Establishment of the Luoping Biota National Geopark in Yunnan, China

Geoparks in China have been a great success story, with 284 national geoparks and 41 of them accorded UNESCO international status, the highest number for any country in the world. We track the progress of one of the geoparks, Luoping Biota National Geopark in Yunnan Province, from initial plans after its discovery as a key site for the exceptional preservation of Middle Triassic marine fossils in 2007, to acceptance as a National Geopark in 2011. Geoparks combine great scientific importance with accessibility and attraction for tourists. The scientific importance of Luoping is in the fossils, thousands of specimens of marine invertebrates, fishes and reptiles, together with rare elements from land (e.g. insects, plants), representing an important phase in the Mesozoic Marine Revolution, when life was recovering from devastation at the end of the Permian, and 8 million years later, had developed stable ecosystems with a new structure, dominated by predatory fishes and reptiles. The touristic importance of the Luoping Biota Geopark has already been demonstrated by rapid development of facilities and high visitor numbers

Exceptional appendage and soft-tissue preservation in a Middle Triassic horseshoe crab from SW China

Abstract Horseshoe crabs are classic “living fossils”, supposedly slowly evolving, conservative taxa, with a long fossil record back to the Ordovician. The evolution of their exoskeleton is well documented by fossils, but appendage and soft-tissue preservation is extremely rare. Here we analyse details of appendage and soft-tissue preservation in Yunnanolimulus luopingensis, a Middle Triassic (ca. 244 million years old) horseshoe crab from Yunnan Province, SW China. The remarkable preservation of anatomical details including the chelicerae, five pairs of walking appendages, opisthosomal appendages with book gills, muscles, and fine setae permits comparison with extant horseshoe crabs. The close anatomical similarity between the Middle Triassic horseshoe crabs and their recent analogues documents anatomical conservatism for over 240 million years, suggesting persistence of lifestyle. The occurrence of Carcinoscorpius-type claspers on the first and second walking legs in male individuals of Y. luopingensis indicates that simple chelate claspers in males are plesiomorphic for horseshoe crabs, and the bulbous claspers in Tachypleus and Limulus are derived

A new millipede (Diplopoda, Helminthomorpha) from the Middle Triassic Luoping biota of Yunnan, Southwest China

AbstractA new helminthomorph millipede,Sinosoma luopingensenew genus new species, from the Triassic Luoping biota of China, has 39 body segments, metazonites with lateral swellings that bear a pair of posterolateral pits (?insertion pits for spine bases), and sternites that are unfused to the pleurotergites. This millipede shares a number of characters with nematophoran diplopods, but lacks the prominent dorsal suture characteristic of that order. Other “millipede” material from the biota is more problematic. Millipedes are a rare part of the Luoping biota, which is composed mainly of marine and near-shore organisms. Occurrences of fossil millipedes are exceedingly rare in Triassic rocks worldwide, comprising specimens from Europe, Asia, and Africa, and consisting of juliform millipedes and millipedes that are either nematophorans or forms very similar to nematophorans.</jats:p

Learning to Reweight Imaginary Transitions for Model-Based Reinforcement Learning

Model-based reinforcement learning (RL) is more sample efficient than model-free RL by using imaginary trajectories generated by the learned dynamics model. When the model is inaccurate or biased, imaginary trajectories may be deleterious for training the action-value and policy functions. To alleviate such problem, this paper proposes to adaptively reweight the imaginary transitions, so as to reduce the negative effects of poorly generated trajectories. More specifically, we evaluate the effect of an imaginary transition by calculating the change of the loss computed on the real samples when we use the transition to train the action-value and policy functions. Based on this evaluation criterion, we construct the idea of reweighting each imaginary transition by a well-designed meta-gradient algorithm. Extensive experimental results demonstrate that our method outperforms state-of-the-art model-based and model-free RL algorithms on multiple tasks. Visualization of our changing weights further validates the necessity of utilizing reweight scheme