A Bayesian neural network predicts the dissolution of compact planetary systems.

We introduce a Bayesian neural network model that can accurately predict not only if, but also when a compact planetary system with three or more planets will go unstable. Our model, trained directly from short N-body time series of raw orbital elements, is more than two orders of magnitude more accurate at predicting instability times than analytical estimators, while also reducing the bias of existing machine learning algorithms by nearly a factor of three. Despite being trained on compact resonant and near-resonant three-planet configurations, the model demonstrates robust generalization to both nonresonant and higher multiplicity configurations, in the latter case outperforming models fit to that specific set of integrations.

Sociodemographic, environmental and labor conditions related to the presence of conjunctivitis and skin irritation in a group of informal street vendors in downtown Medellin, 2015-2019.

Introduction: Occupational diseases are those that may have a causal relationship with occupational activity or environment. However, this definition does not specify how this disease would be identified and acknowledged for workers with subsistence jobs.

Objectives: To determine sociodemographic, labor and environmental conditions that collaborate to explain the presence of eye and skin irritation among informal vendors in downtown Medellin.

Predicting the long-term stability of compact multiplanet systems.

We combine analytical understanding of resonant dynamics in two-planet systems with machine-learning techniques to train a model capable of robustly classifying stability in compact multiplanet systems over long timescales of [Formula: see text] orbits. Our Stability of Planetary Orbital Configurations Klassifier (SPOCK) predicts stability using physically motivated summary statistics measured in integrations of the first [Formula: see text] orbits, thus achieving speed-ups of up to [Formula: see text] over full simulations. This computationally opens up the stability-constrained characterization of multiplanet systems.

TATOOINE'S FUTURE: THE ECCENTRIC RESPONSE OF 'S CIRCUMBINARY PLANETS TO COMMON-ENVELOPE EVOLUTION OF THEIR HOST STARS.

Inspired by the recent discoveries of circumbinary planets orbiting nine close binary stars, we explore the fate of the former as the latter evolve off the main sequence. We combine binary star evolution models with dynamical simulations to study the orbital evolution of these planets as their hosts undergo common-envelope (CE) stages, losing in the process a tremendous amount of mass on dynamical timescales. Five of the systems experience at least one Roche-lobe overflow and CE stage (Kepler-1647 experiences three), and the binary stars either shrink to very short orbits or coalesce; two systems trigger a double-degenerate supernova explosion.