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This study aims to develop a facile ligand-exchange strategy to promote nano-sintering of oleylamine (OAM)-capped silver nanoparticles (AgNPs). By using ligand exchange process with NH₄OH to remove OAM from the surface of AgNP, this study reports effectively reducing the sintering temperature of AgNPs to achieve low-temperature nano-sintering. Compared with untreated AgNPs of OAM-capped, NH₄OH-treated AgNPs possess superior sintering performance that could be applied to a fractional generator device as conductor and in favour of the fabrication of flexible circuit modules.

First, oleylamine is used as reductant to synthesize monodisperse AgNPs by a simple one-step method. Then ligand exchange is used with NH₄OH at different treating times to remove OAM, and micro-Fourier transform infrared spectroscopy and contact angle test are applied to clear the mechanism and structure characteristics of these processes. Finally, NH₄OH-treated AgNPs sediment sintering is used at different temperatures to test electrical resistivity and use ex situ scanning electron microscopy combined with in situ X-ray diffraction to study changes in microstructure in the whole nano-sintering process.

The AgNPs are always capped by organic ligands to prevent nanoparticles agglomeration. And oleylamine used as reductant could synthesize desirable size distributions of 8–32 nm with monodisperse globular shapes, but the low-temperature nano-sintering seemed not to be achieved by the oleylamine-capped AgNPs because OAM is an organic with long C-chain. The ligand exchange approach was enabled to replace the original organic ligands capped on AgNPs with organic ligands of low thermal stability which could promote nano-sintering. After ligand exchange treated AgNPs could be sintered on photo paper, polydimethylsiloxane (PDMS) and polyethylene terephthalate flexible substrates at low temperature.

In this research, the method ligand exchange is used to change the ligand of AgNPs. During ligand exchange, NH₄OH was used to treat AgNPs. Through the treatment of NH₄OH, the change of hydrophilic and hydrophobic properties of AgNPs was successfully realized. The sintering temperature of AgNPs can also be reduced and the properties can be improved. Finally, the applicability of the AgNPs sediment with this nano-sintering process at low temperature for obtaining conductive patterns was evaluated using PDMS as substrates.

Gas pipelines are facing serious risk because of the factors such as long service life, complex working condition and most importantly, corrosion. As one of the main failure reasons of gas pipeline, corrosion poses a great threat to its stable operation. Therefore, it is necessary to analyze the reliability of gas pipelines with corrosion defect. This paper uses the corresponding methods to predict the residual strength and residual life of pipelines.

In this paper, ASME-B31G revised criteria and finite element numerical analysis software are used to analyze the reliability of a special dangerous section of a gas gathering pipeline, and the failure pressure and stress concentration of the pipeline under three failure criteria are obtained. Furthermore, combined with the predicted corrosion rate of the pipeline, the residual service life of the pipeline is calculated.

This paper verifies the feasibility of ASME-B31G revised criteria and finite element numerical analysis methods for reliability analysis of gas pipelines with corrosion defect. According to the calculation results, the maximum safe internal pressure of the pipeline is 9.53 Mpa, and the residual life of the pipeline under the current operating pressure is 38.41 years, meeting the requirements of safe and reliable operation.

The analysis methods and analysis results provide reference basis for the reliability analysis of corroded pipelines, which is of great practical engineering value for the safe and stable operation of natural gas pipelines.

Shanghai is currently faced with a rapid increase in the ageing population and demand for elderly homes. Continuing care retirement community (CCRC) has been emerging as a high-end alternative to offer specialised accommodation to the elderly in major cities. Since the first development in 2008, the industry is now still at the infancy stage. This study aims to examine the investment barriers hindering the supply and demand of CCRCs with an aim to recommend practical and senior housing policy measures to facilitate CCRC developments.

Multiple-case study method was used to confirm whether the literature findings on investment barriers apply to the context of Shanghai. Four representative CCRC development cases in Shanghai were examined, in which qualitative data were collected from interviews with experienced CCRC development managers and quantitative data from a questionnaire survey of the CCRC residents.

Operation management experience, financial risks and government support policy were found to be the main supply barriers. Chinese traditional family-oriented culture and affordability were not the main demand barriers of CCRCs in Shanghai. Poor quality of services and living environment were identified as the main barriers suppressing the demand for CCRC.

Although common trends and views can be drawn from the representative cases in Shanghai to provide valid results, further research should be conducted on other major cities in China so that the results can be widely applied.

Successful CCRC investment strategy should focus on partnering with experienced professional eldercare management companies, provisions of high-quality medical professionals and trained care personnel and delivery of flexible care service, along with intensive capital flows for land, construction and operating costs.

Additional senior housing policy support should be established to promote the CCRC supply to address the ageing needs, particularly granting lands for CCRC developments at Tiers 1 and 2 major cities where the land cost is high.

This research’s practical and policy measures can be applied to enable and promote CCRC developments in Shanghai, thus benefitting both housing investors and the government. The findings also form a baseline for CCRC developments in other major cities.

The purpose of this paper is to examine how the impact of Chinese peer-to-peer (P2P) platform reputation directly and indirectly (mediate effect) affects investors’ (lenders) investment choices.

Using data collected from 478 P2P platforms, this paper calculates platform reputation via a β function after establishing a reputation mechanism by game analysis. This is followed by testing both the direct effect of platform reputation on investors’ investment choices (proxying by transaction volume) and the indirect effect through credit-enhancing information using three regression models (median regression, OLS regression and random effect OLS regression). A robustness test by adding instrument variables is conducted to confirm the findings from the main regressions.

In China, P2P lending platform reputations have played both a direct and indirect (through credit-enhancing information) role on investors’ investment choices.

This paper expands the boundary of P2P online lending research by not only examining the direct, but also, importantly, the indirect effects of platform reputations.

Influencer marketing mediated by social media is prevalent in social commerce. Micro-, meso- and macro-influencers all play an irreplaceable role in marketing. The purpose of this paper is to explore how companies with limited budgets choose influencers according to products' various levels of brand familiarity.

This study constructs an evolutionary game model of influencer marketing based on evolutionary game theory on complex networks. This model initiates various networks to demonstrate how influencers disseminate information and constructs update mechanisms to depict how individuals react to this information based on individuals' information utility and friends' strategies.

Simulation results suggest that companies should invest more in macro-influencers than in meso-influencers, however investing all in macro-influencers is not a good choice. The investment in meso-influencers will increase as brand familiarity decreases, whereas it will not exceed investment in macro-influencers. Furthermore, the accumulation of micro-influencers can accelerate the marketing process.

This study examines the combined effects of micro-influencers, meso-influencers and macro-influencers in marketing by simulating the marketing process initiated by influencers on social media.

The purpose of this paper is to examine the relationship between bank diversity and small- and medium-sized enterprise (SME) firm innovation in China to evaluate the impact of recent bank deregulation.

Using a large data set that includes 8,143 firm-year observations of 1,122 listed SME firms in China and baseline and robustness regression analyses, the authors identify how bank diversity affects firm innovation and via what economic mechanisms. Potential endogeneity problems are considered and addressed in the design and analysis to minimize research bias.

The authors find robust evidence that bank diversity improves firm innovation. Specifically, the findings suggest that the positive effects of bank diversity on firm innovation are only significant for the firms which are more external finance dependent, have fewer growth opportunities and/or located in the provinces having low financial market development.

This study provides novel evidence and insights into the relationship between banking market structure and the determinants of firm innovation in the Chinese context, as a result of China’s banking deregulation.

Since the performance of vehicular users and cellular users (CUE) in Vehicular networks is highly affected by the allocated resources to them. The purpose of this paper is to investigate the resource allocation for vehicular communications when multiple V2V links and a V2I link share spectrum with CUE in uplink communication under different Quality of Service (QoS).

An optimization model to maximize the V2I capacity is established based on slowly varying large-scale fading channel information. Multiple V2V links are clustered based on sparrow search algorithm (SSA) to reduce interference. Then, a weighted tripartite graph is constructed by jointly optimizing the power of CUE, V2I and V2V clusters. Finally, spectrum resources are allocated based on a weighted 3D matching algorithm.

The performance of the proposed algorithm is tested. Simulation results show that the proposed algorithm can maximize the channel capacity of V2I while ensuring the reliability of V2V and the quality of service of CUE.

There is a lack of research on resource allocation algorithms of CUE, V2I and multiple V2V in different QoS. To solve the problem, one new resource allocation algorithm is proposed in this paper. Firstly, multiple V2V links are clustered using SSA to reduce interference. Secondly, the power allocation of CUE, V2I and V2V is jointly optimized. Finally, the weighted 3D matching algorithm is used to allocate spectrum resources.

Previous publications were mainly focused on the effect of textures under lubrication. Under dry sliding, area ratio of surface texturing (pit area ratio) and diameter of pit affect the tribological behavior. This paper aims to investigate the effect of laser surface texturing on tribological behavior of nodular cast iron under dry sliding.

Pit-like textures with different diameters and spaces were fabricated by laser on nodular cast iron (QT600-3). Using nodular cast iron (QT600-3) as the disc specimen and resin matrix composites (UCV018) as the pad specimen, the tribological test was performed with pin-on-disk reciprocating tribo-tester.

The coefficient of friction (COF) of the non-textured specimen was larger than that of the textured one. For the same pit diameter, a larger pit area ratio induced a slight decrease of COF, while wear volume decreased significantly. The pit diameter induced a slight decrease of COF as the pit area ratio, but its effect was weaker.

The experimental studies will help to improve the brake system such as structure modeling of brake disc. Predicting the performance and life of the brake disc in vehicle based on tribological behavior checked in test, it was proved that pit-like texture had application value in vehicle brake system.

This paper showed that the effect of pit area ratio on friction and wear was greater than that of pit diameter. The experimental results will be useful to the design on safety brake disc.

The online profile picture of a doctor serves as a pivotal source of visual information, playing a key role in shaping the doctor’s professionalism in the online health market. Doctors can strategically curate the elements of their online profile pictures, such as attire and background, to either reinforce a formal image or craft a casual image, thereby influencing patients’ doctor choices. Despite this, the relative effectiveness of formal or casual images in swaying patient choices remains unclear. This study endeavors to bridge this knowledge gap.

This study tested the influence of a doctor’s attire and background in their profile picture on patient decision-making, with a focus on discerning variations in impact among patient groups differentiated by the severity of their illnesses (i.e. high-severity versus low-severity conditions). We formulated four hypotheses and tested them through an econometric analysis and a controlled laboratory experiment.

The empirical findings reveal that doctors’ formal profile pictures, characterized by formal attire and backgrounds, exert a more pronounced influence on patient choices than casual images. The severity of a patient’s illness positively moderated the relationship between formal images and patient choices.

These insights make a significant contribution to the understanding of patient behavior in selecting doctors within the online health market. Furthermore, they offer valuable guidance for doctors in optimizing their online profile presentation to better align with patient preferences and expectations.

The purpose of this paper is to present a novel method for fabric defect detection.

The method based on joint low-rank and spare matrix recovery, since patterned fabric is manufactured by a set of predefined symmetry rules, and it can be seen as the superposition of sparse defective regions and low-rank defect-free regions. A robust principal component analysis model with a noise term is designed to handle fabric images with diverse patterns robustly. The authors also estimate a defect prior and use it to guide the matrix recovery process for accurate extraction of various fabric defects.

Experiments on plain and twill, dot-, box- and star-patterned fabric images with various defects demonstrate that the method is more efficient and robust than previous methods.

The authors present a RPCA-based model for fabric defects detection, and show how to incorporate defect prior to improve the detection results. The authors also show that more robust detection and less running time can be obtained by introducing a noise term into the model.