This paper develops Probabilistic Hybrid Action Models (PHAMs), a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans. PHAMs represent aspects of robot behavior that cannot be represented by most action models used in AI planning: the temporal structure of continuous control processes, their non-deterministic effects, and several modes of...

This work presents a defense of causal contrastivism based on contexualism. As argued, our proposal contextualism is compatible with both and binarism, including explanations why in which sense secondary counterfactuals are relevant.

This paper presents an approach to translating Chinese organization names into English based on correlative expansion. Firstly, some candidate translations are generated by using statistical translation method. And several correlative named entities for the input are retrieved from a correlative named entity list. Secondly, three kinds of expansion methods are used to generate some expanded que...

This article presents a new correlative model for surface tension of mixtures. This model is an extension of a predictive model recently proposed by our group. Other correlative models were evaluated and compared to the proposed model. Hydrocarbons mixtures exhibiting chemical nature or shape and chain size asymmetries were chosen as the standard to test the performance of the chosen models at ...

In-resin fluorescence (IRF) protocols preserve fluorescent proteins in resin-embedded cells and tissues for correlative light and electron microscopy, aiding interpretation of macromolecular function within the complex cellular landscape. Dual-contrast IRF samples can be imaged in separate fluorescence and electron microscopes, or in dual-modality integrated microscopes for high resolution corr...