Search Results (977)

This article considers traditional Inuit beliefs and practices as expressed through human–animal relationality, examining the physical and spiritual significance of qimmiit (sled dogs), and how qimmiit functioned as co-travellers with humans across physical and spiritual realms of existence. Drawing on ethnographic and missionary narrative sources, it explores Inuit–Qimmiit relationality as central to survival in the pre-modern period. Consulted sources include the writings of explorer–ethnographer Knud Rasmussen, Church of England missionary Edmund James Peck, anthropologist Franz Boas, explorer–author Peter Freuchen, and Oblate missionary Pierre Henry (Kajualuk). These accounts, despite Euro-centric and Christian biases, provide distinct yet overlapping experiences with sled dogs and understandings of Inuit traditions and worldviews. Read comparatively, these ethnographic texts reveal how qimmiit were essential to mobility and spiritual–social order. The article draws on the Qikiqtani Truth Commission to contextualize the harm and suffering caused by the loss of qimmiit during the dog killings of the 1950s to 1970s. The song “Travel Without Me,” from the Animal Kinship Project and written to commemorate qimmiit in the aftermath of the sled dog slaughter, provides a narrative framework structured around kinship and travel, foregrounding Inuit understandings of shared journeys across human and canine existence and framing Inuit–Qimmiit relations as enduring bonds that traverse both physical life and afterlife. Within Inuit religious cosmologies, relationships between humans and qimmiit extend beyond practical cooperation to encompass shared spiritual existence, relational obligation, and continuity of soul across physical and metaphysical worlds. Ethnographic accounts recorded by Rasmussen, Peck, Boas, Freuchen and Henry describe dogs not merely as working animals but as ensouled beings who participate in travel, naming practices, shamanic mediation, cosmogonic and afterlife narratives. Read through a religious studies lens, these sources reveal a cosmological framework in which mobility and survival are embedded within sacred relational structures linking human and animal life. This article examines Inuit–Qimmiit kinship as a form of physical–spiritual relationality, arguing that dogs function as co-travellers whose relational position across embodied and cosmological domains illuminates Inuit understandings of personhood, cosmological balance, and the continuity of life beyond death. Full article

School classrooms represent complex, interconnected systems where indoor environmental quality critically influences student health, cognitive performance, and educational equity. Yet traditional approaches operate in disciplinary silos, creating systemic failures in design, operation, and maintenance. This narrative review adopts a systems engineering framework to demonstrate how integrated interventions—spanning policy, design, technology, and operations—create resilient, sustainable, and healthy classroom climates. Amid escalating climate change impacts (rising temperatures, heatwaves, wildfires) and emerging threats (airborne pathogens, urban pollution), reactive measures like school closures prove pedagogically counterproductive. This review synthesizes evidence on natural, mechanical, and mixed-mode ventilation systems optimized through advanced control strategies, smart technologies, and health-centred policies. Key findings reveal that synergistic integration of Policy, Management, Construction, Operation, and Smart Technologies, in a systems engineering framework, outperforms singular strategies. Critical interventions include hybrid ventilation coupled with layered defences (HEPA filtration, UVGI), AI-driven adaptive controls using IoT sensors and Model Predictive Control to optimize energy while managing pollutant concentrations, and mandatory IAQ standards rooted in stakeholder education. By framing classrooms as interconnected engineering systems, this work provides actionable insights for architects, engineers, policymakers, and administrators, positioning future school design toward resilience, sustainability, and human-centred health outcomes. Full article

For a robot to operate effectively in human-centric environments, finding objects based on natural language is essential. Zero-shot object goal navigation is a significant challenge where robots must find unseen objects in new environments without prior knowledge. Existing methods often struggle with strategic exploration, leading to inefficient searches. In this study, we propose a hierarchical scene graph-based navigation system to address this challenge. Our core innovations are twofold: dynamically constructing a three-layer “room–workspace–object” hierarchical scene graph without manually pre-tuned parameters, and introducing a novel workspace-based searching strategy. By evaluating semantic relevance at the workspace level rather than the object level, the robot infers probable containers for a target, enabling focused, human-like exploration. Simulation results demonstrate that our system significantly outperforms existing state-of-the-art methods. Quantitatively, our approach improves the Success Rate (SR) by 26.8% (SR 0.4859) under distance-constrained settings and by 20.2% (SR 0.7360) under unconstrained settings, compared to the best baselines. These results validate that our framework offers a robust solution for zero-shot object goal navigation. Full article

Microplastics (MPs) are increasingly recognized as a global environmental threat. Emerging evidence suggests they may have metabolic consequences. In this review, we synthesize current findings from animal and in vitro studies to propose a mechanistic framework linking MP exposure to type 2 diabetes mellitus (T2DM). This framework is uniquely centered on the gut–liver axis and macrophage-centric immune networks. We systematically delineate evidence suggesting that MPs can compromise intestinal barrier integrity, instigate gut dysbiosis, and promote pro-inflammatory M1 polarization of macrophages in experimental models. This immune activation is proposed to subsequently amplify hepatic inflammation, potentially contributing to systemic insulin resistance (IR) and pancreatic β-cell dysfunction. We emphasize that while this pathway is biologically plausible, direct causal evidence in humans remains limited and is a critical knowledge gap. Integrating multi-level evidence from animal models and in vitro systems, we delve into the trans-organ immunometabolic effects of MPs within adipose tissue, pancreas, and skeletal muscle, establishing their role as a novel class of “metabolic disruptors.” Critically, we assess the key controversies and knowledge gaps pertaining to dose–response relationships, particle-specific toxicity (size, polymer type, and additives), the effects of complex environmental mixtures, and the urgent need for robust human validation. We advocate for future research priorities, including multi-omics integration, advanced organ-on-a-chip platforms, prospective cohort studies, and targeted intervention strategies, to propel this field from mechanistic exploration toward clinical and public health relevance. Finally, this synthesis underscores that mitigating the production and environmental release of MPs, alongside developing strategies to impede their bioavailability and accumulation, represents a crucial public health imperative for the prevention of environment-related metabolic diseases. Full article

In intermittent convective cooling environments created by split air conditioners, the dynamic nature of the environment poses challenges to traditional steady-state thermal comfort models in predicting human thermal comfort. Therefore, this study proposes an alliesthesia-informed machine learning framework that encodes alliesthesia theory into explicit mathematical features for predicting dynamic overall thermal comfort. Data were obtained through controlled experiments under intermittent cooling conditions, and a theory-driven feature set incorporating dynamic set points and physio-psycho gap was constructed. The results demonstrate that the gradient boosting model achieved optimal performance under rigorous subject-level cross-validation (test set R² = 0.71). Interpretability analysis confirmed that model decisions are highly dependent on exposure time and alliesthesia features, whose importance far exceeds that of conventional environmental parameters, revealing that the core of thermal comfort perception lies in the dynamic interplay between physiological states and psychological expectations. Furthermore, the proposed few-shot personalized calibration strategy can effectively accommodate individual differences with minimal user data. This study demonstrates that the framework not only enhances prediction accuracy but also improves model interpretability and generalizability by incorporating alliesthesia-inspired feature representations, offering a new perspective for developing next-generation human-centric intelligent environmental control systems. Full article

Local governments are key actors in driving urban renewal. To implement urban renewal initiatives, in-depth research into their policy backgrounds, institutional characteristics, and governance logic is essential. Traditional policy analysis often neglects the value dimension, which undermines the effectiveness of embedding informal institutional values. To complement existing research, this study examines 50 urban renewal policy documents issued in Guangzhou between 1978 and 2025. Using content analysis and grounded theory methods, this study incorporates the value dimension into the traditional “supply–demand–environment” policy analysis framework to examine local governments’ policy preferences in urban renewal, and to interpret its governance logic from the perspective of Williams’ four-level framework. The findings are as follows: (1) Guangzhou’s urban renewal has formed a policy system centered on supply-side policies, supported by environmental policy improvements, with value embedding, demand-driven measures, and multi-dimensional guidance as supplementary components. Local governments show a distinct preference for supply-oriented policy tools. (2) Guangzhou’s urban renewal policies present a pyramid structure with resource allocation at the core and governance structure as the foundation. The policies focus on the optimal allocation of land resources, collaborative actions among government, market, and society, the deep integration of public values, the clarification of property rights rules, and the application of digital technologies. (3) The governance logic of urban renewal forms a four-tier progressive closed-loop: from value anchoring to rule linkage, then to multi-stakeholder collaboration, and finally to factor empowerment, establishing a systematic governance mechanism that balances people-centricity and efficiency. Accordingly, urban renewal should prioritize value embedding and cultural preservation, balance investment in physical assets and human capital, optimize governance structures and policy mixes, coordinate the roles of an effective market and a capable government, improve supply–demand matching and the efficiency of resource allocation, and adjust the complementarity and applicability of policy tools. Full article

Large Language Models (LLMs) are emerging as a new class of intelligent systems capable of reasoning over heterogeneous knowledge and interacting with human operators, yet their role in renewable energy systems remains insufficiently synthesized. This review provides a dedicated, systematic examination of LLMs as knowledge-centric, human-oriented decision-support tools for renewable energy infrastructure. In contrast to existing surveys that primarily emphasize numerical optimization, forecasting, or conventional machine learning methods, this work focuses on how LLMs enable textual reasoning, regulatory interpretation, operational intelligence, and interactive support across energy system lifecycles. We present a structured overview of recent literature, categorizing LLM applications by their functional roles in analysis, control, operation, and policy support. Furthermore, we analyze the contributions of LLMs to key decision-support tasks, including information retrieval, incident analysis, operational coordination, and strategic planning in smart grids and microgrids. The review also critically examines current limitations and risks associated with deploying LLMs in energy systems, including hallucination, reliability, domain adaptation, explainability, and real-time operational constraints. Finally, we identify emerging research directions, including energy-efficient LLM deployment, sustainability-aware AI design, and the alignment of LLM-based solutions with the goals of resilient, low-carbon, and environmentally sustainable energy systems. Full article

The implementation of artificial intelligence (AI) in education is gaining more attention, and as a result, more research is being conducted on the views and conceptualisations of AI by educators. The understanding of teacher candidates is vital for the AI integration in education, which should be human-centred, and still, there is a lack of studies focusing mainly on teacher candidates in the field of the native language. This qualitative phenomenological research aimed to explore metaphors of 46 Turkish language teacher candidates (third- and fourth-year undergraduates in Northern Cyprus) representing their answer to the prompt “AI is like because…”. The data were collected through open-ended questions and analysed using content analysis along with expert validation. Participants produced 46 valid metaphors, which were divided into five thematic categories: (1) AI as Teacher or Learner (21.7%), (2) AI as Method/Strategy (21.7%), (3) AI as Evolving Living Organism (13%), (4) AI as Guide/Helper (21.7%), and (5) AI as Danger/Threat (21.7%). Four groups expressed positive or neutral attitudes towards AI, such as considering it a clever teacher, a useful tool, a growing entity, or a guide. One category revealed negative views, perceiving AI as a destructive force. Overall, 78.3% of participants expressed optimistic views about AI, while 21.7% of them pointed to concerns. Turkish language teacher candidates generally perceive AI as a supportive, human-like assistant in the classroom, but a few of them express concerns about its existence. These results emphasise the importance of incorporating AI literacy and ethics into teacher education. Equipping future language teachers with the skills to use AI in the classroom might be a way of implementing AI in schools that is confident, critical, and human-centred. Full article

The construction industry faces persistent challenges in productivity, efficiency, and sustainability. Digital twin (DT) technology has emerged as a promising pathway for lifecycle optimisation, yet its construction adoption remains limited. Key barriers include fragmentation across project phases, weak data continuity at handover, and conceptual ambiguity between DT and Building Information Modelling (BIM). This systematic literature review analyses 160 peer-reviewed studies (2018–2026) selected from 463 Scopus records using a PRISMA-guided process and inter-rater reliability testing (Cohen’s κ = 0.83). The review clarifies that DTs extend beyond BIM in three ways: they enable bidirectional, automated physical-digital data exchange; integrate heterogeneous real-time sources such as IoT sensors and operational systems; and maintain lifecycle continuity from design through to end-of-life. Select advanced implementations report notable performance gains. These include rework and logistics reductions of up to 80%, cost savings of approximately 5%, schedule acceleration of around two months, energy reductions of 15–30%, and maintenance cost reductions of 10–25%. These figures reflect case-level outcomes from high-performing pilots and should not be read as typical industry benchmarks. Broader adoption remains constrained by interoperability gaps, data quality challenges, digital maturity deficits, misaligned stakeholder incentives, and paper-based regulatory environments. DTs represent a socio-technical transformation, not a standalone technology upgrade. Realising their potential requires coordinated progress in standards development, governance frameworks, collaborative delivery models, and workforce capability. Future research should focus on scalable interoperability, longitudinal lifecycle value validation, human-centred adoption strategies, and sustainability assessment methods to support evidence-based diffusion of DTs in the built environment. Full article

With the advancement of digital technology and Industry 4.0, artificial intelligence (AI) is gradually embedded in human resource management and has become an important digital foundation to support the sustainable transformation of enterprises. However, the research in the manufacturing context, particularly through the challenge perspective at different levels, remains fragmented. This work represents a systematic review of 347 articles from Scopus and Web of Science from 2000 to 2025 and employs a dual-method analysis strategy embracing metrics and in-depth coding on 100 core publications. Excel, Bibliometrix, CiteSpace, Latent Dirichlet Allocation (LDA), and VOSviewer were utilized for quantitative analysis, while open–axial–selective coding of the Grounded theory approach was applied to generate qualitative results. The findings revealed six key challenges in integrating AI-HRM within manufacturing and six approaches to solve the identified issues. The Challenge–Approach Matching Matrix was constructed, illustrating the suitability of different pathways for addressing specific challenges. Analysis of thematic evolution in AI-HRM research resulted in the identification of three distinctive phases and demonstrated a consistent shift from technology-centric approaches towards human–machine collaboration. The primary contribution of this research lies in proposing a Multi-Level Embedded Framework providing a complex view of AI-HRM in a manufacturing sector at micro, meso, and macro levels. The absence of sustainable HR transformation through AI integration was identified as the critical challenge at the macro level. This research provides theoretical and practical implications for designing the sustainable HRM system based on ESG principles and favors the United Nations Sustainable Development Goals 9 and 12. Full article

Access to the sky is a key element of residential environmental quality. In densely built-up urban areas, exposure to the sky is often limited not only quantitatively but, above all, directionally. Traditional illuminance metrics, such as the Sky View Factor (SVF) or Daylight Factor (DF), describe the proportion of visible sky or the amount of light in an averaged manner, without considering its relationship to the functional organisation of the human field of view.This article introduces the Relative Retinal Image (RRI) metric, which evaluates directional access to the sky through geometric analysis of viewing directions in relation to functional zones of the visual field, without reconstructing perceived images or simulating physiological processes. Within this geometric framework, human vision is interpreted as operating simultaneously in two visual cones: a narrow central cone responsible for acute, conscious vision (RRI-A), and a wider peripheral cone enabling the reception of low-resolution but spatially stable stimuli (RRI-B). For clarity, three concentric central ranges are distinguished: foveal (0–2.5°), sharp central (0–5°), and extended interpretative central vision (up to 10°). The proposed approach provides a geometry-based analytical tool that complements existing daylight metrics in the assessment of sustainable residential environments, without formulating normative or biological design prescriptions. Based on geometric and graphical analyses and a case study of the Józefowiec housing estate in Katowice, the results indicate that the directional structure of the sky view may be lost despite compliance with conventional planning criteria. Full article

The peri-implantation window is a tightly regulated temporal phase during which the human endometrium undergoes coordinated molecular remodeling to establish receptivity. MicroRNAs (miRNAs) contribute to implantation-related processes; however, whether dynamic endometrial regulatory signals are functionally reflected in circulation within a defined temporal framework remains unclear. We hypothesized that although individual miRNA identities differ between endometrial tissue and plasma, temporally regulated miRNAs in both compartments may exhibit overlap at the level of enriched biological pathways during the peri-implantation window. To test this hypothesis, we performed time-resolved small RNA sequencing on paired endometrial and plasma samples collected from 62 participants across progesterone exposure days P+3 to P+7 in hormonally controlled cycles. Temporal modeling identified 27 dynamic miRNAs in endometrial tissue and 17 in plasma (FDR < 0.05). Despite limited overlap at the individual miRNA level, functional enrichment analysis revealed recurrent overlap in apoptosis-, cell cycle-, aging-, inflammatory-, and metabolic-related pathways across compartments. Four miRNAs exhibited concordant directional temporal trends between tissue and plasma with moderate correlation coefficients. These findings suggest that dynamic miRNA-associated enrichment patterns during the peri-implantation window may exhibit pathway-level overlap despite divergence in specific molecular identities. This temporally aligned integrative framework provides a pathway-centric perspective for interpreting cross-compartment miRNA-associated temporal patterns and supports a hypothesis-generating systems-level view of human implantation biology. Full article

Affiliated Open Spaces (AOS) constitute vital public assets within high-density vertical cities. However, prevailing scholarship remains largely confined to two-dimensional horizontal perspectives, overlooking the quantitative impact of vertical built environment characteristics on spatial distribution and human behavior. Focusing on four high-density districts in Guangzhou typified by distinct three-dimensional morphologies, this study integrates field surveys, 3D geospatial data acquisition, and 621 valid questionnaires to empirically analyze the impact of 3D spatial features on user behavior and the mediating role of accessibility. Utilizing the ArcGIS 3D Analyst for vertical accessibility measurement and Partial Least Squares Structural Equation Modeling (PLS-SEM) for path analysis, the study tests the hypothesized relationships using multi-source data. The results indicate that (1) a user’s vertical location exerts a significant negative impact on both accessibility and human behavior; (2) building density and building functional diversity indirectly promote user engagement primarily by significantly enhancing accessibility, thereby confirming accessibility as a critical mediator; and (3) significant spatial heterogeneity exists, revealing distinct correlation patterns across varying built environments. This research elucidates the pivotal constraint of “vertical location” and validates the mediating efficacy of accessibility, offering empirical insights for human-centric vertical urban planning. Full article

With global urbanisation anticipated to reach 68% by 2050, there is a significant risk of exacerbating urban transport emissions. Urban transport decarbonisation is a complex adaptive system challenge, the understanding and optimisation of which could be supported by digital twins (DTs). Although prior research has explored digital and big data technology applications, creating actionable insights requires human-centred designs. We conducted a structured workshop to gather practitioner views on how urban-scale DTs can support transport decarbonisation. Specifically, we explored the outcomes they aim to achieve, the interventions they are interested in, and the value digital twinning offers compared to current methods. The data was synthesised and analysed to identify (1) impacts, (2) interventions, (3) location types, (4) data sources and (5) feedback mechanisms of importance to participants. These five aspects are proposed as a framework to support the definition of digital twinning use cases targeting urban transport decarbonisation. Application of the framework encourages creators to explicitly consider the services to be provided to users, how the derived insights influence the real world and the data connections between the physical and digital, noting that these are often overlooked in reported research. A framework application is illustrated through an example use case described for the West Midlands, UK. Full article

Human–technology relationships have become core strategic capabilities and enablers of enterprise sustainability. Contemporary interactions between humans and technology are undergoing a profound transformation toward a more human-centric and value-oriented paradigm, aiming for Industry and Society 5.0, a shift that is particularly salient in banking. The influence of customer experience quality on the strategic foundations of enterprise management is being fundamentally redefined. The purpose of this research is to assess the influence of customer experience on marketing outcomes in the banking industry. To analyze the directions, strengths, and statistical significance of relationships, structural equation modeling (SEM) using partial least squares (PLS) was employed. The research model was tested on a sample of 616 valid responses from customers of banking services in Serbia. The research shows that customer experience positively impacts customer satisfaction, behavioral loyalty intentions, and word-of-mouth, making it a strong predictor of marketing outcomes. The moderating roles of gender, customer segment, and respondents’ regional affiliation were tested, identifying variables that moderate significant relationships between customer experience and marketing outcomes, unveiling detailed insights into demographic and segmentation disparities. The findings offer robust empirical support for managerial decision making in customer experience enhancement initiatives. Full article