In 24 (0.98%) of 2457 patients with congenital heart disease the brachiocephalic vein was in an anomalous position below the aortic arch. This is a much higher proportion of such cases than reported so far. This high frequency may arise from differences in the study population and the method of diagnosis. This venous anomaly was more common in patients with tetralogy of Fallot or ventricular septal defect with pulmonary atresia. Patients with the venous anomaly were more likely to have a right aortic arch. The anomalous course of the brachiocephalic vein from the neck to the junction of the superior vena cava was shown by cross sectional echocardiography. In doubtful cases, Doppler study usually clarified the anatomical arrangement.

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Many video understanding tasks work in the offline setting by assuming that the input video is given from the start to the end. However, many real-world problems require the online setting, making a decision immediately using only the current and the past frames of videos such as in autonomous driving and surveillance systems. In this paper, we present a novel solution for online action detection by using a simple yet effective RNN-based networks called the Future Anticipation and Temporally Smoothing network (FATSnet). The proposed network consists of a module for anticipating the future that can be trained in an unsupervised manner with the cycle-consistency loss, and another component for aggregating the past and the future for temporally smooth frame-by-frame predictions. We also propose a solution to relieve the performance loss when running RNN-based models on very long sequences. Evaluations on TVSeries, THUMOS'14, and BBDB show that our method achieve the state-of-the-art performances compared to the previous works on online action detection.

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