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The paper aims to accurately measure the key motion parameters, such as velocity, azimuth and pitch angle, of the small flying object with a non-uniform curve trajectory. It proposes a measurement method and its calculation model of non-uniform curve trajectory using a photoelectric sensor array.

First, the basic composition of the measurement system and mechanism of photoelectric sensor array are described, respectively. Second, a non-uniform curve mathematical measurement model is constructed differently from the traditional linear trajectory, taking into account the influence of gravity and air resistance. Third, the measurement error of the system is analyzed through numerical simulation. Finally, the accuracy and feasibility of the approach are verified by live-ammunition experiments.

The results show that the systematic error of the hitting point coordinates can be reduced by 9% compared to the traditional linear measurement model. Consequently, this method can meet the higher measurement requirement for the key motion parameters of the small flying object under the non-uniform curve trajectory. Research limitations/implications (if applicable)- although the approach itself is generalizable, the method is unable to detect the motion parameters of multiple small flying objects.

Although the approach itself is generalizable, the method is unable to detect the motion parameters of the multiple small flying objects.

It is evident that the proposed non-uniform curve measurement model is more precise in quantifying the essential characteristics of the small flying object, particularly in consideration of the environmental conditions.

The precise measurement of the key motion parameters of the small flying object can facilitate the enhancement of the protective performance of protective materials.

A novel approach to measurement is proposed, which differs from the conventional uniform trajectory model. To this end, the space construction of the photoelectric sensor array is optimized. The number of the sensors is revised.

The purpose of this study is to identify the determinants of success in peer-to-peer (P2P) lending campaigns, especially amid global financial disruptions like the COVID-19 pandemic. Addressing a notable gap in current research, we explore how factors such as firm uncertainty, loan characteristics (interest rates and maturity) and venture quality (human, social and intellectual capital) influence P2P lending effectiveness. Using multiple regression analysis on data from 523 projects on the October platform, our study aims to enhance the understanding and operational efficiency of P2P platforms, contributing to a more resilient financial ecosystem.

This study employs a quantitative research design using multiple regression analysis to examine the impact of specific variables on the success of P2P lending campaigns. Data were collected from 523 concluded P2P lending projects on the October platform, spanning from 2015 to 2021. Variables of interest include the level of uncertainty of the firm, loan characteristics such as interest rate and maturity and the quality of the venture assessed through human, social and intellectual capital. This method allows for a robust analysis of the factors contributing to the success of P2P lending within a dynamic financial context.

The findings of this study reveal that the success of P2P lending campaigns is significantly influenced by the level of uncertainty of the firm, the interest rate of the loan and the quality of the venture. Specifically, higher uncertainty in firms correlates negatively with campaign success, while competitive interest rates positively impact funding outcomes. Furthermore, ventures that demonstrate robust human capital, particularly those with management teams that possess diverse skills and high qualifications, tend to attract more funding. These results underscore the critical role of strategic financial and human resource planning in enhancing the effectiveness of P2P lending platforms.

This study contributes uniquely to the literature by integrating multiple variables – firm uncertainty, loan characteristics and venture quality – into a comprehensive analysis of success factors in P2P lending. It addresses the scarcity of research examining the combined effects of these factors, particularly in the context of global financial disruptions like the COVID-19 pandemic. By focusing on a specific European platform during a dynamic period, this research provides new insights into how P2P lending can adapt to and thrive amid financial crises. The findings offer valuable guidance for both practitioners and policymakers aiming to optimize P2P lending practices in uncertain economic landscapes.

This study uses a job-demand resource perspective to test a conceptual model in which psychological contract breach has a negative relation with job performance (adaptivity and proficiency) through perceived job insecurity. Further, it has also been proposed that higher levels of role conflict will strengthen the impact of psychological contract breaches on job performance through job insecurity.

Two-wave data were collected from 449 working adults from the retail sector with managerial occupations in Chile. The moderated mediation models were tested through SPSS macro (developed by Preacher and Hayes, 2004).

The findings supported the hypotheses; first, psychological contract breach negatively influences job performance through job insecurity; and second, role conflict moderates the indirect relationship in a way that lower levels of role conflict buffer the relationship between psychological contract breach and job performance through job insecurity (versus higher levels of role conflict).

This study has practical and theoretical implications. On the one hand, it establishes how and when psychological contract breaches might harm individual job performance. On the other hand, it can be a guide to managers and employees who can find evidence about how harmful a breach of employees’ psychological contract can be.

While cyberloafing has emerged as a prevalent issue in numerous workplaces, research on its consequences is still underdeveloped, highlighting a need for further exploration and analysis. Drawing upon the cognitive appraisal theory of emotion, this study investigates the influence of coworkers' cyberloafing on employees' workplace incivility, mediated by negative emotions and moderated by task interdependence.

In Study 1, the hypothesized research model was tested utilizing three-wave time-lagged survey data collected from 333 employees and their coworkers. In Study 2, an additional sample of 274 employees was surveyed. Data were analyzed using hierarchical regression analysis and the bootstrap method.

The results indicated that coworkers' cyberloafing positively influenced employees' workplace incivility, with this relationship mediated by negative emotions. Additionally, task interdependence was found to positively moderate both the direct relationship between coworkers' cyberloafing and negative emotions and the indirect path from coworkers' cyberloafing to employees' workplace incivility through negative emotions.

This study helps managers gain a deeper understanding of cyberloafing's effects, enabling them to manage and curb it more effectively.

Prior research has predominantly explored the effects of cyberloafing on its implementers. However, this study innovatively shifts focus to the observer perspective, empirically demonstrating whether and how coworkers' cyberloafing affects employees' workplace incivility, enriching and expanding the existing literature.

The purpose of this research is to examine the relationship between coaching leadership and employees' taking charge while incorporating the mediating role of work meaningfulness and the moderating role of challenge-hindrance stressor.

A total of 355 pairs of effective samples were collected through a two-stage supervisor-subordinate paired survey. Four hypotheses were tested using hierarchal regression analysis and bootstrapping method.

The findings show that coaching leadership is positively related to taking charge, and work meaningfulness positively mediates the coaching leadership-taking charge relationship; high challenge stressors and high hindrance stressors weaken the positive effect of coaching leadership on work meaningfulness respectively; challenge stressors and hindrance stressors further moderate the indirect relationship of coaching leadership and taking charge through work meaningfulness.

This study provides a new perspective for organizations to activate employees' taking charge, thereby enriching the antecedents of taking charge. By incorporating challenge-hindrance stressor framework, this study also provides answers to when coaching leadership will be less effective.

Corporate hypocrisy occurs when a discrepancy exists between corporate talk and actions. As companies assume more extensive economic, societal and global roles, they are more likely to encounter situations in which their words and actions are inconsistent. Therefore, a company’s ability to cope with such situations is becoming increasingly important. This study aims to examine the negative effects of corporate hypocrisy on corporate reputation. First, it reveals the underlying mechanisms by presenting corporate trust and affective commitment as parallel mediators. Additionally, it explores how corporate social responsibility (CSR) perceptions mitigate the indirect effects of corporate hypocrisy.

Data were collected through an online survey conducted at two time points in the context of Korean retail banking companies. A total of 313 respondents participated in a two-wave online survey using a multistage sampling technique to ensure a representative population sample. This study used the Mplus-based Hayes’ PROCESS Macro to test the research hypotheses.

The results show that corporate hypocrisy negatively affects corporate reputation by impeding customers’ corporate trust and affective commitment. These negative indirect effects are mitigated when customers’ perceptions of CSR are high.

By establishing a parallel moderated mediation model that captures the impact of corporate hypocrisy. To the best of the authors’ knowledge, this study presents important academic and managerial implications that have not been provided in the literature.

Previous studies on housing affordability in China were concentrated in China’s coastal and central regions. The purpose of this paper is to investigate housing affordability of urban residents in Northwest China. Moreover, this paper attempts to understand the consistency and influencing factors of various indicators on the evaluation of housing affordability.

This paper uses multiyear data on house sales, residents’ incomes and living expenses from 2011 to 2022. House price-to-income ratio, housing affordability index and residual income approach were calculated by using these data and used as the measure of housing affordability.

The results show that there are obvious differences in the housing affordability among the Xi’an, Lanzhou and Yinchuan during 2011–2022, and the housing affordability of residents in cities with small population and economic scale is better. The ability of most urban residents to afford suitable housing is still poor, and the ability to afford small-sized housing is better. Most families with below-middle income have poor housing affordability. It is also observed that although various indicators had similarities in the evaluation of residents’ housing affordability, the comprehensive evaluation results of multiple indicators were more reliable.

The research results provide a basis for the decision-making of the government’s urban housing policy and improvement of residents’ housing conditions.

The results have a clear understanding of the housing affordability of urban residents in Northwest China. The study found that the geographical location and topography of the city is also a factor affecting the housing affordability.

The purpose of this study is to use a lifetime income measure to evaluate the long-run housing affordability for an understudied cohort of households in the literature – the millennials. The authors do this in the context of Malaysia, measuring long-run affordability for four housing types across geographic locations and income distributions.

This study calculates a long-run housing affordability index (HAI) using data on house prices and household incomes. Essentially a ratio of predicted lifetime incomes to house prices, the HAI is computed for four common housing types in Malaysia from 2005 to 2016 and for six states in the country. The HAI is also compared across four income percentiles.

The analysis reveals varying patterns of housing affordability among different states in Malaysia. Housing affordability has declined since 2010, with most housing types being unaffordable for millennial-led households with the lowest income. Housing is most affordable for those in the highest income bracket, although even here, there are pockets of unaffordable housing as well.

Based on the findings, this study proposes three targeted interventions to improve housing affordability for Malaysian millennials.

This study fills a gap in the literature by examining the long-run housing affordability of Malaysian millennial-led households based on both geographic location and income distribution. The millennial population is understudied in the housing affordability literature, making this study a valuable contribution to the field.

Aluminum foam-filled thin-walled unit structures have received much attention for their excellent energy absorption properties. To improve the energy absorption effect of car energy absorption box under axial compression, this paper optimizes the fiber lay-up sequence, fiber angle and aluminum foam density of aluminum foam filled carbon fiber reinforced plastic (CFRP) thin-walled square tubes.

Design of sample points required to construct the proxy model using design of experiments (DOE) method, and the data sample points of different models are obtained through Abaqus simulation and test. A double high-precision proxy model with the maximum specific energy absorption (SEA) and the minimum initial peak crash force (PCF) as the evaluation index is constructed based on the response surface function method. The NSGA-II multi-objective genetic algorithm was used to optimize the design parameters and obtain the optimal solution for the Pareto front, and the results were verified by using the multi-objective optimization toolbox in design-expert.

The results show that the optimal solution to the multi-objective optimization problem with the inclusion of the lay-up sequence is ρ = 0.5g/cm3 for a fiber lay-up angle varying in the range ±15–90° and an aluminum foam density varying in the range 0.2g/cm3-0.5g/cm3, with a lay-up method of [±87°/±16°/±15°/±89°]. The two optimization methods correspond to SEA and PCF errors of 2.109% and 4.1828%, respectively. The optimized SEA value is 18.2 J/g and the PCF value is 18,230 N. The optimized design reduces the peak impact force and increases the specific energy absorption, which improves the energy absorption effect of thin-walled energy-absorbing boxes for automobiles.

In this paper, the impact resistance of CFRP thin-walled square tubes filled with aluminum foam is optimized. Based on numerical simulations and experiments to obtain the sample point data for constructing the dual-agent model, we investigate the effect of filling with different densities of aluminum foam under the simultaneous change of fiber lay-up angle and order on its mechanical properties in this process, and carry out the multi-objective optimization design with NSGA-II algorithm.

The purpose of this research is to ascertain the feasibility of fabricating polymer optical fibers (POFs) based textile structures by knitting with Polymethylmethacrylate (PMMA) based optical fibers for textile sensor application. It has long been established that by using the principles of physics, POFs have the capability to function as sensors, detecting strain, temperature and other variables. However, POF applications such as strain and pressure sensing using knitting techniques has since not been very successful due to a number of reasons. Commercially available PMMA-based optical fibers tend to be fragile and susceptible to breakages when subjected to stress during the knitting processes. Also light transmitted within these fibers is prone to leakage due to the curvature that results when optical fibers are interlaced or interlooped within fabric structures.

Using Stoll’s multi-gauge CMS 350 HP knitting machine, five fabric structures namely, 1 × 4 float knit structure, tunnel inlay knit structure, 3:1 fleece fabric and 2:1 fleece fabric structure respectively were used to knit sensor samples. The samples were subsequently tested for length of illumination and sensitivity relative to applied pressure.

The results of this preliminary study establish that embedding plastic optical fibers into a knitted structure during the fabric formation process for soft strain sensor application possible. The best illumination performance was recorded for tunnel inlay structure which had an average of 94 cm course length of POF being illuminated. Sensor sensitivity experiments also establish that the relative spectral intensity of the fiber is sensitive to both light and pressure. Problems encountered and recommendations for further research have also been discussed and proffered.

Due to resource limitations, an innovative technique (use of precision weight set) was used to apply pressure to the sensors. Consequently, information regarding the extent of corresponding sensor deformation has not been used in this initial analysis.

Because the fundamental step toward finding a solution to any engineering problem is the acquisition of reliable data, and considering the fact that most of the popular technologies used for soft textile sensors are still bedeviled with the problem of signal instability and noise, the success of this application thus has the tendency to promote the wide spread adoption of POF sensors for smart apparel applications.

As far as research on soft strain sensors is concerned, to the best of the authors’ knowledge, this is the first study to have attempted to knit deformable sensors using commercially available POFs.