Identifying Population Hollowing Out Regions and Their Dynamic Characteristics across Central China

Continuous urbanization and industrialization lead to plenty of rural residents migrating to cities for a living, which seriously accelerated the population hollowing issues. This generated series of social issues, including residential estate idle and numerous vigorous laborers migrating from undeveloped rural areas to wealthy cities and towns. Quantitatively determining the population hollowing characteristic is the priority task of realizing rural revitalization. However, the traditional field investigation methods have obvious deficiencies in describing socio-economic phenomena, especially population hollowing, due to weak efficiency and low accuracy. Here, this paper conceives a novel scheme for representing population hollowing levels and exploring the spatiotemporal dynamic of population hollowing. The nighttime light images were introduced to identify the potential hollowing areas by using the nightlight decreasing trend analysis. In addition, the entropy weight approach was adopted to construct an index for evaluating the population hollowing level based on statistical datasets at the political boundary scale. Moreover, we comprehensively incorporated physical and anthropic factors to simulate the population hollowing level via random forest (RF) at a grid-scale, and the validation was conducted to evaluate the simulation results. Some findings were achieved. The population hollowing phenomenon decreasing gradually was mainly distributed in rural areas, especially in the north of the study area. The RF model demonstrated the best accuracy with relatively higher R2 (Mean = 0.615) compared with the multiple linear regression (MLR) and the geographically weighted regression (GWR). The population hollowing degree of the grid-scale was consistent with the results of the township scale. The population hollowing degree represented an obvious trend that decreased in the north but increased in the south during 2016–2020 and exhibited a significant reduction trend across the entire study area during 2019–2020. The present study supplies a novel perspective for detecting population hollowing and provides scientific support and a first-hand dataset for rural revitalization

Epidemiological and virological characteristics of pandemic influenza A (H1N1) 2009 in school outbreaks in China

Background: During the 2009 pandemic influenza H1N1 (2009) virus (pH1N1) outbreak, school students were at an increased risk of infection by the pH1N1 virus. However, the estimation of the attack rate showed significant variability. Methods: Two school outbreaks were investigated in this study. A questionnaire was designed to collect information by interview. Throat samples were collected from all the subjects in this study 6 times and sero samples 3 times to confirm the infection and to determine viral shedding. Data analysis was performed using the software STATA 9.0. Findings: The attack rate of the pH1N1 outbreak was 58.3% for the primary school, and 52.9% for the middle school. The asymptomatic infection rates of the two schools were 35.8% and 37.6% respectively. Peak virus shedding occurred on the day of ARI symptoms onset, followed by a steady decrease over subsequent days (p = 0.026). No difference was found either in viral shedding or HI titer between the symptomatic and the asymptomatic infectious groups. Conclusions: School children were found to be at a high risk of infection by the novel virus. This may be because of a heightened risk of transmission owing to increased mixing at boarding school, or a lack of immunity owing to socioeconomic status. We conclude that asymptomatically infectious cases may play an important role in transmission of the pH1N1 virus

FastDMA: an infinium humanmethylation450 beadchip analyzer.

DNA methylation is vital for many essential biological processes and human diseases. Illumina Infinium HumanMethylation450 Beadchip is a recently developed platform studying genome-wide DNA methylation state on more than 480,000 CpG sites and a few CHG sites with high data quality. To analyze the data of this promising platform, we developed FastDMA which can be used to identify significantly differentially methylated probes. Besides single probe analysis, FastDMA can also do region-based analysis for identifying the differentially methylated region (DMRs). A uniformed statistical model, analysis of covariance (ANCOVA), is used to achieve all the analyses in FastDMA. We apply FastDMA on three large-scale DNA methylation datasets from The Cancer Genome Atlas (TCGA) and find many differentially methylated genomic sites in different types of cancer. On the testing datasets, FastDMA shows much higher computational efficiency than current tools. FastDMA can benefit the data analyses of large-scale DNA methylation studies with an integrative pipeline and a high computational efficiency. The software is freely available via http://bioinfo.au.tsinghua.edu.cn/software/fastdma/

The numbers of differentially methylated probes identified by FastDMA and IMA.

<p>The thresholds for the two softwares to identify differentially methylated probes are all set as pvalue <0.01 and FDR <0.05. Each cell shows the number of differentially methylated probes identified in that specified condition. Overlap: number of probes found by both FastDMA and IMA; Genic: genic region; Island: CpG island region; Promoter: promoter region. FastDMA and IMA find more than 98% probes the same.</p

Responses of Ecosystem Services to Climate Change: A Case Study of the Loess Plateau

Exploring the responses of ecosystem services to climate change is an essential prerequisite for understanding the global climate change impact on terrestrial ecosystems and their modeling. This study first evaluated the ecosystem services including net primary productivity (NPP), soil conservation (SC) and water yield (WY), and climate factors including precipitation, temperature, and solar radiation from 2000 to 2020 on the Loess Plateau, and then analyzed their relationships and threshold effects. The results found that precipitation in the region had significantly increased since 2000 while solar radiation decreased; mean annual temperature however did not change significantly. NPP and SC showed an increasing trend while WY showed a decreasing trend. The most significant climate factor affecting ESs was precipitation. With the increase of precipitation, all three types of ecosystem services showed a significant increasing trend, but the facilitating effect for NPP and WY began to be weakened when precipitation reached the thresholds of 490 mm and 600 mm, respectively. This occurred because in regions with already sufficient precipitation to support NPP there is limited capacity for NPP to increase compared to areas of arid grasslands. In these regions, high vegetation cover leads to increased evapotranspiration which reduces the positive influence of increasing precipitation on WY. The results can offer a reference for the level of ecological restoration success

Summarization of the DMR candidates identified by FastDMA.

<p>Summarization of the DMR candidates identified by FastDMA.</p