Rui Feng

1 month ago | nature.com | Jian Liu |Rui Feng |Hanqiang Tang

Studies of the evolutionary law of construction accidents and the formulation of effective risk assessments are crucial for ensuring construction safety and reducing accidents. However, existing research often focuses exclusively on one of the four critical perspectives: human, facilities, environment, and management, with limited systematic theoretical analysis. Current risk assessments typically emphasized the impact of risks at specific points in time, neglecting the cumulative effects of risks over extended periods. This study has explored how hazardous and harmful factors affect the evolution of accidents, then has established a risk assessment model utilizing average mutual information theory. The findings indicate that “Command violations”, “Command errors”, and “Illegal operations” are the primary direct causes, while “Inadequate occupational safety and health management structure and staffing” and “Inadequate or unimplemented occupational health management system” are key management factors. In addition, it also provides practical guidance for construction enterprises to strengthen safety management from aspects such as safety production investment and safety management system integration. These contributions are expected to significantly improve the safety level of construction projects and reduce the occurrence of accidents.

Jan 15, 2025 | pubs.rsc.org | Jie Chen |Rui Feng |Peng Su |Tong Zhou

Highly linear wearable ionic gel based on self-assembled discoid liquid crystal towards human motion monitoring The development of ionic gel with high flexibility, wide operating temperature range, and excellent physicochemical stability is crucial for the next generation of wearable flexible strain sensors.

Jan 15, 2025 | mdpi.com | Junxian Tang |Peijuan Wang |Rui Feng |QING LI

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Jul 20, 2024 | arxiv.org | Rui Feng

May 22, 2024 | analyticalsciencejournals.onlinelibrary.wiley.com | Rui Feng |Sheng Wang |Zhu Wang |Tongtong Liu

Supporting Information Filename Description bmc5894-sup-0001-Supplementary_Materials.docxWord 2007 document , 437 KB Figure S1. Hierarchical cluster analysis of VOWE. Note: Different letters reveal the degrees of association among the samples. S1–S16 represent the chromatographic fingerprints of 16 VOWE samples. Figure S2. Score plots of PCA models of VOWE. Note: 1–4, Xiangyang Hubei, XY HB; 5–8, Nanyang Henan, NY HN; 9–12, Liupanshui Guizhou, LPS GZ; 13–16, Luan Anhui, LA AH. Figure S3.