Search

Background: Against the background of an aging population, older adults living alone in cities are increasingly dependent. However, their use of home and community-based services in China is unsatisfactory. This study attempted to figure out why older adults living alone in cities do not actively seek assistance in China., Methods: In-depth interviews were conducted. A total of 29 older adults were recruited. Content analysis was used to analyze the interview data., Results: Three themes were identified. (1) Desire for independence, despite hardship: The lives of older adults involve many inconveniences, but they preferred to solve problems by themselves, instead of asking for help; (2) Desire to not overburden jiaren (meaning family in Chinese): older adults did not want to disturb families or burden children with caring responsibilities. Moreover, previous experience of failing to obtain care made them reluctant to seek help from jiaren; (3) Desire to not bother wairen (meaning people other than family in Chinese): The lack of trust caused by being unfamiliar with wairen, and the fear of being a burden to others if they were not able to reciprocate, made older adults reluctant to seek help from wairen., Conclusions: Changes in social, economic, and demographic structures have led to gradual failure of family care. Older adults accustomed to an "acquaintance society" have not yet adapted to seeking help from the community. When addressing the problem of care for older adults living alone in cities, it is important to focus on the profound impact of social change., (© 2022. The Author(s).)

Estimation of the water flow from rainfall intensity during storm events is important in hydrology, sewer system control, and environmental protection. The runoff-producing behavior of a sewer system changes from one storm event to another because rainfall loss depends not only on rainfall intensities, but also on the state of the soil and vegetation, the general condition of the climate, and so on. As such, it would be difficult to obtain a precise flowrate estimation without sufficient a priori knowledge of these factors. To establish a model for flow estimation, one can also use statistical methods, such as the neural network STORMNET, software developed at Lyonnaise des Eaux, France, analyzing the relation between rainfall intensity and flowrate data of the known storm events registered in the past for a given sewer system. In this study, the authors propose a fuzzy neural network to estimate the flowrate from rainfall intensity. The fuzzy neural network combines four STORMNETs and fuzzy deduction to better estimate the flowrates. This study's system for flow estimation can be calibrated automatically by using known storm events; no data regarding the physical characteristics of the drainage basins are required. Compared with the neural network STORMNET, this method reduces the mean square error of the flow estimates by approximately 20%. Experimental results are reported herein.