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Under certain assumptions, adaptive thresholds for distributed FDI in each local subsystem are derived, ensuring robustness with respect to interactions among subsystems and system modeling uncertainty.
In Section 3, some conditions are derived ensuring the existence and uniqueness of positive almost periodic solution of system (1.4) by using the theory of exponential dichotomy on time scales and fixed point theorem of monotone operator.
By using exponential dichotomy, the Banach fixed point theory and some inequality analysis technology, some sufficient conditions are derived ensuring existence, uniqueness and global attractivity of almost periodic solution of delayed cellular neural networks (DCNNs) with time-varying coefficients.
By using M-matrix theory, some inequality analysis technology and mathematical induction, some sufficient conditions are derived ensuring existence and global exponential stability of the equilibrium points of delayed cellular neural networks (DCNNS) with impulses.
By using exponential dichotomy, the Banach fixed point theory, constructing suitable Lyapunov functional, and combining Yang inequality, some sufficient conditions are derived ensuring existence, globally exponential stability of almost periodic solution for BAM neural networks with variable coefficients and delays.
Under certain assumptions, adaptive thresholds for distributed sensor fault detection and isolation in each subsystem are derived, ensuring robustness with respect to interactions among subsystems and system modeling uncertainty.
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The model parameters from which the colloidosmotic hypothesis was derived ensure maintenance or rapid restoration of osmotic equilibria between host cell cytoplasm and extracellular medium.
By using Itô's differential formula and the Lyapunov stability theory, sufficient conditions are first derived for ensuring the stability of the stochastic interval delay systems.
Sufficient criteria are first derived for ensuring finite-time boundedness of the underlying system with a given maximum ratio of activation time between unstable subsystems and stable ones.
A model adjusting for the presence in NPS of RSV A, the total number of agents detected in NPS, and the presence of a medical risk factor implicated in severe H1N1 outcomes was derived after ensuring that relationships among included variables were low (nonsignificant contingency coefficients ranging from 0.001 to 0.255).
"The root cause, fundamentally, was that the scientists failed to follow a scientifically derived and ensured protocol that ensured that anthrax was deactivated," said Frieden.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com