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Following Hovland’s persuasion theory, this paper aims to develop a conceptual model and analyzes characteristics of online political deliberation behavior from three aspects (i.e. information, situation and manager). Based on the whole interactive process of online political deliberation, this paper aims to reveal the key points that affect the response effect of the government from the persuasive perspective of online political consultation.

Based on more than 40,000 netizens’ posts and government responses from 2011 to the first half of 2019 of the Chinese political platform, this paper used the text analysis and machine learning methods to extract measurement variables of online political deliberation characteristics and the econometrics analysis method to conduct empirical research.

The results showed that the textual information, political environment and identity of the political objects affect the effectiveness of government response. Furthermore, for different position categories of political officials, the length of political texts, topic categories and emotional tendencies have different effects on the response effectiveness. Additionally, the effect of political time on the effectiveness of response differs.

The findings will help ascertain the characteristics of online political deliberation behavior that affect how effective government response is and provide a theoretical basis for why the public should express their political concerns.

To better understand Nonaka’s SECI model of knowledge creation and its constraints, we revisit the fundamental points of tacit knowledge in the model and provide a critical review on the role of tacit knowledge in business organization. First, the “tacitness” of knowledge is broken down into two parts: implicitness and real tacitness. We argue that the tacit dimension of knowledge in the context of the model is different from that in Polanyi’s original context; it actually includes considerable “implicitness” idiosyncratic in Japanese context. The separation of implicitness from real tacitness suggests carefully considering the potentialities of “unveiling” the secrets of tacit knowledge in different contexts. Second, considering most cases for the model mainly came from certain Japanese manufacturing companies that more or less relates to assemble lines, it is necessary to be cautious when the model is extended for a broader application.

This study uses migrant household survey data from 2008 to 2009 to examine how parental migration decisions are associated with the nutritional status of children in rural and urban China. Results from instrumental variables regressions show a substantial adverse effect of children’s exposure to parental migration on height-for-age Z scores of left-behind children relative to children who migrate with their parents. Additional results from a standard Blinder–Oaxaca decomposition, a quantile decomposition, and a counterfactual distribution analysis all confirm that children who are left behind in rural villages – usually because of the oppressive hukou system – have poorer nutritional status than children who migrate with their parents, and the gaps are biggest at lower portions of the distribution.

The purpose of this paper is to describe a simulation and experimental research concerning the effect of recess depth on the lubrication performance of a hydrostatic thrust bearing by constant rate flow.

The computational fluid dynamics and finite volume method have been used to compute the lubrication characteristics of an annular recess hydrostatic thrust bearing with different recess depths. The performances are oil recess pressure, oil recess temperature and oil film velocity. The recess depth has been optimized. A test rig is established for testing the pressure field of the structure of hydrostatic thrust bearing after recess depth optimization, and experimental results show that experimental data are basically identical with the simulation results, which demonstrates the validity of the proposed numerical simulation method.

The results demonstrate that the oil film temperature decreases and the oil film pressure first increases and then decreases with an increase in the recess depth, but oil film velocity is constant. To sum up comprehensive lubrication performance, the recess depth of 3.5 mm is its optimal value for the annular recess hydrostatic thrust bearing.

The computed results indicate that to get an improved performance from a constant flow hydrostatic thrust bearing, a proper selection of the recess depth is essential.

In a structural optimization design-based single-level response surface, the number of optimal variables is too much, which not only increases the number of experiment times, but also reduces the fitting accuracy of the response surface. In addition, the uncertainty of the optimal variables and their boundary conditions makes the optimal solution difficult to obtain. The purpose of this paper is to propose a method of fuzzy optimization design-based multi-level response surface to deal with the problem.

The main optimal variables are determined by Monte Carlo simulation, and are classified into four levels according to their sensitivity. The linear membership function and the optimal level cut set method are applied to deal with the uncertainties of optimal variables and their boundary conditions, as well as the non-fuzzy processing is carried out. Based on this, the response surface function of the first-level design variables is established based on the design of experiments. A combinatorial optimization algorithm is developed to compute the optimal solution of the response surface function and bring the optimal solution into the calculation of the next level response surface, and so on. The objective value of the fourth-level response surface is an optimal solution under the optimal design variables combination.

The results show that the proposed method is superior to the traditional method in computational efficiency and accuracy, and improves 50.7 and 5.3 percent, respectively.

Most of the previous work on optimization was based on single-level response surface and single optimization algorithm, without considering the uncertainty of design variables. There are very few studies which discuss the optimization efficiency and accuracy of multiple design variables. This research illustrates the importance of uncertainty factors and hierarchical surrogate models for multi-variable optimization design.

The circular economy (CE) proposes that all materials flow in a close-looped system. Waste generated by one production stage may be useful in another. Thus, the idea of a CE is linked to the goal of zero waste (ZW) and promotes a range of sustainable economic, social and environmental benefits in each sector. When we apply this to construction waste management, waste can be managed through reducing, recycling, upcycling and reusing. However, there is an inevitable cost implication associated with this process due to the additional requirement of inventory and waste processing, and this becomes a disincentive to implementing the CE. Formal institutions, referring here to legal rules and regulations, play a critical role in motivating firms and individuals towards a CE. As different countries have different government rules and regulations, and there is limited research on their differences, we review Asia’s and Europe’s legal rules and regulations relevant to the goal of ZW and CE in the construction sector.

Considering the industrial site environment and installation requirements, the straight-beam ultrasound probe with easy installation and good coupling agent adaptability is adopted to replace the traditional water immersion focusing probe for film thickness measurement in cylindrical roller bearings. The straight-beam probe has a large echo receiving range, which will result in measurement regions overlapping and bring about large measurement errors. In this paper, an improved measurement method for film thickness of cylindrical roller bearing with the straight-beam probe is developed.

An improved method is proposed to enhance the spatial resolution of the straight-beam probe. By introducing a correction coefficient based on the percentage of the effective measurement area, the method improves the measuring accuracy successfully.

The experimental results demonstrate that the lubricant-film thickness can be measured to reasonable accuracy by this method and have a better agreement with the theoretical film thickness solutions.

This paper used analytical method and model that is helpful for the improvement of the spatial resolution, which has great influence on the measuring accuracy, is mainly determined by the echo reflection area size of the ultrasound transducer.

This study conducts a comparative study on the performance of reliability assessment methods based on adaptive surrogate models to accurately assess the reliability of automobile components, which is critical to the safe operation of vehicles.

In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components.

By comparing the reliability evaluation problems of four automobile components, the Kriging model and Polynomial Chaos-Kriging (PCK) have better robustness. Considering the trade-off between accuracy and efficiency, PCK is optimal. The Constrained Min-Max (CMM) learning function only depends on sample information, so it is suitable for most surrogate models. In the four calculation examples, the performance of the combination of CMM and PCK is relatively good. Thus, it is recommended for reliability evaluation problems of automobile components.

Although a lot of research has been conducted on adaptive surrogate-model-based reliability evaluation method, there are still relatively few studies on the comprehensive application of this method to the reliability evaluation of automobile component. In this study, different adaptive learning strategies and surrogate models are combined to study their performance in reliability assessment of automobile components. Specially, a superior surrogate-model-based reliability evaluation method combination is illustrated in this study, which is instructive for adaptive surrogate-model-based reliability analysis in the reliability evaluation problem of automobile components.

This study aims to clarify the evolution law of stress field and fracture field during the mining process of inclined coal seam, to prevent the occurrence of roof burst water and impact ground pressure accident during the advancing process of working face.

The evolution law of stress-fracture field under different mining conditions of inclined coal seam was studied by using discrete element method and similar material simulation method.

The overburden stress at the lower end of the coal seam was mainly transmitted to the deep rock mass on the left side, and the overburden stress at the upper end was mainly transmitted to the floor direction. With the increase of the inclined length of the mining coal seam, the development of the fracture zone gradually evolves from the “irregular arch” form to the “transversely developed trapezoid” form. The development range of the fracture zone was always in the internal area of the stress concentration shell.

An original element of this paper is based on the condition that the dip angle of coal seam is 35°, and the evolution law of overburden stress-fracture field during the excavation of coal seam with different lengths was analyzed by UDEC numerical simulation software. The coupling relationship between stress shell and fracture field was proposed, and the development range of fracture zone was determined by stress. The value of this paper is to provide technical support and practical basis for the safety production of a mine working face.

Currently, engineering project design lacks a design framework that fully combines subjective experience and objective data. This study develops an aided design decision-making framework to automatically output the optimal design alternative for engineering projects in a more efficient and objective mode, which synthesizes the design experience.

A database of design components is first constructed to facilitate the retrieval of data and the design alternative screening algorithm is proposed to automatically select all feasible design alternatives. Then back propagation (BP) neural network algorithm is introduced to predict the cost of all feasible design alternatives. Based on the gray relational degree-particle swarm optimization (GRD-PSO) algorithm, the optimal design alternative can be selected considering multiple objectives.

The case study shows that the BP neural network-cost prediction algorithm can well predict the cost of design alternatives, and the framework can be widely used at the design stage of most engineering projects. Design components with low sensitivity to design objectives have been obtained, allowing for the consideration of disregarding their impacts on design objectives in such situations requiring rapid decisions. Meanwhile, design components with high sensitivity to design objective weights have also been obtained, drawing special attention to the effects of changes in the importance of design objectives on the selection of these components. Simultaneously, the framework can be flexibly adjusted to different design objectives and identify key design components, providing decision reference for designers.

The framework proposed in this paper contributes to the knowledge of design decision-making by emphasizing the importance of combining objective data and subjective experience, whose significance is ignored in the existing literature.