Search Results (616)

Due to complex terrain, Earth surface curvature, and limited distribution of radars, there are often serious data gaps in base radar data or in 3D radar reflectivity mosaics of a radar network. These gaps greatly limit the application of radar data in short-term severe convection forecasting and quantitative precipitation estimation for flood events. This paper develops a generative adversarial network (GAN)-based radar data gap-filling model, named RadGF-GAN, for completing gaps in 3D radar reflectivity mosaic data. The 2020–2025 high-resolution (at 1 km grid spacing) outputs of a Weather Research and Forecasting and four-dimensional data assimilation model (WRF-FDDA) in an eastern China region are used to generate the data to train and test RadGF-GAN. Observations of the geostationary satellite FY-4A 15-channel AGRI (Advanced Geostationary Radiation Imager) are simulated with the radiative transfer for TOVS (RTTOV), and the radar reflectivity data are simulated with an empirical diagnostic model. By testing on 1705 test samples for satellite-only, radar-only, and radar–satellite fused inputs, it is demonstrated that the proposed RadGF-GAN gap-filling model significantly outperforms the existing interpolation methods in restoring the spatial distribution and structural textures of the radar reflectivity in the 3D gaps. Furthermore, satellite imager measurements play a great role in reconstructing the overall rainband structures in large 3D gaps, and by jointly inputting radar and satellite data, RadGF-GAN greatly outperforms the model with either radar data or satellite data alone. Full article

Background/Objectives: This study aimed to describe and quantify facial soft tissue changes in two patients who underwent radiotherapy (RT) for head and neck cancers, using three-dimensional (3D) stereophotogrammetry and surface deviation analysis. The aims were (i) to assess the progression of morphological alterations over time (ii) and to evaluate the clinical potential of 3D surface mapping in documenting RT-related aesthetic changes. Methods: Two patients with head and neck cancer undergoing RT were analyzed using three-dimensional stereophotogrammetry (3dMD Trio-system, Atlanta, GA, USA) at three timepoints: before RT (T0), 45 days after the start of RT (T1), and 6 months after the start of RT (T2). Facial 3D scans were processed using Geomagic Control 2014 software (v.3D Systems, Morrisville, NC, USA) to perform standardized alignments and calculate volumetric deviations, create colorimetric deviation maps, and conduct Root Mean Square (RMS) analysis. Results: Between T0 and T1, both patients showed soft tissue volume reduction, primarily in the mandibular and submental regions, likely reflecting acute treatment effects and weight loss. Between T0 and T2, an increase in soft tissue volume was observed, especially in the lower face and neck, consistent with late radiation effects such as lymphedema and post-treatment weight gain. RMS values ranged from 5.53 mm to 6.87 mm across patients and time points, indicating measurable morphological changes. The upper third of the face remained stable and served as a reliable reference region for alignment. Conclusions: RT may be associated with significant, region-specific changes in facial and cervical soft tissues in HNC patients, but these preliminary observations must always be correlated with weight loss and confirmed by further studies. 3D stereophotogrammetry is a reliable, non-invasive method for detecting and quantifying these alterations over time. This technique can offer valuable insights for clinical monitoring and could promote better patient counseling and potentially mitigate the psychological burden associated with facial changes. Full article

PM_2.5 is a major air pollutant characterized by complex sources and strong spatiotemporal heterogeneity. However, accurately quantifying the relative contributions of different factors remains difficult due to the lack of long-term datasets and the strong correlations between meteorological factors and emissions. To address this problem, the study utilizes the China long-term particulate matter (CLPM) dataset developed in previous research to investigate the dominant drivers and regional disparities of PM_2.5 concentration variations from 1980 to 2022. The analysis employs Gaussian Convolution (GC) to model pollutant diffusion, Partial Least Squares (PLS) regression to address multicollinearity, and the Lindeman-Merenda-Gold (LMG) method to quantify the relative contributions of each driver. The results reveal that as the convolution scale increased from 0.25° to 10°, dominant PM_2.5 sources shifted from local anthropogenic emissions to regional biomass burning and large-scale dust transport, highlighting the scale-dependent transition of pollution drivers. Furthermore, PM_2.5 concentrations are predominantly explained by emissions, which account for over 60% of the total variance and exceed 80% in eastern China, while meteorological factors are associated with 12–26%. Among these, total precipitation and downward surface solar radiation have the strongest influences on pollutants. It is important to note that these results reflect the statistical explanatory power of emissions and meteorological variables within the regression model. Overall, this research provides a method for separating the statistical influences of emissions and meteorological factors, offering methods for multi-scale explanatory power of PM_2.5 and other atmospheric pollutants. Full article

Desertification is one of the main threats to high Andean ecosystems, particularly in arid and semi-arid regions subject to increasing climatic and anthropogenic pressures. This study evaluated the spatial-temporal dynamics of desertification in the province of Candarave (Tacna, Peru) by integrating the Remote Sensing-based Desertification Index (RSDI), constructed from a principal component analysis incorporating four biophysical indicators: vegetation greenness, surface moisture, soil grain size, and fraction of solar radiation reflected (albedo), derived from Landsat 5 and 8 satellite images processed in Google Earth Engine. Temporal trends were analyzed using the Mann–Kendall test, while system stability was evaluated using the coefficient of variation, allowing different degrees of stability and environmental degradation to be characterized during the period 2010–2025. The results show that moderate and severe desertification classes predominate in higher altitude areas, covering approximately 92% of the study area, and are characterized by insignificant to weakly significant negative trends associated with high to relatively high temporal volatility. In contrast, stable areas with no significant changes represent 5.3% of the territory, while restoration processes occupy a small proportion, close to 2.7%. The high variability observed in the high Andean sectors is mainly linked to the interaction between reduced water availability, climate variability, and extreme events, as well as anthropogenic pressures, particularly overgrazing and aquifer exploitation. This multitemporal analysis allows us to anticipate the evolution of desertification and highlights the need to strengthen conservation planning in order to reduce the degradation of strategic high Andean ecosystems in the Tacna region. Full article

This article presents a meta-surface-based antenna configuration aimed at enhancing the gain performance for millimeter-wave wireless communication systems. The proposed structure consists of a rectangular meta-surface with circular cut-outs placed beneath a rectangular ring to improve the electromagnetic characteristics of the antenna. A rectangular monopole antenna is designed to operate at dual frequency bands around 38 GHz and 43 GHz. To further enhance radiation performance, Artificial Magnetic Conductor (AMC) structures are incorporated beneath the antenna element. The AMC surface improves the radiation efficiency and stabilizes the antenna characteristics by providing in-phase reflection near the operating frequencies. Simulation results demonstrate that the integration of the AMC structure significantly enhances the antenna gain and impedance matching performance. In particular, the incorporation of a $4\times 4$ AMC array increases the antenna gain from approximately 3.4 dB to 6.4 dB while maintaining stable reflection coefficient characteristics. The proposed design demonstrates improved gain performance and compact structure, making it a promising candidate for millimeter-wave wireless communication applications. Full article

This study presents a computational, simulation-based investigation of the dielectric response of human hand tissues, skin, fat, muscle, and bone to radiofrequency (RF) electromagnetic fields emitted by mobile devices. The widespread adoption of handheld devices and the deployment of fifth-generation (5G) networks, including millimetre-wave (mmWave) bands, have intensified concerns regarding localized human exposure to RF radiation, particularly in the hand, which serves as the primary interface during device operation. Using validated dielectric property datasets, numerical simulations were performed across the frequency range of 0.5–40 GHz, employing the Finite-Difference Time-Domain (FDTD) method to solve Maxwell’s equations, with analytical evaluations conducted in Maple-18. A heterogeneous multilayer hand phantom was developed, and simulations were conducted under controlled exposure conditions, including a transmitted power of 1 W, antenna gain of 2 dBi, and incident power density of 5 W/m², consistent with ICNIRP and NCC safety guidelines. Tissue responses were assessed over a temperature range of 10–40 °C to account for thermal variability. The results demonstrate strong frequency- and temperature-dependent behaviour of dielectric properties, intrinsic impedance, reflection coefficient, attenuation, and specific absorption rate (SAR). At lower frequencies (<1 GHz), RF energy penetrated more deeply with distributed absorption and relatively low SAR values, whereas higher frequencies (3–40 GHz) produced highly localized absorption in superficial tissues, particularly skin and muscle. Increasing temperature led to significant increases in permittivity, conductivity, and SAR, with up to a twofold enhancement observed between 10 °C and 40 °C. These findings confirm that 5G and mmWave exposures result in predominantly surface-confined energy deposition in hand tissues. The study provides a robust computational framework for evaluating hand device electromagnetic interactions and offers quantitative insights relevant to antenna design, exposure compliance assessment, and the development of evidence-based safety guidelines. Full article

Rapid urbanization has significantly increased energy demand in buildings, which now represent nearly 30% of global energy use. In India, buildings are built across highly varied climatic conditions, from hot-dry and warm-humid to cold, high-altitude areas, making climate-responsive envelope design essential to enhance thermal performance. Among envelope components, roofs are the most exposed to solar and outdoor thermal loads, playing a key role in managing indoor heat transfer. This study offers a parametric analysis of climate-responsive roof design strategies for India’s five main climatic zones, using transient simulations and statistical evaluation. The effectiveness of insulation placement, insulation material and thickness, and external surface absorptivity was systematically assessed based on roof heat gain and heat loss. Results indicate that over-slab insulation can lower roof heat gain by approximately 15–35% compared to under-slab insulation in warm-humid, hot-dry, composite, and temperate zones. In comparison, under-slab insulation decreases heat loss by about 10% in colder areas. Among insulation materials, 50 mm polyurethane foam (U = 0.433 W/m²·K) consistently outperformed extruded polystyrene and expanded polystyrene, achieving 82–83% reductions in maximum heat gain in cooling-dominated climates and 89% reductions in heat loss in cold regions relative to uninsulated roofs. When combined with a white reflective surface finish (α = 0.26), the total heat transfer reduction increased further to 89–92%. Surface treatments alone cut heat gain by 37–51% in non-cold climates, highlighting their potential as cost-effective retrofit options. Statistical analysis confirmed that dry-bulb temperature is the primary climatic factor influencing roof heat transfer (R² = 0.86–0.98, p < 0.0001), while solar radiation had a weaker effect, especially in optimized roof systems. The findings emphasize the importance of climate-specific roof design and demonstrate that insulation U-value has a greater impact on thermal performance than surface absorptivity, although both are significant. This research offers practical, climate-adjusted guidance for architects, engineers, and policymakers to enhance the thermal performance of roofs in Indian buildings. It supports the development of more resilient, energy-efficient building envelopes. Full article

The topographic shadow effect can cause surface reflectance distortions in the shadow areas of remote sensing images, particularly in complex mountainous areas. In this study, based on the difference in solar radiation received at the surface of sunlit and shadow areas, we introduced the shadow intensity, vegetation index, and band adjustment factors, and proposed a topographic shadow effect correction (TSEC) method. The method was then tested using eight Landsat 8 OLI scenes under different illumination conditions from two different regions. The results indicate that TSEC effectively corrected the topographic shadow effect. The corrected images exhibited good visual quality without obvious shadow pixels. Importantly, TSEC retained spectral information in sunlit areas while correcting spectral distortion in shadow areas, resulting in strong agreement between spectral curves of shady and sunny slopes. The method demonstrated high stability in normalized difference vegetation index (NDVI) correction, as the difference in NDVI before and after correction was less than 0.07 for the four scenes within the Changjiang study area. Moreover, the TSEC corrected the enhanced vegetation index (EVI) effectively, reducing an initial EVI difference of over 0.35 between the shady and sunny slopes to a maximum of 0.074 for the four scenes within the Wuyi Mountain study area. Relative to four established topographic correction models, the proposed method suppresses the over-correction phenomena typical of self-shadows and minimizes under-correction in cast shadows, resulting in stable overall correction results with few outliers. The TSEC provides a simple and effective method to correct the distorted reflectance in shadow areas using only image and DEM data, which can be adapted to complex mountainous areas and for images with different illumination conditions. Full article

To evaluate the cracking characteristics of asphalt pavements under thermal stresses, the finite element (FE) software ABAQUS 2021 was used in this paper to establish thermal and mechanical parameter models, respectively. The temperature field distributions in winter and summer were analyzed according to the actual situation based on fracture mechanics theory and the extended FE method, as well as the most unfavorable crack type for crack propagation was also studied. Further, the impact of the propagation of transverse cracks on the road surface was investigated by changing the solar radiation, sunshine duration, and wind speed. Finally, the propagation pattern of reflective cracks was observed under the cyclic temperature field. The results show that under the action of the temperature field alone, type I cracks, which are cracks that undergo opening displacement due to the vertical tensile stress acting on the crack surface, are the main type of cracks, while the trend of crack propagation was much higher in winter than in summer. It was also found that changing the parameters of solar radiation, sunshine duration, and wind speed could significantly impact cracking. Under the cyclic temperature field, the length of reflective cracks was proportional to time, and the initial crack length significantly affected the pavement life. Therefore, pavement inspection should be more stringent in winter, and initial cracks should be avoided as much as possible during paving. Full article

Ultraviolet radiation, particularly in the UVC sub-band 200–280 nm, is a non-thermal disinfection technology capable of inactivating a broad spectrum of microorganisms primarily through nucleic acid damage and protein oxidation. Its effectiveness depends on wavelength, irradiance, exposure time, environmental conditions, and microbial characteristics, such as species and repair capacity. In food processing environments, where equipment surfaces and packaging materials are critical control points for microbial contamination, UVC offers several advantages, including the absence of chemical residues, and compatibility with sustainable sanitization strategies. However, efficacy is strongly influenced by surface properties. Smooth, non-porous, reflective materials (stainless steel, glass), and photocatalytic metal coatings, enhance UVC performance, whereas rough, porous, or fibrous surfaces reduce penetration and create shadowing effects that limit microbial inactivation. This review synthesizes current evidence on UV-based decontamination in the food industry, highlighting both its potential and limitations. The findings emphasize that, although UVC radiation is effective in microbial control, its implementation must consider the complex interactions between surface properties, microorganisms and irradiation parameters, requiring optimization for each environment and application. Further research is therefore needed into: (i) wavelength-tuned systems, (ii) hybrid technologies (UV–plasma or UV-photocatalysis), (iii) material integrity and durability of materials under repeated exposure, and (iv) emerging alternative light sources. Full article

Driven by the combined effects of global warming and the urban heat island (UHI) effect, building energy consumption has been rising steadily in recent years. The photovoltaic-cool roof (PVCR) system has emerged as an effective solution for urban energy conservation and carbon reduction. However, existing research on the energy-saving benefits of PVCR remains relatively limited, and none of these studies have considered the interaction between photovoltaic modules and high-reflectivity roofs (also called cool roof, CR). Therefore, field experiments were conducted to compare the thermal performance of the PVCR system against that of three conventional roof configurations, including photovoltaic roof (PVR), asphalt roof (AR), and CR. The results demonstrate that the PVCR system achieves a remarkable daytime cooling effect, with a maximum temperature reduction of 29 °C compared to the AR system, and maintains lower temperature fluctuations throughout the entire day. In addition, the findings reveal that the photovoltaic modules exhibit a lower average temperature when installed on the cool roof, with a temperature decrease of 0.15 °C relative to the asphalt roof. A numerical model incorporating the photothermal interaction between a high-reflectivity surface and PV modules was developed and validated with experimental data. The numerical model considers the interactions between the photovoltaic (PV) modules and the high reflectivity surface, including shortwave radiation reflection, longwave radiative exchange, and convective heat transfer. The sensitivity analysis indicates that a change in the spacing and height of the PV arrays from 0.3 m to 0.5 m increases the relative energy-saving efficiency of the system. The conclusions drawn in this paper can provide a reference for the application of the PVCR system in hot-summer and cold-winter areas. Full article

Recent advances in design, manufacturing and development techniques have been very relevant to making solar collectors feasible for production in a variety of applications. In the field of concentrated solar thermal technologies, several techniques have been developed to achieve high levels of radiation concentration. The generation of concave curvature geometry through the polishing of the reflective surface or through specialized machining is one of the most common methods. However, the way in which these bends are obtained can vary significantly, depending on the required quality of optical concentration for the application. This study presents a simple parametric technique to achieve a parabolic curvature for solar concentration applications. To do this, a controlled bending deformation was applied to a metal hollow profile beam supported by a pin and roller at each of the ends, and only two symmetric point loads were applied to generate a bending moment to induce a bending of a curved shape. It was found that, for a given load configuration, a parabolic geometry was generated along a partial center section of the beam. The analysis carried out showed that under the load configuration analyzed, up to 66% of the beam length adopted a fully parabolic geometry. The technique proposed in this work allows for the creation of parabolas with variable focal distances, offering versatility in the design of solar concentrating systems. It also allows corrective adjustments to be made during the assembly of the complete solar concentrator system. Full article

This data descriptor presents a dataset comprising crop and soil parameters measured in winter wheat fields near the town of Knezha, Bulgaria. The data were collected as part of a project evaluating the potential of vegetation indices derived from Sentinel-2 satellite imagery to predict biophysical and biochemical crop parameters. The core dataset consists of measurements obtained from 20 m × 20 m field plots and includes a broad range of parameters: leaf area index, fraction of absorbed photosynthetically active radiation, vegetation cover fraction, chlorophyll content, above-ground biomass, plant nitrogen content, biological yield, surface soil moisture, spectral reflectance, plant density, crop height, visual assessments of disease or pest damage, and data on weed occurrence. The dataset is complemented by unmanned aerial vehicle imagery, crop calendars, and field management information. The main soil types in the study area were characterized through soil profiles, while meteorological data were obtained from an automated weather station. The data were collected during the 2016–2017 and 2017–2018 agricultural seasons. The dataset is freely available for download and serves as a valuable resource for researchers in remote sensing—particularly for validating satellite-derived products—as well as for specialists involved in winter wheat monitoring, modeling, and agronomic studies. Full article

Understanding mechanisms of asphalt in the process of natural aging is crucial for predicting its long-term durability and optimizing performance under diverse environmental conditions. Despite its importance, the microstructural and micromechanical changes induced by natural aging remain poorly understood, particularly under varying climatic influences. This study addresses this gap by analyzing the effects of natural aging on asphalt’s microscopic properties and identifying key indicators that govern its degradation. Asphalt samples were subjected to natural aging across five climatically distinct regions over 6, 12, and 18 months. Atomic force microscopy (AFM) was employed to characterize surface roughness, adhesion forces, and DMT modulus, while correlation analysis and principal component analysis (PCA) were used to identify relationships among micromechanical indicators and streamline the dataset. The results reveal that natural aging induces irreversible transformations in asphalt’s microstructure, driven by the combined effects of temperature, UV radiation, humidity, and oxygen. These processes promote the evolution of “Bee structures,” increase surface roughness, and accelerate phase separation, alongside chemical modifications such as oxidation and polymerization, leading to progressive material hardening and stiffness. Significant regional and temporal variations in adhesion forces and DMT modulus were observed, reflecting the cumulative impact of environmental factors on asphalt’s aging dynamics. Correlation analysis demonstrated strong associations between surface roughness and “Bee structure” area, while mechanical properties such as stiffness and adhesion were largely decoupled from morphological features. Environmental factors interact in complex ways to drive asphalt aging. Humidity enhances adhesion and stiffness via water-induced capillary forces, while temperature reduces surface roughness and adhesion through molecular reorganization. UV radiation accelerates oxidative degradation, promoting surface erosion and stiffness loss, while altitude modulates these dynamics by influencing temperature and UV exposure. Full article

Thermal radiation from high-yield airbursts constitutes a major damage mechanism. To address thermal radiation transmission in complex environments, a ray-tracing-based computational model is developed. This model incorporates atmospheric attenuation, fireball dynamic evolution, building shadowing, and ground/building reflections. Numerical results demonstrate that building shadowing and ground/building reflections significantly alter the thermal radiation distribution in such environments. The impact of ground and building reflections is directly related to surface reflectivity. At a reflectivity of 0.3, reflected radiation can reach 43% of the direct component. While multi-reflection effects are negligible at low reflectivity, they become significant at higher reflectivity values and must be considered in calculations. Full article