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The thermal and numerical simulation of the mould electromagnetic stirring (M-EMS) during continuous casting (CC) of the GCr15 bearing steel was performed. The thermal simulation apparatus ...

The effect of final electromagnetic stirring on the solidification structure, element segregation, and carbides of GCr15 bearing steel was investigated. The experiment of continuous casting of the steel was carried out by using a continuous casting physical simulation apparatus with the final electromagnetic stirring. The liquid core profile was revealed by the pour-out method during the solidification process. Eight ingots were produced under different electromagnetic stirring parameters for comparison. The results show that, at the final stage of solidification, intense electromagnetic stirring exacerbates the central carbon segregation, resulting in more serious precipitation of the primary carbides. It is also found that the carbides in the segregation area are dominantly M3C type, together with a small amount of M7C3-type and M3C2-type carbides. In this physical simulation model, the optimal stirring parameters to obtain a fine and homogeneous structure are the liquid pool width of 15 mm, current intensity of 150 A, and stirring frequency of 5 Hz.

To perceive self-motion perception, the brain needs to integrate multi-modal sensory signals such as visual, vestibular and proprioceptive cues. Self-motion perception is very complex and involves multi candidate areas. Previous studies related to self-motion perception during passive motion have revealed that some of the areas show selective response to different directions for both visual (optic flow) and vestibular stimuli, such as the dorsal subdivision of the medial superior temporal area (MSTd) and the visual posterior sylvian fissure (VPS), although MSTd is dominated by visual signals and VPS is dominated by vestibular signals. However, none of studies related to self-motion perception have distinguished the different neuron types with distinct neuronal properties in cortical microcircuitry, which limited our understanding of the local circuits for self-motion perception. In the current study, we classified the recorded MSTd and VPS neurons into putative pyramidal neurons and putative interneurons based on the extracellular action potential waveforms and spontaneous firing rates. We found that: (1) the putative interneurons exhibited obviously broader direction tuning than putative pyramidal neurons in response to their dominant (visual for MSTd; vestibular for VPS) stimulation type; (2) either in visual or vestibular condition, the putative interneurons were more responsive but with larger variability than the putative pyramidal neurons for both MSTd and VPS areas; and (3) the timing of vestibular and visual peak directional tuning was earlier in the putative interneurons than that of the putative pyramidal neurons for both MSTd and VPS areas. Based on these findings we speculated that, within the microcircuitry, several adjacent putative interneurons with broad direction tuning receive earlier strong but variable signals, which might act feedforward input to shape the direction tuning of the target putative pyramidal neuron, but each interneuron may participate in several microcircuitries, targeting different output neurons.

In the daily life, we perceive the world around us by integrating multiple sensory cues (visual, auditory, olfactory, gustatory, tactile, vestibular and proprioceptive) to create a coherent, reliable representation that allows us to interact meaningfully with the environment. The integration of different sensory information is necessary for our perception, motor transformation, decision making, learning and memory. In the past decades, many interdisciplinary researchers have been attracted to the field of multisensory research, and tremendous advances have been made in this field. We review the researches on multisensory integration during self-motion perception in the past decades from the candidate areas, the integration principles and the neural correlation of the behaviors, with the intention to provide a comprehensive source for those interested in understanding the neural substrates for multisensory integration. Meanwhile, we also provide a prospect for the future research in this field.