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The recent development and mass administration of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) vaccines allowed for disease control, reducing hospitalizations and mortality. Most of these vaccines target the SARS-CoV-2 Spike (S) protein antigens, culminating with the production of neutralizing antibodies (NAbs) that disrupt the attachment of the virus to ACE2 receptors on the host cells. However, several studies demonstrated that the NAbs typically rise within a few weeks after vaccination but quickly reduce months later. Thus, multiple booster administration is recommended, leading to vaccination hesitancy in many populations. Detecting serum anti-SARS-CoV-2 NAbs can instruct patients and healthcare providers on correct booster strategies. Several in vitro diagnostics kits are available; however, their high cost impairs the mass NAbs diagnostic testing. Recently, we engineered an ACE2 mimetic that interacts with the Receptor Binding Domain (RBD) of the SARS-2 S protein. Here we present the use of this engineered mini-protein (p-deface2 mut) to develop a detection assay to measure NAbs in patient sera using a competitive ELISA assay. Serum samples from twenty-one patients were tested. Nine samples (42.8%) tested positive, and twelve (57.1%) tested negative for neutralizing sera. The data correlated with the result from the standard commercial assay that uses human ACE2 protein. This confirmed that p-deface2 mut could replace human ACE2 in ELISA assays. Using bacterially expressed p-deface2 mut protein is cost-effective and may allow mass SARS-CoV-2 NAbs detection, especially in low-income countries where economical diagnostic testing is crucial. Such information will help providers decide when a booster is required, reducing risks of reinfection and preventing the administration before it is medically necessary. [ABSTRACT FROM AUTHOR]

We study the distributed output‐feedback tracking control problem by linear sampled‐data control for nonlinear multi‐agent systems with unmeasurable states in this paper. Noting that sampled‐data control can effectively reduce implementation cost and time, we develop a novel linear sampled‐data high‐gain homogeneous domination control strategy by integrating backstepping method and high‐gain homogeneous domination method into sampled‐data control. A series of linear sampled‐data output‐feedback controllers and reduced‐order observers are designed to ensure that the output tracking errors can be tuned arbitrarily small while all states of the closed‐loop system are globally bounded. A numerical example is given to verify the effectiveness of the sampled‐data strategy. [ABSTRACT FROM AUTHOR]

This paper considers the distributed tracking control problem for a class of nonlinear multi-agent systems with nonlinearly parameterized control coefficients and inherent nonlinearities. The essential of multi-agent systems makes it difficult to directly generalize the existing works for single nonlinearly parameterized systems with uncontrollable unstable linearization to the case in this paper. To dominate the inherent nonlinearities and nonlinear parametric uncertainties, a powerful distributed adaptive tracking control is presented by combing the algebra graph theory with the distributed backstepping method, which guarantees that all the closed-loop system signals are global bounded while the range of the tracking error between the follower's output and the leader's output can be tuned arbitrarily small. Finally, a numerical example is provided to verify the validity of the developed methods.