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The aging and deterioration of engineering building structures present significant risks to both life and property. Fiber Bragg grating (FBG) sensors, acclaimed for their outstanding reusability, compact form factor, lightweight construction, heightened sensitivity, immunity to electromagnetic interference and exceptional precision, are increasingly being adopted for structural health monitoring in engineering buildings. This research paper aims to evaluate the current challenges faced by FBG sensors in the engineering building industry. It also anticipates future advancements and trends in their development within this field.

This study centers on five pivotal sectors within the field of structural engineering: bridges, tunnels, pipelines, highways and housing construction. The research delves into the challenges encountered and synthesizes the prospective advancements in each of these areas.

The exceptional performance of FBG sensors provides an ideal solution for comprehensive monitoring of potential structural damages, deformations and settlements in engineering buildings. However, FBG sensors are challenged by issues such as limited monitoring accuracy, underdeveloped packaging techniques, intricate and time-intensive embedding processes, low survival rates and an indeterminate lifespan.

This introduces an entirely novel perspective. Addressing the current limitations of FBG sensors, this paper envisions their future evolution. FBG sensors are anticipated to advance into sophisticated multi-layer fiber optic sensing networks, each layer encompassing numerous channels. Data integration technologies will consolidate the acquired information, while big data analytics will identify intricate correlations within the datasets. Concurrently, the combination of finite element modeling and neural networks will enable a comprehensive simulation of the adaptability and longevity of FBG sensors in their operational environments.

In the era of social media, containing and managing online rumors poses a significant challenge. Therefore, a thorough investigation into the factors influencing rumor dissemination becomes increasingly crucial. Key rumor spreaders wield considerable influence over audience behavior and public opinion dissemination, making them pivotal in curbing the spread of rumors. This study aims to categorize these key spreaders and delve into the distinct characteristics of each category.

This paper introduces a method for identifying key rumor spreaders through social network analysis. By utilizing text mining and sentiment analysis on data from typical rumor events on Weibo, we extract 14 characteristics of key spreaders. Subsequently, we develop a method for classifying the roles of these key spreaders and conduct empirical research to validate our findings.

Our study reveals significant variations in the characteristics of key spreaders across different roles. These insights enable managers to implement differentiated management strategies for key spreaders based on their respective roles.

This research sheds light on the diverse characteristics exhibited by key rumor spreaders on social media, providing a novel reference point for enhancing the effectiveness of rumor intervention and control strategies.

Concerns over the pollution caused by internal combustion vehicles have increased owing to population and industrialization increment. Addressing the confrontations, the demand for electric vehicles (EVs) as a combustion engine substitute became necessary in responding to environmental worries from internal combustion. The development of bio lubricant in lubricating the sliding parts of EVs is required to maintain the sustainability idea and to improve the system performance, which this research tends to explore.

In this research, the enhancement of base Jatropha oil was done using polytetrafluoroethylene (PTFE) and hexagonal boron nitrate (h-BN) as additives. Different characterization was conducted on the new formulation to ascertain its anticorrosion tendency. The wear and friction behavior of the formulations on the tribo-pairs surfaces in contact were investigated using ball on flat tribometer to determine their tribological responsiveness as mineral lubricant alternative. To explore the surface topography, surface profilometer, scanning electron microscope and energy dispersive X-ray investigations were PTFE, lubrication and EV carried out.

The test’s input parameters were EVs’ usual load and sliding speed, and the addition concentrations for PTFE were 0.3 Wt.%, 0.4 Wt.%, 0.5 Wt.% and 0.6 Wt.%, whereas h-BN were 0.4 Wt.%, 0.8 Wt.% and 1.2 Wt.%, respectively. The study on corrosion demonstrated resistance when applied PTFE and h-BN additives in Jatropha oil. The analysis revealed that 0.5 Wt.% PTFE + 0.8 Wt.% h-BN concentrations significantly improved the tribological characteristics when compared to the base Jatropha oil. The application of formulations yielded percentage reduction of 8.67%, 10.98%, 7.34% and 7.35%, respectively, for 0.5% poly + 0.5% h-BN, 0.5% poly + 0.6% h-BN, 0.5% poly + 0.7% h-BN, 0.5% poly + 0.8% h-BN against base Jatropha oil under 20 N.

The formulation of PTFE and h-BN for electric transmission with wear and friction effects was accomplished in this paper. The mechanism of particle diffusing at the sliding contact on tribological behavior could be examined based on the created model of operation.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2023-0235/