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The present study employs social network analysis (SNA) to demonstrate the extent to which various building information modeling (BIM) functions can be used to address significant issues faced by the Tanzanian public sector construction projects.

This study adopted secondary data obtained from a comprehensive literature review on core BIM functions and the underlying issues faced by the Tanzanian public sector construction projects. This study then adopted SNA for associating the BIM functions with relevant construction issues.

For Objective 1, the findings revealed that BIM can address 68% of significant issues faced by the Tanzanian public sector construction projects. For Objective 2, the findings revealed that the identified functions mainly addressed issues in the early phases of the project. Finally, for Objective 3, the most effective function was “spatial coordination.”

This literature-based study does not fully capture both the current contextual issues faced by the industry and the BIM capability of stakeholders involved. In addition, this research does not distinguish between public project size and type which can influence the types of issues faced and consequently the use of BIM function. Accordingly, the research presented in this study needs to be complemented by on-the-ground feedback of industry stakeholders and needs to investigate how project size and type impacts the types of issues that emerge and the use of BIM.

With respect to practice, the findings of the present study highlight key BIM functions practitioners can begin to target.

In Tanzania, public sector construction projects contribute greatly to social development of Tanzania's population. Owing to the current state of public sector projects underperforming and the negative impact the projects have on the country's development, an intervention measure such as BIM has the potential to enhance the effective and efficient delivery of these projects and thereby promote the social development of the country's population.

With respect to theory, this study demonstrates how core functions of BIM can be mapped with various construction-related issues in order to evaluate the efficacies of the BIM-based investments for improving overall performance in the public sector projects. With respect to practice, the method illustrated in the present study can be applied by policymakers and practitioners to identify core BIM functions to target to address pressing contextual issues faced by public sector projects in the respective contexts.

Clinical staff working in mental health services experience high levels of work-related stress, burnout and poor well-being. Increased levels of stress, burnout, depression and anxiety and poorer mental well-being among health-care workers are associated with more sick days, absenteeism, lower work satisfaction, increased staff turnover and reduced quality of patient care. Virtual reality (VR) relaxation is a technique whereby experiences of pleasant and calming environments are accessed through a head-mounted display to promote relaxation. The purpose of this paper is to describe the design of a study that assesses the feasibility and acceptability of implementing a multi-session VR relaxation intervention amongst mental health professionals, to improve their relaxation levels and mental well-being.

The study follows a pre–post-test design. Mental health staff will be recruited for five weeks of VR relaxation. The authors will measure the feasibility and acceptability of the VR relaxation intervention as primary outcomes, alongside secondary outcomes evaluating the benefits of VR relaxation for mental well-being.

The study aims to recruit 20–25 health-care professionals working in both inpatient and specialist community mental health settings.

Research indicates the potential of VR relaxation as a low-intensity intervention to promote relaxation and reduce stress in the workplace. If VR relaxation is shown to be feasible and acceptable, when delivered across multiple sessions, there would be scope for large-scale work to investigate its effectiveness as an approach to enable health-care professionals to de-stress, relax and optimise their mental well-being. In turn, this may consequently reduce turnover and improve stress-related sick leave across health-care services.

Reducing aircraft fuel consumption has become a paramount research area, focusing on optimizing operational parameters like speed and altitude during the cruise phase. However, the existing methods for fuel reduction often rely on complex experimental calculations and data extraction from embedded systems, making practical implementation challenging. To address this, this study aims to devise a simple and accessible approach using available information.

In this paper, a novel analytic method to estimate and optimize fuel consumption for aircraft equipped with jet engines is proposed, with a particular emphasis on speed and altitude parameters. The dynamic variations in weight caused by fuel consumption during flight are also accounted for. The derived fuel consumption equation was rigorously validated by applying it to the Boeing 737–700 and comparing the results against the fuel consumption reference tables provided in the Boeing manual. Remarkably, the equation yielded closely aligned outcomes across various altitudes studied. In the second part of this paper, a pioneering approach is introduced by leveraging the particle swarm optimization algorithm (PSO). This novel application of PSO allows us to explore the equation’s potential in finding the optimal altitude and speed for an actual flight from Algiers to Brussels.

The results demonstrate that using the main findings of this study, including the innovative equation and the application of PSO, significantly simplifies and expedites the process of determining the ideal parameters, showcasing the practical applicability of the approach.

The suggested methodology stands out for its simplicity and practicality, particularly when compared to alternative approaches, owing to the ready availability of data for utilization. Nevertheless, its applicability is limited in scenarios where zero wind effects are a prevailing factor.

The research opens up new possibilities for fuel-efficient aviation, with a particular focus on the development of a unique fuel consumption equation and the pioneering use of the PSO algorithm for optimizing flight parameters. This study’s accessible approach can pave the way for more environmentally conscious and economical flight operations.