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Authorities have set up numerous security checkpoints during times of armed conflict to control the flow of commercial and humanitarian trucks into and out of areas of conflict. These security checkpoints have become highly utilized because of the complex security procedures and increased truck traffic, which significantly slow the delivery of relief aid. This paper aims to improve the process at security checkpoints by redesigning the current process to reduce processing time and relieve congestion at checkpoint entrance gates.

A decision-support tool (clearing function distribution model [CFDM]) is used to minimize the effects of security checkpoint congestion on the entire humanitarian supply network using a hybrid simulation-optimization approach. By using a business process simulation, the current and reengineered processes are both simulated, and the simulation output was used to estimate the clearing function (capacity as a function of the workload). For both the AS-IS and TO-BE models, key performance indicators such as distribution costs, backordering and process cycle time were used to compare the results of the CFDM tool. For this, the Kerem Abu Salem security checkpoint south of Gaza was used as a case study.

The comparison results demonstrate that the CFDM tool performs better when the output of the TO-BE clearing function is used.

The efforts will contribute to improving the planning of any humanitarian network experiencing congestion at security checkpoints by minimizing the impact of congestion on the delivery lead time of relief aid to the final destination.

This research investigates how to optimize storage location assignment to decrease the order picking time and the waiting time of orders in the staging area of low-temperature logistics centers, with the goal of reducing food loss caused by temperature abuse.

The authors applied ABC clustering to the products in a simulated database of historical orders modeled after the actual order pattern of a large cold logistics company; then, the authors mined the association rules and calculated the sales volume correlation indices of the ordered products. Finally, the authors generated three different simulated order databases to compare order picking time and waiting time of orders in the staging area under eight different storage location assignment strategies.

All the eight proposed storage location assignment strategies significantly improve the order picking time (by up to 8%) and the waiting time of orders in the staging area (by up to 22%) compared with random placement.

The results of this research are based on a case study and simulated data, which implies that, if the best performing strategies are applied to different environments, the extent of the improvements may vary. Additionally, the authors only considered specific settings in terms of order picker routing, zoning and batching: other settings may lead to different results.

A storage location assignment strategy that adopts dispersion and takes into consideration ABC clustering and shipping frequency provides the best performance in minimizing order picker's travel distance, order picking time, and waiting time of orders in the staging area. Other strategies may be a better fit if the company's objectives differ.

Previous research on optimal storage location assignment rarely considered item association rules based on sales volume correlation. This study combines such rules with several storage planning strategies, ABC clustering, and two warehouse layouts; then, it evaluates their performance compared to the random placement, to find which one minimizes the order picking time and the order waiting time in the staging area, with a 30-min time limit to preserve the integrity of the cold chain. Order picking under these conditions was rarely studied before, because they may be irrelevant when dealing with temperature-insensitive items but become critical in cold warehouses to prevent temperature abuse.

This study aims to improve a construction company's overall project delivery by utilising lean six sigma (LSS) methods combined with building information modelling (BIM) to design, modularise and manufacture various building elements in a controlled factory environment off-site.

A case study in a construction company utilised lean six sigma (LSS) methodology and BIM to identify non-value add waste in the construction process and improve sustainability.

An Irish-based construction company manufacturing modular pipe racks for the pharmaceutical industry utilised LSS to optimise and standardise their off-site manufacturing (OSM) partners process and leverage BIM to design skids which could be manufactured offsite and transported easily with minimal on-site installation and rework required. Productivity was improved, waste was reduced, less energy was consumed, defects were reduced and the project schedule for completion was reduced.

The case study was carried out on one construction company and one construction product type. Further case studies would ensure more generalisability. However, the implementation was tested on a modular construction company, and the methods used indicate that the generic framework could be applied and customized to any offsite company.

This is one of the few studies on implementing offsite manufacturing (OSM) utilising LSS and BIM in an Irish construction company. The detailed quantitative benefits and cost savings calculations presented as well as the use of the LSM methods and BIM in designing an OSM process can be leveraged by other construction organisations to understand the benefits of OSM. This study can help demonstrate how LSS and BIM can aid the construction industry to be more environmentally friendly.

This article aims to address the need for a more structured partnership between civilian and military healthcare, particularly in the context of cross-border threats in the EU. While both systems are driven by the same goal of providing high-quality healthcare services and achieving optimal patient outcomes, they operate under different national approaches and resources.

Two recent crises are presented as examples that highlight the necessity of cooperation between civilian and military medical systems. The Covid-19 Pandemic and the Ukrainian Conflict are described based on the experience gathered by the author as a member of the NATO Centre of Excellence for Military Medicine and form the base to shape a broader perspective on the future of civil-military interaction in healthcare at the European Union level.

The ability to deliver coordinated responses during crises depend on the level of interoperability, preparation and mutual understanding. To improve synergies, a structured partnership should be established, prioritizing common standards of care and shared best practices. Integrating military and civilian healthcare pathways can be especially beneficial in situations where patients are moved from the point of injury or sickness across different military and civilian structures to receive the most appropriate treatment and rehabilitation for their conditions.

The relationship between military and civilian healthcare systems is often discussed at multinational level, but a clear focus is lacking concerning their shared mission, distinct functions and potential for cross-border collaboration.

Project-based learning is one of the most effective methods of transferring academic knowledge and skills to real-world situations in higher education. However, its effectiveness is not much investigated focusing on the students' narrative. This study aims at evaluating the students' experience and perspective on adopting project-based learning in master by research and doctoral programmes for proactive skills development.

This study evaluates the self-reflection of 10 postgraduate students and their supervisor who have participated in developing a software tool for solar photovoltaics (PV) integrated building envelope design, management and the related education.

Findings reveal that the students have effectively improved their knowledge on the subject via collaborating with the industry, self-learning/observation, peer learning, problem-solving and teamwork. Dividing the project into student-led tasks has improved the decision-making and leadership skills, risks identification, planning and time management skills. The overall experience has (1) built up confidence in students, (2) enhanced their creativity and critical thinking and (3) improved their proactive skills and context knowledge.

A clear research gap can be seen in exploring the effectiveness of project-based learning for master by research and doctoral programmes, which mainly focus on extensive research. These programmes do not necessarily focus on developing students' proactive skills, which is the main requirement if they intend to work in the construction industry. This paper addresses the above research gap by demonstrating the effectiveness of project-based learning for developing the proactive skills in a research-intensive learning environment.

With the development of fracturing technology, the research of multi-well hydrofracturing becomes the key issue. Frac-hits in multi-well hydrofracturing has an important effect on fracture propagation and final production of fractured well; in the process of hydrofracturing, there are many implement parameters that can affect frac-hits, and previous studies in this area have not systematically targeted the influence of a single parameter on multi-well hydrofracturing. Therefore, it is of great significance to study the occurrence rule and influence of frac-hits for optimizing the design of fracturing wells.

Based on the proposed numerical models, the effects of different fracturing implement parameters (perforation cluster spacing, well spacing and injection rate) on frac-hits are compared in numerical cases. Through the analysis of fracture network, stress field and microseismic, the effects of different fracturing implement parameters on frac-hits and connections are compared.

The simulation results show that the effect of perforation cluster spacing and well spacing on frac-hits is greater than that of injection rate. Smaller well spacing makes it easier for fractures between adjacent wells to interact with each other, which increases the risk of frac-hits and reduces the risk of fracture connections. Smaller perforation cluster spacing results in larger individual fracture lengths and greater deflection angles, which makes the possibility of frac-hits and connections greater. The lower the injection rate, the lower the probability of frac-hits.

In this study, the influence of different fracturing implement parameters on frac-hits and connections in multi-well hydrofracturing is studied, and the mechanism of frac-hits and connections is analyzed through fracture network, stress field and microseismic analysis. Different simulation results are compared to optimize fracturing well parameter design and provide reference for engineering application.

With increasing demand to enhance collaborative practices in Degree Apprenticeship (DA) programmes like Quantity Surveying Degree Apprenticeships (QSDA), there is a notable lack of models supporting employer engagement, particularly in curriculum design and delivery. This study aims to fill this gap.

A qualitative research approach was employed, utilising semi-structured interviews, focus groups and questionnaires to gather stakeholder perspectives involved in QSDA programmes in England. This process aimed to identify key practice areas, collaboration process and enablers needed to conceptualise a collaborative model for employer engagement in QSDA curriculum design and delivery.

The model highlights four collaborative stages, four practice areas, fourteen focus actions, and twelve enablers essential for provider-employer collaborations in QSDA curriculum design and delivery.

This study introduces a novel curriculum design model emphasising the collaboration process and enablers for provider-employer engagement. It offers new insights for QSDA programme curriculum development and is the first to address this area, contributing to the literature on Degree Apprenticeships in built environment education.

Diabetes is one of the life-threatening chronic diseases, which is already affecting 422m people globally based on (World Health Organization) WHO report as at 2018. This costs individuals, government and groups a whole lot; right from its diagnosis stage to the treatment stage. The reason for this cost, among others, is that it is a long-term treatment disease. This disease is likely to continue to affect more people because of its long asymptotic phase, which makes its early detection not feasible.

In this study, the authors have presented machine learning models with feature selection, which can detect diabetes disease at its early stage. Also, the models presented are not costly and available to everyone, including those in the remote areas.

The study result shows that feature selection helps in getting better model, as it prevents overfitting and removes redundant data. Hence, the study result when compared with previous research shows the better result has been achieved, after it was evaluated based on metrics such as F-measure, Precision-Recall curve and Receiver Operating Characteristic Area Under Curve. This discovery has the potential to impact on clinical practice, when health workers aim at diagnosing diabetes disease at its early stage.

This study has not been published anywhere else.

This paper provides novel evidence on the role of gender in the performance of university students, which is particularly relevant to the debate on the performance of female students in science, technology, engineering and mathematics (STEM) subjects.

Our approach relies on the metafrontier approach proposed by Huang et al. (2014), which measures students' efficiency within a given faculty and the impact of the faculty’s technology on students’ efficiency. We use a sample of 53,159 first-year students in 8 faculties from a large university in southern Italy from 2002–2003 to 2010–2011.

Students’ efficiency is relatively low, reflecting an essential role of unobserved heterogeneity. The different technologies of somewhat similar faculties have minimal impact on efficiency. There is a performance gap against women in five faculties, which on average is strongest for the faculties in the pure and applied science area. This gap increases with the proportion of female students and decreases with female lecturers.

The metafrontier has the benefit of providing relevant policy information on the drivers of student success by relying on data that universities routinely generate and preserve.

The stochastic metafrontier approach allows us to separate the group-specific frontiers from the metafrontier, yielding a decomposition of the efficiency scores of various faculties into technical efficiency scores and technological gaps.

Building Information modelling (BIM) has the potential to significantly minimise the quantity of construction waste (CW), but its adoption is low in construction waste management (CWM). This study examined the factors impeding the adoption of BIM in CWM efforts at the design and precontract stages from the perspective of construction stakeholders in Nigeria.

The study was informed by a post-positivism philosophical stance, which involved using the structured questionnaire as a quantitative research design tool for data collection via snowball sampling technique. The data garnered from construction experts were analysed using Cronbach’s alpha test, normalities test, Frequency, Percentage, Kendall’s coefficient of concordance and Chi-square tests, Analysis of variance (ANOVA), and exploratory factors analysis (EFA).

The study concluded that the awareness of BIM potential for CWM is high, but the adoption in waste management (WM) is low. The factor analysis reduced the twenty assessed factors into four key clusters of impediments to BIM adoption in CWM: (1) knowledge and resistance barriers, (2) support and interest barriers, (3) interoperability and experts' factors, and (4) economic barriers. These factors are critical impediments to BIM-enabled CWM at the design and precontract stage, and there was no significant statistical difference in their rating by the construction stakeholders in Nigeria.

Studies on the impediments to BIM adoption in CWM efforts, primarily at the design and pre-contract stages in emerging countries are scarce. This sought to fill this literature gap by establishing the critical impediments that should be overcome to improve BIM use in CWM.