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In the brain imaging based on electrical impedance tomography, it is sometimes not able to attach 16 electrodes due to space restriction caused by craniotomy. As a result of this, the number of boundary measurements decreases, and spatial resolution of reconstructed conductivity distribution is reduced. The purpose of this study is to enhance reconstruction quality in cases of limited measurement.

A new data expansion method based on the shallow convolutional neural network is proposed. An eight-electrode model is built from which fewer boundary measurements can be obtained. To improve the imaging quality, shallow convolutional neural network is constructed which maps limited voltage data of the 8-electrode model to expanded voltage data of a quasi-16-electrode model. The predicted data is compared with the quasi-16-electrode data. Besides, image reconstruction based on L1 regularization method is conducted.

The results show that the predicted data generally coincides with the quasi-16-electrode data. It is found that images reconstructed with the data of eight-electrode model are the poorest. Nevertheless, imaging results when the limited data is expanded by the proposed method show large improvement, and there is a minor difference with the images recovered with the quasi-16-electrode data. Also, the impact of noise is studied, which shows that the proposed method is robust to noise.

To enhance reconstruction quality in the case of limited measurement, a new data expansion method based on the shallow convolutional neural network is proposed. Both simulation work and phantom experiments have demonstrated that high-quality images of cerebral hemorrhage and cerebral ischemia can be obtained when the limited measurement is expanded by the proposed method.

The primary aim is to identify and examine the critical success factors (CSFs) in FinTech that influence social responsibility (SR). This study aims to differentiate between internal factors (e.g. risk management, innovation, regulatory compliance, technology integration) and external factors (e.g. market conditions and regulatory changes) and offer insights into effective FinTech practices that enhance SR performance.

A comprehensive literature review using the Web of Science database analyzed 143 relevant articles. This review categorizes CSFs and assesses how FinTech practices impact SR.

The findings indicate that strategic FinTech practices, such as innovation in financial services, effective data management and stakeholder collaboration, are crucial for enhancing operational efficiency, fostering sustainability and improving responsiveness to social and environmental needs. This study also highlights current trends in FinTech and SR, emphasizing the integration of FinTech into broader SR strategies.

This study provides valuable insights for practitioners on how to leverage FinTech to enhance SR, including strategies for integrating innovative technologies and improving stakeholder engagement.

By advancing the understanding of how FinTech can contribute to SR, this research highlights the potential for FinTech to drive positive social and environmental outcomes, fostering greater corporate responsibility and sustainability.

This research provides a novel bibliometric analysis of FinTech’s role in advancing SR, offering a comprehensive overview of the CSFs and emerging trends in this field.

This study longitudinally investigated the predictors and mediators of adolescent smartphone addiction by examining the impact of parental smartphone addiction at T1 on adolescent smartphone addiction at T3, as well as the separate and sequential role of adolescent self-esteem and depression at T2 as mediating factors.

This study used a hierarchical regression and the PROCESS macro (Model 6) to investigate research model by collecting 3,904 parent-adolescent pairs. Panel data were collected from three waves of the Korean Children and Youth Panel Survey (KCYPS).

First, the result showed that parental smartphone addiction at T1 significantly and positively predicted adolescent smartphone addiction at T3. Second, the serial mediation analysis revealed that the impact of parental smartphone addiction at T1 on adolescent smartphone addiction at T3 was mediated by adolescent self-esteem and depression at T2 independently and serially.

The findings enhance our comprehension of the impact of parental smartphone addiction, adolescent self-esteem and depression, on adolescent smartphone addiction.

This study aims to emphasize green energy-driven solutions to address environmental sustainability issues, particularly to promote the uptake of electric vehicles (EVs). This study intends to investigate user adoption of EVs as the existing predicament of converting car owners to EV buyers, demanding a push to create a facilitating environment for EV uptake.

A survey-based quantitative study involving 330 car owners and potential buyers was conducted involving four predictors, i.e. financial benefits, social influence, charging infrastructure and range consciousness. Environmental concerns and socio-demographic factors such as age, family income and gender were considered as moderators between these predictors and EV adoption intention. Partial least square structural equation modelling was used to analyse the proposed relationships.

The findings indicated that financial benefits (ß = 0.169, t = 3.930), social influence (ß = 0.099, t = 2.605), range consciousness (ß = 0.239, t = 3.983) and charging infrastructure (ß = 0.142, t = 4.8) significantly impact EV adoption. Family income was the most significant moderator with a large effect size (F square = 0.224), followed by environmental concern (F square = 0.182) and age (F square = 0.042) having a medium moderation effect and, subsequently, gender (F square = 0.010) as a mild moderator.

By analysing environmental concerns as a moderator, this study fosters a novel understanding of how environmental concerns impact EV adoption, which has not been explored. Additionally, the empirical assessment of the socio-economic and socio-demographic factors of EV adoption helps to offer a consumer perspective to the government and policymakers in undertaking initiatives to promote EV adoption.

In the past 10 years, the scale of running events in China has increased dramatically, and the forms of running events have also become rich and diverse. Running is not only a social phenomenon but also a historical and cultural phenomenon as an organic part of human culture with its own sociological values in China. This chapter offers insight into the development of Chinese running culture and how this has emerged from ancient and modern Chinese running cultures based on Foucault's disciplinary power theory, biopower and the technologies of the self. This chapter argues that running culture in China constructs the subjectivity of the Chinese runners under the joint action of the technologies of power and the technologies of the self. The findings acknowledge how Chinese Runners present and express themselves by showing a ‘sense of presence’. Runners illustrate the implicit or explicit meaning and value of a particular way of life through running. Runners regard running as the technology of the self for self-expression and self-creation so that individuals can control their bodies and soul, thoughts, behaviours and ways of existence. Emerging technologies of power provide possibilities for the production of running culture in China, and the current policy under the technologies of power meets the needs of runners. In Chinese running culture, power was not oppressive but productive.

When handling small-sized shafts and holes, achieving optimal safety, size compatibility and shape adaptability using rigid grippers presents significant problems. Recent advancements have introduced soft end-effectors that offer enhanced safety and adaptability for gripping parts. However, these soft end-effectors often struggle to maintain the necessary gripping positional accuracy. The purpose of this paper is to design a soft end-effector specifically engineered to address these problems, combining precise gripping capabilities with improved safety, positional accuracy and adaptability to the size and shape of fragile, small-sized components.

A soft finger with multilayer decreasing drive air chambers is designed to achieve the finger bending increasing from the root to the tip of the finger to improve the flexibility of the fingertip. Additionally, a three-finger self-centering configuration is employed, coupled with an expandable structure to increase the gripping range. Furthermore, a theoretical mathematical model of the finger is established. The physical prototype is manufactured and subjected to experimental testing, including gripping tests on small-sized, fragile shaft holes, to validate its operational performance.

The grasping experiments confirm that the designed end-effector can maintain coaxial positioning and meet adaptability requirements when handling fragile components with small-sized shaft holes. Furthermore, the addition of expanding palm structure increases the gripping attitude and enriches the application scene and gripping space.

The design of multilayer decreasing air chamber structure to solve the problem of poor gripping stability and low positional accuracy of soft manipulator; the expandable palm design is introduced to enhance gripping space; and solved the problem of gripping accuracy in the assembly of fragile parts with small-size shafts and holes.

This study investigates the relationships among digital transformation, technological innovation, industry–university–research collaborations and labor income share in manufacturing firms.

The relationships are tested using an empirical method, constructing regression models, by collecting 1,240 manufacturing firms and 9,029 items listed on the A-share market in China from 2013 to 2020.

The results indicate that digital transformation has a positive effect on manufacturing companies’ labor income share. Technological innovation can mediate the effect of digital transformation on labor income share. Industry–university–research cooperation can positively moderate the promotion effect of digital transformation on labor income share but cannot moderate the mediating effect of technological innovation. Heterogeneity analysis also found that firms without service-based transformation and nonstate-owned firms are better able to increase their labor income share through digital transformation.

This study provides a new path to increase the labor income share of enterprises to achieve common prosperity, which is important for manufacturing enterprises to better transform and upgrade to achieve high-quality development.

This study aims to develop a high-performance nanofluid that can be used in titanium alloys machining. Titanium alloys are difficult-to-cut materials and difficult to be lubricated. This study explored the lubrication performance of various carbon nanoparticles in water-based lubricants for titanium alloys.

The lubricating and antiwear properties of the developed cutting fluid were tested by a tribo-tester. The lubricant performance was evaluated through friction coefficient, wear volume and surface quality. The lubrication mechanism was analyzed through surface morphology, wettability and bonding analysis.

The lubricating performance of four kinds of carbon nanoparticles on titanium alloys was tested and the results showed that single-layer graphene had the smallest COF and wear volume. The interaction between nanoparticles and debris was an important factor that influenced the lubrication performance of nanoparticles for titanium alloy. Moreover, the hybrid nanofluid with graphene and spherical graphite in a ratio of 1:2 achieved a balance between lubricating performance and price, making it the optimal choice.

The developed lubricant containing carbon nanoparticles that can lubricate titanium alloys effectively has great potential in machining titanium alloy as a high-performance cutting fluid in the future.

This paper fulfills an identified need for water-based lubricant for titanium alloys considering the bad tribological properties.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0124/

The purpose of this paper is to study the relationship between high temperature oxidation and temperature rise rate of engine oil attempted to explore a new indicator to evaluate oil degradation.

Accelerated oxidation test combined with molecular simulation and road test is carried out in this paper. The temperature rise characteristics of mineral oil and synthetic oil under different oxidation temperatures (140°C, 155°C and 170°C) and time (50 h, 100 h, 150 h and 200 h) were determined by accelerated oxidation. The mechanism of temperature change characteristics of used oils was analyzed with molecular simulation. Two experimental vehicles carried six road tests with synthetic and mineral oil.

The results of this study show that the temperature rise rate of oxidized mineral and synthetic oil is higher than the new oil. The temperature rise rate is proportional to the oxidation time and oxidation temperature. The synthetic engine oil temperature rise rate is lower than that of the mineral engine oil. The same result was obtained in road tests. Molecular simulation verifies that small molecules were generated after oil oxidation which results in intermolecular friction and increased heat generation.

This paper indicates that temperature rise rate has potential to be taken as an indicator to evaluate oil oxidation which provides a new way for engine oil analysis.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0177/

Organic coatings are widely used for protecting metal equipment and structures from corrosion. Accurate detection and evaluation of the protective performance and service life of coatings are of great importance. This paper aims to review the research progress on performance evaluation and lifetime prediction of organic coatings.

First, the failure forms and aging testing methods of organic coatings are briefly introduced. Then, the technical status and the progress in the detection and evaluation of coating protective performance and the prediction of service life are mainly reviewed.

There are some key challenges and difficulties in this field, which are described in the end.

The progress is summarized from a variety of technical perspectives. Performance evaluation and lifetime prediction include both single-parameter and multi-parameter methods.