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This paper aims to develop resonant vibratory gyroscopes for high sensitive detection. The dynamic characteristics of resonant vibratory gyroscopes are investigated.

Firstly, the working principle and the dynamic output characteristics of the resonant vibratory gyroscope could be described by the damped Mathieu equation. Moreover, an approximate analytical method based on the small parameter perturbation has been used for the purpose of investigating the approximate solution of the damped Mathieu equation. Finally, to verify the feasibility of the approximate analytical method of the damped Mathieu equation, dynamic output characteristics’ experiments of the resonant vibratory gyroscope are built.

The theoretical analysis and numerical simulations show that the approximate solution of the damped Mathieu equation is close to the dynamic output characteristics of the resonant vibratory gyroscope. On the other hand, it is concluded from the tested result that there exists a correlation between the theoretical curve and the experimental data processing result, meaning the damped dynamics analytical method is effective in building resonant vibratory gyroscopes.

This paper seeks to establish a foundation for optimizing and testing the performance of the resonant vibratory gyroscope. To this end, the approximate analytical method of the damped Mathieu equation was discussed. The result of this research has proved that the dynamic characteristics based on the damped Mathieu equation is an effective approach and is instructional in the practical resonant sensor design.

This study aims to ensure the operation safety of high speed trains, it is necessary to carry out nondestructive monitoring of the tensile damage of the gearbox housing material in rail time, yet the traditional tests of mechanical property can hardly meet this requirement.

In this study the acoustic emission (AE) technology is applied in the tensile tests of the gearbox housing material of an high-speed rail (HSR) train, during which the acoustic signatures are acquired for parameter analysis. Afterward, the support vector machine (SVM) classifier is introduced to identify and classify the characteristic parameters extracted, on which basis the SVM is improved and the weighted support vector machine (WSVM) method is applied to effectively reduce the misidentification of the SVM classifier. Through the study of the law of relations between the characteristic values and the tensile life, a degradation model of the gearbox housing material amid tensile is built.

The results show that the growth rate of the logarithmic hit count of AE signals and that of logarithmic amplitude can well characterize the stage of the material tensile process, and the WSVM method can improve the classification accuracy of the imbalanced data to above 94%. The degradation model built can identify the damage occurred to the HSR gearbox housing material amid the tensile process and predict the service life remains.

The results of this study provide new concepts for the life prediction of tensile samples, and more further tests should be conducted to verify the conclusion of this research.

This study empirically examines the curvilinear relationship between top management team task-related demographic faultlines and over-investment, as well as how biodemographic faultlines and industrial environment moderate the curvilinear relationship between task-related demographic faultlines and over-investment.

The study designs the panel data from the listed companies of China's growth enterprises board (GEB) (set up by Shenzhen Stock Exchange in 2009) in the period 2011–2016 and uses hierarchical regression analysis and grouping regression analysis in exploring the curvilinear relationship with the variables involved.

The study provides empirical insights into the relationship on top management team (TMT) task-related demographic faultlines and over-investment, as well as how biodemographic faultlines and industrial environment moderate the relationship between task-related demographic faultlines and over-investment. It suggests that the relationship between task-related demographic faultlines and over-investment is significantly inverted-U. Furthermore, biodemographic faultlines and industrial environment can strengthen the inverted-U relationship between TMT task-related demographic faultlines and over-investment.

The study investigates the influence of task-related demographic faultlines on firm over-investment. The sample is restricted to the listed companies on GEM in China and limited in size. It is also not concerned with the cross-culture contrastive analysis between the Chinese- and Western-listed companies.

The findings suggest that strong/weak TMT task-related demographic faultlines is beneficial in promoting rational investment, but medium TMT task-related demographic faultlines may lead to over-investment.

The study within the crossed-categorization theory, the study provides a contemporary research path by moderating biodemographic faultlines and industrial environments to explain the long-ignored impact of TMT faultlines within a new perspective of firm investment efficiency with a recent significant sample of new emerging countries (e.g. China).

This paper aims to investigate the effect of artificial intelligence (AI)-enabled checkouts on consumers’ purchase intent and evaluations of the retailing atmosphere. It also offers novel findings pertaining to the mediating role of arousal and moderation by innovativeness importance on consumers’ responses toward AI-enabled checkouts.

Three pilot studies, two field studies and one online experiment featuring 1,567 respondents were conducted by manipulating checkout methods.

AI-enabled checkouts lead to a higher level of arousal, which, in turn, yields more favorable store atmosphere evaluations and higher purchase intent. Furthermore, the positive effect of AI-enabled checkouts is moderated by consumers’ innovativeness importance.

This research contributes to the emerging body of AI research and demonstrates a novel perspective by illuminating that under certain circumstances, AI-enabled checkouts lead to more positive outcomes relating to store atmosphere evaluations and purchase intent, as well as the unintended effect of heightened arousal.

This study shows how marketers and practitioners can promote consumers’ evaluations and patronage likelihood effectively by harnessing AI-enabled checkouts for those who consider innovativeness as important.

This research documents the novel findings of how and when AI-enabled checkouts garner more favorable consumer responses.

The purpose of this paper is to examine the factors (including conservation payments) that influence household decisions to participate in off-farm work and estimate the impact of participation on household welfare under the auspices of the Grain for Green (GfG) program.

The authors used survey data from 225 farm households on the Loess Plateau and addressed the possible sample selection and endogeneity problems by employing a jointly estimated endogenous switching regression (ESR) model.

The findings of this paper are as follows: off-farm participation is positively related to households’ educational attainment and negatively related to their land resource endowment and the presence of children; participation in off-farm work exerts positive effects on household income and per capita household income, but negative effects on farm productivity; and conservation payments show no significant impact on off-farm participation, no significant impact on any of the three household welfare indicators for off-farm non-participant households, but a significantly negative impact for off-farm participant households.

This paper makes two contributions. First, the authors address the selection bias and endogeneity problem of GfG participating households by employing the ESR method and explicitly estimating the treatment effects of off-farm participation on their household welfare. Neglecting these problems leads to biased estimates and misleading policy implications. Second, this analysis stresses the important role of government in reducing market or institutional failure and other barriers that impede farmers’ efficient allocation choices instead of compensating households for conserving sloping land, shedding new light on the most effective policy options to achieve the program’s goals.

This paper aims to reveal the influence of the presentation of online product information (POPI) on consumer attitudes in the context of online buying digital products.

Two main experimental designs are used to collect data. The ANOVA, t-test and Bootstrap methods are applied to check hypotheses.

Findings of Study 1 indicate that if the POPI is combined with different types of celebrity endorsement (CE) (real vs virtual), the self-brand connection will be changed and further influence consumer attitudes toward digital products. Study 2 verifies the diverse moderating effects of the type of virtual CE. The CRP (central-route presentation) online product information with SVCE (super-realistic-digital virtual CE) can decrease consumer attitudes, while the PRP (peripheral-route presentation) online product information with AVCE (anthropomorphic virtual CE) can enhance consumer attitudes.

E-commerce enterprises should optimize the current layout of POPI by considering diverse matchings between POPI and CE to increase consumer attitudes. Moreover, marketers could make various schemes of POPI considering (virtual) CE and self-brand connection.

Findings contribute to understanding the relationship between POPI and consumer attitudes considering the mediation of self-brand connection and the mediations of virtual/real CE. Additionally, this study bridges the gap between research on virtual CE and business practices.

The aim of this paper is to solve the toxic and harmful problems caused by traditional volatile corrosion inhibitor (VCI) and to analyze the effect of the layered structure on the enhancement of the volatile corrosion inhibition prevention performance of amino acids.

The carbon dots-montmorillonite (DMT) hybrid material is prepared via hydrothermal process. The effect of the DMT-modified alanine as VCI for mild steel is investigated by volatile inhibition sieve test, volatile corrosion inhibition ability test, electrochemical measurement and surface analysis technology. It demonstrates that the DMT hybrid materials can improve the ability of alanine to protect mild steel against atmospheric corrosion effectively. The presence of carbon dots enlarges the interlamellar spacing of montmorillonite and allows better dispersion of alanine. The DMT-modified alanine has higher volatilization ability and an excellent corrosion inhibition of 85.3% for mild steel.

The DMT hybrid material provides a good template for the distribution of VCI, which can effectively improve the vapor-phase antirust property of VCI.

The increased volatilization rate also means increased VCI consumption and higher costs.

Provides a new way of thinking to replace the traditional toxic and harmful VCI.

For the first time, amino acids are combined with nano laminar structures, which are used to solve the problem of difficult volatilization of amino acids.

The purpose of this study was to determine the effects of chickpea (Cicer arietinum) protein hydrolysates prepared at two degrees of hydrolysis (DH) on lipoprotein profile and on oxidant status in cholesterol-fed rats.

Eighteen male Wistar rats (220 ± 10 g) were divided into three groups and fed for 30 days a diet containing 20 per cent casein supplemented with 1 per cent cholesterol and 0.5 per cent cholic acid. During the experimentation, the first and the second groups received daily by gavage 250 mg of chickpea protein hydrolysates/rat at DH = 8 per cent (CPH8) and DH = 17 per cent (CPH17), respectively. The third group, named control group (CG), received water under the same conditions.

Serum total cholesterol concentrations were reduced in CPH8 (p < 0.0073) and CPH17 (p < 0.0004) groups versus CG. This reduction corresponded to a lower very-low-density lipoprotein (VLDL)-cholesterol (p < 0,0019). CPH17 reduced low-density lipoprotein- and high-density lipoprotein (HDL)-cholesterol (p < 0.0001) but increased apolipoprotein A4 (p < 0.002) concentrations and lecithin-cholesterol acyltransferase activity (p < 0.0001). APOA1 remained unchanged in the treated groups. Liver total and esterified cholesterol contents were twofold lower in both treated groups versus CG. CPH8 increased triacylglycerols and phospholipids (p < 0.0001) contents, while CPH17 decreased those of unesterified cholesterol (p < 0.0016). Compared with CG, CPH8 and CPH17 reduced serum (p < 0.0001) and lipoprotein hydroperoxides by stimulating paraoxonase activity (p < 0.0001). However, only CPH17 treatment reduced serum, VLDL- and HDL-malondialdehyde contents and improved glutathione peroxidase activity (p < 0.061).

Thus, chickpea protein hydrolysates and especially hydrolysed at DH = 17 per cent may have a great potential for use as a nutraceutical to reduce hypercholesterolaemia and, by consequence, oxidative stress. Therefore, the degree of enzymatic hydrolysis has a significant influence on the production of potent bioactive peptides.

This study explores how chatbot gender and symbolic service recovery may improve the satisfaction of angry customers in the context of service failures. It provides a strategy for companies to deploy chatbots effectively in customer anger.

This research relies upon a systematic literature review to propose three hypotheses, and we recruit 826 participants to examine the effect of chatbot gender on angry customers through one lab study and one field study.

This research shows that female chatbots are more likely to increase the satisfaction of angry customers than male chatbots in service failure scenarios. In addition, symbolic recovery (apology vs. appreciation) moderates the effect of chatbot gender on angry customers. Specifically, male (vs. female) chatbots are more effective in increasing the satisfaction of angry customers when using the apology method, whereas female (vs. male) chatbots are more effective when using the appreciation method.

The rapid advancements in artificial intelligence technology have significantly enhanced the effectiveness of chatbots as virtual agents in the field of interactive marketing. Previous research has concluded that chatbots can reduce negative customer feedback following a service failure. However, these studies have primarily focused on the level of chatbot anthropomorphism and the design of conversational texts, rather than the gender of chatbots. Therefore, this study aims to bridge that gap by examining the effect of chatbot gender on customer feedback, specifically focusing on angry customers following service failures.