Search Results (7,057)

Artificial Intelligence (AI) is increasingly embedded in public governance, raising new challenges for anticipating its societal implications while safeguarding democratic accountability within expanding computational infrastructures. This article examines how anticipatory AI governance can be operationalised in the age of supercomputing through a mixed-methods, multistakeholder study conducted in the Basque Country (Spain). The empirical focus is Gipuzkoa, a devolved historical territory with fiscal autonomy and a rapidly developing advanced-computing ecosystem centred in Donostia–San Sebastián, where regional initiatives are positioning the territory within Europe’s emerging high-performance and quantum computing landscape. The study combines participatory action research involving six civil society organisations, seven provincial directorates, and eleven municipalities with an online citizen survey (N = 911). The findings indicate that anticipatory AI governance is supported through four interrelated governance mechanisms: institutional coordination across administrative levels, multistakeholder participation, territorial public capability, and the strategic embedding of advanced computational infrastructures. Rather than evaluating the governance of supercomputing technologies themselves, the analysis examines governance perceptions, institutional practices, and democratic arrangements associated with these infrastructures. The article’s contribution lies in integrating anticipatory AI governance, territorial governance, and advanced computational infrastructures within a devolved city-regional setting, offering evidence-informed insights for regions seeking to strengthen democratic capacity alongside technological innovation. Full article

Urban Heat Islands (UHIs) intensify extreme heat, raise energy demand, and risk citizen thermal comfort in densely built cities. However, spatially detailed, scenario-differentiated estimates of future UHI intensity are still limited for complex coastal mountainous cities. This study set out to forecast UHI intensity variations in Busan, South Korea, under SSP2-4.5 and SSP5-8.5 scenarios. Daily temperatures from 19 automatic weather stations (2010–2014) were spatially interpolated using Empirical Bayesian Kriging Regression (EBKR), which included elevation and coastline distance variables. Among the 16 CMIP6 Global Climate Models (GCMs) tested, CNRM-CM6-1 (r = 0.902, RMSE = 4.937 °C) was chosen and bias-corrected using Empirical Quantile Mapping (EQM). The results reveal that mean maximum UHI intensity rises gradually, with ΔUHI (compared with the 2010–2014 baseline of 0.90 °C) reaching +7.03 °C (SSP2-4.5) and +9.60 °C (SSP5-8.5) in the far future, roughly 1.43 times more under the high-emission scenario. Summer through autumn has a UHI intensity increase, whereas long-term warming concentrates in Busan’s urban core. These findings inform targeted urban heat adaptation strategies, prioritizing green infrastructure, cool urban surfaces, and energy-resilient city planning to protect human well-being. Full article

Public sector organizations are under increasing pressure to modernize service delivery while preserving transparency, interoperability, accountability, and citizen trust. Blockchain technology offers relevant capabilities for these objectives, particularly through shared ledgers, cryptographic verification, and programmable rules. However, its adoption in public sector contexts remains constrained by the lack of architectural guidance tailored to inter-organizational services. This study proposes BRA-PS, a Blockchain Reference Architecture for Public Sector Citizen-Centric Applications, developed from a real-world digitalization project in Quebec, Canada. The architecture organizes components into six layers (presentation, business, communication, smart contract, blockchain, and data) with cross-cutting concerns addressing governance, access control, security, and monitoring. A key design principle is the public–private workflow separation, which enables inter-organizational collaboration while preserving each organization’s operational autonomy and data confidentiality. We validated the architecture through a case study involving a vehicle registration process between two public agencies, supported by a proof-of-concept implementation using Hyperledger Fabric. An Architecture Trade-off Analysis Method (ATAM) evaluation, conducted with a panel of five domain experts, identified six architectural risks, including InterPlanetary File System (IPFS) confidentiality exposure and smart contract inflexibility, six non-risks, six sensitivity points, and six trade-offs across three key quality attributes: autonomy, collaboration, and functional suitability. The results show that BRA-PS can support implementation decisions, clarify stakeholder responsibilities, and expose relevant architectural trade-offs. The recommendations derived from the evaluation provide practical guidance for the adoption of blockchain in citizen-centric public sector services. Full article

Detailed knowledge of biodiversity is fundamental to supporting conservation and management strategies in protected natural areas, especially in mountain systems located in biogeographic transition zones (Chihuahuan Desert and Sierra Madre Oriental regions). The Sierra de Zapalinamé State Natural Reserve is a priority system in northeastern Mexico; however, comprehensive long-term inventories of its terrestrial vertebrate fauna have been limited. The objective of this study was to comprehensively characterize the richness and composition of the terrestrial vertebrate fauna of the Sierra de Zapalinamé State Natural Reserve using a long-term, multi-source dataset integrating systematic field surveys, biological collections, and citizen science records, and to assess the extent to which the reserve represents the vertebrate diversity of northeastern Mexico. A total of 415 terrestrial vertebrate species were recorded, comprising 299 birds, 67 mammals, 42 reptiles, and 7 amphibians. Despite its proximity to urban areas and industrial activities, the reserve maintains high levels of biodiversity, harboring a substantial proportion of the terrestrial vertebrate fauna of northeastern Mexico. The results emphasize the importance of the Sierra de Zapalinamé State Natural Reserve as a regional biodiversity hotspot and support the strengthening of long-term monitoring and management strategies to improve wildlife conservation in underrepresented ecoregions facing increasing environmental pressures. Full article

Global Navigation Satellites Systems (GNSSs) have become a predominant feature in the digital life of citizens, and they provide positioning services in various applications including pedestrian and vehicular navigation. In urban environments with the presence of buildings and another obstacles, GNSS positioning may be unreliable because of non-line-of-sight (NLOS) conditions, and the classification of observed satellite visibility between LOS and NLOS may improve GNSS receivers to improve their performance to provide the positioning services. In this context, machine learning algorithms using features like signal noise ratio, pseudorange, elevation angle, and others have been applied to this problem both in supervised and unsupervised mode. Because the ground truth information on LOS/NLOS conditions may not always be available, unclustering algorithms have been applied for unsupervised classification, but the classification performance is still limited. This paper proposes an ensemble approach where different clustering algorithms, both historical and recently introduced in the literature, are combined to improve the LOS/NLOS classification accuracy. Even if the ensemble approach manages to achieve a significant improvement, a novel and more sophisticated approach is proposed in this paper, where the contributions of each clustering algorithm are weighted. The optimal values of the weights are estimated using various Meta-Heuristics Algorithms (MHA) on a subset of GNSS data where the ground-truth information is available (i.e., labeled data set). In a subsequent step, the performance of the optimal weighted clustering ensemble is evaluated. The approach is applied to a recent public data set with 57 satellites, where it is shown to outperform the specific clustering approaches by a large margin (more than 7%). The Meta Heuristics Algorithm (MHA)s have similar performance, with the Dynamic Opposition Grey Wolf Optimization (DOLGWO) having a minor advantage against the other MHAs. Full article

Background: Contemporary older adults, especially the baby boomer generation, expect to actively shape their communities rather than passively receive services. Supporting ageing in place is a key issue for social sustainability, as communities need to remain inclusive, accessible, and liveable for ageing populations. While participatory approaches are increasingly promoted, implementation remains top–down and expert-driven. Older adults often express their experiences of the built environment through everyday language rich in emotion, memory, and sensory details, yet these forms of knowledge are typically dismissed as informal or subjective. As a result, their lived spatial experiences remain institutionally invisible in age-friendly planning and design. Methods: This exploratory case study analysed textual comments submitted by older adults in a coastal suburb in Queensland through a participatory Citizen Science initiative. An integrative framework combining GIS mapping, content analysis (CA), sentiment analysis (SA), and critical discourse analysis (CDA) was used to examine how older adults describe, evaluate, and negotiate their built environments. Results: GIS mapping showed that older adults chose to document familiar, accessible public spaces, such as parks, civic precincts, and transport corridors, reflecting routine-based patterns of use. Content analysis revealed a focus on modest but essential built environment features, including shaded seating, footpaths, signage, and pedestrian crossings, which supported comfort, safety, and social engagement. Sentiment analysis found that 67% of comments were positive and 18% neutral, indicating broad satisfaction but also strategic emotional framing. CDA identified three exploratory interpretive patterns, Affective Evaluation, Narrative Anchoring, and Modal Negotiation, through which older adults expressed emotion, belonging, and concern within this limited corpus. Conclusions: Ageing in place depends not only on physical infrastructure but also on discursive inclusion, that is, whether older adults’ everyday ways of speaking are heard and recognised in participatory planning. This study shows that older adults actively shape spatial meaning through emotion, memory, and caution, and that their language carries both experiential insight and civic intention. Recognising these discursive signals may help inform more responsive, age-inclusive, and socially sustainable participatory planning. Full article

Marine sport fishing is an increasingly important socioeconomic activity in Mediterranean coastal regions, although its ecological implications and interactions with vulnerable taxa remain poorly understood. This study analyses shore-based marine sport fishing competitions conducted along the southeastern Spanish Mediterranean coast between 2019 and 2025 to characterise sport fishers, evaluate interactions with vulnerable species such as elasmobranchs, and assess the spatial and temporal evolution of catches. The methodology combined structured surveys, fieldwork, and catch data collection during organised fishing competitions held in Alicante and the Region of Murcia. A total of 425 surveys were analysed together with catch records obtained from the Puerto de Mazarrón Fishing Open Championship and local fishing competitions. Results showed that sport fishing activity is predominantly carried out by experienced male fishers maintaining high fishing frequency throughout the year. Many participants reported previous interactions with elasmobranchs, particularly batoids, although limited knowledge among the sport fishers regarding species identification and protected taxa was detected. Catch composition was dominated by a few coastal teleost species, while multivariate analyses revealed significant spatial and temporal variability among fishing sectors and years. Overall, organised sport fishing competitions demonstrate considerable potential as complementary tools for ecological monitoring and conservation in Mediterranean coastal ecosystems. Full article

Rapid coastal urbanization poses severe threats to biodiversity through habitat fragmentation, making continuous monitoring of urban ecosystems essential. While birds serve as sensitive bio-indicators, the long-term spatiotemporal dynamics of their habitats and temporal shifts in environmental drivers remain poorly understood in high-density megacities. This study addresses this gap by developing a trend-explainable machine learning framework to evaluate avian habitat suitability across the western coast of Shenzhen from 2010 to 2020. We applied a standardized filtering protocol to citizen science data and integrated occupancy modeling with a Random Forest algorithm to simulate habitat distributions at 30 m resolution. Spatiotemporal habitat alterations were quantified using Mann–Kendall trend analysis, while SHAP was utilized to diagnose the changing importance and non-linear thresholds of ecological drivers over the decade. Our findings reveal pronounced spatial heterogeneity among six avian guilds. Habitat quality for terrestrial birds, raptors, and songbirds degraded severely in northern industrial regions, whereas targeted ecological restoration facilitated recovery in southern and western urban cores. The analysis further demonstrates dynamic temporal shifts in environmental responses. The restrictive impact of anthropogenic stressors including population density and nighttime light weakened for terrestrial and canopy-dwelling guilds but intensified for waterfowl. Concurrently, natural elements such as vegetation coverage and proximity to water bodies became increasingly important. Based on these spatiotemporal patterns, we delineated five ecological zones to guide targeted conservation interventions. This research provides an analytical framework linking predictive modeling with mechanistic insights, supporting evidence-based biodiversity conservation and sustainable urban planning in rapidly developing coastal landscapes. Full article

Digital Pakistan is a pivotal move towards bridging the gap between old bureaucratic methods and new ones, offering a technologically advanced, modernized form of administration for the masses. This paper will critically analyze the initiative’s effects on the delivery of social services to the population through a methodical SWOT analysis, highlighting existing shortcomings, such as insufficient infrastructure and the digital divide, that limit access for all. Based on a qualitative study using secondary data (2018–2024), it was found that although the adoption of more than 40 e-governance solutions and the Digital Pakistan Hub has led to an increase in transparency and responsiveness of the administration, there still remain great threats, such as security breaches in the cyber-sphere and a 67 percent gender gap in access to the Internet. The findings emphasize that although digital tools have helped ease bureaucracy, they are not very effective because of unequal digital literacy. This means that the paper advocates inclusive policymaking that focuses on boosting digital equity and infrastructural resilience to achieve sustainable public-sector reforms. The findings offer a practical roadmap for policymakers to bridge the technological vision with citizen-centric service delivery. Full article

The Misery Index (MI), also known as the Economic Discomfort Index, is a macroeconomic gauge originally proposed by Arthur M. Okun. It is defined as the unweighted sum of inflation and unemployment rates. This indicator attempts to synthesize the main factors generating economic malaise and collective discomfort, although it has been criticized for being an oversimplification of the economic problems faced by average citizens. Consequently, researchers have modified this index by incorporating variables associated with informality, interest rates, and economic growth, among others. Despite its simplicity, the MI has been utilized to describe the behavior of numerous social phenomena, such as suicide, the inclination to gamble, and tourism. However, the index has also been criticized for the inherent difficulty of associating its behavior with specific policy actions. This paper presents the main criticisms that this index has received, as well as its main applications and the various modifications it has undergone over time. Full article

Biodiversity and landscape heterogeneity are key components of agroecosystem functioning because they support ecosystem services and strengthen the capacity of agricultural systems to undertake sustainable agroecological transitions. This study assesses the landscape structure of the municipality of Ruvo di Puglia, within the Bio-Distretto delle Lame, to evaluate its potential to support such a transition. Bio-districts are territories in which farmers, local authorities, citizens, and other stakeholders collaborate to manage natural and agricultural resources sustainably, often with a strong connection to organic farming. The research combines freely available Sentinel-2 imagery with UAV-based ground truthing to update land-use/land-cover information and to derive landscape indicators. A systematic sampling scheme was designed in QGIS, and UAV flights over 14 areas were used to generate training and validation vectors. Two classification strategies were tested on 2024 Sentinel-2 data: a supervised pixel-based approach and an unsupervised multi-temporal object-based approach (GEOBIA). The best-performing map was obtained from the supervised classification of July NDVI data, with an overall accuracy of 91.76%. In respect to the 2018 official land-cover dataset indicates a decrease in agricultural land (−490.91 ha), a reduction in arable crops (−1216.43 ha), and an increase in permanent crops (+725.52 ha), suggesting a shift toward specialization. At the same time, natural and semi-natural areas increased, improving the landscape potential for ecological functions. However, the high fragmentation detected by the landscape metrics (average patch size approximately 0.25 ha) may limit habitat continuity and species stability. The results should therefore be interpreted as an assessment of landscape structure and potential biodiversity support, rather than as a direct measurement of biological diversity. Strengthening ecotones, hedgerows and semi-natural linear elements with native species would further improve landscape resilience and support agroecological planning. Full article

This study acknowledges the role of high-involvement work practices (HIWPs) in promoting proactive behavior among public organization employees, addressing the need to obtain further insights into the mechanisms and identify contingencies (i.e., both conditional and individual factors) that might impede the effectiveness of such practices. This builds on emerging empirical studies in the public management literature by drawing on social exchange theory and social cognitive theory to empirically test the impact of HIWPs on employees’ proactive behavior, using data collected through a two-wave, time-lagged survey design with a one-month interval from Turkish public organizations. The mediating role of public relations values was also examined, along with the moderating roles of role breadth self-efficacy and employees’ use of normative public values. Relying on 554 data obtained from Turkish public organization employees, this study finds that HIWPs positively impact employees’ proactive behavior and public relations values. Public relations values positively impact employees’ proactive behavior and partially mediate the link between HIWPs and employees’ proactive behavior. Role breadth self-efficacy moderates the positive relationship between HIWPs and public relations values, with the relationship being stronger for employees with high role breadth self-efficacy than for those with low. Employees’ use of normative public values moderates the positive link between public relations values and employees’ proactive behavior, with the relationship being stronger for employees with high use of normative public values than for those with low. The main theoretical and practical implications of the study’s outcomes are outlined and discussed, along with important future research directions. The findings highlight the importance of human-centric organizational practices in fostering public value in VUCA-D environments. By enabling proactive behavior, public organizations can enhance adaptability, support value co-creation with citizens, and strengthen trust in public service systems. Full article

Sustainable urban transportation is fundamentally linked to public health outcomes, specifically the mitigation of fatal traffic risks under environmental stress. While stressors like adverse weather affect entire cities, traditional road safety models often assume uniform risk, thereby masking the spatial inequalities inherent in the urban fabric. This study addresses this gap by investigating the geographically heterogeneous impact of environmental stressors—including rainfall, surface moisture, and lighting conditions—on the conditional probability of fatal crash outcomes in Melbourne, Australia. Analyzing 43,075 severe crashes through a multi-stage geospatial framework (Getis-Ord Gi* and Geographically Weighted Logistic Regression), this research diagnoses how varying urban development patterns mediate the lethality of these stressors. The findings unmask a critical “threshold-crossing” pattern for wet surfaces, where risk transitions from protective to hazardous based on local infrastructure form and street geometry. Significant spatial inequalities are identified: high-density inner-urban cores and adjacent coastal corridors exhibit a heightened sensitivity to visibility failures and moisture, whereas newer industrial peripheries show stronger protective “risk compensation” effects. These results reveal a systemic mismatch between historical urban form and contemporary climate-driven public health risks. By identifying localized “lethality thresholds”, this study provides a robust evidence base for integrated planning and equitable resource allocation. It enables urban planners to move beyond generalized safety warnings toward targeted structural interventions, ensuring that sustainable transportation networks prioritize safety equity for all citizens regardless of their location within the urban environment. Full article

With recent breakthroughs in affective computing and AI algorithms, government chatbots are evolving from function-oriented tools to emotionally responsive agents capable of detecting, decoding, and responding to citizens’ emotional cues. This shift holds significant potential for enhancing citizens’ continued usage intention. Drawing on social presence theory and employing a scenario-based experimental design, this study investigates whether, how, and under what conditions empathy by government chatbots affects citizens’ willingness to continue using such services. The findings reveal that empathy positively influence continued usage intention by enhancing users’ psychological engagement and perceived information richness. However, the strength of this effect is significantly moderated by the type of time pressure. Specifically, under endogenous time pressure, the positive effect of government chatbot empathy is amplified, whereas under exogenous time pressure, the effect is attenuated. This study uncovers the double-edged nature of empathic design in government chatbots, contributing to the literature on human–robot interaction in public service contexts. It also offers practical implications for the adaptive design of empathic government chatbots to optimize citizen engagement and service effectiveness. Full article

Citizen-reporting platforms generate high-volume, multilingual streams of service requests, yet operational triage often relies on coarse category labels and manual inspection. This study develops an explainable analytics pipeline with probability calibration for FixMyStreet Brussels reports, combining text-based urgency modeling, topic discovery, and spatio-temporal hotspot scoring to inform municipal analytic review. From 522,132 raw reports, we build an English-normalized text field for modeling, derive resolution-time outcomes from closed cases, and curate a 1000-item gold standard with an explicit high-urgency class. A TF-IDF logistic regression baseline achieves reasonable classification performance on the labeled split and, after probability calibration, yields confidence estimates that are more suitable for risk-aware prioritization than uncalibrated scores. Topic-level analyses reveal dominant themes related to sidewalks, road damage, and bulky waste, and hotspot scores highlight persistent, high-impact issue clusters. Event detection on aggregated signals did not identify events above the predefined z-score threshold during the analysis window, suggesting that the observed dynamics are more visible as chronic, recurring problems than as abrupt threshold-level anomalies. Explainability audits via Shapley Additive Explanations (SHAP) expose linguistically intuitive drivers for urgent cases (e.g., dangerous, risk, and accident) and complaint-oriented terms (e.g., abandoned, illegal, and dirty), providing transparent hooks for governance review. The analysis is therefore presented as an open-data, English-normalized decision-support prototype rather than as a validated native multilingual triage system. The labeled evidence base contains 2200 distinct human-reviewed reports. It comprises the 1000-report gold standard, a 200-report model-ranked high-urgency candidate set, and a 1000-report expanded validation subset. The expanded validation subset contains 439 high-urgency cases, including 42 cases from a random 500-report corpus sample. To avoid overstating language evidence, this study makes no native multilingual claim. The empirical claim is limited to English-normalized text analytics over reports that were originally submitted in a multilingual civic-reporting setting. Full article