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This study aims to establish a multi-physics-coupled model for an electrostatic particulate matter (PM) sensor. The focus lies on investigating the deposition patterns of particles within the sensor and the variation in the regeneration temperature field.

Computational simulations were initially conducted to analyse the distribution of particles under different temperature and airflow conditions. The study investigates how particles deposit within the sensor and explores methods to expedite the combustion of deposited particles for subsequent measurements.

The results indicate that a significant portion of the particles, approximately 61.8% of the total deposited particles, accumulates on the inside of the protective cover. To facilitate rapid combustion of these deposited particles, a ceramic heater was embedded within the metal shielding layer and tightly integrated with the high-voltage electrode. Silicon nitride ceramic, selected for its high strength, elevated temperature stability and excellent thermal conductivity, enables a relatively fast heating rate, ensuring a uniform temperature field distribution. Applying 27 W power to the silicon nitride heater rapidly raises the gas flow region's temperature within the sensor head to achieve a high-temperature regeneration state. Computational results demonstrate that within 200 s of heater operation, the sensor's internal temperature can exceed 600 °C, effectively ensuring thorough combustion of the deposited particles.

This study presents a novel approach to address the challenges associated with particle deposition in electrostatic PM sensors. By integrating a ceramic heater with specific material properties, the study proposes an effective method to expedite particle combustion for enhanced sensor performance.

Given the current friction and wear challenges faced by automobile parts and bearings, this study aims to identify a novel texture for creating anti-friction and wear-resistant surfaces. This includes detailing the preparation process with the objective of mitigating friction and wear in working conditions.

Femtosecond laser technology was used to create a mango-shaped texture on the surface of GCr15 bearing steel. The optimized processing technology of the texture surface was obtained through adjusting the laser scanning speed. The tribological behavior of the laser-textured surface was investigated using a reciprocating tribometer.

The friction coefficient of the mango-shaped texture surface is 25% lower than that of the conventional surface, this can be attributed to the reduced contact area between the friction ball and the micro-textured surface, leading to stress concentration at the extrusion edge and a larger stress distribution area on the contact part of the ball and disk compared to the conventional surface and the function of the micro-texture in storing wear chips during the sliding process, thereby reducing secondary wear.

The mango-shaped textured surface in this study demonstrates effective solutions for some of the friction and wear issues, offering significant benefits for equipment operation under light load conditions.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0127/

This study aims to investigate the effects of unconditional conservatism on investment efficiency, focusing on both its direct and indirect effects.

We conduct multiple regression analyses on a sample of nonfinancial companies listed on the New York Stock Exchange from 2010 to 2018.

We provide evidence that conditional conservatism plays a central role in mediating the indirect effects of unconditional conservatism on investment efficiency. This is because a decrease in conditional conservatism, following an increase in unconditional conservatism, leads to reduced investment efficiency.

This study offers valuable insights for the growing body of literature on the relationship between accounting conservatism and investment efficiency while emphasizing the critical role of conditional conservatism in mediating the relationship between unconditional conservatism and investment efficiency.

This study has several implications. Practitioners can make informed decisions regarding accounting policies, predict the potential effects of these choices and mitigate the negative impact of unconditional conservatism on investment efficiency. Investors can make more informed decisions by understanding how unconditional and conditional conservatism affect investment efficiency. Standard setters can guide user behavior toward more efficient investment decisions.

Considering the lack of comprehensive understanding in prior literature regarding the underlying mechanisms through which unconditional conservatism influences investment efficiency, this study investigates the direct and indirect effects characterizing this relationship. We provide evidence supporting a new explanation for the relationship between unconditional conservatism and investment efficiency.

This paper aims to examine the role of local/provincial government in influencing corporate social and environmental reporting (CSER) in China, and more specifically, how the underlying economic and political factors associated with local government have influenced the quality of CSER.

The authors used 234 environmentally sensitive companies listed on the Shanghai and Shenzhen Stock Exchanges during 2013 and 2015 as the research sample to test the relationship between CSER and local government’s political connection and economic prioritisation and the potential mediating effect of local economic prioritisation.

The analysis provides evidence that local/provincial government’s political geographical connectedness with the central government has directly and positively influenced the level of CSER, while local prioritisation of economic development has a direct but negative effect on CSER in China. In addition, local/provincial prioritisation of economic development has mediated the relationship between local–central political geographical connectedness and CSER.

While local/provincial governments are heavily influenced by the coercive pressure from the central government, they also act in their own political and economic interests in overseeing CSER at the local level. This study raises the question about the effectiveness of the top-down approach to improving CSER in China and suggests that the central government may need to focus more on coordinating and harmonising different local/provincial governments’ interests to enable achieving a common sustainability goal.

The authors provide evidence revealing how the economic and political contexts of local government have played a significant role in shaping CSER in China. More specifically, this paper addresses a gap in the literature by highlighting the importance of local government oversight power for CSER development and how such oversight is determined by local prioritisation of economic development and political geographical connectedness of local and central governments.

This paper aims to improve the refractive index sensor performance for analytes with large refractive index by adopting the technology of microstructured fiber (MF) and surface plasmon resonance (SPR).

The structure adopts an MF with a hexagonal lattice cladding structure composed of all-circular air holes, and three defect regions are introduced. The liquid analyte that needs to be tested is filled in the defect area. The surface plasmon polarition mode is generated and coupled with the core mode, thus forming a refractive index sensing channel. When the resonance conditions are satisfied, the resonance wavelength will be changed with the refractive index of the liquid analyte. All parameters that may affect the performance of the sensor are numerical simulated, and the structure is optimized through a large number of calculations.

The results demonstrate that the maximum dynamic sensitivity (S_R) can reach to 24,260 nm/RIU, and the average sensitivity (S_R-AV) can reach to 18,046 nm/RIU when the refractive index range is from 1.42 to 1.47. Besides, the sensitivity linearity (R²) is approximately 0.965, and its resolution is 4.1 × 10^–6 RIU. The comparison with some literature results shown that the proposed sensor has certain advantages over the sensors reported in these literatures.

This work proposed an SPR-based refractive index sensor with a simple MF structure. It has a certain reference significance for the design and optimization of SPR-based MF sensors. Moreover, owing to its simple structure, high refractive index sensitivity and linear sensing performance, this sensor will play an important role in the detection of high refractive index liquid analytes.

This study aims to present a novel topology optimization method for effectively minimizing the frequency response over a given frequency interval considering anisotropic features and fiber angles simultaneously.

The variable thickness sheet (VTS) method is used to obtain a free material distribution under the specified volume constraint. The anisotropic equivalent stiffness matrix based on the material fiber angles is considered in the orthotropic material properties model, which ensures a sufficiently large design space to minimize the frequency response. To lessen the computational burden, the quasi-static Ritz vector (QSRV) method is integrated to approximate the structural response.

Compared to considering only one element, the optimization process simultaneously considers the spatially-varying fiber angles and the material distribution, allowing for a broader design space to minimize the frequency response of additive manufacturing (AM) structures. The orthotropic properties play an important role in determining optimal material distribution of the structure. Moreover, the QSRV method makes the frequency response analysis more efficient.

The anisotropic stiffness and spatially-varying angles of the fiber materials induced by the layer-by-layer printing process of carbon fiber reinforced plastics (CFRP) are simultaneously considered to further minimize the frequency response of AM structures, which improves the performance of AM-CFRP structures.

Fierce competition in the crowdfunding market has resulted in high failure rates. Owing to their dedication and efforts, many founders have relaunched failed campaigns as a second attempt. Despite the need for a better understanding, the success of campaign relaunches has not been well-researched. To fill this research gap, this study first theorizes how founders’ learning may enhance their competencies and influence investors’ attribution of entrepreneurial failure. The study then empirically documents the extent and conditions under which such learning efforts impact campaign relaunch performance.

This study examines 5,798 Kickstarter-relaunched campaigns. The founders’ learning efforts are empirically captured by key changes in campaign design that deviate from past business practices. Word movers’ distances and perceptual hashing algorithms (pHash) are used separately to measure differences in campaign textual descriptions and pictorial designs.

Differences in textual descriptions and pictorial designs during campaign failure–relaunch are positively associated with campaign relaunch success. The impacts are further amplified when the previous failures are more severe.

This study is one of the first to examine the success of a campaign relaunch after an initial failure. This study contributes to a better understanding of founders’ learning in crowdfunding contexts and provides insights into the strategies founders can adopt to reap performance benefits.

This study aims to understand the potential influence of several factors that may affect females’ intentions to undergo breast cancer screening (BCS) in Jordan.

A positivistic research methodology was used with the aim of gathering and interpreting the data quantitatively. A questionnaire was created and given to the selected respondents. Females who were at least 18 years old made up the study’s population. In addition, using a sample size of n = 237 was warranted and appropriate. Data were collected from Karak, Tafilah, Aqaba and Ma’an, four cities in southern Jordan. Smart partial least squares version 4.0.9.2 and SPSS version 26 have been used for data analysis.

The findings showed that attitudes, subjective norms, disease susceptibility and cues-to-action among females have a significant impact on their intention to undergo BCS. Whilst, the benefits of using BCS have not been shown to have a substantial impact on females’ intentions to undergo BCS. Furthermore, this study indicated that there were no significant differences between females’ intention to conduct BCS and the control variables (age and education).

There are specific restrictions in place. First, although the study’s sample size of respondents was adequate, it would be advantageous to have a larger sample size in the future to improve the reliability of the results. Second, the BCS behavior in Jordan’s southern cities was the sole subject of this study. Therefore, it would be beneficial to also explore other areas of Jordan. Third, only female candidates for BCS were examined in this study. It might be necessary to do a more thorough investigation to find the obstacles preventing them from performing the test. Fourth, the current study did not analyze the actual behavior required to perform the BCS test; instead, it sought to understand females’ intentions for undergoing the test. Therefore, it would be beneficial to research actual female behavior toward BCS in the future. The current study also used a quantitative research methodology. Therefore, more study is required using qualitative techniques like focus groups, interviews and brainstorming to better understand females’ intentions toward BCS.

According to the author’s best knowledge, this study marks the first effort to highlight behavioral intentions toward performing BCS in the Jordanian context. In addition, by incorporating extra factors obtained from the health belief model within the context of BCS behavior, the current study broadens the theory of reasoned action. This can be viewed as a significant contribution to the subject’s theoretical foundations. Besides, the current study incorporated demographic characteristics and used them as a control variable. This can be seen as another contribution to the literature on health-care marketing in the case of BCS.

Achieving accurate trajectory tracking control of robot manipulators is challenging due to dynamic model errors and uncertain payloads. This paper aims to enhance trajectory tracking performance for robots with n degrees of freedom (DOF).

This study proposes a robust motion control framework that combines uncertainty and disturbance estimator with model-based compensation. The proposed framework ensures precise trajectory tracking in robot manipulators. In addition, uncertainties in the high-DOF robot dynamics are estimated through a simple model-based compensation for system error dynamics. The stability of the closed-loop system of the proposed framework is analyzed and proved.

The results indicate that the proposed framework can significantly reduce tracking errors and increase disturbance resistance. The simulation results of a two-link robotic arm verify the effectiveness of the proposed method. The results of the experiments conducted on a seven-DOF torque-controlled Flexiv4S manipulator demonstrate the superior trajectory tracking performance and robustness of the proposed algorithm.

This study introduces a highly efficient, robust motion control framework for high-DOF robots, which can improve the trajectory tracking performance in the presence of model uncertainties.

This study aims to explore the impact of digital supply chain capability (DSCC) on the supply chain financing performance (SCFP) of Chinese small and medium-sized enterprises (SMEs). The mediating role of information sharing (IS) and the moderating role of environmental uncertainty (EU) were also investigated.

Based on information processing theory (IPT), this paper constructs a theoretical model to investigate the impact of DSCC on SCFP in 276 Chinese SMEs using ordinary least regression to test hypotheses.

The results show that both digital supply chain sensing capability (DSC) and digital supply chain responding capability (DRC) have positive effects on SCFP. IS plays a mediating role in the relationship between DSC and SCFP, while the EU strengthens the relationship between DRC and IS.

First, this study takes a capability perspective to explore the impact of DSCC on SCFP, which extends the related studies taking a technology perspective. Second, the inner mechanism between DSCC and SCFP is revealed by introducing IS as a mediator. Third, boundary conditions for the DSCC–IS link are clarified by considering EU as a source of information processing requirements.