Search Results (5)

This paper studies observer-based stabilization of a normalized incommensurate fractional-order discrete-time SI benchmark model for computer-virus propagation. The model is formulated with Caputo-like fractional-difference operators and allows the susceptible and infected compartments to have different memory orders. In contrast with a predictive malware-forecasting model, the proposed system is explicitly treated as a dimensionless benchmark for qualitative analysis and control design. To clarify how the benchmark can be connected to empirical cybersecurity data, the revised formulation includes a calibration and fractional-order selection procedure based on normalized infection telemetry, admissible parameter sets, and loss minimization. The incommensurate orders are therefore interpreted as identifiable modeling parameters, not as arbitrary constants. The plant, observer, and control laws are formulated on the integer update grid, and the memory terms are implemented through the equivalent Volterra-type convolution representation. A nonlinear Luenberger-type observer is proposed under infected-state measurements, which is justified as a detectability-based cyber-monitoring configuration rather than a full observability assumption. The observer gain design, the full-state feedback design, and the observer-based output-feedback design are derived from first-order linearized incommensurate fractional-order models. The resulting criteria are expressed through characteristic-root conditions associated with linear incommensurate Caputo-type fractional-order difference systems. The scope of the theoretical claims is made explicit: the results provide local linearized-design guarantees and do not establish global or semi-global nonlinear stabilization. The nonlinear residuals, measurement-noise channel, incomplete-measurement formulation, and limitations of the linearized characteristic-root approach are stated explicitly so that the numerical section can assess robustness, sensitivity, and the effective region of attraction of the nonlinear closed loop. Full article

This paper proposes a substation operation risk situational awareness method based on the health state of the main equipment, with the goal of assessing the substation operation risk posture and performing risk prevention and control based on the situational awareness framework. Firstly, a risk propagation model considering the health state of the main equipment is proposed with reference to the SI (Susceptible–Infected) virus propagation model to simulate the risk propagation process among the main equipment of the substation; then, the potential risk severity index of the equipment is constructed based on the temporal set of risk propagation among the equipment within the substation to quantify the operational risk posture of the substation; finally, a case analysis is carried out by using a dual-voltage-level substation, and the results show that the method proposed in this paper can effectively simulate the risk propagation paths between the main equipment of a substation and the severity of the operational risk of each piece of main equipment. Based on the results of the substation operation risk situation assessment, it is used to guide the substation operation and inspection department to optimize the substation main equipment operation and inspection plan formulation, and to find the main equipment defects in time for overhaul and maintenance. Full article

Host metabolic reprogramming is a critical strategy employed by many viruses to support their replication, and the key metabolic enzyme plays important roles in virus infection. This study investigates the role of pyruvate kinase M2 (PKM2), a glycolytic enzyme with non-canonical functions, in the replication of classical swine fever virus (CSFV). Using PK-15 cells and piglet models, we demonstrate that CSFV infection upregulates PKM2 expression both in vitro and in vivo, creating a proviral environment. knockdown of PKM2 by siRNA reduced CSFV proliferation, while PKM2 overexpression significantly increased virus propagation, which was evaluated by viral protein synthesis, genome replication, and progeny virion production. A direct interaction between PKM2 and CSFV NS5B protein was identified by co-immunoprecipitation and GST-pulldown assays, and PKM2 affected NS5B polymerase activity in a dual-luciferase reporter assay, with PKM2 depletion reducing RdRp function by 50%. Temporal analysis of the first viral replication cycle confirmed PKM2-dependent enhancement of CSFV RNA synthesis. These findings establish PKM2 as a proviral host factor that directly binds NS5B to potentiate RdRp activity, thereby bridging metabolic adaptation and viral genome replication. This study provides new evidence of a glycolytic enzyme physically interacting and enhancing viral polymerase function, offering new information about CSFV–host interaction. Full article

Many models of virus propagation in Computer Networks inspired by epidemic disease propagation mathematical models that can be found in the epidemiology field (SIS, SIR, SIRS, etc.) have been proposed in the last two decades. The purpose of these models has been to determine the conditions under which a virus becomes rapidly extinct in a network. The most common models of virus propagation in networks are SIS-type models or their variants. In such models, the conditions that lead to a rapid extinction of the spread of a computer virus have been calculated and its dependence on some parameters inherent to the mathematical model has been observed. In this article, we will try to analyze a particular SIS-type model proposed in the past by Chakrabarti as well as an SIRS-type variation of this model proposed in the past by myself. I will show through simulations the influence that the topology of a network has on the dynamics of the spread of a virus in different network types. In the recent past, there have been interesting articles that demonstrate the relationship between the eigenvalue ${\lambda }_1$ of the adjacency matrix and the reduction in the spread of a virus in a network. From this, the minimization of the spectral radius strategies by edge suppression has been proposed. This problem is NP-complete in its general case and for this reason, heuristic algorithms have been proposed. In this article, I will perform simulations of an SIS-type model in topologies with the same number of nodes but with different structures to compare their epidemic behavior. The simulations will show that regular topologies with small node degrees, i.e., of degree 4, as is the case of the topology that I call Lattice4, have favorable behavior in terms of the fast extinction property, with respect to other denser and less regular topologies such as the binomial topologies as well as Power law topologies. Based on the results of the simulations, my contribution will consist of proposing, as a node isolation strategy, a transformation of the original topology into an approximately regular topology by edge elimination. Although such a transformed topology is not optimal in terms of reducing the propagation of a virus, it induces the rapid extinction of the virus in the network. Full article

In the present article, we research the existence of the positive periodic solutions for a mathematical model that describes the propagation dynamics of a pathogen living within a vector population over a plant population. We propose a generalized compartment model of the susceptible–infected–susceptible (SIS) type. This model is derived primarily based on four assumptions: (i) the plant population is subdivided into healthy plants, which are susceptible to virus infection, and infected plants; (ii) the vector population is categorized into non-infectious and infectious vectors; (iii) the dynamics of pathogen propagation follow the standard susceptible–infected–susceptible pattern; and (iv) the rates of pathogen propagation are time-dependent functions. The main contribution of this paper is the introduction of a sufficient condition for the existence of positive periodic solutions in the model. The proof of our main results relies on a priori estimates of system solutions and the application of coincidence degree theory. Additionally, we present some numerical examples that demonstrate the periodic behavior of the system. Full article