Search Results (608)

While the Ankom RF system facilitates efficient high-throughput in vitro fermentation studies, its high cost and limited flexibility constrain its broader applicability. To address these limitations, we developed and validated a low-cost, modular gas monitoring system (FerME), assembled from commercially available components. To evaluate its performance and reproducibility relative to the Ankom RF system (Ankom Technology, Macedon, NY, USA), in vitro rumen fermentation experiments were conducted under strictly controlled and identical conditions. Whole rumen contents were collected approximately 2 h post-feeding from individual mid- or late-lactation dairy cows and immediately transported to the laboratory. Each fermenter received 50 mL of processed rumen fluid, 100 mL of anaerobically prepared artificial saliva buffer, and 1.2 g of the donor cow’s diet. Bottles were sealed with the respective system’s pressure sensors, flushed with CO₂, and incubated in a 50 L water bath maintained at 39 °C. FerME (New Taipei City, Taiwan) and Ankom RF fermenters were placed side-by-side to ensure uniform thermal conditions. To assess the effect of filter bag use, an additional trial employed Ankom F57 filter bags (Ankom Technology, Macedon, NY, USA; 25 μm pore size). Trial 1 revealed no significant differences in cumulative gas production, volatile fatty acids (VFAs), NH₃-N, or pH between systems (p > 0.05). However, the use of filter bags reduced gas output and increased propionate concentrations (p < 0.05). Trial 2, which employed filter bags in both systems, confirmed comparable results, with the FerME system demonstrating improved precision (CV: 4.8% vs. 13.2%). Gas composition (CH₄ + CO₂: 76–82%) and fermentation parameters remained consistent across systems (p > 0.05). Importantly, with 12 pressure sensors, the total cost of FerME was about half that of the Ankom RF system. Collectively, these findings demonstrate that FerME is a reliable, low-cost alternative for real-time rumen fermentation monitoring and could be suitable for studies in animal nutrition, methane mitigation, and related applications. Full article

Various nature-based solutions (NbS)—such as constructed wetlands, drainage ditches, and vegetated buffer strips—have recently demonstrated strong potential for mitigating pollutant transport in open channels and river systems. Numerical modeling is a widely adopted and effective approach for assessing the performance of these interventions. This study presents the first development of a two-dimensional (2D) meshless advection–diffusion model based on an Eulerian smoothed particle hydrodynamics (SPH) framework, specifically designed to simulate passive pollutant transport in open channel flows. The proposed model marks a pioneering application of the ESPH technique to environmental pollutant transport problems. It couples the 2D depth-averaged shallow water equations with an advection–diffusion equation to represent both fluid motion and pollutant concentration dynamics. A uniform particle arrangement ensures that each fluid particle interacts symmetrically with eight neighboring particles for flux computation. To represent the pollutant transport process, the dispersion coefficient is defined as the sum of molecular and turbulent diffusion components. The turbulent diffusion coefficient is calculated using a prescribed turbulent Schmidt number and the eddy viscosity obtained from a Smagorinsky-type mixing-length turbulence model. Three analytical case studies, including one-dimensional transcritical open channel flow, 2D isotropic and anisotropic diffusion in still water, and advection–diffusion in a 2D uniform flow, are employed to verify the model’s accuracy and convergence. The model demonstrates first-order convergence, with relative root mean square errors (RRMSEs) of approximately 0.2% for water depth and velocity, and 0.1–0.5% for concentration. Additionally, the model is applied to a laboratory experiment involving 2D pollutant dispersion in a 90° junction channel. The simulated results show good agreement with measured velocity and concentration distributions. These findings indicate that the developed model is a reliable and effective tool for evaluating the performance of NbS in mitigating pollutant transport in open channels and river systems. Full article

Mesoscale coastal eddies are key components of ocean circulation, mediating the transport of heat, nutrients, and marine debris. The Surface Water and Ocean Topography (SWOT) mission provides high-resolution sea surface height data, offering a novel opportunity to improve the observation and characterization of these features, especially in coastal regions where conventional altimetry is limited. In this study, we investigate a mesoscale anticyclonic coastal eddy observed southwest of Mallorca Island, in the Balearic Sea, to assess the impact of SWOT-enhanced altimetry in resolving its structure and dynamics. Initial eddy identification is performed using satellite ocean color imagery, followed by a qualitative and quantitative comparison of multiple altimetric datasets, ranging from conventional nadir altimetry to wide-swath products derived from SWOT. We analyze multiple altimetric variables—Sea Level Anomaly, Absolute Dynamic Topography, Velocity Magnitude, Eddy Kinetic Energy, and Relative Vorticity—highlighting substantial differences in spatial detail and intensity. Our results show that SWOT-enhanced observations significantly improve the spatial characterization and dynamical depiction of the eddy. Furthermore, Lagrangian transport simulations reveal how altimetric resolution influences modeled transport pathways and retention patterns. These findings underline the critical role of SWOT in advancing the monitoring of coastal mesoscale processes and improving our ability to model oceanic transport mechanisms. Full article

The growing global demand for energy necessitates the efficient utilization of unconventional petroleum resources, particularly heavy oil reserves. However, extracting, transporting, and processing these resources remain challenging due to their low mobility, low API gravity, and significant concentrations of resins, asphaltenes, heteroatoms, and metals. In recent years, various in situ upgrading techniques have been explored to enhance heavy oil quality, with catalytic aquathermolysis emerging as a promising approach. The effectiveness of this process largely depends on the development of cost-effective, environmentally friendly catalysts. This study investigates the upgrading performance of water-soluble ammonium alum, (NH₄)Al(SO₄)₂·12H₂O, for an extra-heavy oil sample from the Zarafshan Depression, located along the Tajikistan–Uzbekistan border. Comprehensive analyses demonstrate that the catalyst facilitates the breakdown of heavy oil components, particularly resins and asphaltenes, into lighter fractions. As a result, oil viscosity was significantly reduced by 94%, while sulfur content decreased from 896 ppm to 312 ppm. Furthermore, thermogravimetric (TG-DTG) analysis, coupled with Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), and X-ray diffraction (XRD), revealed that the thermal decomposition of ammonium alum produces catalytically active Al₂O₃ nanoparticles. These findings suggest that ammonium alum is a highly effective water-soluble pre-catalyst for hydrothermal upgrading, offering a viable and sustainable solution for the development of extra-heavy oil fields. Full article

Water-lubricated bearings (WLB), due to their pollution-free nature and low noise, are increasingly becoming critical components in aerospace, marine applications, high-speed railway transportation, precision machine tools, etc. However, in practice, water-lubricated bearings suffer severe friction and wear due to low-viscosity water, harsh conditions, and contaminants like sediment, which can compromise the lubricating film and shorten their lifespan. The implementation of micro-textures has been demonstrated to improve the tribological performance of water-lubricated bearings to a certain extent, leading to their widespread adoption for enhancing the frictional dynamics of sliding bearings. The shape, dimensions (including length, width, and depth), and distribution of these micro-textures have a significant influence on the frictional performance. Therefore, this study aims to explore the coupling effect of different micro-texture shapes and distributions on the frictional performance of water-lubricated sliding, using the computational fluid dynamics (CFD) analysis. The results indicate that strategically arranging textures across multiple regions can enhance the performance of the bearing. Specifically, placing linear groove textures in the outlet of the divergent zone and triangular textures in the divergent zone body maximize improvements in the load-carrying capacity and frictional performance. This specific configuration increases the load-carrying capacity by 7.3% and reduces the friction coefficient by 8.6%. Overall, this study provided critical theoretical and technical insights for the optimization of WLB, contributing to the advancement of clean energy technologies and the extension of critical bearing service life. Full article

The Wyrtki Jet (WJ), a pivotal surface circulation system in the equatorial Indian Ocean, exerts significant regulatory control over regional climate dynamics through its intense eastward transport characteristics, which modulate water mass exchange, thermohaline balance, and cross-basin energy transfer. To address the scarcity of in situ observational data, this study developed a satellite remote sensing-driven multi-parameter coupled model and reconstructed the WJ’s seasonal variations using the XGBoost machine learning algorithm. The results revealed that wind stress components, sea surface temperature, and wind stress curl serve as the primary drivers of its seasonal dynamics. The XGBoost model demonstrated superior performance in reconstructing WJ’s seasonal variations, achieving coefficients of determination (R²) exceeding 0.97 across all seasons and maintaining root mean square errors (RMSE) below 0.2 m/s across all seasons. The reconstructed currents exhibited strong consistency with the Ocean Surface Current Analysis Real-time (OSCAR) dataset, showing errors below 0.05 m/s in spring and autumn and under 0.1 m/s in summer and winter. The proposed multi-feature integrated modeling framework delivers a high spatiotemporal resolution analytical tool for tropical Indian Ocean circulation dynamics research, while simultaneously establishing critical data infrastructure to decode monsoon current coupling mechanisms, advancing early warning systems for extreme climatic events, and optimizing regional marine resource governance. Full article

The high water demand of rice cultivation is mainly due to flood irrigation, which requires large volumes not only to meet evapotranspiration needs, but also due to losses from percolation, lateral seepage, and surface runoff. In addition to lowering water use efficiency, surface runoff may transport nutrients. This study aimed to calibrate and validate a daily water balance model to estimate surface runoff losses across three rice-growing seasons. During the first two seasons, different model components were calibrated by comparing simulated and observed water depths. In the final season, the calibrated model was validated using direct runoff measurements obtained from weirs and flowmeters. Results showed strong agreement between model estimates and direct measurements of water depth and surface runoff. Linear regression models showed good fit, with coefficients of determination (R²) above 0.80 for water depth and 0.79 for runoff. A validated daily water balance model, combined with periodic monitoring of water depth, proved to be a reliable tool for estimating surface runoff during the rice-growing season. Total runoff—from irrigation, rainfall, and final drainage—represented between 7.5% and 18% of the total water input. This approach offers a practical tool for improving irrigation water management and understanding runoff-driven nutrient transport. Full article

The pilot study is devoted to the assessment of both the accumulation and spatial distribution of microplastics in the snow cover of the Zhetysu region. The height of snow cover in the study area varied from 4.0 to 80.5 cm, with a volume of melt water ranging from 1.5 to 143 L. The analysis of 53 snow samples taken at different altitudes (from 350 to 1500 m above sea level) showed the presence of microplastics in 92.6% of samples in concentrations from 1 to 12 particles per square meter. In total, 170 microplastic particles were identified. The main polymers identified by Raman spectroscopy were polyethylene (PE), polypropylene (PP), and polystyrene (PS). These are typical components of plastic waste. The spatial distribution of microplastics showed elevated concentrations near settlements and roads. Notable contaminations were also recorded in remote mountainous areas, confirming the significant role of long-range atmospheric transport. Particles smaller than 0.5 mm dominated, having high aerodynamic mobility and capable of long-range atmospheric transport. Quantitative and qualitative characteristics of microplastics in snow cover have been realized for the first time both in Kazakhstan and in the Central Asian region, which contributes to the formation of primary ideas and future approaches about microplastic pollution in continental inland regions. The obtained results demonstrate the importance of atmospheric transport in the distribution of microplastics. They indicate the need for further monitoring and microplastic pollution analyses in Central Asia, taking into account its detection even in hard-to-reach and remote areas. Full article

The event scale method, employed for assessing changes in nitrogen (N) dynamics pre- and post-rain, provides insights into its transport to surface water systems. However, the relationships between N discharge in catchments dominated by different land uses and water quality remain unclear. This study quantified variations in key N components in ponds across forest, paddy field, and orchard catchments before and after six rainfall events. The results showed that nitrate (NO₃⁻-N) was the main N component in the ponds. Post-rainfall, N concentrations increased, with ammonium (NH₄⁺-N) and particulate nitrogen (PN) exhibiting significant elevations in agricultural ponds. Orchard catchments contributed the highest N load to the ponds, while forest catchments contributed the lowest. Following a heavy rainstorm event, total nitrogen (TN) loads in the ponds within forest, paddy field, and orchard catchments reached 6.68, 20.93, and 34.62 kg/ha, respectively. These loads were approximately three times higher than those observed after heavy rain events. The partial least squares structural equation model (PLS-SEM) identified that rainfall amount and changes in water volume were the dominant factors influencing N dynamics. Furthermore, the greater slopes of forest and orchard catchments promoted more N loss to the ponds post-rain. In paddy field catchments, larger catchment areas were associated with decreased N flux into the ponds, while larger pond surface areas minimized the variability in N concentration after rainfall events. In orchard catchment ponds, pond area was positively correlated with N concentrations and loads. This study elucidates the effects of rainfall characteristics and catchment heterogeneity on N dynamics in surface waters, offering valuable insights for developing pollution management strategies to mitigate rainfall-induced alterations. Full article

Buckwheat (Fagopyrum esculentum Moech) is a “gluten-free” pseudocereal with high-quality proteins and human health properties, increasing its cultivation worldwide. However, the role of nitrogen (N) in plant growth and yield components has received little attention in buckwheat. This study evaluated N’s effect on plant traits, photosynthetic performance, and grain yield components in buckwheat under field conditions. For this, Buckwheat cv. “Mancan” seeds were sown using five N rates: 0, 30, 45, 60, and 90 kg N ha⁻¹. Then, physiological performance and grain yield components were evaluated at harvest. Our study revealed that buckwheat plants subjected to 0 and 30 kg N ha⁻¹ showed the greatest chlorophyll fluorescence a parameters including maximum quantum yield of PSII (Fv′/Fm′), effective quantum yield of PSII (ФPSII), and electron transport rate (ETR) among N treatments; meanwhile, at higher N rates (60 and 90 kg N ha⁻¹), these parameters decayed. Similarly, plants treated with 90 kg N ha⁻¹ showed the lowest CO₂ assimilation among N treatments. In general, stomatal conductance (g_s), transpiration (E), and intrinsic water use efficiency (WUE_i) showed no significant changes among N treatments, with the exception of 30 kg N ha⁻¹, which exhibited the highest WUE_i. Concerning plant traits, plants grown under 60 and 90 kg N ha⁻¹ exhibited the greatest plant height, number of branches, shoot biomass, and internode per plant among N treatments. By contrast, 30 kg N ha⁻¹ showed the highest grain number, yield per plant, and grain yield among N treatments in F. esculentum plants. Based on the physiological and productive parameters, F. esculentum seems to have a low N requirement, exhibiting better results under the lowest N rates (30 kg N ha⁻¹). Therefore, F. esculentum could be considered as an alternative for gluten-free food production with low N requirements in agricultural systems of southern Chile. Nonetheless, more studies are required to understand the effect of N biochemical and molecular regulation on plant traits and grain yield components in buckwheat. Full article

Background: The integration of mining and urban spaces in coal-resource-based cities holds significant implications for urban transformation and sustainable development. However, existing research lacks an in-depth analysis of its characteristics and driving factors. Methods: This study takes the central urban area of Huaibei City as a case, utilizing historical documents, POI data, and spatial analysis methods to explore the evolution patterns and influencing factors of mining–urban spatial integration. Standard deviation ellipse analysis was employed to examine historical spatial changes, while a binary logistic regression model and principal component analysis were constructed based on 300 m × 300 m grid units to assess the roles of 11 factors, including location, transportation, commerce, and natural environment. Results: The results indicate that mining–urban spatial integration exhibits characteristics of lag, clustering, transportation dominance, and continuity. Commercial activity density, particularly leisure, dining, and shopping facilities, serves as a core driving factor. Road network density, along with the areas of educational and residential zones, positively promotes integration, whereas water surface areas (such as subsidence zones) significantly inhibit it. Among high-integration areas, Xiangshan District stands as the most economically prosperous city center; Lieshan–Yangzhuang mining area blends traditional and modern elements; and Zhuzhuang–Zhangzhuang mining area reflects the industrial landscape post-transformation. Conclusions: The study reveals diverse integration patterns under the synergistic effects of multiple factors, providing a scientific basis for optimizing spatial layouts and coordinating mining–urban development in coal-resource-based cities. Future research should continue to pay attention to the dynamic changes of spatial integration of mining cities, explore more effective integrated development models, and promote the rational and efficient use of urban space and the sustainable development of cities. Full article

Drinking water biofilm ecosystems harbor complex and dynamic prokaryotic and eukaryotic microbial communities. However, little is known about the impact of copper corrosion on microbial community functions in metabolisms and resistance. This study was conducted to evaluate the impact of upstream Cu pipe materials on downstream viable community structures, pathogen populations, and metatranscriptomic responses of the microbial communities in drinking water biofilms. Randomly transcribed cDNA was generated and sequenced from downstream biofilm samples of either unplasticized polyvinylchloride (PVC) or Cu coupons. Diverse viable microbial organisms with enriched pathogen-like organisms and opportunistic pathogens were active in those biofilm samples. Cu-influenced tubing biofilms had a greater upregulation of genes associated with potassium (K) metabolic pathways (i.e., K-homeostasis, K-transporting ATPase, and transcriptional attenuator), and a major component of the cell wall of mycobacteria (mycolic acids) compared to tubing biofilms downstream of PVC. Other upregulated genes on Cu influenced biofilms included those associated with stress responses (various oxidative resistance genes), biofilm formation, and resistance to toxic compounds. Downregulated genes included those associated with membrane proteins responsible for ion interactions with potassium; respiration–electron-donating reactions; RNA metabolism in eukaryotes; nitrogen metabolism; virulence, disease, and defense; and antibiotic resistance genes. When combined with our previous identification of biofilm community differences, our studies reveal how microbial biofilms adapt to Cu plumbing conditions by fine-tuning gene expression, altering metabolic pathways, and optimizing their structural organization. This study offers new insights into how copper pipe materials affect the development and composition of biofilms in premise plumbing. Specifically, it highlights copper’s role in inhibiting the growth of many microbes while also contributing to the resistance of some microbes within the drinking water biofilm community. Full article

Heavy metal pollution in aquatic ecosystems is a critical environmental issue worldwide. In these ecosystems, the seston adsorbs heavy metals from the water and introduces them into the food web, causing potential environmental and health risks. This study analyses how heavy metals (Cd, Hg, Cr, Cu, Pb, Fe, and Mn) are distributed in the water and seston of the Tampamachoco Lagoon, an ecosystem affected by pollution from a thermoelectric plant and by hydrometeorological variability, both of which influence their concentrations. The relationships among metal distribution, physicochemical variables, and the influence of plant emissions in three seasons (rainy, northerly windstorms, and dry) were analyzed. The metal concentrations in seston (Fe > Mn > Pb > Cu > Cr > Hg) were up to four times higher than in the water column (Fe > Mn > Cr > Cd > Pb > Cu > Hg), emphasizing the key role of particulate matter in metal transport and bioavailability. Particularly, the Cd concentrations exceeded WHO thresholds by 527.6% in the water column during the rainy season, while Hg and Pb exceeded the thresholds of the Mexican criteria for the protection of marine aquatic life by 4.05% and 41.6%, respectively. Principal Component Analyses revealed distinct spatiotemporal distribution patterns for metals in water and seston, reflecting the combined effects of natural variability and anthropogenic inputs. The strong association between metals and seston indicates continued contamination and potential risks to aquatic ecosystems. These findings highlight the environmental impact of metals on seston and the need for monitoring to assess aquatic ecosystems’ health. Our results highlight the importance of understanding how metals are distributed between seston and water, and how climate variability affects pollutant redistribution patterns. We propose that water quality regulations need to be rethought and redirected towards the achievement of new strategic objectives that truly integrate the different pollutant sources whose final destination is water bodies, so as to protect and conserve biodiversity and aquatic ecosystems. Full article

Proton exchange membrane water electrolyzers (PEMWEs) are a promising technology for green hydrogen production. However, the adoption of PEMWE-based hydrogen production systems remains limited due to several challenges, including high material costs, limited performance and durability, and difficulties in scaling the technology. Computational modeling serves as a powerful tool to address these challenges by optimizing system design, improving material performance, and reducing overall costs, thereby accelerating the commercial rollout of PEMWE technology. Despite this, conventional models often oversimplify key components, such as porous transport and catalyst layers, by assuming constant porosity and neglecting the spatial heterogeneity found in real electrodes. This simplification can significantly impact the accuracy of performance predictions and the overall efficiency of electrolyzers. This study develops a mathematical framework for modeling variable porosity distributions—including constant, linearly graded, and stepwise profiles—and derives analytical expressions for permeability, effective diffusivity, and electrical conductivity. These functions are integrated into a three-dimensional multi-domain COMSOL simulation to assess their impact on electrochemical performance and transport behavior. The results reveal that although porosity variations have minimal effect on polarization at low voltages, they significantly influence internal pressure, species distribution, and gas evacuation at higher loads. A notable finding is that reversing stepwise porosity—placing high porosity near the membrane rather than the channel—can alleviate oxygen accumulation and improve current density. A multi-factor comparison highlights this reversed configuration as the most favorable among the tested strategies. The proposed modeling approach effectively connects porous media theory and system-level electrochemical analysis, offering a flexible platform for the future design of porous electrodes in PEMWE and other energy conversion systems. Full article

This review examines the pharmaceutical applications of essential oils (EOs) and terpenes, highlighting their dual role as therapeutic agents and natural penetration enhancers. These volatile, hydrophobic compounds have well-documented antimicrobial, antioxidant, and anti-inflammatory properties. However, their clinical potential is limited by poor water solubility, high volatility, and sensitivity to environmental factors, including light, heat, and oxygen. To address these challenges, various advanced delivery systems have been developed to enhance stability, bioavailability, and controlled release. These systems not only protect chemical integrity but also exploit these compounds’ abilities to interact with lipid membranes, facilitating the transport of active compounds across biological barriers. Additionally, their inherent antimicrobial properties can contribute to the overall stability of formulations. The review critically examines the incorporation of terpenes and major essential oil (EO) components, such as limonene, linalool, eugenol, α-pinene, and menthol, into delivery systems, assessing their performance in enhancing drug permeability and targeting specific tissues. Current challenges and future directions in terpenes and EO-based delivery strategies are discussed, highlighting their promising role in developing multifunctional and efficient pharmaceutical formulations. Full article