Potential tuberculostatic agent: Micelle-forming pyrazinamide prodrug

Pyrazinamide was condensed with the poly(ethylene glycol)-poly(aspartic acid) copolymer (PEG-PASP), a micelle-forming derivative was obtained that was characterized in terms of its critical micelle concentration (CMC) and micelle diameter. The CMC was found by observing the solubility of Sudan III in Poly(ethylene glycol)-poly(pyrazinamidomethyl aspartate) copolymer (PEG-PASP-PZA) solutions. The mean diameter of PEG-PASP-PZA micelles, obtained by analyzing the dynamic light-scattering data, was 78.2 nm. The PEG-PASP-PZA derivative, when assayed for anti-Mycobacterium activity, exhibited stronger activity than the simple drug.

Spectrophotometric determination of ceftazidime in pharmaceutical preparations using neocuproin as a complexing agent

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Experience generalization for multi-agent reinforcement learning

On-line learning methods have been applied successfully in multi-agent systems to achieve coordination among agents. Learning in multi-agent systems implies in a non-stationary scenario perceived by the agents, since the behavior of other agents may change as they simultaneously learn how to improve their actions. Non-stationary scenarios can be modeled as Markov Games, which can be solved using the Minimax-Q algorithm a combination of Q-learning (a Reinforcement Learning (RL) algorithm which directly learns an optimal control policy) and the Minimax algorithm. However, finding optimal control policies using any RL algorithm (Q-learning and Minimax-Q included) can be very time consuming. Trying to improve the learning time of Q-learning, we considered the QS-algorithm. in which a single experience can update more than a single action value by using a spreading function. In this paper, we contribute a Minimax-QS algorithm which combines the Minimax-Q algorithm and the QS-algorithm. We conduct a series of empirical evaluation of the algorithm in a simplified simulator of the soccer domain. We show that even using a very simple domain-dependent spreading function, the performance of the learning algorithm can be improved.

Experimental and theoretical studies on the enhanced photoluminescence activity of zinc sulfide with a capping agent

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Direct and simultaneous spectrophotometric determination of Ni (II) and Co (II) using diethanoldithiocarbamate as complexing agent

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Multi-Agent Simulation of Urban Social Dynamics for Spatial Load Forecasting

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Attachment of 2,2-bipyridine onto a silica gel for application as a sequestering agent for copper, cadmium and lead ions from an aqueous medium

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)