Towards a new definition of EPOC parameters for anionic electrochemical catalysts: case of propene combustion

The electrochemical promotion of catalysis (EPOC) of propene combustion was investigated using Pt sputtered thin film on an O²⁻ conductor, 8 mol% Y₂O₃-stabilized-ZrO₂ (YSZ). In order to separate the influence of the thermal migration of the O²⁻ oxide ions from the electrolyte to the catalyst surface and the impact of an electrical polarization on the catalytic activity, several light-off experiments (cool down and heat up procedures) were successively performed under different polarizations, i.e. OCV, +2 and −2 V. These experiments have clearly shown that the presence of O²⁻ (thermally or electrochemically induced) inhibits the catalytic activity of the platinum for the propene deep oxidation. These results demonstrate the importance to define a normalized rate enhancement ratio, ρ _n , from a reference value of the catalytic rate corresponding to a Pt surface state free of O²⁻ ions.     

A strategy for the electro-organic synthesis of new hydrocaffeic acid derivatives

Electrochemical treatment processes can significantly contribute to the protection of the environment through the minimization of waste and toxic materials in effluents. From a pharmaceutical point of view and due to the existing resemblance between the electrochemical and biological reactions, it can be assumed that the oxidation mechanisms on the electrode and in the body share similar principles. In this paper, the application of electrochemical studies in the design of an environmentally friendly method was delineated for the new hydrocaffeic acid (HCA, 3,4-dihydroxy hydrocinnamic acid) derivatives synthesis at carbon electrodes in an undivided cell. In this cell, the EC mechanism reaction was involved, comprising two steps alternatively; (1) electrochemical oxidation and (2) chemical reaction. In particular, the electro-organic reactions of HCA, an important biological molecule, were studied in a water–acetonitrile (90:10 v/v) mixture in the presence of benzenesulfinic acid (3) and p-toluenesulfinic acid (4). The research included the use of a variety of experimental techniques, such as cyclic voltammetry, controlled-potential electrolysis and product spectroscopic identification.     

NiCoFe/C cathode electrocatalysts for direct ethanol fuel cells

A direct ethanol fuel cell (DEFC), which is less prone to ethanol crossover, is reported. The cell consists of PtRu/C catalyst as the anode, Nafion^® 117 membrane, and Ni–Co–Fe (NCF) composite catalyst as the cathode. The NCF catalyst was synthesized by mixing Ni, Co, and Fe complexes into a polymer matrix (melamine-formaldehyde resins), followed by heating the mixture at 800 °C under inert atmosphere. TEM and EDX experiments suggest that the NCF catalyst has alloy structures of Ni, Co and Fe. The catalytic activity of the NCF catalyst for the oxygen reduction reaction (ORR) was compared with that of commercially available Pt/C (CAP) catalyst at different ethanol concentrations. The decrease in open circuit voltage (V_oc) of the DEFC equipped with the NCF catalysts was less than that of CAP catalyst at higher ethanol concentrations. The NCF catalyst was less prone to ethanol oxidation at cathode even when ethanol crossover occurred through the Nafion^®117 film, which prevents voltage drop at the cathode. However, the CAP catalyst did oxidize ethanol at the cathode and caused a decrease in voltage at higher ethanol concentrations.     

Passivity Analysis of Dynamic Neural Networks with Different Time-scales

Dynamic neural networks with different time-scales include the aspects of fast and slow phenomenons. Some applications require that the equilibrium points of the designed networks are stable. In this paper, the passivity-based approach is used to derive stability conditions for dynamic neural networks with different time-scales. Several stability properties, such as passivity, asymptotic stability, input-to-state stability and bounded input bounded output stability, are guaranteed in certain senses. A numerical example is also given to demonstrate the effectiveness of the theoretical results.     

Improving Neural Networks for Mechanism Kinematic Chain Isomorphism Identification

Detection of isomorphism among kinematic chains is essential in mechanical design, but difficult and computationally expensive. It has been shown that both traditional methods and previously presented neural networks still have a lot to be desired in aspects such as simplifying procedure of identification and adapting automatic computation. Therefore, a new algorithm based on a competitive Hopfield network is developed for automatic computation in the kinematic chain isomorphism problem. The neural approach provides directly interpretable solutions and does not demand tuning of parameters. We have tested the algorithm by solving problems reported in the recent mechanical literature. Simulation results show the effectiveness of the network that rapidly identifies isomorphic kinematic chains.     

Fast and accurate pricing of discretely monitored barrier options by numerical path integration

Barrier options are financial derivative contracts that are activated or deactivated according to the crossing of specified barriers by an underlying asset price. Exact models for pricing barrier options assume continuous monitoring of the underlying dynamics, usually a stock price. Barrier options in traded markets, however, nearly always assume less frequent observation, e.g. daily or weekly. These situations require approximate solutions to the pricing problem. We present a new approach to pricing such discretely monitored barrier options that may be applied in many realistic situations. In particular, we study daily monitored up-and-out call options of the European type with a single underlying stock. The approach is based on numerical approximation of the transition probability density associated with the stochastic differential equation describing the stock price dynamics, and provides accurate results in less than one second whenever a contract expires in a year or less. The flexibility of the method permits more complex underlying dynamics than the Black and Scholes paradigm, and its relative simplicity renders it quite easy to implement.     

Brokers and bricoleurs: entrepreneurship in Wales' online music scene

 The power of some new entrants to the music industry derives from their position as brokers in computer-mediated environments. Brokers act instrumentally to exploit their position within a network which, in turn, depends on their ability to build and sustain links (and, in computer-mediated environments, hyperlinks). Bricolage in computer-mediated entrepreneurship refers to the intuitive manipulation of resources in order to achieve (perhaps tacit) goals. Without careful stewardship of the new intellectual wealth thus created, bricolage may profit neither the individual nor the wider community. Accepted 14 March 2002     

Two topographic maps for data visualisation

We review a new form of self-organizing map which is based on a nonlinear projection of latent points into data space, identical to that performed in the Generative Topographic Mapping (GTM) [Bishop et al. (1997) Neurl Comput 10(1): 215–234]. But whereas the GTM is an extension of a mixture of experts, our new model is an extension of a product of experts [Hinton (2000) Technical report GCNU TR 2000-004, Gatsby Computational Neuroscience Unit, University College, London]. We show visualisation results on some real data sets and compare with the GTM. We then introduce a second mapping based on harmonic averages and show that it too creates a topographic mapping of the data. We compare these mappings on real and artificial data sets. Responsible editor: Soumen Chakrabarti.