Search Results (1,760)

This study examines the kalif structure, a unique and increasingly invisible component of the rural architecture in the Eastern Black Sea region that is currently under threat of extinction, along with the tradition of kalif-guarding integrated with this structure. Historically constructed to protect agricultural production from wildlife, kalifs are not merely functional shelters but also multi-layered memory objects where collective solidarity and social interaction are reproduced. A qualitative research method was adopted for the study, utilizing literature review, on-site physical documentation, and technical analysis centered on Yücehisar village in the Pazar district of Rize. Within the scope of the research, the material use and construction techniques of kalifs are detailed from an architectural perspective, and these practices are evaluated through the lens of Intangible Cultural Heritage. The findings indicate that the loss of the physical presence of kalifs due to the transition from corn to tea cultivation and rural migration signifies the dissolution of a production-based culture of living. Consequently, the study reveals the critical importance of incorporating the kalif and the act of kalif-guarding into academic literature and cultural memory within the framework of Intangible Cultural Heritage standards to preserve local identity and rural memory. Full article

Emotion detection in social media remains challenging, particularly in polarized public debates where emotional expression is often imbalanced across categories. Addressing this challenge, this study compares the performance of multiple computational approaches using a gold-standard dataset of tweets about an ongoing geopolitical conflict. The dataset reflects the authentic, skewed distribution of emotions observed in real-world online discourse. We evaluated lexicon-based methods, classical machine-learning classifiers, deep-learning architectures, transformer models in both fine-tuned and zero-shot configurations, and a zero-shot large language model to assess their effectiveness in capturing both frequent and less frequently expressed emotions. Across approaches, transformer models, especially those fine-tuned for contextual emotion recognition, demonstrated the strongest overall performance, with emotion-specific fine-tuning offering a particular advantage for detecting rare emotion categories. These findings emphasize the importance of evaluating emotion detection methods under realistic class imbalance and highlight both the comparative strengths and limitations of widely used modeling strategies in applied social media research. This study advances emotion analysis and computational social science by offering practical guidance for selecting appropriate emotion detection methods in complex, imbalanced social media contexts. Full article

Large Language Models (LLMs) offer opportunities for processing heterogeneous information streams relevant to energy-market decision-making, but their practical role in forecasting-oriented analytical workflows remains uncertain. This paper presents an exploratory feasibility study of LLM use across four energy-market tasks: geopolitical event monitoring for Dutch Title Transfer Facility (TTF) market context using Global Database of Events, Language, and Tone (GDELT)-based data, structured summarisation of commodity-intelligence articles, prompt-engineered solar-power and grid-load forecasting for Austria, and a short-horizon exploratory TTF price-estimation case. The study is positioned as a pilot investigation and hybrid workflow blueprint rather than as a statistically conclusive forecasting benchmark. A four-layer reference architecture was devised, including structured market data, semi-structured news intelligence, web-scraping concepts, and implemented Twitter/X and GDELT monitoring layers. The empirical cases indicate that LLMs are most useful for text-heavy reasoning, event-context integration, source triage, and structured interpretation. In the 20-article summarisation corpus, Gemini 1.5 Pro achieved higher commodity-direction accuracy than GPT-4, while GPT-4 showed stronger output-format stability. In selected solar case checks, OpenAI models produced plausible generation curves close to the Fraunhofer ISE Energy Charts reference, while Energy Charts remained more accurate for aggregate load estimation in the available benchmark comparison. The two-day TTF experiment illustrated that LLMs can incorporate qualitative geopolitical context into short-horizon reasoning, but it did not establish reliable price-forecasting capability. The Twitter/X monitoring layer is retained as a documented negative pathway, showing the limitations of informal social-media scraping for reproducible market intelligence. Full article

The construction sector accounts for approximately 36% of global final energy consumption and close to 40% of total CO₂ emissions, making it a primary target of international climate policy. Despite this growing attention, the indigenous building traditions of the Ecuadorian Andes remain virtually absent from the international scientific literature on vernacular sustainability. This study presents a systematic field documentation and bioclimatic assessment of vernacular bahareque dwellings in the Kichwa-Saraguro community of Ilincho, canton of Saraguro, province of Loja, Ecuador (2700 m a.s.l.). A field survey of 30 dwellings identified five morphological typologies—I-1P, I-2P, 2B, L, and C—with typology C, a compact C-shaped block with a three-sided portal, accounting for 53.3% of the sample. A structured multi-criteria framework of 48 bioclimatic indicators distributed across eight categories, adapted to the cold-temperate mountain climate of the study area, was applied to quantify each typology’s bioclimatic performance. All typologies exceeded 75% overall compliance on the global Bioclimatic Performance Index (BPI), with typology C achieving the highest value (88.5%). Categories F (Materials and construction) and H (Cultural and social aspects) scored 100% across all typologies, reflecting system-level properties of the bahareque constructive system rather than morphological differences between typological variants; a supplementary morphological BPI restricted to Categories A–E and G is reported. An exploratory, uncalibrated energy simulation of typology C provided indicative evidence consistent with the expected thermal behavior of a high-thermal-mass bahareque envelope, with simulated minimum temperatures in the sleeping area within the American Society of Heating, Refrigerating and Air-Conditioning Engineers (ASHRAE) 55-2013 comfort range (T-min 18.80 °C). Collectively, these findings contribute quantified bioclimatic documentation of vernacular bahareque architecture in Ilincho, identifying attributes—encompassing solar control, spatial compactness, high-thermal-mass envelope performance, and use of locally sourced low-embodied-energy materials—that may inform sustainable rural housing discussions in the Ecuadorian Andes and comparable high-altitude mountain contexts. Its documentation in the indexed scientific literature constitutes a step toward recognizing this constructive heritage as a practical resource for low-carbon building policy. Full article

Background: Blockchain and distributed ledger technologies are increasingly proposed to strengthen traceability, governance, visibility, and coordination in mining and mineral supply chains, but mining-specific evidence remains fragmented. Methods: We conducted a systematic mapping review of peer-reviewed articles indexed in Scopus and Web of Science to examine application contexts, functional roles, technical architectures, evidence types, and adoption constraints of blockchain-enabled systems in these settings. Results: The review shows that blockchain is used across five functional domains: traceability and provenance; governance and secure data control; operational monitoring and inspection; energy and market coordination; and sustainability and environmental surveillance. Permissioned and consortium-based architectures predominated and were commonly combined with sensors, external storage, identity mechanisms, and smart contracts. Evidence was strongest for technical feasibility under simulated, experimental, comparative, or bounded pilot conditions, whereas durable economic, social, and governance outcomes remained less substantiated. Conclusions: Blockchain is most credible in mining contexts when it supports controlled coordination, auditable recordkeeping, and process integrity. Its practical value depends on reliable physical-to-digital data capture, workable governance arrangements, interoperability, and validation under real institutional and operational conditions. Full article

This study examines whether firm-level digital transformation capability (DTC) is associated with stronger operational resilience and whether governance structures condition this relationship. Operational resilience is treated here as a business-sustainability dimension based on continuity and stability of operating outcomes, not as a broad measure of environmental, social, and governance (ESG), environmental, or social sustainability performance. Using an international firm-year panel that combines standardized financial data with disclosure-based measures of implemented digital practices and governance architecture, the analysis provides observational evidence on the role of DTC in strengthening firm adaptability. In the controlled fixed-effects models, DTC is positively associated with the sales resilience ratio (SRR) (β = 0.071) and the cash-flow stability index (CFSI) (β = 0.058); an interquartile increase in DTC corresponds to approximately 0.024 in SRR and 0.019 in CFSI, or roughly 16% and 10% of their sample standard deviations. The association is stronger in firms with stronger internal oversight, auditable review mechanisms, and external ecosystem monitoring. Mechanism analyses point to supply flexibility and data visibility as plausible transmission paths, while additional tests address reproducibility, disclosure-intensity bias, construct validity, alternative governance specifications, placebo timing, restricted-shock logic, and measurement boundaries. Overall, the findings provide evidence consistent with a contingent and observational association between DTC and operational resilience when digital capabilities are embedded within accountable governance frameworks. Full article

Urban informality is a defining feature of Latin American urbanisation, with estimates suggesting that up to 80% of the urban landscape has been informally built. Despite its centrality in urban development, its integration into architectural education remains limited, revealing a gap between the realities of city-making and the professional training offered by universities. This study examines how architecture programmes in Chile, Peru, and Ecuador address urban informality and the extent to which they prepare future professionals to engage with the dominant modes of urban production in the region. Using a qualitative and comparative methodology, the curricula, course descriptions, and academic lines of 50 universities were analysed across three dimensions: (1) the thematic presence of concepts related to informality, (2) the degree of curricular integration—core, transversal, or tangential—and (3) pedagogical orientation, classified as technical–normative, social–critical, or interdisciplinary. The results reveal a fragmented and uneven incorporation of urban informality. Chile shows the highest relative presence, though often embedded indirectly within broader themes such as inequality or sustainability and framed through technical–normative approaches. Peru and Ecuador display even more limited integration, generally confined to isolated courses or electives. The study argues that this marginal incorporation weakens the preparation of professionals working in contexts where informality is a structural urban condition and calls for an “informal turn” in built-environment education. Full article

Domestic Violence affects 1 in 3 women worldwide. Empirical evidence from India suggests that women and girls experience a continuum of violence and discrimination from prenatal stages till death in families that largely continue to operate within a dominantly patriarchal framework. However, the literature on domestic violence in India suffers from problems pertaining to reductive and episodic framing, focusing on short-term prevalence, and frames the impact on survivors largely in terms of clinical constructs such as anxiety, depression, and PTSD. This work argues for a broader, thematic framing of domestic and familial violence and contends that the psychological sequelae of this kind of chronic and systemic discrimination and violence cannot be captured using rigid clinical constructs that dominate psychological literature. We propose a conceptual framework, i.e., SPECTRA (Socially and Psychologically Embedded Continuous Trauma in Relational Architecture), which is partially aligned with the propositions of complex trauma. However, we also critique the origin of complex trauma within hegemonic psychiatry and highlight the need for creating a culturally adapted expansion—to shift the emphasis from an individually rooted, diagnostic framework to a culturally contextualized continuous trauma framework. We utilize seven illustrative case studies to define the tenets of the SPECTRA model. Full article

Heritage-led urban redevelopment is increasingly adopted to advance cultural continuity and social vitality; however, its long-term sustainability is often compromised due to the absence of user-oriented assessment methods. Conventional Post-Occupancy Evaluation (POE) approaches are limited in their ability to capture experiential, social, and participatory dimensions of architectural and urban spaces. This study examines the potential of Virtual Reality (VR) as a participatory POE tool for sustainable heritage redevelopment through the case study of Souq Al Muharraq in Bahrain. A convergent mixed-method approach is employed, integrating immersive VR 360-degree walkthroughs, structured questionnaires, qualitative semi-structured interviews, and expert evaluation. The findings reveal significant discrepancies between design intentions and lived experience, specifically in thermal comfort, circulation, social usability, and informal spatial practices. The study demonstrates that VR supports a user-centered and experiential approach aligned with Sustainable Development Goals (SDGs) 9, 11, and 16. It further proposes a sustainable and cost-efficient framework for architecture and urban projects’ evaluation by enabling early and post-user-centered evaluation of projects to reduce costly revisions and the creation of inclusive, adaptive, and resilient architecture and urban spaces. Full article

Environmental, Social, and Governance (ESG) metrics have become a cornerstone to sustainable finance, yet their measurement and predictability remain constrained by data heterogeneity, methodological divergence, and disclosure bias. This study develops a comprehensive ESG prediction framework grounded in the Design Science Research paradigm, integrating advanced machine learning techniques with rigorous data preprocessing, feature selection, and temporal validation. Using firm-level data from Refinitiv and Bloomberg, the analysis distinguishes between ESG composite performance and disclosure-based robustness, addressing a critical gap in the literature. Ensemble learning models, including Random Forest and XGBoost, are evaluated alongside deep learning architectures using multiple sampling strategies and rolling-window validation. The results demonstrate that ESG performance is moderately forecastable, with ensemble methods consistently outperforming neural networks in structured datasets. In contrast, disclosure robustness exhibits lower predictability, reflecting its dependence on discretionary strategic reporting and institutional factors. The findings highlight the importance of data quality, model selection, and validation design in ESG analytics, while emphasizing the limitations of deep learning in tabular financial contexts. The integration of explainable artificial intelligence further enhances interpretability by identifying key predictors of ESG outcomes. Overall, the study contributes to the literature by providing a robust, interpretable, and methodologically rigorous framework for ESG prediction, with implications for investors, regulators, and corporate decision-making. Full article

Social robots hold promise for enhancing later-life support, but user needs and preferences for multimodal interaction modalities remain underexplored. This study explores awareness, willingness, perceived barriers, and modality–function associations across multiple interaction modalities among middle-aged and older adults, and proposes a conceptual five-layer architecture for design guidance. A questionnaire survey with 199 Chinese respondents (aged 45–64: 89.4%, 65+: 10.6%) examined perceptions of voice, visual, gestural, affective, sEMG, and brain–computer interface interactions. Voice and visual modalities were the most preferred; gesture and affective interactions were moderately accepted; awareness of sEMG was high but may reflect confusion with other sensor technologies; and BCI awareness and willingness were low. Based on survey findings and the literature, a conceptual five-layer architecture is presented to inform future social-robot design. The sample predominantly comprised middle-aged participants, so findings reflect prospective later-life users rather than the broader older-adult population. This study offers user-centered insights into multimodal social-robot interaction and provides design implications for future development rather than evaluating emotional-health interventions. Full article

Historic districts are important built environments in which architectural form and cultural meaning shape residents’ place-based identity and engagement with conservation under urban renewal. However, empirical evidence on which features of the historic environment most strongly support local identity and conservation participation in migrant-intensive, fast-growing cities remains limited. This study investigates the relationships among architectural heritage, religious elements, cultural activities, local identity, sense of belonging, and conservation participation in five historic districts in Shenzhen, China. Using a residents’ questionnaire survey, we applied hierarchical multiple regression and mediation analysis to examine these relationships. The results indicate that architectural heritage is the strongest predictor of local identity, whereas religious atmosphere and cultural activities show comparatively weak effects. Local identity is positively associated with conservation participation, with only limited mediation through sense of belonging. The findings indicate that in migrant-intensive urban settings, architectural distinctiveness plays a stronger role in shaping local identity than religious or other cultural practices. Overall, the study argues that architectural heritage should be seen not only as a physical fabric to be preserved, but also as a resource that can strengthen local identity, participation, and socially sustainable urban renewal. Full article

Lesson planning is a core professional practice for pre-service teachers, yet opportunities for timely, individualized feedback are frequently constrained by educator workload. While generative AI has the potential to enhance planning processes and expand opportunities for individualized feedback, the provision of comprehensive lesson plans may lead to excessive reliance. This conceptual design paper details the development and theoretical underpinnings of an artificial intelligence-assisted feedback tool that provides self-efficacy-strengthening feedback on lesson plans for pre-service teachers. To promote constructive feedback, the AI-assisted feedback tool integrates principles from educational feedback research and structures feedback to foster teachers’ lesson-planning self-efficacy through mastery-oriented affirmations, vicarious examples, social persuasions, and emotional reassurance. Curriculum alignment is incorporated to support content validity and contextual appropriateness. While the initial implementation of the feedback tool focuses on Western Australian teacher education, an explicit transfer perspective is considered for the German vocational education context. The paper describes the iterative development process that follows a design-based research approach including platform evaluation, internal refinement, and expert review by teacher educators in Western Australia. The resulting system prompt architecture comprises 11 dimensions including general baselines, the interaction between the Lesson Planning Coach and PSTs and the theoretical foundations mentioned above. The tools’ environment, including examples for provided feedback on lesson plans, is presented and discussed. Finally, an outlook is given on the planned empirical research to evaluate the effectiveness of the tool. Full article

The National Register of Historic Places (NR) is a structured artifact of meaning-making that encodes disciplinary values linking architectural and cultural significance to wealth and stylistic distinction. In doing so, it systematically underrepresents vernacular, working-class, and the built environments of racially and ethnically marginalized communities. This paper uses artificial intelligence (AI) to examine how that meaning is constructed. We analyze the preservation record across three scales: a national dataset of 100,117 NR listings (1966–2025), a state-level profile of Illinois’s 1997 NR listings, and a close analysis of Lake Forest, Illinois, a community whose exceptional concentration of NR-listed estate architecture makes it an ideal site for examining how preservation significance has been defined and what it excludes. Two parallel AI methods are applied to eighteen Lake Forest nomination documents and their associated photographs. Natural Language Processing (NLP) analyzes nomination text to trace how preservation professionals connect buildings to cultural value; blind AI image analysis examines the same properties to assess how a model trained on cultural imagery constructs visual meaning independently. NLP analysis reveals a corpus dominated by architectural description, with social history, landscape, and labor systematically underrepresented. The visual analysis confirms and amplifies the nomination record’s class-based assumptions while reproducing the same omissions regarding labor, diversity, and community context. These findings inform debates about AI’s potential to audit existing listings and support nominations for underrepresented property types, while showing that without deliberate corrective design and policy reform, such tools are as likely to replicate the preservation system’s inequities as to repair them. Full article

Background: This research explores the intersection between cultural heritage and mental health, analyzing how heritage mediation acts as a strategic asset in the personal recovery of individuals experiencing mental distress. Methods: A systematic review was conducted across PubMed, PsycINFO (via ProQuest Psychology Collection), Scopus, Web of Science, and Google Scholar for the 2015–2026 period, following PRISMA protocols. The methodological quality of 18 selected studies was evaluated using the Mixed Methods Appraisal Tool (MMAT). Results: The findings reveal that the efficacy of these practices stems from a symbiotic interaction between tangible and intangible heritage, functioning as an “identity scaffold” that facilitates the transition from a “patient identity” toward a “citizen identity” with biographical authority. Analysis under the CHIME (Conexión—Hope—Identity—Meaning—Empowerment) framework reveals convergent evidence across the Identity dimension, positioning cultural environments as “third spaces” that mitigate self-stigma. Discussion and Conclusions: Recovery is identified as a circular phenomenon requiring the convergence of clinical and cultural scaffolding. This study advocates for a humanized service architecture where therapeutic practices and affective curating coexist, ensuring the right to identity and social justice within community mental health contexts. Full article