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Fish represent the largest group of vertebrates and display the greatest diversity of auditory structures. However, studies addressing how the form and function of the auditory system change during development to enhance perception of the acoustic environment are rather sparse in this taxon compared to other vertebrate groups. An ontogenetic perspective of the auditory system in fishes provides a readily testable framework for understanding structure–function relationships. Additionally, studying ancestral models such as fish can convey valuable comparable information across vertebrates, as early developmental events are often evolutionary conserved. This chapter reviews the literature on the morphological development of the fish auditory system, with particular focus on the inner ear structures that evolve from an otic placode during early embryonic development and then continue to undergo differentiation and maturation in the postembryonic phase. Moreover, the chapter provides a systematic overview of how auditory sensitivity develops during ontogeny. Although most studies indicate a developmental improvement in auditory sensitivity, there is considerably species-specific variation. Lastly, the paucity of information and literature concerning the development of auditory capabilities for social communication in fishes is also discussed. Further investigation on the development of structure and function of the fish auditory system is recommended in order to obtain a deeper understanding of how ontogenetic morphological changes in the auditory pathway relate to modifications in acoustic reception, auditory processing, and the capacity to communicate acoustically.
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Digital Factory (DF) planning is the key of intelligent factory construction, where intelligent production technologies of big data analysis, cloud computing, blockchain, Internet of Things, artificial intelligence, 5G, Time Sensitive Network (TSN), Digital Twin (DT), additive manufacturing are included. By applying the modern techniques, DF performs great advantages on the aspects of product lifecycle management, enterprise resource planning, operation management, supply chain management, real-time database construction, advanced process control, as well as the new technologies of distributed control system and fieldbus control system. This article delivers a review of key issues of DF top-level design and planning from the aspects of networking, precision, automation and digitalization. Solutions are explored based on 5G, TSN and DT advanced technologies, literately and practically. Additionally, the article describes the method and application of efficient big data comprehensive solution. Therefore, this study contributes valuable decision-making support for DF applications.
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Medical classification is affected by many factors, and the traditional medical classification is usually restricted by factors such as too long text, numerous categories and so on. In order to solve these problems, this paper uses word vector and word vector to mine the text deeply, considering the problem of scattered key features of medical text, introducing long-term and short-term memory network to effectively retain the features of historical information in long text sequence, and using the structure of CNN to extract local features of text, through attention mechanism to obtain key features, considering the problems of many diseases, by using hierarchical classification. To stratify the disease. Combined with the above ideas, a deep DLCF model suitable for long text and multi-classification is designed. This model has obvious advantages in CMDD and other datasets. Compared with the baseline models, this model is superior to the baseline model in accuracy, recall and other indicators.