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Taitema Lake, situated at the terminus of the Tarim River Basin in Northwest China, represents a crucial ecological resource impacted by climate variability and anthropogenic interventions. In this study, we investigate the dynamic changes in Taitema Lake’s area and water quality resulting from the implementation of an ecological water transfer project in 2000. Leveraging Landsat remote sensing data and comprehensive water quality monitoring, we analyzed the relationship between lake area variations and shifts in water quality parameters. Notably, our findings reveal a significant increase in Taitema Lake’s area from 9.4 km2 in 2000 to 320 km2 in 2013. Concurrently, water quality indicators exhibited marked fluctuations, with total salt content ranging from 45,323.6 mg/L in 2000 to 970.4 mg/L in 2010 before increasing to 14,586.3 mg/L by 2014. Furthermore, a linear regression analysis highlights the moderate positive correlation between lake area and mineralization (R2 = 0.506) and sodium levels (R2 = 0.4907). Additionally, chloride (R2 = 0.5681) and sulfate (R2 = 0.6213) concentrations demonstrated a strong negative correlation with the lake area, indicative of a dilution effect. Furthermore, a comparison of water quality indicators between the years of minimum (2008) and maximum (2013) lake area underscores improvements in pH, chemical oxygen demand, and anionic surfactant concentrations as the lake area increased. Our study provides valuable insights into the effectiveness of ecological water management strategies in restoring and maintaining the ecological health of Taitema Lake, thereby informing evidence-based decision-making for the sustainable management of freshwater resources in arid environments.

In arid regions, ecological water replenishment benefits in desert riparian forests are typically evaluated by assessing changes in hydrology (water area and groundwater depth) and vegetation growth before and after it is implemented. While continuous ecological water delivery may enhance ecological benefits, its trajectory remains uncertain. Under the backdrop of ongoing ecological water delivery, this study examines whether ecological benefits continue to improve and identifies strategies for optimal control and efficient utilization of ecological water. Based on an analysis of groundwater level changes and vegetation changes during early, middle, and late stages of ecological water conveyance in the Tarim River, China (2000–2021), ecological water consumption distribution was revealed. A notable observation is that a wide eco-water conveyance did not significantly impact forest growth indicators, such as tree ring density, crown width, and tree ring size, in Populus euphratica trees. Compared to a century ago, there were significant variations in the growth of P. euphratica tree rings over the 20-year ecological water transfer period. The vegetation coverage on riverbanks increased significantly in the early to mid-stages of ecological water conveyance (2000–2015), but then plateaued in the subsequent years (post-2015). There was a significant upward trend in plant diversity on riverbanks and tail lakes during the early stage (2000–2006), but it declined sharply thereafter (post-2006). A recommendation includes constraining the tail lake's water area and using ecological sluice gates and levees to disperse eco-water away from the river to enhance the efficiency of ecological water utilization. As a result of these findings, rational management systems can be developed in similar arid environments.

Objective. Our previous study found that it could significantly increase the expression of IL32 after stimulating the human umbilical cord mesenchymal stem cells (S-HuMSCs). However, its role on the osteogenesis and cranial bone regeneration is still largely unknown. Here, we investigated the possible mechanism of this effect. Material and Methods. A series of experiments, including single-cell sequencing, flow cytometry, quantitative real-time polymerase chain reaction, and western blotting, were carried out to evaluate the characteristic and adipogenic–osteogenic differentiation potential of IL-32 overexpression HuMSCs (IL-32highHuMSCs) through mediating the P38 signaling pathway. Moreover, a rat skull bone defect model was established and treated by directly injecting the IL-32highHuMSCs to conduct its role on the cranial bone regeneration. Results. In total, it found that compared to HuMSCs, IL32 was significantly increased and promoted the osteogenic differentiation (lower expressions of PPARγ, Adiponectin, and C/EBPα, and increased expressions of RUNX2, ALP, BMP2, OPN, SP7, OCN, and DLX5) in the S-HuMSCs (P0.05). Furthermore, these findings were confirmed by the rat skull bone defect model, in which the cranial bone regeneration was more pronounced in the IL-32highHuMSCs treated group compared to those in the HuMSCs group, with higher expressions of RUNX2, ALP, BMP2, and DLX5 (P

Artificial intelligence has undergone rapid development in the last thirty years and has been widely used in the fields of materials, new energy, medicine, and engineering. Similarly, a growing area of research is the use of deep learning (DL) methods in connection with hydrological time series to better comprehend and expose the changing rules in these time series. Consequently, we provide a review of the latest advancements in employing DL techniques for hydrological forecasting. First, we examine the application of convolutional neural networks (CNNs) and recurrent neural networks (RNNs) in hydrological forecasting, along with a comparison between them. Second, a comparison is made between the basic and enhanced long short-term memory (LSTM) methods for hydrological forecasting, analyzing their improvements, prediction accuracies, and computational costs. Third, the performance of GRUs, along with other models including generative adversarial networks (GANs), residual networks (ResNets), and graph neural networks (GNNs), is estimated for hydrological forecasting. Finally, this paper discusses the benefits and challenges associated with hydrological forecasting using DL techniques, including CNN, RNN, LSTM, GAN, ResNet, and GNN models. Additionally, it outlines the key issues that need to be addressed in the future.

The Taklimakan Desert in northwest China stands as a significant contributor to dust storms, with its fringe oases already designated as ecologically fragile due to the severe impacts of these storms. This study focuses on Moyu County, situated on the southwest edge of the Taklimakan Desert, examining the origin and transport pathways of dust storms from 2004 to 2021. The classification involves utilizing a 36 h backward trajectory model and the k-means clustering technique, resulting in three clusters displaying distinct transport pathways and entry directions. Air pollutant concentrations at the study site corresponding to each cluster are analyzed to elucidate the contribution of dust storms from different directions. The results categorize 1952 dusty days into three categories: NE-SE (cluster 1), N-N (cluster 2), and NW-W (cluster 3). The highest frequency of dust storms, accounting for 64% of the total suspended dust weather, originates from the northeast and southeast direction (NE-SE category), with relatively weak intensity, mainly as suspended dust (71.5%). Strong sand storms predominantly occur from the northwest direction (57.8%). Cluster 1 (the southeast direction) exhibits a higher concentration of SO2, NO2, and CO, mainly associated with its pathway over anthropogenically polluted areas. Conversely, Cluster 3 (northwest direction) shows higher PM10 and PM2.5 concentrations due to increased wind speed and stronger dust storm intensity. The study develops dust storm early warning schemes based on 15-day advance predictions, utilizing an 18-year trajectory model and local monitoring data. This proposed warning scheme serves as a predictive tool for potential dust storm events and air pollution levels, aiding in both scientific research and policy formulation for dust storm mitigation and adaptation. The data obtained also hols relevance for conducting further scientific research in this field.