Engineering Journal: Volume-10, Issue-1, January, 2024

Abstract— Cancer is a great threat to the health of all mankind, and cancer monotherapy has been characterized by drawbacks such as toxicity and drug resistance. With the development of network pharmacology, multi-targeted drug combinations have become an ideal choice for cancer treatment. The dosage of combination drugs is usually lower than that of monotherapies, which has the advantages of improving efficacy, reducing toxicity, and delaying the development of drug resistance. In order to obtain better prediction results, this paper proposes a method for constructing drug potential features based on graph embedding model to predict anticancer drug combinations, establishes a control group to validate our method, and selects four performance metrics to measure the prediction performance of the model. The results show that the prediction results obtained from the drug potential features are better than the drug features. The drug potential features we designed can be used as one of the optional features for predicting drug combinations.

Abstract— High accuracy and stability are generally indispensable in industrial control applications of servomechanism. Many unavoidable factors negatively influence the control performance, such as modeling uncertainties. Therefore, this investigation is concerned with the disturbance compensation for the reduction of modeling uncertainty and proposes an adaptive open-loop observer in which the output of the actual plant can asymptotically converge to the output of the nominal plant by using the adaptive gain adjustment. The gain is bounded through the projection-type adaptive law. Furthermore, the backstepping algorithm enhances the robustness for the disturbance attenuation. Additionally, the velocity control of a motor is simulated to confirm the performance of the proposed approach, and the experiments of trajectory tracking on a two-link rotor manipulator is used to verify the ability of the proposed approach.