Scope and Arbitration in Machine Learning Clinical EEG Classification

A key task in clinical EEG interpretation is to classify a recording or session as normal or abnormal. In machine learning approaches to this task, recordings are typically divided into shorter windows for practical reasons, and these windows inherit the label of their parent recording. We hypothesised that window labels derived in this manner can be misleading for example, windows without evident abnormalities can be labelled `abnormal' disrupting the learning process and degrading performance. We explored two separable approaches to mitigate this problem: increasing the window length and introducing a second-stage model to arbitrate between the window-specific predictions within a recording. Evaluating these methods on the Temple University Hospital Abnormal EEG Corpus, we significantly improved state-of-the-art average accuracy from 89.8 percent to 93.3 percent. This result defies previous estimates of the upper limit for performance on this dataset and represents a major step towards clinical translation of machine learning approaches to this problem.Comment: 10 pages, 6 figure

Sugar maple (Acer saccharum March.) growth is influenced by close conspecifics and skid trait proximity following selection harvest

In this study, we quantified the effects of local neighbourhood competition, light availability, and proximity to skid trails on the growth of sugar maple (Acer saccharum Marsh.) trees following selection harvest. We hypothesized that growth would increase with decreasing competition and increasing light availability, but that proximity to skid trails would negatively affect growth. A total of 300 sugar maples were sampled 10 years after selection harvesting in 18 stands in Témiscamingue (Québec, Canada). Detailed tree and skid trail maps were obtained in one 0.4 ha plot per stand. Square-root transformed radial growth data were fitted to a linear mixed model that included tree diameter, crown position, a neighbourhood competition index, light availability (estimated using the SORTIE light model), and distance to the nearest skid trail as explanatory variables. We considered various distance-dependent or -independent indices based on neighbourhood radii ranging from 6 to 12 m. The competition index that provided the best fit to the data was a distance-dependent index computed in a 6 m search radius, but a\ud distance-independent version of the competition index provided an almost equivalent fit to data. Models corresponding to all combinations of main effects were fit to data using maximum likelihood, and weighted averages of parameter estimates were obtained usingmultimodel inference. All predictors had\ud an influence on growth, with the exception of light. Radial growth decreased with increasing tree diameter, level of competition and proximity to skid trails, and varied among crown positions with trees in suppressed and intermediate positions having lower growth rates than codominants and dominants. Our results indicate that in selection managed stands, the radial growth of sugarmaple trees depends on\ud competition from close (6 m) conspecific neighbours, and is still affected by proximity to skid trails 10 years after harvesting. Such results underscore the importance of minimizing the extent of skid trail networks by careful pre-harvest planning of trail layout. We also conclude that the impact of heterogeneity among individual-tree neighbourhoods, such as those resulting from alternative spatial patterns of harvest, can usefully be integrated into models of post-harvest tree growth

Window Stacking Meta-Models for Clinical EEG Classification

Windowing is a common technique in EEG machine learning classification and other time series tasks. However, a challenge arises when employing this technique: computational expense inhibits learning global relationships across an entire recording or set of recordings. Furthermore, the labels inherited by windows from their parent recordings may not accurately reflect the content of that window in isolation. To resolve these issues, we introduce a multi-stage model architecture, incorporating meta-learning principles tailored to time-windowed data aggregation. We further tested two distinct strategies to alleviate these issues: lengthening the window and utilizing overlapping to augment data. Our methods, when tested on the Temple University Hospital Abnormal EEG Corpus (TUAB), dramatically boosted the benchmark accuracy from 89.8 percent to 99.0 percent. This breakthrough performance surpasses prior performance projections for this dataset and paves the way for clinical applications of machine learning solutions to EEG interpretation challenges. On a broader and more varied dataset from the Temple University Hospital EEG Corpus (TUEG), we attained an accuracy of 86.7%, nearing the assumed performance ceiling set by variable inter-rater agreement on such datasets.Comment: 17 pages, 10 figure

Helfrich-Canham bending energy as a constrained non-linear sigma model

The Helfrich-Canham bending energy is identified with a non-linear sigma model for a unit vector. The identification, however, is dependent on one additional constraint: that the unit vector be constrained to lie orthogonal to the surface. The presence of this constraint adds a source to the divergence of the stress tensor for this vector so that it is not conserved. The stress tensor which is conserved is identified and its conservation shown to reproduce the correct shape equation.Comment: 5 page

Do position and species identity of neighbours matter in 8–15-year-old post harvest mesic stands in the boreal mixedwood?

Neighbourhood competition indices (NCI), where position and species identity of neighbours are known, have been used to investigate growth and competitive interactions among adult trees. In this study, we used NCI in 8–15-year-old stands following clear-cutting in a boreal mixedwood forest of eastern Canada to improve our understanding of early successional forest dynamics. Trees of increasing diameter from the center (≥1 cm) to the edge (≥5 cm) were mapped in twenty-five circular 450m2 plots. Target trees (DBH≥1 cm) were sampled in plot center to determine their annual radial stem growth. For each species, we compared a set of growth models using either a spatially explicit NCI or a non-spatial competition index. Both types of indices estimated a species-specific competition coefficient for each pair of competitor–target species. NCI were selected as the best competition model for all target species although differences in variance explained relative to the non-spatial index were small. This likely indicates that competition occurs at the local level but that the high density and the relative uniformity of these young stands creates similar neighbourhoods for most trees in a given stand. The effective neighbourhood radius for competitors varied among species and was smaller for shade tolerant species. Intraspecific neighbours were the strongest competitors for most species. Aspen (Populus tremuloides) was a weak competitor for all species as opposed to balsam fir (Abies balsamea) which was a strong competitor in all cases. These results are in contradiction with some widely used forest policies in North America (e.g. free-to-grow standards) that consider broadleaf species, such as aspen, as the strongest competitors. For these early successional forests, the decision regarding the use of spatial or non-spatial competition indices should rest on the intended use. For even-age management, spatial indices might not justify their use in highdensity stands but they are needed for the simulation of novel harvest techniques creating complex stand structure

Fission of a multiphase membrane tube

A common mechanism for intracellular transport is the use of controlled deformations of the membrane to create spherical or tubular buds. While the basic physical properties of homogeneous membranes are relatively well-known, the effects of inhomogeneities within membranes are very much an active field of study. Membrane domains enriched in certain lipids in particular are attracting much attention, and in this Letter we investigate the effect of such domains on the shape and fate of membrane tubes. Recent experiments have demonstrated that forced lipid phase separation can trigger tube fission, and we demonstrate how this can be understood purely from the difference in elastic constants between the domains. Moreover, the proposed model predicts timescales for fission that agree well with experimental findings

Neighborhood Analyses Of Canopy Tree Competition Along Environmental Gradients In New England Forests

We use permanent-plot data from the USDA Forest Service's Forest Inventory and Analysis (FIA) program for an analysis of the effects of competition on tree growth along environmental gradients for the 14 most abundant tree species in forests of northern New England, USA. Our analysis estimates actual growth for each individual tree of a given species as a function of average potential diameter growth modified by three sets of scalars that quantify the effects on growth of (1) initial target tree size (dbh), (2) local environmental conditions, and (3) crowding by neighboring trees. Potential growth of seven of the 14 species varied along at least one of the two environmental axes identified by an ordination of relative abundance of species in plots. The relative abundances of a number of species were significantly displaced from sites where they showed maximum potential growth. In all of these cases, abundance was displaced to the more resource-poor end of the environmental gradient (either low fertility or low moisture). The pattern was most pronounced among early successional species, whereas late-successional species reached their greatest abundance on sites where they also showed the highest growth in the absence of competition. The analysis also provides empirical estimates of the strength of intraspecific and interspecific competitive effects of neighbors. For all but one of the species, our results led us to reject the hypothesis that all species of competitors have equivalent effects on a target species. Most of the individual pairwise interactions were strongly asymmetric. There was a clear competitive hierarchy among the four most shade-tolerant species, and a separate competitive hierarchy among the shade-intolerant species. Our results suggest that timber yield following selective logging will vary dramatically depending on the configuration of the residual canopy, because of interspecific variation in the magnitude of both the competitive effects of different species of neighbors and the competitive responses of different species of target trees to neighbors. The matrix of competition coefficients suggests that there may be clear benefits in managing for specific mixtures of species within local neighborhoods within stands