The high-pressure behavior of CaMoO4

We report a high-pressure study of tetragonal scheelite-type CaMoO4 up to 29 GPa. In order to characterize its high-pressure behavior, we have combined Raman and optical-absorption measurements with density-functional theory calculations. We have found evidence of a pressure-induced phase transition near 15 GPa. Experiments and calculations agree in assigning the high-pressure phase to a monoclinic fergusonite-type structure. The reported results are consistent with previous powder x-ray-diffraction experiments, but are in contradiction with the conclusions obtained from earlier Raman measurements, which support the existence of more than one phase transition in the pressure range covered by our studies. The observed scheelite-fergusonite transition induces significant changes in the electronic band gap and phonon spectrum of CaMoO4. We have determined the pressure evolution of the band gap for the low- and high-pressure phases as well as the frequencies and pressure dependences of the Raman-active and infrared-active modes. In addition, based upon calculations of the phonon dispersion of the scheelite phase, carried out at a pressure higher than the transition pressure, we propose a possible mechanism for the reported phase transition. Furthermore, from the calculations we determined the pressure dependence of the unit-cell parameters and atomic positions of the different phases and their room-temperature equations of state. These results are compared with previous experiments showing a very good agreement. Finally, information on bond compressibility is reported and correlated with the macroscopic compressibility of CaMoO4. The reported results are of interest for the many technological applications of this oxide.Comment: 36 pages, 10 figures, 8 table

The electronic structure of zircon-type orthovanadates: Effects of high-pressure and cation substitution

The electronic structure of four ternary-metal oxides containing isolated vanadate ions is studied. Zircon-type YVO4, YbVO4, LuVO4, and NdVO4 are investigated by high-pressure optical-absorption measurements up to 20 GPa. First-principles calculations based on density-functional theory were also performed to analyze the electronic band structure as a function of pressure. The electronic structure near the Fermi level originates largely from molecular orbitals of the vanadate ion, but cation substitution influence these electronic states. The studied ortovanadates, with the exception of NdVO4, undergo a zircon-scheelite structural phase transition that causes a collapse of the band-gap energy. The pressure coefficient dEg/dP show positive values for the zircon phase and negative values for the scheelite phase. NdVO4 undergoes a zircon-monazite-scheelite structural sequence with two associated band-gap collapses.Comment: 35 pages, 11 figures, 2 Tables, 52 reference

An exploration strategy for non-stationary opponents

The success or failure of any learning algorithm is partially due to the exploration strategy it exerts. However, most exploration strategies assume that the environment is stationary and non-strategic. In this work we shed light on how to design exploration strategies in non-stationary and adversarial environments. Our proposed adversarial drift exploration (DE) is able to efficiently explore the state space while keeping track of regions of the environment that have changed. This proposed exploration is general enough to be applied in single agent non-stationary environments as well as in multiagent settings where the opponent changes its strategy in time. We use a two agent strategic interaction setting to test this new type of exploration, where the opponent switches between different behavioral patterns to emulate a non-deterministic, stochastic and adversarial environment. The agent’s objective is to learn a model of the opponent’s strategy to act optimally. Our contribution is twofold. First, we present DE as a strategy for switch detection. Second, we propose a new algorithm called R-max# for learning and planning against non-stationary opponent. To handle such opponents, R-max# reasons and acts in terms of two objectives: (1) to maximize utilities in the short term while learning and (2) eventually explore opponent behavioral changes. We provide theoretical results showing that R-max# is guaranteed to detect the opponent’s switch and learn a new model in terms of finite sample complexity. R-max# makes efficient use of exploration experiences, which results in rapid adaptation and efficient DE, to deal with the non-stationary nature of the opponent. We show experimentally how using DE outperforms the state of the art algorithms that were explicitly designed for modeling opponents (in terms average rewards) in two complimentary domains

The structure of a polyketide synthase bimodule core

Polyketide synthases (PKSs) are predominantly microbial biosynthetic enzymes. They assemble highly potent bioactive natural products from simple carboxylic acid precursors. The most versatile families of PKSs are organized as assembly lines of functional modules. Each module performs one round of precursor extension and optional modification, followed by directed transfer of the intermediate to the next module. While enzymatic domains and even modules of PKSs are well understood, the higher-order modular architecture of PKS assembly lines remains elusive. Here, we visualize a PKS bimodule core using cryo-electron microscopy and resolve a two-dimensional meshwork of the bimodule core formed by homotypic interactions between modules. The sheet-like organization provides the framework for efficient substrate transfer and for sequestration of trans-acting enzymes required for polyketide production

Efficiently detecting switches against non-stationary opponents

Interactions in multiagent systems are generally more complicated than single agent ones. Game theory provides solutions on how to act in multiagent scenarios; however, it assumes that all agents will act rationally. Moreover, some works also assume the opponent will use a stationary strategy. These assumptions usually do not hold in real world scenarios where agents have limited capacities and may deviate from a perfect rational response. Our goal is still to act optimally in these cases by learning the appropriate response and without any prior policies on how to act. Thus, we focus on the problem when another agent in the environment uses different stationary strategies over time. This will turn the problem into learning in a non-stationary environment, posing a problem for most learning algorithms. This paper introduces DriftER, an algorithm that (1) learns a model of the opponent, (2) uses that to obtain an optimal policy and then (3) determines when it must re-learn due to an opponent strategy change. We provide theoretical results showing that DriftER guarantees to detect switches with high probability. Also, we provide empirical results showing that our approach outperforms state of the art algorithms, in normal form games such as prisoner’s dilemma and then in a more realistic scenario, the Power TAC simulator

A memetic algorithm based on Artificial Bee Colony for optimal synthesis of mechanisms

En este documento se presenta una propuesta novedosa de un algoritmo híbrido modular, como herramienta para resolver problemas de ingeniería del mundo real. Se implementa y aplica un algoritmo memético, MemMABC, para la solución de dos casos de diseño de mecanismos, con el fin de evaluar su eficiencia y rendimiento. El algoritmo propuesto es simple y flexible debido a su modularidad; estas características lo vuelven altamente reutilizable para ser aplicado en una amplia gama de problemas de optimización. Las soluciones de los casos de estudio también son modulares, siguiendo un esquema de programación estructurada que incluye el uso de variables globales para la configuración, y de subrutinas para la función objetivo y el manejo de las restricciones. Los algoritmos meméticos son una buena opción para resolver problemas duros de optimización, debido a la sinergia derivada de la combinación de sus componentes: una metaheurística poblacional para búsqueda global y un método de refinamiento local. La calidad en los resultados de las simulaciones sugiere que el MemMABC puede aplicarse con éxito para la solución de problemas duros de diseño en ingeniería.In this paper a novel proposal of a modular hybrid algorithm as a tool for solving real-world engineering problems is presented. A memetic algorithm, MemMABC, is implemented with this approach and applied to solve two case studies of mechanism design, in order to evaluate its efficiency and performance. Because of its modularity, the proposed algorithm is simple and flexible; these features make it quite reusable to be applied on different optimization problems, with a wide scope. The solutions of the optimization problems are also modular, following a scheme of structured programming that includes the use of global variables for configuration, and subroutines for the objective function and the restrictions. Memetic algorithms are a good option to solve hard optimization problems, because of the synergy derived from the combination of their components: a global search population-based metaheuristic and a local refinement method. The quality of simulation results suggests that MemMABC can be successfully applied to solve hard problems in engineering design.Peer Reviewe

Acoustically driven arrayed waveguide grating

“© 2015 Optical Society of America. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modifications of the content of this paper are prohibited"We demonstrate compact tunable phased-array wavelength-division multiplexers driven by surface acoustic waves (SAWs) in the low GHz range. The devices comprise two couplers, which respectively split and combine the optical signal, linked by an array of single-mode waveguides (WGs). Two different layouts are presented, in which multi-mode interference couplers or free propagating regions were separately employed as couplers. The multiplexers operate on five equally distributed wavelength channels, with a spectral separation of 2 nm. A standing SAW modulates the refractive index of the arrayed WGs. Each wavelength component periodically switches paths between the output channel previously asigned by the design and the adjacent channels, at a fixed applied acoustic power. The devices were monolithically fabricated on (Al, Ga) As. A good agreement between theory and experiment is achieved.The authors thank W. Seidel, and S. Rauwerdink for preparation of the devices. This research has been supported by the international campus of excellence VLC/CAMPUS and by the program INNCIDE from the Spanish Ministry of Economy and Competitiveness (MINECO), through the program "Valoritza i Transfereix" from the Vice-Principal of Research and Scientific Policy of the Universitat de Valencia and through the program INNOVA (grant SP20120860) from the Universitat Politecnica de Valencia. Financial support by the Spanish MINECO Projects TEC2010-21337 and MAT2012-33483 is gratefully acknowledged. A. Crespo-Poveda and B. 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