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The purpose of this paper is to establish a two-stage grey cloud clustering model to assess the drought risk level of 18 prefecture-level cities in Henan Province.

The clustering process is divided into two stages. In the first stage, grey cloud clustering coefficient vectors are obtained by grey cloud clustering. In the second stage, with the help of the weight kernel clustering function, the general representation of the weight vector group of kernel clustering is given. And a new coefficient vector of kernel clustering that integrates the support factors of the adjacent components was obtained in this stage. The entropy resolution coefficient of grey cloud clustering coefficient vector is set as the demarcation line of the two stages, and a two-stage grey cloud clustering model, which combines grey and randomness, is proposed.

This paper demonstrates that 18 cities in Henan Province are divided into five categories, which are in accordance with five drought hazard levels. And the rationality and validity of this model is illustrated by comparing with other methods.

This paper provides a practical and effective new method for drought risk assessment and, then, provides theoretical support for the government and production departments to master drought information and formulate disaster prevention and mitigation measures.

The model in this paper not only solves the problem that the result and the rule of individual subjective judgment are always inconsistent owing to not fully considering the randomness of the possibility function, but also solves the problem that it’s difficult to ascertain the attribution of decision objects, when several components of grey clustering coefficient vector tend to be balanced. It provides a new idea for the development of the grey clustering model. The rationality and validity of the model are illustrated by taking 18 cities in Henan Province as examples.

The purpose of this paper is to propose a grey clustering model based on kernel and information field to deal with the situation in which both the observation values and the turning points of the whitenization weight function are interval grey numbers.

First, the “unreduced axiom of degree of greyness” was expanded to obtain the inference of “information field not-reducing”. Then, based on the theoretical basis of inference, the expression of whitenization weight function with interval grey number was provided. The grey clustering model and fuzzy clustering model were compared to analyse the relationship and difference between the two models. Finally, the paper model and the fuzzy clustering model were applied to the example analysis, and the interval grey number clustering model was established to analyse the influencing factors of regional drought disaster risk in Henan Province.

The example analysis results illustrate that although the two clustering methods have different theoretical basis, they are suitable for dealing with complex systems with uncertainty or grey characteristic, solving the problem of incomplete system information, which has certain feasibility and rationality. The clustering results of case study show that five influencing factors of regional drought disaster risk in Henan Province are divided into three classes, consistent with the actual situation, and they show the validity and practicability of the clustering model.

The paper proposes a new whitenization weight function with interval grey number that can transform interval grey number operations into real number operations. It not only simplifies the calculation steps, but it has a great significance for the “small data sets and poor information” grey system and has a universal applicability.

This paper aims to investigate how user expectations affect value-added service (VAS) investment and pricing decisions of two-sided platforms. It draws on the information asymmetry theory and offers suggestions on how platform operators can manage user expectations.

According to the game theory, this study considers three user expectations (responsive, passive and wary). By framing the Hotelling duopoly model and comparing the VAS investment, price and platform profits, the optimal platform decision is analyzed and discussed.

The conclusions demonstrate that the monopolistic two-sided platform obtains more profits from the informed users with responsive expectations than uninformed users with passive or wary expectations. The marginal investment cost and cross-network externalities are two key factors that determine the platform's VAS investment and pricing strategies of passive or wary users. Furthermore, considering the expectation preferences, i.e. the uniformed users hold wary expectations with more information and hold passive expectations with less or no information, the results suggest that the proportion of wary users to all uninformed users increases the platform's VAS investment, profits and the price of informed users, and increase (decrease) the price of uninformed users when the cross-network externalities of informed users are relatively small (larger).

These results can provide insightful enlightenment into how platform operators utilize bilateral users' expectations and information level to guide their VAS investment and pricing decisions.

This paper is one of the first to explore the impact of three user expectations and the heterogeneity of preferences in informing users' passive or wary expectations, based on different levels of information on the decision-making of two-sided platforms regarding VAS.

The purpose of this study is to develop a model extending Oriani’s formula by introducing a normalised concentration to simulate hydrogen diffusion in a multi-material system such as coated steels, under the presence of traps.

Implemented through the finite element method based on the analogy between mass diffusion and heat transfer, the governing equation was applied to investigate the combined effects of hydrogen traps and surface oxide films on hydrogen permeation in ferritic steels.

This study shows that the effective diffusivity varies over several orders of magnitude depending on the traps and films. This explains the divergence of measured hydrogen diffusivities in steels. It is revealed that hydrogen permeation in steels with Pd or Ni film is a trapping-dominant transport process, while hydrogen permeation in steel with oxide film is a process controlled by both trapping effect and retarding effect of oxide film. The oxide film enhances total hydrogen concentration within the steel substrate and is therefore detrimental. The Pd or Ni film has a little influence on total hydrogen concentration distribution depending on trapping energy.

Hydrogen flux curves and transient hydrogen concentration distributions can be directly obtained through the developed model. The proposed approach can also be extended to investigate other interstitial (i.e. carbon, oxygen and nitrogen) diffusion with traps revisited in complex systems.

Catechu liquor, which is deep brown-red in color, was purified with a micro-filtration membrane and the stability of catechu dye to different levels of temperatures and pH were investigated in this paper. The effects of the dyeing conditions on color characteristic values and color fastnesses of the dyed wool fabrics were also investigated. The results show that the liquor of catechu dye is stable at pH values of 3-7 and its color changes to a deeper brown-red when its pH value is above 8. The preferable dyeing conditions for wool fabric with refined powder catechu dye are as follows: dyeing temperature of 100±C, pH value of 6.5 for the dye bath and catechu dye of 1-4% (o.w.f).

The dyed wool fabric has good color fastnesses to washing, alkali perspiration and dry rubbing. However, its color fastness rating to wet rubbing is poor, ranging from 2-3. Further research will be needed on this aspect.

This paper aims to establish the mathematical models for the water-lubricated thrust bearing with groove texture considering turbulence and cavitation and numerically analyze the influence of rotary speed, texture depth, groove number and groove width on the static performance of the bearing.

The turbulent Reynolds equation and the Jakobsson–Floberg–Olsson cavitation model are adopted for the analysis. The Payvar–Salant algorithm and Finite difference schemes are used to discretize the governing equations. To illustrate the influence of turbulence, the performance of the bearing predicted by the turbulent and laminar models are compared.

According to the results, the load capacity and the friction force calculated by the turbulent model are greater than those obtained by laminar model, and the deviation between them gradually increases with the increased rotary speed. So, the turbulent effect should be fully considered for high-speed water-lubricated bearing with surface texture. There exists a peak value for the load capacity of the water-lubricated thrust bearing in respect to the texture depth, the number of grooves and the groove width ratio, while the friction force varies slowly with those parameters. Well-designed groove texture can improve the performance of the water-lubricated thrust bearing.

This paper proposes a mathematical model considering turbulent and cavitation effect for water-lubricated thrust bearing with surface texture. This model can be complementary to conventional laminar model which is used to analyze the performance of textured bearing at low rotary speed.

This paper aims to focus on the sensor fault-tolerant control (FTC) for civil aircraft under exterior disturbance.

First, a three-step cubature Kalman filter (TSCKF) is designed to detect and isolate the sensor fault and to reconstruct the sensor signal. Meanwhile, a nonlinear disturbance observer (NDO) is designed for disturbance estimation. The NDO and the TSCKF are combined together and an NDO-TSCKF is proposed to solve the problem of sensor faults and bounded disturbances simultaneously. Furthermore, an FTC scheme is designed based on the nonlinear dynamic inversion (NDI) and the NDO-TSCKF.

The method is verified by a Cessna 172 aircraft model under bias gyro fault and constant angular rate disturbance. The proposed NDO-TSCKF has the ability of signal reconstruction and disturbance estimation. The proposed FTC scheme is also able to solve the sensor fault and disturbance simultaneously.

NDO-TSCKF is the novel algorithm used in sensor signal reconstruction for aircraft. Then, disturbance observer-based FTC can improve the flight control system performances when the system with faults.

The NDO-TSCKF-based FTC scheme can be used to solve the sensor fault and exterior disturbance in flight control. For example, the bias gyro fault with constant angular rate disturbance of a civil aircraft is studied.

Signal reconstruction for critical sensor faults and disturbance observer-based FTC for civil aircraft are useful in modern civil aircraft design and development.

This is the research paper studies on the signal reconstruction and FTC scheme for civil aircraft. The proposed NDO-TSCKF is better than the current reconstruction filter because the failed sensor signal can be reconstructed under disturbances. This control scheme has a better fault-tolerant capability for sensor faults and bounded disturbances than using regular NDI control.

The purpose of this study to provide a reference basis for effectively managing the risk of agrometeorological disasters in Henan Province, speeding up the establishment of a scientific and reasonable system of agrometeorological disasters prevention and reduction and guaranteeing grain security.

Firstly, according to the statistical data of areas covered by natural disaster, areas affected by natural disaster, sown area of grain crops and output of grain crops from 1979 to 2018 in Henan Province, China. We have constructed an agrometeorological disaster risk assessment system for Henan province, China, which is composed of indicators such as rate covered by natural disaster, rate affected by natural disaster, disaster coefficient of variation and disaster vulnerability. The variation characteristics of agrometeorological disasters in Henan Province and their effects on agricultural production are analyzed. Secondly, the grey relational analysis method is used to analyze the relation degree between the main agrometeorological disaster factors and the output of grain crops of Henan Province. Based on the grey BP neural network, the rate covered by various natural disaster and the rate affected by various natural disaster are simulated and predicted.

The results show that: (1) the freeze injury in the study period has a greater contingency, the intensity of the disaster is also greater, followed by floods. Droughts, windstorm and hail are Henan Province normal disasters. (2) According to the degree of disaster vulnerability, the ability to resist agricultural disasters in Henan Province is weak. (3) During the study period, drought and flood are the key agrometeorological disasters affecting the grain output of Henan Province, China.

The systematic analysis and evaluation of agrometeorological disasters are conducive to the sustainable development of agriculture, and at the same time, it can provide appropriate and effective measures for the assessment and reduction of economic losses and risks.

By calculating and analyzing the rate covered by natural disaster, the rate affected by natural disaster, disaster coefficient of variation and disaster vulnerability of crops in Henan Province of China and using grey BP neural network simulation projections for the rate covered by various natural disaster and the rate affected by various natural disaster, the risk assessment system of agrometeorological disasters in Henan is constructed, which provides a scientific basis for systematic analysis and evaluation of agrometeorological disasters.

This study investigates how and when employees' perceived corporate social responsibility (CSR) encourages their workplace pro-environmental behavior (WPB).

Survey data were collected from 189 employees of different industries in southern China. Data were analyzed using PROCESS macro.

This study found that intrinsic motivation mediated the relationship between perceived CSR and WPB. Furthermore, self-concern strengthened the indirect perceived CSR–WPB link.

This study contributes to the existing literature of micro-CSR by highlighting intrinsic motivation as a mediating mechanism explaining how employees' perceived CSR encourages WPB. In addition, studying the moderating effects of other-orientation and self-concern enriches the understanding of when perceived CSR may or may not stimulate employees' WPB.