We are all aware that the key indicators for the state to control the old-age insurance system in the old-age insurance system are the income and expenditure balance of the old-age insurance pooling account and the analysis of the ideal retirement age. In this paper, a better machine algorithm is used. By independently learning the rules present in a large amount of data and gaining new experience and knowledge, machine learning (ML) can increase computer intelligence and give computers decision-making abilities comparable to those of humans. In general, a machine learning algorithm uses the laws it derives from data to predict unknown data after automatically analysing the data. This study’s findings suggest that the ideal retirement age and life expectancy are positively correlated, with the ideal retirement age’s growth rate 12.57 percent higher than that of life expectancy.

The labor participation of the elderly is an important level of labor supply in China, and healthy human capital is one of the main factors affecting the labor participation of the elderly. Based on the data of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) in 2014, this paper uses the Probit model to empirically analyze the impact of the healthy human capital of the elderly in China on their labor force participation rate. The results show that when individual characteristic variables, family characteristic variables and social characteristic variables are added, healthy human capital is positively correlated with labor participation of retired elderly people. The better health status is, the higher labor participation rate is. With the decline in health status, the labor force participation rate of retired elderly people decreased significantly. The influence of healthy human capital on labor participation of the elderly in China is also heterogeneous between urban and rural areas, gender and age, among which the influence of healthy human capital on labor participation of the elderly in rural areas, males and young age groups is higher than that in urban areas, females and elderly retirees.

In this work, we measured the time-resolved terahertz spectroscopy of GeSn thin film and studied the ultrafast dynamics of its photo-generated carriers. The experimental results show that there are photo-generated carriers in GeSn under femtosecond laser excitation at 2500 nm, and its pump-induced photoconductivity can be explained by the Drude-Smith model. The carrier recombination process is mainly dominated by defect-assisted Auger processes and defect capture. The first- and second-order recombination rates are obtained by the rate equation fitting, which are (2.6 ± 1.1) × 10−2 ps−1 and (6.6 ± 1.8) × 10−19 cm3 ps−1, respectively. Meanwhile, we also obtain the diffusion length of photo-generated carriers in GeSn, which is about 0.4 μm, and it changes with the pump delay time. These results are important for the GeSn-based infrared optoelectronic devices, and demonstrate that GeSn materials can be applied to high-speed optoelectronic detectors and other applications.