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This paper describes the development of a digital role play game (RPG) designed to help construction apprentices to better communicate with their supervisors about issues with the potential to impact on their physical and psychological health and safety.

A participatory approach was adopted to utilise the knowledge and insights of the target users to inform the digital RPG development. Apprentices and supervisors were interviewed to identify characteristics of effective supervisor-apprentice communication, which became the RPG’s learning objectives. The scenarios constructed in the RPG were drawn from lived experiences shared by the apprentices in the interviews. During the development process, consultations were conducted with an advisory committee comprising of apprentices and supervisors to improve the realism of the RPG scenarios.

Three scenarios were developed for the RPG. In each scenario, players are asked to make decisions at various interaction points about how the characters should respond to the unfolding and challenging situations. Scripts were developed for the game, which were acted out and motion captured to animate digital MetaHuman characters embedded in a virtual construction site. Two example situations are introduced in this paper to illustrate the development process.

To our knowledge, the RPG introduced is one of the first applications of digital game-based training in the construction industry. The adoption of a participatory design approach ensures that the game content relates to real-world experiences. The digital RPG is highly interactive and engaging in nature and presents a novel approach to developing “soft” skills in construction.

In this paper, based on the density functional theory (DFT) and finite element method (FEM), the elastic, buckling and vibrational behaviors of the monolayer bismuthene are studied.

The computed elastic properties based on DFT are used to develop a finite element (FE) model for the monolayer bismuthene in which the Bi-Bi bonds are simulated by beam elements. Furthermore, mass elements are used to model the Bi atoms. The developed FE model is used to compute Young's modulus of monolayer bismuthene. The model is then used to evaluate the buckling force and fundamental natural frequency of the monolayer bismuthene with different geometrical parameters.

Comparing the results of the FEM and DFT, it is shown that the proposed model can predict Young's modulus of the monolayer bismuthene with an acceptable accuracy. It is also shown that the influence of the vertical side length on the fundamental natural frequency of the monolayer bismuthene is not significant. However, vibrational characteristics of the bismuthene are significantly affected by the horizontal side length.

DFT and FEM are used to study the elastic, vibrational and buckling properties of the monolayer bismuthene. The developed model can be used to predict Young's modulus of the monolayer bismuthene accurately. Effect of the vertical side length on the fundamental natural frequency is negligible. However, vibrational characteristics are significantly affected by the horizontal side length.

The purpose of this paper is to investigate the effect of doping element on the structural, thermal properties, mechanical performance and the failure mechanism of hexagonal nano boron nitride (h-BN)-reinforced basalt fabric (BF)/epoxy composites produced by hand lay-up and vacuum bagging technique. h-BN particles doped to composite materials increased the tensile, bending and impact strength of the composite at certain rates while 1 Wt. % h- BN addition shows the highest tensile and flexural strength.

The epoxy resin was doped with h-BN nanopowder at the certain rates (0, 1, 2 and 4 Wt.%) and the epoxy: hardener ratios used in the study were selected as 80%: 20% by weight. Then, with the aid of a roller by hand lay-up method, a mixture of epoxy + hardeners containing nanoparticles and nanoparticle-free were fed onto BFs, 12 layers of each dimension 30 cm × 30 cm. The surplus epoxy resin was moved away from the composite sheets using the vacuum bagging process and left to cure at room temperature for 24 h. ASTM D3039 for tensile, D7264 for three-point bending and D256 for Izod impact test were performed for the mechanical tests. After the tensile test, the morphologies of the fracture surface were examined with a stereomicroscope and various failure mechanisms are highlighted.

In this study, a series of basalt/epoxy composites with h-BN nanopowders have been prepared to identify the effect of filler ratio on mechanical properties. It has been known from the results of mechanical experiments that the addition of h-BN improves the mechanical performance of materials at a certain rate. The tensile and flexural strengths of h-BN doped composites, increase for concentrations of 1 Wt.% h-BN, but decrease with the increasing content of it. The basalt/epoxy resin composite with higher mechanical properties could be a potential material in the automotive and aerospace industries.

The aim of this study is to contribute to literature within the context of this new combination of composites and their mechanical properties, failure mechanisms. It presents detailed characterization of each composite by using X-ray differaction (XRD), differential scanning calorimetry (DSC), fourier transform infrared spectroscopy (FT-IR) and scanning electron microscopy.

The purpose of this study was conducted at an enterprise that produces fasteners and is one of the leading companies in the sector in terms of market share. Possible defects in the coating of bolts and nuts either lead to products being scrapped or all of the coating process being repeated from beginning to end. In both cases, the enterprise faces a waste of time and excessive costs. Through this project, the six sigma theory and its means were effectively used to improve the efficiency and quality management of the company. The selection of the six sigma project has also contributed to the creation of various documents to be used for project screening and evaluation of financial results.

Six sigma is an optimization strategy that is used to improve the profitability of businesses, avoid waste, scrap and losses, reduce costs and improve the effectiveness of all activities to meet or exceed customers’ needs and expectations. Six sigma’s process improvement model, known as Definition-Measurement-Analysis-Improvement-Control, contributes to the economic and technical achievements of businesses. The normal distribution of a process should be within ±3 sigma of the mean. This represents a scale of 99.7% certainty. However, improving the process through the utilization of the six sigma rule, which accepts normal variabilities of processes twice as strict, will result in an error rate of 3.4 per million instead of 2,700 per million for each product or service.

Using six sigma practices to reduce the costs associated with low quality and to increase economic added value became a cultural practice. With this, the continuation of six sigma practices throughout the Company was intended. The annual cost reduction achieved with the utilization of six sigma practices can be up to $21,780. When time savings are also considered, a loss reduction of about $30,000 each year can be achieved. The coating thickness efficiency increased from 85% to 95% after the improvements made through the six sigma project. There is a significant increase in the efficiency of coating thickness. In addition, the coating thickness efficiency is also close to the target value of 95%–97%.

The results of the study were optimized with the help of deep learning. The performance of the model created in deep learning was quite close to the actual performance. This result implicates the validity of the improvement work. The results may act as a guide for the use of deep learning in new projects.

This study aims to compare the impact of Australian onshore and offshore immigration detention centres (IDCs) on detainees’ health and health-care events.

It uses data extracted from the Australian Government’s quarterly health reports from 2014 to 2017. These reports contain a range of data about the health and well-being of detainees, including complaints/presenting symptoms and number of appointments and hospitalisations. To compare onshore and offshore data sets, the authors calculated the rate of health events per quarter against the estimated quarterly onshore and offshore detention population. They ran a series of two-proportion z-tests for each matched quarter to calculate median z- and p-values for all quarters. These were used as an indicator as to whether the observed differences between onshore and offshore events were statistically significant.

The results suggest that adults detained onshore and offshore have substantial health needs, however, almost all rates were far higher in offshore detention, with people more likely to raise a health-related complaint, access health services and be prescribed medications, often at two to three times the rate of those onshore.

This paper adds to a modest body of literature that explains the health of people detained in Australian IDCs. To the best of the authors’ knowledge, this is the first paper to explore health service utilisation and a range of other variables found in the Australian Government’s quarterly health reports. These findings bolster the evidence which suggests that detention, and particularly offshore detention is particularly harmful to health.

The purpose of this paper was to gain a qualitative view of the participant experience of using home-based transcranial direct current stimulation (tDCS). Acceptability impacts patient preference, treatment adherence and outcomes. However, acceptability is usually assessed by rates of attrition, while multifaceted constructs are not reflected or given meaningful interpretations. tDCS is a novel non-invasive brain stimulation that is a potential treatment for major depressive disorder (MDD). Most studies have provided tDCS in a research centre. As tDCS is portable, the authors developed a home-based treatment protocol that was associated with clinical improvements that were maintained in the long term.

The authors examined the acceptability of home-based tDCS treatment in MDD through questionnaires and individual interviews at three timepoints: baseline, at a six-week course of treatment, and at six-month follow-up. Twenty-six participants (19 women) with MDD in a current depressive episode of at least moderate severity were enrolled. tDCS was provided in a bifrontal montage with real-time remote supervision by video conference at each session. A thematic analysis was conducted of the individual interviews.

Thematic analysis revealed four main themes: effectiveness, side effects, time commitment and support, feeling held and contained. The themes reflected the high acceptability of tDCS treatment, whereas the theme of feeling contained might be specific to this protocol.

Qualitative analysis methods and individual interviews generated novel insights into the acceptability of tDCS as a potential treatment for MDD. Feelings of containment might be specific to the present protocol, which consisted of real-time supervision at each session. Meaningful interpretation can provide context to a complex construct, which will aid in understanding and clinical applications.

Surface roughness has a serious impact on the fatigue strength, wear resistance and life of mechanical products. Realizing the evolution of surface quality through theoretical modeling takes a lot of effort. To predict the surface roughness of milling processing, this paper aims to construct a neural network based on deep learning and data augmentation.

This study proposes a method consisting of three steps. Firstly, the machine tool multisource data acquisition platform is established, which combines sensor monitoring with machine tool communication to collect processing signals. Secondly, the feature parameters are extracted to reduce the interference and improve the model generalization ability. Thirdly, for different expectations, the parameters of the deep belief network (DBN) model are optimized by the tent-SSA algorithm to achieve more accurate roughness classification and regression prediction.

The adaptive synthetic sampling (ADASYN) algorithm can improve the classification prediction accuracy of DBN from 80.67% to 94.23%. After the DBN parameters were optimized by Tent-SSA, the roughness prediction accuracy was significantly improved. For the classification model, the prediction accuracy is improved by 5.77% based on ADASYN optimization. For regression models, different objective functions can be set according to production requirements, such as root-mean-square error (RMSE) or MaxAE, and the error is reduced by more than 40% compared to the original model.

A roughness prediction model based on multiple monitoring signals is proposed, which reduces the dependence on the acquisition of environmental variables and enhances the model's applicability. Furthermore, with the ADASYN algorithm, the Tent-SSA intelligent optimization algorithm is introduced to optimize the hyperparameters of the DBN model and improve the optimization performance.

This study aims to investigate the impacts of pandemic-related media coverage on younger hospitality and tourism employees’ ageist attitudes toward older people by applying the media priming theory and the terror management theory.

This study takes a mixed-method approach through an online survey. A total of 416 usable responses are collected from current US hospitality and tourism employees under 55 years. Qualitative data were analyzed using word cloud. Partial least squares structural equation modeling is then used to test the hypothesized model.

The study’s results show that younger employees' cognitive reaction negatively affects aging anxiety and intergenerational tension, which subsequently influence their willingness to work with older people. Negative media-induced emotions are positively associated with aging anxiety, whereas positive emotions exert no significant impact. Intergenerational contact frequency moderates the effect of intergenerational tension on younger employees’ willingness to work with older people.

This study’s findings contribute to the hospitality and tourism workforce literature by considering the priming effects of media coverage on younger employees’ attitudes toward self-aging and the older group. This study also offers managerial insights on developing effective age-inclusion interventions to reduce workplace ageism in the post-pandemic era.

Existing hospitality and tourism studies on older workers are scant and largely descriptive. To the best of the authors’ knowledge, this study is the first study that assesses the effects of pandemic-related media coverage on workplace ageism toward older people among the current hospitality and tourism workforce.

The study aims to analyse the structural relationships of authenticity, health concern and sustainable intelligence in the farm restaurant context. Different types of restaurants have been targeted to understand consumer behaviour; however, the behavioural intention of visitors dining at the farm restaurants was rarely explored.

With the backdrop of the theory of planned behaviour (TPB), this study highlights the understanding, particularly on personal values associated with the behavioural intention of consumers visiting the farm restaurant. Data were collected, circulating questionnaires onsite and online at a farm restaurant. Structural equation modelling was employed to analyse the data.

Study findings reveal that personal values such as authenticity, health concern and sustainable intelligence positively influence the mediating constructs of TPB towards behavioural intention to revisit the farm restaurant.

This research might be the first one, exclusively focused on understanding the behavioural intention of the consumers visiting the farm restaurant, based on their personal values. This study specifically enriches the farm restaurant literature from the academic perspective and offers insights to farm restaurant owners and managers about the priorities of the consumers visiting the farm restaurant.

Ireland’s ageing population has resulted in an increasing number of older adults living with frailty. Despite growing attention towards older adults’ and health professionals’ perspectives of frailty, occupational therapy research is limited. This study aims to explore occupational therapists’ perceptions of frailty and how their perceptions impact their approach to the assessment and management of frailty.

Using qualitative descriptive design, 19 occupational therapists working with older adults participated in online focus groups. Data were analysed using thematic analysis.

Perceptions of occupational therapists were constructed into three main themes: conceptualising frailty; management of frailty; and advancing frailty practice. Findings indicate that occupational therapists perceived frailty as a multidimensional concept but highlight a reluctance to use frailty terminology with patients. Findings also suggest that although occupational therapists are involved in provision of care for older adults living with frailty, the profession’s scope is not optimised in the assessment and management of frailty.

Findings provide insight into occupational therapists’ perceptions of frailty. Development of a shared understanding of frailty between clinicians and patients and enhancement of undergraduate frailty education are recommended to progress occupational therapy’s role in frailty management.