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Urban environments are shaped by multisensory experiences in which olfaction plays an important yet often overlooked role. This study investigates the relationship between street morphology and urban smellscape in the city centre of Biskra, Algeria, providing the first empirical smellmapping study conducted in the country. The methodology combines smellwalking with a structured questionnaire to document odour types, perceived intensity, and pleasantness. The collected data were georeferenced and analysed using GIS tools, including point-based olfactory mapping and Inverse Distance Weighted (IDW) interpolation to explore spatial patterns of smell perception. The results reveal that specific odour typologies and levels of pleasantness are closely associated with street configuration and building morphology. Streets with continuous façades and active ground-floor uses exhibit distinctive olfactory identities, whereas traffic-dominated streets tend to generate less pleasant smell environments. These findings highlight the relevance of smellscape analysis for informing urban design and improving sensory qualities of public spaces. Full article

Rural adolescents face persistent health inequities driven by limited access to preventive health education, intergenerational engagement, and resources that support lifelong wellness. This study evaluated the effectiveness of Active Aging for L.I.F.E., a school-based intergenerational health literacy program, in improving adolescents’ attitudes toward aging and health. The four-session program, delivered through a train-the-trainer model involving older adults and undergraduate students, was implemented in three rural schools during the 2024–2025 academic year. A total of 86 junior high and high school students participated, with 77 completing pre- and post-program surveys assessing attitudes toward aging, health consciousness, and intergenerational engagement. Paired t-tests and multiple regression analyses examined overall program effects and differences by sex/gender and age group. Students demonstrated significant improvements in aging attitudes, perceived relevance of aging topics, enjoyment of intergenerational interaction, and awareness of health-promoting behaviors across the lifespan. Several baseline sex/gender and age-based gaps in health-related perceptions were reduced following participation, with stronger future-oriented attitude shifts observed among younger adolescents. These findings suggest that brief, scalable intergenerational interventions embedded in rural school settings can support early prevention, health literacy, and community capacity building, offering a promising strategy for advancing rural public health outcomes across the life course. Full article

Artificial Neural Networks (ANNs) are a key component of construction research as Construction 4.0 and data-based problem-solving continue to shape the construction industry. In this paper, a Scopus-based bibliometric analysis of ANNs in construction research was conducted from 2015 to 2025. From an initial set of 9149 publications, 3800 English-language publications were identified and analysed using publication, source, country, citation, and keyword mapping techniques in VOSviewer (version 1.6.20). The publications showed a significant increase after 2018, peaking in 2024. China, India, and the US were key players in ANNs in construction research, and key publications focused on optimisation, concrete property prediction, machine learning, and deep learning. Key publications in ANNs in construction came from Construction and Building Materials, IEEE Transactions on Geoscience and Remote Sensing, and Energy. ANNs in construction research are moving towards hybrid, digitally integrated, and data-based applications, although gaps persist in sustainability, social equity, climate resilience, and underrepresented regions. Full article

Fire is the core safety threat to the survival and development of timber-framed buildings, and passive fire prevention intervention is the core foundation of fire protection systems for timber-framed buildings. Existing reviews suffer from limitations such as incomplete scenario coverage, insufficient breakdown of intervention mechanisms, and a lack of methodological standardization. This study strictly followed the PRISMA 2020 systematic review guidelines, searching the relevant literature from January 2016 to April 2026 on the Web of Science, Scopus, and Science Direct databases. After standardized screening, 89 valid articles were finally included and a systematic study was conducted through bibliometric analysis, keyword visualization, and multi-dimensional classification coding. The results show that the number of publications in this field has been continuously increasing from 2016 to 2025, with China accounting for 31.46% of the total, ranking first globally. The study constructed a core intervention mechanism system for passive fire prevention in timber-framed buildings, covering four categories: intrinsic flame-retardant modification, isolation protection, structural optimization, and spatial control. The working principles, application effects, advantages and disadvantages, and engineering application scenarios of each mechanism were clarified. This study systematically sorts out the core intervention mechanisms of passive fire prevention in timber-framed buildings, clarifies the research status and development trends in this field, and can provide evidence-based support for the design optimization, technology development, and engineering practice of passive fire protection for timber buildings. Full article

Climate change is intensifying flood risks globally, yet preparedness behaviors vary dramatically across governance contexts. While past disaster research suggests that institutional trust enables individual preparedness, this relationship remains unexplored in high-capacity governance systems where citizens hold exceptionally strong confidence in government response. We examined this dynamic in the United Arab Emirates, where several surveys have found extremely high levels of public confidence in the local government institutions. In our survey of 900 respondents in the emirates of Dubai and Sharjah we also found that 97% of the respondents had confidence in local government institutions. However, interestingly we also found that while 77% of residents reported past experience with floods, household flood preparedness was markedly low. Using covariance-based structural equation modeling, we tested whether government trust mediates relationships between flood experience, risk perception, and household preparedness. The results revealed that government trust exhibited a strong negative association with flood preparedness, suggesting that institutional confidence may suppress rather than enable household protective action. Notably, flood experience was associated with reduced government trust, likely reflecting the impact of disappointment with service restoration times that exceeded individual expectations. This erosion of trust created positive mediation, indicating that flood experience was associated with increased preparedness. Conversely, higher risk perception was associated with increased trust, which was associated with reduced preparedness through negative mediation. Direct relationships between flood experience and preparedness were statistically non-significant, indicating complete mediation through the trust pathway. Socioeconomic status was positively associated with flood preparedness, with wealthier residents displaying higher protective behaviors. While these findings seem to challenge conventional disaster preparedness theory, the results align with the moral hazard and dependency arguments. Our results show that state-led disaster management in high-capacity governance systems may inadvertently create dependency that increases systemic vulnerability crowding out endogenous adaptive behavior. Building resilience in such contexts requires reframing institutional trust to emphasize shared responsibility rather than externalized protection. Full article

Building inclusive, high-density cities requires understanding vulnerable groups’ public space usage. While green exposure significantly impacts urban health, existing research frequently overlooks females’ specific needs regarding streetscape visual quality, green space structures, and daily travel experiences. To address this, the study investigates spatial disparities in Suzhou’s historic district. Utilizing multi-source data and mixed modeling strategies, including Partial Least Squares and Ordinary Least Squares (PLS-OLS) and eXtreme Gradient Boosting (XGBoost), the research analyzes how streetscape perceptions and green space characteristics affect female life satisfaction and expressed sentiment. Results indicate three main findings. (1) Streetscape visual features fundamentally drive subjective evaluations. Safe significantly enhances well-being, whereas boring and lively negatively impact life satisfaction, reflecting females’ acute sensitivity to environmental oppressiveness during daily travel. (2) Park diversity elevates expressed sentiment, while patch density positively influences life satisfaction, demonstrating the vital value of fragmented greenery for daily public space usage. (3) Boring precipitously diminishes life satisfaction after surpassing a specific threshold, while park diversity elevates expressed sentiment only after crossing a critical interval. The study establishes an integrated analytical framework linking visual perception, green space structure, emotional response, and satisfaction. These findings provide targeted strategies for enhancing inclusive urban design and optimizing green space allocation to improve streetscape safety and alleviate visual oppressiveness, thereby advancing gender social justice for vulnerable groups in historic districts. Full article

Buildings account for nearly 30% of global energy-related carbon emissions. In rapidly developing economies, the operational phase of buildings represents a major and growing source of emissions. However, emission pathways in hot-summer-cold-winter (HSCW) regions remain understudied. This study analyzes carbon emission peaks and influencing factors in the operational phase of existing civilian buildings in Anhui Province. It integrates energy balance tables, the LEAP model, carbon emission factors, and the STIRPAT model. The energy balance table method disaggregates building energy consumption into urban, rural residential and public sectors. It adjusts for transportation energy by deducting specific proportions of gasoline and diesel from industrial, commercial, and residential sectors. Heating energy calculations are simplified because the region has a HSCW climate with limited centralized heating. The LEAP model projects emissions under four scenarios from 2020 to 2060. The STIRPAT model with ridge regression reveals that the permanent population and energy structure negatively influence residential emissions with elasticities of −2.646 and −1.465, respectively. This finding is consistent with the province’s energy transition, where coal use dropped from 28.48% in 2005 to 0.45% in 2020 and electricity use rose from 39.86% to 59.01%. In contrast, per capita GDP, building area, and energy intensity show positive effects. For public buildings, tertiary industry added value and energy structure are key determinants. Scenario analysis identifies the blueprint scenario as optimal, with residential emissions peaking at 34.29 million tons in 2025 and declining to 9.19 million tons by 2060 through measures such as 10% building retrofits by 2025, 75% energy-saving standards for new constructions, 50% retrofits by 2060, and renewable energy integration with building electrification, outperforming the baseline scenario that peaks in 2036 at 49.46 million tons and other intermediate scenarios. The study underscores that energy structure optimization significantly decouples energy consumption from emissions, offering actionable pathways for dual carbon goals through policy synergies in building efficiency, population management, and clean energy adoption to foster sustainable development and the construction industry’s low-carbon transition. Full article

Public health emergencies require spatial crowdsourcing platforms to finish urgent tasks while limiting unnecessary movement across regions. Most online task assignment studies focus on profit, travel distance, latency, task coverage, or service quality. However, isolation sensitive scenarios need a different assignment goal. In such scenarios, regional crossings should be directly controlled during worker–task matching. This paper studies an isolation sensitive online task assignment problem in spatial crowdsourcing. The service space is modeled as a regional adjacency graph. The matching objective combines cross-region movement cost, an urgency reward for delayed task completion, and a dummy no-assignment cost for carry-over decisions. To handle dynamic arrivals, a time-sliced online process is used. Unfinished tasks are carried over to later time slots, and the priority of each carried-over task increases with waiting time. Based on this framework, we design two algorithms. OnlineKM serves as the basic priority-aware online matching algorithm. OnlineKM builds a matching problem in each time slot and applies KM-based partial matching with the information currently available. OnlineARC further uses δ-balanced adaptive regional coarsening. OnlineARC merges adjacent regions according to recent supply–demand balance before matching. This step adjusts the regional granularity used for movement cost evaluation and helps keep assignments close to local regions when regional merging is suitable. Experiments are conducted using a real-world task locations dataset from a 2022 COVID-19-related scenario in Changchun, with simulated worker availability and online arrivals. The results show that the proposed methods usually reduce the combined assignment objective value under the tested settings. The service quality and movement control metrics show that OnlineARC reduces the cross-region assignment ratio and average hop distance while maintaining a high task completion rate under the representative setting. OnlineKM improves running efficiency through time-sliced matching, while OnlineARC provides a trade-off between adaptive coarsening cost and locality-aware movement cost evaluation. These results suggest that adaptive regional coarsening can serve as a practical heuristic for locality-aware online task assignment in isolation sensitive spatial crowdsourcing under suitable worker–task distributions. Full article

The energy performance of a building reflects its typical energy use and is influenced by factors such as the building envelope (insulation and windows), system efficiency (particularly for heating, cooling, and domestic hot water), and the integration of renewable energy sources. Improving energy performance helps save energy, boost energy independence and security, lower energy costs, and reduce the need for grid investments. Standardizing energy performance assessments enables benchmarking and comparison of building efficiency, encouraging informed decision-making. In this context, the paper presents a knowledge discovery-driven intelligent decision-making system, designed, developed, and tested to identify the best strategies for prioritizing buildings in the envelope process. The system combines data mining techniques with statistical analysis to precisely rank and thoroughly evaluate low-energy-performance buildings and to develop scenario-based strategies for enveloping the buildings to achieve high energy efficiency (associated with nearly zero-energy buildings) under real-world conditions. Testing of the proposed intelligent decision-making system was conducted using a real building database of approximately 3900 records, uploaded from the Romanian central administration website. Under the highest-performance scenario of the envelope-priority strategy, which includes nearly zero-energy building standards, energy savings exceeded 50% across all categories: 51.70% for healthcare, 53.40% for residential, 60.11% for administrative and office buildings, and 69.92% for educational institutions. Overall, the average savings across all building types were 59.81% (644.86 GWh/year). Full article

Against the coordinated advancement of building a maritime power, high-quality development of marine tourism and ecological civilization construction, realizing positive interaction between marine resource conservation and tourism industrial development has emerged as a pivotal issue for high-quality growth in coastal regions. Taking 11 coastal provincial-level administrative regions in China spanning 2008 to 2024 as the research sample, this paper first establishes an evaluation indicator system covering marine resources and the tourism industry. It further adopts an integrated empirical framework encompassing the coupling coordination degree model, spatial Markov chain model, obstacle degree model, fixed-effect model and geographically and temporally weighted regression (GTWR) model to systematically unpack the spatiotemporal differentiation characteristics, internal restrictive obstacle factors and external driving determinants of the two-system coupling coordination. On this basis, a marine resource compensation mechanism for tourist destinations is formulated. Empirical results demonstrate four core findings: (1) In terms of temporal evolution, the overall coupling coordination level keeps rising and goes through three phases: initial development, rapid improvement and post-shock recovery. After a short-term decline triggered by the pandemic, the index rebounds markedly after 2023, showing that the two systems can recover and stabilize. (2) In terms of spatial layout, a persistent stratified spatial pattern featuring “higher coordination in southern coast versus lower coordination in northern coast with three-tier hierarchical differentiation” is identified; high-level neighboring regions exert prominent positive spatial spillover effects, whereas low-level adjacent areas are prone to fall into development lock-in traps. (3) For internal constraint obstacles, the marine resource subsystem is persistently restricted by resource exploitation limits and coastal spatial scarcity, while the dominant bottleneck of the tourism industrial subsystem shifts from insufficient market scale to inadequate human capital supply. (4) Regarding external driving forces, the proportion of tertiary industry and the digital infrastructure constitute core driving contributors, whereas marketization progress and opening-up degree act as primary restrictive factors, with pronounced spatial heterogeneity existing across all driving indicators. Finally, in line with the quasi-public-good attribute and ecological externality of marine resources, this study constructs a differentiated and synergistic marine resource compensation mechanism from three dimensions: stakeholder identification, compensation implementation pathways and institutional guarantee systems. The proposed framework provides theoretical references and practical policy options to facilitate high-level coupling and coordinated development between marine resource preservation and the coastal tourism industry. The marginal contribution of this research lies in integrating coupling coordination measurement, obstacle factor diagnosis, driving mechanism identification and compensation mechanism design into an integrated analytical framework, which delivers theoretical foundations and operable policy solutions for coastal marine resource protection, tourism industrial upgrading and differentiated compensation system construction. Full article

In the context of China’s stock-based urban renewal, public space regeneration in old urban areas increasingly requires attention to everyday use, inclusive access, local memory, and collaborative governance alongside physical upgrading. Drawing on catalyst theory, this study builds an analytical framework linking catalyst classification, potential element identification, effectiveness evaluation, actor collaboration, and renewal strategy transformation. The Guibeicheng area of Wuxi, China, is examined using semi-structured interviews, cognitive maps, qualitative coding, space syntax, the analytic hierarchy process, and actor collaboration analysis. The analysis indicates that behavioral and narrative catalysts are closely associated with residents’ everyday use and place identity. Event catalysts may generate phased amplification effects under specific conditions, while organizational and rule-based governance catalysts mainly provide support conditions for sustaining catalytic effects. Comparing space syntax results with cognitive-map and interview evidence further points to mismatches between configurational potential and perceived everyday activation. These include high-integration spaces with limited evidence of repeated everyday use, high-choice nodes mainly associated with pass-through use, weak everyday connections to historical resources, and limited independent organizational support for high-priority catalysts. On this basis, the study proposes a renewal pathway that combines everyday behavior guidance, event transformation, local narrative embedding, and organizational governance coordination. The findings provide a case-based reference for catalyst-oriented public space regeneration in historic urban areas and suggest potential implications for social sustainability, cultural continuity, and community resilience through spatial activation and long-term collaborative governance. Full article

As an automated alternative to the complexity and resource intensive task of building a machine learning (ML) pipeline, AutoML offers substantial value. Moreover, given the growing number of application areas requiring ML solutions, but having limited technical expertise, the need for AutoML is increasing. The authors describe a novel and modular AutoML pipeline built using object-oriented Python, designed for both regression and classification problems. Unlike other established libraries (TPOT, Auto-sklearn, Hyperopt-sklearn) this new framework provides structure to the output formats (JSON, YAML etc.) used for backend and API integration purposes. Rather than a GUI-based platform (low-code or otherwise) the authors propose a developer oriented/Code Driven AutoML pipeline. Additionally, it includes interpretability through VIF based Feature Engineering and increased extensibility. The experimental results provided by the authors are based upon public insurance data sets and demonstrate that their system performs at least on par with, and in several cases surpasses, the baseline systems tested, and does so in a manner that provides greater modularity and easier deployment. Therefore, this study demonstrates a lightweight, real world ready solution to provide an effective AutoML solution for use in a variety of application areas including NLP, computer vision, and Web-Based Machine Learning Applications. Full article

The construction sector contributes substantially to global greenhouse gas emissions, making material substitutions a key strategy for advancing sustainability transitions. Mass timber has emerged as a low-carbon alternative to mineral-based construction materials, offering biogenic carbon storage and compatibility with prefabricated and industrialized building systems. This study aims to systematically synthesize the economic, cost, and market evidence on mass timber construction by reviewing 143 peer-reviewed publications, with the objective of clarifying what is empirically known and where uncertainties remain. The reviewed literature reveals three core findings. First, economic outcomes are mixed: while several studies report regional value creation, supply-chain upgrading, and alignment with circular-economy principles, others highlight persistent constraints such as limited manufacturing capacity and uneven policy support. Second, construction cost findings vary substantially, ranging from cost parity or modest savings relative to conventional systems to premiums of approximately 10–15%, shaped by regional pricing, labor availability, transportation distance, regulatory conditions, and supply-chain maturity. Third, market-oriented studies consistently identify slow diffusion, limited practitioner experience, and risk-averse investment environments as key barriers to adoption. Overall, the review shows that economic performance is not yet consistently established and underscores the need for more standardized, context-sensitive, and methodologically consistent evaluation frameworks to support informed decision-making and the sustainable scaling of mass timber construction. Full article

Introduction: AQUArestore is a three-year project focused on promoting adaptive ecological restoration strategies for river ecosystems in the vulnerable cross-border region of Portugal. The project responds to pressing environmental challenges across the territory, including severe habitat degradation, climate vulnerability, declining water security, and biodiversity loss, with particular concern for freshwater fish communities, making river restoration essential to preserve native species and freshwater ecosystem services. Objective: The project aims to develop a replicable framework for restoration of Mediterranean transboundary riverine habitats, supporting the objectives of the EU Nature Restoration Law (NRL, Regulation 2024/1991). The consortium AQUArestore will develop (1) robust restoration indicators, (2) implement living labs for restoration experimentation, and (3) establish capacity-building and training programs for technicians and citizens. Methodology: The project kick-off meeting was used to operationalize project tasks, detail the implementation calendar and milestones, and clarify responsibilities of each project member and partner institutions within the different work tasks. The meeting gathered consortium members from the coordinating institution CEF-ISA (researchers at the Instituto Superior de Agronomia) and partners WWF Portugal (an environmental NGO) and Mushmore Cooperative, each one contributing according to their respective expertise and institutional objectives. Results: The AQUArestore project kick-off meeting took place in January 2026 at ISA, Lisbon, and included a presentation of the NRL and a detailed discussion of project task development. In detail, the activities will begin with the compilation of information on previously restored sites (Task 1). This will support the development and validation of environmental and biodiversity indicators of restoration outcomes, including those linked to freshwater fish assemblages and riparian vegetation (Task 2). The project will then establish two living labs as platforms to test nature-based solutions in collaboration with stakeholders and local communities (Task 3). In parallel, AQUArestore will strengthen technical capacity through training for practitioners and public authorities (Task 4). Finally, dissemination will be supported through citizen science, communication activities, and stakeholder engagement, fostering a broader impact (Task 5). Together, these tasks provide an integrated, science-based, and participatory framework aiming to support adaptive river restoration under climate and environmental changes. Conclusions: By integrating ecological restoration, biodiversity and environmental monitoring, and stakeholder engagement, AQUArestore is expected to contribute to the recovery of Mediterranean freshwater ecosystems and improve habitat quality and connectivity for native fish communities, enhancing resilience to climate change and other anthropogenic pressures. Full article

The concept of technological singularity is discussed here in the context of architecture (of buildings, not software). This is the point at which non-human intelligence is conjectured to surpass ordinary human cognitive limits. Empirically constrained AI may already offer a useful corrective to mainstream architectural culture in one crucial aspect—its capacity to evaluate design that adapts to human emotional health. Postwar building architecture as an institutional power system rewards abstraction and stylistic conformity through media prestige while not always accounting for embodied human experience. By narrowing judgment criteria, architectural studio pedagogy trains tacitly for imitation, not seeking evidence that conflicts with dominant formal ideologies. Yet findings from environmental psychology, health-related design research, neuroscience, and recent AI-based studies show that built form measurably affects empathic response and user well-being. This paper examines what effects dominant architectural culture could impose on the public by producing informationally impoverished, stressful environments. We argue that built environment design may suffer from an epistemic closure because (i) architectural education does not foster curiosity in how design affects users—the core mechanism for intelligence development—and (ii) architectural media may legitimate non-adaptive form languages by habituating populations to ignore distress signals from geometries associated with elevated stress markers. However, empirically constrained AI can now be directed to apply that relevant knowledge base to improve the built environment. The most suggestive evidence in the paper is that LLM emotional scores, LLM geometric scores, human eye-tracking, and large public surveys converge on the same designs. In this sense, the AI singularity can be framed as a domain-specific, testable hypothesis in architecture. This paper does not report new generated results derived from Empirically Constrained Scaffolding (ECS), which appear in prior applications, but reproduces the original prompts as an illustration of the method. Full article