Search Results (11,095)

Circuit implementation is a widely accepted method for validating theoretical insights observed in chaotic systems. It also serves as a basis for numerous chaos-based engineering applications, including data encryption, random number generation, secure communication, neuromorphic computing, and so forth. To get feasible, compact, and cost-effective circuit implementations of chaotic systems, the underlying mathematical model may be simplified while preserving all rich nonlinear behaviors. In this framework, this manuscript presents a simplified Hopfield Neural Network (HNN) capable of generating a broad spectrum of complex behaviors using a minimal number of electronic elements. Based on Shil’nikov’s theorem for heteroclinic orbits, the number of non-zero synaptic connections in the matrix weights is reduced, while simultaneously using only one nonlinear activation function. As a result of these simplifications, we obtain the most compact electronic implementation of a tri-neuron HNN with the lowest component count but retaining complex dynamics. Comprehensive theoretical and numerical analyses by equilibrium points, density-colored continuation diagrams, basin of attraction, and Lyapunov exponents, confirm the presence of periodic oscillations, spiking, bursting, and chaos. Such chaotic dynamics range from single-scroll chaotic attractors to double-scroll chaotic attractors, as well as coexisting attractors to transient chaos. A brief security application of an S-Box utilizing the presented HNN is also given. Finally, a physical implementation of the HNN is given to confirm the proposed approach. Experimental observations are in good agreement with numerical results, demonstrating the usefulness of the proposed approach. Full article

Discrete cosine transforms (DCTs) are widely used in intelligent electronic systems for storing, processing, and transmitting data. Their popularity stems, on the one hand, from their unique properties and, on the other hand, from the availability of fast algorithms that minimize the computational and hardware complexity of their implementation. Until recently, the Type VIII DCT had been one of the least studied variants, with virtually no publications addressing fast algorithms for its implementation. However, this situation has changed, making the development of efficient implementation methods for this transform a timely and important research problem. In this paper, several algorithmic solutions for implementing the Type VIII DCT are proposed. A set of Type VIII DCT algorithms for small lengths N = 3, 4, 5, 6, 7 is presented. The effectiveness of the proposed solutions is due to the possibility of successful factorization of small-sized DCT-VIII matrices, leading to a reduction in the computational complexity of implementing transforms of this type. Compared with direct matrix–vector computation, the proposed algorithms achieve an approximate 53% reduction in the number of multiplications, at the cost of an increase of about 21% in the number of additions. This work continues a series of previously published studies aimed at creating a library of small-sized algorithms for discrete trigonometric transforms. Full article

Amniotic membrane (AM) has gained wide application in regenerative medicine due to its biocompatibility and extracellular matrix (ECM) composition. Effective decellularization is essential to minimize immunogenicity while preserving tissue architecture. This study standardized AM procurement and compared a simplified alkaline-based decellularization protocol with a conventional detergent–alkaline method, emphasizing practicality, histological integrity, and collagen preservation. Methods: Human AM was aseptically obtained from placental tissue and processed using either method. Histological analysis with hematoxylin eosin and Masson’s trichrome staining quantified nuclear content and collagen integrity. Results: The alkaline method achieved the greatest nuclear clearance but retained epithelial outlines, indicating partial persistence of cellular structures. In contrast, the detergent method achieved complete morphological decellularization but showed slightly higher residual nuclear signal. Masson’s trichrome staining revealed that the detergent-based method preserved collagen intensity most closely to native tissue (mean gray values: 128.3 ± 28.2 vs. 140.2 ± 23.4), while the alkaline group exhibited significantly reduced staining (177.8 ± 17.2; p < 0.001). Conclusions: the simplified alkaline method provided efficient decellularization with reduced cost, time, and cytotoxic risk, making it a practical approach for AM processing. However, partial ECM alteration suggests that detergent-based methods remain preferable when optimal structural preservation is required. Full article

Empty fruit bunches (EFBs) and kenaf are two abundant sources of lignocellulosic resource agricultural waste with potential as substrates for mycelium-based composites (MBCs). These composites are lightweight, compostable, low-cost, and suitable for packaging applications. However, their performance is highly dependent on the type of lignocellulosic substrate and the processing conditions applied during production. Despite the promising availability of natural fibers, limited research has focused on the drying process that affects the quality of MBCs. This study investigates the effect of different drying times (12, 18, and 24 h) on the physical and mechanical properties of MBCS produced from EFB and kenaf substrates. Following a 20-day incubation period under controlled conditions, the composites were oven-dried and analyzed for mycelial colonization, density measurement, shrinkage, water loss, shore A hardness, impact resistance, and mold growth. The results demonstrated that a drying time of 24 h yielded the best overall performance. Moisture loss (67.00%) and shrinkage (50.70%) increased with longer drying times (24 h), particularly in kenaf-based composites. Extended drying minimized mold contamination and enhanced the structural integrity of the composites. Overall, EFB-based composites achieved the highest Shore A hardness (44.53 HA). These findings show that optimizing the drying time enhances the durability of MBCs, reinforcing their potential as sustainable, biodegradable alternatives to polystyrene and promoting the development of eco-friendly materials. Full article

Active suspension systems can significantly enhance vehicle ride comfort and attitude stability, but often at the cost of increased energy consumption. To achieve both high dynamic performance and reduced energy usage, this study proposes an eigenstructure-oriented optimization method for active suspensions. Controller design is reformulated as a synergistic process of modal regulation and dynamic response optimization, in which partial eigenstructure assignment redistributes the dominant modes and system responses are computed using fourth-order Runge–Kutta integration. An energy-minimization optimization problem with performance constraints is then solved via the sequential quadratic programming (SQP) algorithm. Simulation results show that the proposed method markedly improves vibration performance: peak body acceleration is reduced from 3.48 m/s² to 1.70 m/s² (a 51.1% reduction), and the root mean square (RMS) acceleration decreases from 0.74 to 0.40 (a 45.6% reduction), while body displacement is also significantly suppressed. Compared with passive suspension and proportional–integral–derivative (PID) active suspension, the proposed system achieves superior performance in key indices such as body acceleration and displacement, leading to noticeably improved ride comfort and attitude stability. Furthermore, robustness analysis indicates that the method remains effective under variations in the receptance matrix, with only minor influence on system performance, demonstrating the practical applicability of the proposed control strategy. Full article

Multi-robot rescue path planning (MRRPP) is critical for ensuring the rapid and effective completion of post-disaster rescue tasks. Most studies focus on minimizing the length of rescue paths, the number of robots, and rescue time, neglecting the task utility, which reflects the effect of timely emergency supplies delivery, which is also important for post-disaster rescue. In this study, we integrated multiple optimization indicators into the rescue cost and modeled the problem as a variant of the vehicle routing problem (VRP) with timeliness and battery constraints. A population-based iterative greedy algorithm with Q-learning (QPIG) is proposed to solve it. First, two problem-specific heuristic schemes are designed to generate a high-quality and diverse population. Second, a competition-oriented destruction-reconstruction mechanism is applied to improve the global search ability of the algorithm. In addition, a Q-learning-based local search strategy is developed to enhance the algorithm’s exploitation ability. Moreover, a historical information-based constructive strategy is investigated to accelerate the convergence speed of the algorithm. Finally, the proposed QPIG is validated by comparing it with five efficient algorithms on 56 instances. Experiment results show that the proposed QPIG significantly outperforms compared algorithms in terms of rescue cost and convergence speed. Full article

To address the challenges of insufficient uncertainty characterization and inadequate flexible resource coordination in active distribution network (ADN) planning under high-penetration distributed renewable energy integration, this paper proposes a WGAN-GP-based coordinated source–network–storage expansion planning method for ADNs. First, an improved Wasserstein Generative Adversarial Network (WGAN-GP) model is employed to learn the statistical patterns of wind and photovoltaic (PV) power outputs, generating representative scenarios that accurately capture the uncertainty and correlation of renewable generation. Then, an ADN expansion planning model considering the E-SOP (Energy Storage-integrated Soft Open Point) is developed with the objective of minimizing the annual comprehensive cost, jointly optimizing the siting and sizing of substations, lines, distributed generators, and flexible resources. By integrating the energy storage system on the DC side of the SOP, E-SOP achieves coordinated spatial power flow regulation and temporal energy balancing, significantly enhancing system flexibility and renewable energy accommodation capability. Finally, a Successive Convex Cone Relaxation (SCCR) algorithm is adopted to solve the resulting non-convex optimization problem, enabling fast convergence to a high-precision feasible solution with few iterations. Simulation results on a 54-bus ADN demonstrate that the proposed method effectively reduces annual comprehensive costs and eliminates renewable curtailment while ensuring high renewable penetration, verifying the feasibility and superiority of the proposed model and algorithm. Full article

The present study involves the synthesis of polyvinylpyrrolidone (PVP)-stabilized iron-based trimetallic nanoparticles with different metal addition sequences (Fe/Ag/Zn, Fe/Zn/Ag and Fe/(Zn/Ag)) using the sodium borohydride reduction method. In order to investigate the catalytic reactivity of the nanoparticles, a series of batch experiments were performed using methyl orange dye as a model pollutant. It was found that the Fe/Ag/Zn system showed the maximum catalytic activity compared to the other studied trimetallic systems. About 100% of the methyl orange dye was removed within 1 min and the second-order rate constant obtained was 0.0744 (mg/L)⁻¹ min⁻¹; the rate of reaction was higher than that of the other trimetallic systems. Furthermore, the effects of pH, initial dye concentration and nanoparticle dosage on the degradation of methyl orange were investigated. The results showed that the reactivity of the Fe/Ag/Zn trimetallic nanoparticles was highly dependent on the aforementioned parameters. Higher reactivity was obtained at lower pH, lower initial methyl orange dye concentration and higher nanoparticle dosage. Lastly, liquid chromatography–mass spectroscopy (LC-MS) was used to elucidate the reaction pathway and identify by-products from methyl orange degradation. The developed catalyst demonstrated exceptionally rapid and apparent degradation of methyl orange within one minute, outperforming previously reported bimetallic and trimetallic systems. This work reports a cost-effective nZVI-based trimetallic system containing minimal silver, which shows promising reactivity toward azo dye degradation and may be suitable for future application in textile wastewater treatment. Full article

A stripline-type circulator is essential for the initial low-power characterization of vacuum electron devices such as magnetrons, enabling accurate measurements of startup behavior, oscillation frequency, and mode structure while minimizing reflections and protecting diagnostic equipment. In this study, two broadband S-band stripline circulator prototypes operating in the 2–4 GHz and 3–4 GHz bands were designed, fabricated, and experimentally characterized. A unified design methodology was implemented by using the same ferrite material and coupling angle in both structures, providing procurement simplicity, cost reduction, and technological standardization. This approach also enabled a direct assessment of how bandwidth variations influence circulator behavior. The design goals targeted a transmission efficiency above 90%, isolation exceeding 15 dB, and a voltage standing-wave ratio (VSWR) of 1.2:1. Experimental evaluations, including magnetic field mapping, low-power S-parameter measurements, and high-power tests, confirmed that both prototypes satisfy these specifications, consistently achieving at least 90% transmission across their respective operating bands. Additionally, a comparative analysis between a locally fabricated ferrite and a commercial ferrite sample was conducted, revealing the influence of material properties on transmission stability and high-power behavior. The results demonstrate that broadband stripline circulators employing a common ferrite material can be adapted to different S-band applications, offering a practical, cost-effective, and reliable solution for RF systems. Full article

Cervical cancer, primarily caused by high-risk Human Papilloma Virus (HPV), remains a global health concern. Prognostic biomarkers reflecting systemic inflammation and immune response—the Systemic Immune-Inflammation Index (SII) and the Systemic Inflammation Response Index (SIRI)—have recently attracted interest for their potential predictive value in cervical cancer. We conducted a retrospective observational study including 344 patients who underwent loop electrosurgical excision of cervical intraepithelial neoplasia at Semmelweis University, Budapest, Hungary, between 2021 and 2024. Demographic, cytologic, histologic, and laboratory data were collected, and SII and SIRI were calculated. Statistical analyses, including Receiver Operating Characteristic (ROC) analyses, were performed. Higher SII and SIRI values were significantly associated with higher-grade lesions and invasive carcinoma. ROC analyses indicated good discriminatory performance, with negative predictive values of 96–100%, suggesting potential utility in ruling out malignant transformation. SII and SIRI are simple, cost-effective, and minimally invasive biomarkers that correlate with lesion severity in cervical disease. Their high negative predictive value supports a potential role as complementary rule-out tools in diagnostic evaluation. Further prospective studies are needed to validate these findings and to define clinically meaningful cut-off values for routine use. Full article

The construction industry significantly contributes to global sustainability challenges, producing 30–40 percent of global carbon dioxide emissions and consuming large amounts of natural resources. Pervious concrete has emerged as a sustainable alternative to conventional pavements due to its ability to promote stormwater infiltration and groundwater recharge. However, the absence of fine aggregates creates a highly porous structure that results in reduced compressive strength, limiting its broader structural use. Determining compressive strength traditionally requires destructive laboratory testing of concrete specimens, which demands considerable material, energy, and curing time, often up to 28 days—before results can be obtained. This makes iterative mix design and optimization both slow and resource intensive. To address this practical limitation, this study applies Machine Learning (ML) as a rapid, preliminary estimation tool capable of providing early predictions of compressive strength based on mix composition and curing parameters. Rather than replacing laboratory testing, the developed ML models serve as supportive decision-making tools, enabling engineers to assess potential strength outcomes before casting and curing physical specimens. This can reduce the number of trial batches produced, lower material consumption, and minimize the environmental footprint associated with repeated destructive testing. Multiple ML algorithms were trained and evaluated using data from existing literature and validated through laboratory testing. The results indicate that ML can provide reliable preliminary strength estimates, offering a faster and more resource-efficient approach to guiding mix design adjustments. By reducing the reliance on repeated 28-day test cycles, the integration of ML into previous concrete research supports more sustainable, cost-effective, and time-efficient material development practices. Full article

The electrochemical water splitting process represents a promising and sustainable route for generating high-purity hydrogen with minimal environmental impact. The development of efficient and economically viable electrocatalysts is crucial for enhancing the kinetics of the oxygen evolution reaction (OER), which is a major bottleneck in overall water splitting. In this study, a Co₃V₂O₈/PEG-CTAB electrocatalyst was synthesized and systematically evaluated for its OER activity in alkaline conditions. The nanosheet-like architecture of the PEG-CTAB-assisted Co₃V₂O₈ electrocatalyst facilitates effective interfacial contact, thereby improving charge transport and catalytic accessibility. Among the examined compositions, the Co₃V₂O₈/PEG-CTAB catalyst exhibited superior OER performance, requiring a low overpotential of 298 mV to deliver a current density of 10 mA cm⁻² and displaying a Tafel slope of 90 mV dec⁻¹ in 1 M KOH. Furthermore, the catalyst demonstrated outstanding durability, retaining its electrocatalytic activity after 5000 consecutive CV cycles and prolonged chronopotentiometric testing. The Co₃V₂O₈/PEG-CTAB || Pt-C asymmetric cell required a cell voltage of 1.83 V to reach the threshold current density, confirming its ability to efficiently sustain overall water splitting under alkaline conditions. The enhanced performance is attributed to the synergistic effect of the electrocatalyst, which promotes active site exposure and structural stability. These findings highlight the potential of the Co₃V₂O₈/PEG-CTAB system as a cost-effective and robust electrocatalyst for practical water oxidation applications. Full article

This study presents a comprehensive evaluation of a novel spinneret design to enhance polymer melt extrusion performance in fibre spinning production. Computational fluid dynamics (CFD) simulations using ANSYS Polyflow 2024 R2 are employed to analyse flow behaviour, pressure distribution, and shear profiles within the die. The novel design demonstrates improved flow uniformity, reduced pressure fluctuations, and minimized high-shear regions compared to a baseline spinneret. Experimental validation is conducted through side-by-side extrusion tests using polypropylene and thermoplastic polyurethane, confirming the simulation results. Throughput efficiency tests further reveal that the novel spin pack design significantly reduces residence times by 16% and accelerates purging cycles, indicating fewer polymer stagnation zones and enhanced material changeover efficiency. The computational parametric study conducted on PP shows that the novel design demonstrates improved flow uniformity and a significant reduction in operating pressure, achieving an 11% decrease in die-head pressure compared to the baseline spinneret. Additionally, the optimized geometry successfully minimizes high-shear regions while maintaining a manageable maximum shear rate increase of approximately 19% at the walls, which aids in preventing wall slip. These enhancements lead to lower extrusion pressures and more consistent processing across various polymers. By minimizing material waste and improving process reliability, the new spinneret design contributes to a more sustainable, cost-effective manufacturing process. Overall, these improvements provide a valuable framework for advancing extrusion technologies and optimizing spinneret geometries for high-performance polymer extrusion. The novelty of this work lies in introducing a spinneret geometry specifically optimized to minimize melt residence time, an outcome directly linked to reduced material degradation and waste. Full article

With the increasing penetration of distributed energy resources (DERs) and the rapid development of active distribution networks, the traditional centrally controlled operation mode can no longer meet the flexibility and autonomy requirements under the multi-dimensional coupling of sources, networks, loads, and storage. To achieve regional energy self-balancing and autonomous operation, this paper proposes a partitioned configuration method for energy storage systems (ESSs) in energy-autonomous distribution networks based on autonomous unit division. First, the concept and hierarchical structure of the energy-autonomous distribution network and its autonomous units are clarified, identifying autonomous units as the fundamental carriers of the network’s autonomy. Then, following the principle of “tight coupling within units and loose coupling between units,” a comprehensive indicator system for autonomous unit division is constructed from three aspects: electrical modularity, active power balance, and reactive power balance. An improved genetic algorithm is applied to optimize the division results. Furthermore, based on the obtained division, an ESS partitioned configuration model is developed with the objective of minimizing the total cost, considering the investment and operation costs of ESSs, power purchase cost from the main grid, PV curtailment losses, and network loss cost. The model is solved using the CPLEX solver. Finally, a case study on a typical multi-substation, multi-feeder distribution network verifies the effectiveness of the proposed approach. The results demonstrate that the proposed model effectively improves voltage quality while reducing the total cost by 20.89%, ensuring optimal economic performance of storage configuration and enhancing the autonomy of EADNs. Full article

In response to the decline in the inertia level of the power system caused by the large-scale integration of new energy, this paper proposes a grid-side pumped storage configuration strategy considering inertia constraints. The general pumped storage configuration ignores the duration of pumped storage and selects only single-duration units for capacity and power configuration. A single unit cannot balance rapid frequency response and long-term energy transfer, forcing thermal power to operate at high costs continuously to provide inertia support, while also causing a sharp increase in wind and solar power curtailment. This paper breaks through the limitations of the traditional single-duration pumped storage configuration and proposes a configuration-operation collaborative optimization strategy that combines inertia constraints and pumped storage duration selection. Firstly, starting from the system’s inertia requirements, the minimum inertia required by the system is obtained, respectively, based on the constraints of the system’s frequency change rate and the lowest point of the frequency. Furthermore, the minimum inertia demand constraint of the power system is constructed, and a capacity configuration strategy for grid-side pumped storage is proposed with the goal of minimizing the total operating cost of the power system throughout its entire cycle, taking into account the penalty term of the peak-valley difference index of the load curve and the penalty of the inertia guarantee value of medium and long-term units, while considering the inertia constraint. Finally, the effectiveness and superiority of the proposed method were verified through simulation analysis. Full article