Habitable Climate Scenarios for Proxima Centauri b With a Dynamic Ocean

The nearby exoplanet Proxima Centauri b will be a prime future target for characterization, despite questions about its retention of water. Climate models with static oceans suggest that an Earth-like Proxima b could harbor a small dayside region of surface liquid water at fairly warm temperatures despite its weak instellation. We present the first 3-dimensional climate simulations of Proxima b with a dynamic ocean. We find that an ocean-covered Proxima b could have a much broader area of surface liquid water but at much colder temperatures than previously suggested, due to ocean heat transport and depression of the freezing point by salinity. Elevated greenhouse gas concentrations do not necessarily produce more open ocean area because of possible dynamic regime transitions. For an evolutionary path leading to a highly saline present ocean, Proxima b could conceivably be an inhabited, mostly open ocean planet dominated by halophilic life. For an ocean planet in 3:2 spin-orbit resonance, a permanent tropical waterbelt exists for moderate eccentricity. Simulations of Proxima Centauri b may also be a model for the habitability of planets receiving similar instellation from slightly cooler or warmer stars, e.g., in the TRAPPIST-1, LHS 1140, GJ 273, and GJ 3293 systems.Comment: Submitted to Astrobiology; 38 pages, 12 figures, 5 table

Physical and Mechanical Properties of LoVAR: A New Lightweight Particle-Reinforced Fe-36Ni Alloy

Fe-36Ni is an alloy of choice for low thermal expansion coefficient (CTE) for optical, instrument and electrical applications in particular where dimensional stability is critical. This paper outlines the development of a particle-reinforced Fe-36Ni alloy that offers reduced density and lower CTE compared to the matrix alloy. A summary of processing capability will be given relating the composition and microstructure to mechanical and physical properties

CPPN2GAN: Combining Compositional Pattern Producing Networks and GANs for Large-Scale Pattern Generation

Generative Adversarial Networks (GANs) are proving to be a powerful indirect genotype-to-phenotype mapping for evolutionary search, but they have limitations. In particular, GAN output does not scale to arbitrary dimensions, and there is no obvious way of combining multiple GAN outputs into a cohesive whole, which would be useful in many areas, such as the generation of video game levels. Game levels often consist of several segments, sometimes repeated directly or with variation, organized into an engaging pattern. Such patterns can be produced with Compositional Pattern Producing Networks (CPPNs). Specifically, a CPPN can define latent vector GAN inputs as a function of geometry, which provides a way to organize level segments output by a GAN into a complete level. This new CPPN2GAN approach is validated in both Super Mario Bros. and The Legend of Zelda. Specifically, divergent search via MAP-Elites demonstrates that CPPN2GAN can better cover the space of possible levels. The layouts of the resulting levels are also more cohesive and aesthetically consistent.Comment: GECCO 2020. arXiv admin note: text overlap with arXiv:2004.0015

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics 1.0: A General Circulation Model for Simulating the Climates of Rocky Planets

Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics (ROCKE-3D) is a 3-Dimensional General Circulation Model (GCM) developed at the NASA Goddard Institute for Space Studies for the modeling of atmospheres of Solar System and exoplanetary terrestrial planets. Its parent model, known as ModelE2 (Schmidt et al. 2014), is used to simulate modern and 21st Century Earth and near-term paleo-Earth climates. ROCKE-3D is an ongoing effort to expand the capabilities of ModelE2 to handle a broader range of atmospheric conditions including higher and lower atmospheric pressures, more diverse chemistries and compositions, larger and smaller planet radii and gravity, different rotation rates (slowly rotating to more rapidly rotating than modern Earth, including synchronous rotation), diverse ocean and land distributions and topographies, and potential basic biosphere functions. The first aim of ROCKE-3D is to model planetary atmospheres on terrestrial worlds within the Solar System such as paleo-Earth, modern and paleo-Mars, paleo-Venus, and Saturn's moon Titan. By validating the model for a broad range of temperatures, pressures, and atmospheric constituents we can then expand its capabilities further to those exoplanetary rocky worlds that have been discovered in the past and those to be discovered in the future. We discuss the current and near-future capabilities of ROCKE-3D as a community model for studying planetary and exoplanetary atmospheres.Comment: Revisions since previous draft. Now submitted to Astrophysical Journal Supplement Serie

Development and analysis of a port terminal loader model at RUSAL Aughinish

The present study addresses the analysis of bulk carrier loading and discharge at the RUSAL Aughinish Alumina refinery, located on the west coast of the Republic of Ireland. We design a realistic simulation model taking into account not only deterministic features, but also elements of uncertainty. Following a statistical analysis of the results, we are able to indicate how the most important variables affect large scale performance descriptors such as berth occupancy, queueing hours and costs. The model is thoroughly validated against historical data and is subsequently applied to determine the impact of changes in key parameters on overall port operation and to suggest possible improvements of the modelled system

Urban policy

The employment relationship – that between employer and employee – is at the heart of capitalism and a core issue for public policy. Governments create rules, policies and institutions within which employees, their representatives, employers and their representatives, operate. The interest to governments when creating policy includes the form that bargaining takes, wage and employment levels, the nature and effects of contracting and the rights of workers – much of this boiling down to issues of power. In recent decades, major policy issues have included the federal Labor government’s Prices and Incomes Accords in the 1980s and 1990s, the Coalition government’s ‘WorkChoices’ legislation, the shift to enterprise bargaining, and developments in such areas as minimum wages and pay equity. In this chapter we outline the matters at stake, the players, the policy processes and some of the key issues

Physical and Mechanical Properties of LoVAR: A New Lightweight Particle-Reinforced Fe-36Ni Alloy

Fe-36Ni is an alloy of choice for low thermal expansion coefficient (CTE) for optical, instrument and electrical applications in particular where dimensional stability is critical. This paper outlines the development of a particle-reinforced Fe-36Ni alloy that offers reduced density and lower CTE compared to the matrix alloy. A summary of processing capability will be given relating the composition and microstructure to mechanical and physical properties

Managing AI Risks in an Era of Rapid Progress

In this short consensus paper, we outline risks from upcoming, advanced AI systems. We examine large-scale social harms and malicious uses, as well as an irreversible loss of human control over autonomous AI systems. In light of rapid and continuing AI progress, we propose urgent priorities for AI R&D and governance

Improving the accessibility and transferability of machine learning algorithms for identification of animals in camera trap images: MLWIC2

Motion-activated wildlife cameras (or “camera traps”) are frequently used to remotely and noninvasively observe animals. The vast number of images collected from camera trap projects has prompted some biologists to employ machine learning algorithms to automatically recognize species in these images, or at least filter-out images that do not contain animals. These approaches are often limited by model transferability, as a model trained to recognize species from one location might not work as well for the same species in different locations. Furthermore, these methods often require advanced computational skills, making them inaccessible to many biologists. We used 3 million camera trap images from 18 studies in 10 states across the United States of America to train two deep neural networks, one that recognizes 58 species, the “species model,” and one that determines if an image is empty or if it contains an animal, the “empty-animal model.” Our species model and empty-animal model had accuracies of 96.8% and 97.3%, respectively. Furthermore, the models performed well on some out-of-sample datasets, as the species model had 91% accuracy on species from Canada (accuracy range 36%–91% across all out-of-sample datasets) and the empty-animal model achieved an accuracy of 91%–94% on out-of-sample datasets from different continents. Our software addresses some of the limitations of using machine learning to classify images from camera traps. By including many species from several locations, our species model is potentially applicable to many camera trap studies in North America. We also found that our empty-animal model can facilitate removal of images without animals globally. We provide the trained models in an R package (MLWIC2: Machine Learning for Wildlife Image Classification in R), which contains Shiny Applications that allow scientists with minimal programming experience to use trained models and train new models in six neural network architectures with varying depths

Managing extreme AI risks amid rapid progress

Preparation requires technical research and development, as well as adaptive, proactive governance