Search Results (21,937)

This study, motivated by the pronounced fluid loss characteristics of water-based fracturing fluids, developed a fluid–solid coupling model to investigate water-based fracturing in geological reservoirs. The model was further employed to analyse the effects of multiple factors on fracture propagation and the seepage capacity of water-based fracturing fluids. Moreover, the underlying mechanisms of fracture propagation and seepage enhancement were elucidated from a microscopic molecular perspective. The results obtained that the high apparent viscosity of water-based fracturing fluids not only enhances the fracturing efficiency of reservoir rocks but also results in a reduced seepage volume (−17 mL) in low-permeability reservoirs. Furthermore, the reservoir porosity (+2.5%) exhibits a clear inverse proportional relationship with fracturing efficiency (−0.9 m), while the seepage volume (+7 mL) of water-based fracturing fluids continues to increase. The strength and quantity of hydrogen bonds between molecules in water-based fracturing fluid, influenced by external factors, directly affect fluid seepage. The seepage behaviour of water-based fracturing fluids in geological reservoirs, together with the influence of reservoir conditions on fracture propagation, provides valuable reference data for rock fracturing and reservoir stimulation. However, the absence of data analysis and microscopic images of microscopic molecular dynamics constitutes a challenging problem that demands attention. Full article

This study presents the deployment of Machine Learning (ML) models on low-cost edge devices (ESP32) for real-time water quality prediction in tilapia aquaculture. A compact monitoring and control system was developed with low-cost sensors to capture key environmental parameters under field conditions in Northern Thailand. Three ML models—Multiple Linear Regression (MLR), Decision Tree Regression (DTR), and Random Forest Regression (RFR)—were evaluated. RFR achieved the highest accuracy (R² > 0.80), while MLR, with moderate performance (R² ≈ 0.65–0.72), was identified as the most practical choice for ESP32 deployment due to its computational efficiency and offline operability. The system integrates sensing, prediction, and actuation, enabling autonomous regulation of dissolved oxygen and pH without constant cloud connectivity. Field validation demonstrated the system’s ability to maintain DO within biologically safe ranges and stabilize pH within an hour, supporting fish health and reducing production risks. These findings underline the potential of Edge AIoT as a scalable solution for small-scale aquaculture in resource-limited contexts. Future work will expand seasonal data coverage, explore federated learning approaches, and include economic assessments to ensure long-term robustness and sustainability. Full article

Background/Objectives: Pharmaceutical preparation technologies can enhance the bioavailability of poorly water-soluble drugs. Ursolic acid (UA) has been found to possess anti-cancer and hepatoprotective properties, demonstrating its potential as a therapeutic agent; however, its hydrophobicity and low solubility present challenges in the development of drug formulations. This study investigates the preparation of a nano-UA suspension by wet grinding, researches the influence of process parameters on particle size, and explores the rules of particle breakage and agglomeration by combining model fitting. Methods: Wet grinding experiments were conducted using a laboratory-scale grinding machine. The particle size distributions (PSDs) of UA suspensions under different grinding conditions were measured using a laser particle size analyzer. A single-factor experimental design was employed to optimize operational conditions. Model parameters for a population balance model considering both breakage and agglomeration were determined by an evolutionary algorithm optimization method. By measuring the degree to which UA inhibits the colorimetric reaction between salicylic acid and hydroxyl radicals, its antioxidant capacity in scavenging hydroxyl radicals was indirectly evaluated. Results: Wet grinding process conditions for nano-UA particles were established, yielding a UA suspension with a D50 particle size of 122 nm. The scavenging rate of the final grinding product was improved to three times higher than that of the UA raw material (D50 = 14.2 μm). Conclusions: Preparing nano-UA suspensions via wet grinding technology can significantly enhance their antioxidant properties. Model regression analysis of PSD data reveals that increasing the grinding mill’s stirring speed leads to more uniform particle size distribution, indicating that grinding speed (power) is a critical factor in producing nanosuspensions. Full article

Danube Delta (DD), an ecologically vulnerable site, together with fish populations, which are significant food resources, are largely exposed to heavy metal contamination. This study was developed in the Babina–Cernovca sector of DD in September 2023. Zinc (Zn), and iron (Fe) were identified in water, while copper (Cu), iron (Fe), and manganese (Mn) were in sediments (mud). Proximate composition of the muscle tissues of eight fish species identified in the area was assessed. The muscle was also tested to identify heavy metals contamination. The contamination degree was assessed using bioaccumulation and bioconcentrations factors. The relation between nutritional parameters and metals was tested using bivariate and multivariate analyses. Samples were analyzed by specific laboratory tests, and data were processed using ANOVA, Spearman correlation, Principal Component Analysis (PCA), and hierarchical clustering. S. erythrophthalmus, C. gibelio, and A. alburnus have the highest metal bioaccumulation capacity, exhibiting species-specific accumulation patterns. PCA and clustering analysis reflect the influence of species and environmental factors on heavy metal accumulation in fish tissue. The study integrates the heavy metals content with nutritional parameters in fish muscular tissue, using bivariate and multivariate analysis for assessing fish vulnerability to heavy metals exposure in the Danube River. Full article

Background: Parkinson’s disease (PD) is a neurodegenerative disorder for which no curative therapies currently exist. Experimental models employing 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) reproduce PD features such as striatal dopaminergic dysfunction and motor deficits. Various MPTP dosing regimens are used to screen drug candidates for PD, but their validity is limited because of the predominant use of young male animals. Sex bias is another issue that is underrepresented in PD research, since females are more susceptible to this pathology. Here, we studied the model of bolus administration of MPTP (30 mg/kg) in aged female mice and assessed its sensitivity to the antioxidants fullerene C₆₀ and fullerenol C₆₀(OH)₂₄, given that oxidative stress is a key contributor to PD. Methods: 12-month-old female C57BL/6 mice received fullerene (0.1 mg/kg/day, via diet) or fullerenol (0.15 mg/kg/day, via drinking water). On day 10, mice were injected with MPTP. We studied tremor, piloerection, and behavior in the pole test, rotarod, pole test, and open field. High-performance liquid chromatography (HPLC) was employed to study dopaminergic neurotransmission, and the expression levels of its molecular regulators and nitric oxide synthase (NOS)-related targets were investigated using RT-PCR in the striatum and cortex. Results: MPTP-challenged mice displayed profound impairment in markers of dopaminergic neurotransmission and cellular distress, and showed disrupted motor behavior and vegetative functions. Antioxidant-treated animals that received a bolus injection of MPTP demonstrated partial preservation of tremor response, dopaminergic parameters, and iNOS and nNOS gene expression, although motor performance in the pole test was only modestly improved. Fullerenol appeared more effective in decreasing MPTP-induced neurochemical changes. Conclusions: The applied MPTP model showed its validity in mimicking PD features and was sensitive to low doses of antioxidants, suggesting its usefulness for screening drugs that target oxidative and nitrosative stress. The neuroprotective effects of fullerene-based compounds suggest their potential utility in the treatment of PD. Full article

Ionic rare earths are extracted from primary sources by the in situ chemical leaching method, where the type and concentration of leaching agents significantly affect the mechanical properties and microstructure of the ore body. In this study, MgSO₄ and Al₂(SO₄)₃ solutions of varying concentrations were used as leaching agents to investigate the evolution of shear strength, the characteristics of Duncan–Chang hyperbolic model parameters, and the changes in microstructural pore characteristics of rare earth samples under different leaching conditions. The results show that the stress–strain curves of all samples consistently exhibit strain-hardening behavior under all leaching conditions, and shear strength is jointly influenced by confining pressure and the chemical interaction between the leaching solution and the soil. The samples leached with MgSO₄ exhibited higher shear strength than those treated with water. The samples leached with 3% and 6% Al₂(SO₄)₃ showed increased strength, while 9% Al₂(SO₄)₃ caused a slight decrease. With increasing leaching agent concentration, the cohesion of the samples significantly declined, whereas the internal friction angle remained relatively stable. The Duncan–Chang model accurately described the nonlinear deformation behavior of the rare earth samples, with the model parameter b markedly decreasing as confining pressure increased, indicating that confining stress plays a dominant role in governing the nonlinear response. Under the coupled effects of chemical leaching and mechanical stress, the number and size distribution of pores of the rare earth samples underwent a complex multiscale co-evolution. These results provide theoretical support for the green, efficient, and safe exploitation of ionic rare earth ores. Full article

Coccidiosis represents a major constraint to sheep productivity worldwide, with increasing concerns regarding anticoccidial resistance and growing interest in reducing dependency on conventional synthetic anticoccidials. This investigation evaluated the anticoccidial properties of faveira pods (Parkia platycephala pod—PpP) and their influence on productive performance in naturally infected lambs. Eighteen uncastrated Dorper × Santa Inês crossbred males (20.0 ± 2.5 kg, 5 months) were randomly allocated to three groups: G1 (0% PpP; n = 6), G2 (100% PpP replacing roughage, 30.0% of total diet; n = 6), and the control group (0% PpP plus 20 mg/kg toltrazuril; n = 5). Parasitological assessments, productive performance, and behavioral parameters were monitored over 45 days using oocyst counts, morphometric analysis, digestibility trials, and biometric measurements. Nine Eimeria species were identified, with E. crandallis, E. parva, and E. bakuensis representing 53.5% of total oocyst shedding. Group G2 demonstrated a numerical 8.5% reduction in parasite load compared to G1 (p = 0.42), while toltrazuril achieved 36.6% efficacy (p < 0.05). Species-specific effects were significant for E. crandallis, E. parva, and E. ovinoidalis (p < 0.01). A robust correlation emerged between parasite load and water consumption (r = 0.652, p = 0.0045), establishing a novel behavioral biomarker for coccidiosis monitoring. Environmental oocyst elimination decreased by 43.4% in the P. platycephala group. These findings demonstrate that PpPs possess moderate anticoccidial properties, offering a sustainable complementary strategy for integrated coccidiosis management while contributing to environmental sustainability. Full article

In the context of contemporary climate change, drought is widely recognized as a major stressor affecting plant growth. While numerous studies have demonstrated that Serendipita indica enhances stress resistance in host plants and is widely used in agriculture, research on its symbiotic interactions with woody plants for improving drought tolerance remains limited. This study investigated the effects of S. indica inoculation on the growth of Phoebe sheareri seedlings under varying drought conditions—well-watered (WW), moderate drought (MD), and severe drought (SD)—and explored the physiological mechanisms underlying improved drought resistance. The results showed that under WW conditions, S. indica inoculation promoted seedling growth and development. Under MD and SD conditions, although drought stress inhibited growth, inoculation significantly increased plant biomass, root parameters, chlorophyll content, and photosynthetic efficiency. Additionally, it alleviated drought-induced damage by reducing REC, MDA, H₂O₂, and O₂⁻ levels, while enhancing SOD, POD, and CAT activities, and increasing root ABA, GA, IAA, and CTK content. Under MD stress, adaptive changes in root architecture and hormone levels were observed, including increases in total root length, surface area, volume, average diameter, and elevated IAA and CTK levels—all of which were further enhanced by S. indica inoculation. In conclusion, symbiosis with S. indica improved drought tolerance in P. sheareri seedlings likely through enhanced photosynthesis, antioxidant enzyme activity, and hormone regulation. Full article

In this study, cottonseed oil biodiesel and waste lard biodiesel were produced through a transesterification process and blended with conventional diesel at different ratios (B10 and B20). The performance and emission characteristics of these fuels were systematically evaluated in a single-cylinder, four-stroke, water-cooled diesel engine operating at speeds of 1000–1800 rpm under a constant 50% load. The physicochemical properties of the fuels were analyzed, and engine parameters including brake-specific fuel consumption (BSFC), brake thermal efficiency (BTE), exhaust gas temperature (EGT), and emissions of carbon monoxide (CO), hydrocarbon (HC), carbon dioxide (CO₂), and nitrogen oxides (NOx) were measured. The results demonstrated that, compared with diesel, biodiesel blends significantly reduced CO, HC, and CO₂ emissions. At 1800 rpm, the LB20 blend showed reductions of 31.03% in CO, 47.06% in HCs, and 19.14% in CO₂ relative to diesel. These reductions are mainly attributed to the higher oxygen content and lower hydrogen-to-carbon ratio of biodiesel, which promote more complete combustion. However, all biodiesel blends exhibited higher NOx emissions than diesel, with the increase being more pronounced at higher blend ratios. At 1800 rpm, the LB20 blend recorded the highest NOx emissions, which were 20.63% higher than those of diesel under the same condition. In terms of performance, biodiesel blends showed higher BSFC and lower BTE compared with diesel, mainly due to their lower calorific value and higher viscosity. The lowest BTE and the highest BSFC were both observed with the LB20 blend, at 22.64% and 358.11 g/kWh, respectively. Full article

After the original support system in the auxiliary transportation roadway of the northern wing of the Zhaoxian Mine failed, the extent of damage and deformation varied significantly across different sections of the drift. A single support method could not meet the engineering requirements. Therefore, this paper conducted research on the classification of roadway damage and zoning repair. The overall damage characteristics of the roadway are described by three indicators: roadway deformation, development of rock mass fractures, and water seepage conditions. These are further refined into nine secondary indicators. In summary, a rock mass damage combination weighting evaluation model based on the FAHP–entropy weight TOPSIS method is proposed. According to this model, the degree of damage to the roadway is divided into five grades. After analyzing the damage conditions and support requirements at each grade, corresponding zoning repair plans are formulated by adjusting the parameters of bolts, cables, channel steel beams, and grouting materials. At the same time, the reliability of partition repair is verified using FLAC3D 6.0 numerical simulation software. Field monitoring results demonstrated that this approach not only met the support requirements for the roadway but also improved the utilization rate of support materials. This provides valuable guidance for the design of support systems for roadways with similar heterogeneous damage. Full article

This study establishes an efficient and eco-friendly ultrasound-assisted extraction (UAE) method for total flavonoids present in Cercis chinensis seeds using natural deep eutectic solvents (NADES). Among nine NADES formulations screened, choline chloride–levulinic acid (ChCl–Lev, 1:2) demonstrated optimal performance, yielding 112.1 mg/g total flavonoids. Through Response Surface Methodology (RSM), the ultrasound-assisted extraction (UAE) parameters were explored. Under the optimized conditions (water content of 30%, time of 28 min, temperature of 60 °C, and solvent-to-solid ratio of 1:25 g/mL), the total flavonoid yield reached 128.5 mg/g, representing a 195% improvement compared to conventional ethanol extraction. The recyclability of NADES was successfully achieved via AB-8 macroporous resin, retaining 80.89% efficiency after three cycles. Extraction kinetics, modeled using Fick’s second law, confirmed that the rate constant (k) increased with temperature, highlighting temperature-dependent diffusivity as a key driver of efficiency. The extracted flavonoids exhibited potent antioxidant activity, with IC₅₀ values of 0.86 mg/mL (ABTS•⁺) and 0.69 mg/mL (PTIO•). This work presents a sustainable NADES-UAE platform for flavonoid recovery and offers comprehensive mechanistic and practical insights for green extraction of plant bioactives. Full article

Photocatalytic membrane reactors (PMRs), which combine photocatalysis with membrane separation, represent a pivotal technology for sustainable water treatment and resource recovery. Although extensive research has documented various configurations of photocatalytic-membrane hybrid processes and their potential in water treatment applications, a comprehensive analysis of the interrelationships among reactor architectures, intrinsic physicochemical mechanisms, and overall process efficiency remains inadequately explored. This knowledge gap hinders the rational design of highly efficient and stable reactor systems—a shortcoming that this review seeks to remedy. Here, we critically examine the connections between reactor configurations, design principles, and cutting-edge applications to outline future research directions. We analyze the evolution of reactor architectures, relevant reaction kinetics, and key operational parameters that inform rational design, linking these fundamentals to recent advances in solar-driven hydrogen production, CO₂ conversion, and industrial scaling. Our analysis reveals a significant disconnect between the mechanistic understanding of reactor operation and the system-level performance required for innovative applications. This gap between theory and practice is particularly evident in efforts to translate laboratory success into robust and economically feasible industrial-scale operations. We believe that PMRs will realize their transformative potential in sustainable energy and environmental applications in future. Full article

Berry pomace is a valuable source of dietary fiber (DF) with promising applications in functional food development. This study aimed to evaluate and compare the technological and rheological properties of soluble (SDF) and insoluble (IDF) fiber fractions isolated from cranberry, black currant, lingonberry, and sea buckthorn pomace. SDF fractions demonstrated higher water solubility and lower swelling capacity, compared with IDF fractions. Meanwhile, water and oil retention capacities depended on fiber type and the sources of pomace. Fractionation notably affected color parameters, with SDFs generally being lighter. Rheological analysis revealed pseudoplastic, shear-thinning behavior in all SDF samples, with viscosity dependent on both pH and shear rate. In particular, the black currant SDF demonstrated higher yield stress compared to other SDFs, suggesting enhanced resistance to deformation and superior structural stability under low shear conditions. The consistency coefficient varied across samples, indicating differences in gel-forming potential. These findings highlight the importance of berry source and fiber fraction in determining functionality. The distinct hydration, binding, and rheological properties suggest that both SDF and IDF from berry pomace can be strategically applied as thickeners, stabilizers, or texture enhancers in food systems. This study supports the valorization of berry by-products as sustainable and functional ingredients in the formulation of fiber-enriched foods. Full article

For nearly two decades, the Yellow Sea has experienced recurrent green tides, which are now considered the largest of their kind globally; the mechanism behind these outbreaks remains highly complex and not fully understood. This study investigates the pre-outbreak distribution, abundance, and species composition of suspended macroalgae in the Southern Yellow Sea (SYS) during 2023–2024, along with environmental parameters. The results indicate that suspended macroalgae were predominantly distributed in the nearshore waters, particularly along the shallow beaches of northern Jiangsu. Furthermore, their abundance in the surface water layer significantly exceeded that in the bottom water. A total of 1353 and 493 algal filament samples were collected in 2023 and 2024, respectively. Dominant species included Ulva prolifera, Ulva linza, Ulva flexuosa, and Blidingia sp. Nutrient levels positively correlated with filament abundance. As a primary means of rapid proliferation for U. prolifera, suspended macroalgae contribute significantly to the initial expansion of green tides. Furthermore, their abundance holds promise as a biological indicator for forecasting the scale and extent of impending blooms, thereby providing a critical foundation for elucidating the underlying outbreak mechanisms. Full article

Global Navigation Satellite System (GNSS) meteorology has emerged as a valuable tool for atmospheric monitoring, providing high-resolution, near-real-time data that can significantly improve precipitation nowcasting. This study aims to enhance short-term precipitation forecasting by integrating GNSS-derived Precipitable Water Vapor (PWV)—a key indicator of atmospheric moisture—with traditional meteorological observations. A novel two-step machine learning framework is proposed that combines a Random Forest (RF) model and a Long Short-Term Memory (LSTM) neural network. The RF model first estimates current precipitation based on PWV, surface weather parameters, and auxiliary atmospheric variables. Then, the LSTM network leverages temporal dependencies within the data to predict precipitation for the subsequent hour. This hybrid method capitalizes on the RF’s ability to model complex nonlinear relationships and the LSTM’s strength in handling time series data. The results demonstrate that the proposed approach improves forecasting accuracy, particularly during extreme weather events such as intense rainfall and thunderstorms, outperforming conventional models. By integrating GNSS meteorology with advanced machine learning techniques, this study offers a promising tool for meteorological services, early warning systems, and disaster risk management. The findings highlight the potential of GNSS-based nowcasting for real-time decision-making in weather-sensitive applications. Full article