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Line-FRAP, A Versatile Method to Measure Diffusion Rates In Vitro and In Vivo

Abstract

Not specified

Authors: Debabrata Dey, Shir Marciano, Ariane Nunes-Alves, Vladimir Kiss, Rebecca C Wade, Gideon Schreiber

Date Published: 1st Apr 2021

Publication Type: Journal

TOI-257b (HD 19916b): a warm sub-saturn orbiting an evolved F-type star

Abstract (Expand)

We report the discovery of a warm sub-Saturn, TOI-257b (HD 19916b), based on data from NASA's Transiting Exoplanet Survey Satellite (TESS). The transit signal was detected by TESS and confirmed to … be of planetary origin based on radial velocity observations. An analysis of the TESS photometry, the MINERVA-Australis, FEROS, and HARPS radial velocities, and the asteroseismic data of the stellar oscillations reveals that TOI-257b has a mass of MP = 0.138 ± 0.023 MJ (43.9 ± 7.3 M⊕ ), a radius of RP = 0.639 ± 0.013 RJ (7.16 ± 0.15 R⊕ ), bulk density of 0.65+0.12−0.11 (cgs), and period 18.38818+0.00085−0.00084 days . TOI-257b orbits a bright (V = 7.612 mag) somewhat evolved late F-type star with M* = 1.390 ± 0.046 Msun , R* = 1.888 ± 0.033 Rsun , Teff = 6075 ± 90 K , and vsin i = 11.3 ± 0.5 km s-1. Additionally, we find hints for a second non-transiting sub-Saturn mass planet on a ∼71 day orbit using the radial velocity data. This system joins the ranks of a small number of exoplanet host stars (∼100) that have been characterized with asteroseismology. Warm sub-Saturns are rare in the known sample of exoplanets, and thus the discovery of TOI-257b is important in the context of future work studying the formation and migration history of similar planetary systems.

Authors: Brett C Addison, Duncan J Wright, Belinda A Nicholson, Bryson Cale, Teo Mocnik, Daniel Huber, Peter Plavchan, Robert A Wittenmyer, Andrew Vanderburg, William J Chaplin, Ashley Chontos, Jake T Clark, Jason D Eastman, Carl Ziegler, Rafael Brahm, Bradley D Carter, Mathieu Clerte, Néstor Espinoza, Jonathan Horner, John Bentley, Andrés Jordán, Stephen R Kane, John F Kielkopf, Emilie Laychock, Matthew W Mengel, Jack Okumura, Keivan G Stassun, Timothy R Bedding, Brendan P Bowler, Andrius Burnelis, Sergi Blanco-Cuaresma, Michaela Collins, Ian Crossfield, Allen B Davis, Dag Evensberget, Alexis Heitzmann, Steve B Howell, Nicholas Law, Andrew W Mann, Stephen C Marsden, Rachel A Matson, James H O’Connor, Avi Shporer, Catherine Stevens, C G Tinney, Christopher Tylor, Songhu Wang, Hui Zhang, Thomas Henning, Diana Kossakowski, George Ricker, Paula Sarkis, Martin Schlecker, Pascal Torres, Roland Vanderspek, David W Latham, Sara Seager, Joshua N Winn, Jon M Jenkins, Ismael Mireles, Pam Rowden, Joshua Pepper, Tansu Daylan, Joshua E Schlieder, Karen A Collins, Kevin I Collins, Thiam-Guan Tan, Warrick H Ball, Sarbani Basu, Derek L Buzasi, Tiago L Campante, Enrico Corsaro, L González-Cuesta, Guy R Davies, Leandro de Almeida, Jose-Dias do Nascimento, Rafael A García, Zhao Guo, Rasmus Handberg, Saskia Hekker, Daniel R Hey, Thomas Kallinger, Steven D Kawaler, Cenk Kayhan, James S. Kuszlewicz, Mikkel N Lund, Alexander Lyttle, Savita Mathur, Andrea Miglio, Benoit Mosser, Martin B Nielsen, Aldo M Serenelli, Victor Silva Aguirre, Nathalie Themeßl

Date Published: 1st Apr 2021

Publication Type: Journal

Forecast encompassing tests for the expected shortfall

Abstract

Not specified

Authors: Timo Dimitriadis, Julie Schnaitmann

Date Published: 1st Apr 2021

Publication Type: Journal

SpeciesRax: A tool for maximum likelihood species tree inference from gene family trees under duplication, transfer, and loss

Abstract

Not specified

Authors: Benoit Morel, Paul Schade, Sarah Lutteropp, Tom A. Williams, Gergely J. Szöllősi, Alexandros Stamatakis

Date Published: 29th Mar 2021

Publication Type: Journal

SPART, a versatile and standardized data exchange format for species partition information

Abstract

Not specified

Authors: Aurélien Miralles, Jacques Ducasse, Sophie Brouillet, Tomas Flouri, Tomochika Fujisawa, Paschalia Kapli, L. Lacey Knowles, Sangeeta Kumari, Alexandros Stamatakis, Jeet Sukumaran, Sarah Lutteropp, Miguel Vences, Nicolas Puillandre

Date Published: 22nd Mar 2021

Publication Type: Journal

From Photometric Redshifts to Improved Weather Forecasts: machine learning and proper scoring rules as a basis for interdisciplinary work

Abstract (Expand)

The amount, size, and complexity of astronomical data-sets and databases are growing rapidly in the last decades, due to new technologies and dedicated survey telescopes. Besides dealing with poly-structured … and complex data, sparse data has become a field of growing scientific interest. A specific field of Astroinformatics research is the estimation of redshifts of extra-galactic sources by using sparse photometric observations. Many techniques have been developed to produce those estimates with increasing precision. In recent years, models have been favored which instead of providing a point estimate only, are able to generate probabilistic density functions (PDFs) in order to characterize and quantify the uncertainties of their estimates. Crucial to the development of those models is a proper, mathematically principled way to evaluate and characterize their performances, based on scoring functions as well as on tools for assessing calibration. Still, in literature inappropriate methods are being used to express the quality of the estimates that are often not sufficient and can potentially generate misleading interpretations. In this work we summarize how to correctly evaluate errors and forecast quality when dealing with PDFs. We describe the use of the log-likelihood, the continuous ranked probability score (CRPS) and the probability integral transform (PIT) to characterize the calibration as well as the sharpness of predicted PDFs. We present what we achieved when using proper scoring rules to train deep neural networks as well as to evaluate the model estimates and how this work led from well calibrated redshift estimates to improvements in probabilistic weather forecasting. The presented work is an example of interdisciplinarity in data-science and illustrates how methods can help to bridge gaps between different fields of application.

Authors: Kai Polsterer, Sebastian Lerch, Antonio D'Isanto

Date Published: 5th Mar 2021

Publication Type: InProceedings

Want to track pandemic variants faster? Fix the bioinformatics bottleneck

Abstract

Not specified

Authors: Emma B. Hodcroft, Nicola De Maio, Rob Lanfear, Duncan R. MacCannell, Bui Quang Minh, Heiko A. Schmidt, Alexandros Stamatakis, Nick Goldman, Christophe Dessimoz

Date Published: 4th Mar 2021

Publication Type: Journal

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