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The rule of law presents a new path for understanding and handling religious affairs in contemporary China. The field of religious education is no exception and current legislation has to be improved so that China's religious education can be further promoted. This research examines the legislation and legislative regulations governing China's diversified and dynamic religious education, which includes professional religious studies, religious education embedded in ethnic education, missionary religious education, religious education included in general education, and education on religious policies and regulations. It argues that how to understand and implement the principle of separation of education and religion stands out as the core issue, as China requires a more dialectical and pluralistic religious education.

Efforts to improve coaching effectiveness require an understanding of the common sources of coaches' knowledge acquisition. Sports coaches utilise multiple learning sources, yet limited direct evidence elucidates the manner in which Chinese coaches learn to coach and the evolution of their learning sources throughout their careers' development. This research examines the actual and preferred sources of coaching knowledge for Chinese coaches and analyses changes in learning sources from Junior to Senior level coaches. One hundred coaches from China, including 60 Junior coaches, 23 Intermediate coaches and 17 Senior coaches, completed an online questionnaire. The survey results indicated that coaches acquire knowledge from formal, informal and non-formal learning situations. However, formal coach education (coach education programmes) is the most important source of knowledge acquisition for all coaches. Furthermore, as coaches develop, the sources to acquire knowledge will gradually change from athletic experience to interaction with other coaches. Based on these findings, we suggest that national sport governing bodies build more comprehensive coach education systems by establishing a scientific mentoring system and organising regular coach-themed clinics, seminars, meetings and so on. Future research is needed to examine how coaches in China's dominant programmes learn to coach and how this learning is practically applied. [ABSTRACT FROM AUTHOR]

Recently, a novel duck-origin goose parvovirus (N-GPV) was reported to cause short beak and dwarfism syndrome in ducks. In this study, we performed complete genome sequencing and analyzed three different duck-derived parvoviruses that infected different breeds of ducks. Phylogenetic trees based on gene sequences indicated that they were classical goose parvovirus (C-GPV), Muscovy duck parvovirus (MDPV), and N-GPV. Furthermore, potential recombination events were found. These results improve our understanding of the diversity of duck-derived parvoviruses in Anhui province, eastern China, and provide a reference for the prevention of associated diseases. [ABSTRACT FROM AUTHOR]

• A series of non-linear models was built to predict rice yield and greenhouse gas emission. • GHG emissions in China's rice fields will increase by 2.1% to 4.9% under different climate change scenarios by 2050. • Climate change may weaken GHG emission reduction efforts through optimal management. Paddy rice cultivation is a vital food source but also a significant contributor to greenhouse gas (GHG) emissions, particularly methane. Management measures such as improved water management and fertilization are being pursued to sustain rice production while cutting down the emissions. However, climate change may pose further challenges for sustainable rice agriculture by either impacting rice production or GHG emissions. Based on a database consisting of 1216 observations across China, we established machine learning models predicting rice yield and GHG emissions, taking into account climate, soil, and management variables. We tested three machine learning methods including random forest, support vector machine and artificial neural networks. The models were trained on 70% of the dataset with the remaining 30% used to evaluate the model performance. Random forest performed best with R2 of 0.59 to 0.72 and modelling efficiency of 52% to 72%. Farmland management emerged as the most important variable to the model prediction, followed by climate and soil variables. Rice production and GHG emissions were estimated to be 245.36 Tg and 218.95 Tg CO 2 -eq in 2018, respectively. By the year 2050, rice yield was expected to experience a modest decrease ranging from 0.6% to 1.2% due to the combined effects of global change variables, but GHG emissions were projected to increase by 2.1% to 4.9% under different climate change scenarios (Representative Concentration Pathways) in China. A large spatial variability in the impact of climate change was observed, and climate change will have the most significant impact in the Northeast agricultural region of China due to the warming effect. Through the analysis of region-specific farmland management scenarios, this study underscores a "Code Red" situation, signifying that future climate change could pose unprecedented risks to the sustainability of rice production in China, despite ongoing management improvements. [ABSTRACT FROM AUTHOR]

The rule of law presents a new path for understanding and handling religious affairs in contemporary China. The field of religious education is no exception and current legislation has to be improved so that China's religious education can be further promoted. This research examines the legislation and legislative regulations governing China's diversified and dynamic religious education, which includes professional religious studies, religious education embedded in ethnic education, missionary religious education, religious education included in general education, and education on religious policies and regulations. It argues that how to understand and implement the principle of separation of education and religion stands out as the core issue, as China requires a more dialectical and pluralistic religious education. [ABSTRACT FROM AUTHOR]

Biochar soil amendment (BSA) had been advocated as a promising approach to mitigate greenhouse gas (GHG) emissions in agriculture. However, the net GHG mitigation potential of BSA remained unquantified with regard to the manufacturing process and field application. Carbon footprint (CF) was employed to assess the mitigating potential of BSA by estimating all the direct and indirect GHG emissions in the full life cycles of crop production including production and field application of biochar. Data were obtained from 7 sites (4 sites for paddy rice production and 3 sites for maize production) under a single BSA at 20 t/ha−1 across mainland China. Considering soil organic carbon (SOC) sequestration and GHG emission reduction from syngas recycling, BSA reduced the CFs by 20.37–41.29 t carbon dioxide equivalent ha−1 (CO2‐eq ha−1) and 28.58–39.49 t CO2‐eq ha−1 for paddy rice and maize production, respectively, compared to no biochar application. Without considering SOC sequestration and syngas recycling, the net CF change by BSA was in a range of −25.06 to 9.82 t CO2‐eq ha−1 and −20.07 to 5.95 t CO2‐eq ha−1 for paddy rice and maize production, respectively, over no biochar application. As the largest contributors among the others, syngas recycling in the process of biochar manufacture contributed by 47% to total CF reductions under BSA for rice cultivation while SOC sequestration contributed by 57% for maize cultivation. There was a large variability of the CF reductions across the studied sites whether in paddy rice or maize production, due likely to the difference in GHG emission reductions and SOC increments under BSA across the sites. This study emphasized that SOC sequestration should be taken into account the CF calculation of BSA. Improved biochar manufacturing technique could achieve a remarkable carbon sink by recycling the biogas for traditional fossil‐fuel replacement. Biochar soil amendment with the rate of 20 t/ha reduced the carbon footprints by 29 and 33 t CO2‐eq/ha for paddy rice and maize production, respectively, compared to no biochar application. Syngas recycling in the process of biochar manufacture contributed by 47% to total carbon footprint reductions for rice cultivation while SOC sequestration contributed by 57% for maize cultivation. There was a large variability of the carbon footprint reductions across the studied sites, due likely to the difference in GHG emission reductions and SOC increments under biochar amendment across the sites. [ABSTRACT FROM AUTHOR]

This article seeks to answer two questions: (i) what factors drive firms to decide whether or not to disclose the information related to their greenhouse gas emissions (also called carbon information)? (ii) what forces lead firms to disclose more carbon information? Using data hand-collected from the annual Corporate Social Responsibility reports of China's listed companies from 2008 to 2012, we find the following: (i) firms that operate in sectors of high-emission industries are more likely to make carbon information disclosure ( CID hereafter); (ii) the more companies within one industry that make CID, the more likely it is that a company in that industry will make CID; (iii) companies having a higher sales rank within an industry are more likely to make CID. [ABSTRACT FROM AUTHOR]

Nitrogen (N) deposition has increased significantly globally since the industrial revolution. Previous studies on the response of gaseous emissions to N deposition have shown controversial results, pointing to the system-specific effect of N addition. Here we conducted an N addition experiment in a temperate natural forest in northeastern China to test how potential changes in N deposition alter soil N2O emission and its sources from nitrification and denitrification. Soil N2O emission was measured using closed chamber method and a separate incubation experiment using acetylene inhibition method was carried out to determine denitrification fluxes and the contribution of nitrification and denitrification to N2O emissions between Jul. and Oct. 2012. An NH4NO3 addition of 50 kg N/ha/yr significantly increased N2O and N2 emissions, but their “pulse emission” induced by N addition only lasted for two weeks. Mean nitrification-derived N2O to denitrification-derived N2O ratio was 0.56 in control plots, indicating higher contribution of denitrification to N2O emissions in the study area, and this ratio was not influenced by N addition. The N2O to (N2+N2O) ratio was 0.41–0.55 in control plots and was reduced by N addition at one sampling time point. Based on this short term experiment, we propose that N2O and denitrification rate might increase with increasing N deposition at least by the same fold in the future, which would deteriorate global warming problems. [ABSTRACT FROM AUTHOR]

Ammonia (NH 3) volatilization is one of the main pathways of nitrogen loss from cropland, resulting not only in economic losses, but also environmental and human health impacts. The magnitude and timing of NH 3 emissions from cropland fertilizer application highly depends on agricultural practices, climate and soil factors, which previous studies have typically only considered at coarse spatio-temporal resolution. In this paper, we describe a first highly detailed empirical regression model for ammonia (ERMA) emissions based on 1443 field observations across China. This model is applied at county level by integrating data with unprecedented high spatio-temporal resolution of agricultural practices and climate and soil factors. Results showed that total NH 3 emissions from cropland fertilizer application amount to 4.3 Tg NH 3 yr−1 in 2017 with an overall NH 3 emission factor of 12%. Agricultural production for vegetables, maize and rice are the three largest emitters. Compared to previous studies, more emission hotspots were found in South China and temporally, emission peaks are estimated to occur three months earlier in the year, while the total amount of emissions is estimated to be close to that calculated by previous studies. A second emission peak is identified in October, most likely related to the fertilization of the second crop in autumn. Incorporating these new findings on NH 3 emission patterns will enable a better parametrization of models and hence improve the modelling of air quality and subsequent impacts on ecosystems through reactive N deposition. [Display omitted] • A empirical model of NH 3 emissions from croplands was established. • Two emission peaks are found in April and October following the fertilization. • Total emission was estimated at 4.3 Tg NH 3 yr−1 in 2017 with an emission factor of 12%. • More emission hotspots were found in South China due to warming climate. The highly spatio-temporal resolution NH 3 emission inventory from cropland fertilization was developed by an empirical regression model in 2853 counties of China. [ABSTRACT FROM AUTHOR]

Quantifying methane (CH 4) emissions from paddy fields is essential for evaluating the environmental risks of the paddy rice production system, and improving the accuracy of CH 4 modeling is a key issue that needs to be addressed. Based on a database containing 835 field measurements, both single national and region-specific models were established to estimate CH 4 emissions from paddy fields considering different environmental factors and management patterns using 70% of the measurements. The remaining 30% of the measurements were then used for model evaluation. The performance of the region-specific model was better than that of the single national model. The region-specific model could simulate CH 4 emissions in an unbiased manner with R2 values of 0.15–0.70 and efficiency values of 11–60%. The paddy rice type, water regime, organic amendment, latitude, and soil characteristics (pH and bulk density) were identified as the main drivers in the models. By inputting the high-resolution spatial data of these drivers into the established model, the CH 4 emissions from China's paddy fields were estimated to be 4.75 Tg in 2015, with a 95% confidence interval of 4.19–5.61 Tg. The results indicated that establishing and driving a region-specific model with high-resolution data can improve the estimation accuracy of CH 4 emissions from paddy fields. Image 1 • The region-specific methane emission model performed better than the single national model. • Using high-spatial-resolution database can reduce the estimation uncertainty. • The methane emissions from China's cropland were estimated to be 4.75 Tg in 2015. • The uncertainty in methane emissions estimates was as low as −11.8%∼18.1%. The performance of the region-specific model was better than that of the single national model, and inputting high-resolution data lowered the estimation uncertainty of methane emissions from paddy fields. [ABSTRACT FROM AUTHOR]

Abstract: Examining Chinese publicly traded firms from 2002 to 2005, we find managerial overconfidence to be positively correlated with the rate of firm expansion. In particular, overconfident managers tend to internally expand firms in an aggressive manner. We also find a negative, though not statistically significant, relationship between managerial overconfidence and M&A activity. Lastly, we examine the relationship between managerial overconfidence and firm performance, finding that managerial overconfidence decreases firm profitability due to overinvestment. [Copyright &y& Elsevier]

• The agro-region-specific ammonia models had the better performance than the single national model. • Developing agro-region-specific model and using high-spatial-resolution database can reduce the estimation uncertainty. • The ammonia emissions from China's cropland were estimated to be 4.31 Tg NH 3 -N in 2015. Estimating ammonia (NH 3) volatilization from cropland can identify potential environmental risks and is also important for mitigating NH 3 loss, since cropland is the major anthropogenic source of NH 3. Reducing uncertainties around NH 3 volatilization estimates is a key need. In this study, both a single national model and agro-region-specific models were developed to embody the variation of NH 3 volatilization associated with environmental attributes and management practices for cropland in various agro-regions of China. A database with 951 field measurements across China was established to develop and evaluate the model, in which 75% of the measurements were used for model fitting and 25% were used for evaluation. The agro-region specific model had a better performance than the single national scale model, and the agro-region-specific model could successfully simulate NH 3 emissions with R2 values of 0.41–0.93 as a function of crop type, N fertilizer type and rate, timing of fertilization, soil pH, clay content, bulk density, precipitation, air temperature, and soil total nitrogen content. Inputting high-resolution spatial data into the model, the NH 3 emissions from China's cropland were estimated to be 4.31 Tg NH 3 N in the year 2015 with a 95% confidence interval of 3.64–5.64 Tg NH 3 N, of which paddy rice cultivation accounted for 44%, and maize and wheat cultivation contributed 20% and 16%, respectively. Notable spatial variability was also found in NH 3 emissions from China's cropland due to regional differences in climate, soil and management patterns. This study showed that the accuracy of estimation of farmland NH 3 emissions can be improved by taking meteorological, soil and management variables into account and inputting high-spatial-resolution data into the modeling. [Display omitted] [ABSTRACT FROM AUTHOR]

Bufavirus is a novel virus associated with canine gastroenteritis. Three strains of bufavirus were first detected in dog feces collected from Anhui province in Eastern China. The near-complete genome sequences were amplified. Sequence alignment showed 98.3–99.5% homology between the three bufavirus strains and reference strains. Phylogenetic analysis showed the distributed viruses forming a cluster of close relationships. Selective pressure analysis of the VP2 region indicated that the canine bufavirus (CBuV) was mainly subject to negative selection during evolution. The negative selection site was located on the residue of B-cell epitopes, indicating minimal change to the virus's immunogenicity. Since this is the first report of CBuV circulating in Anhui Province, this study will provide further understanding of the phylogenetic and molecular characteristics of CBuV and serve as a reference for prevention and vaccine development. • Molecular evidence was found for the prevalence of canine bufavirus in Anhui province. • The canine bufavirus was evolutionarily conservative. • Canine bufavirus was mainly subject to negative selection, and part of the site coincides with the B-cell epitope. [ABSTRACT FROM AUTHOR]

The carbon-nutrient-water cycles of farmland ecosystem not only provides support for crop production, but also has an impact on the environment. Comprehensively quantifying the impact of crop production on the environment can provide a basis for crop sustainable production. A series of environmental footprint approaches, including carbon footprint (CF), nitrogen footprint (NF) and water footprint (WF), were optimized to evaluate greenhouse gas (GHG) emissions, reactive nitrogen (Nr) loss and water resource consumption in crop production, and a comprehensive footprint method based on Endpoint modeling was proposed to evaluate the overall environmental impact of crop production in China. The CF, NF and WF of 28 forms of crop production varied from 1206.29 kg CO 2 equivalent (CO 2 -eq) ha -1 of oil crops to 7326.37 kg CO 2 -eq ha -1 of fiber crops, 16.07 kg Nr-eq ha -1 of oil crops to 60.70 kg Nr-eq ha -1 of sugar crops, and 4032.04 m 3 ha -1 oil crops to 12,476.28 m 3 ha -1 of sugar crops, respectively. The contribution of each component to footprints varied greatly among different crops, and fertilizer manufacture, NH 3 volatilization and green WF were generally the main contributors of CF, NF and WF, respectively. The total GHG emissions, Nr loss and water consumption were estimated to be 670.11 Tg CO 2 -eq, 5.50 Tg Nr-eq and 837.06 G m 3 for all crop production of China. The greenhouse vegetable with the highest area-scaled comprehensive footprint was 4.5 times that of the oil crops which had the lowest one. The contribution of crop production to the corresponding environmental impact in China was as low as 3.7%, of which NH 3 volatilization contributed 48% and grain production contributed 72%. Mineral N fertilization was the main driver of the variation of comprehensive footprint between provinces, with reduction of N fertilizer application as an important way to reduce the environmental impact of crop production., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Purpose: This study aimed to investigate the molecular mechanisms of Compound Sidaxue (SX), a prescription of Chinese Miao medicine, in treating rheumatoid arthritis (RA) using network pharmacology and in vivo experimental approaches., Methods: Network pharmacology was adopted to detect the active components of four Traditional Chinese herbal medicine (TCM) of SX, and the key targets and signaling pathways in the treatment of RA were predicted, and the key components and targets were screened for molecular docking. The predicted targets and pathways were validated in bovine type II collagen and incomplete Freund's adjuvant emulsifier-induced rat RA model., Results: In this study, we identified 33 active components from SX, predicted to act on 44 RA-associated targets by network pharmacology. PPI network demonstrated that TNF-α, VEGF-A, IL-2, IL-6, AKT, PI3K, STAT1 may serve as the key targets of SX for the treatment of RA. The main functional pathways involving these key targets include PI3K-AKT signaling pathway, TNF signaling pathway, NF-κB signaling pathway. Molecular docking analysis found that the active components β-amyrin, cajanin, eleutheroside A have high affinity for TNF-α, VEGFA, IL-2, AKT, and PI3K, etc. SX can improve joint swelling in Collagen-induced arthritis (CIA) rats, reduce inflammatory cell infiltration and angiogenesis in joint synovial tissue, and down-regulate IL-2, IL-6, TNF-α, VEGF, PI3K, AKT, p-AKT, NF-κBp65, the expression of p-NF-κBp65, STAT1, and PTGS2 are used to control the exacerbation of inflammation and alleviate the proliferation of synovial pannus, and at the same time play the role of cartilage protection to achieve the effect of treating RA., Conclusion: Through a network pharmacology approach and animal study, we predicted and validated the active compounds of SX and their potential targets for RA treatment. The results suggest that SX can markedly alleviate CIA rat by modulating the VEGF/PI3K/AKT signaling pathway, TNF-α signaling pathway, IL/NF-κB signaling pathway., Competing Interests: The authors report no conflicts of interest in this work., (© 2022 Wu et al.)

Low-molecular-weight (LMW) phthalate acid esters (PAEs) tend to enter the atmosphere, flying for several kilometers, so it is easy to endanger human health. This work is the first to use quantum chemistry calculations (Gaussian 16 program) and computational toxicology (ECOSAR, TEST, and Toxtree software) to comprehensively study the ozonolysis mechanism of six LMW PAEs (dimethyl phthalate (DMP), diethyl phthalate (DEP), dipropyl phthalate (DPP), diisopropyl phthalate (DIP), dibutyl phthalate (DBP), and diisobutyl phthalate (DIBP)) in the atmosphere and the toxicity of DMP (take DMP as an example) in the conversion process. The results show that the electron-donating effect of the ortho position of the LMW PAEs has the most obvious influence on the ozonolysis. We summarized the ozonation reaction law of LMW PAEs at the optimal reaction site. At 298 K, the law of initial ozonolysis total rate constant of the LMW PAEs is k DIP  > k DPP  > k DIBP  > k DMP  > k DEP  > k DBP , and the range is 9.56 × 10 -25  cm 3 molecule -1 s -1 - 1.47 × 10 -22  cm 3 molecule -1 s -1 . According to the results of toxicity assessment, the toxicity of products is lower than DMP for aquatic organisms after ozonolysis. But those products have mutagenicity, developmental toxicity, non-genotoxicity, carcinogenicity, and corrosiveness to the skin. The proposed ozonolysis mechanism promotes our understanding of the environmental risks of PAEs and provides new ideas for studying the degradation of PAEs in the tropospheric gas phase., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Despite research into the response of ammonia (NH 3 ) volatilization in farmland to various meteorological factors, the potential impact of future climate change on NH 3 volatilization is not fully understood. Based on a database consisting of 1063 observations across China, nonlinear NH 3  models considering crop type, meteorological, soil and management variables were established via four machine learning methods, including support vector machine, multi-layer perceptron, gradient boosting machine and random forest (RF). The RF model had the highest R 2 of 0.76 and the lowest RMSE of 0.82 kg NH 3 -N ha - 1 , showing the best simulation capability. Results of model importance indicated that NH 3 emissions of China's cereal production (paddy rice, wheat and maize) in 2018 was estimated to be 3.3 Mt NH 3 emissions of China's cereal production (paddy rice, wheat and maize) in 2018 was estimated to be 3.3 Mt NH 3 -N. By 2050, NH 3 volatilization in the Yangtze river agro-region of China due to high warming effects. However, the potential increase in NH 3 volatilization in the Yangtze river agro-region of China due to high warming effects. However, the potential increase in NH 3 volatilization under future climate change can be mitigated by 26.1-47.5% through various N fertilizer management optimization options., (© 2021 John Wiley & Sons Ltd.)

Updating and refining the N 2 O emission factors (N 2 O-EFs) are vital to reduce the uncertainty in estimates of direct N 2 O emissions. Based on a database with 1151 field measurements across China, the N 2 O-EFs were established via three approaches including the maximum likelihood method, a linear regression with an intercept and a linear regression with the intercept set to 0 using 70% of the observations. The remaining 30% of the observations were then used to evaluate the predicted N 2 O-EFs. The third method had the highest R 2 of 0.39 and the best model efficiency of 0.38 with no significant bias, showing the best calculation efficiency. The results showed that the N 2 O-EFs varied with agroregions, crops, and management patterns. The agroregions of Huang-Huai-Hai and Yangtze River had the higher N 2 O-EFs in maize and wheat seasons than other regions, and the highest N 2 O-EFs of 0.66-0.92% in the rice season was found in the South and Southwest agroregions. Both fertilizer types and water regimes had the remarkable effects on N 2 O emissions from China's crop cultivation were estimated to be 194 Gg N 2 O emissions from China's crop cultivation were estimated to be 194 Gg N 2 O-N with a 95% confidence interval of 180-208 Gg N 2 O-N in the year 2016.

Process-based models are useful tools to integrate the effects of detailed agricultural practices, soil characteristics, mass balance, and climate change on soil N 2 O emissions from soil - plant ecosystems, whereas static, seasonal or annual models often exist to estimate cumulative N 2 O emissions under data-limited conditions. A study was carried out to compare the capability of four models to estimate seasonal cumulative N 2 O fluxes from 419 field measurements representing 65 studies across China's croplands. The models were 1) the DAYCENT model, 2) the DNDC model, 3) the linear regression model (YLRM) of Yue et al. (2018), and 4) IPCC Tier 1 emission factors. The DAYCENT and DNDC models estimated crop yields with R 2 values of 0.60 and 0.66 respectively, but both models showed significant underestimation for all measurements. The estimated seasonal N 2 O emissions with R 2 of 0.31, 0.30, 0.21 and 0.17 for DAYCENT, DNDC, YLRM, and IPCC, respectively. Based on RMSE, modelling efficiency and bias analysis, YLRM performed well on N 2 O emission prediction under no fertilization though bias still existed, while IPCC performed well for cotton and rapeseed and DNDC for soybean. The DAYCENT model accurately predicted the emissions with no bias across other crop and fertilization types whereas the DNDC model underestimated seasonal N 2 O emissions by 0.42 kg N 2 O-N ha -1 for all observed values. Model evaluation indicated that the DAYCENT and DNDC models simulated temporal patterns of daily N 2 O emissions effectively, but both models had difficulty in simulating the timing of the N 2 O fluxes following some events such as fertilization and water regime. According to this evaluation, algorithms for crop production and N 2 O emission should be improved to increase the accuracy in the prediction of unfertilized fields both for DAYCENT and DNDC. The effects of crop types and management modes such as fertilizations should also be further refined for YLRM., (Copyright © 2018 Elsevier B.V. All rights reserved.)