Search Results (10,130)

Background: Vaccinations are essential to protect travelers from infectious diseases, especially in high-risk destinations. However, awareness and adherence to vaccination recommendations vary, influenced by communication, personal beliefs, and behavior. Methods: A focus group was conducted in February 2025 at a local health authority in central Italy, specifically within its travel clinic, to explore travelers’ awareness, attitudes, and behaviors regarding vaccination. The discussion was analyzed using the “3Cs” Vaccine Hesitancy model. Participants were purposively selected to ensure diversity and representativeness. Discussions included past travel experiences, knowledge of required vaccines, motivations for immunization, and barriers to access. Results: Four key thematic areas emerged: socio-cultural/environmental factors, psychological/emotional influences, knowledge/information access, and general health perceptions. Communication gaps often weakened belief in vaccine efficacy and necessity. Cultural background, past experiences, and risk perception heavily influenced decisions. Discussion: Although vaccination is widely viewed as a protective measure, vaccine hesitancy persists due to misinformation and limited institutional trust. The COVID-19 pandemic intensified both awareness and skepticism. The 3Cs model clarified hesitancy levels and barriers, emphasizing the need for effective communication and trust-building. Conclusions: Enhancing access to accurate information, strengthening healthcare professionals’ communicative role, and reducing economic obstacles are crucial. Tailored awareness campaigns and integrated health policies are essential to increasing vaccine uptake, safeguarding traveler health, and limiting global disease spread. Patient or Public Contribution: Members of the public contributed to this study by participating in a focus group, where they shared their personal experiences, perceptions, and opinions regarding travel-related vaccinations. Their insights provided valuable qualitative data that helped inform the study’s findings. However, they were not involved in the study design, the analysis of the data, or the preparation of the manuscript. The role of participants was limited to the data collection phase of the study. Full article

The effort to reduce the intensity of car traffic in city centres is among the core objectives of sustainable development. One important means of achieving this aim is the creation of Park-and-Ride facilities. This article examines the challenges encountered during the planning and construction of a Park-and-Ride designed to ease the transport burden of a larger city, yet situated on the edge of a small historic town in Poland. Using a research-through-design method, the study identifies the project’s challenges. The article highlights the overlooked issue of locating Park-and-Ride schemes within sensitive contexts. The accompanying interventions enabled the realisation of an undertaking, originally conceived as a strictly engineering investment fulfilling global policy objectives, but ultimately adapted to manage local priorities. The pursuit of sustainable transport development thus became an opportunity to foreground the dual role of transport spaces: both as organisers of movement and as educators in conveying cultural meaning. The project serves as an example of how local problems may be addressed through investments framed as advancing global political goals. The Park-and-Ride in Stary Sącz also provides material evidence of the significance of decisions made by local authorities to resolve local challenges while contributing to global goals. Full article

The global shift towards sustainable energy and stringent climate policies has underscored the need for decarbonizing energy systems, electrifying transportation, and transforming supply chains. In this context, China’s new energy vehicle (NEV) industry, as the largest global producer and consumer of automobiles, is pivotal in advancing energy substitution and achieving carbon reduction goals. This study investigates the energy efficiency and supply chain transformation within China’s NEV sector, leveraging panel data from 12 representative provinces over the period 2017–2023. Employing a robust analytical framework that integrates the DEA-BCC model, Malmquist index, and Tobit regression, the study provides a dynamic and regionally differentiated assessment of NEV industry efficiency. The results reveal significant improvements in total factor energy efficiency, predominantly driven by technological progress. R&D intensity, infrastructure development, and environmental regulation are identified as key enablers of efficiency, while excessive government intervention tends to hinder performance. The findings offer valuable empirical insights and policy recommendations for optimizing China’s NEV industry in the context of energy system transformation and sustainable industrial development. Full article

This study examines the impact of sociodemographic factors on the attitudes of EU citizens towards animal welfare and their implications for trade policy. Variations in animal welfare legislation across major commercial blocks create ethical and economic challenges, with the EU implementing stringent standards compared with other countries. Data were drawn from the Special Eurobarometer 533 survey, conducted between the 3rd and 26th March 2023, which employed a multistage, clustered sampling method across all 27 EU Member States, yielding a representative sample of 26,368 respondents. The survey collected detailed information on attitudes toward animal welfare alongside sociodemographic characteristics. The results revealed substantial public support for stricter regulations and informative labelling, with attitudes differing with age (p < 0.001), education (p < 0.001), income (p < 0.001), and political orientation (p < 0.001), according to the multinomial regression applied to each of the independent variables. These results emphasise the importance of these factors in shaping consumer expectations. The findings highlight the need for policymakers to integrate ethical and societal values into trade negotiations, ensuring that policies reflect public concerns, promote fair competition, and encourage higher animal welfare standards internationally. Additionally, understanding the perspectives and motivations of livestock industry stakeholders remains critical for implementing effective welfare strategies. By aligning EU trade policy with citizen values and stakeholder practices, it is possible to advance animal welfare globally while balancing economic and ethical considerations and promoting a fair trade. Full article

With the acceleration of urbanization in China, air pollution is becoming increasingly serious, especially PM_2.5 pollution, which poses a significant threat to public health. The study employed different deep learning models, including recurrent neural network (RNN), artificial neural network (ANN), convolutional Neural Network (CNN), bidirectional Long Short-Term Memory (BiLSTM), Transformer, and novel hybrid interpretable CNN–BiLSTM–Transformer architectures for forecasting daily PM_2.5 concentrations on the integrated dataset. The dataset of meteorological factors and atmospheric pollutants in Qingdao City was used as input features for the model. Among the models tested, the hybrid CNN–BiLSTM–Transformer model achieved the highest prediction accuracy by extracting local features, capturing temporal dependencies in both directions, and enhancing global pattern and key information, with low root Mean Square Error (RMSE) (5.4236 μg/m³), low mean absolute error (MAE) (4.0220 μg/m³), low mean absolute percentage error (MAPE) (22.7791%) and high correlation coefficient (R) (0.9743) values. Shapley additive explanations (SHAP) analysis further revealed that PM₁₀, CO, mean atmospheric temperature, O_3, and SO₂ are the key influencing factors of PM_2.5. This study provides a more comprehensive and multidimensional approach for predicting air pollution, and valuable insights for people’s health and policy makers. Full article

In urban design, public open spaces (POS) are essential for enhancing health and well-being across the lifetime. High-quality public open spaces facilitate the maintenance of optimal physical and mental health in older individuals by encouraging activities like physical exercise and social engagement. Preserving the physical and mental well-being of elderly individuals is a fundamental concern for aging policy. Nevertheless, urbanization presents considerable problems with the provision of public open spaces for activities aimed at the elderly. South Korea has more significant issues than other nations globally. This study, based on data from 477 valid questionnaires collected in and around Tapgol Park in Jung-gu, Seoul, employed a decision tree approach to identify key factors and paths that influence overall satisfaction. The goal was to identify decision paths that improve satisfaction while ensuring interpretability, thereby providing a scientific basis for urban space design and renovation. The results show that: (1) The decision tree of this study presents a hierarchical logic of quietness first, then accessibility and cleanliness, and finally price and vitality, which is consistent with the high frequency of use of Tapgol Park by the elderly and the diverse facilities in the surrounding area. (2) The key to improving the management and satisfaction of Tapgol Park in Seoul is the quietness of the site. (3) When the park is not quiet, users are most sensitive to bottom-line factors, such as commercial supply, evacuation safety, transportation accessibility, price perception, barrier-free, and anti-slips. (4) When the park is quiet, basic comfort factors such as smooth walking, all-day opening, sunlight, and no odor constitute the minimum condition set for entering the comfort zone. (5) Water experience, waterfront accessibility, proximity to cultural resources, and moderate business and community-oriented leisure facilities are key plus points. Methodologically, this study is among the first to apply a decision tree approach to low-income elderly using a small public open space in a historic city center, clarifying the nonlinear and hierarchical relationships among environmental factors within these low-income elderly groups. This provides empirical support and reference for the aging-friendly urban space in world heritage cities and other historical and cultural cities. Full article

The nexus of rapid demographic transition and underdeveloped geriatric infrastructure poses a critical, yet understudied challenge in Sub-Saharan Africa (SSA). As global life expectancies rise, SSA’s older population is projected to triple by 2050, intensifying the need for sustainable age-friendly environments (AFEs) and robust healthy ageing interventions. Informal or family caregiving structures, while vital, are under strain from rapid urbanisation and shifting social dynamics, creating a compelling gap between need and provision. This expert viewpoint draws on the authors’ professional and scholarly experience regarding population ageing, AFEs, and healthy ageing to provide a comprehensive outlook on these issues in SSA. Selective literature searches were conducted in Google Scholar, Scopus and PubMed using targeted keywords and MESH terms, including “ageing in Africa”, “ageing in Sub-Saharan Africa”, “healthy ageing in Africa”, “healthy ageing in Sub-Saharan Africa”, “population ageing in Africa”, “population ageing in Sub-Saharan Africa”, “age-friendly environment in Africa”, and “age-friendly environment in Sub-Saharan Africa.” The authors argue that rapid population ageing in SSA is outpacing existing informal care arrangements, necessitating a strategic shift towards the development of age-friendly environments and more coordinated healthy ageing interventions to bridge the widening gap between demographic change and geriatric support systems. This paper underscores the necessity of proactive, evidence-based policy implementation to secure the well-being of SSA’s burgeoning older population. Full article

Driven by the dual imperatives of global energy transition and sustainable development goals, lithium-ion batteries, as critical energy storage carriers, have seen the assessment of their lifecycle reliability and durability become a core issue underpinning the sustainable operation of clean energy systems. Grounded in a multidimensional perspective of sustainable development, this study aims to establish a quantifiable and monitorable battery reliability evaluation framework to address the challenges to lifespan and performance sustainability faced by batteries under complex multi-stress coupled operating conditions. Lithium-ion batteries are widely used across various fields, making an accurate assessment of their reliability crucial. In this study, to evaluate the lifespan and reliability of lithium-ion batteries when operating in various coupling stress environments, a multi-stress collaborative accelerated model(MCAM) considering interaction is established. The model takes into account the principal stress effects and the interaction effects. The former is developed based on traditional acceleration models (such as the Arrhenius model), while the latter is constructed through the combination of exponential, power, and logarithmic functions. This study firstly considers the scale parameter of the Weibull distribution as an acceleration effect, and the relationship between characteristic life and stresses is explored through the synergistic action of primary and interaction effects. Subsequently, a multi-stress maximum likelihood estimation method that considers interaction effects is formulated, and the model parameters are estimated using the gradient descent algorithm. Finally, the validity of the proposed model is demonstrated through simulation, and numerical examples on lithium-ion batteries demonstrate that accurate lifetime prediction is enabled by the MCAM, with test duration, cost, and resource consumption significantly reduced. This study not only provides a scientific quantitative tool for advancing the sustainability assessment of battery systems, but also offers methodological support for relevant policy formulation, industry standard optimization, and full lifecycle management, thereby contributing to the synergistic development of energy storage technology across the economic, environmental, and social dimensions of sustainability. Full article

This study presents a comprehensive decomposition analysis of waste-to-energy (WtE) in India through a systematic literature review (SLR) employing the PRISMA guidelines. The findings underscore the immense potential of WtE technologies in addressing India’s escalating municipal solid waste (MSW) generation amid rapid urbanization while simultaneously contributing to sustainable energy production and circular economy goals. The thematic analysis reveals four key themes: global trends in MSW generation, MSW as an alternative energy source, WtE approaches within a circular economy framework, and the impact of India’s urban expansion on MSW generation. Despite significant potential, India’s current WtE initiatives face substantial challenges, including inadequate waste segregation, policy gaps, public resistance, technological limitations, and insufficient financial investment. To effectively harness WtE technologies, strategic efforts must focus on robust policy implementation, indigenous technology advancement tailored to India’s waste characteristics, fostering public–private partnerships, and enhancing community engagement to mitigate public concerns. Future research should aim to quantify the economic, environmental, and social impacts of localized WtE interventions to guide scalable solutions. This study contributes valuable insights to policymakers, urban planners, and stakeholders aiming to transition India toward sustainable waste management and energy systems. Full article

In this study, we present Hierarchical Local Interpretable Model-agnostic Explanations (H-LIME), an innovative extension of the LIME technique that provides interpretable machine learning insights across multiple levels of data hierarchy. While traditional local explanation methods focus on instance-level attributions, they often overlook systemic patterns embedded within educational structures. To address this limitation, H-LIME aggregates local explanations across hierarchical layers, Institution Type, Location, and Educational Level, thereby linking individual predictions to broader, policy-relevant trends. We evaluate H-LIME on a student adaptability dataset using a Random Forest model chosen for its superior explanation stability (approximately 4.5 times more stable than Decision Trees). The framework uncovers consistent global predictors of adaptability, such as education level and class duration, while revealing subgroup-specific factors, including network type and financial condition, whose influence varies across hierarchical contexts. This work demonstrates the effectiveness of H-LIME at uncovering multi-level patterns in educational data and its potential for supporting targeted interventions, strategic planning, and evidence-based decision-making. Beyond education, the hierarchical approach offers a scalable solution for enhancing interpretability in domains where structured data relationships are essential. Full article

This study examines the structural evolution of Knowledge Innovation Networks (KINs) and Technology Innovation Networks (TINs) across Chinese cities (2015–2024). Using SCI/SSCI co-authorship and prefecture-level patent data, we construct dual-layer networks and assess their resilience through metrics such as average clustering coefficient, path length, global efficiency, and largest-component ratio. Our framework clarifies how network structure, spatial proximity, and urban hierarchy jointly shape innovation dynamics and opportunity distribution. Three main findings emerge. First, KINs have moved toward polycentricity yet remain hierarchically rigid, with persistent core–periphery gaps despite improved connectivity in tier 2–4 cities. TINs show greater cross-tier adaptability, creating new innovation gateways while intensifying intra-tier polarization. Second, under simulated disruptions, KINs are vulnerable to targeted attacks and exhibit path-dependent degradation, whereas TINs maintain efficiency until a critical threshold, then collapse abruptly. Third, MRQAP analysis reveals that economic and geographic proximity facilitate collaboration in KIN but constrain linkages in TINs, with spatial proximity exerting a stronger influence on knowledge flows. These results demonstrate how innovation networks mediate urban–rural interactions, affect spatial inequality, and shape regional resilience. We argue for differentiated policies that strengthen core–periphery connectivity while mitigating proximity-induced lock-in, fostering more inclusive, resilient, and sustainable urban innovation systems. Full article

Digital economy has profoundly reshaped the global trade landscape, yet its implications for agricultural trade, particularly in major agricultural trading countries, remain relatively underexplored. Using provincial panel data from China covering the period from 2013 to 2023, this study investigates whether digital economy development in China’s agricultural trade generates a digital dividend or instead exacerbates a digital divide. We construct a unified analytical framework and employ two-way fixed-effects models to identify the effects and underlying mechanisms. The results indicate that digital economy development significantly enhances overall agricultural trade performance. Mechanism analyses further show that this effect operates primarily through improvements in agricultural total factor productivity and the upgrading of rural human capital. Notably, the trade-enhancing effects of the digital economy exhibit pronounced regional heterogeneity. These effects are concentrated mainly in eastern and northern regions and are substantially stronger in non-grain-producing areas, while remaining statistically insignificant in central and western regions. This study contributes to the literature by providing a regionally differentiated assessment of the relationship between the digital economy and agricultural trade. It also offers policy implications for narrowing the digital divide through coordinated investments in digital infrastructure, productivity enhancement, and human capital accumulation. Full article

With global energy systems shifting toward sustainable solutions, Dubai faces the challenge of meeting rising energy needs while minimizing environmental impacts. This study explores long-term (LT) strategic planning for Dubai’s power sector through a techno-environmental–economic lens. Using PLEXOS^® modelling software (Version 9.20.0001) and official data from Dubai’s main utility provider, a comprehensive model examines medium- and LT energy pathways. The analysis identifies solar photovoltaic (PV) technology as central to achieving Dubai’s goal of 100% clean energy by 2050. It also highlights the need to cut emissions from natural gas (NG) infrastructure, targeting a goal of 14.5% retirement of NG energy generation capacities by the mid-century. Achieving zero-emission goals will require complementary technologies such as carbon capture (CC), nuclear energy, and energy storage as part of a broader decarbonization strategy. This study further assesses the economic effects of climate policy, showing that moderate carbon pricing could increase the Levelized Cost of Energy (LCOE) by an average of 6% across the forecast horizon. These findings offer valuable guidance for decision-makers and stakeholders, particularly the Dubai Electricity and Water Authority (DEWA), in advancing a carbon-neutral energy system. By 2050, Dubai’s total installed generation capacity is projected to reach 53.3 GW, reflecting the scale of transformation needed to meet its clean energy ambitions. Full article

Understanding the forces that shape farmland rental prices in major agricultural regions such as the U.S. Corn Belt is essential for evaluating the economic and environmental resilience of agricultural regions. This study develops an integrated framework that combines spatial modelling with uncertainty-aware spatial analysis to examine how macroeconomic conditions influence rental dynamics across the core Corn Belt. Using geographically weighted regression, the analysis captures spatial variation in the sensitivity of rental prices to oil prices, interest rates, and economic activity, revealing substantial geographic heterogeneity in macroeconomic exposure. The results reveal pronounced spatial heterogeneity in rental price responses, with geographically weighted models consistently outperforming global linear specifications. Despite strong spatial variation in rental sensitivities, neither prediction uncertainty nor maize yield volatility displays a clear regional pattern, indicating that production stability and model reliability are highly localised. By linking spatially varying rent sensitivities with indicators of economic pressure and production instability, this study provides new insights into agricultural sustainability risk. The findings highlight the importance of place-based policy and region-specific risk management under increasing macroeconomic volatility. Full article

Public open spaces play a vital role in supporting social connection and leisure among residents, enhancing quality of life while contributing to both economic growth and environmental health. The rapid global urbanization underscores the critical link between urban environments and human health, which demands focusing on sustainable, health-conscious urban planning. Accordingly, Public and green spaces are vital in this context, as recognized by global agendas like the Sustainable Development Goals (SDG) 11.7. This research aims to objectively evaluate the availability of public open spaces (POS) in Alexandria, Egypt. This study will utilize Geographic Information System (GIS) to formulate a methodology that incorporates spatial data analysis for quantifying public open spaces and assessing the proportion of the population with convenient access to these areas, evaluating their coverage, service area isochrones, spatial distribution, and proximity to residential areas. The study will benchmark its findings against global standards to expose critical spatial inequalities within cities of the Global South. The primary aim is to present evidence-based recommendations for sustainable urban public space design, tackling availability and accessibility issues to improve the well-being of Alexandria’s expanding urban population. This research offers a scientific foundation to inform policy and decision-making focused on creating more equitable, healthier, and resilient urban environments. Full article