Search Results (1,865)

Background: Research concerning potential resolutions to immigrants’ health care access in Canada is limited, and the viewpoint of immigrant communities regarding priorities and feasible solutions remains inadequately captured. The objective of this article is to portray a research endeavor in which grassroots community members assumed the role of priority-setters for research on primary care access concerns. Aim: This cross-sectional study aimed to identify community-prioritized primary care access research topics among Nepalese Canadian immigrants in Calgary by ranking ten predefined issues based on perceived importance. Methods: We conducted community-based participatory research (CBPR) with the Nepalese community members in Canada. Participants were recruited using snowball sampling through community networks and rated topics using a 5-point Likert scale. A self-administered survey was used to collect participants’ rankings of ten predefined primary care access challenge themes. The themes were identified through comprehensive literature reviews undertaken by the research program team. The questionnaire was pilot-tested and refined based on feedback from team members before being administered. Results: A total of 401 Nepalese immigrants completed the survey, with 50.4% self-identifying as men. Among survey participants, significant gender differences were observed in sociodemographic characteristics, including age distribution, educational attainment, extended health insurance coverage, household income, and length of stay in Canada. Overall, health care cost and lack of resources were identified as the highest research priorities. While both men and women ranked these issues highly, women assigned greater priority to transportation- and culture-related barriers, whereas men generally assigned lower priority to these issues. Conclusions: There is a growing recognition that health solution priority-setting approaches should embrace transdisciplinary collaboration, with community participation as a pivotal factor. The results underscore the value of transdisciplinary, collaborative priority-setting approaches that center community participation to inform health research and interventions aligned with the needs of immigrant communities. Full article

This article investigates how women’s relative absence from medieval textual archives can be reconsidered through the study of visual and material culture. Focusing on Mongol and Yuan China and read in relation to The Travels of Marco Polo, it argues that women’s artistic production functioned as a form of embedded counter-archive that preserves traces of participation obscured in narrative sources. Drawing on Black feminist epistemology as a heuristic framework and employing critical fabulation and poetic inquiry as analytical methods, the study interprets silence as a meaningful historical trace rather than a void, and considers silence not as absence but as a structured condition of archival production. Four case studies—Guan Daosheng’s literati bamboo painting, the handscroll tradition associated with Lady Su Hui, imperial phoenix embroidery, and Silk Road textile fragments—demonstrate distinct modes through which women’s presence becomes materially legible: mediated visibility, formal containment, infrastructural anonymity, and circulatory displacement. These “quiet arts” reveal how women’s labour and creativity persisted within and alongside patriarchal inscriptional systems even when textual attribution receded. In dialogue with the shadow silhouettes of contemporary artist Kara Walker, the article further situates these premodern archives within a broader visual language of absence and recovery. Rather than reconstructing lost biographies, it proposes a transdisciplinary method—integrating art history, feminist theory, theology, and poetic inquiry—for reading material culture as a site where historical silence becomes structurally legible. It proposes a transdisciplinary approach that expands art historical methods for interpreting gender, authorship, and archival silence in medieval visual culture. Full article

This study explores how demystifying Earth Observation (EO) through co-creation pathways and local language can enhance flood resilience and environmental governance in African informal cities. Using case studies from Maiduguri and Hadejia, Nigeria, the research employed a transdisciplinary mixed-methods design combining rapid evidence assessment, surveys, participatory workshops (n = 50 stakeholders) integrating simplified Sentinel-1/2 demonstrations, indigenous knowledge mapping, and pre-/post-engagement surveys on EO familiarity. Non-expert participants were trained to interpret satellite data using local language, linking distant teleconnections with local flood experiences. The findings revealed significant gains in EO literacy and improvements in interpretive confidence, gender-inclusive participation, and policy engagement. Localizing the curriculum enabled participants to translate technical EO concepts into locally meaningful narratives, fostering cognitive empowerment and practical application in flood preparedness and advocacy. The study demonstrates that data democratization is not only a matter of open access but also of open understanding. It advances a conceptual model linking Demystification, Literacy, Empowerment, Co-Production and Resilience, positioning EO as a social technology that bridges scientific and indigenous knowledge systems. The findings contribute to debates on decolonizing environmental science and propose a potential participatory framework for integrating EO into community-based adaptation, legal accountability, and policy reform across Africa’s rapidly urbanizing landscapes. Full article

The increasing penetration of intermittent renewable energy demands innovative solutions to maintain grid stability, resilience, and security in the body of smart cities. This paper presents a novel framework that redefines Bitcoin mining as a form of virtual energy storage, a flexible and controllable load capable of delivering large-scale demand response services, positioning it as a competitive alternative to traditional energy storage systems, including electrical, mechanical, thermal, chemical, and electrochemical storage solutions. By strategically aligning mining activities with grid conditions, Bitcoin mining can absorb excess electricity during periods of oversupply, converting it into digital assets, and reduce operations during times of scarcity, effectively emulating the behavior of conventional energy storage systems without the associated capital expenditures and material requirements. Beyond its operational flexibility, this paper explores the cyber–physical benefits of integrating Bitcoin mining into the power transmission systems as a defensive mechanism against false data injection (FDI) cyberattacks in smart city infrastructure. To achieve this goal, a decentralized and adaptive control strategy is proposed, in which mining loads dynamically adjust based on authenticated grid-state information, thereby improving system observability and hindering adversarial efforts to disrupt state estimation. In addition, to handle the proposed approach, this paper introduces a high-performance algorithm, a combination of quantum-augmented particle swarm optimization and wavelet-oriented whale optimization (QAPSO-WOWO). Simulation results confirm that strategic deployment of mining loads improves grid sustainability by utilizing curtailed renewables, enhances resilience by mitigating load-generation imbalances, and bolsters cybersecurity by reducing the impacts of FDI attacks. This work lays the foundation for a transdisciplinary paradigm shift, positioning Bitcoin mining not as a passive energy consumer but as an active participant in securing and stabilizing the future power grid in smart cities. Full article

Understanding and developing habits in complex systems thinking using STEM-integrated perspectives is essential in addressing education and workforce needs in society. In this study, we investigated a learning intervention that incorporated multiple models designed to improve engineering students’ understanding of complex systems through investigating the mechanobiology of the Venus flytrap. Mechanobiology is a transdisciplinary field that integrates biology, engineering, chemistry, and physics to explore how cells and tissues sense and respond to forces in their environment. We used an exploratory, mixed-methods approach to examine the impact of this new curriculum on investigating flytrap closure and prey digestion. We then evaluated students’ understanding of complex systems characteristics (i.e., many interacting parts, decentralization, non-linear interactions, emergence, and adaptation) and in their ability to transfer these principles to other systems. Qualitative analyses demonstrate that students articulated key systems principles in relation to their understanding of flytrap mechanobiology, while descriptive summaries of pre- and post-surveys suggest broader conceptual gains. Furthermore, students demonstrated the transfer of systems thinking to other contexts and reported an enhanced understanding of real-world STEM research. Full article

Transnational youth frequently navigate multiple languages and continually negotiate not only affiliation, but also the legitimacy of the languages they use within changing linguistic hierarchies. However, their educational experiences are often framed through fragmented classroom practices, deficit-based assessments, and nationally bounded curricular frameworks. In this paper, I respond by theorizing Fictional Linguistic Landscapes (FLL) as a transdisciplinary pedagogical approach that utilizes fiction and participatory cultural practices to position language learning as a form of semiotic design, critical inquiry, and identity (re)work. Grounded in linguistic landscape studies, multiliteracies pedagogy, and fan-based meaning-making, FLL positions learners as world-builders and allows them to experiment with visibility, hierarchy, and language(s) in safe fictional environments. This study outlines the four-phase FLL in Second Language Teaching and Learning (L2TL) cycle and provides five pedagogical design spaces to address issues of raciolinguistic valuation, deficit institutional representations, affective harm, peer-level marginalization, and translocal or return migrant identity negotiation. Rather than viewing imagination as an outcome of teaching, FLLinL2TL structures it as a necessary process for learning, linking creative production to explicit linguistic objectives and reflective justification. I conclude by discussing implications for classroom practice, teacher education, and future research on the potential of the FLLinL2TL approach in transnational education research. Full article

The acceleration of climate change poses a growing threat to human health, particularly by exacerbating non-communicable diseases (NCDs) such as cardiovascular and respiratory conditions. Rising global temperatures amplify air pollution and environmental toxins, disproportionately affecting vulnerable populations. This narrative review explores the complex pathways linking climate-related environmental stressors to adverse health outcomes, focusing on the intermediary roles of epigenetic modifications and alterations in the microbiota. Epigenetic processes, including DNA methylation and histone modifications, may mediate how environmental exposures influence gene expression and disease susceptibility. Concurrently, changes in microbiota composition induced by pollutants and temperature fluctuations can promote inflammatory responses and immune dysfunction. Elucidating these molecular mechanisms is essential for developing targeted interventions and adaptive strategies to mitigate the health impacts of climate change. This review underscores the importance of identifying epigenetic and microbiota-based biomarkers for early risk stratification and for informing public health prevention and adaptation policies. A transdisciplinary approach, grounded in the One Health framework, is critical to addressing the growing burden of climate-sensitive diseases and reducing health inequalities. Full article

This article introduces Memetic/Metaphorical Digital Twins (MDTs) as a novel extension of Digital Twin typologies by twinning conceptual schemes, complementing Industrial, Human, and Cognitive Digital Twins. MDTs embed cultural, organizational, and semiotic knowledge into digital frameworks, enabling the recombination and evolution of knowledge structures across disciplines. Drawing on Schlaile’s economic perspectives and Mavromatidis’s architectural lens of entropy and constructal thermodynamics, this study demonstrates how MDTs can address systemic challenges in communication, knowledge transfer, and design. A Digital Community Platform, under development for supporting decentralized Personal Knowledge Management Systems (PKMS), provides the operational foundation, integrating iterative KM cycles to support knowledge co-creation. Its logic and logistics substitute the traditional document paradigm with a memetic approach by utilizing memes as replicable, adaptive knowledge units, thereby mimicking biological evolution and ecosystem resilience in digital platform environments. It aims to offer distributed, decentralized, bottom-up, affordable, knowledge-worker-centric applications prioritizing personalization, mobility, generativity, and entropy reduction; its mission is to serve a knowledge-co-creating community characterized by highly diverse individual Abilities, Contexts, Means, and Ends (ACME) facing increasingly volatile, uncertain, complex, and ambiguous futures (VUCA). A Boundary Object Taxonomy to Omnify Memetic Storytelling (BOTTOMS) is proposed to further structure atomic units of meaning—such as memes, mythemes, narratemes, and reputemes—into a unified framework for authorship and dissemination. The article situates MDTs within a design science research paradigm, outlines current implementation progress, and identifies future developments, including AI-supported curation, personalized metrics, and expanded boundary objects. Together, these contributions position MDTs as a universal framework for adaptive, transdisciplinary knowledge co-creation. Full article

This study develops a Constraint-Driven Model of Intelligence to explain the emergence of structured meaning in complex systems, reconciling probability and cybernetics. It applies a conceptual–analytic procedure, conducted entirely through logical reasoning and theoretical analysis, without empirical measurement, data acquisition, experimental manipulation, or statistical testing, and is therefore methodologically separate from empirical artificial intelligence research. Phenomena such as model collapse are cited as theoretical instances for epistemic argumentation, without asserting empirical verification. Building on Émile Borel’s Infinite Monkey Theorem, which demonstrates the theoretical inevitability of order in unbounded stochastic processes, and Gregory Bateson’s principle of negative explanation, which defines structure as the result of systematically eliminated alternatives, the analysis formalizes how constraints break ergodicity and generate asymmetry. Shannon’s entropy quantifies the informational effects of constraints, while Simon’s bounded rationality and Turing’s algorithmic limits show how cognitive and computational boundaries produce tractable outcomes. Applied to modern AI, the model accounts for model collapse in recursive training, showing that the loss of asymmetric constraints produces low-entropy, repetitive outputs, demonstrating the epistemic necessity of constraint regulation. Comparing probabilistic and cybernetic accounts of emergence, the study shows that structured intelligence arises not from stochastic exploration alone, but from bounded, recursive, selective processes. This model is transdisciplinary, formalizing how constraints from socioeconomic pressures to subcultural circulation shape diversity, innovation, and functional asymmetry, establishing a generalizable cybernetic epistemology for the generation of structured intelligence and meaning across domains. By formalizing these concepts through set-theoretic derivations and integrative synthesis, this non-empirical model advances a cybernetic epistemology, separate from quantitative AI evaluations or experimental designs. Full article

The objective of this study was to evaluate relationships between antimicrobial use (AMU) and antimicrobial resistance (AMR) in isolates from farmed Atlantic salmon that could represent finfish pathogens in the British Columbia (BC) aquaculture industry using historical surveillance data. Antimicrobial susceptibility data were obtained for 1040 bacterial isolates from farmed Atlantic salmon submissions to the BC Animal Health Centre for 2007–2018. Antimicrobial use data were provided by the BC Ministry of Agriculture and Food from feed mill prescriptions for BC farmed Atlantic salmon for 2007–2018. Multivariable logistic regression models for all bacterial isolates with a random intercept for species were developed to determine associations with outcomes of resistance to trimethoprim-sulfadiazine (SXT), oxytetracycline (OXY), and florfenicol (FLOR). Resistance to SXT, FLOR, and/or OXY were all significantly associated with each resistance outcome in their respective models. Only the SXT resistance model was significantly associated with AMU, specifically potentiated sulfonamide use, but use was not significantly associated with AMR for any other resistance outcome. The results of this study contribute to the rapidly growing and increasingly pertinent body of literature on AMU and AMR in the unique marine aquaculture environment. Future research at the farm level linking pen-specific AMU to AMR outcomes will provide more understanding of selection pressure for AMR at the local level and provide more guidance for antimicrobial stewardship in finfish aquaculture. Full article

Mass selection is increasingly promoted in viticulture to enhance resilience by restoring intra-varietal diversity, yet its effects on the structure and inheritance of plant-associated microbiomes remain poorly understood. Here, we investigated bacterial and fungal communities associated with old grapevine mother plants and their progeny across four Bordeaux estates practicing mass selection, using a fully in situ experimental design. Root and leaf microbiomes were characterized by metabarcoding and analyzed using multivariate ordination, hierarchical clustering, and assembly-process metrics (βNTI and NST). Microbial community composition and structure were primarily shaped by plant compartment and vineyard origin, whereas generation effects were significant but weak. Microbial resemblance between mother vines and their offspring was limited and highly context-dependent, occurring mainly under comparable environmental conditions. Assembly-process analyses revealed heterogeneous deterministic signals, particularly in root-associated bacterial communities, but did not consistently result in phylogenetic similarity between generations. Although inheritance signals were generally weak, their recurrence across multiple vineyards and contrasted field conditions highlights their ecological relevance. By integrating environmental variability, this in situ approach mitigates the adaptive bias in plant–microbiome interactions and shows that mass selection does not rely on systematic microbial transmission but rather operates within a nuanced framework of environmentally mediated interactions. Full article

This paper aims to investigate the aerodynamic variation patterns of twin-rotor vertical-axis wind turbines (TR-VAWTs) considering phase interference under different solidities, and to reveal the interactive mechanism between solidity, phase interference, and aerodynamic loads of TR-VAWTs. This paper first establishes a phase interference aerodynamic analysis model for TR-VAWTs based on two-dimensional computational fluid dynamics (CFD) methods. Secondly, experimental results are used to verify the accuracy of the numerical model. Finally, the variation patterns of aerodynamic forces and wake characteristics of TR-VAWTs under different parameters (solidity, initial phase angle) are explored. The results show that: (1) Each turbine of the side-by-side TR-VAWTs exhibits an increase in the energy utilization coefficient (C_P) in comparison with a single rotor. (2) The phase angle exhibits similar influence patterns on the efficiency of TR-VAWTs with different solidities. As the phase angle varies within the range of 30° to 60°, the efficiencies of rotor 1 and rotor 2 under medium-to-high tip speed ratios are both improved, while within the range of 60° to 90°, the efficiencies of each rotor generally decrease. (3) When TR-VAWTs with different solidities are at intermediate phase angles (90° for two blades, 60° for three blades, and 45° for four blades), the efficiencies of each rotor are basically consistent, which is conducive to power transmission. (4) If the intermediate phase angle is adopted as the reference configuration, the pressure influence on the turbines is minimized, which can not only make the power output more balanced but also improve the wake characteristics to a certain extent. Full article

Microplastic (MP) pollution represents a significant environmental threat, impacting aquatic ecosystems and human health. This review examines critical elements of MP risk assessment, including exposure pathways, properties (polymer type, size, and shape), bioaccumulation, and ecological and health effects. It underscores the challenges of quantifying MP exposure and identifying pollutants, as well as gaps in understanding pollutant adsorption/desorption and biofilm impacts. MPs serve as carriers for organic pollutants, heavy metals, and chemical additives, potentially magnifying toxic effects. Emerging contaminants, such as pharmaceuticals, exacerbate these risks. Laboratory research is crucial to trace MPs through food chains from primary producers to humans and assess bioaccumulation and health impacts. Current assessments, however, are insufficient to provide comprehensive ecological risk evaluations. The review highlights the need for improved methodologies to assess MPs’ fate, trophic transfer, and long-term ecological effects. MPs often release harmful additives like plasticizers and flame retardants, necessitating studies to differentiate the impacts of polymers and additives. It emphasizes integrating MP toxicity data into risk models while fostering collaboration among scientists, policymakers, and communities. The paper advocates for a comprehensive framework combining advanced analytical methods and environmental monitoring to refine risk assessment models. These efforts aim to strengthen public awareness, support informed environmental policies, and promote sustainable practices to mitigate MP pollution impacts. Addressing these research gaps will significantly enhance the scientific understanding of MP risks and guide effective management strategies for environmental and human health protection. Full article

Water sustainability plays a critical role in achieving the Sustainable Development Goals (SDGs), as it influences human well-being, ecosystem integrity, and long-term development pathways. Over the past three decades, a substantial body of research has emerged on water sustainability; however, there remains a limited synthesis of how sustainability has been assessed, how assessment approaches have evolved, and the extent to which they align with the multidimensional intent of the SDGs. This study addresses the gap by combining a systematic review conducted using the PRISMA framework and bibliometric analysis from 1995 to 2025. The results show a marked acceleration in research output after 2015 following the formal adoption of the SDGs, with concentrations in a small number of countries and research hubs. Water sustainability assessment is mainly shaped by technically oriented indicator-based frameworks that emphasise water availability, water quality, and management performance. While these approaches have enabled comparability and methodological consistency, they often provide a partial representation of sustainability with limited integration of governance processes, social equity, cultural contexts, indigenous knowledge, and ecosystem services. The findings highlight the need for assessment approaches that go beyond technical metrics to more integrative and context-sensitive frameworks that can inform policy, support adaptive decisions, and reflect the interconnected nature of sustainable development. Full article

Obesity is well-known as a major risk factor for metabolic disorders, and natural compounds are being explored as alternatives to conventional therapies. While Centella asiatica is well known for its medicinal and dietary benefits, the biological activities of Giant Centella asiatica (GCA), especially when extracted with mineral-rich lava seawater, remain poorly characterized. This study aimed to evaluate the anti-adipogenic and lipid-metabolism-regulating effects of a novel GCA extract (GCA-LS-90) and its ability to stimulate GLP-1 secretion in vitro. GCA-LS-90 significantly inhibited lipid accumulation in 3T3-L1 adipocytes by up to 24.3% at 200 µg/mL (p < 0.001). It downregulated adipogenic transcription factors (C/EBPβ, C/EBPα, PPARγ) and lipogenic regulators (SREBP1c, FAS, G6PD, ME), while upregulating KLF2 (all p < 0.001). Western blotting confirmed reduced SREBP1c and SREBP2 protein expression, increased phosphorylation of AMPKα/ACC, and enhanced HSL activity (p < 0.05–0.001). In STC-1 cells, GCA-LS-90 increased GLP-1 secretion (53.5 pmol/L at 90 µg/mL vs. 41.3 pmol/L in control, p < 0.001). The major compounds, 3,5- and 4,5-di-O-caffeoylquinic acids, reproduced these effects. In conclusion, GCA-LS-90 modulated adipogenesis-, lipid-metabolism-, and GLP-1 secretion-related pathways in vitro, suggesting its potential as a functional ingredient for obesity management. Further in vivo studies are needed to confirm efficacy and translational relevance. Full article