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This paper aims to predict the effect of the hub cavity leakage on the overall performance with numerical simulations in the fan/booster of a high bypass ratio turbofan engine.

Simulations are conducted for leakage at the fan, the outlet of guide vane and the three-stage booster, as well as hub leakage (contain cavities and sealing). The results obtained are compared to the corresponding simulations without hub leakage.

The rotor/stator interaction locations are evaluated to discover a better location. The results show that the seal tooth structure produces secondary flow and turbulence in the root of blade suction surface, which increases the aerodynamic loss. The sealing clearance should be controlled to shrink the turbulent region and decrease the leakage.

This work can provide a theoretical guidance and technical support for the compressor design, which avoid many repeated manufactures and reduce waste of resources.

This work improves the understanding of the impact mechanism of hub cavity leakage on the performance when the clearance size of seal is variable.

Bitcoin (BTC) is significantly correlated with global financial assets such as crude oil, gold and the US dollar. BTC and global financial assets have become more closely related, particularly since the outbreak of the COVID-19 pandemic. The purpose of this paper is to formulate BTC investment decisions with the aid of global financial assets.

This study suggests a more accurate prediction model for BTC trading by combining the dynamic conditional correlation generalized autoregressive conditional heteroscedasticity (DCC-GARCH) model with the artificial neural network (ANN). The DCC-GARCH model offers significant input information, including dynamic correlation and volatility, to the ANN. To analyze the data effectively, the study divides it into two periods: before and during the COVID-19 outbreak. Each period is then further divided into a training set and a prediction set.

The empirical results show that BTC and gold have the highest positive correlation compared with crude oil and the USD, while BTC and the USD have a dynamic and negative correlation. More importantly, the ANN-DCC-GARCH model had a cumulative return of 318% before the outbreak of the COVID-19 pandemic and can decrease loss by 50% during the COVID-19 pandemic. Moreover, the risk-averse can turn a loss into a profit of about 20% in 2022.

The empirical analysis provides technical support and decision-making reference for investors and financial institutions to make investment decisions on BTC.

The paper debunks Peter P. Li’s assertion that Yin-Yang is superior to any other cognitive frames or logical systems for paradox research. The purpose of this paper is to alert the Chinese indigenous management researchers to the danger of Chinese exceptionalism and over-confidence.

To show that Peter P. Li’s assertion is doubtful, the authors identify the flaws in his analysis.

The authors find that there are three serious flaws in Peter P. Li’s analysis. First, there are four defects in the typology of cognitive frames he built in order to compare Yin-Yang with the others. Second, his understanding of dialectics in general and Hegelian dialectics in particular is flawed. And finally, without resorting to Yin-Yang, many scholars can develop theories that are equivalent to those derived from Yin-Yang.

Due to the page limit, this paper only focuses on arguing that Yin-Yang is not superior to other cognitive frames or logical systems without going one step further to explain in which situations Yin-Yang are valuable and might be more suitable than others for helping us understand some research issues.

This paper implies that we should not blindly believe that the Chinese way of thinking and acting is superior to other people’s. Chinese people should be open-minded in the globalized era, not only promoting their own culture but also appreciating and learning from other cultures.

The reduction of cultural exceptionalism and ethnocentrism can make cross-cultural communication and interaction smoother.

This paper is a rigorous critique on the “Yin-Yang being superior” assertion of Peter P. Li.

The coal-fired power plants have been confronted with new operation challenge since the unified carbon trading market was launched in China. To make the optimal decision for the carbon emissions and power production has already been an important subject for the plants. Most of the previous studies only considered the market prices of electricity and coal to optimize the generation plan. However, with the opening of the carbon trading market, carbon emission has become a restrictive factor for power generation. By introducing the carbon-reduction target in the production decision, this study aims to achieve both the environmental and economic benefits for the coal-fired power plants to positively deal with the operational pressure.

A dynamic optimization approach with both long- and short-term decisions was proposed in this study to control the carbon emissions and power production. First, the operation rules of carbon, electricity and coal markets are analyzed, and a two-step decision-making algorithm for annual and weekly production is presented. Second, a production profit model based on engineering constraints is established, and a greedy heuristics algorithm is applied in the Gurobi solver to obtain the amounts of weekly carbon emission, power generation and coal purchasing. Finally, an example analysis is carried out with five generators of a coal-fired power plant for illustration.

The results show that the joint information of the multiple markets of carbon, electricity and coal determines the real profitability of power production, which can assist the plants to optimize their production and increase the profits. The case analyses demonstrate that the carbon emission is reduced by 2.89% according to the authors’ method, while the annual profit is improved by 1.55%.

As an important power producer and high carbon emitter, coal-fired power plants should actively participate in the carbon market. Rather than trade blindly at the end of the agreement period, they should deeply associate the prices of carbon, electricity and coal together and realize optimal management of carbon emission and production decision efficiently.

This paper offers an effective method for the coal-fired power plant, which is struggling to survive, to manage its carbon emission and power production optimally.

This study explores the impact of EN's (venture entrepreneurs, simplified as EN) jealousy fairness concerns coefficient on two-stage venture capital decision-making in cases of symmetrical and asymmetrical information. It discusses the equilibrium solution of two-stage venture.

The principal-agent model was established based on multiple periods, and differentiated contracts were established at different stages. The validity of the models and the contract was verified by numerical simulation.

The results suggest that with the increase in the EN fairness concerns coefficient, the effort level of EN decreases continuously and decreases faster in the second stage because this is the last stage. The level of VC's (venture capitalist, simplified as VC) effort declines first and then increases; that is, VC will increase the effort level when the fairness concerns coefficient increases to a certain threshold. To motivate EN to pay more effort, VC will increase the incentive to EN in the first stage. However, it will reduce the level of incentive to EN in the second stage. In the limited stage of venture investment, consider that the fairness concerns of EN do not make the profits of EN and VC achieve Pareto improvement simultaneously.

First, the authors implanted fairness concerns into multi-stage venture capital and discussed the impact of fairness concerns on the efforts and returns of both parties. Second, among the influencing factors of the project output, the authors consider the bilateral efforts of EN and VC, the working capacity of EN, the initial investment scale, and the external uncertain environment.

The purpose of this paper is to analyze the bird impact damage of fuselage composite stiffened structures by numerical method and to evaluate the damage and the bird impact resistance of different structures.

The deformation and damage of composite stiffened plates during bird impact are numerically analyzed by the explicit finite element software LS-DYNA. A comparative study on the numerical calculation results was conducted by using SPH (Smoothed Particle Hydrodynamics)-FEM (Finite Element Method) modeling and simulation. First, the I-shaped, T-shaped, straight stiffened plates and unstiffened plate were designed. Second, the accuracy of the bird model was verified and further used to evaluate bird strikes on composite stiffened plate. Third, the results of damage modes as well as displacements of the stiffened plates were compared.

The stiffeners can increase the local stiffness of the composite panel, which can effectively inhibit the bird’s movement along the impact direction. Adding stiffeners can change the panel matrix tension damage from global distribution to local distribution mode; however, the impact damage distribution and the ability to inhibit damage propagation can differ for different stiffened panels. Especially, the I-stiffened panel exhibits a better anti-bird strike performance.

The analysis of geometric parameters of structural components by numerical methods can reduce the cost of the design phase and has been widely used in aircraft design. The present study evaluated the bird impact damage of composite stiffened plates with different structures, which provides a guideline for selecting the stiffened plate structure in the fuselage skin.

The purpose of this paper is to show how a quartz crystal microbalance modified with poly (epichlorohydrin) (PECH) is fabricated and used for detection of acetone vapor using a spin‐coating method.

Measurements are based on the frequency shifts due to the adsorption of acetone vapor on the surface of the modified electrodes. A first‐order linear time‐invariant (LTI) system model is used to simulate the sensor response.

It is found that frequency shifts are linear to the concentrations of analyte, and cycle test examination shows good repeatability. The sensitivity to acetone vapor is better than other volatile compounds. A good match result is obtained with the LTI system model.

The device performance opens a potential way for analyzing acetone vapor.

The purpose of this paper is to review systematically the research of grey relation analysis (GRA) models.

Three different approaches, the springboard to build a GRA model, the angle of view in modelling, and the dimension of objects, are analysed, respectively.

The GRA models developed from the models based on relation coefficients of each point in the sequences in early days to the generalized GRA models based on integral or overall perspective. It evolved from the GRA models which measure similarity based on nearness, into the models which consider similarity and nearness, respectively. The objects of the research advanced from the analysis of relationship among curves to that among curved surfaces, and further to the analysis of relationship in three‐dimensional space and even the relationship among super surfaces in n‐dimensional space.

The further research on GRA models is proposed. One is about the property of GRA model. An in‐depth knowledge about the properties of GRA model will help people to understand its function, applicable area and requirements for modelling. The other one is about the extension of research object system. The object to be analysed should be extended from the common sequence of real numbers to grey numbers, vectors, matrices, and even multi‐dimensional matrices, etc.

The purpose of this article is to develop relationships between many major issues relevant to the agriculture supply chain.

With the purpose of gaining an all-encompassing understanding of the agriculture supply chain, this work uses 233 filtered research articles and three bibliometric analysis tools, namely VOSviewer, term frequency-inverse document frequency (TF-IDF) and Person correlation. The collected research publications were also catalogued using Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA).

Using analytic techniques, a total of 12 keywords were obtained. The study found that agri-products are in dire need of digitisation via Internet of things (IoT) and blockchain due to the usage of economic variables and comprehensive management of total food waste throughout transportation, anchoring quality and the predominant variable.

The study was limited to the Scopus and Web of Science (WoS) indexing in order to assess the viability of the linked idea and problem.

This study aims to generate vital knowledge in the field of horticulture-focused agriculture supply chain based on previous justification and relationship formation.