News currently spreads rapidly through the internet. Because fake news stories are designed to attract readers, they tend to spread faster. For most readers, detecting fake news can be challenging and such readers usually end up believing that the fake news story is fact. Because fake news can be socially problematic, a model that automatically detects such fake news is required. In this paper, we focus on data-driven automatic fake news detection methods. We first apply the Bidirectional Encoder Representations from Transformers model (BERT) model to detect fake news by analyzing the relationship between the headline and the body text of news. To further improve performance, additional news data are gathered and used to pre-train this model. We determine that the deep-contextualizing nature of BERT is best suited for this task and improves the 0.14 F-score over older state-of-the-art models.
Background/Aims: Clarithromycin resistance in Helicobacter pylori is associated with point mutations in the 23S ribosomal RNA (rRNA) gene. We investigated the point mutations in the 23S rRNA genes of patients with clarithromycin-resistant H. pylori and compared the H. pylori eradication rates based on the point mutations. Methods: A total of 431 adult patients with H. pylori infection were recruited in Kangdong Sacred Heart Hospital in 2017 and 2018. Patients who did not have point mutations related to clarithromycin resistance and/or had clinically insignificant point mutations were treated with PAC (proton pump inhibitor, amoxicillin, clarithromycin) for seven days, while patients with clinically significant point mutations were treated with PAM (proton pump inhibitor, amoxicillin, metronidazole) for seven days. H. pylori eradication rates were compared. Results: Sequencing-based detection of point mutations identified four mutations that were considered clinically significant (A2142G, A2142C, A2143G, A2143C). The clarithromycin resistance rate was 21.3% in the overall group of patients. A2143G was the most clinically significant point mutation (84/431, 19.5%), while T2182C was the most clinically insignificant point mutation (283/431, 65.7%). The overall H. pylori eradication rate was 83.7%, and the seven-day PAM-treated clarithromycin-resistance group showed a significantly lower eradication rate than the seven-day PAC-treated nonresistance group (ITT; 55.4% (51/92) vs. 74.3% (252/339), p = 0.001, PP; 66.2% (51/77) vs. 88.4% (252/285), p = 0.0001). Conclusions: There were significantly lower eradication rates in the patients with clarithromycin-resistant H. pylori when treated with PAM for seven days. A future study comparing treatment regimens in clarithromycin-resistant H. pylori-infected patients may be necessary.
This paper proposed a triangular inequality-based rewiring method for the rapidly exploring random tree (RRT)-Connect robot path-planning algorithm that guarantees the planning time compared to the RRT algorithm, to bring it closer to the optimum. To check the proposed algorithm’s performance, this paper compared the RRT and RRT-Connect algorithms in various environments through simulation. From these experimental results, the proposed algorithm shows both quicker planning time and shorter path length than the RRT algorithm and shorter path length than the RRT-Connect algorithm with a similar number of samples and planning time.
There was no significant difference in overall bowel cleansing efficacy between PEG/Asc and SP/MC; however, SP/MC showed better tolerability and safety profile than PEG/Asc. The independent factor for inadequate bowel preparation was later colonoscopic starting time when applied split method.
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