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In many cases, the external pipelines of aero-engine are subjected to random excitation. The purpose of this paper is to reduce the vibration response of the pipeline system effectively by adjusting the hoop layout.

In this paper, a spatial pipeline supported by multi-hoops is taken as the object, the methods of solution of the vibration response of the pipeline system by using pseudo excitation and hoop layouts optimization with amplitude reduction of vibration response as the goal are presented. First, the finite element model of the spatial pipeline system is presented. Then, an optimization model spatial pipeline is established. Finally, a case study is carried out to prove the rationality of the random vibration response analysis of the pipeline system. Furthermore, the proposed optimization model and genetic algorithm are applied to optimize the hoop layout.

The results show that the maximum response variance after optimization is reduced by 32.8%, which proves the rationality of the developed hoop layout optimization method.

The pseudo excitation method is used to solve the vibration response of aero-engine pipeline system, and the optimization of the hoop layout for aero-engine spatial pipelines under random excitation to reduce random vibration response is studied systematically.

The authors designed those experiments to test the sensitivity of graphene when it is exposed to NO₂ gas, to find a way to decrease the recovery time of graphene and to find the difference effect between monolayer and bilayer graphene in the experiments.

The authors transferred graphene from film on Cu foil to NO₂ sensor sample and measured the resistances of on monolayer and bilayer graphene when they were exposed to NO₂ gas under different concentration; then, the authors obtained the results.

The results show that monolayer graphene exhibits a linear response when the NO₂ concentration is below 20 ppm. But the monolayer graphene will not be so sensitive to NO₂ gas when the concentration continues to reduce. The desorption time of monolayer graphene is longer when compared with bilayer graphene. It shows faster recovery time and higher response of bilayer graphene under low NO₂ concentration. And the limit detectable NO₂ concentration of bilayer graphene is 50 ppb. Desorption time of bilayer graphene is shortened to below 20 s under UV light.

The authors found a reliable way to decrease the recovery time of graphene when it is exposed NO₂ gas and got the concrete data.

Graphene is a two-dimensional material. Its use has many advantages in gas sensing, but its long desorption process is problematic. The aim of this paper is to design a graphene-based gas sensor, study the response to NO₂ gas concentrations and find ways to accelerate the desorption process.

In one group, the sensor was placed in air to measure its initial resistance. Then, it was exposed to the NO₂ gas at a certain concentration. Finally, the sensor was exposed to light immediately after NO₂ gas exposure was ended. In another group, the sensor was heated using a heating plate at a stable temperature, before taking the measurements. Then the adsorption and desorption experiments were carried on.

Illumination and heating at a suitable temperature can expedite desorption of NO₂ molecules on graphene.

In the paper, two main methods are introduced to accelerate the desorption process when the NO₂ gas is absorbed on graphene. Through a series of experiments and analysis, the authors found that the recovery time could be reduced observably and the recovery performance of the graphene-based NO₂ sensor could be improved effectively.

The purpose of this paper is to examine a new idea of vibration control which minimizes joint‐torques and suppresses vibration of the flexible redundant manipulator.

Using the kinematics redundancy feature of the flexible redundant manipulator, the self‐motion in the joint space can be properly chosen to both suppress vibration and minimize joint‐torques.

The study shows that the flexible redundant manipulator still has the second optimization feature on the premise of vibration suppression. The second optimization feature can be used to minimize joint‐torques on the premise of vibration suppression.

To a flexible redundant manipulator, its joint‐torques and vibration can be reduced simultaneously via its kinematics redundancy feature.

The method and algorithm discussed in the paper can be used to minimize joint‐torques and suppress vibration for the flexible redundant manipulator.

The paper contributes to the study on improving dynamic performance of the flexible redundant manipulator via its kinematics redundancy feature. The second optimization capability of the flexible redundant manipulator is discovered and used to both minimize joint‐torques and suppress vibration.

At present, the scale of China's floating population has reached 376 million people. Compared with the local inhabitants, the poverty problem of the floating population is more complex, and this problem should also attract the attention of all sectors of society. This paper aims to measure and analyze the multidimensional poverty of the floating population in China.

The data used in this paper are the data of the China Migrants Dynamic Survey (CMDS) in China. This survey is a large-scale national migratory population sampling survey organized by the China National Health Commission, covering 31 provinces (autonomous regions and cities) and other autonomous regions. This paper uses the dynamic monitoring and Alkire and Foster (A-F) method to study the multidimensional poverty problem of the floating population.

This study finds that income poverty is no longer the main type of poverty faced by the floating population. The multidimensional poverty of the floating population mainly occurs in the social security and education dimensions, of which social security has become the most severe poverty dimension of the floating population. From the perspective of group differences, compared with the floating population in urban areas, the multidimensional poverty of migrant workers is more serious. However, the poverty of migrant workers is mainly concentrated in one-dimensional poverty and two-dimensional poverty.

In the future, the authors should focus on the social security of the floating population in the place of influx and the education of the floating population.

Through the review of the existing literature, the authors find that the current research on the multidimensional poverty of the floating population is mainly concentrated on the migrant worker groups that move from rural areas to urban areas. However, insufficient attention is paid to the urban floating population groups moving between cities.

In the dynamic landscape of the digital economy, companies are increasingly adopting omnichannel integration strategies to enhance customer experiences. However, the interplay between this strategy and digitalisation in fostering brand trust remains uncharted. Drawing on the social exchange and psychological reactance theories, this study ventures into unexplored territory by examining the impact of omnichannel integration and digital value on brand trust building. It also delves into the boundary roles of customers’ psychological perceptions, both positive (customer empowerment) and negative (privacy concerns and perceived deception), in this process.

This study conducted an online survey of 595 omnichannel users in China and validated the model using partial least squares structural equation modelling (PLS-SEM).

This study’s results have significant implications for businesses. They show that customer perception of omnichannel integration and perceived digital value are critical drivers of omnichannel brand trust, with customer empowerment playing a mediating role. Notably, the study also reveals that customers’ negative psychological perceptions can have different moderating effects, highlighting the need for businesses to address these concerns in their omnichannel strategies.

This study breaks new ground in marketing research by highlighting the benefits of omnichannel integration and incorporating digital perspectives. It demonstrates the positive impact of blending customer perception of omnichannel integration and perceived digital value on brand trust formation. Furthermore, it explores the boundary roles of customers’ psychological perceptions in this process, offering a unique and comprehensive perspective.

Digital technology plays a vital role in empowering omnichannel integration. Research on digital technology has recently attracted attention and rapidly developed. However, a comprehensive assessment of the research status and potential gaps is yet to be conducted. Thus, this study investigated the current research status of digital technology-empowered omnichannel integration, and future research directions are proposed.

A three-stage bibliometric analysis was conducted on 764 articles published from 2000 to 2023, cited in the Web of Science database. Furthermore, performance and thematic analyses were performed.

The most productive contributors and influential articles in this field were identified, and four themes of focus were discovered: service quality, o2o commerce, omnichannel retailing, and digital transformation.

To the best of our knowledge, this work is the first attempt to enable researchers to understand the vast body of published scholarship on digital technology-empowered omnichannel integration.

Liquid-assisted laser surface texturing technology was used to create composite microtextures on triangular guide rail surfaces to enhance their tribological properties.

Numerical simulations were used to investigate the impact of various microtextures on fluid dynamic lubrication. Reciprocating friction and wear tests, followed by mechanistic analysis, examined the combined tribological effects of microtextured surfaces and lubricants.

The numerical simulation outcomes reveal a significant augmentation in the influence of fluid dynamic pressure due to composite microtextures, consequently amplifying the load-bearing capacity of the oil film. The average friction coefficient of composite microtextured samples was approximately 0.136 in reciprocating pin-on-disk friction tests, representing approximately 17% decrease compared to polished samples. Triangular guide rails with composite microtextures demonstrated the lowest average coefficient under conditions of high-speed and heavy-loading in the reciprocating friction and wear tests. Additionally, the presence of composite microtextures was found to promote the formation of adsorbed and friction films during friction, potentially contributing to the enhancement of tribological properties.

Triangular guide rails face high friction and wear, limiting their stability in demanding applications like machine tool guideways. This paper proposes a novel approach for steel triangular guide rails, involving composite microtexturing, numerical fluid simulations, liquid-assisted laser surface texturing and friction-wear testing. By implementing composite microtextures, the method aims to reduce friction coefficients and extend guideway service life, thereby saving energy and reducing maintenance costs. Enhancing the antifriction and antiwear properties of machine tool guideways is crucial for improving performance and longevity.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0183/

This paper proposes an intelligent fault diagnosis method, which aims to obtain the outstanding fault diagnosis results of the gearbox.

An intelligent fault diagnosis method based on energy entropy-weighted complementary ensemble empirical mode decomposition (EWCEEMD) and support vector machine (SVM) optimized by whale optimization algorithm (WOA) is proposed. The raw signal is first denoised by the wavelet noise reduction method. Then, complementary ensemble empirical mode decomposition (CEEMD) is used to generate several intrinsic mode functions (IMFs). Next, energy entropy is used as an indicator to measure the sensibility of the IMF and converted into a weight coefficient by function. After that, IMFs are linearly weighted to form the reconstruction signal, and several features are extracted from the new signal. Finally, the support vector machine optimized by the whale optimization algorithm (WOA-SVM) model is used for gearbox fault classification using feature vectors.

The fault features extracted by this method have a better clustering effect and clear boundaries under each fault mode than the unimproved method. At the same time, the accuracy of fault diagnosis is greatly improved.

In most studies of fault diagnosis, the sensitivity of IMF has not been appreciated. In this paper, energy entropy is chosen to quantify sensitivity. In addition, high classification accuracy can be achieved by applying WOA-SVM as the final classification model, improving the efficiency of fault diagnosis as well.