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This study aims to explore the tower crane safety factors (TCSFs) that influence tower crane safe operations (TCSOs) in modular integrated construction (MiC). It evaluates how the adoption of these factors contributes to achieving TCSOs and promoting sustainable practices (SPs) within MiC.

To achieve this aim, the study employed a systematic search to ensure a comprehensive collection of variables. Additionally, it conducted a questionnaire survey involving professionals and utilized a brainstorming technique to categorize the different variables. Finally, partial least squares structural equation modeling (PLS-SEM) was employed to test the relationship between TCSOs and SPs.

The results of measurement models indicated strong convergent and discriminant validity, with each observed variable correlating well with its latent variable. Moreover, a significant positive correlation between TCSOs and SPs was evidenced by a path coefficient (β = 0.755) and a p-value of <0.05. Lastly, the structural model revealed that the independent variables strongly influence the dependent variable (i.e. SPs) by 57%, underscoring safety's pivotal role in advancing sustainability within MiC projects. These findings provide empirical evidence that improving tower crane safety can directly enhance sustainable practices, offering a dual benefit of increased safety and sustainability for the construction sector.

This study makes a unique and previously undiscovered contribution to the field by identifying the TCSFs in MiC and employing a novel approach by utilizing PLS-SEM to create a unique mathematical model. It offers valuable insights into the relationship between TCSFs, TCSOs and SPs, thus contributing to methodological advancements within Safety Science and providing a foundation for future research and practical implementation in the construction industry.

This study underscores the critical importance of well-functioning sewer systems in achieving smart and sustainable urban drainage within cities. It specifically targets the pressing issue of sewer overflows (SO), widely recognized for their detrimental impact on the environment and public health. The primary purpose of this research is to bridge significant research gaps by investigating the root causes of SO incidents and comprehending their broader ecological consequences.

To fill research gaps, the study introduces the Multi-Phase Causal Inference Fuzzy-Based Framework (MCIF). MCIF integrates the fuzzy Delphi technique, fuzzy DEMATEL method, fuzzy TOPSIS technique and expert interviews. Drawing on expertise from developed countries, MCIF systematically identifies and prioritizes SO causes, explores causal interrelationships, prioritizes environmental impacts and compiles mitigation strategies.

The study's findings are multifaceted and substantially contribute to addressing SO challenges. Utilizing the MCIF, the research effectively identifies and prioritizes causal factors behind SO incidents, highlighting their relative significance. Additionally, it unravels intricate causal relationships among key factors such as blockages, flow velocity, infiltration and inflow, under-designed pipe diameter and pipe deformation, holes or collapse, providing a profound insight into the intricate web of influences leading to SO.

This study introduces originality by presenting the innovative MCIF tailored for SO mitigation. The combination of fuzzy techniques, expert input and holistic analysis enriches the existing knowledge. These findings pave the way for informed decision-making and proactive measures to achieve sustainable urban drainage systems.

This viewpoint aims to provide an overview of graduate employability in Lebanon from the perspective of the Dean of Olayan School of Business at the American University of Beirut, who is a reputable academic leader heading a world-ranked business school. The discussion also looks at the external factors that affect graduate employability in Lebanon with direct references to the Covid-19 pandemic and the economic crisis.

Through conversation with the Dean of a prominent business school in Lebanon, this viewpoint discusses several topics pertaining to the concept of graduate employability.

To boost graduate employability the focus should be on developing the curriculum, engaging with the alumni network, exploiting the board of governors and building on the school’s reputation and legacy.

Crises do offer new opportunities. Covid-19 pandemic has prepared employers to accept the idea of remote working, which has helped in boosting graduate employability in Lebanon.

This study synthesizes the role of artificial intelligence (AI) and automation in systematic literature reviews (SLRs), focusing in particular on efficiency, methodological quality and human–machine collaboration.

A systematic review methodology was applied, analyzing studies from Scopus and Web of Science databases to explore the use of AI and automation in SLRs. A final sample of 28 articles was selected through a rigorous and interdisciplinary screening process.

Our analysis leads to seven themes: human and machine collaboration; efficiency and time savings with AI; methodological quality; analytical methods used in SLRs; analytical tools used in SLRs; SLR stages AI is utilized for and living systematic reviews. These themes highlight AI’s role in enhancing SLR efficiency and quality while emphasizing the critical role of human oversight.

The rapid advancement of AI technologies presents a challenge in capturing the current state of research, suggesting the need for ongoing evaluation and theory development on human–machine collaboration.

The findings suggest the importance of continuously updating AI applications for SLRs and advocating for living systematic reviews to ensure relevance and utility in fast-evolving fields.

Integrating AI and automation in SLRs could democratize access to up-to-date research syntheses, informing policy and practice across various disciplines and redefining the researcher’s role in the digital age.

This review offers a unique synthesis of AI and automation contributions to SLRs, proposing a conceptual model emphasizing the synergy between human expertise and machine efficiency to improve methodological quality.

This paper aims to study the feasibility of proposed method to focus the electroporation ablation by mean of multi-output multi-electrode system.

The proposed method has been developed based on a previously designed electroporation system, which has the capabilities to modify the electric field distribution in real time, and to estimate the impedance distribution. Taking into consideration the features of the system and biological tissues, the problem has been addressed in three phases: modeling, control system design and simulation testing. In the first phase, a finite element analysis model has been proposed to reproduce the electric field distribution within the hepatic tissue, based on the characteristics of the electroporation system. Then, a control strategy has been proposed with the goal of ensuring complete ablation while minimizing the affected volume of healthy tissue. Finally, to check the feasibility of the proposal, several representative cases have been simulated, and the results have been compared with those obtained by a traditional system.

The proposed method achieves the proposed goal, as part of a complex electroporation system designed to improve the targeting, effectiveness and control of electroporation treatments and serve to demonstrate the feasibility of developing new electroporation systems capable of adapting to changes in the preplanning of the treatment in real-time.

The work presents a thorough study of control method to multi-output multi-electrode electroporation system by mean of a rigorous numerical simulation.