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To improve the adaptability of the robot pan–tilt to the high-temperature environment, a design scheme for a composite thermal protection structure composed of aerogel felt, hollow glass, and skin is proposed. The effects of aerogel felt thickness, glass type, and ambient temperature on the thermal protection performance of the structure are studied, using a fluid–solid–thermal coupling model. Numerical results show that the structure exhibits good protection performance, and that the thermal resistance distribution changes the main path of heat transmission. The optimal thickness of the aerogel felt is approximately 8 mm. Compared to 3 mm, 5 mm, and 10 mm thicknesses, 8 mm reduces the maximum temperature by 15.90%, 8.37%, and 6.22%, and reduces the total entropy by 79.23%, 52.44%, and 12.5%. Lower thermal conductivity of the gas inside the hollow glass results in decreased maximum temperatures and total entropy. Using argon-filled hollow glass at 573.15 K decreases maximum temperature by 33.52% and 8.40%, with a total entropy reduction of 33.46% and 6.04%, compared to the single-layer and air-filled glass. Higher ambient temperatures correlate with increased maximum temperature, total entropy, and average surface-heat-transfer coefficient, indicating that the adaptability of the structure to high-temperature environments is limited. [ABSTRACT FROM AUTHOR]

This paper proposes a new risk measurement model that directly incorporate information from high‐frequency data to predict daily Value‐at‐Risk and expected shortfall. In this model, Regular‐Vine copula and Monte Carlo simulation are applied to produce the predicted intraday returns that have nonlinear dependences. And the time‐varying marginal distribution of intraday returns is estimated under the framework of generalized autoregressive score. The model is so named R‐Vine‐Copula‐GAS (abbreviated as RVCGAS). The predicted intraday returns in the same day are added up to obtain the daily return and form its empirical distribution. The risk measurements are then calculated based on this simulated distribution. An empirical analysis is conducted using data from the index in China's stock market and some of its constituents, and the effects of the proposed model and several Benchmark models are compared through some backtestings. The results show that RVCGAS has an advantage over others in predicting tail risk when the risk level is high, since it could cover more risky returns and reduce more costs. [ABSTRACT FROM AUTHOR]

By observing the actual movement of asset prices, we find that there is a persistent shock impact of jumps on prices rather than a transient effect. To address this phenomenon, we propose a new jump-diffusion model that restores the process of price by assuming that its continuous changes are determined by the diffusion process, while individual jumps are inscribed by a filtered Poisson process. We also come up with estimation methods for the parameters involved in the jump process, as well as methods for identifying jumps and determining the duration of the transit impact of jumps based on the actual price series. In terms of simulations, the consistency of the estimation results is verified in detail. Finally, we select two representative indexes in the China's stock market as empirical objects. We build the price models, perform jump tests and parameter estimation for them, and compare the results with that of the traditional multi-sample BN-s to demonstrate the validity and robustness of the proposed models and estimation methods. [ABSTRACT FROM AUTHOR]

Increasing plant density usually increases the intra‐specific competition of maize plants. This study was conducted to determine whether maize (Zea mays L.) hybrid density tolerance is related to intra‐specific competition. Field experiments were conducted using a split‐plot design, the main plots contained four maize hybrids, and subplots were 12 plant densities varied from 1.5 to 18 × 104 plants ha−1. This study focused on dry matter accumulation, grain yield (GY), competition intensity (CI), and absolute severity of competition (ASC) based on the above treatments. Among all tested hybrids, GY exhibited a curvilinear response to plant density, which was well characterized by the Steinhart–Hart equation. Maize hybrids differed in optimum GY in descending order as follows: Zhongdan909 (ZD909) > Xianyu335 (XY335) = Yedan13 (YD13) > Zhongdan2 (ZD2). The CI and ASC of tested maize hybrids indicated that intra‐specific competition increased with increasing plant density. In most cases, the CI and ASC of older maize hybrids were higher than those of modern maize hybrids when plant density exceeded 9.0 × 104 plants ha−1. The results showed that the slope of the linear regression of ASC and plant density (i.e., the k‐value) could be used to compare the intra‐specific CI of maize hybrids, and there were significant negative correlations of k‐value with optimum plant density and GY. Intra‐specific competition is negatively correlated with the density tolerance of maize hybrids. This relationship may provide new insights for determining future maize breeding targets. [ABSTRACT FROM AUTHOR]