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This paper aims to optimize cable-stayed force in asymmetric one-tower cable-stayed bridge formation using an improved particle swarm algorithm. It compares results with the traditional unconstrained minimum bending energy method.

This paper proposes an improved particle swarm algorithm to optimize cable-stayed force in bridge formation. It formulates a quadratic programming mathematical model considering the sum of bending energies of the main girder and bridge tower as the objective function. Constraints include displacements, stresses, cable-stayed force, and uniformity. The algorithm is applied to optimize the formation of an asymmetrical single-tower cable-stayed bridge, combining it with the finite element method.

The study’s findings reveal significant improvements over the minimum bending energy method. Results show that the structural displacement and internal force are within constraints, the maximum bending moment of the main girder decreases, resulting in smoother linear shape and more even internal force distribution. Additionally, the tower top offset decreases, and the bending moment change at the tower-beam junction is reduced. Moreover, diagonal cable force and cable force increase uniformly with cable length growth.

The improved particle swarm algorithm offers simplicity, effectiveness, and practicality in optimizing bridge-forming cable-staying force. It eliminates the need for arbitrary manual cable adjustments seen in traditional methods and effectively addresses the optimization challenge in asymmetric cable-stayed bridges.

This study aims to revisit the relationship between Shariah-compliant firms and earnings management. Specifically, the authors examine whether Shariah-certified firms have lower earnings management than non-Shariah-certified firms and how often a firm must hold its certification to observe considerably reduced earnings management. This study also explores how senior management ethnic dualism affects the association of Shariah certification and earnings management.

The authors analyze the hypothesized association between Shariah certification and earnings management using a panel regression model and several robustness tests, including the Heckman selection model. The sample consists of 547 nonfinancial firms listed on the Bursa Malaysia stock exchange, with 5,478 firm-year observations over the 2001–2016 sample period.

Shariah certification is found to mitigate earnings management, particularly for firms that consistently retain their Shariah status. The longer firms retain their Shariah certification continually, the lower the earnings management. Additionally, the results indicate that the negative impact of Shariah certification on earnings management is driven by ethnic duality when a specific ethnic group dominates the top management.

Firms’ commitment to religious-based screening and continuation of certification plays a significant role in improving earnings quality. Firms are committed to abiding by the Shariah code of conduct instead of using the Shariah status for reputation purposes to attract investors.

For investors, the continuous compliance status is a crucial indicator of a firm’s commitment to comply with Shariah principles and to mitigate earnings management. Regarding policy implications, Shariah-compliance guidelines can constrain earnings manipulation, especially among firms lacking ethnic diversity.

The study shows that Shariah certification must be maintained consecutively to reduce earnings management. Shariah certification’s governance function is crucial in ethnically homogeneous firms, primarily when one ethnic group dominates the senior management.

The diagnosis and prediction methods used for estimating the health conditions of the bearing are of great significance in modern petrochemical industries. This paper aims to discuss the accuracy and stability of improved empirical mode decomposition (EMD) algorithm in bearing fault diagnosis.

This paper adopts the improved adaptive complementary ensemble empirical mode decomposition (ICEEMD) to process the nonlinear and nonstationary signals. Two data sets including a multistage centrifugal fan data set from the laboratory and a motor bearing data set from the Case Western Reserve University are used to perform experiments. Furthermore, the proposed fault diagnosis method, combined with intelligent methods, is evaluated by using two data sets. The proposed method achieved accuracies of 99.62% and 99.17%. Through the experiment of two data, it can be seen that the proposed algorithm has excellent performance in the accuracy and stability of diagnosis.

According to the review papers, as one of the effective decomposition methods to deal with nonlinear nonstationary signals, the method based on EMD has been widely used in bearing fault diagnosis. However, EMD is often used to figure out the nonlinear nonstationarity of fault data, but the traditional EMD is prone to modal confusion, and the white noise in signal reconstruction is difficult to eliminate.

In this paper only the top three optimal intrinsic mode functions (IMFs) are selected, but IMFs with less correlation cannot completely deny their value. Considering the actual working conditions of petrochemical units, the feasibility of this method in compound fault diagnosis needs to be studied.

Different from traditional methods, ICEEMD not only does not need human intervention and setting but also improves the extraction efficiency of feature information. Then, it is combined with a data-driven approach to complete the data preprocessing, and further carries out the fault identification and classification with the optimized convolutional neural network.

Given the scarcity of studies regarding religious food as a destination attraction and limited research on tourist halal food experience, this study aims to explore and compare halal food experience perceived by Muslim and non-Muslim tourists in a non-Islamic destination.

This study was carried out in a halal food street in Yuanjia Village, China. It used a qualitative approach and interviewed 16 Muslim tourists and 20 non-Muslim tourists.

Six themes and 18 attributes of halal food experience were identified. The findings revealed that Muslim tourists saw the reassuring options and religious value of halal food as important experiences. By contrast, the experiences of abundant choices, value for money, sensory pleasure and unique charm were frequently mentioned by non-Muslim tourists. The nature of halal food, the context of China (i.e. Chinese halal food culture) and the feature of research site (i.e. food operation of Yuanjia Village) work together to create such experiences.

To the best of the authors’ knowledge, this is one of the first studies to explore and compare halal food experiences of Muslim and non-Muslim tourists in a non-Islamic country (China). This study suggests that halal food could be an appealing destination attraction, even in non-Islamic destinations. Thus, this study contributes to a better understanding of the halal food experiences and assists destination marketers in promoting halal food.

Smart farming technologies (SFTs) can increase yields and reduce the environmental impacts of farming by improving the efficient use of inputs. This paper is to estimate farmers' preference and willingness to pay (WTP) for a well-defined SFT, smart drip irrigation (SDI) technology.

This study conducted a discrete choice experiment (DCE) among 1,300 maize farmers in North China to understand their WTP for various functions of SDI using mixed logit (MIXL) models.

The results show that farmers have a strong preference for SDI in general and its specific functions of smart sensing and smart control. However, farmers do not have a preference for the function of region-level agronomic planning. Farmers' preferences for different functions of SDI are heterogeneous. Their preference was significantly associated with their education, experience of being village cadres and using computers, household income and holding of land and machines. Further analysis show that farmers' WTP for functions facilitated by hardware is close to the estimated prices, whereas their WTP for functions wholly or partially facilitated by software is substantially lower than the estimated prices.

Findings from the empirical study lead to policy implications for enhancing the design of SFTs by integrating software and hardware and optimizing agricultural extension strategies for SFTs with digital techniques such as videos.

This study provides initial insights into understanding farmers' preferences and WTP for specific functions of SFTs with a DCE.

This paper aims to explore the impact of enterprise niche on dual innovation performance and the moderating role of innovation openness on the relationship between enterprise niche and dual innovation performance.

This study uses the panel data of the enterprise technology patents of China's Top 100 Electronic Information Enterprises from 2009 to 2018. Multiple regression analyses were used to test the hypotheses.

Niche width has a significant positive impact on exploitative and exploratory innovation performance. Niche overlap has an inverted U-shaped effect on exploitative innovation performance and significantly positively affects exploratory innovation performance. Innovation openness negatively moderates the impact of niche width on exploitative innovation performance and positively moderates the impact of niche overlap on exploitative innovation performance.

This study provides new insights into the effects of enterprise niche on dual innovation performance by showing the moderating role of innovation openness. The study finds a strategic logic of moderate niche overlap, clarifies the innovative effect of different innovation openness modes and reveals the construction and management mechanisms of enterprise niche and innovation openness strategy.

Sustainable urban rail transit requires noise barriers. However, these barriers’ durability varies due to the differing aerodynamic impacts they experience. The purpose of this paper is to investigate the aerodynamic discrepancies of trains when they meet within two types of rectangular noise barriers: fully enclosed (FERNB) and semi-enclosed with vertical plates (SERNBVB). The research also considers the sensitivity of the scale ratio in these scenarios.

A 1:16 scaled moving model test analyzed spatiotemporal patterns and discrepancies in aerodynamic pressures during train meetings. Three-dimensional computational fluid dynamics models, with scale ratios of 1:1, 1:8 and 1:16, used the improved delayed detached eddy simulation turbulence model and slip grid technique. Comparing scale ratios on aerodynamic pressure discrepancies between the two types of noise barriers and revealing the flow field mechanism were done. The goal is to establish the relationship between aerodynamic pressure at scale and in full scale.

The aerodynamic pressure on SERNBVB is influenced by the train’s head and tail waves, whereas for FERNB, it is affected by pressure wave and head-tail waves. Notably, SERNBVB's aerodynamic pressure is more sensitive to changes in scale ratio. As the scale ratio decreases, the aerodynamic pressure on the noise barrier gradually increases.

A train-meeting moving model test is conducted within the noise barrier. Comparison of aerodynamic discrepancies during train meets between two types of rectangular noise barriers and the relationship between the scale and the full scale are established considering the modeling scale ratio.

This study aims to improve the offshore wind farm (OWF) site selection evaluation index system and establishes a decision-making model for OWF site selection. It is expected to provide helpful references for the progress of offshore wind power.

Firstly, this paper establishes an evaluation criteria system for OWF site selection, considering six criteria (wind resource, environment, economic, technical, social and risk) and related subcriteria. Then, the Criteria Importance Though Intercrieria Correlation (CRITIC) method is introduced to figure out the weights of evaluation indexes. In addition, the cumulative prospect theory and technique for order preference by similarity to an ideal solution (CPT-TOPSIS) method are employed to construct the OWF site selection decision-making model. Finally, taking the OWF site selection in China as an example, the effectiveness and robustness of the framework are verified by sensitivity analysis and comparative analysis.

This study establishes the OWF site selection evaluation system and constructs a decision-making model under the spherical fuzzy environment. A case of China is employed to verify the effectiveness and feasibility of the model.

In this paper, a new decision-making model is proposed for the first time, considering the ambiguity and uncertainty of information and the risk attitudes of decision-makers (DMs) in the decision-making process.

This study aims to investigate whether there is a relationship between the religiosity levels of chairpersons’ hometowns and the financial reporting quality of companies.

Using a unique hand-collected data set obtained from various sources, the authors use ordinary least squares and logistic regressions to test the hypotheses and further implement various methods to address potential issues such as omitted variables, reverse causality and selection bias problems. In addition, the authors control for the religiosity level of chief executive officers’ (CEOs) hometowns. Finally, the authors divide the sample into two subsamples – companies with strong corporate governance and companies with weak corporate governance – to investigate the effect of chairpersons’ hometown religiosity on financial reporting quality under strong or weak corporate governance.

The findings demonstrate that companies with chairpersons from religious hometowns produce high-quality financial reports. Additional tests, such as the Heckman selection model and instrument variable regression, confirm the robustness of the main results. Controlling for the religiosity level of the CEO’s hometown yields consistent findings with the main results. Finally, additional results indicate that the religiosity levels of chairpersons’ hometowns play a significant role in enhancing financial reporting quality in companies with weak corporate governance.

Companies should consider appointing board members or chairpersons from more religious hometowns, as the empirical results of this study support the positive effects of chairpersons’ hometown religiosity on financial reporting quality.

To the best of the authors’ knowledge, the current study is among the first to demonstrate the relationship between the religiosity level of the chairpersons’ hometown and the financial reporting quality of companies. The study introduces unique hometown religiosity proxies and controls for various variables related to corporate governance, chairperson attributes, company characteristics, and audit firm characteristics.

The paper aims to examine the digital economy's influence on China's regional innovation and development. It focuses on direct effects and spatial spillover across regions, and the mediating role of human capital. This analysis is vital for policy and strategic planning in the digital era.

This study uses panel data from 30 Chinese provinces (2004–2019) and uses the entropy method to quantify the digital economy's development. It investigates its impact on regional innovation using a dynamic spatial Durbin model (SDM) and mediation effect model, assessing direct effects, spatial spillover and human capital's mediating role. Various control variables are included for comprehensive analysis.

Findings show the digital economy significantly boosts regional innovation, acting as a growth driver. However, impacts vary regionally, with the central region gaining more than the eastern and western areas. Spatial spillover effects are mixed, showing negative short-term and positive long-term impacts under different weight matrices. Human capital is crucial for fostering innovation through the digital economy.

The paper offers unique insights into the spatial dynamics of the digital economy's impact on regional innovation in China. It advances understanding of the digital economy's role in regional development using innovative methods like the entropy method and dynamic SDM. Highlighting human capital as a key mediating factor enriches discussions on digital economy strategies for regional innovation.