Search Results (15,132)

Agronomic practices can modify cereal grain chemical composition and processing performance. Long-term evidence linking agricultural management with functionality-related quality remains limited, especially in terms of combined tillage x crop residue management strategy. We evaluated the effects of long-term tillage simplifications and straw management on productivity and processing-relevant traits of winter wheat and spring barley in a split-plot field experiment (Lithuania). Straw was either removed (S0) or chopped and retained (S1), and six tillage systems were compared (conventional ploughing (CP), shallow ploughing (SP), shallow cultivation (SOW), stubble over winter, no-till with cover crops (NTC), and no-till without cover crops (NT)). The yield and starch content of winter wheat and spring barley groats increased with the addition of straw and the application of SOW, NTC, and NT systems. The hectolitre mass of winter wheat and spring barley grains increased with the addition and removal of straw using SP technology. The protein content and wet gluten content of winter wheat and spring barley grains decreased, while the starch content increased, with the addition and removal of straw using SC technology. In wheat, protein content showed weak separation among treatments, while wet gluten and Zeleny sedimentation displayed mostly directional trends (wet gluten–sedimentation correlation: r = 0.844 under S0 and r = 0.984 under S1). In terms of the tillage systems, it can be stated that in most cases, SP and NT increased grain yield and improved quality indicators, while SC and NTC technologies showed opposite results. Soil-function assessment (CEI, 10–25 cm) indicated substantially higher integrated soil functioning under conservation agriculture (e.g., SOW/NTC/NT: 5.28–5.70) than under conventional systems (CP: 3.23). The results support framing sustainable soil management for cereal functionality as a system package: residue retention enables the productivity benefits of reduced-tillage systems while maintaining key quality proxies. Full article

Red mud discharged during alumina production via the Bayer process is characterized by high contents of sodium carbonate, sodium sulfate, and other soluble salts, and it remains poorly utilized and accumulates in long-term stockpiles. Sodium percarbonate has found extensive industrial applications, and its synthesis via the salting-out method represents one of the dominant industrial routes. In this context, sodium sulfate was employed as a salting-out agent. On the basis of relevant ternary systems, the phase equilibrium of the quaternary system Na₂CO₃–Na₂SO₄–H₂O₂–H₂O at 5 °C was systematically investigated and calculated. The objective was to utilize red mud as a waste resource and develop a novel integrated process that favored the wet synthesis of sodium percarbonate while enabling the efficient separation of sodium salts. The solubility data for the ternary subsystems constituting the above quaternary system were correlated using the Pitzer model, yielding the corresponding ion interaction parameters and activity coefficients. The validated model was then applied to predict the phase equilibrium data of the quaternary system. Verification results indicate that the calculated values are in satisfactory agreement with the experimental data. On the basis of the phase equilibrium data of the Na₂CO₃–Na₂SO₄–H₂O₂–H₂O system at 5 °C, a phase diagram was constructed. Along with five solid-phase crystallization fields, three invariant points were identified: the co-saturation point of Na₂SO₄·10H₂O, Na₂CO₃·10H₂O, and Na₂CO₃·1.5H₂O₂·H₂O; the co-saturation point of Na₂SO₄·10H₂O, Na₂CO₃·1.5H₂O₂·H₂O, and Na₂SO₄·0.5H₂O₂·H₂O; and the co-saturation point of Na₂CO₃·1.5H₂O₂·H₂O, Na₂SO₄·0.5H₂O₂·H₂O, and Na₂CO₃·2H₂O₂·H₂O. From phase diagram analysis, a novel wet process route for sodium percarbonate production using waste red mud is proposed. The process involves chemical reaction, crystallization, separation, and drying to obtain the final product. A new process flow diagram for the value-added production of sodium percarbonate is also presented. Full article

Hyperspectral airborne data combined with machine learning has proven effective for characterizing plant nutritional quality. However, terrain, viewing geometry, and illumination can distort spectral signatures, leading to biased models with limited generalizability for large-scale mapping across farms with a heterogeneous landscape. In this study, we developed a framework for mapping pasture quality using airborne hyperspectral imaging while explicitly accounting for in-field acquisition and environmental effects. Nitrogen content (N%) and metabolizable energy (ME) were used as reference indicators across four hill country farms in New Zealand with contrasting environmental and management conditions. Ground truth was obtained using standard laboratory wet chemistry methods and paired with AisaFENIX airborne hyperspectral data, resulting in 1610 spectral samples derived from 161 spatially independent ground plots. Gaussian Process Regression (GPR) and a one-dimensional convolutional neural network (1D-CNN) were trained and evaluated on an independent test dataset. Both models achieved strong predictive performance (R² > 0.8); however, GPR provided more reliable estimates through predictive uncertainty. Using a 95% confidence interval threshold to mask uncertain predictions increased overall performance (R² > 0.9) and consequently improved the reliability of the mapped outputs. This approach enables spatially explicit pasture nutrient assessment to support precision land management for carbon and nitrogen. Full article

Tree bark, an abundant by-product of the timber industry, represents a promising feedstock for sustainable construction. This study investigates the thickness swelling, water absorption, hygroscopicity and mechanical (compressive strength) properties of insulation panels produced from hardwood bark (Tilia spp. and Robinia pseudoacacia) via hydromechanical treatment and a wet-forming process. The panels were produced without added adhesives, relying on the formation of hydrogen bonds during the drying phase to ensure structural integrity. Both bark-based insulation boards (thermal conductivity coefficient 0.055–0.057 W/m·K) showed similar hygroscopic behavior, reaching equilibrium moisture contents of max. 25% at 93.9% RH. Water absorption after 24 h immersion was highly material-dependent; Tilia-based panels showed 57.11 ± 5.81%, and Robinia-based panels 320.61 ± 11.34%. Thickness swelling remained low (max. 6% for Robinia), showing significant orthotropic anisotropy. At 10% compressive strain, the Tilia and Robinia bark-based panels showed compressive strengths of 188 ± 14.6 kPa and 298 ± 18.1 kPa, accordingly. These findings demonstrate that hardwood bark can be successfully valorized into high-performance, binderless insulation, supporting circular economic strategies. Full article

Water pollution control for wetland lakes has undergone a fluctuating development process. Effective pollution management requires not only scientific water quality monitoring data but also clear identification of pollution sources within the study area. Accordingly, this study investigated Mudong Lake, the core area of the Huixian Wetland, and conducted water quality monitoring in January 2023 (dry season) and June 2023 (wet season). Based on the Water Quality Index (WQI) assessment results, water quality was better in the wet season than in the dry season. To identify pollution sources, the Absolute Principal Component Score-Multiple Linear Regression (APCS-MLR) model was applied. The results showed that pollution in the dry season was mainly derived from aquaculture and agricultural non-point source pollution, anthropogenic point source pollution, and internal release from sediments, while pollution in the wet season exhibited mixed characteristics, driven by agricultural non-point sources, domestic sewage discharge, and natural factors. Source apportionment analysis indicated that composite pollution sources (domestic sewage and aquaculture wastewater), agricultural non-point source pollution, and other unidentified sources contributed 43.71%, 34.11%, and 22.18% of the total pollution load, respectively. The findings of this study can provide a scientific basis for pollution control, emission reduction, and the targeted management of Mudong Lake. Full article

Atalantia ceylanica, locally known as Yaki naran (YK), is a native plant of Sri Lanka, growing commonly in the dry and wet–intermediate zones. In this study, powdered samples of Yaki naran (YK) were sequentially extracted using hexane, ethyl acetate (EtOAc), and methanol (MeOH). The resulting extracts were assessed for total phenolic content, antioxidant potentials, and in vitro α-amylase, α-glucosidase, and lipase inhibitory activities using relevant assays. The crude extracts were then subjected to separation and purification by column chromatography and preparative thin-layer chromatography. Although twelve compounds were obtained from the three crude extracts, only three had sufficient yields to proceed. Out of the three pure isolates, compound SAC 4 was identified as 2,4-di-tert-butylphenol, a phenolic compound, by using ¹H and ¹³C NMR data and FTIR spectroscopic data, followed by evaluation of bioactivities such as antioxidant properties, enzyme inhibitory assays, etc. Based on the results of the bioassays, compound SAC 4 was identified to show strong α-glucosidase inhibitory activity, moderate antioxidant activity, and lipase inhibitory activity. Full article

The sustainable utilization of multiple reclaimed pavement materials is a critical pathway toward green highway construction. This study investigates the performance and synergistic mechanisms of cold-recycled mixtures incorporating both Reclaimed Asphalt Pavement (RAP) and Reclaimed Cement-Stabilized Base (RCSB), using emulsified asphalt as the primary binder. A comprehensive experimental program was conducted to evaluate the effects of reclaimed material proportions, mixing sequences, and curing ages on the mechanical strength, moisture susceptibility, and high-temperature stability of the mixtures. Microscopic characterization via Scanning Electron Microscope (SEM) and Energy Dispersive Spectroscopy (EDS) were employed to elucidate the Interfacial Transition Zone (ITZ) evolution. Results indicate that an optimal RCSB incorporation range of 20–40% establishes a robust “stone-to-stone” rigid skeleton, significantly enhancing the splitting strength (up to 0.87 MPa) and durability (Splitting Strength Ratio, TSR > 91%). SEM observations confirm the formation of a dense interpenetrating network structure within this range, where cement hydration products and asphalt films achieve optimal chemo-physical bonding. Exceeding 40% RCSB leads to a moisture-starved state and a sharp decline in dynamic stability due to insufficient binder coating. Micro-morphological characterization reveals that the transition from macro-interfacial debonding to a robust cohesive failure mode is the fundamental driver for the performance peak at 20–40% RCSB. SEM observations confirm the formation of a dense interpenetrating network structure, where cement hydration products successfully anchor into the asphalt film. This optimized ITZ effectively eliminates the stress concentration and aggregate crushing seen in high-RAP mixtures, thereby ensuring superior mechanical integrity. Furthermore, a pre-wetting mixing sequence ensures a high-energy mineral surface that promotes the heterogeneous nucleation of cement. SEM results show that this prevents the competitive adsorption between cement and asphalt, transforming the ITZ from a friable, loose state into a densified crystalline adhesive matrix. Full article

Physics-based simulation of debris flows over complex terrain is essential for hazard assessment, but repeated numerical integration is costly when many scenarios must be explored. We develop a general deep-learning surrogate modelling framework for two-dimensional (2D) debris-flow propagation, here applied to the Morino–Rendinara area (central Italy) using a three-dimensional (3D) Fourier Neural Operator (FNO) trained on synthetic simulations generated by a validated in-house finite-volume shallow-water solver. The solver reproduces debris-flow propagation over complex terrain and is specifically developed for artificial intelligence (AI) applications. It is based on a depth-averaged 2D formulation using the Harten–Lax–van Leer–Contact (HLLC) approximate Riemann solver, hydrostatic reconstruction, positivity-preserving wet–dry treatment, and Voellmy-type basal friction, and was verified through analytical benchmarks, numerical tests, and back-analyses of real events. The dataset was built from four site-specific release settings derived from real topography, combining different released volumes and bulk densities while preserving local geomorphological and rheological characteristics. Each simulation was stored as a full spatio-temporal tensor and used to train an FNO conditioned on coordinates, topography, friction parameters, bulk density, and initial release thickness. Training used a novel loss to emphasize active-flow areas and improve velocity reconstruction, and was performed using a graphics processing unit (GPU). The surrogate shows effective generalization to within-distribution validation samples, with global relative mean squared errors of 5.49% for flow thickness, 5.34% for velocity component u, and 2.60% for v, and mean $R^2$ values of 0.95, 0.94, and 0.97. For a representative sample, the surrogate predicts the full spatio-temporal solution in $0.52$ s, versus about 47 s for the first-order finite-volume solver, corresponding to a speed-up of about $91\times$, with an even larger gap expected for higher-order solvers, since, whilst the computation time of the solver increases as its complexity increases, the computation time of the FNO remains essentially unchanged. These results indicate that the proposed FNO is a reliable site-specific surrogate for rapid approximation of 2D debris-flow dynamics over real terrain, with potential for uncertainty propagation, Monte Carlo analysis, large-ensemble simulation, and hazard-oriented scenario assessment. Full article

To address the pronounced degradation of skid resistance in steel bridge deck pavements exposed to hot, humid, and rainy environments, this study investigates an EA-10 epoxy–asphalt mixture and proposes a gradation design method with skid resistance as the primary performance objective. An orthogonal experimental design was employed to systematically analyze different combinations of sieve passing rates, and after determining an optimum asphalt–aggregate ratio of 6.25%, the skid resistance of the mixtures under various service conditions was evaluated using macrotexture depth, dry friction coefficient, and water-film friction coefficient. The results demonstrate that the formation of skid resistance follows a mechanism in which the macroscopic framework and microscopic pores interact synergistically. The passing rate of the 4.75 mm sieve is the dominant factor governing macrotexture depth, while the 0.3 mm sieve plays a critical regulating role in texture development; meanwhile, the passing rates of the 2.36 mm and 0.6 mm sieves exert a decisive influence on both dry and water-film friction coefficients. When the passing rates of the 4.75 mm, 0.3 mm, 2.36 mm, and 0.6 mm sieves are approximately 70%, 26.5%, 58–61%, and 34%, respectively, the mixture exhibits superior overall skid-resistance performance. Based on the evaluation results of the International Friction Index (IFI), the optimized gradation shows a more stable level of skid resistance under wet and slippery conditions. These findings provide quantitative evidence and engineering guidance for the skid-resistance-oriented gradation design of epoxy–asphalt mixtures used in steel bridge deck pavements in hot and humid regions. Full article

The widespread application of detonation nanodiamonds (DNDs) is limited by surface-coated non-diamond sp² carbon impurities. In this work, an efficient salt-assisted catalytic purification strategy is developed to achieve selective oxidation removal of sp² carbon. DND black powder was mixed with various chloride, carbonate, and bicarbonate salts and thermally treated in air to systematically investigate the effects of anions and cations on purification efficiency. Thermogravimetric analysis reveals that all tested salts significantly reduce the oxidation onset temperature of sp² carbon and exhibit distinct catalytic trends: for anions, bicarbonates > carbonates > chlorides; for cations, Cs⁺ ≈ K⁺ > Na⁺. Among them, KHCO₃ introduced via a wet-wrapping method shows the optimal performance, lowering the oxidation temperature by approximately 160 °C. Moreover, the wet-wrapping process effectively suppresses particle sintering and agglomeration during purification, resulting in purified DNDs with reduced average particle size and markedly improved dispersibility. Mechanistic investigations demonstrate that free alkali metal cations act as active sites, preferentially catalyzing sp² carbon oxidation through a synergistic oxygen spillover–electron transfer mechanism. This study provides an effective and highly selective approach for DND purification. The proposed salt-assisted strategy, integrating catalytic oxidation and dispersion control, also offers valuable insights for the preparation of high-performance nanomaterials. Full article

This study investigates the dry pneumatic separation of wheat flour using a newly designed rotating air classifier to obtain starch- and protein-enriched fractions. The process is based on differences in particle density and size, enabling separation without water or chemical reagents. The influence of key process parameters, including air flow velocity 6–12 m/s, classifier geometry, and particle size distribution, was investigated. Statistical analysis confirmed that the air flow velocity and orifice diameter significantly affect the separation efficiency. The optimal conditions of 9–10 m/s and 1.8 mm resulted in a starch fraction with a purity of about 89% and a protein-enriched fraction containing approximately 45% protein. Regression models (R² > 0.99) demonstrated a strong relationship between the process parameters and fraction yield. Compared with conventional wet fractionation, the proposed method reduces energy consumption by approximately 28% and eliminates water use. These results confirm the feasibility of dry pneumatic classification as a sustainable and efficient technology for producing functional wheat-based ingredients. All experiments were conducted in triplicate (n = 3), and the results are presented as mean ± standard deviation. The reported yields correspond to the fraction mass, while the composition values indicate component purity within each fraction. Full article

The steaming of wood changes its physical, mechanical and chemical properties in a complex way. The information about the wettability, surface free energy, and Janka hardness of steamed beech false heartwood and sapwood is not sufficient; these properties were therefore the main focus of this article. Wettability was determined by contact angle measurement with standard testing liquids. The steaming regime was a significant factor for wetting with redistilled water, and it had a mutual interaction during wetting with diiodomethane along with the factor wood zone. The steaming regimes also significantly influenced the surface free energy of the beech wood. According to the contact angles and surface free energy values, the Mode I steaming regime showed a better wettability than the Mode II regime. Analysis of the Janka hardness values showed that wood zone, steaming regime and anatomical direction significantly influenced the hardness in a mutual interaction. Beech wood steamed with the Mode I steaming regime showed a significantly lower Janka hardness in all anatomical directions; the Mode II steaming regime showed a significantly lower hardness only in the cross directions. The statistical difference between false heartwood and sapwood hardness was not significant only in the tangential direction for both steaming regimes and untreated wood. Full article

Surface protection and functional modification of aircraft-certified aluminum alloys are essential for corrosion resistance, durability, and long-term airworthiness. At the same time, increasingly restrictive environmental regulations motivate the development of alternatives to legacy wet-chemical surface treatments. This study presents an integrated assessment of ultrafast femtosecond laser surface texturing as a surface functionalization approach for Aluminum 6061 alloys within an aerospace manufacturing and sustainability context. Ultrashort-pulse laser processing enables controlled micro- and nano-scale surface topographical modification with limited thermal impact, allowing adjustment of wettability and surface functionality while preserving bulk material integrity. As a dry and contactless process, femtosecond laser treatment eliminates the use of hazardous chemicals, reduces consumable inputs, and generates minimal secondary waste. A streamlined cradle-to-gate life cycle assessment conducted in accordance with ISO 14040/14044 indicates a lower global-warming potential per functional unit compared with conventional surface treatments, including anodization, plasma-assisted coatings, and organic coating systems. Complementary qualitative analyses addressing environmental health and safety, supply-chain risk, and ESG alignment indicate potential advantages related to occupational safety, regulatory compliance, waste management, and end-of-life recyclability. The investigation is performed on planar Aluminum 6061 reference surfaces with a treated area of 25 mm², providing a controlled laboratory-scale basis for analyzing process behavior, functional surface modification, and associated environmental metrics. Within this defined scope, the results support further evaluation of femtosecond laser surface texturing as a surface engineering option for future aerospace manufacturing. Full article

The development of tight heavy-oil reservoirs is severely hampered by the high viscosity and poor mobility of crude oil caused by strong intermolecular stacking interactions among asphaltenes, coupled with the substantial adsorption loss and inadequate deep transport capacity of conventional displacement agents. By targeted penetrant delivery, a novel nanoemulsion system with a well-defined “core–shell” architecture was synthesized to address these critical challenges. The physicochemical properties, stability and oil displacement performance were evaluated. The prepared nanoemulsion exhibited an ultrasmall and uniform particle size distribution between 10 nm and 20 nm. It also demonstrated exceptional dispersibility in aqueous media and remarkable thermal and salinity stability under reservoir conditions. Furthermore, an ultralow critical micelle concentration of approximately 0.01% could be achieved and the oil–water interfacial tension was reduced to 7.3 × 10⁻² mN/m, significantly outperforming the conventional surfactant AES. Core flooding tests revealed that the proposed nanoemulsion enhanced oil recovery by 37.1% and attained a displacement efficiency of 68.9% in oil-wet capillary models. Molecular dynamics simulations further elucidated the underlying synergistic mechanism. The hydrophilic shell minimized adsorption on rock surfaces, facilitating deep migration within nanoporous channels. The hydrophobic core, containing terpinene as a penetrant, effectively disrupted the π-π stacking of asphaltenes due to its nonplanar molecular configuration. This disruption transformed the asphaltene aggregates from a tightly packed state to a dispersed state, resulting in substantial viscosity reduction. This work elucidated the mechanism of asphaltene aggregate disruption by nanoemulsions at the molecular level, offering a promising and theoretically grounded strategy for the efficient exploitation of tight heavy-oil reservoirs. Full article

As critical conduits for pollutant enrichment and transformation, lake inlets govern the biogeochemical cycling of emerging contaminants. This study investigated the occurrence, spatiotemporal heterogeneity, and source–sink dynamics of 15 organophosphate esters (OPEs) in the major inflowing rivers of Poyang Lake, China. Using UPLC–MS/MS, positive matrix factorization (PMF), and risk quotient (RQ) modeling, we identified the mechanisms driving pollutant distribution across three hydrological periods. Alkyl-OPEs (58.19%) and chlorinated OPEs (40.42%) dominated the contaminant burden, with TCPP and TEP identified as the primary congeners. Concentrations exhibited a distinct seasonal gradient, with higher levels during the dry season and lower levels during the wet season, controlled by seasonal hydrological dilution versus evaporative and stagnant accumulation. PMF indicated that source contributions shifted with hydrology: intense wet-season precipitation flushed non-point sources from waste and electronic products (45.1%), while reduced dry-season flow concentrated mixed inputs from agricultural runoff and ship traffic (50.7%). Ecological risk assessment identified EHDPP, TCrP, and TCPP as high-risk contaminants (RQ ≥ 1.0), posing direct threats to aquatic population. These findings highlight the need for adaptive, season-specific management of emerging contaminants at the river–lake interface, specifically by implementing enhanced interception of surface runoff during the wet season and enforcing stringent regulations on localized shipping emissions during the dry season to protect freshwater ecosystems. Full article