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This study aims to better understand the morphological characteristics of single particle and the health risk characteristics of heavy metals in PM_2.5 in different functional areas of Handan City.

High resolution transmission electron microscopy was used to observe the aerosol samples collected from different functional areas of Handan City. The morphology and size distribution of the particles collected on hazy and clear days were compared. The health risk evaluation model was applied to evaluate the hazardous effects of particles on human health in different functional areas on hazy days.

The results show that the particulate matter in different functional areas is dominated by spherical particles in different weather conditions. In particular, the proportion of spherical particles exceeds 70% on the haze day, and the percentage of soot aggregates increases significantly on the clear day. The percentage of each type of particle in the teaching and living areas varied less under different weather conditions. Except for the industrial area, the size distribution of each type of particle in haze samples is larger than that on the clear day. Spherical particles contribute more to the small particle size segment. Soot aggregate and other shaped particles contribute more to the large size segment. The mass concentrations of hazardous elements (HEs) in PM_2.5 in different functional areas on consecutive haze pollution days were illustrated as industrial area > traffic area > living area > teaching area. Compared with the other functional areas, the teaching area had the lowest noncarcinogenic risk of HEs. The lifetime carcinogenic risk values of Cr and As elements in each functional area have exceeded residents’ threshold levels and are at high risk of carcinogenicity. Among the four functional areas, the industrial area has the highest carcinogenic and noncarcinogenic risks. But the effects of HEs on human health in the other functional areas should also be taken seriously and continuously controlled.

The significance of the study is to further understand the morphological characteristics of single particles and the health risks of heavy metals in different functional areas of Handan City. the authors hope to provide a reference for other coal-burning industrial cities to develop plans to improve air quality and human respiratory health.

The purpose of this paper is to study the influence of calcium sulfate whiskers (CSWs) on the thermodynamic properties and shape memory properties of epoxy/cyanate ester shape memory composites.

To improve the mechanical properties of shape memory cyanate ester (CE)/epoxy polymer (EP) resin, high performance CSWs were used to reinforce the thermo-induced shape memory CE/EP composites and the shape memory CSW/CE/EP composites were prepared by molding. The effect of CSW on the mechanical properties and shape memory behavior of shape memory CE/EP composites was investigated.

After CSW filled the shape memory CE/EP composites, the bending strength of the composites is greatly improved. When the content of CSW is 5 Wt.%, the bending strength of the composite is 107 MPa and the bending strength is increased by 29 per cent compared with bulk CE/EP resin. The glass transition temperature and storage modulus of the composites were improved in CE/EP resin curing system. However, when the content of CSW is more than 10 Wt.%, clusters are easily formed between whiskers and the voids between whiskers and matrix increase, which will lead to the decrease of mechanical properties of composites. The results of shape memory test show that the shape memory recovery time of the composites decreases with the decrease of CSW content at the same temperature. In addition, the shape recovery ratio of the composites decreased slightly with the increase of the number of thermo-induced shape memory cycles.

A simple way for fabricating thermo-activated SMP composites has been developed by using CSW.

The outcome of this study will help to fabricate the SMP composites with high mechanical properties and the shape memory CSW/CE/EP composites are expected to be used in space deployable structures.

This study aims to empirically examine the relationships among perceived environmental uncertainty (EV), the level of knowledge distance (KD) and the impact of value network on firm performance.

The quantitative analysis is based on data from 243 Chinese companies with engineering, procurement and construction (EPC) business in the context of the COVID-19 pandemic.

The two dimensions of value network [network centrality (NC) and network openness (NO)] have a different impact on firm performance [financial performance (FP) and market performance (MP)]. NC has a positive impact on FP, but not on MP. NO has a positive effect on MP, but not on FP. A reduced KD mediates the relationship between value network and firm performance. Moreover, it fully mediates the relationship between NC and MP, NO and FP. Finally, during the COVID-19 pandemic, only EV has a moderating effect on KD and MP.

This study is limited in terms of data set because it relies on a limited amount of cross-sectional data from one specific country. Therefore, researchers are encouraged to test the proposed propositions further.

The present findings suggest that EPC professionals should pay more attention to the EV, which may be impacted by policy, technology and the economy. This research has actionable implications for the reform of EPC in the construction industry, and practical recommendations for EPC firms to improve their corporate performance.

The results measure the complementary effects of both dimensions of value network (NC and NO) on two distinct aspects of firm performance (MP and FP) and assess the moderating effect of EV and KD in the context of the COVID-19 pandemics.

The purpose of this study is to explore the economic impact of financial restatements by major customers on the audit opinion of their suppliers, showing that non-financial information disclosure potentially helps auditors make better assessments.

Using a sample of China’s listed firms from 2007 to 2021, the authors aim to find the relationship between customers’ financial restatements and their suppliers’ audit opinions. Heckman selection model, placebo tests and other robustness checks are used as well.

The findings reveal that customers’ financial restatements have a significant effect on the likelihood of suppliers receiving modified audit opinions. This relationship is pronounced when suppliers face a higher level of financial constraints, exhibit poorer accounting conservatism or receive more negative media coverage. Additionally, this effect occurs through increased business risk and information risk, which heightens auditors’ perceived audit risk. Moreover, the study highlights the influence of switching costs, auditor expertise and restatement severity on this relationship.

Risks originating from customers can spread along the supply chain, emphasizing the necessity for auditors to give heightened attention to both the audited firms and their customer information. Moreover, regulators should carefully consider the important impact of customer information disclosures to maximize the protection of the interests of external information users.

This study not only confirms the crucial role of customer information disclosures in annual reports for stakeholders and auditors but also contributes to the existing literature on customer–supplier relationships.

By studying the green development efficiency (GDE) of 33 cities in the provinces of Jiangsu, Zhejiang, and Fujian in China, this study strives to conduct an analysis of the sustainable practices implemented in these developed regions, and derive valuable insights that can foster the promotion of green transformation.

First, the urban green development system (GDS) was decomposed into the economic benefit subsystem (EBS), social benefit subsystem (SBS), and pollution control subsystem (PCS). Then, a mixed network SBM model was proposed to evaluate the GDE during 20152020, with Moran’s I and Bootstrap truncated regression model subsequently applied to measure the spatial characteristics and driving factors of efficiency.

Subsystem efficiency presents a distribution trend of PCS > EBS > SBS. There is a particular spatial aggregation effect in EBS efficiency, whereas SBS and PCS efficiencies have no significant spatial autocorrelation. Furthermore, urbanization level contributes significantly to the efficiency of all subsystems; industrial structure, energy consumption, and technological innovation play a crucial role in EBS and SBS; external openness is a pivotal factor in SBS; and environmental regulation has a significant effect on PCS.

This study further decomposes the black box of GDS into subsystems including the economy, society, and environment. Additionally, by employing a mixed network SBM model and Bootstrap truncated regression model to investigate efficiency and its driving factors from the subsystem perspective, it endeavors to derive more detailed research conclusions and policy implications.

The effect of board intellectual capital on non-profit organizational performance in non-western, less developed economies has been an important yet under-researched area. Given that the institutional and business relationships of a board account for the majority of board intellectual capital, the purpose of this paper is to fill the previously mentioned research gap by addressing how the interactions of the two relationships of board directors influence Chinese philanthropic foundation performance.

Following Creswell's (2014) explanatory sequential mixed-methodology, a qualitative study (Study 1) was first conducted to pre-test the assumptions, and then a quantitative study (Study 2) was carried out based on a secondary database of 1,405 Chinese philanthropic foundations to further examine the hypotheses. Several regression models were built for analyzing the results.

Study 1 confirmed that Chinese philanthropic foundations gained greater revenues and hosted more public welfare activities by leveraging the reinforcing or complementary effects of board directors' intellectual capital to improve organizational performance. Study 2 further examined the hypotheses that the interactions of intellectual capital increased the total revenue and public welfare expenditure of the foundations; however, significant positive relationships were only identified in foundations at the local level, and no significant associations were found in those at the national level.

The research indicates that the intellectual capital of board directors may influence the performance of their philanthropic foundations. Thus, Chinese philanthropic foundations should be more aware of the importance of this influence when determining which candidates will join the board.

The study makes significant contributions to the existing knowledge of the development of non-governmental organizations; it incorporates the resource dependence theory and agency theory into understanding how the intricate interactions between the institutional and business relationships of board directors affect foundation performance and how the jurisdiction affiliations act as a boundary condition for such relationships in a non-western setting such as China.

Flexible eddy current array (FECA) sensor is flexible and light in weight, which has broad application prospects in structural health monitoring. But, the sensor’s sensing channel number is more, increasing the added mass of sensor networks. This paper aims to reduce the sensing channel number by changing the sensing coil layout.

In this paper, FECA sensors with series sensing coil (SSC) layout and interactive sensing coil (ISC) layout are proposed, which reduce the number of sensor’s channels by half. Then, the variation of the output signal of the sensor when the crack expands along both sides of the hole is analyzed by simulation model. Finally, the fatigue crack monitoring experiment is carried out.

For the SSC layout, the simulation results show that the amplitude of each SSC group of the sensor increases when the crack propagates to the left or right. For the ISC layout, when the crack propagates on the right side of bolt hole, the induced voltage of each ISC group decreases. When the crack propagates on the left side of bolt hole, the induced voltage of each ISC group increases. The experiment results are consistent with simulation results, which verifies the correctness of simulation model. Compared with SSC layout, the ISC layout can judge the crack propagation direction. And the crack monitoring accuracy is 1 mm.

The research results provide a certain reference for reducing the number of sensor’s sensing channels. Results of the simulation and experiment show that the ISC layout can judge the crack propagation direction, and the crack monitoring accuracy is 1 mm.

The flexible eddy current array sensor has the characteristics of lightweight and flexibility, which has a great application prospect in the field of fatigue crack monitoring. But the exciting layout and feature signal extraction have a great influence on the crack monitoring characteristics of the sensor. This paper aims to propose a method using crack disturbed voltage as sensitivity to characterize crack propagation.

Flexible eddy current array sensors with reverse and codirectional exciting layout are proposed, and the advantages and disadvantages of three characterization methods based on the change of trans-impedance amplitude, the change of the trans-impedance’s real and imaginary part and the crack disturbed voltage are compared and analyzed by finite element simulation. Finally, the fatigue crack monitoring experiment is carried out.

The crack disturbed voltage and the change of trans-impedance’s imaginary part can effectively characterize the crack propagation for sensors with different exciting layouts. The codirectional exciting layout sensor has better crack identification sensitivity than the reverse exciting layout sensor, especially the induction coil 2. When the distance between the exciting coil and the induction coil is 0.1, 0.2 and 0.3 mm, it is increased by 372.09%, 295.24% and 231.43%, respectively.

Crack disturbed voltage can effectively characterize the crack propagation for sensors with two different exciting layouts.

This paper takes the seven overcapacity industries such as the textile industry, electricity and heat, steel, coal, automobile manufacturing, nonferrous metals and petrochemical industry as research objects and proposes a TOPSIS grey relational projection group decision method with mixed multiattributes, which is used for the ranking of the seven industries with overcapacity and provided relevant departments with a basis for decision-making.

First, an evaluation index system from four aspects is established. Secondly, the attributes of linguistic information are converted into two-dimensional interval numbers and triangular fuzzy numbers, and an evaluation matrix is constructed and normalized. This paper uses the AHP method to determine the subjective weights and uses the coefficient of variation method to determine the objective weights. Moreover, this paper sets up the optimization model with the largest comprehensive evaluation value to determine the combined weights. Finally, the TOPSIS grey relational projection method is proposed to calculate the closeness of grey relational projections and to rank them.

This paper analyzes the problem of overcapacity in seven industries with the TOPSIS grey relational projection method. The results show that the four industries of automobile manufacturing, textile, coal and petrochemical are all in serious overcapacity levels, while the three industries of steel, nonferrous metals and electric power are relatively in weak overcapacity level in the three years of 2016–2018. TOPSIS grey relational projection method ranks the overcapacity degree of the seven major overcapacity industries, making the relative overcapacity degree of each industry more clear and providing a reference for the government to formulate targeted policies and measures for each industry.

By using TOPSIS grey relational projection method to evaluate the overcapacity of the seven major overcapacity industries, on the one hand, it makes the relative overcapacity degree of each industry more clear, on the other hand, it can provides the basis for the government and decision-making departments. This helps them promote better the healthy and orderly economic development of the seven major industries and avoid resource waste caused by overcapacity.

This article solves the single evaluation method caused by the limited indicators in the past, combines TOPSIS and the grey relational projection method and applies it to the overcapacity evaluation of the industry, not only applies it to the evaluation of overcapacity for the first time but also involves novel problems and methods, which expands the scope of application of the model.

The fresh food supply chain industry faces significant challenges in risk management because of the complexity, immature development and unpredictable external environment of imported fresh food supply chains (IFFSCs). This study aims to identify specific risk factors in IFFSCs, demonstrate how these risks are transmitted within the system and provide an analytical framework for managing these risks.

A total of 15 risk factors for IFFSCs through extensive literature review and expert consultation are identified and classified into seven levels using interpretive structural modeling (ISM) to demonstrate the risk transmission path. Fuzzy Matrice d’Impacts Croises-Multiplication Appliance Classement (MICMAC) analysis is then used to analyze the role of each factor.

The interactions of the 15 identified risk factors of IFFSCs, classified into seven levels, are visualized using ISM. The fuzzy MICMAC analysis classifies the factors into four groups, namely, dependent, independent, linkage and autonomous factors, and identifies the relatively critical risk factors in the system.

The findings of this research provide a clear framework for enterprises operating in IFFSCs to understand the specific risks they may face and how these risks interact within the system. The fuzzy MICMAC analysis also classifies and highlights critical risk factors in the system to facilitate the formulation of appropriate mitigation measures.

This study provides enterprises in IFFSCs with a comprehensive understanding of how the risks can be effectively managed and a basis for further exploration. The theoretical model constructed is also a new effort to address the issues of risk in IFFSCs. The ISM and the fuzzy MICMAC analysis offer clear insights for researchers and enterprises to grasp complex concepts.