Search Results (1,225)

Urban green spaces are increasingly recognized as key elements of sustainable urban development; however, their economic implications, particularly for labor productivity, remain underexplored in developing countries. This study examines the impact of urban green spaces on labor productivity across 92 Indonesian cities over the period 2014–2024, while accounting for spatial dependence and dynamic effects. Urban green space is measured using the Normalized Difference Vegetation Index (NDVI), and labor productivity is defined as the ratio of regional economic output to employment. The analysis incorporates control variables including life expectancy, environmental quality (AOD), average years of schooling, and GDP per capita. To address spatial and temporal dynamics, this study employs a Spatial Dynamic Panel Data (SDPD) framework. The results show that urban green spaces have a positive and significant effect on labor productivity. In addition, spatial spillover effects are evident, indicating that productivity in one city is influenced by conditions in neighboring areas. Socio-economic factors, particularly health, education, and economic development, also play a significant role. These findings highlight the economic relevance of urban green infrastructure and underscore the importance of integrating environmental considerations into urban policy to enhance productivity in developing country contexts. Full article

The rapid integration of artificial intelligence (AI) into educational systems is transforming how student performance is analysed and how educational policies are informed by large-scale data. Within this context, machine learning techniques are increasingly used to identify patterns associated with academic success and educational inequality. However, the use of predictive algorithms in education also raises important questions regarding transparency, fairness, and potential algorithmic bias. This study examines the predictive performance and fairness implications of machine learning models used to identify academically resilient students using data from the Programme for International Student Assessment (PISA) 2022. The analysis is based on a dataset containing more than 600,000 student observations across multiple national education systems. Academic resilience is operationalised following the OECD framework, identifying students who belong to the lowest quartile of the socioeconomic status index (ESCS) within their country while simultaneously achieving mathematics performance in the top quartile (PV1MATH). A predictive framework incorporating six supervised learning algorithms—Logistic Regression, Random Forest, Gradient Boosting, XGBoost, LightGBM, and CatBoost—was implemented. The modelling pipeline includes data preprocessing, missing value imputation, class imbalance correction using SMOTE, and model evaluation through multiple classification metrics, including accuracy, F1-score, and the area under the ROC curve (AUC). In addition, fairness diagnostics are conducted to examine potential disparities in prediction outcomes across gender groups, while feature importance analysis and SHAP-based explanations are used to interpret the contribution of key predictors. The results indicate that ensemble-based models achieve the highest predictive performance, particularly those based on gradient boosting techniques. At the same time, the analysis reveals that socioeconomic status, migration background, and school repetition constitute the most influential predictors of academic resilience. Although gender displays relatively low predictive importance, measurable differences in positive prediction rates across gender groups suggest the presence of potential algorithmic disparities. These findings highlight the importance of integrating fairness evaluation, transparency, and interpretability into educational data science workflows. The study contributes to ongoing discussions on the responsible use of artificial intelligence in education by emphasising the need for governance frameworks capable of ensuring that algorithmic systems support equity-oriented educational policies. Full article

This study proposes an integrated analytical framework (IAF) as a tool to simultaneously assess vulnerable social groups within their administrative context. This study hypothesizes that analyzing vulnerable groups through socio-spatial delineation reveals subnational disparities and sub-regional heterogeneity in energy poverty (EP) indicators, associated with additional context-sensitive environmental consequences of energy use. Using Hungarian deprived rural settlements (DRSs) (n = 300) as an example, mixed methods were applied to examine national–regional disparities, intra-regional variations, and the environmental implications of extreme household energy use practices. Results show that both socio-economic indicators and building energy efficiency, and energy-use profiles, fall short of national indicator performance. The sample outlined by the IAF performed homogeneously regarding socio-economic circumstances and showed mild differences in housing quality and energy access. These results indicate not structural differences but variation in underlying regional drivers, highlighting the region-specific manifestation of EP. The energy-use-related environmental assessment was performed using a parametrized building-stock model and the two most extreme energy-use scenarios for households relying on solid fuels. The results suggest that the use of substitute fuels substantially increases the combined emissions of CO₂, CO, PM, NOx, and SOx by up to 32 percentage points. Although limitations constrain the reporting of empirically representative results, findings underscore the potential policy relevance of DRSs in national climate objectives. Full article

Introduction: Increasing rates of youth suicide are a growing concern worldwide. The single highest risk factor for suicide is a prior suicide attempt; however, knowledge around the broader factors that may increase the likelihood of the initial suicide attempt is limited. Understanding these risk factors is critical for clinicians to inform the development of early intervention strategies. This study examines the characteristics of a specific cohort of young people attending a tertiary mental health service in Melbourne, Victoria, following a suicide attempt or with persistent suicidal ideation. Method: A file audit of all young people attending the service was conducted from the commencement of the new service in 2022 through to the end of 2024. One hundred and seventy-one files were examined for specific data, including items such as age, gender, gender diversity, socio-economic factors and neurodivergence. Results: One-sample z proportion tests showed significantly higher proportions of young people who were LGBTIQIA+, transgender, gender diverse or non-binary (TGDNB), neurodivergent, not engaged in employment, education or training (NEET), and international students in the clinical cohort compared with the Australian population. Almost one-fifth of the cohort reported a history of trauma. Discussion: The study provides insight into characteristics observed among a cohort of suicidal young people. Findings highlight that young people from several marginalised groups were more frequently observed in this clinical cohort. The findings have implications for youth mental health services, supporting earlier identification of potential factors associated with suicidality so that prevention strategies can be implemented in a timely manner. Full article

In order to reach net-zero by 2050, we need to have strong decarbonization policies, especially in hard-to-abate clean-ups like steel (8% of the global emissions), cement (7%), and power generation (30%), and negative emissions through direct air capture (DAC) and bioenergy with carbon capture and storage (BECCS). This review paper summarizes the progress in CO₂ capture, compression, transportation, and storage technologies between 2020 and 2025, including energy penalty (20–40%) and cost (15–30%) reductions, with innovations such as metal–organic frameworks (MOFs), bio-inspired catalysts, ionic liquids, and artificial intelligence (AI)-based optimization. This paper, as a new input into the carbon capture and storage (CCS) field, uses the Weighted Sum Model (WSM) as a multi-criteria decision-making tool to rank the best technologies in the capture, storage, monitoring, and transportation sectors. The weights of the criteria are calculated based on Shannon entropy, and the assessment is performed in three conditions, namely, optimistic, pessimistic, and expected. The weights are computed with sensitivity analysis to make the assessment robust. The viability of key projects, such as Northern Lights (Norway, 1.5 MtCO₂/year), Porthos (The Netherlands, 2.5 MtCO₂/year), Quest (Canada, 1 MtCO₂/year), and Petra Nova (USA, 1.6 MtCO₂/year), is evident, and it is projected that, globally, CCS will reach 49 MtCO₂/year across 43 plants in 2025. The review incorporates socio-economic and environmental justice, including barriers such as high costs ($30–600/MtCO₂), energy penalties (1–10 GJ/tCO₂), and opposition between people (20–40% in EU/US). In comparison with previous reviews, this article has a more comprehensive focus, provides quantitative synthesis through WSM, and discusses the implications for researchers, policymakers, and stakeholders towards achieving faster CCS implementation on the path to net-zero. Full article

Background: Obesity remains a major public health challenge, with central and visceral fat distribution conferring particularly high cardiometabolic risk. Lifestyle factors, including diet, physical activity, and sleep quality, have been implicated in adiposity, yet their combined and interactive effects in working populations remain insufficiently characterized. Methods: We conducted a cross-sectional study in 88,343 Spanish employees (53,122 men, 35,221 women) attending occupational health examinations between 2021 and 2024. Obesity was assessed using four complementary indices: body mass index (BMI), waist-to-height ratio (WHtR), Clínica Universidad de Navarra–Body Adiposity Estimator (CUN-BAE), and Metabolic Score for Visceral Fat (METS-VF). Lifestyle factors included sleep quality (Pittsburgh Sleep Quality Index), Mediterranean diet adherence (MEDAS), and physical activity (IPAQ). Multivariable logistic regression models were adjusted for sociodemographic and lifestyle variables, with interaction, stratified, joint exposure, and dose–response analyses. Results: Obesity prevalence varied widely by index, ranging from 18.9% (BMI) to 55.6% (CUN-BAE). Poor sleep quality was independently associated with higher odds of obesity across all indices, particularly central obesity (WHtR OR 1.58, 95% CI 1.48–1.69), with stronger associations observed in women. Physical inactivity and non-adherence to the Mediterranean diet were robust predictors, with inactivity showing the largest effect sizes (METS-VF OR 9.92, 95% CI 8.70–11.15). Interaction analyses indicated that both Mediterranean diet adherence and regular physical activity attenuated the adverse association between poor sleep and obesity outcomes. Restricted cubic spline models revealed a progressive dose–response relationship between increasing PSQI score and central obesity. Joint exposure analyses showed nearly five-fold higher odds of central obesity among workers with concurrent poor sleep, physical inactivity, and low Mediterranean diet adherence. A graded inverse association was observed between a composite healthy lifestyle score (0–3) and obesity, with a score of 3 associated with 72–75% lower odds of BMI-obesity and WHtR-high. Conclusions: In this large occupational cohort, poor sleep quality, physical inactivity, and low Mediterranean diet adherence emerged as independent and combined determinants of general, central, and visceral obesity. Integrated workplace strategies promoting sleep hygiene, physical activity, and dietary quality—particularly among women and lower socioeconomic groups—may represent an effective approach to reducing obesity risk in working populations. Full article

Inland ports play a strategic role in enhancing multimodal connectivity and promoting sustainable freight transport within European corridors. However, the drivers of inland port development remain insufficiently understood, particularly with respect to nonlinear dynamics, interaction effects, and regional heterogeneity. This study investigates the socio-economic, infrastructural, and spatial determinants of inland port throughput using an interpretable machine learning framework. An XGBoost model is built up to estimate eighteen ports’ throughput along the Romanian Danube, over the period 2010–2024. SHAP (Shapley Additive Explanations) values are employed to quantify global importance, nonlinear marginal effects, and interaction structures. Results show that spatial accessibility and road infrastructure are the most influential drivers, while economic sectoral structure and road infrastructure exert nonlinear and scale-dependent effects. Interaction analysis reveals that inland port development is synergy-driven rather than additive, with the strongest complementarities observed between spatial accessibility, multimodal infrastructure, and sectoral structure. Additionally, Kruskal–Wallis tests on SHAP contributions indicate significant heterogeneity across port administrations, suggesting that governance and regional context modulate the realization of economic and infrastructural potential. The findings contribute to port–hinterland interaction analysis by demonstrating that inland port performance emerges from multi-scale, nonlinear, and regionally mediated dynamics. Methodologically, the study illustrates the value of interpretable machine learning for transport systems research. Policy implications emphasize coordinated multimodal investments, accessibility enhancement, and region-specific development strategies to strengthen inland waterway integration within the European transport sector. Full article

Urban agriculture (UA) is closely linked to urban development. It serves as an effective strategy for promoting sustainable urban development. However, existing research on urban agriculture theory offers only a limited multidimensional review of its theoretical development. This paper aims to trace the developmental trajectory of representative urban agriculture theories and provide subsequent researchers with a comprehensive theoretical foundation in the field. Methodologically, this study employs a literature review and structured qualitative comparative analysis, combined with a chronological approach, to analyse representative theories of UA. Concurrently, an analytical framework comprising four dimensions—ecological, socio-economic, technological and design, and spatial relations—has been established, with four evaluation indicators defined for each dimension. This study reviews and compares representative theories across different historical periods to address two research questions: the evolution of UA theories across different historical periods, and the commonalities and differences among various theories across the four dimensions. Through this analysis, the paper discusses the commonalities, differences, and practical implications of different UA theories across each dimension. The research indicates that the ecological dimension forms the foundation of most theories. The spatial relations dimension demonstrates the spatial value of different theories. The design and technological innovation dimension reflects the connection between theory and urban development. The socio-economic dimension highlights the growing attention to UA. Chronological analysis reveals the evolution of UA theories, from the 19th-century concept of integrating agriculture into cities to the mid-to-late 20th-century idea of urban-agricultural coexistence, and finally to the diverse theoretical approaches of the 21st century. This study not only provides a comprehensive review of the development of UA theories but also offers scientific guidance for future practice and research in UA. Full article

Winter tourism is increasingly influenced by changing socio-demographic dynamics, climate change, and evolving leisure preferences. While prior research has examined winter tourist motivations, sustainability strategies and climate change adoption, less attention has been paid to differences between urban and rural residents in their attitudes toward domestic winter leisure tourism. This study addresses this gap by exploring variations in participation patterns, service evaluations, and overall tourism experiences among urban and rural Bulgarian residents. Drawing on a quantitative survey of urban and rural residents (n = 1003), the research systematizes the general characteristics of domestic winter leisure tourism practices and evaluates key tourism service dimensions, including accessibility, accommodation, pricing, infrastructure, and environmental quality. Descriptive statistics and inferential analyses were applied to identify statistically significant differences between groups. The findings reveal distinct behavioural and perceptual patterns: urban residents demonstrate higher participation frequency and place greater emphasis on service quality and diversified amenities, whereas rural residents show stronger sensitivity to pricing and accessibility factors. Differences are also observed in the overall evaluation of the tourism experience, reflecting structural and socio-economic disparities. The study contributes to winter tourism literature by integrating spatial residence into the analysis of domestic tourism demand and experience assessment. The results provide practical implications for destination managers and policymakers seeking to design differentiated marketing strategies and improve service provision in line with the needs of diverse domestic segments. Full article

Background/Objectives: The increasing prevalence of foot and ankle procedures in the United States has coincided with rising costs of care, exposing socioeconomic disparities within this area of orthopedics. Insurance payor status is one such factor that can affect the quality and accessibility of medical care and has been implicated in orthopaedic patient outcomes. While previous studies in other fields of orthopaedics have demonstrated an association between insurance status and access to treatment, length of hospital stay, post-operative outcomes and complication rates, no comprehensive review has yet explored this relationship in foot and ankle surgery. Thus, the goal of this study is to examine the association between insurance payor status and outcomes in foot and ankle procedures. Methods: A systematic review of five databases was conducted, focusing on the interplay between insurance coverage and foot/ankle procedures. Included studies reported on insurance payor status and patient outcomes following foot and ankle surgery. Extracted outcomes included time to be seen by a provider, complication and revision rates, post-operative Emergency Department (ED)/Urgent Care utilization, readmission rates, hospital length of stay, pain, functional scores, discharge destinations, return to work/activity, and follow-up. Meta-analyses were performed using the Revman 5.3 software. Studies that did not qualify for meta-analyses were described qualitatively. Results: Of 1401 studies identified, 24 texts met inclusion and exclusion criteria. Across the 24 studies, there were a total of 20,950 patients. Noninsured patients had a 59% higher risk of ED/urgent care utilization within 30 days of surgery compared to insured patients [Risk Ratio (RR) = 1.59, 95% Confidence Interval (CI) = 1.18 to 2.12, p < 0.05]. Privately insured patients were seen 3.65 days earlier than patients with government insurance [95% CI = 2.02 to 5.27, p < 0.0001]. Worker’s Compensation patients had statistically significant findings for poorer outcomes, higher pain scores, and lower functional scores. Similarly, Medicaid patients also fared worse on functional scores and had delayed access to appointments and treatments. Conclusions: Patients without private insurance have worse pain and functional outcomes, delayed access to care, and increased utilization of emergency resources following foot and ankle procedures. It is crucial for providers to be cognizant of these discrepancies when caring for patients. Further research is needed to better understand the nuances of these insurance-related disparities within foot and ankle subspecialties. Full article

Vegetation net primary productivity (NPP) is a key indicator of ecosystem functioning in tropical rainforests and has important implications for carbon cycling and ecosystem stability. Examining the spatial and temporal variation in vegetation NPP and the factors associated with it can help inform ecosystem management and responses to climate change. In this study, Hainan Tropical Rainforest National Park (HTR), China, was selected as a representative tropical rainforest ecosystem. MODIS NPP data, Landsat imagery, meteorological variables, topographic factors, soil data, and socioeconomic indicators were integrated to analyze the spatiotemporal evolution of vegetation NPP from 2000 to 2023. The Theil–Sen Median trend analysis and Mann–Kendall test were applied to detect temporal trends, while the Optimal Parameter Geographical Detector (OPGD) model was used to identify dominant driving factors and their nonlinear interactions. The results showed that vegetation NPP in HTR exhibited an overall increasing trend during the study period, although short-term fluctuations occurred. Spatially, NPP was higher in the west and south and lower in the east and north. Elevation, soil type, and land use type were the main variables associated with this pattern. Moreover, interactions between natural and human-related factors accounted for more of the spatial variation in NPP than individual factors considered separately. These findings improve the understanding of vegetation productivity dynamics in tropical rainforest ecosystems and provide scientific insights for carbon sequestration enhancement, ecological conservation, and sustainable ecosystem management in tropical rainforests under global climate change. Full article

College dropout is a global challenge due to its high prevalence and its consequences for individuals, institutions, and society, particularly in terms of institutional sustainability, inefficient use of public resources, and human capital loss. This issue is especially salient in engineering, where first-year dropout rates remain high. This study examines factors associated with first-year dropout among engineering students at a Chilean public university, framing dropout as a sustainability challenge for higher education systems. The analysis combines administrative records ($n=825$) with survey data on psychosocial variables ($n=417$). Results show that admission to a first-choice program and early performance are strongly associated with persistence, highlighting admission alignment and early university experience as factors contributing to the sustainable use of institutional resources. Despite equivalent academic performance across genders, a marked discrepancy emerged between students’ high self-reported confidence and limited implementation of learning strategies. Cluster analysis identified a clear performance gradient across socio-educational profiles, with students combining high academic capital, low socioeconomic vulnerability, and first-choice admission showing the most favorable outcomes. These findings underscore the relevance of admission preference, trajectories, and socio-educational context for first-year persistence, with implications for institutional sustainability and the consolidation of human capital in engineering education. Full article

Government funding programs administered by the Australian Research Council (ARC) aim to advance national research priorities while generating scholarly and socio-economic impact. This study employs a descriptive bibliometric benchmarking approach to examine the relationship between funding levels and scholarly output for publications explicitly acknowledging ARC support. Using project-level funding data linked with journal articles published between 2009 and 2016, we analyze 10,565 ARC-funded projects receiving a total of AUD 4.6 billion and producing 54,639 journal publications. On average, each project received approximately AUD 437,720 and generated five publications, corresponding to a cost of about AUD 84,700 per article. We compare research productivity, citation impact, and return on investment across ARC Discovery and Linkage programs, as well as between STEM and HASS disciplines. The results reveal no strong correlation between funding amount and either publication volume or citation impact across ARC programs. STEM projects generally exhibit higher returns on investment and citation impact; however, a subset of HASS projects achieves exceptionally high efficiency relative to funding received. Notably, projects funded below AUD 100,000 demonstrate the highest return on investment in terms of both publication productivity and normalized citation impact. These findings suggest that smaller grants can yield disproportionately high scholarly returns, offering important implications for research funding allocation, efficiency evaluation, and performance assessment in public research systems. Full article

Background: Mindful eating strategies have shown promise in addressing obesity and food insecurity among children. However, limited research has examined the acceptability of mindful eating programs among low-socioeconomic families in rural areas. This study evaluated caregivers’ and teachers’ acceptability and satisfaction with a 14-week, school-based mindful eating program for preschoolers to inform future implementation. The program effectively improved home eating environment, household food insecurity, and child body mass index. Methods: A convergent parallel mixed methods study design was used to evaluate the 14-week mindful eating intervention among 200 preschoolers from 26 Head Start classrooms in rural Michigan, United States. After intervention completion, acceptability and satisfaction data were collected and assessed from 192 caregivers and 23 classroom teachers via (1) quantitative online survey data analyzed using descriptive statistics, and (2) qualitative data from individual interviews completed with a subset of parents and teachers that were analyzed with thematic analysis. Results: Both quantitative and qualitative data showed high acceptability and satisfaction. Caregivers (survey: 88.9%, interview: 94.1%) and teachers (survey: 87.0%, interview: 100%) were satisfied with the program. Teachers (survey: 82.6%, interview: 87.5%) agreed the program improved children’s eating behaviors. Most surveyed caregivers (81.1%) agreed the completion of child letters sent home after the program session helped caregiver–child communication. Several barriers and suggestions for implementation were also identified by interviewed teachers and caregivers, including the limited availability of specific fruits and vegetables in local areas, concerns about preschoolers’ comprehension of curriculum, and recommendations on improving recruitment strategies. Conclusions: This study highlighted the high acceptability and satisfaction of a mindful eating program among caregivers and classroom teachers. The findings offered implications for future interventions to integrate mindful eating programs into early childcare organizations to help address child obesity and food insecurity. Future research exploring nutrition-related policies to sustain implementation of mindful eating programs is needed. Clinical Trial Registration: The clinical trial was registered at ClinicalTrials.gov (NCT05780008) on 27 February 2023. Full article

Background/Objectives: Dietary supplements (DSs) are widely available on the pharmaceutical market. Their consumption frequency has been observed to increase over the years, especially with age. To the best of our knowledge, this is the first study in Poland and Central-Eastern Europe to analyze the use of dietary supplements (DSs) based on a nationally representative, random sample of the elderly population. Methods: We examined 5987 individuals aged 60 years and older to assess the prevalence and types of DSs they use, with particular attention to socio-economic factors associated with their consumption. It also aimed to determine whose recommendations were followed when choosing supplements. Results: The percentage of individuals taking any DSs was 32.1% (95% CI: 29.8–34.4), with a higher proportion among women (38.7% (95% CI: 35.7–41.7)) compared to men (22.8% (95% CI: 20.6–25.1)). A multivariable analysis showed that DSs were more likely to be used by individuals with higher education (Prevalence Ratio (PR) 1.74 (95% CI: 1.47–2.06) for individuals with higher education vs. those with primary education). A link between age and DSs consumption was also observed, with the highest consumption rates found among those in their 80s (PR 1.46 (95% CI: 1.30–1.63) vs. the 60–69 age group). The most commonly used ingredients were vitamins, taken by 76.2% (95% CI: 73.6–78.9) of respondents, minerals (55.9% (95% CI: 52.8–59)), and plant-based preparations (45.0% (95% CI: 42–48)). Although DSs were most often used based on a doctor’s recommendation (58.5% (95% CI: 54.5–62.6)), over a third of patients initiated their use independently. Conclusions: This significant proportion of individuals taking dietary supplements in Poland, often without consultation with healthcare professionals, suggests that these products may be used in the absence of objective indications, which may be associated with adverse effects and potential drug–supplement interactions. This represents an important implication for clinicians, who should always extend the medical history to include information on DSs use. The findings also highlight the need to strengthen regulatory frameworks to ensure the safe use of these products and to optimally protect the health of older adults. Full article