Search Results (191)

The inherent randomness and concealment of rumors in social networks exacerbate their spread, leading to significant societal instability. To explore the mechanisms of rumor propagation for more effective control and mitigation of harm, we propose a novel fractional-order Susceptible-Infected-Negative-Positive-Removed (SINPR) rumor propagation model, which simultaneously incorporates emotional mechanisms by distinguishing between positive and negative emotion spreaders, as well as memory effects through fractional-order derivatives. The proposed model extends traditional frameworks by jointly capturing the bidirectional influence of emotions and the anomalous, history-dependent dynamics often overlooked by integer-order models. First, we calculate the equilibrium points and thresholds of the model, and analyze the stability of the equilibrium, along with the sensitivity and transcritical bifurcation associated with the basic reproduction number. Next, we validate the theoretical results through numerical simulations and analyze the individual effects of fractional-order derivatives and emotional mechanisms. Finally, we predict the rumor propagation process using real datasets. Comparative experiments with other models demonstrate that the fractional-order SINPR model achieves R-squared values of 0.9712 and 0.9801 on two different real datasets, underscoring its effectiveness in predicting trends in rumor propagation. Full article

This article investigates the problem of bending failure in a rectilinear thin-walled rod consisting of a multimodular material exhibiting different elastic properties in tension and compression, with applications to the structural design of space satellites, unmanned aerial vehicles, aeronautical systems, and nano- and micro-class satellites. Nonlinear differential equations have been formulated to describe the propagation of the failure front under transverse loading. Formulas for determining the incubation period of the failure process have been derived, and the problem has been solved. Based on the developed model, new analytical expressions have been obtained for the displacement of the neutral axis, the stiffness of the rod, the distribution of maximum stresses, and the motion of the failure front. The influence of key parameters—such as the singularity coefficient of the damage nucleus and the ratio of the elastic moduli—on the service life and failure dynamics of the rod has been analyzed. Using the obtained results, the effect of the multimodular properties on the long-term strength of thin-walled rods under pure bending has been thoroughly studied. The analysis of the constructed curves shows that an increase in the “fading of memory” (memory-loss) parameter, which characterizes the material’s ability to quickly “forget” previous loadings and return to equilibrium, can, in certain cases, lead to a longer service life. Full article

The utilization of ammonia as a fuel for gas turbines involves practical challenges due to its low reactivity, narrow flammability limits, and slow laminar flame propagation. One of the potential solutions to enhance the combustion reactivity of ammonia is co-firing with syngas. This paper presents an experimental and numerical investigation of the laminar burning velocity (LBV) of ammonia/syngas/air mixtures under elevated pressures (up to 10 bar) and temperatures (up to 473 K). Experiments were conducted in a constant-volume combustion chamber with a total volume of 11 L equipped with a dual-electrode capacitive discharge ignition system. A systematic sensitivity analysis was conducted to experimentally evaluate the system performance under various syngas compositions and equivalence ratios from 0.7 to 1.6 and ultimately identify the factors with the most impact on the system. As a complement to the experiments, a detailed numerical simulation was carried out integrating available kinetic mechanisms—chemical reaction sets and their rates—to support advancements in the understanding and optimization of ammonia/syngas co-firing dynamics. The sensitivity analysis results reveal that LBV is significantly enhanced by increasing the hydrogen content (>50%). Furthermore, the LBV of the gas mixture is found to increase with the use of a rich flame, higher mole fractions of syngas, and higher initial temperatures. The results indicate that higher pressure reduces LBV by 40% but at the same time enhances the adiabatic flame temperature (by 100 K) due to an equilibrium shift. The analysis was also extended to quantify the impact of syngas mole fractions and elevated initial temperatures. The kinetics of the reactions are analyzed through the reaction pathways, and the results reveal how the preferred pathways vary under lean and rich flame conditions. These findings provide valid quantitative design data for optimizing the combustion kinetics of ammonia/syngas blends, offering valuable design data for ammonia-based combustion systems in industrial gas turbines and power generation applications, reducing NOₓ emissions by up to 30%, and guiding future research directions toward kinetic models and emission control strategies. Full article

To address the challenges of low recognition accuracy and substantial model complexity in crop disease identification models operating in complex field environments, this study proposed a novel hybrid model named ConvTransNet-S, which integrates Convolutional Neural Networks (CNNs) and transformers for crop disease identification tasks. Unlike existing hybrid approaches, ConvTransNet-S uniquely introduces three key innovations: First, a Local Perception Unit (LPU) and Lightweight Multi-Head Self-Attention (LMHSA) modules were introduced to synergistically enhance the extraction of fine-grained plant disease details and model global dependency relationships, respectively. Second, an Inverted Residual Feed-Forward Network (IRFFN) was employed to optimize the feature propagation path, thereby enhancing the model’s robustness against interferences such as lighting variations and leaf occlusions. This novel combination of a LPU, LMHSA, and an IRFFN achieves a dynamic equilibrium between local texture perception and global context modeling—effectively resolving the trade-offs inherent in standalone CNNs or transformers. Finally, through a phased architecture design, efficient fusion of multi-scale disease features is achieved, which enhances feature discriminability while reducing model complexity. The experimental results indicated that ConvTransNet-S achieved a recognition accuracy of 98.85% on the PlantVillage public dataset. This model operates with only 25.14 million parameters, a computational load of 3.762 GFLOPs, and an inference time of 7.56 ms. Testing on a self-built in-field complex scene dataset comprising 10,441 images revealed that ConvTransNet-S achieved an accuracy of 88.53%, which represents improvements of 14.22%, 2.75%, and 0.34% over EfficientNetV2, Vision Transformer, and Swin Transformer, respectively. Furthermore, the ConvTransNet-S model achieved up to 14.22% higher disease recognition accuracy under complex background conditions while reducing the parameter count by 46.8%. This confirms that its unique multi-scale feature mechanism can effectively distinguish disease from background features, providing a novel technical approach for disease diagnosis in complex agricultural scenarios and demonstrating significant application value for intelligent agricultural management. Full article

Thylakoid rhodanese-like protein (TROL) serves as a thylakoid membrane hinge linking photosynthetic electron transport chain (PETC) complexes to nicotinamide adenine dinucleotide phosphate (NADPH) synthesis. TROL is the docking site for the flavoenzyme ferredoxin-NADP⁺ oxidoreductase (FNR). Our prior work indicates that the TROL-FNR complex maintains redox equilibrium in chloroplasts and systemically in plant cells. Improvement in the knowledge of redox regulation mechanisms is critical for engineering stress-tolerant plants in times of elevated global drought intensity. To further test this hypothesis and confirm our previous results, we monitored light-independent ROS propagation in the leaves of Arabidopsis wild type (WT), TROL knock-out (KO), and TROL ΔRHO (RHO-domain deletion mutant) mutant plants in situ by using confocal laser scanning microscopy with specific fluorescent probes for the three different ROS: O₂^·−, H₂O₂, and ¹O₂. Plants were grown under the conditions of normal substrate moisture and under drought stress conditions. Under the drought stress conditions, the TROL KO line showed ≈32% less O₂^·− while the TROL ΔRHO line showed ≈49% less H₂O₂ in comparison with the WT. This research confirms the role of dynamical TROL-FNR complex formation in redox equilibrium maintenance by redirecting electrons in alternative sinks under stress and also points it out as promising target for stress-tolerant plant engineering. Full article

In this paper, we present a mathematical model, $M_{siqr}$, to analyze the dynamics of mobile malware propagation in smartphone networks. The model segments the mobile device population into susceptible, exposed, infected, quarantined, and recovered compartments, integrating critical control parameters such as infection and quarantine rates. The analytical results include the derivation of the basic reproduction number, $R_0$, along with equilibrium and stability analyses that provide insights into long-term system behavior. A focused scenario analysis compares the baseline dynamics with a more aggressive malware variant and a more effective quarantine response. The results show that increased infectivity sharply escalates the peak of infection, while enhanced quarantine measures effectively suppress it. This highlights the importance of prompt containment strategies even under more virulent conditions. The sensitivity analysis identifies the infection rate as the most influential parameter driving peak infection, while the quarantine rate exerts the most significant dampening effect. Monte Carlo simulations of parameter uncertainty reveal a consistently high epidemic potential across varied conditions. A parameter sweep across the infection–quarantine space further maps out the conditions under which malware outbreaks can be mitigated or prevented. Overall, the model demonstrates that mobile malware poses sustained epidemic risk under uncertainty, but effective control parameters—particularly quarantine—can drastically alter outbreak trajectories. Full article

Antivirus (patch) is one of the most powerful tools for defending against malware spread. Distributed patching is superior to its centralized counterpart in terms of significantly lower bandwidth requirement. Under the distributed patching mechanism, a novel malware propagation model with double delays and double saturation effects is proposed. The basic properties of the model are discussed. A pair of thresholds, i.e., the first threshold $R_0$ and the second threshold $R_1$, are determined. It is shown that (a) the model admits no malware-endemic equilibrium if $R_0\le 1$, (b) the model admits a unique patch-free malware-endemic equilibrium and admits no patch-endemic malware-endemic equilibrium if $1<R_0\le R_1$, and (c) the model admits a unique patch-free malware-endemic equilibrium and a unique patch-endemic malware-endemic equilibrium if $R_0>R_1$. A criterion for the global asymptotic stability of the malware-free equilibrium is given. A pair of criteria for the local asymptotic stability of the patch-free malware-endemic equilibrium are presented. A pair of criteria for the local asymptotic stability of the patch-endemic malware-endemic equilibrium are derived. Using cybersecurity terms, these theoretical outcomes have the following explanations: (a) In the case where the first threshold can be kept below unity, the malware can be eradicated through distributed patching. (b) In the case where the first threshold can only be kept between unity and the second threshold, the patches may fail completely, and the malware cannot be eradicated through distributed patching. (c) In the case where the first threshold cannot be kept below the second threshold, the patches may work permanently, but the malware cannot be eradicated through distributed patching. The influence of the delays and the saturation effects on malware propagation is examined experimentally. The relevant conclusions reveal the way the delays and saturation effects modulate these outcomes. Full article

As the global energy structure transitions towards cleaner sources, large-scale integration of wind power has become a trend for modern power systems. However, the impact of low-inertia power electronic converters and the fault propagation effects at critical nodes pose significant challenges to power system stability. To this end, a Kuramoto-like model analysis method, considering node importance, is proposed in this paper. First, virtual node technology is utilized to optimize the power grid topology model. Then an improved PageRank algorithm embedded by a critical node identification method is proposed, which simultaneously considers transmission efficiency, coupling transmission probability, and voltage influence among nodes. On this basis, the traditional uniform coupling assumption is eliminated, thereby reallocating the coupling strength between critical nodes. In addition, the Kron method is applied to simplify the power grid model, constructing a hybrid Kuramoto-like model that integrates second-order synchronous machine oscillators and first-order wind power oscillators. Based on this model, the transient stability of the wind power integrated power system is analyzed. Finally, through estimating the attraction region range of the stable equilibrium point, a transient stability criterion is proposed for fault limit removal time assessment. The simulation results of the improved IEEE 39-bus system show that coupling strength optimization based on node importance reduces the system’s average critical coupling strength by 17%, significantly improving synchronization robustness. Time-domain simulations validate the accuracy of the method, with the relative error of fault removal time estimation controlled within 10%. This research provides a new analytical tool for transient stability analysis of wind power integration. Full article

Extreme conditions induced by shock exert unprecedented force on crystal lattice and push atoms away from their equilibrium positions. Nonequilibrium molecular dynamics (MD) simulations are one of the best ways to describe material behavior under shock but are limited by the availability and reliability of potential functions. In this work, a specific embedded atom (EAM) potential of molybdenum (Mo) is built for shock and tested by quasi-isentropic and piston-driven shock simulations. Comparisons of the equation of state, lattice constants, elastic constants, phase transitions under pressure, and phonon dispersion with those in the existing literature validate the reliability of our EAM potential. Quasi-isentropic shock simulations reveal that critical stresses for the beginning of plastic deformation follow a [111] > [110] > [100] loading direction for single crystals, and then polycrystal samples. Phase transitions from BCC to FCC and BCC to HCP promote plastic deformation for single crystals loading along [100] and [110], respectively. Along [111], void directly nucleates at the stress concentration area. For polycrystals, voids always nucleate on the grain boundary and lead to early crack generation and propagation. Piston-driven shock loading confirms the plastic mechanisms observed from quasi-isentropic shock simulation and provides further information on the spall strength and spallation process. 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

Vector-borne diseases pose a significant public health challenge in tropical regions, where complex interactions between hosts, vectors, and the environment drive epidemic dynamics. In this study, we develop a spatio-temporal mathematical model to describe the spread of such diseases, incorporating population dynamics and spatial–temporal factors affecting pathogen transmission. We conduct a theoretical analysis of the model, proving the existence, uniqueness, and positivity of solutions. Additionally, we examine equilibrium states and key epidemiological parameters, including the basic reproduction number. Our findings provide mathematical insights into epidemic propagation and offer a foundation for designing effective control strategies. Full article

The instability of mine roadways is significantly influenced by the coupled effects of groundwater seepage and non-uniform loading. These interactions often induce localized plastic deformation and progressive failure, particularly in the roof and sidewall regions. Seepage elevates pore water pressure and deteriorates the mechanical properties of the rock mass, while non-uniform loading leads to stress concentration. The combined effect facilitates the propagation of microcracks and the formation of shear zones, ultimately resulting in localized instability. This initial damage disrupts the mechanical equilibrium and can evolve into severe geohazards, including roof collapse, water inrush, and rockburst. Therefore, understanding the damage and failure mechanisms of mine roadways at the mesoscale, under the combined influence of stress heterogeneity and hydraulic weakening, is of critical importance based on laboratory experiments and numerical simulations. However, the large scale of in situ roadway structures imposes significant constraints on full-scale physical modeling due to limitations in laboratory space and loading capacity. To address these challenges, a straight-wall circular arch roadway was adopted as the geometric prototype, with a total height of 4 m (2 m for the straight wall and 2 m for the arch), a base width of 4 m, and an arch radius of 2 m. Scaled physical models were fabricated based on geometric similarity principles, using defect-bearing sandstone specimens with dimensions of 100 mm × 30 mm × 100 mm (length × width × height) and pore-type defects measuring 40 mm × 20 mm × 20 mm (base × wall height × arch radius), to replicate the stress distribution and deformation behavior of the prototype. Uniaxial compression tests on water-saturated sandstone specimens were performed using a TAW-2000 electro-hydraulic servo testing system. The failure process was continuously monitored through acoustic emission (AE) techniques and static strain acquisition systems. Concurrently, FLAC^3D 6.0 numerical simulations were employed to analyze the evolution of internal stress fields and the spatial distribution of plastic zones in saturated sandstone containing pore defects. Experimental results indicate that under non-uniform loading, the stress–strain curves of saturated sandstone with pore-type defects typically exhibit four distinct deformation stages. The extent of crack initiation, propagation, and coalescence is strongly correlated with the magnitude and heterogeneity of localized stress concentrations. AE parameters, including ringing counts and peak frequencies, reveal pronounced spatial partitioning. The internal stress field exhibits an overall banded pattern, with localized variations induced by stress anisotropy. Numerical simulation results further show that shear failure zones tend to cluster regionally, while tensile failure zones are more evenly distributed. Additionally, the stress field configuration at the specimen crown significantly influences the dispersion characteristics of the stress–strain response. These findings offer valuable theoretical insights and practical guidance for surrounding rock control, early warning systems, and reinforcement strategies in water-infiltrated mine roadways subjected to non-uniform loading conditions. Full article

Equilibrium Propagation (EP) offers a biologically inspired alternative to backpropagation for training recurrent neural networks, but its reliance on symmetric feedback connections and stability limitations hinders practical adoption. The DirEcted EP (DEEP) model relaxes the symmetry constraint, yet suffers from convergence issues and lacks a principled learning guarantee. In this work, we generalize DEEP by incorporating neuronal leakage, providing new convergence criteria for the network’s dynamics. We additionally propose a novel local learning rule closely linked to the objective function’s gradient and establish sufficient conditions for reliable learning in small networks. Our results resolve longstanding stability challenges and bring energy-based learning models closer to biologically plausible and provably effective neural computation. Full article

Viroids are subviral plant pathogens composed of non-coding, small, circular, single-stranded RNAs that parasitize the transcriptional machinery of their host cells. For many years, viroid-induced diseases were mistakenly attributed to viruses due to similarities in symptoms and pathogenic behavior. However, advances in molecular biology over the past sixty years have clearly distinguished viroids from viruses and other pathogens in terms of genetic composition, structural features, and replication mechanisms. Citrus trees in the Mediterranean region appear to have been associated with viroid infections since ancient times. Nevertheless, the use of propagation material harboring asymptomatic viroid infections allowed for continued production of high-quality fruit. This delicate equilibrium was disrupted with the spread of novel citrus pathogens, prompting the adoption of new horticultural practices that emphasized the elimination of citrus pathogens—including viroids—from propagation material. Concurrently, a contrasting approach emerged in the late 1960s: the experimental use of “graft-transmissible dwarfing agents”—later identified as citrus viroids—to control citrus tree size. Our lab initiated work on citrus viroid-induced dwarfing in the early 1980s and continued this line of research for nearly two decades. Eventually, we concluded that it was impractical to simultaneously promote rigorous sanitation protocols while advocating for the use of viroids to induce dwarfing. This review summarizes key biological and molecular aspects of citrus and avocado viroids investigated in our laboratory, including the development of diagnostic techniques and the exploration of viroid-induced dwarfing as a horticultural tool. Full article

The transmission efficiency of underwater acoustic is doubly constrained by absorption attenuation and geometric spreading losses, with the relative interaction between these loss mechanisms exhibiting complex dynamic variations across the frequency spectrum. Achieving dynamic equilibrium between these frequency-dependent loss mechanisms is key to enhancing acoustic energy transmission performance. To address this, this paper proposes a multi-variable coupled acoustic energy transmission model that systematically integrates the cumulative effects of the propagation distance, the geometric configuration of acoustic source arrays, and the interactive influences of critical environmental factors such as the salinity, temperature, and depth to comprehensively analyze the synergistic mechanisms of absorption loss and geometric spreading loss in practical underwater environments. Based on dynamic response analysis in the frequency dimension, the model identifies and determines the optimal working frequency ranges (i.e., dynamic equilibrium points) for maximizing the efficiency of energy transmission under various propagation conditions and environmental configurations. Both theoretical derivations and numerical simulations consistently reveal a frequency band within the low-to-mid frequency range (approximately 20–100 kHz) which is associated with significantly enhanced transmission efficiency under specific parameter settings. These research findings provide a scientific basis and engineering guidance for frequency selection and the structural optimization of underwater acoustic energy systems, offering substantial theoretical value and application prospects that can strongly support the development of acoustic technologies in ocean engineering, resource exploration, and national defense security. Full article