Divergent determinants on interannual variability of terrestrial water cycle across the globe.

Intensifying variability in precipitation under a changing climate is projected to amplify fluctuation in terrestrial hydrological cycle, leading to more severe water-related disasters. The connections between interannual variability of hydrological components and factors influencing these connections have not been clearly defined yet. Based on terrestrial water budget from Climate Data Record, we identify dominant factors influencing partitioning interannual variability of precipitation (P) into that of evapotranspiration (E), runoff (Q), and water storage deviation (ΔS) across the globe by employing geographical detector model (GDM). Sensitivities of the variability partitioning to dominant factors are quantified for different hydroclimate regions by linear regression model and law of total differential. Results show that dominant factors influencing precipitation variability partitioning (VP) are different across distinct hydroclimate conditions. Comparing the statistical index (q value) of the GDM, it can be seen that surface air temperature (Ta), snow water equivalent (SWE) and water storage capacity (Smax) are dominant factors of VP in humid, semi-arid and arid regions, respectively. Changes in P variability largely can transfer into Q variability in humid region. The P variability partitioned into Q variability is dramatically reduced in semi-arid region with SWE decreasing, while P variability partitioned into ΔS variability increases with Smax increasing in arid region. Joint effects of Ta and coefficient of variation of precipitation (Pcv) are found to be the most important interaction in determining VP across the globe. Furthermore, warmer temperatures in humid region cause >90 % of the change in precipitation variability to be transferred to Q variability change. In semi-arid region with snowfall, decreased SWE has strong effect on changes in ΔS (30-40 %) and Q (20-40 %) variability. Our findings imply a changing VP and more severe impacts of hydrological extremes under future climate, where intensive changes in Ta, SWE and land cover are projected.

Monitoring the damage of armyworm as a pest in summer corn by unmanned aerial vehicle imaging.

BACKGROUND: The timely, rapid, and accurate near real-time observations are urgent to monitor the damage of corn armyworm, because the rapid expansion of armyworm would lead to severe yield losses. Therefore, the potential of machine learning algorithms for identifying the armyworm infected areas automatically and accurately by multispectral unmanned aerial vehicle (UAV) dataset is explored in this study. The study area is in Beicuizhuang Village, Langfang City, Hebei Province, which is the main corn-producing area in the North China Plain. RESULTS: Firstly, we identified the optimal combination of image features by Gini-importance and the comparation of four kinds of machine learning methods including Random Forest (RF), Multilayer Perceptron (MLP), Naive Bayesian (NB) and Support Vector Machine (SVM) was done. And RF was proved to be the most potential with the highest Kappa and OA of 0.9709 and 0.9850, respectively. Secondly, the armyworm infected areas and healthy corn areas were predicted by an optimized RF model in the UAV dataset, and the armyworm incidence levels were classified subsequently. Thirdly, the relationship between the spectral characteristics of different bands and pest incidence levels within the Sentinel-2 and UAV images were analyzed, and the B3 in UAV images and the B6 in Sentinel-2 image were less sensitive for armyworm incidence levels. Therefore, the Sentinel-2 image was used to monitor armyworm in two towns. CONCLUSIONS: The optimized dataset and RF model are effective and reliable, which can be used for identifying the corn damage by armyworm using UAV images accurately and automatically in field-scale. © 2022 Society of Chemical Industry.

Water-energy-ecosystem nexus modeling using multi-objective, non-linear programming in a regulated river: Exploring tradeoffs among environmental flows, cascaded small hydropower, and inter-basin water diversion projects.

Small hydropower (SHP) possesses significant economic, technical, and environmental advantages, and accounts for a large proportion of hydropower development in China. However, the concentrated, cascaded, and diversion-type development of SHP has resulted in long-distance dewatering of river sections, and inter-basin water transfers have led to severe exploitation of water resources and damage to river ecosystems. In this paper, the Datong River Basin, a secondary sub-basin of the Yellow River Basin in China, was selected as the illustrative case, which includes 22 hydropower projects (HPPs) and three inter-basin water diversion projects (WDPs). A nexus system model was established that used weighted multi-objective programming to consider three main objectives: the water resources utilization (local water withdrawal and inter-basin water transfer), energy production (by cascaded HPPs), and riverine environmental conservation. The Tennant method was used to estimate the environmental flows (e-flows) at the cross-sections immediately downstream of the dam/sluice gate and immediately downstream of the hydropower plant of diversion-type HPPs. The decreased percentage of regulated flow in comparison with runoff and the guaranteed rate of e-flow at the control cross-section were introduced to assess the degree of environmental impact to the river. Using a historical series of runoff data during 1956-2016 as the model input (i.e., implicit stochastic method), the Multi-start solver of nonlinear programming of LINGO software was used to conduct optimizations and analyses for multiple scenarios (with/without e-flow, with consideration of various levels of e-flow, and with/without water resources utilization). The sectoral linkages relating to the water-energy-ecosystem (WEE) nexus were quantitatively identified. The possible influences of different boundary conditions (i.e., initial/final reservoir storage, inter-basin water diversion capacity, and climate change) on the WEE nexus were further explored. The present study aims to provide an exemplar for the optimal operation and scientific management of a complicated water resources system in a regulated river with cascaded SHP and inter-basin WDPs.

Revealing the water-energy-food nexus in the Upper Yellow River Basin through multi-objective optimization for reservoir system.

Since the 21st century, the natural runoff from the headwater region of the Yellow River has generally been decreasing, resulting in a particularly prominent contradiction in utilization of water resources. In this study, key components were identified from the perspective of water-energy-food (WEF) nexus, and a WEF nexus model was established for the Upper Yellow River Basin (UYRB), taking into consideration the benefits of water supply to the middle and lower reaches of Yellow River, food growth in major food-producing areas in the UYRB and hydropower utilization of the UYR reservoir system. The Multi-start Solver of LINGO and the ε constraint method were used to carry out multi-objective optimization, revealing the trade-off between the WEF benefits. 1) The model computed the Pareto non-inferior set of solutions for the electricity generated by the UYR reservoir system and the degree to which the water demands of the main intake areas (Ningxia and Inner Mongolia irrigated areas, and Toudaoguai section) are satisfied, quantifying the improvement room for the overall benefits brought about by the jointly optimal operation of the WEF sectors. 2) The historical operation of Longyangxia Reservoir, a multi-year storage reservoir, was evaluated, the results of which show that the realization of the WEF benefits is determined by the proper operation of Longyangxia Reservoir. To guarantee the overall benefits in the long term, Longyangxia Reservoir should maintain a high water level. 3) The trade-offs between the WEF benefits under different boundary conditions were discussed, including various initial/final fore-bay water levels of Longyangxia Reservoir and inflows of various total water amounts from the headwater region of the UYRB. The research reveals the WEF nexus in the UYRB under different scenarios, and moreover, the formulated multi-objective optimization model is a good example that can be extended to other similar WEF nexus systems worldwide.

Mid1ip1b modulates apical reorientation of non-centrosomal microtubule organizing center in epithelial cells.

In most kinds of animal cells, the centrosome serves as the main microtubule organizing center (MTOC) that nucleates microtubule arrays throughout the cytoplasm to maintain cell structure, cell division and intracellular transport. Whereas in epithelial cells, non-centrosomal MTOCs are established in the apical domain for generating asymmetric microtubule fibers and cilia in epithelial cells for the organ morphogenesis during embryonic development. However, the mechanism by which MTOCs localize to the apical domain in epithelial cells remains largely unknown. Here, we show that Mid1ip1b has a close interaction with γ-tubulin protein, the central component of MTOC, and modulates lumen opening of the neural tube, gut, intestine, and kidney of zebrafish. Knockdown or dominant negative effect of Mid1ip1b resulted in failure of lumen formation of the organs as aforementioned. Moreover, the non-centrosomal MTOCs were unable to orientate to the apical domain in Mid1ip1b knockdown epithelial cells, and the centrosomal MTOCs were inaccurately placed in the apical domain, resulting in defective formation of asymmetric microtubules and misplacement of cilia in the apical domain. These data uncover a molecule that controls the proper localization of MTOCs in the apical domain in epithelial cells for organ morphogenesis during embryonic development.

Evaluating and optimizing the operation of the hydropower system in the Upper Yellow River: A general LINGO-based integrated framework.

The hydropower system in the Upper Yellow River (UYR), one of the largest hydropower bases in China, plays a vital role in the energy structure of the Qinghai Power Grid. Due to management difficulties, there is still considerable room for improvement in the joint operation of this system. This paper presents a general LINGO-based integrated framework to study the operation of the UYR hydropower system. The framework is easy to use for operators with little experience in mathematical modeling, takes full advantage of LINGO's capabilities (such as its solving capacity and multi-threading ability), and packs its three layers (the user layer, the coordination layer, and the base layer) together into an integrated solution that is robust and efficient and represents an effective tool for data/scenario management and analysis. The framework is general and can be easily transferred to other hydropower systems with minimal effort, and it can be extended as the base layer is enriched. The multi-objective model that represents the trade-off between power quantity (i.e., maximum energy production) and power reliability (i.e., firm output) of hydropower operation has been formulated. With equivalent transformations, the optimization problem can be solved by the nonlinear programming (NLP) solvers embedded in the LINGO software, such as the General Solver, the Multi-start Solver, and the Global Solver. Both simulation and optimization are performed to verify the model's accuracy and to evaluate the operation of the UYR hydropower system. A total of 13 hydropower plants currently in operation are involved, including two pivotal storage reservoirs on the Yellow River, which are the Longyangxia Reservoir and the Liujiaxia Reservoir. Historical hydrological data from multiple years (2000-2010) are provided as input to the model for analysis. The results are as follows. 1) Assuming that the reservoirs are all in operation (in fact, some reservoirs were not operational or did not collect all of the relevant data during the study period), the energy production is estimated as 267.7, 357.5, and 358.3×108 KWh for the Qinghai Power Grid during dry, normal, and wet years, respectively. 2) Assuming that the hydropower system is operated jointly, the firm output can reach 3110 MW (reliability of 100%) and 3510 MW (reliability of 90%). Moreover, a decrease in energy production from the Longyangxia Reservoir can bring about a very large increase in firm output from the hydropower system. 3) The maximum energy production can reach 297.7, 363.9, and 411.4×108 KWh during dry, normal, and wet years, respectively. The trade-off curve between maximum energy production and firm output is also provided for reference.

Neurons generated from carcinoma stem cells support cancer progression.

Recent evidences show that nervous system acts as a crucial part of cancer microenvironment. Infiltration of nerve fibers into cancer microenvironment has an important active role in cancer progression. The stimulations of both cancer growth and metastasis by members of nervous system such as neurons and glial cells have been demonstrated. However, how the nervous system is built in cancer is largely unknown. Here we show that a fraction of cancer stem cells (CSCs) derived from patients with gastric carcinoma and colorectal carcinoma are capable of producing neurons that are involved in tumor neurogenesis and tumor growth. Cancer stem cell monoclone derived from a single cancer stem cell was able to generate neurons including sympathetic and parasympathetic neurons to take part in the nervous system in cancer tissues. Knocking down the neural cell generating capability of the human CSCs inhibited the growth of xenograft tumors in mouse model. Our data demonstrate that human CSCs are able to produce one of most important components in the cancer microenvironment that are required for cancer development and progression.

Endothelium originated from colorectal cancer stem cells constitute cancer blood vessels.

Tumor growth depends on the formation of blood vessels that provide the supply of nutrients and oxygen. Previous data have shown that glioblastoma stem cells are able to give rise to vascular cells to constitute the functional vessels in tumor tissues. However, which kinds of vascular cells are generated from glioblastoma stem cells is largely debated. In addition, there is little evidence showing that the stem cells from other kinds of tumors can produce vascular cells to constitute the functional blood vessels in tumor tissues. Here we show that cancer stem cells of human colorectal carcinomas (CoCSC) can give rise to vascular endothelial cells and compose the vasculatures in cancer tissues. The human-cell-specific nuclear antigen NuMA+ vascular endothelial cells were detected in the blood vessels in xenografts derived from CoCSC. NuMA+ endothelial cells incorporated into functional blood vessels. Our data indicate that the cancer stem cells derived from human colorectal carcinomas have the capacity to generate functional blood vessels and provide a new mechanism for tumor vasculogenesis in carcinoma.

Single primary fetal lung cells generate alveolar structures in vitro.

Organ morphogenesis, including lung morphogenesis, involves a series of cellular behaviors that are difficult to observe and document in vivo due to current limitations in imaging techniques. Therefore, in vitro models are necessary to study these cellular behaviors as well as basic developmental processes relevant to in vivo morphogenesis. Here, we describe a novel in vitro three-dimensional (3D) culture system for assessing mouse lung alveolar morphogenesis using primary fetal mouse lung cells cultured in Matrigel supplemented with fibroblast growth factor 10 and hepatocyte growth factor. In our in vitro 3D culture system, single primary mouse fetal lung cells successfully grew, developed lumen, and formed multivesicular epithelial structures, resulting in a morphology that was highly similar to that of lung alveoli. This culture system is a useful tool for investigating the cellular and molecular mechanisms involved in lung alveolar morphogenesis.