The effect of dewatering on the combustion behaviour of Loy Yang coal in a drop tube furnace

The Mechanical Thermal Expression (MTE) process is an efficient means of removing water from low-rank coal, however the effect of dewatering on the combustion properties of lignite is largely unknown. This work examines the burnout performance of both dewatered lignite and untreated lignite in a drop tube furnace. The results show that combustion of the MTE-processed lignite is approximately 20% slower under conditions relevant to pulverised-fuel flames. This is apparently due to the reduction in pore volume which occurs during coal dewatering by the MTE process.T. R. Ballantyne, P. J. Ashman and P. J. Mullinge

The agglomeration behaviour of lochiel coal during fluidised bed gasification

Fluidised bed gasification (FBG) is a promising process for utilising high-sodium and highsulphur coals, but agglomeration and defluidisation are potential problems. Experiments have been conducted to investigate these phenomena, to assist in elucidating the mechanisms at play and to develop operating solutions. It was found that agglomeration and defluidisation of Lochiel coal occur, within the 4-hour timeframe of these experiments, only when bed temperature exceeds 850°C and the air/fuel ratio is above 2.5. Agglomerates are composed mainly of silicate material, in combination with Na, Ca, Mg, Al and Fe in varying amounts. It is surmised that non-crystalline phases in agglomerates are sodium disilicate, with inclusions of Ca, Fe, Mg and Al that are expected to lower the mixture melting point, causing FBG operating problems when the total inorganic content of the bed rises above approximately 88wt% and with temperatures exceeding 850°C. It is expected that defluidisation can be avoided if operation is maintained outside of these conditions.D. P. McCullough, P. J. Mullinger and P. J. Ashma

Detecting gamma frequency neural activity using simultaneous multiband EEG-fMRI

The authors thank the Birmingham-Nottingham Strategic Collaboration Fund for funding this research.Synopsis (≤ 100 words): We establish a methodology for optimal combination of simultaneous EEG recording with sparse multiband fMRI that preserves high resolution, whole brain fMRI coverage with broad-band EEG signal measurement uncorrupted by MR gradient artefacts. We demonstrate the ability of this approach to record gamma frequency (>50Hz) EEG signals, that are usually obscured during continuous fMRI data acquisition. In a novel application to a motor task we observe a positive correlation between gamma and BOLD responses, supporting and extending previous findings concerning the coupling between neural and haemodynamic measures of brain activity.PostprintPostprintPeer reviewe

Gasification of Victorian lignite in a laboratory scale fluidised bed gasifier

Posted with permission of the Organising Committee, 5th Asia Pacific Conference on Combustion, The University of Adelaide, ASPACC05.A 200-mm diameter, laboratory-scale atmospheric-pressure fluidised-bed reactor was designed and constructed by the Cooperative Research Centre (CRC) for Clean Power from Lignite. The purpose of this facility is to obt ain experimental data for the air/steam gasification of Australian lignite in order to validate the Centre’s mathematical model of a bubbling fluidised bed gasifier. An air-dried mixture of low-ash Victorian lignite has been used in air-steam and air-only gasification tests. The product syngas composition demonstrated successful gasification of coal with carbon monoxide and hydrogen concentrations each in the range 16-20 vol%. More carbon monoxide was measured in the syngas during coal gasification with air only. The gas composition of major species was observed to be relatively constant within the freeboard of the gasifier

Post-stimulus fMRI and EEG responses: evidence for a neuronal origin hypothesised to be inhibitory

Post-stimulus undershoots, negative responses following cessation of stimulation, are widely observed in functional magnetic resonance (fMRI) blood oxygenation level dependent (BOLD) data. However, the debate surrounding whether the origin of this response phase is neuronal or vascular, and whether it provides functionally relevant information, that is additional to what is contained in primary response, means that undershoots are widely overlooked. We simultaneously recorded electroencephalography (EEG), BOLD and cerebral blood-flow (CBF) [obtained from arterial spin labelled (ASL) fMRI] fMRI responses to hemifield checkerboard stimulation to test the potential neural origin of the fMRI post-stimulus undershoot. The post-stimulus BOLD and CBF signal amplitudes in both contralateral and ipsilateral visual cortex depended on the post-stimulus power of the 8-13 Hz (alpha) EEG neuronal activity, such that trials with highest EEG power showed largest fMRI undershoots in contralateral visual cortex. This correlation in post-stimulus EEG-fMRI responses was not predicted by the primary response amplitude. In the contralateral visual cortex we observed a decrease in both cerebral rate of oxygen metabolism (CMRO2) and CBF during the post-stimulus phase. In addition, the coupling ratio (n) between CMRO2 and CBF was significantly lower during the positive contralateral primary response phase compared with the post-stimulus phase and we propose that this reflects an altered balance of excitatory and inhibitory neuronal activity. Together our data provide strong evidence that the post-stimulus phase of the BOLD response has a neural origin which reflects, at least partially, an uncoupling of the neuronal responses driving the primary and post-stimulus responses, explaining the uncoupling of the signals measured in the two response phases. We suggest our results are consistent with inhibitory processes driving the post-stimulus EEG and fMRI responses. We therefore propose that new methods are required to model the post-stimulus and primary responses independently, enabling separate investigation of response phases in cognitive function and neurological disease

Exploring the origins of EEG motion artefacts during simultaneous fMRI acquisition: implications for motion artefact correction

Motion artefacts (MAs) are induced within EEG data collected simultaneously with fMRI when the subject’s head rotates relative to the magnetic field. The effects of these artefacts have generally been ameliorated by removing periods of data during which large artefact voltages appear in the EEG traces. However, even when combined with other standard post-processing methods, this strategy does not remove smaller MAs which can dominate the neuronal signals of interest. A number of methods are therefore being developed to characterise the MA by measuring reference signals and then using these in artefact correction. These methods generally assume that the head and EEG cap, plus any attached sensors, form a rigid body which can be characterised by a standard set of six motion parameters. Here we investigate the motion of the head/EEG cap system to provide a better understanding of MAs. We focus on the reference layer artefact subtraction (RLAS) approach, as this allows measurement of a separate reference signal for each electrode that is being used to measure brain activity. Through a series of experiments on phantoms and subjects, we find that movement of the EEG cap relative to the phantom and skin on the forehead is relatively small and that this non-rigid body movement does not appear to cause considerable discrepancy in artefacts between the scalp and reference signals. However, differences in the amplitude of these signals is observed which may be due to differences in geometry of the system from which the reference signals are measured compared with the brain signals. In addition, we find that there is non-rigid body movement of the skull and skin which produces an additional MA component for a head shake, which is not present for a head nod. This results in a large discrepancy in the amplitude and temporal profile of the MA measured on the scalp and reference layer, reducing the efficacy of MA correction based on the reference signals. Together our data suggest that the efficacy of the correction of MA using any reference-based system is likely to differ for different types of head movement with head shake being the hardest to correct. This provides new information to inform the development of hardware and post-processing methods for removing MAs from EEG data acquired simultaneously with fMRI data

Nicolas Slonimsky's Role in the Musical Modernism of the Early Twentieth Century

The musical modernism movement of the early twentieth century began with much resistance, but blossomed into a period of inspired experimentation and development. Nicolas Slonimsky played an active role in the midst of this era. He was a composer, pianist, conductor, and writer. Examining the more personal aspects of his relationships with figures that were hallmark examples of this movement reveals Slonimsky's widespread influence. The most significant relationships that are focused on in this thesis include Charles Ives, Henry Cowell, Edgard Varèse, and Léon Theremin. To these men, Slonimsky offered great support, trusted advice, and recommendations to publishers, and he wrote beneficial articles regarding their music. He collaborated with them on their work, encouraged them, and pushed them to new heights. Nicolas Slonimsky was a champion of many musicians during his lifetime, promoting and supporting them, even at his own expense. Slonimsky made significant contributions to the developments of modern music during its growth in the twentieth century

Investigation of the neurovascular coupling in positive and negative BOLD responses in human brain at 7T

Decreases in stimulus-dependent blood oxygenation level dependent (BOLD) signal and their underlying neurovascular origins have recently gained considerable interest. In this study a multi-echo, BOLD-corrected vascular space occupancy (VASO) functional magnetic resonance imaging (fMRI) technique was used to investigate neurovascular responses during stimuli that elicit positive and negative BOLD responses in human brain at 7 T. Stimulus-induced BOLD, cerebral blood volume (CBV), and cerebral blood flow (CBF) changes were measured and analyzed in ‘arterial’ and ‘venous’ blood compartments in macro- and microvasculature. We found that the overall interplay of mean CBV, CBF and BOLD responses is similar for tasks inducing positive and negative BOLD responses. Some aspects of the neurovascular coupling however, such as the temporal response, cortical depth dependence, and the weighting between ‘arterial’ and ‘venous’ contributions, are significantly different for the different task conditions. Namely, while for excitatory tasks the BOLD response peaks at the cortical surface, and the CBV change is similar in cortex and pial vasculature, inhibitory tasks are associated with a maximum negative BOLD response in deeper layers, with CBV showing strong constriction of surface arteries and a faster return to baseline. The different interplays of CBV, CBF and BOLD during excitatory and inhibitory responses suggests different underlying hemodynamic mechanisms

Detection of experimental ERP effects in combined EEG-fMRI: evaluating the benefits of interleaved acquisition and Independent Component Analysis

Copyright © 2011 Elsevier. NOTICE: this is the author’s version of a work that was accepted for publication in Clinical Neurophysiology . Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Clinical Neurophysiology, 2011 Vol. 122 Issue 2, pp. 267-77 DOI: http://dx.doi.org/10.1016/j.clinph.2010.06.033Objective The present study examined the benefit of rapid alternation of EEG and fMRI (a common strategy for avoiding artifact caused by rapid switching of MRI gradients) for detecting experimental modulations of ERPs in combined EEG–fMRI. The study also assessed the advantages of aiding the extraction of specific ERP components by means of signal decomposition using Independent Component Analysis (ICA). Methods ‘Go–nogo’ task stimuli were presented either during fMRI scanning or in the gaps between fMRI scans, resulting in ‘gradient’ and ‘no-gradient’ ERPs. ‘Go–nogo’ differences in the N2 and P3 components were subjected to conventional ERP analysis, as well as single-trial and reliability analyses. Results Comparable N2 and P3 enhancement on ‘nogo’ trials was found in the ‘gradient’ and ‘no-gradient’ ERPs. ICA-based signal decomposition resulted in better validity (as indicated by topography), greater stability and lower measurement error of the predicted ERP effects. Conclusions While there was little or no benefit of acquiring ERPs in the gaps between fMRI scans, ICA decomposition did improve the detection of experimental ERP modulations. Significance Simultaneous and continuous EEG–fMRI acquisition is preferable to interleaved protocols. ICA-based decomposition is useful not only for artifact cancellation, but also for the extraction of specific ERP components

Exploring the relative efficacy of motion artefact correction techniques for EEG data acquired during simultaneous fMRI

Simultaneous EEG-fMRI allows multi-parametric characterisation of brain function, in principle enabling a more complete understanding of brain responses; unfortunately the hostile MRI environment severely reduces EEG data quality. Simply eliminating data segments containing gross motion artefacts [MAs] (generated by movement of the EEG system and head in the MRI scanner’s static magnetic field) was previously believed sufficient. However recently the importance of removal of all MAs has been highlighted and new methods developed.A systematic comparison of the ability to remove MAs and retain underlying neuronal activity using different methods of MA detection and post-processing algorithms is needed to guide the neuroscience community. Using a head phantom, we recorded MAs while simultaneously monitoring the motion using three different approaches: Reference Layer Artefact Subtraction (RLAS), Moire Phase Tracker (MPT) markers, and Wire Loop Motion Sensors (WLMS). These EEG recordings were combined with EEG responses to simple visual tasks acquired on a subject outside the MRI environment. MAs were then corrected using the motion information collected with each of the methods combined with different analysis pipelines.All tested methods retained the neuronal signal. However, often the MA was not removed sufficiently to allow accurate detection of the underlying neuronal signal. We show that the MA is best corrected using the RLAS combined with post-processing using a multi-channel, recursive least squares (M-RLS) algorithm. This method needs to be developed further to enable practical utility; thus, WLMS combined with M-RLS currently provides the best compromise between EEG data quality and practicalities of motion detection