Search Results (2,383)

This study forecasts inbound tourism demand for the United Kingdom, using monthly data from February 1989 to February 2020. In the empirical analysis, we evaluate and compare the performance of five machine learning models (decision trees, random forests, XGBoost, and support vector regression with the RBF and linear kernels) against a more traditional linear SARIMA regression model. Forecasting performance metrics included MSE, RMSE, MAE, R², and MAPE. The SVR RBF kernel model achieves the highest accuracy, with an MAPE of 0.014% on the training set. To enhance model interpretability, feature importance analysis is applied to identify the most influential predictors of tourist arrivals. This research offers significant policy implications, aiding government policymakers and private industry stakeholders in optimizing their planning and decisions, deploying better long-term business strategies and tourism-related services, and optimizing the allocation of public and private resources to support the tourism sector. Full article

Indonesia has identified clean hydrogen as one of the strategic initiatives for its energy transition, recognizing its potential as an energy carrier that can support the achievement of net zero emissions. To deepen the understanding of this emerging technology, this study assesses the readiness of green hydrogen development in Indonesia through a multi-stakeholder perspective combined with a technology readiness evaluation and insights from global developments. Based on stakeholder interviews across government, industry, academia, and energy institutions, this analysis identifies key enabling conditions and barriers for hydrogen deployment in the Indonesian context. This analysis indicates that the readiness level of green hydrogen technology in Indonesia has reached approximately technology readiness level (TRL) 5–TRL 6, suggesting that most initiatives remain at the pilot and demonstration stages. In addition, seven key factors influencing green hydrogen adoption were identified: infrastructure and technology, policy and regulation, finance, application sectors, public acceptance, standardization, and private sector participation. These results provide policy-relevant insights for accelerating hydrogen development and highlight priority areas for advancing Indonesia’s transition toward a low-carbon energy system. Full article

Iodine is an essential micronutrient required for the synthesis of thyroid hormones and the maintenance of metabolic, neurodevelopmental and immune function. As iodine cannot be synthesized endogenously, adequate intake depends on dietary sources and environmental availability. Despite decades of progress in improving iodine supply, both iodine deficiency and excess remain significant global public health challenges. This review summarizes iodine physiology, covering both its role in thyroid hormone synthesis and emerging evidence for extrathyroidal immunomodulatory and antioxidant actions. It summarizes major dietary sources, global intake patterns and current approaches to iodine status assessment, including urinary biomarkers, salivary iodide measurement and dietary screening tools. The clinical consequences of iodine imbalance are examined, ranging from goiter, hypothyroidism and impaired neurocognitive development associated with deficiency, to iodine-induced thyroid dysfunction, autoimmunity and adverse systemic effects linked to excess intake. Special attention is given to vulnerable populations, particularly pregnant women and infants. This review further evaluates public health strategies, including salt iodization and targeted supplementation, while addressing the emerging challenge posed by salt-reduction initiatives. Achieving optimal iodine intake remains essential for thyroid health and population well-being, underscoring the need for coordinated monitoring and policy adaptation. Full article

Worldwide, hypertension is a major risk factor for stroke and cardiovascular diseases, creating serious public health issues. This study aimed to evaluate the risk factors and the prevalence of hypertension in a community in South Africa. Between 2019 and 2023, an observational study with 1029 participants was carried out. The South African Hypertension Society hypertension guidelines were used to determine the prevalence of hypertension. Risk factors, such as anthropometric factors, socioeconomic factors, and lifestyle choices, were evaluated using univariate and multivariate logistic regression analysis. Within the total study population, the mean age was 48 years, and 81.1 percent of the participants were female. The mean blood pressure was 128/82.5 mmHg and 48.7% of the participants were obese. The prevalence of hypertension was 53.6%. Significant risk factors for hypertension included ageing, diabetes, having a higher body mass index, not having formal education, being unemployed, leading a sedentary lifestyle, and living in a rural area. The study highlights the increased prevalence of hypertension in this South African population. The findings were consistent with the current literature with regard to hypertension risk factors, such as age, body mass index, education, and physical activity. Current data highlights the need for focused health education and awareness initiatives that encourage healthy living. Improving healthcare access and addressing the socioeconomic factors should be the main goals of policy initiatives to lessen the impact of hypertension in underprivileged rural communities. Full article

Road traffic injuries represent one of the most critical public health challenges in the Gulf region. Predicting traffic accident severity is therefore a critical component of evidence-based road safety management. In this study, we develop machine learning frameworks for predicting traffic accident severity using Qatar’s national dataset (2020–2025), addressing extreme class imbalance and interpretability. A dataset of 588,023 accident records was systematically preprocessed from 1,000,500 raw reports. We compare three approaches: multi-class (four severity levels), binary (Safe vs. Severe), and cascaded two-stage (combining both). Six classifiers were evaluated across two encoding methods and three balancing strategies. Systematic hyperparameter tuning with 5-fold stratified cross-validation was performed for all models. The binary LightGBM classifier achieved BA = 71.04%, AUC-ROC = 0.772, Sensitivity = 61.03%, and Specificity = 81.05%, demonstrating superior performance over multi-class approaches. Temporal validation on 2025 data (trained on 2020–2024 data) supported good temporal generalization. Analysis of 10,000 test instances identified the time period as the dominant predictor of accident severity. The binary LightGBM framework provides an interpretable and effective approach for severe accident identification and risk prioritization, with SHAP findings supporting targeted temporal enforcement and pedestrian safety as evidence-based policy priorities. Full article

In the SARS-CoV-2 endemic phase, assessing the effectiveness of COVID-19 booster doses in children is essential for public health policy. This study evaluated the vaccine effectiveness (VE) of three doses (primary series plus booster) against severe outcomes, comparing the pandemic and endemic periods and children with and without comorbidities. We carried out a cohort study based on the population, utilizing comprehensive Brazilian data from individuals under 18 years of age with confirmed SARS-CoV-2 infection, spanning from February 2020 to June 2025. The primary exposure of interest was three or more doses of COVID-19 vaccines. The primary outcome of interest was COVID-19-related death. VE and the number needed to vaccinate (NNV) to prevent one death were estimated in a propensity score-matched cohort, with adjustments for confounders. Among 3,730,007 reported pediatric cases, 5472 (0.1%) died, 99% of whom did not receive a booster dose. During the pandemic, the VE against death was higher in children with comorbidities (92.7% [95% CI, 63.5–99.0]; NNV = 23 [19–30]) than in those without (68.2% [25.7–86.4]; NNV = 2000 [1111–9774]). During the endemic period, the VE against death remained high and was comparable between groups: 89.4% (29.8–98.7) and 75.8% (36.4–95.7) for children with and without comorbidities, respectively. Nevertheless, NNV levels were significantly lower in children with comorbidities, reflecting an increased risk at baseline. Although booster doses continue to offer substantial protection against fatal COVID-19 outcomes, the magnitude of this benefit is directly correlated with the baseline risk. Consequently, these findings support the implementation of risk-based prioritization strategies in public health decision-making for children. Full article

Air pollution forecasting is particularly challenging in basins with frequent winter seasons and temperature inversions. In this study, we developed and rigorously evaluated deep learning models to forecast PM₁₀ and the Air Quality Index (AQI) in Igdır, Türkiye, using a five-year, hourly dataset (2020–2024) from the Igdır/Central station (PM₁₀, NO₂, O₃, SO₂; meteorology: pressure, temperature, wind speed, relative humidity, precipitation, cloud cover). Using linear interpolation and Z-score normalization, sine/cosine features (hour, month) were used to encode temporal periodicity, and a 72-h lookback → 24-h look-ahead design was employed. LSTM, GRU, BiLSTM, and CNN-LSTM models were compared under a three-stage ablation (meteorology only; +cyclic encoders; +lagged targets), and their hyperparameters were tuned via Bayesian optimization. The deep learning results were further contextualized against a Multiple Linear Regression (MLR) baseline serving as a snapshot persistence model to evaluate the specific advantage of LSTM’s temporal memory in short-horizon forecasting. Multi-output forecasting is central to the proposed design, featuring a multi-task learning (MTL) framework based on a single shared temporal encoder with two task-specific regression heads that simultaneously predict PM₁₀ and AQI. Compared with separate single-task models, the multi-output setup exploits cross-target covariance (AQI’s dependence on pollutant loads under meteorology), improves data efficiency and generalization through shared representations, and promotes coherent, horizon-stable forecasts across targets, which is particularly valuable when winter stagnation regimes couple PM₁₀ and AQI dynamics. Moreover, this study introduces a structured ablation design to explicitly evaluate the added value of multi-output forecasting under inversion-dominated basin conditions. The results show stepwise gains from cyclic encoders and, most strongly, from lagged target histories. Under the optimized 24-h setting, LSTM performs best (R²_{PM₁₀} = 0.7989, RMSE = 48.74 µg/m³; R²_{AQI} = 0.6626, RMSE = 37.81), marginally surpassing GRU and clearly outperforming BiLSTM and CNN-LSTM. Horizon sensitivity confirms the benefit of nowcasting: when retrained for shorter horizons, LSTM attains R² = 0.9991 for PM₁₀ (MAE = 2.44; RMSE = 3.30 µg/m³) and 0.9535 for AQI (MAE = 4.87; RMSE = 14.03) at 1 h, and R² = 0.9792 (PM₁₀; MAE = 9.70; RMSE = 15.67) and 0.8849 (AQI; MAE = 11.19; RMSE = 22.08) at 6 h. Residual diagnostics reveal heteroskedastic, regime-dependent errors peaking near 0 °C and low winds, as well as a conservative bias that underpredicts extremes. Collectively, the findings show that multi-output, temporally aware deep models enable accurate operational forecasting in Igdır. The proposed framework provides real-time air quality alerts and daily planning, providing decision support for sustainable air quality management, public health protection, and evidence-based urban policy and is transferable to similar continental basin environments. Full article

As a new performance evaluation system, ESG has garnered significant goodwill and tax benefits for a set of benchmark enterprises through its forward-looking corporate values and overall enhancement of public trust. However, as more companies pay attention and invest more in ESG, the pursuit of these ratings also entails increasing costs. Whether the impressive upward trend in ESG ratings genuinely enriches and enhances a company’s reputation, or if the ratings driven by ESG costs are unsustainable over the long term, remains uncertain. In the pursuit of sustainable development, several enterprises may find themselves in a predicament where ESG ratings are on the rise while corporate performance is declining. This paper selects listed companies in China’s petrochemical industry, which exhibit the distinctive characteristics of ESG and corporate performance divergence, as its research sample. It aims to identify the quantitative features of this performance–ESG divergence dilemma and empirically uncover its causes and development pathways. The findings of this research will guide enterprises back to the path of ESG alignment, providing a theoretical foundation for ensuring that companies adhere to a high-quality ESG development path. Furthermore, it offers insights into addressing the gaps in the rating system behind the phenomenon of inflated ESG scores and presents policy-oriented perspectives to help enterprises avoid the pitfalls mentioned above. Full article

Objective: To quantify the gap between oral cancer disease burden and public awareness in Germany, and to characterize research dissemination patterns across social media platforms. Methods: We conducted a multi-dimensional analysis integrating: (1) Robert Koch Institut cancer registry data for oral and maxillofacial malignancies (ICD-10: C00–C06) from 2015 to 2023; (2) Google Trends search interest for cancer-related German terms; (3) Altmetric data for 2581 PubMed-indexed oral cancer publications; and (4) sentiment analysis of 10,308 social media posts. Age-standardized incidence rates were calculated using the European Standard Population. Results: Over the study period, 65,757 oral cavity cancer cases were registered. Google Trends analysis revealed a 64% attention deficit for “Mundkrebs” (oral cancer; mean: 17) compared to “Brustkrebs” (breast cancer; mean: 47). Case numbers declined from 7577 (2019) to 6870 (2023; −9.3%), while age-standardized rates decreased by 15.5% (11.6 to 9.8 per 100,000), with males disproportionately affected (−17.7%). Research dissemination was dominated by X/Twitter (86.2%), with minimal policy document (0.3%) or clinical guideline (0.3%) citations. Sentiment analysis revealed 77% positive public reception. Regional analysis identified an East–West divide, with Eastern German states showing 22% higher search interest. Conclusions: A substantial public awareness deficit exists for oral cancer in Germany, paradoxically widening during a period of declining diagnoses potentially associated with COVID-19-related diagnostic delays. The positive public sentiment toward oral cancer research suggests a favorable environment for targeted awareness campaigns, particularly in Western German states where search interest is lowest. These findings have practical implications for designing regionally tailored awareness campaigns prioritizing anatomically specific terminology. Future research should evaluate the effectiveness of such targeted interventions and assess whether post-pandemic diagnoses present at more advanced stages. Full article

The synergistic management of water resources, the water environment, and the water ecology system (“Three-waters” system) is fundamental to ensuring regional water security and advancing sustainable development. However, existing evaluation indicator systems rely on expert experience and lack quantitative screening criteria, leading to indicator overlap and insufficient representativeness, which restricts the scientificity of management decisions. The study proposes a method integrating meta-analysis with case verification to construct an indicator system. A systematic review of 60 publications (1970–2024) from the Web of Science was conducted and a random effects model was used to merge effect sizes and quantify correlations and heterogeneity between indicators and the “Three-waters” system. The results indicate that the industrial water use proportion (R = −0.77) is the main stress factor in the water resources system, the negative effect of total hardness (R = −0.91) is the most significant in the water environment system, the contribution of the benthic diversity index (R = 0.90) is the most prominent in the water ecology system and vegetation coverage (R = 0.74) exhibits a strong positive effect in the social economic system. The case verification confirms the indicator system established under this method is consistent with the actual situation. This study provides methodological support for system diagnosis, coordinated regulation, and policy formulation, promoting the transformation from single-element to systemic water management. Full article

Urban districts are increasingly exposed to overlapping heat stress and stormwater loads driven by warming trends, more intense rainfall, and continued growth of impervious surfaces. Pavements occupy a large share of the public right-of-way, so their material and structural design offers a scalable pathway for urban climate adaptation. Yet the literature on porous asphalt remains fragmented, with hydrological performance often assessed using infiltration or permeability metrics in isolation, while thermal studies frequently report surface cooling without consistently tracking the governing water budget or its persistence. To reconcile these disconnected strands, this review synthesizes a conceptual hydro-thermal balance framework in which runoff mitigation and heat moderation are treated as a coupled problem controlled by storage, drainage pathways, and evaporative demand. Within this framing, cooling is primarily water-limited: permeability enables wetting and redistribution, but the magnitude and duration of temperature reduction depend on how much water is retained near the surface and how long it remains available for evaporation, rather than on permeability alone. The review integrates the current understanding of mixture structure and pore connectivity, permeability–storage behavior, moisture availability and evaporation, and the operational factors that govern performance persistence. Laboratory and field evaluation approaches are summarized alongside modeling methods used to interpret coupled hydro-thermal responses under different climates. Practical constraints—including clogging, maintenance requirements, and durability risks under repeated moisture–temperature cycling—are discussed as mechanisms that can progressively suppress both infiltration and water availability, undermining long-term function without performance-based specifications and life-cycle planning. Finally, design and policy implications are outlined for integrating porous asphalt into coordinated heat-and-stormwater strategies, and research priorities are identified to advance standardization, long-term monitoring, and coupled hydro-thermal–mechanical assessment. Full article

Gender-based and sexual violence are major public health concerns, and norms about consent are central to their prevention. This study examines how attitudes toward sexual consent relate to digital sexual consent and to the occasional feeling of distrust in public consent campaigns and institutions. We conducted a cross-sectional online survey embedded in the evaluation of a municipal consent campaign in Zaragoza (Spain). Adults (N = 404; 56.7% women) completed a 14-item short version of the Sexual Consent Scale–Revised, two items on digital sexual consent, and three items on institutional reluctance (perceived “sermonizing” tone, distrust in effectiveness, and lack of personal identification with the message). Correlation and multiple regression models with robust standard errors were estimated, controlling for gender, age, education, income, relationship status, and social media use. Attitudes toward sexual consent were strongly and positively associated with digital sexual consent. Gender was the most consistent sociodemographic correlate: men showed less egalitarian attitudes than women across all consent measurements. Institutional reluctance was systematically related to less supportive consent attitudes: perceiving institutional messages as exaggerated or personally irrelevant predicted lower support for sexual and digital consent norms, whereas trust in the campaign’s effectiveness was associated with more egalitarian attitudes. The findings support the continuity between sexual and digital consent and highlight gender and institutional trust as key determinants for the prevention of gender-based and sexual violence. Public health and social policies should integrate digital consent into consent education and co-design campaigns that minimize defensive reactions and rebuild trust in institutions. Full article

Urban accessibility is commonly evaluated using static spatial indicators, which assume stable travel conditions throughout the day. Road congestion, network saturation, and service variability change the function and experience of the built environment (BE). This study tests the Temporal City Framework (TCF) by examining how time of day (TOD) reshapes urban accessibility and travel behaviour with varying levels of congestion. Using 30,288 trip records from the 2022 US National Household Travel Survey (NHTS), duration is operationalised as a sixth dimension of the BE. A time-normalised impedance metric, measured in minutes per mile (MPM), is used that captures realised congestion independently of distance. Temporal impedance (TI) varies strongly with TOD, with substantially higher MPM during peak and midday periods than at night. Compared with nighttime conditions, midday travel requires approximately 19% more time per mile. This indicates a measurable contraction in functional accessibility under identical BE conditions. The TI model outperforms duration-only models, with impedance remaining dominant when both measures are included. These results support interpreting duration as a structural dimension of urban accessibility. TI significantly increases the relative likelihood of active and public transport compared to private cars, even after accounting for absolute trip duration. Hired transport modes (taxi and ride-hailing services) are most prevalent at night, reflecting a greater reliance on on-demand services outside regular daytime schedules. This study tests duration as a structural dimension of the BE by operationalising time-normalised TI. Associations are interpreted as trip-level behavioural constraints rather than causal effects. Planning frameworks based on static travel times systematically misrepresent exposure, equity, and travel mode feasibility. Time-stratified accessibility metrics should therefore be integrated into transport and land-use evaluation and associated policies. Full article

The rapid expansion of bibliometric research has generated a large volume of descriptive “snapshot” studies that map publication trends but offer limited strategic or policy-relevant insight. Although improved database access and visualization tools have broadened participation in bibliometric analysis, methodological variability, limited reproducibility, and insufficient evaluative framing constrain its utility for research governance. We argue that bibliometric studies should not be conducted as ends in themselves, but as methods for addressing clearly defined, decision-relevant questions. We define evaluative bibliometrics as decision-oriented analysis grounded in explicit research questions, theoretically aligned indicator selection, temporal sensitivity, robustness assessment, and contextual interpretation. Key methodological considerations are examined, including database selection, search strategy design, attribution bias, normalization approaches, and science mapping parameters. We further synthesize emerging reporting frameworks and propose an evaluative extension framework that integrates decision-context specification with structured transparency requirements. By reframing bibliometrics as a decision-support discipline rather than a descriptive genre, this paper provides a methodological roadmap for researchers, editors, and institutions seeking to enhance the rigor, interpretability, and strategic relevance of bibliometric evidence. Full article

As an important part of green manufacturing, remanufacturing has important practical significance for alleviating resource shortage and waste, developing circular economy and promoting sustainable development. In recent years, remanufacturing scheduling (RS), which can achieve high efficiency and green remanufacturing through the reasonable allocation of resources, has become a research hotspot in the field of remanufacturing. To offer a comprehensive evaluation of the research dynamics and development trends of RS, this paper systematically reviews the publications from 2010 to 2025 via Scopus, Web of Science, and the IEEE Xplore database. Firstly, the research background of RS, related remanufacturing policies and the generalized connotation of remanufacturing are introduced. Then, selected and valid publications are analyzed from time aspect, country aspect, and keyword aspect through Citespace software. In addition, based on remanufacturing level, modeling idea, optimization objectives, solution method, production scenarios and practical application, publications are further grouped and reviewed. In addition, according to the research gap existing in recent studies, some future development trends are accordingly pointed out, aiming to provide valuable insights for research related to RS. Finally, meaningful conclusions are drawn and the importance of RS is emphasized once again. Full article