A new method for discussing the relationship between CO2 emissions and economic growth is proposed using grey systems theory. GDP and CO2 emissions per capita are separately regarded as the input to, ...and output of, a grey system to establish a non-equigap grey Verhulst model (NE grey Verhulst model). To avoid the errors resulting from substituting a difference equation for a differential equation in grey modelling theory, the derived non-equigap grey Verhulst model (DNE grey Verhulst model) is deduced. Moreover, the structural parameters of the model are optimised using a particle swarm optimisation (PSO) algorithm in an attempt to further improve modelling accuracy. Based on data relating to CO2 emissions and GDP per capita in China from 1990 to 2014, empirical research is conducted which shows that the relationship between CO2 emissions and economic growth exhibits an inverted U-shape and the emissions are in a rapid growth stage on the left of the curve. It is predicted that CO2 emissions per capita will continue to rise from 2016 to 2020 and will not reach their peak before 2030, so the Chinese government should take effective measures to reduce carbon emissions.
•A new method for discussing the relationship between CO2 emissions and economic growth is proposed.•The structural parameters of the new model are optimised by PSO algorithm.•The Kuznets curve for CO2 emissions in China, the largest developing country in the world, is verified.•Policy suggestions are proposed in terms of emission reduction of greenhouse gases.
Motivated by recent experimental observations in α-RuCl_{3}, we study the K-Γ model on the honeycomb lattice in an external magnetic field. By a slave-particle representation and variational ...Monte Carlo calculations, we reproduce the phase transition from zigzag magnetic order to a field-induced disordered phase. The nature of this state depends crucially on the field orientation. For particular field directions in the honeycomb plane, we find a gapless Dirac spin liquid, in agreement with recent experiments on α-RuCl_{3}. For a range of out-of-plane fields, we predict the existence of a Kalmeyer-Laughlin-type chiral spin liquid, which would show an integer-quantized thermal Hall effect.
Ferroptosis is a necrotic form of regulated cell death that was associated with lipid peroxidation and free iron‐mediated Fenton reactions. It has been reported that iron deficiency had been ...implicated in the pathogenesis of intervertebral disc degeneration (IVDD) by activating apoptosis. However, the role of ferroptosis in the process of IVDD has not been illuminated. Here, we demonstrate the involvement of ferroptosis in IVDD pathogenesis. Our in vitro models show the changes in protein levels of ferroptosis marker and enhanced lipid peroxidation level during oxidative stress. Safranin O staining, hematoxylin‐eosin staining, and immunohistochemical were used to assess the IVDD after 8 weeks of surgical procedure in vivo. Treatment with ferrostatin‐1, deferoxamine, and RSL3 demonstrate the role of ferroptosis in tert‐butyl hydroperoxide (TBHP)‐treated annulus fibrosus cells (AFCs) and nucleus pulposus cells (NPCs). Ferritinophagy, nuclear receptor coactivator 4 (NCOA4)‐mediated ferritin selective autophagy, is originated during the process of ferroptosis in response to TBHP treatment. Knockdown and overexpression NCOA4 further prove TBHP may induce ferroptosis of AFCs and NPCs in an autophagy‐dependent way. These findings support a role for oxidative stress‐induced ferroptosis in the pathogenesis of IVDD.
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Ferroptosis is a necrotic form of regulated cell death that was associated with lipid peroxidation and free iron‐mediated Fenton reactions. It has been reported that iron deficiency had been implicated in the pathogenesis of intervertebral disc degeneration (IVDD) by activating apoptosis. However, the role of ferroptosis in the process of IVDD has not been illuminated. Here, we demonstrate the involvement of ferroptosis in IVDD pathogenesis.
The severe acute respiratory syndrome coronavirus 2 (SARS‐Cov‐2), the pathogen of 2019 novel coronavirus disease (COVID‐19), has posed a serious threat to global public health. The WHO has declared ...the outbreak of SARS‐CoV‐2 infection an international public health emergency. Lung lesions have been considered as the major damage caused by SARS‐CoV‐2 infection. However, liver injury has also been reported to occur during the course of the disease in severe cases. Similarly, previous studies have shown that liver damage was common in the patients infected by the other two highly pathogenic coronavirus – severe acute respiratory syndrome coronavirus (SARS‐CoV) and the Middle East respiratory syndrome coronavirus (MERS‐CoV), and associated with the severity of diseases. In this review, the characteristics and mechanism of liver injury caused by SARS‐CoV, MERS‐CoV as well as SARS‐CoV‐2 infection were summarized, which may provide help for further studies on the liver injury of COVID‐19.
Symmetry-protected topological (SPT) phases are bulk-gapped quantum phases with symmetries, which have gapless or degenerate boundary states as long as the symmetries are not broken. The SPT phases ...in free fermion systems, such as topological insulators, can be classified; however, it is not known what SPT phases exist in general interacting systems. We present a systematic way to construct SPT phases in interacting bosonic systems. Just as group theory allows us to construct 230 crystal structures in three-dimensional space, we use group cohomology theory to systematically construct different interacting bosonic SPT phases in any dimension and with any symmetry, leading to the discovery of bosonic topological insulators and superconductors.
Boosting charge separation and transfer of photoanodes is crucial for providing high viability of photoelectrochemical hydrogen (H2) generation. Here, a structural engineering strategy is designed ...and synthesized for uniformly coating an ultrathin CoFe bimetal‐organic framework (CoFe MOF) layer over a BiVO4 photoanode for boosted charge separation and transfer. The photocurrent density of the optimized BiVO4/CoFe MOF(NA) photoanode reaches a value of 3.92 mA cm−2 at 1.23 V versus reversible hydrogen electrode (RHE), up to 6.03 times that of pristine BiVO4, due to the greatly increased efficiency of charge transfer and separation. In addition, this photoanode records one onset potential that is considerably shifted negatively when compared to BiVO4. Transient absorption spectroscopy reveals that the CoFe MOF(NA) prolongs charge recombination lifetime by blocking the hole‐transfer pathway from the BiVO4 to its surface trap states. This work sheds light on boosting charge separation and transfer through structural engineering to enhance the photocurrent of photoanodes for solar H2 production.
Here a structural engineering design to coat an ultrathin bimetal‐organic framework (MOF) layer on the BiVO4 photoanode is demonstrated. This MOF layer can shut down the hole‐transfer channels from the BiVO4 to its surface trap states, build heterojunction with BiVO4 to provide strong carrier drive force and accelerate surface reaction kinetics as a cocatalyst, achieving highly efficient water oxidation performance.
The diffusion of water molecules and clusters across the surfaces of materials is important to a wide range of processes. Interestingly, experiments have shown that on certain substrates, water ...dimers can diffuse more rapidly than water monomers. Whilst explanations for anomalously fast diffusion have been presented for specific systems, the general underlying physical principles are not yet established. We investigate this through a systematic ab initio study of water monomer and dimer diffusion on a range of surfaces. Calculations reveal different mechanisms for fast water dimer diffusion, which is found to be more widespread than previously anticipated. The key factors affecting diffusion are the balance of water-water versus water-surface bonding and the ease with which hydrogen-bond exchange can occur (either through a classical over-the-barrier process or through quantum-mechanical tunnelling). We anticipate that the insights gained will be useful for understanding future experiments on the diffusion and clustering of hydrogen-bonded adsorbates.
Discrete grey model (DGM(1,1)) is considered to be superior to grey model (GM(1,1)) because it can completely simulate the pure exponential sequences. However, owing to practical data generation ...process is interfered by random factors, the superiority of DGM(1,1) model to GM(1,1) model cannot be widely and reliably validated in practical applications. Therefore, by utilizing the Monte-Carlo simulation method, groups of completely random sequences conforming to different distributions are randomly generated and the predictive capabilities of the two models are compared. In addition, the novel grey models of fractional order accumulation (FGM(1,1) and FDGM(1,1)) are introduced for further comparison. The results show that the predictive capabilities of the two models for random sequences conforming to normal distribution are nearly equivalent. However, the predictive capabilities of DGM(1,1) model for the other three kinds of random sequences are all superior to those of GM(1,1) model. The parameters change of completely random sequences influences the predictive capabilities of the two models. The parameters change of random sequences with exponential trend can influence the predictive capability of GM(1,1) model while has no significant influence on the predictive capability of DGM(1,1) model.
•The predictive capabilities of grey models are compared using Monte-Carlo simulation.•Random sequences conforming to different distributions are generated.•24,000 GM(1,1) models and DGM(1,1) models are separately established.•The conclusions can be used as the reference for model selection.
To accurately predict the seasonal fluctuations of the electricity consumption of the primary economic sectors, we propose a seasonal grey model (SGM(1,1) model) based on the accumulation operators ...generated by seasonal factors. We use the proposed model to carry out an empirical analysis based on the seasonal electricity consumption data of the primary industries in China from 2010 to 2016. The results from the SGM (1,1) model are compared with those obtained using the grey model (GM(1,1)), the particle swarm optimization algorithm combines with the grey model (PSO-GM(1,1) model), and the adaptive parameter learning mechanism based seasonal fluctuation GM (1,1) model (APL-SFGM(1,1) model). The results of the comparison show that the SGM(1,1) model can effectively identify seasonal fluctuations in the electricity consumption of the primary industries and its prediction accuracy is significantly higher than those of the GM(1,1), PSO-GM(1,1) and APL-SFGM(1,1) models. The forecast results for China from 2017 to 2020 obtained using the SGM(1,1) model suggest that the electricity consumption of the primary industries is expected to increase slightly, but obvious seasonal fluctuations will still be present. It is forecasted that the annual electricity consumption in 2020 will be 107.645 TWh with an annual growth rate of 2.83%. This prediction can provide the basis for power-supply planning to ensure supply and demand balance in the electricity markets.
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•A seasonal grey model is proposed to predict quarterly electricity consumption.•The proposed model can accurately identify and predict the seasonal fluctuations.•The prediction accuracy is significantly higher than those of traditional models.•The electricity consumption of China's primary economic sectors is predicted.
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