Search

Evaluating the rural population hollowing (RPH) caused by the massive out-migration of rural laborers is essential for China's rural land use policy formulation and rural revitalization. Existing studies mainly assessed the RPH based on survey data or statistical data. The former is mainly based on selected local villages and towns, and cannot be replicated on a large scale, while the latter is usually at the county or city scale and cannot reveal the cyclical migration of rural labors at fine spatial resolutions such as townships. To fill this gap, this paper proposed a social media data based-rural population hollowing (SM-RPH) index, which was calculated by Tencent User Density big data on holidays and non-holidays and was used to characterize the "migratory bird" process of rural laborers. Taking Guangdong Province, China as the case, this study employed the proposed novel index to evaluate the RPH at the county and township scales. This was integrated with a GWR model to explore how the important contributing factors of RPH vary across the province. The results showed a trend of transition from the cold spot areas in the core regions of PRD to the hot spot areas around the PRD. Additionally, this study revealed that distance to the nearest prefecture-level city, total nighttime lighting per capita, fiscal expenditure per unit of GDP and road network density were dominant factors in affecting rural population hollowing, and the influence of these four variables vary considerably throughout the province. Further, k-means cluster was used to group the hollowing towns according to the local coefficients of the influencing factors, and policy zoning was suggested to provide differentiated countermeasures and suggestions for rural revitalization. This methodological framework can be easily applied to other regions, and is expected to be used to evaluate the return characteristics of migrant workers in real time to help monitor the progress of rural revitalization in China and provide decision support for policy makers. • This study proposed a social media data-based index for assess rural population hollowing (RPH). • The index is effective in evaluating the RPH at fine spatial resolutions such as townships. • We revealed the spatially non-stationary relationship between RPH and the associated factors. • We further put forwards the policy zoning and planning implications for rural revitalization. [ABSTRACT FROM AUTHOR]

Introduction Massive thymic hyperplasia is an extremely rare disorder, with fewer than 60 cases reported so far. Majority of the previous cases occurred in neonates, infants, and older children. Presentation of case A man was found to have an anterior mediastinal mass without any symptoms at 30 years of age. Operation was done successfully. The mass measured 112 mm × 191 mm × 184 mm and weighed 2141 g. Histological and immunohistochemical findings further confirmed the diagnosis of massive thymic hyperplasia. The complication of postoperative chylothorax occurred, which has not been previously reported in MTH. After undergoing conservative treatment, the patient finally recovered. Discussion This is the first case of massive thymic hyperplasia reported in an adult (defined as ≥ 18 years old). Chylothorax is one of the potentially fatal complications. However, we carried out effective treatments, which are educational and clinically interesting to surgeons and clinicians. Conclusion Although not previously reported, massive thymic hyperplasia could also be found in adults. The main treatment for massive thymic hyperplasia is surgical removal. Good clinical effects on post-thymectomy chylothorax are available after undergoing conservative treatment. [ABSTRACT FROM AUTHOR]