Accurate mapping of crop yields is essential for informed agricultural decision-making and optimal allocation of resources. Current crop yield datasets are deficient in large-scale, high-resolution information regarding the long-term spatial and temporal distribution of crop yields. To address this challenge, we developed a method of vegetation photosynthesis model combined with transition coefficient, producing a detailed dataset with 10 m resolution, covering major regions of maize, rice, and soybean in Northeast China from 2016 to 2021. The method introduces a dynamic observation index () and a composite yield-conversion coefficient (a), which presents an innovative method for estimating crop yields without field measurements. Validation results show that, for maize, rice, and soybean, the model achieves r values of 0.39, 0.51, and 0.52; MREs of 12.14%, 11.96%, and 14.06%; and rRMSEs of 16.97%, 16.12%, and 17.26%, respectively. The dataset offers valuable insights into crop yield distribution, supporting better agricultural decision-making and resource optimization.

Abstract This study presents a comprehensive evaluation of electromagnetic exposure in operational French fourth generation (4 G)/long term evolution (LTE) networks, combining field measurements with computational modeling to assess both uplink (UL) and downlink (DL) contributions. We introduce the novel Radiated Energy per Bit Transmitted (REBT) metric to quantify network radiated energy efficiency, while characterizing TX power patterns across different services, revealing higher mean-to-maximum power ratios for data services compared to voice calls. Through analysis of a representative 2600 MHz user, we demonstrate field-strength-dependent exposure dynamics: with DL field strength of 1 V/m, UL contributes 30% (head) and 12.8% (whole body) of total exposure, while at 0.38 V/m, UL becomes predominant (75% head, 50.4% whole body). Notably, the relative contribution of UL exposure to the total head exposure is consistently higher than that of DL exposure across all scenarios. All measured exposure levels remain well below ICNIRP safety limits, validating safety compliance of LTE. The study establishes an important methodological framework, combining the global exposure index with detailed transfer function analysis, providing critical insights for both current 4 G and emerging fifth generation (5 G) exposure assessments.

Abstract The presence of vegetation in aquatic environments alters hydrodynamics and sediment resuspension. A recent paradigm has suggested that turbulent kinetic energy (TKE) serves as a better predictor of sediment transport in aquatic canopies than bed shear stress. This observation has led to the development of formulations to predict TKE for vegetated flows in the laboratory. However, model validation from natural heterogeneous field environments is lacking. Here, we explore the application of laboratory‐based formulas in a real environment, characterized by multiple vegetation length scales. We measured turbulence within a sparse canopy of mangrove pneumatophores and saplings during an experimental period with negligible wind‐wave activity. The existing formulations for TKE performed well in the field, but only when using the measured values for horizontal eddy length scales. These length scales accounted for the generation of additional turbulence from the surrounding sapling canopy, leading to notably larger TKE values than in similar laboratory experiments.

Natural hydrogen has emerged globally as a promising natural resource in the energy transition. In the face of climate change and the urgency to diversify energy sources to reduce pollutant emissions, hydrogen emerges as a viable alternative due to its high mass energy density. This work focuses on the prospecting of naturally occurring hydrogen and aims to review the main concepts and fundamentals related to this emerging resource, establishing correlations with the petroleum system to promote knowledge transfer between the two systems. Furthermore, it proposes a workflow to investigate natural hydrogen. Hydrogen prospecting begins with the interpretation of existing geochemical data, seismic data, multiphysics data, and gamma spectrometry, as well as the recognition of subcircular depressions, when applicable, to select targets for evaluation. In the field, static and dynamic measurements of hydrogen exudations should be conducted. The identification of the active hydrogen system involves studying the same elements as the petroleum system, such as generation, which is defined through data and geological maps analysis to trace the rocks and processes associated with hydrogen generation; migration, which aims to understand the preferential pathways taken by the gas, primarily characterized by the interpretation of the structural framework, with particular attention to deep faults; reservoir, which should exhibit good perm-porous properties, characterized based on field samples or analogs; and trap, with seismic recognition of the geometry and sealing layers. In summary, applying knowledge derived from hydrocarbon exploration can facilitate advancements in hydrogen prospecting techniques, contributing to the development of more precise and specific models for this potential resource.

An analytical model for boundary layer wind velocity profiles of landfalling typhoons based on field measurements

Thermal comfort is a fundamental condition for human well-being, work performance, and health, particularly in educational environments located in regions exposed to persistent heat and high humidity. In equatorial cities such as Manaus, inadequate thermal conditions in public schools may contribute to the precarization of teaching work and to adverse health outcomes among education professionals. This study aimed to analyze the influence of thermal discomfort on teaching activities, health, and well-being of teachers in municipal schools located in the East Zone of Manaus, Amazonas, Brazil. The research combined long-term climatic data on air temperature and relative humidity (1992–2023), field measurements conducted in classrooms and outdoor teaching areas during October and November 2024, and semi-structured interviews with teachers. Thermal conditions were assessed using the Thom and Bosen Discomfort Index (DI), while qualitative data were analyzed through thematic content analysis. The results revealed recurrent and elevated levels of thermal discomfort in Manaus, particularly between July and November, with field measurements indicating DI values ranging from 25.7 °C to 30.6 °C. The highest discomfort levels were recorded during the afternoon period, affecting both indoor and outdoor school environments. Teachers reported negative impacts on health and work performance, including fatigue, headaches, respiratory discomfort, and reduced capacity to carry out teaching activities, especially among Physical Education teachers exposed to direct solar radiation. The study concludes that thermal discomfort constitutes a structural factor in the precarization of teaching work in public schools in Manaus. Addressing this issue requires integrated public policies focused on school infrastructure, preventive maintenance, climate-sensitive architectural design, and recognition of thermal comfort as an essential dimension of educational quality and occupational health.

Mitigation effects of building facade buffer zones on wind-driven rain: Insights from field measurements

Abstract Prydz Bay is a major Antarctic Bottom Water production region adjacent to a major cold cavity ice shelf. Its underlying mixing processes are little known, although they determine the intensity of water mass transformation. Using microstructure measurements, we reveal detailed regional variations of dissipation and mixing in Prydz Bay during summer. In the upper layer, turbulence dominates the continental shelf, presenting weak dissipation rate of thermal variance χ θ [ O (10 −10 )°C 2 s −1 ], but showing the elevated dissipation rate of turbulent kinetic energy ε [ O (10 −8 ) W kg −1 ] and thermal eddy diffusivity K θ [ O (10 −4 ) m 2 s −1 ]. On the continental slope, diffusive convection prevails, with one-order greater χ θ and one-order smaller ε and K θ . On the shelf break, turbulence and diffusive convection coexist, with elevated ε , χ θ , and K θ reaching the orders of 10 −8 W kg −1 , 10 −8 °C 2 s −1 , and 10 −4 m 2 s −1 , respectively. Tidal current’s encountering with the ice shelf, background current’s impinging on the rough topography, and the intrusion of modified Circumpolar Deep Water all contribute to these spatial variations. The dissipation ratios Γ for both turbulence (0.05) and diffusive convection (0.14) are statistically smaller than those in waters of mid- and low latitudes because water in Prydz Bay is primarily stratified by salinity; hence, the strong temperature gradient is associated with a weak stratification. Based on these features, we propose a new indicator to differentiate turbulence and double diffusion. This study is helpful for better understanding Antarctic mixing processes, and their contributions to local water mass transformation and to global ocean circulation and climate. Significance Statement Prydz Bay is important in producing Antarctic Bottom Water and hence shaping global ocean circulation and climate. This bottom water production and spreading are catalyzed by microscale mixing, yet the local mixing processes remain unclear. Based on field measurements, we reveal the regional differences in dissipation/mixing intensities and its drivers in upper Prydz Bay during the austral summer. Turbulence and diffusive convection dominate the water in and away from the continental shelf, respectively, leading to spatially contrasted mixing intensities. Notably, an important parameter, dissipation ratio, in Prydz Bay is clearly smaller than that of mid- and low latitudes. This is directly linked to the vertical transition of water masses. This study improves our understanding of mixing in Prydz Bay and its influences on other multiscale dynamics.

Combined wavelet-based optical flow velocimetry and temperature field measurements in alumina-water nanofluids during transient turbulent natural convection

Advanced grid method for discontinuous displacement field measurement

Characterization and influencing factors of hydroxymethanesulfonate (HMS) in the North China plain: integration of field measurements and theoretical calculations

Dataset of the CO2-rich gas emissions in the Eastern Carpathians, Romania.

Mitigating nitrous oxide emissions in wastewater treatment with pure oxygen aeration: A full-scale study.

ABSTRACT Two-dimensional soil consolidation involves coupled vertical and horizontal drainage, posing challenges in accurately predicting consolidation coefficients due to complex boundary conditions and data limitations in real-world applications. This study addresses these issues by evaluating data-driven physics-informed neural networks (PINNs) for solving forward and inverse problems in 2D consolidation with coupled consolidation coefficients. The methodology integrates hard constraints for drainage boundaries and soft constraints for both drainage and impermeable boundaries, enabling precise modelling of excess pore pressure and coefficient interactions. Forward problems were analysed with and without observed data, optimising hyperparameters and assessing sensor arrangement effects on predictions. Inverse problems utilised observed data to estimate vertical and horizontal consolidation coefficients and incorporated noise to simulate practical scenarios. Results show that PINNs accurately predict the full consolidation process, determining coefficients from initial-period data alone and robustly handling noise levels typical in field measurements. This work contributes a novel, efficient PINN-based approach for consolidation analysis with coupled coefficients, offering practical advantages for geotechnical engineering where long-term data is scarce and measurements are error-prone.

Exposure to solar radiation (SR) induces photochemical and thermal damage to ocular tissues, primarily via ultraviolet radiation (UVR), affecting outdoor workers and recreational users globally. Short-term effects include photokeratitis (corneal inflammation, akin to "snow blindness") and photoretinitis, while chronic exposure leads to cataracts, pterygium, corneal degeneration, and eyelid cancers. High-altitude and snowy areas intensify UVR by up to 85% reflection from fresh snow, exacerbating risks for unprotected eyes in both children and adults. This review synthesizes evidence from epidemiological studies, clinical case series, and photobiology research up to 2025, including world health organization (WHO) global burden estimates and occupational exposure data. Key sources encompass PubMed/PMC articles on UVR mechanisms (e. g., Bunsen-Roscoe reciprocity law for cumulative damage) and field measurements of ultraviolet (UV) reflectance in elevated/snowy terrains. Analysis focuses on human health impacts, prioritizing eye-specific outcomes via qualitative synthesis without meta-analysis. Acute UVR exposure causes painful photokeratitis and conjunctivitis, with snow reflection increasing retinal stress and erythropsia (temporary red vision). Chronic effects show outdoor workers with 4-fold higher pterygium odds and substantial cataract burden (e.g., 529,242 DALYs globally per WHO). Skin and immune impacts include immunosuppression and higher skin cancer rates, with solar retinopathy from direct gazing causing permanent macular damage; 100% UV-protective sunglasses mitigate nearly all risks. SR endangers eyes and skin profoundly in reflective environments, urging optometrists and ophthalmologists to recommend 100% UVA/UVB-blocking sunglasses for patients visiting high altitudes or snowy areas. Prioritizing protection prevents acute injuries and chronic diseases, promoting public health education on evidence-based eyewear selection.

Abstract Effective noise control in belt conveyor systems is crucial for promoting environmentally sustainable practices in bulk material transportation. Here, the noise radiation characteristics of long-distance belt conveyor systems are investigated by field measurements and numerical simulations. Field measurements conducted at a cement production facility reveal that operational noise levels exceed both occupational health and environmental regulatory thresholds. Using the finite element method, numerical calculations reveal that the belt speed significantly influences noise radiation patterns, with increased speeds leading to higher noise levels and a shift in dominant noise frequencies toward higher bands. A noise prediction model is developed and verified, showing good agreement with field measurement results. In addition, several noise mitigation strategies are proposed and evaluated, including the installation of sound barriers and the use of polyethylene idlers, as well as a reduction in belt speed during nighttime operations, which effectively reduces noise levels within the corridor and at nearby residential areas. This study provides a comprehensive understanding of noise radiation behavior in belt conveyor systems and delivers practical, engineering-oriented solutions to support more sustainable industrial operations.

To address the high bending stresses and potential structural failure risks caused by differential settlement at expansion joints during bridge widening projects of straight bridges, this paper proposes an “Adaptive Rebound Displacement Compensation Device”. Existing research primarily focuses on analyzing settlement patterns and passive control standards, with limited attention to active dynamic regulation. Notably, the bending stress induced by new pier settlements can reach 3–5 times that of vehicle loads, posing serious safety concerns. Through theoretical derivation, this study clarifies the relationship between superstructure loss of strength and factors such as pier settlement, device stiffness, friction coefficient, and L-shaped baffle angle, and a comprehensive design framework is established accordingly. Combining numerical simulations, laboratory tests, and field measurements from engineering practices, multiple validation approaches are employed. The simulation results demonstrate that the proposed device can limit deck subsidence to 10–20% of pier settlement height, and experimental outcomes align closely with theoretical predictions. This device has been successfully implemented in a bridge widening project on a highway section in Jiangxi Province. It should be noted that all data presented in the paper are derived from finite element method (FEM) numerical simulations, and there are currently no on-site measurements of the device’s performance. FEM analysis indicates that the device demonstrates certain feasibility for practical engineering applications. Compared to scenarios without the installation of this device, bridge deck displacements can be reduced by approximately 16.5%. By enabling adaptive rebound through self-adjustment mechanisms for settlement compensation, this device significantly alleviates bending stresses at expansion joints, breaking through traditional passive control limitations. This study provides an innovative approach for actively controlling settlement differences in the widening of straight bridges, offering significant implications both at the theoretical and practical levels.

<p class="MsoNormal" style="text-align: justify;">The paper presents a quantitative study analyzing how Classical Chinese Gardens (CCGs) have the capacity to regulate the microclimate and the potential effects on the productivity of staff through the Humble Administrator Garden at Suzhou. The study uses a combination of field measurements and Ordinary Least Squares (OLS) regression analysis to determine the effect of important landscape features, such as vegetation, water bodies, architecture, pathways, and corridors, on vital microclimate attributes, such as the air temperature, surface temperature, wind speed, and relative humidity. The study results show that vegetation has a strong cooling effect (β =0.875), humidity control effect (β = 0.250) and all water bodies have a strong cooling effect (β = 0.875) but a weak warming effect (β = 0.125) and Buildings and hard surfaces have a strong cooling effect (β = 0.875) and a weak effect (β = −0.008) of reducing the wind speeds and surface temperatures in corridors, respectively. Among them, trees would offer the best cooling (score 5), grasslands would do the best at controlling the humidity and wind speed (score 5), and water bodies would also contribute to the humidity regulation (score 4) significantly. Combining these results with an existing scheme of thermal sensation and work efficiency, the paper demonstrates the capacity of the microclimate changes to be applied to cognitive functioning and productivity. The study reveals practical recommendations in implementing the traditional Chinese garden design framework to the modern urban space and workspace setting, and presents approaches to enhancing the environmental sustainability, the thermal comfort and finally, the well-being of the staff and their productivity.</p>

ABSTRACT To address the limitations of traditional transformer health index (HI), such as high dependence on data integrity and inability to assist in diagnosing latent faults, this study proposes an HI prediction method based on dynamic Bayesian network (DBN). The method first constructs a DBN for characterising the health state indicator system of power transformers according to their structural composition and operational environmental conditions. Next, the entropy weight method and fuzzy membership function are employed to determine the prior probability tables between DBN nodes, whereas the logistic regression method is used to establish conditional probability tables. Finally, existing literature data and field measurement data are utilised to validate the proposed method. The results demonstrate that: (1) the developed DBN can not only effectively calculate the current HI of transformers but also predict HI values for different future time intervals and (2) it can evaluate the overall health state of transformers and identify potential faults in individual components based on node‐specific HI values. Therefore, this method provides valuable support for operation and maintenance personnel in making informed decisions regarding maintenance strategies, batch retirement and replacement plans.

In urban corridors, roundabouts often operate in close proximity to signalized intersections, yet the safety implications of their mutual interaction remain insufficiently explored. This study combines field measurements and VISSIM (PTV VISSIM Academic 2023, SP 5) microsimulation with the Surrogate Safety Assessment Model (SSAM) to analyze roundabout–signalized intersection pairs under varying outer radii (12–22 m), spacings (40–160 m), signal red times (17–27 s), and traffic distributions. A multiple linear regression model for predicting the total number of conflicts is developed and partially validated using calibrated real-site models for corridors in Osijek and Poreč, Croatia. Small spacings (40 m) increase the total number of conflicts by 40–60% for small roundabouts (R = 12 m) and 20–40% for larger radii compared with isolated operation. Increasing the outer radius (inscribed circle radius) from 12 to 17 m reduces conflicts by up to about 90%, while longer red times further lower conflicts, especially for small roundabouts. The final regression model, based on spacing, red time, and outer radius, explains about 80% of the variance in conflicts and shows good agreement with SSAM estimates within its applicability range, providing a practical tool for safety-oriented design of urban roundabout–signalized intersection corridors, thereby contributing to the goals of developing a sustainable transport system in a complex urban environment.