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The purpose of this paper is to present the latest sensing structure designs and principles of information detection of fiber Bragg grating (FBG) displacement sensors. Research advance and the future work in this field have been described, with the background that displacement and deformation measurements are universal and crucial for structural health monitoring.

This paper analyzes and summarizes the existing FBG displacement sensing technologies from two aspects principle of information detection (wavelength detection, spectral bandwidth detection, light intensity detection, among others) and principle of the sensing elastomer structure design (cantilever beam type, spring type, elastic ring type and other composite structures).

The current research on developing FBG displacement sensors is mainly focused on the sensing method, the construction and design of the elastic structure and the design of new information detection method. The authors hypothesize that the following research trends will be strengthened in future: temperature compensation technology for FBG displacement sensors based on wavelength detection; a study of more diverse elastic structures; and fiber gratings manufactured with special fibers will greatly improve the performance of sensors.

The latest sensing structure designs and principles of information detection of FBG displacement sensors have been proposed, which could provide important reference for research group.

The purpose of this paper is to investigate the cointegration and volatility spillover dynamics between the USA and South Asian stock markets, namely, India, Pakistan and Sri Lanka. The main objective of this study is to provide the knowledge about integration of financial market and volatility spillovers before, during and after global financial crisis to investors, fund managers and policy-makers.

The Johansen and Juselius cointegration test, Granger Causality test and bivaraite EGARCH model have been applied in this study to examine integration and volatility spillovers between selected stock markets.

The findings show that long-term integration between the USA market and South Asian emerging stock markets. It is found that USA stock market has causal relationship with emerging stock markets in short-term. The findings of EGARCH model reveal that asymmetric volatility spillover effects significant in all selected stock markets in pre, during and post-crisis periods. Furthermore, significant volatility spillover is found from stock markets of USA to all selected South Asian markets during and post-crisis periods. However, volatility spillovers from USA to India and Sri-Lanka markets are significant, while insignificant in case of Pakistani market in pre-crisis period. Overall, we find that returns and volatility spillover effects are higher in financial crisis period as compared to non-financial crisis period.

The findings of this paper have important implications for investors, portfolio managers and policy-makers. They can take potential benefits from international portfolio diversification by considering all these facts. The understanding and knowledge of across volatility transmission help them to maximize the gains from diversification and minimize the risk. Policy-makers can develop such strategies which protect the markets of these economies from future financial crisis.

Although in finance literature numerous studies have been conducted on integration between different stock markets, most of the studies investigated the integration and volatility spillovers between developed stock markets. However, many studies also analyzed the integration among emerging stock markets in literature review but it is hard to find studies in the context of South Asian stock markets on the effect of global financial crisis on stock markets. The main contribution of this study is to investigate the stock markets integration and volatility transmission between the USA and South Asia by considering the effect of recent 2007 US subprime financial crisis.

To control one of the joints during the actual movement of the hydraulically driven quadruped robot, all the other joints in the leg need to be locked. Once the joints are unlocked, there is a coupling effect among the joints. Therefore, during the normal exercise of the robot, the movement of each joint is affected by the coupling of other joints. This brings great difficulties to the coordinated motion control of the multi-joints of the robot. Therefore, it is necessary to reduce the influence of the coupling of the hydraulically driven quadruped robot.

To solve the coupling problem with the joints of the hydraulic quadruped robot, based on the principle of mechanism dynamics and hydraulic control, the dynamic mathematical model of the single leg mechanism of the hydraulic quadruped robot is established. On this basis, the coupling dynamics model of the two joints of the thigh and the calf is derived. On the basis of the multivariable decoupling theory, a neural network (NN) model reference decoupling controller is designed.

The simulation and prototype experiment are carried out between the thigh joint and the calf joint of the hydraulic quadruped robot, and the results show that the proposed NN model reference decoupling control method is effective, and this method can reduce the cross-coupling between the thigh and the calf and improve the dynamic characteristics of the single joint of the leg.

The proposed method provides technical support for the mechanical–hydraulic cross-coupling among the joints of the hydraulic quadruped robot, achieving coordinated movement of multiple joints of the robot and promoting the performance and automation level of the hydraulic quadruped robot.

On the basis of the theory of multivariable decoupling, a new decoupling control method is proposed, in which the mechanical–hydraulic coupling is taken as the coupling behavior of the hydraulic foot robot. The method reduces the influence of coupling of system, improves the control precision, realizes the coordinated movement among multiple joints and promotes the popularization and use of the hydraulically driven quadruped robot.

The purpose of this paper is to investigate the impact of product description and involvement on purchase intention in a cross-border e-commerce (CBEC) setting from a psychological perspective.

This study proposes a research model of purchase intention in CBEC based on the involvement theory and commitment-involvement theory. The research model was tested using the covariance-based structural equation modeling technique. Data were collected from consumers on a popular CBEC platform in China.

A high-quality product description has no significant positive effect on purchase intention, but it has significant positive effects on product cognitive involvement, product affective involvement, platform enduring involvement and platform situational involvement. In addition, product affective involvement, platform enduring involvement and platform situational involvement all have significant positive effect on purchase intention, but this effect is not significant in the relationship between product cognitive involvement and purchase intention.

This study calls for sellers to optimize product descriptions on CBEC platforms in order to attract more buyers and generate more profits.

This study integrates two theories of involvement into the research model in the CBEC context. Based on this model, the authors analyzed how product description affects purchase intention under the joint influence of two involvement factors.

Inconel 718 is difficult to machine due to its high toughness and study hardenability. Though the use of cutting fluids alleviates the problem, it is not sustainable. So, supply of a small quantity of specialized coolant to the machining zone or use of a solid lubricant is a possible solution. The purpose of the present work is to improve machinability of Inconel718 using graphene nanoplatelets.

In the present study, graphene is used in the machining of Inconel 718 alloy. Graphene is applied in the following two forms: as a solid lubricant and as an inclusion in cutting fluid. Graphene-based self-lubricating tool and graphene added nanofluids are prepared and applied to turning of Inconel 718 at varying cutting velocities. Performances are compared by measuring cutting forces, cutting temperature, tool wear and surface roughness.

Graphene, in both forms, showed superior performance compared to dry machining. In total, 0.3 Wt.% graphene added nanofluids showed the lowest cutting tool temperature and flank wear with 44.95% and 83.37% decrease, respectively, compared to dry machining and lowest surface roughness, 0.424 times compared to dry machining at 87 m/min.

Graphene could improve the machinability of Inconel 718 when used in tools as a solid lubricant and also when used as a dispersant in cutting fluid. Graphene used as a dispersant in cutting fluid is found to be more effective.

In this paper, microbial transglutaminase (MTG) was applied to process silk fabric for improving its crease resistance under the prerequisite of maintaining other performances. Not only was the effect of MTG on silk fabric investigated through the Fourier transform infrared spectroscopy (FR), but analysis was also undertaken in the microcosmic structure of fibroin through the scanning electron microscope (SEM). Solo MTG treatment as well as compound treatments of MTG followed by hydrogen peroxide, protease and ultrasonic, all showed that MTG can improve the crease resistance of silk fabric. It also enhanced its tensile breaking strength or amended damage in the tensile breaking strength caused by pretreatments.

Simultaneously, comparison with other treatments showed that compound treatment of MTG followed by ultrasonic exerted a better coordinated effect and conferred better performances, which made the wrinkle recovery angle (WRA) increase by 17.4% and tensile breaking strength improve by 11.2% respectively. At the same time, other performances were still maintained well.

This study aims to focus on the impact of multi-level knowledge sharing between and within organizations on the risk control of rural inclusive finance. The paper presents a synergistic risk control system integrating external and internal factors for rural inclusive finance by constructing different knowledge-sharing platforms in an environment, which is full of many uncertainties.

This study is based on survey methods. To achieve the research objectives, the authors adopt a single case study approach. For data collection, the authors apply a wide variety of methods such as semi-structured interviews, field visits, second-hand databases and official websites.

The results emphasize that using multi-level knowledge sharing such as the inter- and intra-organizational level, can facilitate the risk control of rural inclusive finance during the post-COVID-19 era. Furthermore, it is also noted that achieving knowledge sharing at different levels by building diverse knowledge-sharing platforms can promote the risk control of rural inclusive finance from the individual-organization level to the chain level of multi-organization collaboration, which contributes to the formation of symbiotic risk control ecology.

The authors have formed the “Chinese wisdom” to deal with inclusive financial risks and to promote in-depth development in relation to the “last mile” practice of inclusive finance, which means the final and the most important phase of a project. The conclusions contribute to enriching the outcomes regarding the risk control of rural inclusive finance, provide experiences to its sustainable development and offer a reference to other countries with their risk control of rural inclusive finance.

Drawing on the knowledge-sharing approach, this study creatively resolves the persistent problems in the risk control of rural inclusive finance, which forms a powerful supplement to the extant literature. Meanwhile, the paper combines the two contextual factors of the post-COVID-19 era and emerging economies, which can be deemed as a novel attempt.

A robotic wheelchair system was designed to assist disabled people with disabilities to walk.

An anticipated sharing control strategy based on topological map is proposed in this paper, which is used to assist robotic wheelchairs to realize interactive navigation. Then, a robotic wheelchair navigation control system based on the brain-computer interface and topological map was designed and implemented.

In the field of robotic wheelchairs, the problems of poor use, narrow application range and low humanization are still not improved.

In the system, the topological map construction is not restricted by the environment structure, which helps to expand the scope of application; the shared control system can predict the users’ intention and replace the users’ decision to realize human-machine interactive navigation, which has higher security, robustness and comfort.

Inconel 718 is used in gas turbine engines for aerospace applications due to high creep resistance but generating a hole with good surface integrity is challenging because the γ′′ interface is very strong so that slip is difficult in the grain boundary. So, the purpose of this work is to enhance the performance of drilling using a micro texture drill tool filled with solid lubricant.

Three different micro textures such as star shaped with 6-sharp apex, rectangular slots parallel and perpendicular to drill axis are created using laser on the drill tool. Deep cryogenic treatment is done on the textured tool to improve the strength and wear resistance before it is filled with solid lubricant. A detailed experimental investigation is performed to analyse the hole geometry and surface integrity of the drilled hole.

The accuracy of the drilled holes is enhanced in the star shaped texture drill tool over other textured and non-textured tools. A significant improvement in surface finish and hardness are observed and moreover cylindricity error, burr height of the hole is less for the above condition. It is also inferred that, at lower feed rate and higher speed produce hole with an accuracy of 96%.

Aerospace industry is focussing on improving the hole geometry and surface in Inconel 718. This work demonstrates the novel technique to improve drilling of Inconel 718 using laser textured tool filled by the solid lubricant.

Ti6Al4V is a commonly used titanium alloy with several applications in aerospace industry due to its excellent strength to weight ratio. But due to low thermal conductivity, it is categorized as “difficult to machine.” Though machinability can be improved with cutting fluids, it is not preferred due to associated problems. This study aims at eliminating the use of cutting fluid and finding an alternate solution to dry machining of Ti6Al4V. AlTiN coated tools provide good heat and oxidation resistance but have low lubricity. In the present work, graphene, which is known for lubricating properties, is added to the tools using five different methods (tool condition) to form graphene self-lubricated cutting tools.

Graphene-based self-lubricating tools are prepared by using five methods: dip coating (10 dips and 30 dips); drop casting; and filling of micro/macroholes. Performance of these tools is evaluated in terms of cutting forces, surface roughness and tool wear by machining Ti6Al4V and comparing with conventional coated cutting tool.

Self-lubricating tool with micro holes filled with graphene outperformed other tools and showed maximum decrease of 33.42% in resultant cutting forces, 35% in surface roughness (Ra) and 30% in flank wear compared to conventional cutting tool.

Analysis of variance for all forces show that tool condition and machining time have significant influence on all components of cutting forces and resultant cutting forces.