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Previous studies indicate that a college-student’s leader self–efficacy (LSE) enhances the ability to be an effective leader. However, there is limited empirical evidence on the college experiential factors that develop students’ LSE in Historically Black Institutions (HBIs). The purpose of this study is to adapt Astin’s input-environment- outcome (I-E-O) model to identify the effects of college experiential variables (environment) on student LSE development (output) while controlling for precollege variables (input). Pre- and post-data were collected from 200 freshmen studying at two Historically Black Institutions and analyzed using the hierarchical multiple regression (HMR). The findings suggested that precollege LSE and college co-curricular leadership experiences significantly influence students’ LSE development.

Aircraft assembly is the crucial part of aircraft manufacturing, and to meet the high-precision and high-efficiency requirements, cooperative measurement consisting of multiple measurement instruments and automatic assisted devices is being adopted. To achieve the complete data of all assembly features, measurement devices need to be placed at different positions, and the flexible and efficient transfer relies on Automated Guided Vehicles (AGVs) and robots in the large-size space and close range. This paper aims to improve the automatic station transfer in accuracy and flexibility.

A transferring system with Light Detection and Ranging (LiDAR) and markers is established. The map coupling for navigation is optimized. Markers are distributed according to the accumulated uncertainties. The path planning method applied to the collaborative measurement is proposed for better accuracy. The motion planning method is optimized for better positioning accuracy.

A transferring system is constructed and the system is verified in the laboratory. Experimental results show that the proposed system effectively improves positioning accuracy and efficiency, which improves the station transfer for the cooperative measurement.

A Transferring system for collaborative measurement is proposed. The optimized navigation method extends the application of visual markers. With this system, AGV is capable of the cooperative measurement of large aircraft structural parts.

The purpose of this paper is to examine whether income diversification moderates the relationship between human capital and bank performance.

The study uses a sample of 53 banks and panel data for the years 2010–2018. The hypotheses are tested through hierarchical multiple regression and the choice between fixed effect and random effect estimation is based on the results of the Hausman test.

The study finds that human capital and income diversification significantly influence bank performance; however, the direction of the causality varies. While human capital has a positive effect, income diversification has a negative effect. Additionally, the interaction term has a negative and significant effect on bank performance, inferring that income diversification has an antagonistic effect on the human capital and bank performance relationship. For the control variable, liquidity and asset quality negatively affects bank performance while capitalization has a positive effect.

Human capital was measured as human capital efficiency (HCE), which is a quantitative measure of human capital, hence future studies can use qualitative measures. Also, the study focused on commercial banks in East Africa, future researcher may possibly consider other regions and industries, which would shed more insights.

The results of this paper provide valuable insights. Bank managers can get a better understanding of the impact of human capital on bank performance, and the need to invest more in human capital development. Further, the study cautions bank managers that engaging in non-lending activities might destroy the economic value of human capital and ultimately lower performance. The study also recommends that policymakers should address the obstacles to banks' income diversification, for instance relaxing regulations restricting diversification; this might enable banks to leverage related financial service activities for optimal utilization of human capital and improve banks' profitability.

While a good number of previous studies investigated the direct effect of human capital and income diversification on the performance of banks, this study examines the moderating role of income diversification on the relationship between human capital and performance of banks in East Africa.

Model-based systems engineering (MBSE) is an important approach for the transforming process from “document-centered” to “model centered” systems engineering mode in equipment development, which can effectively shorten the equipment development cycle and improve product design quality. This paper aims to understand if MBSE enables to support manufacturing and equipment development.

The paper opted a bibliometric analysis of MBSE in domain of advanced manufacturing from different perspectives such as publication volume, research team, sources and keyword co-occurrence.

Firstly, the application of MBSE in advanced manufacturing can be roughly divided into three stages. And MBSE has been widely implemented globally and has gradually formed several noteworthy teams. Secondly, this article has identified some high-quality sources, with a large number of publications and citations, the most influential publications focus on the practice or guidance of digital twins and intelligent manufacturing. Thirdly, research can be divided into six categories, including systems engineering, digitalization, intelligent manufacturing, product design, model and architecture and MBSE applications.

Because of the chosen research approach, the visualized network tends to lose certain information such as a few keywords may be inaccurately categorized.

This paper comprehensively study the research status of MBSE in advanced manufacturing and forecasts future research trends, emphasizing the combination of intelligent manufacturing and digitization.

This paper fulfills an identified need to understand the current application status and future development trends of MBSE.

This study examines the connection between different digital-twin characteristics and organizational control. Specifically, the study aims to examine whether the digital-twin characteristics exploration, guidance and gamification will affect formal and social control.

The study is based on an analysis of survey results from 139 respondents comprising applied university students who use digital twins.

The results offer an interesting contribution to the literature. The authors consider the digital-twin characteristics exploration, guidance and gamification and investigate their contribution to two types of organizational controls: formal and social. The results show that two characteristics, exploration and gamification, affect the extent to which digital twins can be utilized for social control. Exploration and guidance’s role is significant concerning the extent to which digital twins can be utilized for formal control.

This study contributes to literature by considering multiple digital-twin characteristics and their contribution to two different control outcomes. First, it diverges from previous technical-oriented research by investigating digital twins in a human context. Second, the study is the first to examine digital twins’ effects from an organizational control perspective systematically.

In order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.

First, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.

The cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.

This study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

This paper aims to comprehensively clarify the research status of thermal transport of supercritical aviation kerosene, with particular interests in the effect of cracking on heat transfer.

A brief review of current research on supercritical aviation kerosene is presented in views of the surrogate model of hydrocarbon fuels, chemical cracking mechanism of hydrocarbon fuels, thermo-physical properties of hydrocarbon fuels, turbulence models, flow characteristics and thermal performances, which indicates that more efforts need to be directed into these topics. Therefore, supercritical thermal transport of n-decane is then computationally investigated in the condition of thermal pyrolysis, while the ASPEN HYSYS gives the properties of n-decane and pyrolysis products. In addition, the one-step chemical cracking mechanism and SST k-ω turbulence model are applied with relatively high precision.

The existing surrogate models of aviation kerosene are limited to a specific scope of application and their thermo-physical properties deviate from the experimental data. The turbulence models used to implement numerical simulation should be studied to further improve the prediction accuracy. The thermal-induced acceleration is driven by the drastic density change, which is caused by the production of small molecules. The wall temperature of the combustion chamber can be effectively reduced by this behavior, i.e. the phenomenon of heat transfer deterioration can be attenuated or suppressed by thermal pyrolysis.

The issues in numerical studies of supercritical aviation kerosene are clearly revealed, and the conjugation mechanism between thermal pyrolysis and convective heat transfer is initially presented.

Provisions for the minimisation of human error are essential through governance structures such as recruitment, human resource allocation and education/training. As predictors of safety attitudes/behaviours, employees’ personality traits (e.g. conscientiousness, sensation-seeking, agreeableness, etc.) have been examined in relation to human error and safety education.

This review aimed to explore research activity on the safety attitudes of healthcare staff and their relationship with the different types of personalities, compared to other complex and highly regulated industries. A scoping review was conducted on five electronic databases on all industrial/work areas from 2001 to July 2023. A total of 60 studies were included in this review.

Studies were categorised as driving/traffic and industrial to draw useful comparisons between healthcare. Certain employees’ personality traits were matched to positive and negative relationships with safety attitudes/behaviours. Results are proposed to be used as a baseline when conducting further relevant research in healthcare.

Only two studies were identified in the healthcare sector.

The necessity for additional research in healthcare and for comparisons to other complex and highly regulated industries has been established. Safety will be enhanced through healthcare governance through personality-based recruitment, human resource allocation and education/training.

With China’s economic growth slowing down and the growth rate of fiscal revenue decreasing, the pressure on local government debts is further increasing. Under this background, it is of great significance to clarify the relation between local government debts and China’s economic growth in order to give full play to the positive role of local debts in stabling growth. The paper aims to discuss this issue.

Therefore, this paper explores the impact of Chinese local government debt on economic growth from theoretical and empirical aspects, respectively, and compares the regional differences between different debts and economic growth dynamics.

In the theoretical model part, this paper constructs a three-sector dynamic game model, under the two circumstances of whether local government is subject to debt constraints, and examines the relation between local government debt and economic growth and other variables through numerical simulation. Research shows that when the government is not constrained by debt, there is an inverted “U” relation between government debt and economic growth. When the government is constrained by debt, the economic growth rate gradually decreases as the government debt increases.

In the theoretical analysis part, this paper tries to estimate the amount of local debts under different calibers and examines the impact of different types of local government debts on China’s economic growth and their regional differences. The results show that excessive accumulation of government hidden debts in the eastern region is not conducive to economic growth, while explicit debts in the central and western regions significantly contribute to local economic growth. The results of empirical analysis are basically consistent with the predictions of the theoretical model.

Global climate change characterized by an increase in temperature has become the focus of attention all over the world. China is a sensitive and significant area of global climate change. This paper specifically aims to examine the association between agricultural productivity and the climate change by using China’s provincial agricultural input–output data from 2000 to 2019 and the climatic data of the ground meteorological stations.

The authors used the three-stage spatial Durbin model (SDM) model and entropy method for analysis of collected data; further, the authors also empirically tested the climate change marginal effect on agricultural productivity by using ordinary least square and SDM approaches.

The results revealed that climate change has a significant negative effect on agricultural productivity, which showed significance in robustness tests, including index replacement, quantile regression and tail reduction. The results of this study also indicated that by subdividing the climatic factors, annual precipitation had no significant impact on the growth of agricultural productivity; further, other climatic variables, including wind speed and temperature, had a substantial adverse effect on agricultural productivity. The heterogeneity test showed that climatic changes ominously hinder agricultural productivity growth only in the western region of China, and in the eastern and central regions, climate change had no effect.

The findings of this study highlight the importance of various social connections of farm households in designing policies to improve their responses to climate change and expand land productivity in different regions. The study also provides a hypothetical approach to prioritize developing regions that need proper attention to improve crop productivity.

The paper explores the impact of climate change on agricultural productivity by using the climatic data of China. Empirical evidence previously missing in the body of knowledge will support governments and researchers to establish a mechanism to improve climate change mitigation tools in China.