CrowdChecked: Detecting Previously Fact-Checked Claims in Social Media

While there has been substantial progress in developing systems to automate fact-checking, they still lack credibility in the eyes of the users. Thus, an interesting approach has emerged: to perform automatic fact-checking by verifying whether an input claim has been previously fact-checked by professional fact-checkers and to return back an article that explains their decision. This is a sensible approach as people trust manual fact-checking, and as many claims are repeated multiple times. Yet, a major issue when building such systems is the small number of known tweet--verifying article pairs available for training. Here, we aim to bridge this gap by making use of crowd fact-checking, i.e., mining claims in social media for which users have responded with a link to a fact-checking article. In particular, we mine a large-scale collection of 330,000 tweets paired with a corresponding fact-checking article. We further propose an end-to-end framework to learn from this noisy data based on modified self-adaptive training, in a distant supervision scenario. Our experiments on the CLEF'21 CheckThat! test set show improvements over the state of the art by two points absolute. Our code and datasets are available at https://github.com/mhardalov/crowdchecked-claimsComment: Accepted to AACL-IJCNLP 2022 (Main Conference

Study of thermal behavior of microlayer under vapor bubble at liquid boiling

The results of experimental study of evolution of temperature fields under single vapor bubble obtained by high-speed infrared thermometry with high spatial resolution (13 μm) are presented in this paper. The data were obtained at pool boiling of saturated ethanol and deionized water at atmospheric pressure. Reconstruction of local instantaneous heat flux distribution on the heater surface was carried out with the use of numerical simulation. It is shown that maximal local heat flux was observed in the microlayer region on the bubble growth stage and reached the value an order of magnitude greater than the input heat flux. Based on the results of experimental and numerical researches the estimations of the microlayer thickness were carried out at pool boiling of water and ethanol, which are in good agreement with the experimental data presented in the literature and obtained using laser interferometry

Study of thermal behavior of microlayer under vapor bubble at liquid boiling

The results of experimental study of evolution of temperature fields under single vapor bubble obtained by high-speed infrared thermometry with high spatial resolution (13 μm) are presented in this paper. The data were obtained at pool boiling of saturated ethanol and deionized water at atmospheric pressure. Reconstruction of local instantaneous heat flux distribution on the heater surface was carried out with the use of numerical simulation. It is shown that maximal local heat flux was observed in the microlayer region on the bubble growth stage and reached the value an order of magnitude greater than the input heat flux. Based on the results of experimental and numerical researches the estimations of the microlayer thickness were carried out at pool boiling of water and ethanol, which are in good agreement with the experimental data presented in the literature and obtained using laser interferometry