Search Results (8,202)

Lubricating oil degradation directly impacts friction coefficient, wear rate, and lubrication regime transitions, making precise health quantification essential for predictive tribological maintenance. However, conventional evaluation methods fail to capture subtle tribological changes preceding lubrication failure, often oversimplifying complex multi-parameter relationships critical to friction and wear performance. To address this challenge, this study proposes Seasonal–Trend decomposition using Loess, a Factor Attention Network, a Temporal Convolutional Network, and an Informer with Long Short-Term Memory Variational Autoencoder (SFTI-LVAE) framework for continuous tribological health assessment of diesel engine lubricants. The approach integrates Seasonal–Trend decomposition using Loess (STL) for trend–seasonal separation, a Factor Attention Network (FAN) for multidimensional feature fusion, and a Temporal Convolutional Network (TCN)-enhanced Informer for capturing long-term tribological dependencies. By combining Long Short-Term Memory (LSTM) temporal modeling with Variational Autoencoder (VAE) reconstruction, the method quantifies lubricant health through reconstruction error, establishing a direct correlation between data deviation and tribological performance degradation. Additionally, permutation importance-based feature evaluation and parameter contribution quantification techniques enable deep mechanistic analysis and fault source tracing of lubricant health degradation. Experimental validation using multi-sensor monitoring data demonstrates that SFTI-LVAE achieves a 96.67% fault detection accuracy with zero false alarms, providing early warning 6.47 h before lubrication failure. Unlike traditional anomaly detection methods that only classify conditions as abnormal or normal, the proposed continuous health index reveals gradual tribological degradation processes, capturing subtle viscosity–temperature relationships and wear particle evolution indicating early lubrication regime transitions. The health index correlates strongly with tribological performance indicators, enabling a transition from reactive maintenance to predictive tribological management, providing an innovative solution for equipment health evaluation in the digital tribology era. Full article

In order to investigate the effect of Zataria multiflora Bioss. extract and nanoextract on morphophysiological and phytochemical indices, yield, and essential oil compositions of basil (Ocimum basilicum L. var. Genovese) under salinity stress (0, 25, 50, and 100 mM NaCl), an experiment was conducted as a split-plot design in a basic block with complete randomization and three replications. In the treatment without salinity, nanoextract increased the shoot fresh weight by 34.28%, and regular extract increased it by 8.35% compared to the 0 NaCl without extract. In the treatment without salinity stress, nanoextract decreased the Na content by 17%, and regular extract decreased it by 5%; nanoextract increased the K content by 22.93%, and regular extract increased it by 9.05% compared to the 0 NaCl without extract, respectively. In all salinity concentrations applied, nanoextract showed lower sodium accumulation and higher potassium accumulation rate than regular extract and treatment without extract at the same salinity concentration. The highest total phenols were observed in the 100 mM salinity treatment in both nanoextract and regular extract of Z. multiflora, followed by the 50 mM salinity treatment—nano extract, with 12.33, 11.17, and 10.01 mg GA g⁻¹ FW, respectively. In the non-saline stress treatment, nanoextract increased the proline content by 125%, and regular extract increased it by 79.16% compared to the 0 NaCl without extract. In the treatment without salinity stress, the nano extract increased the level of PAL enzyme by 16.66% and the regular extract by 8.33% compared to the 0 NaCl without extract. The highest antioxidant activity was observed in the 100 mM salinity treatment in both nano extract and regular extract of Z. multiflora, followed by the 50 mM salinity treatment and nano extract with 31.86, 30.60, and 28.21%, respectively. In this study, the results of essential oil analysis indicated the identification of 39 compounds in which linalool, eugenol, carotenoid, methyl chavicol, A-Humulene, and menthol were identified as the main compounds. Among all treatments, Z. multiflora nanoextract, while moderating the effects of stress, showed the highest efficiency in improving the morphophysiological and biochemical traits and essential oil content and secondary metabolites of O. basilicum L. var. Genovese. Full article

This study aimed to develop a novel cream formulation incorporating pectin-based microcapsules loaded with lemon essential oil (LEO), with the goal of enhancing both sensory attributes and microbiological quality. The capsules were added at increasing concentrations (0%, 0.25%, 0.5%, 0.75%, and 1%) to assess their impact. Physicochemical analysis revealed that higher capsule content significantly improved consistency and viscosity. Microbiological evaluations confirmed the absence of key foodborne pathogens, including Salmonella spp., Listeria monocytogenes, Staphylococcus aureus, and Enterobacteriaceae, in all formulations. Additionally, the antibacterial efficacy of the encapsulated LEO was validated against Escherichia coli and Staphylococcus aureus strains. Sensory analysis using paired comparison, ranking, and hedonic tests demonstrated a clear preference for samples enriched with the 0.5% and 0.75% capsules, noted for their enhanced creaminess, pleasant lemon aroma, and well-balanced flavour. Statistical analysis (ANOVA and principal component analysis, PCA) confirmed significant differences among samples, particularly in texture and aroma attributes. These findings highlight the potential of LEO-loaded pectin capsules as a clean-label strategy to improve both the sensory appeal and microbial safety of cream formulations. Full article

Emergency diesel is prone to degradation during long-term storage, and experimental evaluations are costly and slow. Three-dimensional computational fluid dynamics (CFD) simulations were employed to model the diesel conditioning process. A physical model based on the actual dimensions of the storage tank was constructed. The volume of fraction (VOF) model tracked the gas–liquid interface, and the species transport model handled mixture transport. A UDF then recorded inlet and outlet flow rates and velocities in each cycle. The study focused on the effects of different baffle structures and numbers on conditioning efficiency. Results showed that increasing the baffle flow area significantly delays the mixing time but reduces the cycle time. Openings at the bottom of baffles effectively mitigate the accumulation of high-concentration conditioning oil caused by density differences. Increasing the number of baffles decreases the effective volume of the tank and amplifies density differences across the baffles, which shortens the mixing time. However, excessive baffle numbers diminish these benefits. These findings provide essential theoretical guidance for optimizing baffle design in practical diesel tanks, facilitating rapid achievement of emergency diesel quality standards while reducing costs and improving efficiency. Full article

Aeromonas hydrophila (A. hydrophila) is responsible for causing abdominal dropsy, swimming abnormalities, skin ulcerations, and pale gills in fish. Vaccination is an essential strategy for disease prevention in aquaculture. This study evaluated the efficacy of an oral vaccine against A. hydrophila in Ctenopharyngodon idella (C. idella). The vaccine was formulated as feed-based monovalent pellets, incorporating or spraying formalin-killed A. hydrophila on/into commercial feed with 30% crude protein. Mineral and fish oils were used as adjuvants at 10% of the feed. Prior to the trial, the experimental feed groups were subjected to quality and safety tests. Grass carp fingerlings (20 ± 5 g) were divided into seven groups (n = 20 per group): sprayed vaccinated feed with fish oil (SVFF), incorporated vaccinated feed with fish oil (IVFF), sprayed vaccinated feed with mineral oil (SVFM), incorporated vaccinated feed with mineral oil (IVFM), sprayed vaccinated feed (SVF), incorporated vaccinated feed (IVF), and a control group. Feed was provided at 3% of body weight for 60 days. Immunomodulation was investigated through lysozyme activity, antibody titers, and immunoglobulin M (IgM). The IVFF group showed significantly enhanced immunity and growth performance, with an 87% protection rate, 13% mortality, and the highest relative percentage survival (83%) following intraperitoneal A. hydrophila (6.8 × 10⁹ CFU/mL) challenge. Histological analysis indicated minimal pathological changes in the IVFF group compared to controls. Fish oil as an adjuvant enhanced immunity without adverse health effects. Overall, this study demonstrated that feed-based monovalent vaccines effectively improve immune responses and provide protection against A. hydrophila in C. idella. Full article

This study explores the synthesis, characterization, and extraction efficiency of hydrophobic natural deep eutectic solvents (NADESs), along with the allergen-modulating potential of extracted bioactive compounds. Six NADESs were synthesized using binary combinations of camphor, thymol, eugenol, and menthol (1:1 molar ratio) and characterized using Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis and differential thermal analysis (TGA/DTA), density functional theory (DFT), and molecular dynamics simulations (MD simulations). Bioactive compounds were extracted from Thujopsis dolabrata wood biomass via ultrasonic-assisted extraction and analyzed using gas chromatography–mass spectrometry (GC–MS). The total essential oil yield, estimated semiquantitatively by summing the peak areas of key terpenoid compounds, ranged from 1.91% to 7.90% across different NADES systems, indicating their varied extraction capacities. Molecular docking was performed to assess their allergen-modulating interactions with Amb a 1 and Cry j 1. All NADESs exhibited single-stage decomposition (110–125 °C) except camphor–menthol, which recrystallized. FTIR and simulations confirmed strong hydrogen bonding in eugenol-based NADESs, particularly menthol–eugenol. Extraction identified 47 bioactive compounds, with 4,5α-Epoxy-3-methoxy-17-methyl-7α-(4-phenyl-1,3-butadienyl)-6β,7β-(oxymethylene) morphinan as the most abundant (9.31–11.16%). It exhibited the highest binding affinity (Cry j 1: −8.60 kcal/mol, Amb a 1: −7.40 kcal/mol) and lowest inhibition concentration (Cry j 1: 0.49 µM, Amb a 1: 3.74 µM), suggesting strong allergen-modulating potential. Hydrophobic interactions and hydrogen bonding drove protein–ligand binding. These findings highlight NADESs as effective, sustainable solvents for extracting bioactive compounds with allergen-modulating potential. Full article

This study evaluated the effects of lasalocid sodium (LASA) and essential oils on the fermentation and nutritional quality of total mixed ration (TMR) silages. A 4 × 2 factorial design tested four additives—a control (distilled water), LASA (375 mg/kg DM), limonene essential oil (LEO), and a blend of cinnamaldehyde and carvacrol (EOB), both at 400 mg/kg DM—during summer and autumn. The TMRs were formulated to meet the nutritional requirements of lactating cows producing 20 kg of milk per day. After 110 days of ensiling, silages were analyzed for fermentation losses, pH, short-chain fatty acids, ammoniacal nitrogen (NH₃-N), aerobic stability (AS), and chemical composition. The additives significantly improved dry matter recovery (DMR), especially LASA and EOB in autumn. EOB showed the lowest effluent losses and highest AS, with higher acetic acid and lower NH₃-N contents. LEO and EOB increased lactic acid, while LASA reduced ethanol and butyric acid levels in summer. Crude protein increased with LEO in autumn, and LASA and LEO improved total digestible nutrients (TDNs) in summer. EOB-treated silages had higher fiber fractions in autumn, without compromising feed value. Therefore, LASA, LEO, and particularly EOB enhanced silage fermentation and nutrient preservation, with EOB showing the most consistent results across seasons. Full article

This study investigated the potential of Thymus serpyllum L. and Mentha × piperita L. essential oils (EOs), known for their bioactive properties, as adjunctive treatments targeting Basal cell carcinoma cancer stem cells (BCC CSCs). Primary cultures were established from ten BCC tumor samples and their distant resection margins as controls. The chemical composition of the EOs was analyzed by gas chromatography–mass spectroscopy (GC-MS) and attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR). The biological effects were evaluated via colony and spheroid formation, scratch assays, MTT and neutral red cytotoxicity assays, and qRT-PCR for Hh (SHH, PTCH1, SMO, and GLI1) and Notch (Notch1 and JAG1) gene expression. GC analysis identified thymol, p-cymene, and linalool as the main components of the EO of T. serpyllum L., and menthone and menthol in the EO of M. × piperita L. IC50 values were 262 µg/mL for T. serpyllum L. and 556 µg/mL for M. × piperita L. and were applied in all experiments. Both EOs significantly reduced CSC clonogenicity and migration (p < 0.05). The EO of T. serpyllum L. downregulated SMO and GLI1, while the EO of M. × piperita L. upregulated PTCH1, Notch1, and JAG1 (p < 0.05). These findings suggest that both EOs exhibit anticancer effects in BCC CSCs by modulating key oncogenic pathways, supporting their potential in BCC therapy. Full article

Hyperlipidemia, oxidative stress, and excessive inflammatory cytokine production are risk factors for depression. The potential preventive effects of essential oils (EOs) such as cumin and fennel EOs on depression may stem from their hypolipidemic, antioxidant, and anti-inflammatory activities. This work aimed to investigate the effects of cumin and fennel EO nanocapsules in a mouse model of depression caused by a high-fat diet (HFD) and chronic mild stress (CMS) using both in silico and in vivo studies. The cumin and fennel EOs were extracted, analyzed by GC-MS, and encapsulated in nano-form using gum Arabic and maltodextrin as wall materials. The freeze-dried nanocapsules were evaluated in HFD/CMS-treated mice. Molecular docking was used to examine the significance of the oils’ compounds in blocking the active sites of hydroxymethylglutaryl-CoA (HMG-CoA) and indoleamine 2,3-dioxygenase (IDO). According to the molecular docking results, the interactions between EO components and HMG-CoA or IDO indicate that these EOs may have hypercholesterolemic and antidepressive effects. Cumin and fennel EO nanocapsules showed hypolipidemic, antioxidant, and anti-inflammatory effects in vivo. This was demonstrated by the down-regulation of oxidants (ROS, MDA, and NO) and inflammatory markers (TLR4, TNF-α, and IL-6) in the brain, changes in lipid profile parameters, and the up-regulation of antioxidant enzymes (SOD, CAT, and GSH). The in silico and in vivo outputs revealed the potential preventive impact of cumin and fennel EO nanocapsules against depression-like states in the mouse model through the prevention of dyslipidemia, neuroxidation, and neuroinflammation. More human studies are needed to fully understand the antidepressive effects of cumin and fennel EO nanocapsules. Full article

Enhanced oil recovery (EOR) techniques are essential for maximizing hydrocarbon extraction from mature reservoirs. CO₂ injection (CO₂-EOR) is a promising technology that improves oil recovery while contributing to greenhouse gas reduction. This study investigates the potential of miscible CO₂-enhanced oil recovery (CO₂-EOR) in the MakXX oilfield of southeastern Kazakhstan. The aim is to assess oil displacement efficiency and its impact on key rock properties, including porosity, permeability, and mineral composition, under reservoir conditions. Core flooding experiments were conducted at 13 MPa and 42 °C using high-precision equipment to replicate reservoir conditions. The core was analyzed before and after CO₂ injection using SEM, EDS, and XRD. The results revealed a 54% oil recovery efficiency, accompanied by a 19% decrease in permeability and 8% reduction in porosity due to mineral precipitation and clay transformation. These findings provide insight into the performance and limitations of CO₂-EOR and support its application in similar lithology. To confirm and upscale laboratory observations, numerical simulation was conducted using a compositional model. The results demonstrated improved oil recovery, pressure stabilization, and enhanced sweep efficiency under CO₂ injection, supporting the scalability and field applicability of the proposed EOR approach. Full article

As information and sensor technologies advance swiftly, data-driven approaches have emerged as a dominant paradigm in scientific research. In the petroleum industry, precise forecasting of patterns of two-phase flow involving oil and water is essential for enhancing production efficiency and ensuring safety. This study investigates the application of Kolmogorov–Arnold Networks (KAN) for predicting patterns of two-phase flow involving oil and water and compares it with the conventional Multi-Layer Perceptron (MLP) neural network. To obtain real physical data, we conducted the experimental section to simulate the patterns of two-phase flow involving oil and water under various well angles, flow rates, and water cuts at the Key Laboratory of Oil and Gas Resources Exploration Technology of the Ministry of Education, Yangtze University. These data were standardized and used to train both KAN and MLP models. The findings indicate that KAN outperforms the MLP network, achieving 50% faster convergence and 22.2% higher accuracy in prediction. Moreover, the KAN model features a more streamlined structure and requires fewer neurons to attain comparable or superior performance to MLP. This research offers a highly effective and dependable method for predicting patterns of two-phase flow involving oil and water in the dynamic monitoring of production wells. It highlights the potential of KAN to boost the performance of energy systems, particularly in the context of intelligent transformation. Full article

Drag embedment anchors (DEAs) play a vital role in maintaining the stability and safety of offshore structures, including floating wind turbines, oil rigs, and marine renewable energy systems. Accurate prediction of anchor performance is essential for optimizing mooring system designs, reducing costs, and minimizing risks in challenging marine environments. By leveraging advanced machine learning techniques, this research provides innovative solutions to longstanding challenges in geotechnical engineering, paving the way for more efficient and reliable offshore operations. The findings contribute significantly to developing sustainable marine infrastructure while addressing the growing global demand for renewable energy solutions in coastal and deep-water environments. This current study evaluated tree-based machine learning algorithms, e.g., decision tree regression (DTR) and random forest regression (RFR), to predict the holding capacity and efficiency of DEAs in sand seabed. To train and validate the results of machine learning models, the K-fold cross-validation method, with K = 5, was utilized. Eleven geotechnical and geometric parameters, including sand friction angle (φ), fluke-shank angle (α), and anchor dimensions, were analyzed using 23 model configurations. Results demonstrated that RFR outperformed DTR, achieving the highest accuracy for capacity prediction (R = 0.985, RMSE = 344.577 KN) and for efficiency (R = 0.977, RMSE = 0.821 KN). Key findings revealed that soil strength dominated capacity, while fluke-shank angle critically influenced efficiency. Single-parameter models failed to capture complex soil-anchor interactions, underscoring the necessity of multivariate analysis. The ensemble approach of RFR provided superior generalization across diverse seabed conditions, maintaining errors within ±10% for capacity and ±5% for efficiency. Full article

Essential oils (EOs) have gained increasing attention as natural alternatives to synthetic food preservatives due to their broad-spectrum antimicrobial, antioxidant, and antigenotoxic properties. Derived from aromatic plants, EOs possess complex chemical compositions rich in bioactive compounds such as terpenes, phenolics, and aldehydes, which contribute to their effectiveness against foodborne pathogens, oxidative spoilage, and genotoxic contaminants. This review provides a comprehensive examination of the potential of EOs in food preservation, highlighting their mechanisms of action, including membrane disruption, efflux pump inhibition, and reactive oxygen species scavenging. Standard assays such as disk diffusion, MIC/MBC, time-kill kinetics, and comet and micronucleus tests are discussed as tools for evaluating efficacy and safety. Additionally, the use of EOs in diverse food matrices and the reduction in reliance on synthetic additives support cleaner-label products and improved consumer health. The review also examines the sustainability outlook, highlighting the potential for extracting EOs from agricultural byproducts, their integration into green food processing technologies, and alignment with the circular economy and the Sustainable Development Goals. Despite promising results, challenges remain in terms of sensory impact, regulatory approval, and dose optimization. Overall, EOs represent a multifunctional and sustainable solution for modern food preservation systems. Full article

Cinnamomum camphora (L.) Presl, a perennial evergreen tree of the Lauraceae family, exhibits diverse chemotypes and abundant essential oil constituents, which are widely utilized in pharmaceuticals, perfumery, and fine chemicals. Based on the variation in dominant volatile constituents, five chemotypes have been identified: Borneol Chemotype (BC), Camphor Chemotype (CC), Eucalyptol Chemotype (EC), Isoborneol Chemotype (IC), and Linalool Chemotype (LC). Their compositions of monoterpenoids (MT) and sesquiterpenes (SQT) differ significantly. This review systematically summarizes the research progress on MT and SQT in different chemotypes of C. camphora over the past five decades, with a total of 164 compounds identified (83 MT and 81 SQT), and compares the unique and shared constituents among chemotypes. Pharmacological studies indicate that C. camphora essential oils from different chemotypes exhibit strong antibacterial, anti-inflammatory, and antitumor activities, with linalool, camphor, and several SQT compounds showing remarkable biological effects in multiple bacterial, fungal, and tumor cell models. The underlying mechanisms may involve the disruption of cell membrane integrity, inhibition of key metabolic enzymes, interference with genetic transcription, and synergistic effects among multiple constituents. However, research on low-abundance bioactive components in different chemotypes remains limited, and their pharmacological mechanisms require further elucidation. This review provides a systematic reference for the future exploration of bioactive constituents, mechanistic studies, and efficient utilization of essential oils from different chemotypes of C. camphora, offering valuable insights for refined resource exploitation and industrial application. Full article

The global expansion of shale oil and gas extraction has generated widespread attention for its environmental, economic, and political implications. However, its social consequences remain less systematically assessed. This review synthesizes interdisciplinary research on how shale energy development affects communities, particularly in rural and resource-dependent regions. While extraction activities may generate economic opportunities and strengthen national energy security, they are also associated with population influx, pressure on infrastructure, housing shortages, public health risks, and increased political polarization. These impacts can alter social relationships, institutional trust, and access to essential services. By organizing and analyzing key themes in the social science literature, this review offers a structured overview of how shale energy development shapes local experiences and social systems. The goal of the present paper is to support researchers, policymakers, and community stakeholders in understanding the civic, communal, and public dimensions of energy transitions and in developing more equitable and sustainable policy responses. Full article