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The Dingcun locality 54:100 site was first excavated in 1950 s and has since yielded abundant stone artefacts and the famous ‘Dingcun human’ fossils, including three teeth and a parietal fragment. The Dingcun teeth has been regarded as a potential evidence of early emergence and development of ‘modern’ anatomic characters, making them key to understanding the origin and evolution of our species. However, there has been considerable debate regarding the chronology of the Dingcun site. Here we establish a new chronology for the site, based on optical dating of the fossil-bearing sediments and U-series dating of fauna fossils from the cultural layers. Our study shows that the age of the Dingcun human fossil ranges from 298,000 to 225,000 years ago (at 95.4 % confidence interval). This new dating result suggest that the Dingcun hominins represent a Late Middle Pleistocene population in East Asia who had borne some modern dental traits. ....
The natural cycles of the surface-to-atmosphere fluxes of carbon dioxide (CO2) and other important greenhouse gases are changing in response to human influences. These changes need to be quantified to understand climate change and its impacts, but this is difficult to do because natural fluxes occur over large spatial and temporal scales and cannot be directly observed. Flux inversion is a technique that estimates the spatiotemporal distribution of a gas’ fluxes using observations of the gas’ mole fraction and a chemical transport model. To infer trends in fluxes and identify phase shifts and amplitude changes in flux seasonal cycles, we construct a flux-inversion system that uses a novel spatially-varying time-series decomposition of the fluxes. We incorporate this decomposition into the Wollongong Methodology for Bayesian Assimilation of Trace-gases (WOMBAT, Zammit-Mangion et al., Geosci. Model Dev., 15, 2022), a Bayesian hierarchical flux-inversion framework that yields posterio ....
India News: Surat, northwest India, faces an escalating risk of urban malaria fueled by A. stephensi breeding in artificial containers. The study analyzes the imp ....
Understanding the uncertainty of model parameters is crucial for building predictive models. Within the field of spontaneous ignition a slight variation in the model parameters can cause a significant variation in our ability to determine if ignition occurs. We consider this problem through an application to the steel industry. A byproduct of the steelmaking process is stockpiled where oxidation can induce ignition. The resulting ignition process sinters the filter improving the durability. Understanding this process requires careful modelling and consideration of the uncertainty in the reaction kinetics. We examine some experimental data on the filter cake to determine these reaction kinetics. Due to the complex nature of the filter cake, standard estimation techniques are difficult to apply and the uncertainty in our parameters cannot be an input into the larger stockpiles. We apply a Bayesian framework for parameter estimation that considers a distribution for the parameters rather ....