Search Results (49,829)

Biochar has garnered considerable attention as a soil amendment due to its unique physicochemical properties. Its application not only enhances soil carbon sequestration but also improves nutrient availability. Incorporating biochar into soil is regarded as a promising strategy for mitigating global climate change while delivering substantial environmental and agricultural benefits. In this study, biochar was extracted from Siraitia grosvenorii and subsequently modified through alkali treatment. A laboratory incubation experiment was conducted to assess the effects of unmodified (JMC) and modified (GXC) biochar, applied at different rates (1%, 2%, and 4%), on organic carbon mineralization and soil nutrient dynamics. Results indicated that, at equivalent application rates, JMC-treated soils exhibited lower CO₂ emissions than those treated with GXC, with emissions increasing alongside biochar dosage. After the incubation, the 1% JMC treatment exhibited a mineralization rate of 17.3 mg·kg⁻¹·d⁻¹, which was lower than that of the control (CK, 18.8 mg·kg⁻¹·d⁻¹), suggesting that JMC effectively inhibited organic carbon mineralization and reduced CO₂ emissions, thereby contributing positively to carbon sequestration in Siraitia grosvenorii farmland. In contrast, GXC application significantly enhanced soil nutrient levels, particularly increasing available phosphorus (AP) by 14.33% to 157.99%. Furthermore, partial least squares structural equation modeling (PLS-SEM) identified application rate and pH as the key direct factors influencing soil nutrient availability. Full article

The adoption of digital technologies, such as the Internet of Things (IoT), has emerged as a key strategy to improve efficiency, sustainability, and productivity in the agricultural sector, especially in contexts of modernization and digital transformation in developing regions. This study analyzes the key factors influencing the adoption of IoT technologies by farmers in the province of Guayas, Ecuador, and their impact on agricultural yields. The research is grounded in innovation diffusion theory and technology acceptance models, which emphasize the role of perception, usability, training, and economic viability in digital adoption. A total of 250 surveys were administered, with 232 valid responses (92.8% response rate), reflecting strong interest from the agricultural sector in digital transformation and precision agriculture. Using structural equation modeling (SEM), the results confirm that general perception of IoT (β = 0.514), practical functionality (β = 0.488), and technical training (β = 0.523) positively influence adoption, while high implementation costs negatively affect it (β = −0.651), all of which are statistically significant (p < 0.001). Furthermore, adoption has a strong positive effect on agricultural yield (β = 0.795). The model explained a high percentage of variance in both adoption (R² = 0.771) and performance (R² = 0.706), supporting its predictive capacity. These findings underscore the need for public and private institutions to implement targeted training and financing strategies to overcome economic barriers and foster the sustainable integration of IoT technologies in Ecuadorian agriculture. Full article

This paper develops empirical relationships to estimate FAA/EASA and MIL-3013B rules-compliant take-off field performance for single and multi-engine aircraft. Recent experience with modern aircraft flight manuals revealed that popular empirical legacy methods are no longer accurate; improvements in tires and brakes lead to significantly shorter certified distances. This work relies upon a survey of current operational aircraft and extensive numerical simulations of generic configurations to support the development of a collection of new equations to estimate take-off performance for single and multi-engine aircraft under dry and wet conditions. These relationships are individually tailored for civilian and U.S. Military rules; they account for the superior capability of modern braking systems and the implications of minimum-control speed on the certified distance. Full article

Background/Objectives: In recent years, the discharge of antibiotics into rivers and irrigation canals has increased. However, few studies have addressed the impact of these compounds on agricultural fields that use such water to meet crop demands. Methods: In this study, the transport of two types of gentamicin (pure gentamicin and gentamicin sulfate) was modeled at concentrations of 150 and 300 μL/L, respectively, in a soil with more than 60 years of agricultural use. Infiltration tests under constant head conditions and gentamicin transport experiments were conducted in acrylic columns measuring 14 cm in length and 12.7 cm in diameter. The scaling parameters for the Richards equation were obtained from experimental data, while those for the advection–dispersion equation were estimated using inverse methods through a nonlinear optimization algorithm. In addition, a fractal-based model for saturated hydraulic conductivity was employed. Results: It was found that the dispersivity of gentamicin sulfate is 3.1 times higher than that of pure gentamicin. Based on the estimated parameters, two simulation scenarios were conducted: continuous application of gentamicin and soil flushing after antibiotic discharge. The results show that the transport velocity of gentamicin sulfate in the soil may have short-term consequences for the emergence of resistant microorganisms due to the destination of wastewater containing antibiotic residues. Conclusions: Finally, further research is needed to evaluate the impact of antibiotics on soil physical properties, as well as their effects on irrigated crops, animals that consume such water, and the soil microbiota. Full article

As a core device in low-voltage distribution networks, the distribution zone transformer (DZT) is influenced by short circuits, overloads, and unbalanced loads, which cause thermal aging, mechanical stress, and eventually deformation of the winding, resulting in parameter deviations from nameplate values and impairing system operation. However, existing identification methods typically require synchronized high- and low-voltage data and are limited to symmetric three-phase conditions, which limits their application in practical distribution systems. To address these challenges, this paper proposes a parameter identification method for DZTs under three-phase unbalanced conditions. Firstly, based on the transformer’s T-equivalent circuit considering the load, the power flow equations are derived without involving the synchronization issue of high-voltage and low-voltage side data, and the sum of the impedances on both sides is treated as an independent parameter. Then, a novel power flow equation under three-phase unbalanced conditions is established, and an adaptive recursive least squares (ARLS) solution method is constructed using the measurement data sequence provided by the smart meter of the intelligent transformer terminal unit (TTU) to achieve online identification of the transformer winding parameters. The effectiveness and robustness of the method are verified through practical case studies. Full article

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

The shallow water equations (SWEs) model fluid flow in rivers, coasts, and tsunamis. Their nonlinearity challenges analytical solutions. We present a numerical algorithm combining the finite integration method with Chebyshev polynomial expansion (FIM-CPE) to solve one- and two-dimensional SWEs. The method transforms partial differential equations into integral equations, approximates spatial terms via Chebyshev polynomials, and uses forward differences for time discretization. Validated on stationary lakes, dam breaks, and Gaussian pulses, the scheme achieved errors below ${10}^{-12}$ for water height and velocity, while conserving mass with volume deviations under ${10}^{-5}$. Comparisons showed superior shock-capturing versus finite difference methods. For two-dimensional cases, it accurately resolved wave interactions over complex topographies. Though limited to wet beds and small-scale two-dimensional problems, the method provides a robust simulation tool. Full article

To improve the sampling efficiency of Markov Chain Monte Carlo in complex parameter spaces, this paper proposes an adaptive sampling method that integrates a swarm intelligence mechanism called the BeeSwarm-MH algorithm. The method combines global exploration by scout bees with local exploitation by worker bees. It employs multi-stage perturbation intensities and adaptive step-size tuning to enable efficient posterior sampling. Focusing on Bayesian inference for parameter estimation in the soliton solutions of the two-dimensional complex Ginzburg–Landau equation, we design a dedicated inference framework to systematically compare the performance of BeeSwarm-MH with the classical Metropolis–Hastings algorithm. Experimental results demonstrate that BeeSwarm-MH achieves comparable estimation accuracy while significantly reducing the required number of iterations and total computation time for convergence. Moreover, it exhibits superior global search capabilities and adaptive features, offering a practical approach for efficient Bayesian inference in complex physical models. Full article

The importance of non-performing loans (NPLs) for the stability of financial sectors is difficult to overestimate. The NPL level depends on numerous factors; this study’s goal is to determine the impact of macroeconomic factors on NPLs with the mediation effect of foreign, saving and social factors in Kazakhstan’s banking sector. To determine the affecting factors, the authors performed a systematic literature review. To determine the dependencies between constructs, the Partial Least Squares Structural Equation Modeling (PLS-SEM) method was used. Macroeconomic factors’ direct effect on non-performing loans (NPLs) was examined; a significant negative dependence was determined. The mediation effect of foreign, saving, and social factors was investigated. Foreign factors have a mediation effect, strengthening the dependence between macro factors and NPLs. Nevertheless, they do not have a mediating effect; moreover, they balance and make the effect of macro factors on NPLs statistically insignificant. These findings allow policy-makers to stabilize the situation on NPLs in the financial markets of developing countries like Kazakhstan by directly influencing not only the financial sector but also other sectors of the national economy. Full article

The aim of this work is to study a class of nabla fractional difference equations with anti-periodic conditions. First, we construct the related Green’s function. After deducing some of its useful properties, we obtain an upper bound for its sum. Then, using this bound, we are able to obtain three existence results based on the Banach contraction principle, Brouwer’s fixed point theorem, and Leray–Schauder’s nonlinear alternative, respectively. Then, we show some non-existence results for the studied problem, and existence results are also provided for a system of two equations of the considered type. Finally, we outline some particular examples in order to demonstrate the theoretical findings. Full article

Under conservation tillage in the Huang-Huai-Hai wheat–maize rotation area, the ridge-clearing no-till seeder for strip tillage mitigates the adverse impacts of surface residues on seeding quality by clearing stubble specifically within the seed rows, demonstrating significant potential for application and promotion. However, the inadequate understanding of the seeder’s operational performance and governing mechanisms under varying field conditions hinders its high-quality and efficient implementation. To address this issue, this study selected the stubble height, forward speed, and stubble knife rotational speed (PTO speed) as experimental factors. Employing a three-factor quasi-level orthogonal experimental design, coupled with response surface regression analysis, this research systematically elucidated the interaction mechanisms among these factors concerning the seeding depth consistency and seed spacing uniformity of the seeder. An optimized parameter-matching model was subsequently derived through equation system solving. Field trials demonstrated that a lower forward speed improved the seed spacing uniformity and seeding depth consistency, whereas high speeds increased the missing rates and spacing deviations. An appropriate stubble height enhanced the seed spacing accuracy, but an excessive height compromised depth precision. Higher PTO speeds reduced multiple indices but impaired depth accuracy. Response surface analysis based on the regression models demonstrated that the peak value of the seed spacing qualification index occurred within the forward speed range of 8–9 km/h and the stubble height range of 280–330 mm, with the stubble height being the dominant factor. Similarly, the peak value of the seeding depth qualification index occurred within the stubble height range of 300–350 mm and the forward speed range of 7.5–9 km/h, with the forward speed as the primary factor. Validation confirmed that combining stubble heights of 300−330 mm, forward speeds of 8−9 km/h, and PTO speeds of 540 r/min optimized both metrics. This research reveals nonlinear coupling relationships between operational parameters and seeding quality metrics, establishes a stubble–speed dynamic matching model, and provides a theoretical foundation for the intelligent control of seeders in conservation tillage systems. 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

Consider a class of coupled discrete-time Riccati equations arising from jump systems. To compute their solutions when systems reach a steady state, we propose an operator Newton method and correspondingly establish its quadratic convergence under suitable assumptions. The advantage of the proposed method lies in the fact that its subproblems are solved using the operator Smith method, which allows it to maintain quadratic convergence in both the inner and outer iterations. Moreover, it does not require the constant term matrix of the equation to be invertible, making it more broadly applicable than existing inverse-free iterative methods. For large-scale problems, we develop a low-rank variant by incorporating truncation and compression techniques into the operator Newton framework. A complexity analysis is also provided to assess its scalability. Numerical experiments demonstrate that the presented low-rank operator Newton method is highly effective in approximating solutions to large-scale structured coupled Riccati equations. Full article

This paper explores the intervening role in SEP performance of corporate environmental, cultural, and ethnic activities (ECEAs) and diversity, equity, inclusion, and social initiatives (DEISIs) on blockchain adoption (BCA) strategy, particularly useful in the Western Balkans (WB), which demands transparency due to extended fraud and ethnic complexities. In this domain, a question has been raised: In BCA strategies, is there any correlation between SEP performance and ECEAs and DEISIs in a mediating role? A serial mediation model was tested on a dataset of 630 WB and EU companies, and the research conceptual model was validated by CFA (Confirmation Factor Analysis), and the SEM (Structural Equation Model) fit was assessed. We found a statistically sound (significant, positive) correlation between BCA and ESG success performance, especially in the innovation and integrity ESG performance success indicators, when DEISIs mediate. The findings confirmed the influence of technology, and environmental, cultural, ethnic, and social factors on BCA strategy. The findings revealed some important issues of BCA that are of worth to WB companies’ managers to address BCA for better performance. This study adds to the literature on corporate blockchain transformation, especially for organizations seeking investment opportunities in new international markets to diversify their assets and skill pool. Furthermore, it contributes to a deeper understanding of how DEI initiatives impact the correlation between business transformation and socioeconomic performance, which is referred to as the “social impact”. Full article

This study applies Computational Fluid Dynamics (CFD) and mathematical modeling to examine uterine and umbilical arterial blood flow during pregnancy, providing a more detailed understanding of hemodynamic changes across gestation. Statistical analysis of Doppler ultrasound data from a large cohort of more than 200 pregnant women (in the second and third trimesters) reveals significant increases in the umbilical arterial peak systolic velocity ($PSV$) between the 22nd and 30th weeks, while uterine artery velocities remain relatively stable, suggesting adaptations in vascular resistance during pregnancy. By combining the Navier–Stokes equations with Doppler ultrasound-derived inlet velocity profiles, we quantify several key fluid dynamics parameters, including time-averaged wall shear stress ($TAWSS$), oscillatory shear index ($OSI$), relative residence time ($RRT$), Reynolds number ($Re$), and Dean number ($De$), evaluating laminar flow stability in the uterine artery and secondary flow patterns in the umbilical artery. Since blood exhibits shear-dependent viscosity and complex rheological behavior, modeling it as a non-Newtonian fluid is essential to accurately capture pulsatile flow dynamics and wall shear stresses in these vessels. Unlike conventional imaging techniques, CFD offers enhanced visualization of blood flow characteristics such as streamlines, velocity distributions, and instantaneous particle motion, providing insights that are not easily captured by Doppler ultrasound alone. Specifically, CFD reveals secondary flow patterns in the umbilical artery, which interact with the primary flow, a phenomenon that is challenging to observe with ultrasound. These findings refine existing hemodynamic models, provide population-specific reference values for clinical assessments, and improve our understanding of the relationship between umbilical arterial flow dynamics and fetal growth restriction, with important implications for maternal and fetal health monitoring. Full article