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The purpose of this study is to (1) improve the spectral features of the second-order uniformly non-oscillatory (UNO) slope limiters, and (2) numerical simulation of the unified-form of generalized fully-coupled saturated thermo-poro-elastic systems in the axisymmetric cylindrical coordinate via cell-adaptive Kurganov-Tadmor (KT) central high-resolution scheme using the UNO limiters.

(1) The spectral features of the UNO limiter are improved by compression-adaptive MINMOD (MM) limiters, achieved by blending different types of MM limiters to achieve less numerical dissipation and dispersion. These blended MM limiters preserve the total variation diminishing (TVD) feature over non-uniform non-centered cells. Also, the spectral features of the central schemes using the UNO limiters are investigated. (2) For the thermo-poro-elastic problem, corresponding first-order hyperbolic system is provided, including flux, source, diffusion and nonlinear terms. Where, there are different interacting components in the source and flux terms. The nonlinear terms are also considered by the Picard-like linearization concept.

Compression-adaptive UNO limiters would be stable over adapted cells with centered and non-centered cells. The benchmarks confirm that both spectral features and numerical accuracy are improved. For the generalized thermo-poro-elastic problem, corresponding responses including the shock waves can properly be captured.

Studying heat effects (e.g. hot fluid or freezing) and explosions on tunnels. Also, the UNO limiters could be used for simulations of various systems of conservation laws.

The water-lubricated hydrodynamic herringbone groove journal bearing (HGJB) is capable of running at high speed. However, when running at a low speed, it suffers from a low load-carrying capacity due to the weak hydrodynamic effect. To overcome this problem, this study proposes a hybrid water-lubricated HGJB and aims to investigate its dynamic characteristics.

A hybrid lubrication model applicable to the hybrid water-lubricated HGJB is established based on the boundary fitted coordinate system, which considers the turbulent, thermal and tilting effects, and the finite difference method is used to calculate the dynamic characteristics of the hybrid water-lubricated HGJB.

The result shows that the hybrid HGJB has larger dynamic coefficients and better system stability compared with the hydrodynamic HGJB when running at low speed. Furthermore, the stiffness of hybrid HGJB are mainly governed by the hydrodynamic effect rather than the hydrostatic effect when running at high speed.

The proposed hybrid water-lubricated HGJB shows excellent dynamic characteristics at either low speed or high speed; and the hybrid water-lubricated HGJB has a large load-carrying capacity when running at low speed and has a good dynamic stability when running at high speed.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0233/

As an ancient art form, embroidery has strong practicality and artistic value. However, current embroidery style migration models produce images with unclear textures and a lack of stitch detail. So, in this paper, we propose a cyclic consistent embroidery style migration network with texture constraints, which is called Texture Cycle GAN (TCGAN).

The model is based on the existing Cycle GAN network with an additional texture module. This texture module is implemented using a pre-trained Markovian adversarial network to synthesize embroidery texture features. The overall algorithm consists of two generative adversarial networks (for style migration) and the Markovian adversarial network (for texture synthesis).

Qualitative and quantitative experiments show that, compared with the existing convolutional neural network style transfer algorithm, the introduction of the texture-constrained embroidery style transfer model TCGAN can effectively learn the characteristics of style images, generate digital embroidery works with clear texture and natural stitches and achieve more realistic embroidery simulation effects.

By improving the algorithm for image style migration and designing a reasonable loss function, the generated embroidery patterns are made more detailed, which shows that the model can improve the realism of embroidery style simulation and help to improve the standard of embroidery craftsmanship, thus promoting the development of the embroidery industry.

The objective of this study is to utilize empirical research and analysis to examine the coupling coordination relationship between new quality productivity and higher vocational education sustainable development.

To this end, an evaluation index system for the new quality productivity and higher vocational education sustainable development was constructed. The panel data of 30 Chinese provinces from 2016 to 2022 were then analyzed using the entropy method, the coupling coordination degree model, the Tobit regression model and Dagum’s Gini coefficient.

The findings indicate that the coupling coordination degree of new quality productivity and higher vocational education sustainable development exhibited an upward trend, though significant regional disparities were observed, with the highest coupling coordination degree recorded in the eastern region and the lowest in the northeastern region.

The study’s findings further suggest that the three factors of technological innovation level, rationalization of industrial structure and advanced industrial structure have a significant positive influence on the coupling coordination degree, while the level of government intervention has a significant negative influence on the Coupling Coordination Degree. The study posits that augmenting policy support, optimizing the government’s role, reinforcing the drive for technological innovation, and enhancing regional cooperation and exchange are imperative to foster high-quality development of the integration of industry and education between new quality productivity and higher vocational education.

This study aims to explore the factors influencing the evolution of emerging technology innovation network (ETIN) in combination with the key attributes and life cycle of emerging technologies, particularly the impact of multiple knowledge attributes and technology life cycle on the ETIN evolution.

This study collects 5G patent data and their citation information from the Derwent Innovations Index to construct a 5G technology innovation network (5GIN) as a sample network and conducts an empirical analysis of the 5GIN using the temporal exponential random graph model (TERGM).

The results indicate that during the 5GIN evolution, the network scale continues to expand and exhibits increasingly significant core-periphery structure, scale-free characteristic, small-world characteristic and community structure. Furthermore, the findings suggest that the multiple knowledge attributes based on the key attributes of emerging technologies, including knowledge novelty, coherence, growth and impact, have a significant positive influence on the ETIN evolution. Meanwhile, the temporal evolution of ETIN is also found to be correlated with the life cycle of emerging technologies.

This study extends the exploration of emerging technology research from a complex network perspective, providing a more realistic explanatory framework for the factors influencing ETIN evolution. It further highlights the important role that multiple knowledge attributes and the technology life cycle play within this framework.

During the cooperation process between prefabricated building construction enterprises (PBCEs) and Internet platforms (IPs), the sentiments of both parties influence their behavioral strategies. They are the key to improving the informatization and operational efficiency of the prefabricated building industry chain (PBIC).

This paper introduces mental accounting theory and rank-dependent expected utility theory to construct the MA-RDEU game model, exploring the evolutionary mechanism between sentiment and behavioral strategies of PBCEs and IPs.

The study indicates that (1) a mixed strategy equilibrium can be achieved when both parties have no sentiments. (2) PBCEs and IPs are more likely to achieve an optimal equilibrium for cooperation if the latter is optimistic. In contrast, pessimism may lead both parties to prioritize self-interest when only one party has a sentiment. (3) The combined impact of sentiments and behavioral strategies on decision-making is significant: the influence of sentiments from PBCEs or IPs on the optimal strategy for achieving cooperation is contingent upon the behavioral strategies of the other party; different behavioral strategies of IPs or PBCEs can have varying effects on sentiments when both parties have sentiments. (4) The influence of external factors on the sentiments and behavior strategies of PBCEs and IPs is apparent. PBCEs and IPs should concurrently consider the combined influence of external factors and sentiments to contribute to the realization of cooperation between the two parties. Additionally, government supervision is an effective means to restrain “free-riding” behavior.

Finally, based on the above conclusions, the paper proposes measures to improve the construction of service-oriented IPs and establish a mechanism for monitoring and adjusting risk sentiments. Meanwhile, this paper also indicates that under the combined effect of the government, PBCEs and IPs, the influence of external factors on sentiments can be maintained within a controllable scope and the risks of uncertainty can be mitigated.

The accurate prediction of driving torque demand is essential for the development of motion controllers for mobile robots on complex terrains. This paper aims to propose a hybrid model of torque prediction, adaptive EC-GPR, for mobile robots to address the problem of estimating the required driving torque with unknown terrain disturbances.

An error compensation (EC) framework is used, and the preliminary prediction driving torque value is achieved using Gaussian process regression (GPR). The error is predicted using a continuous hidden Markov model to generate compensation for the prediction residual caused by terrain disturbances and uncertainties. As the final step, a gain coefficient is used to adaptively tune the significance of the compensation term through parameter resetting. The proposed model is verified on a sample set, including the driving torque of a mobile robot on three different sandy terrains with two driving modes.

The results show that the adaptive EC-GPR yields the highest prediction accuracy when compared with existing methods.

It is demonstrated that the proposed model can predict the driving torque accurately for mobile robots in an unconstructed environment without terrain identification.

This study aims to design a small-size conformable flexible micro-electro-mechanical system (MEMS) vector hydrophone to meet the miniaturization requirements of unmanned underwater vehicle.

The cilia receive the acoustic signal to oscillate to cause changes in the stress on the beam, which in turn causes changes in the piezoresistive resistance on the beam, and changes in the resistance cause changes in the output voltage.

The results show that the flexible hydrophone in the paper has a sensitivity of −182 dB@1 kHz (re 1V/µPa) at 1 Pa sound pressure, can detect low-frequency hydroacoustic signals from 20 to 550 Hz and has good spatial directivity, and the flexible substrate permits the hydrophone to realize bending deformation, which can be well attached to the surface of the object.

In this study, a finite element simulation model of the hydrophone microstructure is constructed and its performance is verified by simulation. The success rate of the proposed MEMS transfer process is as high as 94%, and the prepared piezoresistors exhibit excellent resistance characteristics and high consistency. These results provide innovative ideas to enhance the performance and stability and achieve miniaturization of hydrophones.

Air pollution poses a significant global threat to both human health and environmental stability, acknowledged by the World Health Organization as a leading cause of non-communicable diseases (NCDs) and a notable contributor to climate change. This chapter offers a comprehensive review of the impacts of air pollution on health, highlighting the complex interactions with genetic predispositions and epigenetic mechanisms. The consequences of air pollution to health are extensive, spanning respiratory diseases, cardiovascular disorders, adverse pregnancy outcomes, neurodevelopmental disorders, and heightened mortality rates. Genetic factors play a pivotal role in shaping individual responses to air pollution, influencing susceptibility to respiratory illnesses and the severity of symptoms. Additionally, epigenetic changes triggered by exposure to pollutants have been linked to respiratory health issues, cancer development and progression, and even transgenerational effects spanning multiple generations. As countries, including the UK, pursue ambitious targets for reducing emissions, ongoing research into the complex interplay of air pollution, genetics, and epigenetics is essential. By unravelling the underlying mechanisms and advancing preventive and therapeutic strategies, we can protect public health and promote sustainable environmental practices in the face of this pervasive global challenge.

Despite smart construction technology's great potential to improve the productivity of the architectural, engineering and construction (AEC) industry, the implementation of smart construction technology has failed to achieve the expected benefits due to the negative usage behaviors of construction enterprise employees. This study aims to identify the determinants and their configuration effects on the smart construction technology usage behavior (SCTUB) based on the Technology-Organization-Environment (TOE) framework. This study then verifies the practical paths to improve the employee's SCTUB from the configuration perspective.

A mixed-method approach involving survey and qualitative comparative analysis (QCA) is conducted in this study. Based on the detailed literature review and semi-structured interview, this study identifies the factors and proposes the TOE framework to determine the configuration conditions affecting employee's SCTUB and verify practical paths to promote this user behavior.

The TOE framework's technical, organizational and environmental elements are interdependent. The emergence of a high SCTUB is not determined by a single determinant but by configuration conditions. Four equifinal conditions (e.g. organization-technology type, technology-organization type, environment type and organization-technology balanced type) are verified to promote construction enterprise employee's SCTUB.

The four verified configuration conditions could guide construction enterprises to formulate complementary strategies for promoting the construction enterprises' employees to implement smart construction technology and achieve the enterprise's digital transformation.

The inter-dependence of the three-dimension factors, namely technical, organizational and environmental elements are explored to enrich the literature on the TOE framework. Meanwhile, the configuration effects of these factors on usage behavior are identified, expanding the literature on the information technology acceptance model.