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Proper prediction of productivity can enable the enhanced estimation, realistic scheduling, and accurate cost forecasting of construction processes. Due to the existence of different labor sources (unionized and non-unionized), the prediction of productivity is still a significant problem in India. Moreover, the construction procurement processes and on-site performance are the predominant elements that can result in improved project outcomes. Thereby, the consideration of labor constraints and site conditions will play an important role in productivity improvement.

This study investigates the factors affecting construction site productivity. A total of 28 factors are grouped under 7 categories as follows: labor constraints, safety and quality procurements, material and equipment (ME), site management, project working condition, delay controls, construction methods and techniques, and external factors. Furthermore, by involving these factors, the questionnaire survey was conducted among Indian construction practitioners. As a result, 204 responses were received and the data were analyzed using a reliability test, relative importance index (RII), and analysis of variance (ANOVA).

The result of this study highlighted the importance of strategic construction management activities in terms of effective planning of ME, planning and realistic scheduling of construction activities, proper communication, information sharing, etc. Thus, this study provides a clear insight to the Indian construction practitioners in determining the effect of these site factors on the successful execution of their projects.

In this paper, the problem of construction productivity in India and its causes are explained effectively. This study examines the preference of labor contract, labor source, and most importantly, the factors affecting site productivity. Moreover, the other lagging issues regarding the management of construction activities are also described in detail.

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.

The purpose of the paper is to investigate photochemical machining characteristics of stainless steel (AISI 304-SS304) parts with a novel design are investigated experimentally from the aspect of process parameters. The effects of phototool pattern geometry, ultraviole (UV) exposure time and etching time on of AISI 304 were evaluated.

The designed semi-automated photochemical manufacturing (PCM) equipment consists of 4 units, which include UV exposure, etching, developing and surface cleaning units. Experimental procedure has been designed via Taguchi method. Results were evaluated via Analysis of Variance (ANOVA) method.

Etching time is the most effective factor in PCM quality of AISI 304 stainless steel. Surface roughness is sensitive to geometrical pattern of the phototool for PCM of AISI 304 UV exposure time is less influential on the PCM quality for stainless steel.

The designed PCM equipment prototype is not fully automated, which requires automation for part replacements into units. The effects of the temperature inside chemical processing units on process characteristics cannot be evaluated due to equipment limitations. The effects of surface cleaning time inside surface cleaning unit are not analyzed.

The utilized PCM equipment is semi-automated equipment, with which the process parameters such as etching time, surface cleaning time, UV exposure time and developing time can be controlled. Different from literature, the effects of phototool pattern geometries on the photochemical machining quality parameters are evaluated for the processing of AISI 304. The effects of processing parameters on dimensional accuracy, which is not common in the literature for AISI 304 stainless steel, are also evaluated.