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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.

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.

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.

The purpose of this paper is to explore domestic experiential travel by Chinese millennials, a group of consumers who will increasingly influence the global travel and tourism industry.

A qualitative research method was adopted to explore motivations and memorable experiences of Chinese millennials who successfully mountain biked the Qinghai–Tibet Highway in China.

For Chinese millennial mountain bikers in Tibet, experiential travel motivations and experiences are important. During the trip, they challenged their mental and physical abilities, enjoyed nature, bonded with friends and perceived a warm welcome by Tibetan families. This study adds to existing knowledge on experiential travel, as it was found that transformation was perceived as important outcome of the trip. Participants perceived personal change in attitude and behaviour, which will help them face everyday life challenges.

Further research could focus on gaining insight into other types of Chinese adventure tourists, on comparing wishes and demands of Chinese with other mountain bikers and on developments in transformative travel.

Adventure tourism organisations could adjust their tourism product range to cater more for Chinese millennials who aim to improve their physical and mental skills.

In-depth research into motivations and experiences of Chinese millennials is scarce. The influence of Chinese millennials on the tourism market is already large and will continue to increase.

This paper aims to discuss financial reporting under economic policy uncertainty.

The paper uses discourse analysis to examine financial reporting under economic policy uncertainty.

The paper identifies the link between economic policy uncertainty and financial reporting, in terms of earnings management and fair value accounting. It argues that high economic policy uncertainty will transmit fewer new information to firms which can motivate managers to influence accounting numbers in the direction of the desired financial reporting outcome.

The relationship between economic policy uncertainty and financial reporting has not been studied. This paper is one of the first papers to relate economic policy uncertainty to financial reporting behavior.

The purpose of this paper is to provide a new approach to solving the interval-valued intuitionistic fuzzy stochastic multi-criteria decision-making (MCDM) problems.

To transform the interval-valued intuitionistic fuzzy number (IVIFN) into a computational numerical value, a new precision score (P-score) function is developed based on the degrees of membership, non-membership and hesitation. The prospect decision-making matrix is derived by applying P-score function and Prospect theory. A new criteria weighting model is put forward based on the least square method, the maximizing deviation method and Prospect theory. Consequently, combined criteria weighting model with the prospect decision-making matrix, the integrated prospect value is derived which presents a measurement scale for ranking the order of alternatives.

As a result, the method of the interval-valued intuitionistic fuzzy stochastic MCDM is suggested. In this method, the new P-score function responses the comprehensive information of the criteria. The prospect decision-making matrix can reflect the risk attitude of the decision maker. The new criteria weighting model can express both the subjective considerations of the decision maker and the objective information meaning.

The research results may lack generalizability for other fuzzy decision making because of the chosen research approach for IVIFN decision making. Therefore, researchers are encouraged to test the proposed propositions further.

The developed approach can be applied in many decision-making fields such as selection of renewable energy alternatives, assessment of flexible manufacturing system alternatives and human resource alternatives performance evaluation, etc. where the evaluation values are IVIFNs.

This paper succeeds in studying the interval-valued intuitionistic fuzzy MCDM based on Prospect theory, which has not been reported in the existing academic literature.