Search Results (897)

A methodology for deriving high-resolution (5-km) surface shortwave radiative (SWR) fluxes over the Arctic was applied to observations acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) during the spring and summer melt season (March–September) of 2007, when the Arctic experienced a historically significant and well-documented decline in sea ice extent. The derived SWR fluxes were used to estimate solar heat input into the Arctic Ocean during the melt season, a task that had not previously been undertaken at such high spatial resolution. According to the National Snow and Ice Data Center (NSIDC), Arctic sea ice extent reached a record minimum of 4.13 million km² on 16 September 2007, approximately 38% below the 1979–2000 climatological mean and 24% below the previous record minimum in 2005. This extreme reduction in sea ice resulted in several weeks of ice-free opening along portions of the ‘Northwest Passage’. Availability of high spatial resolution SWR fluxes in the Arctic is particularly important for improving estimates of solar heat input into the Arctic Ocean, especially within the highly heterogeneous marginal ice zone. To facilitate comparison with sea ice concentration products from NSIDC, the MODIS-derived 5-km SWR fluxes were aggregated to 0.25° equal-area grid cells (approximately 25 km resolution). Our results show that the abrupt increase in the open water fraction produced anomalies in solar heating to the upper ocean exceeding 300%, hereby enhancing the ice–albedo feedback mechanism and promoting further sea ice melt. The estimated monthly cumulative solar heat input to the ocean for a nominal 1° grid cell was 164.9 MJ m⁻² in May. In contrast, the corresponding four 0.25° sub-grid cells, resolved using the high-resolution MODIS data, exhibited cumulative heat inputs of 58.0, 93.0, 189.3, and 296.4 MJ m⁻², respectively. Although the average heat input for the 1° grid cell (165 MJ m⁻² was similar to the average value obtained from the four 0.25° grid cells (159 MJ m⁻² the substantial sub-grid variability is important because the oceanic and sea-ice responses to solar heating are highly nonlinear. Consequently, unresolved spatial variability can significantly affect the magnitude of derived quantities and associated feedback processes. These findings demonstrate the importance of high-spatial-resolution radiative flux information for accurately quantifying ocean heating and ice–ocean interactions in the Arctic. Full article

Background/Objectives: Automated insulin delivery (AID) systems have improved the management of type 1 diabetes (T1D), but exercise and nutrition remain challenging because they rapidly alter glucose flux, substrate oxidation, hepatic glucose output, insulin requirements, and fuel availability. This narrative review aimed to synthesize current evidence on the interaction between AID systems, physical activity, and nutritional strategies from a metabolism-oriented perspective. Methods: A narrative bibliographic approach was used to integrate evidence from clinical trials, observational studies, technical studies, consensus statements, and reviews involving people with T1D across different life stages, including pediatric, adolescent, adult, and pregnancy-related contexts, when available. The review focused on AID systems, exercise physiology, nutritional strategies, meal announcement, bolus adjustment, dual-hormone systems, metabolic biomarkers, and emerging metabolomic approaches. Results: AID systems generally improve time in range and reduce hypoglycemia across several user groups, although most exercise- and nutrition-specific evidence comes from adult and pediatric/adolescent cohorts rather than pregnancy-specific exercise studies. Exercise-related glucose responses remain highly dependent on user input, exercise modality, insulin on board, meal timing, and metabolic state. Planned exercise announcement, prandial bolus reduction before postprandial activity, and individualized carbohydrate intake remain key strategies. Biomarkers such as lactate, ketone bodies, non-esterified fatty acids, and counter-regulatory hormones may help explain interindividual variability and support future personalization. Conclusions: Nutrition and exercise management in AID users should be interpreted as a dynamic metabolic interface among exogenous insulin, endogenous counter-regulation, substrate availability, and algorithmic control. Emerging approaches, including activity sensors, adaptive algorithms, dual-hormone systems, digital twins, and metabolomics-informed personalization, may improve safety and reduce user burden, but several remain exploratory and require further validation in diverse free-living conditions. Full article

Magnetic flux leakage (MFL) testing is a vital non-destructive testing method used to identify defects in oil and gas pipelines and critical components. However, variations in defect geometry and testing conditions can lead to inaccurate data and imbalanced feature distributions, which compromise detection outcomes. To address these challenges, this paper presents a defect classification approach for MFL testing based on generating expansion and the Dual-Channel Vision Transformer (DC-ViT). First, COMSOL finite element software (version 6.1) was used to simulate magnetic flux leakage for different types of pipeline defects. Axial and radial dual-channel signals were extracted to create the initial dataset. Next, a Conditional Variational Autoencoder (CVAE) was used for Generate Expansion to effectively mitigate sample scarcity and defect category imbalance. Finally, the DC-ViT model was constructed and trained using the Generate Expansion dataset as input to achieve multidimensional feature fusion and classification prediction for defects. Experimental results demonstrate 97.97% detection accuracy. The DC-ViT model outperforms traditional convolutional neural networks and single-channel models in terms of accuracy, precision, recall, and F1-score. These results validate the method’s effectiveness and robustness in complex defect scenarios and offer a novel approach to magnetic leakage signal detection. Full article

Mass–balance discrepancies exist between estimated land-based inputs and observed marine plastic inventories. While current global mass–balance models predominantly treat the open ocean as a passive terminal sink, they overlook the rapid expansion of offshore and deep-sea industrial frontiers. This review identifies offshore and deep-sea activities as active, in situ emission nodes of microplastics (MPs). Through a bibliometric analysis and numerical descriptions of studies, we document that direct offshore emissions are underrepresented in the current literature. By synthesizing these limited quantitative data, preliminary metrics indicate localized MP enrichment signals and elevated biological exposure near specific offshore infrastructures. Furthermore, plastics released directly into the marine environment bypass terrestrial weathering, undergoing distinct multiscale aging pathways governed by the complex interplay of wave-induced physical fragmentation bounded by critical size thresholds, UV-driven chemical photo-oxidation, and biological interactions. We conclude that refining global plastic budgets supports moving toward an integrated ocean-industrial framework. However, the synthesis remains constrained by data scarcity and high methodological heterogeneity across different environmental matrices. Future strategies must prioritize standardized in situ flux quantification and the incorporation of MP emission risks into offshore Environmental Impact Assessments. Full article

Rice–fish co-culture is widely promoted for mitigating nitrous oxide (N₂O) emissions from paddy soils, yet how the duration of co-culture reshapes the underlying nitrogen-cycling microbial community under low-nitrogen input remains poorly understood. This study aimed to (i) characterize how co-culture duration alters the rhizosphere microbial functional potential for N₂O production and consumption, and (ii) identify the water and soil variables linking fish activity to that response. The experiment was conducted during the 2024 rice growing season in the Qingtian rice–fish system (Zhejiang Province, China), a traditional agricultural heritage system managed without chemical fertilizer or supplementary feed. Three treatments (i.e., rice monoculture, first-year co-culture, and long-established (~10-year) co-culture) were compared using six independently bunded replicate plots each. Rhizosphere soils were collected at the tillering, heading and maturity stages for shotgun metagenomic profiling of nitrogen-cycling functional genes, with concurrent measurement of N₂O flux and water and soil physicochemical properties. Fluxes were uniformly low and did not differ among treatments (p > 0.05), defining a substrate-limited baseline. Against this baseline, first-year co-culture induced a coordinated shift toward complete denitrification (nosZ increased by 25–33% across all stages; nosZ/(nirK + nirS) rose to 0.99 at heading), associated with a transient water organic carbon pulse and dissolved-oxygen availability. The long-established system resembled monoculture, indicating a non-monotonic, duration-dependent response. Full article

Accurate modeling of topside ionospheric electron density is essential for improving GNSS positioning and understanding upper-atmosphere dynamics. A new four-dimensional (spatial and temporal) topside electron density model is developed using global GNSS radio occultation data within an L2-regularized artificial neural network framework. The model combines both empirical and physical variables, including geomagnetic coordinates, temporal parameters, solar flux ($F_{10.7}$), geomagnetic activity index ($Kp$), and key ionospheric parameters (NmF2 and hmF2). To support the modeling framework, two sub-models are first constructed to estimate NmF2 and hmF2 when direct measurements are unavailable. The full model is trained using COSMIC-1 data and evaluated against independent datasets, including COSMIC-1, GRACE, and incoherent scatter radar (ISR). The results show that the proposed sub-models reduce relative errors by 4.5% for hmF2 and 11.0% for NmF2 compared with IRI-2016. For the full topside $N_e$ modeling, the proposed approach achieves improvements of 35%, 36%, and 53% relative to IRI-2016 when evaluated against COSMIC-1, GRACE, and ISR datasets, respectively. A systematic analysis of input variables further indicates that both physical drivers and ionospheric structural parameters play essential roles in determining model performance. The new model incorporated with NmF2 and hmF2 sub-models still achieves a 16% improvement over IRI-2016 based on ISR data. In addition to statistical improvements, the model reproduces key ionospheric features, including the equatorial ionization anomaly (EIA) and the midlatitude summer nighttime anomaly (MSNA), under different solar activity conditions. These results demonstrate that the proposed model captures not only the statistical variability but also the underlying physical behavior of the topside ionosphere. Full article

Support structures in liquid hydrogen tanks act as localized thermal bridges between the ambient temperature outer vessel and the cryogenic inner vessel. However, the difference between support thermal bridge-induced localized heat input and equivalent uniform heat input remains insufficiently clarified, especially regarding their effects on local thermal behavior and support position-dependent thermodynamic response. In this study, a gas–liquid two-phase CFD model was developed for a 37.4 m³ liquid hydrogen tank at a 50% filling ratio. Localized heat flux regions were used to represent support thermal bridges, and an equivalent uniform heat input case with the same total heat input was introduced for comparison. The results show that localized support heat input concentrates the high-temperature region near the support-corresponding wall area and induces stronger local natural convection with a maximum velocity of approximately 0.27 m/s, compared to approximately 0.14 m/s in the uniform heat input case. The uniform heat input case produces a slightly higher overall gas-phase pressure, but it cannot capture the local heat accumulation and flow field reconstruction caused by support thermal bridges. Circumferential support position variation mainly affects the relative position between the localized heat source, gas region, liquid region, and gas–liquid interface. Upper support position variation has a more pronounced influence on local peak temperature and flow intensity than lower support variation. Axial support position variation mainly shifts the local high-temperature and high-velocity regions along the tank length, while its influence on overall pressure response is limited. These results indicate that equivalent uniform heat input can approximate the overall pressurization trend, but localized support heat input boundaries should be retained when local temperature fields, flow structures, and support layout effects are of concern. Full article

The forthcoming joint NASA/ASI (National Aeronautics and Space Administration/Italian Space Agency) Surface Biology and Geology Thermal Infrared (SBG-TIR) mission will operate in a sun-synchronous polar orbit collecting data on a global scale. The mission will acquire thermal infrared observations together with limited visible and near-infrared (VNIR) observations, consisting of two spectral bands and one panchromatic channel. In this context, and particularly given the limited number of VNIR bands, accurate retrieval of Vegetation Fractional Cover (FC) and Leaf Area Index (LAI) is particularly relevant. This is because it enables the synergistic use of VNIR and TIR observations to support vegetation monitoring and surface energy flux estimation during the mission. This study evaluates different machine learning approaches under different configurations for the retrieval of FC and LAI using the VNIR observations expected from the SBG-TIR mission. Synthetic datasets generated with the Soil Canopy Observation, Photochemistry and Energy Fluxes (SCOPE) radiative transfer model were used for model training and validation. Different input configurations were tested, including VNIR bands, the panchromatic channel, vegetation indices, and observation geometry variables. Model performance was assessed on independent test data, including uncertainty quantification. The optimal configuration, using Gaussian Process Regression (GPR), achieved RMSE values of 0.046 for FC and 0.053 m²/m² for LAI using a seven-channel input set, while yielding R² values greater than 0.9 for both variables. These results are consistent with previous studies, supporting the validity of the proposed approach. The trained models were subsequently applied to Sentinel-2 and evaluated against GBOV (Ground-Based Observations for Validation) reference measurements and standard Sentinel-2 biophysical products. The results showed strong statistical agreement with the Biophysical Processor implemented in the ESA Sentinel Application Platform (SNAP) toolbox, confirming the robustness of the proposed framework for operational estimation and mapping of FC and LAI in the context of the SBG-TIR space mission. Full article

Neutron capture reactions provide essential nuclear physics input for modeling the synthesis of heavy elements in stars. The growing precision of stellar spectroscopy and isotopic measurements in presolar SiC grains now demands cross sections with improved accuracy over the full energy range, and access to unstable nuclei relevant to slow (s-) process branchings and the intermediate (i-) process. This article reviews recent progress in direct neutron capture measurements, focusing on time-of-flight (TOF) experiments at CERN n_TOF and complementary activation techniques. Substantial advances have been achieved for stable s-only and bottleneck isotopes, significantly improving constraints on s-process models. In parallel, the combination of high instantaneous neutron fluxes and advanced detector systems has facilitated first-time neutron capture measurements on several radioactive branching-point nuclei. Feasibility studies, however, reveal current limitations related to sample availability, background conditions, and restricted energy coverage. In this context, the complementarity between TOF and activation emerges as a central strategy. Future developments, including high-flux facilities and novel inverse kinematics experiments in ion storage rings, are expected to extend the boundaries of neutron capture measurements, overcoming current limitations and helping unlock new frontiers in our understanding of stellar nucleosynthesis. Full article

The La Mancha region (a semi-arid area of southeast Spain) hosts the world’s highest concentration of vineyards and is also one of the regions with the largest areas devoted to almond tree cultivation. Viticulture and nut fruit trees (mainly almonds) are one of the region’s principal sources of economic revenue. The Two-Source Energy Balance (TSEB) model can assist management of water resources. A simplified version of the TSEB approach (STSEB) was previously tested in a vineyard and almonds to estimate sensible heat (H) and latent heat (LE) fluxes using a parallel scheme method based on the Monin–Obukov similarity theory (MOST). This study introduces a method based on Surface Renewal (SR) theory to partition the sensible heat flux using low-frequency measurements as input. The latter was friendlier than the parallel MOST method under unstable conditions and than the series SR and MOST methods. The objective was to compare the MOST and SR models within a parallel scheme method. During the 2014 and 2015 growing season, measurements were collected in a 4 ha row crop drip-irrigated Tempranillo vineyard. Hourly sensible heat flux measured by an eddy covariance (EC) system and evapotranspiration (ET) registered by a 9 m² monolithic large weighting lysimeter were used as a reference. ET estimates were obtained as a residual of the energy balance equation (known as the residual method) using three methods for estimating sensible heat flux, H_SR, H_MOST and H_EC, yielding ET_SR-RE, ET_MOST-RE and ET_EC-RE, respectively. For sensible heat flux, the index of agreement (IA expressed in %) for 2014 and 2015 was 93% and 83%, respectively, using SR, and 84% and 78%, respectively, for MOST. This represents a 6–10% improvement using SR. For evapotranspiration, the ET_SR-RE and ET_MOST-RE IA showed similar performance in both years (around 88%), while ET_EC-RE yielded the best results (92% and 89% for 2014 and 2015, respectively). In addition, half-hourly EC fluxes, during the growing season of 2017, were used as a reference in an almond orchard. The SR sensible heat flux performed better (IA = 93%) than MOST (IA = 86%) in this case, whereas for the latent heat flux, the residual method performed the best, resulting in an IA of 81% for SR and of 78% for MOST. Overall, SR performed better than MOST, particularly under unstable conditions with wind speeds above 1 ms⁻¹. Full article

Tomato, cucumber, and sweet pepper represent the backbone of greenhouse vegetable cultivation. Over recent decades, developments in agronomic practices have been central to improving yield, resource-use efficiency, resilience to abiotic stresses, and product quality. This review synthesizes dispersed evidence on water and nutrient management, cultivar improvement, grafting, canopy management, biological inputs, and postharvest-oriented agronomy, while highlighting that the three crops exhibit markedly different responses to these practices. These responses are primarily driven by crop-specific differences in source–sink balance, root-zone regulation, canopy architecture, reproductive stability, and postharvest metabolic regulation. Tomato typically demonstrates substantial improvements in yield and water use efficiency under optimized fertigation strategies, with canopy management additionally promoting source–sink balance and stress resilience. Cucumber, by contrast, is particularly sensitive to water deficits, salinity, and nutrient imbalances, necessitating stricter control of irrigation and fertilization to maintain stable root-zone water flux and transpiration dynamics. Sweet pepper often exhibits greater physiological complexity, as yield stability is strongly influenced by microclimate-sensitive metabolic and ionic balance, frequently associated with trade-offs in quality, including firmness, color development, and nutritional composition. The success of grafting, microbial inoculants, and biostimulants further varies considerably among crops, reinforcing the need for crop-specific strategies rather than generalized approaches. Postharvest-oriented agronomy, involving the regulation of nutrient supply, harvest timing, and canopy structure, is becoming increasingly important for prolonging shelf life and improving quality in line with market demands. Sustainability-oriented practices, including nutrient recycling and water-saving strategies, additionally contribute to reducing environmental burdens while maintaining profitability. By identifying species-specific physiological constraints and agronomic priorities, this review highlights that crop-customized and physiologically integrated management strategies are essential for improving productivity, resilience, and quality in protected cultivation. Full article

As sustainable development becomes increasingly important, technologies for liquid hydrogen (LH₂) storage and transportation are advancing rapidly. Safety concerns regarding LH₂ tanks in fire accidents require further attention. In this study, a one-dimensional thermodynamic model was developed based on layer-by-layer analysis to assess the heat transfer performance of the insulation structure in LH₂ tanks under fire conditions. Through the transformation of the solving target and iteration rules, a novel and efficient solution method was proposed for such thermodynamic problems. The thermodynamic performance of the insulation structure coupled with spray-on foam and variable-density multilayer under normal temperature (NT) and standardized fire conditions (863.15 K) was analyzed, and the effects of insulation structure parameters and environmental factors were evaluated. A case study of a 500 L vehicle LH₂ tank was conducted using the software package BoilFAST, with the total heat leakage as the key input, to analyze the evolution of internal pressure and temperature. Results show that within the insulation structure, temperature decreases rapidly by 80.35% and 89.55% under fire and NT conditions, respectively. Spray-on foam insulation thickness, layer density, residual gas pressure, and hydrogen temperature exert minor effects, while the temperature of the external environment and the number of layers significantly affect the heat flux under the fire condition. Under the NT condition, heat leakage is primarily attributed to support structures and accessory pipelines, whereas under the fire condition, heat leakage from the insulation structure becomes the main source, accounting for 63%. This study provides a reference for heat transfer assessment of LH₂ tanks in fire scenarios. Full article

The two-source energy balance model pyTSEB-PT was used to model latent heat fluxes from sunflower and wheat crops before senescence, grown on the same field in consecutive years. Input maps for the pyTSEB model were prepared using UAV-acquired multispectral/thermal imagery and ground control canopy leaf angle distribution (χ) and leaf area index (LAI) estimations based on canopy light transmission measurements by linear ceptometers. The modelled sensible and latent heat fluxes (H_pyTSEB, LE_pyTSEB) were validated against eddy covariance-measured respective fluxes (H_eddy, LE_eddy). Actual χ (χ_a) was estimated from 2 h courses of canopy light transmission values and ranged between 0.5 and 1.2 for wheat and between 2.8 and 5.8 for sunflower crops, respectively, affecting canopy light extinction coefficients (k) and LAI in both crops compared to the case of the generally assumed spherical leaf angle distribution (χ = 1). Vegetation cover fraction (f_c) was 3.4% smaller in wheat when using χ_a instead of χ₁, but this led to only minor—though significant—changes in modelled T_can, T_soil and canopy and surface resistances. The effect of leaf angle distribution on the combined validation of sensible and latent heat flux data was shown primarily in sunflower due to the decrease in sensible heat flux error, while validation improvement was not detectable in the case of wheat. Using field-calibrated thermal images instead of uncalibrated ones strongly improved validation results (fit of modelled vs. measured sensible and latent heat fluxes), showing the necessity of field calibration of the thermal camera when the data are used for vegetation energy balance modelling. Full article

Membrane distillation (MD) is a promising technology for high-salinity water treatment, but scaling still remains a critical limitation to stable operation. This study introduces a novel approach by exploring vibration signal design as a control variable for scaling mitigation in hollow-fiber DCMD, shifting from the conventional treatment of vibration as a fixed-frequency mechanical input. The influence of different vibration modes, including fixed, random, and patterned (music-derived structured non-stationary excitation) vibrations, on CaSO₄ scaling in hollow-fiber direct contact membrane distillation (DCMD) was systematically investigated. Bench-scale experiments were conducted using synthetic saline feed (35,000 mg/L NaCl and 2000 mg/L CaSO₄) under both outside-in and inside-out configurations. The results reveal that vibration modifies flux decline behavior by delaying the critical volume concentration factor (VCF_cr) and reducing post-critical scaling kinetics. In the outside-in mode, patterned vibration achieved the highest critical VCF (3.39) and lowest scale formation rate, indicating effective suppression of nucleation and crystal growth. In contrast, fixed-frequency vibration (100 Hz) was more effective in the inside-out mode, owing to resonance-induced amplification of vibration transmissibility (>140%), which enhanced local shear at the membrane surface. Spectral analysis shows that patterned vibration provides broadband and non-stationary excitation with multiple dominant frequencies, enabling continuous disruption of scaling processes, whereas random vibration lacks structured energy distribution. Furthermore, patterned vibration reduced energy consumption by 16–23% compared to fixed and random modes while maintaining comparable or superior fouling mitigation. These findings demonstrate that vibration pattern design, coupled with system resonance characteristics, is a key factor in optimizing MD performance and energy efficiency. Full article

A Wedge Shaped T–Type magnetic flux concentrator (MFC) is proposed to improve the magnetic detection capability of tunneling magnetoresistance (TMR) sensors. The TMR chip used in this work integrates a CoFeSiB soft magnetic thin film on-chip and exhibits a sensitivity of 251 mV/Oe with a magnetic noise of 65.3 pT/sqrt(Hz). Based on magnetic circuit analysis and finite-element simulations, the key structural parameters of the Wedge Shaped T–Type MFC were optimized, including the air-gap distance, aspect ratio, and input–output cross-sectional ratio. The optimal parameters were determined as an air gap of 200 μm, an aspect ratio of 2, and a cross-sectional compression ratio exceeding 100. Sixteen MFC structures with different sizes were fabricated and integrated with the TMR sensors for experimental evaluation. The results show that the external flux concentrator does not introduce additional voltage noise while significantly improving the sensor response. With optimized structures, the sensor sensitivity increases from 251 mV/Oe to 17,812 mV/Oe, and the magnetic noise is reduced from 65.3 pT/sqrt(Hz) to 0.92 pT/sqrt(Hz) at 1 Hz. The experimental results demonstrate that the Wedge Shaped T–Type MFC effectively enhances the magnetic field gain and significantly improves the detection limit of TMR sensors. Full article