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Contemporary interpretations of mental health recovery emphasize the need to understand better the lived experience of people with mental health conditions and how they define the idea of recovery. While traction for such ideas has been building in many western countries, the recovery movement is still in its early stages within most Asian countries. Hence, this study aims to add to this growing effort by understanding various factors that influence the recovery of people with mental health conditions in Singapore.

Braun and Clarke’s thematic analysis was used on the qualitative data provided by 21 participants.

Four themes were revealed: double-edged nature of social support, challenges accessing mental health support, personalized coping strategies and societal influences. As a result, the authors could better understand various factors that influenced the recovery process of people with mental health conditions in Singapore, such as the high costs and low levels of literacy regarding pathways to mental health services. In addition, the importance of societal influences on mental health recovery was highlighted, and their impact could be seen through the participants’ sharing.

These findings form a foundation from which future research and recovery-oriented interventions can work from to provide more tailored approaches to supporting people with mental health conditions.

This study identified cultural nuances to notions of recovery that are commonly found in personal recovery constructs that need to be considered when working within culturally diverse populations.

The paper aims to identify the critical constraints that impede heritage building (HB) facility managers from discharging their duties effectively and develop an index model to guide HB maintenance management (HBMM) practitioners to the critical constraints.

A literature review was conducted to identify HBMM constraints. Facilty management practitioners assessed the constraints' significance through an online survey. The factor analysis was used to shortlist and group the constraints, and the constraint clusters were analyzed by the fuzzy synthetic evaluation technique. A significant index cluster to determine HBMM constraints criticality was generated using the linear additive model.

Embracing a total of 16 HBMM constraints, the three clusters identified are: (1) managerial and inadequacy constraints, (2) pressure and bureaucracy constraints and (3) HB peculiarities constraints. Based on the generated significant index, the HB peculiarities cluster was identified as the most significant.

The study was conducted in a particular jurisdiction, limiting the generalizability of the result. Future research should address this limitation by covering more jurisdictions.

The significant index model (SIM) developed enables HBMM practitioners to objectively assess the criticality of HB constraints and facilitates them to effectively strategize and allocate resources for HBMM.

The SIM, which transforms subjective judgment into the objective assessment of the HBMM constraints' criticality, can assist practitioners, policymakers and other HBMM stakeholders in implementing strategies for the sustainability of HBs.

In smart cities striving for innovation, development, and prosperity, hydrogen offers a promising path for decarbonization. However, its effective integration into the evolving energy landscape requires understanding regional intricacies and identifying areas for improvement. This chapter examines hydrogen transport from production to utilization, evaluating technologies’ pros, cons, and process equations and using Analytic Hierarchy Process (AHP) as a Multi-Criteria Decision-Making (MCDM) tool to assess these technologies based on multiple criteria. It also explores barriers and opportunities in hydrogen transport within the 21st-century energy transition, providing insights for overcoming challenges. Evaluation criteria for hydrogen transport technologies were ranked by relative importance, with energy efficiency topping the list, followed by energy density, infrastructure requirements, cost, range, and flexibility. Safety, technological maturity, scalability, and compatibility with existing infrastructure received lower weights. Hydrogen transport technologies were categorized into three performance levels: low, medium, and high. Hydrogen tube trailers ranked lowest, while chemical hydrides, hydrail, liquid organic hydrogen carriers, hydrogen pipelines, and hydrogen blending exhibited moderate performance. Compressed hydrogen gas, liquid hydrogen, ammonia carriers, and hydrogen fueling stations demonstrated the highest performance. The proposed framework is crucial for next-gen smart cities, cutting emissions, boosting growth, and speeding up development with a strong hydrogen infrastructure. This makes the region a sustainable tech leader, improving air quality and well-being. Aligned with Gulf Region goals, it is key for smart cities. Policymakers, industries, and researchers can use these insights to overcome barriers and seize hydrogen transport tech opportunities.

Although many conventional level-set approaches can be used for segmenting images containing factors such as noise and intensity inhomogeneities, they still can impact the accuracy of the results seriously. To solve this problem, a level-set method for fast image segmentation based on pre-fitting and bilateral filtering is proposed.

Firstly, an improved bilateral filter was investigated for image preprocessing. Secondly, by computing the local average intensity of the preprocessed enhanced picture, two local pre-fitting functions were defined. Thirdly, a new level-set energy functional was defined. Finally, a new distance regularized energy term based on the logarithmic and polynomial functions is proposed to evolve the level-set function in a smooth state.

The experimental results demonstrate that the proposed model has an excellent segmentation capability for images with noise and intensity inhomogeneities and has different degrees of performance improvement compared with the mainstream models.

(C1) An improved bilateral filter was investigated and integrated into the model. (C2) Proposing two local pre-fitting functions by computing the local average intensity of the preprocessed enhanced image. (C3) Proposing a new level-set energy functional. (C4) A new distance regularized energy term based on the logarithmic and polynomial functions is proposed to evolve the level set function in a smooth state. (C5) Analyzing and comparing the performance of the proposed model with other similar models.

This study aims to assess the feasibility of laser powder bed fusion (LPBF) processing using as-received gas-atomized spherical Neodymium-Iron-Boron (NdFeB) powder (17–68 µm), compared to literature methods that sieve to a narrow size range (<40 µm).

The research involves single track and layer printing, process optimization and subsequent heat treatment and magnetic annealing. The experimental approach includes conducting systematic printing trials to assess the impact of various parameters on printed track and layer quality, and refining printing parameters through iterative testing. Heat treatment and magnetic annealing are applied to achieve the desired magnetic properties.

A minimum linear energy density of 0.10 J/mm is required for continuous track formation, with track width largely unaffected by varying linear energy densities. An optimal hatch spacing of approximately 42% overlap avoids layer defects, with 0.10 mm spacing suitable for layer thicknesses between 30 and 80 µm. A stable processing window for energy density (EA) of 0.6–1.0 J/mm² was identified, allowing cuboid printing despite some discontinuous tracks, indicating potential fusion issues. Maximizing volumetric energy density (EV) within this range correlates positively with part density, achieving 92% density, coercivity of 490 kA/m and remanence of 496 mT. Post-treatment, density increased to 96%, coercivity to 582 kA/m and remanence to 544 mT.

This study fills a significant gap in LPBF literature for NdFeB by using the original wider size range of spherical powder without sieving, demonstrating improved cost-effectiveness, material efficiency and build efficiency. These findings offer practical recommendations for addressing the challenges related to LPBF processing of NdFeB powder.

Competitiveness is an important personality trait that has been studied in various disciplines and has been shown to predict critical work outcomes at the individual level. Despite this, the role of competitiveness in groups and teams has received scant attention amongst organizational researchers. Aiming to promote future research on the role of competitiveness as both an adaptive and maladaptive trait – particularly in the context of work – the authors review competitiveness and its effects on individual and team stress and Well-Being, giving special attention to the processes of cohesion and conflict and situational moderators. The authors illustrate a dynamic multilevel model of individual and team difference factors, competitive processes, and individual and team outcomes to highlight competitiveness as a consequential occupational stressor. Furthermore, the authors discuss the feedback loops that inform the different factors, highlight important avenues for future research, and offer practical solutions for managers to reduce unhealthy competition.

In this article, the authors try to determine why and under what conditions consumers intend to buy green and what the consequences are. Relying on theories of reasoned action and theory of planned behaviour (TPB), the authors offer that the green purchase intention (GPI) is impressed by environmental and personality components. Provide statements about the determinants and key implications of such market identification.

This chapter explores the landscape of higher education in Singapore as the nation positions itself to emerge stronger after the pandemic. A focus on three major issues facing higher education − digital transformation, job readiness of graduates, and access to quality education, describes education-based initiatives for addressing these challenges in Singapore. Local autonomous universities are woven into the tapestry of sustainable growth and development within Singapore’s economy. Connections between the development of education-based initiatives are made to illustrate how these institutions of continuous learning are positioning for relevance considering current developments and to suggest some areas for enhancement for promoting lifelong learning opportunities for all.