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This paper examines the impact of economic freedom on the financial fragility of 1,496 non-financial SMEs in Vietnam over the period 2012–2020. We also evaluate the effect of ownership structure on the relationship between economic freedom and financial fragility. Our findings provide evidence that an increase in the degree of aggregated economic freedom and its categories – rule of law, regulatory efficiency, and market openness – help firms reduce the level of financial fragility. However, an increased government size tends to worsen their financial risk. Regarding the impact of ownership, our results reveal that greater rule of law, regulatory efficiency, and market openness have a positive influence on foreign-owned firms, enabling them to maintain lower levels of financial fragility compared to non-foreign-owned firms. However, foreign-owned firms experience a higher level of financial fragility relative to domestically private-owned firms due to increased government size. Furthermore, our analysis indicates that there is no difference in the effect of economic freedom on financial fragility between state-owned and non-state-owned firms in Vietnam. This finding has implications for recognizing the importance of foreign ownership and economic freedom in emerging markets. It also encourages foreign shareholders to design appropriate policies to mitigate financial risk.

This paper presents an effective biogeography-based optimization (BBO) for optimal location and sizing of solar photovoltaic distributed generation (PVDG) units to reduce power losses while maintaining voltage profile and voltage harmonic distortion at the limits. This applied algorithm was motivated by biogeography, that the study of the distribution of biological species through time and space. This technique is able to expand the searching space and retain good solution group at each generation. Therefore, the applied method can significantly improve performance. The effectiveness of the applied algorithm is validated by testing it on IEEE 33-bus and IEEE 69-bus radial distribution systems. The obtained results are compared with the genetic algorithm (GA), the particle swarm optimization algorithm (PSO) and the artificial bee colony algorithm (ABC). As a result, the applied algorithm offers better solution quality and accuracy with faster convergence.

Urban villages have been theorised in three dominant ways: as ethnic enclaves in migration studies, as the UK Urban Village Concept, and as villages-in-the-city in the Global South. Whether these interpretations can coexist within a single urban context remains insufficiently examined. This study addresses this gap through Da Lat, Viet Nam, where rapid urbanisation and the state-led Green Urban Village pilot project have brought these models into direct interaction. The study adopts a multidisciplinary, multi-method approach combining historical and literature review, spatial mapping, expert-based Delphi assessment, topic modelling, and multi-criteria evaluation using the Analytic Hierarchy Process with optimisation techniques. A total of 74 villages were assessed across eight evaluation criteria using a context-sensitive scoring framework. Findings confirm the coexistence of ViCs, core attributes associated with ethnic enclaves, and a future-oriented Urban Village Concept. Most existing villages scored positively, demonstrating strong socio-cultural and spatial embeddedness, while the ecological dimension remains underdeveloped. The Green Urban Village pilot aligns with environmental objectives but shows weak contextual integration. A scenario-based integration with an adjacent village yields a more balanced performance across all criteria. The study empirically demonstrates the coexistence of hybrid urban village forms and analytically illustrates how a relational approach – here referred to as Green Urban Village 2.0 – could anchor sustainability-oriented planning within existing village structures. The findings contribute to urban village theory and offer context-sensitive insights for sustainable neighbourhood planning in Viet Nam and comparable settings.

PurposeThis study examines the convergence of energy diversification, financial development and per-capita income in OECD countries.Design/methodology/approachThe research employs the club convergence test to assess convergence among OECD countries and uses Granger causality tests and panel regressions to identify the determinants of convergence, using data from 1997 to 2021.FindingsThe convergence tests showed no overall convergence but revealed convergence clubs for each factor. Granger causality tests indicated short-run bi-directional relationships between the variables. Long-run panel regression analysis confirmed that technological progress significantly improves per capita income and energy diversification. Additionally, it revealed bi-directional relationships between energy diversification and financial development, a uni-directional relationship from financial development to per capita income and a U-shaped effect of per capita income on energy diversification, with a turning point at $67,112.8 per year.Practical implicationsThe findings suggest that within each convergence club, implementing microeconomic incentives for technology development and diffusion in energy, production and financial services could help lagging countries catch up.Originality/valueThis study pioneers the testing of convergence in energy diversification, financial development and per capita income in OECD countries and identifies the determinants of this convergence.

Universities are well placed to adopt and use the UN Sustainable Development Goals (SDGs) on their campuses to educate and showcase how the SDGs can be delivered in the built environment. Green infrastructure, such as green roofs, green walls, or green parks, are highly visual implementations with environmental and social benefits that contribute to several SDGs, such as 3 (good health and wellbeing), 10 (reduced inequalities), 11 (sustainable cities and communities), 13 (climate action) and 15 (life on land). These features may be referenced in sustainability teaching and learning, which may raise and heighten awareness of the social, economic, and environmental benefits of green infrastructure. In this study, we explored users’ perceptions of the extent to which a university campus green roof contributes to the SDGs and whether users focussed more on its social or environmental benefits. Statistical analyses, namely independent samples t-tests and analysis of variance, were conducted to determine what influenced users’ perceptions of the green roof. The analyses revealed that users’ perceptions did not differ largely by sociodemographic characteristics, though students perceived the social benefits as greater than university staff. Those with greater knowledge of green roofs perceived its environmental benefits as greater, but not the social benefits. The findings demonstrate the importance of green infrastructure on university campuses for encouraging engagement with the SDGs, whilst indicating that knowledge of such infrastructure increases appreciation of their environmental credentials.

Fruit ripening in response to propylene (an ethylene analog), 1-methylcyclopropene (1-MCP, an ethylene action inhibitor), and low temperature (5°C) treatments was characterized in \"Kosui\" kiwifruit ( × ). Propylene treatment induced ethylene production, with increased expression levels of ( ) ( ) and ( ), and rapid fruit softening together with increased expression levels of ( ) and ( ) within 5 days (d). Fruit soluble solids concentration (SSC) and contents of sucrose, glucose, and fructose together with the expression levels of ( ), , and ( ) increased rapidly after 5 d exposure to propylene. Furthermore, propylene exposure for 5 d was sufficient to induce the production of key aroma volatile compounds, ethyl- and methyl butanoate, accompanied with increased expression levels of ( ). Application of 1-MCP at the start of the experiment, followed by continuous exposure to propylene, significantly delayed fruit softening, changes in SSC and sugars, and strongly suppressed the production of ethylene, aroma volatiles, and expression of associated genes. During storage, fruit softening, SSC and sugar increase, and increased expression of genes associated with cell wall modification and carbohydrate metabolism were registered without detectable ethylene production; however, these changes occurred faster at 5°C compared to 22°C. Interestingly, ethyl and methyl butanoate as well as expression were undetectable in kiwifruit during storage, while they were rescued by post-storage propylene exposure, indicating that the production of aroma volatile compounds is strongly ethylene-dependent. Transcript levels of a NAC-related transcription factor (TF), , increased in response to both propylene and low temperature treatments, while was exclusively up-regulated by propylene. By contrast, transcript levels of a MADS-box TF, , exclusively increased in response to low temperature. The above findings indicate that kiwifruit ripening is inducible by either ethylene or low temperature signals. However, fruit ripened by low temperature were deficient in ethylene-dependent aroma volatiles, suggesting that ethylene signaling is non-functional during low temperature-modulated ripening in kiwifruit. These data provide further evidence that ethylene-dependent and low temperature-modulated ripening in kiwifruit involve different regulatory mechanisms.

Alpha-mangostin (MGS) is a natural xanthone compound extracted from mangosteen pericarps. It has great potential as an excellent anticancer agent. However, the extremely low solubility of MGS in water seriously impedes its medical application. Previously, we found that cyclodextrin (CD)-based hyperbranched polymer nanoparticles (CDNPs) solubilize MGS by encapsulating it in the CD cavity and that their binding constants are 100 times higher than those of native CDs. Our findings suggested that CDNPs could be good carriers of MGS. Here, we prepared three types of CDNP from α-, β-, and ɣCDs and compared them in terms of MGS release and in vitro and in vivo anticancer efficacy. βCDNP/MGS demonstrated the greatest anticancer efficacy, while no efficacy was observed for the other CDNPs. MGS release from CDNPs/MGS can be explained by a model in which the slow and rapid modes are connected in series; before release, MGS must shift from the slow to the rapid mode. We assumed that the slow and rapid modes are related to the interior and surface CDs of CDNPs. βCDNP/MGS showed the slowest release in the slow mode. We assume that slow release in the slow mode is essential for MGS retention until the cancerous region is reached.We examined drug release behavior and anticancer efficacy of cyclodextrin-based nanoparticles (CDNPs) containing alpha-mangostin (MGS) in three different type of CDs (α-, β-, and γ-CD). βCDNP containing MGS demonstrated the best anticancer efficacy, while no efficacy was observed for the other CDNPs. Our findings suggested the anticancer efficacy might depend on the drug retention capability in which the interior and surface CDs in the CDNPs relate to the slow and rapid release modes, respectively. We assume the drug retention capability of slow release mode is important for performing the anticancer efficacy.

The advent of satellite-borne machine learning hardware accelerators has enabled the onboard processing of payload data using machine learning techniques such as convolutional neural networks (CNNs). A notable example is using a CNN to detect the presence of clouds in the multispectral data captured on Earth observation (EO) missions, whereby only clear sky data are downlinked to conserve bandwidth. However, prior to deployment, new missions that employ new sensors will not have enough representative datasets to train a CNN model, while a model trained solely on data from previous missions will underperform when deployed to process the data on the new missions. This underperformance stems from the domain gap, i.e., differences in the underlying distributions of the data generated by the different sensors in previous and future missions. In this paper, we address the domain gap problem in the context of onboard multispectral cloud detection. Our main contributions lie in formulating new domain adaptation tasks that are motivated by a concrete EO mission, developing a novel algorithm for bandwidth-efficient supervised domain adaptation, and demonstrating test-time adaptation algorithms on space deployable neural network accelerators. Our contributions enable minimal data transmission to be invoked (e.g., only 1% of the weights in ResNet50) to achieve domain adaptation, thereby allowing more sophisticated CNN models to be deployed and updated on satellites without being hampered by domain gap and bandwidth limitations.

The study examines the influence of board structure on the economic, environmental, and social dimensions of corporate sustainability performance from the perspective of agency theory and stakeholder theory. If a firm’s commitment to sustainable development is to satisfy environmental and social needs and to develop long-term relationships with all stakeholders for sustainable business, we expect that a board of directors would demonstrate their commitment by enhancing all different dimensions of sustainability. Based on a panel analysis of data from the emerging East Asian markets between 2011 and 2016, we identify which board attributes promote corporate sustainability performance and also prove that some attributes fit well with some particular sustainability dimensions. The findings have important implications by identifying the role of corporate boards in sustainability performance and providing a foundation for their efforts to enhance sustainable development.