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.

Automatic artefact removal from event-related potentials via clustering

This paper outlines a method for automatic artefact removal from multichannel recordings of event-related potentials (ERPs). The proposed method is based on, firstly, separation of the ERP recordings into independent components using the method of temporal decorrelation source separation (TDSEP). Secondly, the novel lagged auto-mutual information clustering (LAMIC) algorithm is used to cluster the estimated components, together with ocular reference signals, into clusters corresponding to cerebral and non-cerebral activity. Thirdly, the components in the cluster which contains the ocular reference signals are discarded. The remaining components are then recombined to reconstruct the clean ERPs.

Modified level set method with Canny operator for image noise removal

The level set method is commonly used to address image noise removal. Existing studies concentrate mainly on determining the speed function of the evolution equation. Based on the idea of a Canny operator, this letter introduces a new method of controlling the level set evolution, in which the edge strength is taken into account in choosing curvature flows for the speed function and the normal to edge direction is used to orient the diffusion of the moving interface. The addition of an energy term to penalize the irregularity allows for better preservation of local edge information. In contrast with previous Canny-based level set methods that usually adopt a two-stage framework, the proposed algorithm can execute all the above operations in one process during noise removal.

Influence of earthworm Eisenia fetida on removal efficiency of N and P in vertical flow constructed wetland.

This study investigates biomass, density, photosynthetic activity, and accumulation of nitrogen (N) and phosphorus (P) in three wetland plants (Canna indica, Typha augustifolia, and Phragmites austrail) in response to the introduction of the earthworm Eisenia fetida into a constructed wetland. The removal efficiency of N and P in constructed wetlands were also investigated. Results showed that the photosynthetic rate (P n), transpiration rate (T r), and stomatal conductance (S cond) of C. indica and P. austrail were (p < 0.05) significantly higher when earthworms were present. The addition of E. fetida increased the N uptake value by above-ground of C. indica, T. augustifolia, and P. australis by 185, 216, and 108 %, respectively; and its P uptake value increased by 300, 355, and 211 %, respectively. Earthworms could enhance photosynthetic activity, density, and biomass of wetland plants in constructed wetland, resulting in the higher N and P uptake. The addition of E. fetida into constructed wetland increased the removal efficiency of TN and TP by 10 and 7 %, respectively. The addition of earthworms into vertical flow constructed wetland increased the removal efficiency of TN and TP, which was related to higher photosynthetic activity and N and P uptake. The addition of earthworms into vertical flow constructed wetland and plant harvests could be the significantly sustainable N and P removal strategy

Enhancing the crystallization and orientation of electrospinning poly (lactic acid) (PLLA) by combining with additives

PLLA is a thermoplastic biopolymer and can be used in industrial applications for medical and filtration applications. The brittleness of PLLA is attributed to slow crystallization rates and its glass transition temperature (Tg) is high (60 °C); for this reason, its applications are limited. The orientation, morphology, and crystal structure of the electrospun fibers was investigated by SEM, POM, DSC, FTIR, XRD, and SAXS. Combining with additives leads to a large decrease of fiber diameter, viscosity, and changes of fiber morphology and crystal structure compared to pure PLLA. DSC showed that the Tg of PLLA decreased about 15 °C and there was no change in relaxation enthalpy by the addition of plasticizer. FT-IR indicate a strong interaction between PLLA and additives; a new band appears in the PLLA blend at 1,756 cm−1 at room temperature as a crystalline band without any annealing. In addition, WAXD indicated that the intensities of the two peaks at (200/110) and (203) increased for the blend at room temperature without any annealing in comparison with PLLA; this means that PHB crystallizes in the amorphous region of PLLA. The POM experiments agree with the results from DSC, FTIR, and WAXS measurements, confirming that adding PHB results in an increase in the number of nuclei with much smaller spherulites and enhances the crystallization behavior of this material, thereby improving its potential for applications.

Enhanced MALDI MS sensitivity by weak base additives and glycerol sample coating

The concept of rationally designing MALDI matrices has been extended to the next “whole sample” level. These studies have revealed some unexpected and exploitable insights in improving MALDI sensitivity. It is shown that (i) additives which only provide additional laser energy absorption are best to be avoided; (ii) the addition of proton donors in the form of protonated weak bases can be highly beneficial; (iii) the addition of glycerol for coating crystalline samples is highly recommended. Overall, analytical sensitivity has been significantly increased compared to the current “gold” standards in MALDI MS, and new insights into the mechanisms and processes of MALDI have been gained.

Automated artifact removal from the electroencephalogram; a comparative study

Contamination of the electroencephalogram (EEG) by artifacts greatly reduces the quality of the recorded signals. There is a need for automated artifact removal methods. However, such methods are rarely evaluated against one another via rigorous criteria, with results often presented based upon visual inspection alone. This work presents a comparative study of automatic methods for removing blink, electrocardiographic, and electromyographic artifacts from the EEG. Three methods are considered; wavelet, blind source separation (BSS), and multivariate singular spectrum analysis (MSSA)-based correction. These are applied to data sets containing mixtures of artifacts. Metrics are devised to measure the performance of each method. The BSS method is seen to be the best approach for artifacts of high signal to noise ratio (SNR). By contrast, MSSA performs well at low SNRs but at the expense of a large number of false positive corrections.

FORCe: fully online and automated artifact removal for brain-computer interfacing

A fully automated and online artifact removal method for the electroencephalogram (EEG) is developed for use in brain-computer interfacing. The method (FORCe) is based upon a novel combination of wavelet decomposition, independent component analysis, and thresholding. FORCe is able to operate on a small channel set during online EEG acquisition and does not require additional signals (e.g. electrooculogram signals). Evaluation of FORCe is performed offline on EEG recorded from 13 BCI particpants with cerebral palsy (CP) and online with three healthy participants. The method outperforms the state-of the-art automated artifact removal methods Lagged auto-mutual information clustering (LAMIC) and Fully automated statistical thresholding (FASTER), and is able to remove a wide range of artifact types including blink, electromyogram (EMG), and electrooculogram (EOG) artifacts.

Terrestrial exposure of oilfield flowline additives diminish soil structural stability and remediative microbial function

Onshore oil production pipelines are major installations in the petroleum industry, stretching many thousands of kilometres worldwide which also contain flowline additives. The current study focuses on the effect of the flowline additives on soil physico-chemical and biological properties and quantified the impact using resilience and resistance indices. Our findings are the first to highlight deleterious effect of flowline additives by altering some fundamental soil properties, including a complete loss of structural integrity of the impacted soil and a reduced capacity to degrade hydrocarbons mainly due to: (i) phosphonate salts (in scale inhibitor) prevented accumulation of scale in pipelines but also disrupted soil physical structure; (ii) glutaraldehyde (in biocides) which repressed microbial activity in the pipeline and reduced hydrocarbon degradation in soil upon environmental exposure; (iii) the combinatory effects of these two chemicals synergistically caused severe soil structural collapse and disruption of microbial degradation of petroleum hydrocarbons.

Re-creation of heathland on improved pasture using topsoil removal and sulphur amendments: edaphic drivers and impacts on ericoid mycorrhizas

Understanding the factors that drive successful re-creation and restoration of lowland heaths is crucially important for achieving the long-term conservation of this threatened habitat type. In this study we investigated the changes in soil chemistry, plant community and interactions between Calluna vulgaris and symbiotic ericoid mycorrhizas (ERM) that occurred when improved pasture was subjected to one of three treatments (i) acidification with elemental sulphur (ii) acidification with ferrous sulphur (iii) removal of the topsoil. We found that the soil stripping treatment produced the greatest reduction in available phosphate but did not decrease soil pH. Conversely, acidification with elemental sulphur decreased pH but increased availability of phosphate and potentially toxic cations. The elemental sulphur treatment produced plant communities that most closely resembled those on surrounding heaths and acid grasslands. The most important driver was low pH and concomitant increased availability of potentially toxic cations. Plant community development was found to be little related to levels of available soil phosphate, particularly at low pH. The elemental sulphur treatment also produced the best germination and growth of C. vulgaris over 4–5 years. However, this treatment was found to inhibit the development of symbiotic relationships between C. vulgaris and ERM. This may affect the long-term persistence of re-created vegetation and its interactions with other components of heathland communities.

Impact of instantaneous sea ice removal in a coupled general circulation model

The impact of extreme sea ice initial conditions on modelled climate is analysed for a fully coupled atmosphere ocean sea ice general circulation model, the Hadley Centre climate model HadCM3. A control run is chosen as reference experiment with greenhouse gas concentration fixed at preindustrial conditions. Sensitivity experiments show an almost complete recovery from total removal or strong increase of sea ice after four years. Thus, uncertainties in initial sea ice conditions seem to be unimportant for climate modelling on decadal or longer time scales. When the initial conditions of the ocean mixed layer were adjusted to ice-free conditions, a few substantial differences remained for more than 15 model years. But these differences are clearly smaller than the uncertainty of the HadCM3 run and all the other 19 IPCC fourth assessment report climate model preindustrial runs. It is an important task to improve climate models in simulating the past sea ice variability to enable them to make reliable projections for the 21st century.