Search Results (1,275)

This study investigates long-term land surface temperature (LST) trends along the shoreline of Lake Drūkšiai, a transboundary lake in eastern Lithuania that formerly served as a cooling reservoir for the Ignalina Nuclear Power Plant (INPP). Although the INPP was decommissioned in 2009, its legacy continues to influence the lake’s thermal regime. Using Landsat 8 thermal infrared imagery and NDVI-based methods, we analysed spatial and temporal LST variations from 2013 to 2024. The results indicate persistent temperature anomalies and elevated LST values, particularly in zones previously affected by thermal discharges. The years 2020 and 2024 exhibited the highest average LST values; some years (e.g., 2018) showed lower readings due to localised environmental factors such as river inflow and seasonal variability. Despite a slight stabilisation observed in 2024, temperatures remain higher than those recorded in 2013, suggesting that pre-industrial thermal conditions have not yet been restored. These findings underscore the long-term environmental impacts of industrial activity and highlight the importance of satellite-based monitoring for the sustainable management of land, water resources, and coastal zones. Full article

This literature review explores the role of symmetry in thermal sciences, fluid dynamics, and energy applications, emphasizing the theoretical and practical implications. Symmetry is a fundamental tool for simplifying complex problems, enhancing computational efficiency, and improving system design across multiple engineering and physics domains. Thermal and fluid processes are applied in several modern energy use technologies, essentially involving the complex, multidimensional interaction of fluid mechanics and thermodynamics, such as renewable energy applications, combustion diagnostics, or Computational Fluid Dynamics (CFD)-based optimization, where symmetry is highly considered to simplify geometric parameters. Indeed, the interconnection between experimental analysis and the numerical simulation of processes is an important field. Symmetry operates as a unifying principle, its presence determining everything from the stability of turbulent flows to the efficiency of nuclear reactors, revealing hidden patterns that transcend scales and disciplines. Rotational invariance in pipelines; rotors of hydraulic, thermal, and wind turbines, and in many other cases, for instance, not only lowers computational cost but also guarantees that solutions validated in the laboratory can be effectively scaled up to industrial applications, demonstrating its crucial role in bridging theoretical concepts and real-world implementation. Thus, a wide range of symmetry solutions is exhibited in this research area, the results of which contribute to the development of science and fast information for decision making in industry. In this review, essential findings from prominent research were synthesized, highlighting how symmetry has been conceptualized and applied in these contexts. Full article

Broth cooking is a traditional pretreatment and ripening strategy for high-commercial-value dehydrated marine food, effectively enhancing its texture and rehydration properties. In this work, we characterized the structural information of Maillard reaction products (MRPs) derived from beef scrap stock and investigated their effects on the texture and rehydration performance of dehydrated abalone. The optical and structural properties of the MRPs were analyzed using X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), transmission electron microscopy (TEM), and fluorescence spectroscopy. These MRPs showed osmosis in abalone processing including pretreatment and drying. Low-field nuclear magnetic resonance (LF-NMR) results revealed that MRP pretreatment improved the moisture migration and physicochemical properties of dehydrated abalone. These findings suggest that MRPs, owing to their high osmotic efficiency and nanoscale size, could serve as promising food additives and potential alternatives to traditional penetrating agents in the food industry, enhancing the rehydration performance of dried seafood and reducing quality deterioration. Full article

The cosmetics industry has been seeking to develop products with renewable natural ingredients to reduce the use of or even replace synthetic substances. Biosurfactants can help meet this demand. These natural compounds are renewable, biodegradable, and non-toxic or have low toxicity, offering minimal risk to humans and the environment, which has attracted the interest of an emerging consumer market and, consequently, the cosmetics industry. The aim of the present study was to produce a biosurfactant from the yeast Starmerella bombicola ATCC 22214 cultivated in a mineral medium containing 10% soybean oil and 5% glucose. The biosurfactant reduced the surface tension of water from 72.0 ± 0.1 mN/m to 33.0 ± 0.3 mN/m after eight days of fermentation. The yield was 53.35 ± 0.39 g/L and the critical micelle concentration was 1000 mg/L. The biosurfactant proved to be a good emulsifier of oils used in cosmetic formulations, with emulsification indices ranging from 45.90 ± 1.69% to 68.50 ± 1.10%. The hydrophilic–lipophilic balance index demonstrated the wetting capacity of the biosurfactant and its tendency to form oil-in-water (O/W) emulsions, with 50.0 ± 0.20% foaming capacity. The biosurfactant did not exhibit cytotoxicity in the MTT assay or irritant potential. Additionally, an antioxidant activity of 58.25 ± 0.32% was observed at a concentration of 40 mg/mL. The compound also exhibited antimicrobial activity against various pathogenic microorganisms. The characterisation of the biosurfactant using magnetic nuclear resonance and Fourier transform infrared spectroscopy revealed that the biomolecule is a glycolipid with an anionic nature. The results demonstrate that biosurfactant produced in this work has potential as an active biotechnological ingredient for innovative, eco-friendly cosmetic formulations. Full article

A numerical method is proposed for evaluating the axial stress–strain relationship of FRP-confined concrete. In this method, empirical formulae for the compressive strength and strain at peak stress of confined concrete are obtained by fitting experimental data collected from the literature. It is then assumed that when FRP-confined concrete and actively confined concrete are subjected to the same lateral strain and confining pressure at a specific loading stage, their axial stress–strain relationships are identical at that stage. Based on this assumption, a numerical method for the axial stress–strain relationship of FRP-confined concrete is developed by combining the stress–strain model of actively confined concrete with the axial–lateral strain correlation. Finally, the validity of this numerical method is verified with experimental data with various geometric and material parameters, demonstrating a reasonable agreement between predicted stress–strain curves and measured ones. A parametric analysis is conducted to reveal that the stress–strain curve is independent of the specimen length for strong FRP confinement with small failure strains, while the specimen length exhibits a significant effect on the softening branch for weak FRP confinement. Therefore, for weakly FRP-confined concrete, it is recommended to consider the specimen length effect in evaluating the axial stress–strain relationship. Full article

Ricinus communis (Euphorbiaceae), commonly known as the castor oil plant, is prized for its versatile applications in medicine, industry, and agriculture. It features large, deeply lobed leaves with vibrant colours, robust stems with anthocyanin pigments, and extensive root systems for nutrient absorption. Its terminal panicle-like inflorescences bear monoecious flowers, and its seeds are enclosed in prickly capsules. Throughout its various parts, R. communis harbours a diverse array of bioactive compounds. Leaves contain tannins, which exhibit astringent and antimicrobial properties, and alkaloids like ricinine, known for anti-inflammatory properties, as well as flavonoids like rutin, offering antioxidant and antibacterial properties. Roots contain ellagitannins, lupeol, and indole-3-acetic acid, known for anti-inflammatory and liver-protective effects. Seeds are renowned for ricin, ricinine, and phenolic compounds crucial for industrial applications such as biodegradable polymers. Pharmacologically, it demonstrates antioxidant effects from flavonoids and tannins, confirmed through minimum inhibitory concentration (MIC) assays for antibacterial activity. It shows potential in managing diabetes via insulin signalling pathways and exhibits anti-inflammatory properties by activating nuclear factor erythroid 2-related factor 2 (Nrf2). Additionally, it has anti-fertility effects and potential anticancer activity against cancer stem cells. This review aims to summarize Ricinus communis’s botanical properties, therapeutic uses, chemical composition, pharmacological effects, and industrial applications. Integrating the current knowledge offers insights into future research directions, emphasizing the plant’s diverse roles in agriculture, medicine, and industry. Full article

Bis(2-ethylhexyl) phosphate (P204) is widely used in extraction processes in the nuclear and rare earth industries. However, its high solubility in water results in high levels of total organic carbon and phosphorus in aqueous environments, and may also lead to radioactive contamination when it is used to combine with radionuclides. In this paper, we characterized a coconut shell activated carbon (CSAC) and a coal-based activated carbon (CBAC) for the adsorption of P204 and then evaluated their adsorption performance through batch and column experiments. The results found that, except for the main carbon matrix, CSAC and CBAC carried rich oxygen-containing functional groups and a small amount of inorganic substances. Both adsorbents had porous structures with pore diameters less than 4 nm. CSAC and CBAC showed good removal performance for P204 under low pH conditions, with removal efficiencies significantly higher than those of commonly used adsorption resins (XAD-4 and IRA900). The adsorption kinetics of P204 conformed to the pseudo-second-order kinetic model, and the adsorption isotherms conformed to the Langmuir model, indicating a monolayer chemical reaction mechanism. Both adsorbents exhibited strong anti-interference capabilities; their adsorption performance for P204 did not change greatly with the ambient temperature or the concentrations of common interfering ions. Column experiments demonstrated that CSAC could effectively fix dissolved P204 with a removal efficiency exceeding 90%. The fixed P204 could be desorbed with acetone. The findings provide an effective method for the recovery of P204 and the regeneration of spent activated carbon, which shows promise for practical applications in the future. Full article

HPMC, regulating slurry properties, is widely used in cement-based materials. Research on the application of HPMC in gangue slurry is still in its early stages. Moreover, the interactive effects of various factors on gangue slurry performance have not been thoroughly investigated. The work examined the effects of slurry concentration (X₁), maximum gangue particle size (X₂), and HPMC dosage (X₃) on slurry performance using response surface methodology (RSM). The microstructure of the slurry was characterized via scanning electron microscopy (SEM) and polarized light microscopy (PLM), while low-field nuclear magnetic resonance (LF-NMR) was employed to analyze water distribution. Additionally, industrial field tests were conducted. The results are presented below. (1) X₁ and X₃ exhibited a negative correlation with layering degree and slump flow, while X₂ showed a positive correlation. Slurry concentration had the greatest impact on slurry performance, followed by maximum particle size and HPMC dosage. HPMC significantly improved slurry stability, imposing the minimum negative influence on fluidity. Interaction terms X₁X₂ and X₁X₃ significantly affected layering degree and slump flow, while X₂X₃ significantly affected layering degree instead of slump flow. (2) Derived from the RSM, the statistical models for layering degree and slump flow define the optimal slurry mix proportions. The gangue gradation index ranged from 0.40 to 0.428, with different gradations requiring specific slurry concentration and HPMC dosages. (3) HPMC promoted the formation of a 3D floc network structure of fine particles through adsorption-bridging effects. The spatial supporting effect of the floc network inhibited the sedimentation of coarse particles, which enhanced the stability of the slurry. Meanwhile, HPMC only converted a small amount of free water into floc water, which had a minimal impact on fluidity. HPMC addition achieved the synergistic optimization of slurry stability and fluidity. (4) Field industrial trials confirmed that HPMC-optimized gangue slurry demonstrated significant improvements in both stability and flowability. The optimized slurry achieved blockage-free pipeline transportation, with a maximum spreading radius exceeding 60 m in the goaf and a maximum single-borehole backfilling volume of 2200 m³. Full article

This study aims to address the challenges posed by uneven energy amplitude and a low signal-to-noise ratio (SNR) in the total focus imaging of coarse-crystalline elastic anisotropic materials. A novel method for acoustic field correction vector-coherent total focus imaging, based on the materials’ properties, is proposed. To demonstrate the effectiveness of this method, a test specimen, an austenitic stainless steel nozzle weld, was employed. Seven side-drilled hole defects located at varying positions and depths, each with a diameter of 2 mm, were examined. An ultrasound simulation model was developed based on material backscatter diffraction results, and the scattering attenuation compensation factor was optimized. The acoustic field correction function was derived by combining acoustic field directivity with diffusion attenuation compensation. The phase coherence weighting coefficients were calculated, followed by image reconstruction. The results show that the proposed method significantly improves imaging amplitude uniformity and reduces the structural noise caused by the coarse crystal structure of austenitic stainless steel. Compared to conventional total focus imaging, the detection SNR of the seven defects increased by 2.34 dB to 10.95 dB. Additionally, the defect localization error was reduced from 0.1 mm to 0.05 mm, with a range of 0.70 mm to 0.88 mm. Full article

Microbial contamination is a global concern with impacts on a variety of industries ranging from marine to biomedical applications. Recent research on hydrophilic polymer-based coatings is focused on combining antifouling polymers with nanomaterials to enhance mechanical, optical, and stimuli-responsive properties, yielding colour changing, self-healing, and super hydrophilic materials. This study combines the hydrophilic and antifouling properties of vitamin B5 analogous methacrylamide (B5AMA)-based polymers with stimuli-responsive anthocyanin-dye-loaded cellulose nanocrystals (CNCs) to develop antifouling materials with colour changing capabilities upon bacterial contamination. Poly(B5AMA)-grafted CNCs were prepared through surface-initiated photoiniferter reversible addition fragmentation chain transfer (SP-RAFT) polymerization and characterized through proton nuclear magnetic resonance (¹H-NMR), transmission electron microscopy (SEM/TEM), and X-ray photon spectroscopy (XPS) to confirm the formation of surface-grafted polymer chains. The bare CNCs and poly(B5AMA)-grafted CNCs were loaded with anthocyanin dye and evaluated for pH-dependent colour changing capabilities. Interestingly, anthocyanin-loaded CNCs demonstrated vibrant colour changes in both solution and dried film form upon bacterial contamination; however, limited colour changing capabilities of the composites, specifically in dried film form, were attributed to the enhanced dispersibility and antifouling capabilities of the polymer-coated CNCs. Full article

This study presents a detailed and comprehensive investigation into the macro-scale performance, strength gain mechanisms, environment and economic performance of graphene oxide (GO)-enhanced low-emission concrete. A comprehensive experimental program evaluated fresh and hardened properties, including slump retention, bleeding, air content, compressive, flexural, and tensile strength, drying shrinkage, and elastic modulus. Scanning Electron Microscopy (SEM), energy-dispersive spectroscopy (EDS), Thermogravimetric analysis (TGA) and proton nuclear magnetic resonance (¹H-NMR) was employed to examine microstructural evolution and early age water retention, confirming GO’s role in accelerating cement hydration and promoting C-S-H formation. Optimal performance was achieved at 0.05% GO (by binder weight), resulting in a 25% increase in 28-day compressive strength without compromising workability. This outcome is attributed to a tailored, non-invasive mixing strategy, wherein GO was pre-dispersed during synthesis and subsequently blended without the use of invasive mixing methods such as high shear mixing or ultrasonication. Fourier-transform infrared (FTIR) spectroscopy further validated the chemical compatibility of GO and PCE and confirmed the compatibility and efficiency of the admixture. Sustainability metrics, including embodied carbon and strength-normalized cost indices (USD/MPa), indicated that, although GO increased material cost, the overall cost-performance ratio remained competitive at breakeven GO prices. Enhanced efficiency also led to lower net embodied CO₂ emissions. By integrating mechanical, microstructural, and environmental analyses, this study demonstrates GO’s multifunctional benefits and provides a robust basis for its industrial implementation in sustainable infrastructure. Full article

Concrete is a fundamental material in structural engineering, widely used in critical infrastructure such as bridges, nuclear power plants, and dams. These structures may be subjected to extreme dynamic loads resulting from natural disasters, industrial accidents, or missile impacts. Therefore, a comprehensive understanding of concrete behavior under high strain rates is essential for safe and resilient design. Experimental investigations, particularly spalling tests, have highlighted the strain-rate sensitivity of concrete in dynamic tensile loading conditions. This study presents a macroscopic 3D discrete element model specifically developed to simulate the dynamic response of concrete subjected to extreme loading. Unlike conventional continuum-based models, the proposed discrete element framework is particularly suited to capturing damage and fracture mechanisms in cohesive materials. A key innovation lies in incorporating a physically grounded strain-rate dependency directly into the local cohesive laws that govern inter-element interactions. The originality of this work is further underlined by the validation of the discrete element model under dynamic tensile loading through the simulation of spalling tests on normalstrength concrete at strain rates representative of severe impact scenarios (30–115 s⁻¹). After calibrating the model under quasi-static loading, the simulations accurately reproduce key experimental outcomes, including rear-face velocity profiles and failure characteristics. Combined with prior validations under high confining pressure, this study reinforces the capability of the discrete element method for modeling concrete subjected to extreme dynamic loading, offering a robust tool for predictive structural assessment and design. Full article

Amid growing global concerns about environmental sustainability and food security, plant-based meat substitutes have emerged as a promising alternative to conventional meat. However, current formulations, especially those based on soy protein isolate (SPI) often fail to replicate the desired texture and structural integrity. To address this limitation, this study aimed to evaluate the use of whole yeast powder (WYP) combined with SPI for producing plant-based meat analogues via high-moisture extrusion. Seven groups were designed: a control group with 0% WYP, five treatment groups with 5%, 10%, 20%, 30%, and 40% WYP, and one reference group containing 20% yeast protein powder (YPP). Although lower in protein content than yeast protein powder (YPP), whole yeast powder exhibits superior water-binding capacity and network-forming ability owing to its complex matrix and fiber content. At a 20% inclusion level, whole yeast powder demonstrated a higher fibrous degree (1.84 ± 0.02 vs. 1.81 ± 0.04), greater hardness (574.93 ± 5.84 N vs. 531.18 ± 17.34 N), and increased disulfide bonding (95.33 ± 0.92 mg/mL vs. 78.41 ± 0.78 mg/mL) compared to 20% YPP. Scanning electron microscopy (SEM) and low-field nuclear magnetic resonance (LF-NMR) revealed that whole yeast powder facilitated the formation of aligned fibrous networks and enhanced water binding. Fourier transform infrared spectroscopy (FTIR) confirmed an increase in β-sheet content (0.267 ± 0.003 vs. 0.260 ± 0.003), which contributed to improved protein aggregation. Increasing the WYP content to 30–40% led to a decline in these parameters, including a reduced fibrous degree (1.69 ± 0.06 at 40% WYP) and weakened molecular interactions (p < 0.05). The findings highlight 20% WYP as the optimal substitution level, offering superior textural enhancement and fibrous structure formation compared to YPP. These results suggest that WYP is not only a cost-effective and processing-friendly alternative to YPP but also holds great promise for scalable industrial application in the plant-based meat sector. Its compatibility with extrusion processes and ability to improve sensory and structural attributes supports its relevance for sustainable meat analogue production. Full article

This study chemically characterized three Pleurotus ostreatus fruiting bodies cultivated in the Iberian Peninsula under different conditions (biological and industrial), with emphasis on polysaccharide analysis. Comprehensive comparative data on cultivation-dependent nutritional variations will potentially improve their nutritional and therapeutic applications. Industrial mushrooms (POC and POA) contained significantly higher carbohydrate content (74%), while the biologically cultivated mushroom (POL) exhibited more protein (22.6%), fat (4.2%), and ashes (8.0%). Monosaccharide analysis showed glucose dominance (28.7–45.5%), with mannose, galactose, xylose, and arabinose also present. Trehalose was the primary free sugar (4.8–14.9%). The (1→3)(1→6)-β-glucans varied significantly across samples (POL: 20.5%; POC: 29.3%; POA: 34.3%). Nuclear magnetic resonance analysis suggested complex polysaccharide arrangements. Water-soluble carbohydrates and proteins showed molecular weight distributions of 0.18–21 kDa and 0.20–75 kDa, respectively. All mushrooms were rich in essential amino acids, phosphorus (2.79–3.07%), potassium (0.56–0.68%), linoleic acid (0.82–1.14%), and oleic acid (0.22–0.31%). Fourier transform infrared confirmed a mushroom-specific biochemical profile. These findings corroborate the high nutritional value of POL, POC, and POA, with a significant contribution to the daily requirements of fiber, protein, and minerals (phosphorus, potassium, magnesium, iron, zinc, copper, and selenium), making them suitable for functional foods and nutraceuticals with cultivation-dependent nutritional profiles. Full article

To ensure the safety of nuclear power production, nuclear power plants deploy numerous sensors to monitor various physical indicators during production, enabling the early detection of anomalies. Efficient anomaly detection relies on complete sensor data. However, compared to conventional energy sources, the extreme physical environment of nuclear power plants is more likely to negatively impact the normal operation of sensors, compromising the integrity of the collected data. To address this issue, we propose an anomaly detection method for nuclear power data: Neural Normal Stochastic Process (NNSP). This method does not require imputing missing sensor data. Instead, it directly reads incomplete monitoring data through a sequentialization structure and encodes it as continuous latent representations in a neural network. This approach avoids additional “processing” of the raw data. Moreover, the continuity of these representations allows the decoder to specify supervisory signals at time points where data is missing or at future time points, thereby training the model to learn latent anomaly patterns in incomplete nuclear power monitoring data. Experimental results demonstrate that our model outperforms five mainstream baseline methods—ARMA, Isolation Forest, LSTM-AD, VAE, and NeutraL AD—in anomaly detection tasks on incomplete time series. On the Power Generation System (PGS) dataset with a 15% missing rate, our model achieves an F1 score of 83.72%, surpassing all baseline methods and maintaining strong performance across multiple industrial subsystems. Full article