The unimolecular reactions of Criegee intermediates (CIs) are thought to be one of the significant sources of atmospheric OH radicals. However, stark discrepancies exist in the unimolecular reaction rate of the methyl-substituted CI CH3CHOO, typically from ozonolysis of alkenes such as trans-2-butene, between the results of ozonolysis of alkene experiments and the up-to-date theoretical calculations. That no further progress has been made since the method that directly produces CIs in the laboratory was developed is mostly attributed to the existence of two conformers, syn- and anti-CH3CHOO, and the methodological limitations of sensitive conformer-specific detection. We report a conformer-specific measurement of the unimolecular reaction rate of syn-CH3CHOO by using a high-repetition-rate laser-induced fluorescence method. At 298 K, the observed value of 182 ± 66 s–1 is in good agreement with recent theoretical calculations.

Semantic segmentation of surgical instruments plays a crucial role in robot-assisted surgery. However, accurate segmentation of cataract surgical instruments is still a challenge due to specular reflection and class imbalance issues. In this paper, an attention-guided network is proposed to segment the cataract surgical instrument. A new attention module is designed to learn discriminative features and address the specular reflection issue. It captures global context and encodes semantic dependencies to emphasize key semantic features, boosting the feature representation. This attention module has very few parameters, which helps to save memory. Thus, it can be flexibly plugged into other networks. Besides, a hybrid loss is introduced to train our network for addressing the class imbalance issue, which merges cross entropy and logarithms of Dice loss. A new dataset named Cata7 is constructed to evaluate our network. To the best of our knowledge, this is the first cataract surgical instrument dataset for semantic segmentation. Based on this dataset, RAUNet achieves state-of-the-art performance 97.71% mean Dice and 95.62% mean IOU.