Abstract: A reinforcement learning (RL) method for educational course selection includes the following steps: a) an action space and a state space are established, where actions of the action space represent actions associated with educational material and states of the state space represent learning states associated with a student; b) an action is selected from the action space; c) a next state is calculated based on the selected action and a current state; d) a reward is generated based on the current state and the next state; e) a Q-value is updated in a corresponding position in a Q-value table based on the reward; and f) the state is updated and the process returns to step b) when a final state is not reached, and an optimized action is output to the student when the final state is reached. The optimized action represents an educational course recommendation.

Abstract: The present invention relates to a dosage regime of a peptide analogues of [alpha]-melanocyte-stimulating hormone ([alpha]-MSH), which possesses an increased efficacy compared to the native [alpha]-MSH peptide in the treatment or prevention of kidney injury or disease.

Abstract: The present invention relates to a dosage regime of a peptide analogues of [alpha]-melanocyte-stimulating hormone ([alpha]-MSH), which possesses an increased efficacy compared to the native [alpha]-MSH peptide in the treatment or prevention of kidney injury or disease.

Abstract: The present invention relates to a dosage regime of a peptide analogues of [alpha]-melanocyte-stimulating hormone ([alpha]-MSH), which possesses an increased efficacy compared to the native [alpha]-MSH peptide in the treatment or prevention of kidney injury or disease.