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This paper covers the development of a novel defect model for concrete highway bridges. The proposed defect model is intended to facilitate the identification of bridge’s condition information (i.e. defects), improve the efficiency and accuracy of bridge inspections by supporting practitioners and even machines with digitalised expert knowledge, and ultimately automate the process.

The research design consists of three major phases so as to (1) categorise common defect with regard to physical entities (i.e. bridge element), (2) establish internal relationships among those defects and (3) relate defects to their properties and potential causes. A mixed-method research approach, which includes a comprehensive literature review, focus groups and case studies, was employed to develop and validate the proposed defect model.

The data collected through the literature and focus groups were analysed and knowledge were extracted to form the novel defect model. The defect model was then validated and further calibrated through case study. Inspection reports of nearly 300 bridges in China were collected and analysed. The study uncovered the relationships between defects and a variety of inspection-related elements and represented in the form of an accessible, digitalised and user-friendly knowledge model.

The contribution of this paper is the development of a defect model that can assist inexperienced practitioners and even machines in the near future to conduct inspection tasks. For one, the proposed defect model can standardise the data collection process of bridge inspection, including the identification of defects and documentation of their vital properties, paving the path for the automation in subsequent stages (e.g. condition evaluation). For another, by retrieving rich experience and expert knowledge which have long been reserved and inherited in the industrial sector, the inspection efficiency and accuracy can be considerably improved.

Unconventional machining processes, particularly ultrasonic vibration cutting (UVC), can overcome such technical bottlenecks. However, the precise mechanism through which UVC affects the in-service functional performance of advanced aerospace materials remains obscure. This limits their industrial application and requires a deeper understanding.

The surface integrity and in-service functional performance of advanced aerospace materials are important guarantees for safety and stability in the aerospace industry. For advanced aerospace materials, which are difficult-to-machine, conventional machining processes cannot meet the requirements of high in-service functional performance owing to rapid tool wear, low processing efficiency and high cutting forces and temperatures in the cutting area during machining.

To address this literature gap, this study is focused on the quantitative evaluation of the in-service functional performance (fatigue performance, wear resistance and corrosion resistance) of advanced aerospace materials. First, the characteristics and usage background of advanced aerospace materials are elaborated in detail. Second, the improved effect of UVC on in-service functional performance is summarized. We have also explored the unique advantages of UVC during the processing of advanced aerospace materials. Finally, in response to some of the limitations of UVC, future development directions are proposed, including improvements in ultrasound systems, upgrades in ultrasound processing objects and theoretical breakthroughs in in-service functional performance.

This study provides insights into the optimization of machining processes to improve the in-service functional performance of advanced aviation materials, particularly the use of UVC and its unique process advantages.

Social engineering is crucial in today’s digital landscape. As technology advances, malicious individuals exploit human judgment and trust. This study explores how age, education and occupation affect individuals’ awareness, skills and perceptions of social engineering.

A quantitative research approach was used to survey a diverse demographic of Egyptian society. The survey was conducted in February 2023, and the participants were sourced from various Egyptian social media pages covering different topics. The collected data was analyzed using descriptive and inferential statistics, including independent samples t-test and ANOVA, to compare awareness and skills across different groups.

The study revealed that younger individuals and those with higher education tend to research social engineering more frequently. Males display a higher level of awareness but score lower in terms of social and psychological consequences as well as types of attacks when compared to females. The type of attack cannot be predicted based on age. Higher education is linked to greater awareness and ability to defend against attacks. Different occupations have varying levels of awareness, skills, and psychosocial consequences. The study emphasizes the importance of increasing awareness, education and implementing cybersecurity measures.

This study’s originality lies in its focus on diverse Egyptian demographics, innovative recruitment via social media, comprehensive exploration of variables, statistical rigor, practical insights for cybersecurity education and diversity in educational and occupational backgrounds.

Unlike traditional industries, the e-cigarette is an epoch-making innovative product originating in China and occupying an absolute competitive advantage in the international market. The traditional A-U model describes the laws and characteristics of technological innovation in developed countries. In contrast, the inverse A-U model depicts the process of “secondary innovation” in late-developing countries through digestion and absorption. This paper aims to find out that if the e-cigarette, as a “first innovation” industry in a late-developing country, conform to the A-U model or conform to the “inverse A-U model”.

This paper takes the patent data of e-cigarettes from 2004 to 2021 as the research object, and uses Python’s Jieba segment words to divide product innovation and process innovation, and then uses statistical analysis methods to conduct empirical analyses on these data.

Thus, an improved A-U model suitable for the e-cigarette industry is proposed. In this model, product innovation in the e-cigarette industry appeared earlier than process innovation, but the synchronous development of product and process innovation is not lagging. The improved A-U model in the e-cigarette industry is not only different from the traditional A-U model but also does not conform to the inverse A-U model.

It is conducive to expanding and clarifying the theoretical contribution and applicable boundaries of the A-U model and has sparked thinking and exploration of the A-U model in e-cigarettes and emerging industries.

On this basis, suggestions on the development path and countermeasures of the e-cigarette industry are put forward.

Based on the e-cigarette industry, this paper takes patents as the research object and provides the method of dividing product innovation and process innovation, and proposes an A-U model suitable for the e-cigarette industry on this basis. By comparing the traditional A-U model with the inverse A-U model in latecomer countries, the background and causes of e-cigarette A-U model heterogeneity are analyzed from different stages and overall morphology. Based on this, the heterogeneity characteristics of e-cigarette innovation are summarized and sorted out.

Construction sustainability (CS) is a strategic reaction to the sustainability expectations of the construction industry's external stakeholders. The extant literature has viewed the environmental, social and economic dimensions of CS as having independent effects on financial performance. Due to the influence of common stakeholders, however, interactions in these dimensions will be present in their effect on financial performance. Accordingly, this study identifies the mechanisms of the interactions between the three CS dimensions and how they jointly affect financial performance.

Content analysis of GRI reports of 60 large construction organisations, followed by a hierarchical regression analysis was used to identify the interactions between environmental, social and economic CS in their effect on financial performance.

Economic CS was found to indirectly, and not directly, affect financial performance, the effect being mediated by both environmental and social CS. Environmental CS was found to have a strong negative effect on financial performance, whilst social CS was found to have a strongly significant positive effect on financial performance.

The motivation for engaging in CS is that investment in economic CS will have a positive effect on both environmental and social CS outcomes, which, in turn can have a combined effect on financial performance.

This is one of the first studies investigating the effect of interactions between the environmental, social and economic CS dimensions on the financial performance of construction organisations. It is also one of the first studies that applies a sociotechnical framework to this relationship.