Search Results (770)

Ground-surface temperature (GST) in maritime Antarctic ice-free areas is influenced by atmospheric forcing, snow cover, surface energy and topography. Previous PERMATHERMAL studies in Livingston and Deception Islands have shown changes in air and ground-surface thermal regimes, with fewer cold conditions, greater thawing influence and strong snow-cover modulation. However, the interval in which GST responds effectively to radiative and topographic forcing remains poorly explored. We characterize the station- and season-specific timing of the thermally effective GST thawing period and evaluate topographic and modeled potential controls on its thermal intensity and cumulative effect around the Spanish Antarctic Station Juan Carlos I, Hurd Peninsula, Livingston Island. Onset and end were objectively delimited by using three consecutive days with daily mean GST > 0.5 °C and daily thermal amplitude > 1.0 °C. Hourly GST records from six PERMATHERMAL stations were combined with potential radiation, potential insolation and topographic variables derived from a high-resolution UAV-based DEM. Accumulated thawing degree days were strongly influenced by period duration. Mean thermal intensity was primarily associated with elevation, while mean modeled potential radiation provided additional explanatory power only when combined with elevation. This UAV–GIS–GST approach provides a simple framework for assessing local surface–atmosphere coupling in remote Antarctic ice-free areas. Full article

Using monthly and daily reanalysis data from the NCEP/NCAR and ERA-5 spanning 1980 to 2025, this study investigates the key preceding forcing factors influencing winter temperatures in the Bohai Sea and northern Yellow Sea (BSNYS) region. The analysis reveals that autumn sea ice anomalies in the Barents–Kara Seas serve as an important predictor for winter temperature anomalies in this region. Sea ice anomalies in this region typically persist from autumn to winter, continuously feeding back to the atmosphere and altering the temperature gradient. This induces lower-tropospheric baroclinic instability, which in turn drives atmospheric circulation adjustments through the feedback of transient eddies onto the mean flow, further strengthens the Eurasian (EU)-like teleconnection pattern, and ultimately affects the climate in the BSNYS region. Furthermore, the correlation between autumn Barents–Kara sea ice and winter temperature anomalies in the BSNYS region shifts from insignificant to significant when comparing the longer period (1950–2025) with the study period, likely due to the enhanced interannual variability of autumn sea ice in this region. This study reveals the key physical processes through which autumn Arctic sea ice influences the winter climate in the mid-latitude BSNYS region, and serves as a useful benchmark for seasonal prediction of winter temperatures in this region. Full article

A multi-analytical investigation was carried out to elucidate the deterioration processes affecting the stone materials of the Arca di Cansignorio della Scala in Verona (Italy) and to characterize the surviving traces of its original polychrome and gilded decoration. The study combined macroscopic mapping, stratigraphic sampling, optical microscopy (OM), environmental scanning electron microscopy coupled with energy-dispersive X ray spectroscopy (ESEM-EDS), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and ion chromatography (IC). The monument, predominantly carved from Candoglia marble, exhibits three principal weathering patterns: (i) rain washed areas affected by marble decohesion, (ii) grey deposits corresponding to dirt accumulation areas; and (iii) sulphation-induced black crusts developed in dirt wetting areas. In addition, severe mechanical deterioration was found to be associated with early twentieth-century structural consolidation interventions involving embedded iron bars, whose corrosion-driven volumetric expansion generated vertical cracking. Stratigraphic and microanalytical investigations revealed the presence of original azurite-based polychromy, proteinaceous and lipidic binding media, lead white preparatory layers, and multiple applications of gold leaf. The analytical results highlight the complex interplay between environmental exposure, atmospheric pollution, the incompatibility of materials introduced during past restorations campaigns. Furthermore, they contribute to a better understanding of the composition, execution techniques and preservation state of the surviving decorative layers, providing a scientific basis for future conservation strategies. Full article

Endothelial responses to oxidative stress are influenced by the presence of blood flow and shear stress. To better capture these conditions in vitro, we developed an endothelium-on-a-chip model for the study of acute oxidative injury in EA.hy926 cells under flow. We adapted the culture conditions for use outside a conventional 5% CO₂ atmosphere, and we improved endothelial adhesion and retention under flow by collagen coating of the chip surface. Our model tolerated shear stress of up to 0.89 Pa, which corresponds to the in vivo values experienced by endothelial cells in the aorta and venous system. On this model, we designed an acute oxidative injury protocol based on high concentrations of hydrogen peroxide (H₂O₂) as an endogenous source of oxidative stress and 2,2′-azobis(2-amidinopropane) dihydrochloride (AAPH) as an exogenous molecule. The inclusion of flow increased the apparent sensitivity of the model to oxidative injury compared to static conditions, as the IC₅₀ values decreased from 16.2 mM to 12.0 mM for H₂O₂ and from 100.7 mM to 72.5 mM for AAPH under flow conditions. Pretreatment with quercetin (1.5 µM) reduced AAPH-induced oxidative injury, thus showing the potential applicability of the model for antioxidant screening assays. Full article

The search for extraterrestrial life has traditionally focused on environments where liquid H₂O is stable over long timescales, such as subsurface aquifers, hydrothermal systems, or ice-rich deposits. However, many planetary bodies are characterized by active cycles of particulate transport involving either mineral dust or atmospheric aerosols. In planetary science, these are commonly distinguished as refractory particles (non-volatile mineral dust) and volatile or mixed aerosol particles, including condensates such as ices, organics, or acidic droplets. Here, we propose the concept of planetary aerobiomes, defined as distributed particle-associated microbial persistence and dispersal systems in extraterrestrial environments. In this framework, refractory mineral particles may act as mobile particle-associated microenvironments that could support microbial survival and dispersal, while in some cases also providing partial physical shielding from environmental stressors. Drawing on observations from terrestrial dust-associated microbiomes and mineral–microbe interactions, particle-associated systems may represent previously overlooked ecological substrates in planetary environments. Rather than replacing models centred on environments with persistent liquid H₂O, this perspective expands them by considering particle-associated microenvironments as transient but potentially relevant biosignature-preservation niches in arid, dust-dominated worlds such as Mars, as well as in aerosol-rich environments including Titan, Venus, and icy moons. We further discuss the implications for life-detection strategies, highlighting atmospheric particles as potential reservoirs of biosignatures, and consider their relevance for applied microbiology, including in situ resource utilization (ISRU) and bioregenerative life-support systems (BLSS). Beyond astrobiological implications, understanding microbial persistence within particle-associated extreme environments may provide useful models for applied microbiology, including stress-resilient microbial engineering, biomining, contamination control, and bioregenerative technologies for space exploration. Full article

Rapid Arctic warming has significantly altered sea ice–atmosphere boundary layer processes, which low-resolution models struggle to resolve accurately. This study evaluates the historical performance (1958–2014) of four high-resolution models from CMIP6 HighResMIP—EC-Earth3P-HR, CNRM-CM6-1-HR, HadGEM3-GC3.1-HH, and Fgoals-f3-H—against ORAS5 and CMEMS reanalysis datasets and examines their physical response to rapid warming under the SSP5-8.5 scenario (2015–2025). Results show substantial intermodel differences in simulating Arctic sea ice thickness, mixed layer depth, sea surface temperature and salinity, and deep convection. HadG-EM3-GC3.1-HH and CNRM-CM6-1-HR perform best overall, reliably reproducing trends in the two major deep convection regions, meridional temperature–salinity gradients, and long-term evolution with lower biases and higher correlations. Under decadal strong warming, models generally simulate shoaling mixed layers in deep convection zones and upper-water destabilization in the Canada Basin, but responses in sea ice, eddy kinetic energy, and transect temperature–salinity vary markedly. HadGEM3-GC3.1-HH and CNRM-CM6-1-HR better represent physical quantities and ocean stratification consistent with observed real-world responses. We conclude that these two models are more suitable for studies of Arctic sea ice–atmosphere boundary layer changes and deep convection, providing a basis for high-resolution model selection and Arctic climate projection. Full article

Even under a warming climate, winter sea ice in the Bohai Sea continues to threaten ships and offshore/coastal infrastructure. Reliable pre-season prediction of the overall wintertime sea ice condition in the Bohai Sea, as represented by the Bohai Sea Ice Grade (BSIG), is therefore important for disaster preparedness and mitigation. Based on the 1979–2024 BSIG record, this study compares seven statistical and AI-based seasonal prediction methods: analog year analysis, multiple linear regression, stepwise regression, Principal Component Regression, a cross-correlation-based regression model, support vector regression, and the Bayesian Ensemble Bohai Ice Grade Net (BE-BIGNet). As potential precursors, we considered sea ice extent in 14 Arctic regions together with 114 large-scale atmospheric and oceanic circulation indices. The results suggest substantial differences in predictive skill among the methods. Among the tested approaches, BE-BIGNet, which combines Bayesian regularization with bootstrap median ensembling, achieves strong full-period performance and stable skill during the independent test period, suggesting that it may provide a useful framework for operational BSIG forecasting in the Bohai Sea. Full article

This paper presents a theoretical engineering feasibility analysis of the RK-X photocatalytic process for In Situ Resource Utilisation (ISRU) on Mars. Experimental validation under simulated Martian conditions is the essential next step before any mission deployment claim can be made. The RK-X process converts the two most abundant Martian resources, atmospheric carbon dioxide (CO₂) and subsurface water ice (H₂O), into formic acid (HCOOH) and oxygen (O₂) through a fulvic acid-based photocatalytic cycle validated at the industrial scale in Hungary. A reference module processing 10 tonnes of CO₂ per Earth year yields 10.459 tonnes of formic acid and 3.636 tonnes of oxygen, sufficient to sustain a six-person crew for approximately two Earth years with a 198% safety margin over nominal respiratory demand. The economic analysis indicates that importing equivalent oxygen from Earth costs $1.82–$3.64 million per year; equivalent energy storage (Li-ion) costs $30.5–$61 million for one-time use. Formic acid stores 15.25 MWh of energy in ambient-stable liquid form at a round-trip efficiency of 68.64% without cryogenic infrastructure. A photovoltaic array of 55.37 m² provides the primary energy source; a kilowatt-class nuclear fission reactor constitutes the strategic opportunity for continuous, dust-storm-immune operation with free thermal co-generation. Three critical research gaps have been identified requiring laboratory validation before Mars deployment: (i) catalyst performance at the Martian CO₂ partial pressure (p(CO₂) < 10 mbar, T = 15 °C); (ii) water ice and dry ice extraction at an operational scale; and (iii) integrated closed-loop system demonstration. Built on Earth-proven chemistry with identified, addressable development pathways, the RK-X process theoretically resolves the problems of oxygen supply, seasonal energy storage, water management, and cryogenic infrastructure within a single closed-loop chemical cycle. Full article

The Northern Sea Route (NSR) is becoming increasingly accessible as Arctic sea ice declines, motivating data-driven forecasts of seasonal navigability. We compiled a 13-year (2013–2025) monthly dataset of AMSR2 sea ice concentration (SIC) and ERA5 atmospheric reanalysis variables over the NSR corridor (68–80° N, 30–180° E) and benchmarked a hierarchy of forecasting models for 1-, 3-, and 6-month lead times. Baselines (climatology, persistence, anomaly persistence, SARIMA, ridge regression) were compared with compact deep learning architectures (LSTM, Transformer; 10,000–70,000 parameters) trained on 12-month sequences with anomaly targets and five-seed ensembles. Three findings emerge. First, the seasonal cycle explains 98.0% of the monthly SIC variance, so climatology alone yields RMSE = 4.56% and three-class navigability accuracy of 87.5%. Second, SARIMA, the compact LSTM ensemble, random forest, and MLP_small all yield small positive skill scores over climatology: SARIMA achieves the lowest 1-month RMSE (3.98%, skill score +0.239), while the compact LSTM ensemble shows positive skill at all horizons (mean skill score +0.038); however, the bootstrap confidence intervals overlap and these differences are not statistically distinguishable from climatology. Third, all skilful models converge to identical classification metrics (accuracy 0.875, macro-F1 0.78, κ = 0.76); McNemar tests and overlapping bootstrap confidence intervals show no statistically significant differences. Permutation importance confirms that AMSR2 ice-state features dominate, whereas the high raw correlations of ERA5 radiation variables collapse after detrending. These results indicate that compact statistical and deep learning models are equivalent for NSR seasonal navigability prediction and that honest baseline comparison is essential when seasonal cycles dominate. Full article

Atmospheric ice accretion on transmission lines threatens the safe operation of power systems, whereas existing monitoring methods mainly focus on ice thickness, load, or morphology and provide limited material-related information for distinguishing ice types. This study investigates the dielectric response of ice and snow samples to evaluate its feasibility for preliminary ice-type discrimination. Artificial glaze ice and natural snow samples were measured using a self-built temperature-controlled parallel-plate system within 10–100 kHz. The effects of freezing-water conductivity, temperature, surface water film, and snow density were examined, and representative glaze ice, dry snow, and wet snow samples were further compared under the same measurement framework. The results show that the dielectric constant generally decreases with frequency, while conductivity, water film, and density mainly increase the response magnitude and, in some cases, alter the prominence of loss-related features. These trends are consistent with reported dielectric dispersion, conductive loss, and snow density-related mixing behavior. Dielectric loss provides clearer differences between glaze ice and snow-related samples than dielectric constant alone, whereas dry and wet snow require combined consideration of dielectric constant and loss. A preliminary two-step hierarchical framework is therefore proposed for the tested sample set. Further validation over broader frequency ranges and conductor-like geometries is required before practical application. Full article

During the worldwide energy transition, wind power has become a leading development direction. Compared to large-scale horizontal-axis wind turbines (HAWTs), small-scale vertical-axis wind turbines (VAWTs) show potential, lack yaw mechanisms, adapt to wind direction changes, and are cost-effective. However, small-scale VAWTs operate in the near-surface atmospheric boundary layer and are sensitive to low-temperature and high-humidity climates, which cause blade icing. Ice buildup leads to fluctuations in aerodynamic loads, reduces power output, and diminishes stability. This study focuses on the NACA-0018 airfoil, using a low-temperature wind tunnel platform to simulate freezing durations to obtain ice characteristics on the blade surface. Based on ice profiles, numerical models were developed. Computational fluid dynamics (CFD) techniques were used to perform unsteady simulations of aerodynamic performance at various icing durations, investigating the influence on the power coefficient. The results indicate that the effect of icing duration on the average power coefficient depends on TSR. At the 5 min icing stage, the optimal tip-speed ratio decreases. Icing deteriorates aerodynamic performance at high tip-speed ratios, while producing positive optimization effects at low tip-speed ratios. This paper reveals the variation patterns of aerodynamic performance and differentiated mechanisms during the icing process of small vertical-axis wind turbine blades, providing a theoretical basis and data support for the development of surface anti-icing technologies and safe, efficient operation in low-temperature environments. Full article

The new method proposed in this study, featuring a one-finger gripper, uses three types of forces—van der Waals force, capillary force, and coupling force due to ice—to grip and release microobjects to submillimeter-sized objects (5 to 300 µm). The gravitational force of an object can be neglected in the case of microobjects, but this is not the case for submillimeter-sized objects. This is the first reason that we use the coupling force due to ice; the second reason is that the shape of a micro- or submillimeter-sized object does not matter in this case. The usage of all three forces yields greater versatility regarding objects of different sizes and shapes and, consequently, greater overall reliability in gripping or releasing compared with methods that use only one or two of the mentioned forces. In this study, the laboratory set-up involved the active control of the temperature for both the one-finger gripper and the releasing surface for objects from −25 °C to 40 °C in a closed dust-free chamber in atmospheric air at relative humidity (RH) = 30%. A relatively low RH was achieved with the RH controller, enabling the release or grip procedures to last approx. 2–3 s for microobjects and 6 s for submillimeter-sized objects with the same equipment. Full article

Gondolas are a useful mode of transportation in the mountainous regions. In regions located at high altitudes, atmospheric icing is a significant safety hazard to gondola infrastructure. In this study, multiphase numerical simulations of ice accretion on the monopole gondola tower were performed and validated against experimental and analytical model results. An analytical model has limitations for calculating ice loads on large cylinder diameters, and conducting experiments on large cylinders is also challenging due to practical constraints. Ansys FENSAP-ICE 2025 R2, as the primary numerical simulation tool, appears to be an attractive alternative for better estimation of ice loads on structures with larger diameters. The numerical analysis demonstrates that the ice accretion on the access ladder of the gondola tower is more critical than its main structure. This is because the ice growth on the smaller components is higher than on the larger components. A solution based on passive structural design is suggested, in which a semi-circle-shaped wind shield is introduced along the windward side of the tower which successfully diverts the flow by creating a protective droplet shadow on the trailing components, significantly reducing the accreted ice loads. It can also serve as a safety barrier for maintenance personnel. The study also showed that increasing the shield diameter ultimately reduced overall ice accretion, due to the dominant droplet drag forces over inertial forces. Full article

Accurate cloud and cloud-shadow segmentation is a crucial step in optical remote sensing image preprocessing, playing a significant role in subsequent applications such as land-cover classification and change detection. However, the complexity of cloud/shadow shapes and noise interference (e.g., snow and ice, buildings, complex backgrounds, and atmospheric optics) make this task challenging. Although existing deep learning methods have achieved remarkable results in cloud segmentation tasks, a better balance between computational efficiency and segmentation accuracy is still needed. Traditional deep learning models have good detail and generalization capabilities due to their local feature extraction ability and spatial invariance, but they are relatively weak in processing global context information, leading to false positives and false negatives in complex scenarios. Encoders based on state space models (such as VMamba) can effectively capture global context through long-range dependency modeling, but there is still room for optimization in computational efficiency. Additionally, complex attention mechanisms (such as CBAM) can improve feature representation capability, but the large number of parameters limits the deployment efficiency of models. This paper conducts a systematic architectural exploration of the MCloudX cloud segmentation network, seeking a balance between efficiency and accuracy from three directions: backbone network modernization, encoder efficiency optimization, and attention mechanism lightweighting. Through comprehensive ablation experiments on SPARCS and L8-Biome datasets, we systematically evaluate the independent and synergistic effects of each component and validate them on Biome_3 and SPARCS datasets. Experimental results show that the proposed optimization configuration (ResNet50+LocalMamba+ECA-Net) significantly improves computational efficiency while maintaining comparable accuracy to the baseline. We name this optimization configuration LECloud, providing valuable empirical references for future research on efficient remote sensing segmentation architectures. Full article

This article provides a comprehensive review of current state of knowledge regarding the ongoing development of hydrogen-fueled internal combustion engines (H₂ICE). It describes the key challenges, the resolution of which will determine further progress in the development, practical application, and popularization of H₂ICE. The article details the problems associated with creating and optimizing the fuel mixture in the H₂ICE cylinder. It also highlights directions for development of hydrogen injection, ignition, and boosting processes. The risks resulting from abnormal combustion processes and the related optimization of combustion strategies in H₂ICE are extensively discussed. Problems and difficulties associated with adapting existing engine designs to hydrogen fueling are also considered. Attention is paid to the different degradation patterns and the requirements placed on engine lubricating oil when fueling engines with hydrogen. The article then describes emissions from hydrogen-fueled engines, with particular emphasis on high NOx emissions and methods for reducing those emissions. The last part of the article discusses the influence of hydrogen admixture in various hydrocarbon fuels on combustion processes, engine performance and harmful exhaust emissions into the atmosphere. The article stands out in that it identifies and describes the most important challenges that determine the further development of H₂ICE engines. It also provides a comprehensive overview of the current state of knowledge in the field of ongoing development of hydrogen-powered internal combustion engines (H₂ICE). Full article