The Late Devonian Frasnian–Famennian (F–F) mass extinction has been long-time debated by non-volcanic causes, extra-terrestrial impacts, and large igneous province (LIP) eruptions. To better understand the ultimate cause of the F–F mass extinction, here we investigate the chemostratigraphy of mercury (Hg) and total organic carbon (TOC) on two marine F–F strata in the Dushan area, South China. In both sections, high Hg and Hg/TOC anomalies were observed near the F–F boundary. These anomalies are in line with those recently observed in Morocco, Germany, Poland, and north Russia, suggesting a global Hg flux. The Late Devonian LIP eruptions, which are believed to have emitted massive amounts of Hg, could be responsible for the global Hg and Hg/TOC anomalies around the F–F boundary. The observed Hg and Hg/TOC anomalies coincide with the extinction of Frasnian fauna in the Dushan area, implying a causal link between the Viluy, Kola, and Pripyat-Dnieper-Donets LIP eruptions and the F–F mass extinction.

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Big data and machine learning are poised to revolutionize the field of artificial intelligence and represent a step towards building an intelligent society. Big data is considered to be the key to unlocking the next great waves of growth in productivity, the value of data is realized through machine learning. In this survey, we begin with an introduction to the general field of data pricing and distributed machine learning then progress to the main streams of data pricing and mechanism design methods. Our survey will cover several current areas of research within the field of data pricing, including the incentive mechanism design for federated learning, reinforcement learning, auction, crowdsourcing, and blockchain, especially, focus on reward function for machine learning and payment scheme. In parallel, we highlight the pricing scheme in data transactions, focusing on data evaluation via distributed machine learning. To conclude, we discuss some research challenges and future directions of data pricing for machine learning.

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