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The paper aims to highlight a wireless pressure-sensitive micro-device with high pressure sensitivity and accuracy. It is based on the partially stabilized Zirconia (PSZ) ceramic material which is capable of excellent elasticity and robustness.

The paper begins with a general introduction to the wireless interrogating method and then the fabrication processes of the device using high temperature co-fired ceramic (HTCC) technology are described in detail.

A passive wireless micro-device made from a novel material-PSZ ceramic on pressure monitoring is fabricated and tested and the authors proved that the device possesses an advantages over some proposed wireless sensors on interrogating distance. The pressure sensitivity of the device is 336 kHz/bar at readout distance 2.5 cm and that is an excellent property.

The paper shows a new design scheme for wireless pressure measurement. The future application of the wireless device indicates the problem on external packaging and wire connection could be avoided. The allowable interrogation distance between the device and readout circuit reaches 2.5 cm which is mentioned for the first time so far. The distance is long enough to insert a thermal insulation material which can protect the vulnerable readout circuit from harsh environment, so the research finding is meaningful for the modern measurement technology.

The purpose of this study is to investigate the influence of geometric parameters of removable panels on the sealing characteristics of ceramic wafer seal structure subjected to high-temperature gas flow.

Based on the laminar flow Reynolds equation, the theoretical and numerical calculation models were constructed to investigate the influence of external convex deformation of removable panel on leakage rate. The theoretical formula for leakage rate after deformation of the removable panel was derived, and the flow field and leakage characteristics of ceramic wafer seal under different operating parameters were studied.

The leakage rate exhibits consistent trends between theoretical calculation, numerical simulation and experimental value, with a maximum discrepancy of 8.9%. This validates the accuracy of both the theoretical model and numerical simulation. As the deformation angle of the removable panel increases, the sealing gap gradually widens, resulting in a compromised sealing effect. Moreover, the leakage rate in the central region of the sealing area is lower compared to that at both ends.

The leakage of the ceramic wafer seal structure under the removable panel with different deformation angles can be monitored based on Reynolds equation. The pseudo-transient numerical calculation method can be used to determine the leakage value of the micro-state ceramic wafer seal structure. These research findings provide a theoretical foundation and numerical investigation approach for studying ceramic wafer seal structures.

With the continuous deepening of China's mixed-ownership reform, the participants in the reform have gradually expanded from state-owned enterprises to private enterprises. Whether state-owned equity participation in private enterprises can facilitate the development of environmental, social and governance (ESG) performance in private enterprises is a question that needs urgent examination. This study aims to investigate the impact of state-owned equity participation on the ESG performance of private enterprises.

Using Chinese listed companies as the research sample, this study uses econometric methods such as multiple regression to analyze the relationship between state-owned equity and the ESG performance of private enterprises. Additionally, it explores the underlying mechanisms and influencing factors of this relationship.

There is a significant inverted U-shaped relationship between state-owned equity and the ESG performance of private enterprises. Mechanism analysis reveals that resource effects and governance effects play a mediating role in this nonlinear relationship. Furthermore, the authors find that environmental regulation and managers' attention to the environment positively moderate the relationship between state-owned equity participation and ESG performance.

A reasonable equity structure is crucial for enhancing corporate ESG performance. Moderate state-owned equity participation helps to leverage resource integration and governance advantages, which will assist private enterprises in maximizing ESG performance and achieving sustainable development.

In advancing the process of mixed-ownership reform, the government should maintain an appropriate proportion of state-owned equity to avoid excessive intervention in enterprise decision-making. At the same time, it should ensure that enterprises can genuinely undertake their social and environmental responsibilities while pursuing economic benefits. This is of great significance for promoting sustainable economic and social development.

This study integrates state-owned equity, ESG and nonlinear relationships into a single research framework. It explores the internal mechanisms and influencing factors of their relationship, overcoming the limitations of previous studies and provides a new perspective for understanding the impact of state-owned equity on corporate ESG performance.

Does the history of the bureaucratic system, along with the establishment of the Great Wall during the Ming and Qing dynasties (1368–1911), affect firm behavior across the borderlands of the Great Wall?

The Ming and Qing dynasties built a centralized administrative system in the borderlands on the south side of the Great Wall, in contrast to the “feudal lordship” system on the north side. Employing a regression discontinuity analysis framework with the Great Wall as a geographical discontinuity, we examine the long-run effects of the Great Wall on firms’ earnings management.

Using a large sample of nonlisted firms in the central core frontier region, we show that the earnings management of firms in the region south of the Great Wall is significantly curtailed compared with firms in the north of it, and this effect is more pronounced for non-SOEs. Our findings are robust to a battery of tests to account for alternative explanations.

Overall, by emphasizing the role of institutions, like legal system, shaped in history on firms’ earnings management, this study sheds new light on institutional determinants of firms’ behaviors in earnings information disclosure.

First, we enrich our understanding of the institutional determinants of firms’ financial reporting outcomes. Second, our findings shed new light on the long-term effects of historical ruling styles on modern corporate behavior.

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 purpose of this paper is to detect abnormal data of complex and sophisticated industrial equipment with sensors quickly and accurately. Due to the rapid development of the Internet of Things, more and more equipment is equipped with sensors, especially more complex and sophisticated industrial equipment is installed with a large number of sensors. A large amount of monitoring data is quickly collected to monitor the operation of the equipment. How to detect abnormal data quickly and accurately has become a challenge.

In this paper, the authors propose an approach called Multiple Group Correlation-based Anomaly Detection (MGCAD), which can detect equipment anomaly quickly and accurately. The single-point anomaly degree of equipment and the correlation of each kind of data sequence are modeled by using multi-group correlation probability model (a probability distribution model which is helpful to the anomaly detection of equipment), and the anomaly detection of equipment is realized.

The simulation data set experiments based on real data show that MGCAD has better performance than existing methods in processing multiple monitoring data sequences.

The MGCAD method can detect abnormal data quickly and accurately, promote the intelligent level of smart articles and ultimately help to project the real world into cyber space in CrowdIntell Network.

The purpose of this study is to investigate the influence of dimple radius, depth and density on the lubrication performance of the plunger.

A lubrication model was adopted to consider eccentricity and deformation during the working process of the plunger, and a rig test was performed to confirm the simulation results. The texture was fabricated using laser surface texturing.

The simulation results suggested that when dimple radius or depth increases, oil film thickness of the plunger increases before decreasing, and asperity friction displays an opposite trend. Therefore, appropriate microdimple texture could facilitate lubrication performance improvement and reduce the wear. Microdimples were then lased on the plunger surface, and a basic tribological test was conducted to validate the simulation results. The experimental results suggested that the average friction coefficient decreased from 0.18 to 0.13, a reduction of 27.8%.

The introduction of microdimple on a plunger couple to reduce friction and improve lubrication is expected to provide a new approach to developing high-performance plunger couple and improve the performance of the internal combustion engine. If applied, the surface texture could help reduce friction by around 27% and cap the cost relative to the plugger friction.

The microdimple texture was introduced into the plunger couple of a vehicle to reduce the friction and improve the performance. Findings suggested that surface texture could be used in the automotive industry to improve oil efficiency and lubrication performance.

The peer review history for this article is available at: http://dx.doi.org/10.1108/ILT-07-2020-0259.

The behavioral decision-making of digital-self is one of the important research contents of the network of crowd intelligence. The factors and mechanisms that affect decision-making have attracted the attention of many researchers. Among the factors that influence decision-making, the mind of digital-self plays an important role. Exploring the influence mechanism of digital-selfs’ mind on decision-making is helpful to understand the behaviors of the crowd intelligence network and improve the transaction efficiency in the network of CrowdIntell.

In this paper, the authors use behavioral pattern perception layer, multi-aspect perception layer and memory network enhancement layer to adaptively explore the mind of a digital-self and generate the mental representation of a digital-self from three aspects including external behavior, multi-aspect factors of the mind and memory units. The authors use the mental representations to assist behavioral decision-making.

The evaluation in real-world open data sets shows that the proposed method can model the mind and verify the influence of the mind on the behavioral decisions, and its performance is better than the universal baseline methods for modeling user interest.

In general, the authors use the behaviors of the digital-self to mine and explore its mind, which is used to assist the digital-self to make decisions and promote the transaction in the network of CrowdIntell. This work is one of the early attempts, which uses neural networks to model the mental representation of digital-self.