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To improve hydro-chemical modeling and forecasting, there is a need to better understand flood-induced variability in water chemistry and the processes controlling it in watersheds. In the literature, assumptions are often made, for instance, that stream c ...
We investigate the ground-state properties of the highly degenerate noncoplanar phase of the classical bilinear-biquadratic Heisenberg model on the triangular lattice with Monte Carlo simulations. For that purpose, we introduce an Ising pseudospin represen ...
Since its discovery, the superconducting phase in water-intercalated sodium cobaltates NaxCoO2 center dot yH(2)O (x similar to 0.3, y similar to 1.3) has posed fundamental challenges in terms of experimental investigation and theoretical understanding. By ...
Extreme events can be statistically characterised as excesses of a high threshold. Inference in this case has to account for dependence between excesses. The peaks over threshold approach suggests pre-processing the series by defining clusters of successiv ...
Ever since the observation that collinearity, that is, the sequential activity of Hox genes based on their relative positions within their gene clusters, is conserved throughout most of the animal kingdom, the question has been raised as to what are the un ...
Acquisition of three-dimensional (3D) spectral data is nowadays common using many different microanalytical techniques. In order to proceed to the 3D reconstruction, data processing is necessary not only to deal with noisy acquisitions but also to segment ...
A systematic classification and accepted nomenclature of neuron types is much needed but is currently lacking. This article describes a possible taxononnical solution for classifying GABAergic interneurons of the cerebral cortex based on a novel, web-based ...
Kernelized Support Vector Machines (SVM) have gained the status of o-the-shelf classiers, able to deliver state of the art performance on almost any problem. Still, their practical use is constrained by their computational and memory complexity, which grow ...
This paper offers a methodological contribution for computing the distance between two empirical distributions in an Euclidean space of very large dimension. We propose to use decision trees instead of relying on standard quantification of the feature spac ...
More and more areas use graphs for the representation of their data because it gives a connection-oriented perspective. Unfortunately, datasets are constantly growing in size, while devices have increasingly smaller screens (tablets, smartphones, etc). In ...