Small-Signal Stability Constrained Optimal Power Flow: A Convexification Approach. (arXiv:1911.12001v1 [math.OC])

In this paper, a novel Convexified Small-Signal Stability Constraint Optimal Power Flow (SCOPF) has been presented that does not rely on eigenvalue analysis. The proposed methodology is based on the sufficient condition for small-signal stability, developed as a Bilinear Matrix Inequality (BMI) and uses network structure-preserving Differential Algebraic Equation (DAE) modeling of power system. The…

A Consistent Discrete 3D Hodge-type Decomposition: implementation and practical evaluation. (arXiv:1911.12173v1 [math.NA])

The Hodge decomposition provides a very powerful mathematical method for the analysis of 2D and 3D vector fields. It states roughly that any vector field can be $L^2$-orthogonaly decomposed into a curl-free, divergence-free, and a harmonic field. The harmonic field itself can be further decomposed into three components, two of which are closely tied to…

Classification of Single-lead Electrocardiograms: TDA Informed Machine Learning. (arXiv:1911.12253v1 [q-bio.QM])

Atrial Fibrillation is a heart condition characterized by erratic heart rhythms caused by chaotic propagation of electrical impulses in the atria, leading to numerous health complications. State-of-the-art models employ complex algorithms that extract expert-informed features to improve diagnosis. In this note, we demonstrate how topological features can be used to help accurately classify single lead…

Dynamic virtual ecosystems as a tool for detecting large-scale responses of biodiversity to environmental and land-use change. (arXiv:1911.12257v1 [q-bio.QM])

In the face of biodiversity loss, we rely upon measures of diversity to describe the health of ecosystems and to direct policymakers and conservation efforts. However, there are many complexities in natural systems that can easily confound biodiversity measures, giving misleading interpretations of the system status and, as a result, there is yet to be…

On generative models of T-cell receptor sequences. (arXiv:1911.12279v1 [q-bio.QM])

In this comment on Davidsen et al., “Deep generative models for T cell receptor protein sequences”, eLife 2019;8:e46935, we compare the performance of the variational auto-encoder presented in that article to a previously proposed approach for which a software implementation, SONIA, has been recently released. We find that SONIA performs as well as the variational…

ComHapDet: A Spatial Community Detection Algorithm for Haplotype Assembly. (arXiv:1911.12285v1 [cs.SI])

Background: Haplotypes, the ordered lists of single nucleotide variations that distinguish chromosomal sequences from their homologous pairs, may reveal an individual’s susceptibility to hereditary and complex diseases and affect how our bodies respond to therapeutic drugs. Reconstructing haplotypes of an individual from short sequencing reads is an NP-hard problem that becomes even more challenging in…

Fully Unsupervised Probabilistic Noise2Void. (arXiv:1911.12291v1 [eess.IV])

Image denoising is the first step in many biomedical image analysis pipelines and Deep Learning (DL) based methods are currently best performing. A new category of DL methods such as Noise2Void or Noise2Self can be used fully unsupervised, requiring nothing but the noisy data. However, this comes at the price of reduced reconstruction quality. The…