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This study aims to investigate whether gender diversity in audit committees affects the purchase of nonaudit services in China. Results from family and nonfamily firms are compared and the critical mass participation of females are further examined.

The sample comprises 1,834 Chinese listed companies from 2012 to 2021, among which 910 are family firms. The Heckman (1979) two-stage model is used to mitigate the potential endogeneity issue in the selection of gender diversity. Propensity score matching is also used to further alleviate the endogeneity problem in relation to family firms.

Results show a significant and negative correlation between the gender diversity in audit committees and nonaudit service fees. This association is more apparent in nonfamily than in family firms. Findings are consistent and robust to endogeneity tests and sensitivity analyses. The analysis of critical mass and symbolic participation shows that three female directors can more significantly restrain nonaudit fees than one to two females on the board.

This study contributes to literature on resource dependence theory, which posits that audit committees help enterprises establish contact with auditors, improve the company legitimacy, assist in communication and provide relevant expertise. This study also relates to agency theory, which holds that differences in the severity of types I and II agency problems between family and nonfamily firms lead to differences in auditor selection and related costs.

Extending from previous research on the relation between the gender diversity in audit committees and nonaudit fees, the present study delves into this connection within the context of China, an emerging economy. As a result, this investigation offers novel insights and expands upon current knowledge. In addition, the correlation between the gender diversity of audit committees and nonaudit fees is explored for family and nonfamily firms.

The purpose of this paper is to analyze the bird impact damage of fuselage composite stiffened structures by numerical method and to evaluate the damage and the bird impact resistance of different structures.

The deformation and damage of composite stiffened plates during bird impact are numerically analyzed by the explicit finite element software LS-DYNA. A comparative study on the numerical calculation results was conducted by using SPH (Smoothed Particle Hydrodynamics)-FEM (Finite Element Method) modeling and simulation. First, the I-shaped, T-shaped, straight stiffened plates and unstiffened plate were designed. Second, the accuracy of the bird model was verified and further used to evaluate bird strikes on composite stiffened plate. Third, the results of damage modes as well as displacements of the stiffened plates were compared.

The stiffeners can increase the local stiffness of the composite panel, which can effectively inhibit the bird’s movement along the impact direction. Adding stiffeners can change the panel matrix tension damage from global distribution to local distribution mode; however, the impact damage distribution and the ability to inhibit damage propagation can differ for different stiffened panels. Especially, the I-stiffened panel exhibits a better anti-bird strike performance.

The analysis of geometric parameters of structural components by numerical methods can reduce the cost of the design phase and has been widely used in aircraft design. The present study evaluated the bird impact damage of composite stiffened plates with different structures, which provides a guideline for selecting the stiffened plate structure in the fuselage skin.

In the post-pandemic era urban ecosystem planning has become critically important. Given the emphasis on relevant issues concerning the complex interactions between human civilizations and natural systems within urban environments in the new normal, this article aims to enrich the field of knowledge management developing a cross-cultural analysis for clarifying the role of knowledge in planning and urban ecosystems.

This paper is conceptual in nature. Based on a theoretical foundation built by a critical literature review and data from the China Statistical Yearbook and China’s National Bureau of Statistics, this paper introduces some emerging real-impact topics regarding the connections between humanistic knowledge and urban planning. A comparative analysis between the capital city of Chang’an in the Tang dynasty of China and the capital city of Athens in Ancient Greek was used for explaining the influence of knowledge on successful urban planning.

The understanding the role of cross-cultural differences in knowledge management and practices for urban ecosystems offer the opportunities for rethinking consolidated approach to the interaction among social, economic, and environmental dimensions in urban settings.

This paper implies a new inter-disciplinary research field of great interest for the real impact KM community by illuminating how knowledge management is central in urban planning and across cultures.

With the rapid development of railway-intelligent video technology, scene understanding is becoming more and more important. Semantic segmentation is a major part of scene understanding. There is an urgent need for an algorithm with high accuracy and real-time to meet the current railway requirements for railway identification. In response to this demand, this paper aims to explore a variety of models, accurately locate and segment important railway signs based on the improved SegNeXt algorithm, supplement the railway safety protection system and improve the intelligent level of railway safety protection.

This paper studies the performance of existing models on RailSem19 and explores the defects of each model through performance so as to further explore an algorithm model dedicated to railway semantic segmentation. In this paper, the authors explore the optimal solution of SegNeXt model for railway scenes and achieve the purpose of this paper by improving the encoder and decoder structure.

This paper proposes an improved SegNeXt algorithm: first, it explores the performance of various models on railways, studies the problems of semantic segmentation on railways and then analyzes the specific problems. On the basis of retaining the original excellent MSCAN encoder of SegNeXt, multiscale information fusion is used to further extract detailed features such as multihead attention and mask, solving the problem of inaccurate segmentation of current objects by the original SegNeXt algorithm. The improved algorithm is of great significance for the segmentation and recognition of railway signs.

The model constructed in this paper has advantages in the feature segmentation of distant small objects, but it still has the problem of segmentation fracture for the railway, which is not completely segmented. In addition, in the throat area, due to the complexity of the railway, the segmentation results are not accurate.

The identification and segmentation of railway signs based on the improved SegNeXt algorithm in this paper is of great significance for the understanding of existing railway scenes, which can greatly improve the classification and recognition ability of railway small object features and can greatly improve the degree of railway security.

This article introduces an enhanced version of the SegNeXt algorithm, which aims to improve the accuracy of semantic segmentation on railways. The study begins by investigating the performance of different models in railway scenarios and identifying the challenges associated with semantic segmentation on this particular domain. To address these challenges, the proposed approach builds upon the strong foundation of the original SegNeXt algorithm, leveraging techniques such as multi-scale information fusion, multi-head attention, and masking to extract finer details and enhance feature representation. By doing so, the improved algorithm effectively resolves the issue of inaccurate object segmentation encountered in the original SegNeXt algorithm. This advancement holds significant importance for the accurate recognition and segmentation of railway signage.

This paper aims to examine the relationship between environmental, social and governance (ESG) performance and systemic risk sensitivity of Chinese listed companies. From the consumer loyalty and investor structure perspectives, the relationship between ESG performance and systemic risk sensitivity is analyzed.

Since Morgan Stanley Capital International (MSCI) ESG officially began to analyze and track China A-shares from 2018, 275 listed companies in the SynTao Green ESG testing list for 2015–2021 are selected as the initial model. To measure the systematic risk sensitivity, this study uses the beta coefficient, from capital asset pricing model (CPAM), employing statistics and data (STATA) software.

The study reveals that high ESG rating companies have high corresponding consumer loyalty and healthy trading structure of institutional investors, thereby the systemic risk sensitivity is lower. This paper reveals that companies with high ESG rating are significantly less sensitive to systemic risk than those with low ESG rating. At the same time, ESG has a weaker impact on the systemic risk of high-cap companies than low-cap companies.

The study helps the companies understand the influence of market value on the relationship between ESG performance and systemic risk sensitivity. Moreover, this paper explains explicitly why ESG performance insulates a firm’s stock from market downturns with the lens of consumer loyalty theory and investor structure theory.

The paper provides new insights on the company’s ESG performance that significantly affects the company’s systemic risk sensitivity.

This paper aims to present a method to measure the rolling friction coefficient in an easy and fast way. The aim is also to measure the rolling friction coefficient between a small steel ball and a cylindrical aluminum surface.

An analytical model of the tribosystem of a freely rolling ball and a cylindrical surface is established. The rolling friction coefficient is evaluated from images recorded by a high-speed camera. The coefficient between a 1.58-mm diameter steel ball and a cylindrical aluminum surface is measured. A background subtraction algorithm is used to determine the position of the small steel ball.

The angular positions of the ball are predicted using the analytical model, and a good agreement is found between the experimental and theoretical results.

An optical method for evaluating the rolling friction coefficient is presented, and the value of this coefficient between a small steel ball and a cylindrical aluminum surface is evaluated.

To solve several “inorganic” problems generated recently by community development in China (e.g., waste of social resources, environmental pollution, and decreased economic energy efficiency), focus should be on improving the community traffic organic micro-circulation system. As a historic and mixed functional urban community, the micro-circulation system of Xi'an Railway Bureau exhibits representativeness and complexity. Based on existing research results and years of follow-up investigations, which concentrate on circulation patterns and inherent organic development requirements of the community traffic micro-circulation system, this paper builds an evaluation index system. Value function method was used to implement the index factor quantitative analysis and comprehensive evaluation. Several related strategies were proposed to improve the organic micro-circulation system of the community, which is based on the analysis of the evaluation, in order to adopt the trend in both increasing urban development and stock updating. The analysis results demonstrate that it is necessary to present guiding renewal strategies on community land, road, people, and the environment for those mixed functional communities which use progressive renewed mode. It compensates the problems of overly strong export-oriented system, which is caused by the lack of organic traffic micro-circulation, so as to achieve the selective opening of community external. The study mainly highlights the significance of the systematic analysis of evaluation in influencing strategies on community renewal.

From the atom economy and environmentally friendly point of views, the development of clean and green approaches using ionic liquids (ILs) as recyclable catalysts has attracted increasing attention. The purpose of this study is to investigate the effect of task-specific ILs content on the one-pot three-component Biginelli reaction.

A series of halogen-free quaternary ammonium ILs functionalized with –SO₃H group were prepared and characterized by ¹H nuclear magnetic resonance (NMR), ¹³C NMR and electrospray ionization mass spectrometry. The ILs were used as catalysts for Biginelli reaction among aromatic aldehydes, urea or thiourea and β-dicarbonyl compounds. Anions and cations of ILs were varied to observe their effects on and contributions to the catalysts. The influencing factors, such as the amount of catalyst, solvent, reaction time and reaction temperature, were investigated.

The effect and contribution of cations of ILs were observed. Results showed that 3-(N, N-dimethylhexadecylammonium) propanesulfonic acid toluene sulfate ([DHPA][Tos]) showed comparable catalytic activity. Good adaptability to the reaction substrate and maximum product yield was observed when [DHPA][Tos] was used as catalyst. It was found that Biginelli reaction catalyzed by 10 mol% [DHPA][Tos] for 3 h under solvent-free conditions at 80 °C gave the best yield of 94%. Post-processing steps were simple, and the catalyst could be reused easily.

This paper demonstrates that ILs containing a long carbon chain and a bulky Tos anion efficiently promoted the reaction, in which the long carbon chains facilitate mass transfer in the reaction system.

This study is aimed to measure the intertemporal financial efficiency of 16 emerging economy countries (BRICS and N-11) and further to investigate the mechanisms of financial development on energy efficiency covering the period 2008–2020.

The dynamic data envelopment analysis model is used to measure financial efficiency dynamically. The generalized method of moments is used to investigate the effects of financial efficiency on energy efficiency. In the proposed approach, energy efficiency is the dependent variable, whereas financial efficiency, GDP per capita, industrial structure upgrade index, urbanization level and export trade structure are the regressors. Generalized moment estimation is performed.

There is heterogeneity in the level of financial development at different stages of economic development. The impact of financial efficiency on energy efficiency is related to the type of industries to which financial institutions are allocated. With the financial development of emerging economies, enterprises in technology-intensive industries are becoming the main contributors to higher profits for financial institutions, the products and results of these enterprises reduce energy consumption and increase energy efficiency. In addition, residents with rising levels of wealth holdings prefer low-carbon and environmentally friendly products, which indirectly improves energy efficiency. Per capita GDP and urbanization have no significant impact on the energy efficiency of emerging economies. The optimization and upgrading of the industrial structure of emerging economies has played a role in promoting energy efficiency. The export trade structure has a restraining effect on energy efficiency.

The findings contribute value by supporting a positive link between Financial Development and Energy Efficiency in the emerging economies. Enterprises in technology-intensive industries have gradually become the main force that brings higher profits to financial institutions. The products and achievements of these enterprises will reduce energy consumption and improve energy efficiency. The findings of this study provide emerging economies with an objective view of their financial development and energy efficiency, while also providing governments and policymakers with ways to improve energy efficiency and achieve sustainable development.

This study aims to assess financial development and debt status impact on energy efficiency in Nigeria as a developing economy.

This study combined the autoregressive distributed lag (ARDL), fully modified ordinary least squares and canonical cointegration regression analytical methods to estimate the parameters for energy efficiency policy recommendations. Secondary data between 1990 and 2020 were used for the analysis.

The result confirms the long-run nexus between energy efficiency, financial development and total debt stock. Furthermore, the ARDL estimates for this study’s key variables show that financial development promotes energy efficiency in the short run but hinders long-run energy efficiency. Total debt stock limits energy efficiency in Nigeria in short- and long-run periods.

The limitation of this study is that the scope is limited to Nigeria as a developing economy. The need to support energy efficiency projects is a global call requiring cross-country analysis. Despite this study’s focus on Nigeria, it provides useful insights that can guide energy efficiency policy through the financial sector and debt management.

The financial sector must ensure the availability of long-term credit facilities to clean energy investors. The government must maintain a sustainable debt profile to pave the way for capital expenditure on clean energy projects that promote energy efficiency.

The environmental consequences of energy intensity are being felt globally, with the developing countries most vulnerable. The cheapest way to curb these consequences is to promote energy efficiency to reduce the disastrous effect. Driving energy efficiency requires investment in energy-efficient technology but the challenge for developing economies, i.e. Nigeria’s funding, remains challenging amid a blotted debt profile. This becomes crucial to investigate how financial sector development and debt management can accelerate energy-efficient investments in Nigeria.