Search Results (22,978)

For the measurement of electrical conductivity of metal materials, the traditional contact measurement method has a limited test range and requires periodic electronic calibration. In order to overcome the above shortcomings, this paper takes the inductive response of an RLC circuit driven by alternating sources as the research object and proposes a non-contact method for conductivity measurement of non-ferromagnetic metals engaged by a single-layer solenoid sensor. The effect of the circuit parameters on the inductive sensor characteristics has been described with different resonant modes, and the electric conductivities of different metals can be theoretically calculated based on eddy current. Moreover, the Comsol Multiphysics software is used to conduct finite element analysis to compare the experimental results and the simulation, which is consistent with the theoretical analysis. The measured accuracy of the inductive sensor is verified to be higher than 91% in parallel resonance, which exhibits higher stability and precision than that of series mode. The implementation of this project will provide the theoretical basis and data reference for the detection of electromagnetic properties of unknown metals and has a wide range of applications in non-destructive testing, engineering construction detection, and other fields. Full article

This paper investigates the nonlinear dynamics of the wheel-side planetary reducer, considering the tooth wear effect. The tooth wear model based on the Archard adhesion wear theory is established, and the impact of tooth wear on meshing stiffness and piecewise-linear backlash of the planetary gear system is discussed. Then, the torsional vibration model and dimensionless differential equations considering tooth wear for the wheel-side planetary reducer are established, in which meshing excitations include time-varying mesh stiffness (TVMS), piecewise-linear backlash, and transmission error. The dynamic responses are numerically solved using the fourth-order Runge–Kutta method. On this basis, the nonlinear dynamics, such as the bifurcation and chaos properties of the wheel-side planetary reducer with tooth wear, are analyzed. Simulation results demonstrate that the existence of tooth wear reduces meshing stiffness and increases backlash. The reduction in the meshing stiffness changes the bifurcation path and chaotic amplitude of the system, inducing chaotic phenomena more easily. The increase in the gear backlash causes a higher amplitude of the relative displacement and more severe vibration. Full article

In order to obtain a gradient coating with excellent performance, novel titanium-modified plasma nitriding was primarily used as a support layer for the PVD coating of 38CrMoAl steel. The samples were subjected to titanium-modified plasma nitriding by placing sponge titanium around the samples, resulting in a thicker ductile diffusion layer and a thinner and denser compound layer. The research results showed that this thinner, denser compound layer formed by titanium-modified plasma nitriding provides stronger support for the AlCrN coating and thus bring about better performance compared to a conventional plasma nitrided layer, with the adhesion strength increasing from 16.8 N to 29.4 N, which is 42.8% higher than the conventional PN compound layer; the surface hardness increasing from 3650 HV_0.05 to 3780 HV_0.05; the friction coefficient and wear rate reducing from 0.64 and 5.4849 × 10⁻⁶ mm³/(N·m) to 0.61 and 2.3060 × 10⁻⁶ mm³/(N·m), respectively; and the wear performance improving by 137.85%. Additionally, the corrosion potential increased from −979.2 mV to −711.51 mV, and the value of impedance increased from 1.5515 × 10⁴ Ω·cm² to 9.4518 × 10⁴ Ω·cm², resulting in a significant improvement in corrosion resistance. In all, the novel support layer by titanium-modified plasma nitriding can provide much better support for AlCrN coating and thus bring about excellent enhanced performances, including adhesion strength and wear and corrosion resistance. Therefore, it is of great value in the PVD coating field, and it can provide valuable insights into gradient coating technology. Full article

The transformation of natural ecosystems into agroecosystems due to changes in land use/land cover (LULC) has been shown to significantly affect soil characterization and classification. The impact of LULC on soil taxonomy was assessed in a primary forest located in central–eastern Honduras, which had been deforested approximately forty years prior to the study. Morphological, physical, and physicochemical analyses were performed by describing 10 representative profiles, applying the Soil Taxonomy (ST) and World Reference Base for Soil Resources (WRB) nomenclatures. LULC resulted in physical degradation in agricultural areas, as evidenced by lighter-colored horizons (P02), reduced granular structure (P01, P02, P05), higher bulk densities (≤1.73 Mg m⁻³), and surface crusting (P02, P05); this phenomenon was also observed in pastures (P06–P09). SOC loss was 62% in croplands, 47–53% in agroforestry systems (P03) and fruit tree plantations (P04), and 25% in pastures. All profiles exhibited pH values between 6.5 and 8.4 and complete base saturation (BS), except for P08 and P09, which had pH values below 5.5, high levels of Al³⁺, and reduced BS (50–60%). Mollic epipedons and variability in the endopedons were also observed. According to the ST of the System of Soil Classification (SSC), the soils were classified as Mollisols, Entisols, Vertisols, and Alfisols; and as Phaeozems, Fluvisols, Gleysols, Anthrosols, Gypsisols, and Plinthosols by the WRB. We advocate for the inclusion of Anthropogenic Soils as a distinct Order within Soil Taxonomy (ST). The implementation of sustainable agricultural practices, in conjunction with the formulation of regulatory frameworks governing land use based on capacity and suitability, is imperative, particularly within the context of fragile tropical systems. Full article

This study aims to elucidate the geochemical reactions between CO₂-saturated water and rocks in CO₂-enhanced geothermal system (CO₂-EGS) reservoirs by focusing on andesite found in island arc regions, such as Japan. Laboratory flow tests of CO₂-saturated water (3 wt.% CO₂) and rocks (particle size: 0.14–1 mm) were conducted under varying temperature (150–250 °C) and flow rate (0.3 and 1.0 mL/min) conditions using a flow-through reactor. Elevated temperatures enhanced the dissolution of silicate minerals, reflected by increased Na⁺, K⁺, Ca²⁺, and Si concentrations, whereas those of Fe²⁺ and Al³⁺ remained low, suggesting secondary mineral precipitation. The dissolution process was dominant at 150 °C. Al-bearing minerals, such as gibbsite and boehmite, as well as clay minerals, including beidellite and kaolinite, were predominant at higher temperatures (200–250 °C). Carbonate minerals were not observed, attributable to low pH and limited availability of divalent cations. Flow rate substantially influenced Si dissolution rates, with lower flow rates promoting longer residence times and higher Si dissolution rates. These results indicate that the test conditions simulate the environment around the injection well, where the fluid is acidic and dissolution is the main reaction in the rock. Although a small amount of secondary minerals precipitated and the Si dissolution rates were of the same order of magnitude as those for labradorite, it may be considered that andesite has less impact on permeability variations than basalt near the injection well in CO₂-EGS reservoirs. Full article

Under the strategic goal of agricultural modernization, agricultural socialization services have become an important means of enhancing agricultural efficiency and guaranteeing food security. Based on microdata from 3811 farm households in seven provinces, this paper integrates labor force structural characteristics with digital literacy to construct a comprehensive analytical framework and empirically examines their effects on the degree of access to agricultural socialized services (DASS) through ordered logit model and moderated effects models. The results show that labor force characteristics significantly affect DASS, and the higher the degree of feminization, aging, and part-time employment, the higher the degree of access to services; digital literacy as a whole significantly improves DASS for farm households and shows heterogeneous moderating effects under different labor force characteristics. Therefore, this paper suggests formulating differentiated socialized service promotion strategies, deepening the digitalization of agricultural services, strengthening the digital technology training of rural laborers in various ways, enhancing DASS, effectively improving the efficiency of agricultural production, and supporting the dual goals of food security and rural revitalization. Full article

Excessive phosphorus emissions are a significant driver of severe eutrophication in water bodies, and developing an efficient and cost-effective adsorbent for phosphorus removal is imperative. In this study, a Na-type zeolite was synthesized from coal gangue sourced from an open-pit mine in Xinjiang province, China. The synthesis process involved drying, crushing, alkali activation, aging, hydrothermal crystallization, and Na⁺ ion exchange. Orthogonal design identified the optimal synthesis parameters: an alkali-to-ash ratio of 1:1, aging at 20 °C for 12 h, and crystallization at 130 °C for 12 h. Aging time exerted the greatest influence on the phosphate removal efficiency. The optimized zeolite exhibited excellent phosphate adsorption performance, achieving a removal efficiency of up to 96% and a capacity of 16 mg/g. The adsorption kinetics followed both pseudo-first-order and pseudo-second-order models, indicating processes governed by combined physical and chemical mechanisms. Isotherm data fitting with Freundlich and Langmuir models suggested the presence of both homogeneous and heterogeneous active sites. Thermodynamic studies confirmed a spontaneous and endothermic process, increasingly favorable at higher temperatures. Characterizations via scanning electron microscopy (SEM), X-ray diffraction (XRD), X-ray fluorescence (XRF) spectroscopy, and Fourier transform infrared (FTIR) spectroscopy confirmed the formation of Na-type zeolite and revealed structural and compositional changes following phosphate adsorption. Aluminum and calcium binding played key roles in the chemical adsorption mechanisms. This work not only offers a high-efficiency, low-cost solution for phosphorus removal from wastewater but also provides a sustainable pathway for the valorization of coal gangue in the Zhundong area of Xinjiang, China. Full article

We develop a rigorous algebraic–analytic framework for multidual complex numbers ${\mathbb{DC}}_n$ within the setting of Clifford analysis and establish a comprehensive theory of hyperholomorphic multidual complex-valued functions. Our main contributions are (i) a fully coupled multidual Cauchy–Riemann system derived from the Dirac operator, yielding precise differentiability criteria; (ii) generalized conjugation laws and the associated norms that clarify metric and geometric structure; and (iii) explicit operator and kernel constructions—including generalized Cauchy kernels and Borel–Pompeiu-type formulas—that produce new representation theorems and regularity results. We further provide matrix–exponential and functional calculus representations tailored to ${\mathbb{DC}}_n$, which unify algebraic and analytic viewpoints and facilitate computation. The theory is illustrated through a portfolio of examples (polynomials, rational maps on invertible sets, exponentials, and compositions) and a solvable multidual boundary value problem. Connections to applications are made explicit via higher-order automatic differentiation (using nilpotent infinitesimals) and links to kinematics and screw theory, highlighting how multidual analysis expands classical holomorphic paradigms to richer, nilpotent-augmented coordinate systems. Our results refine and extend prior work on dual/multidual numbers and situate multidual hyperholomorphicity within modern Clifford analysis. We close with a concise summary of notation and a set of concrete open problems to guide further development. Full article

Fuel with a tight lattice structure in the reactor core is an important design direction for high-performance water reactors. Due to the dispersed flow characteristic, research on post-dryout heat transfer is limited. However, a better understanding of post-dryout heat transfer characteristics under accident conditions is significantly important for fuel design and safety analysis. This study experimentally investigates the characteristics of post-dryout dispersed flow heat transfer in a 3-rod tight-lattice bundle with a pitch-to-diameter ratio of 1.2. The working conditions are as follows: system pressure ranging from 6 to 10 MPa, mass flux between 65 to 200 kg/(m²s), and heat flux varying from 75 to 200 kW/m². Circumferentially non-uniform heat transfer is obviously observed. The wall temperature is higher in the narrow gaps between rods, while lower in the vicinity of the subchannel center. The specific mechanisms of the above phenomena are analyzed. Parametric effects on post-dryout heat transfer are discussed and illustrated. Using the experimental data, commonly utilized correlations for transition boiling and film boiling are evaluated. In order to improve the prediction accuracy, new heat transfer correlations for transition boiling and film boiling in the tight-lattice under low mass flux and low heat flux are developed based on the experimental data and mechanistic analysis. Full article

A Universal Numerical Integrator (UNI) is a computational framework that combines a classical numerical integration method, such as Euler, Runge–Kutta, or Adams–Bashforth, with a universal approximator of functions, such as a feed-forward neural network (including MLP, SVM, RBF, among others) or a fuzzy inference system. The Euler-Type Universal Numerical Integrator (E–TUNI) is a particular case of UNI based on the first-order Euler integrator and is designed to model non-linear dynamic systems observed in real-world scenarios accurately. The UNI framework can be organized into three primary methodologies: the NARMAX model (Non-linear AutoRegressive Moving Average with eXogenous input), the mean derivatives approach (which characterizes E–TUNI), and the instantaneous derivatives approach. The E–TUNI methodology relies exclusively on mean derivative functions, distinguishing it from techniques that employ instantaneous derivatives. Although it is based on a first-order scheme, the E–TUNI achieves an accuracy level comparable to that of higher-order integrators. This performance is made possible by the incorporation of a neural network acting as a universal approximator, which significantly reduces the approximation error. This article provides a comprehensive overview of the E–TUNI methodology, focusing on its application to the modeling of non-linear autonomous dynamic systems and its use in predictive control. Several computational experiments are presented to illustrate and validate the effectiveness of the proposed method. Full article

Background/Objectives: The objective of this study is to compare the optical and visual quality provided by the advanced monofocal intraocular lens (IOL) ISOPure and the standard monofocal IOL MicroPure in cataract patients, using objective and subjective assessments. Methods: This prospective, single-blind clinical study includes 28 patients with cataracts, bilaterally implanted with either the ISOPure or MicroPure IOL. Eligible eyes had no ocular comorbidities and regular corneal astigmatism ≤ 1.00 D. Three months postoperatively, uncorrected distance and intermediate (UDVA, UIVA) and corrected distance and intermediate (CDVA, DCIVA) visual acuities were measured at 4 m, 80 cm, and 66 cm under photopic (85 cd/m²) and mesopic (3.5 cd/m²) conditions. Photic phenomena, including halo and glare, were evaluated. Objective optical quality was assessed using Objective Scattering Index (OSI), Modulation Transfer Function (MTF), Strehl Ratio (SR), and ocular aberrations. Subjective patient satisfaction was evaluated using Quality of Vision (QoV) and Catquest-9SF questionnaires. Results: Under photopic conditions, logMAR DCIVA at 80 cm, UIVA at 66 cm, and DCIVA at 66 cm were 0.18 ± 0.06, 0.25 ± 0.12, and 0.20 ± 0.13, respectively, for ISOPure, and 0.22 ± 0.06, 0.30 ± 0.09, and 0.25 ± 0.09 for MicroPure (p = 0.05, 0.02, and 0.05, respectively). No significant differences were observed in halo/glare size or intensity, OSI, MTF, or SR. However, statistically significant differences were found in higher-order total aberrations for pupil sizes of 3.0, 4.0 mm, and 5.0 mm. Questionnaires indicated greater satisfaction and functional intermediate vision with ISOPure. Conclusions: The ISOPure IOL offers superior intermediate vision without compromising distance vision, delivering a balanced combination of optical quality, functional performance, and patient satisfaction. Full article

In the context of circular economy, waste generated by fruit processing can be used to produce new materials with a wide range of uses. This study presents a method to synthesize biochar from peach kernel or grape pit waste. The adsorbents were tested in the removal of hexavalent chromium from synthetic wastewater with Cr⁶⁺ concentrations specific to plating processes. Characterization by BET, SEM, FTIR, and TG-DTG confirmed the formation of porous structures, and a well-functionalized surface. The effects of contact time, initial Cr⁶⁺ concentration, and adsorbent dose were investigated in static conditions. Both materials are efficient in hexavalent chromium removal, with sorption equilibrium achieved within 180 min. Kinetic studies indicated that the removal process follows a pseudo-second-order model. Equilibrium studies showed that optimal sorption occurred at pH = 6, with sorption capacities of 78.54 mg/g for biochar from peach kernels and 67.57 mg/g for biochar from grape pits. Hexavalent chromium followed a Sips adsorption isotherm for both biochars. Following the reusability study, it can be concluded that biochar from peach kernels maintains removal efficiency higher than 75% after four cycles. Full article

Oil refineries depend greatly on the estimation of crude oil properties in order to understand the oil’s behaviour and the product fractions expected from the refining process. In yield estimation, the crude oil source and variant can cause variability in prediction and lead to the need for repeatable analysis. The necessity for fast, accurate, and high-generalization yield estimation initiates the framework of this review. This paper aims to comprehensively review the available techniques for estimating the yield of petroleum products in the petroleum refining industry. The review provides a brief overview of petroleum refining processes and high-value products, followed by a description of the traditional method, which utilizes laboratory analysis to offer detailed findings, but requires a tedious methodology. The improvement of yield estimation leads to process simulation, modelling, and machine learning, enabling a fast response and better prediction with higher accuracy. Thorough case studies related to simulation software, models, and algorithms are presented to discover the process and model development, applications, advantages, and drawbacks. Enhancing petroleum product yield estimation provides reliable techniques for oil refiners that enable them to achieve optimized production aligned with sustainability and modernization goals. Full article

With the rapid development of big data and artificial intelligence, the problem of image privacy leakage has become increasingly prominent, especially for images containing sensitive information such as faces, which poses a higher security risk. In order to improve the security and efficiency of image privacy protection, this paper proposes an image encryption scheme that integrates face detection and multi-level encryption technology. Specifically, a multi-task convolutional neural network (MTCNN) is used to accurately extract the face area to ensure accurate positioning and high processing efficiency. For the extracted face area, a hierarchical encryption framework is constructed using chaotic systems, lightweight block permutations, RNA cryptographic systems, and bit diffusion, which increases data complexity and unpredictability. In addition, a key update mechanism based on dynamic feedback is introduced to enable the key to change in real time during the encryption process, effectively resisting known plaintext and chosen plaintext attacks. Experimental results show that the scheme performs well in terms of encryption security, robustness, computational efficiency, and image reconstruction quality. This study provides a practical and effective solution for the secure storage and transmission of sensitive face images, and provides valuable support for image privacy protection in intelligent systems. Full article

Latent heat thermal energy storage (LHTES) based on phase change materials (PCMs) is receiving increasing interest since it offers high energy storage density while enabling the integration of variable renewable energies, hence boosting the transition towards a climate-neutral future. Despite the advantages that PCMs offer in providing a nearly isothermal solid–liquid phase transition, they still face some challenges that limit their deployment in real applications such as low thermal conductivity, phase separation, and supercooling, which affect charging and discharging rates. X-ray computed tomography (XCT) is a non-destructive imaging technique widely used in materials science for both qualitative and quantitative analysis of material microstructures and their evolution. Recent advances in laboratory-XCT instrumentation enabled short acquisition times on the order of tens of seconds which allows the investigation of dynamic processes in situ by time-lapse XCT measurements. These advances open new opportunities for revealing information on the morphology of solid–liquid PCMs. Despite the fact that XCT imaging has significant potential for energy research, its application in the field of PCMs is fairly new. A key enabler of applications of XCT to PCMs is the density difference between solid and liquid PCMs, which was found to be higher than 7% for all investigated PCMs. This enabled solid and liquid phases to be distinguished one from the other and properly quantified over time. The present work reviews the principles of laboratory-based XCT and the recent applications of XCT technology in the characterisation of PCMs, with emphasis on the study of the solid–liquid phase transition and validation of numerical PCM models by addressing the potentialities and challenges of XCT in PCM research. Full article