Personal, social, and ecological influences on loneliness and satisfaction among rural-to-urban migrants in Shanghai, China

Working PaperThis study examined personal, social, and ecological influences on loneliness and satisfaction among rural-urban migrants in Shanghai, China. Data used in this study were from the Shanghai Rural-to-Urban Migrant Worker Survey conducted by the Institute of Demographic Research, Fudan University, China. A host of demographic, socioeconomic, psychological, and ecological factors were identified as strong correlates of loneliness and satisfaction. In addition to upward social mobility manifested in socioeconomic achievement and improvement in living condition, living arrangement, psychosocial factors, and ecological contexts also exhibited important influences on mental well-being of rural-to-urban migrants in Shanghai. Friendly and helpful attitudes and equal treatment of the receiving urban community were associated with better mental health of these migrant workers. The effect of private or institutional discrimination was overwhelmingly negative on migrant mental well-being over and above other demographic, socioeconomic and psychological variables. Establishing neighborhood public facilities such as library and gym and taking measures to encourage family reunion of the migrants seem to be potentially fruitful ways to promote migrant mental well-being in China. But most essentially, policy makers should consider ways to reduce institutional inequalities disadvantaging rural-to-urban migrants and to help change the perennial image of rural-to-urban migrants as secondary citizens in cities

Control energy of complex networks towards distinct mixture states

Controlling complex networked systems is a real-world puzzle that remains largely unsolved. Despite recent progress in understanding the structural characteristics of network control energy, target state and system dynamics have not been explored. We examine how varying the final state mixture affects the control energy of canonical and conformity-incorporated dynamical systems. We find that the control energy required to drive a network to an identical final state is lower than that required to arrive a non-identical final state. We also demonstrate that it is easier to achieve full control in a conformity-based dynamical network. Finally we determine the optimal control strategy in terms of the network hierarchical structure. Our work offers a realistic understanding of the control energy within the final state mixture and sheds light on controlling complex systems.This work was funded by The National Natural Science Foundation of China (Grant Nos. 61763013, 61703159, 61403421), The Natural Science Foundation of Jiangxi Province (No. 20171BAB212017), The Measurement and Control of Aircraft at Sea Laboratory (No. FOM2016OF010), and China Scholarship Council (201708360048). The Boston University Center for Polymer Studies is supported by NSF Grants PHY-1505000, CMMI-1125290, and CHE-1213217, and by DTRA Grant HDTRA1-14-1-0017. (61763013 - National Natural Science Foundation of China; 61703159 - National Natural Science Foundation of China; 61403421 - National Natural Science Foundation of China; 20171BAB212017 - Natural Science Foundation of Jiangxi Province; FOM2016OF010 - Measurement and Control of Aircraft at Sea Laboratory; 201708360048 - China Scholarship Council; PHY-1505000 - NSF; CMMI-1125290 - NSF; CHE-1213217 - NSF; HDTRA1-14-1-0017 - DTRA)Published versio