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The purpose of this paper is to explore the effect of the feeling awe on individuals' endorsement of conformist attitudes in consumption choices and the mediating role of social connectedness in generating this effect.

We test our hypotheses across three studies. Study 1 used an online survey. Study 2 and 3 conducted two laboratory experiments to induce awe and measured consumer conformity in two consumption choice tasks.

This research shows that both dispositional awe and induced awe can increase individuals' preferences for majority-endorsed vs. minority-endorsed choice alternatives in subsequently unrelated consumption situations, and this effect is mediated by perceptions of social connectedness with other decision-makers.

Marketers can promote the sales of mass-market products through inducing awe.

Public regulators could utilize people's incidental awe as an effective policy intervention to nudge individual cooperation in some cases.

The research is the first to demonstrate a novel consequence of awe on consumer decision-making. It also highlights the significance of desire for social connectedness that explains why the feeling of awe develops conformity to the opinions of unknown people.

This paper aims to solve the problem of public resource allocation among vulnerable groups by proposing a new method called uncertain α-coordination value based on uncertain cooperative game.

First, explicit forms of uncertain Shapley value with Chouqet integral form and uncertain centre-of-gravity of imputation-set (CIS) value are defined separately on the basis of uncertainty theory and cooperative game. Then, a convex combination of the two values above called the uncertain α-coordination value is used as the best solution. This study proves that the proposed methods meet the basic properties of cooperative game.

The uncertain α-coordination value is used to solve a public medical resource allocation problem in fuzzy coalitions and uncertain payoffs. Compared with other methods, the α-coordination value can solve such problem effectively because it balances the worries of vulnerable group’s further development and group fairness.

In this paper, an extension of classical cooperative game called uncertain cooperative game is proposed, in which players choose any level of participation in a game and relate uncertainty with the value of the game. A new function called uncertain α-Coordination value is proposed to allocate public resources amongst vulnerable groups in an uncertain environment, a topic that has not been explored yet. The definitions of uncertain Shapley value with Choquet integral form and uncertain CIS value are proposed separately to establish uncertain α-Coordination value.

Soft robotics is a burgeoning field owing to its high adaptability and safety in human–machine interaction and unstructured environments. However, the feedback control of soft actuators with flexible sensors is still a challenge.

To address this issue, this study proposes an optical fibre-based sensing membrane for the posture measurement of soft pneumatic bending actuators. The major contribution is the development of a flexible sensing membrane with a high sensitivity and repeatability for the feedback control of soft actuators. The characteristics of sensing membrane were analysed. The relationship between wavelength shift and bending curvature was derived. The curvatures of soft actuator were measured at four bending status, and the postures were reconstructed.

The results indicate that the measurement error is less than 2.1% of the actual bending curvature. The sensitivity is up to 212.8 pm/m⁻¹, and the signal fluctuation in repeated measurements is negligible. This approach has broad application prospects in soft robotics, because it makes the optical fibre achieve more strength and compatible with soft actuators, thus improving the sensing accuracy, sensitivity and reliability of fibre sensors.

Different from previous approaches, an optical fibre with FBGs is embedded into a multilayered polyimide film to form a flexible sensing membrane, and the membrane is embedded into a soft pneumatic bending actuator as the smart strain limited layer which is able to measure the posture in real time. This approach makes the optical fibre stronger and compatible with the soft pneumatic bending actuator, and the sensing accuracy, sensitivity and reliability are improved. The proposed sensing configuration is effective for the feedback control of the soft pneumatic bending actuators.

The purpose of this paper is to improve the performance of the genetic algorithm-based compliant robot path planning (GACRPP) in complex dynamic environment by proposing an improved bidirectional rapidly exploring random tree (Bi-RRT)-based population initialization method.

To achieve GACRPP in complex dynamic environment with high performance, an improved Bi-RRT-based population initialization method is proposed. First, the grid model is adopted to preprocess the working space of mobile robot. Second, an improved Bi-RRT is proposed to create multi-cluster connections between the starting point and the goal point. Third, the backtracking method is used to generate the initial population based on the multi-cluster connections generated by the improved Bi-RRT. Subsequently, some comparative experiments are implemented where the performances of the improved Bi-RRT-based population initialization method are compared with other population initialization methods, and the comparison results of the improved genetic algorithm (IGA) combining with the different population initialization methods are shown. Finally, the optimal path is further smoothed with the help of the technique of quadratic B-spline curves.

It is shown in the experiment results that the improved Bi-RRT-based population initialization method is capable of deriving a more diversified initial population with less execution time and the IGA combining with the proposed population initialization method outperforms the one with other population initialization methods in terms of the length of optimal path and the execution time.

In this paper, the Bi-RRT is introduced as a population initialization method into the GACRPP problem. An improved Bi-RRT is proposed for the purpose of increasing the diversity of initial population. To characterize the diversity of initial population, a new notion of breadth is defined in terms of Hausdorff distance between different paths.

During running-in, the change in the honed cylinder liner surface alters the performance and efficiency of the piston ring-pack system. The present paper, thus, aims to investigate the surface topography and wear and friction evolution of a cylinder liner surface during the running-in tests on a reciprocating ring–liner tribometer under a mixed lubrication regime. After an initial period of rapid wear termed “running-in wear”, a relatively long-term steady-state surface topography can emerge. A numerical model is developed to predict the frictional performance of a piston ring-pack system at the initial and steady-state stages.

The liner surfaces are produced by slide honing (SH) and plateau honing (PH). The bearing area parameter (Rk family), commonly used in the automotive industry, is used to quantitatively characterize the surface topography change during the running-in process. A wear volume-sensitive surface roughness parameter, Rktot, is used to show the wear evolution.

The experimental results show that a slide-honed surface leads to reduced wear, and it reduces the costly running-in period compared to the plateau-honed surface. The simulation results show that running-in is a beneficial wear process that leads to a reduced friction mean effective pressure at the steady-state.

To simulate the mixed lubrication performance of a ring–liner system with non-Gaussian roughness, a one-dimensional homogenized mixed lubrication model was established. The real surface topography instead of its statistical properties is taken into account.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

Land value varies at a micro level depending on the location’s economic, geographical and political determinants. The purpose of this study is to present a comprehensive assessment of the determinants affecting land value in the Indian city of Thiruvananthapuram in the state of Kerala.

The global influence of the identified 20 explanatory variables on land value is measured using the traditional hedonic price modeling approach. The localized spatial variations of the influencing parameters are examined using the non-parametric regression method, geographically weighted regression. This study used advertised land value prices collected from Web sources and screened through field surveys.

Global regression results indicate that access to transportation facilities, commercial establishments, crime sources, wetland classification and disaster history has the strongest influence on land value in the study area. Local regression results demonstrate that the factors influencing land value are not stationary in the study area. Most variables have a different influence in Kazhakootam and the residential areas than in the central business district region.

This study confirms findings from previous studies and provides additional evidence in the spatial dynamics of land value creation. It is to be noted that advanced modeling approaches used in the research have not received much attention in Indian property valuation studies. The outcomes of this study have important implications for the property value fixation of urban Kerala. The regional variation of land value within an urban agglomeration shows the need for a localized method for land value calculation.

This study aims to present a new haptic-enabled virtual assembly system for the automatic generation and objective assessment of assembly plans. The system is intended to be used as an assembly planning tool along the product development process.

The generation of product assembly plans is based on the analysis of the assembly movements and operations performed by the user during the virtual assembly execution, and the objective assessment of product assembly is based on the definition and computation of new proposed assembly metrics.

To evaluate the system, a case study corresponding to the assembly of a mechanical component is presented and analyzed. The results demonstrate that the proposed system is an effective tool to plan and evaluate different product assembly strategies in a more practical and objective approach than existing assembly planning methods.

Although the virtual assembly execution time is larger than the real assembly execution time, the assembly planning and evaluation results provided by the system are valid. However, the development of higher performance collision detection algorithms is needed to reduce the simulation time.

The proposed virtual assembly system is able to not only simulate and automatically generate assembly plans but also objectively assess them from the virtual assembly task execution. The introduction and use of several assembly performance metrics to objectively evaluate assembly strategies in virtual assembly also represents a novel contribution.

Thermal behavior of light-emitting diode (LED) device under different operating conditions must be known to enhance its reliability and efficiency in various applications. The purpose of this study is to report the influence of input current and ambient temperature on thermal resistance of InGaAlP low-power surface-mount device (SMD) LED.

Thermal parameters of the LED were measured using thermal transient measurement via Thermal Transient Tester (T3Ster). The experimental results were validated using computational fluid dynamics (CFD) software.

As input current increases from 50 to 90 mA at 25°C, the relative increase in LED package (ΔR_thJS) and total thermal resistance (ΔR_thJA) is about 10 and 4 per cent, respectively. In addition, at 50 mA and ambient temperature from 25 to 65°C, the ΔR_thJS and ΔR_thJA are roughly 28 and 22 per cent, respectively. A good agreement between simulation and experiment results of junction temperature.

Most of previous studies have focused on thermal management of high-power LEDs. There were no studies on thermal analysis of low-power SMD LED so far. This work will help in predicting the thermal performance of low-power LEDs in solid-state lighting applications.

The purpose of this study is to explore the factors influencing customers’ revisit intentions of green hotels after the COVID-19 pandemic.

The study is based on the existing literatures and interviews of 404 respondents visiting hotels after the pandemic. The partial least square structural equation modeling is used to analyze the data.

The findings show that green attitude, green personality and personal norms significantly influence post-COVID-19 green hotel revisit intentions.

The findings of the study may be useful to hotel operators in formulating focused business strategies improving customers’ green hotel revisit intentions and coping with the new normal business environment of the hospitality industry.

The study presents a unique case highlighting how the hospitality business is changing after the COVID-19 pandemic. The study provides important insights for industry operators by integrating attitudes, personality and norms of the customers in examining the green hotels revisit intentions.