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Wireless sensor networks (WSNs) encounter a significant challenge in ensuring network security due to their operational constraints. This challenge stems from the potential infiltration of malware into WSNs, where a single infected node can rapidly propagate worms to neighboring nodes. To address this issue, this research introduces a stochastic S E I R S model to characterize worm spread in WSNs. Initially, we established that our model possesses a globally positive solution. Subsequently, we determine a threshold value for our stochastic system and derive a set of sufficient conditions that dictate the persistence or extinction of worm spread in WSNs based on the mean behavior. Our study reveals that environmental randomness can impede the spread of malware in WSNs. Moreover, by utilizing various parameter sets, we obtain approximate solutions that showcase these precise findings and validate the effectiveness of the proposed S E I R S model, which surpasses existing models in mitigating worm transmission in WSNs.

In this paper, we investigate an norovirus (NoV) epidemic model with stochastic perturbation and the new definition of a nonlocal fractal–fractional derivative in the Atangana–Baleanu–Caputo (ABC) sense. First we present some basic properties including equilibria and the basic reproduction number of the model. Further, we analyze that the proposed stochastic system has a unique global positive solution. Next, the sufficient conditions of the extinction and the existence of a stationary probability measure for the disease are established. Furthermore, the fractal–fractional dynamics of the proposed model under Atangana–Baleanu–Caputo (ABC) derivative of fractional order “ p ” and fractal dimension “ q ” have also been addressed. Besides, coupling the non-linear functional analysis with fixed point theory, the qualitative analysis of the proposed model has been performed. The numerical simulations are carried out to demonstrate the analytical results. It is believed that this study will comprehensively strengthen the theoretical basis for comprehending the dynamics of the worldwide contagious diseases.

Since the discovery of the phenomenon of surface-enhanced Raman scattering (SERS), it has gradually become an important tool for the analysis of material compositions and structures. The applications of SERS have been expanded from the fields of environmental and materials science to biomedicine due to the extremely high sensitivity and non-destructiveness of SERS-based analytical technology that even allows single-molecule detection. This article provides a comprehensive overview of the surface-enhanced Raman scattering (SERS) phenomenon. The content is divided into several main sections: basic principles and the significance of Raman spectroscopy; historical advancements and technological progress in SERS; and various practical applications across different fields. We also discuss how electromagnetic fields contribute to the SERS effect, the role of chemical interactions in enhancing Raman signals, a modeling and computational approaches to understand and predict SERS effects.

HighlightsConstructing a porous carbon fiber/polymethacrylimide (CP) structure for acquiring promising electromagnetic absorption performance and withstanding both elevated temperature and high strength in a low density.The absorption bandwidth of CP composite can reach ultra-wideband absorption of 14 GHz at room temperature and even cover the whole X-band at 473 K.The lightweight of the CP composite with a density of only 110 mg cm−3 coupled with high compressive strength of 1.05 MPa even at 453 K.Realizing ultra-wideband absorption, desirable attenuation capability at high temperature and mechanical requirements for real-life applications remains a great challenge for microwave absorbing materials. Herein, we have constructed a porous carbon fiber/polymethacrylimide (CP) structure for acquiring promising microwave absorption performance and withstanding both elevated temperature and high strength in a low density. Given the ability of porous structure to induce desirable impedance matching and multiple reflection, the absorption bandwidth of CP composite can reach ultra-wideband absorption of 14 GHz at room temperature and even cover the whole X-band at 473 K. Additionally, the presence of imide ring group in polymethacrylimide and hard bubble wall endows the composite with excellent heat and compressive behaviors. Besides, the lightweight of the CP composite with a density of only 110 mg cm−3 coupled with high compressive strength of 1.05 MPa even at 453 K also satisfies the requirements in engineering applications. Compared with soft and compressible aerogel materials, we envision that the rigid porous foam absorbing material is particularly suitable for environmental extremes.

The global consequences of Coronavirus (COVID-19) have been evident by several hundreds of demises of human beings; hence such plagues are significantly imperative to predict. For this purpose, the mathematical formulation has been proved to be one of the best tools for the assessment of present circumstances and future predictions. In this article, we propose a fractional epidemic model of coronavirus (COVID-19) with vaccination effects. An arbitrary order model of COVID-19 is analyzed through three different fractional operators namely, Caputo, Atangana-Baleanu-Caputo (ABC), and Caputo-Fabrizio (CF), respectively. The fractional dynamics are composed of the interaction among the human population and the external environmental factors of infected peoples. It gives an extra description of the situation of the epidemic. Both the classical and modern approaches have been tested for the proposed model. The qualitative analysis has been checked through the Banach fixed point theory in the sense of a fractional operator. The stability concept of Hyers-Ulam idea is derived. The Newton interpolation scheme is applied for numerical solutions and by assigning values to different parameters. The numerical works in this research verified the analytical results. Finally, some important conclusions are drawn that might provide further basis for in-depth studies of such epidemics.

The coronavirus (COVID-19) expanded rapidly and affected almost the whole world since December 2019. COVID-19 has an unusual ability to spread quickly through airborne viruses and substances. Taking into account the disease’s natural progression, this study considers that viral spread is unpredictable rather than deterministic. The continuous time Markov chain (CTMC) stochastic model technique has been used to anticipate upcoming states using random variables. The suggested study focuses on a model with five distinct compartments. The first class contains Lévy noise-based infection rates (termed as vulnerable people), while the second class refers to the infectious compartment having similar perturbation incidence as the others. We demonstrate the existence and uniqueness of the positive solution of the model. Subsequently, we define a stochastic threshold as a requisite condition for the extinction and durability of the disease’s mean. By assuming that the threshold value R0D is smaller than one, it is demonstrated that the solution trajectories oscillate around the disease-free state (DFS) of the corresponding deterministic model. The solution curves of the SDE model fluctuate in the neighborhood of the endemic state of the base ODE system, when R0P>1 elucidates the definitive persistence theory of the suggested model. Ultimately, numerical simulations are provided to confirm our theoretical findings. Moreover, the results indicate that stochastic environmental disturbances might influence the propagation of infectious diseases. Significantly, increased noise levels could hinder the transmission of epidemics within the community.

Development of fifth‐generation technology leads to a growing demand for materials with exceptional thermal property, mechanical strength, and low dielectric loss. However, ensuring the broad application of such materials by comprehensively investigating their aging mechanisms and service lifetimes remains a challenge. In this work, we have developed a glass fiber (GF) reinforced liquid crystal polymer composite (GF/LCP) and conducted a thorough exploration of its aging mechanism, behavior, and service lifetime under thermal and oxidative conditions. On the basis of the general Arrhenius model, the composite maintains a high level of functionality for a remarkable 18 years at 150 °C and 1.5 years at 200 °C. Despite the extremely high thermal resistance of GF/LCP composite, the LCP matrix exhibits localized brittle fracture, and the main chains still undergo gradual degradation to generate phenolic groups, which ultimately leads to severe pulverization and mass loss. However, a high degree of connection maintenance between GF and LCP components is still reserved. This work provides a valuable reference for the reliable application of 5G materials under thermal and oxidative conditions. A kind of glass fiber (GF) reinforced liquid crystal polymer (GF/LCP) composite and comprehensively investigated its aging behavior, mechanism, and service lifetime under long‐term thermal and oxidative conditions. Assisted by the general Arrhenius model, the composite maintained a high level of quality for 18 years at 150 °C. The aging mechanism was deeply investigated.

The periodic thermal loads to which electronic devices are exposed during operation induce alternating thermal stresses due to the mismatched coefficients of thermal expansion (CTE) between the solder joints and the surrounding materials. This leads to cyclic thermal strain, ultimately causing crack initiation, propagation, and failure of interconnect structures. This study investigates thermal fatigue failure of Sn3.5Ag solder joints induced by cyclic thermal stresses from CTE mismatch. Numerical simulations and experiments reveal that alternating shear strain concentrates at the joint–pad interface, serving as the crack initiation site. This study proposes a hypothesis: extracting the equivalent viscoplastic strain range from the steady-state hysteretic response after cyclic stabilization and applying it to the Coffin–Manson model can mitigate the strain overestimation inherent to methods based on the initial transient impact, thereby providing a more reasonable physical basis for thermal fatigue life evaluation. Based on this, the thermal fatigue life of the solder joint is predicted to be 18,930 cycles. Analysis confirms significantly higher viscoplastic strain energy density at this critical point, indicating energy dissipation drives damage. This study addresses the above hypothesis from three aspects: deformation mechanism, cyclic response, and energy dissipation, providing a key basis for developing a highly reliable method for assessing solder joint life.

The development of fifth‐generation technology has resulted in increased demand for materials with low dielectric losses and superior thermal and mechanical properties. However, ensuring the widespread use of such materials by investigating their aging mechanisms and operating lifetimes remains challenging. In this study, a glass‐fiber (GF)‐reinforced acrylate‐styrene‐acrylonitrile/polycarbonate (ASA/GF/PC) composite is designed and comprehensively investigated its aging behavior, mechanism, and service lifetime under long‐term hygrothermal conditions. Based on the general Peck model, the composite maintains a high level of quality for over 10 years, including under harsh conditions of 40 °C and 80% relative humidity. The aging mechanism is primarily ascribed to cracking between the GF fibers and matrix, the breaking of chemical bonds, the generation of new cross‐linked domains, and physical aging. These findings provide valuable insights into the long‐term utilization of ASA/GF/PC composites in harsh environments. A kind of glass fiber (GF) reinforced acrylate‐styrene‐acrylonitrile/polycarbonate (ASA/GF/PC) composite and comprehensively investigated its aging behavior, mechanism, and service lifetime under long‐term hygrothermal conditions. Assisted by the general Peck model, the composite maintains a high level of quality for over 10 years, even under harsh conditions of 40 °C and 80% relative humidity.

In this paper, we consider the dynamical behaviour of a stochastic coronavirus (COVID-19) susceptible-infected-removed epidemic model with the inclusion of the influence of information intervention and Lévy noise. The existence and uniqueness of the model positive solution are proved. Then, we establish a stochastic threshold as a sufficient condition for the extinction and persistence in mean of the disease. Based on the available COVID-19 data, the parameters of the model were estimated and we fit the model with real statistics. Finally, numerical simulations are presented to support our theoretical results.