Temperature dependence of femtosecond laser induced refractive index change in Nd3+-doped phosphate glass

We report refractive index change in a femtosecond laser irradiated Nd3+-doped phosphate glass. The effects of annealing temperature on the refractive index change of the glass have been investigated. Absorption spectra of the glass sample before and after femtosecond laser irradiation and subsequent annealing were measured. The results indicate that multiphoton absorption can undertake although there are intrinsic absorption for the glass in irradiation wavelength. The results may be useful for fabrication of three-dimensional integrated optics devices and waveguide laser devices in this glass. (c) 2004 Elsevier B.V. All rights reserved.

Preparation and spectroscopic properties of Er3+-doped high silica glass fabricated by sintering nanoporous glass

A compact nonporous high silica (SiO2 % > 96%) glass containing 3400 ppm Er3+ ions, which was about ten times higher than that in Er-doped silica fiber amplifier (EDSFA), was synthesized by sintering porous glass immersed into erbium nitrate solution. The 1532 nm fluorescence has a FWHM (Full Width at Half Maximum) of 45 nm wider than that of EDSFA and possesses the glass with potential application in broadband fiber amplifiers. The Judd-Ofelt theoretical analysis reflects that Er3+ ions are located in a higher covalent environment which are comparable to those of aluminosilicate glass. (c) 2005 Elsevier B.V. All rights reserved.

Integrated assessment of environmental pollution using diverse sentinel organisms within Basque marine environments

294 p.

Systematic and evolutionary studies of the terrestrial gastropods Helicoidea and Pyramidula

178 p.

Learning Multirobot Hose Transportation and Deployment by Distributed Round-Robin Q-Learning

Multi-Agent Reinforcement Learning (MARL) algorithms face two main difficulties: the curse of dimensionality, and environment non-stationarity due to the independent learning processes carried out by the agents concurrently. In this paper we formalize and prove the convergence of a Distributed Round Robin Q-learning (D-RR-QL) algorithm for cooperative systems. The computational complexity of this algorithm increases linearly with the number of agents. Moreover, it eliminates environment non sta tionarity by carrying a round-robin scheduling of the action selection and execution. That this learning scheme allows the implementation of Modular State-Action Vetoes (MSAV) in cooperative multi-agent systems, which speeds up learning convergence in over-constrained systems by vetoing state-action pairs which lead to undesired termination states (UTS) in the relevant state-action subspace. Each agent's local state-action value function learning is an independent process, including the MSAV policies. Coordination of locally optimal policies to obtain the global optimal joint policy is achieved by a greedy selection procedure using message passing. We show that D-RR-QL improves over state-of-the-art approaches, such as Distributed Q-Learning, Team Q-Learning and Coordinated Reinforcement Learning in a paradigmatic Linked Multi-Component Robotic System (L-MCRS) control problem: the hose transportation task. L-MCRS are over-constrained systems with many UTS induced by the interaction of the passive linking element and the active mobile robots.

Cellular and molecular responses of zebrafish to legacy and emerging pollutants: the specific cases of PAHs and metal oxide nanoparticles

270 p.