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The purposes of this paper are to find out the correlations between the changes of food companies’ environments and the strategic reactions of food companies after the media disclosed that there were food safety incidents out there in the food markets.

This paper uses a randomly sampling survey of 139 food enterprises in China. After statistical significance and statistical power were examined, canonical correlation analysis was used as the main data analysis technique of this research.

Based on the environment-strategy paradigm, the authors found that the changes of the competition environment, resource environment, and institution environment in the food industry have significant association with food companies’ strategic reactions such as public relations, networking with firms and futurity after food safety incidents in the food market were disclosed.

The paper is the first to quantitatively examine the relationships between the changes of food companies’ environments and the strategic reactions of food companies after the media disclosed that there were food safety incidents in the food markets. The findings of this paper send novel and important messages to government decision makers and the public, evidencing how food companies strategically respond to external environmental changes, and suggesting that the institution-builder as well as the media have more work to do in the aftermath of food safety incidents.

The persistence and virality of conspiracy theories online have raised significant concerns. This study revisits Rogers’ Diffusion of Innovations theory to examine the spread of conspiracy theories on social media, specifically focusing on how factors influencing their diffusion evolve over time.

The study analyzes over 1.18 million COVID-19-related tweets using a combination of natural language processing, social network analysis and machine learning techniques. It explores the dynamic roles of novelty, content negativity, influencers, echo chamber members and social bots in the diffusion of conspiracy theories.

The results indicate that novelty, influencers, echo chamber members and social bots are positively associated with the spread of conspiracy theories. The initial dissemination of conspiracy theories is primarily driven by content novelty and influencer involvement. Over time, the perpetuation of these theories becomes increasingly influenced by content negativity and the involvement of echo chamber members and social bots. Social bots serve as important connectors within echo chambers and their removal significantly reduces network cohesion.

The findings provide practical guidance for social media platforms and policymakers in monitoring diffusion patterns and applying targeted interventions.

This study introduces a time-sensitive approach to understanding the spread of conspiracy theories on social media. By identifying the key drivers at different stages of the diffusion process, this study offers valuable insights for developing effective strategies to counteract the proliferation of conspiracy theories at various points in their lifecycle.

The CL60 steel wheels of subway vehicles operating on specific lines require frequent refurbishment due to rapid wear and tear. Considering this issue, MoS₂-based and graphite-based solid lubricants are used to reduce the wear rate of subway wheels and extend their service life.

Under laboratory conditions, the effect of MoS₂-based and graphite-based solid lubricants on the friction and wear performance of subway wheels and rails was evaluated using a modified GPM-60 wear testing machine.

Under laboratory conditions, MoS₂-based solid lubricants have the best effect in reducing wheel/rail wear, compared to the control group without lubrication, at 2 × 105 revolutions, the total wheel-rail wear decreased by 95.07%. However, when three types of solid lubricants are used separately, the hardness evolution of the wheel-rail contact surface exhibits different characteristics.

The research results provide important support for improving the lifespan of wheel and rail, extending the service cycle of wheel and rail, reducing the operating costs of subway systems, improving the safety of subway systems and providing wear reduction maintenance for other high wear mechanical components.

The experiment was conducted through the design and modification of a GPM-60 testing machine for wear testing. The experiment simulated the wheel-rail contact situation under actual subway operation and evaluated the effects of three different solid lubricants, MoS₂-based and graphite-based, on the wear performance and surface hardening evolution of subway wheel-rail.

Based on the survey data of 1,152 households in three provinces of Shaanxi, Gansu and Ningxia on the Loess Plateau, this paper aims to empirically analyze the impact of aging and off-farm employment on farmers’ adoption behavior of soil and water conservation technology. This paper analyzes the moderating effect of social network and the mediating effect of technological cognition in this impact relationship.

Based on the above analysis, the second part of this paper is based on relevant theories and constructs a theoretical model of the relationship of aging, off-farm employment, social network, technology cognition and farmers’ adoption behavior of soil and water conservation technology. The third part introduces research methods, variable selection and descriptive statistics analysis of variables. The fourth part, based on the data of Shaanxi, Gansu and Ningxia provinces in the Loess Plateau in 2016, empirically analyzes the impact of aging, off-farm employment and social network on the farmers’ adoption behavior of soil and water conservation technology. This paper further examines the moderating effect of social network and the mediating effect of technology cognition in this influence relationship. Finally, based on the findings of the empirical study, this paper puts forward countermeasures and suggestions.

First, aging and off-farm employment have a significant negative impact on farmers’ adoption behavior of soil and water conservation technology, while social network has a significant positive effect. Second, social network has alleviated the effect of aging and off-farm employment on restraining farmers’ adoption behavior of soil and water conservation technology. Third, aging and off-farm employment have restrained farmers’ cognition of soil and water conservation technology. Social network has promoted farmers’ cognition of soil and water conservation technology. Social network plays a moderating role in the impact of aging and off-farm employment on farmers’ cognition of soil and water conservation technology. Technology cognition plays a mediating role in the impact of social network on farmers’ adoption behavior of soil and water conservation technology.

This paper integrates the aging, off-farm employment and social network into the same analytical framework and reveals their impact on farmers’ adoption behavior of soil and water conservation technology and its action mechanism, which enriches the impact of human capital and social network on farmers’ adoption behavior of soil and water conservation technology. Then taking the social network as a moderator variable, the paper verifies its moderating effect on the relationship of aging, off-farm employment and farmers’ adoption behavior of soil and water conservation technology. Farmers’ technology cognition should be included in the analysis framework to examine the impact of aging, off-farm employment and social network on farmers’ cognition of soil and water conservation technology. Taking the technology cognition as a mediator variable, the paper verifies its mediating effect on the relationship of aging, off-farm employment and farmers’ adoption behavior of soil and water conservation technology.

This study aims to offer a comprehensive exploration of the potential and challenges associated with sensor fusion-based virtual reality (VR) applications in the context of enhanced physical training. The main objective is to identify key advancements in sensor fusion technology, evaluate its application in VR systems and understand its impact on physical training.

The research initiates by providing context to the physical training environment in today’s technology-driven world, followed by an in-depth overview of VR. This overview includes a concise discussion on the advancements in sensor fusion technology and its application in VR systems for physical training. A systematic review of literature then follows, examining VR’s application in various facets of physical training: from exercise, skill development and technique enhancement to injury prevention, rehabilitation and psychological preparation.

Sensor fusion-based VR presents tangible advantages in the sphere of physical training, offering immersive experiences that could redefine traditional training methodologies. While the advantages are evident in domains such as exercise optimization, skill acquisition and mental preparation, challenges persist. The current research suggests there is a need for further studies to address these limitations to fully harness VR’s potential in physical training.

The integration of sensor fusion technology with VR in the domain of physical training remains a rapidly evolving field. Highlighting the advancements and challenges, this review makes a significant contribution by addressing gaps in knowledge and offering directions for future research.

The purpose of this study was to investigate the microstructural evolution and hydrolytic stability of poly(phenylborosiloxane) (PPhBS) to further use and develop the oligomers as heat-resistant modifiers.

PPhBS was synthesized by direct co-condensation of boric acid (BA) and phenyltriethoxysilane (PTEOS). The structural evolution of PPhBS at high temperature was investigated by Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), differential thermal analysis (DTA), in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) and 29Si nuclear magnetic resonance (NMR) spectroscopy. In addition, the change in the morphology of the PPhBS powder was examined to demonstrate the evolution of the chemical bonds, and the hydrolytic stability of PPhBS was investigated by a combination of X-ray diffraction (XRD) analysis, measurement of the mass loss in water and FTIR spectroscopy.

The results revealed that a cross-linking network was gradually formed with increasing temperature through the condensation of the residual hydroxyl groups in PPhBS, and the Si-OH and B-OH bonds remained even at a high temperature of 450°C. Furthermore, heat treatment improved the hydrolytic stability of the oligomer. The hydrolysis of the B-O-B bonds in PPhBS was reversible, whereas the Si-O-Si and Si-O-B bonds were highly resistant to hydrolysis.

The prepared PPhBS can be used as a heat-resistant modifier in adhesives, sealants, coatings and composite matrices.

Investigation of the structural evolution of a polyborosiloxane at high temperature by DRIFTS is a novel approach that avoided interference from moisture in the air. The insoluble mass fraction and the FTIR spectrum of PPhBS washed with water were used to investigate the hydrolytic stability of PPhBS.

The purpose of this paper is to present the sensing mechanism, design issues, performance evaluation and applications for planar capacitive sensors. In the context of characterisation and imaging of a dielectric material under test (MUT), a systematic study of sensor modelling, features and design issues is needed. In addition, the influencing factors on sensitivity distribution, and the effect of conductivity on sensor performance need to be further studied for planar capacitive sensors.

While analytical methods can provide accurate solutions to sensors of simple geometries, numerical modelling is preferred to obtain sensor response to different design parameters and properties of MUT, and to derive the sensitivity distributions of various electrode designs. Several important parameters have been used to evaluate the response of the sensors in different sensing modes. The designs of different planar capacitive sensor arrays are presented and experimentally evaluated.

The response features and design guidelines for planar capacitive sensors in different sensing modes have been summarised, showing that the sensor in the transmission mode or the single‐electrode mode is suitable for material characterisation and imaging, while the sensor in the shunt mode is suitable for proximity/displacement measurement. The sensitivity distribution of the sensor depends largely on the geometry of the electrodes. Conductivity causes positive changes for the sensor in the transmission and single‐electrode mode, but negative changes for the sensor in the shunt mode. Experimental results confirm that sensing depths of the sensor arrays and the influence of buried conductor on capacitance measurements are in agreement with simulations.

Experimental verification is needed when a sensor is designed.

This paper provides a comprehensive study for planar capacitive sensors in terms of sensor design, evaluation and applications.

The purpose of this paper is to develop a novel interval Multi-Objective Optimization by a Ratio Analysis plus the Full Multiplicative Form(MULTIMOORA) with combination weights to evaluate the employment quality of college graduates, where the criteria are expressed by interval numbers and the weights of criteria are completely unknown.

Firstly, considering the subjective uncertainty of the weights of the criteria, the interval best worst method (I-BWM) was present to determine the subjective weights of the criteria. Secondly, by the improved interval number distance measure, an improved interval deviation maximization method (I-MDM) was introduced to detemine the objective weights. In the following, based on the I-BWM and the improved I-MDM, a combination weighting method that takes into account the subjective and objective weights is proposed. Finally, a multi-criteria decision-making method based on the interval MULTIMOORA with combination weights is present to evaluate the employment quality of college graduates, and then a comparative analysis with some of the existing distance measures of interval numberswas conducted to illustrate the flexibility.

According to the data of the Report on Employment Quality of Chinese College Graduats released by Mycos Research Institute in 2016–2020 and 2021–2022, the proposed method was used to evaluate the employment quality of college graduates during the period before and after the COVID-19 epidemic. The results verify that the method is more reasonable because the subjective and objective weights of the criteria can be fully considered. Finally, the feasibility and practicability of the proposed method are further verified by varying parameters.

Present an evaluation method on the employment quality of college graduates based on the Interval MULTIMOORA with combination weights considering the subjective and objective weights. And the proposed method is proved that it can provide a more reasonable evaluation results. At the same time, it is verified that the feasibility and the practicability of the proposed method are affected by varying parameters in the paper.

Artificial intelligence (AI) has gained significant momentum in recent years. Among AI-infused systems, one prominent application is context-aware systems. Although the fusion of AI and context awareness has given birth to personalized and timely AI-powered context-aware systems, several challenges still remain. Given the “black box” nature of AI, the authors propose that human–AI collaboration is essential for AI-powered context-aware services to eliminate uncertainty and evolve. To this end, this study aims to advance a research agenda for facilitators and outcomes of human–AI collaboration in AI-powered context-aware services.

Synthesizing the extant literature on AI and context awareness, the authors advance a theoretical framework that not only differentiates among the three phases of AI-powered context-aware services (i.e. context acquisition, context interpretation and context application) but also outlines plausible research directions for each stage.

The authors delve into the role of human–AI collaboration and derive future research questions from two directions, namely, the effects of AI-powered context-aware services design on human–AI collaboration and the impact of human–AI collaboration.

This study contributes to the extant literature by identifying knowledge gaps in human–AI collaboration for AI-powered context-aware services and putting forth research directions accordingly. In turn, their proposed framework yields actionable guidance for AI-powered context-aware service designers and practitioners.

This paper aims to build a theoretical model of the impact of farmers’ adoption behavior of soil and water conservation measures on the agricultural output to analyze the impact of farmers’ adoption behavior of soil and water conservation measures on agricultural output.

Based on the field survey data of 808 farmers households in three provinces (regions) of the Loess Plateau, this paper using the endogenous switching regression model to analyze the effect of farmers’ adoption behavior of soil and water conservation measures on agricultural output.

Soil erosion has a significant negative impact on agricultural output, and soil erosion has a significant positive impact on farmers’ adoption of soil and water conservation measures. Farmers adopt soil and water conservation measures such as engineering measures, biological measures and tillage measures to cope with soil erosion, which can increase agricultural output. Based on the counterfactual hypothesis, if farmers who adopt soil and water conservation measures do not adopt the corresponding soil and water conservation measures, their average output per ha output will decrease by 2.01%. Then, if farmers who do not adopt soil and water conservation measures adopt the corresponding soil and water conservation measures, their average output per ha output will increase by 12.12%. Government support and cultivated land area have a significant positive impact on farmers’ adoption behavior of soil and water conservation measures.

The research limitation is the lack of panel data.

Soil erosion has a significant negative impact on agricultural output, and soil erosion has a significant positive impact on farmers’ adoption of soil and water conservation measures. Farmers adopt soil and water conservation measures such as engineering measures, biological measures and tillage measures to cope with soil erosion, which can increase agricultural output.

The conclusion provides a reliable empirical basis for the government to formulate and implement relevant policies.

The contributions of this paper are as follows: the adoption behavior of soil and water conservation measures and agricultural output are included into the same analytical framework for empirical analysis, revealing the influencing factors of farmers’ adoption behavior of soil and water conservation measures and their output effects, enriching existing research. Using endogenous switching regression model and introducing instrumental variables to overcome the endogenous problem between the adoption behavior of soil and water conservation measures and agricultural output, and to analyze the influencing factors of farmers’ adoption behavior of soil and water conservation measures and its impact on agricultural output. Using the counter-factual idea to ensure that the two matched individuals have the same or similar attributes, to evaluate the average treatment effect of the behavior of soil and water conservation measures, to estimate the real impact of adaptation measures on agricultural output as accurately as possible and to avoid misleading policy recommendations.