Search Results (1,878)

Regular social, economic and agricultural interactions occurred between the Horn of Africa and Southern Arabian Peninsula for millennia, raising questions about potential geo-culinary exchanges, including of the little-studied fermented flatbreads produced in these areas. A comparative analysis of Somali laxoox/canjeero, Ethiopian injera, Sudanese kisra and Yemeni/Saudi lahoh was conducted by combining a literature review and consultations with 17 local experts, then processing the data in a hierarchical cluster analysis to quantify “biocultural” diversity. In an interdisciplinary approach, technical aspects (bread appearance, ingredients, and production stages) and cultural characteristics (consumption patterns and social function) were considered to identify key descriptors of the breads. A dendrogram generated through cluster analysis of a binary (0/1) matrix, structured with the key descriptors, showed that each bread has a distinct biocultural identity, and enabled the quantification of their similarities. Somali laxoox/canjeero and Yemeni/Saudi lahoh had a 64% similarity to each other (Jaccard index); each had a 53% similarity to Ethiopian injera; while all of them were 41% similar to Sudanese kisra. Hierarchical cluster analysis, applied for the first time to flatbreads, contributes to their comprehensive characterization and comparison in this unique geographic region and lays the foundations for policies to protect their identity and quality. Full article

Food waste presents a major challenge to global sustainability. Up to 60% of this waste occurs at the household level, at which point labeling confusion causes avoidable loss. The present study employed the motivation–opportunity–ability framework to conduct a narrative synthesis of 82 studies and pieces of gray literature, incorporating policies and industry practices to elucidate how food labeling modulates food waste behavior through interactions with consumer motivation, external opportunities, and individual abilities. Food labeling should be considered a systemic intervention tool spanning the entire food supply chain rather than mere carriers of information. The present findings indicate that although standardizing quality and safety label terminology mitigates cognitive confusion, it may have limited efficacy to reduce food waste. Extending shelf life and providing explicit storage guidance are critical strategies that are often undervalued and comparatively underexplored. Labels most effectively reduce waste when they simultaneously activate motivation, opportunity, and ability. When all three elements cannot be activated concurrently, stakeholders should prioritize improving external opportunities or enhancing individual abilities rather than stimulating motivation. Food labeling interventions can only be effective at waste mitigation if systemic and transdisciplinary synergy is achieved among all stakeholders in food supply chains. Full article

Leaders and managers frequently face the need to make highly complex decisions with incomplete or fragmented information. Traditional decision support systems largely emphasize the visualization of data but often fall short in producing context-sensitive insights that can directly inform decision-making. This paper examines how narrative techniques combined with machine learning can strengthen communication across organizational hierarchies, particularly by improving the transfer of tacit expertise and contextual knowledge. To explore this, a transdisciplinary literature review was conducted using articles published within the last five years from databases such as Scopus, Web of Science, and ScienceDirect. The review highlights that narrative-driven reporting has been most commonly applied in fields such as accounting and sustainability, where expert interpretation replaces purely numerical summaries with more meaningful analytical explanations. Such approaches can also embed sentiment and personalization, commonly referred to as Narrative Disclosure Tone. Building on this foundation, the study investigates how Artificial Intelligence-driven decision support can formally integrate narrative elements to enhance report clarity, usability, and strategic relevance. Findings suggest that combining machine learning with expert-driven narrative reporting supports more innovative decision support systems and facilitates the alignment of tacit knowledge with data-driven insights. Full article

(1) Background: The increasing contribution of anthropogenic electromagnetic radiation has altered the Earth’s electromagnetic landscape and poses a serious problem for electromagnetic ecology and medicine. The aim of this study was to develop a working theoretical framework to describe the current state of interaction between the human body and electromagnetic fields in the external environment and to facilitate transdisciplinary collaboration among scientists in studying and addressing this problem. (2) Methods: Extensive research has been conducted in the literature to provide a comprehensive presentation of data, enabling a working concept of the interaction between the human body and electromagnetic fields in the external environment. (3) Results: General data, theoretical foundations, mechanisms, and results of the interaction of external electromagnetic fields with the human body were presented. (4) Conclusions: There is a proven interaction between the human body and external electromagnetic fields, as the body is part of the Earth’s electromagnetic landscape and has biophysical mechanisms for coupling with it. The increase in anthropogenic electromagnetic radiation is an electromagnetic environmental problem, and this requires further study of the safety issues and the impact of anthropogenic electromagnetic fields on the human body, and a reassessment of their biological impact on the human body, tightening the standards and requirements for electromagnetic safety in places where people live, a moratorium on further deployment of 5G, urgent application of the precautionary principle, and stricter exposure limits, especially for Wireless Communication Electromagnetic Fields. Full article

Background: This study compared two xenogeneic bone graft materials, A-Oss (bovine-derived) and The Graft (porcine-derived), using a rabbit calvarial defect model and a canine mandibular dehiscence-type defect model. Methods: Healing was evaluated at 6 and 12 weeks in rabbits and at 24 weeks in mongrel dogs. Micro-computed tomography quantified mineralized tissue fill (defect closure) in rabbits and, in dogs, the compartments classified as new bone and residual graft, together with vertical and horizontal volumetric maintenance. Hematoxylin and eosin (H&E) sections provided complementary qualitative observations. Results: In rabbits, defect closure did not differ between materials at 6 weeks (67.1 ± 12.7% vs. 70.2 ± 15.1%, p = 0.090) or 12 weeks (78.6 ± 5.9% vs. 72.3 ± 0.9%, p = 0.124). In dogs, new bone was similar between groups (43.5 ± 3.2% vs. 45.9 ± 1.1%, p = 0.208), whereas residual graft showed a numerical trend toward higher values with A-Oss (20.2 ± 3.5% vs. 13.3 ± 4.5%, p = 0.069). Vertical volume maintenance also trended higher with A-Oss (91.1 ± 1.6% vs. 87.8 ± 1.3%, p = 0.056), while horizontal maintenance was comparable (94.5 ± 1.8% vs. 91.4 ± 2.8%, p = 0.241). Histology in both models showed graft particles within the defect/augmented regions with surrounding eosinophilic matrix and intervening tissue spaces. Conclusions: Overall, both materials produced similar healing profiles across models, with small between-material differences most apparent in the canine dehiscence setting. Full article

Contemporary societies are facing converging crises, including environmental degradation, worsening social inequalities, aging populations, and increasingly costly healthcare systems, prompting sustainable health to be proposed as an integrative conceptual perspective for rethinking health, its determinants, and collective action. This narrative review aims to trace the historical evolution of the concept, clarify the vision it offers for public health, and identify its implications for research, policy, and intervention. A literature search (May 2025) was conducted in PubMed, Google Scholar, and Google, with no restrictions on language, time period, or document type. Of 40 relevant documents, 21 were selected for in-depth analysis by two independent reviewers, with duplicate data extraction. The results show that sustainable health broadens the World Health Organisation (WHO) definition of health by incorporating sustainability, intergenerational justice, ecological limits, and social equity. Close to, but distinct from Planetary Health, One Health, and EcoHealth, sustainable health is based on ecological, social and ethical, economic, behavioral, intergenerational, and systemic/intersectoral dimensions. Sustainable health thus emerges as a systemic and transdisciplinary conceptual approach for transforming health systems, living environments, and public policy, requiring further conceptual clarification, robust interdisciplinary research programs, and intersectoral initiatives involving communities. Full article

The world evolves continuously across space and time. Massive volumes of data are generated through sensing, simulation, remote observation, and human activities, capturing dynamic processes in environmental, social, economic, and engineered systems. Critical insights are embedded within these large-scale spatiotemporal datasets. Spatiotemporal Data Science provides a conceptual and methodological framework for analyzing such data by integrating spatiotemporal thinking, computational infrastructure, artificial intelligence, and domain knowledge. The field advances methods for data acquisition, harmonization, modeling, visualization, and decision support, enabling applications in natural disaster response, public health, climate adaptation, infrastructure resilience, and geopolitical analysis. By leveraging emerging technologies—including generative Artificial Intelligence (AI), large-scale cloud platforms, Graphics Processing Unit (GPU) acceleration, and digital twin systems—Spatiotemporal Data Science enables scalable, interoperable, and solution-oriented research and innovation. It represents a critical frontier for scientific discovery, engineering advancement, technological innovation, education, and societal benefit. Spatiotemporal Data Science is a transdisciplinary field that studies and models dynamic phenomena across space and time by integrating spatial theory, temporal reasoning, artificial intelligence, and scalable computational infrastructure. It enables the development of adaptive, predictive, and increasingly autonomous systems for understanding and managing complex real-world processes. Full article

Biological manipulation via physical stimuli such as light and magnetism has become a central goal in modern biotechnology. Among these modalities, magnetic fields offer unique advantages, including deep tissue penetration and untethered interventions in living systems. An ideal platform for such a magnetogenetic toolkit would be a genetically encodable protein with tunable magnetic features under physiological conditions. However, the development of such tools has been hindered by the lack of robust and stable protein scaffolds with strong intrinsic magnetic properties. Inspired by animal magnetoreception in nature, here, we rationally designed and systematically screened single-chain variants of the magnetoreceptor MagR. Through nine iterative rounds of design and experimental validation, we generated 25 constructs and ultimately identified a stable single-chain-dimer-based-tetramer, SDT-MagR, as the optimal magnetic molecular platform. This engineered protein exhibits exceptional structural stability and state-dependent magnetic behavior, showing ferrimagnetic-like characteristics in the solid state and paramagnetic behavior in solution. With enhanced magnetic susceptibility, purified SDT-MagR can be directly attracted by a magnet in vitro, establishing it as a promising new platform for future biomagnetic manipulation and magnetogenetics applications. Full article

Multi-agent reinforcement learning involves interacting agents whose learning processes are coupled through a shared environment. This work introduces a discrete-time approximation model for multi-agent Boltzmann Q-learning that accounts for agents’ update frequencies. We demonstrate why previous models do not accurately represent the actual stochastic learning dynamics while our model can reproduce several complex emergent dynamic regimes, including transient cooperation and metastable states in social dilemmas like the Prisoner’s Dilemma. We show that increasing the discount factor can prevent convergence by inducing oscillations through a supercritical Neimark–Sacker bifurcation, which transforms the unique stable fixed point into a stable limit cycle. This analysis provides a deeper understanding of the complexities of multi-agent learning dynamics and the conditions under which convergence may not be achieved. Full article

Sustainable hydrogen production in water-scarce regions poses critical environmental challenges due to limited freshwater availability and the energy intensity of seawater treatment. This study examines the environmental trade-offs of providing water for hydrogen production via seawater desalination (with or without brine treatment) or freshwater purification, using a comprehensive life cycle assessment (LCA) framework. The assessment centers on three water-stressed countries: the United Arab Emirates (UAE), Spain, and Australia. Results reveal clear trade-offs between freshwater conservation and marine environmental pressures. Brine treatment reduces nutrient-related marine impacts but increases energy-related burdens, particularly under fossil-dominated electricity systems. Water sourcing for electrolysis coupled with energy-intensive desalination systems generally exhibits higher environmental pressures than alternative configurations, whereas freshwater-based supply for hydrogen production pathways shows lower burdens in several impact categories but raise concerns regarding freshwater resource use. Sensitivity analysis confirms that system performance is strongly influenced by water demand and electricity characteristics, highlighting the importance of aligning hydrogen deployment strategies with regional energy and water conditions. Overall, the findings demonstrate that water sourcing decisions play a critical role in shaping the environmental sustainability of hydrogen systems in water-stressed regions and must be evaluated through integrated water–energy planning. Full article

Understanding how environmental enrichment influences behavioural time allocation is particularly important for threatened primate species maintained under human care. Accordingly, we investigated whether environmental enrichment (EE) influences behavioural time allocation in yellow-breasted capuchin monkeys (Sapajus xanthosternos), aiming to inform evidence-based husbandry practices in zoological settings. Employing the standard ethological approach of behavioural coding, we observed 20 capuchins housed in three groups comprising adult and juvenile males and females. We recorded behavioural categories including: aggressive, exploratory, affiliative/play, general activity, alert, inactivity, and abnormal behaviour. To evaluate individual engagement with EE, we applied the ABA paradigm, wherein phases A1 and A2 (controls) represented standard zoo conditions, while phase B corresponded to the implementation of an EE programme. Each phase spanned 10 days, and behavioural data were collected via focal animal sampling (2 × 10 min focal sessions per animal per day), resulting in a total of 1200 focal sessions. Behavioural time allocation was analysed using a multivariate generalized linear mixed modelling approach that accounted for the interdependence among behavioural categories. Based on previous studies, we predicted that environmental enrichment may promote higher levels of play and exploration and lower aggression and inactivity. However, despite by-eye suggestions of increases in play and decreases in activity during enrichment, when behavioural categories were analysed simultaneously within the multivariate framework, overall behaviour time budgets and behavioural diversity were found not to change significantly across experimental phases. There were also no sex or age effects on behaviour. This indicates that for S. xanthosternos, the enrichment protocol used here did not provide sufficient novelty or complexity to alter established activity patterns. Integrated analytical approaches are needed to further evaluate the effectiveness of enrichment strategies to ensure they are tailored to specific cognitive and social needs of complex species; future studies could explore how social dynamics, enclosure design, and environmental complexity interact to shape behavioural responses to enrichment. Full article

Transdisciplinary Research (TDR) leverages shared concepts to foster mutual learning among diverse stakeholders, relying on “boundary objects” to shape collective identities and visions. However, the existing literature often overlooks the critical roles of subjectivity and conflict in this process. This paper introduces an analytical framework to examine the construction of these objects, using the “Oasis Project” in the Ecuadorian Andes as a central case study. A research-action project on pesticide-free territories in Ecuador unearthed a question during its implementation on how to achieve collective action when key actors are in conflict with each other. Using TDR to find boundary objects where different viewpoints can find shared meaning, it was determined that there is not enough conceptual clarity in the literature around how conflict can actually help achieve coordination. Using a variety of qualitative methods, such as interviews, participatory observation, and analysis of WhatsApp group message texts, this study shows how the novel concepts of boundary entanglements and conflicts can help other researchers and practitioners facilitate impactful TDR. This study emphasizes three transformative lessons for sustainability science: first, boundary objects are inherently dynamic, evolving through continuous social negotiation rather than static definition; second, their successful consolidation requires deep integration into local knowledge systems, cultural norms, and governance structures; and third, and perhaps most critically, conflict and operational breakdowns are not indicators of failure; rather, they serve as vital diagnostic tools that unveil hidden power relations and epistemic boundaries, providing essential moments for critical reflection and the recalibration of collaborative sustainability strategies. Full article

PFAS contamination represents a slow, invisible chronic technological disaster with documented long-term psychosocial impacts on affected communities. However, existing research has predominantly focused on toxicological and biomedical outcomes, leaving the lived experiences and narrative dimensions of contamination underexplored. This study investigates how residents of PFAS-contaminated communities experience and narrate environmental contamination by applying Edelstein’s Theory of Environmental Turbulence (TET) and integrating a bottom-up stage-based model of psychosocial reaction with narrative epidemiology. Twenty-five personal narratives were selected from the digital archive Living With PFAS and analyzed through thematic analysis. Three main themes emerged, corresponding to the TET dimensions of lifescape, lifestyle, and lifestrain, articulated across twelve subthemes: inversion of health, self, home community and place, environment, livelihood, trust, environmental stigma, shock and fear, chronic concern, anger, parental guilt and relation strain. The findings demonstrate that PFAS contamination produces multidimensional disruptions that extend beyond toxic exposure to encompass identity, social relationships, institutional trust, and collective memory. Integrating TET with Psycho-Social Impact Assessment (PSIA) offers a theoretically grounded and exploratory transdisciplinary framework for identifying hidden suffering and informing more responsive environmental health policies and community interventions. Full article

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