Search Results (204)

Against the background of observed climate change, which increases the risk of glacier-system degradation and the formation of hidden crevasses, the development of lightweight, wideband, and highly directional antenna systems has become a key factor in ensuring the safety of logistics operations and enhancing the spatial resolution and interpretability of ground-penetrating radar monitoring of near-surface snow–ice layers. The effectiveness of such systems is largely determined by the characteristics of the antenna unit, including the operating frequency band, gain, radiation pattern, weight, and resilience under extreme climatic conditions. The aim of this review is to provide a systematic analysis of modern Vivaldi antenna designs and Vivaldi-based antenna arrays, as well as to assess their prospects for application in X-band ground-penetrating radar systems for probing Antarctic snow-ice media. The paper considers the main types of ground-penetrating radar (GPR) antennas, their advantages and limitations, substantiates the priority of detecting hazardous near-surface inhomogeneities, and analyzes the capabilities of the X-band for the high-resolution identification of these inhomogeneities. Particular attention is paid to modern modifications of Vivaldi antennas, including antipodal, balanced, director-loaded, metamaterial-based, and array configurations. The analysis shows that Vivaldi antennas represent a promising basis for lightweight, wideband, and directional GPR systems; however, they require further improvement in terms of gain enhancement, sidelobe and back-lobe suppression, radiation-pattern stabilization, and adaptation to Antarctic operating conditions. Future research should focus on the development of adaptive and phased Vivaldi arrays, the use of metamaterials, Electromagnetic Band-Gap/Frequency-Selective Surfaces (EBG/FSS) structures, and director elements, the creation of lightweight, frost-resistant substrate materials, the advancement of multi-polarization multiple-input multiple-output (MIMO) systems, and the integration of antenna arrays with synthetic aperture radar (SAR) processing adapted to a multilayer snow–ice medium. Full article

Despite advances in topic modeling, extracting coherent themes from short, noisy, health-related social media texts remains a methodological challenge. This paper presents a preliminary and exploratory empirical investigation of a prompt-driven Large Language Model (LLM) pipeline for topic modeling of 504 multiple sclerosis (MS)-related posts from Platform X. Two in-context learning strategies—zero-shot and few-shot prompting—were compared using GPT-4o-mini, with topic quality assessed through a multi-layered evaluation framework that leveraged GPT-4 for automated coherence and diversity scoring, complemented by human validation for coherence and document-level faithfulness. Within this experimental setting, few-shot prompting achieved the highest human agreement score (87.5%) alongside high coherence (4.9/5.0), while zero-shot prompting yielded the highest coherence score (5.0/5.0), with 79.2% human agreement. Both configurations demonstrated high thematic diversity (4.6/5.0) and produced themes largely judged as faithfully grounded in the source posts across the full corpus, with few-shot prompting demonstrating consistently stronger faithfulness and greater thematic stability. Nonetheless, these findings suggest that prompt-driven LLM pipelines — particularly few-shot approaches—show promise as a human-aligned and interpretable method for topic modeling of short, noisy, health-related social media texts. Full article

Electroencephalography records brain electrical activity arising from synchronized synaptic activity of neurons in the cerebral cortex, as measured at the scalp surface. In this work, neural activity is modeled as an equivalent current dipole with arbitrary orientation located within the innermost conductive layer. To represent the head anatomy, the volume conductor is modeled as a central brain compartment enclosed by concentric spherical shells representing the cerebrospinal fluid (CSF), skull, and scalp, with different conductivity values. The present study incorporates anisotropic conductivity with distinct radial and tangential components within a multilayer spherical head model by extending existing analytical formulations. While analytical solutions for isotropic spherical models are well established, anisotropic formulations are typically addressed using numerical or approximate methods. By applying spherical harmonics to the Poisson equation in layered anisotropic media, analytical expressions are derived for the electric potential generated by dipole sources. The forward model is evaluated using electrode positions $\left(\theta ,\phi \right)$ defined according to the EEGLAB layout, for a representative configuration with a head radius of $9.2 \mathrm{c}\mathrm{m}$. Quantitative comparisons are performed using MAG and RDM metrics for homogeneous and inhomogeneous anisotropic conductivity models. The results indicate that conductivity anisotropy significantly influences both the magnitude and spatial distribution of scalp potentials, particularly due to attenuation and spatial smoothing effects introduced by the skull layer. The analytical expressions derived contribute to the theoretical study of EEG forward modeling in anisotropic layered media and may serve as reference solutions for the assessment of numerical formulations. Full article

Tropical lignocellulosic residues are increasingly relevant feedstocks for lignin-containing nanocellulose composites, but their performance cannot be predicted from botanical origin or bulk lignin percentage alone. This review defines the interface as the geometrical boundary between phases and the interphase as the finite, compositionally graded region in which lignin distribution, nanocellulose morphology, adsorbed water, and the surrounding matrix jointly govern stress transfer and mass transport. Using an evidence-weighted framework, the literature is organized into the following categories: residual-lignin nanofibrils, redeposited-lignin systems, lignin nanoparticle assemblies, compatibilized thermoplastic hybrids, and all-lignocellulosic sheets. Representative quantitative observations show that controlled residual lignin can the increase water contact angle from approximately 35 degrees to 78 degrees and reduce oxygen permeability by up to 200-fold in nanopapers, while selected PLA/LCNF systems show tensile-strength and modulus increases of 37% and 61%, respectively; however, high or poorly distributed lignin can suppress fibrillation, lower viscosity, weaken gel networks, and reduce reproducibility. The most defensible near-term product windows are packaging layers, grease/oil barrier papers, coatings, paper-like multilayers, and selected porous media. Thermoplastic matrices remain process-sensitive, and biomedical, additive-manufacturing, nano-reactor, and energy-material claims require stronger validation of the extractables, rheology, humidity history, TEA/LCA metrics, and end-of-life behavior. This review, therefore, provides a critical, application-backward roadmap for tropical biorefineries in which interfacial function, wet handling, drying energy, and process integration are assessed together rather than treated as independent variables. The abbreviations used in the abstract are defined as follows: CNFs, cellulose nanofibrils; CNC, cellulose nanocrystals; LCNF, lignin-containing cellulose nanofibrils; LCNCs, lignin-containing cellulose nanocrystals; PLA, poly(lactic acid); PHB, polyhydroxybutyrate; PHAs, polyhydroxyalkanoates; PVA, poly(vinyl alcohol); DESs, deep eutectic solvents; TEA, techno-economic analysis; LCA, life-cycle assessment; ML, machine learning. Full article

Hydraulic fracture network initiation and propagation in tight sandstone are strongly controlled by mineral heterogeneity and fluid–solid interaction. However, existing numerical models still have limited capability in simultaneously representing multi-mineral distributions and dynamically coupled fracture-fluid processes. In this study, a two-dimensional polygonal discrete element fluid–solid coupled model was established based on mineralogical images of tight sandstone. Compared with conventional continuum-based approaches, the proposed model is better suited to describing fracture initiation, branching, and network evolution in multi-mineral granular media. Under dimensionless operating conditions calibrated against field data, coupled and uncoupled formulations were systematically compared to evaluate the role of hydro-mechanical interaction during hydraulic fracturing. The coupled simulations generated consistently more fractures than the uncoupled simulations over the investigated injection-rate range, with an average increase of 28.7% and a maximum increase of 67.2%. Compared with the uncoupled model, the coupled model also predicted higher breakdown pressures and stronger fracture-tip pressure concentrations, and the breakdown pressure increased with injection rate. Under low injection rates, the coupled formulation reproduced pressure-buildup-driven fracture-tip advance, whereas the uncoupled formulation failed to sustain fracture propagation. Under higher injection rates, the coupled formulation produced multilayered and highly branched fracture networks, while the uncoupled formulation mainly generated simple first-order branching. These results demonstrate that hydro-mechanical coupling is a controlling mechanism for fluid-energy dissipation, fracture-tip pressure evolution, and complex fracture network formation in tight sandstone. This study provides an image-based polygonal DEM framework for evaluating hydro-mechanical fracture network evolution in multi-mineral tight sandstone. Full article

The adsorption and desorption behavior of the azo dye Orange II (OII) was investigated using composite beads prepared from shrimp shell–derived chitosan (50 wt%) and montmorillonite-rich clay. The structural and morphological properties of the synthesized beads were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM) and FT-IR (Fourier Transform Infrared Spectroscopy). Batch adsorption experiments were performed to evaluate the removal efficiency of OII from aqueous solutions under various conditions, revealing that a low adsorbent dosage (0.5 g L⁻¹) and an acidic medium (pH 4) provided optimal adsorption performance. Adsorption kinetics and equilibrium isotherms were analyzed to elucidate the adsorption mechanism. Thermodynamic parameters indicated that the adsorption process was spontaneous (ΔG° < 0) and endothermic (ΔH° > 0). Equilibrium data were fitted to both Langmuir and Freundlich isotherm models, with the Freundlich model providing the best correlation (R² = 0.99), suggesting multilayer adsorption on a heterogeneous surface. The adsorption capacity increased significantly with temperature, rising from 98.35 mg g⁻¹ at 298 K to 182.57 mg g⁻¹ at 318 K, further confirming the endothermic nature of the process. Kinetic analysis revealed relatively rapid adsorption, with maximum adsorption capacities increasing from approximately 100 mg g⁻¹ at 25 °C to 123 mg g⁻¹ at 45 °C. Regeneration and reusability tests demonstrated that the composite beads could be reused through adsorption–desorption cycles; however, a gradual decline in removal efficiency was observed, decreasing from 97% in the first cycle to 25% after the fifth cycle. This decrease is likely associated with partial structural degradation or the detachment of bead components during repeated regeneration. Overall, the results highlight the potential of chitosan–clay composite beads as promising and sustainable adsorbents for the removal of azo dyes from aqueous media. Full article

The increasing use of layered materials in various modern industries demands effective non-destructive testing methods. Guided wave testing is a promising solution, but accurate dispersion curves are essential for its reliable implementation. These curves are crucial for the appropriate selection of testing parameters and for the reliable interpretation of inspection results. This study, therefore, aims to develop and verify a computationally efficient and versatile tool for calculating dispersion curves in multilayered media. We propose an approach based on the semi-analytical finite element (SAFE) method implemented in COMSOL Multiphysics 6.2. This approach employs commercial finite element software capabilities, including optimized solvers and the ability to handle complex material properties (e.g., layer anisotropy) and geometries, thus avoiding the need for specialized code. We present the theoretical background and implementation details of the proposed approach in COMSOL Multiphysics. The calculated dispersion curves show excellent agreement with those obtained from the established software Dispersion Calculator 3.1, with a relative error of no more than 0.001%. These results confirm the applicability of the developed SAFE implementation for calculating dispersion characteristics of multilayered structures and support its use in developing novel guided wave ultrasonic testing techniques for multilayered composite materials. Full article

Understanding the coupled dynamics of groundwater flow and salinity transport is essential for the sustainable management of aquifer systems, particularly in irrigated and semi-arid regions where evaporation, recharge variability, and groundwater abstraction strongly influence hydrogeological regimes. In multilayer porous media, groundwater-level fluctuations and salt migration processes are closely interconnected, since hydraulic gradients control solute transport while salinity variations may affect flow behaviour through density-related mechanisms. In this study, a nonlinear mathematical model is developed to describe groundwater-level evolution and salt transport within a two-layer porous medium consisting of a phreatic layer and an underlying confined aquifer. The model accounts for filtration processes, interlayer hydraulic exchange, density-dependent effects, and external forcing factors including surface recharge, evaporation, and pumping. For numerical implementation, the governing equations are discretized using a finite-difference scheme with central spatial approximations and an implicit Crank–Nicolson-type temporal formulation. A hybrid second-order time approximation is introduced for the main-layer equation to improve numerical smoothness and stability. The resulting tridiagonal algebraic systems are solved using the Thomas algorithm within an iterative quasi-linearization framework, ensuring both computational efficiency and numerical robustness. Simulation results reveal a clear difference in the dynamical behaviour of the two layers. The phreatic aquifer exhibits rapid and high-amplitude responses to external forcing, whereas the confined aquifer demonstrates slower and smoother hydraulic and geochemical adjustments. Sensitivity analysis further identifies the filtration coefficient, transmissivity, porosity, density-related parameters, surface flux, and pumping intensity as the dominant factors governing groundwater dynamics and salinity redistribution. The proposed modelling framework provides a reliable tool for analysing coupled groundwater–salinity processes and offers a scientifically grounded basis for groundwater monitoring, salinization risk assessment, and sustainable aquifer management. Full article

Propyl-paraben (PrP) is a common preservative found in cosmetics and pharmaceutical products. It is classified as a category 1 endocrine-disrupting compound, which highlights the importance of efficiently removing it from water during treatment processes. This study investigates the potential of using Leptolyngbya sp. dominated cyanobacterial biomass residues, in both their raw and hydrothermally treated (hydrochar) forms, for the removal of PrP from aqueous media. Batch and fixed-bed column experiments were carried out under varying conditions to assess adsorption kinetics and equilibrium behavior. Both raw biomass and hydrochar exhibited satisfactory PrP removal, achieving maximum adsorption capacities of 224.58 and 258.55 mg/g respectively, at 10 mg/L initial PrP concentration and 23.33 mg/L adsorbent dosage. Equilibrium data were best described by the Freundlich isotherm model, indicating a heterogeneous surface and multilayer adsorption. The kinetic analysis revealed that the adsorption behavior, for both adsorbents, was best described by the pseudo-second-order model, while the thermodynamic evaluation revealed negative ΔH° and ΔS° values, confirming an exothermic, physisorption-driven process. The adsorption mechanism was further investigated through surface characterization techniques, including Fourier Transform Infrared Spectroscopy, Scanning Electron Microscopy, N₂ physisorption, and zeta potential analysis. The findings demonstrate the potential of microalgal biomass as a low-cost, sustainable biosorbent, for emerging contaminants, reinforcing its role in advanced water treatment and circular economy strategies. Full article

Metal oxide nanoparticles dispersed in water are difficult to recover because of their small size and colloidal stability. In this study, the interfacial adsorption behavior of Fe₂O₃, CoO, and CuO nanoparticles at hydrophobic ionic liquid (IL)–water interfaces was investigated and compared with that at molecular solvent–water interfaces. When CuO nanoparticle dispersions were shaken with hydrophobic ILs, bis(trifluoromethanesulfonyl)imide ([NTf₂]⁻) salts of 1-butyl-3-methylimidazolium ([BMIm]⁺) and 1-octyl-3-methylimidazolium ([OMIm]⁺), the nanoparticles were removed from the aqueous phase and accumulated at the IL–water interface, while negligible Cu was detected in the bulk IL phase. The removal efficiency decreased with increasing ionic strength below 0.05 mol/dm³ and increased with pH, indicating that electrostatic interactions between charged nanoparticles and the IL–water interface contribute to adsorption. Adsorption isotherms were empirically fitted with the Langmuir equation to estimate the maximum adsorption capacity. For negatively charged Fe₂O₃ and CuO nanoparticles, the maximum adsorption capacities at IL–water interfaces exceeded those at molecular solvent–water interfaces and the theoretical monolayer capacity estimated from nanoparticle size, suggesting multilayer adsorption or aggregation at the interfaces. These results demonstrate the potential of hydrophobic IL–water interfaces for the separation and recovery of metal oxide nanoparticles from aqueous media. Full article

Empirical parameter settings in steam-based soil disinfestation for Panax notoginseng (a valuable medicinal plant) often hinder the simultaneous optimization of pathogen control and energy efficiency. To address this limitation, this study aims to develop a parameter regulation framework that integrates multi-output regression with scenario-oriented intelligent decision-making. Initially, a comprehensive dataset comprising critical parameters—steam pressure (P_steam), soil compaction (C_soil), and heating time (t_heat)—was established. A random search (RS) hyperparameter optimization scheme was employed to comparatively evaluate the multi-output predictive performance of Random Forest (RF), Support Vector Regression (SVR), and Multilayer Perceptron (MLP) for the joint estimation of soil temperature (T_soil) and root-rot pathogen kill rate (Kill_rate). Subsequently, by integrating total energy consumption (E_total) and operating electricity cost models, a constrained search algorithm was implemented to develop three objective-oriented decision modes: “maximize Kill_rate”, “minimize C_electricity”, and “maximize Efficiency”. Results demonstrate that the RS-optimized SVR yielded superior multi-output performance, achieving R² of 0.968 for T_soil (MAE = 2.44 °C) and 0.808 for Kill_rate (MAE = 7.85%). Compared to conventional empirical configurations, the proposed decision modes exhibited significant advantages across diverse scenarios. In the “maximize Kill_rate” mode, dynamic extensions of t_heat facilitated theoretical complete inactivation even under challenging heating conditions, effectively eliminating disinfection “blind spots” inherent in fixed-duration strategies. Under the “minimize C_electricity” mode, precise regulation of P_steam reduced operational electricity costs by 18.2% while satisfying the constraint of Kill_rate ≥ 95%. Furthermore, the “maximize Efficiency” mode identified an optimal operating point at C_soil = 64 kPa (P_steam = 0.4 MPa, t_heat = 13 min), thereby mitigating performance degradation associated with excessive tillage or high media rigidity and achieving an optimized cost–benefit ratio. By synthesizing high-fidelity multi-output regression with a flexible multi-mode decision-making framework, this study provides an intelligent solution for soil disinfestation in protected agriculture, facilitating the coordinated optimization of phytosanitary efficacy, energy expenditure, and economic viability. Full article

This paper addresses the challenge of accurately measuring liquid level interfaces in multiphase mixed media by proposing a detection method based on ultrasonic transmission. First, a mathematical model of the ultrasonic measurement system was established, and the acoustic field characteristics of transducers with different frequencies and diameters in slurry were simulated and analyzed to determine the optimal excitation frequency and probe diameter. On this basis, an echo sound pressure calculation model based on the side-incidence method was constructed, and a formula for calculating the liquid level interface height was derived. Finally, an experimental test platform with a multi-layer steel container was built to measure the propagation velocity, attenuation coefficient, and acoustic impedance coefficient of ultrasound in the slurry, verifying the feasibility of the liquid level interface measurement method. Full article

In marine service environments, material surfaces inevitably suffer from wear damage, which can compromise the integrity of protective coatings and further affect their corrosion resistance. Therefore, investigating the post-wear corrosion resistance of coatings is of great significance. In this work, single-layer CrN coatings, CrAlN coatings, and CrN/CrAlN multilayer coatings were deposited on stainless-steel substrates by arc ion plating, and the microstructure, tribological properties, and corrosion behavior before and after wear were systematically investigated. Wear tests were performed under applied loads of 2.5 N and 5 N. The corrosion behavior in the unworn condition and the post-wear corrosion resistance condition was evaluated in a 3.5 wt.% NaCl solution. The results showed that all coatings exhibited a face-centered cubic (FCC) structure, while the CrN/CrAlN multilayer coating possessed the smallest average grain size (13.47 nm). Under applied loads of 2.5 N and 5 N, the CrN/CrAlN multilayer coating exhibited the lowest wear rate, indicating the best wear resistance. In the unworn condition, the CrN/CrAlN multilayer coating showed the lowest corrosion current density (2.74 × 10⁻¹⁰ A/cm²) and the most positive corrosion potential (0.025 V), demonstrating the best corrosion resistance. After wear under a load of 5 N, the CrN/CrAlN multilayer coating retained a low corrosion current density (3.35 × 10⁻¹⁰ A/cm²), in contrast to the marked increases observed for the single-layer coatings. The enhanced performance is considered to be mainly associated with the periodic heterogeneous interfaces in the multilayer structure, which help suppress crack propagation and prolong the penetration path of corrosive media. Full article

This paper presents a probabilistic–statistical approach to the analysis of diffusion processes in randomly nonhomogeneous multilayered bodies under conditions of incomplete experimental information on the boundary. The boundary condition is reconstructed from experimental data using linear regression, while the solution of the corresponding contact initial-boundary value problem is obtained in the form of a Neumann series and averaged over an ensemble of phase configurations. A system of statistical estimates for the solution is developed, including confidence intervals and two-sided critical regions, which provide complementary characteristics of uncertainty. Numerical experiments are performed for six representative samples differing in sample size, variance, and observation interval. It is shown that, despite significant differences in the statistical properties of the input data, the averaged concentration field preserves a qualitatively stable spatio-temporal structure. The results of the article address gaps in existing research by applying a probabilistic-statistical approach that consistently integrates two key elements for the analysis of diffusion processes in multilayer media. The first of these is the reconstruction of boundary conditions using linear regression to recover the conditions at the body boundary based on incomplete experimental data. The second key point is the analysis of uncertainty propagation by combining the regression model with a probabilistic analysis of the corresponding contact initial-boundary value problem, which allows us to quantitatively assess how the errors in the experimental data affect the final solution. From the point of view of mathematical modeling methods, the novelty of the approach lies in the creation of a structural-hierarchical scheme that synthesizes the approaches of mathematical statistics and the theory of random fields. The developed method is a theoretical and computational innovative basis for the analysis of specific physical and technological processes. Full article

Nuclear energy has emerged as a crucial technological solution for ensuring energy security and achieving carbon neutrality goals, given its ultra-high energy density and near-zero carbon emissions against the backdrop of rapid socioeconomic development, increasing energy demands, and accelerated global transition toward low-carbon energy structures. As the core component for energy conversion in nuclear reactors, fuel elements critically determine reactor efficiency and safety performance, with the fission product retention capability of silicon carbide layers in multilayer-coated fuel particles having been thoroughly validated through high-temperature gas-cooled reactor irradiation tests. The precise sphericity control of large-sized UO₂ fuel kernels represents a fundamental requirement for enhancing tristructural isotropic (TRISO) fuel particle performance and advancing Generation IV nuclear power plant development. This study presents a sphericity control strategy based on sol–gel processing that synergistically integrates physicochemical regulation of gelling media with multi-field washing flow field optimization. By implementing silicone oil-mediated interfacial tension gradient control, we effectively suppressed gel sphere destabilization while developing an innovative three-phase sequential washing technique involving kerosene washing, anhydrous ethanol interfacial transition, and ammonia solution replacement, which significantly enhanced mass transfer diffusion in stagnant liquid films and revolutionized fuel microsphere washing technology with improved efficiency and quality. Experimental results demonstrate that this integrated approach increases kernel sphericity qualification to 99.8%, reduces washing solution consumption by 79%, and achieves an average sphericity of 1.03. The research establishes a coupling mechanism between gelling media and multi-field washing processes, elucidating the synergistic effect between interfacial tension regulation and washing optimization, thereby providing both theoretical foundations and engineering application basis for the precision manufacturing of high-performance nuclear fuels. Full article