King Abdullah

Nanostructured Metal Oxides Based Enzymatic Electrochemical Biosensors

Studies of nanobiosensors based on semiconductor nanostructured metal oxides are of practical and theoretical importance in biological science, environmental science and analytical chemistry (Wang et al., 2005; Luo et al., 2006; Valentini & Palleschi (2008); Chopra et al., 2007). These one-dimensional nanostructured metal oxides have profound applications in optics, optoelectronics, sensors, and actuators duo to their semiconducting, piezoelectric, and pyroelectric properties (Wang et al., 2005; Chopra et al., 2007; Kerman et al., 2008; Chow et al., 2005). Nanostructured metal oxides not only possesses high surface area, nontoxicity, good biocompatibility and chemical stability, but also shows fast electron communication features made the materials to be able to function as biomimetic membrane material to fix and modify proteins (Wang et al., 2005; Chopra et al., 2007; Valentini & Palleschi (2008)). These biomimetic and high electron communication features, high surface to volume ratio and electro-catalytic activity of the nanosized materials make them ideal as immobilization matrices, as transduction platform and/or mediators. Stability, sensitivity, selectivity and other analytical characteristics of biosensors are essential features to design desirable microenviroment for the direct electron transfer between the enzyme’s active sites and the electrode. To improve these characteristics various conventional materials matrices have been proposed. Among them nanostructured metal oxides matrices not only retain the bioactivity of the immobilized enzyme but also enhanced the sensing characteristics such as sensitivity, selectivity and low detection limit of the fabricated amperomatric enzymatic biosensors. Morphology of the nanosized material is one of the most ideally suited important factor to determine the properties for biosensor applications since they are conductive, biocompatible, easily functionalized while they have very large surface area. Nanosized metal oxides based electrochemical enzymatic biosensors have active surfaces that can easily be modified for immobilization of biomolecules. However, this advantage may not apply to many non-oxide semiconductor nanomaterials because their surfaces are not stable in an air environment, which leads to formation of an insulating native oxide layer and may degrade device reliability and sensitivity. Whereas, nanostructured metal oxides based electrochemical transducer surfaces promote the direct electron transfer reactions, amplify and orient the analytic signal of the biorecognition events. When a redox protein is immobilized on a biocompatible metal oxide electrode surface, it will exhibit reasonably fast electron transfer kinetic and permit the

A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation

ThisstudyevaluatesandcomparestheperformancesofseveralvariantsofthepopularensembleKalmanfilter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf of Mexico coastline, the authorsimplementandcomparethestandardstochasticensembleKalmanfilter(EnKF)andthreedeterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.

Forecasting the Aegean Sea hydrodynamics within the POSEIDON-II operational system

The development and first assessment of a high resolution eddy-resolving forecasting system for the Aegean Sea hydrodynamics, developed as part of the POSEIDON-II European Economic Area (EEA) Grants project and the European Coastal Sea Operational Observing and Forecasting (ECOOP) European Union (EU) project, is presented.The system uses an assimilation scheme based on a localized version of the Singular Evolutive Extended Kalman (SEEK) filter with partial evolution of its correction directions.The filter is used to correct the forecast state of a 1/30o Princeton Ocean Model (POM) of the Aegean Sea on a weekly basis. Data assimilation experiments are performed over a 12-month period to estimate the impact of observations insertion on the forecasting skill of the modelling system.The accuracy of the hydrodynamic state identification is assessed by the relevance of the assimilation system in fitting the data, and in forecasting future variability. The results of the assimilation system are also inter-compared with the forecasts estimated by an identical forecasting system that is re-initialized on a weekly basis from the basin wide MFS model analysis using a proper downscaling technique.

Spin-orbit-coupled transport and spin torque in a ferromagnetic heterostructure

Ferromagnetic heterostructures provide an ideal platform to explore the nature of spin-orbit torques arising from the interplay mediated by itinerant electrons between a Rashba-type spin-orbit coupling and a ferromagnetic exchange interaction. For such a prototypic system, we develop a set of coupled diffusion equations to describe the diffusive spin dynamics and spin-orbit torques. We characterize the spin torque and its two prominent--out-of-plane and in-plane--components for a wide range of relative strength between the Rashba coupling and ferromagnetic exchange. The symmetry and angular dependence of the spin torque emerging from our simple Rashba model is in an agreement with experiments. The spin diffusion equation can be generalized to incorporate dynamic effect such as spin pumping and magnetic damping.