Effect of Vitamin D on the HMGB1/RAGE Pathway and Adipokines Levels in Obese Asthmatic Mice

Compared to common asthma, obese asthma is difficult to control. Previous studies have shown that vitamin D (Vit D) has a therapeutic effect on asthma. Nevertheless, the action mechanism of Vit D for obese asthma are not well known. In this study, we, therefore, induced obesity and established an obese asthma mouse model using ovalbumin (OVA) stimulation and applied treatment with Vit D (100 ng/kg). Accordingly, thirty mice were randomly divided into 5 equal groups of normal control, asthma, obese asthma, asthma+Vit D, and obese asthma+ Vit D. The levels of inflammatory factors and adipokines were measured by the ELISA assay; then the quantitative reverse transcription PCR (qRT-PCR) method was used to evaluate the expression of high mobility group box 1(HMGB1) and receptor for advanced glycation end products [RAGE] genes.T he results showed that OVA sensitization significantly increased airway resistance, the levels of inflammatory cytokines, and HMGB and RAGE expression in asthmatic and obese asthmatic mice, as compared to the control group. Also, these changes in the obese asthmatic group were notably higher than those in the asthmatic one. In addition, the treatment of asthmatic and obese asthmatic mice with Vit D significantly reduced the raw, serum and BALF levels of inflammatory cytokines, as well as the expression of HMGB1 and RAGE mRNA. To conclude, the present study showed that vitamin D might attenuate lung injury by up-regulating HMGB1 and RAGE expression. Our findings, thus, may offer new concepts and approaches for the treatment and prevention of obese asthma

The Electric Current Effect on Electrochemical Deconsolidation of Spherical Fuel Elements

For High-Temperature Gas-Cooled Reactor in China, fuel particles are bonded into spherical fuel elements by a carbonaceous matrix. For the study of fuel failure mechanism from individual fuel particles, an electrochemical deconsolidation apparatus was developed in this study to separate the particles from the carbonaceous matrix by disintegrating the matrix into fine graphite powder. The deconsolidated graphite powder and free particles were characterized by elemental analysis, X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectrometer (EDS), and ceramography. The results showed that the morphology, size distribution, and element content of deconsolidated graphite matrix and free particles were notably affected by electric current intensity. The electrochemical deconsolidation mechanism of spherical fuel element was also discussed

Reduced carbon emission estimates from fossil fuel combustion and cement production in China.

Nearly three-quarters of the growth in global carbon emissions from the burning of fossil fuels and cement production between 2010 and 2012 occurred in China. Yet estimates of Chinese emissions remain subject to large uncertainty; inventories of China's total fossil fuel carbon emissions in 2008 differ by 0.3 gigatonnes of carbon, or 15 per cent. The primary sources of this uncertainty are conflicting estimates of energy consumption and emission factors, the latter being uncertain because of very few actual measurements representative of the mix of Chinese fuels. Here we re-evaluate China's carbon emissions using updated and harmonized energy consumption and clinker production data and two new and comprehensive sets of measured emission factors for Chinese coal. We find that total energy consumption in China was 10 per cent higher in 2000-2012 than the value reported by China's national statistics, that emission factors for Chinese coal are on average 40 per cent lower than the default values recommended by the Intergovernmental Panel on Climate Change, and that emissions from China's cement production are 45 per cent less than recent estimates. Altogether, our revised estimate of China's CO2 emissions from fossil fuel combustion and cement production is 2.49 gigatonnes of carbon (2 standard deviations = ±7.3 per cent) in 2013, which is 14 per cent lower than the emissions reported by other prominent inventories. Over the full period 2000 to 2013, our revised estimates are 2.9 gigatonnes of carbon less than previous estimates of China's cumulative carbon emissions. Our findings suggest that overestimation of China's emissions in 2000-2013 may be larger than China's estimated total forest sink in 1990-2007 (2.66 gigatonnes of carbon) or China's land carbon sink in 2000-2009 (2.6 gigatonnes of carbon).This is the author accepted manuscript. The final version is available from NPG via http://dx.doi.org/10.1038/nature1467

Low-Resource Machine Translation Based on Training Strategy with Changing Gradient Weight

In recent years, neural network models such as Transformer have achieved significant success in machine translation. However, training these models relies on rich labeled data, posing a challenge for low-resource machine translation due to the limited scale of parallel corpora. This limitation often leads to subpar performance and a susceptibility to overfitting on high-frequency vocabulary, thereby reducing the model’s generalization ability on the test set. To alleviate these issues, this paper proposes a strategy of gradient weight modification. Specifically, it suggests multiplying the gradients generated for each new batch by a coefficient on top of the Adam algorithm. This coefficient incrementally increases, aiming to weaken the model’s dependence on high-frequency features during early training while maintaining the rapid convergence advantage of the algorithm in the later stages. This paper also outlines the modified training process, including adjustments and decay of coefficients, to emphasize different aspects at different training stages. The goal of this strategy is to enhance attention to low-frequency vocabulary and prevent the model from overfitting to high-frequency terms. Experimental translation tasks are conducted on three low-resource bilingual datasets, and the proposed method demonstrates improvements of 0.72, 1.37, and 1.04 BLEU scores relative to the baseline model on the respective test set

Research on the Policy Effect and Mechanism of Carbon Emission Trading on the Total Factor Productivity of Agricultural Enterprises

Given the rural revitalization strategy in the new era, agricultural development is faced with the dual constraints of resources and the environment. Promoting the green development of agriculture is one of the important missions to solve major social issues in the new era. The implementation goal of the carbon emission trading system is to achieve a win-win situation between carbon emission reduction and green development. To evaluate the effectiveness of the carbon emission trading system on agricultural enterprises, this paper uses a double-difference model to analyze the policy effect and mechanism research path of the impact of the carbon emission trading system on the total factor productivity of agricultural enterprises. The results based on the panel data of listed agricultural companies from 2010 to 2020 show that (1) carbon emission trading rights have significantly improved the total factor productivity of agricultural enterprises; (2) green innovation in carbon emission trading rights have an impact on the total factor productivity of agricultural enterprises; and (3) heterogeneity analysis shows that the effect of carbon emission trading rights on the total factor productivity of agricultural enterprises mainly exists in large-scale, nonstate-owned, high-debt enterprises, enterprises in the eastern region, and enterprises with government subsidies. Therefore, in the future, China should continue to implement the current carbon emission trading rights system in air pollution control, and at the same time, it needs to be supplemented by government intervention and other means for long-term governance. In conclusion, the study provides a reference value for promoting the realization of the long-term goal of “low carbon” and “high quality” green development of agricultural economy and for making reasonable and effective behavioral decisions for the survival and development of enterprises

The Effect of Environmental Regulation on Corporate Environmental Governance Behavior and Its Mechanisms

Environmental regulation is an institutional guarantee for achieving green and sustainable economic development, and the implementation effect of environmental regulation policies is a concern for all sectors of society. This paper empirically examines the impact of environmental regulation on firms’ environmental governance behavior using a double difference model with the help of a quasi-natural experiment, the new Environmental Protection Law, and analyzes the mediating effect of central environmental protection inspectors using data from listed companies in China from 2011 to 2020. It was found that environmental regulation significantly enhances firms’ motivation to participate in environmental governance and central environmental protection inspectors play a mediating role in the impact of environmental regulation on firms’ environmental governance behavior. Furthermore, heterogeneity analysis shows that the enhancement effect of environmental regulation on firms’ environmental governance behavior mainly exists in large-scale firms and nonstate enterprises