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Young children’s user experiences of educational applications (apps) can potentially support their cognitive development and improve the quality of parent–child relationships. However, to realize such potential, app designers must consider children’s emotional needs. Through a comprehensive review of the relevant literature, this paper develops an interactive design framework that can trigger three positive emotions, which is then used as a scale to conduct a design analysis of 72 apps available on the Australian and Chinese Apple App Store. We found that the interactive design scale based on emotional design is feasible; and an interactive design method that focuses on emotions affects the emotional benefits of parent–child users from apps and obtaining higher user ratings. It is thus demonstrated that paying attention to these design criteria will affect the emotional benefits young children receive from apps, thereby increasing users’ interest and support for the product. Lastly, we discuss the implications of improving the methods emotional experience and encourage future designers to bridge the gap between research and practice.

Background Patients with spinal cord injury (SCI) often present with different degrees of neuropathic pain (NP). Glia-mediated inflammatory response plays a key role. The transient receptor potential vanilloid subtype 1 (TRPV1), as an ion channel receptor closely related to pain, plays an important role in NP, although its mechanism remains unclear. We explored the role of TRPV1 in NP after SCI and its effect on the proliferation and activation of C-X3-C motif chemokine ligand 1 (CX3CL1)-positive glial cells. Methods The SCI rat model was established using the modified Allen’s spinal cord injury model. After SCI, rats in each group were administered the TRPV1 antagonist SB705498 (10 mg/kg) or 2 mL of vehicle intragastrically for 7 consecutive days. The hindlimb motor function of rats after injury was assessed by the Basso, Beattie, and Bresnahan rating scale; Von Frey fibres and plantar thermal stimulation were used to evaluate the changes in rats’ mechanical paw withdrawal threshold (PWT) and thermal paw withdrawal latency (PWL), respectively; haematoxylin and eosin staining, double immunofluorescent staining, and Western blotting were used to investigate the role of TRPV1 in NP after SCI and its effect on the proliferation and activation of CX3CL1-positive glial cells. Results The chemokine CX3CL1 was mainly expressed in the dorsal horn neurons of the spinal cord and also to a certain extent in microglia, astrocytes, and oligodendrocytes after SCI. The expression of TRPV1 and CX3CL1 in the dorsal horn of the spinal cord in rats was significantly upregulated, and the PWT and PWL of rats were significantly decreased after SCI. The TRPV1 antagonist not only inhibited the activation of TRPV1, but also significantly inhibited the apoptosis of neurons and oligodendrocytes and proliferation and activation of inflammation-related CX3CL1-positive glial cells induced by SCI. Conclusion These results suggest that TRPV1 is involved in the occurrence and development of NP after SCI in rats by mediating the proliferation and activation of CX3CL1-positive glial cells in the dorsal horn of the spinal cord; inhibition of TRPV1 activity attenuates the proliferation and activation of CX3CL1-positive glial cells, thereby reducing symptoms of central sensitisation.

In order to study the method of feature extraction of 3D art design model based on deep learning, in this study, a network community media communication research on 3D art creation based on deep learning and evolution strategy was proposed. The research results showed that the two feature extraction methods were reliable and robust. Based on the evolutionary strategy, the evolution matrix function was used to extract the characteristics of people’s preferences. The experimental results showed that the process is feasible. It can be concluded that the method based on the method of deep learning and interactive evolution strategy, the feasibility of social media communication research of 3D art creation network based on deep learning and evolution strategy was verified by the combination of scientific creation and artistic creation by sacrificing time expenditure.