Search Results (286)

The rapid decarbonisation of urban districts is accelerating the deployment of rooftop photovoltaic (PV) systems, household battery energy storage systems (BESSs) and electric vehicles (EVs). However, the high variability of urban micro-generation creates substantial forecasting errors at the urban–grid interface, imposing high balancing costs on distribution system operators (DSOs) and local energy communities. Traditional metrics fail to assess how effectively internal peer-to-peer (P2P) flexibility offsets these forecast mismatches prior to grid settlement. To address this gap, this paper presents a novel methodological framework and a non-parametric indicator: the Community Imbalance Neutralisation Index (CINI). Formulated in a generalised, scalable matrix structure applicable to any heterogeneous urban neighbourhood (N households), CINI quantifies the relative reduction in net community-level imbalance relative to the cumulative sum of uncoordinated individual forecast errors. CINI ranges from 0 per cent (no collective mitigation) to 100 per cent (perfect internal neutralisation). Complementing this index, an adaptive day-ahead scheduling algorithm is introduced to determine the optimal community energy purchase requirement (E_forecast). The proposed framework is numerically evaluated using a high-resolution synthetic benchmark annual dataset with 15 min intervals (35,040 intervals) representing a Central European urban residential cluster equipped with diverse combinations of PV, BESS and managed EV charging infrastructure. The simulation results demonstrate that active cVPP coordination reduces annual grid-facing imbalance energy from 188.73 MWh to 143.88 MWh, increasing the annual CINI score from 57.22% to 67.39% (+10.17 percentage points) compared with the uncoordinated baseline. Notably, the framework reveals a ‘Winter Flexibility Paradox’, achieving its highest relative efficacy during the winter months (+13.88 percentage points in December). Furthermore, sensitivity analyses show that scaling flexibility up to 40 kW achieves a CINI score of 91.22%, revealing diminishing marginal returns and critical technological saturation thresholds. The proposed CINI metric and E_forecast dispatch algorithm provide city planners, municipal energy managers and DSOs with a transparent diagnostic tool to design dynamic socio-economic tariff incentives, optimise urban micro-grid sizing, prevent free-rider dynamics, and foster resilient, self-balancing smart cities. Full article

Fungal biosynthetic gene clusters (BGCs) offer a genomic entry point for natural-product discovery, but predicted regions alone neither establish pathway activity nor identify metabolites. Armillaria is a useful model because chemically rich, forest-associated species span pathogenic and saprotrophic lifestyles. We analysed nine assemblies in a role-aware design: seven independent taxa with high completeness assessed using Benchmarking Universal Single-Copy Orthologs (BUSCO), an A. mellea BUSCO duplication-sensitivity sample and an A. solidipes intraspecific strain control for A. ostoyae. The analysis resolved a terpene-rich repertoire containing a shared but edge-robust gene cluster family (GCF) component alongside unevenly distributed candidate families. Targeted neighbourhood analysis recovered protoilludene synthase (PRO1) orthologs in all assemblies (92.2–100.0% amino-acid identity); the core neighbourhood was retained across the seven primary taxa, whereas flanking tailoring-associated genes varied. Notably, the A. gallica PRO1 ortholog lay 23,614 bp outside the nearest antiSMASH region. Thus, whole-region prediction can obscure pathway-centred conservation in basidiomycetes. The resulting framework prioritises reproducible candidates while reserving chemical identity, expression and ecological function for direct validation. Full article

Post-disaster reconstruction often prioritises the rapid delivery of housing and infrastructure, yet the long-term everyday performance of commercial environments embedded in recovery plans remains poorly understood. This study investigates why broadly similar post-disaster commercial blocks in Yenikent (Sakarya, Türkiye) have developed markedly different levels of spatial vitality and long-term everyday use. Yenikent is a state-led satellite city developed after the 1999 Marmara Earthquake, where residential, administrative and service functions were relocated to higher ground as part of a planned secondary urban centre. Twenty-five years later, these purpose-built commercial centres display markedly different levels and forms of everyday use, ranging from active neighbourhood service hubs to abandoned urban voids. Using a multiple-case, mixed-methods design, the study analyses all twelve post-disaster commercial clusters (eighteen buildings) through sectional and morphological analysis, a four-indicator Spatial Vitality Matrix (stationary activity, pedestrian flow, physical permeability, and active occupancy), and 88 semi-structured interviews with businesses, users, and neighbourhood headmen. The findings identify three dominant trajectories: (i) relatively robust service hubs sustained by institutional and neighbourhood anchors, (ii) fragile clusters where vitality is concentrated along accessible ground-level edges while upper or internal spaces shift towards storage, institutional, or ancillary uses, and (iii) functionally obsolete complexes associated with peripheral siting, poor topographic adaptation, and weak accessibility. The results further demonstrate that formal occupancy is not necessarily equivalent to spatial vitality: sectional relationships with the terrain, entrance legibility, façade permeability, and the integration of anchors into shared circulation are closely associated with whether commercial spaces sustain everyday activity. Interview evidence additionally reveals case-specific differences in perceived safety and gendered use of internal corridors and courtyards. The study supports a section-sensitive approach to post-disaster commercial development that prioritises topographic adaptation, legible access, active edges, and the integration of everyday anchors into shared spatial networks. Full article

Graph topology and model architecture are routinely co-designed in GNN-based fraud detection, making it impossible to attribute performance gains to either component. We address this by fixing the training loop, features, and evaluation protocol while independently varying the graph construction strategy and GNN architecture. Three strategies are evaluated: multi-relation temporal, hybrid structural similarity, and intra-group, each evaluated across three GNN architectures (GATv2, GCN, and GraphSAGE). A feature-identical MLP with no graph structure serves as an empirical anchor. On the Sparkov dataset, all three GNN strategies exceed the MLP by 5.0–9.7 F1 points, confirming that topology contributes genuine discriminative value when per-cardholder histories are dense. On the IBM dataset, the intra-group strategy collapses 6.9 F1 points below the MLP, a consequence of near-empty neighbourhoods (mean degree 1.1) following down-sampling, while multi-relation retains ranking advantages in AUC (Area Under the Curve; 0.985) and Average Precision (0.908) despite marginal F1 parity. Across both datasets, multi-relation temporal construction is the highest-performing strategy, achieving F1 0.908 and AUC 0.994 on Sparkov and F1 0.831 on IBM, though this ranking is not entirely architecture-independent: GraphSAGE narrowly inverts the multi-relation/intra-group order on Sparkov. These results suggest that graph construction quality, rather than mere graph presence, matters more for GNN performance than connectivity alone under the conditions evaluated here. Full article

Rapid, reliable, and energy-efficient data collection is essential for disaster response, where terrestrial communication networks may be disrupted or unavailable. Unmanned Aerial Vehicles (UAVs) provide a flexible means of collecting critical sensing data, but their operation is constrained by limited onboard energy, stochastic wireless conditions, complex three-dimensional environments, and stringent latency requirements. This paper presents a structured multi-UAV framework that separates mission optimisation into spatial, temporal, and safety layers. In the spatial layer, a three-dimensional Travelling Salesman Problem with Neighbourhoods (3D-TSPN) formulation enables UAVs to collect data by entering valid sensing regions rather than visiting exact sensor coordinates. An Age of Information (AoI)-aware Genetic Algorithm (GA) optimises the sensor-visitation sequence, while Rapidly Exploring Random Tree Connect (RRT-Connect) generates obstacle-aware feasible paths in the three-dimensional environment. In the temporal layer, a Lyapunov-based controller selects between local processing and binary offloading to a single Mobile Edge Computing (MEC) node according to queue backlog, processing delay, energy consumption, information freshness, wireless-link feasibility, and task deadlines. In the safety layer, continuous-time conflict detection and bounded temporal or spatial adjustments are used to monitor and mitigate inter-UAV and obstacle-related risks. The framework is evaluated under stochastic wireless, mobility, computation, and obstacle conditions using 20 independent random seeds. Across the corresponding 20 proposed-policy runs, it achieves a 100% mission-validity rate, complete sensor coverage, no dropped tasks, and zero final collision or near-miss events. Compared with planning-oriented and MEC-oriented baselines, the proposed framework achieves lower information age, average delay, processing delay, energy consumption, and system cost under the evaluated conditions, while maintaining reliable multi-UAV coordination. The layered design also clarifies the contribution of each component: 3D-TSPN provides spatial flexibility, the AoI-aware GA improves route sequencing, RRT-Connect supports obstacle-aware path feasibility, Lyapunov control enables queue-aware processing decisions, and safety monitoring supports coordinated multi-UAV operation. These results indicate that integrating spatial planning, computation control, and safety coordination within a clearly separated layered architecture can provide an effective solution for multi-UAV disaster-response data collection in complex three-dimensional environments. Full article

This paper presents the Post-Stimulus Time-Dependent Event Descriptor (P-TED), a novel “pure event” feature descriptor designed for neuromorphic vision data. Unlike conventional frame-based approaches or hybrid methods that transform event data into intermediate representations, P-TED operates directly on asynchronous event streams, thereby preserving the intrinsic low-latency and high-temporal-resolution advantages of event-based sensors. The descriptor integrates two complementary feature sets: a motion feature vector, which aggregates spatial relationships within a Moore neighbourhood to quantify stimulus direction, and a pattern feature vector, which employs rate encoding to capture temporal excitation signatures. The efficacy of the P-TED framework is validated through three distinct experiments: object and character recognition (MNIST-DVS and CIFAR10-DVS), mobile robot movement analysis, and complex non-rigid robotic hand gesture recognition (RoShamBo). Experimental results demonstrate that the P-TED achieves a significant reduction in classification latency, requiring only 2.7 ms compared to the 10.3 ms recorded by the state-of-the-art Distribution-Aware Retinal Transform (DART) framework. Additionally, P-TED exhibits superior robustness in disambiguating symmetric and mirrored motions, as well as in maintaining stability under non-linear fluctuations in event density caused by changing scale. This work establishes P-TED as a high-speed, computationally efficient, and explainable solution for real-time neuromorphic robotic vision systems. Full article

As China’s dominant urban housing form, gated residential communities deploy layered spatial access controls governing who may enter and move through neighbourhood space. While neighbourhood social sustainability has attracted substantial scholarly attention, how micro-spatial governance arrangements affect the inclusiveness of residential built environments toward essential service workers remains underexplored. Drawing on Lefebvre’s theory of the production of space, this study uses food delivery riders—who navigate gated community access controls dozens of times daily—as an analytical lens to evaluate how neighbourhood spatial governance shapes social inclusiveness. Vignette-based survey data from 445 riders across 157 cities in 27 Chinese provinces were analysed using structural equation modeling. Results show that cumulative anxiety from procedural delays, detours, and elevator waiting is the dominant pathway through which spatial governance undermines riders’ perceived spatial inclusion—operationalised through occupational dignity indicators—with elevator-based spatial stratification identified as a concrete, low-cost intervention target within the spatial-channeling mechanism. Technology-mediated access partially mitigates face-to-face exclusion but leaves underlying spatial inequalities intact. Demographic invariance across all tested variables confirms that diminished inclusion arises from the governance regime itself. The findings position neighbourhood spatial governance as a measurable dimension of urban social sustainability—one concretely testable through the experience of essential service workers—and identify low-cost built-environment interventions for inclusive residential design. While the study focuses on riders as a single user group, the analytical framework is transferable to evaluating how residential built environments accommodate diverse non-resident populations. Full article

Climate change is intensifying heat-related risks in Mediterranean urban environments, increasing the need for pedestrian-scale approaches that combine spatial diagnostics with lived thermal experience. The pilot study develops a three-layer diagnostic framework for assessing outdoor thermal comfort in the central neighbourhoods of Urla, İzmir, Türkiye. The framework integrates UMEP-SOLWEIG microclimatic modelling, citizen science field measurements and structured thermal perception diaries. First, Physiological Equivalent Temperature (PET) and mean radiant temperature (Tmrt) were modelled for 24 November 2023 and used as spatial diagnostic layers to identify three pilot areas with distinct urban morphologies. Second, an independent citizen science thermal walk campaign was conducted on 5 November 2025, during which 12 volunteers recorded in situ air temperature and relative humidity at predefined measurement points. Third, participants completed thermal diaries based on ASHRAE Standard 55 to document thermal sensation, comfort, preference, acceptability and adaptive responses. The modelling and fieldwork components were not designed as same-day validation datasets but as complementary layers for interpreting spatial thermal patterns and perceived thermal conditions. The results show that modelled PET values were relatively homogeneous across the three areas, while field-measured air temperature and subjective thermal responses varied more clearly at the pedestrian scale. These differences suggest that surface conditions, shading, spatial openness and user perception may jointly shape outdoor thermal experience, although the findings should be interpreted as descriptive tendencies due to the single autumn fieldwork session and small sample size. The study contributes a cautious, repeatable pilot framework for linking spatial screening, citizen-generated microclimatic data and structured perception evidence in climate-responsive urban design and local climate governance. Full article

Park audits can inform neighbourhood-scale urban design strategies that support health. However, interpreting park audit data is time-consuming and requires specialised expertise. Recent advances in large language models suggest potential for assisting with structured data interpretation, but their application to park audits remains unexplored. This study examined whether a large language model (ChatGPT-5) can assist in interpreting park audit data from public parks in Dhaka City, Bangladesh. Using a modified park audit tool, 59 parks were audited, of which 26 met the predefined completeness threshold and were included in the analysis. ChatGPT-5 and human experts received identical park audit datasets and instructions for interpretation. Outputs were evaluated using content analysis and a pre-defined scoring framework to assess accuracy and comprehensiveness. Paired t-tests compared ChatGPT-5 outputs with the expert benchmark. ChatGPT-5 showed no statistically significant difference from the expert benchmark in overall accuracy in this sample (p = 0.13). The unadjusted analysis showed a higher recommendation-match count for ChatGPT-5 (p < 0.05), but this result should be interpreted as exploratory because multiple criteria were tested. No statistically significant differences were detected across accuracy domains or other comprehensiveness criteria. These findings suggest that ChatGPT-5 may assist with preliminary interpretation of structured park audit data. However, the results do not establish equivalence with expert assessment. Expert review remains necessary to assess feasibility, contextual relevance, and alignment with local planning standards. Full article

Cities face increasingly complex sustainability challenges that demand cross-sector collaboration, yet existing participatory tools rarely integrate internationally recognised sustainability frameworks with systems-based visualisation in a way that supports coordinated action across diverse stakeholders. This paper presents the Placemaking Maptivity, a card-based serious game that operationalises the ISO 37101 cross-analysis matrix—six sustainability purposes against twelve areas of action—as a shared analytical scaffold for participatory neighbourhood planning. Following a Design Science Research approach, this formative artefact-development study iteratively refined the tool through four rounds of beta testing in online, in-person, and mixed-stakeholder international configurations, drawing use cases from the EU-funded REEFLEX, PROBONO, and eFORT projects. Each game mechanic is traced to a defined learning objective using the Learning Mechanics–Game Mechanics (LM-GM) framework. Stakeholder feedback across iterations provides preliminary observations that the Maptivity supports identification of multi-purpose contributions, mapping of interdependencies, and collaborative prioritisation of next steps while highlighting facilitation, timing, and contextual adaptation as critical success factors. Whether the tool improves planning quality, learning outcomes, or decision-making effectiveness compared to alternative approaches remains a question for future, more rigorously designed evaluation studies. We discuss the formative character of these results, set out limitations, and propose a more rigorous summative evaluation protocol to support broader scaling and adoption of the methodology. Full article

Vernacular settlements retain tangible fabric and intangible knowledge that can support climate-responsive conservation, adaptive reuse, and urban regeneration, yet these dimensions are often assessed separately. This study applies a values-based conservation framework to examine how heritage significance is expressed through settlement morphology, material systems, environmental performance, community knowledge, and continuing use in two historic settlements and one contemporary neighbourhood in Oman. Heritage significance is interpreted through six interconnected domains: historical-continuity, architectural-spatial, environmental, material-technical, social-cultural, and functional-economic value. A comparative mixed-method case-study design combined field observation, photographic documentation, urban and architectural morphological analysis, semi-structured interviews, and building-performance simulation. The findings show that the historic settlements achieved greater built intensity through attached buildings, shared walls, limited setbacks, shaded routes, mixed functions, and layered public–private organization. Interview evidence associated these characteristics with privacy, shared-resource management, traditional construction knowledge, social continuity, adaptive reuse, and continued occupation. Simulation results indicated substantially lower cooling-energy demand in the representative vernacular dwellings, whereas the contemporary villas achieved higher daylight levels and thermal conditions closer to neutrality under mechanical cooling. The study concludes that vernacular heritage should neither be conserved as static physical fabric nor reproduced literally. Interventions related to tourism, infrastructure, accessibility, privacy, commercial reuse, and residential continuity should be negotiated among stakeholders. Full article

Dense tropical cities face increasing outdoor heat stress and require reliable microclimate modelling tools to support climate-responsive urban planning. However, the performance of these models remains insufficiently documented under tropical conditions. The objective of this study is to experimentally validate the performance of ENVI-met for outdoor thermal comfort assessment in a dense tropical neighbourhood on Reunion Island. Validation was performed using a network of 11 low-cost weather stations distributed across the study area, providing observations of air temperature, relative humidity, wind speed and globe temperature, from which mean radiant temperature (MRT) and the Universal Thermal Climate Index (UTCI) were derived. Model performance was evaluated through multipoint validation, error-propagation analysis and sensitivity experiments. Results show that ENVI-met reproduces air temperature and relative humidity with good accuracy (RMSE of 1.2 °C and 5%), while larger uncertainties are observed for wind speed (up to 4 m s⁻¹) and MRT (up to 8 °C), with strong spatial variability. Error-propagation analysis indicates that 62% of the UTCI error variance is explained by combined microclimate simulation errors, with radiative conditions emerging as the dominant contributor. Sensitivity analyses identify boundary wind forcing as the main source of modelling uncertainty. Overall, the proposed validation framework provides practical guidance for improving ENVI-met applications in tropical urban environments and supports more robust climate-responsive urban design. Full article

Complete neighbourhoods, places where residents can meet their daily needs on foot, have become a central component of healthy and sustainable urban planning. Yet most assessment frameworks are calibrated for dense metropolitan environments, leaving rural and peri-urban municipalities without operational tools suited to their territorial needs. This article presents MilieuxVie, an open-source, browser-based interactive mapping application developed for the Laurentides health region of Québec (76 municipalities, 11 land-based unorganised territories, 2 indigenous territories and 4 aquatic administrative units; 93 territorial units in total; ~680,000 inhabitants). The tool evaluates the spatial accessibility of 12 service categories drawn from the Vivre en Ville (2026) complete-neighbourhood framework and OpenStreetMap data, using 2026 residential parcels from the provincial property assessment roll as origin points and weighting results by number of dwelling units. Three adaptive radius tiers (dense, intermediate, rural), based on residential dwelling-unit density (dwellings per km² of residentially designated urban land), scale the distance standards to settlement density. Because thresholds are scaled to settlement density, scores express context-relative service proximity rather than a uniform pedestrian standard and should not be read as directly comparable absolute accessibility across rural, peri-urban, and urban settings. A dedicated urban perimeter mode further disaggregates analysis to sub-municipal built-up zones, aligning the tool with Québec’s provincial Government land-use planning guidelines (GLPG). Gap analysis outputs identify which service types fall below the 70% coverage target, helping elected officials and planners identify where to focus further analysis. Results illustrate the scope of accessibility deficits across the region and highlight the analytical limits of uniform distance thresholds when applied beyond metropolitan contexts. Scores differ significantly across different settings (Kruskal–Wallis p = 0.006); the adaptive radius tiers narrow but do not close the structural gap, with rural municipalities scoring significantly lower than dense ones. The tool is freely available and requires no software installation, making it directly deployable by local planning offices. Full article

Piezoelectric actuators are widely used in precision manufacturing, high-end equipment and aerospace fields due to their high precision, fast response and flexible structure. However, continuous smooth displacement output over a large travel range with high-torque requirement is still a problem that needs to be solved, which greatly limits their application scope. Therefore, this work proposes a smooth-motion walking-type piezoelectric actuator over a large travel range with high torque inspirited by the bipedal walking mechanism. The driving legs with high stiffness and large displacement of the actuator are divided into two groups; by imitating the bipedal walking gait of humans, the driving trajectories of the two sets of driving legs are alternately integrated to adjust the balance between the driving torque and the resistance torque, ensuring that the resultant force torque acting on the rotor is zero, thereby achieving smooth motion in a large travel range with high torque. The multi-objective optimization algorithm of the neighbourhood cultivation genetic algorithm (NCGA) is adopted to optimize the structure design of the driving legs by considering the stiffness and displacement, in order to achieve the balance of high stiffness and large displacement at the foot end of the driving leg. The linear fitting coefficients of the output displacements of the actuator all reach above 0.999, the resolution is 0.4 µrad, and the maximum output torque is better than 1.31 N·m. These performances will greatly expand the application fields of piezoelectric actuators, especially in deep space optical tracking scenarios. Full article

The complete community paradigm, emphasising walkable, self-sufficient neighbourhoods, has gained significant global traction, yet the role of sports and physical activity spaces within such frameworks remains undertheorised, particularly in dense Chinese urban environments. This paper introduces the Chrono-Adaptive Sports Space Index (CASI), a preliminary evaluative framework whose diagnostic utility is demonstrated through three contrasting case studies. CASI integrates temporal usage dynamics, demographic composition, smart-city sensor data, and multi-generational programming flexibility to assess sports environments within China’s 15-Minute Complete Community (完整社区, Wánzhěng Shèqū) policy framework. Unlike existing frameworks that assess sports spaces through static metrics, CASI proposes that sports environments must be evaluated across four temporal dimensions: diurnal rhythms, weekly cycles, seasonal transitions, and demographic lifecycle shifts. The four sub-indices are weighted equally (25 points each) as a deliberate first-generation design choice reflecting the absence of pre-existing empirical benchmarks; this assumption requires empirical validation in future research. Through exploratory multi-case analysis of communities in Shanghai (Jing’an District), Chengdu (Tianfu New Area), and Beijing (Chaoyang District), this study provides preliminary evidence suggesting that temporally inert sports spaces may be associated with utilisation losses of 38–52% during off-peak periods and the systematic exclusion of elderly and child populations; these figures should be treated as indicative estimates pending broader empirical validation. A Chrono-Adaptive Design Protocol (CADP) is proposed as a conceptual, practice-informed protocol awaiting prospective empirical evaluation. This research is better characterised as a framework development and initial exploratory application study rather than a validation of a mature instrument. Its primary contribution is a new theoretical and diagnostic lens for complete community planning, together with an agenda for the empirical work needed to develop CASI into a broadly applicable assessment tool. The study’s limitations and a structured five-priority future research agenda are presented in a dedicated section following the Conclusions. Full article