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The purpose of this review is to comprehensively consider the material properties and processing of additive titanium alloy and provide a new perspective for the robotic grinding and polishing of additive titanium alloy blades to ensure the surface integrity and machining accuracy of the blades.

At present, robot grinding and polishing are mainstream processing methods in blade automatic processing. This review systematically summarizes the processing characteristics and processing methods of additive manufacturing (AM) titanium alloy blades. On the one hand, the unique manufacturing process and thermal effect of AM have created the unique processing characteristics of additive titanium alloy blades. On the other hand, the robot grinding and polishing process needs to incorporate the material removal model into the traditional processing flow according to the processing characteristics of the additive titanium alloy.

Robot belt grinding can solve the processing problem of additive titanium alloy blades. The complex surface of the blade generates a robot grinding trajectory through trajectory planning. The trajectory planning of the robot profoundly affects the machining accuracy and surface quality of the blade. Subsequent research is needed to solve the problems of high machining accuracy of blade profiles, complex surface material removal models and uneven distribution of blade machining allowance. In the process parameters of the robot, the grinding parameters, trajectory planning and error compensation affect the surface quality of the blade through the material removal method, grinding force and grinding temperature. The machining accuracy of the blade surface is affected by robot vibration and stiffness.

This review systematically summarizes the processing characteristics and processing methods of aviation titanium alloy blades manufactured by AM. Combined with the material properties of additive titanium alloy, it provides a new idea for robot grinding and polishing of aviation titanium alloy blades manufactured by AM.

The purpose of this study is to reveal the mechanism of humble leadership inducing abusive supervision from the low-status compensation perspective, examining the mediation role of leader perceived thread to status. Besides, the moderation effect of regulatory focus on the mediation path is discussed.

This study conducted a three-wave longitudinal survey. The data was collected from 438 leaders and their employees in five Chinese enterprises. This study used Mplus 7.4 and adopted a bootstrapping technique for data analysis.

Humble leadership has a positive effect on leader perceived threat to status. Leader perceived threat to status plays a mediation role between humble leadership and leader abusive supervision. Leader regulatory focus is the “gate valve” that humble leadership fosters leader abusive supervision. That is, when the leader promotion focus is high, leader perceived threat to status bred by humble leadership is low, resulting in less abusive supervision. When the leader prevention focus is high, humble leadership brings relatively more abusive supervision through perceived threat to status.

This study explores why humble leadership breeds abusive supervision behaviors and reveals the mechanism behind the negative effect of humble leadership based on low-status compensation theory. This study not only promotes the continuous development of the field of humble leadership research through empirical research but also provides guidance for effectively suppressing the negative effects of humble leadership, promoting strengths and avoiding weaknesses and suppressing inappropriate management behaviors in management practice.

This paper aims to use active fine lane management methods to solve the problem of congestion in a weaving area and provide theoretical and technical support for traffic control under the environment of intelligent connected vehicles (ICVs) in the future.

By analyzing the traffic capacities and traffic behaviors of domestic and foreign weaving areas and combining them with field investigation, the paper proposes the active and fine lane management methods for ICVs to optimal driving behavior in a weaving area. The VISSIM simulation of traffic flow vehicle driving behavior in weaving areas of urban expressways was performed using research data. The influence of lane-changing in advance on the weaving area was evaluated and a conflict avoidance area was established in the weaving area. The active fine lane management methods applied to a weaving area were verified for different scenarios.

The results of the study indicate that ICVs complete their lane changes before they reach a weaving area, their time in the weaving area does not exceed the specified time and the delay of vehicles that pass through the weaving area decreases.

Based on the vehicle group behavior, this paper conducts a simulation study on the active traffic management control-oriented to ICVs. The research results can optimize the management of lanes, improve the traffic capacity of a weaving area and mitigate traffic congestion on expressways.

This paper aims to explore the effects of leadership style and trust in leadership on employees’ affective commitment under the epidemic situation.

A total of 580 valid questionnaires were collected online targeting the hospitality and tourism employees working from home during the particular period of the COVID-19 Coronavirus crisis. Structural equation modeling was used to analyze the data with AMOS software.

The findings indicated that perceived transformational leadership was a positive predictor of trust in leadership and affective commitment. In addition to the positive contribution to commitment, trust in leadership also mediated the relationship between transformational leadership and organizational commitment.

The current study contributes to the literature on leadership and organizational commitment. The results of this study may provide a valuable guide to organizations, leaders and young employees.

变革型领导对员工信任及员工情感承诺的影响研究

本文旨在研究在新冠疫情背景下, 变革型领导对员工信任度以及情感承诺的影响。

本文研究对象为旅游及酒店行业工作人员, 由于新冠疫情, 调查问卷通过线上的方式向居家办公的酒店工作人员进行发放, 调查结束共收集到580份有效问卷, 利用AMOS软件对收集到的数据进行结构方程分析。

本研究发现, 变革型领导对员工组织信任具有正向影响, 员工信任对员工的组织情感承诺具有正向影响, 变革型领导正向影响员工的组织情感承诺, 并且, 变革型领导通过增强员工信任度, 正向影响员工的组织情感承诺, 即员工信任在变革型领导和情感承诺中间起中介作用。

本研究为拓展企业管理领域研究做出了贡献, 本文研究结果验证了相关的领导理论及组织管理理论, 丰富了职业承诺领域的研究, 为组织、领导以及青年员工的职业发展提供了参考借鉴。

Investigación sobre la influencia del liderazgo transformacional en la confianza y el compromiso emocional de los empleados

Este artículo tiene como objetivo estudiar la influencia del liderazgo transformacional en la confianza y el compromiso emocional de los empleados bajo el impacto del Covid-19.

El objeto de investigación de este artículo es el personal del sector turístico y hotelero. Se recogieron un total de 580 cuestionarios válidos y se analizaron los datos recopilados mediante ecuación estructural utilizando el software AMOS.

Esta investigación encontró que el liderazgo transformacional tiene una influencia positiva en la confianza de los empleados, la confianza de los empleados tiene una influencia positiva en el compromiso emocional de los empleados, el liderazgo transformacional afecta positivamente el compromiso emocional de los empleados y la confianza de los empleados juega un papel intermediario entre el liderazgo transformacional y el compromiso emocional.

Esta investigación enriquece la investigación sobre la teoría del liderazgo y el compromiso organizacional, y proporciona una referencia para el desarrollo profesional de organizaciones, líderes y empleados jóvenes.

According to the problem of crude oil price forecasting, the purpose of this paper is to propose a multi-step prediction method based on the empirical mode decomposition, long short-term memory network and GM (1,1) model.

First, the empirical mode decomposition method is used to decompose the crude oil price series into several components with different frequencies. Then, each subsequence is classified and synthesized based on the specific periodicity and other properties to obtain several components with different significant characteristics. Finally, all components are substituted into a suitable prediction model for fitting. LSTM models with different parameters are constructed for predicting specific components, which approximately and respectively represent short-term market disturbance and long-term influences. Rolling GM (1,1) model is constructed to simulate a series representing the development trend of oil price. Eventually, all results obtained from forecasting models are summarized to evaluate the performance of the model.

The model is respectively applied to simulate daily, weekly and monthly WTI crude oil price sequences. The results show that the model has high accuracy on the prediction, especially in terms of series representing long-term influences with lower frequency. GM (1,1) model has excellent performance on fitting the trend of crude oil price.

This paper combines GM (1,1) model with LSTM network to forecast WTI crude oil price series. According to the different characteristics of different sequences, suitable forecasting models are constructed to simulate the components.

Currently, there is a dearth of research studies regarding macro analysis of the workforce productivity of the US construction industry. The purpose of this paper is to calculate the workforce productivity changes of the US construction industry from 2006 to 2016, with the number of laborers as input and value of construction industry as output.

The present study introduced the data envelopment analysis (DEA) based Malmquist productivity index model to measure the workforce productivity of the US construction industry from 2006 to 2016.

The results indicated that the workforce productivity of the US construction industry experienced a continuous decline, except for the increases from 2011 to 2013 and from 2014 to 2015. It was also shown that there were gaps in the workforce productivity development level among all states and nine regions in the US construction industry. Besides, the relationship between workforce productivity and four aspects, including real estate price, workforce, climate distribution and economic factors, was analyzed.

The calculation of the productivity of the US construction industry is based on the premise that the external environment is fixed and unchanged from 2006 to 2016, but the multi-level DEA model for further calculation is required for obtaining more effective conclusions.

This paper measures the workforce productivity of the US construction industry over the past 11 years, which added latest analysis and knowledge into the construction industry, providing decision-makers with advice and data support to formulate policies to improve workforce productivity.

This study provided both government decision-makers and industrial practitioners with important macro background environment information, which will facilitate the improvement of workforce productivity in the construction industry in different regions of the US.

The purpose of this paper is to assess the hydrogen embrittlement sensitivity of carbon gradient heterostructure materials and to verify the reliability of the scratch method.

The surface-modified layer of 18CrNiMo7-6 alloy steel was delaminated to study its hydrogen embrittlement characteristics via hydrogen permeation, electrochemical hydrogen charging and scratch experiments.

The results showed that the diffusion coefficients of hydrogen in the surface and matrix layers are 3.28 × 10⁻⁷ and 16.67 × 10⁻⁷ cm²/s, respectively. The diffusible-hydrogen concentration of the material increases with increasing hydrogen-charging current density. For a given hydrogen-charging current density, the diffusible-hydrogen concentration gradually decreases with increasing depth in the surface-modified layer. Fracture toughness decreases with increasing diffusible-hydrogen concentration, so the susceptibility to hydrogen embrittlement decreases with increasing depth in the surface-modified layer.

The reliability of the scratch method in evaluating the fracture toughness of the surface-modified layer material is verified. An empirical formula is given for fracture toughness as a function of diffused-hydrogen concentration.

This study aims to investigate the factors that affect the intention to use public mobile libraries and enhance the quality of mobile library services to attract and retain users.

A questionnaire survey was conducted with 391 valid users in China. Based on the stimulus–response theory and user individual characteristics, a model was developed to examine the factors influencing the intention to use public mobile libraries. The model was tested using statistical software, such as SPSS 25.0 and AMOS 24.0.

The results indicate that technological factors, content factors, individual factors and psychological factors significantly influence the intention to use public mobile libraries. The impact of system quality and perceived ease of use in technological factors is relatively balanced. Among content factors, information quality is the most significant, while information literacy has a greater influence compared to subjective norms in individual factors. In psychological factors, perceived matching and perceived pleasure both positively influence usage intention, while perceived cost has a negative impact.

Firstly, this study only investigates users’ intention to use, but intention does not necessarily equate to actual usage behaviour (King and He,2006). Future research can introduce new variables to explore users’ adoption and continuous usage behaviours. Secondly, this study does not differentiate between different types of mobile library users. Future research can consider different user types, such as potential users and current users, to investigate the similarities and differences in their willingness to adopt mobile library services. Thirdly, this study is primarily cross-sectional. Future research can consider longitudinal studies to provide more in-depth insights into user behaviour.

This paper identifies external and internal stimulus factors and conducts a comprehensive investigation into the factors influencing the intention to use public mobile libraries, thus providing generalizable research findings. Unlike previous studies, this research introduces the information literacy variable, enriching the model of factors affecting users' intention to use mobile libraries and yielding more comprehensive conclusions. Consequently, the study aims to be grounded in the actual usage ideas and intentions of diverse user groups, constructing a model that highlights factors influencing the intention to use public mobile library services.

From a social perspective, this study offers four implications for improving the utilization of public mobile libraries. Firstly, it is crucial to integrate digital resources, enhance information quality in public mobile libraries and improve platform usability. Secondly, adopting a user-oriented approach is essential to improve the service level of public mobile libraries and stimulate residents’ participation. Thirdly, efforts should be made to strengthen user information literacy and increase information utilization. Fourthly, top-level design improvements, effective promotion efforts and user behaviour guidance are essential for the success of public mobile libraries.

This study contributes to the improvement of public mobile library services and the advancement of modern public cultural services by identifying the key factors that drive the intention to use such services. The findings have practical implications for promoting high-quality development and enhancing the popularity of public mobile libraries.

This paper aims to present a systematic literature review and bibliometric analysis of research papers published on chat generative pre-trained transformer (ChatGPT), an OpenAI-developed large-scale generative language model. The study’s objective is to provide a comprehensive assessment of the present status of research on ChatGPT and identify current trends and themes in the literature.

A total of 328 research article data was extracted from Scopus for bibliometric analysis, to investigate publishing trends, productive countries and keyword analysis around the topic and 34 relevant research publications were selected for an in-depth systematic literature review.

The findings indicate that ChatGPT research is still in its early stages, with the current emphasis on applications such as natural language processing and understanding, dialogue systems, speech processing and recognition, learning systems, chatbots and response generation. The USA is at the forefront of publishing on this topic and new keywords, e.g. “patient care”, “medical”, “higher education” and so on are emerging themes around the topic.

These findings underscore the importance of ongoing research and development to address these limitations and ensure that ChatGPT is used responsibly and ethically. While systematic review research on ChatGPT heralds exciting opportunities, it also demands a careful understanding of its nuances to harness its potential effectively.

Overall, this study provides a valuable resource for researchers and practitioners interested in ChatGPT at this early stage and helps to identify the grey areas around this topic.