Search Results (281)

In the present work, the third-order nonlinear optical (NLO) response of some recently synthesized, functionally substituted Boron–Dipyrromethene (BODIPY) derivatives is studied, and their nonlinear optical properties are investigated using the Z-scan technique, employing 4 ns, visible (532 nm) and near-infrared (1064 nm) laser excitation. The present findings demonstrate the importance of functionalization of the BODIPY core and the versatility it offers for the modification of the photophysical properties of these chromophores, allowing for the very efficient tuning of both the magnitude and the sign of the nonlinear absorption and refraction of the BODIPYs, making them very promising materials for several optoelectronic applications. The obtained results are discussed and compared with the results of other similar BODIPYs reported in the literature. Full article

Biomechanical modeling of the cornea is crucial for understanding the progression of some ocular diseases and optimizing surgical treatments. However, hyperelastic non-linear material models, such as those used for corneal tissue, often yield highly variable parameter sets in the scientific literature, influenced by factors like the chosen optimization intervals and differences between tensile and inflation test curve optimization, both of which are addressed in this study. This variability complicates the understanding of corneal mechanical properties. In this research, the aim is to optimize and calibrate the key parameters of the corneal material model, particularly focusing on $c_1$, $c_2$, $k_1$ and $k_2$, using the Holzapfel–Gasser–Ogden (HGO) hyperelastic model, and a novel methodology is proposed that separately estimates the isotropic and anisotropic components in a stepwise manner, addressing the issue of multiple parameter sets fitting experimental curves similarly. This approach helps to standardize corneal material models and improve the reliability of parameter estimations. Moreover, accurate biomechanical characterization within this framework contributes not only to clinical applications but also to biomimetics, inspiring the design of artificial corneal substitutes and bioengineered materials. Full article

When the outer sheath of submarine cables is damaged, the degradation of cross-linked polyethylene (XLPE) insulation by anions in seawater becomes a critical factor affecting cable service life. This study investigates 500 kV three-core XLPE insulation and systematically reveals the differential and synergistic degradation mechanisms of major seawater anions (Cl⁻, SO₄²⁻, HCO₃⁻). Accelerated aging tests at 90 °C were conducted using solution systems simulating both single-ion and composite environments, combined with electrical performance evaluation, Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). Results show that seawater causes significantly greater deterioration of resistivity, breakdown strength, and molecular structure than any single-ion solution. Mechanistic analysis demonstrates that Cl⁻ induces nucleophilic substitution, SO₄²⁻ promotes oxidative chain scission, and HCO₃⁻ facilitates hydrolysis via pH regulation, while their coexistence produces nonlinear synergistic effects through oxidative reactions, electrochemical coupling, and ion transport. This work provides the first systematic comparison of individual and combined anion effects on XLPE, offering new mechanistic insights and quantitative evidence for understanding multi-ion degradation, with implications for insulation material design, protective strategies, and service life prediction of submarine cables. Full article

One of the essential parts of contemporary cryptographic systems is s-boxes (Substitution Boxes), which give encryption algorithms more complexity and resilience due to their nonlinear structure. In this study, we propose CSBA (Cuckoo Search–Bees Algorithm), a hybrid evolutionary method that combines the strengths of Cuckoo Search and Bees algorithms, to generate s-box structures with strong cryptographic properties. The initial population is generated with a high-diversity four-dimensional Memristive Lu chaotic map, taking advantage of the random yet deterministic nature of chaotic systems. This proposed method was designed with inspiration from biological systems. It was developed based on the foraging strategies of bees and the reproductive strategies of cuckoos. This nature-inspired structure enables an efficient scanning of the solution space. The resultant s-boxes’ fitness was assessed using the nonlinearity value. These s-boxes were then optimized using the hybrid CSBA algorithm suggested in this paper as well as the Bees algorithm. The performance of the proposed approaches was measured using SAC, nonlinearity, BIC-SAC, BIC-NL, maximum difference distribution, and linear uniformity (LU) metrics. Compared to other studies in the literature that used metaheuristic algorithms to generate s-boxes, the proposed approach demonstrates good performance. In particular, the average value of 109.75 obtained for the nonlinearity metric demonstrates high success. Therefore, this study demonstrates that robust and reliable s-boxes can be generated for symmetric encryption algorithms using the developed metaheuristic algorithms. Full article

Technological advancements are a key engine for improving productivity and are fundamental to enhancing the resilience of the agricultural economy by influencing production methods and driving structural transformation. The objective of this study is to analyze the impact of technological progress on agricultural economic resilience in China, with particular attention to (i) its direct effects on resistance, recovery, and reconstruction; (ii) its indirect effects through the upgrading of the agricultural industrial structure; and (iii) its potential nonlinear effects under different structural thresholds. To achieve this, a multidimensional evaluation framework has been developed to assess agricultural economic resilience through three distinct dimensions: resistance, recovery, and reconstruction. Using fixed effects, mediation, threshold and spatial Durbin models, we empirically analyze the impact pathways. The results suggest that technological progress significantly increases agricultural resilience, with robustness confirmed by various tests including model substitution and variable replacement. Furthermore, regional heterogeneity is evident, with the central region showing the strongest positive effect. The mediation analysis shows that modernization of industrial structure serves as an important transmission channel, while the threshold regression identifies nonlinear effects, with significant improvements occurring beyond certain structural thresholds. The results underline the importance of promoting technological innovation in agriculture, developing region-specific support measures and accelerating structural optimization to strengthen the resilience of agriculture. Full article

In order to enhance the performance of 112 Gb/s polarization-multiplexed quadrature phase-shift keying (PM-QPSK) coherent optical receivers, a novel digital signal processing (DSP) framework is presented in this study. The suggested method combines cutting-edge signal processing techniques to address important constraints in long-distance, high data rate coherent systems. The framework uses overlap frequency domain equalization (OFDE) for chromatic dispersion (CD) compensation, which offers a cheaper computational cost and higher dispersion control precision than traditional time-domain equalization. An adaptive carrier phase recovery (CPR) technique based on mean-squared differential phase (MSDP) estimation is incorporated to manage phase noise induced by cross-phase modulation (XPM), providing dependable correction under a variety of operating situations. When combined, these techniques significantly increase Q factor performance, and optimum systems can handle transmission distances of up to 2400 km. The suggested DSP approach improves phase stability and dispersion tolerance even in the presence of nonlinear impairments, making it a viable and effective choice for contemporary coherent optical networks. The framework’s competitiveness was evaluated by comparing it against the most recent, cutting-edge DSP methods that were released after 2021. These included CPR systems that were based on kernels, transformers, and machine learning. The findings show that although AI-driven approaches had the highest absolute Q factors, they also required a large amount of computing power. On the other hand, the suggested OFDE in conjunction with adaptive CPR achieved Q factors of up to 11.7 dB over extended distances with a significantly reduced DSP effort, striking a good balance between performance and complexity. Its appropriateness for scalable, long-haul 112 Gb/s PM-QPSK systems is confirmed by a complexity versus performance trade-off analysis, providing a workable and efficient substitute for more resource-intensive alternatives. Full article

Classification prediction technology, which utilizes labeled data for training to enable autonomous decision, has emerged as a pivotal tool across numerous fields. The Elman neural network (ENN) exhibits potential in tackling nonlinear problems. However, its computational process faces inherent limitations in escaping local optimum and experiencing a slow convergence rate. To improve these shortcomings, an ENN classifier based on Hyperactivity Rat Swarm Optimizer (HRSO), named HRSO-ENNC, is proposed in this paper. Initially, HRSO is divided into two phases, search and mutation, by means of a nonlinear adaptive parameter. Subsequently, five search actions are introduced to enhance the global exploratory and local exploitative capabilities of HRSO. Furthermore, a stochastic roaming strategy is employed, which significantly improves the ability to jump out of local positions. Ultimately, the integration of HRSO and ENN enables the substitution of the original gradient descent method, thereby optimizing the neural connection weights and thresholds. The experiment results demonstrate that the accuracy and stability of HRSO-ENNC have been effectively verified through comparisons with other algorithm classifiers on benchmark functions, classification datasets and an AlSi10Mg process classification problem. Full article

With the increasing switching frequencies and power densities in modern power converters, the prediction and mitigation of common-mode (CM) noise are becoming increasingly essential. Even though powerful, simulation methods are hindered by the difficulties in modeling power semiconductors and the long simulation time. As an alternative, the measurement-based substitution model is demonstrated in the paper, which simplifies the non-linear converter with a linear circuit network with multiple independent sources. Transfer functions are then defined and characterized to evaluate the conversion ratio from different sources to the CM noise produced on the attached cables. Good agreements are observed between the predicted and measured CM noise under several test conditions. Additionally, the proposed method facilitates dominant noise source identification and the corresponding noise suppression. The proposed method offers advantages over the existing approach, including simplicity in the characterization of transfer functions and the least disturbance to the test setup. Full article

With the continuous depletion of natural river sand resources and the escalating ecological degradation caused by excessive sand mining, manufactured sand has emerged as a sustainable and environmentally favorable alternative aggregate, playing an increasingly important role in the advancement of green construction materials. Nevertheless, the shrinkage behavior of manufactured sand concrete (MSC) exhibits significant deviations from that of conventional natural sand concrete due to differences in the material characteristics. Existing shrinkage prediction models—such as ACI 209, CEB-FIP 2010, B3, and GL 2000—fail to adequately incorporate the specific properties and substitution effects of manufactured sand, thereby limiting their predictive accuracy and applicability. To bridge this gap, the present study conducted a systematic evaluation of the four aforementioned classical shrinkage prediction models based on experimental data from MSC specimens incorporating varying replacement rates of manufactured sand. The findings revealed that models such as B3 and CEB-FIP 2010 neglected the influence of critical characteristics of manufactured sand—namely, particle morphology, gradation, and stone powder content—on the cementitious matrix and interfacial transition zone, which led to substantial prediction discrepancies. Accordingly, a nonlinear regression-based correction function was developed, introducing the manufactured sand content as a key influencing variable to recalibrate and enhance the ACI 209 and GL 2000 models for a more accurate application to MSC. The modified models exhibited markedly improved fitting performance and predictive robustness across the full range of manufactured sand replacement ratios (0–100%), thereby offering a more reliable framework for modeling the shrinkage development of MSC. Full article

To evaluate the feasibility of substituting mechanical testing with finite element simulation for basalt-fiber-grid-reinforced concrete, this study fabricated two-way slab specimens with varying basalt fiber grid layers. Flexural tests revealed load–deflection response characteristics of both fiber-reinforced and plain concrete. An ANSYS-based refined finite element model successfully replicated bending deformation patterns and grid failure modes under identical conditions, with experimental-simulation comparisons validating model accuracy (error < 8%). Through parametric secondary development, the model was extended to analyze 9 single-layer and 72 double-layer grid configurations. A high-precision response surface model (R² ≥ 0.99) was established via nonlinear regression, enabling rapid performance prediction for arbitrary grid arrangements. This computational framework provides a reliable simulation tool for digital design of fiber-reinforced concrete components. Full article

Optimizing agricultural structure serves as a crucial pathway to promote sustainable rural economic development. This study focuses on a representative village in the mountainous region of North China, where agricultural production is constrained by perennial low-temperature conditions, resulting in widespread adoption of single-cropping systems. There exists an urgent need to enhance both economic returns and risk resilience of limited arable land through refined cultivation planning. However, traditional planting strategies face difficulties in synergistically optimizing long-term benefits from multi-crop combinations, while remaining vulnerable to climate fluctuations, market volatility, and complex inter-crop relationships. These limitations lead to constrained land productivity and inadequate economic resilience. To address these challenges, we propose an integrated decision-making approach combining stochastic programming, robust optimization, and data-driven modeling. The methodology unfolds in three phases: First, we construct a stochastic programming model targeting seven-year total profit maximization, which quantitatively analyzes relationships between decision variables (crop planting areas) and stochastic variables (climate/market factors), with optimal planting solutions derived through robust optimization algorithms. Second, to address natural uncertainties, we develop an integer programming model for ideal scenarios, obtaining deterministic optimization solutions via genetic algorithms. Furthermore, this study conducts correlation analyses between expected sales volumes and cost/unit price for three crop categories (staples, vegetables, and edible fungi), establishing both linear and nonlinear regression models to quantify how crop complementarity–substitution effects influence profitability. Experimental results demonstrate that the optimized strategy significantly improves land-use efficiency, achieving a 16.93% increase in projected total revenue. Moreover, the multi-scenario collaborative optimization enhances production system resilience, effectively mitigating market and environmental risks. Our proposal provides a replicable decision-making framework for sustainable intensification of agriculture in cold-region rural areas. Full article

With the growing demand for secure image communication, effective encryption solutions are critical for safeguarding visual data from unauthorized access. The substitution box (S-box) in AES (Advanced Encryption Standard) is critical for ensuring nonlinearity and security. However, the static S-box used in AES is vulnerable to algebraic attacks, side-channel attacks, and so on. This study offers a novel Lorenz key and Chua key-based Reversible Substitution Box (LCK-SB) for image encryption, which takes advantage of the chaotic behavior of the Lorenz and Chua key systems to improve security due to nonlinear jumps and mixed chaotic behavior while maintaining optimal quantum cost, area, and power. The suggested method uses a hybrid Lorenz and Chua key generator to create a highly nonlinear and reversible S-box, which ensures strong confusion and diffusion features. The performance of the LCK-SB approach is examined on field-programmable gate array (FPGA) and application-specific integrated circuit (ASIC) platforms, and the findings show that quantum cost, delay, and power are decreased by 97%, 74.6%, and 35%, respectively. Furthermore, the formal security analysis shows that the suggested technique efficiently resists threats. The theoretical analysis and experimental assessment show that the suggested system is more secure for picture encryption, making it suitable for real-time and high-security applications. Full article

This paper selects 50 listed commercial banks in China from 2012 to 2023 as research samples, and employs the fixed effects model and Hansen’s threshold regression method to systematically examine the impact mechanism and non-linear characteristics of FinTech development on the profitability of commercial banks. The key findings are summarized as follows: (1) FinTech significantly undermines the overall profitability of commercial banks by reshaping the competitive landscape of the industry and intensifying the technology substitution effect. This is primarily reflected in the reduction in traditional interest income and the erosion of market share in intermediary business. (2) Heterogeneity analysis indicates that large state-owned banks and joint-stock banks experience more pronounced negative impacts compared to small and medium-sized banks. (3) Additional research findings reveal a significant single-threshold effect between FinTech and bank profitability, with a critical value of 4.169. When the development level of FinTech surpasses this threshold, its inhibitory effect diminishes substantially, suggesting that after achieving a certain degree of technological integration, commercial banks may partially alleviate external competitive pressures through synergistic effects. This study offers crucial empirical evidence and theoretical support for commercial banks to develop differentiated technology strategies and for regulatory authorities to design dynamically adaptable policy frameworks. Full article

Functionally graded materials (FGMs) have the potential to revolutionize the oil and gas transportation sector, due to their increased strengths and efficiencies as pipelines. Conventional pipelines frequently face serious problems such as extreme weather, pressure changes, corrosion, and stress-induced pipe bursts. By analyzing the mechanical and thermal performance of FGM-based pipes under various operating conditions, this study investigates the possibility of using them as a more reliable substitute. In the current study, the post-buckling and nonlinear vibration behaviors of pipes composed of FGMs transporting heavy crude oil were examined using a Timoshenko beam framework. The material properties of the FGM pipe were observed to change gradually across the thickness, following a power-law distribution, and were influenced by temperature variations. In this regard, two types of FGM pipes are considered: one with a metal-rich inner surface and ceramic-rich outer surface, and the other with a reverse configuration featuring metal on the outside and ceramic on the inside. The nonlinear governing equations (NGEs) describing the system’s nonlinear dynamic response were formulated by considering nonlinear strain terms through the von Kármán assumptions and employing Hamilton’s principle. These equations were then discretized using Galerkin’s method to facilitate the analytical investigation. The Runge–Kutta method was employed to address the nonlinear vibration problem. It is concluded that, compared with pipelines made from conventional materials, those constructed with FGMs exhibit enhanced thermal resistance and improved mechanical strength. Full article

In this study, we outline a modified harmonic balance method for solving non-homogenous integrable dispersionless equations and obtaining the corresponding periodic solutions, a research field which shows limited investigation. This study is the first to solve this nonlinear problem, based on a recently developed harmonic balance method combined with Vieta’s substitution technique. A set of analytical formulas are generated from the modified harmonic balance method and used to compute the approximate periodic solutions of the dispersionless equations. The main advantage of this method is that the computation effort required in the solution procedure can be smaller. The results of the modified harmonic balance method show reasonable agreement with those obtained using the classic harmonic balance method. Our proposed solution method can decouple the nonlinear algebraic equations generated in the harmonic balance process. We also investigated the effects of various parameters on nonlinear periodic responses and harmonic convergence. Full article