Search Results (19,123)

Background: Respiratory diseases remain a major contributor to mortality in Europe, yet national long-term analyses rarely explore sex- and age-specific temporal patterns in detail. Large international datasets provide aggregated estimates but may obscure country-specific trend changes relevant for public health planning. The aim of the study was to assess long-term trends in mortality from chronic lower respiratory diseases (ICD-10: J40–J47) as well as pneumonia and influenza. (ICD-10: J10–J18) in Poland, with particular emphasis on sex- and age-specific trajectories and joinpoint-defined changes over time. Methods: All deaths among Polish residents aged ≥65 years were analysed using nationwide mortality registry data. Age-standardised death rates (SDRs) were calculated, and temporal trends were assessed using joinpoint regression models to estimate annual percentage changes (APC) and average annual percentage change (AAPC). Results: The proportion of deaths attributable to respiratory diseases increased in both men and women across early (65–74 years) and late (≥75 years) old age. Mortality from chronic lower respiratory diseases declined throughout the study period among men, with the most pronounced reductions observed in the early 2000s, particularly among those aged ≥75 years, while trends among women remained largely stable or showed only gradual declines. In contrast, mortality from pneumonia and influenza rose markedly across all sex and age subgroups, with distinct trend reversals observed after 2008–2009. Conclusions: Long-term respiratory mortality trends in Poland exhibit marked sex- and age-specific differences that are not fully captured by aggregated international analyses. These findings highlight the importance of country-level, stratified assessments when interpreting respiratory mortality patterns and underscore the need for caution when relying on single time-point indicators for risk assessment and policy planning. Full article

Urban green spaces (UGSs) are vital ecological infrastructure supporting climate resilience, public health, and environmental equity. Despite UGS’s importance, the distribution of UGS in rapidly growing desert cities is wildly disproportionate, as evidenced by a recent study that links UGS availability with road hierarchy using the Road Buffer Framework. Using Landsat 8-derived UGS (overall accuracy = 0.885; Kappa = 0.853), OpenStreetMap Roads, and WorldPop Population Data, this study found that UGS availability per capita is very low across all road classifications (0.020–0.033 m²/person) and falls significantly short of the World Health Organization’s (WHO) recommendation of 9 m²/person. Primary roads only marginally improved based on distance from roadways (0.026–0.032 m²/person), and secondary roads are experiencing little to no change (0.025–0.026 m²/person). Further, Tertiary roads show the most significant loss, with only 0.022 m²/person available within the 0–300 m buffers containing the most people. In addition, urban green spaces are still significantly inequitable, as demonstrated by Gini coefficient results of >0.80, peaking at 0.895, indicating that UGS availability per capita is substantially below international benchmarks. Therefore, the findings highlight the need of incorporating roadside greening, small park areas, and greenways into our transportation planning efforts to support the UN’s Sustainable Development Goals (SDG) 3, 10, 11, and 13. Full article

This article presents the simulation methodology and results of dual fuel combustion for internal combustion engines (ICE). Simulations were performed in ANSYS Forte^®, which modeled flame propagation using the G-equation model, and results were validated against experimental data. The article also presents results from simulations performed in Converge CFD^®, which used the SAGE combustion model, presented in previous work. Typical combustion modelling challenges in such ICE simulations are discussed, and the applied methodology is described. The range of methane-air equivalence ratio was 0.47 ≤ ϕ ≤0.57 across four load conditions with a rotational velocity range of 1228 ≤ RPM ≤ 1800. The methane-air combustion at these low equivalence ratios led to the required tuning of the stretch factor coefficient used in the flame speed model in ANSYS Forte^® due to methane’s thermo-diffusive effects at lean equivalence ratios. As a result, the flame stretch factor coefficient was found to increase with decreasing equivalence ratio. The study thus demonstrates the importance of flame stretch sensitivity and thermo-diffusive instabilities in ICE combustion through CFD combustion simulations. Full article

Background/Objectives: Human papillomavirus (HPV) is the most common sexually transmitted virus worldwide and is frequently detected in women of reproductive age. In this population, HPV-related diseases and their management may affect reproductive health and pregnancy outcomes. This narrative review summarizes the current evidence on HPV infection and HPV-related diseases in relation to fertility, pregnancy, and neonatal outcomes, and discusses preventive strategies, with a particular focus on HPV vaccination. Methods: An international, multidisciplinary team of clinicians from the European Society of Gynaecological Oncology (ESGO) Prevention Committee reviewed the literature on HPV, HPV-related diseases, HPV vaccination, and reproductive outcomes, without time restrictions, prioritizing studies judged to meaningfully reflect the available evidence. Results: The most consistent evidence linking HPV-related conditions to adverse pregnancy outcomes relates to the treatment of cervical precancer, particularly excisional procedures, which are associated with an increased risk of preterm birth and mid-trimester pregnancy loss. In contrast, evidence that maternal HPV detection alone causes adverse pregnancy or neonatal outcomes remains limited and inconsistent. Data on HPV infection and subfertility are scarce and heterogeneous. Management of HPV-related lesions during pregnancy remains challenging and requires careful balancing of maternal safety with avoidance of unnecessary interventions. HPV DNA has been detected in neonatal samples, but convincing evidence for clinically relevant vertical transmission is lacking. Available data indicate that inadvertent HPV vaccination shortly before or during pregnancy is not associated with adverse pregnancy outcomes. Conclusions: Current evidence suggests that reproductive risks are more strongly associated with the treatment of HPV-related diseases than with HPV infection itself. Preventive strategies—especially HPV vaccination—remain central to reducing HPV-related disease burden. Although HPV vaccines are not routinely recommended during pregnancy, evidence supports the safety of inadvertent exposure around conception or during gestation, while potential long-term benefits of vaccination regarding reproductive health require further study. Full article

Focusing on the construction of a 58-m-diameter double-layer steel space frame dome at the Han Culture Museum Assembly Hall, this study addresses scheme selection and safety control challenges in staggered jacking of large-span spatial structures. A three-dimensional finite element model in MIDAS Gen simulated the three-stage jacking process to compare three temporary support layouts. Numerical evaluation metrics included maximum vertical displacements, peak internal forces, the proportion of members undergoing stress state transitions, and spatio-temporal evolution of stress concentrations. Scheme B demonstrated superior performance, reducing peak vertical displacement by 44% under critical conditions, lowering peak stresses, and enabling more uniform internal force redistribution—effectively mitigating tension–compression cycling and buckling risks. Crucially, only nodal displacements and support elevations were monitored in situ using a 3D system based on magnetic prisms and total stations; no strain or force measurements were conducted due to practical constraints during construction. Monitoring data show good agreement with simulated displacements and support elevations under Scheme B, validating the model’s deformation response. However, localized deviations—including a 29 mm deflection discrepancy and elevation errors up to 28 mm—reveal the influence of uneven boundary conditions, with potential implications for long-term structural behavior. The findings confirm that numerical predictions of deformation are reliable, while internal forces remain unvalidated by field data. The integrated approach of “scheme comparison–construction simulation–full-process displacement monitoring” proves effective for safety control and decision-making in complex jacking operations, offering a transferable framework for similar large-span double-layer space frame projects. Full article

Avoiding highway infrastructure construction cost overruns and reducing associated claims and disputes continues to be a challenge in many countries. Research is needed in identifying notable project planning and management deficiencies that are likely to cause cost overruns. The literature suggests numerous potential causes of cost overrun but the clustering of cause variables and relative importance of clusters has not been researched. The research reported here addresses this knowledge gap using predictive models developed with data contributed by several agencies in participating countries and suggests mitigation measures. Following a review of methods and data sources, a methodological framework is advanced that encompasses statistical methods well suited for providing a scientific basis for identifying important clusters of cost overrun variables. Fifty-three completed questionnaires contributed by knowledge experts and experienced managers from Canada, the United States, the Middle East, and Australia met the sample requirements of statistical methods. Starting from 53 variables, the principal component-supported factor analysis method identified clusters of cost overrun variables and their relative importance was inferred with developed logistic regression models. Deeper insights into the causes of cost overruns obtained from this research suggest mitigation measures (e.g., improved qualification and experience of personnel, enhanced planning and design practices, risk analysis of inputs to cost estimation process) that are within reach of managers. The results can enhance infrastructure planning and management practice including a reduction in claims and disputes. Full article

Although cardiovascular disease (CVD) is the leading cause of mortality globally, it remains insufficiently understood in large parts of the world. The scientific foundations underpinning CVD risk prediction, diagnostics, and treatment are extensively derived from homogenous datasets, primarily including White, male participants from high-income countries. This lack of diversity and inclusion can lead to biased evidence, which in turn contributes to reduced diagnostic accuracy and the under-representation of key populations, and ultimately limits the generalizability of trial results and guidelines. In this paper, we discuss that diversity in cardiovascular data is a scientific necessity for valid and globally applicable knowledge and not just a matter of fairness. Drawing from emerging initiatives in genomics, digital health, and participatory research, we propose a global roadmap to reshape how cardiovascular research is conducted. This includes strategies such as data donation frameworks, inclusive biobanking, equitable AI development, and international policy change. Only by integrating diversity into scientific methodologies can we ensure that cardiovascular guidelines are effective, inclusive, and just. Full article

Accurate estimation of the State of Charge (SOC) for lithium-ion batteries is a core function of the Battery Management System (BMS). However, LiFePO₄ batteries present specific challenges for SOC estimation due to the characteristic plateau in their open-circuit voltage (OCV) versus SOC relationship. Moreover, data-driven estimation approaches often face significant difficulties stemming from measurement noise and interference, the highly nonlinear internal dynamics of the battery, and the time-varying nature of key battery parameters. To address these issues, this paper proposes a Long Short-Term Memory (LSTM) model integrated with feature engineering, physical constraints, and the Extended Kalman Filter (EKF). First, the model’s temporal perception of the historical charge–discharge states of the battery is enhanced through the fusion of temporal voltage information. Second, a post-processing strategy based on physical laws is designed, utilizing the Particle Swarm Optimization (PSO) algorithm to search for optimal correction factors. Finally, the SOC obtained from the previous steps serves as the observation input to EKF filtering, enabling a probabilistically weighted fusion of the data-driven model output and the EKF to improve the model’s dynamic tracking performance. When applied to SOC estimation of LiFePO₄ batteries under various operating conditions and temperatures ranging from 0 °C to 50 °C, the proposed model achieves average Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) as low as 0.46% and 0.56%, respectively. These results demonstrate the model’s excellent robustness, adaptability, and dynamic tracking capability. Additionally, the proposed approach only requires derived features from existing input data without the need for additional sensors, and the model exhibits low memory usage, showing considerable potential for practical BMS implementation. Furthermore, this study offers an effective technical pathway for state estimation under a “physical information–data-driven–filter fusion” framework, enabling accurate SOC estimation of lithium-ion batteries across multiple operating scenarios. Full article

Background: Despite the implementation of numerous evidence-based interventions, the 2024 Point-in-Time count in the United States (U.S.) reported that 259,473 people in families with children under 18 years old were experiencing homelessness, a record high since the count began in 2007. Recent findings suggest that co-developed interventions may increase engagement with vulnerable populations and, in turn, the effectiveness of health-based programs among them. Objective: In this review, we sought to systematically search and assess the current evidence on co-developed community-based interventions with and for children under age 18 and families experiencing homelessness (CFEH) in high-income countries and their impact on health and well-being outcomes. Methods: Seven databases (e.g., Medline, CINAHL, Embase) and four additional scholarly sources (e.g., Health CASCADE) were searched (publication dates between January 2000 and February 2025). In our analysis, methodological “quality” was assessed through two primary criteria: internal validity and the extent of CFEH involvement. Results: A total of 1617 studies were screened for eligibility, and nine studies were found to have co-developed interventions with CFEH in the U.S. (n = 6) and the United Kingdom (n = 3). These were categorized thematically by socio-structural, behavioral, and combined intervention types. Five studies reported positive engagement among families and staff, whereas three reported improved mental health outcomes. Conclusions: This review highlights the potential impact of co-developed interventions on CFEH’s mental and physical well-being as well as process-based outcomes. Limitations include different definitions of “co-” terminology and homelessness across studies, as well as a lack of transparency about the extent of CFEH’s involvement in these studies. The dearth of evidence indicates that future research should employ community-based participatory research while striking a balance of working with CFEH and other partners and ensuring the data are reliable and reproducible. Full article

Honey fraud represents a persistent and analytically challenging form of food adulteration, driven by globalised supply chains, strong economic incentives and asymmetries in regulatory oversight and analytical capacity. Conventional physicochemical, spectroscopic and isotopic methods provide legally robust tools for routine control, yet increasingly struggle to detect sophisticated adulteration strategies that are compositionally optimised to mimic authentic honey profiles. These challenges are amplified in a global context, where heterogeneous enforcement landscapes and fragmented analytical infrastructures create exploitable vulnerabilities across international trade networks. This narrative review synthesises current knowledge on honey fraud typologies and critically evaluates established analytical approaches alongside emerging omics-based authentication strategies, including genomics, metabolomics, proteomics and microbiome profiling. Omics-based approaches extend authenticity assessment beyond single-marker paradigms by capturing multidimensional biological and compositional signatures, thereby improving sensitivity to subtle and system-aware fraud (i.e., adulteration strategies that adapt to prevailing analytical detection methods and regulatory thresholds) strategies. To maintain evidentiary clarity, this review explicitly distinguishes between analytically demonstrated vulnerabilities, technically feasible adulteration scenarios and fraud practices documented in regulatory or enforcement contexts. Advanced technology-driven strategies are therefore discussed as potential system-level risks rather than confirmed large-scale honey fraud cases. This differentiation not only safeguards evidentiary precision but also highlights the structural limits of purely analytical solutions. Beyond analytical performance, honey authentication is framed as a systemic challenge embedded in global food systems. This review highlights the need for integrated, data-driven and scalable authentication frameworks that align analytical innovation with reference harmonisation, governance structures and international regulatory cooperation to support resilient and globally robust honey authenticity control. Full article

This study investigates how the origin and language of public attention influence financial markets during geopolitical conflict, using Israel’s experience during the 2023–2025 Gaza War as a case study. We use Google Trends data—in Hebrew, English, and Arabic, sourced both worldwide and domestically—to explain fluctuations in the Tel Aviv Stock Exchange’s TA-35 Index and the Israeli shekel’s exchange rates (USD/ILS and EUR/ILS). The results uncover a striking asymmetry: international searches, especially those in Hebrew and English, have significant power to explain Israeli market performance, while local, domestic searches are largely insignificant. Specifically, global Hebrew attention is positively associated with the shekel appreciating, suggesting that expressions of confidence or solidarity from the diaspora may actively reinforce market stability. In contrast, spikes in global English-language searches correspond with lower equity returns and temporary shekel depreciation, consistent with heightened international risk perception. These findings demonstrate that transnational behavioral networks and diaspora attention critically shape financial resilience during war. By integrating behavioral finance, conflict economics, and computational analytics, this research shows that the geographic and linguistic origin of attention, not just its sheer volume, is the key determinant of market reactions in times of crisis. Full article

The Galileo Search and Rescue (SAR) service is the contribution from the European constellation to the international Cospas–Sarsat system. This system uses a variety of space and ground infrastructure to detect and localize distress signals from beacons on the 406 MHz frequency. Satellites in different orbits detect the signals coming from the Earth and transmit them back to Earth stations that route them to the appropriate government authorities. On top of the standard detection and relay service, the Galileo constellation is the first to offer a Return Link Service (RLS) that acknowledges the processing of the distress signal with a Return Link Message (RLM) back to the originating beacon. This RLM is transmitted in the SAR field of the E1 signal I/NAV message, which allocates 20 bits every 2 s page. Therefore, transmitting a short RLM (80 bits) takes four consecutive pages or eight seconds. Moreover, each RLM is transmitted in parallel from two Galileo satellites. The RLS has been active since 2020, avoiding the spotlight of the GNSS community. This paper presents an analysis of the SAR Return Link Messages extracted from more than 3 months of signal-in-space data to investigate the current bandwidth use, monitor the type of SAR usage, and detect anomalies in the service. To extract and parse the Return Link Messages, we have developed and published an open-source Python library called GalileoSARlib on GitHub, which is also detailed in the paper. Full article

Background/Objectives: Türkiye is located at the intersection of major international migration routes and plays a critical role in global migrant health. The growing immigrant and refugee population has introduced new challenges to healthcare systems (HCSs), particularly in emergency departments (EDs). This study aims to address a gap in the literature by evaluating the reasons foreign nationals present to the ED, their diagnostic distribution, and access to healthcare services in relation to sociodemographic characteristics. Methods: This retrospective study included foreign nationals who presented to the Emergency Department of Balikesir University Hospital between January 2020 and June 2025. Sociodemographic and clinical data were obtained from the hospital information management system. Data analysis was performed using IBM SPSS Statistics 27.0. Descriptive statistics were used to summarize demographic and clinical characteristics, including gender, nationality, admission period, diagnosis groups, laboratory testing, consultations, and patient outcomes. Results: A total of 6366 foreign nationals were included. Of these, 66.4% were female and 33.6% were male, with a mean age of 31.9 years for females and 26.8 years for males. Syrians constituted the largest group (50%). ED visits occurred most frequently in spring (30.1%) and peaked in 2024. The majority of patients (99.3%) were managed as outpatients. The most common diagnoses were internal medicine-related conditions (36.1%) and genitourinary emergencies (32.2%). Consultations were most frequently requested from the obstetrics and gynecology department (21.2%). Overall, 92.9% of patients were discharged from the ED. Conclusions: The findings suggest that foreign nationals often use emergency services as an alternative to primary healthcare. Low rates of laboratory and imaging utilization indicate that most ED visits were for non-urgent and uncomplicated conditions. Factors such as language barriers, communication difficulties, prolonged observation times, and limited social support may contribute to this pattern. This study provides comprehensive local data on the emergency care utilization of foreign nationals in Türkiye and offers valuable insights for healthcare planning and policy development. Full article

Biosecurity plays a central role in preventing disease transmission in dairy production systems and animal welfare. However, quantitative data on biosecurity implementation in smallholder and medium-scale dairy farms remains inconsistent, especially in developing countries. This study provides a structured assessment of on-farm biosecurity practices in northern Kosovo using a standardized, risk-based scoring approach. A cross-sectional survey was conducted on 55 dairy farms using the unmodified Biocheck.UGent™ dairy questionnaire. External and internal biosecurity scores were calculated through predefined, weighted algorithms and analyzed using non-parametric descriptive statistics. Farm-level results were subsequently compared with international reference values derived from the Biocheck.UGent™ global database. The median biosecurity scores for Kosovo farms were 47.8% for external biosecurity and 29.0% for internal biosecurity, indicating uneven implementation with pronounced weaknesses in measures designed to limit within-herd transmission. The lowest-scoring domains were purchase and reproduction and feed and water within external biosecurity, and working organization and equipment, calf management, and calving management within internal biosecurity. In contrast, visitors and farmworkers, control of vermin and other animals among external measures, and adult cattle management among internal measures, showed relatively higher scores, although all remained below international reference levels. When compared with the global overall biosecurity reference median of 76.7% derived from the Biocheck.UGent™ database, the biosecurity performance of the surveyed dairy farms in Kosovo was substantially lower. This gap does not indicate a complete absence of biosecurity measures but rather an uneven application, with the most pronounced deficiency observed in routine practices that govern within-herd disease transmission. The use of a risk-based scoring system allowed these weaknesses to be identified in a structured manner and placed the Kosovo results within an international benchmarking framework. In this context, the approach functions as a practical diagnostic tool, enabling farmers and veterinarians to prioritize feasible, epidemiological-relevant improvements within small- and medium-scale dairy production settings. Full article

Objective: To map and characterize artificial intelligence (AI) applications in post-liver transplantation (LT) care, summarize comparative performance where available, and identify methodological and translational gaps. Methods: We conducted a scoping review in accordance with PRISMA-ScR. A comprehensive search of electronic databases was performed from inception through 1 April 2025. We included primary studies evaluating AI applications in the post-LT period (model development, validation, or implementation). Comparative studies were defined as those reporting head-to-head evaluation of at least two algorithmic models for the same task with quantitative performance metrics. Single-model studies were retained for evidence mapping but analyzed separately. Reviews and the other non-primary literature were included for contextual mapping. Results: The search yielded 3088 records. After deduplication, 2408 were screened, 191 full texts were assessed, and 65 studies were included. Of these, 52 reported primary outcome data. Clinical prediction studies (n = 43) focused on graft survival, rejection, fibrosis, oncologic recurrence, mortality, and composite outcomes. Operational studies (n = 3) evaluated early warning or bedside decision-support systems, and system-level studies (n = 6) examined benchmarking, donor–recipient matching, explainability, fairness, and cross-domain modeling. Most studies were retrospective and single-center, with internal validation commonly reported and external validation uncommon. Conclusions: AI research in post-LT care is expanding, with a predominant focus on clinical prediction. However, limited external validation, heterogeneous methods, and scarce real-world implementation constrain clinical readiness. Standardized evaluation and prospective integration are needed to determine whether AI tools can support decision-making and improve post-transplant outcomes. Full article