Preservation of catechin antioxidant properties loaded in carbohydrate nanoparticles

Epigallocatechin gallate (EGCG), an antioxidant with several pharmacological and biological activities, was encapsulated in carbohydrate particles to preserve its antioxidant properties and improve its bioavailability. Gum arabic–maltodextrin particles loaded with EGCG (EGCG/P) were successfully produced by homogenization and spray-drying, with an EGCG loading efficiency of 96 ± 3%. Spray-dried particles are spherical or corrugated and polydisperse with diameters less than 20 m. The particles in aqueous suspension revealed two main populations, with mean average diameters of 40 nm and 400 nm. Attenuated total reflection-infrared spectroscopy (ATR-IR) confirmed that EGCG was incorporated in the carbohydrate matrix by intermolecular interactions, maintaining its chemical integrity. Atomic force microscopy imaging proved the particle spherical shape and size. The present study demonstrates that the carbohydrate matrix is able to preserve EGCG antioxidant properties, as proof of concept to be used as polymeric drug carrier.

Reinforcement Learning Based on the Bayesian Theorem for Electricity Markets Decision Support

This paper presents the applicability of a reinforcement learning algorithm based on the application of the Bayesian theorem of probability. The proposed reinforcement learning algorithm is an advantageous and indispensable tool for ALBidS (Adaptive Learning strategic Bidding System), a multi-agent system that has the purpose of providing decision support to electricity market negotiating players. ALBidS uses a set of different strategies for providing decision support to market players. These strategies are used accordingly to their probability of success for each different context. The approach proposed in this paper uses a Bayesian network for deciding the most probably successful action at each time, depending on past events. The performance of the proposed methodology is tested using electricity market simulations in MASCEM (Multi-Agent Simulator of Competitive Electricity Markets). MASCEM provides the means for simulating a real electricity market environment, based on real data from real electricity market operators.