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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.

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.

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.

To contribute to achieving the Sustainable Development Goals, this study aims to explore how to encourage innovative green behaviors among college students and the mechanisms behind the formation of green innovation behavior. Specifically, this study examines the influences of schools, mentors and college students themselves.

A multilevel, multisource study involving 261 students from 51 groups generally supported this study’s predictions.

Proenvironmental and responsible mentors significantly predicted innovative green behavior among college students. In addition, creative motivation mediated the logical chain among green intellectual capital, emotional intelligence and green innovation behavior.

The study findings offer new insights into the conditions required for college students to engage in green innovation. In addition, they provide practical implications for cultivating green innovation among college students.

The authors proposed and tested a multilevel theory based on the ability–motivation–opportunity framework. In this model, proenvironmental and responsible mentors, green intellectual capital and emotional intelligence triggered innovative green behavior among college students through creative motivation.

This chapter intends to provoke thought around assumptions about young people providing care, what influences how young carers are perceived and how stigma and judgement associated with caring are discussed. We conclude by emphasising the significance of the role as an educator in creating discussion about the breadth and diversity of care experiences. This role includes both educating young people about young caring and being mindful that your students may currently be or previously been a young carer.

Social media has become an inescapable part of our lives. However, recent research suggests that excessive use of social media may lead to fatigue and users’ disengagement. This study aims to examine which brand-related factors contribute to social media fatigue (SMF) and its subsequent role on driving lurking behaviors, particularly among young consumers.

Based on survey data from 282 young users of social media, a holistic model of brand-related drivers and outcomes of SMF was tested, emphasizing the contribution of brands’ social media presence to users’ disengagement.

Research shows that branded content overload and irrelevance, as well as branded ads intrusiveness significantly impact SMF, which in turn plays a mediating role between brand-related drivers and lurking behaviors. The authors further conclude that the impact of SMF on lurking is stronger for users who follow a larger set of brands.

The study contributes to social media research by addressing its “dark side” and empirically validating the role of brands’ social media presence in developing young users’ fatigue and disengagement. The study further adds to the scant literature on SMF, which was mostly developed outside the branding field. Research also provides valuable insights to brands on how to improve their social media performance.