Energy transition is central to both economic development and climate-change mitigation and has become a shared global challenge. Given the close relationship between conventional energy prices and the development of the new-energy industry, this study investigates systemic risk spillovers among three crude-oil futures, two natural-gas futures, and five Chinese new-energy sector indices. We employ a quantile time-frequency-connectedness framework and an out-of-sample-validated link-prediction model to assess both realized spillovers and potential changes in the network structure. The results reveal that network connectedness is time-varying and asymmetric across quantiles, with short-horizon connectedness accounting for the majority of average system-wide connectedness. Overall connectedness also increases markedly during major crisis episodes. INE crude-oil futures and both natural-gas futures are net receivers of shocks, whereas WTI and Brent crude-oil futures consistently act as net transmitters, with Brent playing the dominant role under extreme market conditions. As the investment horizon lengthens, the solar sector shifts from a net risk receiver to a net risk transmitter. In the predicted network, the solar sector emerges as the market most likely to initiate new short-term spillover links. This finding reflects a prospective, model-implied tendency rather than a causal relationship. These findings offer useful implications for energy market policy, portfolio risk management, and investment decisions involving new-energy companies.

Oil-tea Camellia (OTC) is a valuable oil crop with diverse applications across the food, cosmetics, and medicine sectors. However, understanding the impact of chromosome polyploidization on genome evolution and phenotypic diversity in OTC remains challenging. This study addressed this knowledge gap by focusing on the origins and impacts of OTC polyploidization. The chromosomal karyotypes of 10 representative samples were examined, and their relationships were elucidated through hierarchical clustering analysis of karyotype parameters. Based on the phylogeny of the genus Camellia, the ancestral 1 C-value and 1 Cx-value were reconstructed, revealing an increase in the 1 C-value and a reduction in the 1 Cx-value associated with polyploidization. Notable positive correlations between ploidy level, genome size, and fruit size were highlighted by phylogenetic generalized least squares analysis. The phenotypic characteristics and chromosomal evolution of OTC were reconstructed. It was inferred that the genus Camellia, which was originally diploid, underwent 11 chromosomal duplication events. With the emergence of polyploidization, phenotypic traits transitioned from small fruits, autumn-winter flowering, and white flowers to larger fruits, spring flowering, and red flowers. Biogeographically, it is suggested that OTC first appeared in the Lingnan region, and subsequent species dispersion and hybridization significantly influenced the emergence of polyploid species. In conclusion, evidence has shown that OTC polyploidization increases genome size and enhances phenotypic diversity. This research enhances our understanding of the complex genetic mechanisms that drive species evolution, influence genome changes, and contribute to the domestication of Camellia plants. Furthermore, these findings offer insights that can inform future breeding and cultivation strategies for OTC.

Background: Several clinical studies have suggested that the early administration of statins could reduce the risk of in-hospital mortality in acute myocardial infarction (AMI) patients. Recently, some studies have identified that stimulating lymphangiogenesis after AMI could improve cardiac function by reducing myocardial edema and inflammation. This study aimed to identify the effect of rosuvastatin on postinfarct lymphangiogenesis and to identify the underlying mechanism of this effect. Method: Myocardial infarction (MI) was induced by ligation of the left anterior descending coronary artery in mice orally administered rosuvastatin for 7 days. The changes in cardiac function, pathology, and lymphangiogenesis following MI were measured by echocardiography and immunostaining. EdU, Matrigel tube formation, and scratch wound assays were used to evaluate the effect of rosuvastatin on the proliferation, tube formation, and migration of the lymphatic endothelial cell line SVEC4-10. The expression of miR-107-3p, miR-491-5p, and VEGFR3 was measured by polymerase chain reaction (PCR) and Western blotting. A gain-of-function study was performed using miR-107-3p and miR-491-5p mimics. Results: The rosuvastatin-treated mice had a significantly improved ejection fraction and increased lymphatic plexus density 7 days after MI. Rosuvastatin also reduced myocardial edema and inflammatory response after MI. We used a VEGFR3 inhibitor to partially reverse these effects. Rosuvastatin promoted the proliferation, migration, and tube formation of SVEC4-10 cells. PCR and Western blot analyses revealed that rosuvastatin intervention downregulated miR-107-3p and miR-491-5p and promoted VEGFR3 expression. The gain-of-function study showed that miR-107-3p and miR-491-5p could inhibit the proliferation, migration, and tube formation of SVEC4-10 cells. Conclusion: Rosuvastatin could improve heart function by promoting lymphangiogenesis after MI by regulating the miRNAs/VEGFR3 pathway.

The convergence of geopolitical tensions and economic disruptions may lead to significant fluctuations in the stock markets of BRICS countries. Against this background, in order to accurately meet new recovery opportunities of the stock market, the research on the spillover effect of the stock market is of great practical significance. This paper examines monthly stock market closing data from March 2001 to March 2023. It first uses the DY spillover index to analyze the spillover effects between economic policy uncertainty, geopolitical risks and the stock markets in BRICS countries. Then, based on the data obtained through the DY spillover index, this study draws a network chart using complex network and compares the difference of spillover effects before and after the pandemic. It finds that: The total spillover index is greater than 0, there is a bidirectional spillover effect between the variables, and there is an asymmetric feature. This feature is also confirmed by the fact that the overflow values between the indices on the network chart are inconsistent; the Russian stock index, the Brazilian stock index, the Indian stock index and the South African stock index are all risk bearers. But the Shanghai Composite Index, economic policy uncertainty and geopolitical risk are all risk recipients. To this end, the conclusions of this study can provide some theoretical basis for the policy makers of the BRICS countries to promote the smooth operation of their stock markets.

In the post-epidemic era, global economic policies have been uncertain and the stock market has been volatile. It is crucial to investigate the spillover effect of economic policy uncertainty (EPU) on the stock market for accurately hedging risks and seizing recovery opportunities. This paper applies the DY spillover index and network analysis to study the spillover effect between the U.S. EPU and the U.S. and Asian stock markets. The empirical results show a significant spillover effect in both the U.S. and Asian stock markets, with EPU as the recipient of risk spillover and stock indices as the transmitters. The stock markets in Japan and South Korea react more strongly to shifts in the U.S. EPU. All transmitters attain their maximum values in both the TO and FROM directions in 2020. The from-direction spillover indices of the U.S. stock market are less volatile in 2020 than those of the Asian stock market, indicating that the outbreak of the COVID-19 epidemic has a greater impact on the Asian stock market than the U.S. stock market. These conclusions have substantial implications for asset management, investment diversification and aversion to unsystematic risk in major economic shocks.

This paper investigates the relationship between EPU, oil and stock markets in the BRIC countries under different market conditions. The multivariate quantile VAR approach is used to analyze the possible asymmetric linkage across the entire distribution rather than only on the conditional mean. The empirical results show that, when the Brent oil market is prosperous, EPU in China and India has a negative impact on the oil returns, whereas EPU in Russia and Brazil has a positive effect. Generally, BRIC's EPU has a reverse effect on the stock markets. The economic policies of China and Russia are more vulnerable to fluctuations in oil and stock markets. The BRIC's stock markets are more affected by negative oil returns, whereas the oil markets are more affected by positive stock returns.

With the development of informatization, intelligence and precision of modern agriculture, i.e. there is a need for the integration of artificial intelligence (AI) with Internet of Things (IoT) systems, which is called AIoT (AI + IoT) systems. In this paper, we design an AIoT system for the smart agriculture based on the concept of front-rear end separation and the framework of MVVM (Model-View-View Model), through which it is possible to handle complex business logic and makes the integrating the AI algorithms much easier. Specifically, the system consists of a remote data service platform, the data collection terminals build on Raspberry Pi and the wireless data transmission using narrow-band Internet of Things (NB-IoT) modules. The data service platform is designed with the separated front-end and rear-end. The front-end is a web page constructed by the Vue.js and Element, while the rear-end business logic processing is constructed using the Python Django framework. The data interaction between the front and rear ends is realized through Axios. In such a way, the data in the front-end and the rear-end are decoupled, which makes it possible to improve the capability in dealing with complex data and makes it easy to carry out add-on development and extend new functions. Based on the data service platform, a series of basic application functions are integrated, including real-time data monitoring, historical data query, data visualization and abnormal data alerting, etc. Moreover, we integrate a deep-learning-based plant disease and pest detection algorithm in the propose system to show its scalability. In addition, the system also combines edge computing technology to improve the overall response efficiency of the system. The system has a convenient expansion interface and can be used as a basic development platform for various agricultural IoT applications, such as the soil environmental monitoring system and the intelligent disease and pest monitoring system, etc.

This paper investigates the nonlinear Granger causality and spillover effects among geopolitical risk, crude oil and Chinese disaggregated sectoral stock markets by using a multivariate nonlinear Granger causality test and connectedness network analysis. The nonlinear Granger causality and spillover effects are shown to be heterogeneous across sectors. The nonlinear Granger causality indicates Brent oil is likely to play a more important role in geopolitical risk and Chinese stock markets, especially for the Energy and Financial sectors. But the connectedness network analysis suggests that geopolitical risk is the net receiver of spillover effects from WTI oil and the net transmitter to Brent oil. Chinese sectoral stock markets are the main provider of spillover effects in crude oil and geopolitical risk, and its spillover effects are stronger for the Consumer Discretionary, Industrials, Materials, Health Care and Information Technology sectors. In addition, crude oil may play an essential function as an intermediary receiver of Chinese sectoral stock market shocks to geopolitical risk.

In recent years, the function of the lymphatic system in atherosclerosis has attracted attention due to its role in immune cell trafficking, cholesterol removal from the periphery, and regulation of the inflammatory response. However, knowledge of the mechanisms regulating lymphangiogenesis and lymphatic function in the pathogenesis of atherosclerosis is limited. Endothelial microparticles carrying circulating microRNA (miRNA)s are known to mediate cell–cell communication, and our previous research showed that miRNA-19b in EMPs (EMPmiR-19b) was significantly increased in circulation and atherosclerotic vessels, and this increase in EMPmiR-19b promoted atherosclerosis. The present study investigated whether atherogenic EMPmiR-19b influences pathological changes of the lymphatic system in atherosclerosis. We first verified increased miR-19b levels and loss of lymphatic system function in atherosclerotic mice. Atherogenic western diet-fed ApoE-/- mice were injected with phosphate-buffered saline, EMPs carrying control miRNA (EMPcontrol), or EMPmiR-19b intravenously. The function and distribution of the lymphatic system was assessed via confocal microscopy, Evans blue staining, and pathological analysis. The results showed that lymphatic system dysfunction existed in the early stage of atherosclerosis, and the observed pathological changes persisted at the later stage, companied by an increased microRNA-19b level. In ApoE-/- mice systemically treated with EMPmiR-19b, the distribution, transport function, and permeability of the lymphatic system were significantly inhibited. In vitro experiments showed that miRNA-19b may damage the lymphatic system by inhibiting lymphatic endothelial cell migration and tube formation, and a possible mechanism is the inhibition of transforming growth factor beta receptor type II (TGF-βRII) expression in lymphatic endothelial cells by miRNA-19b. Together, our findings demonstrate that atherogenic EMPmiR-19b may destroy lymphatic system function in atherosclerotic mice by downregulating TGF-βRII expression.

This paper uses time-frequency analysis, including wavelet analysis and time-frequency domain causality, to evaluate the relationship between public attention to the COVID-19 pandemic, crude oil, and gold markets in the G7 countries over time and frequency. Empirical findings show that WTI oil lead gold returns during the COVID-19 outbreak, and vice versa when Omicron spread. The relationship between public attention to the COVID-19 and WTI oil/gold markets appears to be heterogeneous for G7 countries. European public attention caused by the COVID-19 outbreak has a strong impact on gold returns at the 32-64 day frequency, while public attention generated by Omicron has a significant effect on WTI oil returns at 4-128 day frequency. The public in the US and Canada is more concerned about the global stock and WTI oil markets slump than the COVID-19 pandemic. The Italian public seems to be the most sensitive to the EU's economic support plan. The heterogeneity of the public attention-oil/gold nexus in the G7 implies that portfolio diversification across markets and investment horizons may be extremely beneficial.

Hybrid beamforming (HBF) is a promising approach to obtain a better balance between hardware complexity and system performance in massive MIMO communication systems. However, the HBF optimization problem is a challenging task due to its nonconvex property in terms of design complexity and spectral efficiency (SE) performance. In this work, a low-complexity convolutional neural network (CNN)-based HBF algorithm is proposed to solve the SE maximization problem under the constant modulus constraint and transmit power constraint in a multiple-input single-output (MISO) system. The proposed CNN framework uses multiple convolutional blocks to extract more channel features. Considering that the solutions for the HBF are hard to obtain, we derive an unsupervised learning mechanism to avoid any labeled data when training the constructed CNN. We discuss the performance of the proposed algorithm in terms of both the generalization ability for multiple CSIs and the specific solving ability for an individual CSI, respectively. Simulations show its advantages in both SE and complexity over other related algorithms.

This paper studies the relationship between public attention, crude oil and gold markets in G7 countries during the COVID-19 pandemic by using wavelet methods and multi-scale quantile Granger causality. Empirical results reveal that there is a strong linkage among public attention to the COVID-19 pandemic, oil and gold markets in G7 countries on all the time and frequency domains, indicating that during the COVID-19 period, investors quickly associate any fluctuations in the markets with the pandemic and continue to pay attention to it. The two-way Granger causality is found between public attention, oil and gold markets, except the median. In the short term, the causal relationship from gold returns to public attention displays asymmetry, but the causality between the public attention, oil and gold returns shows a strong symmetry in the medium and long term.

Camellia oleifera is a woody edible oil crop with economical importance. This study established an efficient protocol for the induction of callus, the multiplication of a suspension cell line, and the isolation and purification of protoplasts in Camellia oleifera. It is shown that the callus induction was best when anthers were treated with the hormone of 0.5 mg/L NAA (Naphthaleneacetic acid), 2.0 mg/L 2,4-D (2,4-Dichlorophenoxyacetic acid) and 0.5 mg/L 6-BA (6-Benzylaminopurine) at 4 degrees C for 15 days. Callus was further multiplied on MS (Murashige and Skoog) medium augmented with 5% coconut water, 2 mg/L 2,4-D, 0.5 mg/L 6-BA, pH 5.8. Though three types of induced callus transferred to the same liquid medium with the ratio of 1 g callus inoculated into 30 ml liquid medium, it was found that the suspension culture effect of loose particles callus was the best. The maximum yield (11.7 x 10(6)/g.FW) and highest viability (95.1%) of protoplast were reached when cell suspension (cultured for 6 days) was inoculated for 14 h in enzyme solution made of 0.4 mol/L mannitol mixture solution, 1.0% (w/v) Cellulase R-10 and 1.0% (w/v) Macerozyme R-10. The study lays a foundation for future research in cell fusion and transient gene expression in Camellia oleifera.

This paper investigates the relationship between investor attention and the major cryptocurrency markets by wavelet-based quantile Granger causality. The wavelet analysis illustrates the interdependence between investor attention and the cryptocurrency returns. Multi-scale quantile Granger causality based on wavelet decomposition further demonstrates bidirectional Granger causality between investor attention and the returns of Bitcoin, Ethereum, Ripple and Litecoin for all quantiles, except for the medium. Among them, the Granger causality from investor attention to the returns is relatively very weak for Ethereum. In the short term, the Granger causality from these cryptocurrency returns to investor attention seems symmetric, but in the medium-and longterm, the causality shows some asymmetry. The Granger causality from investor attention to these cryptocurrency returns is asymmetric and varies across cryptocurrencies and time scales. Specifically, investor attention has a relatively stronger impact on the cryptocurrency returns in bearish markets than that in bullish markets in the short term.

构建双机制的非线性FAVAR模型,从贝叶斯角度出发,研究中国高耗能行业能源消费对宏观经济以及环境污染因素的影响效应.利用中国高耗能行业的能源消费以及废气排放数据,结合贝叶斯方法进行非线性FAVAR模型的参数估计,结果发现中国高耗能行业的能源消费增加和减少对国内生产总值、外商直接投资等宏观经济因素以及主要环境污染因素都具有非对称影响效应.但是,高耗能能源消费增加或减少的冲击一般都是短期效应,不具有长期影响效应.

This paper uses continuous and discrete wavelet tools to evaluate the dynamic correlation and causality between the U.S. economic policy uncertainty (EPU) and stock markets in China and India from 1997 to 2018. The dynamic correlation in the time-frequency domain is obtained by continuous wavelet coherence, and the causality over time and frequencies is tested by the linear and non-linear Granger causality based on discrete wavelet transform. The results show that the interaction between EPU in the U.S. and stock returns in China and India is weak in the short term but gradually becomes stronger in the long term, especially when significant financial events occur. There is no Granger causality in the short term; however, there is unidirectional or bidirectional causality in the medium and long term. These conclusions may provide useful reference for policymakers and investors in Chinese and Indian stock markets to prevent cross-country risk contagion from the U.S.

针对传统面板协整检验在建模过程中易受异常值影响以及其原假设设置的主观选择问题,本文利用动态公共因子刻画面板数据潜在的截面相关结构,提出基于动态因子的截面相关结构的贝叶斯分位面板协整检验,结合各个主要分位数水平下参数的条件后验分布,设计结合卡尔曼滤波的Gibbs抽样算法,进行贝叶斯分位面板协整检验;并进行Monte Carlo仿真实验验证贝叶斯分位面板协整检验的可行性与有效性.同时,采用中国各省金融发展和经济增长的面板数据进行实证研究,结果发现在各主要分位数水平下中国金融发展和经济增长之间具有协整关系.研究结果表明:贝叶斯分位面板协整检验方法避免了传统面板数据协整方法由于原假设设置不同而发生误判的问题,克服了异常值的影响,能够提供全面准确的模型参数估计和协整检验结果.

文章利用中国行业面板数据建立门限面板数据模型,分析进出口及外商直接投资对能源消耗强度的非线性门限效应.进而运用门限面板数据格兰杰因果检验,研究了不同行业进出口与能源消耗强度之间的非线性格兰杰因果关系.结果 表明:进口会对能源消耗强度作用不显著且偏小,出口则会降低能源消耗强度.外商直接投资存在两个个门限,第一机制显著降低能源消耗强度,而第二、三机制则会提升能源消耗强度,且第三阶段效应大于第二阶段.同时,外商直接投资与能源消耗强度存在双向格兰杰因果关系,而进口额及出口额在不同机制中与能源消耗强度格兰杰因果关系不同,且不同行业间存在差异.

传统门限机制转换模型存在参数估计最优化计算复杂以及参数不可识别的问题,本文构建双机制的贝叶斯门限机制转换协整模型研究国际石油价格与股市之间的非线性动态关系.利用八个亚太股票市场和国际石油价格的数据,结合MCMC抽样算法进行贝叶斯分析,着重考察国际石油—股市之间的非对称效应,结果发现国际石油价格与韩国、马来西亚股市之间具有门限机制转换的非线性协整关系,表明国际石油价格与韩国、马来西亚股市存在非对称效应,而国际石油价格与日本、澳大利亚、印度、印度尼西亚、台湾和新加坡股市之间没有非对称效应.进一步,格兰杰因果检验结果发现,国际石油价格与日本、澳大利亚、韩国、印度、马来西亚、印度尼西亚和新加坡股票价格指数之间存在双向格兰杰因果关系,而与台湾股票价格指数之间没有明显的格兰杰因果关系.

文章针对面板协整检验存在检验势不稳定和原假设设置主观选择的问题,构建贝叶斯分位面板协整模型,结合非对称Laplace分布的似然函数推断参数的后验条件分布,设计Gibbs抽样方案,提出基于面板数据模型的贝叶斯分位协整检验方法,并利用国际原油价格与中国各行业股票价格数据进行实证分析.研究结果表明:贝叶斯分位面板协整检验方法解决了检验势不稳定以及原假设主观设置的问题,能够给出更全面有效的协整检验判断.