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https://www.selleckchem.com/products/cx-5461.html As many countries fear and even experience the emergence of a second wave of COVID-19, reminding health care workers (HCWs) and other hospital employees of the critical role they play in preventing SARS-CoV-2 transmission is more important than ever. Building and strengthening the intrinsic motivation of HCWs to apply infection prevention and control (IPC) guidelines to avoid contaminating their colleagues, patients, friends, and relatives is a goal that must be energetically pursued. A high rate of nosocomial infections during the first COVID-19 wave was detected by IPC specialists and further cemented their belief in the need for an engaging intervention that could improve compliance with COVID-19 safe behaviors. Our aim was to develop a serious game that would promote IPC practices with a specific focus on COVID-19 among HCWs and other hospital employees. The first 3 stages of the SERES framework were used to develop this serious game. A brainswarming session between developers and IPC specialists waement systems.This paper is concerned with the problem of finite-time H∞ state estimation for genetic regulatory networks with randomly occurring uncertainties. The persistent dwell-time switching, as a more versatile class of switching signal, is considered in this paper. Besides, several random variables that obey the Bernoulli distribution are used to represent randomly occurring uncertainties. The overriding purpose of this paper is to design an estimator to ensure that the estimation error system is stochastically finite-time bounded and satisfies the H∞ performance. The sufficient conditions for the explicit form of the estimator gains can be obtained by the Lyapunov method. Finally, a numerical example is given to verify the correctness and feasibility of the proposed method.The firing rate of some biological neurons such as neocortical pyramidal neurons is consistent with fractional order derivative, and the fr

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