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In large-scale environments, LIO-SAM (Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping) exhibits poor robustness due to the accumulation of errors caused by factors such as the prevalence of similar surroundings and the lack of features in certain open areas. Therefore, the purpose of this study is to optimize the loop detection module of LIO-SAM to reduce error accumulation and enhance mapping and localization performance.

Based on the LIO-SAM framework, the LinK3D (Linear Keypoints Representation for 3D LiDAR Point Cloud) feature extraction algorithm is integrated in the front end, while the BoW3D (Bag of Words for Real-Time Loop Closing in 3D LiDAR SLAM) loop detection algorithm is integrated in the back end. The features extracted by LinK3D serve as the range factors for the LiDAR, the BoW3D generates loop closure factors and these, along with inertial measurement unit (IMU) preintegration factors and global positioning system (GPS) factors, are added to the factor graph of LIO-SAM. This addition of constraints enhances the mapping and localization effects, optimizing the overall mapping and localization performance.

Based on the electrically controlled car, experiments were conducted in the experimental scenario proposed in this paper. Compared to LIO-SAM, the method presented in this paper significantly reduces cumulative errors. While ensuring real-time performance, it demonstrates superior mapping and localization effects.

This paper proposes and validates a method that integrates LinK3D, BoW3D and LIO-SAM, named LB-LIOSAM, which enhances the accuracy of feature extraction, optimizes the loop detection module of LIO-SAM and improves its mapping and localization performance in specific environmental scenarios.

This paper aims to review the studies on intersection control with connected and automated vehicles (CAVs).

The most seminal and recent research in this area is reviewed. This study specifically focuses on two categories: CAV trajectory planning and joint intersection and CAV control.

It is found that there is a lack of widely recognized benchmarks in this area, which hinders the validation and demonstration of new studies.

In this review, the authors focus on the methodological approaches taken to empower intersection control with CAVs. The authors hope the present review could shed light on the state-of-the-art methods, research gaps and future research directions.

Furniture plays a significant role in daily life. Advanced computational and manufacturing technologies provide new opportunities to create novel, high-performance and customized furniture. This paper aims to enhance furniture design and production by developing a new workflow in which computer graphics, topology optimization and advanced manufacturing are integrated to achieve innovative outcomes.

Workflow development is conducted by exploring state-of-the-art computational and manufacturing technologies to improve furniture design and production. Structural design and fabrication using the workflow are implemented.

An efficient transdisciplinary workflow is developed, in which computer graphics, topology optimization and advanced manufacturing are combined. The workflow consists of the initial design, the optimization of the initial design, the postprocessing of the optimized results and the manufacturing and surface treatment of the physical prototypes. Novel chairs and tables, including flat pack designs, are produced using this workflow. The design and fabrication processes are simple, efficient and low-cost. Both additive manufacturing and subtractive manufacturing are used.

The research outcomes are directly applicable to the creation of novel furniture, as well as many other structures and devices.

A new workflow is developed by taking advantage of the latest topology optimization methods and advanced manufacturing techniques for furniture design and fabrication. Several pieces of innovative furniture are designed and fabricated as examples of the presented workflow.

This study aims to provide a comprehensive overview of pro-environmental behavior (PEB) research within higher education institutions (HEIs), highlighting current trends and future challenges.

Using 198 journal articles from the Web of Science, the study conducts co-citation, bibliographic coupling and co-word analyses to map influential publications and forecast trends.

The co-citation analysis revealed three distinct clusters: value-driven environmental behavior, intention-based environmental behavior and green organizational practices and employee PEB. The bibliographic coupling and the co-word analysis revealed more nuanced clusters, holistically identifying academic activities towards PEB. The authors conclude that more strategic and PEB-oriented HEI’s actions are crucial due to the social responsibility of the universities for sustainable development.

This paper provides valuable insights into the expanding area of PEB research and climate leadership empowerment within HEIs. The practical implications of this research are significant for HEIs. It guides the creation of effective policies and interventions to foster sustainable behavior and reduce environmental harm. The study shows the development of educational programs and campaigns promoting sustainable practices among individuals and communities, emphasizing the role of HEIs in cultivating a sustainability-conscious generation.

This study aims to present the Chinese entrepreneurial environment and explore Chinese tertiary students’ online-startup motivation on live streaming platforms. Based on the COM-B behaviour changing theory, this paper discovers various influencing factors from environmental opportunity and personal capability aspects. It analyses their effects under the cooperative system established among official departments, industries and universities. Meanwhile, considering social and cultural control, it also refers to the uncertainty-avoidance dimension from the Hofstede cultural theory and re-evaluates its influence on Chinese tertiary students’ online-startup motivation.

The authors analyse 474 responses from online questionnaires through partial least squares path modelling and variance-based structural equation modelling. The paper claims that environmental opportunity and personal capability factors positively affect students’ online-startup motivation, but uncertainty-avoidance thinking plays a negative role. The study also measures the importance-performance map analysis to explore additional findings and discuss managerial implications.

Both platform support and official department support positively impact Chinese tertiary students’ online-startup motivation and entrepreneurial skills learned from universities are beneficial for them to build online-startup confidence. Meanwhile, influenced by the cooperative system implemented among official departments, industries and universities, official department support positively affects platform support and entrepreneurial skills. Conversely, influenced by Chinese traditional Confucian culture, uncertainty-avoidance thinking negatively affects tertiary students’ online-startup motivation.

This paper demonstrates the analysis of Chinese tertiary students’ online-startup motivation drawing on the COM-B behaviour changing and Hofstede cultural theories. Specifically, this study divides influencing factors into three specific aspects as follows: environmental opportunity, personal capability and social and cultural control. Unlike existing research applying traditional research models, the combination of the COM-B behaviour changing theory and the Hofstede cultural theory could be conducive to making the research model reflect influencing factors and present their different relationships.

Urging people to avoid stockpiling was a common declaration made by governments during the COVID-19 pandemic outbreak, yet empty supermarket shelves and supply shortages of basic products were observed worldwide. This study aims to (a) identify the factors that activate consumer personal norms towards socially responsible behaviours, specifically resisting stockpiling, and (b) examine how fear moderates the link between personal norms and consumer engagement in stockpiling during public crises.

The study recruited a sample of US consumers who were responsible for household grocery shopping during the COVID-19 pandemic. A total of 593 individuals participated in the study, and the collected data were analysed using structural equation modelling.

The results show that awareness of the negative consequences of stockpiling and a sense of personal responsibility for those consequences activate personal norms towards responsible shopping during public crises. However, perceived fear has the opposite effect, encouraging stockpiling. In addition, fear weakens the negative relationship between personal norms and stockpiling.

This study extends the norm activation model and indicates that personal norms may not always promote responsible behaviours when fear is high. It is unique in that it sheds light on non-mainstream responsible consumption behaviours (e.g. resisting stockpiling), and the interaction between consumption and social responsibility.