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The development of high-speed aerial vehicles urgently requires high-performance integrated materials for ablation resistance, thermal insulation and oxidant protection under high temperature. The previously prepared carbon aerogel composites (C/CA), with ultra-high temperature thermal insulation properties, were impregnated with SiCO precursor sol and pyrolysed in nitrogen atmosphere at 1200°C. The impregnation/pyrolysis process was performed once, twice and thrice to obtain three different C/C-SiCO nanoporous ceramic composites. Further, TaSi2-MoSi2-borosilicate glass (TM-BG) coating or TaSi2-MoSi2-ZrB2-borosilicate glass (TMZBG) coating was prepared on the surface of the C/C-SiCO through slurry brushing combined with graphite powder embedded sintering process. By simulating the actual application environment through oxygen acetylene flame ablation test, the ablation resistance of the samples was studied and their oxidation mechanism was analysed. The results show that the ablation rate of the C/C-SiCO after 200 s ablation at 1600 °C decreases with the increase of the number of impregnation/pyrolysis steps and that the ablation resistance of the coating modified C/C-SiCO was significantly enhanced. The addition of ZrB2 to the coating improves the compatibility between the substrates and the coating, and the TMZ-BG coated sample has better ablation resistance. At high temperature, the borosilicate glass in the coating is in a viscous flow state. Meanwhile the SiO2 generated by the oxidation of other silicide raw materials forms a dense glass layer on the coating surface, which can be used as an oxygen barrier to provide better protection for the substrates. The coating-modified C/C-SiCO porous ceramic composites are expected to be used as a high-temperature ablation-resistant material for the thermal protection system of new aerospace vehicles.

SUMMARY: Domestication has dramatically increased crop size and biomass, reflecting the enhanced accumulation of photosynthates. However, we still lack solid empirical data on the impacts of domestication on photosynthetic rates at different light intensities and on leaf anatomy, and of the relationships of photosynthesis with aboveground biomass. In this study, we measured the photosynthetic rate at three photosynthetic photon flux densities of 2000 (high), 1000 (moderate) and 400 μmol m−2 sec−1 (low light intensity), dark respiration, relative chlorophyll content (SPAD), leaf morphology, and aboveground biomass in 40 wild, 91 semiwild, and 42 domesticated cotton genotypes. The study was replicated for two years (growing years 2018 and 2019). During the first domestication stage (transition from wild to semiwild genotypes), domestication led to higher photosynthetic rates measured under high light intensity, higher SPAD, larger leaf area (LA), and lower leaf mass per unit area (LMA), contributing to greater aboveground biomass accumulation in both study years. During the second domestication stage (transition from semiwild to domesticated genotypes), domestication significantly enhanced photosynthesis under low light intensity and reduced LMA, which were associated with increased aboveground biomass in both study years. In conclusion, photosynthesis improvement at different light intensities has been a gradual domestication phase specific process with the rate of photosynthesis enhanced under high light during the first domestication stage, and under low light during the second domestication stage. We argue that these differences reflect a higher proportion of LA photosynthesizing under low light due to enhanced canopy expansion at the second domestication stage. Significance Statement: Photosynthesis improvement at different light intensities has been a gradual domestication phase specific process with the rate of photosynthesis enhanced under high light during the first domestication stage, and under low light during the second domestication stage. [ABSTRACT FROM AUTHOR]

Efficient initiation of oblique detonation waves (ODWs) is crucial for optimizing the performance of oblique detonation wave engines. A novel approach is proposed for enhancing ODW initiation through expansion waves in this research. Validation of the expansion wave-reinforced initiation method is conducted via numerical simulations employing multi-species reactive Euler equations and a pressure-dependent reaction mechanism. Results demonstrate a significant reduction in the initiation length of ODWs with the addition of an expansion wave ahead of the wedge, contrasting with the absence of detonation wave initiation on a wedge lacking an expansion wave. A theoretical model, based on expansion wave and shock wave relations, along with constant volume combustion theory, elucidates the underlying mechanism of reinforcement. The model reveals that crossing the expansion wave elevates the fluid's Mach number and locally enlarges the flow deflection angle on the wedge surface, without altering the wedge's structure. Furthermore, post-shock temperature increases and pressure decreases compared to the wedge not encountering an expansion wave. The heightened temperature predominantly triggers ODW initiation, thus reinforcing the process. Theoretical analyses indicate the reinforcement's greater efficacy at lower inflow temperatures and lower inflow Mach numbers, suggesting the expansion wave's suitability for initiation in the early flight stages of an aircraft equipped with oblique detonation wave engines. [ABSTRACT FROM AUTHOR]

This paper employs a shrinkage method named Adaptive Lasso (ALasso) to predict the realized volatility (RV) of the China's stock market with numerous predictors. We observed from the out‐of‐sample predictions that the ALasso model exhibits better predictive power than its competitors, implying that the ALasso method can select stronger predictors in the forecasting process than competing models. In addition, the predictability of ALasso method is better in low volatility periods than in high volatility periods. Finally, several robustness check methods, including different forecasting windows, different low and high volatility division, and different volatility measures, supported our results. [ABSTRACT FROM AUTHOR]

Using the dynamic connectedness framework of Antonakakis et al. (2020), this paper explores the financial stress spillover characteristic across nine Asian countries during major economic, political and public health emergency events, especially during COVID-19. We first find a substantial increase in the intensity of total financial stress spillover across nine Asian countries during COVID-19. Second, there are clear differences in the financial stress spillover networks across Asian countries during different economic and political events. In particular, in the first three months after the outbreak of COVID-19, there was considerable month-to-month variation in the financial stress spillover network. Singapore and Japan are the major net transmitter and receiver of financial stress shocks, respectively, during all considered events. During COVID-19, China, as the first country to detect and contain COVID-19, is the strongest net financial stress shock receiver in March 2020, but transmitted net financial stress shocks in February 2020, when the epidemic in China is serious. [ABSTRACT FROM AUTHOR]

Cyclic electron flow around photosystem I (CEF-PSI) is shown to be an important protective mechanism to photosynthesis in cotton leaves. However, it is still unclear how CEF-PSI is regulated in non-foliar green photosynthetic tissues such as bracts. In order to learn more about the regulatory function of photoprotection in bracts, we investigated the CEF-PSI attributes in Yunnan 1 cotton genotypes (Gossypium bar-badense L.) between leaves and bracts. Our findings demonstrated that cotton bracts possessed PROTON GRADIENT REGULATION5 (PGR5)-mediated and the choroplastic NAD(P)H dehydrogenase (NDH)-mediated CEF-PSI by the same mechanism as leaves, albeit at a lower rate than in leaves. The ATP synthase activity of bracts was also lower, while the proton gradient across thylakoid membrane (ΔpH), rate of synthesis of zeaxanthin, and heat dissipation were higher than those of the leaves. These results imply that cotton leaves under high light conditions primarily depend on CEF to activate ATP synthase and optimize ATP/NADPH. In contrast, bracts mainly protect photosynthesis by establishing a ΔpH through CEF to stimulate the heat dissipation process. [ABSTRACT FROM AUTHOR]

Tissue engineering is an alternative method for preparing small‐caliber (<6 mm) vascular grafts. Dynamic mechanical conditioning is being researched as a method to improve mechanical properties of tissue engineered blood vessels. This method attempts to induce unique reaction in implanted cells that regenerate the matrix around them, thereby improving the overall mechanical stability of the grafts. In this study, we used a bioreactor to seed endothelial cells and smooth muscle cells into the inner and outer layers of the electrospun spider silk protein scaffold respectively to construct vascular grafts. The cell proliferation, mechanical properties, blood compatibility and other indicators of the vascular grafts were characterized in vitro. Furthermore, the vascular grafts were implanted in Sprague Dawley rats, and the vascular grafts' patency, extracellular matrix formation, and inflammatory response were evaluated in vivo. We aimed to construct spider silk protein vascular grafts with the potential for in vivo implantation by using a pulsating flow bioreactor. The results showed that, when compared with the static culture condition, the dynamic culture condition improved cell proliferation on vascular scaffolds and enhanced mechanical function of vascular scaffolds. In vivo experiments also showed that the dynamic culture of vascular grafts was more beneficial for the extracellular matrix deposition and anti‐thrombogenesis, as well as reducing the inflammatory response of vascular grafts. In conclusion, dynamic mechanical conditioning aid in the resolution of challenges impeding the application of electrospun scaffolds and have the potential to construct small‐caliber blood vessels with regenerative function for cardiovascular tissue repair. [ABSTRACT FROM AUTHOR]

To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1468-5957.2009.02163.x Byline: Xiafei Li (1), Chris Brooks (1), Joelle Miffre (1) Keywords: value premium; time-varying volatility; CAPM; GJR-GARCH(1,1)-M Abstract: Abstract: Numerous studies have documented the failure of the static and conditional capital asset pricing models to explain the difference in returns between value and growth stocks. This paper examines the post-1963 value premium by employing a model that captures the time-varying total risk of the value-minus-growth portfolios. Our results show that the time-series of value premia is strongly and positively correlated with its volatility. This conclusion is robust to the criterion used to sort stocks into value and growth portfolios and to the country under review (the US and the UK). Our paper is consistent with evidence on the possible role of idiosyncratic risk in explaining equity returns, and also with a separate strand of literature concerning the relative lack of reversibility of value firms' investment decisions. Author Affiliation: (1)The authors are respectively, from Nottingham University Business School; ICMA Centre, University of Reading; and EDHEC Business School, Nice, France. They would like to thank the editor, Norman Strong, and an anonymous referee for very useful comments on a previous version of this paper. They are also grateful to J. Doukas, H. Lohre, N. Todorovic and seminar participants at the EDHEC-EFM 2008 symposium for their comments. All remaining errors are the authors' own. Article History: (Paper received July 2008; revised version accepted June 2009) Article note: (*) Address for correspondence: Chris Brooks, ICMA Centre, University of Reading, Whiteknights, Reading RG6 6BA, UK., e-mail: C.Brooks@rdg.ac.uk

This paper focuses on distinguishing the predictive power of five newly developed uncertainty indices, that is, global and US economic policy uncertainty (GEPU and US EPU), global geopolitical risk (GPR), US monetary policy uncertainty (MPU) and equity market volatility (EMV), on crude oil market volatility. We construct the extended GARCH‐MIDAS models to assess the forecasting ability of these indices and then compare them with four commonly used oil volatility drivers: oil supply, oil demand, oil speculation and interest rate. Firstly, the in‐sample analysis suggests that all uncertainty indices and traditional determinants have significant impacts on oil volatility. Secondly, the out‐of‐sample evaluations suggest that US MPU, EMV and EPU indices are more powerful than other predictors to improve the forecasting accuracy of crude oil volatility, and US EMV exhibits the best prediction ability. Then, we find that EPU and MPU indices are more effective in forecasting high volatility in crude oil market, while traditional determinants together with US EMV index are more helpful in predicting low oil volatility. Finally, the forecasts of bad oil volatility can be improved by all predictors except for GEPU index, while the forecasts of good oil volatility can only be enhanced by US MPU, EMV and EPU. [ABSTRACT FROM AUTHOR]

In this paper, we detect the contributions of various predictors in terms of density forecasts of monthly West Texas Intermediate (WTI) crude oil prices. In the first step, we use a simple predictive regression of crude oil prices on different predictors one‐by‐one as explanatory variables, and then two kinds of criteria, Log Score and Continuous Ranked Probability Score (CRPS), are employed to evaluate the density forecasting accuracy of them. In the second step, we utilize a CRPS‐weighted combination and an equal‐weighted combination, respectively, to assemble various density forecasting results in the first step. Finally, a novel test proposed by Rossi and Sekhposyan (2019) is adopted to verify the correct calibration of predictive densities by these two combination methods as well as an AR benchmark model. The empirical results indicate that those predictors proved to perform well (poor) in point forecasts of crude oil price in extant literature do not necessarily offer high (low) density forecasting accuracy. Interestingly, WTI oil futures price is the only predictor that can produce good out‐of‐sample density forecasts across various time horizons. In addition, we find that the two model combination methods can beat the AR benchmark in density forecasting of crude oil price. However, no model can produce correct calibration of predictive densities for crude oil price at time horizons longer than about 5 years. [ABSTRACT FROM AUTHOR]

Being more and more popular in the past 10 years, Bitcoin has drawn extensive attention from the press, scholars, and practitioners. The aim of this paper is to investigate which predictor is more predictive for Bitcoin volatility from the aspects of in‐sample and out‐of‐sample in a high‐speed changing world. We utilise the GARCH‐MIDAS model to examine the predictive power of five crucial predictors, including VIX, GVZ, Google Trends, GEPU, and GPR. Our findings provide strong evidence that GVZ exhibits strongest predictability for Bitcoin volatility over other competing predictors. Other empirical results based on different out‐of‐sample forecasting periods, alternative loss functions and combination methods further ensure our major conclusions are robust. [ABSTRACT FROM AUTHOR]