Electronic and magnetic properties of Ti(2)O(3), Cr(2)O(3), and Fe(2)O(3) calculated by the screened exchange hybrid density functional.

The electronic and magnetic properties of the transition metal sesqui-oxides Cr(2)O(3), Ti(2)O(3), and Fe(2)O(3) have been calculated using the screened exchange (sX) hybrid density functional. This functional is found to give a band structure, bandgap, and magnetic moment in better agreement with experiment than the local density approximation (LDA) or the LDA+U methods. Ti(2)O(3) is found to be a spin-paired insulator with a bandgap of 0.22 eV in the Ti d orbitals. Cr(2)O(3) in its anti-ferromagnetic phase is an intermediate charge transfer Mott-Hubbard insulator with an indirect bandgap of 3.31 eV. Fe(2)O(3), with anti-ferromagnetic order, is found to be a wide bandgap charge transfer semiconductor with a 2.41 eV gap. Interestingly sX outperforms the HSE functional for the bandgaps of these oxides.

Calculation of metallic and insulating phases of V2O3 by hybrid density functionals.

The electronic structure of vanadium sesquioxide V2O3 in its different phases has been calculated using the screened exchange hybrid density functional. The hybrid functional accurately reproduces the experimental electronic properties of all three phases, the paramagnetic metal (PM) phase, the anti-ferromagnetic insulating phase, and the Cr-doped paramagnetic insulating (PI) phase. We find that a fully relaxed supercell model of the Cr-doped PI phase based on the corundum structure has a monoclinic-like local strain around the substitutional Cr atoms. This is found to drive the PI-PM transition, consistent with a Peierls-Mott transition. The PI phase has a calculated band gap of 0.15 eV, in good agreement with experiment.

Anti-counterfeiting and supply chain security

Counterfeit trade developed into a severe problem for many industries. While established security features such as holograms, micro printings or chemical markers do not seem to efficiently avert trade in illicit imitation products, RFID technology, with its potential to automate product authentications, may become a powerful tool to enhance brand and product protection. The following contribution contains an overview on the implication of product counterfeiting on affected companies, provides a starting point for a structured requirements definition for RFID-based anti-counterfeiting systems, and outlines several principal solution approaches that are discussed in greater detail in the subsequent chapters. © 2008 Springer-Verlag Berlin Heidelberg.

Addition of ferromagnetic CoFe2O4 to YBCO thin films for enhanced flux pinning

An attempt has been made to prepare a YBa2Cu3O 7-δ (YBCO) thin film doped with ferromagnetic CoFe 2O4. Transmission electron microscopy of the resultant samples shows, however, that Y(Fe, Co)O3 forms as a nanoparticulate dispersion throughout the film in preference to CoFe2O4, leaving the YBCO yttrium deficient. As a consequence, the superconducting properties of the sample are poor, with a self-field critical current density of just 0.25 MA cm-2. Magnetic measurements indicate however that the Y(Fe, Co)O3 content, together with any other residual phases, is also ferromagnetic, and some interesting features are present in the in-field critical current behaviour, including a reduced dependence on applied field and a strong c-axis peak in the angular dependence. The work points the way towards future attempts utilising YFeO3 as an effective ferromagnetic pinning additive for YBCO. © 2009 Elsevier B.V. All rights reserved.

Bayesian model selection for time series using Markov chain Monte Carlo

We present a stochastic simulation technique for subset selection in time series models, based on the use of indicator variables with the Gibbs sampler within a hierarchical Bayesian framework. As an example, the method is applied to the selection of subset linear AR models, in which only significant lags are included. Joint sampling of the indicators and parameters is found to speed convergence. We discuss the possibility of model mixing where the model is not well determined by the data, and the extension of the approach to include non-linear model terms.

The design of an agent for modelling supply chain network dynamics

A useful insight into managerial decision making can be found from simulation of business systems, but existing work on simulation of supply chain behaviour has largely considered non-competitive chains. Where competitive agents have been examined, they have generally had a simple structure and been used for fundamental examination of stability and equilibria rather than providing practical guidance to managers. In this paper, a new agent for the study of competitive supply chain network dynamics is proposed. The novel features of the agent include the ability to select between competing vendors, distribute orders preferentially among many customers, manage production and inventory, and determine price based on competitive behaviour. The structure of the agent is related to existing business models and sufficient details are provided to allow implementation. The agent is tested to demonstrate that it recreates the main results of the existing modelling and management literature on supply chain dynamics. A brief exploration of competitive dynamics is given to confirm that the proposed agent can respond to competition. The results demonstrate that overall profitability for a supply chain network is maximised when businesses operate collectively. It is possible for an individual business to achieve higher profits by adopting a more competitive stance, but the consequence of this is that the overall profitability of the network is reduced. The agent will be of use for a broad range of studies on the long-run effect of management decisions on their network of suppliers and customers.

Direct parameter extraction in capacitively transduced micromechanical resonators using the anti-resonance

This paper presents a method for the fast and direct extraction of model parameters for capacitive MEMS resonators from their measured transmission response such as quality factor, resonant frequency, and motional resistance. We show that these parameters may be extracted without having to first de-embed the resonator motional current from the feedthrough. The series and parallel resonances from the measured electrical transmission are used to determine the MEMS resonator circuit parameters. The theoretical basis for the method is elucidated by using both the Nyquist and susceptance frequency response plots, and applicable in the limit where CF > CmQ; commonly the case when characterizing MEMS resonators at RF. The method is then applied to the measured electrical transmission for capacitively transduced MEMS resonators, and compared against parameters obtained using a Lorentzian fit to the measured response. Close agreement between the two methods is reported herein. © 2010 IEEE.