Managing the Three Gorges Dam to Implement Environmental Flows in the Yangtze River

The construction of the Three Gorges Dam, along with other development in the Yangtze River basin, has had profound consequences for the river's flow and sediment regime. This has had major impacts on the geomorphology and ecology of the river downstream of the dam, with related impacts on biodiversity, including fish populations, livelihoods, and water security in the middle and lower Yangtze. Changes to fish populations have included a fall of around 90% in the total number of fish fry for the four economically-important Chinese carp species, caused at least in part by alterations in the flow regime. In response, there has been increased research into the significance of flow regimes for Chinese carp, as well as other aspects of river health. A partnership between the Chinese Government, the dam operator, scientists, and conservationists has led to pilot environmental flow releases over a 5-year period in an attempt to mitigate some of these impacts. Subsequent monitoring has shown that numbers of fish fry are increasing from the low they had fallen to in 2008. Drawing on lessons from the pilot environmental flow releases, in October 2015 the official regulations that govern operations of the Three Gorges Dam were amended to incorporate additional objectives, including incorporating environmental flow releases as part of the routine operation of the dam. This paper describes the processes that led to the environmental flow program from Three Gorges, a review of monitoring data collected during the pilot environmental flow releases, the subsequent amendment of the dam operating rules, and prospects for expanding environmental flow implementation in the Yangtze River in coming years

Evolution of vegetation and climate variability on the Tibetan Plateau over the past 1.74 million years

The Tibetan Plateau exerts a major influence on Asian climate, but its long-term environmental history remains largely unknown. We present a detailed record of vegetation and climate changes over the past 1.74 million years in a lake sediment core from the Zoige Basin, eastern Tibetan Plateau. Results show three intervals with different orbital- and millennial-scale features superimposed on a stepwise long-term cooling trend. The interval of 1.74–1.54 million years ago is characterized by an insolation-dominated mode with strong ~20,000-year cyclicity and quasi-absent millennial-scale signal. The interval of 1.54–0.62 million years ago represents a transitional insolation-ice mode marked by ~20,000- and ~40,000-year cycles, with superimposed millennial-scale oscillations. The past 620,000 years are characterized by an ice-driven mode with 100,000-year cyclicity and less frequent millennial-scale variability. A pronounced transition occurred 620,000 years ago, as glacial cycles intensified. These new findings reveal how the interaction of low-latitude insolation and high-latitude ice-volume forcing shaped the evolution of the Tibetan Plateau climate.publishedVersio

Chebyshev Neural Network-Based Adaptive Nonsingular Terminal Sliding Mode Control for Hypersonic Vehicles

This paper presents an adaptive nonsingular terminal sliding mode control approach for the attitude control of a hypersonic vehicle with parameter uncertainties and external disturbances based on Chebyshev neural networks (CNNs). First, a new nonsingular terminal sliding surface is proposed for a general uncertain nonlinear system. Then, a nonsingular sliding mode control is designed to achieve finite-time tracking control. Furthermore, to relax the requirement for the upper bound of the lumped uncertainty including parameter uncertainties and external disturbances, a CNN is used to estimate the lumped uncertainty. The network weights are updated by the adaptive law derived from the Lyapunov theorem. Meanwhile, a low-pass filter-based modification is added into the adaptive law to achieve fast and low-frequency adaptation when using high-gain learning rates. Finally, the proposed approach is applied to the attitude control of the hypersonic vehicle and simulation results illustrate its effectiveness

Uncertainty Ordinal Multi-Instance Learning for Breast Cancer Diagnosis

Ordinal multi-instance learning (OMIL) deals with the weak supervision scenario wherein instances in each training bag are not only multi-class but also have rank order relationships between classes, such as breast cancer, which has become one of the most frequent diseases in women. Most of the existing work has generally been to classify the region of interest (mass or microcalcification) on the mammogram as either benign or malignant, while ignoring the normal mammogram classification. Early screening for breast disease is particularly important for further diagnosis. Since early benign lesion areas on a mammogram are very similar to normal tissue, three classifications of mammograms for the improved screening of early benign lesions are necessary. In OMIL, an expert will only label the set of instances (bag), instead of labeling every instance. When labeling efforts are focused on the class of bags, ordinal classes of the instance inside the bag are not labeled. However, recent work on ordinal multi-instance has used the traditional support vector machine to solve the multi-classification problem without utilizing the ordinal information regarding the instances in the bag. In this paper, we propose a method that explicitly models the ordinal class information for bags and instances in bags. Specifically, we specify a key instance from the bag as a positive instance of bags, and design ordinal minimum uncertainty loss to iteratively optimize the selected key instances from the bags. The extensive experimental results clearly prove the effectiveness of the proposed ordinal instance-learning approach, which achieves 52.021% accuracy, 61.471% sensitivity, 47.206% specificity, 57.895% precision, and an 59.629% F1 score on a DDSM dataset

Biocatalytic C-C Bond Formation for One Carbon Resource Utilization

The carbon-carbon bond formation has always been one of the most important reactions in C1 resource utilization. Compared to traditional organic synthesis methods, biocatalytic C-C bond formation offers a green and potent alternative for C1 transformation. In recent years, with the development of synthetic biology, more and more carboxylases and C-C ligases have been mined and designed for the C1 transformation in vitro and C1 assimilation in vivo. This article presents an overview of C-C bond formation in biocatalytic C1 resource utilization is first provided. Sets of newly mined and designed carboxylases and ligases capable of catalyzing C-C bond formation for the transformation of CO2, formaldehyde, CO, and formate are then reviewed, and their catalytic mechanisms are discussed. Finally, the current advances and the future perspectives for the development of catalysts for C1 resource utilization are provided

Stretchable alkenamides terminated Ti3C2Tx MXenes to release strain for lattice‐stable mixed‐halide perovskite solar cells with suppressed halide segregation

Abstract Bandgap‐tunable mixed‐halide perovskite materials have attracted considerable interest because of their indispensability as top counterparts in tandem solar cells. However, the soft and disordered lattice always suffers from severe phase segregation under illumination, which is particularly susceptible to residual lattice strain. Herein, we report a strain regulation strategy by using alkenamides terminated Ti3C2Tx MXenes as an additive into perovskite precursor. Apart from the role of a template for grain growth to obtain high‐quality films, the stretchable alkyl chain promotes lattice shrinkage or expansion to form an elastic grain boundary to eliminate the spatially distributed stain and shut down ion migration channels. As a result, the all‐inorganic perovskite solar cells based on CsPbIBr2 and CsPbI2Br halides achieve prolonged device stability under harsh conditions and the best power conversion efficiencies up to 11.06% and 14.30%, respectively

Atractylenolide I ameliorates cancer cachexia through inhibiting biogenesis of IL‐6 and tumour‐derived extracellular vesicles

Abstract Background Atractylenolide I (AI) is a natural sesquiterpene lactone isolated from Atractylodes macrocephala Koidz, known as Baizhu in traditional Chinese medicine. AI has been found to ameliorate cancer cachexia in clinic cancer patients and in tumour‐bearing mice. Here, we checked the influence of AI on biogenesis of IL‐6 and extracellular vesicles (EVs) in cancer cachexia mice and then focused on studying mechanisms of AI in inhibiting the production of tumour‐derived EVs, which contribute to the ameliorating effects of AI on cancer cachexia. Methods C26 tumour‐bearing BALB/c mice were applied as animal model to examine the effects of AI (25 mg/kg) in attenuating cachexia symptoms, serum IL‐6 and EVs levels. IL‐6 and EVs secretion of C26 tumour cells treated with AI (0.31–5 μM) was further observed in vitro. The in vitro cultured C2C12 myotubes and 3T3‐L1 mature adipocytes were used to check the potency of conditioned medium of C26 cells treated with AI (0.625–5 μM) in inducing muscle atrophy and lipolysis. The glycolysis potency of C26 cells under AI (0.31–5 μM) treatment was evaluated by measuring the extracellular acidification rate using Seahorse XFe96 Analyser. Levels of related signal proteins in both in vitro and in vivo experiments were examined using western blotting to study the possible mechanisms. STAT3 overexpression or knockout C26 cells were also used to confirm the effects of AI (5 μM). Results AI ameliorated cancer cachexia symptoms (P < 0.05), improved grip strength (P < 0.05) and decreased serum EVs (P < 0.05) and IL‐6 (P < 0.05) levels of C26 tumour‐bearing mice. AI directly inhibited EVs biogenesis (P < 0.001) and IL‐6 secretion (P < 0.01) of cultured C26 cells. The potency of C26 medium in inducing C2C12 myotube atrophy (+59.54%, P < 0.001) and 3T3‐L1 adipocyte lipolysis (+20.73%, P < 0.05) was significantly attenuated when C26 cells were treated with AI. AI treatment inhibited aerobic glycolysis and the pathway of STAT3/PKM2/SNAP23 in C26 cells. Furthermore, overexpression of STAT3 partly antagonized the effects of AI in suppressing STAT3/PKM2/SNAP23 pathway, EVs secretion, glycolysis and the potency of C26 medium in inducing muscle atrophy and lipolysis, whereas knockout of STAT3 enhanced the inhibitory effect of AI on these values. The inhibition of AI on STAT3/PKM2/SNAP23 pathway was also observed in C26 tumour tissues. Conclusions AI ameliorates cancer cachexia by decreasing the production of IL‐6 and EVs of tumour cells. The decreasing effects of AI on EVs biogenesis are based on its inhibition on STAT3/PKM2/SNAP23 pathway

A Universal Grain “Cage” to Suppress Halide Segregation of Mixed-Halide Inorganic Perovskite Solar Cells

Bandgap-tunable mixed-halide perovskites offer exciting opportunities to construct efficient multijunction tandem solar cells. However, the ion migration always causes halide segregation, which inevitably creates detrimental defects and deteriorates the photovoltaic performances. Here, we report a universal caging strategy to suppress halide segregation by in situ formation of conjugated covalent organic frameworks (COFs) catalyzed by PbX2 (X = Br and I) during the formation of mixed-halide perovskite. Through theoretical calculation and systematic investigation, the strong electron-donating feature of COFs is shown to effectively solidify the soft lattice and impede the iodide ion transport from bulk to grain boundary, decelerating the light-induced halide-demixing process. Finally, the nonradiative recombination is significantly reduced, boosting efficiency up to 11.50% for an inorganic CsPbIBr2 perovskite solar cell and 14.35% for a CsPbI2Br cell with a prolonged shelf life and an improved photostability