Robustness of mutual information to inter-subject variability for automatic artefact removal from EEG

The externally recorded electroencephalogram (EEG) is contaminated with signals that do not originate from the brain, collectively known as artefacts. Thus, EEG signals must be cleaned prior to any further analysis. In particular, if the EEG is to be used in online applications such as Brain-Computer Interfaces (BCIs) the removal of artefacts must be performed in an automatic manner. This paper investigates the robustness of Mutual Information based features to inter-subject variability for use in an automatic artefact removal system. The system is based on the separation of EEG recordings into independent components using a temporal ICA method, RADICAL, and the utilisation of a Support Vector Machine for classification of the components into EEG and artefact signals. High accuracy and robustness to inter-subject variability is achieved.

A multi-center study: Intra-scan and inter-scan variability of diffusion spectrum imaging

The objective of this study was to investigate whether it is possible to pool together diffusion spectrum imaging data from four different scanners, located at three different sites. Two of the scanners had identical configuration whereas two did not. To measure the variability, we extracted three scalar maps (ADC, FA and GFA) from the DSI and utilized a region and a tract-based analysis. Additionally, a phantom study was performed to rule out some potential factors arising from the scanner performance in case some systematic bias occurred in the subject study. This work was split into three experiments: intra-scanner reproducibility, reproducibility with twin-scanner settings and reproducibility with other configurations. Overall for the intra-scanner and twin-scanner experiments, the region-based analysis coefficient of variation (CV) was in a range of 1%-4.2% and below 3% for almost every bundle for the tract-based analysis. The uncinate fasciculus showed the worst reproducibility, especially for FA and GFA values (CV 3.7-6%). For the GFA and FA maps, an ICC value of 0.7 and above is observed in almost all the regions/tracts. Looking at the last experiment, it was found that there is a very high similarity of the outcomes from the two scanners with identical setting. However, this was not the case for the two other imagers. Given the fact that the overall variation in our study is low for the imagers with identical settings, our findings support the feasibility of cross-site pooling of DSI data from identical scanners.

Intra-subject variability in attention-deficit hyperactivity disorder

BACKGROUND: This study is based on a comprehensive survey of the neuropsychological attention-deficit hyperactivity disorder (ADHD) literature and presents the first psychometric analyses of different parameters of intra-subject variability (ISV) in patients with ADHD compared to healthy controls, using the Continuous Performance Test, a Go-NoGo task, a Stop Signal Task, as well as N-back tasks. METHODS: Data of 57 patients with ADHD and 53 age- and gender-matched controls were available for statistical analysis. Different parameters were used to describe central tendency (arithmetic mean, median), dispersion (standard deviation, coefficient of variation, consecutive variance), and shape (skewness, excess) of reaction time distributions, as well as errors (commissions and omissions). RESULTS: Group comparisons revealed by far the strongest effect sizes for measures of dispersion, followed by measures of central tendency, and by commission errors. Statistical control of ISV reduced group differences in the other measures substantially. One (patients) or two (controls) principal components explained up to 67% of the inter-individual differences in intra-individual variability. CONCLUSIONS: Results suggest that, across a variety of neuropsychological tests, measures of ISV contribute best to group discrimination, with limited incremental validity of measures of central tendency and errors. Furthermore, increased ISV might be a unitary construct in ADHD.

Inter-cycle variability of in-cylinder pressure parameters in an ethanol fumigated common rail diesel engine

The effects of ethanol fumigation on the inter-cycle variability of key in-cylinder pressure parameters in a modern common rail diesel engine have been investigated. Specifically, maximum rate of pressure rise, peak pressure, peak pressure timing and ignition delay were investigated. A new methodology for investigating the start of combustion was also proposed and demonstrated—which is particularly useful with noisy in-cylinder pressure data as it can have a significant effect on the calculation of an accurate net rate of heat release indicator diagram. Inter-cycle variability has been traditionally investigated using the coefficient of variation. However, deeper insight into engine operation is given by presenting the results as kernel density estimates; hence, allowing investigation of otherwise unnoticed phenomena, including: multi-modal and skewed behaviour. This study has found that operation of a common rail diesel engine with high ethanol substitutions (>20% at full load, >30% at three quarter load) results in a significant reduction in ignition delay. Further, this study also concluded that if the engine is operated with absolute air to fuel ratios (mole basis) less than 80, the inter-cycle variability is substantially increased compared to normal operation.

In-cylinder pressure and inter-cycle variability analysis for a compression ignition engine : Bayesian approaches

This thesis introduced Bayesian statistics as an analysis technique to isolate resonant frequency information in in-cylinder pressure signals taken from internal combustion engines. Applications of these techniques are relevant to engine design (performance and noise), energy conservation (fuel consumption) and alternative fuel evaluation. The use of Bayesian statistics, over traditional techniques, allowed for a more in-depth investigation into previously difficult to isolate engine parameters on a cycle-by-cycle basis. Specifically, these techniques facilitated the determination of the start of pre-mixed and diffusion combustion and for the in-cylinder temperature profile to be resolved on individual consecutive engine cycles. Dr Bodisco further showed the utility of the Bayesian analysis techniques by applying them to in-cylinder pressure signals taken from a compression ignition engine run with fumigated ethanol.

The influence of fatty acid methyl ester profiles on inter-cycle variability in a heavy duty compression ignition engine

With the advent of alternative fuels, such as biodiesels and related blends, it is important to develop an understanding of their effects on inter-cycle variability which, in turn, influences engine performance as well as its emission. Using four methanol trans-esterified biomass fuels of differing carbon chain length and degree of unsaturation, this paper provides insight into the effect that alternative fuels have on inter-cycle variability. The experiments were conducted with a heavy-duty Cummins, turbo-charged, common-rail compression ignition engine. Combustion performance is reported in terms of the following key in-cylinder parameters: indicated mean effective pressure (IMEP), net heat release rate (NHRR), standard deviation of variability (StDev), coefficient of variation (CoV), peak pressure, peak pressure timing and maximum rate of pressure rise. A link is also established between the cyclic variability and oxygen ratio, which is a good indicator of stoichiometry. The results show that the fatty acid structures did not have a significant effect on injection timing, injection duration, injection pressure, StDev of IMEP, or the timing of peak motoring and combustion pressures. However, a significant effect was noted on the premixed and diffusion combustion proportions, combustion peak pressure and maximum rate of pressure rise. Additionally, the boost pressure, IMEP and combustion peak pressure were found to be directly correlated to the oxygen ratio. The emission of particles positively correlates with oxygen content in the fuel as well as in the air-fuel mixture resulting in a higher total number of particles per unit of mass.

Local inter-session variability modelling for object classification

Object classification is plagued by the issue of session variation. Session variation describes any variation that makes one instance of an object look different to another, for instance due to pose or illumination variation. Recent work in the challenging task of face verification has shown that session variability modelling provides a mechanism to overcome some of these limitations. However, for computer vision purposes, it has only been applied in the limited setting of face verification. In this paper we propose a local region based intersession variability (ISV) modelling approach, and apply it to challenging real-world data. We propose a region based session variability modelling approach so that local session variations can be modelled, termed Local ISV. We then demonstrate the efficacy of this technique on a challenging real-world fish image database which includes images taken underwater, providing significant real-world session variations. This Local ISV approach provides a relative performance improvement of, on average, 23% on the challenging MOBIO, Multi-PIE and SCface face databases. It also provides a relative performance improvement of 35% on our challenging fish image dataset.

Inter-cycle variability of ignition delay in an ethanol fumigated common rail diesel engine

An experimental study has been performed to investigate the ignition delay of a modern heavy-duty common-rail diesel engine run with fumigated ethanol substitutions up to 40% on an energy basis. The ignition delay was determined through the use of statistical modelling in a Bayesian framework this framework allows for the accurate determination of the start of combustion from single consecutive cycles and does not require any differentiation of the in-cylinder pressure signal. At full load the ignition delay has been shown to decrease with increasing ethanol substitutions and evidence of combustion with high ethanol substitutions prior to diesel injection have also been shown experimentally and by modelling. Whereas, at half load increasing ethanol substitutions have increased the ignition delay. A threshold absolute air to fuel ratio (mole basis) of above ~110 for consistent operation has been determined from the inter-cycle variability of the ignition delay, a result that agrees well with previous research of other in-cylinder parameters and further highlights the correlation between the air to fuel ratio and inter-cycle variability. Numerical modelling to investigate the sensitivity of ethanol combustion has also been performed. It has been shown that ethanol combustion is sensitive to the initial air temperature around the feasible operating conditions of the engine. Moreover, a negative temperature coefficient region of approximately 900{1050 K (the approximate temperature at fuel injection) has been shown with for n-heptane and n-heptane/ethanol blends in the numerical modelling. A consequence of this is that the dominate effect influencing the ignition delay under increasing ethanol substitutions may rather be from an increase in chemical reactions and not from in-cylinder temperature. Further investigation revealed that the chemical reactions at low ethanol substitutions are different compared to the high (> 20%) ethanol substitutions.

Improving out-domain PLDA speaker verification using unsupervised inter-dataset variability compensation approach

Experimental studies have found that when the state-of-the-art probabilistic linear discriminant analysis (PLDA) speaker verification systems are trained using out-domain data, it significantly affects speaker verification performance due to the mismatch between development data and evaluation data. To overcome this problem we propose a novel unsupervised inter dataset variability (IDV) compensation approach to compensate the dataset mismatch. IDV-compensated PLDA system achieves over 10% relative improvement in EER values over out-domain PLDA system by effectively compensating the mismatch between in-domain and out-domain data.

Sampling Methods for Exploring Between Subject Variability in Cardiac Electrophysiology Experiments

Between-subject and within-subject variability is ubiquitous in biology and physiology and understanding and dealing with this is one of the biggest challenges in medicine. At the same time it is difficult to investigate this variability by experiments alone. A recent modelling and simulation approach, known as population of models (POM), allows this exploration to take place by building a mathematical model consisting of multiple parameter sets calibrated against experimental data. However, finding such sets within a high-dimensional parameter space of complex electrophysiological models is computationally challenging. By placing the POM approach within a statistical framework, we develop a novel and efficient algorithm based on sequential Monte Carlo (SMC). We compare the SMC approach with Latin hypercube sampling (LHS), a method commonly adopted in the literature for obtaining the POM, in terms of efficiency and output variability in the presence of a drug block through an in-depth investigation via the Beeler-Reuter cardiac electrophysiological model. We show improved efficiency via SMC and that it produces similar responses to LHS when making out-of-sample predictions in the presence of a simulated drug block.

Crystallographic and modelling studies on Mycobacterium tuberculosis RuvA: Additional role of RuvB-binding domain and inter species variability

RuvA, along with RuvB, is involved in branch migration of heteroduplex DNA in homologous recombination. The structures of three new crystal forms of RuvA from Mycobacterium tuberculosis (MtRuvA) have been determined. The RuvB-binding domain is cleaved off in one of them. Detailed models of the complexes of octameric RuvA from different species with the Holliday junction have also been constructed. A thorough examination of the structures presented here and those reported earlier brings to light the hitherto unappreciated role of the RuvB-binding domain in determining inter-domain orientation and oligomerization. These structures also permit an exploration of the interspecies variability of structural features such as oligomerization and the conformation of the loop that carries the acidic pin, in terms of amino acid substitutions. These models emphasize the additional role of the RuvB-binding domain in Holliday junction binding. This role along with its role in oligomerization could have important biological implications.

Inter-annual variability of precipitation constrains the production response of boreal Pinus sylvestris to nitrogen fertilization

© 2015 Published by Elsevier B.V.Tree growth resources and the efficiency of resource-use for biomass production determine the productivity of forest ecosystems. In nutrient-limited forests, nitrogen (N)-fertilization increases foliage [N], which may increase photosynthetic rates, leaf area index (L), and thus light interception (IC). The product of such changes is a higher gross primary production and higher net primary production (NPP). However, fertilization may also alter carbohydrate partitioning from below- to aboveground, increasing aboveground NPP (ANPP). We analyzed effects of long-term N-fertilization on NPP, and that of long-term carbon storing organs (NPPS) in a Pinus sylvestris forest on sandy soil, a wide-ranging forest type in the boreal region. We based our analyses on a combination of destructive harvesting, consecutive mensuration, and optical measurements of canopy openness. After eight-year fertilization with a total of 70gNm^-2, ANPP was 27±7% higher in the fertilized (F) relative to the reference (R) stand, but although L increased relative to its pre-fertilization values, IC was not greater than in R. On the seventh year after the treatment initiation, the increase of ANPP was matched by the decrease of belowground NPP (78 vs. 92gCm^-2yr^-1; ~17% of NPP) and, given the similarity of IC, suggests that the main effect of N-fertilization was changed carbon partitioning rather than increased canopy photosynthesis. Annual NPPS increased linearly with growing season temperature (T) in both treatments, with an upward shift of 70.2gCm^-2yr^-1 by fertilization, which also caused greater amount of unexplained variation (r²=0.53 in R, 0.21 in F). Residuals of the NPPS-T relationship of F were related to growing season precipitation (P, r²=0.48), indicating that T constrains productivity at this site regardless of fertility, while P is important in determining productivity where N-limitation is alleviated. We estimated that, in a growing season average T (11.5±1.0°C; 33-year-mean), NPPS response to N-fertilization will be nullified with P 31mm less than the mean (325±85mm), and would double with P 109mm greater than the mean. These results suggest that inter-annual variation in climate, particularly in P, may help explaining the reported large variability in growth responses to fertilization of pine stands on sandy soils. Furthermore, forest management of long-rotation systems, such as those of boreal and northern temperate forests, must consider the efficiency of fertilization in terms of wood production in the context of changes in climate predicted for the region.