Search Results (6,560)

Elastomeric ablative coatings are essential for protecting solid rocket motor (SRM) combustion chambers from extreme thermal and erosive environments, and their performance is governed by both material composition and processing strategy. This review examines the main elastomer systems used for SRM insulation, including ethylene propylene diene monomer (EPDM), nitrile butadiene rubber (NBR), hydroxyl-terminated polybutadiene (HTPB), polyurethane (PU), silicone-based compounds, and related hybrids, and discusses how their rheological behavior, cure kinetics, thermal stability, and ablation mechanisms affect manufacturability and in-service performance. A comprehensive assessment of coating technologies is presented, covering casting, molding, centrifugal forming, spraying, automated deposition, and emerging additive-manufacturing approaches for complex geometries. Emphasis is placed on processing parameters that control adhesion to metallic substrates, layer uniformity, defect formation, and thermomechanical integrity under high-heat-flux exposure. The review integrates current knowledge on how material choice, surface preparation, and application sequence collectively determine insulation efficiency under operational SRM conditions. Practical aspects such as scalability, compatibility with complex chamber architectures, and integration with quality-control tools are highlighted. By comparing the capabilities and limitations of different materials and technologies, the study identifies key development trends and outlines remaining challenges for improving the durability, structural robustness, and ablation resistance of next-generation elastomeric coatings for SRMs. Full article

Wetlands in dryland regions are rapidly degrading under the combined effects of climate change and human regulation, yet long-term, seasonally resolved assessments of surface water extent (SWE) and its dynamics remain scarce. Here, we map and analyze seasonal surface water extent (SWE) over the period 2000–2024 in the Ile River Delta (IRD), south-eastern Kazakhstan, using Landsat TM/ETM+/OLI data within the Google Earth Engine (GEE) framework. We integrate multiple indices using the modified Normalized Difference Water Index (mNDWI), Automated Water Extraction Index (AWEI) variants, Water Index 2015 (WI2015), and Multi-Band Water Index (MBWI) with dynamic Otsu thresholding. The resulting index-wise binary water maps are merged via ensemble agreement (intersection, majority, union) to delineate three SWE regimes: stable (persists most of the time), periodic (appears regularly but not in every season), and ephemeral (appears only occasionally). Validation against Sentinel-2 imagery showed high accuracy F1-Score/Overall accuracy (F1/OA ≈ 0.85/85%), confirming our workflow to be robust. Hydroclimatic drivers were evaluated through modified Mann–Kendall (MMK) and Spearman’s (r) correlations between SWE, discharge (D), water level (WL), precipitation (P), and air temperature (AT), while a hybrid ensemble–occurrence framework was applied to identify degradation and transition patterns. Trend analysis revealed significant long–term declines, most pronounced during summer and fall. Discharge is predominantly controlled by stable spring SWE, while discharge and temperature jointly influence periodic SWE in summer–fall, with warming reducing the delta surface water. Ephemeral SWE responds episodically to flow pulses, whereas precipitation played a limited role in this semi–arid region. Spatially, area(s) of interest (AOI)-II/III (the main distributary system) support the most extensive yet dynamic wetlands. In contrast, AOI-I and AOI-IV host smaller, more constrained wetland mosaics. AOI-I shows persistence under steady low flows, while AOI-IV reflects a stressed system with sporadic high-water levels. Overall, the results highlight the dominant influence of flow regulation and distributary allocation on IRD hydrology and the need for ecologically timed releases, targeted restoration, and transboundary cooperation to sustain delta resilience. Full article

This study systematically investigates the microstructural evolution and mechanical properties of GH2787 superalloy following solution treatment at 1140 °C and subsequent aging within the temperature range of 770 °C to 920 °C. The results indicate that aging at 770 °C and 820 °C promotes the precipitation of a high density of finely dispersed γ′ precipitates with minimal interparticle spacing. In contrast, a significant coarsening of the γ′ particles, accompanied by a sparse distribution and a notable increase in interparticle spacing, was observed at the higher aging temperatures of 870 °C and 920 °C. Mechanical characterization reveals that the ultimate tensile strength (UTS) and yield strength (YS) experienced a moderate decrease as the aging temperature increased from 770 °C to 820 °C, followed by a pronounced drop at 870 °C and 920 °C. Conversely, the impact toughness exhibited a non-monotonic trend: it gradually decreased, reaching a minimum at 820 °C, before rapidly increasing with further rises in aging temperature. Quantitative analysis of the strengthening contributions demonstrates that solid-solution and precipitation strengthening are the dominant mechanisms. The marked decline in yield strength at elevated aging temperatures is primarily attributed to the diminished precipitation strengthening effect due to γ′ coarsening. Furthermore, the variation in impact toughness can be linked to the proportion and size of dimples observed on the fracture surfaces, indicating a transition in the fracture mechanism driven by microstructural evolution. Full article

Despite the ecological sensitivity of the Yangtze River Source Region (YRSR), the current research critically lacks a quantified assessment of the spatial occurrence probability of Retrogressive Thaw Slumps (RTSs) in this specific high-altitude terrain. This study aims to bridge this knowledge gap by establishing a robust susceptibility assessment framework to accurately model the spatial distribution and risk levels of RTSs. The innovations of this research include (i) the construction of a complete and up-to-date 2024 RTS inventory for the entire YRSR based on high-resolution optical remote sensing; (ii) the integration of time-series spectral features (e.g., vegetation and moisture trends) alongside static topographic variables to enhance the physical interpretability of machine learning models; and (iii) the application of advanced ensemble learning algorithms combined with SHAP analysis to establish a comprehensive RTS susceptibility zonation. The results reveal a rapid intensification of instability, evidenced by an 83.5% surge in RTS abundance, with the CatBoost model achieving exceptional accuracy (AUC = 0.994), and identifying that specific static topographic factors (particularly elevations between 4693 and 4812 m and north-to-east aspect) and dynamic spectral anomalies (indicated by declining vegetation vigor and increasing surface wetness) are the dominant drivers controlling RTS distribution. This study provides essential baseline data and spatial guidance for ecological conservation and engineering maintenance in the Asian Water Tower, demonstrating a highly effective paradigm for monitoring permafrost hazards under climate warming. Full article

This study provides a quantitative assessment of the combined effects of progressive urbanization and changes in precipitation patterns (PPs) on the urban water cycle. The primary objective was to evaluate historical (1940–2024) and projected (to 2060) changes in total annual surface runoff (TSR) and retention capacity (RC) in the highly urbanized catchment of the Dłubnia River in Cracow, Poland. Simulations were performed using the EPA SWMM hydrodynamic model, supported by digitized historical land-use maps and long-term meteorological records. The results demonstrate that the dominant driver of the observed 6.4-fold increase in TSR and 6.8-fold loss of retention capacity (LRC) over the study period was the progressive increase in impervious surfaces. Although inter-annual variability in the amount and structure of annual precipitation (AP) strongly correlates with annual TSR (r = 0.97), its contribution to the long-term upward trend in TSR is marginal (r = 0.19). Land use and land cover change (LULC) exhibits an extremely strong correlation with the long-term TSR trend (r = 0.998). The study also highlights the high effectiveness of nature-based solutions (NbSs), particularly bioretention cells (BCs)/rain gardens, in mitigating the adverse hydrological effects of excessive surface sealing. Implementation of BCs covering just 3–4% of the total drained roof and road area is sufficient to fully offset the projected combined negative impacts of further urbanization and climate change (CC) in scope Representative Concentration Pathways (RCP4.5 and RCP8.5) projections on catchment retention capacity by 2060. These findings position strategically targeted, relatively small-scale bioretention as one of the most effective and feasible urban adaptation measures in mature, densely developed cities. Full article

This paper introduces an iceberg-based digital risk twin (DRT) framework for the health monitoring of complex engineering systems. The proposed model transforms multidimensional sensor and contextual data into a structured, interpretable three-dimensional geometry that captures both observable and latent risk components. Each monitored parameter is represented as a vertical geometric sheet whose height encodes a normalized risk level, producing an evolving iceberg structure in which the visible and submerged regions distinguish emergent anomalies from latent degradation. A formal mathematical formulation is developed, defining the mappings from the risk vector to geometric height functions, spatial layout, and surface composition. The resulting parametric representation provides both analytical tractability and intuitive visualization. A case study involving an aircraft fuel system demonstrates the capacity of the DRT to reveal dominant risk drivers, parameter asymmetries, and temporal trends not easily observable in traditional time-series analysis. The model is shown to integrate naturally into AI-enabled health management pipelines, providing an interpretable intermediary layer between raw data streams and advanced diagnostic or predictive algorithms. Owing to its modular structure and domain-agnostic formulation, the DRT approach is applicable beyond aviation, including power grids, rail systems, and industrial equipment monitoring. The results indicate that the iceberg representation offers a promising foundation for enhancing explainability, situational awareness, and decision support in the monitoring of complex engineering systems. Full article

In recent years, human activities have impacted surface water and groundwater and their interactions with natural water bodies. Lake Cuitzeo is one of Mexico’s most important water bodies but has significantly reduced its flooded area in recent years. Previous studies did not explicitly evaluate the combined effects of hydrological variables on lake dynamics, limiting the understanding of how basin-scale processes influence lake-level. The objective of this study is to evaluate the change in spatio-temporal patterns of hydrological variables under climatic and anthropogenic stress in the Lake Cuitzeo endorheic basin. The proposed methodology uses the SWAT model to analyze at the basin scale, land use and land cover changes, and trends in precipitation and their effect on hydrological processes. Consequently, groundwater flow interactions were assessed for the first time for the Cuitzeo Lake Basin using an automatically coupled SWAT-MODFLOW (v3, 2019), despite limited observational data. A statistically significant change in mean precipitation was detected beginning in 2015, with a decrease of 10.22% compared to the 1973–2014 mean. Land use and land cover changes between 1997 and 2013 resulted in a 26.20% increase in surface runoff. In contrast, estimated evapotranspiration decreased by 1.77%, potentially associated with the reduction in forest cover. As a combined effect of decreased precipitation and land use and land cover change, groundwater percolation declined by 6.34%. Overall, the combined effects of climatic variables and anthropogenic activities have altered lake–aquifer interaction. Full article

Through a comprehensive analysis of urban vegetation summer seasonal and interannual patterns in the Bucharest metropolis in Romania, this study explored the response of urban vegetation to heat waves’ (HWs) impact in relation to multi-climatic parameters variability from a spatiotemporal perspective during 2000–2024, with a focus on summer HWs periods (June–August), and particularly on the hottest summer 2024. Statistical correlation, regression, and linear trend analysis were applied to multiple long-term MODIS Terra/Aqua and MERRA-2 Reanalysis satellite and in situ climate data time series. To support the decline in urban vegetation during summer hot periods due to heat stress, this study found strong negative correlations between vegetation biophysical observables and urban thermal environment parameters at both the city center and metropolitan scales. In contrast, during the autumn–winter–spring seasons (September–May), positive correlations have been identified between vegetation biophysical observables and a few climate parameters, indicating their beneficial role for vegetation growth from 2000 to 2024. The recorded decreasing trend in evapotranspiration from 2000 to 2024 during summer HW periods in Bucharest's metropolis was associated with a reduction in the evaporative cooling capacity of urban vegetation at high air temperatures, diminishing vegetation’s key function in mitigating urban heat stress. The slight decline in land surface albedo in the Bucharest metropolis due to increased urbanization may explain the enhanced air temperatures and the severity of HWs, as evidenced by 41 heat wave events (HWEs) and 222 heat wave days (HWDs) recorded during the summer (June–August) period from 2000 to 2024. During the severe 2024 summer heat wave episodes in the south-eastern part of Romania, a rise of 5.89 °C in the mean annual land surface temperature and a rise of 6.76 °C in the mean annual air temperature in the Bucharest metropolitan region were observed. The findings of this study provide a refined understanding of heat stress’s impact on urban vegetation, essential for developing effective mitigation strategies and prioritizing interventions in vulnerable areas. Full article

Cloud-based Earth observation platforms, such as data cubes, enable reproducible analyses of long-term satellite time series for climate and urban studies. In parallel, Essential Climate Variables (ECVs) provide a standardised framework for monitoring climate dynamics, with urban land cover and temperature being particularly relevant in historic urban contexts. This study analyses long-term trends and statistical associations between satellite-based ECVs and urbanisation indicators within the Historic Urban Landscape (HUL) of Sfax (Tunisia) from 1985 to 2021. Using the Digital Earth Africa (DEA) data cube, we derived six urban spectral indices (USIs), land surface temperature, air temperature at 2 m, wind characteristics, and precipitation from Landsat and ERA5 reanalysis data. An automated and reproducible Python-based workflow was implemented to assess USI behaviour, evaluate their performance against the Global Human Settlement Layer (GHSL), and explore spatio-temporal co-variations between urbanisation and climate variables. Results reveal a consistent increase in air and surface temperatures alongside a decreasing precipitation trend over the study period. The USIs demonstrate comparable accuracy levels (≈88–90%) in delineating urban areas, with indices based on SWIR and NIR bands (NDBI, BUI, NBI) showing the strongest statistical associations with temperature variables. Correlation and multivariate regression analyses indicate that temporal variations in USIs are more strongly associated with air temperature than with land surface temperature; however, these relationships reflect statistical co-variation rather than causality. By integrating satellite-based ECVs within a data cube framework, this study provides an operational methodology for long-term monitoring of urban-climate interactions in historic Mediterranean cities, supporting both climate adaptation strategies and the objectives of the UNESCO HUL approach. Full article

Tillage practices critically influence soil’s physical properties, which are fundamental to sustainable agriculture in temperate climates. This review evaluates how conventional tillage (CvT; e.g., moldboard and chisel plowing), reduced tillage (RT), and conservation tillage (CT), particularly no-tillage (NT), affect six key indicators: bulk density (BD), saturated hydraulic conductivity (Ks), wet aggregate stability (WAS), penetration resistance (PR), available water capacity (AWC), and soil organic carbon (SOC). Special emphasis is placed on differentiating topsoil and subsoil responses to inform climate-resilient land management. A total of 70 peer-reviewed studies published between 1991 and 2025 were analyzed. Data were extracted for BD, Ks, WAS, PR, AWC, and SOC across tillage systems. Depths were standardized into topsoil (0–10 cm) and composite (>10 cm) categories. Descriptive statistics were used to synthesize cross-study trends. NT showed lower mean BD in the topsoil (1.32 ± 0.08 Mg/m³) compared with moldboard plow (1.33 ± 0.09) and chisel tillage (1.39 ± 0.12); however, the effects of tillage on BD were not statistically significant, while BD was higher at composite depths under NT (1.56 ± 0.09 Mg/m³), indicating subsoil compaction. Ks improved under NT, reaching 4.2 mm/h with residue retention. WAS rose by 33.4%, and SOC increased by 25% under CT systems. PR tended to be elevated in deeper layers under NT. Overall, CT, particularly NT, improves surface soil’s physical health and SOC accumulation in temperate agroecosystems; however, persistent subsoil compaction highlights the need for depth-targeted management strategies, such as controlled traffic, periodic subsoil alleviation, or deep-rooted cover crops, to sustain long-term soil functionality and climate-resilient production systems. Full article

With rapid socioeconomic development and intensified human activities, nitrogen (N) loads have continued to rise, exerting significant impacts on the environment. Most existing studies focus on single cities or short time periods, which limits their ability to capture nitrogen dynamics under rapid urbanization. Based on statistical data from multiple cities in Zhejiang Province from 2011 to 2021, this study applied nitrogen balance accounting and statistical analysis to systematically evaluate the spatiotemporal variations in nitrogen inputs, outputs, and surpluses, as well as their driving factors. The results indicate that although nitrogen inputs and outputs fluctuated over the past decade, the overall nitrogen surplus showed an increasing trend, with the nitrogen surplus per unit area rising from 49.89 kg/(ha·a) in 2011 to 62.59 kg/(ha·a) in 2021. Zhejiang’s nitrogen load was higher than the national average but remained below the levels of highly urbanized regions such as the Yangtze River Delta and Pearl River Delta. Accelerated urbanization and increasing anthropogenic pressures were identified as major contributors to the rising nitrogen surplus, with significant inter-city disparities. Cities like Hangzhou, Ningbo, Wenzhou, and Jinhua were found to face higher risks of nitrogen pollution. Redundancy analysis and Pearson correlation analysis revealed that nitrogen surplus was positively correlated with cropland area, livestock population, total population, precipitation, GDP, and industrial output, further highlighting the dominant role of human activities in nitrogen cycling. This study provides the long-term quantitative assessment of nitrogen balance under multi-city coupling at the provincial scale and identifies key influencing factors. These findings provide scientific support for integrated nitrogen management across multiple environmental compartments in Zhejiang Province, including surface water, groundwater, agricultural systems, and urban wastewater, under conditions of rapid urbanization. Full article

In marine hydrodynamics, the core of the boundary element method (BEM) lies in the numerical calculation of the free-surface Green’s function. With the rise of artificial intelligence, using neural networks to fit Green’s function has become a new trend, yet most existing studies are confined to fitting Green’s function in infinite water depth. In this paper, a neural network fitting method for a finite-depth Green’s function is proposed. The classical Multilayer Perceptron (MLP) network and the emerging Kolmogorov–Arnold Network (KAN) are employed to conduct global and partition-based fitting experiments. Experiments indicate that the partition-based KAN fitting model achieves higher fitting accuracy, with most regions reaching 4D fitting precision. For large-scale data input, the average time for the model to calculate a single Green’s function value is 0.0868 microseconds, which is significantly faster than the 0.1120 s required by the traditional numerical integration method. These results demonstrate that the KAN can serve as an accurate and efficient model for finite-depth Green’s functions. The proposed KAN-based fitting method not only reduces the computational cost of numerical evaluation of Green’s functions but also maintains high prediction precision, providing an alternative approach to accelerate BEM calculations for floating body hydrodynamic analysis. Full article

During the long-term operation of composite insulators in transmission lines, they are easily affected by harsh environments, resulting in hidden defects such as surface contamination, shed damage, and adhesive failure. A defect detection method based on microwave for composite insulators was proposed, and a corresponding numerical simulation model was established. A large-aperture horn antenna model with a wide frequency band and high gain was built, the accuracy of which was verified. In the simulation, shed crack defects were selected as representative probes to model typical defects in the sheds, sheath, and core rod of composite insulators. This study investigated defects with varying severity levels and spatial distributions while also exploring optimal placement configurations for detection antennas. An experimental platform was built for testing, and it was found that the experimental results showed a similar changing trend to the simulation results, which further verified the accuracy of the simulation model and the feasibility of simulating defects. Full article

With the industry development of sea cucumber Apostichopus japonicus aquaculture, the indoor high cost and low survival rate have become serious problems. Therefore, it is necessary to optimize substrate selection for seedling protection in outdoor pond net cages. This study explores the succession of periphyton on the different substrate surface types, including a curvimurate net (CU), nylon mesh (NM), and ground cages (including a ground cage net (CN) and ground cage plate (CP)), and their effects on the seedling protection of sea cucumbers. In addition, we monitored the substrates’ dry weight, chlorophyll-a, and the community composition of substrates, alongside seedling growth, yield, and survival rate. The results show that a total of 7 phyla, 23 genera, and 31 species were detected on the substrates, with diatoms dominating (19 species) and Chlorophyta (4 species) being the main species. The CU had the highest total number of alga species attached, significantly higher than the other substrates in week 13 (p < 0.05). In week 9, the diatom density dropped to its lowest point, and, after September, it rose with the decrease in water temperature. In terms of dry weight with and without ash, CP increased rapidly in the early stage, with NM, CU, and CP being significantly higher than CN in week 13 (p < 0.05). The chlorophyll-a content showed a decreasing–increasing–decreasing trend, with CU reaching 3.62 ± 0.48 μg/cm² in the 13th week, significantly higher than other substrates (p < 0.05). Finally, the A. japonicus survival rate and yield in the CU group at week 12 were significantly higher than those in the NM and ground cage groups (p < 0.05). At week 17, the average weight, yield, and survival rate in the CU group were still optimal, with the yield 5.76 times that in the initial dosage. These results suggest that the CU has a suitable mesh size, has good permeability, and may stably support sediment, which is conducive to the growth of benthic diatoms. In addition, it can provide sufficient natural feed and a good habitat environment and is the preferred substrate for A. japonicus seedling protection in outdoor pond net cages. Full article

Background: Prolonged sitting has been associated with adverse cardiovascular and neuromuscular responses; however, the temporal onset of these acute physiological changes remains unclear. This study aimed to determine the acute effects of prolonged sitting on blood flow, blood pressure, and muscle activity. Methods: A non-controlled clinical trial was conducted with 21 healthy adults (22.5 ± 1.60 years), both male and female. Participants remained seated continuously for three hours, with data collected every 20 min, including infrared thermography, blood pressure, and electromyographic activity. Skin temperature was measured using infrared thermography on the calf region of both legs, and the mean temperature was analyzed. Systolic and diastolic blood pressure were measured using an oscillometric device, and mean arterial pressure was subsequently calculated. Muscle activity was assessed through surface electromyography, using median frequency and root mean square values. Statistical analysis was performed using the Friedman test and the Durbin–Conover post hoc test, along with a subjective trend analysis of each variable over time. Results: A significant reduction was observed in both calf skin temperature and median frequency after 60 min of uninterrupted sitting (p < 0.05). Mean and systolic blood pressure exhibited an increasing trend after 160 min (p < 0.05). Conclusions: The exposure–response data from this study may contribute to the planning of future interventions aimed at refining recommendations for breaking up prolonged sitting periods. Full article