Search Results (5,200)

Energy security and efficiency governance are among the most critical policy challenges facing emerging economies in the post-Paris Agreement era. While international frameworks such as the IFCMA Climate Policy Database provide unprecedented comparative data on national mitigation instruments, the role of artificial intelligence (AI) in optimizing policy design across the efficiency–security nexus remains underexplored. This study develops an AI-driven analytical framework—integrating K-Means clustering, Principal Component Analysis (PCA), and Random Forest classification—and applies it to the April 2026 edition of the IFCMA Climate Policy Database, encompassing 4627 active policy instruments across 42 countries. We systematically compare the policy instrument portfolios of nine emerging economies with those of thirty-two developed counterparts, with a particular focus on energy efficiency standards, fiscal instruments, and strategic security objectives. The results reveal that emerging economies exhibit structural under-utilization of performance standards and trading schemes, disproportionately high energy security objective ratios relative to their efficiency instrument sophistication, and an over-reliance on tax instruments compared to their counterparts in developed economies. The Random Forest classifier achieves 83.1% cross-validated accuracy in predicting emerging economy status from policy features, with performance standards and efficiency objectives as the strongest discriminators. Three distinct policy regime archetypes are identified: Standard-Dominant Mixed (Cluster A), Tax-and-Label-Dominant (Cluster B), and Trading-Intensive Transition (Cluster C). These findings provide AI-supported, evidence-based policy intelligence for governments seeking to move beyond minimum regulatory compliance and align energy efficiency governance with strategic energy security objectives. Full article

Background: The nationally advertised mass media campaign Act-FAST UK, delivered in multiple waves since its launch in 2009, has increased public awareness of stroke symptoms. However, many stroke patients still delay in calling for help and reach the hospital too late to receive emergency treatments. The reasons for this cognitive dissonance between recognition of symptoms and urgent seeking of emergency medical services (EMS) are unclear. Aims: This study aimed to quantify cognitive, psychological, and knowledge-based barriers to help-seeking in patients with acute stroke or transient ischaemic attack (TIA), as well as in intervening witnesses, and to examine their association with the use of EMS as the initial point of contact. Methods: We interviewed patients admitted to a hyperacute stroke unit with a stroke or transient ischaemic attack (TIA) from 2013 to 2016. People who contacted emergency services on the patient’s behalf (intervening witnesses (IWs)) were also interviewed when available. Reasons given for delays in calling for help were related to correct symptom recognition, and whether/at what time, emergency services were contacted after symptoms onset. Results: A total of 602 patients (429 with stroke, 173 with TIA) along with 128 witnesses who intervened in calling for help in those cases (IWs) were interviewed. In the subset of patients with both measures available, there was a strong positive correlation between NIHSS score and number of FAST symptoms (Spearman’s rho = 0.645, p < 0.001), providing supportive evidence for the use of FAST symptom count as a proxy measure of stroke severity. A total of 469 (77.9%) of the patients were aware of a media education campaign about stroke, but only 145 (24.1%) had attributed their own symptoms to stroke at onset. However, correct self-diagnosis of stroke was not associated with direct calls to the EMS (OR 1.43, 95% CI 0.84–2.45). Cognitive, psychological or emotional barriers to help-seeking, as reported by prior published studies, were reported by 463 (81.2%) of the patients we interviewed but in only 63 (53.3%) of the IWs (p < 0.001). Amongst the patient cohort, “not thinking symptoms were serious” (275, 45.7%) and “waiting to see if symptoms would go away” (285, 47.3%) were most strongly negatively associated with EMS use (OR 0.52, 95% CI 0.32–0.84 and OR 0.34, 95% CI 0.21–0.55, respectively). Only 55 (9.1%) of the patients interviewed had been aware of any time-critical stroke treatment prior to their stroke. Eighteen stroke patients (4.2%) reached hospital in time to receive thrombolysis, but an additional 170 (39%) could have been considered for this treatment (i.e., had no apparent other contraindications from a notes review) had they arrived within 4 h of symptom onset. Conclusions: Future public education campaigns may be more effective if they specifically address factors associated with delays in calling for help after stroke symptoms and emphasise the existence of emergency treatments, which are also time-critical. More effective public education may have the potential to increase the proportion of patients arriving in time to benefit from such treatments. Full article

The initial seconds after an earthquake are critical for rapid magnitude estimation to support real-time early warning. This study evaluates the determination of P-wave moment magnitude (M_wp) using strong-motion records from the 23 April 2025 Marmara Sea earthquake. High-quality accelerometric data from the Turkish National Strong Motion Network were analysed to extract early P-wave features within the first 3 s after P-wave onset. Results show significant rupture-directivity effects, whereby stations located approximately along the fault strike and rupture-propagation direction recorded larger ground-motion amplitudes and higher station-based Mwp estimates than stations located near nodal directions. The mean M_wp was 6.5 ± 0.2, consistent with the Global Centroid Moment Tensor (GCMT) moment magnitude estimate. Magnitude estimation was achievable within 8–20 s of P-wave arrival, confirming the method’s real-time applicability. Our findings demonstrate that strong-motion P-wave analysis can provide rapid and reliable magnitude estimates suitable for earthquake early warning, tsunami warning, and rapid-response applications. In the Marmara Sea region, where tsunami arrival times may be on the order of 20–30 min and critical infrastructure is concentrated in densely populated coastal areas, rapid determination of magnitude within seconds of earthquake initiation can provide valuable information for emergency management and hazard mitigation decisions. Full article

The inclusion of the cement industry into China’s national carbon emissions trading system in 2025 has fundamentally altered the compliance environment for high-emission enterprises, transforming carbon allowances from passive regulatory instruments into dynamic assets whose management directly affects financial performance. We develop a multi-scenario carbon asset management decision model tailored to the intensity-based benchmarking mechanism adopted by the national market. The model centres on the quota surplus-deficit variable EA4, which is computed from enterprise-level emission intensity relative to the industry benchmark, and decomposes the management problem into sequential selling and buying subproblems linked by coupled decision boundaries. A systematic parameter framework is constructed, and the model is applied to two cement enterprises—Enterprise A, a leading producer with a clear allowance surplus, and Enterprise B, a mid-tier producer operating near the benchmark boundary—through historical backtesting over the 2024–2025 period. Three principal findings emerge. First, the intensity benchmarking mechanism creates a dual-leverage effect whereby a 1.4% improvement in emission intensity (from 0.8112 to 0.8000 t/t) increases the quota surplus by 27%, a nonlinearity not captured by conventional compliance-cost models. Second, the model-driven strategy outperforms traditional experience-based approaches by 36.8% (baseline scenario, +95.20 vs. +69.58 MRMB) and 37.3% (risk scenario, −44.55 vs. −71.08 MRMB), with the improvement rate remaining consistent across both enterprises, suggesting that trading timing outweighs instrument selection in determining compliance cost outcomes. Third, dynamic CEA–CCER allocation captures an incremental 2.33 MRMB through the exploitation of a transient price inversion, a gain invisible to single-instrument strategies. Sensitivity analysis confirms that the relative advantage is robust to carbon price variations (±30%) and CCER offset caps (2–10%), while emission intensity and carry-over allowances represent the most consequential parameters for strategy direction, with EA4 crossing zero near the industry benchmark (I ≈ 0.85). The framework provides actionable decision support for cement and other high-emission enterprises navigating the unified carbon market, and contributes a quantitative methodology to the emerging field of environmental management accounting. This study contributes to Sustainable Development Goal 13 (Climate Action), Goal 7 (Affordable and Clean Energy), and Goal 9 (Industry, Innovation, and Infrastructure) by providing operational tools for decarbonisation in carbon-intensive industries. Full article

The Singaporean government’s Green Plan 2030 aims to “galvanize a whole-of-nation movement and advance [its] national agenda on sustainable development,” transforming the Garden City into a City in Nature. The state’s #OneMillionTrees campaign, which intends to plant a million trees over a decade, seems less focused on climate adaptation, given Singapore’s unresolved environmental issues such as oil refinement, terraforming, and hyperconsumption. Instead, it appears to superficially address deeper socioenvironmental wounds inflicted on the postcolonial people and land. In this article, I explore the visual culture of Singapore’s ableist-nationalist greening campaigns alongside artworks such as Marvin Tang’s A Guide to Tree Planting and History of 39 Cuttings—Hybrids, and Woong Soak Teng’s Ways to Tie Trees and Rules for Photographing a Scoliotic Patient. I argue that Tang and Woong highlight adaptation issues in the face of eco-ableist sustainability in Singapore, challenging simplistic notions of climate adaptation by attending to vulnerable, sexed and gendered more-than-human bodies. The field of art history has an opportunity to probe ableist visions of ecological sustainability—within an emerging discourse between environmental justice and disability studies—by historicizing and interpreting such art, as it speaks to enduring, more-than-human impairment and climate adaptation. Full article

This paper offers a theoretical-interpretive contribution to the sociology of lifelong learning (LLL), exploring a sociological reframing of lifelong learning through the concept of social love as an analytical framework for reading the institutional practices of universities in the domain of LLL. Drawing on classical and contemporary sociological traditions (including recognition theory, French pragmatic sociology, and relational sociology), the paper develops the argument that lifelong learning, when understood as a relational and generative practice, can be interpreted through the four dimensions of social love: overabundance, care, recognition, and universalism. The paper proposes what can be interpreted as a theoretical and educational transposition of the World Love Index (WLI) framework: a shift in scale, from the nation-state to the university, and in domain, from general social policy to educational practice, that preserves the core logic of the WLI while adapting it to the context of higher education. This transposition responds to a gap explicitly identified within the WLI research program and contributes to the debate on the civic and relational dimensions of higher education. Empirically, the paper draws on a national survey conducted within the Italian University Network for Lifelong Learning (RUIAP), which mapped lifelong learning services across 27 universities between 2022 and 2023. The survey data are used not as a basis for hypothesis testing but as exploratory empirical material through which to illustrate and develop the proposed framework, following a logic of theory elaboration. The findings reveal a heterogeneous and evolving system, characterized by uneven levels of institutionalization across the four dimensions: recognition practices are most widely present, though concentrated on formal pathways; care emerges in dedicated services for vulnerable and non-traditional populations; universalism remains largely unrealized in terms of territorial outreach; and overabundance (institutional investment exceeding regulatory compliance) is present in limited but analytically significant cases. The study concludes that understanding LLL as a practice of social love offers new insights into the civic mission of universities and their contribution to fostering social cohesion and democratic participation. It further proposes the need for observatories of institutional social love in higher education (such as RUIAP) and identifies directions for future research and policy oriented toward the generation of relational goods and the common good within university systems. Full article

Digital financial services have expanded rapidly across emerging economies and are often presented as tools for advancing women’s economic inclusion. However, the extent to which digital finance is associated with lower gender inequality depends on the broader structural conditions in which women live and work. This study examines the relationship between digital financial participation, labor market integration, and gender inequality in Brazil using nationally representative microdata from the 2025 Global Findex survey. Three outcomes are examined: digital account ownership, use of any digital payment, and engagement in merchant digital payments. Multivariate logit models show moderate gender gaps at early stages of digital financial participation. However, these gaps are not uniform across the population. The interaction results show that gender differences are concentrated mainly among individuals outside employment and among those without internet access. Among employed and digitally connected individuals, the gender gap becomes small and statistically insignificant across the three outcomes. A nonlinear decomposition shows that observable socioeconomic characteristics explain only a small share of the aggregate gender gap, especially for account ownership and any digital payment use. Additional robustness checks using probit and complementary log-log models support the main pattern of results. This suggests that the gender gap cannot be explained only by differences in education, income, employment, or internet access, and may also reflect unobserved household, institutional, or social constraints. The findings suggest that digital finance alone does not equalize participation. Rather, women’s digital financial participation is closely associated with their position in the labor market and their access to digital infrastructure. Because the analysis is based on cross-sectional data, the results should be interpreted as conditional associations rather than causal effects. Digital financial expansion is therefore more likely to support gender inclusion when it is linked to broader policies that strengthen women’s labor force attachment, digital connectivity, and economic autonomy. Full article

Against the backdrop of rapid urbanization, urban land-resource use faces the dual challenge of improving efficiency while maintaining ecological sustainability. Enhancing urban land green use efficiency contributes to the achievement of the United Nations Sustainable Development Goals, particularly SDG 11 and SDG 15. As an emerging governance approach for urban green infrastructure, the National Sponge City Policy (NSCP) aims to address urban waterlogging through nature-based solutions while improving land multifunctionality and ecological carrying capacity. Based on city-level panel data from 2005 to 2022, this study employs a difference-in-differences (DID) approach to identify the policy effect of the NSCP on ULGUE and further examines three transmission channels: innovation effects, infrastructure-support effects, and population-agglomeration effects. The novelty of this study lies in integrating the NSCP into the analytical framework of urban land green use efficiency, extending previous research that mainly focused on waterlogging control, water-resource management, and ecological benefits, and further developing a “policy intervention-factor reallocation-ULGUE improvement” mechanism pathway. The empirical results show that the NSCP significantly improves land green use efficiency in pilot areas, and this conclusion remains valid across multiple robustness checks. The mechanism analysis indicates that strengthened green innovation capacity, improved green infrastructure, and population agglomeration are key channels through which the policy effect is realized. Heterogeneity analysis further reveals that the policy effect varies across regions, dominant industrial structures, and industrial-base types. Overall, the NSCP promotes green spatial governance and efficient resource utilization, providing important institutional experience for coordinating ecological protection and urban development. Full article

Renewable energy curtailment has emerged as a growing challenge on the Korean mainland grid as photovoltaic (PV) and wind power capacity continues to expand toward national carbon neutrality targets. Plus demand response (Plus DR), in which electricity consumers increase consumption during curtailment periods, has been introduced as a demand-side mitigation measure. Buildings represent a potential resource for Plus DR participation. However, existing studies have primarily focused on load-reduction DR, and Plus DR availability by building use type under curtailment conditions has not been systematically quantified. This study estimates Plus DR availability of building loads by use type—department store, hotel, general commercial, public facility, apartment, and school—based on representative building load profiles, PV generation data, and 2025 curtailment occurrence data from the Korean mainland grid. Curtailment events were concentrated in the 10:00–16:00 window with peak frequency at 12:00 (80 events). The combined Plus DR availability across the six use types averaged 290.3 kW during curtailment hours, peaking at 300.9 kW at 14:00. The estimated Plus DR availability operated primarily through the load-increase pathway (additional grid consumption) rather than the surplus absorption pathway (reduced PV export). Surplus generation was observed only in the school at 13:00 (0.77 kW). These results provide a quantitative basis for identifying suitable building types and curtailment-responsive time windows for building-based Plus DR program design on the Korean mainland, and may serve as a reference for mainland DR market development. Full article

This paper investigates the role of cross-border trade in shaping participation in global value chains (GVCs) in developing and emerging economies over the period 2000–2022. It tests the central hypothesis that greater trade intensity enhances integration into fragmented global production systems. Using panel data methods, the analysis examines the effects of trade openness alongside foreign direct investment, logistics performance, GDP per capita, and domestic value added. The results provide strong evidence that trade openness is the dominant driver of GVC participation, with a robust and economically meaningful elasticity. Domestic value added is also positively associated with GVC integration, suggesting that deeper global engagement can coincide with increased domestic value creation. GDP per capita exerts a weaker but significant effect, while foreign direct investment and logistics performance do not show direct statistical significance in the preferred specification. These findings highlight trade as the primary transmission mechanism linking national economies to global production networks, while also pointing to a complementary role of domestic capabilities. At the same time, increased reliance on cross-border trade may heighten exposure to external shocks, underscoring a key policy trade-off. The study concludes that effective GVC integration requires balancing openness with strategies that strengthen resilience and value capture. Full article

Digital transformation has become a strategic pillar of modernization in public administration; however, evidence from emerging economies shows that technology implementation alone does not guarantee institutional transformation. This study examines the structural relationships among digital competencies, change management, technology adoption, and digital transformation in public administration institutions in Lima, Peru, incorporating Digital Inclusion Practices (DIP) as a moderating variable. A quantitative, non-experimental, cross-sectional design was applied to a sample of 358 public servants working in ministries, national agencies, regional administrative units, and municipal governments located in Lima. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results indicate that digital competencies and change management are positively associated with technology adoption, and that change management and technology adoption show significant positive relationships with digital transformation. Technology adoption partially mediates the relationships between digital competencies and digital transformation, and between change management and digital transformation. Additionally, digital competencies show a direct and statistically significant, although weak, relationship with digital transformation. The moderating relationship involving DIP was not statistically significant. These findings suggest that digital governance in emerging public administrations may depend less on individual skills alone and more on structured institutional processes that support effective technology adoption, strategic change management, and institutional modernization. Full article

Amid the increasingly stringent technological blockade imposed by some Western developed countries, and against the backdrop of rapid advances in artificial intelligence (AI) and emerging Industry 5.0 paradigms, enhancing indigenous innovation capabilities and overcoming key technological bottlenecks has become an urgent imperative. Drawing on path dependence and path creation theories, as well as the Stimulus–Organism–Response (SOR) framework, this study develops an analytical framework to examine how technological blockade accelerates indigenous innovation in latecomer countries. Using a multiple-case study design, the proposed framework is examined through two strategic technology domains: generative artificial intelligence and new energy vehicles (NEVs). Data were collected through technical documentation, publicly available interview materials involving key stakeholders, and third-party reports. The findings indicate that technological blockade accelerates the transition from imitative to indigenous innovation in latecomer countries. Further mechanism analysis reveals that the external pressure formation mechanism, endogenous motivation activation mechanism, and innovation behavior transformation mechanism jointly constitute a pressure-driven transformation mechanism. Specifically, technological blockade, as an external stimulus, disrupts the existing path-dependent state of imitative innovation; the blockade-induced pressure activates the endogenous motivation of innovation actors, which is further reinforced under national foundational conditions and policy guidance; and under the combined influence of external pressure and endogenous motivation, innovation actors’ behaviors undergo significant changes, gradually shifting from reliance on external technologies and resources toward indigenous R&D and breakthroughs in key technologies. This process ultimately drives the transition from imitative to indigenous innovation, marking a shift from path dependence to path creation. By demonstrating how technological blockade accelerates the transition of the innovation trajectory, this study offers theoretical insights for latecomer countries facing external technological constraints and provides policy implications for building resilient innovation ecosystems and enhancing technological autonomy in the era of AI-driven industrial transformation. Full article

Industrial settlements of the East Kazakhstan Region face a persistent technogenic burden driven by the dense concentration of non-ferrous metallurgy and heat-and-power enterprises, further compounded by unfavorable pollutant dispersion conditions inherent to the region’s mountain–basin topography. This study evaluated spatiotemporal associations between annual mean concentrations of NO₂, SO₂, H₂S, and CO, the integrated air pollution index (API₅), and primary neoplasm morbidity across five settlements over the period 2014–2024. A retrospective ecological analysis was carried out for Ust-Kamenogorsk, Ridder, Altai, Shemonaikha, and the settlement of Glubokoe, incorporating Spearman’s rank correlation, lag analysis (1–3 years), and the Mann–Kendall trend test. Throughout the study period, neoplasm morbidity in the region consistently exceeded the national average by a factor of 1.3 to 2.0. In Ust-Kamenogorsk—where metallurgical SO₂ and NO₂ emissions are most heavily concentrated—strong positive associations were found in children for SO₂ (ρ = 0.791, p < 0.05) and in adolescents for NO₂ and CO, reflecting elevated inhalation exposure under conditions of chronic pollution. The negative associations with API₅ observed in Ridder and Altai, where the index showed a statistically significant downward trend, are interpreted as evidence of the inertial character of oncological processes and the lasting influence of cumulative past exposure. Across all studied settlements, SO₂ emerged as the most consistent predictor of morbidity variation. These findings support prioritizing stricter emission controls for SO₂ and NO₂ from metallurgical and energy facilities, establishing oncological screening programs for children and adolescents in chronically polluted areas, and strengthening ambient air monitoring—measures whose effective implementation will require coordinated action between public health authorities and environmental regulators. Full article

Western theories and empirical comparative research on attitudes toward immigrants and their rights have largely overlooked Latin America. To address this gap, we conducted multilevel ordered logistic regression analyses on Latinobarómetro surveys from 17 countries (N = 19,004). The findings show that support for immigrants’ social rights is more contingent on immigration-related benefits—especially cultural enrichment—than on perceived threats. When threats do mobilize opposition, the perceived fiscal burden emerges as the sole significant driver, overriding both concerns about labor market competition and fears of rising crime. Furthermore, right-wing individuals were no less supportive of immigrants’ social rights than left-wing individuals. Instead, the most welfare-chauvinist attitudes were found among the politically disengaged. At the macrosocial level, the results provide evidence that contextual factors not only exert a direct statistical effect on public support for immigrants’ social rights but also moderate the influence of perceived micro-level threats. In particular, the national unemployment rate and the immigrant stock exacerbate the exclusionary effect of the perceived fiscal burden on levels of support among citizens. Ultimately, these findings challenge some theoretical assumptions derived from intergroup threat theory, provide novel evidence for the Threat-Benefit Model, and further suggest a distinct political dynamic in the region. Full article