摘要：The accurate simulation and prediction of runoff in alpine glaciated watersheds is of increasing importance for the comprehensive management and utilization of water resources. In this study, long short-term memory (LSTM), a state-of-the-art artificial neural network algorithm, is applied to simulate the daily discharge of two data-sparse glaciated watersheds in the Tianshan Mountains in Central Asia. Two other classic machine learning methods, namely extreme gradient boosting (XGBoost) and support vector regression (SVR), along with a distributed hydrological model (Soil and Water Assessment Tool (SWAT) and an extended SWAT model (SWAT_Glacier) are also employed for comparison. This paper aims to provide an efficient and reliable method for simulating discharge in glaciated alpine regions that have insufficient observed meteorological data. The two typical basins in this study are the main tributaries (the Kumaric and Toxkan rivers) of the Aksu River in the south Tianshan Mountains, which are dominated by snow and glacier meltwater and precipitation. Our comparative analysis indicates that simulations from the LSTM shows the best agreement with the observations. The performance metrics Nash-Sutcliffe efficiency coefficient (NS) and correlation coefficient (R2) of LSTM are higher than 0.90 in both the training and testing periods in the Kumaric River Basin, and NS and R2 are also higher than 0.70 in the Toxkan River Basin. Compared to classic machine learning algorithms, LSTM shows significant advantages over most evaluating indices. XGBoost also has high NS value in the training period, but is prone to overfitting the discharge. Compared with the widely used hydrological models, LSTM has advantages in predicting accuracy, despite having fewer data inputs. Moreover, LSTM only requires meteorological data rather than physical characteristics of underlying data. As an extension of SWAT, the SWAT_Glacier model shows good adaptability in discharge simulation, outperforming the original SWAT model, but at the cost of increasing the complexity of the model. Compared with the oftentimes complex semi-distributed physical hydrological models, the LSTM method not only eliminates the tedious calibration process of hydrological parameters, but also significantly reduces the calculation time and costs. Overall, LSTM shows immense promise in dealing with scarce meteorological data in glaciated catchments.
摘要： Net primary productivity (NPP), as an important variable and ecological indicator in grassland ecosystems, can reflect environmental change and the carbon budget level. The Ili River Valley is a wetland nestled in the hinterland of the Eurasian continent, which responds sensitively to the global climate change. Understanding carbon budget and their responses to climate change in the ecosystem of Ili River Valley has a significant effect on the adaptability of future climate change and sustainable development. In this study, we calculated the NPP and analyzed its spatio-temporal pattern of the Ili River Valley during the period 2000–2014 using the normalized difference vegetation index (NDVI) and an improved Carnegie-Ames-Stanford (CASA) model. Results indicate that validation showed a good performance of CASA over the study region, with an overall coefficient of determination (R2) of 0.65 and root mean square error (RMSE) of 20.86 g C/(m2•a). Temporally, annual NPP of the Ili River Valley was 599.19 g C/(m2•a) and showed a decreasing trend from 2000 to 2014, with an annual decrease rate of –3.51 g C/(m2•a). However, the spatial variation was not consistent, in which 55.69% of the areas showed a decreasing tendency, 12.60% of the areas remained relatively stable and 31.71% appeared an increasing tendency. In addition, the decreasing trends in NPP were not continuous throughout the 15-year period, which was likely being caused by a shift in climate conditions. Precipitation was found to be the dominant climatic factor that controlled the inter-annual variability in NPP. Furthermore, the correlations between NPP and climate factors differed along the vertical zonal. In the medium-high altitudes of the Ili River Valley, the NPP was positively correlated to precipitation and negatively correlated to temperature and net radiation. In the low-altitude valley and high-altitude mountain areas, the NPP showed a negative correlation with precipitation and a weakly positive correlation with temperature and net radiation. The results suggested that the vegetation of the Ili River Valley degraded in recent years, and there was a more complex mechanism of local hydrothermal redistribution that controlled the growth of vegetation in this valley ecosystem.
摘要：Natural steroids have been showing notable cytotoxic activities, which are quite interesting lead compounds for the development of anticancer drug including estramustine and prednimustine. Considering that these semi-synthetic molecules are nitrogen mustard functionalized steroidal derivatives, the present review is focused on the methodologies of introducing nitrogen atom or nitrogen-containing heterocycles on A～D rings or side chains of steroids, and analysis of the structure-activity relationship (SAR) for these man-made cytotoxic steroids
摘要： Abstract: To face the challenges of keeping healthy in increasing population sizes of both ageing and developing people in China, a fundamental request from the public health is the development of lifespan normative trajectories of brain and behavior. This paper introduces the Chinese Color Nest Project (CCNP 2013–2022), a large-scale tenyear program of modeling brain and behavioral trajectories for human lifespan (6–85 years old). We plan to gradually collect the behavioral and brain imaging data at ages across the lifespan on nationwide and depict the normal trajectory of Chinese brain development across the lifespan, based on the accelerated longitudinal design in the coming next 10 years starting at 2013. Various psychiatric disorders have been demonstrated highly relevant to abnormal events during the neurodevelopment regarding their onset ages of first episodes. Therefore, delineation of normative growth curves of brain and cognition in typically developing children is extremely useful for monitoring, early detecting and intervention of various neurodevelopmental disorders. In this paper, we detailed the developing part of CCNP, devCCNP. It tracked 192 healthy children and adolescents (6–18 years old) in Beibei district of Chongqing for the first 5 years of the full CCNP cohort (2013–2017). To demonstrate the feasibility of implementing the longterm follow-up of CCNP, we here comprehensively document devCCNP in terms of its experimental design, sample strategies, data acquisition and storage as well as some preliminary results and data sharing roadmap for future. Specifically, we first describe the accelerated longitudinal sampling design as well as its exact ratio of sample dropping off during the data collection. Second, we present several initial findings such as canonical growth curves of cortical surface areas of a set of well-established large-scale functional networks of the human brain. Finally, together with records generated by many psychological and behavioral tests, we will provide an individual growing-up report for each family participating the program, initiating the potential guidance on the individual academic and social development. The resources introduced in the current work can provide first-hand data for a series of coming Chinese brain development studies, such as Chinese Standard MRI Brain Templates, Normative Growth Curves of Chinese Brain and Cognition as well as Mapping of Language Areas in Chinese Developing Brain. These would not only offer normative references of the atypical brain and cognition development for Chinese population but also serve as a strong force on accelerating the pace of integrating Chinese brain development into the national brain program or Chinese Brain Project.
摘要：描述了在兰州盆地渐新统韩家井组底部的黄砂层中新发现的巨犀化石：黄河巨犀(Paraceratherium huangheense sp. nov.) (新种), 该化石产出层位的古地磁年龄为距今31.5Ma。新种主要特征为：P2之前无齿槽痕迹，一对下门齿粗壮，互相靠近，向前平伸且略微上翘，下颏孔位于p3之下，水平支下缘平直， p2前的齿隙部分向上隆起，下颌角圆钝，上升支后缘斜向后上方，齿式： ?·?·3·3/1·0·3·3。除个体较大、下颌后缘有所不同之外，其下颌的总体特征与巴基斯坦的Paraceratherium bugtiense最为接近，显示两者可能具有较近的亲缘关系。新标本的发现为确定经典的Dera Bugti地点产大巨犀化石层位的年代提供了新的证据，并为青藏高原的隆升讨论提供了新的哺乳动物化石证据。