Search for: All records

Abstract Caldera lake sediments of the early Eocene Tufolitas Laguna del Hunco (Chubut Province, Argentina) host one of the world’s best-preserved and most diverse fossil plant assemblages, but the exceptional quality of preservation remains unexplained. The fossils have singular importance because they include numerous oldest and unique occurrences in South America of genera that today are restricted to the West Pacific region, where many of them are now vulnerable to extinction. Lacustrine depositional settings are often considered optimal for preservation as passive receptors of suspended sediment delivered, often seasonally, from lakeshores. However, caldera lakes can be influenced by a broader range of physical and chemical processes that enhance or decrease fossil preservation potential. Here, we use Laguna del Hunco to provide a new perspective on paleoenvironmental controls on plant fossil preservation in tectonically active settings. We establish a refined geochronological framework for the Laguna del Hunco deposits and present a detailed history of processes active during ∼ 200,000 years of lake filling from 52.217 ± 0.014 Ma to 51.988 ± 0.035 Ma, the time interval that encompasses nearly all fossil deposition. Detailed facies analysis shows that productive fossil localities reside within high-deposition-rate beds associated with high-energy density flows and wave-reworked lake-floor sediments, challenging traditional views that low-energy environments are required for well-preserved plant fossils. These results demonstrate that even delicate fossil components like fruits and flowers can survive high-energy transport, underscoring the importance of rapid burial as a primary control on fossil preservation. Short, steep sediment-transport networks may facilitate terrestrial fossil preservation by limiting opportunities for biochemical degradation on land and providing relatively frequent, high-energy depositional events, which quickly transport and bury organic material following events such as landslides from steep, wet, surrounding slopes. Our new model for plant taphonomy opens a path toward finding and understanding other exceptional biotas in environments once considered unlikely for preservation. 

Legged robots with point or small feet are nearly impossible to control instantaneously but are controllable over the time scale of one or more steps, also known as step-to-step control. Previous approaches achieve step-to-step control using optimization by (1) using the exact model obtained by integrating the equations of motion, or (2) using a linear approximation of the step-to-step dynamics. The former provides a large region of stability at the expense of a high computational cost while the latter is computationally cheap but offers limited region of stability. Our method combines the advantages of both. First, we generate input/output data by simulating a single step. Second, the input/output data is curve fitted using a regression model to get a closed-form approximation of the step-to-step dynamics. We do this model identification offline. Next, we use the regression model for online optimal control. Here, using the spring-load inverted pendulum model of hopping, we show that both parametric (polynomial and neural network) and non-parametric (gaussian process regression) approximations can adequately model the step-to-step dynamics. We then show this approach can stabilize a wide range of initial conditions fast enough to enable real-time control. Our results suggest that closed-form approximation of the step-to-step dynamics provides a simple accurate model for fast optimal control of legged robots.