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From an agency perspective, the authors investigate whether family ownership and control configurations are systematically associated with a firm's choice of auditor and audit fees. Agency theory is an economic theory that purposes the existence of a contract between two parties, principals and agents. Auditor choice and audit fees by family firms provide interesting insights given the unique nature of the agency problems faced by such firms.

The authors employ Big-4 auditors (PWC, KPMG, E&Y and Deloitte) as a proxy for high quality auditor (Big N) for the auditor choice model. For the audit fee model, the dependent variable is the natural logarithm of audit fees (LnAF). The authors use two measures for family firm as explanatory variables: (1) a dummy variable (FAM_Control), which equals one if the firm is classified as a family firm and (2) FAM_Ownership, which is an indicator variable with a value of one if a firm has family members who hold CEO position, occupy board seats, or hold at least 10% of the firm's equity. Data of Chinese listed firms from 2011 to 2021 are used. The authors adopt the Heckman (1979) two-stage model to mitigate the potential endogeneity issue involved in the selection of Big-N auditors.

The findings suggest that compared with non-family firms, Chinese family firms have a less tendency to employ Big-4 auditors due to less severe agency problems between owners and managers. Additionally, Chinese family firms sustain higher audit fees than non-family firms. Similar to the prior literature, however, Chinese family firms audited by Big-4 auditors incur lower audit fees than family firms audited by non-Big-4 auditors in this study. In contrast to young-family firms, old-family firms are less likely to pick top-tier auditors and sustain lower audit fees. Consistent and robust results are found from endogeneity tests and sensitivity analyses.

The empirical evidence provides a unique insight, for accounting practitioners, policymakers, family owners and other capital market participants concerning the diverse effects of various family ownership and control features on selecting high-quality auditors and audit fees. This study advances the understanding, showing that a lower demand for audit quality occurs in Chinese family firms as they encounter less severe Type I agency problems. However, the more severe Type II agency problems in Chinese family firms sustain higher audit fees due to higher audit risk and greater audit effort.

This work focused on the sulphonation modification research of highly crosslinking non-polarity macroporous adsorption resin (MAR) LX1180; the adsorption behaviour of LX1180 and its chloromethylation- and sulphonation-modified products (LX1180-Cl and LX1180-SO₃₋); and the influence of the structure parameters matching degree of MAR and flavonoids on the adsorption feature and adsorption kinetics.

LX1180-SO₃₋ was obtained by the processes of chloromethylation first and then sulphonation. LX1180-Cl and LX1180-SO₃₋ were prepared through the principle of substitution reaction from LX1180 and LX1180-Cl, respectively. First, Monochloromethyl ether (ME), pre-treated ZnCl₂, NaCl and iron powder were added into the swollen LX1180 to obtain the chloromethylated LX1180. Thereafter, NaCl, NaOH and SAA were added into the swollen LX1180-Cl to obtain the sulphonation modification LX1180. The conditions were investigated and optimised; the structures of LX1180-Cl and LX1180-SO₃₋ were characterised by Fourier transform infrared chromatography (FTIR) and a specific surface area instrument. Finally, the adsorption kinetics and adsorption isotherm were used to evaluate the adsorption capacity of LX1180-Cl and LX1180-SO₃₋ for flavonoids, and the adsorptions and desorptions of LX1180-SO₃₋ with different sulphonation degree on different flavonoids were investigated systemically.

Results showed that LX1180-Cl and LX1180-SO₃₋ had been prepared successfully, and that after the sulphonation, the adsorption capacity tended to increase with the increase of adsorption time, and the equilibrium adsorption capacity of LX1180-SO₃₋ was also higher than that of LX1180.

The research only investigated the adsorption and desorption properties for only one kind of functional group, and other functional groups should also be studied in future work.

This contribution can provide a further base for the research of separation and purification of natural products with the aim to improve food additive removal or isolation and purification of flavonoids used for healthcare applications.

The adsorptions and desorptions of LX1180-SO₃₋ with different sulphonation degree on different flavonoids were investigated. The relationship between sulphonation degree and the adsorption and desorption capacities of flavonoids were also explored, and the results showed that with the increase of sulphonation degree, the adsorption of LX1180-SO₃₋ to rutin and cyanidin was maximum, while the desorption ratio was minimum at the same sulphonation degree; this phenomenon could be ascribed to the variation in the polarity matching degree.

This study aims to examine the unique nature of family firms by investigating the moderating effect of chief executive officer (CEO) identity on CEO career horizon and the auditor’s client risk assessment. Consistent with literature on family businesses, the level of CEO attachment to socio-emotional wealth (SEW) varies among family businesses.

This study used a longitudinal sample of 2,063 non-financial family firm-year observations from 2005 to 2016 listed on the Bursa Malaysia. The study used the general method of moments (GMM), which controls for endogeneity concerns.

The results reveal that, without the moderating effect of CEO identity, the relationship between CEO career horizon and auditor’s risk assessment is positive, which suggests that the auditor’s risk perception of retiring CEOs is very high. However, the interaction of CEO identity reverses the relationship as evidenced by the negative and significant coefficient on the interacted terms. The finding suggests that the auditor’s perceived risk associated with CEO career horizon is lower in family firms with CEOs affiliated to family members or in which the CEO has an equity stake. Overall, the findings provide compelling evidence that the extent of the CEO’s attachment to the firm’s SEW affects the auditor’s client risk assessment.

The findings of the study serve as an enlightenment to policymakers such as Bursa Malaysia and Security Commission that within the family-controlled firms, differences still exist; therefore, there might be a need for future regulatory initiative to cater for the specific need of family-controlled firms.

The study contributes to prior literature by departing from the agency theory adopted in previous studies on auditor choice in family firms under the assumption that family firms are homogenous.

The purpose of this paper is to prepare a higher chloromethylation degree (CD) modified macroporous adsorption resin (MAR, LX1180-Cl) and further study their adsorption performance.

CD and crosslinking degree were evaluated using stationary potential step and rotating-disk method, the adsorption performance of LX1180-Cl and LX1180 for flavonoids were studied using the UV-VIS spectrophotometry.

This research realized high CD (9.6 mass %) on high crosslinking MAR, LX1180. In tandem, the adsorption performance of them to flavonoids finds that the matching degree of polarity (presented with CD) and size were the critical factor to adsorption. It was also found that the reaction time had reduced to 24 h with the addition of iron particles into the zinc chloride (ZnCl₂) catalyst.

The study on reaction mechanism and the function principle of hybrid catalyst were speculated, but not the rigid experimental result.

This contribution can provide a rule for the separation and purification of natural products with the aim to improve food additive removal or isolation and purification of flavonoids used for healthcare applications.

This contribution provided a novel way to obtain high degree of CD with high crosslinking MAR, CD of commercially available MAR was improved by 2.5 times to 9.6 percent under crosslinking degree at 58.2 percent, compared with reported CD value (ca. 4.2 percent under crosslinking degree at 20.0 percent), which will be useful in the following further systematically research about the adsorption and separation selectivity of MAR. Besides, the primitive chosen principle of MAR according to the substrate was also presented. Moreover, the chloromethylation mechanism, although speculative, was briefly presented, which will stimulate the related study.

The use of enterprise social media (ESM) can promote knowledge sharing within project teams. However, the potential mechanism of ESM affordances influencing knowledge sharing has not been fully studied. This paper aims to develop a theoretical model to explore how individual psychological cognition and environmental factors affect ESM affordances.

An empirical research using ESM applications was conducted in China, and 214 valid responses were collected for data analysis. Partial least squares structural equation modeling method was performed to test the theoretical model and hypotheses.

The results suggest the following implications: (1) the visibility, persistence, editability and association of ESM affordances all have a positive effect on the effectiveness of knowledge sharing in project teams. (2) The psychological safety and psychological empowerment of team members have a significant positive influence on ESM affordances. (3) The project task complexity positively moderates the positive effects which the visibility and association have on the effectiveness of knowledge sharing, and negatively moderates the positive relationship between the editability and knowledge sharing.

Based on the social cognitive theory, this paper highlights the roles of psychological cognitive factors and project task context in the effect of ESM affordances having on knowledge sharing within project teams. Moreover, it provides valuable suggestions for project managers in project and knowledge management.

Under the rural revitalization, the effect of China's implementation of rural prefabricated housing is not obvious. Cost has become the biggest obstacle to its development. Therefore, it is necessary to study the factors influencing the cost of prefabricated buildings in villages and clarify the focus of cost control.

This paper focuses on the whole process of prefabricated housing construction in villages in China and uses grounded theory to identify and screen out 27 related factors that affect the construction cost of prefabricated buildings. A system dynamics model is used to dynamically analyze the influencing factors. The engineering examples in rural areas of southern Shaanxi are simulated. Finally, five key factors that influence cost are obtained. Based on this, cost control countermeasures are proposed for rural prefabricated housing in southern Shaanxi.

The results show that: the key factors affecting the cost of prefabricated buildings in villages include the selection of production methods, the degree of design standardization, the quality of construction personnel, the level of construction technology and the circulation cycle of molds. The cost of prefabricated housing in villages can be controlled through five aspects: mass production of components, design exchange and feasibility analysis, improvement of employee professionalism, strict selection of construction schemes and technologies and improvement of mold turnover rate.

The system dynamics model applied in this paper is based on the idealized state. The system boundary is narrow and has a certain subjectivity. It needs further detailed research to make it closer to the engineering practice. In addition, this paper applies the rural engineering example in southern Shaanxi to carry out a single case study, and the universality of the research results needs to be further tested. There are many village construction projects and building types, so the research results can be further enriched through large sample research.

Rural construction is an important step in the implementation of rural revitalization. Exploring the factors that affect the key costs of prefabricated buildings in villages and towns in view of the particularity of rural areas will help provide a reference for their cost control and help the rural development of prefabricated houses.

The research results of this paper can provide a reference for the development of prefabricated buildings in other rural revitalization areas.

Different from the traditional research on urban prefabricated buildings, this paper focuses on rural areas and explores the core factors affecting the cost of prefabricated buildings from the micro level. This study establishes a system dynamics model suitable for the cost control of prefabricated housing at the village level and provides methods for its cost control. Based on the identified key factors affecting costs, cost control measures were proposed for prefabricated housing tailored to the unique characteristics of villages.

The purpose of this paper is to assess state-of-the-art techniques for quantifying flow distortion in the inlets of turbofan engines, particularly with respect to the prospects for future flight applications.

To adequately characterize the flow fields of complex aircraft inlet distortions, the author has incorporated laser velocimetry techniques, namely, stereoscopic particle image velocimetry (PIV) and Doppler velocimetry based on filtered Rayleigh scattering (FRS), into inlet distortion studies.

Overall, the results and experience indicate that the pathway for integration of FRS technologies into flight systems is clearer and more robust than that of PIV.

While always a concern, the topic of inlet distortion has grown in importance as contemporary airframe designers seek extremely compact and highly integrated inlets. This research offers a means for gaining new understanding of the in situ aerodynamic phenomena involved with complex inlet distortion.

This paper presents unique applications of turbofan inlet velocimetry methods while providing an original assessment of technological challenges involved with progressing advanced velocimetry techniques for flight measurements.

Crack detection of pavement is a critical task in the periodic survey. Efficient, effective and consistent tracking of the road conditions by identifying and locating crack contributes to establishing an appropriate road maintenance and repair strategy from the promptly informed managers but still remaining a significant challenge. This research seeks to propose practical solutions for targeting the automatic crack detection from images with efficient productivity and cost-effectiveness, thereby improving the pavement performance.

This research applies a novel deep learning method named TransUnet for crack detection, which is structured based on Transformer, combined with convolutional neural networks as encoder by leveraging a global self-attention mechanism to better extract features for enhancing automatic identification. Afterward, the detected cracks are used to quantify morphological features from five indicators, such as length, mean width, maximum width, area and ratio. Those analyses can provide valuable information for engineers to assess the pavement condition with efficient productivity.

In the training process, the TransUnet is fed by a crack dataset generated by the data augmentation with a resolution of 224 × 224 pixels. Subsequently, a test set containing 80 new images is used for crack detection task based on the best selected TransUnet with a learning rate of 0.01 and a batch size of 1, achieving an accuracy of 0.8927, a precision of 0.8813, a recall of 0.8904, an F1-measure and dice of 0.8813, and a Mean Intersection over Union of 0.8082, respectively. Comparisons with several state-of-the-art methods indicate that the developed approach in this research outperforms with greater efficiency and higher reliability.

The developed approach combines TransUnet with an integrated quantification algorithm for crack detection and quantification, performing excellently in terms of comparisons and evaluation metrics, which can provide solutions with potentially serving as the basis for an automated, cost-effective pavement condition assessment scheme.

On-orbit service technology is one of the key technologies of space manipulation activities such as spacecraft life extension, fault spacecraft capture, on-orbit debris removal and so on. It is known that the failure satellites, space debris and enemy spacecrafts in space are almost all non-cooperative targets. Relatively accurate pose estimation is critical to spatial operations, but also a recognized technical difficulty because of the undefined prior information of non-cooperative targets. With the rapid development of laser radar, the application of laser scanning equipment is increasing in the measurement of non-cooperative targets. It is necessary to research a new pose estimation method for non-cooperative targets based on 3D point cloud. The paper aims to discuss these issues.

In this paper, a method based on the inherent characteristics of a spacecraft is proposed for estimating the pose (position and attitude) of the spatial non-cooperative target. First, we need to preprocess the obtained point cloud to reduce noise and improve the quality of data. Second, according to the features of the satellite, a recognition system used for non-cooperative measurement is designed. The components which are common in the configuration of satellite are chosen as the recognized object. Finally, based on the identified object, the ICP algorithm is used to calculate the pose between two frames of point cloud in different times to finish pose estimation.

The new method enhances the matching speed and improves the accuracy of pose estimation compared with traditional methods by reducing the number of matching points. The recognition of components on non-cooperative spacecraft directly contributes to the space docking, on-orbit capture and relative navigation.

Limited to the measurement distance of the laser radar, this paper considers the pose estimation for non-cooperative spacecraft in the close range.

The pose estimation method for non-cooperative spacecraft in this paper is mainly applied to close proximity space operations such as final rendezvous phase of spacecraft or ultra-close approaching phase of target capture. The system can recognize components needed to be capture and provide the relative pose of non-cooperative spacecraft. The method in this paper is more robust compared with the traditional single component recognition method and overall matching method when scanning of laser radar is not complete or the components are blocked.

This paper introduces a new pose estimation method for non-cooperative spacecraft based on point cloud. The experimental results show that the proposed method can effectively identify the features of non-cooperative targets and track their position and attitude. The method is robust to the noise and greatly improves the speed of pose estimation while guarantee the accuracy.

Previous research concerning automatic extraction of research topics mostly used rule-based or topic modeling methods, which were challenged due to the limited rules, the interpretability issue and the heavy dependence on human judgment. This study aims to address these issues with the proposal of a new method that integrates machine learning models with linguistic features for the identification of research topics.

First, dependency relations were used to extract noun phrases from research article texts. Second, the extracted noun phrases were classified into topics and non-topics via machine learning models and linguistic and bibliometric features. Lastly, a trend analysis was performed to identify hot research topics, i.e. topics with increasing popularity.

The new method was experimented on a large dataset of COVID-19 research articles and achieved satisfactory results in terms of f-measures, accuracy and AUC values. Hot topics of COVID-19 research were also detected based on the classification results.

This study demonstrates that information retrieval methods can help researchers gain a better understanding of the latest trends in both COVID-19 and other research areas. The findings are significant to both researchers and policymakers.