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Projecting how the East Asian summer monsoon (EASM) rainfall will change with global warming is essential for human sustainability. Reconstructing Holocene climate can provide critical insight into its forcing and future variability. However, quantitative reconstructions of Holocene summer precipitation are lacking for tropical and subtropical China, which is the core region of the EASM influence. Here we present high-resolution annual and summer rainfall reconstructions covering the whole Holocene based on the pollen record at Xinjie site from the lower Yangtze region. Summer rainfall was less seasonal and ~ 30% higher than modern values at ~ 10–6 cal kyr BP and gradually declined thereafter, which broadly followed the Northern Hemisphere summer insolation. Over the last two millennia, however, the summer rainfall has deviated from the downward trend of summer insolation. We argue that greenhouse gas forcing might have offset summer insolation forcing and contributed to the late Holocene rainfall anomaly, which is supported by the TraCE-21 ka transient simulation. Besides, tropical sea-surface temperatures could modulate summer rainfall by affecting evaporation of seawater. The rainfall pattern concurs with stalagmite and other proxy records from southern China but differs from mid-Holocene rainfall maximum recorded in arid/semiarid northern China. Summer rainfall in northern China was strongly suppressed by high-northern-latitude ice volume forcing during the early Holocene in spite of high summer insolation. In addition, the El Niño/Southern Oscillation might be responsible for droughts of northern China and floods of southern China during the late Holocene. Furthermore, quantitative rainfall reconstructions indicate that the Paleoclimate Modeling Intercomparison Project (PMIP) simulations underestimate the magnitude of Holocene precipitation changes. Our results highlight the spatial and temporal variability of the Holocene EASM precipitation and potential forcing mechanisms, which are very helpful for calibration of paleoclimate models and prediction of future precipitation changes in East Asia in the scenario of global warming.

In recent years, the extraction of hypoglycemic peptides from food proteins has gained increasing attention. Neuropeptides, hormone peptides, antimicrobial peptides, immune peptides, antioxidant peptides, hypoglycemic peptides and antihypertensive peptides have become research hotspots. In this study, bioinformatic methods were used to screen and predict the properties of pig collagen-derived hypoglycemic peptides, and their inhibitory effects on α-glucosidase were determined in vitro . Two peptides (RL and NWYR) were found to exhibit good water solubility, adequate ADMET (absorption, distribution, metabolism, elimination, and toxicity) properties, potentially high biological activity, and non-toxic. After synthesizing these peptides, NWYR showed the best inhibitory effect on α-glucosidase with IC 50 = 0.200±0.040 mg/mL, and it can regulate a variety of biological processes, play a variety of molecular functions in different cellular components, and play a hypoglycemic role by participating in diabetic cardiomyopathy and IL-17 signaling pathway. Molecular docking results showed that NWYR had the best binding effect with the core target DPP4 (4n8d), with binding energy of -8.8 kcal/mol. NWYR mainly bonded with the target protein through hydrogen bonding, and bound with various amino acid residues such as Asp-729, Gln-731, Leu-765, etc., thus affecting the role of the target in each pathway. It is the best core target for adjuvant treatment of T2DM. In short, NWYR has the potential to reduce type 2 diabetes, providing a basis for further research or food applications as well as improved utilization of pig by-products. However, in subsequent studies, it is necessary to further verify the hypoglycemic ability of porcine collagen active peptide (NWYR), and explore the hypoglycemic mechanism of NWYR from multiple perspectives such as key target genes, protein expression levels and differences in metabolites in animal models of hyperglycemia, which will provide further theoretical support for its improvement in the treatment of T2DM.

For practical lithium–sulfur batteries (LSBs), the high sulfur loading and lean‐electrolyte are necessary conditions to achieve the high energy density. However, such extreme conditions will cause serious battery performance fading, due to the uncontrolled deposition of Li2S and lithium dendrite growth. Herein, the tiny Co nanoparticles embedded N‐doped carbon@Co9S8 core–shell material (CoNC@Co9S8NC) is designed to address these challenges. The Co9S8NC‐shell effectively captures lithium polysulfides (LiPSs) and electrolyte, and suppresses the lithium dendrite growth. The CoNC‐core not only improves electronic conductivity, but also promotes Li+ diffusion as well as accelerates Li2S deposition/decomposition. Consequently, the cell with CoNC@Co9S8NC modified separator delivers a high specific capacity of 700 mAh g−1 with a low‐capacity decay rate of 0.035% per cycle at 1.0 C after 750 cycles under a sulfur loading of 3.2 mg cm−2 and a E/S ratio of 12 µL mg−1, and a high initial areal capacity of 9.6 mAh cm−2 under a high sulfur loading of 8.8 mg cm−2 and a low E/S ratio of 4.5 µL mg−1. Besides, the CoNC@Co9S8NC exhibits an ultralow overpotential fluctuation of 11 mV at a current density of 0.5 mA cm–2 after 1000 h during a continuous Li plating/striping process. The uncontrolled deposition of Li2S and lithium dendrites growth lead to the extremely low sulfur utilization and premature failure of LSBs. Here, this work designs the tiny Co nanoparticles embedded N‐doped carbon@Co9S8 core–shell catalyst to address these challenges. It as an interlayer material accelerates the Li2S deposition–decomposition and alleviates lithium dendrites growth under high sulfur loading and lean‐electrolyte conditions.

Dam is an important way of water-resources utilization in large rivers. To date, more than 50 000 dams with various sizes have been constructed in the Yangtze River basin, with many other dams proposed to be constructed by 2020. Dam construction has played significant roles in flood control, irrigation, navigation, and energy supply; however, the enormous negative effects, such as landslides, ecological problems, and water quality decline, could surpass positive gains. Although a long and complicated evaluation process had been carried out and the countermeasures for numerous foreseen negative impacts of the Three Gorges Dam (TGD) had been implemented, many uncertainties and debating opinions on the benefits and costs of this project still exist. In this review, we synthesize the negative impacts that have occurred as a result of the TGD, including reservoir-triggered seismicity, landslides, water quality control, ecological problems, siltation, and sediment discharge decline to assure an environmentally friendly operation of the TGD and regional sustainable development in the Yangtze River basin, especially in the Three Gorges Reservoir region.

Reducing oxidative stress is a crucial therapeutic strategy for ameliorating diabetic myocardial ischemia/reperfusion (MI/R) injury. Honokiol (HKL) acts as an effective cardioprotective agent for its strong antioxidative activity. However, its roles and underlying mechanisms against MI/R injury in type 1 diabetes (T1D) remain unknown. Since SIRT1 and Nrf2 are pivotal regulators in diabetes mellitus patients suffering from MI/R injury, we hypothesized that HKL ameliorates diabetic MI/R injury via the SIRT1-Nrf2 signaling pathway. Streptozotocin-induced T1D rats and high-glucose-treated H9c2 cells were exposed to HKL, with or without administration of the SIRT1 inhibitor EX527, SIRT1 siRNA, or Nrf2 siRNA, and then subjected to I/R operation. We found that HKL markedly improved the postischemic cardiac function, decreased the infarct size, reduced the myocardial apoptosis, and diminished the reactive oxygen species generation. Intriguingly, HKL remarkably activated SIRT1 signaling, enhanced Nrf2 nuclear translocation, increased antioxidative signaling, and decreased apoptotic signaling. However, these effects were largely abolished by EX527 or SIRT1 siRNA. Additionally, our cellular experiments showed that Nrf2 siRNA blunted the cytoprotective effects of HKL, without affecting SIRT1 expression and activity. Collectively, these novel findings indicate that HKL abates MI/R injury in T1D by ameliorating myocardial oxidative damage and apoptosis via the SIRT1-Nrf2 signaling pathway.

Transition metal oxides are promising candidates for the next generation of spintronic devices due to their fascinating properties that can be effectively engineered by strain, defects, and microstructure. An excellent example can be found in ferroelastic LaCoO 3 with paramagnetism in bulk. In contrast, unexpected ferromagnetism is observed in tensile-strained LaCoO 3 films, however, its origin remains controversial. Here we simultaneously reveal the formation of ordered oxygen vacancies and previously unreported long-range suppression of CoO 6 octahedral rotations throughout LaCoO 3 films. Supported by density functional theory calculations, we find that the strong modification of Co 3 d -O 2 p hybridization associated with the increase of both Co-O-Co bond angle and Co-O bond length weakens the crystal-field splitting and facilitates an ordered high-spin state of Co ions, inducing an emergent ferromagnetic-insulating state. Our work provides unique insights into underlying mechanisms driving the ferromagnetic-insulating state in tensile-strained ferroelastic LaCoO 3 films while suggesting potential applications toward low-power spintronic devices. Transition metal oxides are a promising class of materials to engineer multiferroic properties for next-generation spintronic devices. Here, the authors demonstrate an emergent and robust ferromagnetic-insulating state in ferroelastic LaCoO 3 epitaxial films by strain-defect-microstructure manipulated electronic and magnetic states.

This paper focuses on the relationship between green credit and industrial green total factor productivity under the dual carbon target. In recent years, weather extremes that break historical extremes have occurred frequently around the world, and the resulting loss of life and property has deepened people’s concern about climate change. As a responsible developing country, China has set the goal of reaching peak carbon emissions and reducing carbon intensity by 60–65% by 2030. In this context, based on China’s provincial-level data from 2006 to 2019, this paper first measures the growth rate of industrial green total factor productivity using the SBM-ML model, and then analyzes the impact of green credit on industrial green total factor productivity under the double carbon target by constructing the transmission mechanism of the energy consumption structure and the regulation mechanism of environmental regulation on green credit. We then analyze the impact of green credit on industrial green total factor productivity under the dual carbon target by constructing the transmission mechanism of the energy consumption structure and the regulation mechanism of environmental regulation on green credit. We find that green credit can improve the energy consumption structure and thus increase industrial green total factor productivity. In addition, the study finds that the interaction effect of green credit and environmental regulation suppresses the positive impact of green credit on industrial green TFP. This paper provides empirical evidence and policy implications for the orderly promotion of carbon peaking and carbon neutral efforts to effectively improve industrial green total factor productivity and promote high-quality economic development.

Nb-doped SrSnO3 (SSNO) thin films were epitaxially grown on LaAlO3(001) single-crystal substrates using pulsed laser deposition under various oxygen pressures and substrate temperatures. The crystalline structure, electrical, and optical properties of the films were investigated in detail. X-ray diffraction results show that the cell volume of the films reduces gradually with increasing oxygen pressure while preserving the epitaxial characteristic. X-ray photoelectron spectroscopy analysis confirms the Nb5+ oxidation state in the SSNO films. Hall-effect measurements were performed and the film prepared at 0.2 Pa with the 780 °C substrate temperature exhibits the lowest room-temperature resistivity of 31.3 mΩcm and Hall mobility of 3.31 cm2/Vs with a carrier concentration at 6.03 × 1019/cm3. Temperature-dependent resistivity of this sample displays metal-semiconductor transition and is explained mainly by electron-electron effects. Optical transparency of the films is more than 70% in the wavelength range from 600 to 1800 nm. The band gaps increase from 4.35 to 4.90 eV for the indirect gap and 4.82 to 5.29 eV for the direct by lowering oxygen pressure from 20 to 1 × 10−3 Pa, which can be interpreted by Burstein-Moss effect and oxygen vacancies generated in the high vacuum.

To reduce the danger for firefighters and ensure the safety of firefighters as much as possible, based on the back propagation neural network (BPNN) the fire sensor multi-sensor information fusion detection system is investigated. According to previous studies, the information sources and information processing methods for the design of this study are first explained. Then, the basic structure and flowchart of the research object in this study are designed. Based on the structure diagram and flowchart, the BPNN is selected to fuse the feature layers in this study, and the fuzzy control is selected to fuse the decision layers in this study. The multi-sensor information fusion detection system collects information for the sensors first, processes the collected information, and sends it to the processor of the robot. The processor analyzes and processes the received signal, and transmits the obtained information to the control terminal through the wireless communication system. Through the tests in this study, it is found that when the number of hidden layer nodes of the BPNN is 7, the optimal training result is obtained. On this basis, the test of BPNN in this study is performed. The test results show that after 127 iterations, the error of the BPNN reaches the lowest target value, indicating that the BPNN achieves an excellent level of accuracy. The trained BPNN has a running time of 0.0276 s and a mean square error of 0.0013. The smaller the mean square error value is, the higher the accuracy of the BPNN is, which shows that the BPNN meets the high precision requirements of this study. The research on the multi-sensor information fusion detection system of fire robots in this study can provide theoretical support for the research on forest fire detection in China. Since the proposed BPNN-based robot is applied to the inspection and processing of forest remaining fire, the results are applicable to the forests of various countries, with a wide range of applications.

Natural components of breast milk, human milk oligosaccharides (HMOs) and osteopontin (OPN) have been shown to have a variety of functional activities and are widely used in infant formulas. However, the preventive and therapeutic effects of both on influenza viruses are not known. In this study, antiviral assays using a human laryngeal carcinoma cell line (HEP-2) showed that 3′-sialyllactose (3′-SL) and OPN had the best antiviral ability with IC50 values of 33.46 μM and 1.65 μM, respectively. 3′-SL (10 μM) and OPN (4 μM) were used in combination to achieve 75% inhibition. Further studies found that the combination of 200 μg/mL of 3′-SL with 500 μg/mL of OPN exerted the best antiviral ability. The reason for this was related to reduced levels of the cytokines TNF-α, IL-6, and iNOS in relation to mRNA expression. Plaque assay and TCID50 assay found the same results and verified synergistic effects. Our research indicates that a combination of 3′-SL and OPN can effectively reduce inflammatory storms and exhibit anti-influenza virus effects through synergistic action.