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This study aims to develop an improved understanding of the formation of citizens' purchase intention to increase the adoption of prefabricated housing (PH).

An integrative model of the theory of planned behavior (TPB) and norm activation model (NAM) was proposed based on previous studies. To verify the conceptual model, an analysis was conducted after data collection from a questionnaire survey. Lastly, findings were presented by explaining the formation of purchase intention in the egoistic and altruistic contexts. Practical implications were likewise discussed.

Findings manifest that citizens' purchase intention is influenced by egoistic and altruistic cognitions. An effective strategy is to show citizens the pro-environmental features of PH to promote its adoption because they value the environmental performance of housing. Meanwhile, consumers' social fitness also plays an essential role in decision-making, and the dual contradiction in the PH market is revealed.

This study extends the knowledge of psychological decision-making theories in the field of purchase intention toward PH by proposing an integrative framework of TPB and NAM. Results indicate a systematic and comprehensive understanding of consumers' decision-making in the PH domain. Moreover, results of this research contribute to specifying and refining the applicable contexts of TPB and NAM by adding two antecedents: subjective knowledge and environmental concern. This research contributes to the literature by being one of the first to investigate purchase intention toward a high-cost product with invisible technological innovation.

This study explores citizens’ acceptance of prefabricated housing (PH) from the perspective of socio-demographic and psychological factors, aiming to reveal the formation of PH acceptance and realize a sustainable development of PH.

This study proposed hypotheses drawing on procedural justice theory and uncertainty management theory. A survey of 245 respondents was conducted, and the collected data was analyzed in a stepwise multiple regression model. Then, the psychological influencing mechanism was demonstrated using a mediation model.

Results of the data analysis manifested that citizens’ acceptance of PH was influenced by socio-demographic and psychological factors, where psychological factors had more significant effects on acceptance than socio-demographic factors. The psychological mechanism was examined by verifying the mediating role of uncertainty between procedural justice and the acceptance of PH. Furthermore, a scientific strategy for developing PH was proposed based on this empirical study.

This study extends the knowledge of procedural justice theory by investigating people’s acceptance in the PH context. This study is also one of the first studies to unveil the psychological mechanism toward a high-cost product with invisible technological innovation. This study contributes to the literature by introducing uncertainty management theory to a controversial issue, examining and expanding its application in a complicated context. Moreover, results highlight the positive influence of fair processes on controversial issues.

The importance of sustainable public procurement is growing in many countries and industries, including higher education institutions (HEIs) in China. However, in China, the practice of sustainable public procurement is currently limited due to various reasons. This study aims to identify the main challenges faced by Chinese HEIs when it comes to sustainable public procurement. The identification of the challenges encountered by HEIs in sustainable public procurement practices not only has practical significance in terms of improving efficiency, sustainability, competitiveness and guiding policymaking but also has theoretical significance in terms of enriching the knowledge body, facilitating the dissemination of sustainability and supporting international comparative research. To identify these challenges, the study gathered data from a small sample of procurement supervisors, experts and commissioners in HEIs using the Delphi method. The study concludes that Chinese HEIs can address the challenges of sustainable public procurement through measures such as fundraising, technology and equipment upgrading, supply chain optimization, regulatory compliance and raising awareness and providing training.

To pinpoint the challenges of sustainable public procurement faced by HEIs in China, this study began by obtaining data from a small sample of procurement supervisors, experts and commissioners in HEIs who are knowledgeable about the issue through the Delphi method. Secondly, the collected challenge factors were also subjected to a literature review to identify the most common challenges in recent papers published around the world. Thus, it was possible to assess the relationship between the challenges mentioned by researchers in China and other countries.

The main challenges faced by HEIs in China in implementing sustainable public procurement are the focus on economic efficiency, the experience and awareness of procurement staff, policy ambiguity as well as culture, management mechanisms and leadership attitudes in the organizations. The study concludes that Chinese HEIs can effectively overcome the challenges of implementing sustainable public procurement through a variety of measures, including fundraising, technology and equipment upgrading, supply chain optimization, regulatory compliance and awareness raising and training.

Some limitations should be considered in this study. Judging by the sample size, it is clear that the results of the study are limited. Although the number of experts involved in the study is required, caution should be exercised when generalizing the results, as this may not be representative of the entire population. In future studies, the use of a larger sample size could be considered to overcome this problem. Related to this limitation is the uneven geographical distribution of the sample, and this study only considered the situation of HEIs in Jiangsu Province, China, which is not representative of the national region.

The practical significance can be seen in two aspects. First, accurately identifying challenges can help HEIs optimize the implementation of their sustainable purchasing policies, leading to more efficient resource allocation and reduced unnecessary resource consumption. Second, by addressing these challenges, HEIs can better fulfill their social role in sustainable development, contributing to the triple bottom line of the economy, environment and society. Implementing sustainable procurement strategies not only enhances the social image of HEIs but also attracts a broader student base and financial support, ultimately improving their competitive position in the education market. A deeper understanding of these challenges provides policymakers with a basis to develop a more operational and targeted policy framework to support sustainable procurement in HEIs.

This study succeeded in answering two research questions that provide practical implications for public procurement practitioners, researchers and policymakers. Although HEIs in China do not practice sustainable public procurement at a high rate, however, with the spread of sustainability and environmental awareness, more and more HEIs are beginning to realize the importance of sustainability and are gradually taking it into account in their procurement.

The findings of the study not only significantly enrich the existing body of knowledge on sustainable public procurement, but also support the selection of challenge variables that must be addressed first to facilitate the application of sustainable procurement in China’s HEIs.

The smoothness of the high-speed railway (HSR) on the bridge may exceed the allowable standard when an earthquake causes vibrations for HSR bridges, which may threaten the safety of running trains. Indeed, few studies have evaluated the exceeding probability of rail displacement exceeding the allowable standard. The purposes of this article are to provide a method for investigating the exceeding probability of the rail displacement of HSRs under seismic excitation and to calculate the exceeding probability.

In order to investigate the exceeding probability of the rail displacement under different seismic excitations, the workflow of analyzing the smoothness of the rail based on incremental dynamic analysis (IDA) is proposed, and the intensity measure and limit state for the exceeding probability analysis of HSRs are defined. Then a finite element model (FEM) of an assumed HSR track-bridge system is constructed, which comprises a five-span simply-supported girder bridge supporting a finite length CRTS II ballastless track. Under different seismic excitations, the seismic displacement response of the rail is calculated; the character of the rail displacement is analyzed; and the exceeding probability of the rail vertical displacement exceeding the allowable standard (2mm) is investigated.

The results show that: (1) The bridge-abutment joint position may form a step-like under seismic excitation, threatening the running safety of high-speed trains under seismic excitations, and the rail displacements at mid-span positions are bigger than that at other positions on the bridge. (2) The exceeding probability of rail displacement is up to about 44% when PGA = 0.01g, which is the level-five risk probability and can be described as 'very likely to happen'. (3) The exceeding probability of the rail at the mid-span positions is bigger than that above other positions of the bridge, and the mid-span positions of the track-bridge system above the bridge may be the most hazardous area for the running safety of trains under seismic excitation when high-speed trains run on bridges.

The work extends the seismic hazardous analysis of HSRs and would lead to a better understanding of the exceeding probability for the rail of HSRs under seismic excitations and better references for the alert of the HSR operation.

Reactive dyes are believed to have great potential for nylon dyeing, but these anionic dyes tend to rush toward the nylon at the beginning of the process, resulting in uneven dyeing. Achieving uniformity gets even harder when the dyeing is performed under exposure to eco-friendly technique microwave irradiations. This study aims to achieve rapid and homogenous results by intermittent shaking and non-continuous exposure to microwave.

A set of reactive red dyes, based on the same chromophore and different substituents in the auxochrome part, was applied to the nylon fabric without any leveling agent. A series of experiments were designed to investigate the effect of different dye structures, exhaustion pH, liquor ratio, exhaustion time and fixation time to obtain an optimum recipe under the microwave dyeing technique.

Dyeing performance was characterized based on the color strength, exhaustion and fixation percentages and color fastness values. The characterization showed that better results can be achieved at a liquor ratio of 1:15 at exhaustion pH 2.7 which is also the isoelectric point of nylon, with 5.5 to 7 min of exhaustion and 6 to 8 min of fixation time for different dyes. Microwave dyed samples secured higher color strength values and provided better exhaustion and fixation than the conventional dye samples. Furthermore, the X-ray diffraction results verified that there was no considerable difference in the morphological structure of nylon with microwave exposure.

An applied technique is disclosed in this work to achieve uniform dyeing on nylon 66 with reactive dyes without any leveling agent under exposure to eco-friendly rapid heating microwave irradiations.

The aim of this paper is to enhance the control performance of dexterous hands, enabling them to handle the high data flow from multiple sensors and to meet the deployment requirements of deep learning methods on dexterous hands.

A distributed control architecture was designed, comprising embedded motion control subsystems and a host control subsystem built on ROS. The design of embedded controller state machines and clock synchronization algorithms ensured the stable operation of the entire distributed control system.

Experiments demonstrate that the entire system can operate stably at 1KHz. Additionally, the host can accomplish learning-based estimates of contact position and force.

This distributed architecture provides foundational support for the large-scale application of machine learning algorithms on dexterous hands. Dexterity hands utilizing this architecture can be easily integrated with robotic arms.

This study aims to examine the impact of logistics and merchant certification information on consumer behaviour in hybrid retail platforms. Furthermore, it explores the moderating role of online shopping experience on the certification effect.

The authors utilize transaction-level data from over 2.5 million consumers involving 30,000 stock keeping units (SKUs) on JD.com in March 2018. They analyse the impact of different types of certification information on consumer behaviour using ordinary linear regression and linear probability models.

The findings reveal that, compared with information without certification, (1) single logistics certification information can enhance consumers' search depth and purchase intention; (2) dual logistics and merchant certification information also has a positive impact on consumer behaviour; and (3) single certification information is more effective for inexperienced consumers, while dual certification is more effective for experienced consumers.

Theoretically, this study contributes to the literature on certification information in hybrid retail platforms and broadens information communication methods for online shopping. Our discovery is meaningful for managers in locating customers and allocating resources. In addition, we encourage online retailers to utilize certification information to engage consumer.

The purpose of this study is to extract the response of the simultaneous low-velocity impact of multiple impactors on a porous functionally graded (FG) aluminum plate.

To design a porous FG structure, a series of functions are applied using the porosity coefficient, and mechanical properties including Young’s modulus, shear modulus and the density of the porous structure are presented as a function of the axis placed in the direction of the plate thickness. The first-order shear deformation theory of the plate is used. To simulate the contact process between each impactor and the plate, a nonlinear Hertz contact force is considered for that impactor independently.

ABAQUS finite element software is used for the verification process of the theorical equations. The effects of porous function type, radius and initial velocity of impactor are investigated for the simultaneous impact of five impactors on porous FG aluminum plate with a simply supported boundary condition. Histories of contact force and displacement of the impactor placed in the center of the beam are analyzed in detail with the changes of the mentioned parameters.

Due to the advantages of porous aluminum plate such as high energy absorption and low weight, such structures may be subjected to the simultaneous impact of multiple impactors, which is studied in this research.

The multi-objective optimization configuration strategy is proposed due to the configuration of EMAs in fault-tolerant control of active magnetic bearing with redundant electromagnetic actuators involving high-dimensional, nonlinear, conflicting goals.

A multi-objective optimization model for bias current coefficients is established based on the nonlinear model of active magnetic bearings with redundant electromagnetic actuators. Based on the non-dominated sorting genetic algorithm III, a numerical method is used to obtain feasible and non-inferior sets for the bias current coefficient.

(1) The conflicting relationship among the three optimization objectives was analyzed for various failure modes of EAMs. (2) For different EMAs' failure modes, the multi-objective optimization configuration strategy can simultaneously achieve the optimal or sub-optimal effective EMF, flux margins, and stability of EMF. Moreover, the characteristics of the optimal Pareto front are consistent with the physical properties of the AMB. (3) Compared with the feasible configuration of C0, the non-inferior configurations can significantly improve the performance of AMB, and the advantages of the multi-objective optimization configuration strategy become more prominent as the asymmetry of the residual supporting structure intensifies.

i) Considering the variation of the rotor displacement during the support reconstruction, a decision-making model that can accurately characterize the dynamic performance of AMB is presented. (ii) The interaction law between AMB and rotor under different failure modes of EMAs is analyzed, and the configuration principles for redundant EMAs are proposed. (iii) Based on the dynamic characteristics of AMB during the support reconstruction, effective EMF, energy consumption, and the Pearson correlation coefficient between the desired EMFs and the decoupled control currents are used as objective functions. iv. The NSGA-III is combined with the decision-making model to address the multi-objective optimization configuration problem of C0.

This study aims to tackle control challenges in soft robots by proposing a visually-guided reinforcement learning approach. Precise tip trajectory tracking is achieved for a soft arm manipulator.

A closed-loop control strategy uses deep learning-powered perception and model-free reinforcement learning. Visual feedback detects the arm’s tip while efficient policy search is conducted via interactive sample collection.

Physical experiments demonstrate a soft arm successfully transporting objects by learning coordinated actuation policies guided by visual observations, without analytical models.

Constraints potentially include simulator gaps and dynamical variations. Future work will focus on enhancing adaptation capabilities.

By eliminating assumptions on precise analytical models or instrumentation requirements, the proposed data-driven framework offers a practical solution for real-world control challenges in soft systems.

This research provides an effective methodology integrating robust machine perception and learning for intelligent autonomous control of soft robots with complex morphologies.