No abstract

The core protein of HCV can interact with translin protein. This can partly explain the molecular mechanism for hepatocellular carcinoma and lymphoma caused by HCV.

As a conventional and persistent topic, a single bubble freely ascending in Newtonian liquids is investigated based on its shape and motion predictions using the strategy of machine learning. The dataset for training, validating, and testing neural networks is composed of the current experimental results and the extensively collected data from previous research works, which covers a broad range of dimensionless parameters that are [Formula: see text], and [Formula: see text]. The novel models of the aspect ratio E and drag coefficient [Formula: see text] are proposed based on a backpropagation neural network. The comparisons of the conventional correlations indicate that the new E model presents a significant superiority. This E model also has a good capability to predict the minimum E as about 0.26 that is consistent with the theoretical value [Formula: see text]. Moreover, the [Formula: see text] models are divided into E-independent and E-dependent types. The performances of these two type models are quite similar and both agree well with the experimental results. The errors of the [Formula: see text] predictions for Re > 1 are mostly in the range of [Formula: see text].

For decades, it has been proven by numerous experiments and simulations that a single bubble freely rises in an unstable path and shape in a surface tension force dominant regime. Using time-resolved tomographic particle image velocimetry combined with three-dimensional shadow image reconstruction, the present study experimentally provides a full three-dimensional diagnosis of the shape and wake structures of a zigzagging bubble. An ellipsoidal bubble with an equivalent diameter of [Formula: see text] = 5.47 mm freely rising in stagnant water is investigated at a terminal Reynolds number of 1390 with a zigzag path. The results show a typical double-threaded vortex structure generated during the initial ascending stage. In the regular zigzagging stage, a four-ring mode of vortex generation is observed, which is composed of alternatively discharged and induced hairpin vortices. Thanks to the volumetric measurement, the shedding or inducing mechanism of complicated wake structures is clearly achieved. We speculate that the secondary shape oscillation of the bubble is excited by the shedding of the primary hairpin vortex. Frequencies of the bubble trajectory, variation of velocity, and bubble shape oscillation are analyzed in detail. Their associated harmonics are classified to indicate the interactions between the bubble and the wakes.