A Large-field J=1-0 Survey of CO and Its Isotopologues Toward the Cassiopeia A Supernova Remnant

We have conducted a large-field simultaneous survey of $^{12}$CO, $^{13}$CO, and C$^{18}$O $J=1-0$ emission toward the Cassiopeia A (Cas A) supernova remnant (SNR), which covers a sky area of $3.5^{\circ}\times3.1^{\circ}$. The Cas giant molecular cloud (GMC) mainly consists of three individual clouds with masses on the order of $10^4-10^5\ M_{\odot}$. The total mass derived from the $\rm{^{13}CO}$ emission of the GMC is 2.1$\times10^{5}\ M_{\odot}$ and is 9.5$\times10^5\ M_{\odot}$ from the $\rm{^{12}CO}$ emission. Two regions with broadened (6$-$7 km s$^{-1}$) or asymmetric $^{12}$CO line profiles are found in the vicinity (within a 10$'\times10'$ region) of the Cas A SNR, indicating possible interactions between the SNR and the GMC. Using the GAUSSCLUMPS algorithm, 547 $^{13}$CO clumps are identified in the GMC, 54$\%$ of which are supercritical (i.e. $\alpha_{\rm{vir}}<2$). The mass spectrum of the molecular clumps follows a power-law distribution with an exponent of $-2.20$. The pixel-by-pixel column density of the GMC can be fitted with a log-normal probability distribution function (N-PDF). The median column density of molecular hydrogen in the GMC is $1.6\times10^{21}$ cm$^{-2}$ and half the mass of the GMC is contained in regions with H$_2$ column density lower than $3\times10^{21}$ cm$^{-2}$, which is well below the threshold of star formation. The distribution of the YSO candidates in the region shows no agglomeration.Comment: 24 pages, 18 figure

Drought monitoring and early warning in China: a review of research to pave the way for operational systems

Geographic and socio-economic factors combined make China particularly vulnerable to droughts. Here we review academic literature to assess publication trends on the topics of drought monitoring and early warning in China, exploring the common themes and recent advances presented. Literature searches for the 1970–2017 period were made for a range of search terms relating to drought monitoring. It was found that publications on these topics started to appear sporadically in 1989 and have increased rapidly since the early 2000s, with the rate of publication increasing over the last eight years. The scope of studies varied, often with the spatial scale considered: at the national scale, studies focused on evaluating existing indices, while new indices were developed and tested at the regional scale – relating, in general, to monitoring agricultural and meteorological droughts. At the catchment scale, novel monitoring techniques were developed, often incorporating other data types such as modelled data or soil moisture measurements. National scale operational drought monitoring in China is currently being improved and updated. However, although operational systems are discussed in the literature, there is a still a disconnect between theory and practice with the most recent advances not yet operationalised. Here, we identify the methods and approaches which can be translated from the experimental case study scale to the national operational scale

Porosity Prediction of Granular Materials through Discrete element method and back propagation neural network algorithm

Granular materials are used directly or as the primary ingredients of the mixtures in industrial manufacturing, agricultural production and civil engineering. It has been a challenging task to compute the porosity of a granular material which contains a wide range of particle sizes or shapes. Against this background, this paper presents a newly developed method for the porosity prediction of granular materials through Discrete Element Modeling (DEM) and the Back Propagation Neural Network algorithm (BPNN). In DEM, ball elements were used to simulate particles in granular materials. According to the Chinese specifications, a total of 400 specimens in different gradations were built and compacted under the static pressure of 600 kPa. The porosity values of those specimens were recorded and applied to train the BPNN model. The primary parameters of the BPNN model were recommended for predicting the porosity of a granular material. Verification was performed by a self-designed experimental test and it was found that the prediction accuracy could reach 98%. Meanwhile, considering the influence of particle shape, a shape reduction factor was proposed to achieve the porosity reduction from sphere to real particle shape

Effect of β3-adrenoceptor on cardiac fibrosis in rat cardiac fibroblast cells and its potential mechanism

Purpose: To investigate the effect of β3-adrenoceptors (β3-AR) up-regulation on fibrosis in cardiac fibroblast cells in rats and its potential mechanism.Methods: Cardiac fibroblast cells (CFB) were isolated and identified from rats’ hearts. The β3-ARupregulated cardiac fibroblast cells were constructed by lentiviral transfection technology. Thereafter, Ang II was used to induce fibrosis in cardiac fibroblast cells, and subsequently, Western blot assay was performed to investigate fibrosis related marker proteins (TGF-β, Smad-2, p-Smad-2, Col-I and Col-III) in cardiac fibroblast cells.Results: β3-AR up-regulated cardiac fibroblast cells were successfully constructed. Furthermore, the results show that up-regulation of β3-AR increased the expressions of TGF-β, p-Smad-2, Col-I and Col- III proteins in Ang II treated cardiac fibroblast cells.Conclusion: The results suggest that up-regulation of β3-AR aggravates fibrosis of cardiac fibroblast cells. In other words, inhibition of β3-AR expressions in cardiac tissues would be beneficial for treating cardiac fibrosis and its related cardiac diseases.Keywords: Cardiac fibrosis, β3-AR, TGF/Smads, Col-I/III, Cardiac fibroblast cell

Does non-stationarity of extreme precipitation exist in the Poyang Lake Basin of China?

Study region Poyang Lake Basin, China. Study focus This study aimed to investigate whether there are non-stationary characteristics of extreme precipitation in the Poyang Lake Basin (PLB) of China, and the trends of non-stationary characteristics from 1959 to 2019. The spatio-temporal variations of extreme precipitation were analysed from three fundamental aspects: duration, frequency, and intensity, based on the prewhitening Mann-Kendall (PWMK) test. Non-stationary variations and the risk of extreme precipitation were investigated based on the generalized additive models for location, scale, and shape (GAMLSS). New hydrological insights for the region (1) the intensity and frequency of extreme precipitation increased significantly, whereas there was a significant decrease in extreme precipitation duration in the PLB. (2) The duration of extreme precipitation showed significant non-stationary characteristics in the western PLB. At the Nanchang site, 83.3 % of the extreme precipitation intensity indices showed non-stationary characteristics. The RX1day (maximum 1-day precipitation amount) and RX5day (maximum 5-day precipitation amount) increased significantly for different return periods under non-stationary conditions in the northwestern PLB. (3) The risk of extreme precipitation can be captured using the GAMLSS. The stationary method underestimated the extreme precipitation intensity (e.g., RX1day) compared to the GAMLSS for longer return periods in the PLB. More attention should be paid to the increase and fluctuation of the return period of extreme precipitation caused by the mean non-stationarity and variance non-stationarity

Balance between poverty alleviation and air pollutant reduction in China

Key targets of the sustainable development goals might be in contradiction to each other. For example, poverty alleviation may exacerbate air pollution by increasing production and associated emissions. This paper investigates the potential impacts of achieving different poverty eradication goals on typical air pollutants in China by capturing household consumption patterns for different income groups and locations, and linking it to China’s multi-regional input-output table and various scenarios. We find that ending extreme poverty, i.e. lifting people above the poverty line of USD 1.90 a day in 2011 purchasing power parity (PPP), increases China’s household emissions by only less than 0.6%. The contribution increases to 2.4%–4.4% when adopting the USD 3.20 PPP poverty line for lower-middle-income countries. Technical improvements in economic sectors can easily offset poverty-alleviation-induced emissions in both scenarios. Nevertheless, when moving all impoverished residents below the USD 5.50 PPP poverty line for upper-middle-income countries, household emissions in China would increase significantly by 18.5%–22.3%. Counteracting these additional emissions would require national emission intensity in production to decrease by 23.7% for SO2, 13.6% for NOx, 82.1% for PM2.5, and 58.0% for PM10. Required synergies between poverty alleviation and emission reduction call for changes in household lifestyles and production

Optimal wholesale price and technological innovation under dual credit policy on carbon emission reduction in a supply chain

The adoption of new energy vehicles (NEVs) can effectively reduce vehicle exhaust emissions and achieve carbon peaking and carbon neutrality goals in the transportation sector. To facilitate the development of NEVs, the Chinese government issued the dual credit policy (DCP). However, whether the DCP can promote the technological innovation of NEVs and effectively reduce carbon emissions in the transportation sector remains to be studied. This study constructed the decision-making model of NEVs under the DCP and obtained the optimal strategy to study the impact of the DCP on carbon emissions. Furthermore, we constructed a bargaining game model based on an alliance strategy to demonstrate the coordination of the NEV supply chain. The results showed that implementing the DCP can effectively reduce carbon emissions in the transportation field. The higher the technological innovation credit coefficient or credit price, the more significant the DCP’s incentive effect on reducing carbon emissions. Decentralized decision-making weakens the DCP’s incentive effect on reducing carbon emissions. The bargaining game based on alliance negotiation can enable independent companies to achieve carbon emission reduction when making centralized decisions so that the DCP’s incentive effect on reducing carbon emissions is optimized. The alliance between manufacturers is not to increase profits but to enhance their product advantages. However, suppliers can gain higher profits by participating in the alliance, which provides a theoretical reference for the alliance’s cooperation in decision-making