High-intensity interval training has the potential to induce favorable physiological remodeling similar or superior to moderate-intensity continuous training in metabolic diseases, despite lower exercise volume.
Does high-intensity interval training improve physiological adaptations and health outcomes in individuals with metabolic type diseases compared to moderate-intensity continuous training?
HIIT is a promising, time-efficient alternative to MICT for managing metabolic diseases, though optimal prescriptive variables and safety for clinical populations require further investigation.
Wireless sensor networks have become incredibly popular due to the Internet of Things' (IoT) rapid development. IoT routing is the basis for the efficient operation of the perception-layer network. As a popular type of machine learning, reinforcement learning techniques have gained significant attention due to their successful application in the field of network communication. In the traditional Routing Protocol for lowpower and Lossy Networks (RPL) protocol, to solve the fairness of control message transmission between IoT terminals, a fair broadcast suppression mechanism, or Drizzle algorithm, is usually used, but the Drizzle algorithm cannot allocate priority. Moreover, the Drizzle algorithm keeps changing its redundant constant k value but never converges to the optimal value of k. To address this problem, this paper uses a combination based on reinforcement learning (RL) and trickle timer. This paper proposes an RL Intelligent Adaptive Trickle-Timer Algorithm (RLATT) for routing optimization of the IoT awareness layer. RLATT has triple-optimized the trickle timer algorithm. To verify the algorithm's effectiveness, the simulation is carried out on Contiki operating system and compared with the standard trickling timer and Drizzle algorithm. Experiments show that the proposed algorithm performs better in terms of packet delivery ratio (PDR), power consumption, network convergence time, and total control cost ratio.
Stephen Pearson (Wed,) conducted a review in Metabolic type disease (Obesity, Type 2 Diabetes, Metabolic Syndrome). High-intensity interval training (HIIT) vs. Moderate-intensity continuous training (MICT) was evaluated. High-intensity interval training has the potential to induce favorable physiological remodeling similar or superior to moderate-intensity continuous training in metabolic diseases, despite lower exercise volume.