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This paper proposes an adaptive fault-tolerant control strategy for a hybrid vertical take-off and landing (VTOL) unmanned aerial vehicle (UAV) to simultaneously compensate actuator faults and model uncertainties. With the proposed adaptive control schemes, both actuator faults and model uncertainties can be accommodated without the knowledge of fault information and uncertainty bounds. The proposed control scheme is constructed with two separate control modules. The low-level control allocation module is used to distribute the virtual control signals among the available redundant actuators. The high-level control module is constructed with an adaptive sliding mode controller, which is employed to maintain the overall system tracking performance in both faulty and uncertain conditions. In the case of actuator faults and model uncertainties, the adaptive scheme will be triggered to generate more virtual control signals to compensate the virtual control error and maintain the desired system tracking performance. The effectiveness of the proposed control strategy is validated through comparative simulation tests under different faulty and uncertain scenarios.

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Therapeutic tumor vaccines have attracted considerable attention in the past decade; they can induce tumor regression, eradicate minimal residual disease, establish lasting immune memory and avoid non-specific and adverse side effects. However, the challenge in the field of therapeutic tumor vaccines is ensuring the delivery of immune components to the lymph nodes (LNs) to activate immune cells. The clinical response rate of traditional therapeutic tumor vaccines falls short of expectations due to inadequate lymph node delivery. With the rapid development of nanotechnology, a large number of nanoplatform-based LN-targeting nanovaccines have been exploited for optimizing tumor immunotherapies. In addition, some nanovaccines possess non-invasive visualization performance, which is benefit for understanding the kinetics of nanovaccine exposure in LNs. Herein, we present the parameters of nanoplatforms, such as size, surface modification, shape, and deformability, which affect the LN-targeting functions of nanovaccines. The recent advances in nanoplatforms with different components promoting LN-targeting are also summarized. Furthermore, emerging LNs-targeting nanoplatform-mediated imaging strategies to both improve targeting performance and enhance the quality of LN imaging are discussed. Finally, we summarize the prospects and challenges of nanoplatform-based LN-targeting and /or imaging strategies, which optimize the clinical efficacy of nanovaccines in tumor immunotherapies.

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