Bromate removal from drinking water by semiconductor photocatalysis

The semiconductor photocatalyst, platinised titanium dioxide, Pt/TiO2, is used to promote the destruction of bromate ions to bromide and oxygen by 254 nm ultraviolet light. The kinetics of bromate removal are first order with respect to [BrO3-] and are inhibited, although not completely, by competitive adsorption by other anions, including bromide and sulfate ions. The Pt/TiO2 can be used not only as a powder dispersion, but also as a thin film in a flow reactor for the destruction of bromate ions. Copyright (C) 1996 Elsevier Science Ltd

The removal of bromate from potable water using granular activated carbon

Bromate in drinking water, at a level of microgrammes/litre, is a problem in ozonated waters but can be adsorbed, to a certain extent, by granular activated carbon. The adsorption capacity of granular activated carbon for bromate is significantly lowered when there are high concentrations of other anions, most notably chloride and sulphate, present in the water.

Hänsch--Couillaud locking of Mach--Zehnder interferometer for carrier removal from a phase-modulated optical spectrum

We describe and analyse the operation and stabilization of a Mach--Zehnder interferometer, which separates the carrier and the first-order sidebands of a phase-modulated laser field, and which is locked using the H\"ansch--Couillaud method. In addition to the necessary attenuation, our interferometer introduces, via total internal reflection, a significant polarization-dependent phase delay. We employ a general treatment to describe an interferometer with an object which affects the field along one path, and we examine how this phase delay affects the error signal. We discuss the requirements necessary to ensure the lock point remains unchanged when phase modulation is introduced, and we demonstrate and characterize this locking experimentally. Finally, we suggest an extension to this locking strategy using heterodyne detection.

Methodology for Validating Artifact Removal Techniques for Physiological Signals

Artifact removal from physiological signals is an essential component of the biosignal processing pipeline. The need for powerful and robust methods for this process has become particularly acute as healthcare technology deployment undergoes transition from the current hospital-centric setting toward a wearable and ubiquitous monitoring environment. Currently, determining the relative efficacy and performance of the multiple artifact removal techniques available on real world data can be problematic, due to incomplete information on the uncorrupted desired signal. The majority of techniques are presently evaluated using simulated data, and therefore, the quality of the conclusions is contingent on the fidelity of the model used. Consequently, in the biomedical signal processing community, there is considerable focus on the generation and validation of appropriate signal models for use in artifact suppression. Most approaches rely on mathematical models which capture suitable approximations to the signal dynamics or underlying physiology and, therefore, introduce some uncertainty to subsequent predictions of algorithm performance. This paper describes a more empirical approach to the modeling of the desired signal that we demonstrate for functional brain monitoring tasks which allows for the procurement of a ground truth signal which is highly correlated to a true desired signal that has been contaminated with artifacts. The availability of this ground truth, together with the corrupted signal, can then aid in determining the efficacy of selected artifact removal techniques. A number of commonly implemented artifact removal techniques were evaluated using the described methodology to validate the proposed novel test platform. © 2012 IEEE.