Search Results (7,518)

Tight oil reservoirs are characterized by poor petrophysical properties. After hydraulic fracturing, the low flowback rate of fracturing fluid readily leads to the formation of a water invasion zone in the near-wellbore region, which severely restricts the performance of Carbon dioxide (CO₂) huff-n-puff. To clarify the damage mechanism of the water invasion zone on CO₂ huff-n-puff in tight oil reservoirs and determine the key regulatory parameters, tight cores with a relative water invasion zone length Δδ = 0.3 were adopted as the research subject. Five groups of injection–soaking–production time combinations were designed, and single-factor analysis was implemented using the control variable method. Integrated with numerical simulation and nuclear magnetic resonance (NMR) testing, the influence of the water invasion zone, pore crude oil mobilization characteristics, and parameter regulation effects were systematically explored. The results demonstrate that the water invasion zone occupies effective pore throats to form a continuous water-phase barrier, hindering CO₂ seepage and mass transfer. After four huff-n-puff cycles, the cumulative recovery factor of the water-invaded model is 4.13 percentage points lower than that of the water-free model. After four huff-n-puff cycles, the cumulative recovery factor of the water-invaded model is 4.13 percentage points lower than that of the water-free model. The NMR T₂ spectra of cores with and without water invasion exhibit remarkable discrepancies: the water-free core presents a unimodal structure, while the water-invaded core features a distinctive bimodal structure, with obvious staged characteristics in crude oil mobilization. The recovery factor declines nonlinearly and sharply with the increase of Δδ, verifying that the water invasion zone length is the dominant controlling factor. The regulation effects of injection, soaking, and production time differ significantly: injection time serves as the pivotal parameter for enhancing oil recovery. Prolonging injection time can strengthen displacement intensity and dismantle the water-phase barrier, thereby elevating the recovery factor, whereas soaking time and production time have no significant improvement effect. The results can provide valuable references for the parameter optimization of CO₂ huff-n-puff in water-invaded tight oil reservoirs. Full article

This article analyses how capacity building programmes interact with structural constraints in mission-oriented climate policy, focusing on the Italian pilot Let’sGOv (GOverning the Transition through Pilot Actions) within the EU Mission “100 Climate-Neutral and Smart Cities by 2030”. Using an iterative, reflexive methodology (document analysis, direct observation, and qualitative analysis of questionnaires, workshop outputs, and online training feedback), it examines how municipal actors experience and reinterpret capacity building across three coupled dimensions: internal organisational capacity, external stakeholder relations, and multilevel governance interfaces. The empirical setting is a network of nine Italian Mission Cities (Bergamo, Bologna, Florence, Milan, Padua, Parma, Prato, Rome, Turin) supported by technical partners. The bench-learning pathway combined barrier diagnosis, an intensive in-person workshop, and a codesigned online curriculum structured around three thematic clusters (engagement, data, climate finance). Findings indicate that persistent barriers—departmental silos, resource and time scarcity, rigid human resources and procurement routines, asymmetric data access, and regulatory instability—are not removed by capacity building; rather, they are progressively articulated, specified, and reframed into actionable organisational and policy demands. Bench-learning strengthens diagnostic and relational capacities and enables modest institutional innovations (templates, protocols, internal task forces, shared policy briefs), while “hard” governance infrastructures largely remain unchanged. The paper argues that networked capacity building contributes to the emergence of nascent, project-dependent multilevel interfaces only when it supports collective negotiation with national actors and translates local experimentation into durable multilevel interfaces, mitigating risks of projectification and downward responsibility shifting. Full article

The agricultural sector is increasingly confronted with numerous challenges, including declining prices for agricultural products, escalating production costs, intensified globalization, rapid industrialization, urban expansion and growing competition in global markets. To promote rural development and improve farmers’ livelihoods through diversified sources of income, agritourism has been identified as a viable alternative strategy. This study aims to determine the factors influencing farmers’ willingness to participate in agritourism in Mpumalanga Province, South Africa. Primary data were collected from November 2022 to June 2023 using a structured questionnaire and a simple random sampling technique to select 100 farmers. A logistics regression model was used to analyse data. The findings revealed that profitability, non-farm employment, the number of labourers, and access to information positively influence WTP. Age also positively influenced WTP, while marital status showed a negative but significant effect. The findings imply that farmers with stronger financial capacity, labour availability and access to information are more likely to consider agritourism as a diversification strategy. The study suggests strengthening extension services, improving farm profitability and enhancing access to information to increase readiness to engage in agritourism. Full article

Crown-level tree species semantic segmentation enables fine-grained forest inventory and management. Current high-precision tree species classification typically relies on multi-source remote sensing data, the acquisition and processing of which remain costly for large-area applications, making low-cost unmanned aerial vehicle (UAV) RGB imagery an attractive option for large-scale forest mapping. However, in heterogeneous forests, complex canopy structures and the limited spectral discriminability of low-cost UAV RGB imagery make 2D appearance cues alone insufficient for reliable species discrimination, crown delineation, and accurate separation of adjacent crowns. This often leads to inter-class confusion, blurred crown boundaries, and poor recognition of small crowns. To address these limitations, this paper proposes MonoCrown (MCrown), which strengthens geometric and contextual representation for distinguishing visually similar species and delineating crowns from single-temporal UAV RGB imagery. To compensate for the insufficiency of appearance cues, MCrown introduces monocular depth inferred offline from the same RGB image as a frozen geometric prior, and integrates cross-window global–local attention (CW-GLA), bidirectional cross-modal attention (BiCoAttn), and depth-adaptive injection (DAI) to capture long-range dependencies and promote complementary use of appearance and geometric features, especially for small crowns with similar visual patterns in complex scenes. To validate the method’s effectiveness, a crown-level UAV RGB dataset covering approximately 40 km² was constructed. Systematic comparative experiments were conducted on the proposed dataset and on public benchmarks, supporting the effectiveness of the proposed approach across ten dominant classes, especially for small crowns and visually similar categories. Its mean Intersection over Union (mIoU) and overall accuracy (OA) reached 74.1% and 87.3%, respectively. The method achieves high-precision crown-level tree species semantic segmentation using single-temporal UAV RGB as the sole acquired modality, while monocular depth inferred from the same RGB image serves only as a frozen geometric prior, without requiring multispectral, multi-temporal, or active-sensor acquisitions. This offers a practical solution for crown-level tree species mapping in heterogeneous forests. Full article

The increasing emphasis on sustainable construction has positioned regulatory frameworks as critical drivers of sustainable building construction project delivery (SBCPD), particularly in developing countries such as South Africa. However, the effectiveness of different regulatory instruments remains insufficiently understood. This study investigates the influence of regulatory factors on SBCPD by examining two key constructs: Compulsory Enforcement and Incentivisation (CEI) and the Sustainable Building National Framework (SBNF). A quantitative research design was adopted, and data were analysed using Principal Component Analysis (PCA), Confirmatory Factor Analysis (CFA), and Structural Equation Modelling (SEM) to assess the relationships between regulatory mechanisms and project delivery outcomes. The findings reveal that CEI does not exhibit a statistically significant influence on SBCPD when modelled as a combined construct, despite showing significance when tested independently. This suggests that aggregating compulsory and voluntary regulatory instruments may weaken their explanatory power due to underlying interaction effects. In contrast, SBNF demonstrates a strong and statistically significant positive influence on SBCPD, highlighting the critical role of government-led policies, institutional frameworks, and certification systems in shaping sustainable construction practices. The study contributes to theory by advancing our understanding of regulatory hybridity and the role of institutional drivers in sustainable construction. In practice, the findings underscore the need for coherent, well-articulated policy frameworks, strengthened enforcement capacity, and strategic alignment between voluntary and mandatory instruments. The study concludes that government-led frameworks remain the primary catalyst for sustainable construction delivery in developing economies. These insights provide valuable guidance for policymakers and industry stakeholders seeking to enhance sustainability performance in the built environment. Full article

Despite strong evidence that gender-diverse leadership improves organizational innovation and performance, women remain underrepresented in leadership pipelines worldwide, particularly in Asia. While prior research largely examines the outcomes of gender diversity at the firm level, far less is known about the psychological and social factors that shape women’s leadership aspirations in the first place. Addressing this gap, this study applies Social Cognitive Career Theory (SCCT) to explain how contextual support and developmental experiences influence women’s leadership aspirations in a collectivist business environment. Using survey data from 400 adult women in Indonesia and structural equation modelling, the study examines how parental involvement shapes personal mastery, how personal mastery strengthens leadership self-efficacy, and how self-efficacy, role models, and perceived leadership traits jointly predict leadership aspiration. The findings show that parental involvement indirectly contributes to leadership aspiration through personal mastery and self-efficacy, while role models and leadership traits also play significant roles. Among all predictors, self-efficacy emerges as the strongest driver of women’s leadership aspiration. This study makes three contributions. First, it extends SCCT beyond traditional STEM career research into the domain of leadership aspiration. Second, it provides rare empirical evidence from a collectivist Asian context, highlighting the role of family and social environment in shaping women’s leadership pathways. Third, it shifts the focus of gender diversity research from representation outcomes to the formation of the female leadership pipeline, offering actionable insight for educators, families, and organizations seeking to foster future women leaders. Full article

Background/Objectives: Psychological variables such as body image, self-esteem, and life satisfaction have become important research topics in recent years, particularly in their relationships with individuals’ eating attitudes. The purpose of this study is to examine the predictive effect of body image and self-esteem on eating attitudes in emerging adults and to evaluate the mediating role of life satisfaction in this relationship. Method: The study included 402 participants aged 18–30. Data were collected using the Eating Attitudes Test (EAT-26), the Rosenberg Self-Esteem Scale (RSS), the Body Image Scale (BIS), and the Life Satisfaction Scale (LSS). The analyses included correlational analyses to examine relationships among eating attitudes, body image, self-esteem, and life satisfaction; multivariate regression to test the predictive roles of body image, self-esteem, and life satisfaction on eating attitudes; and structural equation modeling to evaluate the mediating role of life satisfaction in the relationships between body image, self-esteem, and eating attitudes. Result: The correlational analysis revealed that eating attitudes are associated with body image, life satisfaction, and self-esteem. Body image was identified as the most influential predictor of eating attitudes. Structural equation modeling indicated that life satisfaction mediates the relationship between self-esteem and eating attitudes. Conclusions: Body image, self-esteem, and life satisfaction play a crucial role in shaping eating attitudes among emerging adults. The mediating effect of life satisfaction underscores psychological well-being as a key regulatory factor rather than solely an outcome. Promoting positive body image, strengthening self-esteem, and enhancing life satisfaction through preventive and psychoeducational programs may help protect against disordered eating attitudes in this population. Full article

Under low-light conditions, visible-spectrum images are prone to detail loss and contrast degradation, which substantially limits object detection performance. Although infrared imagery can provide complementary cues, direct fusion often introduces noise interference and thus undermines detection stability. To address this issue, this paper proposes a discriminative enhancement and selective fusion method for low-light cross-spectral object detection. Specifically, a task-oriented discriminative Retinex enhancement module is introduced at the front end to mitigate illumination interference while strengthening structural information. Meanwhile, a spectral-selective cross-scale fusion module is designed to suppress noise propagation through adaptive weighting and cross-scale interaction. In addition, mutual information loss and cross-scale consistency constraints are incorporated to enhance cross-spectral feature representation and prediction stability. Experimental results on multiple public datasets demonstrate that the proposed method can consistently improve the accuracy and robustness of object detection under low-light conditions. Full article

This systematic review synthesises the qualitative literature on Māori leadership to examine how leadership is conceptualised, enacted, and constrained, and what this implies for Aotearoa New Zealand’s health system. Across included studies, Māori leadership is grounded in whakapapa-based legitimacy, tikanga and mātauranga Māori, and collective responsibility for relational, cultural, and intergenerational wellbeing; these foundations persist across “traditional” and “contemporary” settings, with differences reflecting institutional conditions rather than shifts in core values. Interpreting the literature through a Māori cultural lens, the review shows that leadership is often exercised within Crown-dominated organisations where Māori authority is not the default, requiring leaders to navigate multiple accountabilities to iwi and communities, organisational mandates, and statutory obligations. Hybridity emerges as a structurally produced feature of practice, integrating Māori relational ethics with bureaucratic, professional, and governance requirements and ongoing translation work to make Māori priorities legible within institutional systems. Health-sector evidence illustrates how commissioning, funding, and accountability arrangements can limit Māori decision-making, increase leadership burden, and constrain sustainability and leadership pipelines. The review concludes that strengthening Māori leadership in health requires organisational and system change—such as clearer Māori decision rights, resourced Māori-led priority setting, and accountability mechanisms that operationalise equity and anti-racism—alongside targeted research on governance, commissioning, and system design. Full article

There exists a complex and intimate interplay between ecosystem services and human well-being. This coordination not only concerns regional sustainable development but also depends on the structural balance of various service functions within ecosystems. Therefore, based on three-phase data from 2000 to 2020, this study investigates the coupling coordination relationship between ecosystem services and human well-being in the Northeast Black Soil Region, along with its driving factors and influence pathways. Key ecosystem services and human well-being levels were quantified, introducing a two-level coupling coordination model: D1 (coordination between total ecosystem service provision and human well-being) and D2 (coordination between internal ecosystem service balance and human well-being). Results indicate that: (1) From 2000 to 2020, the Ecosystem Service Index showed an initial rise followed by a decline. Synergistic relationships among ecosystem services strengthened, while trade-offs between cultural services (Shannon diversity index) and other services persisted. High human well-being zones were highly concentrated in provincial capitals, indicating the gradual formation of a priority development pattern. (2) The coupling coordination level of D2 was significantly weaker overall than that of D1. Compared to the overall supply level, the coordination of internal ecosystem service functions was a more critical factor constraining regional comprehensive development. (3) Landscape patterns are the primary factor governing the coupling relationship between regional ecosystem services and human well-being. Future efforts should focus on optimizing landscape configurations to enhance both human well-being and ecosystem coordination. This study contributes to a better understanding of the relationship between ecosystem services and human well-being from the perspectives of both aggregate coordination and internal balance, and also provides valuable insights for research and management measures in regions characterized by intensive agricultural development and rapid urbanization. Full article

This study investigates the influence of adhesive type on the bond performance between CFRP plates and steel interfaces through static tensile double-shear tests. Three types of adhesives (Araldite 420A/B, 2015-1, Sikadur-30CN) were tested under four bond lengths. The results indicate that adhesive strength significantly affects failure characteristics, with distinct material performance differences observed. Bond length influences the stress distribution, enhancing dispersion while potentially altering damage progression. High-performance adhesives exhibit superior shear resistance and fracture energy due to improved viscous properties, whereas moderately plastic adhesives achieve adaptive deformation and durable bonding by enhancing the flow and substrate contact. These findings provide a theoretical basis for material selection in CFRP-strengthened steel structures and offer actionable guidance for structural repair engineering applications. Full article

This article presents the design and development of an interactive architecture oriented toward the management of traditional vallenato, a musical genre recognized as an Intangible Cultural Heritage of Humanity by UNESCO. Architecture combines the principles of contextual awareness and the use of massive open online courses (MOOCs) to face the current challenges of preservation, dissemination, and teaching of this cultural expression, threatened by commercialization and the loss of its traditional roots. Through a modular structure, adaptive technological tools are integrated to capture, process, and use contextual information, personalizing learning experiences and strengthening the link between communities and their cultural heritage. The proposal consists of several functional layers, including context management, user profiles, educational resources, and a persistence unit, each designed to ensure the interoperability and sustainability of cultural data. In addition, the capacity of architecture to be used in other cultural contexts is highlighted, expanding its impact on different artistic manifestations and heritages worldwide. This article includes a comparative analysis with other existing models, highlighting the advantages of this solution in terms of customization and adaptability. Finally, opportunities for improvement and expansion are explored, as well as the pending challenges in the implementation of this technological tool in educational and cultural environments. Full article

Culturally unsafe mental health services contribute to persistent inequities for Aboriginal and Torres Strait Islander peoples, yet existing cultural safety frameworks lack clear, prioritised, community-endorsed implementation guidance. This study aimed to establish Aboriginal consensus on cultural safety principles, implementation priorities and practical actions for culturally safe mental health services. A three-round modified Delphi study was conducted with 37 Aboriginal participants from Western Australia with expertise in mental health, social and emotional wellbeing and lived experience. In Round 1, participants completed an online survey rating the importance of cultural safety principles and identifying those requiring urgent action. In Rounds 2 and 3, facilitated yarning sessions reviewed findings, refined principles, grouped them into implementation domains, and identified priority actions. Aboriginal Participatory Action Research ensured Aboriginal leadership and governance throughout. All principles achieved strong consensus for importance. The most urgent priorities were trustworthiness, Aboriginal governance, trauma-informed care, addressing racism and strengthening the Aboriginal workforce. Participants organised the refined principles into six implementation domains, with Leadership and Governance identified as foundational to reform. Trustworthiness was reframed as an aspirational outcome requiring structural change. This study provides a community-endorsed, prioritised framework for translating cultural safety principles into mental health service practice and policy. Full article

This study investigates the determinants of GDP per capita across 26 European Union member states over the period of 2006–2024, with a particular focus on entrepreneurship, institutional quality, and macroeconomic factors. Given the presence of long-run income differences across EU countries, the analysis explicitly accounts for structural heterogeneity in economic development and institutional capacity. To ensure robust estimation in the presence of cross-sectional dependence and slope heterogeneity, the study employs advanced panel econometric techniques, including tests for cross-sectional dependence, unit roots, and cointegration. Long-run relationships and short-run dynamics are estimated using the Cross-Sectionally Augmented Autoregressive Distributed Lag (CS-ARDL) model, complemented by robustness checks based on the Augmented Mean Group (AMG) and Common Correlated Effects Mean Group (CCEMG) estimators. In addition, the Method of Moments Quantile Regression (MMQR) is applied to capture heterogeneity across different points of the income distribution, thereby reflecting long-run income disparities among EU member states. The empirical results confirm the existence of a stable long-run equilibrium relationship among the variables. The baseline CS-ARDL estimates indicate that institutional quality, entrepreneurial activity, trade openness, and government expenditure exert positive and statistically significant effects on GDP per capita, while financial development exhibits a negative effect and foreign direct investment remains insignificant. In the short run, entrepreneurship and trade openness contribute positively to GDP per capita, whereas government expenditure and credit expansion generate contractionary effects. The robustness analysis using AMG and CCEMG estimators largely supports these findings, as the direction of the coefficients remains consistent across alternative specifications, although some variation in statistical significance is observed due to differences in the treatment of cross-sectional dependence and unobserved common factors. The MMQR results further reveal substantial heterogeneity across the income distribution, indicating that the effects of key determinants vary depending on countries’ long-run income levels. In particular, trade openness and institutional quality exert stronger positive effects in lower-income quantiles, while the adverse effects of excessive financial development are more pronounced in higher-income quantiles. Overall, the findings underscore the importance of promoting productive entrepreneurship, strengthening institutional frameworks, facilitating trade integration, and ensuring efficient financial intermediation to enhance GDP per capita within the European Union. The results also highlight the need for differentiated policy approaches that explicitly account for long-run income heterogeneity, structural differences, and varying institutional capacities across EU member states. Full article

For power-grid applications such as transmission corridor inspection, substation asset inspection, and post-disaster emergency repair, reliable UAV self-localization under GNSS-degraded or GNSS-denied conditions is critical to ensuring operational safety and accurate defect geotagging. Due to substantial discrepancies in viewpoint, scale, and geometric structure between oblique UAV images and nadir satellite images, conventional RGB-based cross-view retrieval methods often suffer from unstable alignment and insufficient geometric modeling, particularly in scenarios with repetitive textures and partial overlap. To address these challenges, we propose a cross-view visual geo-localization model that integrates RGBD multimodal inputs with multi-scale attention enhancement. Specifically, MiDaS is used to estimate relative depth from UAV imagery, which is concatenated with RGB to form a four-channel input, while satellite images are padded with an additional zero channel to maintain dimensional consistency. A shared-weight ViTAdapter is adopted to learn joint semantic–geometric representations, and a lightweight Efficient Multi-scale Attention (EMA) module is adopted on spatial feature maps to strengthen multi-scale spatial consistency. In addition, an IoU-weighted InfoNCE loss is employed to accommodate partial matching during training, thereby improving the robustness of feature alignment. Experiments on the GTA-UAV dataset under the cross-area protocol show stable performance across both retrieval and localization metrics. Specifically, Recall@1, Recall@5, and Recall@10 reach 18.12%, 38.83%, and 49.47%, respectively; AP is 28.01 and SDM@3 is 0.53; meanwhile, the top-1 geodesic distance error Dis@1 is 1052.73 m. These results indicate that explicit geometric priors combined with multi-scale spatial enhancement can effectively improve cross-view feature alignment, leading to enhanced robustness and accuracy for localization in challenging power inspection scenarios. Full article