Search Results (9,667)

Background: Artificial intelligence (AI) has shown promise in the interpretation of electrocardiograms (ECGs) using signal-based deep learning models. In parallel, large language models (LLMs) have gained increasing visibility in clinical practice, including exploratory applications in ECG analysis. Whether a general-purpose LLM can meaningfully discriminate cardiovascular disease from athlete ECGs during PPS remains unknown. We aimed to evaluate the diagnostic performance of a general-purpose LLM for this task. Methods: In this multicentre diagnostic accuracy study, we evaluated a commercially available LLM (ChatGPT, version 5) in 2950 competitive athletes undergoing PPS. All athletes underwent resting 12-lead ECG, with second- and third-line investigations performed when clinically indicated. The reference outcome was confirmed cardiovascular disease after full diagnostic work-up (n = 450, 15.3%). For each ECG, the LLM generated a numeric score (0–100) representing the inferred likelihood of underlying disease using a standardized prompt and without task-specific fine-tuning. Discriminative performance was assessed using receiver operating characteristic (ROC) analysis. Misclassification patterns were analysed according to International ECG Criteria. Results: GPT-derived scores demonstrated a marked floor effect, with a median value of 0 (IQR 0–2) in both diseased and non-diseased athletes and substantial overlap between groups. The area under the ROC curve was 0.52 (95% CI 0.49–0.55), indicating performance close to random classification. At the Youden-derived threshold, 79% of athletes with confirmed disease were incorrectly classified as negative. False-negative cases were predominantly characterized by borderline ECG patterns (82%), and a substantial number of red-flag ECG abnormalities were also missed. Conclusions: In this PPS cohort, a general-purpose LLM used in a naïve configuration showed no clinically meaningful ability to discriminate between cardiovascular disease and athlete ECGs. Without task-specific training or domain adaptation, such models should not be used for diagnostic triage in athlete screening. Full article

Analysis of Estates Return Information Collection (ERIC) 2018/19–2024/25 data for 1104 acute NHS hospital sites in England found persistently high energy use intensity (EUI), averaging 211 kWh/m² in 2024/25, with total acute-sector energy use of 9.99 billion kWh, with approximately 75% derived from gas. Longitudinal trends indicated relatively stable EUI despite portfolio growth. Cross-sectional exploratory analyses for 2024/25 showed that clinical floor area share (mean 59%) exhibited the strongest observed association with EUI (r = 0.52, R² = 0.27), followed by gross internal area (r = 0.39, R² = 0.15) and backlog intensity (r = 0.23). Associations between building age cohorts and EUI were generally weak or negligible, except for a weak positive association for 1985–94 buildings (r = 0.064) and a moderate negative association for 2005–14 buildings (r = −0.126). Among the decarbonization and operational indicators examined, renewable electricity fraction showed the strongest bivariate association with EUI (R² = 0.224), followed by water intensity (R² = 0.101), gas share (R² = 0.085), LED coverage (R² = 0.027), climate incidents (R² = 0.020), and waste intensity (R² = 0.004). Sites with heat decarbonization plans, high LED coverage, or heat pump installations tended to exhibit higher EUI values alongside differing renewable electricity uptake patterns, potentially reflecting the prioritization of interventions at more energy-intensive facilities. Overall, the findings suggest that hospital energy intensity is associated with functional mix, estate characteristics, and decarbonization-related indicators, although these relationships should be interpreted as exploratory associations rather than independent causal effects. The study provides a national-scale exploratory benchmarking assessment intended to inform future multivariable and longitudinal research on NHS estate decarbonization strategies. Full article

Background/Objectives: Fall armyworm (FAW) (Spodoptera frugiperda) is a major constraint to maize production in Sub-Saharan Africa, including Mozambique. This study aimed to evaluate maize genotypes for resistance to FAW under greenhouse and field conditions and to assess the association between phenotypic resistance and genomic variation based on single nucleotide polymorphisms (SNPs). Methods: A total of 20 maize genotypes from the Agricultural Research Institute of Mozambique (IIAM) and the International Maize and Wheat Improvement Center (CIMMYT) were evaluated. FAW damage was quantified using the area under the damage progress curve (AUDPC). Phenotypic data were analyzed using ANOVA and mixed models, while molecular analysis was conducted using 10,603 SNP markers located on chromosomes previously associated with FAW resistance. Results: Significant genotypic differences were observed under greenhouse conditions (F = 1.94, p = 0.012) and in the field (p = 0.021), although environmental factors reduced variation in the field. Genotypes such as CML67, CML338, and Kenya amarelo (Acc3550) exhibited consistently lower AUDPC values across environments, indicating stable resistance. However, SNP allele proportion was not significantly associated with phenotypic resistance (r = 0.34, p = 0.147), and regression and ANOVA analyses confirmed the absence of a significant relationship (p > 0.05). Conclusions: FAW resistance in maize is quantitatively inherited and not explained by general genomic variation across candidate regions. Phenotypic screening remains essential, and further studies are required to identify specific loci for effective marker-assisted selection. The identified stable genotypes represent valuable resources for breeding FAW-resistant maize adapted to Mozambique. Full article

This paper presents a finite element study of friction ring springs, with emphasis on the internal stress distribution between inner and outer rings and their damping capacity. A detailed two-dimensional axisymmetric model was developed and compared against experimental measurements, showing close agreement in load–displacement response. In parallel, the classical analytical approach was validated in terms of stress and deformation values. To enable efficient parametric studies, a reduced one-element finite element model representing the periodic structure of the spring was also developed. This simplified model reproduces the response of the complete axisymmetric model while reducing the computational cost by over 80%. Beyond reproducing global mechanical behavior, the study provides detailed insight into the ring interactions as a function of the cone angle, friction coefficient, and the ratio of inner to outer cross-sectional areas. The results show that an optimal design should favor higher circumferential stresses in the inner rings, as their compressive stress state and radial confinement make them more resistant to buckling and crack initiation than the outer rings, which are subjected to tension. The findings provide useful guidelines for the modeling and design of friction ring springs and contribute to the broader understanding of friction-based energy-dissipation systems. Full article

Although Vietnam is committed to complying with international frameworks on gender equality such as CEDAW, the Beijing Platform, and the 2030 Agenda, women still face many barriers in exercising their land use rights in practice. This study uses a doctrinal legal research method combined with comparative analysis to: (i) systematically analyze the provisions on gender equality in the 2024 Land Law; (ii) compare these provisions with the 2013 Land Law and relevant international standards; and (iii) assess the challenges in implementation from the perspective of substantive equality. The results show three notable areas of progress: (1) gender equality is recognized for the first time as a specific right of land users; (2) gender discrimination is included in the list of prohibited acts in land management and use; and (3) the scope and procedures for joint land use rights certification for spouses are clarified. However, gaps in legislative drafting, enforcement mechanisms, and the persistence of patriarchal social norms continue to widen the gap between equality on paper and equality in practice, as evidenced by the persistent 32% proportion of certificates registered solely in men’s names with no updated official data released nearly four years later; the absence of specific sanctions for gender discrimination in land use under Decree 123/2024/ND-CP; and the lack of mandatory enforcement mechanisms for joint spousal certification under the 2024 Law’s implementing regulations. Based on this, the article proposes several recommendations to improve the law and strengthen enforcement mechanisms to better align with CEDAW and SDG 5.a standards. Full article

This study addresses, within the framework of fracture mechanics, the structural analysis of the DEMO (demonstration power plant) divertor—a key component in fusion reactors—subjected to particularly severe loading conditions. A global model of the divertor was developed using Finite Element Method (FEM) analysis through the software ANSYS Workbench 2024, including all structural subcomponents. Thermal and internal pressure load cases were considered. The FEM analysis enabled the identification of critical areas prone to stress concentration. Based on the global results, a submodeling technique was applied to analyze locally critical components with higher resolution. On these submodels, a Linear Elastic Fracture Mechanics (LEFM) analysis was performed using the FRANC3D (v 8.6.2) software. Static semi-elliptical cracks were introduced in various configurations, and the stress intensity factor was evaluated to assess their criticality. Subsequently, an incremental crack growth analysis was conducted to simulate crack propagation based on the local stress field, also accounting for directional variations. Finally, a lifetime analysis was carried out using Paris’ law, estimating the fatigue cycles for an arbitrary crack propagation under the given loading conditions. The entire procedure was repeated for each subcomponent and loading condition, resulting in a broad and detailed understanding of the fracture response of the system. This approach provides crucial insights for the design, inspection, and long-term maintenance of the divertor. Full article

On 28 March 2025, a Mw 7.7 earthquake struck central Myanmar, where rapid mapping of early impacts is crucial for post-earthquake assessment and emergency response. Existing nighttime light studies often emphasize single-scale brightness loss, with limited characterization of azimuthal differences within intensity zones and their coupling with population/building exposure, although these factors are essential for explaining spatially uneven earthquake impacts and for improving the interpretation of nighttime light loss patterns. This study integrates daily VIIRS nighttime lights (500 m) with USGS intensity and population/building density to build an intensity–azimuth framework with six directional sectors, quantify pre-/post-earthquake changes at county, patch, and pixel scales, apply bivariate LISA to detect local coupling patterns, and validate against CEMS Rapid Mapping. The results show clear scale complementarity: county aggregation robustly delineates the macro impact extent but smooths internal contrasts; pixel analysis captures fragmented disturbances yet is noise-sensitive; patch-based mapping best aligns with built-up areas at 500 m resolution and shows higher agreement with CEMS in well-lit urban areas. Azimuth–intensity patterns indicate more concentrated NTL reduction in north–south high-intensity zones (NTL = −0.53–−15.67 nW·cm⁻²·sr⁻¹), with local rebounds in some east–west sectors. The framework provides interpretable support for rapid loss assessment and priority-based resource allocation. Full article

During coalbed methane (CBM) production, coal reservoir pore/fracture structure varies dynamically under the action of fluid–solid coupling. And coal reservoir permeability changes accordingly. In order to factually investigate the dynamic changes in coal reservoir permeability in the CBM well drainage process, a comparative simulation experiment on the difference in coal permeability sensitivity to confining pressure (external pressure) and pore pressure (internal pressure) was carried out in this study. The results show that coal permeability presents a typical negative exponential decline with a decrease in pore pressure. The pore pressure sensitivity experiment can effectively simulate the permeability sensitivity characteristics caused by coal reservoir pressure. Based on the negative exponential function relationship between permeability and effective stress, a new calculating method for the effective stress coefficient was deduced. Namely, its value could be expressed as the quotient of the pore pressure sensitivity curve regression coefficient divided by the confining pressure sensitivity curve regression coefficient. A dynamic theoretical model for coal reservoir permeability characterized by reservoir pressure was systematically constructed based on the unique fluid (gas/liquid)–solid coupling characteristics of coal reservoirs. Furthermore, the general characteristics of the stress sensitivity of coal permeability during coalbed methane (CBM) recovery were analyzed. The dynamic evolution characteristics of coal reservoir permeability in the study area were further examined. Taking the production and drainage data of a typical actual CBM production well as an example, the theories regarding the permeability sensitivity of coal reservoirs to reservoir pressure presented in this paper were validated in practice. This indirectly confirmed the rationality and accuracy of the calculation method for the effective stress coefficient obtained through laboratory-based permeability sensitivity simulation experiments. This research provides robust theoretical support for the systematic monitoring and prediction of fluid production, reservoir pressure, and permeability during the CBM production process, carrying significant practical implications. Full article

Street soundscapes significantly shape communities’ environmental perceptions, behaviour and urban sustainability. Previous research has mainly focused on physical and acoustic aspects, while limited attention has been given to emotional and behavioural dimensions. This study explores how expert participants perceive street soundscapes through personal, physical, behavioural, and emotional dimensions, using international online focus groups with soundscape experts, urban planners, and policymakers (n = 12). Analysis followed a deductive thematic approach establishing four main a priori themes, with additional inductive coding used to refine these themes. The findings reveal that perception is shaped by contextual, cultural, temporal, multisensory, and environmental affordance factors. Notably, silence was found to carry a dilemma—perceived as either safe or unsafe depending on pedestrian density—and religious and cultural soundmarks were identified as evoking place attachment and belonging, areas largely overlooked in existing literature. These soundscapes were associated with emotional responses, including comfort, safety, restoration, and belonging, and with pedestrian behaviour encompassing mobility choices, coping strategies, and social interactions. Furthermore, seven out of ten Healthy Streets metrics were directly referenced by participants, highlighting the close relationship between acoustic environments and healthy streets design. Future studies should examine cultural, temporal, and spatial street characteristics and their effects on human behaviour and emotional responses. Full article

This study examines the transformation of the Balaton region in Hungary from a traditional tourist destination into an international retirement migration destination for older adults from Western Europe. Migration theories and models are applied to illustrate the relationships between migration and development and to explore how tourism, lifestyle aspirations, and socio-economic factors influence the settlement decisions of older migrants. Empirical findings suggest that prior tourism experience can mitigate the uncertainty associated with migration and foster belonging. However, many retirees move to Hungary with limited knowledge of the country, relying on social networks and real estate agents for information. These retired migrants also utilize local services and infrastructure, including healthcare and community spaces, which shape their daily lives and help them integrate into the community. The migration of older adults stimulates the development of peripheral rural areas through real estate purchases, renovations, and small-scale entrepreneurial activities, particularly in the accommodation sector. This challenges the traditional perception of older-age migrants as inactive. Full article

Using truck GPS trajectory data, this study measures the intensity of economic spatial linkages in Hubei Province at both administrative and cross-administrative scales and examines the hierarchical structure and spatial pattern of its urban economic network. By comparing the results with existing regional plans, the study provides empirical support for regional coordination and spatial planning. Network centrality analysis, linkage intensity measurement, and community detection algorithms are integrated to construct a topological model of the urban economic network from three dimensions: urban node hierarchy, inter-city linkage intensity, and urban cluster structure. To overcome administrative boundary constraints, a 5 km × 5 km grid-based approach is applied to identify functionally connected urban economic communities. The results indicate that Hubei Province’s urban economic network exhibits a highly dominant core accompanied by multiple secondary supporting centers. While the Wuhan Metropolitan Area demonstrates high economic activity, internal horizontal linkages remain relatively weak, and the roles of Yichang and Xiangyang as regional sub-centers require further strengthening. Grid-based analysis further reveals pronounced cross-administrative economic linkages. Accordingly, this study suggests strengthening support for regional sub-centers and promoting better alignment between administrative space and functional space within the spatial planning system, with enhanced cross-regional coordination. Full article

Investigating slope deformation in densely vegetated or remote areas is a major challenge for slope stability assessment. This study introduces and validates an integrated UAV-borne low-frequency Ground Penetrating Radar (UAV-GPR) and LiDAR methodology to characterize an unstable slope in Melizzano, Southern Italy. Radar data were acquired along an east–west transect at ~1 m above ground level, while high-resolution LiDAR were used to generate a detailed Digital Terrain Model for topographic correction and geomorphological analysis. The processed radargram images subsurface features down to ~15 m, revealing a laterally continuous high-amplitude reflector at ~10 m, interpreted as a key main sliding surface. Chaotic reflections above this interface indicate heterogeneous deposits associated with gravitational deformation, while more homogeneous reflections below correspond to stable geological units. The geometry of the reflector suggests a compound landslide mechanism. Borehole data validate the geophysical interpretation, showing depth discrepancies lower than 2 m. The integration of UAV-GPR and LiDAR enables a reliable correlation between surface morphology and subsurface structures. This non-invasive, spatially continuous approach provides an effective framework for subsurface characterization and for improving the interpretation of landslide geometry and internal structure in challenging environments. This study demonstrates the capability of low-frequency UAV-borne GPR to detect deep-seated sliding surfaces (>10 m) in vegetated environments when integrated with high-resolution LiDAR topography. Full article

Despite growing recognition of holistic care in gerontology, the role of spirituality and religion in physiotherapy practice remains underexplored. This study examines Maltese physiotherapists’ perceptions and awareness of religious and spiritual care in the treatment of older persons, contributing to an untapped area in local research and adding to the limited international literature, particularly within Mediterranean and predominantly Catholic healthcare contexts. A questionnaire was distributed via SurveyMonkey to government sector physiotherapists in Malta. Findings revealed that while physiotherapists recognised the importance of incorporating spiritual and religious considerations into older persons’ care, they often viewed such care as outside their clinical responsibilities. Key barriers included limited training, insufficient knowledge, and time constraints. Notably, physiotherapists with personal religious or spiritual beliefs were more inclined to integrate these aspects into their practice compared to their atheist or agnostic counterparts. The study underlines the need for enhanced training at both undergraduate and postgraduate levels and advocates for qualitative research to deepen understanding of the barriers and facilitators to spiritual care. Addressing these gaps will promote holistic, person-centred care that respects individual beliefs, ultimately enhancing outcomes for older persons. Full article

It is commonly accepted that vegetation plays an important role in climatic studies conducted at local, national, and international scales. The aim of this study is to examine the cooling effects of tree species in the cities and to reveal how they affect the microclimate in İzzetpaşa Neighborhood of Elazığ province of Turkiye. This study, which was conducted by purchasing ENVI-met 5.6.1 microclimate software, aimed to create the most appropriate microclimate scenarios in order to mitigate the urban heat island (UHI). Among the nine scenarios in which different tree species were used; the greatest cooling effect was obtained from the scenario where Acer platanoides L. was used. It was determined that the air temperature dropped by 0.8 °C compared to the base scenario and by 3.0 °C compared to the scenario in which a tree cover was not used. The lowest cooling effect was detected in the scenarios where Pinus sylvestris L. and Abies cilicica Carr. were used. In general, it was observed that there was no significant temperature decrease in the scenarios where coniferous trees were used. In scenarios where deciduous trees were used, more temperature decreases were detected compared to the coniferous trees. According to the winter simulation results of these scenarios, the daily average air temperature values vary between −0.6 and +0.1 °C compared to the base scenario. In the scenario where Acer platanoides L. was used, where the highest cooling effect was observed, the highest relative humidity rate and the lowest Tmrt value were determined. Evaluating the cooling effect of high vegetation on a species basis in reducing the UHI effect as a basis for planning in urban areas will constitute a key strategy in improving the UHI effect. It is envisaged that this study may provide a solution to help reduce the UHI in studies to be carried out in urban areas. Full article

Accurate prediction of forest fires is crucial for enhancing regional fire prevention and control. Existing models frequently rely on static factors such as weather and terrain, while insufficiently taking into account the Fuel Moisture Content (FMC), a critical internal factor that directly determines fire behavior. Instead, proxies like the Normalized Difference Vegetation Index (NDVI) are commonly employed, which weakens the physical foundation of predictions. This study assesses the marginal contribution of integrating dynamic FMC into fire prediction models. Concentrating on California, we developed a random-forest-based model that incorporates high-resolution FMC products retrieved by our team, along with meteorological, topographic, vegetation, and anthropogenic data. Through comparative experiments and SHapley Additive exPlanations (SHAP) analysis, we evaluated model improvements and the contribution mechanisms of key drivers. The results indicated that: (1) Incorporating FMC significantly enhanced model performance, with precision and specificity increasing by 3.93% and 3.60%, respectively, and the Area Under the Curve (AUC) showing improvements, suggesting heightened sensitivity in detecting actual fire occurrences. (2) SHAP analysis disclosed nonlinear effects and threshold dynamics: temperature was the dominant positive driver (the fire risk soared above 20 °C); FMC demonstrated a negative correlation with fire risk, with 100% serving as a potential threshold; elevation presented an inverted U-shaped pattern (the peak risk occurred at 1000–1500 m); and population density exhibited a shifting influence from positive to negative. (3) The monthly risk maps for California in 2023 captured the seasonal progression of fire risk and spatial patterns consistent with historical fire points. The fire risk map for 9 September 2020 also demonstrated consistency with the spatial distribution of the actual fire points on that day. This study validates that the integration of dynamic FMC strengthens the mechanistic foundation and early-warning capacity of fire prediction models, providing scientific backing for targeted fire management. Full article