Search Results (2,956)

Family caregivers provide up to 90% of care in Alberta’s communities and play an essential role in sustaining the province’s health and social care systems, yet they remain under-recognized and insufficiently supported. To address this gap, we co-designed the Alberta Family Caregiver Strategy and Action Plan (2024–2025), a provincial framework developed through participatory research and collective impact methods. Guided by principles of co-production, equity, and lived experience, the project engaged over 500 stakeholders, including caregivers, healthcare providers, educators, employers, and policymakers, through Phase 1 interviews (health/community leaders, n = 44; Family and Community Support Services (FCSS), n = 47; navigation experts, n = 9), Phase 2 co-design team consultations, and Phase 3 sector roundtables (n = 52). Using reflexive thematic analysis, we identified four foundational caregiver strategies, Recognition, Partnership, Needs Assessment, and Navigation, and four enabling conditions: Education, Workplace Supports, Policy and Research and Data Infrastructure. These elements were synthesized into an eight-priority Alberta Caregiver Strategy and Action Plan Framework, a practical way to connect validated priorities with coordinated, measurable implementation across settings. Participants emphasized four key enablers essential to making caregiver inclusion more feasible and sustainable: education, workplace supports, policy infrastructure, and research and evaluation. Findings highlight strong cross-sector consensus that caregiver inclusion must be embedded into routine practice, supported by consistent policy, and reinforced through provincial coordination with local adaptation. The Alberta Family Caregiver Strategy provides a practical, evidence-informed plan for transforming fragmented supports into a coherent, caregiver-inclusive ecosystem that strengthens both caregiver well-being and system sustainability. Full article

Greece lies within the Mediterranean global biodiversity hotspot and harbors exceptional plant richness and endemism, including numerous medicinal and aromatic plants (MAPs). These taxa underpin long ethnobotanical traditions and contemporary bioeconomy niches (culinary herbs, essential oils, phototherapeutics). The aim of this review is to map (i) the biodiversity knowledge base for Greek MAPs, (ii) recent ethnobotanical evidence, and (iii) sustainability pathways (conservation, cultivation, value chains, and regulation) in a Mediterranean context. The information is presented and analyzed in a critical manner. A total of 115 research studies were systematically reviewed based on the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines. Key findings highlight that (i) Greece is a regional plant-diversity hotspot with many MAP endemics in Lamiaceae; (ii) contemporary ethnobotanical knowledge persists and adapts; and (iii) strong sustainability levers exist through Natura 2000 coverage, Good Agricultural and Collection Practice (GACP) and European Medicines Agency (EMA) frameworks, and Protected Designation of Origin (PDO)/United Nations Educational, Scientific and Cultural Organization (UNESCO) recognitions (e.g., Krokos Kozanis saffron, Chios mastic), although threats from climate and land-use change remain significant. In conclusion, Greek MAPs combine high biodiversity value, living ethnobotanical traditions, and tangible bioeconomic opportunities. Their sustainable prospects depend on integrating habitat protection, GACP and FairWild Standard (FairWild)-aligned wild collection and cultivation, domestication of priority endemics, and climate-resilience planning, all supported by traceable value chains and Access and Benefit-Sharing (ABS)/Nagoya Protocol compliance. The review concludes with practical recommendations and a prioritized list of flagship taxa for “conservation through use.” Full article

Background: Care homes are complex care environments where supporting residents’ identity, wellbeing, and sense of personhood is central to person-centred care. Reminiscence is widely recognised as a psychosocial approach that can support these outcomes. However, existing evidence has largely focused on group-based interventions, with comparatively limited attention given to how individual reminiscence is implemented and sustained within care home practice. Methods: This study was an implementation-focused qualitative exploration of staff experiences of introducing and embedding individualised reminiscence in care home practice. Care home staff participated in four monthly workshops that introduced principles of individualised reminiscence and supported them to plan and implement reminiscence with at least one resident. Participants used either the InspireD digital reminiscence app (n = 19) or non-digital approaches such as life story books (n = 2), depending on local preferences and perceived suitability. Three focus groups were conducted with 21 care home staff to explore experiences of implementing individualised reminiscence and perceptions of its impact on residents, staff, and families. Data were analysed using reflexive thematic analysis. Results: Four interrelated themes were identified: (1) reminiscence within pressured systems; (2) resident experience and identity; (3) adapting and sustaining practice; and (4) families as partners in reminiscence. Participants described challenges associated with workload pressures, role expectations, and variability in family involvement, which influenced how reminiscence was adopted in practice. Despite these constraints, participants described perceived benefits for residents, including perceived improvements in mood, engagement, and expressions of identity. Participants also discussed perceived increased staff confidence, strengthened staff–resident relationships, and enhanced awareness of person-centred care practices. Conclusions: Findings highlight the perceived potential of individualised reminiscence to support person-centred and relational care in care homes, while identifying key contextual influences on implementation. Further research is needed to examine sustainability and effectiveness using comparative and mixed-method designs. Full article

Teachers’ language assessment literacy (LAL) encompasses the knowledge and competencies required to design and implement assessment practices that support learning. Although prior research has documented general trends in LAL development, less is known about how individual teachers, particularly student teachers, interpret, appropriate, and negotiate formative assessment (FA) task design within the context of initial teacher education (ITE). Adopting an in-depth qualitative case study approach, this study examines how a single student teacher in a Chinese initial teacher education developed her cognition and classroom practice related to FA tasks across a teaching methodology course and a practicum. Drawing on thematic analysis of semi-structure interviews, lesson plans, classroom observations, stimulated recall interviews, and reflective journals, the study traces developmental changes and the contextual factors shaping the student teacher’s LAL in relation to FA tasks. Findings show that the sustained engagement with FA task design supported more sophisticated understandings of FA, including (1) an increased recognition of the pedagogical necessity of incorporating authentic FA tasks into lesson planning, (2) a growing aspiration to implement FA-oriented instruction that promotes higher-order thinking, (3) an enhanced awareness of the empowering role of FA tasks in fostering students’ self-regulated learning, and (4) a more nuanced understanding of the challenges inherent in implementing FA practices. Meanwhile, the case illustrates how pre-existing assessment conceptions, school culture norms, and limited targeted mentoring can constrain LAL development in relation to FA. By providing a fine-grained account of developmental processes, this study offers insights into how ITE can mediate student teachers’ engagement with FA task design. The findings have implications for teacher education programs in other similar educational contexts, particularly regarding the integration of FA task design into assessment courses and the provision of sustained, context-sensitive support during teaching practicum. Full article

This study introduces an Impact Thinking Approach (ITA) as a strategic framework to strengthen traceability implementation in the fashion and textile industry. The research examines how ESG impact dimensions shape sustainable strategy definition and how traceability can act as a strategic enabler rather than a mere compliance tool. A mixed-method design combining a narrative literature review, content analysis of 69 sustainability sources, and a two-round Delphi study with 19 experts was employed to identify, evaluate, and prioritize impact drivers related to traceability adoption. The resulting ITA framework connects regulatory requirements, impact materiality, and traceability demands into a unified structure that clarifies the strategic relevance of environmental, social, and governance dimensions. Findings reveal that governance-related factors—particularly data transparency, stakeholder engagement, innovation capacity, and cross-sector partnerships—are the strongest enablers for activating effective traceability schemes. The framework provides practitioners with structured guidance for integrating traceability into sustainable business strategies and for developing impact-aligned KPIs and decision-making mechanisms. The study contributes theoretical insights into the ESG–traceability nexus and offers a practical model to support regulatory alignment, organizational readiness, and long-term strategic planning. Full article

The rapid adoption of generative artificial intelligence (AI) in higher education has intensified a pedagogical dilemma: while AI tools can increase immediate classroom engagement, they do not necessarily foster the self-regulated learning (SRL) capacities required for ethical and reflective professional practice, particularly in human-service fields. In this two-time-point, pre-post cohort-level (repeated cross-sectional) evaluation, we examined a six-week AI-integrated curriculum incorporating explicit SRL scaffolding among social work undergraduates at a Taiwanese university (pre-test N = 37; post-test N = 35). Because the surveys were administered anonymously and individual responses could not be linked across time, pre-post comparisons were conducted at the cohort level using independent samples. The participating students completed the AI-Enhanced Learning Attitude Scale (AILAS); this is a 30-item instrument grounded in the Technology Acceptance Model, Attitude Theory and SRL frameworks, assessing six dimensions of AI-related learning attitudes. Prior pilot evidence suggested an engagement regulation gap, characterized by relatively strong learning process engagement but weaker learning planning and learning habits. Accordingly, the curriculum incorporated weekly goal-setting activities, structured reflection tasks, peer accountability mechanisms, explicit instructor modeling of SRL strategies and simple progress tracking tools. The conducted psychometric analyses demonstrated excellent internal consistency for the total scale at the post-test stage (Cronbach’s α = 0.95). The independent-samples t-tests indicated that, at the post-test stage, the cohorts reported higher mean scores across most dimensions, with the largest cohort-level differences in Learning Habits (Cohen’s d = 0.75, p = 0.003) and Learning Process (Cohen’s d = 0.79, p = 0.002). After Bonferroni adjustment, improvements in the Learning Desire, Learning Habits and Learning Process dimensions and the Overall Attitude scores remained statistically robust. In contrast, the Learning Planning dimension demonstrated only marginal improvement (d = 0.46, p = 0.064), suggesting that higher-order planning skills may require longer or more sustained instructional support. No statistically significant gender differences were identified at the post-test stage. Taken together, the findings presented in this study offer preliminary, design-consistent evidence that SRL-oriented pedagogical scaffolding, rather than AI technology itself, may help narrow the engagement regulation gap, while the consolidation of autonomous planning capacities remains an ongoing instructional challenge. Full article

Accurate immobilization is critical in head and neck (H&N) radiotherapy to ensure precise dose delivery while minimizing irradiation of surrounding healthy tissues. However, conventional thermoplastic masks cannot secure 100% replicas of the patient’s surface and are often limited by mechanical weakness, patient discomfort, and workflow inefficiencies. Recently, the best replicas of the patient’s face have been obtained by exploring personal CT or MRI scans of patients that are used for manufacturing of immobilization masks. This study aimed to design and evaluate customizable immobilization masks using acrylonitrile butadiene styrene (ABS)-based composites reinforced with bismuth oxide (Bi₂O₃) and to compare their mechanical performance against commercial thermoplastic masks. ABS and ABS/Bi₂O₃ composite filaments (5, 10, and 20 wt%) were fabricated and characterized by tensile testing. A patient-specific virtual mask was modeled and subjected to finite element analysis (FEA) under clinically relevant loading scenarios, including neck flexion and lateral bending. Results were benchmarked against two commercial thermoplastic masks. ABS and ABS-based composites exhibited significantly higher stiffness (1.7–2.5 GPa) and yield strength (20–25 MPa) compared to commercial thermoplastics (0.25–0.3 GPa, ~7 MPa; p < 0.001). FEA simulations revealed markedly reduced displacement in ABS masks (1–5 mm at 2 mm thickness; <1 mm at 4 mm thickness) relative to commercial masks, which exceeded 20 mm under lateral load. Hybrid configurations with reinforced edges further optimized rigidity while limiting material usage. Customized ABS-based immobilization masks outperform conventional thermoplastics in mechanical stability and displacement control, with the potential to reduce planning margins and improve patient comfort. In addition, ABS-based masks can be recycled, and Bi₂O₃-filled composites can be reused for printing new immobilization masks, thus contributing to a reduced amount of plastic waste. These findings support their promise as next-generation immobilization devices for precision radiotherapy, warranting further clinical validation, workflow integration and sustainable implementation within a circular economy. Full article

Digital transformation in port logistics represents a profound and systemic shift in the way maritime trade and supply chain operations are designed, coordinated, and governed through the pervasive integration of advanced digital technologies and data-driven management practices. It extends beyond the mere digitization of paper-based documents into electronic formats and beyond the digitalization of isolated processes with IT tools. Transformation involves reconfiguring organizational structures, decision-making logics, and value creation models around connectivity, automation, and predictive intelligence. In practice, it includes the adoption of smart port technologies such as the Internet of Things, 5G communication networks, digital twins, blockchain-based trade documentation, and artificial intelligence applied to vessel scheduling and cargo planning. It also encompasses collaborative platforms like port community systems that link shipping companies, terminal operators, freight forwarders, customs, and hinterland transport providers into data-driven ecosystems. The purpose of digital transformation is not only to improve efficiency and reduce operational bottlenecks, but also to enhance resilience against disruptions, ensure sustainability in line with decarbonization goals, and reposition ports as orchestrators of trade networks rather than passive providers of physical infrastructure. Full article

Background. Enhanced Recovery After Surgery (ERAS) is a structured, multidisciplinary programme designed to optimise the entire perioperative pathway through evidence-based, patient-centred, standardised care. The objective of this report is to determine whether it is feasible to implement an ERAS^® program in orthopaedic surgery within our institution for primary THA and TKA. Methods. This single-centre quality-improvement project followed the ERAS^® Society certification framework to create and implement an enhanced-recovery pathway for primary total hip and knee arthroplasty. The three-phase roadmap comprised baseline pathway mapping and audit, pilot implementation and refinement, and full roll-out, punctuated by four multidisciplinary seminars. Key aspects of this programme included preoperative education, minimal fasting and early return to feeding, rational choice of regional anaesthesia techniques, administration of multimodal analgesia, reduction in urinary and surgical catheterization, active management of the risk of blood loss and deep vein thrombosis, optimisation of surgical workflow and techniques, and early mobilisation of patients. Global- and element-level compliance was tracked prospectively; ≥70% compliance was required for certification. External ERAS^® Society review at month 15 confirmed data integrity, sustainability planning, and successful certification. Continuous feedback loops drove micro-teaching and order-set optimisation throughout deployment phases. Results. Our ERAS programme for primary THA and TKA was introduced in April 2022. The definitive programme contained 24 mandatory elements grouped into three perioperative areas. After the fourth seminar, the rate of compliance was 81%. The certification was obtained in June 2023. Conclusions. Implementing an ERAS^® programme for primary total hip and knee arthroplasty is feasible within a high-volume academic institution when supported by multidisciplinary teamwork, robust data collection, and iterative feedback mechanisms. Further high-quality outcome-focused research is required to evaluate the clinical impact of individual ERAS components and to validate a personalised ERAS programme incorporating emerging technologies. Full article

Smart-city last-mile rail access, referred to in this entry simply as last-mile access, captures how travelers connect to and from rail stations during the first or last leg of a journey. It encompasses both the design of multimodal connections and the experience of accessibility that results from them. On the supply side, last-mile access involves the coordination of walking, cycling, micromobility, and feeder transit with rail services, supported by digital systems that unify planning, ticketing, and payment. On the demand side, it reflects how efficiently and equitably travelers can reach stations within these coordinated networks. Together, these physical and institutional dimensions extend the functional reach of rail, reduce transfer barriers, and reinforce its role as the backbone of sustainable urban mobility. As cities strive to reduce car dependency while promoting inclusivity and accessibility, last-mile access has become a key indicator of how infrastructure, technology, and governance intersect to deliver more equitable transportation systems. Full article

Fragmented, sector-by-sector governance is poorly suited to cascading risks that couple climate, food, water, health, biodiversity, soils, energy, and environmental quality. This paper addresses the translation gap between integrative security–sustainability paradigms and the routine machinery of government, including planning, budgeting, procurement, and accountability. We develop the Spheres of Security (SOS) model as a conceptual–operational method organised around four overlapping spheres (biophysical, economic, social, and governance) and a repeatable cycle—diagnose → co-design → deliver → demonstrate → adapt—illustrated through two stylised vignettes (urban heat and health; watershed food–water–energy). SOS introduces an auditable overlap rule and an Overlap Score, supported by lean assurance, to make verified multi-sphere co-benefits commissionable and to surface trade-offs transparently within normal, accountable institutions (consistent with weak securitisation). We provide implementation guidance, including minimum institutional preconditions and staged entry-point options for jurisdictions where pooled budgets and full administrative integration are not immediately feasible. Full article

The integration of virtual reality (VR) technologies in museums and cultural heritage has expanded rapidly, driven by demand for immersive visitor experiences. Yet comprehensive studies on their long-term sustainability and operational challenges remain scarce. This mixed-methods study combines scientometric analysis of 1635 Web of Science publications (1997–2025) using VOSviewer 1.6.20 with longitudinal evidence from three VR installations deployed by the authors in Romanian museums representing understudied Central/Eastern European contexts. Analysis maps global trends, collaborations, and regional gaps, while practical evaluation addresses durability, usability, maintenance, technological obsolescence, multi-user management, and headset hygiene. Findings reveal VR’s engagement and preservation potential but highlight constraints limiting long-term viability. Strategic planning, adaptive design, and maintenance frameworks emerge as critical for sustainability. Limitations include WoS exclusivity and regional focus, while findings offer actionable insights for diverse institutional contexts. Full article

This study examined the effectiveness of an Artificial Intelligence (AI)-supported self-coaching system designed to improve preschool teachers’ implementation of embedded instruction (EI) for young children with autism in inclusive early childhood classrooms. Using a multiple-probe across participants single-case design with four teacher–child dyads, the study evaluated changes in teacher fidelity, child learning outcomes, maintenance, generalization, and teacher perceptions. Following baseline and an initial EI training, teachers engaged in weekly AI-supported self-coaching cycles that included planning, data entry, reflection, and AI-generated individualized feedback. Results demonstrated clear functional relations between the introduction of the AI-supported system and increases in teachers’ EI fidelity. All teachers reached high levels of accurate implementation, maintained their performance after AI supports were withdrawn, and generalized EI procedures to non-targeted routines. Correspondingly, children showed substantial improvements in unprompted correct responding on individualized goals, with gains sustained across maintenance and generalization probes. Social validity data indicated that teachers found both EI and AI-supported self-coaching highly acceptable, feasible, and helpful for guiding instructional decision-making. Findings provide promising initial evidence that AI-supported self-coaching can serve as a scalable, cost-effective professional development approach that strengthens teacher practice and enhances learning outcomes for young children with autism in inclusive preschool settings. Full article

This review explores the transformative role of three-dimensional (3D) printing in radiation therapy for cancer treatment, emphasizing its potential to deliver patient-specific, cost-effective, and sustainable medical devices. The integration of 3D printing enables rapid fabrication of customized boluses, compensators, immobilization devices, and GRID collimators tailored to individual anatomical and clinical requirements. Comparative analysis reveals that additive manufacturing surpasses conventional machining in design flexibility, lead time reduction, and material efficiency, while offering significant cost savings and recyclability benefits. Case studies demonstrate that 3D-printed GRID collimators achieve comparable dosimetric performance to traditional devices, with peak-to-valley dose ratios optimized for spatially fractionated radiation therapy. Furthermore, emerging applications of artificial intelligence (AI) in conjunction with 3D printing promise automated treatment planning, generative device design, and real-time quality assurance, and are paving the way for adaptive and intelligent radiotherapy solutions. Regulatory considerations, including FDA guidelines for additive manufacturing, are discussed to ensure compliance and patient safety. Despite challenges such as material variability, workflow standardization, and large-scale clinical validation, evidence indicates that 3D printing significantly enhances therapeutic precision, reduces toxicity, and improves patient outcomes. This review underscores the synergy between 3D printing and AI-driven innovations as a cornerstone for next-generation radiation oncology, offering a roadmap for clinical adoption and future research. Full article

The particle exhaust system plays a pivotal role in fusion reactors and is essential for ensuring both the feasibility and sustained operation of the fusion reaction. For the successful development of such a system, density control is of great importance and some key design parameters include the neutral gas pressure and the resulting particle fluxes. This study presents a simplified conductance-based model for estimating neutral gas pressure distributions in the particle exhaust system of fusion reactors, focusing specifically on the sub-divertor region. In the proposed model, the pumping region is represented as an interconnected set of reservoirs and channels. Mass conservation and conductance relations, appropriate for all flow regimes, are applied. The model was benchmarked against complex 3D DIVGAS simulations across representative operating scenarios of the Wendelstein 7-X (W7-X) stellarator. Despite geometric simplifications, the model is capable of predicting pressure values at several key locations inside the particle exhaust area of W7-X, as well as various types of particle fluxes. The developed model is computationally efficient for large-scale parametric studies, exhibiting an average deviation of approximately 20%, which indicates reasonable predictive accuracy considering the model simplifications and the flow problem complexity. Its application may assist early-stage engineering design, pumping performance improvement, and operational planning for W7-X and other future fusion reactors. Full article