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.

Alternative method for producing organic fertiliser from anaerobic digestion liquor and limestone powder:High Shear wet granulation

Generally, the solid and liquid fractions (digestate) from Anaerobic Digestion (AD) energy production are considered as waste. This has a negative impact on the sustainability of AD processes because of the financial outlay required to treat digestate before being discharged into municipal water treatment plants or natural water bodies. The main aim of this research was to investigate feasibility of producing an organic fertiliser using anaerobic digestate and limestone powders as the raw materials employing a high shear granulation process. Two-level factorial experimental design was used to determine the influence of granulation process variables on, the strength, resistance to attrition and yield of the granules. It was concluded from the study that it is technically feasible to produce organic fertiliser granules of acceptable strength and product yield. Increasing the liquid-to-solid ratio during granulation leads to increased granule strength and better product yield. Although the strength of the granules produced was lower than typical strength of commercial synthetic fertiliser granules (about 5 to 7. MPa), this could be improved by mixing the digestate with a polymeric binder or coating the particles post granulation. © 2012 Elsevier B.V.

Microwave-assisted Cu-catalyzed Ullmann ether synthesis in a continuous-flow milli-plant

The combination of milli-scale processing and microwave heating has been investigated for the Cu-catalyzed Ullmann etherification in fine-chemical synthesis, providing improved catalytic activity and selective catalyst heating. Wall-coated and fixed-bed milli-reactors were designed and applied in the Cu-catalyzed Ullmann-type CO coupling of phenol and 4-chloropyridine. In a batch reactor the results show clearly increased yields for the microwave heated process at low microwave powers, whereas high powers and catalyst loadings reduced the benefits of microwave heating. Slightly higher yields were found in the Cu/ZnO wall-coated as compared to the Cu/TiO fixed-bed flow-reactor. The benefit here is that the reaction occurs at the surface of the metal nanoparticles confined within a support film making the nano-copper equally accessible. Catalyst deactivation was mainly caused by Cu oxidation and coke formation; however, at longer process times leaching played a significant role. Catalyst activity could partially be recovered by removal of deposited by-product by means of calcination. After 6h on-stream the reactor productivities were 28.3 and 55.1kgprod/(mR3h) for the fresh Cu/ZnO wall-coated and Cu/TiO fixed-bed reactor, respectively. Comparison of single- and multimode microwaves showed a threefold yield increase for single-mode microwaves. Control of nanoparticles size and loading allows to avoid high temperatures in a single-mode microwave field and provides a novel solution to a major problem for combining metal catalysis and microwave heating. Catalyst stability appeared to be more important and provided twofold yield increase for the CuZn/TiO catalyst as compared to the Cu/TiO catalyst due to stabilized copper by preferential oxidation of the zinc. For this catalyst a threefold yield increase was observed in single-mode microwaves which, to the best of our knowledge, led to a not yet reported productivity of 172kgprod/(mR3h) for the microwave and flow Ullmann CO coupling. © 2012 Elsevier B.V.

Deactivation mechanism of a Au/CeZrO4 catalyst during a low-temperature water gas shift reaction

On-stream deactivation during a water gas shift (WGS) reaction over gold supported on a ceria-zirconia catalyst was examined. Although the fresh catalyst has very high low temperature (<200 degrees C) for WGS activity, a significant loss of CO conversion is found under steady-state operations over hours. This has been shown to be directly related to the concentration of water in the gas phase. The same catalyst also undergoes thermal deactivation above 250 degrees C, and using a combined experimental and theoretical approach, a common deactivation mechanism is proposed. In both cases, the gold nanoparticles, which are found under reaction conditions, are thought to detach from the oxide support either through hydrolysis, <200 degrees C, or thermally, > 200 degrees C. This process reduces the metal-support interaction, which is considered to be critical in determining the high activity of the catalyst.

Catalyst distribution and carbon nanotube morphology in multilayer forests by mixed CVD processes

Carbon nanotubes can be grown as forests of aligned fibers on a substrate with a catalyst coated prior to or added during synthesis. A major process interruption can initiate the growth of second and successive layers of forest on top or at the base of the existing layers which are thereby lifted up. We report on the generation of multilayer CNT forests where the first forest is generated either by catalyst coinjection (CCI) of ferrocene with hydrocarbon (xylene) or by catalyst predeposition (CPD) of iron followed with hydrocarbon (acetylene). Subsequent layers are then produced by CCI alone to give uniform (all CCI) or mixed (CPD and CCI) structures to study the distribution of the iron catalyst and CNT morphology and to determine whether the CPD forest templates or otherwise influences the growth of subsequent CCI forests. The bottom-up base growth of second and subsequent CCI forests is reaction rate controlled. CCI multilayer forests accumulate catalyst (iron) in a variety of distinct locations. A pre-existing CPD forest modifies subsequent CCI forest initiation, morphology, and catalyst distribution but does not itself accumulate catalyst or change appearance. © 2009 American Chemical Society.

Arsenic removal from soil with high iron content using a natural surfactant and phosphate

An environment friendly arsenic removal technique from contaminated soil with high iron content has been studied. A natural surfactant extracted from soapnut fruit, phosphate solution and their mixture was used separately as extractants. The mixture was most effective in desorbing arsenic, attaining above 70 % efficiency in the pH range of 4–5. Desorption kinetics followed Elovich model. Micellar solubilization by soapnut and arsenic exchange mechanism by phosphate are the probable mechanisms behind arsenic desorption. Sequential extraction reveals that the mixed soapnut–phosphate system is effective in desorbing arsenic associated with amphoteric–Fe-oxide forms. No chemical change to the wash solutions was observed by Fourier transform-infrared spectra. Soil:solution ratio, surfactant and phosphate concentrations were found to affect the arsenic desorption process. Addition of phosphate boosted the performance of soapnut solution considerably. Response surface methodology approach predicted up to 80 % desorption of arsenic from soil when treated with a mixture of ≈1.5 % soapnut, ≈100 mM phosphate at a soil:solution ratio of 1:30.

Ambient Temperature Hydrocarbon Selective Catalytic Reduction of NOx Using Atmospheric Pressure Nonthermal Plasma Activation of a Ag/Al2O3 Catalyst

Atmospheric pressure nonthermal-plasma-activated catalysis for the removal of NOx using hydrocarbon selective catalytic reduction has been studied utilizing toluene and n-octane as the hydrocarbon reductant. When the plasma was combined with a Ag/Al2O3 catalyst, a strong enhancement in activity was observed when compared with conventional thermal activation with high conversions of both. NOx and hydrocarbons obtained at temperature at temperature ≤250 °C, where the silver catalyst is normally inactive. Importantly, even in the absence of an external heat source, significant activity was obtained. This low temperature activity provides the basis for applying nonthermal plasmas to activate emission control catalysts during cold start conditions, which remains an important issue for mobile and stationary applications.

Adsorption Study using Optimised 3D Organised Mesoporous Silica Coated with Fe and Al Oxides for Specific As(III) and As(V) Removal from Contaminated Synthetic Groundwater

This work presents the possibility of optimising 3D Organised Mesoporous Silica (OMS) coated with both iron and aluminium oxides for the optimal removal of As(III) and As(V) from synthetic contaminated water. The materials developed were fully characterised and were tested for removing arsenic in batch experiments. The effect of total Al to Fe oxides coating on the selective removal of As(III) and As(V) was studied. It was shown that 8% metal coating was the optimal configuration for the coated OMS materials in removing arsenic. The effect of arsenic initial concentration and pH, kinetics and diffusion mechanisms was studied, modelled and discussed. It was shown that the advantage of an organised material over an un-structured sorbent was very limited in terms of kinetic and diffusion under the experimental conditions. It was shown that physisorption was the main adsorption process involved in As removal by the coated OMS. Maximum adsorption capacity of 55 mg As(V).g-1 was noticed at pH 5 for material coated with 8% Al oxides while 35 mg As(V).g-1 was removed at pH 4 for equivalent material coated with Fe oxides.

Performance Evaluation of Two-Stage Electrokinetic Washing as Soil Remediation Method for Lead Removal using Different Wash Solutions

The study explores the application of a two-stage electrokinetic washing system on remediation of lead (Pb) contaminated soil. The process involved an initial soil washing, followed by an electrokinetic process. The use of electrokinetic process in soil washing not only provided additional driving force for transporting the desorbed Pb away from the soil but also reduced the high usage of wash solution. In this study, the effect of NaNO3, HNO3, citric acid and EDTA as wash solutions on two-stage electrokinetic washing system were evaluated. The results revealed that a two-stage electrokinetic washing process enhanced Pb removal efficiency by 2.52-9.08% and 4.98-20.45% in comparison to a normal electrokinetic process and normal washing process, respectively. Low pH and adequate current were the most important criteria in the removal process as they provided superior desorption and transport properties. The effect of chelating by EDTA was less dominant as it delayed the removal process by forming a transport loop in anode region between Pb ion and complexes. HNO3 was not suitable as wash solution in electrokinetic washing in spite of offering highest removal efficiency as it caused pH fluctuation in the cathode chamber, corroded graphite anode and showed high power consumption. In contrast, citric acid not only yielded high Pb removal efficiency with low power consumption but also maintained a low soil: solution ratio of 1 g: <1 mL, stable pH and electrode integrity. Possible transport mechanisms for Pb under each wash solution are also discussed in this work.

Optimisation of Kinetic Parameters for an After-treatment Catalyst

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. 
Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved. The reaction rate sub-model uses global reaction kinetics to describe the surface reaction rate of the gas species and is based on the Langmuir Hinshelwood equation further developed by Voltz et al. [1] The reactions can be modelled using the pre-exponential and activation energies of the Arrhenius equations and the inhibition terms. 
The reaction kinetic parameters of aftertreatment models are found from experimental data, where a measured light-off curve is compared against a predicted curve produced by a mathematical model. The kinetic parameters are usually manually tuned to minimize the error between the measured and predicted data. This process is most commonly long, laborious and prone to misinterpretation due to the large number of parameters and the risk of multiple sets of parameters giving acceptable fits. Moreover, the number of coefficients increases greatly with the number of reactions. Therefore, with the growing number of reactions, the task of manually tuning the coefficients is becoming increasingly challenging. 
In the presented work, the authors have developed and implemented a multi-objective genetic algorithm to automatically optimize reaction parameters in AxiSuite®, [2] a commercial aftertreatment model. The genetic algorithm was developed and expanded from the code presented by Michalewicz et al. [3] and was linked to AxiSuite using the Simulink add-on for Matlab. 
The default kinetic values stored within the AxiSuite model were used to generate a series of light-off curves under rich conditions for a number of gas species, including CO, NO, C_{3H8 and C3H6. These light-off curves were used to generate an objective function.} 
This objective function was used to generate a measure of fit for the kinetic parameters. The multi-objective genetic algorithm was subsequently used to search between specified limits to attempt to match the objective function. In total the pre-exponential factors and activation energies of ten reactions were simultaneously optimized. 
The results reported here demonstrate that, given accurate experimental data, the optimization algorithm is successful and robust in defining the correct kinetic parameters of a global kinetic model describing aftertreatment processes.

Experimental design and batch experiments for optimization of Cr(VI) removal from aqueous solutions by hydrous cerium oxide nanoparticles

Hydrous cerium oxide (HCO) was synthesized by intercalation of solutions of cerium(III) nitrate and sodium hydroxide and evaluated as an adsorbent for the removal of hexavalent chromium from aqueous solutions. Simple batch experiments and a 2⁵ factorial experimental design were employed to screen the variables affecting Cr(VI) removal efficiency. The effects of the process variables; solution pH, initial Cr(VI) concentration, temperature, adsorbent dose and ionic strength were examined. Using the experimental results, a linear mathematical model representing the influence of the different variables and their interactions was obtained. Analysis of variance (ANOVA) demonstrated that Cr(VI) adsorption significantly increases with decreased solution pH, initial concentration and amount of adsorbent used (dose), but slightly decreased with an increase in temperature and ionic strength. The optimization study indicates 99% as the maximum removal at pH 2, 20 °C, 1.923 mM of metal concentration and a sorbent dose of 4 g/dm³. At these optimal conditions, Langmuir, Freundlich and Redlich–Peterson isotherm models were obtained. The maximum adsorption capacity of Cr(VI) adsorbed by HCO was 0.828 mmol/g, calculated by the Langmuir isotherm model. Desorption of chromium indicated that the HCO adsorbent can be regenerated using NaOH solution 0.1 M (up to 85%). The adsorption interactions between the surface sites of HCO and the Cr(VI) ions were found to be a combined effect of both anion exchange and surface complexation with the formation of an inner-sphere complex.

The Application of Semiconductor Photocatalysis for the Removal of Cyanotoxins from Water and Design Concepts for Solar Photocatalytic Reactors for Large Scale Water Treatment

There has been a significant increase in the occurrence of cyanobacterial blooms in freshwaters over the past few decades due to escalating nutrient levels. These cyanobacteria release a range of toxins, for example microcystins which are chemically very stable. Many cyanotoxins are consequently very difficult to remove from water using existing treatment technologies. Semiconductor photocatalysis, however, has proven to be a very effective process for the removal of these compounds from water. In this chapter we consider the application of this highly versatile and exciting technology for the decomposition of cyanotoxins. Furthermore design concepts for solar photocatalytic reactors that could be utilized for the removal of these toxins are also considered

Removal of microorganisms and their chemical metabolites from water using semiconductor photocatalysis

Semiconductor photocatalysis has been applied to the remediation of an extensive range of chemical pollutants in water over the past 30 years. The application of this versatile technology for removal of micro-organisms and cyanotoxins has recently become an area that has also been the subject of extensive research particularly over the past decade. This paper considers recent research in the application of semiconductor photocatalysis for the treatment of water contaminated with pathogenic micro-organisms and cyanotoxins. The basic processes involved in photocatalysis are described and examples of recent research into the use of photocatalysis for the removal of a range of microorganisms are detailed. The paper concludes with a review of the key research on the application of this process for the removal of chemical metabolites generated from cyanobacteria.