Search Results (683)

The aim of the article is to determine the control range of a multiphase squirrel cage induction generator with more than three stator phases, operating in a wide range of driving speeds. The generator produces an output DC voltage using a multiphase converter operating as a PWM rectifier. The entire speed range is divided into intervals in which the sequence of stator phase voltages and, in effect, the number of pole pairs, is changed. In each interval, the output voltage is regulated by the frequency and amplitude of the stator voltages causing the highest possible power efficiency of the generator. The system can be scalar controlled or regulated using field orientation. Generator characteristics are calculated based on the set of steady-state equations derived from differential equations describing the multiphase induction machine. The calculation results are compared with simulations and with the steady-state measurement of the vector-controlled nine-phase generator. Recognizing the reliability of the obtained results, calculations are performed for a twelve-phase generator, obtaining satisfactory efficiency from 70% to 85% in the generator speed range from 0.2 to 1.0 of the assumed reference speed of 314 rad/s. The generator producing DC voltage can charge an electrical energy storage system or can be used directly to provide electrical power. This solution is not patented. Full article

A rotating imperfect ring resonator of the gyroscope is modeled by a rotating thin ring with evenly distributed point masses. The free response of the rotating ring structure at constant speed is investigated, including the steady elastic deformation and wave response. The dynamic equations are formulated by using Hamilton’s principle in the ground-fixed coordinates. The coordinate transformation is applied to facilitate the solution of the steady deformation, and the displacements and tangential tension for the deformation are calculated by the perturbation method. Employing Galerkin’s method, the governing equation of the free vibration is casted in matrix differential operator form after the separation of the real and imaginary parts with the inextensional assumption. The natural frequencies are calculated through the eigenvalue analysis, and the numerical results are obtained. The effects of the point masses on the natural frequencies of the forward and backward traveling wave curves of different orders are discussed, especially on the measurement accuracy of gyroscopes for different cases. In the ground-fixed coordinates, the frequency splitting results in a crosspoint of the natural frequencies of the forward and backward traveling waves. The finite element method is applied to demonstrate the validity and accuracy of the model. Full article

Background/Objectives: Urban green space has been increasingly recognized as a determinant of maternal and child health. This study investigated the association between prenatal exposure to different types of green space and the risk of congenital anomalies in South Korea. Methods: We analyzed data from the National Health Insurance Service (N = 142,422). Green space exposure was measured at the area level and categorized into grassland and forest; statistical analysis was performed using generalized estimating equations and generalized additive models to analyze the associations. Additionally, subgroup and sensitivity analyses were performed. Results: GEE analysis showed that a 10% increase in the proportion of grassland in a residential district was associated with a reduced risk of nervous system (adjusted odds ratio [aOR]: 0.77, 95% confidence interval [CI]: 0.63–0.94) and genitourinary system anomalies (aOR: 0.83, 95% CI: 0.71–0.97). The subgroup analysis results showed significance only for male infants, but the difference between the sexes was not significant. In the quartile-based analysis, we found a slightly significant p-value for trend for the effect of forests on digestive system anomalies, but the trend was toward increasing risk. In a sensitivity analysis with different exposure classifications, the overall and nervous system anomalies in built green space showed that the risk decreased as green space increased compared to that in the lowest quartile. Conclusions: Our results highlight the importance of spatial environmental factors during pregnancy and suggest that different types of green spaces differentially impact the offspring’s early health outcomes. This study suggests the need for built environment planning as part of preventive maternal and child health strategies. Full article

The objective of this investigation is to obtain numerical solutions for a variety of mathematical models in a wide range of disciplines, such as chemical kinetics, neurosciences, nonlinear optics, metallurgical separation/alloying processes, and asset dynamics in mathematical finance. This research features numerical simulations conducted with a remarkably low error measure, providing a visual representation of the examined models in these areas. The proposed method is the double Laplace–Adomian decomposition method, which facilitates the numerical acquisition and analysis of solutions. This paper presents the first report of numerical simulations employing this innovative methodology to address these problems. The findings are expected to benefit the natural sciences, mathematical modeling, and their practical applications, representing the innovative aspect of this article. Additionally, this method can analyze many classes of partial differential equations, whether linear or nonlinear, without the need for linearization or discretization. Full article

Wave deformation and sediment transport nearest the shoreside are among the main reasons for sand erosion and beach profile changes. In particular, identifying the areas of incident-wave breaking and longshore current generation parallel to the shoreline is important for understanding the morphological changes of coastal beaches. In this study, a two-phase incompressible flow model along with a sandy sloping topography was employed to investigate the wave deformation and longshore current generation areas in a circular wave basin model. The finite volume method (FVM) was implemented to discretize the governing equations in cylindrical coordinates, the volume-of-fluid method (VOF) was adopted to differentiate the air–water interfaces in the control cells, and the zonal embedded grid technique was employed for grid generation in the cylindrical computational domain. The water surface elevations and velocity profiles were measured in different wave conditions, and the measurements showed that the maximum water levels per wave were high and varied between cases, as well as between cross-sections in a single case. Additionally, the mean water levels were lower in the adjacent positions of the approximated wave-breaking zones. The wave-breaking positions varied between cross-sections in a single case, with the incident-wave height, mean water level, and wave-breaking position measurements indicating the influence of downstream flow variation in each cross-section on the sloping topography. The cross-shore velocity profiles became relatively stable over time, while the longshore velocity profiles predominantly moved in the alongshore direction, with smaller fluctuations, particularly during the same time period and in measurement positions near the wave-breaking zone. The computed velocity profiles also varied between cross-sections, and for the velocity profiles along the cross-shore and longshore directions nearest the wave-breaking areas where the downstream flow had minimal influence, it was presumed that there was longshore-current generation in the sloping topography nearest the shoreside. The computed results were compared with the experimental results and we observed similar characteristics for wave profiles in the same wave period case in both models. In the future, further investigations can be conducted using the presented circular wave basin model to investigate the oblique wave deformation and longshore current generation in different sloping and wave conditions. Full article

This study reports the synthesis and characterization of Co_xNi_1−xFe₂O₄ (x = 0, 0.2, 0.4, 0.6, 0.8, 1) nanoparticles using a co-precipitation method. In this approach, metal ions are precipitated in the presence of a stabilizing agent, which is a common and effective method for nanoparticle preparation. The microstructure and magnetic properties were studied after calcination at 600 °C and heat treatment at 1000 °C. X-ray diffraction (XRD) and Fourier transform infrared (FTIR) spectroscopy confirmed the formation of a single-phase spinel structure. The average crystallite size, calculated using the (311) diffraction peak and the Scherrer equation, ranged from 13 to 19 nm. Scanning electron microscopy (SEM) showed that the nanoparticles had a spherical morphology. Thermogravimetric and differential thermal analysis (TG-DTA) revealed a three-step weight loss process. Magnetic measurements, including remanent magnetization, saturation magnetization, and coercivity, were performed using a vibrating sample magnetometer (VSM) at room temperature. The replacement of Ni²⁺ with Co²⁺ enhanced the magnetic properties, resulting in increased magnetic moment and anisotropy. These effects are attributed to changes in cation distribution, exchange interactions, surface effects, and magnetocrystalline anisotropy. Overall, Co²⁺ doping improved the magnetic behavior of nickel ferrite, indicating its potential for application in memory devices and magnetic recording media. Full article

Hydraulic excavators operate in harsh environments where direct measurement of actuator chamber pressures and boom displacement is often unreliable or infeasible. This study presents a novel control strategy that estimates actuator chamber pressures from work port pressures using differential equations, eliminating the need for direct pressure or position sensors. A fuzzy logic-based proportional–derivative (PD) controller is developed to mitigate boom oscillations, particularly under high-inertia load conditions and variable operator inputs. The controller dynamically adjusts gains through fuzzy logic-based gain scheduling, enhancing adaptability across a wide range of operating conditions. The proposed method addresses the limitations of classical PID controllers, which struggle with the nonlinearities, parameter uncertainties, and instability introduced by counterbalance valves and pressure-compensated proportional valves. Experimental data is used to design fuzzy rules and membership functions, ensuring robust performance. Simulation and full-scale experimental validation demonstrate that the fuzzy PD controller significantly reduces pressure overshoot (by 23% during extension and 32% during retraction) and decreases settling time (by 31.23% and 28%, respectively) compared to conventional systems. Frequency-domain stability analysis confirms exponential stability and improved damping characteristics. The proposed control scheme enhances system reliability and safety, making it ideal for excavators operating in remote or rugged terrains where conventional sensor-based systems may fail. This approach is generalizable and does not require modifications to the existing hydraulic circuit, offering a practical and scalable solution for modern hydraulic machinery. Full article

River barriers constitute a key factor that is degrading river connectivity and represent a critical research focus in riverine ecosystem conservation. Management authorities and river restoration agencies globally have increasingly employed barrier removal or modification for connectivity restoration projects in recent years, practices that are widely discussed and empirically supported in academia. However, existing research predominantly focuses on large dams in primary rivers, overlooking the more severe fragmentation caused by low-head barriers within low-order streams. This study targets the Yanjing River (total length: 70 km), a third-order tributary of the Yangtze River basin, implementing culvert modification and complete removal measures, respectively, for two river barriers distributed within its terminal 9 km reach. Using differential analysis, principal component analysis (PCA), cluster analysis, Mantel tests, and structural equation modeling (SEM), we systematically examined the mechanisms by which connectivity restoration projects influences aquatic habitat and fish diversity, the evolution of reach heterogeneity, and intrinsic relationships between aquatic environmental factors and diversity metrics. Results indicate that (1) the post-restoration aquatic habitat significantly improved with marked increases in fish diversity metrics, where hydrochemical factors and species diversity exhibited the highest sensitivity to connectivity changes; (2) following restoration, the initially barrier-fragmented river segments (upstream, middle, downstream) exhibited significantly decreased differences in aquatic habitat and fish diversity, demonstrating progressive homogenization across reaches; (3) hydrological factors exerted stronger positive effects on fish diversity than hydrochemical factors did, particularly enhancing species diversity, with a significant positive synergistic effect observed between species diversity and functional diversity. These studies demonstrate that “culvert modification and barrier removal” represent effective project measures for promoting connectivity restoration in low-order streams and eliciting positive ecological effects, though they may reduce the spatial heterogeneity of short-reach rivers in the short term. It is noteworthy that connectivity restoration projects should prioritize the appropriate improvement of hydrological factors such as flow velocity, water depth, and water surface width. Full article

In this paper, we develop an HIV/AIDS epidemic model that incorporates a saturated incidence rate to reflect the limited transmission capacity and the impact of behavioral saturation in contact patterns. The model is formulated as a system of seven non-linear ordinary differential equations representing key population compartments. In addition to model formulation, we introduce an optimal control problem involving three control measures: educational campaigns, screening of unaware infected individuals, and antiretroviral treatment for aware infected individuals. We begin by establishing the positivity and boundedness of the model solutions under constant control inputs. The existence and local and global stability of both the disease-free and endemic equilibrium points are analyzed, depending on the effective reproduction number (${\mathcal{R}}_e$). Bifurcation analysis reveals that the model undergoes a forward bifurcation at ${\mathcal{R}}_e=1$. A local sensitivity analysis of ${\mathcal{R}}_e$ identifies the disease transmission rate as the most sensitive parameter. The optimal control problem is then formulated by incorporating the dynamics of infected subpopulations, control costs, and time-dependent controls. The existence of optimal control solutions is proven, and the necessary conditions for optimality are derived using Pontryagin’s Maximum Principle. Numerical simulations support the theoretical analysis and confirm the stability of the equilibrium points. The optimal control strategies, evaluated using the Incremental Cost-Effectiveness Ratio (ICER), indicate that implementing both screening and treatment (Strategy D) is the most cost-effective intervention. These results provide important insights for designing effective and economically sustainable HIV/AIDS intervention policies. Full article

The increasing penetration of distributed energy resources (DERs) and power electronic loads challenges the modeling and control of modern distribution networks (DNs). The traditional models often fail to capture the complex aggregate dynamics required for advanced control strategies. This paper proposes a novel framework for DN power regulation based on Neural Ordinary Differential Equations (NODEs) and Model Predictive Control (MPC). NODEs are employed to develop a data-driven, continuous-time dynamic model capturing the aggregate relationship between the voltage at the point of common coupling (PCC) and the network’s power consumption, using only PCC measurements. Building upon this NODE model, an MPC strategy is designed to regulate the DN’s active power by manipulating the PCC voltage. To ensure computational tractability for real-time applications, a local linearization technique is applied to the NODE dynamics within the MPC, transforming the optimization problem into a standard Quadratic Programming (QP) problem that can be solved efficiently. The framework’s efficacy is comprehensively validated through simulations. The NODE model demonstrates high accuracy in predicting the dynamic behavior in a DN against a detailed simulator, with maximum relative errors below 0.35% for active power. The linearized NODE-MPC controller shows effective tracking performance, constraint handling, and computational efficiency, with typical QP solve times below 0.1 s within a 0.1 s control interval. The validation includes offline tests using the NODE model and online co-simulation studies using CloudPSS and Python via Redis. Application scenarios, including Conservation Voltage Reduction (CVR) and supply–demand balancing, further illustrate the practical potential of the proposed approach for enhancing the operation and efficiency of modern distribution networks. Full article

Nutritional risk factors are country-specific and change over time, requiring systematic verification. Objective: The study was designed to develop a nutritional risk factors model for seniors living in a Polish community. Methods: The pilot study was conducted in 2022 and 2023 among 301 people aged 60 and older in the Lower Silesia region of Poland. The questionnaire contained 107 test items describing dietary problems rated on a five-point Likert scale. The pre-study concerned understanding of the test items, rating the reproducibility (kappa statistic) and reliability of the scale (α-Cronbach coefficient). The factor structure of the model was developed using structural equation modelling (SEM) in the program R (version 4.3.2.). An exploratory factor analysis (EFA) extracted the three-factor model. Results: The factors were described as unhealthy eating (eight test items), irregularities related to meals (four test items), and perception of body weight (four test items). The model was verified using confirmatory factor analysis (CFA). The model’s acceptability was confirmed based on data matching indexes, convergent accuracy, differential accuracy, and measurement reliability. There was variation in the identified nutritional risk factors by gender, education, social activity, and family relationships. Conclusions: Focusing on irregularities in nutrition and perception of body weight as nutritional risk factors reveals a very narrow perspective in diagnosing nutritional risk, thus further testing of the model, in a representative group of older people in Poland and other countries, is necessary to confirm the results obtained. Full article

Phase stability at low radio frequencies is severely impacted by ionospheric propagation delays. Radio interferometers such as the giant metrewave radio telescope (GMRT) are capable of detecting changes in the ionosphere’s total electron content (TEC) over larger spatial scales and with greater sensitivity compared to conventional tools like the global navigation satellite system (GNSS). Thanks to its unique design, featuring both a dense central array and long outer arms, and its strategic location, the GMRT is particularly well-suited for studying the sensitive ionospheric region located between the northern peak of the equatorial ionization anomaly (EIA) and the magnetic equator. In this study, we observe the bright flux calibrator 3C48 for ten hours to characterize and study the low-latitude ionosphere with the upgraded GMRT (uGMRT). We outline the methods used for wideband data reduction and processing to accurately measure differential TEC ($\delta \mathrm{TEC}$) between antenna pairs, achieving a precision of< mTECU (1 mTECU = ${10}^{-3}$ TECU) for central square antennas and approximately mTECU for arm antennas. The measured $\delta \mathrm{TEC}$ values are used to estimate the TEC gradient across GMRT arm antennas. We measure the ionospheric phase structure function and find a power-law slope of $\beta =1.72\pm 0.07$, indicating deviations from pure Kolmogorov turbulence. The inferred diffractive scale, the spatial separation over which the phase variance reaches $1{\mathrm{rad}}^2$, is ∼6.66 km. The small diffractive scale implies high phase variability across the field of view and reduced temporal coherence, which poses challenges for calibration and imaging. Full article

This study develops a novel framework for supply chain financial resilience (SCFR) by integrating complex adaptive systems theory with supply chain finance and resilience concepts. To explore how disruption risks propagate through the supply chain, we propose an SEIJR epidemic model that categorizes node enterprises into five distinct states: susceptible (S), exposed (E), infected (I), quarantined (J), and recovered (R). Transitions between these states are captured using differential equations. Through numerical simulations linking this epidemiological approach to financial resilience metrics, we demonstrate several key findings: first, disruption risks temporarily reduce resilience; second, properly managed risk propagation through timely isolation and effective mitigation can transform disruptions into opportunities for systemic improvement; third, isolation measures need to work alongside recovery mechanisms to significantly improve the overall resilience of supply chain finance. Our results show that optimal isolation strategies enable the system to reach a risk-free equilibrium while simultaneously elevating the supply chain’s long-term financial resilience above initial levels. These findings offer theoretical and practical guidance for dynamic, adaptive risk management strategies in supply chain finance. Empirical validation and other research topics will be explored in subsequent studies. Full article

Microfluidic devices offer well-defined physical environments that are suitable for effective cell seeding and in vitro three-dimensional (3D) cell culture experiments. These platforms have been employed to model in vivo conditions for studying mechanical forces, cell–extracellular matrix (ECM) interactions, and to elucidate transport mechanisms in 3D tissue-like structures, such as tumor and lymph node organoids. Studies have shown that fluid flow behavior in microfluidic slides (µ-slides) directly influences shear stress, which has emerged as a key factor affecting cell proliferation and differentiation. This study investigates fluid flow in the porous channel of a µ-slide using computational fluid dynamics (CFD) techniques to analyze the impact of perfusion flow rate and porous properties on resulting shear stresses. The model of the µ-slide filled with a permeable biomaterial is considered. Porous media fluid flow in the channel is characterized by adding a momentum loss term to the standard Navier–Stokes equations, with a physiological range of permeability values. Numerical simulations are conducted to obtain data and contour plots of the filtration velocity and flow-induced shear stress distributions within the device channel. The filtration flow is subsequently measured by performing protein perfusions into the slide embedded with native human-derived ECM, while the flow rate is controlled using a syringe pump. The relationships between inlet flow rate and shear stress, as well as filtration flow and ECM permeability, are analyzed. The findings provide insights into the impact of shear stress, informing the optimization of perfusion conditions for studying tissues and cells under fluid flow. Full article

This paper introduces a functional framework for modeling cyclical and feedback-driven information flow using a generalized family of derangetropy operators. In contrast to scalar entropy measures such as Shannon entropy, these operators act directly on probability densities, providing a topographical representation of information across the support of the distribution. The proposed framework captures periodic and self-referential aspects of information evolution through functional transformations governed by nonlinear differential equations. When applied recursively, these operators induce a spectral diffusion process governed by the heat equation, with convergence toward a Gaussian characteristic function. This convergence result establishes an analytical foundation for describing the long-term dynamics of information under cyclic modulation. The framework thus offers new tools for analyzing the temporal evolution of information in systems characterized by periodic structure, stochastic feedback, and delayed interaction, with potential applications in artificial neural networks, communication theory, and non-equilibrium statistical mechanics. Full article