The long-term dynamic comprehensive evaluation of the water resource carrying capacity (WRCC) and the analysis of its potential driving mechanism in arid areas are contemporary research issues and technical means of mitigating and coordinating the conflict between severe resource shortages and human needs. The purpose of this study was to explore the distribution of the WRCC and the spatiotemporal heterogeneity of drivers in arid areas based on an improved two-dimensional spatiotemporal dynamic evaluation model. The results show that (1) the spatial distribution of the WRCC in Xinjiang, China, is high in the north, low in the south, high in the west, and low in the east. (2) From 2005 to 2020, the centers of gravity of the WRCC in northern and southern Xinjiang moved to the southeast and west, respectively, and the spatial distribution exhibited slight diffusion. (3) The factors influencing the WRCC exhibit more obvious spatial and temporal heterogeneity. The domestic waste disposal rate and ecological water use rate were the main factors influencing the WRCC in the early stage, while the GDP per capita gradually played a dominant role in the later stage. (4) In the next 30 years, the WRCC in Xinjiang will increase. The results provide a theoretical reference for the sustainable development of water resources in arid areas.
Gravitation , Water Resources , Humans , China , Diffusion , Head
Circadian clocks are evolved to adapt to the daily environmental changes under different conditions. The ability to maintain circadian clock functions in response to various stresses and perturbations is important for organismal fitness. Here, we show that the nutrient-sensing GCN2 signaling pathway is required for robust circadian clock function under amino acid starvation in Neurospora. The deletion of GCN2 pathway components disrupts rhythmic transcription of clock gene frq by suppressing WC complex binding at the frq promoter due to its reduced histone H3 acetylation levels. Under amino acid starvation, the activation of GCN2 kinase and its downstream transcription factor CPC-1 establish a proper chromatin state at the frq promoter by recruiting the histone acetyltransferase GCN-5. The arrhythmic phenotype of the GCN2 kinase mutants under amino acid starvation can be rescued by inhibiting histone deacetylation. Finally, genome-wide transcriptional analysis indicates that the GCN2 signaling pathway maintains robust rhythmic expression of metabolic genes under amino acid starvation. Together, these results uncover an essential role of the GCN2 signaling pathway in maintaining the robust circadian clock function in response to amino acid starvation, and demonstrate the importance of histone acetylation at the frq locus in rhythmic gene expression.
Circadian Clocks , Neurospora crassa , Acetylation , Amino Acids/metabolism , Circadian Clocks/genetics , Circadian Rhythm/genetics , Fungal Proteins/metabolism , Gene Expression Regulation, Fungal , Histones/metabolism , Neurospora crassa/genetics , Nutrients , Signal Transduction
The ongoing pandemic of COVID-19 has aroused widespread concern around the world and poses a severe threat to public health worldwide. In this paper, the autoregressive integrated moving average (ARIMA) model was used to predict the epidemic trend of COVID-19 in mainland of China. We collected the cumulative cases, cumulative deaths, and cumulative recovery in mainland of China from January 20 to June 30, 2020, and divided the data into experimental group and test group. The ARIMA model was fitted with the experimental group data, and the optimal model was selected for prediction analysis. The predicted data were compared with the test group. The average relative errors of actual cumulative cases, deaths, recovery and predicted values in each province are between -22.32%-22.66%, -9.52%-0.08%, -8.84%-1.16, the results of the comprehensive experimental group and test group show The error of fitting and prediction is small, the degree of fitting is good, the model supports and is suitable for the prediction of the epidemic situation, which has practical guiding significance for the prevention and control of the epidemic situation. HighlightsO_LIWe predicted future COVID-19 occurrences in mainland of China based on ARIMA model. C_LIO_LIWe validated the model based on the previous outbreak data with actual data for June, 2020. C_LIO_LIThe measures taken by the government have contained spread of the epidemic C_LIO_LIThe combination of multiple models may improve the robustness of the model C_LI
