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In this review, polyoxometalate-based fiber materials, including preparation and application, are introduced, showing promising performances in catalysis and optical property.

【Background and objective】 Groundwater is the most important water resource for agricultural production in many regions around the world and its spatiotemporal changes are affected by a multitude of natural and anthropogenic factors. Understanding their quantitative relationship is hence imperative not only to sustain agricultural production but also to safeguard the development of other sectors. Taking an irrigation district in central China as an example, this paper analyzed the fluctuation of its groundwater depth in response to climate change and anthropogenic activity. 【Method】 The analysis was based on groundwater and meteorological data measured from 1952-2013 from the People’s Victory Canal Irrigation District. Their changes and relationship were analyzed using the decadal volatility analysis, mutation test analysis, gray correlation analysis, sensitivity analysis, double cumulative curve method, and the relative contribution rate method. 【Result】 The groundwater depth in the district has been increasing at an average rate of 0.8 m/10a. The maximum coefficient of variation of the groundwater depth from 1952—1959 was 27.33%; the coefficients of variation of the precipitation, evaporation, average temperature and the amount of irrigation water all peaked in 1960s, though the variation of the evaporation and average temperature was not as strong as other factors. Abrupt changes in groundwater depth, precipitation, evaporation, average temperature and irrigation water amount occurred in 1984, 1970s, 1972, 1973 and 1993—1996, respectively. The influence of each factor on groundwater depth was ranked in the order of average temperature > precipitation > irrigation water amount > evaporation, while the sensitivity of groundwater depth to different factors was ranked in the order of average temperature > evaporation > precipitation > the amount of irrigation water. On average, the contributions of the different factors to groundwater depth change were ranked in the order of average temperature > evaporation > irrigation water amount > precipitation. The average temperature contributed most to the groundwater depth change accounting for 38.16%, and the least was precipitation contributing 17.40%. Irrigation water affected groundwater depth mostly from 2002 to 2013, contributing 47.05% of the change. 【Conclusion】 The factors affecting the groundwater depth in the district varied with time, with evaporation being dominant from 1952 to 1963, average temperature from 1964 to 2001, and irrigation from 2002 to 2013.

【Background and objective】 The Yellow River is the second largest river in China, flowing through six provinces across the county from the west to the east. The rapid economic development and the increased anthropogenic activity over the past four decades, however, have resulted in changes in its runoffs and water quality both temporally and spatially. Understanding these changes can help improve water management and maintain ecological sustainability of the river. The purpose of this paper is to present the results of a survey on the water quality of Yellow River and its tributaries. 【Method】 We selected 12 sections in the river and its tributaries, and measured pH, dissolved oxygen (DO), permanganate index (CODMn) and ammonia nitrogen (NH3) in each section at different seasons. Spatiotemporal variations in these chemical properties were analyzed using the multivariate statistical method, and the quality of the water at each section was quantified using a water pollution index (WPI). 【Result】 Water quality of the river was the best in the mainstream, followed by its tributaries Huangshui River and Weihe River, with the water quality in Fen river being the worst. All four chemical properties varied spatiotemporally. The WPI measured at different seasons in the sections at Minhe Bridge in Haidong, Tongguan Suspension Bridge in Weinan, and Yuncheng Hejin Bridge in Yuncheng, reached Class IV water quality standard or above at frequencies of 66.30%, 98.91% and 78.62%, respectively. In general, the water quality of all sections was poor in spring and winter but improved in summer and autumn. During the measuring period, the WPI in all sections had been in decrease, especially the sections at Minhe Bridge in Haidong, Zhongwei Xintun, and Tianshui Niubei. Cluster analysis based on the WPI index was consistent with the spatiotemporal distribution of the pollutant concentrations, and the seasonal fluctuation in WPI at Minhe Bridge in Haidong, Tongguan Suspension Bridge in Weinan, and Hejin Bridge in Yuncheng, was higher, especially from January to March, than that in other sections. 【Conclusion】 The water quality of Yellow River and its tributaries varied spatiotemporally, but overall it has been improving.

【Background】 The Yellow River Basin is an important grain base of China. The spatial-temporal matching characteristics of water and soil resources directly affect the level of grain production in this basin. 【Objective】 In order to find out the reasons for the structural water shortage caused by the unbalanced resource matching of the Yellow River Basin. 【Method】 Based on the comprehensive analysis framework of “green water” and “blue water”, the Gini coefficient, the generalized agricultural water and soil resources matching coefficient, the coefficient of variation, and the Spearman rank correlation coefficient were used to analyzes the matching status and spatial-temporal matching characteristics of water and soil resources. 【Result】 The results show that the irrigation “blue water” in 9 provinces along the Yellow River from 2010 to 2016 is relatively matched with the area of land in the basin; the “green water” indicator of precipitation is increased to evaluate the matching degree of agricultural water and soil resources of the provinces in the secondary sub-regions along the Yellow River, among them Sichuan Province (above Longyangxia) is better, the Inner Mongolia Autonomous Region (inflow zone) is poor, the difference between them is about 2.3 times; the time variation of water and soil resources of each province in the secondary sub-regions shows a downward trend, indicating that the development of irrigation "blue water" has stabilized; the province in different secondary sub-regions has different water and soil spatial matching, the proportion of “blue water” in provinces with a better water and soil resources matching is higher. 【Conclusion】 In view of the matching characteristics of agricultural water and soil resources in the Yellow River Basin (including the obvious differences in the spatial-temporal matching, and the limited potential of water resources development and water-saving space), it is particularly important to implements interconnected water system project and inter-basin water transfer-supply project.

Objective To investigate the effect of resveratrol (RSV) on epithelial-mesenchymal transition of MDA-MB-231 cells by down-regulating POLD1 expression. Methods CCK-8 was used to detect the effect of RSV on the activity of MDA-MB-231 cells. POLD1-OE and POLD1-NC cell lines were constructed by transfecting MDA-MB-231 cells with recombinant lentivirus. Western blot was used to detect the expression of POLD1, E-cadherin, N-cadherin and Vimentin after RSV treatment. Transwell invasion experiment and the scratch test were used to detect the cells invasion and migration abilities of each experimental group. Results RSV could significantly inhibit the survival of MDA-MB-231 cells, reduce the expression of POLD1, N-cadherin and Vimentin, increase the expression of E-cadherin, and inhibit the abilities of cell invasion and migration. Increasing the POLD1 expression could reduce the above-mentioned biological effects of RSV on MDA-MB-231 cells. Conclusion RSV could significantly inhibit the viability and EMT of MDA-MB-231 cells by down-regulating the expression of POLD1.

【Objective】 Soil water and nutrients combine to impact crop growth and nitrogen cycling. The objective of this paper is to study how groundwater depth and nitrogen fertilization modulate yield and nitrogen use efficiency of summer maize, as well as its consequent impact on nitrate dynamics. 【Method】 The experiments were conducted in lysimeters under different combinations of groundwater depth and nitrogen application. We compared three groundwater depths: 2.0 m (G1), 3.0 m (G2) and 4.0 m (G3); on top of these were two nitrogen treatments: conventional nitrogen fertilization used by local farmers (N2), and reducing it by 20% (N1), with no nitrogen fertilization and water control as control (WN). During the experiment, we measured the growth traits of the summer maize and nitrate dynamics in soil in each treatment. 【Result】 The leaf area index (LAI) was affected by groundwater depth but peaked at the grouting stage in all treatments. When nitrogen application was the same, LAI in G1 at mature stage was higher than that in G2 and G3 at a significant level. When groundwater depth was the same, increasing nitrogen application boosted LAI at mature stage. When nitrogen was applied at conventional level, the number of days that maize saw a rapid growth in G1 was 3.99% and 12.91% longer than that in G2 and G3, while its associated growth rate reduced by 9.69% and 14.65% respectively; G3 gave the highest yield. Reducing nitrogen application reduced the yield in G2 and G3 more significantly than in G1 due to the reduction in rapid-growth duration. Keeping nitrogen application at conventional level in G1 increased soil NO3- in top 20 cm of soil by 75.92% and 90.03%, and in 20~40 cm of soil by 30.56% and 130.95%, respectively, compared with that in G2 and G3. Reducing nitrogen application by 20% increased the grain yield per plant by 9.13% at significant level. Pearson correlation analysis showed that when nitrogen was applied at the conventional level, nitrate in 0~40 cm of soil varied with groundwater depth and was negatively correlated with the yield with R2 varying from 0.827 to 0.883. 【Conclusion】 High nitrogen fertilization and shallow groundwater facilitated vegetative growth, but was unfavorable for reproductive growth thereby reducing the yield of the summer maize. Reducing nitrogen application coupled with shallowing the groundwater will benefit both yield and nitrogen use efficiency.

Stem cell-assisted transplantation technology has been widely used in superficial soft tissue defect remodeling, and has been the trend of the future in postoperative reconstruction of breast cancer. Adipose-derived stem cells(ADSCs) possess excellent abilities of proliferation, multi-differentiation, paracrine and so on, and they are very important in efficacy optimization of autologous fat grafting. However, ADSCs have been proved to promote the proliferation, epithelialization of breast cancer cells and the formation of new blood vessels in breast cancer in vitro, arousing a controversy about oncology safety. This review aims to outline the potential role of ADSCs in breast reconstruction and discuss their safety impact on breast cancer.

Predominantly extensive flood irrigation method leads to wastage of water resources. Therefore, exploring efficient and water-saving agricultural irrigation methods is crucial. This study has developed an intelligent irrigation big data management platform that integrates data collection, management, visualization, analysis, decision-making, and remote management. Its goal is to improve water resource utilization efficiency through digital management and intelligent control. The platform utilizes embedded systems, the Internet of Things(IoT), and Internet technologies, as well as "3S" (GIS, RS, and GPS) technology. It follows the design model of "1+1+N" and includes the construction of a crop water requirement forecasting model, an irrigation decision-making model, an irrigation data center, an irrigation data management system, and four application systems. The entire platform is based on the B/S architecture and programmed using the Java language. The platform has been successfully implemented in several demonstration bases across regions such as Hebei, Henan, Shandong, Jiangsu, etc. It has gathered data on the growth, irrigation, weather, soil, and other aspects of various crops from 8 research teams and 24 experimental bases. On average, it collects 18 829 pieces of data per day, helping management personnel understand the overall situation. It integrates software systems from multiple teams and 62 sets of IoT devices to present the growth and environmental status of crops in a timely and quantitative manner, achieving dynamic monitoring of agricultural areas and assisting production decisions. It has also generated crop water demand forecasts and irrigation decision-making plans, accomplished remote irrigation targets, and through field experiments, validated the effectiveness of automatic irrigation, increasing the irrigation water utilization efficiency by more than 31% at its highest. The platform meets the application needs of different agricultural scenarios through thematic visualizations such as field industry, greenhouse center, digital scientific research, and regional irrigation. The smart irrigation big data management platform serves as a convenient tool for agricultural production and cross-regional management. Its construction and application provide valuable references for the development of digital agricultural irrigation systems. [ABSTRACT FROM AUTHOR]

Improving the agricultural water resources allocation efficiency (AWRAE) and promoting the efficient and intensive utilization of agricultural water resources and high-quality development is an effective path to alleviate the water scarcity in one basin. In this study, the AWRAE and its influencing factors were measured and evaluated by constructing the evaluation system of the AWRAE in nine provinces (autonomous regions) of the Yellow River Basin, which consists of the super-efficiency slacks-based model (SBM), standard deviation ellipse (SDE), spatial autocorrelation analysis, Malmquist index and Tobit regression model. The results show that the value of AWRAE is 0.768 and it is at the medium level in the whole Yellow River Basin. The AWRAE values in the nine provinces (autonomous regions) ranking from large to small are Sichuan > Shaanxi > Ningxia > Henan > Inner Mongolia > Shanxi > Qinghai > Shandong > Gansu, and the AWRAE values show a significant increasing trend in Shanxi, Henan, Inner Mongolia and Shandong. The gravity center of the AWRAE keeps wandering along the provincial boundaries of Gansu and Shaanxi, which presents a counterclockwise rotation trend; the AWRAE of Shaanxi exhibits significant H-H aggregation in 2000, 2005, 2010, and 2015 (p < 0.05) while the agglomeration is not significant in 2020. The AWRAE has been continuously improved in which the technological progress change (Techch) and technical efficiency change (Effch) play an important positive role while the pure technical efficiency change (Pech) acts as the negative role in the Yellow River Basin. Moreover, the key influencing factors on the AWRAE in different provinces and autonomous regions are significantly different; for example, the total power of agricultural machinery (AMTP) has a significant positive effect on AWRAE in most provinces, but the annual average precipitation (AAP), agricultural water (AW), water saving irrigated area (WIA) and water saving irrigation machinery (WIM) have significant negative effects on the efficiency of AWRAE in Qinghai. The research results can provide quantitative support for agricultural water-saving and stable grain yield increase in the Yellow River Basin. [ABSTRACT FROM AUTHOR]