The Topology ToolKit

This system paper presents the Topology ToolKit (TTK), a software platform designed for topological data analysis in scientific visualization. TTK provides a unified, generic, efficient, and robust implementation of key algorithms for the topological analysis of scalar data, including: critical points, integral lines, persistence diagrams, persistence curves, merge trees, contour trees, Morse-Smale complexes, fiber surfaces, continuous scatterplots, Jacobi sets, Reeb spaces, and more. TTK is easily accessible to end users due to a tight integration with ParaView. It is also easily accessible to developers through a variety of bindings (Python, VTK/C++) for fast prototyping or through direct, dependence-free, C++, to ease integration into pre-existing complex systems. While developing TTK, we faced several algorithmic and software engineering challenges, which we document in this paper. In particular, we present an algorithm for the construction of a discrete gradient that complies to the critical points extracted in the piecewise-linear setting. This algorithm guarantees a combinatorial consistency across the topological abstractions supported by TTK, and importantly, a unified implementation of topological data simplification for multi-scale exploration and analysis. We also present a cached triangulation data structure, that supports time efficient and generic traversals, which self-adjusts its memory usage on demand for input simplicial meshes and which implicitly emulates a triangulation for regular grids with no memory overhead. Finally, we describe an original software architecture, which guarantees memory efficient and direct accesses to TTK features, while still allowing for researchers powerful and easy bindings and extensions. TTK is open source (BSD license) and its code, online documentation and video tutorials are available on TTK's website

Lattice cleaving: a multimaterial tetrahedral meshing algorithm with guarantees

pre-printWe introduce a new algorithm for generating tetrahedral meshes that conform to physical boundaries in volumetric domains consisting of multiple materials. The proposed method allows for an arbitrary number of materials, produces high-quality tetrahedral meshes with upper and lower bounds on dihedral angles, and guarantees geometric fidelity. Moreover, the method is combinatoric so its implementation enables rapid mesh construction. These meshes are structured in a way that also allows grading, to reduce element counts in regions of homogeneity. Additionally, we provide proofs showing that both element quality and geometric fidelity are bounded using this approach

Transits and Occultations of an Earth-Sized Planet in an 8.5-Hour Orbit

We report the discovery of an Earth-sized planet ($1.16\pm 0.19 R_\oplus$) in an 8.5-hour orbit around a late G-type star (KIC 8435766, Kepler-78). The object was identified in a search for short-period planets in the {\it Kepler} database and confirmed to be a transiting planet (as opposed to an eclipsing stellar system) through the absence of ellipsoidal light variations or substantial radial-velocity variations. The unusually short orbital period and the relative brightness of the host star ($m_{\rm Kep}$ = 11.5) enable robust detections of the changing illumination of the visible hemisphere of the planet, as well as the occultations of the planet by the star. We interpret these signals as representing a combination of reflected and reprocessed light, with the highest planet dayside temperature in the range of 2300 K to 3100 K. Follow-up spectroscopy combined with finer sampling photometric observations will further pin down the system parameters and may even yield the mass of the planet.Comment: Accepted for publication, ApJ, 10 pages and 6 figure

Random Forest as a Predictive Analytics Alternative to Regression in Institutional Research

In institutional research, modern data mining approaches are seldom considered to address predictive analytics problems. The goal of this paper is to highlight the advantages of tree-based machine learning algorithms over classic (logistic) regression methods for data-informed decision making in higher education problems, and stress the success of random forest in circumstances where the regression assumptions are often violated in big data applications. Random forest is a model averaging procedure where each tree is constructed based on a bootstrap sample of the data set. In particular, we emphasize the ease of application, low computational cost, high predictive accuracy, flexibility, and interpretability of random forest machinery. Our overall recommendation is that institutional researchers look beyond classical regression and single decision tree analytics tools, and consider random forest as the predominant method for prediction tasks. The proposed points of view are detailed and illustrated through a simulation experiment and analyses of data from real institutional research projects. Accessed 3,712 times on https://pareonline.net from January 13, 2018 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right

Etidronate prevents, but does not reverse, ectopic mineralization in a mouse model of pseudoxanthoma elasticum (

Pseudoxanthoma elasticum (PXE) and generalized arterial calcification of infancy (GACI) are heritable disorders manifesting with ectopic tissue mineralization. Most cases of PXE and some cases of GACI are caused by mutations in the ABCC6 gene, resulting in reduced plasma pyrophosphate (PPi) levels. There is no effective treatment for these disorders. It has been suggested that administration of bisphosphonates, stable and non-hydrolyzable PPi analogs, could counteract ectopic mineralization in these disorders. In this study we tested the potential efficacy of etidronate, a first generation bisphosphonate, on ectopic mineralization in the muzzle skin of Abcc6-/- mice, a model of PXE. The Abcc6-/- mice received subcutaneous injections of etidronate, 0.283 and 3.40 mg/kg per injection (0.01× and 0.12×), twice a week, in both prevention and reversal studies. Ectopic mineralization in the dermal sheath of vibrissae in muzzle skin was determined by histopathologic analysis and by direct chemical assay for calcium content. Subcutaneous injection of etidronate prevented ectopic mineralization but did not reverse existing mineralization. The effect of etidronate was accompanied by alterations in the trabecular bone microarchitecture, determined by micro-computed tomography. The results suggest that etidronate may offer a potential treatment modality for PXE and GACI caused by ABCC6 mutations. Etidronate therapy should be initiated in PXE patients as soon as the diagnosis is made, with careful monitoring of potential side effects